From 1c592c52b62880f5f4bb2aef382f67b9851a26db Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Tue, 16 Dec 2025 17:46:56 +0100
Subject: [PATCH 1/9] :memo: Docs: adding no bio groups demo :construction:

---
 docs/tutorial/demo-mgnify-ww-biomes.ipynb | 7168 +++++++++++++++++++++
 1 file changed, 7168 insertions(+)
 create mode 100644 docs/tutorial/demo-mgnify-ww-biomes.ipynb

diff --git a/docs/tutorial/demo-mgnify-ww-biomes.ipynb b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
new file mode 100644
index 0000000..5f8cd61
--- /dev/null
+++ b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
@@ -0,0 +1,7168 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ad5a71b5",
+   "metadata": {},
+   "source": [
+    "# `ABaCo` demo: No biological labels e.g., Mgnify tomoatos"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bcc12d4b",
+   "metadata": {},
+   "source": [
+    "In this demo we will implement ABaCo for batch correction on Mgnify study [MGYS00001135](https://www.ebi.ac.uk/metagenomics/studies/MGYS00001135#overview) and ENA Bioproject [PRJEB13832](https://www.ebi.ac.uk/ena/browser/view/PRJEB13832), a proof-of-concept study for surveilling infections diseases and AMR via metagenomics analysis of local sewage samples in Copenhagen.\n",
+    "\n",
+    "-----\n",
+    "**Data Description:**\n",
+    "- The metagenomics dataset collected by the Technical University of Denmark (DTU) and analysed via Mgnify [pipeline version 2.0](https://www.ebi.ac.uk/metagenomics/pipelines/2.0) is a dataset composed of 54 samples with 749 identified taxa at the genus level. \n",
+    "- The samples were collected from 3 different wastewater treatment plant (WWTP) locations, accounting for the biological source of variation. \n",
+    "- Samples were analyzed on 2 different dates accounting for the technical source of variation (i.e., batch effect).\n",
+    "- The sample data and metadata were retrieved from the [Mgnify API](https://docs.mgnify.org/src/docs/api.html) using the following [mgnifyapi repo](https://github.com/Multiomics-Analytics-Group/Retrieve_info_MGnifyAPI/tree/angel-learning) and stored as an Annotated Dataset [AnnData](https://anndata.readthedocs.io/en/latest/index.html). \n",
+    "\n",
+    "**Goal:**\n",
+    "\n",
+    "With ABaCo the aim is to remove the technical variation (batch effect) while maintaining any biological variation (wastewater treatment plant location). \n",
+    "\n",
+    "-----\n",
+    "\n",
+    "To start we read in the annotated dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f94eae83",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>taxa</th>\n",
+       "      <th>ERZ12633510</th>\n",
+       "      <th>ERZ12633501</th>\n",
+       "      <th>ERZ12633502</th>\n",
+       "      <th>ERZ12633503</th>\n",
+       "      <th>ERZ12633504</th>\n",
+       "      <th>ERZ12633505</th>\n",
+       "      <th>ERZ12633506</th>\n",
+       "      <th>ERZ12633507</th>\n",
+       "      <th>ERZ12633517</th>\n",
+       "      <th>ERZ12633508</th>\n",
+       "      <th>ERZ12633518</th>\n",
+       "      <th>ERZ12633509</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>sk__Archaea</td>\n",
+       "      <td>3</td>\n",
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+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>sk__Archaea;k__;p__Thaumarchaeota;c__Nitrososp...</td>\n",
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+      ],
+      "text/plain": [
+       "                                                taxa  ERZ12633510  \\\n",
+       "0                                        sk__Archaea            3   \n",
+       "1  sk__Archaea;k__;p__Euryarchaeota;c__Methanococ...            0   \n",
+       "2  sk__Archaea;k__;p__Euryarchaeota;c__Methanomic...            0   \n",
+       "3  sk__Archaea;k__;p__Euryarchaeota;c__Thermoplas...            0   \n",
+       "4  sk__Archaea;k__;p__Thaumarchaeota;c__Nitrososp...            1   \n",
+       "\n",
+       "   ERZ12633501  ERZ12633502  ERZ12633503  ERZ12633504  ERZ12633505  \\\n",
+       "0            0            2            3            0            1   \n",
+       "1            0            1            0            0            0   \n",
+       "2            0            0            0            0            0   \n",
+       "3            0            1            0            0            0   \n",
+       "4            0            0            0            0            0   \n",
+       "\n",
+       "   ERZ12633506  ERZ12633507  ERZ12633517  ERZ12633508  ERZ12633518  \\\n",
+       "0            2            0            0            3            0   \n",
+       "1            0            0            0            0            0   \n",
+       "2            1            0            0            0            0   \n",
+       "3            0            0            0            0            0   \n",
+       "4            0            0            0            0            0   \n",
+       "\n",
+       "   ERZ12633509  \n",
+       "0            1  \n",
+       "1            0  \n",
+       "2            0  \n",
+       "3            1  \n",
+       "4            0  "
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import requests \n",
+    "from io import StringIO\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "datasets = {\n",
+    "    \"MGYS00006205\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006205/pipelines/5.0/file/ERP140107_taxonomy_abundances_SSU_v5.0.tsv\",\n",
+    "    \"MGYS00006231\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006231/pipelines/5.0/file/ERP139927_taxonomy_abundances_SSU_v5.0.tsv\",\n",
+    "    \"MGYS00006204\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006204/pipelines/5.0/file/ERP140102_taxonomy_abundances_SSU_v5.0.tsv\"\n",
+    "}\n",
+    "\n",
+    "dfs = {}\n",
+    "for key, url in datasets.items():\n",
+    "    # download\n",
+    "    response = requests.get(url)\n",
+    "    # treat as file\n",
+    "    file_like = StringIO(response.content.decode('utf-8'))\n",
+    "    # read into pd df\n",
+    "    dfs[key] = pd.read_csv(file_like, sep='\\t')\n",
+    "    # add a column with the dataset url (batches)\n",
+    "    #dfs[url]['source'] = url\n",
+    "    # rename sampleid col to taxa\n",
+    "    dfs[key] = dfs[key].rename(columns={\"#SampleID\": \"taxa\"})\n",
+    "# sanity check\n",
+    "dfs[\"MGYS00006205\"].head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "61f54861",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 531 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
+      "Columns: 138 entries, ERZ12633510 to ERZ12633499\n",
+      "dtypes: float64(138)\n",
+      "memory usage: 576.6+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# join datasets on taxa col\n",
+    "inter_joined = dfs[\"MGYS00006205\"].merge(\n",
+    "    dfs[\"MGYS00006231\"], on='taxa', how='outer',\n",
+    ")\n",
+    "joined = inter_joined.merge(\n",
+    "    dfs[\"MGYS00006204\"], on='taxa', how='outer',\n",
+    ")\n",
+    "# put taxa in index\n",
+    "joined = joined.set_index('taxa')\n",
+    "\n",
+    "joined.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "319d691e",
+   "metadata": {},
+   "source": [
+    "Using anndata to annotated the samples and taxa"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b6303749",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# preparing obs metadata\n",
+    "dfs_T = {}\n",
+    "for key in dfs:\n",
+    "    # transpose\n",
+    "    dfs_T[key] = dfs[key].T\n",
+    "    # drop taxa row\n",
+    "    dfs_T[key] = dfs_T[key].drop('taxa')\n",
+    "    # add source column\n",
+    "    dfs_T[key]['source'] = key\n",
+    "    # dummy bio column\n",
+    "    dfs_T[key]['bio'] = np.random.choice([\"Group1\"], size = len(dfs_T[key]))\n",
+    "    # drop allother cols\n",
+    "    dfs_T[key] = dfs_T[key][['source', 'bio']]\n",
+    "\n",
+    "obsm = pd.concat(dfs_T.values())\n",
+    "\n",
+    "varm = joined.reset_index()[['taxa']]\n",
+    "varm = varm['taxa'].str.split(';', expand=True)\n",
+    "varm.columns = [\n",
+    "    \"superkingdom\", \"kingdom\",\"phylum\", \"class\", \n",
+    "    \"order\", \"family\", \"genus\", \"species\"\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d98ecaf7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning: Transforming to str index.\n",
+      "  return dispatch(args[0].__class__)(*args, **kw)\n",
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2118209775.py:15: ImplicitModificationWarning: Setting element `.layers['nona']` of view, initializing view as actual.\n",
+      "  adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import anndata as ad\n",
+    "import numpy as np\n",
+    "import scanpy as sc\n",
+    "\n",
+    "# init anndata object\n",
+    "full = ad.AnnData(\n",
+    "    X=joined.T.values,\n",
+    "    obs=obsm,\n",
+    "    var=varm,    \n",
+    ")\n",
+    "# must have genus level\n",
+    "adata = full[:, ~full.var['genus'].isna()]\n",
+    "\n",
+    "# layer with no na\n",
+    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "80fcd19b",
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+   "outputs": [
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+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# hist\n",
+    "import plotly.graph_objects as go\n",
+    "from scipy import stats\n",
+    "\n",
+    "# agg by fake bio group \n",
+    "bio_mean = sc.get.aggregate(\n",
+    "    adata,\n",
+    "    by=\"bio\",\n",
+    "    axis=\"obs\",\n",
+    "    func='mean',\n",
+    "    layer='nona'\n",
+    ").to_df('mean').T\n",
+    "\n",
+    "# init fig\n",
+    "fig = go.Figure()\n",
+    "# add traces\n",
+    "fig.add_trace(go.Histogram(x=bio_mean['Group1'], name='Group1'))\n",
+    "#fig.add_trace(go.Histogram(x=bio_mean['Group2'], name='Group2'))\n",
+    "\n",
+    "# Overlay both histograms\n",
+    "fig.update_layout(barmode='overlay')\n",
+    "# Reduce opacity to see both histograms\n",
+    "fig.update_traces(opacity=0.75)\n",
+    "fig.show()\n",
+    "\n",
+    "# no diff in stats \n",
+    "#stats.ttest_ind(bio_mean['Group1'], bio_mean['Group2'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66663906",
+   "metadata": {},
+   "source": [
+    "The columns (variables, vars) are the different taxa annotated with taxonomic ranks (sk = super kingdom, k = kingdom, p = phylum, c = class, o = order, f = family, g = genus).\n",
+    "\n",
+    "The rows (observations, obs) are the metadata for the different samples in the study MGYS00001135. \n",
+    "\n",
+    "The ones of interest for this demo are: \n",
+    "- The `analysis_completed_date` which accounts for batch effect for our purposes, and\n",
+    "- `ww_plant` which are the different sampling locations and we will use as our biological variance that we wish to retain after batch correction.\n",
+    "\n",
+    "-----\n",
+    "\n",
+    "We can easily extract a df from anndata so that we meet the data format required for abaco."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1d77b8ab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 138 entries, 0 to 137\n",
+      "Columns: 223 entries, index to bio\n",
+      "dtypes: category(1), float64(220), object(2)\n",
+      "memory usage: 239.7+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "batch_col = 'source'\n",
+    "bio_col = 'bio'\n",
+    "id_col = 'index'\n",
+    "\n",
+    "# the raw counts as df\n",
+    "df_taxa = adata.to_df()\n",
+    "\n",
+    "# appending on the categorical data of interest\n",
+    "df_all = pd.concat([df_taxa, adata.obs[[batch_col, bio_col]]], axis=1).reset_index()\n",
+    "df_all = df_all.fillna(0)\n",
+    "\n",
+    "df_all['bio'] = df_all['bio'].astype('category')\n",
+    "\n",
+    "df_all.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79dfcc4f",
+   "metadata": {},
+   "source": [
+    "**`pd.DataFrame` Requirements for ABaCo:**\n",
+    "\n",
+    "The dataset contains the following making it compatible with the ABaCo framework:\n",
+    "\n",
+    "| id_col | batch_col  | bio_col  | count1 | count2 | ... |\n",
+    "|--------|------------|----------|--------|--------|-----|\n",
+    "| A      | 24/07/2025 | RA       | #      | #      | ... |\n",
+    "| B      | 15/06/2024 | RD       | #      | #      | ... |\n",
+    "| C      | 24/07/2025 | RL       | #      | #      | ... |\n",
+    "\n",
+    "- The data has categorical columns: \n",
+    "    1. unique ids to identify the observations/samples e.g. sample id col\n",
+    "    2. ids for the batch/factor groupings to be corrected by abaco. e.g. dates of sample analysis batch_col\n",
+    "    3. biological/experimental factor variation for abaco to retain when correcting batch effect e.g., sampling location bio_col\n",
+    "\n",
+    "- And taxa counts to be trained on. \n",
+    "\n",
+    "We can use `abaco.BatchEffectPlots.plotPCoA()` to visualize any batch and biological effects based on the given categories. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "128ba953",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ">> clustergrammer2 backend version 0.18.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/anglup/GitHub/abaco/.venv/lib/python3.11/site-packages/skbio/stats/ordination/_principal_coordinate_analysis.py:157: RuntimeWarning:\n",
+      "\n",
+      "EIGH: since no value for dimensions is specified, PCoA for all dimensions will be computed, which may result in long computation time if the original distance matrix is large.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+       "        </script>\n",
+       "        <script>/**\n",
+       "* plotly.js v3.3.0\n",
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t=e[0],r=e[1],n=e[2],i=e[3],a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],f=e[10],h=e[11],d=e[12],v=e[13],_=e[14],b=e[15],p=t*o-r*a,k=t*s-n*a,E=t*l-i*a,S=r*s-n*o,L=r*l-i*o,x=n*l-i*s,C=u*v-c*d,M=u*_-f*d,g=u*b-h*d,P=c*_-f*v,T=c*b-h*v,z=f*b-h*_;return p*z-k*T+E*P+S*g-L*M+x*C}});var Cte=ye((Grr,kte)=>{kte.exports=nrt;function nrt(e,t,r){var n=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=t[6],c=t[7],f=t[8],h=t[9],d=t[10],v=t[11],_=t[12],b=t[13],p=t[14],k=t[15],E=r[0],S=r[1],L=r[2],x=r[3];return e[0]=E*n+S*s+L*f+x*_,e[1]=E*i+S*l+L*h+x*b,e[2]=E*a+S*u+L*d+x*p,e[3]=E*o+S*c+L*v+x*k,E=r[4],S=r[5],L=r[6],x=r[7],e[4]=E*n+S*s+L*f+x*_,e[5]=E*i+S*l+L*h+x*b,e[6]=E*a+S*u+L*d+x*p,e[7]=E*o+S*c+L*v+x*k,E=r[8],S=r[9],L=r[10],x=r[11],e[8]=E*n+S*s+L*f+x*_,e[9]=E*i+S*l+L*h+x*b,e[10]=E*a+S*u+L*d+x*p,e[11]=E*o+S*c+L*v+x*k,E=r[12],S=r[13],L=r[14],x=r[15],e[12]=E*n+S*s+L*f+x*_,e[13]=E*i+S*l+L*h+x*b,e[14]=E*a+S*u+L*d+x*p,e[15]=E*o+S*c+L*v+x*k,e}});var Pte=ye((Hrr,Lte)=>{Lte.exports=art;function art(e,t,r){var n=r[0],i=r[1],a=r[2],o,s,l,u,c,f,h,d,v,_,b,p;return t===e?(e[12]=t[0]*n+t[4]*i+t[8]*a+t[12],e[13]=t[1]*n+t[5]*i+t[9]*a+t[13],e[14]=t[2]*n+t[6]*i+t[10]*a+t[14],e[15]=t[3]*n+t[7]*i+t[11]*a+t[15]):(o=t[0],s=t[1],l=t[2],u=t[3],c=t[4],f=t[5],h=t[6],d=t[7],v=t[8],_=t[9],b=t[10],p=t[11],e[0]=o,e[1]=s,e[2]=l,e[3]=u,e[4]=c,e[5]=f,e[6]=h,e[7]=d,e[8]=v,e[9]=_,e[10]=b,e[11]=p,e[12]=o*n+c*i+v*a+t[12],e[13]=s*n+f*i+_*a+t[13],e[14]=l*n+h*i+b*a+t[14],e[15]=u*n+d*i+p*a+t[15]),e}});var Rte=ye((jrr,Ite)=>{Ite.exports=ort;function ort(e,t,r){var n=r[0],i=r[1],a=r[2];return e[0]=t[0]*n,e[1]=t[1]*n,e[2]=t[2]*n,e[3]=t[3]*n,e[4]=t[4]*i,e[5]=t[5]*i,e[6]=t[6]*i,e[7]=t[7]*i,e[8]=t[8]*a,e[9]=t[9]*a,e[10]=t[10]*a,e[11]=t[11]*a,e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}});var Fte=ye((Wrr,Dte)=>{Dte.exports=srt;function srt(e,t,r,n){var i=n[0],a=n[1],o=n[2],s=Math.sqrt(i*i+a*a+o*o),l,u,c,f,h,d,v,_,b,p,k,E,S,L,x,C,M,g,P,T,z,O,V,G;return Math.abs(s)<1e-6?null:(s=1/s,i*=s,a*=s,o*=s,l=Math.sin(r),u=Math.cos(r),c=1-u,f=t[0],h=t[1],d=t[2],v=t[3],_=t[4],b=t[5],p=t[6],k=t[7],E=t[8],S=t[9],L=t[10],x=t[11],C=i*i*c+u,M=a*i*c+o*l,g=o*i*c-a*l,P=i*a*c-o*l,T=a*a*c+u,z=o*a*c+i*l,O=i*o*c+a*l,V=a*o*c-i*l,G=o*o*c+u,e[0]=f*C+_*M+E*g,e[1]=h*C+b*M+S*g,e[2]=d*C+p*M+L*g,e[3]=v*C+k*M+x*g,e[4]=f*P+_*T+E*z,e[5]=h*P+b*T+S*z,e[6]=d*P+p*T+L*z,e[7]=v*P+k*T+x*z,e[8]=f*O+_*V+E*G,e[9]=h*O+b*V+S*G,e[10]=d*O+p*V+L*G,e[11]=v*O+k*V+x*G,t!==e&&(e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15]),e)}});var Ote=ye((Xrr,zte)=>{zte.exports=lrt;function lrt(e,t,r){var n=Math.sin(r),i=Math.cos(r),a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],f=t[10],h=t[11];return t!==e&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15]),e[4]=a*i+u*n,e[5]=o*i+c*n,e[6]=s*i+f*n,e[7]=l*i+h*n,e[8]=u*i-a*n,e[9]=c*i-o*n,e[10]=f*i-s*n,e[11]=h*i-l*n,e}});var Bte=ye((Zrr,qte)=>{qte.exports=urt;function urt(e,t,r){var n=Math.sin(r),i=Math.cos(r),a=t[0],o=t[1],s=t[2],l=t[3],u=t[8],c=t[9],f=t[10],h=t[11];return t!==e&&(e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15]),e[0]=a*i-u*n,e[1]=o*i-c*n,e[2]=s*i-f*n,e[3]=l*i-h*n,e[8]=a*n+u*i,e[9]=o*n+c*i,e[10]=s*n+f*i,e[11]=l*n+h*i,e}});var Ute=ye((Yrr,Nte)=>{Nte.exports=crt;function crt(e,t,r){var n=Math.sin(r),i=Math.cos(r),a=t[0],o=t[1],s=t[2],l=t[3],u=t[4],c=t[5],f=t[6],h=t[7];return t!==e&&(e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15]),e[0]=a*i+u*n,e[1]=o*i+c*n,e[2]=s*i+f*n,e[3]=l*i+h*n,e[4]=u*i-a*n,e[5]=c*i-o*n,e[6]=f*i-s*n,e[7]=h*i-l*n,e}});var Gte=ye((Krr,Vte)=>{Vte.exports=frt;function frt(e,t,r){var n,i,a,o=r[0],s=r[1],l=r[2],u=Math.sqrt(o*o+s*s+l*l);return Math.abs(u)<1e-6?null:(u=1/u,o*=u,s*=u,l*=u,n=Math.sin(t),i=Math.cos(t),a=1-i,e[0]=o*o*a+i,e[1]=s*o*a+l*n,e[2]=l*o*a-s*n,e[3]=0,e[4]=o*s*a-l*n,e[5]=s*s*a+i,e[6]=l*s*a+o*n,e[7]=0,e[8]=o*l*a+s*n,e[9]=s*l*a-o*n,e[10]=l*l*a+i,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e)}});var jte=ye((Jrr,Hte)=>{Hte.exports=hrt;function hrt(e,t,r){var n=t[0],i=t[1],a=t[2],o=t[3],s=n+n,l=i+i,u=a+a,c=n*s,f=n*l,h=n*u,d=i*l,v=i*u,_=a*u,b=o*s,p=o*l,k=o*u;return e[0]=1-(d+_),e[1]=f+k,e[2]=h-p,e[3]=0,e[4]=f-k,e[5]=1-(c+_),e[6]=v+b,e[7]=0,e[8]=h+p,e[9]=v-b,e[10]=1-(c+d),e[11]=0,e[12]=r[0],e[13]=r[1],e[14]=r[2],e[15]=1,e}});var Xte=ye(($rr,Wte)=>{Wte.exports=drt;function drt(e,t){return e[0]=t[0],e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=t[1],e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[10]=t[2],e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}});var Yte=ye((Qrr,Zte)=>{Zte.exports=vrt;function vrt(e,t){return e[0]=1,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=1,e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[10]=1,e[11]=0,e[12]=t[0],e[13]=t[1],e[14]=t[2],e[15]=1,e}});var Jte=ye((eir,Kte)=>{Kte.exports=prt;function prt(e,t){var r=Math.sin(t),n=Math.cos(t);return e[0]=1,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=n,e[6]=r,e[7]=0,e[8]=0,e[9]=-r,e[10]=n,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}});var Qte=ye((tir,$te)=>{$te.exports=grt;function grt(e,t){var r=Math.sin(t),n=Math.cos(t);return e[0]=n,e[1]=0,e[2]=-r,e[3]=0,e[4]=0,e[5]=1,e[6]=0,e[7]=0,e[8]=r,e[9]=0,e[10]=n,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}});var tre=ye((rir,ere)=>{ere.exports=mrt;function mrt(e,t){var r=Math.sin(t),n=Math.cos(t);return e[0]=n,e[1]=r,e[2]=0,e[3]=0,e[4]=-r,e[5]=n,e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[10]=1,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}});var ire=ye((iir,rre)=>{rre.exports=yrt;function yrt(e,t){var r=t[0],n=t[1],i=t[2],a=t[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,f=n*s,h=i*o,d=i*s,v=i*l,_=a*o,b=a*s,p=a*l;return e[0]=1-f-v,e[1]=c+p,e[2]=h-b,e[3]=0,e[4]=c-p,e[5]=1-u-v,e[6]=d+_,e[7]=0,e[8]=h+b,e[9]=d-_,e[10]=1-u-f,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}});var are=ye((nir,nre)=>{nre.exports=_rt;function _rt(e,t,r,n,i,a,o){var s=1/(r-t),l=1/(i-n),u=1/(a-o);return e[0]=a*2*s,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=a*2*l,e[6]=0,e[7]=0,e[8]=(r+t)*s,e[9]=(i+n)*l,e[10]=(o+a)*u,e[11]=-1,e[12]=0,e[13]=0,e[14]=o*a*2*u,e[15]=0,e}});var sre=ye((air,ore)=>{ore.exports=xrt;function xrt(e,t,r,n,i){var a=1/Math.tan(t/2),o=1/(n-i);return e[0]=a/r,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=a,e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[10]=(i+n)*o,e[11]=-1,e[12]=0,e[13]=0,e[14]=2*i*n*o,e[15]=0,e}});var ure=ye((oir,lre)=>{lre.exports=brt;function brt(e,t,r,n){var i=Math.tan(t.upDegrees*Math.PI/180),a=Math.tan(t.downDegrees*Math.PI/180),o=Math.tan(t.leftDegrees*Math.PI/180),s=Math.tan(t.rightDegrees*Math.PI/180),l=2/(o+s),u=2/(i+a);return e[0]=l,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=u,e[6]=0,e[7]=0,e[8]=-((o-s)*l*.5),e[9]=(i-a)*u*.5,e[10]=n/(r-n),e[11]=-1,e[12]=0,e[13]=0,e[14]=n*r/(r-n),e[15]=0,e}});var fre=ye((sir,cre)=>{cre.exports=wrt;function wrt(e,t,r,n,i,a,o){var s=1/(t-r),l=1/(n-i),u=1/(a-o);return e[0]=-2*s,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=-2*l,e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[10]=2*u,e[11]=0,e[12]=(t+r)*s,e[13]=(i+n)*l,e[14]=(o+a)*u,e[15]=1,e}});var dre=ye((lir,hre)=>{var Trt=zO();hre.exports=Art;function Art(e,t,r,n){var i,a,o,s,l,u,c,f,h,d,v=t[0],_=t[1],b=t[2],p=n[0],k=n[1],E=n[2],S=r[0],L=r[1],x=r[2];return Math.abs(v-S)<1e-6&&Math.abs(_-L)<1e-6&&Math.abs(b-x)<1e-6?Trt(e):(c=v-S,f=_-L,h=b-x,d=1/Math.sqrt(c*c+f*f+h*h),c*=d,f*=d,h*=d,i=k*h-E*f,a=E*c-p*h,o=p*f-k*c,d=Math.sqrt(i*i+a*a+o*o),d?(d=1/d,i*=d,a*=d,o*=d):(i=0,a=0,o=0),s=f*o-h*a,l=h*i-c*o,u=c*a-f*i,d=Math.sqrt(s*s+l*l+u*u),d?(d=1/d,s*=d,l*=d,u*=d):(s=0,l=0,u=0),e[0]=i,e[1]=s,e[2]=c,e[3]=0,e[4]=a,e[5]=l,e[6]=f,e[7]=0,e[8]=o,e[9]=u,e[10]=h,e[11]=0,e[12]=-(i*v+a*_+o*b),e[13]=-(s*v+l*_+u*b),e[14]=-(c*v+f*_+h*b),e[15]=1,e)}});var pre=ye((uir,vre)=>{vre.exports=Srt;function Srt(e){return\"mat4(\"+e[0]+\", \"+e[1]+\", \"+e[2]+\", \"+e[3]+\", \"+e[4]+\", \"+e[5]+\", \"+e[6]+\", \"+e[7]+\", \"+e[8]+\", \"+e[9]+\", \"+e[10]+\", \"+e[11]+\", \"+e[12]+\", \"+e[13]+\", \"+e[14]+\", \"+e[15]+\")\"}});var OO=ye((cir,gre)=>{gre.exports={create:vte(),clone:gte(),copy:yte(),identity:zO(),transpose:bte(),invert:Tte(),adjoint:Ste(),determinant:Ete(),multiply:Cte(),translate:Pte(),scale:Rte(),rotate:Fte(),rotateX:Ote(),rotateY:Bte(),rotateZ:Ute(),fromRotation:Gte(),fromRotationTranslation:jte(),fromScaling:Xte(),fromTranslation:Yte(),fromXRotation:Jte(),fromYRotation:Qte(),fromZRotation:tre(),fromQuat:ire(),frustum:are(),perspective:sre(),perspectiveFromFieldOfView:ure(),ortho:fre(),lookAt:dre(),str:pre()}});var T6=ye(fh=>{\"use strict\";var Mrt=OO();fh.init2dArray=function(e,t){for(var r=new Array(e),n=0;n<e;n++)r[n]=new Array(t);return r};fh.transposeRagged=function(e){var t=0,r=e.length,n,i;for(n=0;n<r;n++)t=Math.max(t,e[n].length);var a=new Array(t);for(n=0;n<t;n++)for(a[n]=new Array(r),i=0;i<r;i++)a[n][i]=e[i][n];return a};fh.dot=function(e,t){if(!(e.length&&t.length)||e.length!==t.length)return null;var r=e.length,n,i;if(e[0].length)for(n=new Array(r),i=0;i<r;i++)n[i]=fh.dot(e[i],t);else if(t[0].length){var a=fh.transposeRagged(t);for(n=new Array(a.length),i=0;i<a.length;i++)n[i]=fh.dot(e,a[i])}else for(n=0,i=0;i<r;i++)n+=e[i]*t[i];return n};fh.translationMatrix=function(e,t){return[[1,0,e],[0,1,t],[0,0,1]]};fh.rotationMatrix=function(e){var t=e*Math.PI/180;return[[Math.cos(t),-Math.sin(t),0],[Math.sin(t),Math.cos(t),0],[0,0,1]]};fh.rotationXYMatrix=function(e,t,r){return fh.dot(fh.dot(fh.translationMatrix(t,r),fh.rotationMatrix(e)),fh.translationMatrix(-t,-r))};fh.apply3DTransform=function(e){return function(){var t=arguments,r=arguments.length===1?t[0]:[t[0],t[1],t[2]||0];return fh.dot(e,[r[0],r[1],r[2],1]).slice(0,3)}};fh.apply2DTransform=function(e){return function(){var t=arguments;t.length===3&&(t=t[0]);var r=arguments.length===1?t[0]:[t[0],t[1]];return 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.maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' viewBox='0 0 29 29'%3E%3Cpath d='M10 13c-.75 0-1.5.75-1.5 1.5S9.25 16 10 16h9c.75 0 1.5-.75 1.5-1.5S19.75 13 19 13z'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-zoom-in .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' viewBox='0 0 29 29'%3E%3Cpath d='M14.5 8.5c-.75 0-1.5.75-1.5 1.5v3h-3c-.75 0-1.5.75-1.5 1.5S9.25 16 10 16h3v3c0 .75.75 1.5 1.5 1.5S16 19.75 16 19v-3h3c.75 0 1.5-.75 1.5-1.5S19.75 13 19 13h-3v-3c0-.75-.75-1.5-1.5-1.5'/%3E%3C/svg%3E\")}}.maplibregl-ctrl button.maplibregl-ctrl-fullscreen .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23333' viewBox='0 0 29 29'%3E%3Cpath d='M24 16v5.5c0 1.75-.75 2.5-2.5 2.5H16v-1l3-1.5-4-5.5 1-1 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d='M24 16v5.5c0 1.75-.75 2.5-2.5 2.5H16v-1l3-1.5-4-5.5 1-1 5.5 4 1.5-3zM6 16l1.5 3 5.5-4 1 1-4 5.5 3 1.5v1H7.5C5.75 24 5 23.25 5 21.5V16zm7-11v1l-3 1.5 4 5.5-1 1-5.5-4L6 13H5V7.5C5 5.75 5.75 5 7.5 5zm11 2.5c0-1.75-.75-2.5-2.5-2.5H16v1l3 1.5-4 5.5 1 1 5.5-4 1.5 3h1z'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-shrink .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23fff' viewBox='0 0 29 29'%3E%3Cpath d='M18.5 16c-1.75 0-2.5.75-2.5 2.5V24h1l1.5-3 5.5 4 1-1-4-5.5 3-1.5v-1zM13 18.5c0-1.75-.75-2.5-2.5-2.5H5v1l3 1.5L4 24l1 1 5.5-4 1.5 3h1zm3-8c0 1.75.75 2.5 2.5 2.5H24v-1l-3-1.5L25 5l-1-1-5.5 4L17 5h-1zM10.5 13c1.75 0 2.5-.75 2.5-2.5V5h-1l-1.5 3L5 4 4 5l4 5.5L5 12v1z'/%3E%3C/svg%3E\")}}@media (forced-colors:active) and (prefers-color-scheme:light){.maplibregl-ctrl button.maplibregl-ctrl-fullscreen 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o={redraw:i.redraw},s={},l=[];return o.prepareFn=function(){for(var u=Array.isArray(t)?t.length:0,c=n.slice(0,u),f=0;f<c.length;f++){var h=c[f],d=e._fullData[h],v=d._module;if(v){if(v.animatable){var _=v.basePlotModule.name;s[_]||(s[_]=[]),s[_].push(h)}e.data[c[f]]=xa.extendTrace(e.data[c[f]],t[f])}}var b=ja.expandObjectPaths(ja.extendDeepNoArrays({},r)),p=/^[xy]axis[0-9]*$/;for(var k in b)p.test(k)&&delete b[k].range;xa.extendLayout(e.layout,b),delete e.calcdata,xa.supplyDefaults(e),xa.doCalcdata(e);var E=ja.expandObjectPaths(r);if(E){var S=e._fullLayout._plots;for(var L in S){var 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nL=lb(),M3=pv();loe.exports={moduleType:\"component\",name:\"colorscale\",attributes:Tu(),layoutAttributes:wq(),supplyLayoutDefaults:ioe(),handleDefaults:Qh(),crossTraceDefaults:aoe(),calc:gv(),scales:nL.scales,defaultScale:nL.defaultScale,getScale:nL.get,isValidScale:nL.isValid,hasColorscale:M3.hasColorscale,extractOpts:M3.extractOpts,extractScale:M3.extractScale,flipScale:M3.flipScale,makeColorScaleFunc:M3.makeColorScaleFunc,makeColorScaleFuncFromTrace:M3.makeColorScaleFuncFromTrace}});var Ru=ye((znr,coe)=>{\"use strict\";var uoe=Dr(),Sot=vv().isTypedArraySpec;coe.exports={hasLines:function(e){return e.visible&&e.mode&&e.mode.indexOf(\"lines\")!==-1},hasMarkers:function(e){return e.visible&&(e.mode&&e.mode.indexOf(\"markers\")!==-1||e.type===\"splom\")},hasText:function(e){return e.visible&&e.mode&&e.mode.indexOf(\"text\")!==-1},isBubble:function(e){var t=e.marker;return uoe.isPlainObject(t)&&(uoe.isArrayOrTypedArray(t.size)||Sot(t.size))}}});var E3=ye((Onr,foe)=>{\"use strict\";var 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e===\"solid\"?e=\"\":e===\"dot\"?e=r+\"px,\"+r+\"px\":e===\"dash\"?e=3*r+\"px,\"+3*r+\"px\":e===\"longdash\"?e=5*r+\"px,\"+5*r+\"px\":e===\"dashdot\"?e=3*r+\"px,\"+r+\"px,\"+r+\"px,\"+r+\"px\":e===\"longdashdot\"&&(e=5*r+\"px,\"+2*r+\"px,\"+r+\"px,\"+2*r+\"px\"),e};function Ioe(e,t,r,n){var i=t.fillpattern,a=t.fillgradient,o=Aa.getPatternAttr,s=i&&(o(i.shape,0,\"\")||o(i.path,0,\"\"));if(s){var l=o(i.bgcolor,0,null),u=o(i.fgcolor,0,null),c=i.fgopacity,f=o(i.size,0,8),h=o(i.solidity,0,.3),d=t.uid;Aa.pattern(e,\"point\",r,d,s,f,h,void 0,i.fillmode,l,u,c)}else if(a&&a.type!==\"none\"){var v=a.type,_=\"scatterfill-\"+t.uid;if(n&&(_=\"legendfill-\"+t.uid),!n&&(a.start!==void 0||a.stop!==void 0)){var b,p;v===\"horizontal\"?(b={x:a.start,y:0},p={x:a.stop,y:0}):v===\"vertical\"&&(b={x:0,y:a.start},p={x:0,y:a.stop}),b.x=t._xA.c2p(b.x===void 0?t._extremes.x.min[0].val:b.x,!0),b.y=t._yA.c2p(b.y===void 0?t._extremes.y.min[0].val:b.y,!0),p.x=t._xA.c2p(p.x===void 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t=woe[e],r=t.n;Aa.symbolList.push(r,String(r),e,r+100,String(r+100),e+\"-open\"),Aa.symbolNames[r]=e,Aa.symbolFuncs[r]=t.f,Aa.symbolBackOffs[r]=t.backoff||0,t.needLine&&(Aa.symbolNeedLines[r]=!0),t.noDot?Aa.symbolNoDot[r]=!0:Aa.symbolList.push(r+200,String(r+200),e+\"-dot\",r+300,String(r+300),e+\"-open-dot\"),t.noFill&&(Aa.symbolNoFill[r]=!0)});var Wot=Aa.symbolNames.length,Xot=\"M0,0.5L0.5,0L0,-0.5L-0.5,0Z\";Aa.symbolNumber=function(e){if(Sb(e))e=+e;else if(typeof e==\"string\"){var t=0;e.indexOf(\"-open\")>0&&(t=100,e=e.replace(\"-open\",\"\")),e.indexOf(\"-dot\")>0&&(t+=200,e=e.replace(\"-dot\",\"\")),e=Aa.symbolNames.indexOf(e),e>=0&&(e+=t)}return e%100>=Wot||e>=400?0:Math.floor(Math.max(e,0))};function Roe(e,t,r,n){var i=e%100;return Aa.symbolFuncs[i](t,r,n)+(e>=200?Xot:\"\")}var Toe=Fot(\"~f\"),Doe={radial:{type:\"radial\"},radialreversed:{type:\"radial\",reversed:!0},horizontal:{type:\"linear\",start:{x:1,y:0},stop:{x:0,y:0}},horizontalreversed:{type:\"linear\",start:{x:1,y:0},stop:{x:0,y:0},reversed:!0},vertical:{type:\"linear\",start:{x:0,y:1},stop:{x:0,y:0}},verticalreversed:{type:\"linear\",start:{x:0,y:1},stop:{x:0,y:0},reversed:!0}};Aa.gradient=function(e,t,r,n,i,a){var o=Doe[n];return Foe(e,t,r,o.type,i,a,o.start,o.stop,!1,o.reversed)};function Foe(e,t,r,n,i,a,o,s,l,u){var c=i.length,f;n===\"linear\"?f={node:\"linearGradient\",attrs:{x1:o.x,y1:o.y,x2:s.x,y2:s.y,gradientUnits:l?\"userSpaceOnUse\":\"objectBoundingBox\"},reversed:u}:n===\"radial\"&&(f={node:\"radialGradient\",reversed:u});for(var h=new Array(c),d=0;d<c;d++)f.reversed?h[c-1-d]=[Toe((1-i[d][0])*100),i[d][1]]:h[d]=[Toe(i[d][0]*100),i[d][1]];var v=t._fullLayout,_=\"g\"+v._uid+\"-\"+r,b=v._defs.select(\".gradients\").selectAll(\"#\"+_).data([n+h.join(\";\")],Du.identity);b.exit().remove(),b.enter().append(f.node).each(function(){var p=dd.select(this);f.attrs&&p.attr(f.attrs),p.attr(\"id\",_);var k=p.selectAll(\"stop\").data(h);k.exit().remove(),k.enter().append(\"stop\"),k.each(function(E){var S=Gq(E[1]);dd.select(this).attr({offset:E[0]+\"%\",\"stop-color\":Kd.tinyRGB(S),\"stop-opacity\":S.getAlpha()})})}),e.style(a,Hq(_,t)).style(a+\"-opacity\",null),e.classed(\"gradient_filled\",!0)}Aa.pattern=function(e,t,r,n,i,a,o,s,l,u,c,f){var h=t===\"legend\";s&&(l===\"overlay\"?(u=s,c=Kd.contrast(u)):(u=void 0,c=s));var d=r._fullLayout,v=\"p\"+d._uid+\"-\"+n,_,b,p=function(O,V,G,Z,H){return Z+(H-Z)*(O-V)/(G-V)},k,E,S,L,x={},C=Gq(c),M=Kd.tinyRGB(C),g=C.getAlpha(),P=f*g;switch(i){case\"/\":_=a*Math.sqrt(2),b=a*Math.sqrt(2),k=\"M-\"+_/4+\",\"+b/4+\"l\"+_/2+\",-\"+b/2+\"M0,\"+b+\"L\"+_+\",0M\"+_/4*3+\",\"+b/4*5+\"l\"+_/2+\",-\"+b/2,E=o*a,L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\"\\\\\":_=a*Math.sqrt(2),b=a*Math.sqrt(2),k=\"M\"+_/4*3+\",-\"+b/4+\"l\"+_/2+\",\"+b/2+\"M0,0L\"+_+\",\"+b+\"M-\"+_/4+\",\"+b/4*3+\"l\"+_/2+\",\"+b/2,E=o*a,L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\"x\":_=a*Math.sqrt(2),b=a*Math.sqrt(2),k=\"M-\"+_/4+\",\"+b/4+\"l\"+_/2+\",-\"+b/2+\"M0,\"+b+\"L\"+_+\",0M\"+_/4*3+\",\"+b/4*5+\"l\"+_/2+\",-\"+b/2+\"M\"+_/4*3+\",-\"+b/4+\"l\"+_/2+\",\"+b/2+\"M0,0L\"+_+\",\"+b+\"M-\"+_/4+\",\"+b/4*3+\"l\"+_/2+\",\"+b/2,E=a-a*Math.sqrt(1-o),L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\"|\":_=a,b=a,L=\"path\",k=\"M\"+_/2+\",0L\"+_/2+\",\"+b,E=o*a,L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\"-\":_=a,b=a,L=\"path\",k=\"M0,\"+b/2+\"L\"+_+\",\"+b/2,E=o*a,L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\"+\":_=a,b=a,L=\"path\",k=\"M\"+_/2+\",0L\"+_/2+\",\"+b+\"M0,\"+b/2+\"L\"+_+\",\"+b/2,E=a-a*Math.sqrt(1-o),L=\"path\",x={d:k,opacity:P,stroke:M,\"stroke-width\":E+\"px\"};break;case\".\":_=a,b=a,o<Math.PI/4?S=Math.sqrt(o*a*a/Math.PI):S=p(o,Math.PI/4,1,a/2,a/Math.sqrt(2)),L=\"circle\",x={cx:_/2,cy:b/2,r:S,opacity:P,fill:M};break;default:_=a,b=a,L=\"path\",x={d:i,opacity:P,fill:M};break}var T=[i||\"noSh\",u||\"noBg\",c||\"noFg\",a,o].join(\";\"),z=d._defs.select(\".patterns\").selectAll(\"#\"+v).data([T],Du.identity);z.exit().remove(),z.enter().append(\"pattern\").each(function(){var O=dd.select(this);if(O.attr({id:v,width:_+\"px\",height:b+\"px\",patternUnits:\"userSpaceOnUse\",patternTransform:h?\"scale(0.8)\":\"\"}),u){var V=Gq(u),G=Kd.tinyRGB(V),Z=V.getAlpha(),H=O.selectAll(\"rect\").data([0]);H.exit().remove(),H.enter().append(\"rect\").attr({width:_+\"px\",height:b+\"px\",fill:G,\"fill-opacity\":Z})}var N=O.selectAll(L).data([0]);N.exit().remove(),N.enter().append(L).attr(x)}),e.style(\"fill\",Hq(v,r)).style(\"fill-opacity\",null),e.classed(\"pattern_filled\",!0)};Aa.initGradients=function(e){var t=e._fullLayout,r=Du.ensureSingle(t._defs,\"g\",\"gradients\");r.selectAll(\"linearGradient,radialGradient\").remove(),dd.select(e).selectAll(\".gradient_filled\").classed(\"gradient_filled\",!1)};Aa.initPatterns=function(e){var t=e._fullLayout,r=Du.ensureSingle(t._defs,\"g\",\"patterns\");r.selectAll(\"pattern\").remove(),dd.select(e).selectAll(\".pattern_filled\").classed(\"pattern_filled\",!1)};Aa.getPatternAttr=function(e,t,r){return e&&Du.isArrayOrTypedArray(e)?t<e.length?e[t]:r:e};Aa.pointStyle=function(e,t,r,n){if(e.size()){var i=Aa.makePointStyleFns(t);e.each(function(a){Aa.singlePointStyle(a,dd.select(this),t,i,r,n)})}};Aa.singlePointStyle=function(e,t,r,n,i,a){var o=r.marker,s=o.line;if(a&&a.i>=0&&e.i===void 0&&(e.i=a.i),t.style(\"opacity\",n.selectedOpacityFn?n.selectedOpacityFn(e):e.mo===void 0?o.opacity:e.mo),n.ms2mrc){var l;e.ms===\"various\"||o.size===\"various\"?l=3:l=n.ms2mrc(e.ms),e.mrc=l,n.selectedSizeFn&&(l=e.mrc=n.selectedSizeFn(e));var u=Aa.symbolNumber(e.mx||o.symbol)||0;e.om=u%200>=100;var c=Wq(e,r),f=jq(e,r);t.attr(\"d\",Roe(u,l,c,f))}var h=!1,d,v,_;if(e.so)_=s.outlierwidth,v=s.outliercolor,d=o.outliercolor;else{var b=(s||{}).width;_=(e.mlw+1||b+1||(e.trace?(e.trace.marker.line||{}).width:0)+1)-1||0,\"mlc\"in e?v=e.mlcc=n.lineScale(e.mlc):Du.isArrayOrTypedArray(s.color)?v=Kd.defaultLine:v=s.color,Du.isArrayOrTypedArray(o.color)&&(d=Kd.defaultLine,h=!0),\"mc\"in e?d=e.mcc=n.markerScale(e.mc):d=o.color||o.colors||\"rgba(0,0,0,0)\",n.selectedColorFn&&(d=n.selectedColorFn(e))}if(e.om)t.call(Kd.stroke,d).style({\"stroke-width\":(_||1)+\"px\",fill:\"none\"});else{t.style(\"stroke-width\",(e.isBlank?0:_)+\"px\");var p=o.gradient,k=e.mgt;k?h=!0:k=p&&p.type,Du.isArrayOrTypedArray(k)&&(k=k[0],Doe[k]||(k=0));var E=o.pattern,S=Aa.getPatternAttr,L=E&&(S(E.shape,e.i,\"\")||S(E.path,e.i,\"\"));if(k&&k!==\"none\"){var x=e.mgc;x?h=!0:x=p.color;var C=r.uid;h&&(C+=\"-\"+e.i),Aa.gradient(t,i,C,k,[[0,x],[1,d]],\"fill\")}else if(L){var M=!1,g=E.fgcolor;!g&&a&&a.color&&(g=a.color,M=!0);var P=S(g,e.i,a&&a.color||null),T=S(E.bgcolor,e.i,null),z=E.fgopacity,O=S(E.size,e.i,8),V=S(E.solidity,e.i,.3);M=M||e.mcc||Du.isArrayOrTypedArray(E.shape)||Du.isArrayOrTypedArray(E.path)||Du.isArrayOrTypedArray(E.bgcolor)||Du.isArrayOrTypedArray(E.fgcolor)||Du.isArrayOrTypedArray(E.size)||Du.isArrayOrTypedArray(E.solidity);var G=r.uid;M&&(G+=\"-\"+e.i),Aa.pattern(t,\"point\",i,G,L,O,V,e.mcc,E.fillmode,T,P,z)}else Du.isArrayOrTypedArray(d)?Kd.fill(t,d[e.i]):Kd.fill(t,d);_&&Kd.stroke(t,v)}};Aa.makePointStyleFns=function(e){var t={},r=e.marker;return t.markerScale=Aa.tryColorscale(r,\"\"),t.lineScale=Aa.tryColorscale(r,\"line\"),sL.traceIs(e,\"symbols\")&&(t.ms2mrc=Not.isBubble(e)?Uot(e):function(){return(r.size||6)/2}),e.selectedpoints&&Du.extendFlat(t,Aa.makeSelectedPointStyleFns(e)),t};Aa.makeSelectedPointStyleFns=function(e){var t={},r=e.selected||{},n=e.unselected||{},i=e.marker||{},a=r.marker||{},o=n.marker||{},s=i.opacity,l=a.opacity,u=o.opacity,c=l!==void 0,f=u!==void 0;(Du.isArrayOrTypedArray(s)||c||f)&&(t.selectedOpacityFn=function(S){var L=S.mo===void 0?i.opacity:S.mo;return S.selected?c?l:L:f?u:Poe*L});var h=i.color,d=a.color,v=o.color;(d||v)&&(t.selectedColorFn=function(S){var L=S.mcc||h;return S.selected?d||L:v||L});var _=i.size,b=a.size,p=o.size,k=b!==void 0,E=p!==void 0;return sL.traceIs(e,\"symbols\")&&(k||E)&&(t.selectedSizeFn=function(S){var L=S.mrc||_/2;return S.selected?k?b/2:L:E?p/2:L}),t};Aa.makeSelectedTextStyleFns=function(e){var t={},r=e.selected||{},n=e.unselected||{},i=e.textfont||{},a=r.textfont||{},o=n.textfont||{},s=i.color,l=a.color,u=o.color;return t.selectedTextColorFn=function(c){var f=c.tc||s;return c.selected?l||f:u||(l?f:Kd.addOpacity(f,Poe))},t};Aa.selectedPointStyle=function(e,t){if(!(!e.size()||!t.selectedpoints)){var r=Aa.makeSelectedPointStyleFns(t),n=t.marker||{},i=[];r.selectedOpacityFn&&i.push(function(a,o){a.style(\"opacity\",r.selectedOpacityFn(o))}),r.selectedColorFn&&i.push(function(a,o){Kd.fill(a,r.selectedColorFn(o))}),r.selectedSizeFn&&i.push(function(a,o){var s=o.mx||n.symbol||0,l=r.selectedSizeFn(o);a.attr(\"d\",Roe(Aa.symbolNumber(s),l,Wq(o,t),jq(o,t))),o.mrc2=l}),i.length&&e.each(function(a){for(var o=dd.select(this),s=0;s<i.length;s++)i[s](o,a)})}};Aa.tryColorscale=function(e,t){var r=t?Du.nestedProperty(e,t).get():e;if(r){var n=r.color;if((r.colorscale||r._colorAx)&&Du.isArrayOrTypedArray(n))return zot.makeColorScaleFuncFromTrace(r)}return Du.identity};var Bq={start:1,end:-1,middle:0,bottom:1,top:-1};function zoe(e,t,r,n,i){var a=dd.select(e.node().parentNode),o=t.indexOf(\"top\")!==-1?\"top\":t.indexOf(\"bottom\")!==-1?\"bottom\":\"middle\",s=t.indexOf(\"left\")!==-1?\"end\":t.indexOf(\"right\")!==-1?\"start\":\"middle\",l=n?n/.8+1:0,u=(lL.lineCount(e)-1)*Bot+1,c=Bq[s]*l,f=r*.75+Bq[o]*l+(Bq[o]-1)*u*r/2;e.attr(\"text-anchor\",s),i||a.attr(\"transform\",tM(c,f))}function Ooe(e,t){var r=e.ts||t.textfont.size;return Sb(r)&&r>0?r:0}Aa.textPointStyle=function(e,t,r){if(e.size()){var n;if(t.selectedpoints){var i=Aa.makeSelectedTextStyleFns(t);n=i.selectedTextColorFn}var a=t.texttemplate,o=r._fullLayout;e.each(function(s){var l=dd.select(this),u=a?Du.extractOption(s,t,\"txt\",\"texttemplate\"):Du.extractOption(s,t,\"tx\",\"text\");if(!u&&u!==0){l.remove();return}if(a){var c=t._module.formatLabels,f=c?c(s,t,o):{},h={};Vot(h,t,s.i),u=Du.texttemplateString({data:[h,s,t._meta],fallback:t.texttemplatefallback,labels:f,locale:o._d3locale,template:u})}var 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n=e.nticks,i;n||(e.type===\"category\"||e.type===\"multicategory\"?(i=e.tickfont?Jo.bigFont(e.tickfont.size||12):15,n=e._length/i):(i=e._id.charAt(0)===\"y\"?40:80,n=Jo.constrain(e._length/i,4,9)+1),e._name===\"radialaxis\"&&(n*=2)),e.minor&&e.minor.tickmode!==\"array\"||e.tickmode===\"array\"&&(n*=100),e._roughDTick=Math.abs(r[1]-r[0])/n,Qn.autoTicks(e,e._roughDTick),e._minDtick>0&&e.dtick<e._minDtick*2&&(e.dtick=e._minDtick,e.tick0=e.l2r(e._forceTick0))}e.ticklabelmode===\"period\"&&Hst(e),e.tick0||(e.tick0=e.type===\"date\"?\"2000-01-01\":0),e.type===\"date\"&&e.dtick<.1&&(e.dtick=.1),Sse(e)};function nB(e){return+e.substring(1)}function Hst(e){var t;function r(){return!(Ih(e.dtick)||e.dtick.charAt(0)!==\"M\")}var n=r(),i=Qn.getTickFormat(e);if(i){var a=e._dtickInit!==e.dtick;/%[fLQsSMX]/.test(i)||(/%[HI]/.test(i)?(t=xm,a&&!n&&e.dtick<xm&&(e.dtick=xm)):/%p/.test(i)?(t=s_,a&&!n&&e.dtick<s_&&(e.dtick=s_)):/%[Aadejuwx]/.test(i)?(t=Ov,a&&!n&&e.dtick<Ov&&(e.dtick=Ov)):/%[UVW]/.test(i)?(t=Zp,a&&!n&&e.dtick<Zp&&(e.dtick=Zp)):/%[Bbm]/.test(i)?(t=F3,a&&(n?nB(e.dtick)<1:e.dtick<ML)&&(e.dtick=\"M1\")):/%[q]/.test(i)?(t=oB,a&&(n?nB(e.dtick)<3:e.dtick<SL)&&(e.dtick=\"M3\")):/%[Yy]/.test(i)&&(t=TL,a&&(n?nB(e.dtick)<12:e.dtick<AL)&&(e.dtick=\"M12\")))}n=r(),n&&e.tick0===e._dowTick0&&(e.tick0=e._rawTick0),e._definedDelta=t}function jst(e,t,r){for(var n=0;n<e.length;n++){var i=e[n].value,a=n,o=n+1;n<e.length-1?(a=n,o=n+1):n>0?(a=n-1,o=n):(a=n,o=n);var s=e[a].value,l=e[o].value,u=Math.abs(l-s),c=r||u,f=0;c>=AL?u>=AL&&u<=Pst?f=u:f=TL:r===oB&&c>=SL?u>=SL&&u<=Ist?f=u:f=oB:c>=ML?u>=ML&&u<=Rst?f=u:f=F3:r===Zp&&c>=Zp?f=Zp:c>=Ov?f=Ov:r===s_&&c>=s_?f=s_:r===xm&&c>=xm&&(f=xm);var h;f>=u&&(f=u,h=!0);var d=i+f;if(t.rangebreaks&&f>0){for(var v=84,_=0,b=0;b<v;b++){var p=(b+.5)/v;t.maskBreaks(i*(1-p)+p*d)!==CL&&_++}f*=_/v,f||(e[n].drop=!0),h&&u>Zp&&(f=u)}(f>0||n===0)&&(e[n].periodX=i+f/2)}}Qn.calcTicks=function(t,r){for(var n=t.type,i=t.calendar,a=t.ticklabelstep,o=t.ticklabelmode===\"period\",s=t.range[0]>t.range[1],l=!t.ticklabelindex||Jo.isArrayOrTypedArray(t.ticklabelindex)?t.ticklabelindex:[t.ticklabelindex],u=Jo.simpleMap(t.range,t.r2l,void 0,void 0,r),c=u[1]<u[0],f=Math.min(u[0],u[1]),h=Math.max(u[0],u[1]),d=Math.max(1e3,t._length||0),v=[],_=[],b=[],p=[],k=[],E=t.minor&&(t.minor.ticks||t.minor.showgrid),S=1;S>=(E?0:1);S--){var L=!S;S?(t._dtickInit=t.dtick,t._tick0Init=t.tick0):(t.minor._dtickInit=t.minor.dtick,t.minor._tick0Init=t.minor.tick0);var x=S?t:Jo.extendFlat({},t,t.minor);if(L?Qn.prepMinorTicks(x,t,r):Qn.prepTicks(x,r),x.tickmode===\"array\"){S?(b=[],v=pse(t,!L)):(p=[],_=pse(t,!L));continue}if(x.tickmode===\"sync\"){b=[],v=Wst(t);continue}var C=dB(u),M=C[0],g=C[1],P=Ih(x.dtick),T=n===\"log\"&&!(P||x.dtick.charAt(0)===\"L\"),z=Qn.tickFirst(x,r);if(S){if(t._tmin=z,z<M!==c)break;(n===\"category\"||n===\"multicategory\")&&(g=c?Math.max(-.5,g):Math.min(t._categories.length-.5,g))}var O=null,V=z,G;if(S){var Z;P?Z=t.dtick:n===\"date\"?typeof t.dtick==\"string\"&&t.dtick.charAt(0)===\"M\"&&(Z=F3*t.dtick.substring(1)):Z=t._roughDTick,G=Math.round((t.r2l(V)-t.r2l(t.tick0))/Z)-1}var H=x.dtick;for(x.rangebreaks&&x._tick0Init!==x.tick0&&(V=aB(V,t),c||(V=Qn.tickIncrement(V,H,!c,i))),S&&o&&(V=Qn.tickIncrement(V,H,!c,i),G--);c?V>=g:V<=g;V=Qn.tickIncrement(V,H,c,i)){if(S&&G++,x.rangebreaks&&!c){if(V<M)continue;if(x.maskBreaks(V)===CL&&aB(V,x)>=h)break}if(b.length>d||V===O)break;O=V;var N={value:V};S?(T&&V!==(V|0)&&(N.simpleLabel=!0),a>1&&G%a&&(N.skipLabel=!0),b.push(N)):(N.minor=!0,p.push(N))}}if(!p||p.length<2)l=!1;else{var j=(p[1].value-p[0].value)*(s?-1:1);mlt(j,t.tickformat)||(l=!1)}if(!l)k=b;else{var re=b.concat(p);o&&b.length&&(re=re.slice(1)),re=re.sort(function(Gt,Nt){return Gt.value-Nt.value}).filter(function(Gt,Nt,Jt){return Nt===0||Gt.value!==Jt[Nt-1].value});var oe=re.map(function(Gt,Nt){return Gt.minor===void 0&&!Gt.skipLabel?Nt:null}).filter(function(Gt){return Gt!==null});oe.forEach(function(Gt){l.map(function(Nt){var Jt=Gt+Nt;Jt>=0&&Jt<re.length&&Jo.pushUnique(k,re[Jt])})})}if(E){var _e=t.minor.ticks===\"inside\"&&t.ticks===\"outside\"||t.minor.ticks===\"outside\"&&t.ticks===\"inside\";if(!_e){for(var Ee=b.map(function(Gt){return Gt.value}),Ce=[],me=0;me<p.length;me++){var ie=p[me],Se=ie.value;if(Ee.indexOf(Se)===-1){for(var Le=!1,Ae=0;!Le&&Ae<b.length;Ae++)1e7+b[Ae].value===1e7+Se&&(Le=!0);Le||Ce.push(ie)}}p=Ce}}o&&jst(k,t,t._definedDelta);var Fe;if(t.rangebreaks){var Pe=t._id.charAt(0)===\"y\",ge=1;t.tickmode===\"auto\"&&(ge=t.tickfont?t.tickfont.size:12);var Re=NaN;for(Fe=b.length-1;Fe>-1;Fe--){if(b[Fe].drop){b.splice(Fe,1);continue}b[Fe].value=aB(b[Fe].value,t);var ce=t.c2p(b[Fe].value);(Pe?Re>ce-ge:Re<ce+ge)?b.splice(c?Fe+1:Fe,1):Re=ce}}mB(t)&&Math.abs(u[1]-u[0])===360&&b.pop(),t._tmax=(b[b.length-1]||{}).value,t._prevDateHead=\"\",t._inCalcTicks=!0;var Ze,ut=function(Gt){Gt.text=\"\",t._prevDateHead=Ze};b=b.concat(p);function pt(Gt,Nt){var Jt=Qn.tickText(Gt,Nt.value,!1,Nt.simpleLabel),sr=Nt.periodX;return sr!==void 0&&(Jt.periodX=sr,(sr>h||sr<f)&&(sr>h&&(Jt.periodX=h),sr<f&&(Jt.periodX=f),ut(Jt))),Jt}var Zt;for(Fe=0;Fe<b.length;Fe++){var st=b[Fe].minor,lt=b[Fe].value;st?(l&&k.indexOf(b[Fe])!==-1?Zt=pt(t,b[Fe]):Zt={x:lt},Zt.minor=!0,_.push(Zt)):(Ze=t._prevDateHead,Zt=pt(t,b[Fe]),(b[Fe].skipLabel||l&&k.indexOf(b[Fe])===-1)&&ut(Zt),v.push(Zt))}return v=v.concat(_),t._inCalcTicks=!1,o&&v.length&&(v[0].noTick=!0),v};function wse(e,t){return e.rangebreaks&&(t=t.filter(function(r){return e.maskBreaks(r.x)!==CL})),t}function Wst(e){var t=e._mainAxis,r=[];if(t._vals){for(var n=0;n<t._vals.length;n++)if(!t._vals[n].noTick){var i=t.l2p(t._vals[n].x),a=e.p2l(i),o=Qn.tickText(e,a);t._vals[n].minor&&(o.minor=!0,o.text=\"\"),r.push(o)}}return r=wse(e,r),r}function pse(e,t){var r=Jo.simpleMap(e.range,e.r2l),n=dB(r),i=Math.min(n[0],n[1]),a=Math.max(n[0],n[1]),o=e.type===\"category\"?e.d2l_noadd:e.d2l;e.type===\"log\"&&String(e.dtick).charAt(0)!==\"L\"&&(e.dtick=\"L\"+Math.pow(10,Math.floor(Math.min(e.range[0],e.range[1]))-1));for(var s=[],l=0;l<=1;l++)if(!(t!==void 0&&(t&&l||t===!1&&!l))&&!(l&&!e.minor)){var u=l?e.minor.tickvals:e.tickvals,c=l?[]:e.ticktext;if(u){Jo.isArrayOrTypedArray(c)||(c=[]);for(var f=0;f<u.length;f++){var h=o(u[f]);if(h>i&&h<a){var d=Qn.tickText(e,h,!1,String(c[f]));l&&(d.minor=!0,d.text=\"\"),s.push(d)}}}}return s=wse(e,s),s}var bL=[2,5,10],gse=[1,2,3,6,12],mse=[1,2,5,10,15,30],Xst=[1,2,3,7,14],Tse=[-.046,0,.301,.477,.602,.699,.778,.845,.903,.954,1],Ase=[-.301,0,.301,.699,1],Zst=[15,30,45,90,180];function _m(e,t,r){return t*Jo.roundUp(e/t,r)}Qn.autoTicks=function(e,t,r){var n;function i(f){return Math.pow(f,Math.floor(Math.log(t)/Math.LN10))}if(e.type===\"date\"){e.tick0=Jo.dateTick0(e.calendar,0);var a=2*t;if(a>TL)t/=TL,n=i(10),e.dtick=\"M\"+12*_m(t,n,bL);else if(a>F3)t/=F3,e.dtick=\"M\"+_m(t,1,gse);else if(a>Ov){if(e.dtick=_m(t,Ov,e._hasDayOfWeekBreaks?[1,2,7,14]:Xst),!r){var o=Qn.getTickFormat(e),s=e.ticklabelmode===\"period\";s&&(e._rawTick0=e.tick0),/%[uVW]/.test(o)?e.tick0=Jo.dateTick0(e.calendar,2):e.tick0=Jo.dateTick0(e.calendar,1),s&&(e._dowTick0=e.tick0)}}else a>xm?e.dtick=_m(t,xm,gse):a>oM?e.dtick=_m(t,oM,mse):a>EL?e.dtick=_m(t,EL,mse):(n=i(10),e.dtick=_m(t,n,bL))}else if(e.type===\"log\"){e.tick0=0;var l=Jo.simpleMap(e.range,e.r2l);if(e._isMinor&&(t*=1.5),t>.7)e.dtick=Math.ceil(t);else if(Math.abs(l[1]-l[0])<1){var u=1.5*Math.abs((l[1]-l[0])/t);t=Math.abs(Math.pow(10,l[1])-Math.pow(10,l[0]))/u,n=i(10),e.dtick=\"L\"+_m(t,n,bL)}else e.dtick=t>.3?\"D2\":\"D1\"}else e.type===\"category\"||e.type===\"multicategory\"?(e.tick0=0,e.dtick=Math.ceil(Math.max(t,1))):mB(e)?(e.tick0=0,n=1,e.dtick=_m(t,n,Zst)):(e.tick0=0,n=i(10),e.dtick=_m(t,n,bL));if(e.dtick===0&&(e.dtick=1),!Ih(e.dtick)&&typeof e.dtick!=\"string\"){var c=e.dtick;throw e.dtick=1,\"ax.dtick error: \"+String(c)}};function Sse(e){var t=e.dtick;if(e._tickexponent=0,!Ih(t)&&typeof t!=\"string\"&&(t=1),(e.type===\"category\"||e.type===\"multicategory\")&&(e._tickround=null),e.type===\"date\"){var r=e.r2l(e.tick0),n=e.l2r(r).replace(/(^-|i)/g,\"\"),i=n.length;if(String(t).charAt(0)===\"M\")i>10||n.substr(5)!==\"01-01\"?e._tickround=\"d\":e._tickround=+t.substr(1)%12===0?\"y\":\"m\";else if(t>=Ov&&i<=10||t>=Ov*15)e._tickround=\"d\";else if(t>=oM&&i<=16||t>=xm)e._tickround=\"M\";else if(t>=EL&&i<=19||t>=oM)e._tickround=\"S\";else{var a=e.l2r(r+t).replace(/^-/,\"\").length;e._tickround=Math.max(i,a)-20,e._tickround<0&&(e._tickround=4)}}else if(Ih(t)||t.charAt(0)===\"L\"){var o=e.range.map(e.r2d||Number);Ih(t)||(t=Number(t.substr(1))),e._tickround=2-Math.floor(Math.log(t)/Math.LN10+.01);var s=Math.max(Math.abs(o[0]),Math.abs(o[1])),l=Math.floor(Math.log(s)/Math.LN10+.01),u=e.minexponent===void 0?3:e.minexponent;Math.abs(l)>u&&(z3(e.exponentformat)&&e.exponentformat!==\"SI extended\"&&!vB(l)||z3(e.exponentformat)&&e.exponentformat===\"SI extended\"&&!pB(l)?e._tickexponent=3*Math.round((l-1)/3):e._tickexponent=l)}else e._tickround=null}Qn.tickIncrement=function(e,t,r,n){var i=r?-1:1;if(Ih(t))return Jo.increment(e,i*t);var a=t.charAt(0),o=i*Number(t.substr(1));if(a===\"M\")return Jo.incrementMonth(e,o,n);if(a===\"L\")return Math.log(Math.pow(10,e)+o)/Math.LN10;if(a===\"D\"){var s=t===\"D2\"?Ase:Tse,l=e+i*.01,u=Jo.roundUp(Jo.mod(l,1),s,r);return Math.floor(l)+Math.log(b0.round(Math.pow(10,u),1))/Math.LN10}throw\"unrecognized dtick \"+String(t)};Qn.tickFirst=function(e,t){var r=e.r2l||Number,n=Jo.simpleMap(e.range,r,void 0,void 0,t),i=n[1]<n[0],a=i?Math.floor:Math.ceil,o=dB(n)[0],s=e.dtick,l=r(e.tick0);if(Ih(s)){var u=a((o-l)/s)*s+l;return(e.type===\"category\"||e.type===\"multicategory\")&&(u=Jo.constrain(u,0,e._categories.length-1)),u}var c=s.charAt(0),f=Number(s.substr(1));if(c===\"M\"){for(var h=0,d=l,v,_,b;h<10;){if(v=Qn.tickIncrement(d,s,i,e.calendar),(v-o)*(d-o)<=0)return i?Math.min(d,v):Math.max(d,v);_=(o-(d+v)/2)/(v-d),b=c+(Math.abs(Math.round(_))||1)*f,d=Qn.tickIncrement(d,b,_<0?!i:i,e.calendar),h++}return Jo.error(\"tickFirst did not converge\",e),d}else{if(c===\"L\")return Math.log(a((Math.pow(10,o)-l)/f)*f+l)/Math.LN10;if(c===\"D\"){var p=s===\"D2\"?Ase:Tse,k=Jo.roundUp(Jo.mod(o,1),p,i);return Math.floor(o)+Math.log(b0.round(Math.pow(10,k),1))/Math.LN10}else throw\"unrecognized dtick \"+String(s)}};Qn.tickText=function(e,t,r,n){var i=Mse(e,t),a=e.tickmode===\"array\",o=r||a,s=e.type,l=s===\"category\"?e.d2l_noadd:e.d2l,u,c=function(b){var p=e.l2p(b);return p>=0&&p<=e._length?b:null};if(a&&Jo.isArrayOrTypedArray(e.ticktext)){var f=Jo.simpleMap(e.range,e.r2l),h=(Math.abs(f[1]-f[0])-(e._lBreaks||0))/1e4;for(u=0;u<e.ticktext.length&&!(Math.abs(t-l(e.tickvals[u]))<h);u++);if(u<e.ticktext.length)return i.text=String(e.ticktext[u]),i.xbnd=[c(i.x-.5),c(i.x+e.dtick-.5)],i}function d(b){if(b===void 0)return!0;if(r)return b===\"none\";var p={first:e._tmin,last:e._tmax}[b];return b!==\"all\"&&t!==p}var v=r?\"never\":e.exponentformat!==\"none\"&&d(e.showexponent)?\"hide\":\"\";if(s===\"date\"?Yst(e,i,r,o):s===\"log\"?Kst(e,i,r,o,v):s===\"category\"?Jst(e,i):s===\"multicategory\"?$st(e,i,r):mB(e)?elt(e,i,r,o,v):Qst(e,i,r,o,v),n||(e.tickprefix&&!d(e.showtickprefix)&&(i.text=e.tickprefix+i.text),e.ticksuffix&&!d(e.showticksuffix)&&(i.text+=e.ticksuffix)),e.labelalias&&e.labelalias.hasOwnProperty(i.text)){var _=e.labelalias[i.text];typeof _==\"string\"&&(i.text=_)}return(e.tickson===\"boundaries\"||e.showdividers)&&(i.xbnd=[c(i.x-.5),c(i.x+e.dtick-.5)]),i};Qn.hoverLabelText=function(e,t,r){r&&(e=Jo.extendFlat({},e,{hoverformat:r}));var n=Jo.isArrayOrTypedArray(t)?t[0]:t,i=Jo.isArrayOrTypedArray(t)?t[1]:void 0;if(i!==void 0&&i!==n)return Qn.hoverLabelText(e,n,r)+\" - \"+Qn.hoverLabelText(e,i,r);var a=e.type===\"log\"&&n<=0,o=Qn.tickText(e,e.c2l(a?-n:n),\"hover\").text;return a?n===0?\"0\":Cb+o:o};function Mse(e,t,r){var n=e.tickfont||{};return{x:t,dx:0,dy:0,text:r||\"\",fontSize:n.size,font:n.family,fontWeight:n.weight,fontStyle:n.style,fontVariant:n.variant,fontTextcase:n.textcase,fontLineposition:n.lineposition,fontShadow:n.shadow,fontColor:n.color}}function Yst(e,t,r,n){var i=e._tickround,a=r&&e.hoverformat||Qn.getTickFormat(e);n=!a&&n,n&&(Ih(i)?i=4:i={y:\"m\",m:\"d\",d:\"M\",M:\"S\",S:4}[i]);var o=Jo.formatDate(t.x,a,i,e._dateFormat,e.calendar,e._extraFormat),s,l=o.indexOf(`\n",
+       "`);if(l!==-1&&(s=o.substr(l+1),o=o.substr(0,l)),n&&(s!==void 0&&(o===\"00:00:00\"||o===\"00:00\")?(o=s,s=\"\"):o.length===8&&(o=o.replace(/:00$/,\"\"))),s)if(r)i===\"d\"?o+=\", \"+s:o=s+(o?\", \"+o:\"\");else if(!e._inCalcTicks||e._prevDateHead!==s)e._prevDateHead=s,o+=\"<br>\"+s;else{var u=uM(e),c=e._trueSide||e.side;(!u&&c===\"top\"||u&&c===\"bottom\")&&(o+=\"<br> \")}t.text=o}function Kst(e,t,r,n,i){var a=e.dtick,o=t.x,s=e.tickformat,l=typeof a==\"string\"&&a.charAt(0);if(i===\"never\"&&(i=\"\"),n&&l!==\"L\"&&(a=\"L3\",l=\"L\"),s||l===\"L\")t.text=lM(Math.pow(10,o),e,i,n);else if(Ih(a)||l===\"D\"&&(e.minorloglabels===\"complete\"||Jo.mod(o+.01,1)<.1)){var u;e.minorloglabels===\"complete\"&&!(Jo.mod(o+.01,1)<.1)&&(u=!0,t.fontSize*=.75);var c=Math.pow(10,o).toExponential(0),f=c.split(\"e\"),h=+f[1],d=Math.abs(h),v=e.exponentformat;v===\"power\"||z3(v)&&v!==\"SI extended\"&&vB(h)||z3(v)&&v===\"SI extended\"&&pB(h)?(t.text=f[0],d>0&&(t.text+=\"x10\"),t.text===\"1x10\"&&(t.text=\"10\"),h!==0&&h!==1&&(t.text+=\"<sup>\"+(h>0?\"\":Cb)+d+\"</sup>\"),t.fontSize*=1.25):(v===\"e\"||v===\"E\")&&d>2?t.text=f[0]+v+(h>0?\"+\":Cb)+d:(t.text=lM(Math.pow(10,o),e,\"\",\"fakehover\"),a===\"D1\"&&e._id.charAt(0)===\"y\"&&(t.dy-=t.fontSize/6))}else if(l===\"D\")t.text=e.minorloglabels===\"none\"?\"\":String(Math.round(Math.pow(10,Jo.mod(o,1)))),t.fontSize*=.75;else throw\"unrecognized dtick \"+String(a);if(e.dtick===\"D1\"){var _=String(t.text).charAt(0);(_===\"0\"||_===\"1\")&&(e._id.charAt(0)===\"y\"?t.dx-=t.fontSize/4:(t.dy+=t.fontSize/2,t.dx+=(e.range[1]>e.range[0]?1:-1)*t.fontSize*(o<0?.5:.25)))}}function Jst(e,t){var r=e._categories[Math.round(t.x)];r===void 0&&(r=\"\"),t.text=String(r)}function $st(e,t,r){var n=Math.round(t.x),i=e._categories[n]||[],a=i[1]===void 0?\"\":String(i[1]),o=i[0]===void 0?\"\":String(i[0]);r?t.text=o+\" - \"+a:(t.text=a,t.text2=o)}function 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Pe=Object.keys(t._linepositions||{});for(a=0;a<Pe.length;a++){o=Pe[a],s=l._plots[o];var ge=t._linepositions[o]||[],Re=ge[0],ce=ge[1],Ze=ge[2],ut=Qn.makeTickPath(t,Re,Ze?_e[0]:Ee[0],{minor:Ze})+Qn.makeTickPath(t,ce,Ze?_e[1]:Ee[1],{minor:Ze});Qn.drawTicks(e,t,{vals:g,layer:s[c+\"axislayer\"],path:ut,transFn:C})}}var pt=[];if(pt.push(function(){return Qn.drawLabels(e,t,{vals:E,layer:_,plotinfo:s,transFn:M,labelFns:Qn.makeLabelFns(t,p)})}),t.type===\"multicategory\"){var Zt={x:2,y:10}[c];pt.push(function(){var lt={x:\"height\",y:\"width\"}[c],Gt=x()[lt]+Zt+(t._tickAngles[u+\"tick\"]?t.tickfont.size*sM:0);return Qn.drawLabels(e,t,{vals:alt(t,E),layer:_,cls:u+\"tick2\",repositionOnUpdate:!0,secondary:!0,transFn:C,labelFns:Qn.makeLabelFns(t,p+Gt*_e[4])})}),pt.push(function(){return t._depth=_e[4]*(x(\"tick2\")[t.side]-p),ult(e,t,{vals:G,layer:_,path:Qn.makeTickPath(t,p,_e[4],{len:t._depth}),transFn:C})})}else t.title.hasOwnProperty(\"standoff\")&&pt.push(function(){t._depth=_e[4]*(x()[t.side]-p)});var st=nM.getComponentMethod(\"rangeslider\",\"isVisible\")(t);return!r.skipTitle&&!(st&&t.side===\"bottom\")&&pt.push(function(){return clt(e,t)}),pt.push(function(){var lt=t.side.charAt(0),Gt=zst[t.side].charAt(0),Nt=Qn.getPxPosition(e,t),Jt=z?t.ticklen:0,sr,wr,cr,$e;(t.automargin||st||t._shiftPusher)&&(t.type===\"multicategory\"?sr=x(\"tick2\"):(sr=x(),c===\"x\"&&lt===\"b\"&&(t._depth=Math.max(sr.width>0?sr.bottom-Nt:0,Jt))));var St=0,Qt=0;if(t._shiftPusher&&(St=Math.max(Jt,sr.height>0?lt===\"l\"?Nt-sr.left:sr.right-Nt:0),t.title.text!==l._dfltTitle[c]&&(Qt=(t._titleStandoff||0)+(t._titleScoot||0),lt===\"l\"&&(Qt+=_se(t))),t._fullDepth=Math.max(St,Qt)),t.automargin){wr={x:0,y:0,r:0,l:0,t:0,b:0};var Vt=[0,1],_t=typeof t._shift==\"number\"?t._shift:0;if(c===\"x\"){if(lt===\"b\"?wr[lt]=t._depth:(wr[lt]=t._depth=Math.max(sr.width>0?Nt-sr.top:0,Jt),Vt.reverse()),sr.width>0){var 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t.automargin==\"string\"&&(yse(wr,t.automargin),yse(cr,t.automargin)),R3.autoMargin(e,gB(t),wr),R3.autoMargin(e,Cse(t),cr),R3.autoMargin(e,Lse(t),$e)}),Jo.syncOrAsync(pt)}};function yse(e,t){if(e){var r=Object.keys(fse).reduce(function(n,i){return t.indexOf(i)!==-1&&fse[i].forEach(function(a){n[a]=1}),n},{});Object.keys(e).forEach(function(n){r[n]||(n.length===1?e[n]=0:delete e[n])})}}function nlt(e,t){var r=[],n,i=function(a,o){var s=a.xbnd[o];s!==null&&r.push(Jo.extendFlat({},a,{x:s}))};if(t.length){for(n=0;n<t.length;n++)i(t[n],0);i(t[n-1],1)}return r}function alt(e,t){for(var r=[],n={},i=0;i<t.length;i++){var a=t[i];n[a.text2]?n[a.text2].push(a.x):n[a.text2]=[a.x]}for(var o in n)r.push(Mse(e,Jo.interp(n[o],.5),o));return r}function olt(e,t){var r=[],n,i,a=t.length&&t[t.length-1].x<t[0].x,o=function(l,u){var c=l.xbnd[u];c!==null&&r.push(Jo.extendFlat({},l,{x:c}))};if(e.showdividers&&t.length){for(n=0;n<t.length;n++){var s=t[n];s.text2!==i&&o(s,a?1:0),i=s.text2}o(t[n-1],a?0:1)}return 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n=e._fullLayout,i=t._id,a=t.zerolinelayer===\"above traces\",o=r.cls||i+\"tick\",s=r.vals.filter(function(j){return j.text}),l=r.labelFns,u=r.secondary?0:t.tickangle,c=(t._prevTickAngles||{})[o],f=r.layer.selectAll(\"g.\"+o).data(t.showticklabels?s:[],PL),h=[];f.enter().append(\"g\").classed(o,1).append(\"text\").attr(\"text-anchor\",\"middle\").each(function(j){var re=b0.select(this),oe=e._promises.length;re.call(kb.positionText,l.xFn(j),l.yFn(j)).call(Xp.font,{family:j.font,size:j.fontSize,color:j.fontColor,weight:j.fontWeight,style:j.fontStyle,variant:j.fontVariant,textcase:j.fontTextcase,lineposition:j.fontLineposition,shadow:j.fontShadow}).text(j.text).call(kb.convertToTspans,e),e._promises[oe]?h.push(e._promises.pop().then(function(){d(re,u)})):d(re,u)}),IL(t,[cse]),f.exit().remove(),r.repositionOnUpdate&&f.each(function(j){b0.select(this).select(\"text\").call(kb.positionText,l.xFn(j),l.yFn(j))});function d(j,re){j.each(function(oe){var 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a._offset+a._length};function _se(e){var t=e.title.font.size,r=(e.title.text.match(kb.BR_TAG_ALL)||[]).length;return e.title.hasOwnProperty(\"standoff\")?t*(Lb+r*sM):r?t*(r+1)*sM:t}function clt(e,t){var r=e._fullLayout,n=t._id,i=n.charAt(0),a=t.title.font.size,o,s=(t.title.text.match(kb.BR_TAG_ALL)||[]).length;if(t.title.hasOwnProperty(\"standoff\"))t.side===\"bottom\"||t.side===\"right\"?o=t._depth+t.title.standoff+a*Lb:(t.side===\"top\"||t.side===\"left\")&&(o=t._depth+t.title.standoff+a*(iM+s*sM));else{var l=uM(t);if(t.type===\"multicategory\")o=t._depth;else{var u=1.5*a;l&&(u=.5*a,t.ticks===\"outside\"&&(u+=t.ticklen)),o=10+u+(t.linewidth?t.linewidth-1:0)}l||(i===\"x\"?o+=t.side===\"top\"?a*(t.showticklabels?1:0):a*(t.showticklabels?1.5:.5):o+=t.side===\"right\"?a*(t.showticklabels?1:.5):a*(t.showticklabels?.5:0))}var 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Pe=Fe[0].height,ge=qL(Fe,n,d,l),Re=Ee?ge:Z;u||(Re+=h),Re+c+me-h>=n._maxWidth&&(N=Math.max(N,Se),me=0,ie+=Ce,n._height+=Ce,Ce=0),Dh.setTranslate(this,P[0]+c+me,P[1]+c+ie+Pe/2+h),Se=me+ge+h,me+=Re,Ce=Math.max(Ce,Pe)}),Ee?(n._width=me+f,n._height=Ce+v):(n._width=Math.max(N,Se)+f,n._height+=Ce+v)}}n._width=Math.ceil(Math.max(n._width+P[0],n._titleWidth+2*(c+ed.titlePad))),n._height=Math.ceil(Math.max(n._height+P[1],n._titleHeight+2*(c+ed.itemGap))),n._effHeight=Math.min(n._height,n._maxHeight);var Le=e._context.edits,Ae=Le.legendText||Le.legendPosition;r.each(function(Fe){var Pe=Mp.select(this).select(\".\"+a+\"toggle\"),ge=Fe[0].height,Re=Fe[0].trace.legendgroup,ce=qL(Fe,n,d);l&&Re!==\"\"&&(ce=E[Re]);var Ze=Ae?d:g||ce;!s&&!u&&(Ze+=h/2),Dh.setRect(Pe,0,-ge/2,Ze,ge)})}function tut(e,t,r,n){var i=e._fullLayout,a=i[t],o=UL(a),s=VL(a),l=a.xref===\"paper\",u=a.yref===\"paper\";e._fullLayout._reservedMargin[t]={};var c=a.y<.5?\"b\":\"t\",f=a.x<.5?\"l\":\"r\",h={r:i.width-r,l:r+a._width,b:i.height-n,t:n+a._effHeight};if(l&&u)return OB.autoMargin(e,t,{x:a.x,y:a.y,l:a._width*U3[o],r:a._width*xle[o],b:a._effHeight*xle[s],t:a._effHeight*U3[s]});l?e._fullLayout._reservedMargin[t][c]=h[c]:u||a.orientation===\"v\"?e._fullLayout._reservedMargin[t][f]=h[f]:e._fullLayout._reservedMargin[t][c]=h[c]}function UL(e){return Rh.isRightAnchor(e)?\"right\":Rh.isCenterAnchor(e)?\"center\":\"left\"}function VL(e){return Rh.isBottomAnchor(e)?\"bottom\":Rh.isMiddleAnchor(e)?\"middle\":\"top\"}function GL(e){return e._id||\"legend\"}});var GB=ye(VB=>{\"use strict\";var Fb=Oa(),My=Eo(),kle=cd(),zf=Dr(),rut=zf.pushUnique,NB=zf.strTranslate,iut=zf.strRotate,nut=y3(),T0=ru(),aut=Jse(),bm=So(),vd=ka(),HL=yv(),wm=ho(),out=hd().zindexSeparator,H3=qa(),Sg=ip(),zb=FS(),sut=EB(),lut=BB(),zle=zb.YANGLE,UB=Math.PI*zle/180,uut=1/Math.sin(UB),cut=Math.cos(UB),fut=Math.sin(UB),Qc=zb.HOVERARROWSIZE,sl=zb.HOVERTEXTPAD,Cle={box:!0,ohlc:!0,violin:!0,candlestick:!0},hut={scatter:!0,scattergl:!0,splom:!0};function Lle(e,t){return e.distance-t.distance}VB.hover=function(t,r,n,i){t=zf.getGraphDiv(t);var a=r.target;zf.throttle(t._fullLayout._uid+zb.HOVERID,zb.HOVERMINTIME,function(){dut(t,r,n,i,a)})};VB.loneHover=function(t,r){var n=!0;Array.isArray(t)||(n=!1,t=[t]);var i=r.gd,a=Ule(i),o=Vle(i),s=t.map(function(b){var p=b._x0||b.x0||b.x||0,k=b._x1||b.x1||b.x||0,E=b._y0||b.y0||b.y||0,S=b._y1||b.y1||b.y||0,L=b.eventData;if(L){var x=Math.min(p,k),C=Math.max(p,k),M=Math.min(E,S),g=Math.max(E,S),P=b.trace;if(H3.traceIs(P,\"gl3d\")){var T=i._fullLayout[P.scene]._scene.container,z=T.offsetLeft,O=T.offsetTop;x+=z,C+=z,M+=O,g+=O}L.bbox={x0:x+o,x1:C+o,y0:M+a,y1:g+a},r.inOut_bbox&&r.inOut_bbox.push(L.bbox)}else L=!1;return{color:b.color||vd.defaultLine,x0:b.x0||b.x||0,x1:b.x1||b.x||0,y0:b.y0||b.y||0,y1:b.y1||b.y||0,xLabel:b.xLabel,yLabel:b.yLabel,zLabel:b.zLabel,text:b.text,name:b.name,idealAlign:b.idealAlign,borderColor:b.borderColor,fontFamily:b.fontFamily,fontSize:b.fontSize,fontColor:b.fontColor,fontWeight:b.fontWeight,fontStyle:b.fontStyle,fontVariant:b.fontVariant,nameLength:b.nameLength,textAlign:b.textAlign,trace:b.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:b.hovertemplate||!1,hovertemplateLabels:b.hovertemplateLabels||!1,eventData:L}}),l=!1,u=qle(s,{gd:i,hovermode:\"closest\",rotateLabels:l,bgColor:r.bgColor||vd.background,container:Fb.select(r.container),outerContainer:r.outerContainer||r.container}),c=u.hoverLabels,f=5,h=0,d=0;c.sort(function(b,p){return b.y0-p.y0}).each(function(b,p){var k=b.y0-b.by/2;k-f<h?b.offset=h-k+f:b.offset=0,h=k+b.by+b.offset,p===r.anchorIndex&&(d=b.offset)}).each(function(b){b.offset-=d});var v=i._fullLayout._invScaleX,_=i._fullLayout._invScaleY;return Nle(c,l,v,_),n?c:c.node()};function dut(e,t,r,n,i){r||(r=\"xy\"),typeof r==\"string\"&&(r=r.split(out)[0]);var a=Array.isArray(r)?r:[r],o,s=e._fullLayout,l=s.hoversubplots,u=s._plots||[],c=u[r],f=s._has(\"cartesian\"),h=t.hovermode||s.hovermode,d=(h||\"\").charAt(0)===\"x\",v=(h||\"\").charAt(0)===\"y\",_,b;if(f&&(d||v)&&l===\"axis\"){for(var p=a.length,k=0;k<p;k++)if(o=a[k],u[o]){_=wm.getFromId(e,o,\"x\"),b=wm.getFromId(e,o,\"y\");var E=(d?_:b)._subplotsWith;if(E&&E.length)for(var S=0;S<E.length;S++)rut(a,E[S])}}if(c&&l!==\"single\"){var L=c.overlays.map(function(wi){return wi.id});a=a.concat(L)}for(var x=a.length,C=new Array(x),M=new Array(x),g=!1,P=0;P<x;P++)if(o=a[P],u[o])g=!0,C[P]=u[o].xaxis,M[P]=u[o].yaxis;else if(s[o]&&s[o]._subplot){var T=s[o]._subplot;C[P]=T.xaxis,M[P]=T.yaxis}else{zf.warn(\"Unrecognized subplot: \"+o);return}if(h&&!g&&(h=\"closest\"),[\"x\",\"y\",\"closest\",\"x unified\",\"y unified\"].indexOf(h)===-1||!e.calcdata||e.querySelector(\".zoombox\")||e._dragging)return HL.unhoverRaw(e,t);var z=s.hoverdistance;z===-1&&(z=1/0);var O=s.spikedistance;O===-1&&(O=1/0);var V=[],G=[],Z,H,N,j,re,oe,_e,Ee,Ce,me,ie,Se,Le,Ae={hLinePoint:null,vLinePoint:null},Fe=!1;if(Array.isArray(t))for(h=\"array\",N=0;N<t.length;N++)re=e.calcdata[t[N].curveNumber||0],re&&(oe=re[0].trace,re[0].trace.hoverinfo!==\"skip\"&&(G.push(re),oe.orientation===\"h\"&&(Fe=!0)));else{var Pe=e.calcdata.slice();for(Pe.sort(function(wi,On){var qn=wi[0].trace.zorder||0,Fn=On[0].trace.zorder||0;return qn-Fn}),j=0;j<Pe.length;j++)re=Pe[j],oe=re[0].trace,oe.hoverinfo!==\"skip\"&&Sg.isTraceInSubplots(oe,a)&&(G.push(re),oe.orientation===\"h\"&&(Fe=!0));var ge=!i,Re,ce;if(ge)\"xpx\"in t?Re=t.xpx:Re=C[0]._length/2,\"ypx\"in t?ce=t.ypx:ce=M[0]._length/2;else{if(nut.triggerHandler(e,\"plotly_beforehover\",t)===!1)return;var Ze=i.getBoundingClientRect();Re=t.clientX-Ze.left,ce=t.clientY-Ze.top,s._calcInverseTransform(e);var ut=zf.apply3DTransform(s._invTransform)(Re,ce);if(Re=ut[0],ce=ut[1],Re<0||Re>C[0]._length||ce<0||ce>M[0]._length)return HL.unhoverRaw(e,t)}if(t.pointerX=Re+C[0]._offset,t.pointerY=ce+M[0]._offset,\"xval\"in t?Z=Sg.flat(a,t.xval):Z=Sg.p2c(C,Re),\"yval\"in t?H=Sg.flat(a,t.yval):H=Sg.p2c(M,ce),!My(Z[0])||!My(H[0]))return zf.warn(\"Fx.hover failed\",t,e),HL.unhoverRaw(e,t)}var pt=1/0;function Zt(wi,On){for(j=0;j<G.length;j++)if(re=G[j],!(!re||!re[0]||!re[0].trace)&&(oe=re[0].trace,!(oe.visible!==!0||oe._length===0)&&[\"carpet\",\"contourcarpet\"].indexOf(oe._module.name)===-1)){if(Ce=h,Sg.isUnifiedHover(Ce)&&(Ce=Ce.charAt(0)),oe.type===\"splom\"?(Ee=0,_e=a[Ee]):(_e=Sg.getSubplot(oe),Ee=a.indexOf(_e)),Se={cd:re,trace:oe,xa:C[Ee],ya:M[Ee],maxHoverDistance:z,maxSpikeDistance:O,index:!1,distance:Math.min(pt,z),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:vd.defaultLine,name:oe.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},s[_e]&&(Se.subplot=s[_e]._subplot),s._splomScenes&&s._splomScenes[oe.uid]&&(Se.scene=s._splomScenes[oe.uid]),Ce===\"array\"){var qn=t[j];\"pointNumber\"in qn?(Se.index=qn.pointNumber,Ce=\"closest\"):(Ce=\"\",\"xval\"in qn&&(me=qn.xval,Ce=\"x\"),\"yval\"in qn&&(ie=qn.yval,Ce=Ce?\"closest\":\"y\"))}else wi!==void 0&&On!==void 0?(me=wi,ie=On):(me=Z[Ee],ie=H[Ee]);if(Le=V.length,z!==0)if(oe._module&&oe._module.hoverPoints){var Fn=oe._module.hoverPoints(Se,me,ie,Ce,{finiteRange:!0,hoverLayer:s._hoverlayer,hoversubplots:l,gd:e});if(Fn)for(var ra,la=0;la<Fn.length;la++)ra=Fn[la],My(ra.x0)&&My(ra.y0)&&V.push(mut(ra,h))}else zf.log(\"Unrecognized trace type in hover:\",oe);if(h===\"closest\"&&V.length>Le&&(V.splice(0,Le),pt=V[0].distance),f&&O!==0&&V.length===0){Se.distance=O,Se.index=!1;var Ut=oe._module.hoverPoints(Se,me,ie,\"closest\",{hoverLayer:s._hoverlayer});if(Ut&&(Ut=Ut.filter(function(ri){return ri.spikeDistance<=O})),Ut&&Ut.length){var wt,rr=Ut.filter(function(ri){return ri.xa.showspikes&&ri.xa.spikesnap!==\"hovered data\"});if(rr.length){var nr=rr[0];My(nr.x0)&&My(nr.y0)&&(wt=lt(nr),(!Ae.vLinePoint||Ae.vLinePoint.spikeDistance>wt.spikeDistance)&&(Ae.vLinePoint=wt))}var Er=Ut.filter(function(ri){return ri.ya.showspikes&&ri.ya.spikesnap!==\"hovered data\"});if(Er.length){var Xr=Er[0];My(Xr.x0)&&My(Xr.y0)&&(wt=lt(Xr),(!Ae.hLinePoint||Ae.hLinePoint.spikeDistance>wt.spikeDistance)&&(Ae.hLinePoint=wt))}}}}}Zt();function st(wi,On,qn){for(var Fn=null,ra=1/0,la,Ut=0;Ut<wi.length;Ut++)_&&_._id!==wi[Ut].xa._id||b&&b._id!==wi[Ut].ya._id||(la=wi[Ut].spikeDistance,qn&&Ut===0&&(la=-1/0),la<=ra&&la<=On&&(Fn=wi[Ut],ra=la));return Fn}function lt(wi){return wi?{xa:wi.xa,ya:wi.ya,x:wi.xSpike!==void 0?wi.xSpike:(wi.x0+wi.x1)/2,y:wi.ySpike!==void 0?wi.ySpike:(wi.y0+wi.y1)/2,distance:wi.distance,spikeDistance:wi.spikeDistance,curveNumber:wi.trace.index,color:wi.color,pointNumber:wi.index}:null}var Gt={fullLayout:s,container:s._hoverlayer,event:t},Nt=e._spikepoints,Jt={vLinePoint:Ae.vLinePoint,hLinePoint:Ae.hLinePoint};e._spikepoints=Jt;var sr=function(){var wi=V.filter(function(qn){return _&&_._id===qn.xa._id&&b&&b._id===qn.ya._id}),On=V.filter(function(qn){return!(_&&_._id===qn.xa._id&&b&&b._id===qn.ya._id)});wi.sort(Lle),On.sort(Lle),V=wi.concat(On),V=_ut(V,h)};sr();var wr=h.charAt(0),cr=(wr===\"x\"||wr===\"y\")&&V[0]&&hut[V[0].trace.type];if(f&&O!==0&&V.length!==0){var $e=V.filter(function(wi){return wi.ya.showspikes}),St=st($e,O,cr);Ae.hLinePoint=lt(St);var Qt=V.filter(function(wi){return wi.xa.showspikes}),Vt=st(Qt,O,cr);Ae.vLinePoint=lt(Vt)}if(V.length===0){var _t=HL.unhoverRaw(e,t);return f&&(Ae.hLinePoint!==null||Ae.vLinePoint!==null)&&Rle(Nt)&&Ile(e,Ae,Gt),_t}if(f&&Rle(Nt)&&Ile(e,Ae,Gt),Sg.isXYhover(Ce)&&V[0].length!==0&&V[0].trace.type!==\"splom\"){var It=V[0];Cle[It.trace.type]?V=V.filter(wi=>wi.trace.index===It.trace.index):V=[It];var mt=V.length,er=Fle(\"x\",It,s),lr=Fle(\"y\",It,s);Zt(er,lr);var Tr=[],Lr={},ti=0,Br=function(wi){var On=Cle[wi.trace.type]?Ole(wi):wi.trace.index;if(!Lr[On])ti++,Lr[On]=ti,Tr.push(wi);else{var qn=Lr[On]-1,Fn=Tr[qn];qn>0&&Math.abs(wi.distance)<Math.abs(Fn.distance)&&(Tr[qn]=wi)}},Vr;for(Vr=0;Vr<mt;Vr++)Br(V[Vr]);for(Vr=V.length-1;Vr>mt-1;Vr--)Br(V[Vr]);V=Tr,sr()}var dt=e._hoverdata,Ge=[],Je=Ule(e),je=Vle(e);for(let wi of V){var tt=Sg.makeEventData(wi,wi.trace,wi.cd);if(wi.hovertemplate!==!1){var xt=!1;wi.cd[wi.index]&&wi.cd[wi.index].ht&&(xt=wi.cd[wi.index].ht),wi.hovertemplate=xt||wi.trace.hovertemplate||!1}if(wi.xa&&wi.ya){var Ie=wi.x0+wi.xa._offset,xe=wi.x1+wi.xa._offset,ke=wi.y0+wi.ya._offset,vt=wi.y1+wi.ya._offset,ir=Math.min(Ie,xe),ar=Math.max(Ie,xe),vr=Math.min(ke,vt),ii=Math.max(ke,vt);tt.bbox={x0:ir+je,x1:ar+je,y0:vr+Je,y1:ii+Je}}wi.eventData=[tt],Ge.push(tt)}e._hoverdata=Ge;var pi=h===\"y\"&&(G.length>1||V.length>1)||h===\"closest\"&&Fe&&V.length>1,$r=vd.combine(s.plot_bgcolor||vd.background,s.paper_bgcolor),di=qle(V,{gd:e,hovermode:h,rotateLabels:pi,bgColor:$r,container:s._hoverlayer,outerContainer:s._paper.node(),commonLabelOpts:s.hoverlabel,hoverdistance:s.hoverdistance}),ji=di.hoverLabels;if(Sg.isUnifiedHover(h)||(put(ji,pi,s,di.commonLabelBoundingBox),Nle(ji,pi,s._invScaleX,s._invScaleY)),i&&i.tagName){var In=H3.getComponentMethod(\"annotations\",\"hasClickToShow\")(e,Ge);aut(Fb.select(i),In?\"pointer\":\"\")}!i||n||!yut(e,t,dt)||(dt&&e.emit(\"plotly_unhover\",{event:t,points:dt}),e.emit(\"plotly_hover\",{event:t,points:e._hoverdata,xaxes:C,yaxes:M,xvals:Z,yvals:H}))}function Ole(e){return[e.trace.index,e.index,e.x0,e.y0,e.name,e.attr,e.xa?e.xa._id:\"\",e.ya?e.ya._id:\"\"].join(\",\")}var vut=/<extra>([\\s\\S]*)<\\/extra>/;function qle(e,t){var r=t.gd,n=r._fullLayout,i=t.hovermode,a=t.rotateLabels,o=t.bgColor,s=t.container,l=t.outerContainer,u=t.commonLabelOpts||{};if(e.length===0)return[[]];var c=t.fontFamily||zb.HOVERFONT,f=t.fontSize||zb.HOVERFONTSIZE,h=t.fontWeight||n.font.weight,d=t.fontStyle||n.font.style,v=t.fontVariant||n.font.variant,_=t.fontTextcase||n.font.textcase,b=t.fontLineposition||n.font.lineposition,p=t.fontShadow||n.font.shadow,k=e[0],E=k.xa,S=k.ya,L=i.charAt(0),x=L+\"Label\",C=k[x];if(C===void 0&&E.type===\"multicategory\")for(var M=0;M<e.length&&(C=e[M][x],C===void 0);M++);var g=G3(r,l),P=g.top,T=g.width,z=g.height,O=C!==void 0&&k.distance<=t.hoverdistance&&(i===\"x\"||i===\"y\");if(O){var V=!0,G,Z;for(G=0;G<e.length;G++)if(V&&e[G].zLabel===void 0&&(V=!1),Z=e[G].hoverinfo||e[G].trace.hoverinfo,Z){var H=Array.isArray(Z)?Z:Z.split(\"+\");if(H.indexOf(\"all\")===-1&&H.indexOf(i)===-1){O=!1;break}}V&&(O=!1)}var N=s.selectAll(\"g.axistext\").data(O?[0]:[]);N.enter().append(\"g\").classed(\"axistext\",!0),N.exit().remove();var j={minX:0,maxX:0,minY:0,maxY:0};if(N.each(function(){var _t=Fb.select(this),It=zf.ensureSingle(_t,\"path\",\"\",function(ii){ii.style({\"stroke-width\":\"1px\"})}),mt=zf.ensureSingle(_t,\"text\",\"\",function(ii){ii.attr(\"data-notex\",1)}),er=u.bgcolor||vd.defaultLine,lr=u.bordercolor||vd.contrast(er),Tr=vd.contrast(er),Lr=u.font,ti={weight:Lr.weight||h,style:Lr.style||d,variant:Lr.variant||v,textcase:Lr.textcase||_,lineposition:Lr.lineposition||b,shadow:Lr.shadow||p,family:Lr.family||c,size:Lr.size||f,color:Lr.color||Tr};It.style({fill:er,stroke:lr}),mt.text(C).call(bm.font,ti).call(T0.positionText,0,0).call(T0.convertToTspans,r),_t.attr(\"transform\",\"\");var Br=G3(r,mt.node()),Vr,dt;if(i===\"x\"){var Ge=E.side===\"top\"?\"-\":\"\";mt.attr(\"text-anchor\",\"middle\").call(T0.positionText,0,E.side===\"top\"?P-Br.bottom-Qc-sl:P-Br.top+Qc+sl),Vr=E._offset+(k.x0+k.x1)/2,dt=S._offset+(E.side===\"top\"?0:S._length);var Je=Br.width/2+sl,je=Vr;Vr<Je?je=Je:Vr>n.width-Je&&(je=n.width-Je),It.attr(\"d\",\"M\"+(Vr-je)+\",0L\"+(Vr-je+Qc)+\",\"+Ge+Qc+\"H\"+Je+\"v\"+Ge+(sl*2+Br.height)+\"H\"+-Je+\"V\"+Ge+Qc+\"H\"+(Vr-je-Qc)+\"Z\"),Vr=je,j.minX=Vr-Je,j.maxX=Vr+Je,E.side===\"top\"?(j.minY=dt-(sl*2+Br.height),j.maxY=dt-sl):(j.minY=dt+sl,j.maxY=dt+(sl*2+Br.height))}else{var tt,xt,Ie;S.side===\"right\"?(tt=\"start\",xt=1,Ie=\"\",Vr=E._offset+E._length):(tt=\"end\",xt=-1,Ie=\"-\",Vr=E._offset),dt=S._offset+(k.y0+k.y1)/2,mt.attr(\"text-anchor\",tt),It.attr(\"d\",\"M0,0L\"+Ie+Qc+\",\"+Qc+\"V\"+(sl+Br.height/2)+\"h\"+Ie+(sl*2+Br.width)+\"V-\"+(sl+Br.height/2)+\"H\"+Ie+Qc+\"V-\"+Qc+\"Z\"),j.minY=dt-(sl+Br.height/2),j.maxY=dt+(sl+Br.height/2),S.side===\"right\"?(j.minX=Vr+Qc,j.maxX=Vr+Qc+(sl*2+Br.width)):(j.minX=Vr-Qc-(sl*2+Br.width),j.maxX=Vr-Qc);var xe=Br.height/2,ke=P-Br.top-xe,vt=\"clip\"+n._uid+\"commonlabel\"+S._id,ir;if(Vr<Br.width+2*sl+Qc){ir=\"M-\"+(Qc+sl)+\"-\"+xe+\"h-\"+(Br.width-sl)+\"V\"+xe+\"h\"+(Br.width-sl)+\"Z\";var ar=Br.width-Vr+sl;T0.positionText(mt,ar,ke),tt===\"end\"&&mt.selectAll(\"tspan\").each(function(){var ii=Fb.select(this),pi=bm.tester.append(\"text\").text(ii.text()).call(bm.font,ti),$r=G3(r,pi.node());Math.round($r.width)<Math.round(Br.width)&&ii.attr(\"x\",ar-$r.width),pi.remove()})}else T0.positionText(mt,xt*(sl+Qc),ke),ir=null;var vr=n._topclips.selectAll(\"#\"+vt).data(ir?[0]:[]);vr.enter().append(\"clipPath\").attr(\"id\",vt).append(\"path\"),vr.exit().remove(),vr.select(\"path\").attr(\"d\",ir),bm.setClipUrl(mt,ir?vt:null,r)}_t.attr(\"transform\",NB(Vr,dt))}),Sg.isUnifiedHover(i)){s.selectAll(\"g.hovertext\").remove();let _t=e.filter(It=>It.hoverinfo!==\"none\");if(_t.length===0)return[];var re=n.hoverlabel,oe=re.font,_e=_t[0],Ee=((i===\"x unified\"?_e.xa:_e.ya).unifiedhovertitle||{}).text,Ce=Ee?zf.hovertemplateString({data:i===\"x unified\"?[{xa:_e.xa,x:_e.xVal}]:[{ya:_e.ya,y:_e.yVal}],fallback:_e.trace.hovertemplatefallback,locale:n._d3locale,template:Ee}):C,me={showlegend:!0,legend:{title:{text:Ce,font:oe},font:oe,bgcolor:re.bgcolor,bordercolor:re.bordercolor,borderwidth:1,tracegroupgap:7,traceorder:n.legend?n.legend.traceorder:void 0,orientation:\"v\"}},ie={font:oe};sut(me,ie,r._fullData);var Se=ie.legend;Se.entries=[];for(var Le=0;Le<_t.length;Le++){var Ae=_t[Le];if(Ae.hoverinfo!==\"none\"){var Fe=Ple(Ae,!0,i,n,C),Pe=Fe[0],ge=Fe[1];Ae.name=ge,ge!==\"\"?Ae.text=ge+\" : \"+Pe:Ae.text=Pe;var Re=Ae.cd[Ae.index];Re&&(Re.mc&&(Ae.mc=Re.mc),Re.mcc&&(Ae.mc=Re.mcc),Re.mlc&&(Ae.mlc=Re.mlc),Re.mlcc&&(Ae.mlc=Re.mlcc),Re.mlw&&(Ae.mlw=Re.mlw),Re.mrc&&(Ae.mrc=Re.mrc),Re.dir&&(Ae.dir=Re.dir)),Ae._distinct=!0,Se.entries.push([Ae])}}Se.entries.sort(function(It,mt){return It[0].trace.index-mt[0].trace.index}),Se.layer=s,Se._inHover=!0,Se._groupTitleFont=re.grouptitlefont,lut(r,Se);var ce=s.select(\"g.legend\"),Ze=G3(r,ce.node()),ut=Ze.width+2*sl,pt=Ze.height+2*sl,Zt=_t[0],st=(Zt.x0+Zt.x1)/2,lt=(Zt.y0+Zt.y1)/2,Gt=!(H3.traceIs(Zt.trace,\"bar-like\")||H3.traceIs(Zt.trace,\"box-violin\")),Nt,Jt;L===\"y\"?Gt?(Jt=lt-sl,Nt=lt+sl):(Jt=Math.min.apply(null,_t.map(function(It){return Math.min(It.y0,It.y1)})),Nt=Math.max.apply(null,_t.map(function(It){return Math.max(It.y0,It.y1)}))):Jt=Nt=zf.mean(_t.map(function(It){return(It.y0+It.y1)/2}))-pt/2;var sr,wr;L===\"x\"?Gt?(sr=st+sl,wr=st-sl):(sr=Math.max.apply(null,_t.map(function(It){return Math.max(It.x0,It.x1)})),wr=Math.min.apply(null,_t.map(function(It){return Math.min(It.x0,It.x1)}))):sr=wr=zf.mean(_t.map(function(It){return(It.x0+It.x1)/2}))-ut/2;var cr=E._offset,$e=S._offset;Nt+=$e,sr+=cr,wr+=cr-ut,Jt+=$e-pt;var St,Qt;return sr+ut<T&&sr>=0?St=sr:wr+ut<T&&wr>=0?St=wr:cr+ut<T?St=cr:sr-st<st-wr+ut?St=T-ut:St=0,St+=sl,Nt+pt<z&&Nt>=0?Qt=Nt:Jt+pt<z&&Jt>=0?Qt=Jt:$e+pt<z?Qt=$e:Nt-lt<lt-Jt+pt?Qt=z-pt:Qt=0,Qt+=sl,ce.attr(\"transform\",NB(St-1,Qt-1)),ce}var Vt=s.selectAll(\"g.hovertext\").data(e,function(_t){return Ole(_t)});return Vt.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var _t=Fb.select(this);_t.append(\"rect\").call(vd.fill,vd.addOpacity(o,.8)),_t.append(\"text\").classed(\"name\",!0),_t.append(\"path\").style(\"stroke-width\",\"1px\"),_t.append(\"text\").classed(\"nums\",!0).call(bm.font,{weight:h,style:d,variant:v,textcase:_,lineposition:b,shadow:p,family:c,size:f})}),Vt.exit().remove(),Vt.each(function(_t){var It=Fb.select(this).attr(\"transform\",\"\"),mt=_t.color;Array.isArray(mt)&&(mt=mt[_t.eventData[0].pointNumber]);var er=_t.bgcolor||mt,lr=vd.combine(vd.opacity(er)?er:vd.defaultLine,o),Tr=vd.combine(vd.opacity(mt)?mt:vd.defaultLine,o),Lr=_t.borderColor||vd.contrast(lr),ti=Ple(_t,O,i,n,C,It),Br=ti[0],Vr=ti[1],dt=It.select(\"text.nums\").call(bm.font,{family:_t.fontFamily||c,size:_t.fontSize||f,color:_t.fontColor||Lr,weight:_t.fontWeight||h,style:_t.fontStyle||d,variant:_t.fontVariant||v,textcase:_t.fontTextcase||_,lineposition:_t.fontLineposition||b,shadow:_t.fontShadow||p}).text(Br).attr(\"data-notex\",1).call(T0.positionText,0,0).call(T0.convertToTspans,r),Ge=It.select(\"text.name\"),Je=0,je=0;if(Vr&&Vr!==Br){Ge.call(bm.font,{family:_t.fontFamily||c,size:_t.fontSize||f,color:Tr,weight:_t.fontWeight||h,style:_t.fontStyle||d,variant:_t.fontVariant||v,textcase:_t.fontTextcase||_,lineposition:_t.fontLineposition||b,shadow:_t.fontShadow||p}).text(Vr).attr(\"data-notex\",1).call(T0.positionText,0,0).call(T0.convertToTspans,r);var tt=G3(r,Ge.node());Je=tt.width+2*sl,je=tt.height+2*sl}else Ge.remove(),It.select(\"rect\").remove();It.select(\"path\").style({fill:lr,stroke:Lr});var xt=_t.xa._offset+(_t.x0+_t.x1)/2,Ie=_t.ya._offset+(_t.y0+_t.y1)/2,xe=Math.abs(_t.x1-_t.x0),ke=Math.abs(_t.y1-_t.y0),vt=G3(r,dt.node()),ir=vt.width/n._invScaleX,ar=vt.height/n._invScaleY;_t.ty0=(P-vt.top)/n._invScaleY,_t.bx=ir+2*sl,_t.by=Math.max(ar+2*sl,je),_t.anchor=\"start\",_t.txwidth=ir,_t.tx2width=Je,_t.offset=0;var vr=(ir+Qc+sl+Je)*n._invScaleX,ii,pi;if(a)_t.pos=xt,ii=Ie+ke/2+vr<=z,pi=Ie-ke/2-vr>=0,(_t.idealAlign===\"top\"||!ii)&&pi?(Ie-=ke/2,_t.anchor=\"end\"):ii?(Ie+=ke/2,_t.anchor=\"start\"):_t.anchor=\"middle\",_t.crossPos=Ie;else{if(_t.pos=Ie,ii=xt+xe/2+vr<=T,pi=xt-xe/2-vr>=0,(_t.idealAlign===\"left\"||!ii)&&pi)xt-=xe/2,_t.anchor=\"end\";else if(ii)xt+=xe/2,_t.anchor=\"start\";else{_t.anchor=\"middle\";var 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\"+e.yLabel+\")\",(e.text||e.text===0)&&!Array.isArray(e.text)&&(s+=(s?\"<br>\":\"\")+e.text),e.extraText!==void 0&&(s+=(s?\"<br>\":\"\")+e.extraText),a&&s===\"\"&&!e.hovertemplate&&(o===\"\"&&a.remove(),s=o),(h=(f=e.trace)==null?void 0:f.hoverlabel)!=null&&h.split&&(e.hovertemplate=\"\");let{hovertemplate:c=!1}=e;if(c){let d=e.hovertemplateLabels||e;e[l+\"Label\"]!==i&&(d[l+\"other\"]=d[l+\"Val\"],d[l+\"otherLabel\"]=d[l+\"Label\"]),s=zf.hovertemplateString({data:[e.eventData[0]||{},e.trace._meta],fallback:e.trace.hovertemplatefallback,labels:d,locale:n._d3locale,template:c}),s=s.replace(vut,(v,_)=>(o=Dle(_,e.nameLength),\"\"))}return[s,o]}function put(e,t,r,n){var i=t?\"xa\":\"ya\",a=t?\"ya\":\"xa\",o=0,s=1,l=e.size(),u=new Array(l),c=0,f=n.minX,h=n.maxX,d=n.minY,v=n.maxY,_=function(Z){return Z*r._invScaleX},b=function(Z){return Z*r._invScaleY};e.each(function(Z){var H=Z[i],N=Z[a],j=H._id.charAt(0)===\"x\",re=H.range;c===0&&re&&re[0]>re[1]!==j&&(s=-1);var oe=0,_e=j?r.width:r.height;if(r.hovermode===\"x\"||r.hovermode===\"y\"){var Ee=Ble(Z,t),Ce=Z.anchor,me=Ce===\"end\"?-1:1,ie,Se;if(Ce===\"middle\")ie=Z.crossPos+(j?b(Ee.y-Z.by/2):_(Z.bx/2+Z.tx2width/2)),Se=ie+(j?b(Z.by):_(Z.bx));else if(j)ie=Z.crossPos+b(Qc+Ee.y)-b(Z.by/2-Qc),Se=ie+b(Z.by);else{var Le=_(me*Qc+Ee.x),Ae=Le+_(me*Z.bx);ie=Z.crossPos+Math.min(Le,Ae),Se=Z.crossPos+Math.max(Le,Ae)}j?d!==void 0&&v!==void 0&&Math.min(Se,v)-Math.max(ie,d)>1&&(N.side===\"left\"?(oe=N._mainLinePosition,_e=r.width):_e=N._mainLinePosition):f!==void 0&&h!==void 0&&Math.min(Se,h)-Math.max(ie,f)>1&&(N.side===\"top\"?(oe=N._mainLinePosition,_e=r.height):_e=N._mainLinePosition)}u[c++]=[{datum:Z,traceIndex:Z.trace.index,dp:0,pos:Z.pos,posref:Z.posref,size:Z.by*(j?uut:1)/2,pmin:oe,pmax:_e}]}),u.sort(function(Z,H){return Z[0].posref-H[0].posref||s*(H[0].traceIndex-Z[0].traceIndex)});var p,k,E,S,L,x,C;function M(Z){var H=Z[0],N=Z[Z.length-1];if(k=H.pmin-H.pos-H.dp+H.size,E=N.pos+N.dp+N.size-H.pmax,k>.01){for(L=Z.length-1;L>=0;L--)Z[L].dp+=k;p=!1}if(!(E<.01)){if(k<-.01){for(L=Z.length-1;L>=0;L--)Z[L].dp-=E;p=!1}if(p){var j=0;for(S=0;S<Z.length;S++)x=Z[S],x.pos+x.dp+x.size>H.pmax&&j++;for(S=Z.length-1;S>=0&&!(j<=0);S--)x=Z[S],x.pos>H.pmax-1&&(x.del=!0,j--);for(S=0;S<Z.length&&!(j<=0);S++)if(x=Z[S],x.pos<H.pmin+1)for(x.del=!0,j--,E=x.size*2,L=Z.length-1;L>=0;L--)Z[L].dp-=E;for(S=Z.length-1;S>=0&&!(j<=0);S--)x=Z[S],x.pos+x.dp+x.size>H.pmax&&(x.del=!0,j--)}}}for(;!p&&o<=l;){for(o++,p=!0,S=0;S<u.length-1;){var g=u[S],P=u[S+1],T=g[g.length-1],z=P[0];if(k=T.pos+T.dp+T.size-z.pos-z.dp+z.size,k>.01){for(L=P.length-1;L>=0;L--)P[L].dp+=k;for(g.push.apply(g,P),u.splice(S+1,1),C=0,L=g.length-1;L>=0;L--)C+=g[L].dp;for(E=C/g.length,L=g.length-1;L>=0;L--)g[L].dp-=E;p=!1}else S++}u.forEach(M)}for(S=u.length-1;S>=0;S--){var O=u[S];for(L=O.length-1;L>=0;L--){var V=O[L],G=V.datum;G.offset=V.dp,G.del=V.del}}}function Ble(e,t){var r=0,n=e.offset;return t&&(n*=-fut,r=e.offset*cut),{x:r,y:n}}function gut(e){var t={start:1,end:-1,middle:0}[e.anchor],r=t*(Qc+sl),n=r+t*(e.txwidth+sl),i=e.anchor===\"middle\";return i&&(r-=e.tx2width/2,n+=e.txwidth/2+sl),{alignShift:t,textShiftX:r,text2ShiftX:n}}function Nle(e,t,r,n){var i=function(o){return o*r},a=function(o){return o*n};e.each(function(o){var s=Fb.select(this);if(o.del)return s.remove();var l=s.select(\"text.nums\"),u=o.anchor,c=u===\"end\"?-1:1,f=gut(o),h=Ble(o,t),d=h.x,v=h.y,_=u===\"middle\",b=\"hoverlabel\"in o.trace?o.trace.hoverlabel.showarrow:!0,p;_?p=\"M-\"+i(o.bx/2+o.tx2width/2)+\",\"+a(v-o.by/2)+\"h\"+i(o.bx)+\"v\"+a(o.by)+\"h-\"+i(o.bx)+\"Z\":b?p=\"M0,0L\"+i(c*Qc+d)+\",\"+a(Qc+v)+\"v\"+a(o.by/2-Qc)+\"h\"+i(c*o.bx)+\"v-\"+a(o.by)+\"H\"+i(c*Qc+d)+\"V\"+a(v-Qc)+\"Z\":p=\"M\"+i(c*Qc+d)+\",\"+a(v-o.by/2)+\"h\"+i(c*o.bx)+\"v\"+a(o.by)+\"h\"+i(-c*o.bx)+\"Z\",s.select(\"path\").attr(\"d\",p);var k=d+f.textShiftX,E=v+o.ty0-o.by/2+sl,S=o.textAlign||\"auto\";S!==\"auto\"&&(S===\"left\"&&u!==\"start\"?(l.attr(\"text-anchor\",\"start\"),k=_?-o.bx/2-o.tx2width/2+sl:-o.bx-sl):S===\"right\"&&u!==\"end\"&&(l.attr(\"text-anchor\",\"end\"),k=_?o.bx/2-o.tx2width/2-sl:o.bx+sl)),l.call(T0.positionText,i(k),a(E)),o.tx2width&&(s.select(\"text.name\").call(T0.positionText,i(f.text2ShiftX+f.alignShift*sl+d),a(v+o.ty0-o.by/2+sl)),s.select(\"rect\").call(bm.setRect,i(f.text2ShiftX+(f.alignShift-1)*o.tx2width/2+d),a(v-o.by/2-1),i(o.tx2width),a(o.by+2)))})}function mut(e,t){var r=e.index,n=e.trace||{},i=e.cd[0],a=e.cd[r]||{};function o(h){return h||My(h)&&h===0}var s=Array.isArray(r)?function(h,d){var v=zf.castOption(i,r,h);return o(v)?v:zf.extractOption({},n,\"\",d)}:function(h,d){return zf.extractOption(a,n,h,d)};function l(h,d,v){var _=s(d,v);o(_)&&(e[h]=_)}if(l(\"hoverinfo\",\"hi\",\"hoverinfo\"),l(\"bgcolor\",\"hbg\",\"hoverlabel.bgcolor\"),l(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),l(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),l(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),l(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),l(\"fontWeight\",\"htw\",\"hoverlabel.font.weight\"),l(\"fontStyle\",\"hty\",\"hoverlabel.font.style\"),l(\"fontVariant\",\"htv\",\"hoverlabel.font.variant\"),l(\"nameLength\",\"hnl\",\"hoverlabel.namelength\"),l(\"textAlign\",\"hta\",\"hoverlabel.align\"),e.posref=t===\"y\"||t===\"closest\"&&n.orientation===\"h\"?e.xa._offset+(e.x0+e.x1)/2:e.ya._offset+(e.y0+e.y1)/2,e.x0=zf.constrain(e.x0,0,e.xa._length),e.x1=zf.constrain(e.x1,0,e.xa._length),e.y0=zf.constrain(e.y0,0,e.ya._length),e.y1=zf.constrain(e.y1,0,e.ya._length),e.xLabelVal!==void 0&&(e.xLabel=\"xLabel\"in e?e.xLabel:wm.hoverLabelText(e.xa,e.xLabelVal,n.xhoverformat),e.xVal=e.xa.c2d(e.xLabelVal)),e.yLabelVal!==void 0&&(e.yLabel=\"yLabel\"in e?e.yLabel:wm.hoverLabelText(e.ya,e.yLabelVal,n.yhoverformat),e.yVal=e.ya.c2d(e.yLabelVal)),e.zLabelVal!==void 0&&e.zLabel===void 0&&(e.zLabel=String(e.zLabelVal)),!isNaN(e.xerr)&&!(e.xa.type===\"log\"&&e.xerr<=0)){var u=wm.tickText(e.xa,e.xa.c2l(e.xerr),\"hover\").text;e.xerrneg!==void 0?e.xLabel+=\" +\"+u+\" / -\"+wm.tickText(e.xa,e.xa.c2l(e.xerrneg),\"hover\").text:e.xLabel+=\" \\xB1 \"+u,t===\"x\"&&(e.distance+=1)}if(!isNaN(e.yerr)&&!(e.ya.type===\"log\"&&e.yerr<=0)){var c=wm.tickText(e.ya,e.ya.c2l(e.yerr),\"hover\").text;e.yerrneg!==void 0?e.yLabel+=\" +\"+c+\" / -\"+wm.tickText(e.ya,e.ya.c2l(e.yerrneg),\"hover\").text:e.yLabel+=\" \\xB1 \"+c,t===\"y\"&&(e.distance+=1)}var f=e.hoverinfo||e.trace.hoverinfo;return f&&f!==\"all\"&&(f=Array.isArray(f)?f:f.split(\"+\"),f.indexOf(\"x\")===-1&&(e.xLabel=void 0),f.indexOf(\"y\")===-1&&(e.yLabel=void 0),f.indexOf(\"z\")===-1&&(e.zLabel=void 0),f.indexOf(\"text\")===-1&&(e.text=void 0),f.indexOf(\"name\")===-1&&(e.name=void 0)),e}function Ile(e,t,r){var n=r.container,i=r.fullLayout,a=i._size,o=r.event,s=!!t.hLinePoint,l=!!t.vLinePoint,u,c;if(n.selectAll(\".spikeline\").remove(),!!(l||s)){var f=vd.combine(i.plot_bgcolor,i.paper_bgcolor);if(s){var h=t.hLinePoint,d,v;u=h&&h.xa,c=h&&h.ya;var _=c.spikesnap;_===\"cursor\"?(d=o.pointerX,v=o.pointerY):(d=u._offset+h.x,v=c._offset+h.y);var b=kle.readability(h.color,f)<1.5?vd.contrast(f):h.color,p=c.spikemode,k=c.spikethickness,E=c.spikecolor||b,S=wm.getPxPosition(e,c),L,x;if(p.indexOf(\"toaxis\")!==-1||p.indexOf(\"across\")!==-1){if(p.indexOf(\"toaxis\")!==-1&&(L=S,x=d),p.indexOf(\"across\")!==-1){var 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p=b[mue][1],k=b[yue][1],E=b[_ue][1],S=b[xue][1],L=b[mue][2],x=b[yue][2],C=b[_ue][2],M=b[xue][2],g=s.xaxis&&(s.xaxis.type===\"date\"||s.xaxis.type===\"log\"),P=s.yaxis&&(s.yaxis.type===\"date\"||s.yaxis.type===\"log\");g&&(p=c_(s.xaxis,p),k=c_(s.xaxis,k),E=c_(s.xaxis,E),S=c_(s.xaxis,S)),P&&(L=c_(s.yaxis,L),x=c_(s.yaxis,x),C=c_(s.yaxis,C),M=c_(s.yaxis,M));var T=(k+S)/2,z=(L+C)/2,O=(S-k+E-p)/2,V=(M-x+C-L)/2,G=rct({x0:T,y0:z,x1:T+O*Kut,y1:z+V*Jut});g&&(G.x0=JL(s.xaxis,G.x0),G.x1=JL(s.xaxis,G.x1)),P&&(G.y0=JL(s.yaxis,G.y0),G.y1=JL(s.yaxis,G.y1)),_.x0=G.x0,_.y0=G.y0,_.x1=G.x1,_.y1=G.y1}else _.type=\"path\",u&&c&&ict(v,u,c),_.path=tct(v),b=null;return _}Aue.exports={newShapes:nct,createShapeObj:Tue}});var ZB=ye((Par,Sue)=>{\"use strict\";var act=Mg(),oct=act.selectMode,sct=Q1(),lct=sct.clearOutline,XB=u_(),uct=XB.readPaths,cct=XB.writePaths,fct=XB.fixDatesForPaths;Sue.exports=function(t,r){if(t.length){var n=t[0][0];if(n){var 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x=_;switch(L.type){case\"rect\":k(\"x0\",x.x0),k(\"x1\",x.x1),k(\"y0\",x.y0),k(\"y1\",x.y1);break;case\"path\":k(\"path\",x.path);break}}}return c===void 0?(E.push(_),E):p?p.getUpdateObj():{}}}}});var pM=ye((Iar,Mue)=>{\"use strict\";Mue.exports={segmentRE:/[MLHVQCTSZ][^MLHVQCTSZ]*/g,paramRE:/[^\\s,]+/g,paramIsX:{M:{0:!0,drawn:0},L:{0:!0,drawn:0},H:{0:!0,drawn:0},V:{},Q:{0:!0,2:!0,drawn:2},C:{0:!0,2:!0,4:!0,drawn:4},T:{0:!0,drawn:0},S:{0:!0,2:!0,drawn:2},Z:{}},paramIsY:{M:{1:!0,drawn:1},L:{1:!0,drawn:1},H:{},V:{0:!0,drawn:0},Q:{1:!0,3:!0,drawn:3},C:{1:!0,3:!0,5:!0,drawn:5},T:{1:!0,drawn:1},S:{1:!0,3:!0,drawn:5},Z:{}},numParams:{M:2,L:2,H:1,V:1,Q:4,C:6,T:2,S:4,Z:0}}});var f_=ye(Dd=>{\"use strict\";var Ob=pM(),Eue=Dr(),eP=ho();Dd.rangeToShapePosition=function(e){return e.type===\"log\"?e.r2d:function(t){return t}};Dd.shapePositionToRange=function(e){return e.type===\"log\"?e.d2r:function(t){return t}};Dd.decodeDate=function(e){return function(t){return t.replace&&(t=t.replace(\"_\",\" \")),e(t)}};Dd.encodeDate=function(e){return function(t){return e(t).replace(\" \",\"_\")}};Dd.extractPathCoords=function(e,t,r){var n=[],i=e.match(Ob.segmentRE);return i.forEach(function(a){var o=t[a.charAt(0)].drawn;if(o!==void 0){var s=a.substr(1).match(Ob.paramRE);if(!(!s||s.length<o)){var l=s[o],u=r?l:Eue.cleanNumber(l);n.push(u)}}}),n};Dd.getDataToPixel=function(e,t,r,n,i){var a=e._fullLayout._size,o;if(t)if(i===\"domain\")o=function(l){return t._length*(n?1-l:l)+t._offset};else{var s=Dd.shapePositionToRange(t);o=function(l){var u=gM(t,r);return t._offset+t.r2p(s(l,!0))+u},t.type===\"date\"&&(o=Dd.decodeDate(o))}else n?o=function(l){return a.t+a.h*(1-l)}:o=function(l){return a.l+a.w*l};return o};Dd.getPixelToData=function(e,t,r,n){var i=e._fullLayout._size,a;if(t)if(n===\"domain\")a=function(s){var l=(s-t._offset)/t._length;return r?1-l:l};else{var o=Dd.rangeToShapePosition(t);a=function(s){return o(t.p2r(s-t._offset))}}else r?a=function(s){return 1-(s-i.t)/i.h}:a=function(s){return(s-i.l)/i.w};return a};Dd.roundPositionForSharpStrokeRendering=function(e,t){var r=Math.round(t%2)===1,n=Math.round(e);return r?n+.5:n};Dd.makeShapesOptionsAndPlotinfo=function(e,t){var r=e._fullLayout.shapes[t]||{},n=e._fullLayout._plots[r.xref+r.yref],i=!!n;return i?n._hadPlotinfo=!0:(n={},r.xref&&r.xref!==\"paper\"&&(n.xaxis=e._fullLayout[r.xref+\"axis\"]),r.yref&&r.yref!==\"paper\"&&(n.yaxis=e._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}};Dd.makeSelectionsOptionsAndPlotinfo=function(e,t){var r=e._fullLayout.selections[t]||{},n=e._fullLayout._plots[r.xref+r.yref],i=!!n;return i?n._hadPlotinfo=!0:(n={},r.xref&&(n.xaxis=e._fullLayout[r.xref+\"axis\"]),r.yref&&(n.yaxis=e._fullLayout[r.yref+\"axis\"])),{options:r,plotinfo:n}};Dd.getPathString=function(e,t){var r=t.type,n=eP.getRefType(t.xref),i=eP.getRefType(t.yref),a=eP.getFromId(e,t.xref),o=eP.getFromId(e,t.yref),s=e._fullLayout._size,l,u,c,f,h=gM(a,t.x0shift),d=gM(a,t.x1shift),v=gM(o,t.y0shift),_=gM(o,t.y1shift),b,p,k,E;if(a?n===\"domain\"?u=function(O){return a._offset+a._length*O}:(l=Dd.shapePositionToRange(a),u=function(O){return a._offset+a.r2p(l(O,!0))}):u=function(O){return s.l+s.w*O},o?i===\"domain\"?f=function(O){return o._offset+o._length*(1-O)}:(c=Dd.shapePositionToRange(o),f=function(O){return o._offset+o.r2p(c(O,!0))}):f=function(O){return s.t+s.h*(1-O)},r===\"path\")return a&&a.type===\"date\"&&(u=Dd.decodeDate(u)),o&&o.type===\"date\"&&(f=Dd.decodeDate(f)),hct(t,u,f);if(t.xsizemode===\"pixel\"){var S=u(t.xanchor);b=S+t.x0+h,p=S+t.x1+d}else b=u(t.x0)+h,p=u(t.x1)+d;if(t.ysizemode===\"pixel\"){var L=f(t.yanchor);k=L-t.y0+v,E=L-t.y1+_}else k=f(t.y0)+v,E=f(t.y1)+_;if(r===\"line\")return\"M\"+b+\",\"+k+\"L\"+p+\",\"+E;if(r===\"rect\")return\"M\"+b+\",\"+k+\"H\"+p+\"V\"+E+\"H\"+b+\"Z\";var x=(b+p)/2,C=(k+E)/2,M=Math.abs(x-b),g=Math.abs(C-k),P=\"A\"+M+\",\"+g,T=x+M+\",\"+C,z=x+\",\"+(C-g);return\"M\"+T+P+\" 0 1,1 \"+z+P+\" 0 0,1 \"+T+\"Z\"};function hct(e,t,r){var n=e.path,i=e.xsizemode,a=e.ysizemode,o=e.xanchor,s=e.yanchor;return n.replace(Ob.segmentRE,function(l){var u=0,c=l.charAt(0),f=Ob.paramIsX[c],h=Ob.paramIsY[c],d=Ob.numParams[c],v=l.substr(1).replace(Ob.paramRE,function(_){return f[u]?i===\"pixel\"?_=t(o)+Number(_):_=t(_):h[u]&&(a===\"pixel\"?_=r(s)-Number(_):_=r(_)),u++,u>d&&(_=\"X\"),_});return u>d&&(v=v.replace(/[\\s,]*X.*/,\"\"),Eue.log(\"Ignoring extra params in segment \"+l)),c+v})}function gM(e,t){t=t||0;var r=0;return t&&e&&(e.type===\"category\"||e.type===\"multicategory\")&&(r=(e.r2p(1)-e.r2p(0))*t),r}});var KB=ye((Dar,Pue)=>{\"use strict\";var dct=Dr(),X3=ho(),kue=ru(),Cue=So(),vct=u_().readPaths,YB=f_(),pct=YB.getPathString,Lue=M6(),gct=$h().FROM_TL;Pue.exports=function(t,r,n,i){if(i.selectAll(\".shape-label\").remove(),!!(n.label.text||n.label.texttemplate)){var a;if(n.label.texttemplate){var o={};if(n.type!==\"path\"){var s=X3.getFromId(t,n.xref),l=X3.getFromId(t,n.yref);for(var u in Lue){var c=Lue[u](n,s,l);c!==void 0&&(o[u]=c)}}a=dct.texttemplateStringForShapes({data:[o],fallback:n.label.texttemplatefallback,locale:t._fullLayout._d3locale,template:n.label.texttemplate})}else a=n.label.text;var f={\"data-index\":r},h=n.label.font,d={\"data-notex\":1},v=i.append(\"g\").attr(f).classed(\"shape-label\",!0),_=v.append(\"text\").attr(d).classed(\"shape-label-text\",!0).text(a),b,p,k,E;if(n.path){var S=pct(t,n),L=vct(S,t);b=1/0,k=1/0,p=-1/0,E=-1/0;for(var x=0;x<L.length;x++)for(var C=0;C<L[x].length;C++)for(var M=L[x][C],g=1;g<M.length;g+=2){var P=M[g],T=M[g+1];b=Math.min(b,P),p=Math.max(p,P),k=Math.min(k,T),E=Math.max(E,T)}}else{var z=X3.getFromId(t,n.xref),O=n.x0shift,V=n.x1shift,G=X3.getRefType(n.xref),Z=X3.getFromId(t,n.yref),H=n.y0shift,N=n.y1shift,j=X3.getRefType(n.yref),re=function(Le,Ae){var Fe=YB.getDataToPixel(t,z,Ae,!1,G);return Fe(Le)},oe=function(Le,Ae){var Fe=YB.getDataToPixel(t,Z,Ae,!0,j);return Fe(Le)};b=re(n.x0,O),p=re(n.x1,V),k=oe(n.y0,H),E=oe(n.y1,N)}var _e=n.label.textangle;_e===\"auto\"&&(n.type===\"line\"?_e=mct(b,k,p,E):_e=0),_.call(function(Le){return Le.call(Cue.font,h).attr({}),kue.convertToTspans(Le,t),Le});var Ee=Cue.bBox(_.node()),Ce=yct(b,k,p,E,n,_e,Ee),me=Ce.textx,ie=Ce.texty,Se=Ce.xanchor;_.attr({\"text-anchor\":{left:\"start\",center:\"middle\",right:\"end\"}[Se],y:ie,x:me,transform:\"rotate(\"+_e+\",\"+me+\",\"+ie+\")\"}).call(kue.positionText,me,ie)}};function mct(e,t,r,n){var i,a;return a=Math.abs(r-e),r>=e?i=t-n:i=n-t,-180/Math.PI*Math.atan2(i,a)}function yct(e,t,r,n,i,a,o){var s=i.label.textposition,l=i.label.textangle,u=i.label.padding,c=i.type,f=Math.PI/180*a,h=Math.sin(f),d=Math.cos(f),v=i.label.xanchor,_=i.label.yanchor,b,p,k,E;if(c===\"line\"){s===\"start\"?(b=e,p=t):s===\"end\"?(b=r,p=n):(b=(e+r)/2,p=(t+n)/2),v===\"auto\"&&(s===\"start\"?l===\"auto\"?r>e?v=\"left\":r<e?v=\"right\":v=\"center\":r>e?v=\"right\":r<e?v=\"left\":v=\"center\":s===\"end\"?l===\"auto\"?r>e?v=\"right\":r<e?v=\"left\":v=\"center\":r>e?v=\"left\":r<e?v=\"right\":v=\"center\":v=\"center\");var S={left:1,center:0,right:-1},L={bottom:-1,middle:0,top:1};if(l===\"auto\"){var x=L[_];k=-u*h*x,E=u*d*x}else{var C=S[v],M=L[_];k=u*C,E=u*M}b=b+k,p=p+E}else k=u+3,s.indexOf(\"right\")!==-1?(b=Math.max(e,r)-k,v===\"auto\"&&(v=\"right\")):s.indexOf(\"left\")!==-1?(b=Math.min(e,r)+k,v===\"auto\"&&(v=\"left\")):(b=(e+r)/2,v===\"auto\"&&(v=\"center\")),s.indexOf(\"top\")!==-1?p=Math.min(t,n):s.indexOf(\"bottom\")!==-1?p=Math.max(t,n):p=(t+n)/2,E=u,_===\"bottom\"?p=p-E:_===\"top\"&&(p=p+E);var g=gct[_],P=i.label.font.size,T=o.height,z=(T*g-P)*h,O=-(T*g-P)*d;return{textx:b+z,texty:p+O,xanchor:v}}});var iP=ye((Far,Bue)=>{\"use strict\";var _ct=Dr(),xct=_ct.strTranslate,Iue=yv(),Fue=Mg(),bct=Fue.drawMode,zue=Fue.selectMode,Oue=qa(),Rue=ka(),rP=ZL(),wct=rP.i000,Tct=rP.i090,Act=rP.i180,Sct=rP.i270,Mct=Q1(),que=Mct.clearOutlineControllers,$B=u_(),tP=$B.pointsOnRectangle,JB=$B.pointsOnEllipse,Ect=$B.writePaths,kct=QL().newShapes,Cct=QL().createShapeObj,Lct=ZB(),Pct=KB();Bue.exports=function e(t,r,n,i){i||(i=0);var a=n.gd;function o(){e(t,r,n,i++),(JB(t[0])||n.hasText)&&s({redrawing:!0})}function s(H){var N={};n.isActiveShape!==void 0&&(n.isActiveShape=!1,N=kct(r,n)),n.isActiveSelection!==void 0&&(n.isActiveSelection=!1,N=Lct(r,n),a._fullLayout._reselect=!0),Object.keys(N).length&&Oue.call((H||{}).redrawing?\"relayout\":\"_guiRelayout\",a,N)}var l=a._fullLayout,u=l._zoomlayer,c=n.dragmode,f=bct(c),h=zue(c);(f||h)&&(a._fullLayout._outlining=!0),que(a),r.attr(\"d\",Ect(t));var d,v,_,b,p;if(!i&&(n.isActiveShape||n.isActiveSelection)){p=Ict([],t);var k=u.append(\"g\").attr(\"class\",\"outline-controllers\");P(k),Z()}if(f&&n.hasText){var E=u.select(\".label-temp\"),S=Cct(r,n,n.dragmode);Pct(a,\"label-temp\",S,E)}function L(H){_=+H.srcElement.getAttribute(\"data-i\"),b=+H.srcElement.getAttribute(\"data-j\"),d[_][b].moveFn=x}function x(H,N){if(t.length){var j=p[_][b][1],re=p[_][b][2],oe=t[_],_e=oe.length;if(tP(oe)){var Ee=H,Ce=N;if(n.isActiveSelection){var me=Due(oe,b);me[1]===oe[b][1]?Ce=0:Ee=0}for(var ie=0;ie<_e;ie++)if(ie!==b){var Se=oe[ie];Se[1]===oe[b][1]&&(Se[1]=j+Ee),Se[2]===oe[b][2]&&(Se[2]=re+Ce)}if(oe[b][1]=j+Ee,oe[b][2]=re+Ce,!tP(oe))for(var Le=0;Le<_e;Le++)for(var Ae=0;Ae<oe[Le].length;Ae++)oe[Le][Ae]=p[_][Le][Ae]}else oe[b][1]=j+H,oe[b][2]=re+N;o()}}function C(){s()}function M(){if(t.length&&t[_]&&t[_].length){for(var H=[],N=0;N<t[_].length;N++)N!==b&&H.push(t[_][N]);H.length>1&&!(H.length===2&&H[1][0]===\"Z\")&&(b===0&&(H[0][0]=\"M\"),t[_]=H,o(),s())}}function g(H,N){if(H===2){_=+N.srcElement.getAttribute(\"data-i\"),b=+N.srcElement.getAttribute(\"data-j\");var j=t[_];!tP(j)&&!JB(j)&&M()}}function P(H){d=[];for(var N=0;N<t.length;N++){var j=t[N],re=tP(j),oe=!re&&JB(j);d[N]=[];for(var _e=j.length,Ee=0;Ee<_e;Ee++)if(j[Ee][0]!==\"Z\"&&!(oe&&Ee!==wct&&Ee!==Tct&&Ee!==Act&&Ee!==Sct)){var Ce=re&&n.isActiveSelection,me;Ce&&(me=Due(j,Ee));var ie=j[Ee][1],Se=j[Ee][2],Le=H.append(Ce?\"rect\":\"circle\").attr(\"data-i\",N).attr(\"data-j\",Ee).style({fill:Rue.background,stroke:Rue.defaultLine,\"stroke-width\":1,\"shape-rendering\":\"crispEdges\"});if(Ce){var Ae=me[1]-ie,Fe=me[2]-Se,Pe=Fe?5:Math.max(Math.min(25,Math.abs(Ae)-5),5),ge=Ae?5:Math.max(Math.min(25,Math.abs(Fe)-5),5);Le.classed(Fe?\"cursor-ew-resize\":\"cursor-ns-resize\",!0).attr(\"width\",Pe).attr(\"height\",ge).attr(\"x\",ie-Pe/2).attr(\"y\",Se-ge/2).attr(\"transform\",xct(Ae/2,Fe/2))}else Le.classed(\"cursor-grab\",!0).attr(\"r\",5).attr(\"cx\",ie).attr(\"cy\",Se);d[N][Ee]={element:Le.node(),gd:a,prepFn:L,doneFn:C,clickFn:g},Iue.init(d[N][Ee])}}}function T(H,N){if(t.length)for(var j=0;j<t.length;j++)for(var re=0;re<t[j].length;re++)for(var oe=0;oe+2<t[j][re].length;oe+=2)t[j][re][oe+1]=p[j][re][oe+1]+H,t[j][re][oe+2]=p[j][re][oe+2]+N}function z(H,N){T(H,N),o()}function O(H){_=+H.srcElement.getAttribute(\"data-i\"),_||(_=0),v[_].moveFn=z}function V(){s()}function G(H){H===2&&Rct(a)}function Z(){if(v=[],!!t.length){var H=0;v[H]={element:r[0][0],gd:a,prepFn:O,doneFn:V,clickFn:G},Iue.init(v[H])}}};function Ict(e,t){for(var r=0;r<t.length;r++){var n=t[r];e[r]=[];for(var i=0;i<n.length;i++){e[r][i]=[];for(var a=0;a<n[i].length;a++)e[r][i][a]=n[i][a]}}return e}function Due(e,t){var r=e[t][1],n=e[t][2],i=e.length,a,o,s;return a=(t+1)%i,o=e[a][1],s=e[a][2],o===r&&s===n&&(a=(t+2)%i,o=e[a][1],s=e[a][2]),[a,o,s]}function Rct(e){if(zue(e._fullLayout.dragmode)){que(e);var t=e._fullLayout._activeSelectionIndex,r=(e.layout||{}).selections||[];if(t<r.length){for(var n=[],i=0;i<r.length;i++)i!==t&&n.push(r[i]);delete e._fullLayout._activeSelectionIndex;var a=e._fullLayout.selections[t];e._fullLayout._deselect={xref:a.xref,yref:a.yref},Oue.call(\"_guiRelayout\",e,{selections:n})}}}});var sP=ye((zar,Yue)=>{\"use strict\";var Dct=Oa(),jue=qa(),Nue=Dr(),Z3=ho(),Fct=u_().readPaths,zct=iP(),aP=KB(),Wue=Q1().clearOutlineControllers,QB=ka(),tN=So(),Oct=vl().arrayEditor,Uue=yv(),Vue=Ag(),qb=pM(),Ep=f_(),eN=Ep.getPathString;Yue.exports={draw:rN,drawOne:Xue,eraseActiveShape:Nct,drawLabel:aP};function rN(e){var t=e._fullLayout;t._shapeUpperLayer.selectAll(\"path\").remove(),t._shapeLowerLayer.selectAll(\"path\").remove(),t._shapeUpperLayer.selectAll(\"text\").remove(),t._shapeLowerLayer.selectAll(\"text\").remove();for(var r in t._plots){var n=t._plots[r].shapelayer;n&&(n.selectAll(\"path\").remove(),n.selectAll(\"text\").remove())}for(var i=0;i<t.shapes.length;i++)t.shapes[i].visible===!0&&Xue(e,i)}function nP(e){return!!e._fullLayout._outlining}function oP(e){return!e._context.edits.shapePosition}function Xue(e,t){e._fullLayout._paperdiv.selectAll('.shapelayer [data-index=\"'+t+'\"]').remove();var r=Ep.makeShapesOptionsAndPlotinfo(e,t),n=r.options,i=r.plotinfo;if(!n._input||n.visible!==!0)return;if(n.layer===\"above\")o(e._fullLayout._shapeUpperLayer);else if(n.xref===\"paper\"||n.yref===\"paper\")o(e._fullLayout._shapeLowerLayer);else if(n.layer===\"between\")o(i.shapelayerBetween);else if(i._hadPlotinfo){var a=i.mainplotinfo||i;o(a.shapelayer)}else 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t=e._context.toImageButtonOptions||{},r=t.format||\"png\";return r===\"png\"?tl(e,\"Download plot as a PNG\"):tl(e,\"Download plot\")},icon:Pl.camera,click:function(e){var t=e._context.toImageButtonOptions,r={format:t.format||\"png\"};lP.notifier(tl(e,\"Taking snapshot - this may take a few seconds\"),\"long\"),[\"filename\",\"width\",\"height\",\"scale\"].forEach(function(n){n in t&&(r[n]=t[n])}),A0.call(\"downloadImage\",e,r).then(function(n){lP.notifier(tl(e,\"Snapshot succeeded\")+\" - \"+n,\"long\")}).catch(function(){lP.notifier(tl(e,\"Sorry, there was a problem downloading your snapshot!\"),\"long\")})}};Il.sendDataToCloud={name:\"sendDataToCloud\",title:function(e){return tl(e,\"Edit in Chart Studio\")},icon:Pl.disk,click:function(e){Kue.sendDataToCloud(e)}};Il.editInChartStudio={name:\"editInChartStudio\",title:function(e){return tl(e,\"Edit in Chart 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r=t.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=e._fullLayout,o={},s=Jue.list(e,null,!0),l=a._cartesianSpikesEnabled,u,c;if(n===\"zoom\"){var f=i===\"in\"?.5:2,h=(1+f)/2,d=(1-f)/2,v,_;for(c=0;c<s.length;c++)if(u=s[c],_=u.modebardisable===\"none\"||u.modebardisable.indexOf(i===\"auto\"||i===\"reset\"?\"autoscale\":\"zoominout\")===-1,_&&!u.fixedrange)if(v=u._name,i===\"auto\")o[v+\".autorange\"]=!0;else if(i===\"reset\")u._rangeInitial0===void 0&&u._rangeInitial1===void 0?o[v+\".autorange\"]=!0:u._rangeInitial0===void 0?(o[v+\".autorange\"]=u._autorangeInitial,o[v+\".range\"]=[null,u._rangeInitial1]):u._rangeInitial1===void 0?(o[v+\".range\"]=[u._rangeInitial0,null],o[v+\".autorange\"]=u._autorangeInitial):o[v+\".range\"]=[u._rangeInitial0,u._rangeInitial1],u._showSpikeInitial!==void 0&&(o[v+\".showspikes\"]=u._showSpikeInitial,l===\"on\"&&!u._showSpikeInitial&&(l=\"off\"));else{var 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r=t.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=e._fullLayout._subplots.gl3d||[],o={},s=n.split(\".\"),l=0;l<a.length;l++)o[a[l]+\".\"+s[1]]=i;var u=i===\"pan\"?i:\"zoom\";o.dragmode=u,A0.call(\"_guiRelayout\",e,o)}Il.resetCameraDefault3d={name:\"resetCameraDefault3d\",_cat:\"resetCameraDefault\",title:function(e){return tl(e,\"Reset camera to default\")},attr:\"resetDefault\",icon:Pl.home,click:iN};Il.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",_cat:\"resetCameraLastSave\",title:function(e){return tl(e,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:Pl.movie,click:iN};function iN(e,t){for(var r=t.currentTarget,n=r.getAttribute(\"data-attr\"),i=n===\"resetLastSave\",a=n===\"resetDefault\",o=e._fullLayout,s=o._subplots.gl3d||[],l={},u=0;u<s.length;u++){var 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v=o[d],_=c+\".\"+v+\".showspikes\";l[_]=!1,s[_]=f[v].showspikes}}r._previousVal=s}return l}function Vct(e,t){var r=$ue(e,t);A0.call(\"_guiRelayout\",e,r)}Il.zoomInGeo={name:\"zoomInGeo\",_cat:\"zoomin\",title:function(e){return tl(e,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:Pl.zoom_plus,click:nN};Il.zoomOutGeo={name:\"zoomOutGeo\",_cat:\"zoomout\",title:function(e){return tl(e,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:Pl.zoom_minus,click:nN};Il.resetGeo={name:\"resetGeo\",_cat:\"reset\",title:function(e){return tl(e,\"Reset\")},attr:\"reset\",val:null,icon:Pl.autoscale,click:nN};Il.hoverClosestGeo={name:\"hoverClosestGeo\",_cat:\"hoverclosest\",title:function(e){return tl(e,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:Pl.tooltip_basic,gravity:\"ne\",click:ece};function nN(e,t){for(var r=t.currentTarget,n=r.getAttribute(\"data-attr\"),i=r.getAttribute(\"data-val\")||!0,a=e._fullLayout,o=a._subplots.geo||[],s=0;s<o.length;s++){var l=o[s],u=a[l];if(n===\"zoom\"){var c=u.projection.scale,f=i===\"in\"?2*c:.5*c;A0.call(\"_guiRelayout\",e,l+\".projection.scale\",f)}}n===\"reset\"&&Y3(e,\"geo\")}Il.hoverClosestPie={name:\"hoverClosestPie\",_cat:\"hoverclosest\",title:function(e){return tl(e,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:Pl.tooltip_basic,gravity:\"ne\",click:ece};function Que(e){var t=e._fullLayout;return t.hovermode?!1:t._has(\"cartesian\")?t._isHoriz?\"y\":\"x\":\"closest\"}function ece(e){var t=Que(e);A0.call(\"_guiRelayout\",e,\"hovermode\",t)}Il.resetViewSankey={name:\"resetSankeyGroup\",title:function(e){return tl(e,\"Reset view\")},icon:Pl.home,click:function(e){for(var t={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<e._fullData.length;r++){var n=e._fullData[r]._viewInitial;t[\"node.groups\"].push(n.node.groups.slice()),t[\"node.x\"].push(n.node.x.slice()),t[\"node.y\"].push(n.node.y.slice())}A0.call(\"restyle\",e,t)}};Il.toggleHover={name:\"toggleHover\",title:function(e){return tl(e,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:Pl.tooltip_basic,gravity:\"ne\",click:function(e,t){var r=$ue(e,t);r.hovermode=Que(e),A0.call(\"_guiRelayout\",e,r)}};Il.resetViews={name:\"resetViews\",title:function(e){return tl(e,\"Reset views\")},icon:Pl.home,click:function(e,t){var r=t.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),Bv(e,t),r.setAttribute(\"data-attr\",\"resetLastSave\"),iN(e,t),Y3(e,\"geo\"),Y3(e,\"mapbox\"),Y3(e,\"map\")}};Il.toggleSpikelines={name:\"toggleSpikelines\",title:function(e){return tl(e,\"Toggle Spike Lines\")},icon:Pl.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(e){var t=e._fullLayout,r=t._cartesianSpikesEnabled;t._cartesianSpikesEnabled=r===\"on\"?\"off\":\"on\",A0.call(\"_guiRelayout\",e,Gct(e))}};function Gct(e){for(var t=e._fullLayout,r=t._cartesianSpikesEnabled===\"on\",n=Jue.list(e,null,!0),i={},a=0;a<n.length;a++){var o=n[a];i[o._name+\".showspikes\"]=r?!0:o._showSpikeInitial}return i}Il.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(e){return tl(e,\"Reset view\")},attr:\"reset\",icon:Pl.home,click:function(e){Y3(e,\"mapbox\")}};Il.resetViewMap={name:\"resetViewMap\",_cat:\"resetView\",title:function(e){return tl(e,\"Reset view\")},attr:\"reset\",icon:Pl.home,click:function(e){Y3(e,\"map\")}};Il.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(e){return tl(e,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:Pl.zoom_plus,click:tce};Il.zoomInMap={name:\"zoomInMap\",_cat:\"zoomin\",title:function(e){return tl(e,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:Pl.zoom_plus,click:rce};Il.zoomOutMapbox={name:\"zoomOutMapbox\",_cat:\"zoomout\",title:function(e){return tl(e,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:Pl.zoom_minus,click:tce};Il.zoomOutMap={name:\"zoomOutMap\",_cat:\"zoomout\",title:function(e){return tl(e,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:Pl.zoom_minus,click:rce};function tce(e,t){ice(e,t,\"mapbox\")}function rce(e,t){ice(e,t,\"map\")}function ice(e,t,r){for(var n=t.currentTarget,i=n.getAttribute(\"data-val\"),a=e._fullLayout,o=a._subplots[r]||[],s=1.05,l={},u=0;u<o.length;u++){var c=o[u],f=a[c].zoom,h=i===\"in\"?s*f:f/s;l[c+\".zoom\"]=h}A0.call(\"_guiRelayout\",e,l)}function Y3(e,t){for(var r=e._fullLayout,n=r._subplots[t]||[],i={},a=0;a<n.length;a++)for(var o=n[a],s=r[o]._subplot,l=s.viewInitial,u=Object.keys(l),c=0;c<u.length;c++){var f=u[c];i[o+\".\"+f]=l[f]}A0.call(\"_guiRelayout\",e,i)}});var oN=ye((qar,lce)=>{\"use strict\";var ace=aN(),Hct=Object.keys(ace),oce=[\"drawline\",\"drawopenpath\",\"drawclosedpath\",\"drawcircle\",\"drawrect\",\"eraseshape\"],sce=[\"v1hovermode\",\"hoverclosest\",\"hovercompare\",\"togglehover\",\"togglespikelines\"].concat(oce),K3=[],jct=function(e){if(sce.indexOf(e._cat||e.name)===-1){var t=e.name,r=(e._cat||e.name).toLowerCase();K3.indexOf(t)===-1&&K3.push(t),K3.indexOf(r)===-1&&K3.push(r)}};Hct.forEach(function(e){jct(ace[e])});K3.sort();lce.exports={DRAW_MODES:oce,backButtons:sce,foreButtons:K3}});var sN=ye((Nar,uce)=>{\"use strict\";var Bar=oN();uce.exports={editType:\"modebar\",orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\",editType:\"modebar\"},bgcolor:{valType:\"color\",editType:\"modebar\"},color:{valType:\"color\",editType:\"modebar\"},activecolor:{valType:\"color\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},add:{valType:\"string\",arrayOk:!0,dflt:\"\",editType:\"modebar\"},remove:{valType:\"string\",arrayOk:!0,dflt:\"\",editType:\"modebar\"}}});var fce=ye((Uar,cce)=>{\"use strict\";var Wct=Dr(),mM=ka(),Xct=vl(),Zct=sN();cce.exports=function(t,r){var n=t.modebar||{},i=Xct.newContainer(r,\"modebar\");function a(s,l){return Wct.coerce(n,i,Zct,s,l)}a(\"orientation\"),a(\"bgcolor\",mM.addOpacity(r.paper_bgcolor,.5));var o=mM.contrast(mM.rgb(r.modebar.bgcolor));a(\"color\",mM.addOpacity(o,.3)),a(\"activecolor\",mM.addOpacity(o,.7)),a(\"uirevision\",r.uirevision),a(\"add\"),a(\"remove\")}});var pce=ye((Var,vce)=>{\"use strict\";var lN=Oa(),Yct=Eo(),cP=Dr(),hce=WL(),Kct=l6().version,Jct=new DOMParser;function dce(e){this.container=e.container,this.element=document.createElement(\"div\"),this.update(e.graphInfo,e.buttons),this.container.appendChild(this.element)}var Tm=dce.prototype;Tm.update=function(e,t){this.graphInfo=e;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this.element.setAttribute(\"role\",\"toolbar\"),this._uid=i,this.element.className=\"modebar modebar--custom\",r.displayModeBar===\"hover\"&&(this.element.className+=\" modebar--hover ease-bg\"),n.modebar.orientation===\"v\"&&(this.element.className+=\" vertical\",t=t.reverse());var a=n.modebar,o=\"#\"+i+\" .modebar-group\";document.querySelectorAll(o).forEach(function(f){f.style.backgroundColor=a.bgcolor});var s=!this.hasButtons(t),l=this.hasLogo!==r.displaylogo,u=this.locale!==r.locale;if(this.locale=r.locale,(s||l||u)&&(this.removeAllButtons(),this.updateButtons(t),r.watermark||r.displaylogo)){var c=this.getLogo();r.watermark&&(c.className=c.className+\" watermark\"),n.modebar.orientation===\"v\"?this.element.insertBefore(c,this.element.childNodes[0]):this.element.appendChild(c),this.hasLogo=!0}this.updateActiveButton(),cP.setStyleOnHover(\"#\"+i+\" .modebar-btn\",\".active\",\".icon path\",\"fill: \"+a.activecolor,\"fill: \"+a.color,this.element)};Tm.updateButtons=function(e){var t=this;this.buttons=e,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach(function(r){var n=t.createGroup();r.forEach(function(i){var a=i.name;if(!a)throw new Error(\"must provide button 'name' in button config\");if(t.buttonsNames.indexOf(a)!==-1)throw new Error(\"button name '\"+a+\"' is taken\");t.buttonsNames.push(a);var o=t.createButton(i);t.buttonElements.push(o),n.appendChild(o)}),t.element.appendChild(n)})};Tm.createGroup=function(){var e=document.createElement(\"div\");e.className=\"modebar-group\";var t=this.graphInfo._fullLayout.modebar;return e.style.backgroundColor=t.bgcolor,e};Tm.createButton=function(e){var t=this,r=document.createElement(\"button\");r.setAttribute(\"type\",\"button\"),r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var n=e.title;n===void 0?n=e.name:typeof n==\"function\"&&(n=n(this.graphInfo)),(n||n===0)&&(r.setAttribute(\"data-title\",n),r.setAttribute(\"aria-label\",n)),e.attr!==void 0&&r.setAttribute(\"data-attr\",e.attr);var i=e.val;i!==void 0&&(typeof i==\"function\"&&(i=i(this.graphInfo)),r.setAttribute(\"data-val\",i));var a=e.click;if(typeof a!=\"function\")throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",function(s){e.click(t.graphInfo,s),t.updateActiveButton(s.currentTarget)}),r.setAttribute(\"data-toggle\",e.toggle||!1),e.toggle&&lN.select(r).classed(\"active\",!0);var o=e.icon;return typeof o==\"function\"?r.appendChild(o()):r.appendChild(this.createIcon(o||hce.question)),r.setAttribute(\"data-gravity\",e.gravity||\"n\"),r};Tm.createIcon=function(e){var t=Yct(e.height)?Number(e.height):e.ascent-e.descent,r=\"http://www.w3.org/2000/svg\",n;if(e.path){n=document.createElementNS(r,\"svg\"),n.setAttribute(\"viewBox\",[0,0,e.width,t].join(\" \")),n.setAttribute(\"class\",\"icon\");var i=document.createElementNS(r,\"path\");i.setAttribute(\"d\",e.path),e.transform?i.setAttribute(\"transform\",e.transform):e.ascent!==void 0&&i.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+e.ascent+\")\"),n.appendChild(i)}if(e.svg){var a=Jct.parseFromString(e.svg,\"application/xml\");n=a.childNodes[0]}return n.setAttribute(\"height\",\"1em\"),n.setAttribute(\"width\",\"1em\"),n};Tm.updateActiveButton=function(e){var t=this.graphInfo._fullLayout,r=e!==void 0?e.getAttribute(\"data-attr\"):null;this.buttonElements.forEach(function(n){var i=n.getAttribute(\"data-val\")||!0,a=n.getAttribute(\"data-attr\"),o=n.getAttribute(\"data-toggle\")===\"true\",s=lN.select(n),l=function(f,h){var d=t.modebar,v=f.querySelector(\".icon path\");v&&(h||f.matches(\":hover\")?v.style.fill=d.activecolor:v.style.fill=d.color)};if(o){if(a===r){var u=!s.classed(\"active\");s.classed(\"active\",u),l(n,u)}}else{var c=a===null?a:cP.nestedProperty(t,a).get();s.classed(\"active\",c===i),l(n,c===i)}})};Tm.hasButtons=function(e){var t=this.buttons;if(!t||e.length!==t.length)return!1;for(var r=0;r<e.length;++r){if(e[r].length!==t[r].length)return!1;for(var n=0;n<e[r].length;n++)if(e[r][n].name!==t[r][n].name)return!1}return!0};function $ct(e){return e+\" (v\"+Kct+\")\"}Tm.getLogo=function(){var e=this.createGroup(),t=document.createElement(\"a\");return t.href=\"https://plotly.com/\",t.target=\"_blank\",t.setAttribute(\"data-title\",$ct(cP._(this.graphInfo,\"Produced with Plotly.js\"))),t.className=\"modebar-btn plotlyjsicon modebar-btn--logo\",t.appendChild(this.createIcon(hce.newplotlylogo)),e.appendChild(t),e};Tm.removeAllButtons=function(){for(;this.element.firstChild;)this.element.removeChild(this.element.firstChild);this.hasLogo=!1};Tm.destroy=function(){cP.removeElement(this.container.querySelector(\".modebar\"))};function Qct(e,t){var r=e._fullLayout,n=new dce({graphInfo:e,container:r._modebardiv.node(),buttons:t});return r._privateplot&&lN.select(n.element).append(\"span\").classed(\"badge-private float--left\",!0).text(\"PRIVATE\"),n}vce.exports=Qct});var yce=ye((Gar,mce)=>{\"use strict\";var eft=hf(),gce=Ru(),uN=qa(),tft=ip().isUnifiedHover,rft=pce(),fP=aN(),ift=oN().DRAW_MODES,nft=Dr().extendDeep;mce.exports=function(t){var r=t._fullLayout,n=t._context,i=r._modeBar;if(!n.displayModeBar&&!n.watermark){i&&(i.destroy(),delete r._modeBar);return}if(!Array.isArray(n.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(n.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var a=n.modeBarButtons,o;Array.isArray(a)&&a.length?o=cft(a):!n.displayModeBar&&n.watermark?o=[]:o=aft(t),i?i.update(t,o):r._modeBar=rft(t,o)};function aft(e){var t=e._fullLayout,r=e._fullData,n=e._context;function i(N,j){if(typeof j==\"string\"){if(j.toLowerCase()===N.toLowerCase())return!0}else{var re=j.name,oe=j._cat||j.name;if(re===N||oe===N.toLowerCase())return!0}return!1}var a=t.modebar.add;typeof a==\"string\"&&(a=[a]);var o=t.modebar.remove;typeof o==\"string\"&&(o=[o]);var s=n.modeBarButtonsToAdd.concat(a.filter(function(N){for(var j=0;j<n.modeBarButtonsToRemove.length;j++)if(i(N,n.modeBarButtonsToRemove[j]))return!1;return!0})),l=n.modeBarButtonsToRemove.concat(o.filter(function(N){for(var j=0;j<n.modeBarButtonsToAdd.length;j++)if(i(N,n.modeBarButtonsToAdd[j]))return!1;return!0})),u=t._has(\"cartesian\"),c=t._has(\"gl3d\"),f=t._has(\"geo\"),h=t._has(\"pie\"),d=t._has(\"funnelarea\"),v=t._has(\"ternary\"),_=t._has(\"mapbox\"),b=t._has(\"map\"),p=t._has(\"polar\"),k=t._has(\"smith\"),E=t._has(\"sankey\"),S=oft(t),L=tft(t.hovermode),x=[];function C(N){if(N.length){for(var j=[],re=0;re<N.length;re++){for(var oe=N[re],_e=fP[oe],Ee=_e.name.toLowerCase(),Ce=(_e._cat||_e.name).toLowerCase(),me=!1,ie=0;ie<l.length;ie++){var Se=l[ie].toLowerCase();if(Se===Ee||Se===Ce){me=!0;break}}me||j.push(fP[oe])}x.push(j)}}var M=[\"toImage\"];n.showEditInChartStudio?M.push(\"editInChartStudio\"):n.showSendToCloud&&M.push(\"sendDataToCloud\"),C(M);var g=[],P=[],T=[],z=[];(u||h||d||v)+f+c+_+b+p+k>1?(P=[\"toggleHover\"],T=[\"resetViews\"]):f?(g=[\"zoomInGeo\",\"zoomOutGeo\"],P=[\"hoverClosestGeo\"],T=[\"resetGeo\"]):c?(P=[\"hoverClosest3d\"],T=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):_?(g=[\"zoomInMapbox\",\"zoomOutMapbox\"],P=[\"toggleHover\"],T=[\"resetViewMapbox\"]):b?(g=[\"zoomInMap\",\"zoomOutMap\"],P=[\"toggleHover\"],T=[\"resetViewMap\"]):h?P=[\"hoverClosestPie\"]:E?(P=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],T=[\"resetViewSankey\"]):P=[\"toggleHover\"],u&&P.push(\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"),(lft(r)||L)&&(P=[]),u&&!S&&(g=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],T[0]!==\"resetViews\"&&(T=[\"resetScale2d\"])),c?z=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:u&&!S||v?z=[\"zoom2d\",\"pan2d\"]:_||b||f?z=[\"pan2d\"]:p&&(z=[\"zoom2d\"]),sft(r)&&z.push(\"select2d\",\"lasso2d\");var O=[],V=function(N){O.indexOf(N)===-1&&P.indexOf(N)!==-1&&O.push(N)};if(Array.isArray(s)){for(var G=[],Z=0;Z<s.length;Z++){var H=s[Z];typeof H==\"string\"?(H=H.toLowerCase(),ift.indexOf(H)!==-1?(t._has(\"mapbox\")||t._has(\"map\")||t._has(\"cartesian\"))&&z.push(H):H===\"togglespikelines\"?V(\"toggleSpikelines\"):H===\"togglehover\"?V(\"toggleHover\"):H===\"hovercompare\"?V(\"hoverCompareCartesian\"):H===\"hoverclosest\"?(V(\"hoverClosestCartesian\"),V(\"hoverClosestGeo\"),V(\"hoverClosest3d\"),V(\"hoverClosestPie\")):H===\"v1hovermode\"&&(V(\"hoverClosestCartesian\"),V(\"hoverCompareCartesian\"),V(\"hoverClosestGeo\"),V(\"hoverClosest3d\"),V(\"hoverClosestPie\"))):G.push(H)}s=G}return C(z),C(g.concat(T)),C(O),uft(x,s)}function oft(e){for(var t=eft.list({_fullLayout:e},null,!0),r=0;r<t.length;r++){var n=t[r].modebardisable;if(!t[r].fixedrange&&n!==\"autoscale+zoominout\"&&n!==\"zoominout+autoscale\")return!1}return!0}function sft(e){for(var t=!1,r=0;r<e.length&&!t;r++){var n=e[r];!n._module||!n._module.selectPoints||(uN.traceIs(n,\"scatter-like\")?(gce.hasMarkers(n)||gce.hasText(n))&&(t=!0):uN.traceIs(n,\"box-violin\")?(n.boxpoints===\"all\"||n.points===\"all\")&&(t=!0):t=!0)}return t}function lft(e){for(var t=0;t<e.length;t++)if(!uN.traceIs(e[t],\"noHover\"))return!1;return!0}function uft(e,t){if(t.length)if(Array.isArray(t[0]))for(var r=0;r<t.length;r++)e.push(t[r]);else e.push(t);return e}function cft(e){for(var t=nft([],e),r=0;r<t.length;r++)for(var n=t[r],i=0;i<n.length;i++){var a=n[i];if(typeof a==\"string\")if(fP[a]!==void 0)t[r][i]=fP[a];else throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"))}return t}});var cN=ye((Har,_ce)=>{\"use strict\";_ce.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:sN(),supplyLayoutDefaults:fce(),manage:yce()}});var fN=ye((jar,xce)=>{\"use strict\";var fft=$h().FROM_BL;xce.exports=function(t,r,n){n===void 0&&(n=fft[t.constraintoward||\"center\"]);var i=[t.r2l(t.range[0]),t.r2l(t.range[1])],a=i[0]+(i[1]-i[0])*n;t.range=t._input.range=[t.l2r(a+(i[0]-a)*r),t.l2r(a+(i[1]-a)*r)],t.setScale()}});var Nb=ye(yM=>{\"use strict\";var Bb=Dr(),hN=Tg(),Eg=hf().id2name,hft=Rd(),bce=fN(),dft=ym(),vft=fs().ALMOST_EQUAL,pft=$h().FROM_BL;yM.handleDefaults=function(e,t,r){var n=r.axIds,i=r.axHasImage,a=t._axisConstraintGroups=[],o=t._axisMatchGroups=[],s,l,u,c,f,h,d,v;for(s=0;s<n.length;s++)c=Eg(n[s]),f=e[c],h=t[c],gft(f,h,{axIds:n,layoutOut:t,hasImage:i[c]});function _(M,g){for(s=0;s<M.length;s++){l=M[s];for(u in l)t[Eg(u)][g]=l}}for(_(o,\"_matchGroup\"),s=0;s<a.length;s++){l=a[s];for(u in l)if(h=t[Eg(u)],h.fixedrange){for(var b in l){var p=Eg(b);(e[p]||{}).fixedrange===!1&&Bb.warn(\"fixedrange was specified as false for axis \"+p+\" but was overridden because another axis in its constraint group has fixedrange true\"),t[p].fixedrange=!0}break}}for(s=0;s<a.length;){l=a[s];for(u in l){h=t[Eg(u)],h._matchGroup&&Object.keys(h._matchGroup).length===Object.keys(l).length&&(a.splice(s,1),s--);break}s++}_(a,\"_constraintGroup\");var k=[\"constrain\",\"range\",\"autorange\",\"rangemode\",\"rangebreaks\",\"categoryorder\",\"categoryarray\"],E=!1,S=!1;function L(){v=h[d],d===\"rangebreaks\"&&(S=h._hasDayOfWeekBreaks)}for(s=0;s<o.length;s++){l=o[s];for(var x=0;x<k.length;x++){d=k[x],v=null;var C;for(u in l)if(c=Eg(u),f=e[c],h=t[c],d in h){if(!h.matches&&(C=h,d in f)){L();break}v===null&&d in f&&L()}if(d===\"range\"&&v&&f.range&&f.range.length===2&&f.range[0]!==null&&f.range[1]!==null&&(E=!0),d===\"autorange\"&&v===null&&E&&(v=!1),v===null&&d in C&&(v=C[d]),v!==null)for(u in l)h=t[Eg(u)],h[d]=d===\"range\"?v.slice():v,d===\"rangebreaks\"&&(h._hasDayOfWeekBreaks=S,dft(h,t))}}};function gft(e,t,r){var 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Fe=\"M0,0\";Ece(c,o)&&(oe=hP(c,\"bottom\",u,i),H=c._offset+c._length+(oe?n:0),_e=hP(c,\"top\",u,i),N=c._offset-(_e?n:0),j=f(c,u,\"left\"),re=f(c,u,\"right\"),Ee=!c._anchorAxis||o!==c._mainSubplot,Ee&&(c.mirror===\"allticks\"||c.mirror===\"all\")&&(c._linepositions[o]=[j,re]),Fe=Le(c,ie,Se),Ee&&c.showline&&(c.mirror===\"all\"||c.mirror===\"allticks\")&&(Fe+=ie(j)+ie(re)),s.ylines.style(\"stroke-width\",c._lw+\"px\").call(_M.stroke,c.showline?c.linecolor:\"rgba(0,0,0,0)\")),s.ylines.attr(\"d\",Fe)}return xM.makeClipPaths(e),Jp.previousPromises(e)}function Ece(e,t){return(e.ticks||e.showline)&&(t===e._mainSubplot||e.mirror===\"all\"||e.mirror===\"allticks\")}function kce(e,t,r){if(!r.showline||!r._lw)return!1;if(r.mirror===\"all\"||r.mirror===\"allticks\")return!0;var n=r._anchorAxis;if(!n)return!1;var i=Cy.FROM_BL[t];return r.side===t?n.domain[i]===e.domain[i]:r.mirror&&n.domain[1-i]===e.domain[1-i]}function hP(e,t,r,n){if(kce(e,t,r))return r._lw;for(var i=0;i<n.length;i++){var a=n[i];if(a._mainAxis===r._mainAxis&&kce(e,t,a))return a._lw}return 0}pd.drawMainTitle=function(e){var t=e._fullLayout.title,r=e._fullLayout,n=Lft(r),i=Pft(r),a=Cft(r,i),o=kft(r,n);if(Sce.draw(e,\"gtitle\",{propContainer:r,propName:\"title.text\",subtitlePropName:\"title.subtitle.text\",placeholder:r._dfltTitle.plot,subtitlePlaceholder:r._dfltTitle.subtitle,attributes:{x:o,y:a,\"text-anchor\":n,dy:i}}),t.text&&t.automargin){var s=dP.select(e).selectAll(\".gtitle\"),l=J3.bBox(dP.select(e).selectAll(\".g-gtitle\").node()).height,u=Mft(e,t,l);if(u>0){Eft(e,a,u,l),s.attr({x:o,y:a,\"text-anchor\":n,dy:Cce(t.yanchor)}).call(pN.positionText,o,a);var c=(t.text.match(pN.BR_TAG_ALL)||[]).length;if(c){var f=Cy.LINE_SPACING*c+Cy.MID_SHIFT;t.y===0&&(f=-f),s.selectAll(\".line\").each(function(){var b=+this.getAttribute(\"dy\").slice(0,-2)-f+\"em\";this.setAttribute(\"dy\",b)})}var h=dP.select(e).selectAll(\".gtitle-subtitle\");if(h.node()){var d=s.node().getBBox(),v=d.y+d.height,_=v+Sce.SUBTITLE_PADDING_EM*t.subtitle.font.size;h.attr({x:o,y:_,\"text-anchor\":n,dy:Cce(t.yanchor)}).call(pN.positionText,o,_)}}}};function Aft(e,t,r,n,i){var a=t.yref===\"paper\"?e._fullLayout._size.h:e._fullLayout.height,o=S0.isTopAnchor(t)?n:n-i,s=r===\"b\"?a-o:o;return S0.isTopAnchor(t)&&r===\"t\"||S0.isBottomAnchor(t)&&r===\"b\"?!1:s<i}function Sft(e,t,r,n,i){var a=0;return r===\"middle\"&&(a+=i/2),e===\"t\"?(r===\"top\"&&(a+=i),a+=n-t*n):(r===\"bottom\"&&(a+=i),a+=t*n),a}function Mft(e,t,r){var n=t.y,i=t.yanchor,a=n>.5?\"t\":\"b\",o=e._fullLayout.margin[a],s=0;return t.yref===\"paper\"?s=r+t.pad.t+t.pad.b:t.yref===\"container\"&&(s=Sft(a,n,i,e._fullLayout.height,r)+t.pad.t+t.pad.b),s>o?s:0}function Eft(e,t,r,n){var i=\"title.automargin\",a=e._fullLayout.title,o=a.y>.5?\"t\":\"b\",s={x:a.x,y:a.y,t:0,b:0},l={};a.yref===\"paper\"&&Aft(e,a,o,t,n)?s[o]=r:a.yref===\"container\"&&(l[o]=r,e._fullLayout._reservedMargin[i]=l),Jp.allowAutoMargin(e,i),Jp.autoMargin(e,i,s)}function kft(e,t){var r=e.title,n=e._size,i=0;switch(t===Ice?i=r.pad.l:t===Rce&&(i=-r.pad.r),r.xref){case\"paper\":return n.l+n.w*r.x+i;case\"container\":default:return e.width*r.x+i}}function Cft(e,t){var r=e.title,n=e._size,i=0;if(t===\"0em\"||!t?i=-r.pad.b:t===Cy.CAP_SHIFT+\"em\"&&(i=r.pad.t),r.y===\"auto\")return n.t/2;switch(r.yref){case\"paper\":return n.t+n.h-n.h*r.y+i;case\"container\":default:return e.height-e.height*r.y+i}}function Cce(e){return e===\"top\"?Cy.CAP_SHIFT+.3+\"em\":e===\"bottom\"?\"-0.3em\":Cy.MID_SHIFT+\"em\"}function Lft(e){var t=e.title,r=xft;return S0.isRightAnchor(t)?r=Rce:S0.isLeftAnchor(t)&&(r=Ice),r}function Pft(e){var t=e.title,r=\"0em\";return S0.isTopAnchor(t)?r=Cy.CAP_SHIFT+\"em\":S0.isMiddleAnchor(t)&&(r=Cy.MID_SHIFT+\"em\"),r}pd.doTraceStyle=function(e){var t=e.calcdata,r=[],n;for(n=0;n<t.length;n++){var i=t[n],a=i[0]||{},o=a.trace||{},s=o._module||{},l=s.arraysToCalcdata;l&&l(i,o);var u=s.editStyle;u&&r.push({fn:u,cd0:a})}if(r.length){for(n=0;n<r.length;n++){var c=r[n];c.fn(e,c.cd0)}gN(e),pd.redrawReglTraces(e)}return Jp.style(e),Nv.getComponentMethod(\"legend\",\"draw\")(e),Jp.previousPromises(e)};pd.doColorBars=function(e){return Nv.getComponentMethod(\"colorbar\",\"draw\")(e),Jp.previousPromises(e)};pd.layoutReplot=function(e){var t=e.layout;return e.layout=void 0,Nv.call(\"_doPlot\",e,\"\",t)};pd.doLegend=function(e){return Nv.getComponentMethod(\"legend\",\"draw\")(e),Jp.previousPromises(e)};pd.doTicksRelayout=function(e){return 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r=e._fullData,n=[],i=[],a,o;for(t._hasOnlyLargeSploms&&t._splomGrid.draw(),a=0;a<r.length;a++){var s=r[a];s.visible===!0&&s._length!==0&&(s.type===\"splom\"?t._splomScenes[s.uid].draw():s.type===\"scattergl\"?S0.pushUnique(n,s.xaxis+s.yaxis):s.type===\"scatterpolargl\"&&S0.pushUnique(i,s.subplot))}for(a=0;a<n.length;a++)o=t._plots[n[a]],o._scene&&o._scene.draw();for(a=0;a<i.length;a++)o=t[i[a]]._subplot,o._scene&&o._scene.draw()}};pd.doAutoRangeAndConstraints=function(e){for(var t=xM.list(e,\"\",!0),r,n={},i=0;i<t.length;i++)if(r=t[i],!n[r._id]){n[r._id]=1,_ft(e,r),Mce(e,r);var a=r._matchGroup;if(a)for(var o in a){var 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L=_[0],x=_[1];x.node().addEventListener(\"click\",function(){return Oft(e,L)})}}function zft(e,t,r){var n=r.xref+r.yref;Fce.setClipUrl(e,\"clip\"+t._fullLayout._uid+n,t)}function Oft(e,t){if(pP(e)){var r=t.node(),n=+r.getAttribute(\"data-index\");if(n>=0){if(n===e._fullLayout._activeSelectionIndex){yN(e);return}e._fullLayout._activeSelectionIndex=n,e._fullLayout._deactivateSelection=yN,vP(e)}}}function qft(e){if(pP(e)){var t=e._fullLayout.selections.length-1;e._fullLayout._activeSelectionIndex=t,e._fullLayout._deactivateSelection=yN,vP(e)}}function yN(e){if(pP(e)){var t=e._fullLayout._activeSelectionIndex;t>=0&&(Dce(e),delete e._fullLayout._activeSelectionIndex,vP(e))}}});var Nce=ye((Yar,Bce)=>{function Bft(){var e,t=0,r=!1;function n(i,a){return e.list.push({type:i,data:a?JSON.parse(JSON.stringify(a)):void 0}),e}return e={list:[],segmentId:function(){return t++},checkIntersection:function(i,a){return n(\"check\",{seg1:i,seg2:a})},segmentChop:function(i,a){return 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Hce=ye((Jar,Gce)=>{var Uft={create:function(){var e={root:{root:!0,next:null},exists:function(t){return!(t===null||t===e.root)},isEmpty:function(){return e.root.next===null},getHead:function(){return e.root.next},insertBefore:function(t,r){for(var n=e.root,i=e.root.next;i!==null;){if(r(i)){t.prev=i.prev,t.next=i,i.prev.next=t,i.prev=t;return}n=i,i=i.next}n.next=t,t.prev=n,t.next=null},findTransition:function(t){for(var r=e.root,n=e.root.next;n!==null&&!t(n);)r=n,n=n.next;return{before:r===e.root?null:r,after:n,insert:function(i){return i.prev=r,i.next=n,r.next=i,n!==null&&(n.prev=i),i}}}};return e},node:function(e){return e.prev=null,e.next=null,e.remove=function(){e.prev.next=e.next,e.next&&(e.next.prev=e.prev),e.prev=null,e.next=null},e}};Gce.exports=Uft});var Wce=ye(($ar,jce)=>{var wM=Hce();function Vft(e,t,r){function n(v,_){return{id:r?r.segmentId():-1,start:v,end:_,myFill:{above:null,below:null},otherFill:null}}function 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k=l.index,E=l.matches_pt1?s:o,S=l.matches_head,d=n[k],L=S?d[0]:d[d.length-1],x=S?d[1]:d[d.length-2],C=S?d[d.length-1]:d[0],M=S?d[d.length-2]:d[1];if(t.pointsCollinear(x,L,E)&&(S?(r&&r.chainRemoveHead(l.index,E),d.shift()):(r&&r.chainRemoveTail(l.index,E),d.pop()),L=x),t.pointsSame(C,E)){n.splice(k,1),t.pointsCollinear(M,C,L)&&(S?(r&&r.chainRemoveTail(l.index,L),d.pop()):(r&&r.chainRemoveHead(l.index,L),d.shift())),r&&r.chainClose(l.index),i.push(d);return}S?(r&&r.chainAddHead(l.index,E),d.unshift(E)):(r&&r.chainAddTail(l.index,E),d.push(E));return}function g(V){r&&r.chainReverse(V),n[V].reverse()}function P(V,G){var Z=n[V],H=n[G],N=Z[Z.length-1],j=Z[Z.length-2],re=H[0],oe=H[1];t.pointsCollinear(j,N,re)&&(r&&r.chainRemoveTail(V,N),Z.pop(),N=j),t.pointsCollinear(N,re,oe)&&(r&&r.chainRemoveHead(G,re),H.shift()),r&&r.chainJoin(V,G),n[V]=Z.concat(H),n.splice(G,1)}var T=l.index,z=u.index;r&&r.chainConnect(T,z);var O=n[T].length<n[z].length;l.matches_head?u.matches_head?O?(g(T),P(T,z)):(g(z),P(z,T)):P(z,T):u.matches_head?P(T,z):O?(g(T),P(z,T)):(g(z),P(T,z))}),i}Xce.exports=Gft});var Kce=ye((eor,Yce)=>{function TM(e,t,r){var n=[];return e.forEach(function(i){var a=(i.myFill.above?8:0)+(i.myFill.below?4:0)+(i.otherFill&&i.otherFill.above?2:0)+(i.otherFill&&i.otherFill.below?1:0);t[a]!==0&&n.push({id:r?r.segmentId():-1,start:i.start,end:i.end,myFill:{above:t[a]===1,below:t[a]===2},otherFill:null})}),r&&r.selected(n),n}var Hft={union:function(e,t){return TM(e,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],t)},intersect:function(e,t){return TM(e,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],t)},difference:function(e,t){return TM(e,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],t)},differenceRev:function(e,t){return TM(e,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],t)},xor:function(e,t){return TM(e,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],t)}};Yce.exports=Hft});var $ce=ye((tor,Jce)=>{var jft={toPolygon:function(e,t){function r(a){if(a.length<=0)return 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vt=ti._offset-xe/xt,ir=Br._offset-ke/Ie;Lr.clipRect.call(d_.setTranslate,xe,ke).call(d_.setScale,xt,Ie),Lr.plot.call(d_.setTranslate,vt,ir).call(d_.setScale,1/xt,1/Ie),(xt!==Lr.xScaleFactor||Ie!==Lr.yScaleFactor)&&(d_.setPointGroupScale(Lr.zoomScalePts,xt,Ie),d_.setTextPointsScale(Lr.zoomScaleTxt,xt,Ie)),d_.hideOutsideRangePoints(Lr.clipOnAxisFalseTraces,Lr),Lr.xScaleFactor=xt,Lr.yScaleFactor=Ie}}}}function Qt(It,mt,er){return It.fixedrange?0:P&&L.xaHash[It._id]?mt:T&&(L.isSubplotConstrained?L.xaHash:L.yaHash)[It._id]?er:0}function Vt(It,mt){return mt?(It.range=It._r.slice(),DN(It,mt),_t(It,mt)):0}function _t(It,mt,er){return It._length*(1-mt)*Kht[er||It.constraintoward||\"middle\"]}return re}function phe(e,t,r,n){var i=k0.ensureSingle(e.draglayer,t,r,function(a){a.classed(\"drag\",!0).style({fill:\"transparent\",\"stroke-width\":0}).attr(\"data-subplot\",e.id)});return i.call(Xht,n),i.node()}function ghe(e,t,r,n,i,a,o){var s=phe(e,\"rect\",t,r);return qN.select(s).call(d_.setRect,n,i,a,o),s}function uhe(e,t){for(var r=0;r<e.length;r++)if(!e[r].fixedrange)return t;return\"\"}function ndt(e,t){var r=e.range[t],n=Math.abs(r-e.range[1-t]),i;return e.type===\"date\"?r:e.type===\"log\"?(i=Math.ceil(Math.max(0,-Math.log(n)/Math.LN10))+3,nhe(\".\"+i+\"g\")(Math.pow(10,r))):(i=Math.floor(Math.log(Math.abs(r))/Math.LN10)-Math.floor(Math.log(n)/Math.LN10)+4,nhe(\".\"+String(i)+\"g\")(r))}function zN(e,t,r,n,i){for(var a=0;a<e.length;a++){var o=e[a];if(!o.fixedrange)if(o.rangebreaks){var s=o._id.charAt(0)===\"y\",l=s?1-t:t,u=s?1-r:r;n[o._name+\".range[0]\"]=o.l2r(o.p2l(l*o._length)),n[o._name+\".range[1]\"]=o.l2r(o.p2l(u*o._length))}else{var c=o._rl[0],f=o._rl[1]-c;n[o._name+\".range[0]\"]=o.l2r(c+f*t),n[o._name+\".range[1]\"]=o.l2r(c+f*r)}}if(i&&i.length){var h=(t+(1-r))/2;zN(i,h,1-h,n,[])}}function che(e,t){for(var r=0;r<e.length;r++){var n=e[r];if(!n.fixedrange){if(n.rangebreaks){var i=0,a=n._length,o=n.p2l(i+t)-n.p2l(i),s=n.p2l(a+t)-n.p2l(a),l=(o+s)/2;n.range=[n.l2r(n._rl[0]-l),n.l2r(n._rl[1]-l)]}else n.range=[n.l2r(n._rl[0]-t/n._m),n.l2r(n._rl[1]-t/n._m)];n.limitRange&&n.limitRange()}}}function adt(e){return 1-(e>=0?Math.min(e,.9):1/(1/Math.max(e,-.3)+3.222))}function odt(e,t,r){return e?e===\"nsew\"?r?\"\":t===\"pan\"?\"move\":\"crosshair\":e.toLowerCase()+\"-resize\":\"pointer\"}function mhe(e,t,r,n,i){return e.append(\"path\").attr(\"class\",\"zoombox\").style({fill:t>.2?\"rgba(0,0,0,0)\":\"rgba(255,255,255,0)\",\"stroke-width\":0}).attr(\"transform\",dhe(r,n)).attr(\"d\",i+\"Z\")}function yhe(e,t,r){return e.append(\"path\").attr(\"class\",\"zoombox-corners\").style({fill:ahe.background,stroke:ahe.defaultLine,\"stroke-width\":1,opacity:0}).attr(\"transform\",dhe(t,r)).attr(\"d\",\"M0,0Z\")}function _he(e,t,r,n,i,a){e.attr(\"d\",n+\"M\"+r.l+\",\"+r.t+\"v\"+r.h+\"h\"+r.w+\"v-\"+r.h+\"h-\"+r.w+\"Z\"),xhe(e,t,i,a)}function xhe(e,t,r,n){r||(e.transition().style(\"fill\",n>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),t.transition().style(\"opacity\",1).duration(200))}function ON(e){qN.select(e).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}function bhe(e){lhe&&e.data&&e._context.showTips&&(k0.notifier(k0._(e,\"Double-click to zoom back out\"),\"long\"),lhe=!1)}function sdt(e,t){return\"M\"+(e.l-.5)+\",\"+(t-np-.5)+\"h-3v\"+(2*np+1)+\"h3ZM\"+(e.r+.5)+\",\"+(t-np-.5)+\"h3v\"+(2*np+1)+\"h-3Z\"}function ldt(e,t){return\"M\"+(t-np-.5)+\",\"+(e.t-.5)+\"v-3h\"+(2*np+1)+\"v3ZM\"+(t-np-.5)+\",\"+(e.b+.5)+\"v3h\"+(2*np+1)+\"v-3Z\"}function kP(e){var t=Math.floor(Math.min(e.b-e.t,e.r-e.l,np)/2);return\"M\"+(e.l-3.5)+\",\"+(e.t-.5+t)+\"h3v\"+-t+\"h\"+t+\"v-3h-\"+(t+3)+\"ZM\"+(e.r+3.5)+\",\"+(e.t-.5+t)+\"h-3v\"+-t+\"h\"+-t+\"v-3h\"+(t+3)+\"ZM\"+(e.r+3.5)+\",\"+(e.b+.5-t)+\"h-3v\"+t+\"h\"+-t+\"v3h\"+(t+3)+\"ZM\"+(e.l-3.5)+\",\"+(e.b+.5-t)+\"h3v\"+t+\"h\"+t+\"v3h-\"+(t+3)+\"Z\"}function fhe(e,t,r,n,i){for(var a=!1,o={},s={},l,u,c,f,h=(i||{}).xaHash,d=(i||{}).yaHash,v=0;v<t.length;v++){var _=t[v];for(l in r)if(_[l]){for(c in _)!(i&&(h[c]||d[c]))&&!(c.charAt(0)===\"x\"?r:n)[c]&&(o[c]=l);for(u in n)!(i&&(h[u]||d[u]))&&_[u]&&(a=!0)}for(u in n)if(_[u])for(f in _)!(i&&(h[f]||d[f]))&&!(f.charAt(0)===\"x\"?r:n)[f]&&(s[f]=u)}a&&(k0.extendFlat(o,s),s={});var b={},p=[];for(c in o){var k=FN(e,c);p.push(k),b[k._id]=k}var E={},S=[];for(f in s){var L=FN(e,f);S.push(L),E[L._id]=L}return{xaHash:b,yaHash:E,xaxes:p,yaxes:S,xLinks:o,yLinks:s,isSubplotConstrained:a}}function whe(e,t){if(!Hht)e.onwheel!==void 0?e.onwheel=t:e.onmousewheel!==void 0?e.onmousewheel=t:e.isAddedWheelEvent||(e.isAddedWheelEvent=!0,e.addEventListener(\"wheel\",t,{passive:!1}));else{var r=e.onwheel!==void 0?\"wheel\":\"mousewheel\";e._onwheel&&e.removeEventListener(r,e._onwheel),e._onwheel=t,e.addEventListener(r,t,{passive:!1})}}function hhe(e){var t=[];for(var r in e)t.push(e[r]);return t}The.exports={makeDragBox:idt,makeDragger:phe,makeRectDragger:ghe,makeZoombox:mhe,makeCorners:yhe,updateZoombox:_he,xyCorners:kP,transitionZoombox:xhe,removeZoombox:ON,showDoubleClickNotifier:bhe,attachWheelEventHandler:whe}});var UN=ye(LP=>{\"use strict\";var udt=Oa(),CP=vf(),cdt=yv(),fdt=Ag(),Cg=NN().makeDragBox,gd=hd().DRAGGERSIZE;LP.initInteractions=function(t){var r=t._fullLayout;if(t._context.staticPlot){udt.select(t).selectAll(\".drag\").remove();return}if(!(!r._has(\"cartesian\")&&!r._has(\"splom\"))){var n=Object.keys(r._plots||{}).sort(function(a,o){if((r._plots[a].mainplot&&!0)===(r._plots[o].mainplot&&!0)){var s=a.split(\"y\"),l=o.split(\"y\");return 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c=s._mainLinePosition;s.side===\"top\"&&(c-=gd),Cg(t,o,s._offset+s._length*.1,c,s._length*.8,gd,\"\",\"ew\"),Cg(t,o,s._offset,c,s._length*.1,gd,\"\",\"w\"),Cg(t,o,s._offset+s._length*.9,c,s._length*.1,gd,\"\",\"e\")}if(a===l._mainSubplot){var f=l._mainLinePosition;l.side!==\"right\"&&(f-=gd),Cg(t,o,f,l._offset+l._length*.1,gd,l._length*.8,\"ns\",\"\"),Cg(t,o,f,l._offset+l._length*.9,gd,l._length*.1,\"s\",\"\"),Cg(t,o,f,l._offset,gd,l._length*.1,\"n\",\"\")}}});var i=r._hoverlayer.node();i.onmousemove=function(a){a.target=t._fullLayout._lasthover,CP.hover(t,a,r._hoversubplot)},i.onclick=function(a){a.target=t._fullLayout._lasthover,CP.click(t,a)},i.onmousedown=function(a){t._fullLayout._lasthover.onmousedown(a)},LP.updateFx(t)}};LP.updateFx=function(e){var t=e._fullLayout,r=t.dragmode===\"pan\"?\"move\":\"crosshair\";fdt(t._draggers,r)}});var Mhe=ye((Tor,She)=>{\"use strict\";var Ahe=qa();She.exports=function(t){for(var r=Ahe.layoutArrayContainers,n=Ahe.layoutArrayRegexes,i=t.split(\"[\")[0],a,o,s=0;s<n.length;s++)if(o=t.match(n[s]),o&&o.index===0){a=o[0];break}if(a||(a=r[r.indexOf(i)]),!a)return!1;var l=t.substr(a.length);return l?(o=l.match(/^\\[(0|[1-9][0-9]*)\\](\\.(.+))?$/),o?{array:a,index:Number(o[1]),property:o[3]||\"\"}:!1):{array:a,index:\"\",property:\"\"}}});var khe=ye(NM=>{\"use strict\";var hdt=my(),VN=w6(),BM=G1(),ddt=R6().sorterAsc,GN=qa();NM.containerArrayMatch=Mhe();var vdt=NM.isAddVal=function(t){return t===\"add\"||hdt(t)},Ehe=NM.isRemoveVal=function(t){return t===null||t===\"remove\"};NM.applyContainerArrayChanges=function(t,r,n,i,a){var o=r.astr,s=GN.getComponentMethod(o,\"supplyLayoutDefaults\"),l=GN.getComponentMethod(o,\"draw\"),u=GN.getComponentMethod(o,\"drawOne\"),c=i.replot||i.recalc||s===VN||l===VN,f=t.layout,h=t._fullLayout;if(n[\"\"]){Object.keys(n).length>1&&BM.warn(\"Full array edits are incompatible with other edits\",o);var d=n[\"\"][\"\"];if(Ehe(d))r.set(null);else if(Array.isArray(d))r.set(d);else return BM.warn(\"Unrecognized full array edit value\",o,d),!0;return c?!1:(s(f,h),l(t),!0)}var v=Object.keys(n).map(Number).sort(ddt),_=r.get(),b=_||[],p=a(h,o).get(),k=[],E=-1,S=b.length,L,x,C,M,g,P,T,z;for(L=0;L<v.length;L++){if(C=v[L],M=n[C],g=Object.keys(M),P=M[\"\"],T=vdt(P),C<0||C>b.length-(T?0:1)){BM.warn(\"index out of range\",o,C);continue}if(P!==void 0)g.length>1&&BM.warn(\"Insertion & removal are incompatible with edits to the same index.\",o,C),Ehe(P)?k.push(C):T?(P===\"add\"&&(P={}),b.splice(C,0,P),p&&p.splice(C,0,{})):BM.warn(\"Unrecognized full object edit value\",o,C,P),E===-1&&(E=C);else for(x=0;x<g.length;x++)z=o+\"[\"+C+\"].\",a(b[C],g[x],z).set(M[g[x]])}for(L=k.length-1;L>=0;L--)b.splice(k[L],1),p&&p.splice(k[L],1);if(b.length?_||r.set(b):r.set(null),c)return!1;if(s(f,h),u!==VN){var O;if(E===-1)O=v;else{for(S=Math.max(b.length,S),O=[],L=0;L<v.length&&(C=v[L],!(C>=E));L++)O.push(C);for(L=E;L<S;L++)O.push(L)}for(L=0;L<O.length;L++)u(t,O[L])}else l(t);return!0}});var zhe=ye(C0=>{\"use strict\";var Ihe=Eo(),Rhe=qa(),Uv=Dr(),UM=Mc(),Dhe=hf(),Fhe=ka(),VM=Dhe.cleanId,pdt=Dhe.getFromTrace,HN=Rhe.traceIs,gdt=[\"x\",\"y\",\"z\"];C0.clearPromiseQueue=function(e){Array.isArray(e._promises)&&e._promises.length>0&&Uv.log(\"Clearing previous rejected promises from queue.\"),e._promises=[]};C0.cleanLayout=function(e){var t,r;e||(e={}),e.xaxis1&&(e.xaxis||(e.xaxis=e.xaxis1),delete e.xaxis1),e.yaxis1&&(e.yaxis||(e.yaxis=e.yaxis1),delete e.yaxis1),e.scene1&&(e.scene||(e.scene=e.scene1),delete e.scene1);var n=(UM.subplotsRegistry.cartesian||{}).attrRegex,i=(UM.subplotsRegistry.polar||{}).attrRegex,a=(UM.subplotsRegistry.ternary||{}).attrRegex,o=(UM.subplotsRegistry.gl3d||{}).attrRegex,s=Object.keys(e);for(t=0;t<s.length;t++){var l=s[t];if(n&&n.test(l)){var u=e[l];u.anchor&&u.anchor!==\"free\"&&(u.anchor=VM(u.anchor)),u.overlaying&&(u.overlaying=VM(u.overlaying)),u.type||(u.isdate?u.type=\"date\":u.islog?u.type=\"log\":u.isdate===!1&&u.islog===!1&&(u.type=\"linear\")),(u.autorange===\"withzero\"||u.autorange===\"tozero\")&&(u.autorange=!0,u.rangemode=\"tozero\"),u.insiderange&&delete u.range,delete u.islog,delete u.isdate,delete u.categories,PP(u,\"domain\")&&delete u.domain}}var c=Array.isArray(e.annotations)?e.annotations.length:0;for(t=0;t<c;t++){var f=e.annotations[t];Uv.isPlainObject(f)&&($3(f,\"xref\"),$3(f,\"yref\"))}var h=Array.isArray(e.shapes)?e.shapes.length:0;for(t=0;t<h;t++){var d=e.shapes[t];Uv.isPlainObject(d)&&($3(d,\"xref\"),$3(d,\"yref\"))}var v=Array.isArray(e.images)?e.images.length:0;for(t=0;t<v;t++){var _=e.images[t];Uv.isPlainObject(_)&&($3(_,\"xref\"),$3(_,\"yref\"))}var b=e.legend;return b&&(b.x>3?(b.x=1.02,b.xanchor=\"left\"):b.x<-2&&(b.x=-.02,b.xanchor=\"right\"),b.y>3?(b.y=1.02,b.yanchor=\"bottom\"):b.y<-2&&(b.y=-.02,b.yanchor=\"top\")),e.dragmode===\"rotate\"&&(e.dragmode=\"orbit\"),Fhe.clean(e),e.template&&e.template.layout&&C0.cleanLayout(e.template.layout),e};function $3(e,t){var r=e[t],n=t.charAt(0);r&&r!==\"paper\"&&(e[t]=VM(r,n,!0))}C0.cleanData=function(e){for(var t=0;t<e.length;t++){var r=e[t],n;if(r.type===\"histogramy\"&&\"xbins\"in r&&!(\"ybins\"in r)&&(r.ybins=r.xbins,delete r.xbins),r.type===\"histogramy\"&&C0.swapXYData(r),(r.type===\"histogramx\"||r.type===\"histogramy\")&&(r.type=\"histogram\"),\"scl\"in r&&!(\"colorscale\"in r)&&(r.colorscale=r.scl,delete r.scl),\"reversescl\"in r&&!(\"reversescale\"in r)&&(r.reversescale=r.reversescl,delete 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o=[Qo.previousPromises];a.layoutReplot?o.push(Au.layoutReplot):Object.keys(n).length&&($he(e,a,i)||Qo.supplyDefaults(e),a.legend&&o.push(Au.doLegend),a.layoutstyle&&o.push(Au.layoutStyles),a.axrange&&VP(o,i.rangesAltered),a.ticks&&o.push(Au.doTicksRelayout),a.modebar&&o.push(Au.doModeBar),a.camera&&o.push(Au.doCamera),a.colorbars&&o.push(Au.doColorBars),o.push(HM)),o.push(Qo.rehover,Qo.redrag,Qo.reselect),ap.add(e,GM,[e,i.undoit],GM,[e,i.redoit]);var s=Sa.syncOrAsync(o,e);return(!s||!s.then)&&(s=Promise.resolve(e)),s.then(function(){return e.emit(\"plotly_relayout\",i.eventData),e})}function $he(e,t,r){var n=e._fullLayout;if(!t.axrange)return!1;for(var i in t)if(i!==\"axrange\"&&t[i])return!1;var a,o,s=function(d,v){return Sa.coerce(a,o,wdt,d,v)},l={};for(var u in r.rangesAltered){var c=Vv.id2name(u);if(a=e.layout[c],o=n[c],bdt(a,o,s,l),o._matchGroup){for(var f in o._matchGroup)if(f!==u){var 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Ce=L.range[0],me=L.range[1];_e?(Ce<=0&&me<=0&&E(V+\".autorange\",!0),Ce<=0?Ce=me/1e6:me<=0&&(me=Ce/1e6),E(V+\".range[0]\",Math.log(Ce)/Math.LN10),E(V+\".range[1]\",Math.log(me)/Math.LN10)):(E(V+\".range[0]\",Math.pow(10,Ce)),E(V+\".range[1]\",Math.pow(10,me)))}Array.isArray(n._subplots.polar)&&n._subplots.polar.length&&n[M.parts[0]]&&M.parts[1]===\"radialaxis\"&&delete n[M.parts[0]]._subplot.viewInitial[\"radialaxis.range\"],L0.getComponentMethod(\"annotations\",\"convertCoords\")(e,Z,g,E),L0.getComponentMethod(\"images\",\"convertCoords\")(e,Z,g,E)}else E(V+\".autorange\",!0),E(V+\".range\",null);Ec(n,V+\"._inputRange\").set(null)}else if(z.match(Edt)){var ie=Ec(n,C).get(),Se=(g||{}).type;(!Se||Se===\"-\")&&(Se=\"linear\"),L0.getComponentMethod(\"annotations\",\"convertCoords\")(e,ie,Se,E),L0.getComponentMethod(\"images\",\"convertCoords\")(e,ie,Se,E)}var Le=IP.containerArrayMatch(C);if(Le){c=Le.array,f=Le.index;var Ae=Le.property,Fe=N||{editType:\"calc\"};f!==\"\"&&Ae===\"\"&&(IP.isAddVal(g)?k[C]=null:IP.isRemoveVal(g)?k[C]=(Ec(r,c).get()||[])[f]:Sa.warn(\"unrecognized full object value\",t)),v_.update(b,Fe),u[c]||(u[c]={});var Pe=u[c][f];Pe||(Pe=u[c][f]={}),Pe[Ae]=g,delete t[C]}else z===\"reverse\"?(G.range?G.range.reverse():(E(V+\".autorange\",!0),G.range=[1,0]),Z.autorange?b.calc=!0:b.plot=!0):(C===\"dragmode\"&&(g===!1&&H!==!1||g!==!1&&H===!1)||n._has(\"scatter-like\")&&n._has(\"regl\")&&C===\"dragmode\"&&(g===\"lasso\"||g===\"select\")&&!(H===\"lasso\"||H===\"select\")?b.plot=!0:N?v_.update(b,N):b.calc=!0,M.set(g))}}for(c in u){var ge=IP.applyContainerArrayChanges(e,a(r,c),u[c],b,a);ge||(b.plot=!0)}for(var Re in S){L=Vv.getFromId(e,Re);var ce=L&&L._constraintGroup;if(ce){b.calc=!0;for(var Ze in ce)S[Ze]||(Vv.getFromId(e,Ze)._constraintShrinkable=!0)}}(rde(e)||t.height||t.width)&&(b.plot=!0);var ut=n.shapes;for(f=0;f<ut.length;f++)if(ut[f].showlegend){b.calc=!0;break}return(b.plot||b.calc)&&(b.layoutReplot=!0),{flags:b,rangesAltered:S,undoit:k,redoit:p,eventData:l}}function rde(e){var t=e._fullLayout,r=t.width,n=t.height;return e.layout.autosize&&Qo.plotAutoSize(e,e.layout,t),t.width!==r||t.height!==n}function BP(e,t,r,n){e=Sa.getGraphDiv(e),vh.clearPromiseQueue(e),Sa.isPlainObject(t)||(t={}),Sa.isPlainObject(r)||(r={}),Object.keys(t).length&&(e.changed=!0),Object.keys(r).length&&(e.changed=!0);var i=vh.coerceTraceIndices(e,n),a=Jhe(e,Sa.extendFlat({},t),i),o=a.flags,s=tde(e,Sa.extendFlat({},r)),l=s.flags;(o.calc||l.calc)&&(e.calcdata=void 0),o.clearAxisTypes&&vh.clearAxisTypes(e,i,r);var u=[];l.layoutReplot?u.push(Au.layoutReplot):o.fullReplot?u.push(_l._doPlot):(u.push(Qo.previousPromises),$he(e,l,s)||Qo.supplyDefaults(e),o.style&&u.push(Au.doTraceStyle),(o.colorbars||l.colorbars)&&u.push(Au.doColorBars),l.legend&&u.push(Au.doLegend),l.layoutstyle&&u.push(Au.layoutStyles),l.axrange&&VP(u,s.rangesAltered),l.ticks&&u.push(Au.doTicksRelayout),l.modebar&&u.push(Au.doModeBar),l.camera&&u.push(Au.doCamera),u.push(HM)),u.push(Qo.rehover,Qo.redrag,Qo.reselect),ap.add(e,BP,[e,a.undoit,s.undoit,a.traces],BP,[e,a.redoit,s.redoit,a.traces]);var c=Sa.syncOrAsync(u,e);return(!c||!c.then)&&(c=Promise.resolve(e)),c.then(function(){return e.emit(\"plotly_update\",{data:a.eventData,layout:s.eventData}),e})}function KN(e){return function(r){r._fullLayout._guiEditing=!0;var n=e.apply(null,arguments);return r._fullLayout._guiEditing=!1,n}}var qdt=[{pattern:/^hiddenlabels/,attr:\"legend.uirevision\"},{pattern:/^((x|y)axis\\d*)\\.((auto)?range|title\\.text)/},{pattern:/axis\\d*\\.showspikes$/,attr:\"modebar.uirevision\"},{pattern:/(hover|drag)mode$/,attr:\"modebar.uirevision\"},{pattern:/^(scene\\d*)\\.camera/},{pattern:/^(geo\\d*)\\.(projection|center|fitbounds)/},{pattern:/^(ternary\\d*\\.[abc]axis)\\.(min|title\\.text)$/},{pattern:/^(polar\\d*\\.radialaxis)\\.((auto)?range|angle|title\\.text)/},{pattern:/^(polar\\d*\\.angularaxis)\\.rotation/},{pattern:/^(mapbox\\d*)\\.(center|zoom|bearing|pitch)/},{pattern:/^(map\\d*)\\.(center|zoom|bearing|pitch)/},{pattern:/^legend\\.(x|y)$/,attr:\"editrevision\"},{pattern:/^(shapes|annotations)/,attr:\"editrevision\"},{pattern:/^title\\.text$/,attr:\"editrevision\"}],Bdt=[{pattern:/^selectedpoints$/,attr:\"selectionrevision\"},{pattern:/(^|value\\.)visible$/,attr:\"legend.uirevision\"},{pattern:/^dimensions\\[\\d+\\]\\.constraintrange/},{pattern:/^node\\.(x|y|groups)/},{pattern:/^level$/},{pattern:/(^|value\\.)name$/},{pattern:/colorbar\\.title\\.text$/},{pattern:/colorbar\\.(x|y)$/,attr:\"editrevision\"}];function qhe(e,t){for(var r=0;r<t.length;r++){var n=t[r],i=e.match(n.pattern);if(i){var a=i[1]||\"\";return{head:a,tail:e.substr(a.length+1),attr:n.attr}}}}function Bhe(e,t){var r=Ec(t,e).get();if(r!==void 0)return r;var n=e.split(\".\");for(n.pop();n.length>1;)if(n.pop(),r=Ec(t,n.join(\".\")+\".uirevision\").get(),r!==void 0)return r;return t.uirevision}function Ndt(e,t){for(var r=0;r<t.length;r++)if(t[r]._fullInput.uid===e)return r;return-1}function Udt(e,t,r){for(var n=0;n<t.length;n++)if(t[n].uid===e)return n;return!t[r]||t[r].uid?-1:r}function Nhe(e,t){var r=Sa.isPlainObject(e),n=Array.isArray(e);return r||n?(r&&Sa.isPlainObject(t)||n&&Array.isArray(t))&&JSON.stringify(e)===JSON.stringify(t):e===t}function Vdt(e,t,r,n){var i=n._preGUI,a,o,s,l,u,c,f,h,d,v,_=[],b={},p={};for(a in i){if(u=qhe(a,qdt),u){if(d=u.head,v=u.tail,o=u.attr||d+\".uirevision\",s=Ec(n,o).get(),l=s&&Bhe(o,t),l&&l===s){if(c=i[a],c===null&&(c=void 0),f=Ec(t,a),h=f.get(),Nhe(h,c)){h===void 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The template has \"+e.templateCount+\" traces, the data only has \"+e.dataCount+\" of this type.\":t=\"The template has \"+e.templateCount+\" traces of type \"+e.traceType+\" but there are none in the data.\";break;case\"reused\":t=\"Some of the templates of type \"+e.traceType+\" were used more than once. 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s=Ovt.isBubble(t),l=(t.line||{}).color,u;if(o=o||{},l&&(n=l),a(\"marker.symbol\"),a(\"marker.opacity\",s?.7:1),a(\"marker.size\"),o.noAngle||(a(\"marker.angle\"),o.noAngleRef||a(\"marker.angleref\"),o.noStandOff||a(\"marker.standoff\")),a(\"marker.color\",n),Pde(t,\"marker\")&&Ide(t,r,i,a,{prefix:\"marker.\",cLetter:\"c\"}),o.noSelect||(a(\"selected.marker.color\"),a(\"unselected.marker.color\"),a(\"selected.marker.size\"),a(\"unselected.marker.size\")),o.noLine||(l&&!Array.isArray(l)&&r.marker.color!==l?u=l:s?u=Lde.background:u=Lde.defaultLine,a(\"marker.line.color\",u),Pde(t,\"marker.line\")&&Ide(t,r,i,a,{prefix:\"marker.line.\",cLetter:\"c\"}),a(\"marker.line.width\",s?1:0)),s&&(a(\"marker.sizeref\"),a(\"marker.sizemin\"),a(\"marker.sizemode\")),o.gradient){var c=a(\"marker.gradient.type\");c!==\"none\"&&a(\"marker.gradient.color\")}}});var R0=ye((Gor,Dde)=>{\"use strict\";var qvt=Dr().isArrayOrTypedArray,Bvt=pv().hasColorscale,Nvt=Qh();Dde.exports=function(t,r,n,i,a,o){o||(o={});var s=(t.marker||{}).color;if(s&&s._inputArray&&(s=s._inputArray),a(\"line.color\",n),Bvt(t,\"line\"))Nvt(t,r,i,a,{prefix:\"line.\",cLetter:\"c\"});else{var l=(qvt(s)?!1:s)||n;a(\"line.color\",l)}a(\"line.width\"),o.noDash||a(\"line.dash\"),o.backoff&&a(\"line.backoff\")}});var eT=ye((Hor,Fde)=>{\"use strict\";Fde.exports=function(t,r,n){var i=n(\"line.shape\");i===\"spline\"&&n(\"line.smoothing\")}});var D0=ye((jor,zde)=>{\"use strict\";var Uvt=Dr();zde.exports=function(e,t,r,n,i){i=i||{},n(\"textposition\"),Uvt.coerceFont(n,\"textfont\",i.font||r.font,i),i.noSelect||(n(\"selected.textfont.color\"),n(\"unselected.textfont.color\"))}});var Ig=ye((Wor,qde)=>{\"use strict\";var KP=ka(),Ode=Dr().isArrayOrTypedArray;function Vvt(e){for(var t=KP.interpolate(e[0][1],e[1][1],.5),r=2;r<e.length;r++){var n=KP.interpolate(e[r-1][1],e[r][1],.5);t=KP.interpolate(t,n,e[r-1][0]/e[r][0])}return t}qde.exports=function(t,r,n,i,a){a||(a={});var o=!1;if(r.marker){var s=r.marker.color,l=(r.marker.line||{}).color;s&&!Ode(s)?o=s:l&&!Ode(l)&&(o=l)}var u;if(a.moduleHasFillgradient){var c=i(\"fillgradient.type\");if(c!==\"none\"){i(\"fillgradient.start\"),i(\"fillgradient.stop\");var f=i(\"fillgradient.colorscale\");f&&(u=Vvt(f))}}i(\"fillcolor\",KP.addOpacity((r.line||{}).color||o||u||n,.5))}});var Vde=ye((Xor,Ude)=>{\"use strict\";var Bde=Dr(),Gvt=qa(),Hvt=pf(),jvt=Sm(),tT=Ru(),Wvt=Q3(),Xvt=Pg(),Zvt=Cde(),Yvt=$p(),Kvt=R0(),Nde=eT(),Jvt=D0(),$vt=Ig(),Qvt=Dr().coercePattern;Ude.exports=function(t,r,n,i){function a(d,v){return Bde.coerce(t,r,Hvt,d,v)}var o=Wvt(t,r,i,a);if(o||(r.visible=!1),!!r.visible){Xvt(t,r,i,a),a(\"xhoverformat\"),a(\"yhoverformat\"),a(\"zorder\");var s=Zvt(t,r,i,a);i.scattermode===\"group\"&&r.orientation===void 0&&a(\"orientation\",\"v\");var l=!s&&o<jvt.PTS_LINESONLY?\"lines+markers\":\"lines\";a(\"text\"),a(\"hovertext\"),a(\"mode\",l),tT.hasMarkers(r)&&Yvt(t,r,n,i,a,{gradient:!0}),tT.hasLines(r)&&(Kvt(t,r,n,i,a,{backoff:!0}),Nde(t,r,a),a(\"connectgaps\"),a(\"line.simplify\")),tT.hasText(r)&&(a(\"texttemplate\"),a(\"texttemplatefallback\"),Jvt(t,r,i,a));var u=[];(tT.hasMarkers(r)||tT.hasText(r))&&(a(\"cliponaxis\"),a(\"marker.maxdisplayed\"),u.push(\"points\")),a(\"fill\",s?s.fillDflt:\"none\"),r.fill!==\"none\"&&($vt(t,r,n,a,{moduleHasFillgradient:!0}),tT.hasLines(r)||Nde(t,r,a),Qvt(a,\"fillpattern\",r.fillcolor,!1));var c=(r.line||{}).color,f=(r.marker||{}).color;(r.fill===\"tonext\"||r.fill===\"toself\")&&u.push(\"fills\"),a(\"hoveron\",u.join(\"+\")||\"points\"),r.hoveron!==\"fills\"&&(a(\"hovertemplate\"),a(\"hovertemplatefallback\"));var h=Gvt.getComponentMethod(\"errorbars\",\"supplyDefaults\");h(t,r,c||f||n,{axis:\"y\"}),h(t,r,c||f||n,{axis:\"x\",inherit:\"y\"}),Bde.coerceSelectionMarkerOpacity(r,a)}}});var Hb=ye((Zor,Gde)=>{\"use strict\";var ept=Nb().getAxisGroup;Gde.exports=function(t,r,n,i,a){var o=r.orientation,s=r[{v:\"x\",h:\"y\"}[o]+\"axis\"],l=ept(n,s)+o,u=n._alignmentOpts||{},c=i(\"alignmentgroup\"),f=u[l];f||(f=u[l]={});var h=f[c];h?h.traces.push(r):h=f[c]={traces:[r],alignmentIndex:Object.keys(f).length,offsetGroups:{}};var d=i(\"offsetgroup\")||\"\",v=h.offsetGroups,_=v[d];r._offsetIndex=0,(a!==\"group\"||d)&&(_||(_=v[d]={offsetIndex:Object.keys(v).length}),r._offsetIndex=_.offsetIndex)}});var aU=ye((Yor,Hde)=>{\"use strict\";var tpt=Dr(),rpt=Hb(),ipt=pf();Hde.exports=function(t,r){var n,i,a,o=r.scattermode;function s(h){return tpt.coerce(i._input,i,ipt,h)}if(r.scattermode===\"group\")for(a=0;a<t.length;a++)i=t[a],i.type===\"scatter\"&&(n=i._input,rpt(n,i,r,s,o));for(a=0;a<t.length;a++){var l=t[a];if(l.type===\"scatter\"){var u=l.fill;if(!(u===\"none\"||u===\"toself\")&&(l.opacity=void 0,u===\"tonexty\"||u===\"tonextx\"))for(var c=a-1;c>=0;c--){var f=t[c];if(f.type===\"scatter\"&&f.xaxis===l.xaxis&&f.yaxis===l.yaxis){f.opacity=void 0;break}}}}}});var Wde=ye((Kor,jde)=>{\"use strict\";var npt=Dr(),apt=X6();jde.exports=function(e,t){function r(i,a){return npt.coerce(e,t,apt,i,a)}var n=t.barmode===\"group\";t.scattermode===\"group\"&&r(\"scattergap\",n?t.bargap:.2)}});var Rg=ye((Jor,Zde)=>{\"use strict\";var opt=Eo(),Xde=Dr(),spt=Xde.dateTime2ms,JP=Xde.incrementMonth,lpt=fs(),upt=lpt.ONEAVGMONTH;Zde.exports=function(t,r,n,i){if(r.type!==\"date\")return{vals:i};var a=t[n+\"periodalignment\"];if(!a)return{vals:i};var o=t[n+\"period\"],s;if(opt(o)){if(o=+o,o<=0)return{vals:i}}else if(typeof o==\"string\"&&o.charAt(0)===\"M\"){var l=+o.substring(1);if(l>0&&Math.round(l)===l)s=l;else return{vals:i}}for(var u=r.calendar,c=a===\"start\",f=a===\"end\",h=t[n+\"period0\"],d=spt(h,u)||0,v=[],_=[],b=[],p=i.length,k=0;k<p;k++){var E=i[k],S,L,x;if(s){for(S=Math.round((E-d)/(s*upt)),x=JP(d,s*S,u);x>E;)x=JP(x,-s,u);for(;x<=E;)x=JP(x,s,u);L=JP(x,-s,u)}else{for(S=Math.round((E-d)/o),x=d+S*o;x>E;)x-=o;for(;x<=E;)x+=o;L=x-o}v[k]=c?L:f?x:(L+x)/2,_[k]=L,b[k]=x}return{vals:v,starts:_,ends:b}}});var F0=ye(($or,Kde)=>{\"use strict\";var oU=pv().hasColorscale,sU=gv(),Yde=Ru();Kde.exports=function(t,r){Yde.hasLines(r)&&oU(r,\"line\")&&sU(t,r,{vals:r.line.color,containerStr:\"line\",cLetter:\"c\"}),Yde.hasMarkers(r)&&(oU(r,\"marker\")&&sU(t,r,{vals:r.marker.color,containerStr:\"marker\",cLetter:\"c\"}),oU(r,\"marker.line\")&&sU(t,r,{vals:r.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}});var km=ye((Qor,Jde)=>{\"use strict\";var Yf=Dr();Jde.exports=function(t,r){for(var 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b=s<2||i[0]!==i[s-1]||a[0]!==a[s-1];b&&(d===\"tozerox\"||d===\"tonextx\"&&(f||h===\"h\"))?v.tozero=!0:!(t.error_y||{}).visible&&(d===\"tonexty\"||d===\"tozeroy\"||!cU.hasMarkers(t)&&!cU.hasText(t))&&(v.padded=!1,v.ppad=0),b&&(d===\"tozeroy\"||d===\"tonexty\"&&(f||h===\"v\"))?_.tozero=!0:(d===\"tonextx\"||d===\"tozerox\")&&(_.padded=!1),u&&(t._extremes[u]=YM.findExtremes(r,i,v)),c&&(t._extremes[c]=YM.findExtremes(n,a,_))}function ive(e,t){if(cU.hasMarkers(e)){var r=e.marker,n=1.6*(e.marker.sizeref||1),i;if(e.marker.sizemode===\"area\"?i=function(u){return Math.max(Math.sqrt((u||0)/n),3)}:i=function(u){return Math.max((u||0)/n,3)},uU.isArrayOrTypedArray(r.size)){var a={type:\"linear\"};YM.setConvert(a);for(var o=a.makeCalcdata(e.marker,\"size\"),s=new Array(t),l=0;l<t;l++)s[l]=i(o[l]);return s}else return i(r.size)}}function nve(e,t){var r=ave(t),n=e._firstScatter;n[r]||(n[r]=t.uid)}function ave(e){var t=e.stackgroup;return e.xaxis+e.yaxis+e.type+(t?\"-\"+t:\"\")}function fU(e,t,r,n){var i=e.stackgroup;if(i){var a=t._scatterStackOpts[r._id+n._id][i],o=a.orientation===\"v\"?n:r;if(o.type===\"linear\"||o.type===\"log\")return a}}ove.exports={calc:dpt,calcMarkerSize:ive,calcAxisExpansion:rve,setFirstScatter:nve,getStackOpts:fU}});var lve=ye((rsr,sve)=>{\"use strict\";sve.exports=$P;var vpt=Dr().distinctVals;function $P(e,t){this.traces=e,this.sepNegVal=t.sepNegVal,this.overlapNoMerge=t.overlapNoMerge;for(var r=1/0,n=t.posAxis._id.charAt(0),i=[],a=0;a<e.length;a++){for(var o=e[a],s=0;s<o.length;s++){var l=o[s],u=l.p;u===void 0&&(u=l[n]),u!==void 0&&i.push(u)}o[0]&&o[0].width1&&(r=Math.min(o[0].width1,r))}this.positions=i;var c=vpt(i);this.distinctPositions=c.vals,c.vals.length===1&&r!==1/0?this.minDiff=r:this.minDiff=Math.min(c.minDiff,r);var f=(t.posAxis||{}).type;(f===\"category\"||f===\"multicategory\")&&(this.minDiff=1),this.binWidth=this.minDiff,this.bins={}}$P.prototype.put=function(t,r,n){var i=this.getLabel(t,r,n),a=this.bins[i]||0;return this.bins[i]=a+n,a};$P.prototype.get=function(t,r,n){var i=this.getLabel(t,r,n);return this.bins[i]||0};$P.prototype.getLabel=function(t,r,n){var i=n<0&&this.sepNegVal?\"v\":\"^\",a=this.overlapNoMerge?t:Math.round(t/this.binWidth);return i+a+\"g\"+r}});var jb=ye((isr,hve)=>{\"use strict\";var q0=Eo(),p_=Dr().isArrayOrTypedArray,rT=fs().BADNUM,ppt=qa(),KM=ho(),gpt=Nb().getAxisGroup,QP=lve();function mpt(e,t){for(var r=t.xaxis,n=t.yaxis,i=e._fullLayout,a=e._fullData,o=e.calcdata,s=[],l=[],u=0;u<a.length;u++){var c=a[u];if(c.visible===!0&&ppt.traceIs(c,\"bar\")&&c.xaxis===r._id&&c.yaxis===n._id&&(c.orientation===\"h\"?s.push(o[u]):l.push(o[u]),c._computePh))for(var f=e.calcdata[u],h=0;h<f.length;h++)typeof f[h].ph0==\"function\"&&(f[h].ph0=f[h].ph0()),typeof f[h].ph1==\"function\"&&(f[h].ph1=f[h].ph1())}var d={xCat:r.type===\"category\"||r.type===\"multicategory\",yCat:n.type===\"category\"||n.type===\"multicategory\",mode:i.barmode,norm:i.barnorm,gap:i.bargap,groupgap:i.bargroupgap};dU(e,r,n,l,d),dU(e,n,r,s,d)}function dU(e,t,r,n,i){if(n.length){var a,o,s,l,u;switch(xpt(r,n),i.mode){case\"overlay\":hU(e,t,r,n,i);break;case\"group\":for(a=[],o=[],s=0;s<n.length;s++)l=n[s],u=l[0].trace,u.offset===void 0?o.push(l):a.push(l);o.length&&bpt(e,t,r,o,i),a.length&&hU(e,t,r,a,i);break;case\"stack\":case\"relative\":for(a=[],o=[],s=0;s<n.length;s++)l=n[s],u=l[0].trace,u.base===void 0?o.push(l):a.push(l);_pt(o),o.length&&wpt(e,t,r,o,i),a.length&&hU(e,t,r,a,i);break}ypt(n),kpt(n,t)}}function ypt(e){var t,r,n,i,a,o,s;for(t=0;t<e.length;t++)r=e[t],n=r[0].trace,i=r[0].t,i.cornerradiusvalue===void 0&&(a=n.marker?n.marker.cornerradius:void 0,a!==void 0&&(o=q0(a)?+a:+a.slice(0,-1),s=q0(a)?\"px\":\"%\",i.cornerradiusvalue=o,i.cornerradiusform=s))}function _pt(e){if(!(e.length<2)){var t,r,n,i,a,o,s;for(t=0;t<e.length&&(r=e[t],n=r[0].trace,a=n.marker?n.marker.cornerradius:void 0,a===void 0);t++);if(a!==void 0)for(o=q0(a)?+a:+a.slice(0,-1),s=q0(a)?\"px\":\"%\",t=0;t<e.length;t++)r=e[t],i=r[0].t,i.cornerradiusvalue=o,i.cornerradiusform=s}}function xpt(e,t){var r,n;for(r=0;r<t.length;r++){var i=t[r],a=i[0].trace,o=a.type===\"funnel\"?a._base:a.base,s,l=a.orientation===\"h\"?a.xcalendar:a.ycalendar,u=e.type===\"category\"||e.type===\"multicategory\"?function(){return null}:e.d2c;if(p_(o)){for(n=0;n<Math.min(o.length,i.length);n++)s=u(o[n],0,l),q0(s)?(i[n].b=+s,i[n].hasB=1):i[n].b=0;for(;n<i.length;n++)i[n].b=0}else{s=u(o,0,l);var c=q0(s);for(s=c?s:0,n=0;n<i.length;n++)i[n].b=s,c&&(i[n].hasB=1)}}}function hU(e,t,r,n,i){for(var a=0;a<n.length;a++){var o=n[a],s=new QP([o],{posAxis:t,sepNegVal:!1,overlapNoMerge:!i.norm});vU(e,t,s,i),i.norm?(fve(s),pU(r,s,i)):cve(r,s)}}function bpt(e,t,r,n,i){var a=new QP(n,{posAxis:t,sepNegVal:!1,overlapNoMerge:!i.norm});vU(e,t,a,i),Mpt(a,t),i.norm?(fve(a),pU(r,a,i)):cve(r,a)}function wpt(e,t,r,n,i){var a=new QP(n,{posAxis:t,sepNegVal:i.mode===\"relative\",overlapNoMerge:!(i.norm||i.mode===\"stack\"||i.mode===\"relative\")});vU(e,t,a,i),Spt(r,a,i);for(var o=0;o<n.length;o++)for(var s=n[o],l=s[0].t.offsetindex,u=0;u<s.length;u++){var c=s[u];if(c.s!==rT){var f=c.b+c.s===a.get(c.p,l,c.s);f&&(c._outmost=!0)}}i.norm&&pU(r,a,i)}function vU(e,t,r,n){var i=e._fullLayout,a=r.positions,o=r.distinctPositions,s=r.minDiff,l=r.traces,u=l.length,c=a.length!==o.length,f=s*(1-n.gap),h,d,v,_;if(t._id===\"angularaxis\")h=f,d=h*(1-(n.groupgap||0)),v=-d/2;else{var b=gpt(i,t._id)+l[0][0].trace.orientation;_=i._alignmentOpts[b]||{}}for(var p=0;p<u;p++){var k=l[p],E=k[0].trace;if(t._id!==\"angularaxis\"){var S=_[E.alignmentgroup]||{},L=Object.keys(S.offsetGroups||{}).length;L?h=f/L:h=c?f/u:f,d=h*(1-(n.groupgap||0)),L?v=((2*E._offsetIndex+1-L)*h-d)/2:v=c?((2*p+1-u)*h-d)/2:-d/2}var x=k[0].t;x.barwidth=d,x.offsetindex=E._offsetIndex||0,x.poffset=v,x.bargroupwidth=f,x.bardelta=s}r.binWidth=l[0][0].t.barwidth/100,Tpt(r),Apt(t,r),t._id===\"angularaxis\"?uve(t,r):uve(t,r,c)}function Tpt(e){var t=e.traces,r,n;for(r=0;r<t.length;r++){var i=t[r],a=i[0],o=a.trace,s=a.t,l=o._offset||o.offset,u=s.poffset,c;if(p_(l)){for(c=Array.prototype.slice.call(l,0,i.length),n=0;n<c.length;n++)q0(c[n])||(c[n]=u);for(n=c.length;n<i.length;n++)c.push(u);s.poffset=c}else l!==void 0&&(s.poffset=l);var f=o._width||o.width,h=s.barwidth;if(p_(f)){var d=Array.prototype.slice.call(f,0,i.length);for(n=0;n<d.length;n++)q0(d[n])||(d[n]=h);for(n=d.length;n<i.length;n++)d.push(h);if(s.barwidth=d,l===void 0){for(c=[],n=0;n<i.length;n++)c.push(u+(h-d[n])/2);s.poffset=c}}else f!==void 0&&(s.barwidth=f,l===void 0&&(s.poffset=u+(h-f)/2))}}function Apt(e,t){for(var r=t.traces,n=iT(e),i=0;i<r.length;i++)for(var a=r[i],o=a[0].t,s=o.poffset,l=p_(s),u=o.barwidth,c=p_(u),f=0;f<a.length;f++){var h=a[f],d=h.w=c?u[f]:u;h.p===void 0&&(h.p=h[n],h[\"orig_\"+n]=h[n]);var v=(l?s[f]:s)+d/2;h[n]=h.p+v}}function uve(e,t,r){var n=t.traces,i=t.minDiff,a=i/2;KM.minDtick(e,t.minDiff,t.distinctPositions[0],r);for(var o=0;o<n.length;o++){var s=n[o],l=s[0],u=l.trace,c=[],f,h,d,v;for(v=0;v<s.length;v++)f=s[v],h=f.p-a,d=f.p+a,c.push(h,d);if(u.width||u.offset){var _=l.t,b=_.poffset,p=_.barwidth,k=p_(b),E=p_(p);for(v=0;v<s.length;v++){f=s[v];var S=k?b[v]:b,L=E?p[v]:p;h=f.p+S,d=h+L,c.push(h,d)}}u._extremes[e._id]=KM.findExtremes(e,c,{padded:!1})}}function cve(e,t){for(var r=t.traces,n=iT(e),i=0;i<r.length;i++){for(var a=r[i],o=a[0].trace,s=o.type===\"scatter\",l=o.orientation===\"v\",u=[],c=!1,f=0;f<a.length;f++){var h=a[f],d=s?0:h.b,v=s?l?h.y:h.x:d+h.s;h[n]=v,u.push(v),h.hasB&&u.push(d),(!h.hasB||!h.b)&&(c=!0)}o._extremes[e._id]=KM.findExtremes(e,u,{tozero:c,padded:!0})}}function Spt(e,t,r){var n=iT(e),i=t.traces,a,o,s,l,u,c,f;for(l=0;l<i.length;l++)if(a=i[l],o=a[0].trace,o.type===\"funnel\")for(f=a[0].t.offsetindex,u=0;u<a.length;u++)c=a[u],c.s!==rT&&t.put(c.p,f,-.5*c.s);for(l=0;l<i.length;l++){a=i[l],o=a[0].trace,s=o.type===\"funnel\",f=o.type===\"barpolar\"?0:a[0].t.offsetindex;var h=[];for(u=0;u<a.length;u++)if(c=a[u],c.s!==rT){var d;s?d=c.s:d=c.s+c.b;var v=t.put(c.p,f,d),_=v+d;c.b=v,c[n]=_,r.norm||(h.push(_),c.hasB&&h.push(v))}r.norm||(o._extremes[e._id]=KM.findExtremes(e,h,{tozero:!0,padded:!0}))}}function fve(e){for(var t=e.traces,r=0;r<t.length;r++)for(var n=t[r],i=n[0].t.offsetindex,a=0;a<n.length;a++){var o=n[a];o.s!==rT&&e.put(o.p,i,o.b+o.s)}}function Mpt(e,t){for(var r=e.traces,n=0;n<r.length;n++){var i=r[n],a=i[0].trace,o=i[0].t.offsetindex;if(a.base===void 0)for(var s=new QP([i],{posAxis:t,sepNegVal:!0,overlapNoMerge:!0}),l=0;l<i.length;l++){var u=i[l];if(u.p!==rT){var c=s.put(u.p,o,u.b+u.s);c&&(u.b=c)}}}}function pU(e,t,r){var n=t.traces,i=iT(e),a=r.norm===\"fraction\"?1:100,o=a/1e9,s=e.l2c(e.c2l(0)),l=r.mode===\"stack\"?a:s;function u(x){return q0(e.c2l(x))&&(x<s-o||x>l+o||!q0(s))}for(var c=0;c<n.length;c++){for(var f=n[c],h=f[0].t.offsetindex,d=f[0].trace,v=[],_=!1,b=!1,p=0;p<f.length;p++){var k=f[p];if(k.s!==rT){var E=Math.abs(a/t.get(k.p,h,k.s));k.b*=E,k.s*=E;var S=k.b,L=S+k.s;k[i]=L,v.push(L),b=b||u(L),k.hasB&&(v.push(S),b=b||u(S)),(!k.hasB||!k.b)&&(_=!0)}}d._extremes[e._id]=KM.findExtremes(e,v,{tozero:_,padded:b})}}function Ept(e,t,r,n){for(var i=iT(n),a=0;a<e.length;a++)for(var o=e[a],s=0;s<o.length;s++){var l=o[s],u=l[i];l._sMin=t[u],l._sMax=r[u]}}function kpt(e,t){var r=iT(t),n={},i,a,o,s=1/0,l=-1/0;for(i=0;i<e.length;i++)for(o=e[i],a=0;a<o.length;a++){var u=o[a].p;q0(u)&&(s=Math.min(s,u),l=Math.max(l,u))}var c=1e4/(l-s),f=n.round=function(M){return String(Math.round(c*(M-s)))},h={},d={},v=e.some(function(M){var g=M[0].trace;return\"marker\"in g&&g.marker.cornerradius});for(i=0;i<e.length;i++){o=e[i],o[0].t.extents=n;var _=o[0].t.poffset,b=p_(_);for(a=0;a<o.length;a++){var p=o[a],k=p[r]-p.w/2;if(q0(k)){var E=p[r]+p.w/2,S=f(p.p);n[S]?n[S]=[Math.min(k,n[S][0]),Math.max(E,n[S][1])]:n[S]=[k,E]}if(p.p0=p.p+(b?_[a]:_),p.p1=p.p0+p.w,p.s0=p.b,p.s1=p.s0+p.s,v){var L=Math.min(p.s0,p.s1)||0,x=Math.max(p.s0,p.s1)||0,C=p[r];h[C]=C in h?Math.min(h[C],L):L,d[C]=C in d?Math.max(d[C],x):x}}}v&&Ept(e,h,d,t)}function iT(e){return e._id.charAt(0)}hve.exports={crossTraceCalc:mpt,setGroupPositions:dU}});var gve=ye((nsr,pve)=>{\"use strict\";var dve=O0(),vve=jb().setGroupPositions;function Cpt(e,t){for(var r=t.xaxis,n=t.yaxis,i=e._fullLayout,a=e._fullData,o=e.calcdata,s=[],l=[],u=0;u<a.length;u++){var c=a[u];c.visible===!0&&c.type===\"scatter\"&&c.xaxis===r._id&&c.yaxis===n._id&&(c.orientation===\"h\"?s.push(o[u]):c.orientation===\"v\"&&l.push(o[u]))}var f={mode:i.scattermode,gap:i.scattergap};vve(e,r,n,l,f),vve(e,n,r,s,f)}pve.exports=function(t,r){t._fullLayout.scattermode===\"group\"&&Cpt(t,r);var n=r.xaxis,i=r.yaxis,a=n._id+i._id,o=t._fullLayout._scatterStackOpts[a];if(o){var s=t.calcdata,l,u,c,f,h,d,v,_,b,p,k,E,S,L,x;for(var C in o){p=o[C];var M=p.traceIndices;if(M.length){for(k=p.stackgaps===\"interpolate\",E=p.groupnorm,p.orientation===\"v\"?(S=\"x\",L=\"y\"):(S=\"y\",L=\"x\"),x=new Array(M.length),l=0;l<x.length;l++)x[l]=!1;d=s[M[0]];var g=new Array(d.length);for(l=0;l<d.length;l++)g[l]=d[l][S];for(l=1;l<M.length;l++){for(h=s[M[l]],u=c=0;u<h.length;u++){for(v=h[u][S];v>g[c]&&c<g.length;c++)gU(h,u,g[c],l,x,k,S),u++;if(v!==g[c]){for(f=0;f<l;f++)gU(s[M[f]],c,v,f,x,k,S);g.splice(c,0,v)}c++}for(;c<g.length;c++)gU(h,u,g[c],l,x,k,S),u++}var P=g.length;for(u=0;u<d.length;u++){for(_=d[u][L]=d[u].s,l=1;l<M.length;l++)h=s[M[l]],h[0].trace._rawLength=h[0].trace._length,h[0].trace._length=P,_+=h[u].s,h[u][L]=_;if(E)for(b=(E===\"fraction\"?_:_/100)||1,l=0;l<M.length;l++){var T=s[M[l]][u];T[L]/=b,T.sNorm=T.s/b}}for(l=0;l<M.length;l++){h=s[M[l]];var z=h[0].trace,O=dve.calcMarkerSize(z,z._rawLength),V=Array.isArray(O);if(O&&x[l]||V){var G=O;for(O=new Array(P),u=0;u<P;u++)O[u]=h[u].gap?0:V?G[h[u].i]:G}var Z=new Array(P),H=new Array(P);for(u=0;u<P;u++)Z[u]=h[u].x,H[u]=h[u].y;dve.calcAxisExpansion(t,z,n,i,Z,H,O),h[0].t.orientation=p.orientation}}}}};function gU(e,t,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,e.splice(t,0,s),t&&r===e[t-1][o]){var l=e[t-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=Lpt(e,t,r,o));t||(e[0].t=e[1].t,e[0].trace=e[1].trace,delete e[1].t,delete e[1].trace)}function Lpt(e,t,r,n){var i=e[t-1],a=e[t+1];return a?i?i.s+(a.s-i.s)*(r-i[n])/(a[n]-i[n]):a.s:i.s}});var yU=ye((asr,wve)=>{\"use strict\";var 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re=Math.max(3,H.mrc||0),oe=1-1/re,_e=Math.abs(l.c2p(H.y)-c);return _e<re?oe*_e/re:_e-re+oe},k=function(H){var N=Math.max(d,H.mrc||0),j=s.c2p(H.x)-u,re=l.c2p(H.y)-c;return Math.max(Math.sqrt(j*j+re*re)-N,1-d/N)},E=Ive.getDistanceFunction(i,b,p,k);if(Ive.getClosest(a,E,t),t.index!==!1){var S=a[t.index],L=s.c2p(S.x,!0),x=l.c2p(S.y,!0),C=S.mrc||1;t.index=S.i;var M=a[0].t.orientation,g=M&&(S.sNorm||S.s),P=M===\"h\"?g:S.orig_x!==void 0?S.orig_x:S.x,T=M===\"v\"?g:S.orig_y!==void 0?S.orig_y:S.y;return nI.extendFlat(t,{color:Gpt(o,S),x0:L-C,x1:L+C,xLabelVal:P,y0:x-C,y1:x+C,yLabelVal:T,spikeDistance:k(S),hovertemplate:o.hovertemplate}),Hpt(S,o,t),Vpt.getComponentMethod(\"errorbars\",\"hoverInfo\")(S,o,t),[t]}}function z(H){if(!H)return!1;var N=H.node();try{var j=new DOMPoint(f[0],f[1]);return N.isPointInFill(j)}catch(oe){var re=N.ownerSVGElement.createSVGPoint();return re.x=f[0],re.y=f[1],N.isPointInFill(re)}}function O(H){var N,j=[],re=1/0,oe=-1/0,_e=1/0,Ee=-1/0,Ce;for(N=0;N<H.length;N++){var me=H[N];me.contains(f)&&(j.push(me),_e=Math.min(_e,me.ymin),Ee=Math.max(Ee,me.ymax))}if(j.length===0)return null;_e=Math.max(_e,0),Ee=Math.min(Ee,l._length),Ce=(_e+Ee)/2;var ie,Se,Le,Ae,Fe,Pe,ge;for(N=0;N<j.length;N++)for(Se=j[N].pts,ie=1;ie<Se.length;ie++)Pe=Se[ie-1][1],ge=Se[ie][1],Pe>Ce!=ge>=Ce&&(Ae=Se[ie-1][0],Fe=Se[ie][0],ge-Pe&&(Le=Ae+(Fe-Ae)*(Ce-Pe)/(ge-Pe),re=Math.min(re,Le),oe=Math.max(oe,Le)));return re=Math.max(re,0),oe=Math.min(oe,s._length),{x0:re,x1:oe,y0:Ce,y1:Ce}}if(h.indexOf(\"fills\")!==-1&&o._fillElement){var V=z(o._fillElement)&&!z(o._fillExclusionElement);if(V){var G=O(o._polygons);G===null&&(G={x0:f[0],x1:f[0],y0:f[1],y1:f[1]});var Z=TU.defaultLine;return TU.opacity(o.fillcolor)?Z=o.fillcolor:TU.opacity((o.line||{}).color)&&(Z=o.line.color),nI.extendFlat(t,{distance:t.maxHoverDistance,x0:G.x0,x1:G.x1,y0:G.y0,y1:G.y1,color:Z,hovertemplate:!1}),delete t.index,o.text&&!nI.isArrayOrTypedArray(o.text)?t.text=String(o.text):t.text=o.name,[t]}}}});var fT=ye((dsr,Fve)=>{\"use strict\";var Dve=Ru();Fve.exports=function(t,r){var n=t.cd,i=t.xaxis,a=t.yaxis,o=[],s=n[0].trace,l,u,c,f,h=!Dve.hasMarkers(s)&&!Dve.hasText(s);if(h)return[];if(r===!1)for(l=0;l<n.length;l++)n[l].selected=0;else for(l=0;l<n.length;l++)u=n[l],c=i.c2p(u.x),f=a.c2p(u.y),u.i!==null&&r.contains([c,f],!1,l,t)?(o.push({pointNumber:u.i,x:i.c2d(u.x),y:a.c2d(u.y)}),u.selected=1):u.selected=0;return o}});var Ove=ye((vsr,zve)=>{\"use strict\";zve.exports={xaxis:{valType:\"subplotid\",dflt:\"x\",editType:\"calc+clearAxisTypes\"},yaxis:{valType:\"subplotid\",dflt:\"y\",editType:\"calc+clearAxisTypes\"}}});var SU=ye((psr,Nve)=>{\"use strict\";var QM=qa().traceIs,AU=I3();Nve.exports=function(t,r,n,i){n(\"autotypenumbers\",i.autotypenumbersDflt);var a=n(\"type\",(i.splomStash||{}).type);a===\"-\"&&(jpt(r,i.data),r.type===\"-\"?r.type=\"linear\":t.type=r.type)};function jpt(e,t){if(e.type===\"-\"){var r=e._id,n=r.charAt(0),i;r.indexOf(\"scene\")!==-1&&(r=n);var a=Wpt(t,r,n);if(a){if(a.type===\"histogram\"&&n==={v:\"y\",h:\"x\"}[a.orientation||\"v\"]){e.type=\"linear\";return}var o=n+\"calendar\",s=a[o],l={noMultiCategory:!QM(a,\"cartesian\")||QM(a,\"noMultiCategory\")};if(a.type===\"box\"&&a._hasPreCompStats&&n==={h:\"x\",v:\"y\"}[a.orientation||\"v\"]&&(l.noMultiCategory=!0),l.autotypenumbers=e.autotypenumbers,Bve(a,n)){var u=qve(a),c=[];for(i=0;i<t.length;i++){var f=t[i];!QM(f,\"box-violin\")||(f[n+\"axis\"]||n)!==r||(f[u]!==void 0?c.push(f[u][0]):f.name!==void 0?c.push(f.name):c.push(\"text\"),f[o]!==s&&(s=void 0))}e.type=AU(c,s,l)}else if(a.type===\"splom\"){var h=a.dimensions,d=h[a._axesDim[r]];d.visible&&(e.type=AU(d.values,s,l))}else e.type=AU(a[n]||[a[n+\"0\"]],s,l)}}}function Wpt(e,t,r){for(var n=0;n<e.length;n++){var i=e[n];if(i.type===\"splom\"&&i._length>0&&(i[\"_\"+r+\"axes\"]||{})[t])return i;if((i[r+\"axis\"]||r)===t){if(Bve(i,r))return i;if((i[r]||[]).length||i[r+\"0\"])return i}}}function qve(e){return{v:\"x\",h:\"y\"}[e.orientation||\"v\"]}function Bve(e,t){var r=qve(e),n=QM(e,\"box-violin\"),i=QM(e._fullInput||{},\"candlestick\");return n&&!i&&t===r&&e[r]===void 0&&e[r+\"0\"]===void 0}});var aI=ye((gsr,Uve)=>{\"use strict\";var Xpt=vv().isTypedArraySpec;function Zpt(e,t){var r=t.dataAttr||e._id.charAt(0),n={},i,a,o;if(t.axData)i=t.axData;else for(i=[],a=0;a<t.data.length;a++){var s=t.data[a];s[r+\"axis\"]===e._id&&i.push(s)}for(a=0;a<i.length;a++){var l=i[a][r];for(o=0;o<l.length;o++){var u=l[o];u!=null&&(n[u]=1)}}return Object.keys(n)}Uve.exports=function(t,r,n,i){if(r.type===\"category\"){var a=t.categoryarray,o=Array.isArray(a)&&a.length>0||Xpt(a),s;o&&(s=\"array\");var l=n(\"categoryorder\",s),u;l===\"array\"&&(u=n(\"categoryarray\")),!o&&l===\"array\"&&(l=r.categoryorder=\"trace\"),l===\"trace\"?r._initialCategories=[]:l===\"array\"?r._initialCategories=u.slice():(u=Zpt(r,i).sort(),l===\"category ascending\"?r._initialCategories=u:l===\"category 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S=o(\"zerolinelayer\"),L=o(\"zerolinecolor\",a),x=o(\"zerolinewidth\"),C=n(\"zeroline\",i.showGrid||!!L||!!x);C||(delete r.zerolinelayer,delete r.zerolinecolor,delete r.zerolinewidth)}}});var r4=ye((ysr,Yve)=>{\"use strict\";var Hve=Eo(),Jpt=qa(),t4=Dr(),$pt=vl(),Qpt=Yd(),MU=Rd(),jve=bb(),Wve=S3(),e0t=e_(),t0t=t_(),r0t=aI(),i0t=e4(),n0t=_B(),Xve=ym(),oI=hd().WEEKDAY_PATTERN,a0t=hd().HOUR_PATTERN;Yve.exports=function(t,r,n,i,a){var o=i.letter,s=i.font||{},l=i.splomStash||{},u=n(\"visible\",!i.visibleDflt),c=r._template||{},f=r.type||c.type||\"-\",h;if(f===\"date\"){var d=Jpt.getComponentMethod(\"calendars\",\"handleDefaults\");d(t,r,\"calendar\",i.calendar),i.noTicklabelmode||(h=n(\"ticklabelmode\"))}!i.noTicklabelindex&&(f===\"date\"||f===\"linear\")&&n(\"ticklabelindex\");var v=\"\";(!i.noTicklabelposition||f===\"multicategory\")&&(v=t4.coerce(t,r,{ticklabelposition:{valType:\"enumerated\",dflt:\"outside\",values:h===\"period\"?[\"outside\",\"inside\"]:o===\"x\"?[\"outside\",\"inside\",\"outside left\",\"inside left\",\"outside right\",\"inside right\"]:[\"outside\",\"inside\",\"outside top\",\"inside top\",\"outside bottom\",\"inside bottom\"]}},\"ticklabelposition\")),i.noTicklabeloverflow||n(\"ticklabeloverflow\",v.indexOf(\"inside\")!==-1?\"hide past domain\":f===\"category\"||f===\"multicategory\"?\"allow\":\"hide past div\"),Xve(r,a),n0t(t,r,n,i),r0t(t,r,n,i),i.noHover||(f!==\"category\"&&n(\"hoverformat\"),i.noUnifiedhovertitle||n(\"unifiedhovertitle.text\"));var _=n(\"color\"),b=_!==MU.color.dflt?_:s.color,p=l.label||a._dfltTitle[o];if(t0t(t,r,n,f,i),!u)return r;n(\"title.text\",p),t4.coerceFont(n,\"title.font\",s,{overrideDflt:{size:t4.bigFont(s.size),color:b}}),jve(t,r,n,f);var k=i.hasMinor;if(k&&($pt.newContainer(r,\"minor\"),jve(t,r,n,f,{isMinor:!0})),e0t(t,r,n,f,i),Wve(t,r,n,i),k){var E=i.isMinor;i.isMinor=!0,Wve(t,r,n,i),i.isMinor=E}i0t(t,r,n,{dfltColor:_,bgColor:i.bgColor,showGrid:i.showGrid,hasMinor:k,attributes:MU}),k&&!r.minor.ticks&&!r.minor.showgrid&&delete r.minor,(r.showline||r.ticks)&&n(\"mirror\");var S=f===\"multicategory\";if(!i.noTickson&&(f===\"category\"||S)&&(r.ticks||r.showgrid)&&(S?(n(\"tickson\",\"boundaries\"),delete r.ticklabelposition):n(\"tickson\")),S){var L=n(\"showdividers\");L&&(n(\"dividercolor\"),n(\"dividerwidth\"))}if(f===\"date\")if(Qpt(t,r,{name:\"rangebreaks\",inclusionAttr:\"enabled\",handleItemDefaults:o0t}),!r.rangebreaks.length)delete r.rangebreaks;else{for(var x=0;x<r.rangebreaks.length;x++)if(r.rangebreaks[x].pattern===oI){r._hasDayOfWeekBreaks=!0;break}if(Xve(r,a),a._has(\"scattergl\")||a._has(\"splom\"))for(var C=0;C<i.data.length;C++){var M=i.data[C];(M.type===\"scattergl\"||M.type===\"splom\")&&(M.visible=!1,t4.warn(M.type+\" traces do not work on axes with rangebreaks. Setting trace \"+M.index+\" to `visible: false`.\"))}}return r};function o0t(e,t,r){function n(h,d){return t4.coerce(e,t,MU.rangebreaks,h,d)}var i=n(\"enabled\");if(i){var a=n(\"bounds\");if(a&&a.length>=2){var o=\"\",s,l;if(a.length===2){for(s=0;s<2;s++)if(l=Zve(a[s]),l){o=oI;break}}var u=n(\"pattern\",o);if(u===oI)for(s=0;s<2;s++)l=Zve(a[s]),l&&(t.bounds[s]=a[s]=l-1);if(u)for(s=0;s<2;s++)switch(l=a[s],u){case oI:if(!Hve(l)){t.enabled=!1;return}if(l=+l,l!==Math.floor(l)||l<0||l>=7){t.enabled=!1;return}t.bounds[s]=a[s]=l;break;case a0t:if(!Hve(l)){t.enabled=!1;return}if(l=+l,l<0||l>24){t.enabled=!1;return}t.bounds[s]=a[s]=l;break}if(r.autorange===!1){var c=r.range;if(c[0]<c[1]){if(a[0]<c[0]&&a[1]>c[1]){t.enabled=!1;return}}else if(a[0]>c[0]&&a[1]<c[1]){t.enabled=!1;return}}}else{var f=n(\"values\");if(f&&f.length)n(\"dvalue\");else{t.enabled=!1;return}}}}var s0t={sun:1,mon:2,tue:3,wed:4,thu:5,fri:6,sat:7};function Zve(e){if(typeof e==\"string\")return s0t[e.substr(0,3).toLowerCase()]}});var lI=ye((_sr,Kve)=>{\"use strict\";var l0t=Eo(),sI=Dr();Kve.exports=function(t,r,n,i){var a=i.counterAxes||[],o=i.overlayableAxes||[],s=i.letter,l=i.grid,u=i.overlayingDomain,c,f,h,d,v,_;l&&(f=l._domains[s][l._axisMap[r._id]],c=l._anchors[r._id],f&&(h=l[s+\"side\"].split(\" \")[0],d=l.domain[s][h===\"right\"||h===\"top\"?1:0])),f=f||[0,1],c=c||(l0t(t.position)?\"free\":a[0]||\"free\"),h=h||(s===\"x\"?\"bottom\":\"left\"),d=d||0,v=0,_=!1;var b=sI.coerce(t,r,{anchor:{valType:\"enumerated\",values:[\"free\"].concat(a),dflt:c}},\"anchor\"),p=sI.coerce(t,r,{side:{valType:\"enumerated\",values:s===\"x\"?[\"bottom\",\"top\"]:[\"left\",\"right\"],dflt:h}},\"side\");if(b===\"free\"){if(s===\"y\"){var k=n(\"autoshift\");k&&(d=p===\"left\"?u[0]:u[1],_=r.automargin?r.automargin:!0,v=p===\"left\"?-3:3),n(\"shift\",v)}n(\"position\",d)}n(\"automargin\",_);var E=!1;if(o.length&&(E=sI.coerce(t,r,{overlaying:{valType:\"enumerated\",values:[!1].concat(o),dflt:!1}},\"overlaying\")),!E){var S=n(\"domain\",f);S[0]>S[1]-1/4096&&(r.domain=f),sI.noneOrAll(t.domain,r.domain,f),r.tickmode===\"sync\"&&(r.tickmode=\"auto\")}return n(\"layer\"),r}});var ape=ye((xsr,npe)=>{\"use strict\";var Wb=Dr(),Jve=ka(),u0t=ip().isUnifiedHover,c0t=HB(),$ve=vl(),f0t=u3(),Qve=Rd(),h0t=SU(),epe=r4(),d0t=Nb(),tpe=lI(),kU=hf(),Cm=kU.id2name,rpe=kU.name2id,v0t=hd().AX_ID_PATTERN,ipe=qa(),uI=ipe.traceIs,EU=ipe.getComponentMethod;function cI(e,t,r){Array.isArray(e[t])?e[t].push(r):e[t]=[r]}npe.exports=function(t,r,n){var i=r.autotypenumbers,a={},o={},s={},l={},u={},c={},f={},h={},d={},v={},_,b;for(_=0;_<n.length;_++){var p=n[_];if(uI(p,\"cartesian\")){var k;if(p.xaxis)k=Cm(p.xaxis),cI(a,k,p);else if(p.xaxes)for(b=0;b<p.xaxes.length;b++)cI(a,Cm(p.xaxes[b]),p);var E;if(p.yaxis)E=Cm(p.yaxis),cI(a,E,p);else if(p.yaxes)for(b=0;b<p.yaxes.length;b++)cI(a,Cm(p.yaxes[b]),p);if(p.type===\"funnel\"?p.orientation===\"h\"?(k&&(o[k]=!0),E&&(f[E]=!0)):E&&(s[E]=!0):p.type===\"image\"?(E&&(h[E]=!0),k&&(h[k]=!0)):(E&&(u[E]=!0,c[E]=!0),(!uI(p,\"carpet\")||p.type===\"carpet\"&&!p._cheater)&&k&&(l[k]=!0)),p.type===\"carpet\"&&p._cheater&&k&&(o[k]=!0),uI(p,\"2dMap\")&&(d[k]=!0,d[E]=!0),uI(p,\"oriented\")){var S=p.orientation===\"h\"?E:k;v[S]=!0}}}var L=r._subplots,x=L.xaxis,C=L.yaxis,M=Wb.simpleMap(x,Cm),g=Wb.simpleMap(C,Cm),P=M.concat(g),T=Jve.background;x.length&&C.length&&(T=Wb.coerce(t,r,f0t,\"plot_bgcolor\"));var z=Jve.combine(T,r.paper_bgcolor),O,V,G,Z,H;function N(){var St=a[O]||[];H._traceIndices=St.map(function(Qt){return Qt.index}),H._annIndices=[],H._shapeIndices=[],H._selectionIndices=[],H._imgIndices=[],H._subplotsWith=[],H._counterAxes=[],H._name=H._attr=O,H._id=V}function j(St,Qt){return Wb.coerce(Z,H,Qve,St,Qt)}function re(St,Qt){return Wb.coerce2(Z,H,Qve,St,Qt)}function oe(St){return 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T=i.getPointAtLength(C),z=i.getPointAtLength(C-.1);b=Math.atan2(T.y-z.y,T.x-z.x),v=i.getPointAtLength(Math.max(0,C-f));var O=M?h+f:f;M+=C-O+\"px,\"+C+\"px\",t.style(\"stroke-dasharray\",M)}function V(){t.style(\"stroke-dasharray\",\"0px,100px\")}function G(Z,H,N,j){Z.path&&(Z.noRotate&&(N=0),x0t.select(i.parentNode).append(\"path\").attr({class:t.attr(\"class\"),d:Z.path,transform:A0t(H.x,H.y)+T0t(N*180/Math.PI)+w0t(j)}).style({fill:b0t.rgb(n.arrowcolor),\"stroke-width\":0}))}u&&G(o,d,_,l),c&&G(a,v,b,s)}});var gI=ye((Ssr,Ape)=>{\"use strict\";var xpe=Oa(),LU=qa(),S0t=Mc(),y_=Dr(),PU=y_.strTranslate,n4=ho(),Yb=ka(),Iy=So(),bpe=vf(),IU=ru(),RU=Ag(),i4=yv(),M0t=vl().arrayEditor,E0t=_pe();Ape.exports={draw:k0t,drawOne:wpe,drawRaw:Tpe};function k0t(e){var t=e._fullLayout;t._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<t.annotations.length;r++)t.annotations[r].visible&&wpe(e,r);return S0t.previousPromises(e)}function wpe(e,t){var r=e._fullLayout,n=r.annotations[t]||{},i=n4.getFromId(e,n.xref),a=n4.getFromId(e,n.yref);i&&i.setScale(),a&&a.setScale(),Tpe(e,n,t,!1,i,a)}function m_(e,t,r,n,i){var a=i[r],o=i[r+\"ref\"],s=r.indexOf(\"y\")!==-1,l=n4.getRefType(o)===\"domain\",u=s?n.h:n.w;return e?l?a+(s?-t:t)/e._length:e.p2r(e.r2p(a)+t):a+(s?-t:t)/u}function Tpe(e,t,r,n,i,a){var o=e._fullLayout,s=e._fullLayout._size,l=e._context.edits,u,c;n?(u=\"annotation-\"+n,c=n+\".annotations\"):(u=\"annotation\",c=\"annotations\");var f=M0t(e.layout,c,t),h=f.modifyBase,d=f.modifyItem,v=f.getUpdateObj;o._infolayer.selectAll(\".\"+u+'[data-index=\"'+r+'\"]').remove();var _=\"clip\"+o._uid+\"_ann\"+r;if(!t._input||t.visible===!1){xpe.selectAll(\"#\"+_).remove();return}var b={x:{},y:{}},p=+t.textangle||0,k=o._infolayer.append(\"g\").classed(u,!0).attr(\"data-index\",String(r)).style(\"opacity\",t.opacity),E=k.append(\"g\").classed(\"annotation-text-g\",!0),S=l[t.showarrow?\"annotationTail\":\"annotationPosition\"],L=t.captureevents||l.annotationText||S;function x(j){var re={index:r,annotation:t._input,fullAnnotation:t,event:j};return n&&(re.subplotId=n),re}var C=E.append(\"g\").style(\"pointer-events\",L?\"all\":null).call(RU,\"pointer\").on(\"click\",function(){e._dragging=!1,e.emit(\"plotly_clickannotation\",x(xpe.event))});t.hovertext&&C.on(\"mouseover\",function(){var 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V=t.font,G=o._meta?y_.templateString(t.text,o._meta):t.text,Z=C.append(\"text\").classed(\"annotation-text\",!0).text(G);function H(j){return j.call(Iy.font,V).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[t.align]||\"middle\"}),IU.convertToTspans(j,e,N),j}function N(){var j=Z.selectAll(\"a\");if(j.size()===1&&j.text()===Z.text()){var re=C.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":j.attr(\"xlink:href\"),\"xlink:xlink:show\":j.attr(\"xlink:show\")}).style({cursor:\"pointer\"});re.node().appendChild(T.node())}var oe=C.select(\".annotation-text-math-group\"),_e=!oe.empty(),Ee=Iy.bBox((_e?oe:Z).node()),Ce=Ee.width,me=Ee.height,ie=t.width||Ce,Se=t.height||me,Le=Math.round(ie+2*P),Ae=Math.round(Se+2*P);function Fe(je,tt){return tt===\"auto\"&&(je<1/3?tt=\"left\":je>2/3?tt=\"right\":tt=\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[tt]}for(var Pe=!1,ge=[\"x\",\"y\"],Re=0;Re<ge.length;Re++){var ce=ge[Re],Ze=t[ce+\"ref\"]||ce,ut=t[\"a\"+ce+\"ref\"],pt={x:i,y:a}[ce],Zt=(p+(ce===\"x\"?0:-90))*Math.PI/180,st=Le*Math.cos(Zt),lt=Ae*Math.sin(Zt),Gt=Math.abs(st)+Math.abs(lt),Nt=t[ce+\"anchor\"],Jt=t[ce+\"shift\"]*(ce===\"x\"?1:-1),sr=b[ce],wr,cr,$e,St,Qt,Vt=n4.getRefType(Ze);if(pt&&Vt!==\"domain\"){var _t=pt.r2fraction(t[ce]);(_t<0||_t>1)&&(ut===Ze?(_t=pt.r2fraction(t[\"a\"+ce]),(_t<0||_t>1)&&(Pe=!0)):Pe=!0),wr=pt._offset+pt.r2p(t[ce]),St=.5}else{var It=Vt===\"domain\";ce===\"x\"?($e=t[ce],wr=It?pt._offset+pt._length*$e:wr=s.l+s.w*$e):($e=1-t[ce],wr=It?pt._offset+pt._length*$e:wr=s.t+s.h*$e),St=t.showarrow?.5:$e}if(t.showarrow){sr.head=wr;var mt=t[\"a\"+ce];if(Qt=st*Fe(.5,t.xanchor)-lt*Fe(.5,t.yanchor),ut===Ze){var er=n4.getRefType(ut);er===\"domain\"?(ce===\"y\"&&(mt=1-mt),sr.tail=pt._offset+pt._length*mt):er===\"paper\"?ce===\"y\"?(mt=1-mt,sr.tail=s.t+s.h*mt):sr.tail=s.l+s.w*mt:sr.tail=pt._offset+pt.r2p(mt),cr=Qt}else sr.tail=wr+mt,cr=Qt+mt;sr.text=sr.tail+Qt;var lr=o[ce===\"x\"?\"width\":\"height\"];if(Ze===\"paper\"&&(sr.head=y_.constrain(sr.head,1,lr-1)),ut===\"pixel\"){var Tr=-Math.max(sr.tail-3,sr.text),Lr=Math.min(sr.tail+3,sr.text)-lr;Tr>0?(sr.tail+=Tr,sr.text+=Tr):Lr>0&&(sr.tail-=Lr,sr.text-=Lr)}sr.tail+=Jt,sr.head+=Jt}else Qt=Gt*Fe(St,Nt),cr=Qt,sr.text=wr+Qt;sr.text+=Jt,Qt+=Jt,cr+=Jt,t[\"_\"+ce+\"padplus\"]=Gt/2+cr,t[\"_\"+ce+\"padminus\"]=Gt/2-cr,t[\"_\"+ce+\"size\"]=Gt,t[\"_\"+ce+\"shift\"]=Qt}if(Pe){C.remove();return}var ti=0,Br=0;if(t.align!==\"left\"&&(ti=(ie-Ce)*(t.align===\"center\"?.5:1)),t.valign!==\"top\"&&(Br=(Se-me)*(t.valign===\"middle\"?.5:1)),_e)oe.select(\"svg\").attr({x:P+ti-1,y:P+Br}).call(Iy.setClipUrl,z?_:null,e);else{var 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qn=t.arrowwidth,Fn=t.arrowcolor,ra=t.arrowside,la=k.append(\"g\").style({opacity:Yb.opacity(Fn)}).classed(\"annotation-arrow-g\",!0),Ut=la.append(\"path\").attr(\"d\",\"M\"+xe+\",\"+ke+\"L\"+xt+\",\"+Ie).style(\"stroke-width\",qn+\"px\").call(Yb.stroke,Yb.rgb(Fn));if(E0t(Ut,ra,t),l.annotationPosition&&Ut.node().parentNode&&!n){var wt=xt,rr=Ie;if(t.standoff){var nr=Math.sqrt(Math.pow(xt-xe,2)+Math.pow(Ie-ke,2));wt+=t.standoff*(xe-xt)/nr,rr+=t.standoff*(ke-Ie)/nr}var Er=la.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(xe-wt)+\",\"+(ke-rr),transform:PU(wt,rr)}).style(\"stroke-width\",qn+6+\"px\").call(Yb.stroke,\"rgba(0,0,0,0)\").call(Yb.fill,\"rgba(0,0,0,0)\"),Xr,ri;i4.init({element:Er.node(),gd:e,prepFn:function(){var Qr=Iy.getTranslate(C);Xr=Qr.x,ri=Qr.y,i&&i.autorange&&h(i._name+\".autorange\",!0),a&&a.autorange&&h(a._name+\".autorange\",!0)},moveFn:function(Qr,Oi){var 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r=kpe(e,t),n=r.on,i=r.off.concat(r.explicitOff),a={},o=e._fullLayout.annotations,s,l;if(n.length||i.length){for(s=0;s<n.length;s++)l=Mpe(e.layout,\"annotations\",o[n[s]]),l.modifyItem(\"visible\",!0),Spe.extendFlat(a,l.getUpdateObj());for(s=0;s<i.length;s++)l=Mpe(e.layout,\"annotations\",o[i[s]]),l.modifyItem(\"visible\",!1),Spe.extendFlat(a,l.getUpdateObj());return C0t.call(\"update\",e,{},a)}}function kpe(e,t){var r=e._fullLayout.annotations,n=[],i=[],a=[],o=(t||[]).length,s,l,u,c,f,h,d,v;for(s=0;s<r.length;s++)if(u=r[s],c=u.clicktoshow,c){for(l=0;l<o;l++)if(f=t[l],h=f.xaxis,d=f.yaxis,h._id===u.xref&&d._id===u.yref&&h.d2r(f.x)===Epe(u._xclick,h)&&d.d2r(f.y)===Epe(u._yclick,d)){u.visible?c===\"onout\"?v=i:v=a:v=n,v.push(s);break}l===o&&u.visible&&c===\"onout\"&&i.push(s)}return{on:n,off:i,explicitOff:a}}function Epe(e,t){return t.type===\"log\"?t.l2r(e):t.d2r(e)}});var FU=ye((Esr,Ppe)=>{\"use strict\";var DU=Dr(),hT=ka();Ppe.exports=function(t,r,n,i){i(\"opacity\");var 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zU=Dr(),Kb=ho(),I0t=Yd(),R0t=FU(),D0t=Ub();Ipe.exports=function(t,r){I0t(t,r,{name:\"annotations\",handleItemDefaults:F0t})};function F0t(e,t,r){function n(E,S){return zU.coerce(e,t,D0t,E,S)}var i=n(\"visible\"),a=n(\"clicktoshow\");if(i||a){R0t(e,t,r,n);for(var o=t.showarrow,s=[\"x\",\"y\"],l=[-10,-30],u={_fullLayout:r},c=0;c<2;c++){var f=s[c],h=Kb.coerceRef(e,t,u,f,\"\",\"paper\");if(h!==\"paper\"){var d=Kb.getFromId(u,h);d._annIndices.push(t._index)}if(Kb.coercePosition(t,u,n,h,f,.5),o){var v=\"a\"+f,_=Kb.coerceRef(e,t,u,v,\"pixel\",[\"pixel\",\"paper\"]);_!==\"pixel\"&&_!==h&&(_=t[v]=\"pixel\");var b=_===\"pixel\"?l[c]:.4;Kb.coercePosition(t,u,n,_,v,b)}n(f+\"anchor\"),n(f+\"shift\")}if(zU.noneOrAll(e,t,[\"x\",\"y\"]),o&&zU.noneOrAll(e,t,[\"ax\",\"ay\"]),a){var p=n(\"xclick\"),k=n(\"yclick\");t._xclick=p===void 0?t.x:Kb.cleanPosition(p,u,t.xref),t._yclick=k===void 0?t.y:Kb.cleanPosition(k,u,t.yref)}}}});var zpe=ye((Csr,Fpe)=>{\"use strict\";var OU=Dr(),Jb=ho(),z0t=gI().draw;Fpe.exports=function(t){var r=t._fullLayout,n=OU.filterVisible(r.annotations);if(n.length&&t._fullData.length)return OU.syncOrAsync([z0t,O0t],t)};function O0t(e){var t=e._fullLayout;OU.filterVisible(t.annotations).forEach(function(r){var n=Jb.getFromId(e,r.xref),i=Jb.getFromId(e,r.yref),a=Jb.getRefType(r.xref),o=Jb.getRefType(r.yref);r._extremes={},a===\"range\"&&Dpe(r,n),o===\"range\"&&Dpe(r,i)})}function Dpe(e,t){var r=t._id,n=r.charAt(0),i=e[n],a=e[\"a\"+n],o=e[n+\"ref\"],s=e[\"a\"+n+\"ref\"],l=e[\"_\"+n+\"padplus\"],u=e[\"_\"+n+\"padminus\"],c={x:1,y:-1}[n]*e[n+\"shift\"],f=3*e.arrowsize*e.arrowwidth||0,h=f+c,d=f-c,v=3*e.startarrowsize*e.arrowwidth||0,_=v+c,b=v-c,p;if(s===o){var k=Jb.findExtremes(t,[t.r2c(i)],{ppadplus:h,ppadminus:d}),E=Jb.findExtremes(t,[t.r2c(a)],{ppadplus:Math.max(l,_),ppadminus:Math.max(u,b)});p={min:[k.min[0],E.min[0]],max:[k.max[0],E.max[0]]}}else 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kc=Ub(),N0t=mc().overrideAll,U0t=vl().templatedArray;Vpe.exports=N0t(U0t(\"annotation\",{visible:kc.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:kc.xanchor,xshift:kc.xshift,yanchor:kc.yanchor,yshift:kc.yshift,text:kc.text,textangle:kc.textangle,font:kc.font,width:kc.width,height:kc.height,opacity:kc.opacity,align:kc.align,valign:kc.valign,bgcolor:kc.bgcolor,bordercolor:kc.bordercolor,borderpad:kc.borderpad,borderwidth:kc.borderwidth,showarrow:kc.showarrow,arrowcolor:kc.arrowcolor,arrowhead:kc.arrowhead,startarrowhead:kc.startarrowhead,arrowside:kc.arrowside,arrowsize:kc.arrowsize,startarrowsize:kc.startarrowsize,arrowwidth:kc.arrowwidth,standoff:kc.standoff,startstandoff:kc.startstandoff,hovertext:kc.hovertext,hoverlabel:kc.hoverlabel,captureevents:kc.captureevents}),\"calc\",\"from-root\")});var Hpe=ye((Rsr,Gpe)=>{\"use strict\";var BU=Dr(),V0t=ho(),G0t=Yd(),H0t=FU(),j0t=mI();Gpe.exports=function(t,r,n){G0t(t,r,{name:\"annotations\",handleItemDefaults:W0t,fullLayout:n.fullLayout})};function W0t(e,t,r,n){function i(s,l){return BU.coerce(e,t,j0t,s,l)}function a(s){var l=s+\"axis\",u={_fullLayout:{}};return u._fullLayout[l]=r[l],V0t.coercePosition(t,u,i,s,s,.5)}var o=i(\"visible\");o&&(H0t(e,t,n.fullLayout,i),a(\"x\"),a(\"y\"),a(\"z\"),BU.noneOrAll(e,t,[\"x\",\"y\",\"z\"]),t.xref=\"x\",t.yref=\"y\",t.zref=\"z\",i(\"xanchor\"),i(\"yanchor\"),i(\"xshift\"),i(\"yshift\"),t.showarrow&&(t.axref=\"pixel\",t.ayref=\"pixel\",i(\"ax\",-10),i(\"ay\",-30),BU.noneOrAll(e,t,[\"ax\",\"ay\"])))}});var Zpe=ye((Dsr,Xpe)=>{\"use strict\";var jpe=Dr(),Wpe=ho();Xpe.exports=function(t){for(var r=t.fullSceneLayout,n=r.annotations,i=0;i<n.length;i++)X0t(n[i],t);t.fullLayout._infolayer.selectAll(\".annotation-\"+t.id).remove()};function X0t(e,t){var 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w0e=ye((Wsr,b0e)=>{\"use strict\";var vgt=Dr(),jU=ho(),pgt=Yd(),ggt=HU(),mgt=\"images\";b0e.exports=function(t,r){var n={name:mgt,handleItemDefaults:ygt};pgt(t,r,n)};function ygt(e,t,r){function n(h,d){return vgt.coerce(e,t,ggt,h,d)}var i=n(\"source\"),a=n(\"visible\",!!i);if(!a)return t;n(\"layer\"),n(\"xanchor\"),n(\"yanchor\"),n(\"sizex\"),n(\"sizey\"),n(\"sizing\"),n(\"opacity\");for(var o={_fullLayout:r},s=[\"x\",\"y\"],l=0;l<2;l++){var u=s[l],c=jU.coerceRef(e,t,o,u,\"paper\",void 0);if(c!==\"paper\"){var f=jU.getFromId(o,c);f._imgIndices.push(t._index)}jU.coercePosition(t,o,n,c,u,0)}return t}});var M0e=ye((Xsr,S0e)=>{\"use strict\";var T0e=Oa(),_gt=So(),mT=ho(),A0e=hf(),xgt=Wp();S0e.exports=function(t){var r=t._fullLayout,n=[],i={},a=[],o,s;for(s=0;s<r.images.length;s++){var l=r.images[s];if(l.visible)if(l.layer===\"below\"&&l.xref!==\"paper\"&&l.yref!==\"paper\"){o=A0e.ref2id(l.xref)+A0e.ref2id(l.yref);var u=r._plots[o];if(!u){a.push(l);continue}u.mainplot&&(o=u.mainplot.id),i[o]||(i[o]=[]),i[o].push(l)}else l.layer===\"above\"?n.push(l):a.push(l)}var c={x:{left:{sizing:\"xMin\",offset:0},center:{sizing:\"xMid\",offset:-1/2},right:{sizing:\"xMax\",offset:-1}},y:{top:{sizing:\"YMin\",offset:0},middle:{sizing:\"YMid\",offset:-1/2},bottom:{sizing:\"YMax\",offset:-1}}};function f(S){var L=T0e.select(this);if(this._imgSrc!==S.source)if(L.attr(\"xmlns\",xgt.svg),!t._context.staticPlot||S.source&&S.source.slice(0,5)===\"data:\")L.attr(\"xlink:href\",S.source),this._imgSrc=S.source;else{var x=new Promise(function(C){var M=new Image;this.img=M,M.setAttribute(\"crossOrigin\",\"anonymous\"),M.onerror=g,M.onload=function(){var P=document.createElement(\"canvas\");P.width=this.width,P.height=this.height;var T=P.getContext(\"2d\",{willReadFrequently:!0});T.drawImage(this,0,0);var z=P.toDataURL(\"image/png\");L.attr(\"xlink:href\",z),C()},L.on(\"error\",g),M.src=S.source,this._imgSrc=S.source;function g(){L.remove(),C()}}.bind(this));t._promises.push(x)}}function h(S){var L=T0e.select(this),x=mT.getFromId(t,S.xref),C=mT.getFromId(t,S.yref),M=mT.getRefType(S.xref)===\"domain\",g=mT.getRefType(S.yref)===\"domain\",P=r._size,T,z;x!==void 0?T=typeof S.xref==\"string\"&&M?x._length*S.sizex:Math.abs(x.l2p(S.sizex)-x.l2p(0)):T=S.sizex*P.w,C!==void 0?z=typeof S.yref==\"string\"&&g?C._length*S.sizey:Math.abs(C.l2p(S.sizey)-C.l2p(0)):z=S.sizey*P.h;var O=T*c.x[S.xanchor].offset,V=z*c.y[S.yanchor].offset,G=c.x[S.xanchor].sizing+c.y[S.yanchor].sizing,Z,H;switch(x!==void 0?Z=typeof S.xref==\"string\"&&M?x._length*S.x+x._offset:x.r2p(S.x)+x._offset:Z=S.x*P.w+P.l,Z+=O,C!==void 0?H=typeof S.yref==\"string\"&&g?C._length*(1-S.y)+C._offset:C.r2p(S.y)+C._offset:H=P.h-S.y*P.h+P.t,H+=V,S.sizing){case\"fill\":G+=\" slice\";break;case\"stretch\":G=\"none\";break}L.attr({x:Z,y:H,width:T,height:z,preserveAspectRatio:G,opacity:S.opacity});var N=x&&mT.getRefType(S.xref)!==\"domain\"?x._id:\"\",j=C&&mT.getRefType(S.yref)!==\"domain\"?C._id:\"\",re=N+j;_gt.setClipUrl(L,re?\"clip\"+r._uid+re:null,t)}function d(S){return[S.xref,S.x,S.sizex,S.yref,S.y,S.sizey].join(\"_\")}function v(S,L){return S._index-L._index}var _=r._imageLowerLayer.selectAll(\"image\").data(a,d),b=r._imageUpperLayer.selectAll(\"image\").data(n,d);_.enter().append(\"image\"),b.enter().append(\"image\"),_.exit().remove(),b.exit().remove(),_.each(function(S){f.bind(this)(S),h.bind(this)(S)}),b.each(function(S){f.bind(this)(S),h.bind(this)(S)}),_.sort(v),b.sort(v);var p=Object.keys(r._plots);for(s=0;s<p.length;s++){o=p[s];var k=r._plots[o];if(k.imagelayer){var E=k.imagelayer.selectAll(\"image\").data(i[o]||[],d);E.enter().append(\"image\"),E.exit().remove(),E.each(function(S){f.bind(this)(S),h.bind(this)(S)}),E.sort(v)}}}});var C0e=ye((Zsr,k0e)=>{\"use strict\";var E0e=Eo(),bgt=m6();k0e.exports=function(t,r,n,i){r=r||{};var a=n===\"log\"&&r.type===\"linear\",o=n===\"linear\"&&r.type===\"log\";if(a||o){for(var s=t._fullLayout.images,l=r._id.charAt(0),u,c,f=0;f<s.length;f++)if(u=s[f],c=\"images[\"+f+\"].\",u[l+\"ref\"]===r._id){var h=u[l],d=u[\"size\"+l],v=null,_=null;if(a){v=bgt(h,r.range);var b=d/Math.pow(10,v)/2;_=2*Math.log(b+Math.sqrt(1+b*b))/Math.LN10}else v=Math.pow(10,h),_=v*(Math.pow(10,d/2)-Math.pow(10,-d/2));E0e(v)?E0e(_)||(_=null):(v=null,_=null),i(c+l,v),i(c+\"size\"+l,_)}}}});var P0e=ye((Ysr,L0e)=>{\"use strict\";L0e.exports={moduleType:\"component\",name:\"images\",layoutAttributes:HU(),supplyLayoutDefaults:w0e(),includeBasePlot:OM()(\"images\"),draw:M0e(),convertCoords:C0e()}});var yI=ye((Ksr,I0e)=>{\"use strict\";I0e.exports={name:\"updatemenus\",containerClassName:\"updatemenu-container\",headerGroupClassName:\"updatemenu-header-group\",headerClassName:\"updatemenu-header\",headerArrowClassName:\"updatemenu-header-arrow\",dropdownButtonGroupClassName:\"updatemenu-dropdown-button-group\",dropdownButtonClassName:\"updatemenu-dropdown-button\",buttonClassName:\"updatemenu-button\",itemRectClassName:\"updatemenu-item-rect\",itemTextClassName:\"updatemenu-item-text\",menuIndexAttrName:\"updatemenu-active-index\",autoMarginIdRoot:\"updatemenu-\",blankHeaderOpts:{label:\"  \"},minWidth:30,minHeight:30,textPadX:24,arrowPadX:16,rx:2,ry:2,textOffsetX:12,textOffsetY:3,arrowOffsetX:4,gapButtonHeader:5,gapButton:2,activeColor:\"#F4FAFF\",hoverColor:\"#F4FAFF\",arrowSymbol:{left:\"\\u25C4\",right:\"\\u25BA\",up:\"\\u25B2\",down:\"\\u25BC\"}}});var WU=ye((Jsr,D0e)=>{\"use strict\";var wgt=ec(),Tgt=Lh(),Agt=Ao().extendFlat,Sgt=mc().overrideAll,Mgt=E6(),R0e=vl().templatedArray,Egt=R0e(\"button\",{visible:{valType:\"boolean\"},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},args2:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\",dflt:\"\"},execute:{valType:\"boolean\",dflt:!0}});D0e.exports=Sgt(R0e(\"updatemenu\",{_arrayAttrRegexps:[/^updatemenus\\[(0|[1-9][0-9]+)\\]\\.buttons/],visible:{valType:\"boolean\"},type:{valType:\"enumerated\",values:[\"dropdown\",\"buttons\"],dflt:\"dropdown\"},direction:{valType:\"enumerated\",values:[\"left\",\"right\",\"up\",\"down\"],dflt:\"down\"},active:{valType:\"integer\",min:-1,dflt:0},showactive:{valType:\"boolean\",dflt:!0},buttons:Egt,x:{valType:\"number\",min:-2,max:3,dflt:-.05},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"right\"},y:{valType:\"number\",min:-2,max:3,dflt:1},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},pad:Agt(Mgt({editType:\"arraydraw\"}),{}),font:wgt({}),bgcolor:{valType:\"color\"},bordercolor:{valType:\"color\",dflt:Tgt.borderLine},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"arraydraw\"}}),\"arraydraw\",\"from-root\")});var q0e=ye(($sr,O0e)=>{\"use strict\";var _I=Dr(),F0e=Yd(),z0e=WU(),kgt=yI(),Cgt=kgt.name,Lgt=z0e.buttons;O0e.exports=function(t,r){var n={name:Cgt,handleItemDefaults:Pgt};F0e(t,r,n)};function Pgt(e,t,r){function n(o,s){return _I.coerce(e,t,z0e,o,s)}var i=F0e(e,t,{name:\"buttons\",handleItemDefaults:Igt}),a=n(\"visible\",i.length>0);a&&(n(\"active\"),n(\"direction\"),n(\"type\"),n(\"showactive\"),n(\"x\"),n(\"y\"),_I.noneOrAll(e,t,[\"x\",\"y\"]),n(\"xanchor\"),n(\"yanchor\"),n(\"pad.t\"),n(\"pad.r\"),n(\"pad.b\"),n(\"pad.l\"),_I.coerceFont(n,\"font\",r.font),n(\"bgcolor\",r.paper_bgcolor),n(\"bordercolor\"),n(\"borderwidth\"))}function Igt(e,t){function r(i,a){return _I.coerce(e,t,Lgt,i,a)}var n=r(\"visible\",e.method===\"skip\"||Array.isArray(e.args));n&&(r(\"method\"),r(\"args\"),r(\"args2\"),r(\"label\"),r(\"execute\"))}});var U0e=ye((Qsr,N0e)=>{\"use strict\";N0e.exports=Mf;var Og=Oa(),B0e=ka(),yT=So(),xI=Dr();function Mf(e,t,r){this.gd=e,this.container=t,this.id=r,this.position=null,this.translateX=null,this.translateY=null,this.hbar=null,this.vbar=null,this.bg=this.container.selectAll(\"rect.scrollbox-bg\").data([0]),this.bg.exit().on(\".drag\",null).on(\"wheel\",null).remove(),this.bg.enter().append(\"rect\").classed(\"scrollbox-bg\",!0).style(\"pointer-events\",\"all\").attr({opacity:0,x:0,y:0,width:0,height:0})}Mf.barWidth=2;Mf.barLength=20;Mf.barRadius=2;Mf.barPad=1;Mf.barColor=\"#808BA4\";Mf.prototype.enable=function(t,r,n){var i=this.gd._fullLayout,a=i.width,o=i.height;this.position=t;var s=this.position.l,l=this.position.w,u=this.position.t,c=this.position.h,f=this.position.direction,h=f===\"down\",d=f===\"left\",v=f===\"right\",_=f===\"up\",b=l,p=c,k,E,S,L;!h&&!d&&!v&&!_&&(this.position.direction=\"down\",h=!0);var x=h||_;x?(k=s,E=k+b,h?(S=u,L=Math.min(S+p,o),p=L-S):(L=u+p,S=Math.max(L-p,0),p=L-S)):(S=u,L=S+p,d?(E=s+b,k=Math.max(E-b,0),b=E-k):(k=s,E=Math.min(k+b,a),b=E-k)),this._box={l:k,t:S,w:b,h:p};var C=l>b,M=Mf.barLength+2*Mf.barPad,g=Mf.barWidth+2*Mf.barPad,P=s,T=u+c;T+g>o&&(T=o-g);var z=this.container.selectAll(\"rect.scrollbar-horizontal\").data(C?[0]:[]);z.exit().on(\".drag\",null).remove(),z.enter().append(\"rect\").classed(\"scrollbar-horizontal\",!0).call(B0e.fill,Mf.barColor),C?(this.hbar=z.attr({rx:Mf.barRadius,ry:Mf.barRadius,x:P,y:T,width:M,height:g}),this._hbarXMin=P+M/2,this._hbarTranslateMax=b-M):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var O=c>p,V=Mf.barWidth+2*Mf.barPad,G=Mf.barLength+2*Mf.barPad,Z=s+l,H=u;Z+V>a&&(Z=a-V);var N=this.container.selectAll(\"rect.scrollbar-vertical\").data(O?[0]:[]);N.exit().on(\".drag\",null).remove(),N.enter().append(\"rect\").classed(\"scrollbar-vertical\",!0).call(B0e.fill,Mf.barColor),O?(this.vbar=N.attr({rx:Mf.barRadius,ry:Mf.barRadius,x:Z,y:H,width:V,height:G}),this._vbarYMin=H+G/2,this._vbarTranslateMax=p-G):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var j=this.id,re=k-.5,oe=O?E+V+.5:E+.5,_e=S-.5,Ee=C?L+g+.5:L+.5,Ce=i._topdefs.selectAll(\"#\"+j).data(C||O?[0]:[]);if(Ce.exit().remove(),Ce.enter().append(\"clipPath\").attr(\"id\",j).append(\"rect\"),C||O?(this._clipRect=Ce.select(\"rect\").attr({x:Math.floor(re),y:Math.floor(_e),width:Math.ceil(oe)-Math.floor(re),height:Math.ceil(Ee)-Math.floor(_e)}),this.container.call(yT.setClipUrl,j,this.gd),this.bg.attr({x:s,y:u,width:l,height:c})):(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(yT.setClipUrl,null),delete this._clipRect),C||O){var me=Og.behavior.drag().on(\"dragstart\",function(){Og.event.sourceEvent.preventDefault()}).on(\"drag\",this._onBoxDrag.bind(this));this.container.on(\"wheel\",null).on(\"wheel\",this._onBoxWheel.bind(this)).on(\".drag\",null).call(me);var ie=Og.behavior.drag().on(\"dragstart\",function(){Og.event.sourceEvent.preventDefault(),Og.event.sourceEvent.stopPropagation()}).on(\"drag\",this._onBarDrag.bind(this));C&&this.hbar.on(\".drag\",null).call(ie),O&&this.vbar.on(\".drag\",null).call(ie)}this.setTranslate(r,n)};Mf.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(yT.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(\".drag\",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(\".drag\",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)};Mf.prototype._onBoxDrag=function(){var t=this.translateX,r=this.translateY;this.hbar&&(t-=Og.event.dx),this.vbar&&(r-=Og.event.dy),this.setTranslate(t,r)};Mf.prototype._onBoxWheel=function(){var t=this.translateX,r=this.translateY;this.hbar&&(t+=Og.event.deltaY),this.vbar&&(r+=Og.event.deltaY),this.setTranslate(t,r)};Mf.prototype._onBarDrag=function(){var t=this.translateX,r=this.translateY;if(this.hbar){var n=t+this._hbarXMin,i=n+this._hbarTranslateMax,a=xI.constrain(Og.event.x,n,i),o=(a-n)/(i-n),s=this.position.w-this._box.w;t=o*s}if(this.vbar){var l=r+this._vbarYMin,u=l+this._vbarTranslateMax,c=xI.constrain(Og.event.y,l,u),f=(c-l)/(u-l),h=this.position.h-this._box.h;r=f*h}this.setTranslate(t,r)};Mf.prototype.setTranslate=function(t,r){var n=this.position.w-this._box.w,i=this.position.h-this._box.h;if(t=xI.constrain(t||0,0,n),r=xI.constrain(r||0,0,i),this.translateX=t,this.translateY=r,this.container.call(yT.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-r),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+r-.5)}),this.hbar){var a=t/n;this.hbar.call(yT.setTranslate,t+a*this._hbarTranslateMax,r)}if(this.vbar){var o=r/i;this.vbar.call(yT.setTranslate,t,r+o*this._vbarTranslateMax)}}});var J0e=ye((elr,K0e)=>{\"use strict\";var _T=Oa(),o4=Mc(),s4=ka(),xT=So(),e0=Dr(),bI=ru(),Rgt=vl().arrayEditor,G0e=$h().LINE_SPACING,es=yI(),Dgt=U0e();K0e.exports=function(t){var r=t._fullLayout,n=e0.filterVisible(r[es.name]);function i(h){o4.autoMargin(t,Z0e(h))}var a=r._menulayer.selectAll(\"g.\"+es.containerClassName).data(n.length>0?[0]:[]);if(a.enter().append(\"g\").classed(es.containerClassName,!0).style(\"cursor\",\"pointer\"),a.exit().each(function(){_T.select(this).selectAll(\"g.\"+es.headerGroupClassName).each(i)}).remove(),n.length!==0){var o=a.selectAll(\"g.\"+es.headerGroupClassName).data(n,Fgt);o.enter().append(\"g\").classed(es.headerGroupClassName,!0);for(var s=e0.ensureSingle(a,\"g\",es.dropdownButtonGroupClassName,function(h){h.style(\"pointer-events\",\"all\")}),l=0;l<n.length;l++){var u=n[l];Ugt(t,u)}var c=\"updatemenus\"+r._uid,f=new Dgt(t,s,c);o.enter().size()&&(s.node().parentNode.appendChild(s.node()),s.call(ZU)),o.exit().each(function(h){s.call(ZU),i(h)}).remove(),o.each(function(h){var d=_T.select(this),v=h.type===\"dropdown\"?s:null;o4.manageCommandObserver(t,h,h.buttons,function(_){XU(t,h,h.buttons[_.index],d,v,f,_.index,!0)}),h.type===\"dropdown\"?(j0e(t,d,s,f,h),H0e(s,h)&&l4(t,d,s,f,h)):l4(t,d,null,null,h)})}};function Fgt(e){return e._index}function zgt(e){return+e.attr(es.menuIndexAttrName)==-1}function H0e(e,t){return+e.attr(es.menuIndexAttrName)===t._index}function XU(e,t,r,n,i,a,o,s){t.active=o,Rgt(e.layout,es.name,t).applyUpdate(\"active\",o),t.type===\"buttons\"?l4(e,n,null,null,t):t.type===\"dropdown\"&&(i.attr(es.menuIndexAttrName,\"-1\"),j0e(e,n,i,a,t),s||l4(e,n,i,a,t))}function j0e(e,t,r,n,i){var a=e0.ensureSingle(t,\"g\",es.headerClassName,function(h){h.style(\"pointer-events\",\"all\")}),o=i._dims,s=i.active,l=i.buttons[s]||es.blankHeaderOpts,u={y:i.pad.t,yPad:0,x:i.pad.l,xPad:0,index:0},c={width:o.headerWidth,height:o.headerHeight};a.call(YU,i,l,e).call(Y0e,i,u,c);var f=e0.ensureSingle(t,\"text\",es.headerArrowClassName,function(h){h.attr(\"text-anchor\",\"end\").call(xT.font,i.font).text(es.arrowSymbol[i.direction])});f.attr({x:o.headerWidth-es.arrowOffsetX+i.pad.l,y:o.headerHeight/2+es.textOffsetY+i.pad.t}),a.on(\"click\",function(){r.call(ZU,String(H0e(r,i)?-1:i._index)),l4(e,t,r,n,i)}),a.on(\"mouseover\",function(){a.call(W0e)}),a.on(\"mouseout\",function(){a.call(X0e,i)}),xT.setTranslate(t,o.lx,o.ly)}function l4(e,t,r,n,i){r||(r=t,r.attr(\"pointer-events\",\"all\"));var a=!zgt(r)||i.type===\"buttons\"?i.buttons:[],o=i.type===\"dropdown\"?es.dropdownButtonClassName:es.buttonClassName,s=r.selectAll(\"g.\"+o).data(e0.filterVisible(a)),l=s.enter().append(\"g\").classed(o,!0),u=s.exit();i.type===\"dropdown\"?(l.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),u.transition().attr(\"opacity\",\"0\").remove()):u.remove();var c=0,f=0,h=i._dims,d=[\"up\",\"down\"].indexOf(i.direction)!==-1;i.type===\"dropdown\"&&(d?f=h.headerHeight+es.gapButtonHeader:c=h.headerWidth+es.gapButtonHeader),i.type===\"dropdown\"&&i.direction===\"up\"&&(f=-es.gapButtonHeader+es.gapButton-h.openHeight),i.type===\"dropdown\"&&i.direction===\"left\"&&(c=-es.gapButtonHeader+es.gapButton-h.openWidth);var v={x:h.lx+c+i.pad.l,y:h.ly+f+i.pad.t,yPad:es.gapButton,xPad:es.gapButton,index:0},_={l:v.x+i.borderwidth,t:v.y+i.borderwidth};s.each(function(b,p){var k=_T.select(this);k.call(YU,i,b,e).call(Y0e,i,v),k.on(\"click\",function(){_T.event.defaultPrevented||(b.execute&&(b.args2&&i.active===p?(XU(e,i,b,t,r,n,-1),o4.executeAPICommand(e,b.method,b.args2)):(XU(e,i,b,t,r,n,p),o4.executeAPICommand(e,b.method,b.args))),e.emit(\"plotly_buttonclicked\",{menu:i,button:b,active:i.active}))}),k.on(\"mouseover\",function(){k.call(W0e)}),k.on(\"mouseout\",function(){k.call(X0e,i),s.call(V0e,i)})}),s.call(V0e,i),d?(_.w=Math.max(h.openWidth,h.headerWidth),_.h=v.y-_.t):(_.w=v.x-_.l,_.h=Math.max(h.openHeight,h.headerHeight)),_.direction=i.direction,n&&(s.size()?Ogt(e,t,r,n,i,_):qgt(n))}function Ogt(e,t,r,n,i,a){var o=i.direction,s=o===\"up\"||o===\"down\",l=i._dims,u=i.active,c,f,h;if(s)for(f=0,h=0;h<u;h++)f+=l.heights[h]+es.gapButton;else for(c=0,h=0;h<u;h++)c+=l.widths[h]+es.gapButton;n.enable(a,c,f),n.hbar&&n.hbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),n.vbar&&n.vbar.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\")}function qgt(e){var t=!!e.hbar,r=!!e.vbar;t&&e.hbar.transition().attr(\"opacity\",\"0\").each(\"end\",function(){t=!1,r||e.disable()}),r&&e.vbar.transition().attr(\"opacity\",\"0\").each(\"end\",function(){r=!1,t||e.disable()})}function YU(e,t,r,n){e.call(Bgt,t).call(Ngt,t,r,n)}function Bgt(e,t){var r=e0.ensureSingle(e,\"rect\",es.itemRectClassName,function(n){n.attr({rx:es.rx,ry:es.ry,\"shape-rendering\":\"crispEdges\"})});r.call(s4.stroke,t.bordercolor).call(s4.fill,t.bgcolor).style(\"stroke-width\",t.borderwidth+\"px\")}function Ngt(e,t,r,n){var i=e0.ensureSingle(e,\"text\",es.itemTextClassName,function(s){s.attr({\"text-anchor\":\"start\",\"data-notex\":1})}),a=r.label,o=n._fullLayout._meta;o&&(a=e0.templateString(a,o)),i.call(xT.font,t.font).text(a).call(bI.convertToTspans,n)}function V0e(e,t){var r=t.active;e.each(function(n,i){var a=_T.select(this);i===r&&t.showactive&&a.select(\"rect.\"+es.itemRectClassName).call(s4.fill,es.activeColor)})}function W0e(e){e.select(\"rect.\"+es.itemRectClassName).call(s4.fill,es.hoverColor)}function X0e(e,t){e.select(\"rect.\"+es.itemRectClassName).call(s4.fill,t.bgcolor)}function Ugt(e,t){var r=t._dims={width1:0,height1:0,heights:[],widths:[],totalWidth:0,totalHeight:0,openWidth:0,openHeight:0,lx:0,ly:0},n=xT.tester.selectAll(\"g.\"+es.dropdownButtonClassName).data(e0.filterVisible(t.buttons));n.enter().append(\"g\").classed(es.dropdownButtonClassName,!0);var i=[\"up\",\"down\"].indexOf(t.direction)!==-1;n.each(function(c,f){var h=_T.select(this);h.call(YU,t,c,e);var d=h.select(\".\"+es.itemTextClassName),v=d.node()&&xT.bBox(d.node()).width,_=Math.max(v+es.textPadX,es.minWidth),b=t.font.size*G0e,p=bI.lineCount(d),k=Math.max(b*p,es.minHeight)+es.textOffsetY;k=Math.ceil(k),_=Math.ceil(_),r.widths[f]=_,r.heights[f]=k,r.height1=Math.max(r.height1,k),r.width1=Math.max(r.width1,_),i?(r.totalWidth=Math.max(r.totalWidth,_),r.openWidth=r.totalWidth,r.totalHeight+=k+es.gapButton,r.openHeight+=k+es.gapButton):(r.totalWidth+=_+es.gapButton,r.openWidth+=_+es.gapButton,r.totalHeight=Math.max(r.totalHeight,k),r.openHeight=r.totalHeight)}),i?r.totalHeight-=es.gapButton:r.totalWidth-=es.gapButton,r.headerWidth=r.width1+es.arrowPadX,r.headerHeight=r.height1,t.type===\"dropdown\"&&(i?(r.width1+=es.arrowPadX,r.totalHeight=r.height1):r.totalWidth=r.width1,r.totalWidth+=es.arrowPadX),n.remove();var a=r.totalWidth+t.pad.l+t.pad.r,o=r.totalHeight+t.pad.t+t.pad.b,s=e._fullLayout._size;r.lx=s.l+s.w*t.x,r.ly=s.t+s.h*(1-t.y);var l=\"left\";e0.isRightAnchor(t)&&(r.lx-=a,l=\"right\"),e0.isCenterAnchor(t)&&(r.lx-=a/2,l=\"center\");var u=\"top\";e0.isBottomAnchor(t)&&(r.ly-=o,u=\"bottom\"),e0.isMiddleAnchor(t)&&(r.ly-=o/2,u=\"middle\"),r.totalWidth=Math.ceil(r.totalWidth),r.totalHeight=Math.ceil(r.totalHeight),r.lx=Math.round(r.lx),r.ly=Math.round(r.ly),o4.autoMargin(e,Z0e(t),{x:t.x,y:t.y,l:a*({right:1,center:.5}[l]||0),r:a*({left:1,center:.5}[l]||0),b:o*({top:1,middle:.5}[u]||0),t:o*({bottom:1,middle:.5}[u]||0)})}function Z0e(e){return es.autoMarginIdRoot+e._index}function Y0e(e,t,r,n){n=n||{};var i=e.select(\".\"+es.itemRectClassName),a=e.select(\".\"+es.itemTextClassName),o=t.borderwidth,s=r.index,l=t._dims;xT.setTranslate(e,o+r.x,o+r.y);var u=[\"up\",\"down\"].indexOf(t.direction)!==-1,c=n.height||(u?l.heights[s]:l.height1);i.attr({x:0,y:0,width:n.width||(u?l.width1:l.widths[s]),height:c});var f=t.font.size*G0e,h=bI.lineCount(a),d=(h-1)*f/2;bI.positionText(a,es.textOffsetX,c/2-d+es.textOffsetY),u?r.y+=l.heights[s]+r.yPad:r.x+=l.widths[s]+r.xPad,r.index++}function ZU(e,t){e.attr(es.menuIndexAttrName,t||\"-1\").selectAll(\"g.\"+es.dropdownButtonClassName).remove()}});var Q0e=ye((tlr,$0e)=>{\"use strict\";var Vgt=yI();$0e.exports={moduleType:\"component\",name:Vgt.name,layoutAttributes:WU(),supplyLayoutDefaults:q0e(),draw:J0e()}});var u4=ye((rlr,ege)=>{\"use strict\";ege.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}});var KU=ye((ilr,ige)=>{\"use strict\";var tge=ec(),Ggt=E6(),Hgt=Ao().extendDeepAll,jgt=mc().overrideAll,Wgt=NS(),rge=vl().templatedArray,$b=u4(),Xgt=rge(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});ige.exports=jgt(rge(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:Xgt,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:Hgt(Ggt({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:Wgt.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:tge({})},font:tge({}),activebgcolor:{valType:\"color\",dflt:$b.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:$b.railBgColor},bordercolor:{valType:\"color\",dflt:$b.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:$b.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:$b.tickLength},tickcolor:{valType:\"color\",dflt:$b.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:$b.minorTickLength}}),\"arraydraw\",\"from-root\")});var sge=ye((nlr,oge)=>{\"use strict\";var bT=Dr(),nge=Yd(),age=KU(),Zgt=u4(),Ygt=Zgt.name,Kgt=age.steps;oge.exports=function(t,r){nge(t,r,{name:Ygt,handleItemDefaults:Jgt})};function Jgt(e,t,r){function n(f,h){return bT.coerce(e,t,age,f,h)}for(var i=nge(e,t,{name:\"steps\",handleItemDefaults:$gt}),a=0,o=0;o<i.length;o++)i[o].visible&&a++;var s;if(a<2?s=t.visible=!1:s=n(\"visible\"),!!s){t._stepCount=a;var l=t._visibleSteps=bT.filterVisible(i),u=n(\"active\");(i[u]||{}).visible||(t.active=l[0]._index),n(\"x\"),n(\"y\"),bT.noneOrAll(e,t,[\"x\",\"y\"]),n(\"xanchor\"),n(\"yanchor\"),n(\"len\"),n(\"lenmode\"),n(\"pad.t\"),n(\"pad.r\"),n(\"pad.b\"),n(\"pad.l\"),bT.coerceFont(n,\"font\",r.font);var c=n(\"currentvalue.visible\");c&&(n(\"currentvalue.xanchor\"),n(\"currentvalue.prefix\"),n(\"currentvalue.suffix\"),n(\"currentvalue.offset\"),bT.coerceFont(n,\"currentvalue.font\",t.font)),n(\"transition.duration\"),n(\"transition.easing\"),n(\"bgcolor\"),n(\"activebgcolor\"),n(\"bordercolor\"),n(\"borderwidth\"),n(\"ticklen\"),n(\"tickwidth\"),n(\"tickcolor\"),n(\"minorticklen\")}}function $gt(e,t){function r(a,o){return bT.coerce(e,t,Kgt,a,o)}var n;if(e.method!==\"skip\"&&!Array.isArray(e.args)?n=t.visible=!1:n=r(\"visible\"),n){r(\"method\"),r(\"args\");var i=r(\"label\",\"step-\"+t._index);r(\"value\",i),r(\"execute\")}}});var mge=ye((alr,gge)=>{\"use strict\";var qg=Oa(),wI=Mc(),__=ka(),Bg=So(),t0=Dr(),Qgt=t0.strTranslate,c4=ru(),emt=vl().arrayEditor,Rs=u4(),QU=$h(),cge=QU.LINE_SPACING,JU=QU.FROM_TL,$U=QU.FROM_BR;gge.exports=function(t){var r=t._context.staticPlot,n=t._fullLayout,i=tmt(n,t),a=n._infolayer.selectAll(\"g.\"+Rs.containerClassName).data(i.length>0?[0]:[]);a.enter().append(\"g\").classed(Rs.containerClassName,!0).style(\"cursor\",r?null:\"ew-resize\");function o(c){c._commandObserver&&(c._commandObserver.remove(),delete c._commandObserver),wI.autoMargin(t,fge(c))}if(a.exit().each(function(){qg.select(this).selectAll(\"g.\"+Rs.groupClassName).each(o)}).remove(),i.length!==0){var s=a.selectAll(\"g.\"+Rs.groupClassName).data(i,rmt);s.enter().append(\"g\").classed(Rs.groupClassName,!0),s.exit().each(o).remove();for(var l=0;l<i.length;l++){var u=i[l];imt(t,u)}s.each(function(c){var f=qg.select(this);lmt(c),wI.manageCommandObserver(t,c,c._visibleSteps,function(h){var d=f.data()[0];d.active!==h.index&&(d._dragging||dge(t,f,d,h.index,!1,!0))}),nmt(t,qg.select(this),c)})}};function fge(e){return Rs.autoMarginIdRoot+e._index}function tmt(e,t){for(var r=e[Rs.name],n=[],i=0;i<r.length;i++){var a=r[i];a.visible&&(a._gd=t,n.push(a))}return n}function rmt(e){return e._index}function imt(e,t){var r=Bg.tester.selectAll(\"g.\"+Rs.labelGroupClass).data(t._visibleSteps);r.enter().append(\"g\").classed(Rs.labelGroupClass,!0);var n=0,i=0;r.each(function(v){var _=qg.select(this),b=hge(_,{step:v},t),p=b.node();if(p){var k=Bg.bBox(p);i=Math.max(i,k.height),n=Math.max(n,k.width)}}),r.remove();var a=t._dims={};a.inputAreaWidth=Math.max(Rs.railWidth,Rs.gripHeight);var o=e._fullLayout._size;a.lx=o.l+o.w*t.x,a.ly=o.t+o.h*(1-t.y),t.lenmode===\"fraction\"?a.outerLength=Math.round(o.w*t.len):a.outerLength=t.len,a.inputAreaStart=0,a.inputAreaLength=Math.round(a.outerLength-t.pad.l-t.pad.r);var s=a.inputAreaLength-2*Rs.stepInset,l=s/(t._stepCount-1),u=n+Rs.labelPadding;if(a.labelStride=Math.max(1,Math.ceil(u/l)),a.labelHeight=i,a.currentValueMaxWidth=0,a.currentValueHeight=0,a.currentValueTotalHeight=0,a.currentValueMaxLines=1,t.currentvalue.visible){var c=Bg.tester.append(\"g\");r.each(function(v){var _=TI(c,t,v.label),b=_.node()&&Bg.bBox(_.node())||{width:0,height:0},p=c4.lineCount(_);a.currentValueMaxWidth=Math.max(a.currentValueMaxWidth,Math.ceil(b.width)),a.currentValueHeight=Math.max(a.currentValueHeight,Math.ceil(b.height)),a.currentValueMaxLines=Math.max(a.currentValueMaxLines,p)}),a.currentValueTotalHeight=a.currentValueHeight+t.currentvalue.offset,c.remove()}a.height=a.currentValueTotalHeight+Rs.tickOffset+t.ticklen+Rs.labelOffset+a.labelHeight+t.pad.t+t.pad.b;var f=\"left\";t0.isRightAnchor(t)&&(a.lx-=a.outerLength,f=\"right\"),t0.isCenterAnchor(t)&&(a.lx-=a.outerLength/2,f=\"center\");var h=\"top\";t0.isBottomAnchor(t)&&(a.ly-=a.height,h=\"bottom\"),t0.isMiddleAnchor(t)&&(a.ly-=a.height/2,h=\"middle\"),a.outerLength=Math.ceil(a.outerLength),a.height=Math.ceil(a.height),a.lx=Math.round(a.lx),a.ly=Math.round(a.ly);var d={y:t.y,b:a.height*$U[h],t:a.height*JU[h]};t.lenmode===\"fraction\"?(d.l=0,d.xl=t.x-t.len*JU[f],d.r=0,d.xr=t.x+t.len*$U[f]):(d.x=t.x,d.l=a.outerLength*JU[f],d.r=a.outerLength*$U[f]),wI.autoMargin(e,fge(t),d)}function nmt(e,t,r){(r.steps[r.active]||{}).visible||(r.active=r._visibleSteps[0]._index),t.call(TI,r).call(cmt,r).call(omt,r).call(smt,r).call(umt,e,r).call(amt,e,r);var n=r._dims;Bg.setTranslate(t,n.lx+r.pad.l,n.ly+r.pad.t),t.call(pge,r,!1),t.call(TI,r)}function TI(e,t,r){if(t.currentvalue.visible){var n=t._dims,i,a;switch(t.currentvalue.xanchor){case\"right\":i=n.inputAreaLength-Rs.currentValueInset-n.currentValueMaxWidth,a=\"left\";break;case\"center\":i=n.inputAreaLength*.5,a=\"middle\";break;default:i=Rs.currentValueInset,a=\"left\"}var o=t0.ensureSingle(e,\"text\",Rs.labelClass,function(h){h.attr({\"text-anchor\":a,\"data-notex\":1})}),s=t.currentvalue.prefix?t.currentvalue.prefix:\"\";if(typeof r==\"string\")s+=r;else{var l=t.steps[t.active].label,u=t._gd._fullLayout._meta;u&&(l=t0.templateString(l,u)),s+=l}t.currentvalue.suffix&&(s+=t.currentvalue.suffix),o.call(Bg.font,t.currentvalue.font).text(s).call(c4.convertToTspans,t._gd);var c=c4.lineCount(o),f=(n.currentValueMaxLines+1-c)*t.currentvalue.font.size*cge;return c4.positionText(o,i,f),o}}function amt(e,t,r){var n=t0.ensureSingle(e,\"rect\",Rs.gripRectClass,function(i){i.call(vge,t,e,r).style(\"pointer-events\",\"all\")});n.attr({width:Rs.gripWidth,height:Rs.gripHeight,rx:Rs.gripRadius,ry:Rs.gripRadius}).call(__.stroke,r.bordercolor).call(__.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function hge(e,t,r){var n=t0.ensureSingle(e,\"text\",Rs.labelClass,function(o){o.attr({\"text-anchor\":\"middle\",\"data-notex\":1})}),i=t.step.label,a=r._gd._fullLayout._meta;return a&&(i=t0.templateString(i,a)),n.call(Bg.font,r.font).text(i).call(c4.convertToTspans,r._gd),n}function omt(e,t){var r=t0.ensureSingle(e,\"g\",Rs.labelsClass),n=t._dims,i=r.selectAll(\"g.\"+Rs.labelGroupClass).data(n.labelSteps);i.enter().append(\"g\").classed(Rs.labelGroupClass,!0),i.exit().remove(),i.each(function(a){var o=qg.select(this);o.call(hge,a,t),Bg.setTranslate(o,eV(t,a.fraction),Rs.tickOffset+t.ticklen+t.font.size*cge+Rs.labelOffset+n.currentValueTotalHeight)})}function lge(e,t,r,n,i){var a=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[a]._index;o!==r.active&&dge(e,t,r,o,!0,i)}function dge(e,t,r,n,i,a){var o=r.active;r.active=n,emt(e.layout,Rs.name,r).applyUpdate(\"active\",n);var s=r.steps[r.active];t.call(pge,r,a),t.call(TI,r),e.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:i,previousActive:o}),s&&s.method&&i&&(t._nextMethod?(t._nextMethod.step=s,t._nextMethod.doCallback=i,t._nextMethod.doTransition=a):(t._nextMethod={step:s,doCallback:i,doTransition:a},t._nextMethodRaf=window.requestAnimationFrame(function(){var l=t._nextMethod.step;l.method&&(l.execute&&wI.executeAPICommand(e,l.method,l.args),t._nextMethod=null,t._nextMethodRaf=null)})))}function vge(e,t,r){if(t._context.staticPlot)return;var n=r.node(),i=qg.select(t);function a(){return r.data()[0]}function o(){var s=a();t.emit(\"plotly_sliderstart\",{slider:s});var l=r.select(\".\"+Rs.gripRectClass);qg.event.stopPropagation(),qg.event.preventDefault(),l.call(__.fill,s.activebgcolor);var u=uge(s,qg.mouse(n)[0]);lge(t,r,s,u,!0),s._dragging=!0;function c(){var h=a(),d=uge(h,qg.mouse(n)[0]);lge(t,r,h,d,!1)}i.on(\"mousemove\",c),i.on(\"touchmove\",c);function f(){var h=a();h._dragging=!1,l.call(__.fill,h.bgcolor),i.on(\"mouseup\",null),i.on(\"mousemove\",null),i.on(\"touchend\",null),i.on(\"touchmove\",null),t.emit(\"plotly_sliderend\",{slider:h,step:h.steps[h.active]})}i.on(\"mouseup\",f),i.on(\"touchend\",f)}e.on(\"mousedown\",o),e.on(\"touchstart\",o)}function smt(e,t){var r=e.selectAll(\"rect.\"+Rs.tickRectClass).data(t._visibleSteps),n=t._dims;r.enter().append(\"rect\").classed(Rs.tickRectClass,!0),r.exit().remove(),r.attr({width:t.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each(function(i,a){var o=a%n.labelStride===0,s=qg.select(this);s.attr({height:o?t.ticklen:t.minorticklen}).call(__.fill,t.tickcolor),Bg.setTranslate(s,eV(t,a/(t._stepCount-1))-.5*t.tickwidth,(o?Rs.tickOffset:Rs.minorTickOffset)+n.currentValueTotalHeight)})}function lmt(e){var t=e._dims;t.labelSteps=[];for(var r=e._stepCount,n=0;n<r;n+=t.labelStride)t.labelSteps.push({fraction:n/(r-1),step:e._visibleSteps[n]})}function pge(e,t,r){for(var n=e.select(\"rect.\"+Rs.gripRectClass),i=0,a=0;a<t._stepCount;a++)if(t._visibleSteps[a]._index===t.active){i=a;break}var o=eV(t,i/(t._stepCount-1));if(!t._invokingCommand){var s=n;r&&t.transition.duration>0&&(s=s.transition().duration(t.transition.duration).ease(t.transition.easing)),s.attr(\"transform\",Qgt(o-Rs.gripWidth*.5,t._dims.currentValueTotalHeight))}}function eV(e,t){var r=e._dims;return r.inputAreaStart+Rs.stepInset+(r.inputAreaLength-2*Rs.stepInset)*Math.min(1,Math.max(0,t))}function uge(e,t){var r=e._dims;return Math.min(1,Math.max(0,(t-Rs.stepInset-r.inputAreaStart)/(r.inputAreaLength-2*Rs.stepInset-2*r.inputAreaStart)))}function umt(e,t,r){var n=r._dims,i=t0.ensureSingle(e,\"rect\",Rs.railTouchRectClass,function(a){a.call(vge,t,e,r).style(\"pointer-events\",\"all\")});i.attr({width:n.inputAreaLength,height:Math.max(n.inputAreaWidth,Rs.tickOffset+r.ticklen+n.labelHeight)}).call(__.fill,r.bgcolor).attr(\"opacity\",0),Bg.setTranslate(i,0,n.currentValueTotalHeight)}function cmt(e,t){var r=t._dims,n=r.inputAreaLength-Rs.railInset*2,i=t0.ensureSingle(e,\"rect\",Rs.railRectClass);i.attr({width:n,height:Rs.railWidth,rx:Rs.railRadius,ry:Rs.railRadius,\"shape-rendering\":\"crispEdges\"}).call(__.stroke,t.bordercolor).call(__.fill,t.bgcolor).style(\"stroke-width\",t.borderwidth+\"px\"),Bg.setTranslate(i,Rs.railInset,(r.inputAreaWidth-Rs.railWidth)*.5+r.currentValueTotalHeight)}});var _ge=ye((olr,yge)=>{\"use strict\";var fmt=u4();yge.exports={moduleType:\"component\",name:fmt.name,layoutAttributes:KU(),supplyLayoutDefaults:sge(),draw:mge()}});var AI=ye((slr,bge)=>{\"use strict\";var xge=Lh();bge.exports={bgcolor:{valType:\"color\",dflt:xge.background,editType:\"plot\"},bordercolor:{valType:\"color\",dflt:xge.defaultLine,editType:\"plot\"},borderwidth:{valType:\"integer\",dflt:0,min:0,editType:\"plot\"},autorange:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"range[0]\":void 0,\"range[1]\":void 0}},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"calc\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"calc\",impliedEdits:{\"^autorange\":!1}}],editType:\"calc\",impliedEdits:{autorange:!1}},thickness:{valType:\"number\",dflt:.15,min:0,max:1,editType:\"plot\"},visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"},editType:\"calc\"}});var tV=ye((llr,wge)=>{\"use strict\";wge.exports={_isSubplotObj:!0,rangemode:{valType:\"enumerated\",values:[\"auto\",\"fixed\",\"match\"],dflt:\"match\",editType:\"calc\"},range:{valType:\"info_array\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},editType:\"calc\"}});var SI=ye((ulr,Tge)=>{\"use strict\";Tge.exports={name:\"rangeslider\",containerClassName:\"rangeslider-container\",bgClassName:\"rangeslider-bg\",rangePlotClassName:\"rangeslider-rangeplot\",maskMinClassName:\"rangeslider-mask-min\",maskMaxClassName:\"rangeslider-mask-max\",slideBoxClassName:\"rangeslider-slidebox\",grabberMinClassName:\"rangeslider-grabber-min\",grabAreaMinClassName:\"rangeslider-grabarea-min\",handleMinClassName:\"rangeslider-handle-min\",grabberMaxClassName:\"rangeslider-grabber-max\",grabAreaMaxClassName:\"rangeslider-grabarea-max\",handleMaxClassName:\"rangeslider-handle-max\",maskMinOppAxisClassName:\"rangeslider-mask-min-opp-axis\",maskMaxOppAxisClassName:\"rangeslider-mask-max-opp-axis\",maskColor:\"rgba(0,0,0,0.4)\",maskOppAxisColor:\"rgba(0,0,0,0.2)\",slideBoxFill:\"transparent\",slideBoxCursor:\"ew-resize\",grabAreaFill:\"transparent\",grabAreaCursor:\"col-resize\",grabAreaWidth:10,handleWidth:4,handleRadius:1,handleStrokeWidth:1,extraPad:15}});var Mge=ye(EI=>{\"use strict\";var hmt=hf(),dmt=ru(),Age=SI(),vmt=$h().LINE_SPACING,MI=Age.name;function Sge(e){var t=e&&e[MI];return t&&t.visible}EI.isVisible=Sge;EI.makeData=function(e){for(var t=hmt.list({_fullLayout:e},\"x\",!0),r=e.margin,n=[],i=0;i<t.length;i++){var a=t[i];if(Sge(a)){n.push(a);var o=a[MI];o._id=MI+a._id,o._height=(e.height-r.b-r.t)*o.thickness,o._offsetShift=Math.floor(o.borderwidth/2)}}e._rangeSliderData=n};EI.autoMarginOpts=function(e,t){var r=e._fullLayout,n=t[MI],i=t._id.charAt(0),a=0,o=0;if(t.side===\"bottom\"&&(a=t._depth,t.title.text!==r._dfltTitle[i])){o=1.5*t.title.font.size+10+n._offsetShift;var s=(t.title.text.match(dmt.BR_TAG_ALL)||[]).length;o+=s*t.title.font.size*vmt}return{x:0,y:t._counterDomainMin,l:0,r:0,t:0,b:n._height+a+Math.max(r.margin.b,o),pad:Age.extraPad+n._offsetShift*2}}});var Lge=ye((flr,Cge)=>{\"use strict\";var kI=Dr(),Ege=vl(),kge=hf(),pmt=AI(),gmt=tV();Cge.exports=function(t,r,n){var i=t[n],a=r[n];if(!(i.rangeslider||r._requestRangeslider[a._id]))return;kI.isPlainObject(i.rangeslider)||(i.rangeslider={});var o=i.rangeslider,s=Ege.newContainer(a,\"rangeslider\");function l(L,x){return kI.coerce(o,s,pmt,L,x)}var u,c;function f(L,x){return kI.coerce(u,c,gmt,L,x)}var h=l(\"visible\");if(h){l(\"bgcolor\",r.plot_bgcolor),l(\"bordercolor\"),l(\"borderwidth\"),l(\"thickness\"),l(\"autorange\",!a.isValidRange(o.range)),l(\"range\");var d=r._subplots;if(d)for(var v=d.cartesian.filter(function(L){return L.substr(0,L.indexOf(\"y\"))===kge.name2id(n)}).map(function(L){return L.substr(L.indexOf(\"y\"),L.length)}),_=kI.simpleMap(v,kge.id2name),b=0;b<_.length;b++){var p=_[b];u=o[p]||{},c=Ege.newContainer(s,p,\"yaxis\");var k=r[p],E;u.range&&k.isValidRange(u.range)&&(E=\"fixed\");var S=f(\"rangemode\",E);S!==\"match\"&&f(\"range\",k.range.slice())}s._input=o}}});var Ige=ye((hlr,Pge)=>{\"use strict\";var mmt=hf().list,ymt=Tg().getAutoRange,_mt=SI();Pge.exports=function(t){for(var r=mmt(t,\"x\",!0),n=0;n<r.length;n++){var i=r[n],a=i[_mt.name];a&&a.visible&&a.autorange&&(a._input.autorange=!0,a._input.range=a.range=ymt(t,i))}}});var zge=ye((dlr,Fge)=>{\"use strict\";var CI=Oa(),xmt=qa(),bmt=Mc(),Jf=Dr(),LI=Jf.strTranslate,Dge=So(),x_=ka(),wmt=Eb(),Tmt=ph(),rV=hf(),Amt=yv(),Smt=Ag(),rl=SI();Fge.exports=function(e){for(var t=e._fullLayout,r=t._rangeSliderData,n=0;n<r.length;n++){var i=r[n][rl.name];i._clipId=i._id+\"-\"+t._uid}function a(s){return s._name}var o=t._infolayer.selectAll(\"g.\"+rl.containerClassName).data(r,a);o.exit().each(function(s){var l=s[rl.name];t._topdefs.select(\"#\"+l._clipId).remove()}).remove(),r.length!==0&&(o.enter().append(\"g\").classed(rl.containerClassName,!0).attr(\"pointer-events\",\"all\"),o.each(function(s){var l=CI.select(this),u=s[rl.name],c=t[rV.id2name(s.anchor)],f=u[rV.id2name(s.anchor)];if(u.range){var h=Jf.simpleMap(u.range,s.r2l),d=Jf.simpleMap(s.range,s.r2l),v;d[0]<d[1]?v=[Math.min(h[0],d[0]),Math.max(h[1],d[1])]:v=[Math.max(h[0],d[0]),Math.min(h[1],d[1])],u.range=u._input.range=Jf.simpleMap(v,s.l2r)}s.cleanRange(\"rangeslider.range\");var _=t._size,b=s.domain;u._width=_.w*(b[1]-b[0]);var p=Math.round(_.l+_.w*b[0]),k=Math.round(_.t+_.h*(1-s._counterDomainMin)+(s.side===\"bottom\"?s._depth:0)+u._offsetShift+rl.extraPad);l.attr(\"transform\",LI(p,k)),u._rl=Jf.simpleMap(u.range,s.r2l);var E=u._rl[0],S=u._rl[1],L=S-E;if(u.p2d=function(G){return G/u._width*L+E},u.d2p=function(G){return(G-E)/L*u._width},s.rangebreaks){var x=s.locateBreaks(E,S);if(x.length){var C,M,g=0;for(C=0;C<x.length;C++)M=x[C],g+=M.max-M.min;var P=u._width/(S-E-g),T=[-P*E];for(C=0;C<x.length;C++)M=x[C],T.push(T[T.length-1]-P*(M.max-M.min));for(u.d2p=function(G){for(var Z=T[0],H=0;H<x.length;H++){var N=x[H];if(G>=N.max)Z=T[H+1];else if(G<N.min)break}return Z+P*G},C=0;C<x.length;C++)M=x[C],M.pmin=u.d2p(M.min),M.pmax=u.d2p(M.max);u.p2d=function(G){for(var Z=T[0],H=0;H<x.length;H++){var N=x[H];if(G>=N.pmax)Z=T[H+1];else if(G<N.pmin)break}return(G-Z)/P}}}if(f.rangemode!==\"match\"){var z=c.r2l(f.range[0]),O=c.r2l(f.range[1]),V=O-z;u.d2pOppAxis=function(G){return(G-z)/V*u._height}}l.call(Cmt,e,s,u).call(Lmt,e,s,u).call(Pmt,e,s,u).call(Rmt,e,s,u,f).call(Dmt,e,s,u).call(Fmt,e,s,u),Mmt(l,e,s,u),kmt(l,e,s,u,c,f),s.side===\"bottom\"&&wmt.draw(e,s._id+\"title\",{propContainer:s,propName:s._name+\".title.text\",placeholder:t._dfltTitle.x,attributes:{x:s._offset+s._length/2,y:k+u._height+u._offsetShift+10+1.5*s.title.font.size,\"text-anchor\":\"middle\"}})}))};function Rge(e){return typeof e.clientX==\"number\"?e.clientX:e.touches&&e.touches.length>0?e.touches[0].clientX:0}function Mmt(e,t,r,n){if(t._context.staticPlot)return;var i=e.select(\"rect.\"+rl.slideBoxClassName).node(),a=e.select(\"rect.\"+rl.grabAreaMinClassName).node(),o=e.select(\"rect.\"+rl.grabAreaMaxClassName).node();function s(){var l=CI.event,u=l.target,c=Rge(l),f=c-e.node().getBoundingClientRect().left,h=n.d2p(r._rl[0]),d=n.d2p(r._rl[1]),v=Amt.coverSlip();this.addEventListener(\"touchmove\",_),this.addEventListener(\"touchend\",b),v.addEventListener(\"mousemove\",_),v.addEventListener(\"mouseup\",b);function _(p){var k=Rge(p),E=+k-c,S,L,x;switch(u){case i:if(x=\"ew-resize\",h+E>r._length||d+E<0)return;S=h+E,L=d+E;break;case a:if(x=\"col-resize\",h+E>r._length)return;S=h+E,L=d;break;case o:if(x=\"col-resize\",d+E<0)return;S=h,L=d+E;break;default:x=\"ew-resize\",S=f,L=f+E;break}if(L<S){var C=L;L=S,S=C}n._pixelMin=S,n._pixelMax=L,Smt(CI.select(v),x),Emt(e,t,r,n)}function b(){v.removeEventListener(\"mousemove\",_),v.removeEventListener(\"mouseup\",b),this.removeEventListener(\"touchmove\",_),this.removeEventListener(\"touchend\",b),Jf.removeElement(v)}}e.on(\"mousedown\",s),e.on(\"touchstart\",s)}function Emt(e,t,r,n){function i(s){return r.l2r(Jf.constrain(s,n._rl[0],n._rl[1]))}var a=i(n.p2d(n._pixelMin)),o=i(n.p2d(n._pixelMax));window.requestAnimationFrame(function(){xmt.call(\"_guiRelayout\",t,r._name+\".range\",[a,o])})}function kmt(e,t,r,n,i,a){var o=rl.handleWidth/2;function s(p){return Jf.constrain(p,0,n._width)}function l(p){return Jf.constrain(p,0,n._height)}function u(p){return Jf.constrain(p,-o,n._width+o)}var c=s(n.d2p(r._rl[0])),f=s(n.d2p(r._rl[1]));if(e.select(\"rect.\"+rl.slideBoxClassName).attr(\"x\",c).attr(\"width\",f-c),e.select(\"rect.\"+rl.maskMinClassName).attr(\"width\",c),e.select(\"rect.\"+rl.maskMaxClassName).attr(\"x\",f).attr(\"width\",n._width-f),a.rangemode!==\"match\"){var h=n._height-l(n.d2pOppAxis(i._rl[1])),d=n._height-l(n.d2pOppAxis(i._rl[0]));e.select(\"rect.\"+rl.maskMinOppAxisClassName).attr(\"x\",c).attr(\"height\",h).attr(\"width\",f-c),e.select(\"rect.\"+rl.maskMaxOppAxisClassName).attr(\"x\",c).attr(\"y\",d).attr(\"height\",n._height-d).attr(\"width\",f-c),e.select(\"rect.\"+rl.slideBoxClassName).attr(\"y\",h).attr(\"height\",d-h)}var v=.5,_=Math.round(u(c-o))-v,b=Math.round(u(f-o))+v;e.select(\"g.\"+rl.grabberMinClassName).attr(\"transform\",LI(_,v)),e.select(\"g.\"+rl.grabberMaxClassName).attr(\"transform\",LI(b,v))}function Cmt(e,t,r,n){var i=Jf.ensureSingle(e,\"rect\",rl.bgClassName,function(l){l.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})}),a=n.borderwidth%2===0?n.borderwidth:n.borderwidth-1,o=-n._offsetShift,s=Dge.crispRound(t,n.borderwidth);i.attr({width:n._width+a,height:n._height+a,transform:LI(o,o),\"stroke-width\":s}).call(x_.stroke,n.bordercolor).call(x_.fill,n.bgcolor)}function Lmt(e,t,r,n){var i=t._fullLayout,a=Jf.ensureSingleById(i._topdefs,\"clipPath\",n._clipId,function(o){o.append(\"rect\").attr({x:0,y:0})});a.select(\"rect\").attr({width:n._width,height:n._height})}function Pmt(e,t,r,n){var i=t.calcdata,a=e.selectAll(\"g.\"+rl.rangePlotClassName).data(r._subplotsWith,Jf.identity);a.enter().append(\"g\").attr(\"class\",function(s){return rl.rangePlotClassName+\" \"+s}).call(Dge.setClipUrl,n._clipId,t),a.order(),a.exit().remove();var o;a.each(function(s,l){var u=CI.select(this),c=l===0,f=rV.getFromId(t,s,\"y\"),h=f._name,d=n[h],v={data:[],layout:{xaxis:{type:r.type,domain:[0,1],range:n.range.slice(),calendar:r.calendar},width:n._width,height:n._height,margin:{t:0,b:0,l:0,r:0}},_context:t._context};r.rangebreaks&&(v.layout.xaxis.rangebreaks=r.rangebreaks),v.layout[h]={type:f.type,domain:[0,1],range:d.rangemode!==\"match\"?d.range.slice():f.range.slice(),calendar:f.calendar},f.rangebreaks&&(v.layout[h].rangebreaks=f.rangebreaks),bmt.supplyDefaults(v);var _=v._fullLayout.xaxis,b=v._fullLayout[h];_.clearCalc(),_.setScale(),b.clearCalc(),b.setScale();var p={id:s,plotgroup:u,xaxis:_,yaxis:b,isRangePlot:!0};c?o=p:(p.mainplot=\"xy\",p.mainplotinfo=o),Tmt.rangePlot(t,p,Imt(i,s))})}function Imt(e,t){for(var r=[],n=0;n<e.length;n++){var i=e[n],a=i[0].trace;a.xaxis+a.yaxis===t&&r.push(i)}return r}function Rmt(e,t,r,n,i){var a=Jf.ensureSingle(e,\"rect\",rl.maskMinClassName,function(u){u.attr({x:0,y:0,\"shape-rendering\":\"crispEdges\"})});a.attr(\"height\",n._height).call(x_.fill,rl.maskColor);var o=Jf.ensureSingle(e,\"rect\",rl.maskMaxClassName,function(u){u.attr({y:0,\"shape-rendering\":\"crispEdges\"})});if(o.attr(\"height\",n._height).call(x_.fill,rl.maskColor),i.rangemode!==\"match\"){var s=Jf.ensureSingle(e,\"rect\",rl.maskMinOppAxisClassName,function(u){u.attr({y:0,\"shape-rendering\":\"crispEdges\"})});s.attr(\"width\",n._width).call(x_.fill,rl.maskOppAxisColor);var l=Jf.ensureSingle(e,\"rect\",rl.maskMaxOppAxisClassName,function(u){u.attr({y:0,\"shape-rendering\":\"crispEdges\"})});l.attr(\"width\",n._width).style(\"border-top\",rl.maskOppBorder).call(x_.fill,rl.maskOppAxisColor)}}function Dmt(e,t,r,n){if(!t._context.staticPlot){var i=Jf.ensureSingle(e,\"rect\",rl.slideBoxClassName,function(a){a.attr({y:0,cursor:rl.slideBoxCursor,\"shape-rendering\":\"crispEdges\"})});i.attr({height:n._height,fill:rl.slideBoxFill})}}function Fmt(e,t,r,n){var i=Jf.ensureSingle(e,\"g\",rl.grabberMinClassName),a=Jf.ensureSingle(e,\"g\",rl.grabberMaxClassName),o={x:0,width:rl.handleWidth,rx:rl.handleRadius,fill:x_.background,stroke:x_.defaultLine,\"stroke-width\":rl.handleStrokeWidth,\"shape-rendering\":\"crispEdges\"},s={y:Math.round(n._height/4),height:Math.round(n._height/2)},l=Jf.ensureSingle(i,\"rect\",rl.handleMinClassName,function(d){d.attr(o)});l.attr(s);var u=Jf.ensureSingle(a,\"rect\",rl.handleMaxClassName,function(d){d.attr(o)});u.attr(s);var c={width:rl.grabAreaWidth,x:0,y:0,fill:rl.grabAreaFill,cursor:t._context.staticPlot?void 0:rl.grabAreaCursor},f=Jf.ensureSingle(i,\"rect\",rl.grabAreaMinClassName,function(d){d.attr(c)});f.attr(\"height\",n._height);var h=Jf.ensureSingle(a,\"rect\",rl.grabAreaMaxClassName,function(d){d.attr(c)});h.attr(\"height\",n._height)}});var qge=ye((vlr,Oge)=>{\"use strict\";var zmt=Dr(),Omt=AI(),qmt=tV(),iV=Mge();Oge.exports={moduleType:\"component\",name:\"rangeslider\",schema:{subplots:{xaxis:{rangeslider:zmt.extendFlat({},Omt,{yaxis:qmt})}}},layoutAttributes:AI(),handleDefaults:Lge(),calcAutorange:Ige(),draw:zge(),isVisible:iV.isVisible,makeData:iV.makeData,autoMarginOpts:iV.autoMarginOpts}});var PI=ye((plr,Nge)=>{\"use strict\";var 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nV=ye((glr,Uge)=>{\"use strict\";Uge.exports={yPad:.02,minButtonWidth:30,rx:3,ry:3,lightAmount:25,darkAmount:10}});var Hge=ye((mlr,Gge)=>{\"use strict\";var II=Dr(),Vmt=ka(),Gmt=vl(),Hmt=Yd(),Vge=PI(),aV=nV();Gge.exports=function(t,r,n,i,a){var o=t.rangeselector||{},s=Gmt.newContainer(r,\"rangeselector\");function l(d,v){return II.coerce(o,s,Vge,d,v)}var u=Hmt(o,s,{name:\"buttons\",handleItemDefaults:jmt,calendar:a}),c=l(\"visible\",u.length>0);if(c){var f=Wmt(r,n,i);l(\"x\",f[0]),l(\"y\",f[1]),II.noneOrAll(t,r,[\"x\",\"y\"]),l(\"xanchor\"),l(\"yanchor\"),II.coerceFont(l,\"font\",n.font);var h=l(\"bgcolor\");l(\"activecolor\",Vmt.contrast(h,aV.lightAmount,aV.darkAmount)),l(\"bordercolor\"),l(\"borderwidth\")}};function jmt(e,t,r,n){var i=n.calendar;function a(l,u){return II.coerce(e,t,Vge.buttons,l,u)}var o=a(\"visible\");if(o){var s=a(\"step\");s!==\"all\"&&(i&&i!==\"gregorian\"&&(s===\"month\"||s===\"year\")?t.stepmode=\"backward\":a(\"stepmode\"),a(\"count\")),a(\"label\")}}function 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Sme=ye((Clr,Ame)=>{\"use strict\";var f4=Dr(),Tme=mc().overrideAll,h4=hV(),Qb={error_x:f4.extendFlat({},h4),error_y:f4.extendFlat({},h4)};delete Qb.error_x.copy_zstyle;delete Qb.error_y.copy_zstyle;delete Qb.error_y.copy_ystyle;var d4={error_x:f4.extendFlat({},h4),error_y:f4.extendFlat({},h4),error_z:f4.extendFlat({},h4)};delete d4.error_x.copy_ystyle;delete d4.error_y.copy_ystyle;delete d4.error_z.copy_ystyle;delete d4.error_z.copy_zstyle;Ame.exports={moduleType:\"component\",name:\"errorbars\",schema:{traces:{scatter:Qb,bar:Qb,histogram:Qb,scatter3d:Tme(d4,\"calc\",\"nested\"),scattergl:Tme(Qb,\"calc\",\"nested\")}},supplyDefaults:fme(),calc:gme(),makeComputeError:dV(),plot:_me(),style:wme(),hoverInfo:Ayt};function Ayt(e,t,r){(t.error_y||{}).visible&&(r.yerr=e.yh-e.y,t.error_y.symmetric||(r.yerrneg=e.y-e.ys)),(t.error_x||{}).visible&&(r.xerr=e.xh-e.x,t.error_x.symmetric||(r.xerrneg=e.x-e.xs))}});var Eme=ye((Llr,Mme)=>{\"use strict\";Mme.exports={cn:{colorbar:\"colorbar\",cbbg:\"cbbg\",cbfill:\"cbfill\",cbfills:\"cbfills\",cbline:\"cbline\",cblines:\"cblines\",cbaxis:\"cbaxis\",cbtitleunshift:\"cbtitleunshift\",cbtitle:\"cbtitle\",cboutline:\"cboutline\",crisp:\"crisp\",jsPlaceholder:\"js-placeholder\"}}});var Dme=ye((Plr,Rme)=>{\"use strict\";var w_=Oa(),gV=cd(),OI=Mc(),kme=qa(),Dy=ho(),zI=yv(),B0=Dr(),Ug=B0.strTranslate,Ime=Ao().extendFlat,mV=Ag(),Ng=So(),yV=ka(),Syt=Eb(),Myt=ru(),Eyt=pv().flipScale,kyt=r4(),Cyt=lI(),Lyt=Rd(),_V=$h(),Cme=_V.LINE_SPACING,Lme=_V.FROM_TL,Pme=_V.FROM_BR,gf=Eme().cn;function Pyt(e){var t=e._fullLayout,r=t._infolayer.selectAll(\"g.\"+gf.colorbar).data(Iyt(e),function(n){return n._id});r.enter().append(\"g\").attr(\"class\",function(n){return n._id}).classed(gf.colorbar,!0),r.each(function(n){var i=w_.select(this);B0.ensureSingle(i,\"rect\",gf.cbbg),B0.ensureSingle(i,\"g\",gf.cbfills),B0.ensureSingle(i,\"g\",gf.cblines),B0.ensureSingle(i,\"g\",gf.cbaxis,function(o){o.classed(gf.crisp,!0)}),B0.ensureSingle(i,\"g\",gf.cbtitleunshift,function(o){o.append(\"g\").classed(gf.cbtitle,!0)}),B0.ensureSingle(i,\"rect\",gf.cboutline);var a=Ryt(i,n,e);a&&a.then&&(e._promises||[]).push(a),e._context.edits.colorbarPosition&&Dyt(i,n,e)}),r.exit().each(function(n){OI.autoMargin(e,n._id)}).remove(),r.order()}function Iyt(e){var t=e._fullLayout,r=e.calcdata,n=[],i,a,o,s;function l(E){return Ime(E,{_fillcolor:null,_line:{color:null,width:null,dash:null},_levels:{start:null,end:null,size:null},_filllevels:null,_fillgradient:null,_zrange:null})}function u(){typeof s.calc==\"function\"?s.calc(e,o,i):(i._fillgradient=a.reversescale?Eyt(a.colorscale):a.colorscale,i._zrange=[a[s.min],a[s.max]])}for(var c=0;c<r.length;c++){var f=r[c];if(o=f[0].trace,!!o._module){var h=o._module.colorbar;if(o.visible===!0&&h)for(var d=Array.isArray(h),v=d?h:[h],_=0;_<v.length;_++){s=v[_];var b=s.container;a=b?o[b]:o,a&&a.showscale&&(i=l(a.colorbar),i._id=\"cb\"+o.uid+(d&&b?\"-\"+b:\"\"),i._traceIndex=o.index,i._propPrefix=(b?b+\".\":\"\")+\"colorbar.\",i._meta=o._meta,u(),n.push(i))}}}for(var p in t._colorAxes)if(a=t[p],a.showscale){var k=t._colorAxes[p];i=l(a.colorbar),i._id=\"cb\"+p,i._propPrefix=p+\".colorbar.\",i._meta=t._meta,s={min:\"cmin\",max:\"cmax\"},k[0]!==\"heatmap\"&&(o=k[1],s.calc=o._module.colorbar.calc),u(),n.push(i)}return n}function Ryt(e,t,r){var n=t.orientation===\"v\",i=t.len,a=t.lenmode,o=t.thickness,s=t.thicknessmode,l=t.outlinewidth,u=t.borderwidth,c=t.bgcolor,f=t.xanchor,h=t.yanchor,d=t.xpad,v=t.ypad,_=t.x,b=n?t.y:1-t.y,p=t.yref===\"paper\",k=t.xref===\"paper\",E=r._fullLayout,S=E._size,L=t._fillcolor,x=t._line,C=t.title,M=C.side,g=t._zrange||w_.extent((typeof L==\"function\"?L:x.color).domain()),P=typeof x.color==\"function\"?x.color:function(){return x.color},T=typeof L==\"function\"?L:function(){return L},z=t._levels,O=Fyt(r,t,g),V=O.fill,G=O.line,Z=Math.round(o*(s===\"fraction\"?n?S.w:S.h:1)),H=Z/(n?S.w:S.h),N=Math.round(i*(a===\"fraction\"?n?S.h:S.w:1)),j=N/(n?S.h:S.w),re=k?S.w:r._fullLayout.width,oe=p?S.h:r._fullLayout.height,_e=Math.round(n?_*re+d:b*oe+v),Ee={center:.5,right:1}[f]||0,Ce={top:1,middle:.5}[h]||0,me=n?_-Ee*H:b-Ce*H,ie=n?b-Ce*j:_-Ee*j,Se=Math.round(n?oe*(1-ie):re*ie);t._lenFrac=j,t._thickFrac=H,t._uFrac=me,t._vFrac=ie;var Le=t._axis=zyt(r,t,g);Le.position=H+(n?_+d/S.w:b+v/S.h);var Ae=[\"top\",\"bottom\"].indexOf(M)!==-1;if(n&&Ae&&(Le.title.side=M,Le.titlex=_+d/S.w,Le.titley=ie+(C.side===\"top\"?j-v/S.h:v/S.h)),!n&&!Ae&&(Le.title.side=M,Le.titley=b+v/S.h,Le.titlex=ie+d/S.w),x.color&&t.tickmode===\"auto\"){Le.tickmode=\"linear\",Le.tick0=z.start;var Fe=z.size,Pe=B0.constrain(N/50,4,15)+1,ge=(g[1]-g[0])/((t.nticks||Pe)*Fe);if(ge>1){var Re=Math.pow(10,Math.floor(Math.log(ge)/Math.LN10));Fe*=Re*B0.roundUp(ge/Re,[2,5,10]),(Math.abs(z.start)/z.size+1e-6)%1<2e-6&&(Le.tick0=0)}Le.dtick=Fe}Le.domain=n?[ie+v/S.h,ie+j-v/S.h]:[ie+d/S.w,ie+j-d/S.w],Le.setScale(),e.attr(\"transform\",Ug(Math.round(S.l),Math.round(S.t)));var ce=e.select(\".\"+gf.cbtitleunshift).attr(\"transform\",Ug(-Math.round(S.l),-Math.round(S.t))),Ze=Le.ticklabelposition,ut=Le.title.font.size,pt=e.select(\".\"+gf.cbaxis),Zt,st=0,lt=0;function Gt(cr,$e){var St={propContainer:Le,propName:t._propPrefix+\"title.text\",traceIndex:t._traceIndex,_meta:t._meta,placeholder:E._dfltTitle.colorbar,containerGroup:e.select(\".\"+gf.cbtitle)},Qt=cr.charAt(0)===\"h\"?cr.substr(1):\"h\"+cr;e.selectAll(\".\"+Qt+\",.\"+Qt+\"-math-group\").remove(),Syt.draw(r,cr,Ime(St,$e||{}))}function Nt(){if(n&&Ae||!n&&!Ae){var cr,$e;M===\"top\"&&(cr=d+S.l+re*_,$e=v+S.t+oe*(1-ie-j)+3+ut*.75),M===\"bottom\"&&(cr=d+S.l+re*_,$e=v+S.t+oe*(1-ie)-3-ut*.25),M===\"right\"&&($e=v+S.t+oe*b+3+ut*.75,cr=d+S.l+re*ie),Gt(Le._id+\"title\",{attributes:{x:cr,y:$e,\"text-anchor\":n?\"start\":\"middle\"}})}}function Jt(){if(n&&!Ae||!n&&Ae){var cr=Le.position||0,$e=Le._offset+Le._length/2,St,Qt;if(M===\"right\")Qt=$e,St=S.l+re*cr+10+ut*(Le.showticklabels?1:.5);else if(St=$e,M===\"bottom\"&&(Qt=S.t+oe*cr+10+(Ze.indexOf(\"inside\")===-1?Le.tickfont.size:0)+(Le.ticks!==\"inside\"&&t.ticklen||0)),M===\"top\"){var Vt=C.text.split(\"<br>\").length;Qt=S.t+oe*cr+10-Z-Cme*ut*Vt}Gt((n?\"h\":\"v\")+Le._id+\"title\",{avoid:{selection:w_.select(r).selectAll(\"g.\"+Le._id+\"tick\"),side:M,offsetTop:n?0:S.t,offsetLeft:n?S.l:0,maxShift:n?E.width:E.height},attributes:{x:St,y:Qt,\"text-anchor\":\"middle\"},transform:{rotate:n?-90:0,offset:0}})}}function sr(){if(!n&&!Ae||n&&Ae){var cr=e.select(\".\"+gf.cbtitle),$e=cr.select(\"text\"),St=[-l/2,l/2],Qt=cr.select(\".h\"+Le._id+\"title-math-group\").node(),Vt=15.6;$e.node()&&(Vt=parseInt($e.node().style.fontSize,10)*Cme);var _t;if(Qt?(_t=Ng.bBox(Qt),lt=_t.width,st=_t.height,st>Vt&&(St[1]-=(st-Vt)/2)):$e.node()&&!$e.classed(gf.jsPlaceholder)&&(_t=Ng.bBox($e.node()),lt=_t.width,st=_t.height),n){if(st){if(st+=5,M===\"top\")Le.domain[1]-=st/S.h,St[1]*=-1;else{Le.domain[0]+=st/S.h;var It=Myt.lineCount($e);St[1]+=(1-It)*Vt}cr.attr(\"transform\",Ug(St[0],St[1])),Le.setScale()}}else lt&&(M===\"right\"&&(Le.domain[0]+=(lt+ut/2)/S.w),cr.attr(\"transform\",Ug(St[0],St[1])),Le.setScale())}e.selectAll(\".\"+gf.cbfills+\",.\"+gf.cblines).attr(\"transform\",n?Ug(0,Math.round(S.h*(1-Le.domain[1]))):Ug(Math.round(S.w*Le.domain[0]),0)),pt.attr(\"transform\",n?Ug(0,Math.round(-S.t)):Ug(Math.round(-S.l),0));var mt=e.select(\".\"+gf.cbfills).selectAll(\"rect.\"+gf.cbfill).attr(\"style\",\"\").data(V);mt.enter().append(\"rect\").classed(gf.cbfill,!0).attr(\"style\",\"\"),mt.exit().remove();var er=g.map(Le.c2p).map(Math.round).sort(function(Br,Vr){return Br-Vr});mt.each(function(Br,Vr){var dt=[Vr===0?g[0]:(V[Vr]+V[Vr-1])/2,Vr===V.length-1?g[1]:(V[Vr]+V[Vr+1])/2].map(Le.c2p).map(Math.round);n&&(dt[1]=B0.constrain(dt[1]+(dt[1]>dt[0])?1:-1,er[0],er[1]));var Ge=w_.select(this).attr(n?\"x\":\"y\",_e).attr(n?\"y\":\"x\",w_.min(dt)).attr(n?\"width\":\"height\",Math.max(Z,2)).attr(n?\"height\":\"width\",Math.max(w_.max(dt)-w_.min(dt),2));if(t._fillgradient)Ng.gradient(Ge,r,t._id,n?\"vertical\":\"horizontalreversed\",t._fillgradient,\"fill\");else{var Je=T(Br).replace(\"e-\",\"\");Ge.attr(\"fill\",gV(Je).toHexString())}});var lr=e.select(\".\"+gf.cblines).selectAll(\"path.\"+gf.cbline).data(x.color&&x.width?G:[]);lr.enter().append(\"path\").classed(gf.cbline,!0),lr.exit().remove(),lr.each(function(Br){var Vr=_e,dt=Math.round(Le.c2p(Br))+x.width/2%1;w_.select(this).attr(\"d\",\"M\"+(n?Vr+\",\"+dt:dt+\",\"+Vr)+(n?\"h\":\"v\")+Z).call(Ng.lineGroupStyle,x.width,P(Br),x.dash)}),pt.selectAll(\"g.\"+Le._id+\"tick,path\").remove();var Tr=_e+Z+(l||0)/2-(t.ticks===\"outside\"?1:0),Lr=Dy.calcTicks(Le),ti=Dy.getTickSigns(Le)[2];return Dy.drawTicks(r,Le,{vals:Le.ticks===\"inside\"?Dy.clipEnds(Le,Lr):Lr,layer:pt,path:Dy.makeTickPath(Le,Tr,ti),transFn:Dy.makeTransTickFn(Le)}),Dy.drawLabels(r,Le,{vals:Lr,layer:pt,transFn:Dy.makeTransTickLabelFn(Le),labelFns:Dy.makeLabelFns(Le,Tr)})}function wr(){var cr,$e=Z+l/2;Ze.indexOf(\"inside\")===-1&&(cr=Ng.bBox(pt.node()),$e+=n?cr.width:cr.height),Zt=ce.select(\"text\");var St=0,Qt=n&&M===\"top\",Vt=!n&&M===\"right\",_t=0;if(Zt.node()&&!Zt.classed(gf.jsPlaceholder)){var It,mt=ce.select(\".h\"+Le._id+\"title-math-group\").node();mt&&(n&&Ae||!n&&!Ae)?(cr=Ng.bBox(mt),St=cr.width,It=cr.height):(cr=Ng.bBox(ce.node()),St=cr.right-S.l-(n?_e:Se),It=cr.bottom-S.t-(n?Se:_e),!n&&M===\"top\"&&($e+=cr.height,_t=cr.height)),Vt&&(Zt.attr(\"transform\",Ug(St/2+ut/2,0)),St*=2),$e=Math.max($e,n?St:It)}var er=(n?d:v)*2+$e+u+l/2,lr=0;!n&&C.text&&h===\"bottom\"&&b<=0&&(lr=er/2,er+=lr,_t+=lr),E._hColorbarMoveTitle=lr,E._hColorbarMoveCBTitle=_t;var Tr=u+l,Lr=(n?_e:Se)-Tr/2-(n?d:0),ti=(n?Se:_e)-(n?N:v+_t-lr);e.select(\".\"+gf.cbbg).attr(\"x\",Lr).attr(\"y\",ti).attr(n?\"width\":\"height\",Math.max(er-lr,2)).attr(n?\"height\":\"width\",Math.max(N+Tr,2)).call(yV.fill,c).call(yV.stroke,t.bordercolor).style(\"stroke-width\",u);var Br=Vt?Math.max(St-10,0):0;e.selectAll(\".\"+gf.cboutline).attr(\"x\",(n?_e:Se+d)+Br).attr(\"y\",(n?Se+v-N:_e)+(Qt?st:0)).attr(n?\"width\":\"height\",Math.max(Z,2)).attr(n?\"height\":\"width\",Math.max(N-(n?2*v+st:2*d+Br),2)).call(yV.stroke,t.outlinecolor).style({fill:\"none\",\"stroke-width\":l});var Vr=n?Ee*er:0,dt=n?0:(1-Ce)*er-_t;if(Vr=k?S.l-Vr:-Vr,dt=p?S.t-dt:-dt,e.attr(\"transform\",Ug(Vr,dt)),!n&&(u||gV(c).getAlpha()&&!gV.equals(E.paper_bgcolor,c))){var Ge=pt.selectAll(\"text\"),Je=Ge[0].length,je=e.select(\".\"+gf.cbbg).node(),tt=Ng.bBox(je),xt=Ng.getTranslate(e),Ie=2;Ge.each(function(di,ji){var In=0,wi=Je-1;if(ji===In||ji===wi){var On=Ng.bBox(this),qn=Ng.getTranslate(this),Fn;if(ji===wi){var ra=On.right+qn.x,la=tt.right+xt.x+Se-u-Ie+_;Fn=la-ra,Fn>0&&(Fn=0)}else if(ji===In){var Ut=On.left+qn.x,wt=tt.left+xt.x+Se+u+Ie;Fn=wt-Ut,Fn<0&&(Fn=0)}Fn&&(Je<3?this.setAttribute(\"transform\",\"translate(\"+Fn+\",0) \"+this.getAttribute(\"transform\")):this.setAttribute(\"visibility\",\"hidden\"))}})}var xe={},ke=Lme[f],vt=Pme[f],ir=Lme[h],ar=Pme[h],vr=er-Z;n?(a===\"pixels\"?(xe.y=b,xe.t=N*ir,xe.b=N*ar):(xe.t=xe.b=0,xe.yt=b+i*ir,xe.yb=b-i*ar),s===\"pixels\"?(xe.x=_,xe.l=er*ke,xe.r=er*vt):(xe.l=vr*ke,xe.r=vr*vt,xe.xl=_-o*ke,xe.xr=_+o*vt)):(a===\"pixels\"?(xe.x=_,xe.l=N*ke,xe.r=N*vt):(xe.l=xe.r=0,xe.xl=_+i*ke,xe.xr=_-i*vt),s===\"pixels\"?(xe.y=1-b,xe.t=er*ir,xe.b=er*ar):(xe.t=vr*ir,xe.b=vr*ar,xe.yt=b-o*ir,xe.yb=b+o*ar));var ii=t.y<.5?\"b\":\"t\",pi=t.x<.5?\"l\":\"r\";r._fullLayout._reservedMargin[t._id]={};var $r={r:E.width-Lr-Vr,l:Lr+xe.r,b:E.height-ti-dt,t:ti+xe.b};k&&p?OI.autoMargin(r,t._id,xe):k?r._fullLayout._reservedMargin[t._id][ii]=$r[ii]:p||n?r._fullLayout._reservedMargin[t._id][pi]=$r[pi]:r._fullLayout._reservedMargin[t._id][ii]=$r[ii]}return B0.syncOrAsync([OI.previousPromises,Nt,sr,Jt,OI.previousPromises,wr],r)}function Dyt(e,t,r){var n=t.orientation===\"v\",i=r._fullLayout,a=i._size,o,s,l;zI.init({element:e.node(),gd:r,prepFn:function(){o=e.attr(\"transform\"),mV(e)},moveFn:function(u,c){e.attr(\"transform\",o+Ug(u,c)),s=zI.align((n?t._uFrac:t._vFrac)+u/a.w,n?t._thickFrac:t._lenFrac,0,1,t.xanchor),l=zI.align((n?t._vFrac:1-t._uFrac)-c/a.h,n?t._lenFrac:t._thickFrac,0,1,t.yanchor);var f=zI.getCursor(s,l,t.xanchor,t.yanchor);mV(e,f)},doneFn:function(){if(mV(e),s!==void 0&&l!==void 0){var u={};u[t._propPrefix+\"x\"]=s,u[t._propPrefix+\"y\"]=l,t._traceIndex!==void 0?kme.call(\"_guiRestyle\",r,u,t._traceIndex):kme.call(\"_guiRelayout\",r,u)}}})}function Fyt(e,t,r){var n=t._levels,i=[],a=[],o,s,l=n.end+n.size/100,u=n.size,c=1.001*r[0]-.001*r[1],f=1.001*r[1]-.001*r[0];for(s=0;s<1e5&&(o=n.start+s*u,!(u>0?o>=l:o<=l));s++)o>c&&o<f&&i.push(o);if(t._fillgradient)a=[0];else if(typeof t._fillcolor==\"function\"){var h=t._filllevels;if(h)for(l=h.end+h.size/100,u=h.size,s=0;s<1e5&&(o=h.start+s*u,!(u>0?o>=l:o<=l));s++)o>r[0]&&o<r[1]&&a.push(o);else a=i.map(function(d){return d-n.size/2}),a.push(a[a.length-1]+n.size)}else t._fillcolor&&typeof t._fillcolor==\"string\"&&(a=[0]);return n.size<0&&(i.reverse(),a.reverse()),{line:i,fill:a}}function zyt(e,t,r){var n=e._fullLayout,i=t.orientation===\"v\",a={type:\"linear\",range:r,tickmode:t.tickmode,nticks:t.nticks,tick0:t.tick0,dtick:t.dtick,tickvals:t.tickvals,ticktext:t.ticktext,ticks:t.ticks,ticklen:t.ticklen,tickwidth:t.tickwidth,tickcolor:t.tickcolor,showticklabels:t.showticklabels,labelalias:t.labelalias,ticklabelposition:t.ticklabelposition,ticklabeloverflow:t.ticklabeloverflow,ticklabelstep:t.ticklabelstep,tickfont:t.tickfont,tickangle:t.tickangle,tickformat:t.tickformat,exponentformat:t.exponentformat,minexponent:t.minexponent,separatethousands:t.separatethousands,showexponent:t.showexponent,showtickprefix:t.showtickprefix,tickprefix:t.tickprefix,showticksuffix:t.showticksuffix,ticksuffix:t.ticksuffix,title:t.title,showline:!0,anchor:\"free\",side:i?\"right\":\"bottom\",position:1},o=i?\"y\":\"x\",s={type:\"linear\",_id:o+t._id},l={letter:o,font:n.font,noAutotickangles:o===\"y\",noHover:!0,noTickson:!0,noTicklabelmode:!0,noInsideRange:!0,calendar:n.calendar};function u(c,f){return 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Y1t(e,t,r,n,i,a){var o=!!a.isHorizontal,s=!!a.constrained,l=a.angle||0,u=i.width,c=i.height,f=Math.abs(t-e),h=Math.abs(n-r),d;o?d=h>2*Gv?Gv:0:d=f>2*Gv?Gv:0;var v=1;s&&(v=o?Math.min(1,h/c):Math.min(1,f/u));var _=jye(l),b=Wye(i,_),p=(o?b.x:b.y)/2,k=(i.left+i.right)/2,E=(i.top+i.bottom)/2,S=(e+t)/2,L=(r+n)/2,x=0,C=0,M=o?Pm(t,e):Pm(r,n);return o?(S=t-M*d,x=M*p):(L=n+M*d,C=-M*p),{textX:k,textY:E,targetX:S,targetY:L,anchorX:x,anchorY:C,scale:v,rotate:_}}function K1t(e,t,r,n,i){var a=t[0].trace,o=a.texttemplate,s;return o?s=$1t(e,t,r,n,i):a.textinfo?s=Q1t(t,r,n,i):s=ST.getValue(a.text,r),ST.coerceString(N1t,s)}function J1t(e,t){var r=ST.getValue(e.textposition,t);return ST.coerceEnumerated(U1t,r)}function $1t(e,t,r,n,i){var a=t[0].trace,o=Fd.castOption(a,r,\"texttemplate\");if(!o)return\"\";var s=a.type===\"histogram\",l=a.type===\"waterfall\",u=a.type===\"funnel\",c=a.orientation===\"h\",f,h,d,v;c?(f=\"y\",h=i,d=\"x\",v=n):(f=\"x\",h=n,d=\"y\",v=i);function _(x){return 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L.q1=gh.interp(C,.25),L.q3=gh.interp(C,.75);L.lf=x1e(L,C,M),L.uf=b1e(L,C,M),L.lo=w1e(L),L.uo=T1e(L);var pt=A1e(L,M);L.ln=L.med-pt,L.un=L.med+pt,Fe=Math.min(Fe,L.ln),Pe=Math.max(Pe,L.un),L.pts2=x.filter(T),o.push(L)}r.notched&&gh.isTypedArray(me)&&(me=Array.from(me)),r._extremes[c._id]=ZI.findExtremes(c,r.notched?me.concat([Fe,Pe]):me,{padded:!0})}return A_t(o,r),o.length>0?(o[0].t={num:n[s],dPos:S,posLetter:d,valLetter:f,labels:{med:Oy(t,\"median:\"),min:Oy(t,\"min:\"),q1:Oy(t,\"q1:\"),q3:Oy(t,\"q3:\"),max:Oy(t,\"max:\"),mean:r.boxmean===\"sd\"||r.sizemode===\"sd\"?Oy(t,\"mean \\xB1 \\u03C3:\").replace(\"\\u03C3\",r.sdmultiple===1?\"\\u03C3\":r.sdmultiple+\"\\u03C3\"):Oy(t,\"mean:\"),lf:Oy(t,\"lower fence:\"),uf:Oy(t,\"upper fence:\")}},n[s]++,o):[{t:{empty:!0}}]};function b_t(e,t,r,n){var i=t in e,a=t+\"0\"in e,o=\"d\"+t in e;if(i||a&&o){var s=r.makeCalcdata(e,t),l=x_t(e,r,t,s).vals;return[l,s]}var u;a?u=e[t+\"0\"]:\"name\"in e&&(r.type===\"category\"||IV(e.name)&&[\"linear\",\"log\"].indexOf(r.type)!==-1||gh.isDateTime(e.name)&&r.type===\"date\")?u=e.name:u=n;for(var c=r.type===\"multicategory\"?r.r2c_just_indices(u):r.d2c(u,0,e[t+\"calendar\"]),f=e._length,h=new Array(f),d=0;d<f;d++)h[d]=c;return[h]}function w_t(e,t){for(var r=e.length,n=new Array(r+1),i=0;i<r;i++)n[i]=e[i]-t;return n[r]=e[r-1]+t,n}function T_t(e){for(var t=new Array(e),r=0;r<e;r++)t[r]=[];return t}var PV={text:\"tx\",hovertext:\"htx\"};function m1e(e,t,r){for(var n in PV)gh.isArrayOrTypedArray(t[n])&&(Array.isArray(r)?gh.isArrayOrTypedArray(t[n][r[0]])&&(e[PV[n]]=t[n][r[0]][r[1]]):e[PV[n]]=t[n][r])}function A_t(e,t){if(gh.isArrayOrTypedArray(t.selectedpoints))for(var r=0;r<e.length;r++){for(var n=e[r].pts||[],i={},a=0;a<n.length;a++)i[n[a].i]=a;gh.tagSelected(n,t,i)}}function y1e(e,t){return e.v-t.v}function _1e(e){return e.v}function x1e(e,t,r){return 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a=r.orientation===\"h\",o=t.val,s=t.pos,l=!!s.rangebreaks,u=n.bPos,c=n.wdPos||0,f=n.bPosPxOffset||0,h=r.whiskerwidth||0,d=r.showwhiskers!==!1,v=r.notched||!1,_=v?1-2*r.notchwidth:1,b,p;Array.isArray(n.bdPos)?(b=n.bdPos[0],p=n.bdPos[1]):(b=n.bdPos,p=n.bdPos);var k=e.selectAll(\"path.box\").data(r.type!==\"violin\"||r.box.visible?a2.identity:[]);k.enter().append(\"path\").style(\"vector-effect\",i?\"none\":\"non-scaling-stroke\").attr(\"class\",\"box\"),k.exit().remove(),k.each(function(E){if(E.empty)return CT.select(this).attr(\"d\",\"M0,0Z\");var S=s.c2l(E.pos+u,!0),L=s.l2p(S-b)+f,x=s.l2p(S+p)+f,C=l?(L+x)/2:s.l2p(S)+f,M=r.whiskerwidth,g=l?L*M+(1-M)*C:s.l2p(S-c)+f,P=l?x*M+(1-M)*C:s.l2p(S+c)+f,T=s.l2p(S-b*_)+f,z=s.l2p(S+p*_)+f,O=r.sizemode===\"sd\",V=o.c2p(O?E.mean-E.sd:E.q1,!0),G=O?o.c2p(E.mean+E.sd,!0):o.c2p(E.q3,!0),Z=a2.constrain(O?o.c2p(E.mean,!0):o.c2p(E.med,!0),Math.min(V,G)+1,Math.max(V,G)-1),H=E.lf===void 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h.forEach(function(d){d.t=n,d.trace=r}),h},c=e.selectAll(\"g.points\").data(l?u:[]);c.enter().append(\"g\").attr(\"class\",\"points\"),c.exit().remove();var f=c.selectAll(\"path\").data(function(h){var d,v=h.pts2,_=Math.max((h.max-h.min)/10,h.q3-h.q1),b=_*1e-9,p=_*C_t,k=[],E=0,S;if(r.jitter){if(_===0)for(E=1,k=new Array(v.length),d=0;d<v.length;d++)k[d]=1;else for(d=0;d<v.length;d++){var L=Math.max(0,d-L1e),x=v[L].v,C=Math.min(v.length-1,d+L1e),M=v[C].v;l!==\"all\"&&(v[d].v<h.lf?M=Math.min(M,h.lf):x=Math.max(x,h.uf));var g=Math.sqrt(p*(C-L)/(M-x+b))||0;g=a2.constrain(Math.abs(g),0,1),k.push(g),E=Math.max(g,E)}S=r.jitter*2/(E||1)}for(d=0;d<v.length;d++){var P=v[d],T=P.v,z=r.jitter?S*k[d]*(a2.pseudoRandom()-.5):0,O=h.pos+s+o*(r.pointpos+z);r.orientation===\"h\"?(P.y=O,P.x=T):(P.x=O,P.y=T),l===\"suspectedoutliers\"&&T<h.uo&&T>h.lo&&(P.so=!0)}return v});f.enter().append(\"path\").classed(\"point\",!0),f.exit().remove(),f.call(k_t.translatePoints,i,a)}function R1e(e,t,r,n){var i=t.val,a=t.pos,o=!!a.rangebreaks,s=n.bPos,l=n.bPosPxOffset||0,u=r.boxmean||(r.meanline||{}).visible,c,f;Array.isArray(n.bdPos)?(c=n.bdPos[0],f=n.bdPos[1]):(c=n.bdPos,f=n.bdPos);var h=e.selectAll(\"path.mean\").data(r.type===\"box\"&&r.boxmean||r.type===\"violin\"&&r.box.visible&&r.meanline.visible?a2.identity:[]);h.enter().append(\"path\").attr(\"class\",\"mean\").style({fill:\"none\",\"vector-effect\":\"non-scaling-stroke\"}),h.exit().remove(),h.each(function(d){var v=a.c2l(d.pos+s,!0),_=a.l2p(v-c)+l,b=a.l2p(v+f)+l,p=o?(_+b)/2:a.l2p(v)+l,k=i.c2p(d.mean,!0),E=i.c2p(d.mean-d.sd,!0),S=i.c2p(d.mean+d.sd,!0);r.orientation===\"h\"?CT.select(this).attr(\"d\",\"M\"+k+\",\"+_+\"V\"+b+(u===\"sd\"?\"m0,0L\"+E+\",\"+p+\"L\"+k+\",\"+_+\"L\"+S+\",\"+p+\"Z\":\"\")):CT.select(this).attr(\"d\",\"M\"+_+\",\"+k+\"H\"+b+(u===\"sd\"?\"m0,0L\"+p+\",\"+E+\"L\"+_+\",\"+k+\"L\"+p+\",\"+S+\"Z\":\"\"))})}D1e.exports={plot:L_t,plotBoxAndWhiskers:P1e,plotPoints:I1e,plotBoxMean:R1e}});var JI=ye((fur,F1e)=>{\"use 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i,a,o,s,l;for(r=r||.01,n=n||.01,o=0;o<t.length;o++){for(s=t[o],l=0;l<s.starts.length;l++)a=s.starts[l],ube(s,a,\"edge\",r,n);for(i=0;Object.keys(s.crossings).length&&i<1e4;)i++,a=Object.keys(s.crossings)[0].split(\",\").map(Number),ube(s,a,void 0,r,n);i===1e4&&M8.log(\"Infinite loop in contour?\")}};function P4(e,t,r,n){return Math.abs(e[0]-t[0])<r&&Math.abs(e[1]-t[1])<n}function Mbt(e,t){var r=e[2]-t[2],n=e[3]-t[3];return Math.sqrt(r*r+n*n)}function ube(e,t,r,n,i){var a=t.join(\",\"),o=e.crossings[a],s=Ebt(o,r,t),l=[cbe(e,t,[-s[0],-s[1]])],u=e.z.length,c=e.z[0].length,f=t.slice(),h=s.slice(),d;for(d=0;d<1e4;d++){if(o>20?(o=zT.CHOOSESADDLE[o][(s[0]||s[1])<0?0:1],e.crossings[a]=zT.SADDLEREMAINDER[o]):delete e.crossings[a],s=zT.NEWDELTA[o],!s){M8.log(\"Found bad marching index:\",o,t,e.level);break}l.push(cbe(e,t,s)),t[0]+=s[0],t[1]+=s[1],a=t.join(\",\"),P4(l[l.length-1],l[l.length-2],n,i)&&l.pop();var v=s[0]&&(t[0]<0||t[0]>c-2)||s[1]&&(t[1]<0||t[1]>u-2),_=t[0]===f[0]&&t[1]===f[1]&&s[0]===h[0]&&s[1]===h[1];if(_||r&&v)break;o=e.crossings[a]}d===1e4&&M8.log(\"Infinite loop in contour?\");var b=P4(l[0],l[l.length-1],n,i),p=0,k=.2*e.smoothing,E=[],S=0,L,x,C,M,g,P,T,z,O,V,G;for(d=1;d<l.length;d++)T=Mbt(l[d],l[d-1]),p+=T,E.push(T);var Z=p/E.length*k;function H(re){return l[re%l.length]}for(d=l.length-2;d>=S;d--)if(L=E[d],L<Z){for(C=0,x=d-1;x>=S&&L+E[x]<Z;x--)L+=E[x];if(b&&d===l.length-2)for(C=0;C<x&&L+E[C]<Z;C++)L+=E[C];g=d-x+C+1,P=Math.floor((d+x+C+2)/2),!b&&d===l.length-2?M=l[l.length-1]:!b&&x===-1?M=l[0]:g%2?M=H(P):M=[(H(P)[0]+H(P+1)[0])/2,(H(P)[1]+H(P+1)[1])/2],l.splice(x+1,d-x+1,M),d=x+1,C&&(S=C),b&&(d===l.length-2?l[C]=l[l.length-1]:d===0&&(l[l.length-1]=l[0]))}for(l.splice(0,S),d=0;d<l.length;d++)l[d].length=2;if(!(l.length<2))if(b)l.pop(),e.paths.push(l);else{r||M8.log(\"Unclosed interior contour?\",e.level,f.join(\",\"),l.join(\"L\"));var N=!1;for(z=0;z<e.edgepaths.length;z++)if(V=e.edgepaths[z],!N&&P4(V[0],l[l.length-1],n,i)){l.pop(),N=!0;var j=!1;for(O=0;O<e.edgepaths.length;O++)if(G=e.edgepaths[O],P4(G[G.length-1],l[0],n,i)){j=!0,l.shift(),e.edgepaths.splice(z,1),O===z?e.paths.push(l.concat(G)):(O>z&&O--,e.edgepaths[O]=G.concat(l,V));break}j||(e.edgepaths[z]=l.concat(V))}for(z=0;z<e.edgepaths.length&&!N;z++)V=e.edgepaths[z],P4(V[V.length-1],l[0],n,i)&&(l.shift(),e.edgepaths[z]=V.concat(l),N=!0);N||e.edgepaths.push(l)}}function Ebt(e,t,r){var n=0,i=0;return e>20&&t?e===208||e===1114?n=r[0]===0?1:-1:i=r[1]===0?1:-1:zT.BOTTOMSTART.indexOf(e)!==-1?i=1:zT.LEFTSTART.indexOf(e)!==-1?n=1:zT.TOPSTART.indexOf(e)!==-1?i=-1:n=-1,[n,i]}function cbe(e,t,r){var n=t[0]+Math.max(r[0],0),i=t[1]+Math.max(r[1],0),a=e.z[i][n],o=e.xaxis,s=e.yaxis;if(r[1]){var l=(e.level-a)/(e.z[i][n+1]-a),u=(l!==1?(1-l)*o.c2l(e.x[n]):0)+(l!==0?l*o.c2l(e.x[n+1]):0);return[o.c2p(o.l2c(u),!0),s.c2p(e.y[i],!0),n+l,i]}else{var c=(e.level-a)/(e.z[i+1][n]-a),f=(c!==1?(1-c)*s.c2l(e.y[i]):0)+(c!==0?c*s.c2l(e.y[i+1]):0);return[o.c2p(e.x[n],!0),s.c2p(s.l2c(f),!0),n,i+c]}}});var pbe=ye((gcr,vbe)=>{\"use strict\";var yG=b8(),kbt=Eo();vbe.exports={\"[]\":hbe(\"[]\"),\"][\":hbe(\"][\"),\">\":_G(\">\"),\"<\":_G(\"<\"),\"=\":_G(\"=\")};function dbe(e,t){var r=Array.isArray(t),n;function i(a){return kbt(a)?+a:null}return yG.COMPARISON_OPS2.indexOf(e)!==-1?n=i(r?t[0]:t):yG.INTERVAL_OPS.indexOf(e)!==-1?n=r?[i(t[0]),i(t[1])]:[i(t),i(t)]:yG.SET_OPS.indexOf(e)!==-1&&(n=r?t.map(i):[i(t)]),n}function hbe(e){return function(t){t=dbe(e,t);var r=Math.min(t[0],t[1]),n=Math.max(t[0],t[1]);return{start:r,end:n,size:n-r}}}function _G(e){return function(t){return t=dbe(e,t),{start:t,end:1/0,size:1/0}}}});var xG=ye((mcr,mbe)=>{\"use strict\";var gbe=Dr(),Cbt=pbe(),Lbt=C4();mbe.exports=function(t,r,n){for(var i=t.type===\"constraint\"?Cbt[t._operation](t.value):t,a=i.size,o=[],s=Lbt(i),l=n.trace._carpetTrace,u=l?{xaxis:l.aaxis,yaxis:l.baxis,x:n.a,y:n.b}:{xaxis:r.xaxis,yaxis:r.yaxis,x:n.x,y:n.y},c=i.start;c<s;c+=a)if(o.push(gbe.extendFlat({level:c,crossings:{},starts:[],edgepaths:[],paths:[],z:n.z,smoothing:n.trace.line.smoothing},u)),o.length>1e3){gbe.warn(\"Too many contours, clipping at 1000\",t);break}return o}});var bG=ye((ycr,_be)=>{\"use strict\";var OT=Dr();_be.exports=function(e,t){var r,n,i,a=function(l){return l.reverse()},o=function(l){return l};switch(t){case\"=\":case\"<\":return e;case\">\":for(e.length!==1&&OT.warn(\"Contour data invalid for the specified inequality operation.\"),n=e[0],r=0;r<n.edgepaths.length;r++)n.edgepaths[r]=a(n.edgepaths[r]);for(r=0;r<n.paths.length;r++)n.paths[r]=a(n.paths[r]);for(r=0;r<n.starts.length;r++)n.starts[r]=a(n.starts[r]);return e;case\"][\":var s=a;a=o,o=s;case\"[]\":for(e.length!==2&&OT.warn(\"Contour data invalid for the specified 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s=r.x.length,l=r.y.length,u=-1/0,c=1/0;for(i=0;i<l;i++)c=Math.min(c,n[i][0]),c=Math.min(c,n[i][s-1]),u=Math.max(u,n[i][0]),u=Math.max(u,n[i][s-1]);for(i=1;i<s-1;i++)c=Math.min(c,n[0][i]),c=Math.min(c,n[l-1][i]),u=Math.max(u,n[0][i]),u=Math.max(u,n[l-1][i]);var f=t.value,h,d;switch(t._operation){case\">\":f>u&&(r.prefixBoundary=!0);break;case\"<\":(f<c||r.starts.length&&f===c)&&(r.prefixBoundary=!0);break;case\"[]\":h=Math.min(f[0],f[1]),d=Math.max(f[0],f[1]),(d<c||h>u||r.starts.length&&d===c)&&(r.prefixBoundary=!0);break;case\"][\":h=Math.min(f[0],f[1]),d=Math.max(f[0],f[1]),h<c&&d>u&&(r.prefixBoundary=!0);break}break}}});var E8=ye(jv=>{\"use strict\";var R4=Oa(),zd=Dr(),qy=So(),Pbt=tc(),Tbe=ru(),bbe=ho(),wbe=ym(),Ibt=h8(),Abe=gG(),Sbe=mG(),Rbt=xG(),Dbt=bG(),Mbe=wG(),I4=L4(),Dm=I4.LABELOPTIMIZER;jv.plot=function(t,r,n,i){var a=r.xaxis,o=r.yaxis;zd.makeTraceGroups(i,n,\"contour\").each(function(s){var l=R4.select(this),u=s[0],c=u.trace,f=u.x,h=u.y,d=c.contours,v=Rbt(d,r,u),_=zd.ensureSingle(l,\"g\",\"heatmapcoloring\"),b=[];d.coloring===\"heatmap\"&&(b=[s]),Ibt(t,r,b,_),Abe(v),Sbe(v);var p=a.c2p(f[0],!0),k=a.c2p(f[f.length-1],!0),E=o.c2p(h[0],!0),S=o.c2p(h[h.length-1],!0),L=[[p,S],[k,S],[k,E],[p,E]],x=v;d.type===\"constraint\"&&(x=Dbt(v,d._operation)),Fbt(l,L,d),zbt(l,x,L,d),Obt(l,v,t,u,d),Bbt(l,r,t,u,L)})};function Fbt(e,t,r){var n=zd.ensureSingle(e,\"g\",\"contourbg\"),i=n.selectAll(\"path\").data(r.coloring===\"fill\"?[0]:[]);i.enter().append(\"path\"),i.exit().remove(),i.attr(\"d\",\"M\"+t.join(\"L\")+\"Z\").style(\"stroke\",\"none\")}function zbt(e,t,r,n){var i=n.coloring===\"fill\"||n.type===\"constraint\"&&n._operation!==\"=\",a=\"M\"+r.join(\"L\")+\"Z\";i&&Mbe(t,n);var o=zd.ensureSingle(e,\"g\",\"contourfill\"),s=o.selectAll(\"path\").data(i?t:[]);s.enter().append(\"path\"),s.exit().remove(),s.each(function(l){var u=(l.prefixBoundary?a:\"\")+Ebe(l,r);u?R4.select(this).attr(\"d\",u).style(\"stroke\",\"none\"):R4.select(this).remove()})}function Ebe(e,t){var r=\"\",n=0,i=e.edgepaths.map(function(p,k){return k}),a=!0,o,s,l,u,c,f;function h(p){return Math.abs(p[1]-t[0][1])<.01}function d(p){return Math.abs(p[1]-t[2][1])<.01}function v(p){return Math.abs(p[0]-t[0][0])<.01}function _(p){return Math.abs(p[0]-t[2][0])<.01}for(;i.length;){for(f=qy.smoothopen(e.edgepaths[n],e.smoothing),r+=a?f:f.replace(/^M/,\"L\"),i.splice(i.indexOf(n),1),o=e.edgepaths[n][e.edgepaths[n].length-1],u=-1,l=0;l<4;l++){if(!o){zd.log(\"Missing end?\",n,e);break}for(h(o)&&!_(o)?s=t[1]:v(o)?s=t[0]:d(o)?s=t[3]:_(o)&&(s=t[2]),c=0;c<e.edgepaths.length;c++){var b=e.edgepaths[c][0];Math.abs(o[0]-s[0])<.01?Math.abs(o[0]-b[0])<.01&&(b[1]-o[1])*(s[1]-b[1])>=0&&(s=b,u=c):Math.abs(o[1]-s[1])<.01?Math.abs(o[1]-b[1])<.01&&(b[0]-o[0])*(s[0]-b[0])>=0&&(s=b,u=c):zd.log(\"endpt to newendpt is not vert. or 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Fbe=ye((Scr,Dbe)=>{\"use strict\";Dbe.exports={attributes:cG(),supplyDefaults:tbe(),crossTraceDefaults:y8(),calc:pG(),plot:E8().plot,layerName:\"contourlayer\",style:C8(),colorbar:L8(),hoverPoints:SG(),moduleType:\"trace\",name:\"histogram2dcontour\",basePlotModule:ph(),categories:[\"cartesian\",\"svg\",\"2dMap\",\"contour\",\"histogram\",\"showLegend\"],meta:{}}});var Obe=ye((Mcr,zbe)=>{\"use strict\";zbe.exports=Fbe()});var MG=ye((Ecr,Gbe)=>{\"use strict\";var qbe=Eo(),Ybt=fG(),Ube=ka(),Bbe=Ube.addOpacity,Kbt=Ube.opacity,Vbe=b8(),Nbe=Dr().isArrayOrTypedArray,Jbt=Vbe.CONSTRAINT_REDUCTION,$bt=Vbe.COMPARISON_OPS2;Gbe.exports=function(t,r,n,i,a,o){var s=r.contours,l,u,c,f=n(\"contours.operation\");if(s._operation=Jbt[f],Qbt(n,s),f===\"=\"?l=s.showlines=!0:(l=n(\"contours.showlines\"),c=n(\"fillcolor\",Bbe((t.line||{}).color||a,.5))),l){var h=c&&Kbt(c)?Bbe(r.fillcolor,1):a;u=n(\"line.color\",h),n(\"line.width\",2),n(\"line.dash\")}n(\"line.smoothing\"),Ybt(n,i,u,o)};function Qbt(e,t){var 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i2e=ye((Icr,r2e)=>{\"use strict\";var e2e=Dr(),h2t=Sm(),qT=Ru(),d2t=$p(),v2t=R0(),t2e=eT(),p2t=D0(),g2t=Ig(),m2t=kG();r2e.exports=function(t,r,n,i){function a(h,d){return e2e.coerce(t,r,m2t,h,d)}var o=a(\"a\"),s=a(\"b\"),l=a(\"c\"),u;if(o?(u=o.length,s?(u=Math.min(u,s.length),l&&(u=Math.min(u,l.length))):l?u=Math.min(u,l.length):u=0):s&&l&&(u=Math.min(s.length,l.length)),!u){r.visible=!1;return}r._length=u,a(\"sum\"),a(\"text\"),a(\"hovertext\"),r.hoveron!==\"fills\"&&(a(\"hovertemplate\"),a(\"hovertemplatefallback\"));var c=u<h2t.PTS_LINESONLY?\"lines+markers\":\"lines\";a(\"mode\",c),qT.hasMarkers(r)&&d2t(t,r,n,i,a,{gradient:!0}),qT.hasLines(r)&&(v2t(t,r,n,i,a,{backoff:!0}),t2e(t,r,a),a(\"connectgaps\")),qT.hasText(r)&&(a(\"texttemplate\"),a(\"texttemplatefallback\"),p2t(t,r,i,a));var 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o.x0=Math.max(Math.min(o.x0,c),u),o.x1=Math.max(Math.min(o.x1,c),u),a}var f=o.cd[o.index],h=o.trace,d=o.subplot;o.a=f.a,o.b=f.b,o.c=f.c,o.xLabelVal=void 0,o.yLabelVal=void 0;var v={};v[h.subplot]={_subplot:d};var _=h._module.formatLabels(f,h,v);o.aLabel=_.aLabel,o.bLabel=_.bLabel,o.cLabel=_.cLabel;var b=f.hi||h.hoverinfo,p=[];function k(S,L){p.push(S._hovertitle+\": \"+L)}if(!h.hovertemplate){var E=b.split(\"+\");E.indexOf(\"all\")!==-1&&(E=[\"a\",\"b\",\"c\"]),E.indexOf(\"a\")!==-1&&k(d.aaxis,o.aLabel),E.indexOf(\"b\")!==-1&&k(d.baxis,o.bLabel),E.indexOf(\"c\")!==-1&&k(d.caxis,o.cLabel)}return o.extraText=p.join(\"<br>\"),o.hovertemplate=h.hovertemplate,a}});var p2e=ye((Ocr,v2e)=>{\"use strict\";v2e.exports=function(t,r,n,i,a){if(r.xa&&(t.xaxis=r.xa),r.ya&&(t.yaxis=r.ya),i[a]){var o=i[a];t.a=o.a,t.b=o.b,t.c=o.c}else t.a=r.a,t.b=r.b,t.c=r.c;return t}});var M2e=ye((qcr,S2e)=>{\"use strict\";var b2e=Oa(),A2t=cd(),PG=qa(),By=Dr(),Fm=By.strTranslate,I8=By._,NT=ka(),R8=So(),F4=ym(),IG=Ao().extendFlat,S2t=Mc(),E_=ho(),g2e=yv(),m2e=vf(),w2e=Mg(),y2e=w2e.freeMode,M2t=w2e.rectMode,RG=Eb(),E2t=Of().prepSelect,k2t=Of().selectOnClick,C2t=Of().clearOutline,L2t=Of().clearSelectionsCache,T2e=hd();function A2e(e,t){this.id=e.id,this.graphDiv=e.graphDiv,this.init(t),this.makeFramework(t),this.updateFx(t),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}S2e.exports=A2e;var zm=A2e.prototype;zm.init=function(e){this.container=e._ternarylayer,this.defs=e._defs,this.layoutId=e._uid,this.traceHash={},this.layers={}};zm.plot=function(e,t){var r=this,n=t[r.id],i=t._size;r._hasClipOnAxisFalse=!1;for(var a=0;a<e.length;a++){var o=e[a][0].trace;if(o.cliponaxis===!1){r._hasClipOnAxisFalse=!0;break}}r.updateLayers(n),r.adjustLayout(n,i),S2t.generalUpdatePerTraceModule(r.graphDiv,r,e,n),r.layers.plotbg.select(\"path\").call(NT.fill,n.bgcolor)};zm.makeFramework=function(e){var t=this,r=t.graphDiv,n=e[t.id],i=t.clipId=\"clip\"+t.layoutId+t.id,a=t.clipIdRelative=\"clip-relative\"+t.layoutId+t.id;t.clipDef=By.ensureSingleById(e._clips,\"clipPath\",i,function(o){o.append(\"path\").attr(\"d\",\"M0,0Z\")}),t.clipDefRelative=By.ensureSingleById(e._clips,\"clipPath\",a,function(o){o.append(\"path\").attr(\"d\",\"M0,0Z\")}),t.plotContainer=By.ensureSingle(t.container,\"g\",t.id),t.updateLayers(n),R8.setClipUrl(t.layers.backplot,i,r),R8.setClipUrl(t.layers.grids,i,r)};zm.updateFx=function(e){e._ternarylayer.selectAll(\"g.toplevel\").style(\"cursor\",e.dragmode===\"pan\"?\"move\":\"crosshair\")};zm.updateLayers=function(e){var t=this,r=t.layers,n=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];e.aaxis.layer===\"below traces\"&&n.push(\"aaxis\",\"aline\"),e.baxis.layer===\"below traces\"&&n.push(\"baxis\",\"bline\"),e.caxis.layer===\"below traces\"&&n.push(\"caxis\",\"cline\"),n.push(\"frontplot\"),e.aaxis.layer===\"above traces\"&&n.push(\"aaxis\",\"aline\"),e.baxis.layer===\"above traces\"&&n.push(\"baxis\",\"bline\"),e.caxis.layer===\"above traces\"&&n.push(\"caxis\",\"cline\");var i=t.plotContainer.selectAll(\"g.toplevel\").data(n,String),a=[\"agrid\",\"bgrid\",\"cgrid\"];i.enter().append(\"g\").attr(\"class\",function(o){return\"toplevel \"+o}).each(function(o){var s=b2e.select(this);r[o]=s,o===\"frontplot\"?s.append(\"g\").classed(\"scatterlayer\",!0):o===\"backplot\"?s.append(\"g\").classed(\"maplayer\",!0):o===\"plotbg\"?s.append(\"path\").attr(\"d\",\"M0,0Z\"):o===\"aline\"||o===\"bline\"||o===\"cline\"?s.append(\"path\"):o===\"grids\"&&a.forEach(function(l){r[l]=s.append(\"g\").classed(\"grid \"+l,!0)})}),i.order()};var BT=Math.sqrt(4/3);zm.adjustLayout=function(e,t){var r=this,n=e.domain,i=(n.x[0]+n.x[1])/2,a=(n.y[0]+n.y[1])/2,o=n.x[1]-n.x[0],s=n.y[1]-n.y[0],l=o*t.w,u=s*t.h,c=e.sum,f=e.aaxis.min,h=e.baxis.min,d=e.caxis.min,v,_,b,p,k,E;l>BT*u?(p=u,b=p*BT):(b=l,p=b/BT),k=o*b/l,E=s*p/u,v=t.l+t.w*i-b/2,_=t.t+t.h*(1-a)-p/2,r.x0=v,r.y0=_,r.w=b,r.h=p,r.sum=c,r.xaxis={type:\"linear\",range:[f+2*d-c,c-f-2*h],domain:[i-k/2,i+k/2],_id:\"x\"},F4(r.xaxis,r.graphDiv._fullLayout),r.xaxis.setScale(),r.xaxis.isPtWithinRange=function(V){return V.a>=r.aaxis.range[0]&&V.a<=r.aaxis.range[1]&&V.b>=r.baxis.range[1]&&V.b<=r.baxis.range[0]&&V.c>=r.caxis.range[1]&&V.c<=r.caxis.range[0]},r.yaxis={type:\"linear\",range:[f,c-h-d],domain:[a-E/2,a+E/2],_id:\"y\"},F4(r.yaxis,r.graphDiv._fullLayout),r.yaxis.setScale(),r.yaxis.isPtWithinRange=function(){return!0};var S=r.yaxis.domain[0],L=r.aaxis=IG({},e.aaxis,{range:[f,c-h-d],side:\"left\",tickangle:(+e.aaxis.tickangle||0)-30,domain:[S,S+E*BT],anchor:\"free\",position:0,_id:\"y\",_length:b});F4(L,r.graphDiv._fullLayout),L.setScale();var x=r.baxis=IG({},e.baxis,{range:[c-f-d,h],side:\"bottom\",domain:r.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:b});F4(x,r.graphDiv._fullLayout),x.setScale();var C=r.caxis=IG({},e.caxis,{range:[c-f-h,d],side:\"right\",tickangle:(+e.caxis.tickangle||0)+30,domain:[S,S+E*BT],anchor:\"free\",position:0,_id:\"y\",_length:b});F4(C,r.graphDiv._fullLayout),C.setScale();var M=\"M\"+v+\",\"+(_+p)+\"h\"+b+\"l-\"+b/2+\",-\"+p+\"Z\";r.clipDef.select(\"path\").attr(\"d\",M),r.layers.plotbg.select(\"path\").attr(\"d\",M);var g=\"M0,\"+p+\"h\"+b+\"l-\"+b/2+\",-\"+p+\"Z\";r.clipDefRelative.select(\"path\").attr(\"d\",g);var P=Fm(v,_);r.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",P),r.clipDefRelative.select(\"path\").attr(\"transform\",null);var T=Fm(v-x._offset,_+p);r.layers.baxis.attr(\"transform\",T),r.layers.bgrid.attr(\"transform\",T);var z=Fm(v+b/2,_)+\"rotate(30)\"+Fm(0,-L._offset);r.layers.aaxis.attr(\"transform\",z),r.layers.agrid.attr(\"transform\",z);var O=Fm(v+b/2,_)+\"rotate(-30)\"+Fm(0,-C._offset);r.layers.caxis.attr(\"transform\",O),r.layers.cgrid.attr(\"transform\",O),r.drawAxes(!0),r.layers.aline.select(\"path\").attr(\"d\",L.showline?\"M\"+v+\",\"+(_+p)+\"l\"+b/2+\",-\"+p:\"M0,0\").call(NT.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),r.layers.bline.select(\"path\").attr(\"d\",x.showline?\"M\"+v+\",\"+(_+p)+\"h\"+b:\"M0,0\").call(NT.stroke,x.linecolor||\"#000\").style(\"stroke-width\",(x.linewidth||0)+\"px\"),r.layers.cline.select(\"path\").attr(\"d\",C.showline?\"M\"+(v+b/2)+\",\"+_+\"l\"+b/2+\",\"+p:\"M0,0\").call(NT.stroke,C.linecolor||\"#000\").style(\"stroke-width\",(C.linewidth||0)+\"px\"),r.graphDiv._context.staticPlot||r.initInteractions(),R8.setClipUrl(r.layers.frontplot,r._hasClipOnAxisFalse?null:r.clipId,r.graphDiv)};zm.drawAxes=function(e){var t=this,r=t.graphDiv,n=t.id.substr(7)+\"title\",i=t.layers,a=t.aaxis,o=t.baxis,s=t.caxis;if(t.drawAx(a),t.drawAx(o),t.drawAx(s),e){var l=Math.max(a.showticklabels?a.tickfont.size/2:0,(s.showticklabels?s.tickfont.size*.75:0)+(s.ticks===\"outside\"?s.ticklen*.87:0)),u=(o.showticklabels?o.tickfont.size:0)+(o.ticks===\"outside\"?o.ticklen:0)+3;i[\"a-title\"]=RG.draw(r,\"a\"+n,{propContainer:a,propName:t.id+\".aaxis.title.text\",placeholder:I8(r,\"Click to enter Component A title\"),attributes:{x:t.x0+t.w/2,y:t.y0-a.title.font.size/3-l,\"text-anchor\":\"middle\"}}),i[\"b-title\"]=RG.draw(r,\"b\"+n,{propContainer:o,propName:t.id+\".baxis.title.text\",placeholder:I8(r,\"Click to enter Component B title\"),attributes:{x:t.x0-u,y:t.y0+t.h+o.title.font.size*.83+u,\"text-anchor\":\"middle\"}}),i[\"c-title\"]=RG.draw(r,\"c\"+n,{propContainer:s,propName:t.id+\".caxis.title.text\",placeholder:I8(r,\"Click to enter Component C title\"),attributes:{x:t.x0+t.w+u,y:t.y0+t.h+s.title.font.size*.83+u,\"text-anchor\":\"middle\"}})}};zm.drawAx=function(e){var t=this,r=t.graphDiv,n=e._name,i=n.charAt(0),a=e._id,o=t.layers[n],s=30,l=i+\"tickLayout\",u=P2t(e);t[l]!==u&&(o.selectAll(\".\"+a+\"tick\").remove(),t[l]=u),e.setScale();var c=E_.calcTicks(e),f=E_.clipEnds(e,c),h=E_.makeTransTickFn(e),d=E_.getTickSigns(e)[2],v=By.deg2rad(s),_=d*(e.linewidth||1)/2,b=d*e.ticklen,p=t.w,k=t.h,E=i===\"b\"?\"M0,\"+_+\"l\"+Math.sin(v)*b+\",\"+Math.cos(v)*b:\"M\"+_+\",0l\"+Math.cos(v)*b+\",\"+-Math.sin(v)*b,S={a:\"M0,0l\"+k+\",-\"+p/2,b:\"M0,0l-\"+p/2+\",-\"+k,c:\"M0,0l-\"+k+\",\"+p/2}[i];E_.drawTicks(r,e,{vals:e.ticks===\"inside\"?f:c,layer:o,path:E,transFn:h,crisp:!1}),E_.drawGrid(r,e,{vals:f,layer:t.layers[i+\"grid\"],path:S,transFn:h,crisp:!1}),E_.drawLabels(r,e,{vals:c,layer:o,transFn:h,labelFns:E_.makeLabelFns(e,0,s)})};function P2t(e){return e.ticks+String(e.ticklen)+String(e.showticklabels)}var yd=T2e.MINZOOM/2+.87,I2t=\"m-0.87,.5h\"+yd+\"v3h-\"+(yd+5.2)+\"l\"+(yd/2+2.6)+\",-\"+(yd*.87+4.5)+\"l2.6,1.5l-\"+yd/2+\",\"+yd*.87+\"Z\",R2t=\"m0.87,.5h-\"+yd+\"v3h\"+(yd+5.2)+\"l-\"+(yd/2+2.6)+\",-\"+(yd*.87+4.5)+\"l-2.6,1.5l\"+yd/2+\",\"+yd*.87+\"Z\",D2t=\"m0,1l\"+yd/2+\",\"+yd*.87+\"l2.6,-1.5l-\"+(yd/2+2.6)+\",-\"+(yd*.87+4.5)+\"l-\"+(yd/2+2.6)+\",\"+(yd*.87+4.5)+\"l2.6,1.5l\"+yd/2+\",-\"+yd*.87+\"Z\",F2t=\"m0.5,0.5h5v-2h-5v-5h-2v5h-5v2h5v5h2Z\",_2e=!0;zm.clearOutline=function(){L2t(this.dragOptions),C2t(this.dragOptions.gd)};zm.initInteractions=function(){var e=this,t=e.layers.plotbg.select(\"path\").node(),r=e.graphDiv,n=r._fullLayout._zoomlayer,i,a;this.dragOptions={element:t,gd:r,plotinfo:{id:e.id,domain:r._fullLayout[e.id].domain,xaxis:e.xaxis,yaxis:e.yaxis},subplot:e.id,prepFn:function(T,z,O){e.dragOptions.xaxes=[e.xaxis],e.dragOptions.yaxes=[e.yaxis],i=r._fullLayout._invScaleX,a=r._fullLayout._invScaleY;var V=e.dragOptions.dragmode=r._fullLayout.dragmode;y2e(V)?e.dragOptions.minDrag=1:e.dragOptions.minDrag=void 0,V===\"zoom\"?(e.dragOptions.moveFn=x,e.dragOptions.clickFn=p,e.dragOptions.doneFn=C,k(T,z,O)):V===\"pan\"?(e.dragOptions.moveFn=g,e.dragOptions.clickFn=p,e.dragOptions.doneFn=P,M(),e.clearOutline(r)):(M2t(V)||y2e(V))&&E2t(T,z,O,e.dragOptions,V)}};var o,s,l,u,c,f,h,d,v,_;function b(T){var z={};return z[e.id+\".aaxis.min\"]=T.a,z[e.id+\".baxis.min\"]=T.b,z[e.id+\".caxis.min\"]=T.c,z}function p(T,z){var O=r._fullLayout.clickmode;x2e(r),T===2&&(r.emit(\"plotly_doubleclick\",null),PG.call(\"_guiRelayout\",r,b({a:0,b:0,c:0}))),O.indexOf(\"select\")>-1&&T===1&&k2t(z,r,[e.xaxis],[e.yaxis],e.id,e.dragOptions),O.indexOf(\"event\")>-1&&m2e.click(r,z,e.id)}function k(T,z,O){var V=t.getBoundingClientRect();o=z-V.left,s=O-V.top,r._fullLayout._calcInverseTransform(r);var G=r._fullLayout._invTransform,Z=By.apply3DTransform(G)(o,s);o=Z[0],s=Z[1],l={a:e.aaxis.range[0],b:e.baxis.range[1],c:e.caxis.range[1]},c=l,u=e.aaxis.range[1]-l.a,f=A2t(e.graphDiv._fullLayout[e.id].bgcolor).getLuminance(),h=\"M0,\"+e.h+\"L\"+e.w/2+\", 0L\"+e.w+\",\"+e.h+\"Z\",d=!1,v=n.append(\"path\").attr(\"class\",\"zoombox\").attr(\"transform\",Fm(e.x0,e.y0)).style({fill:f>.2?\"rgba(0,0,0,0)\":\"rgba(255,255,255,0)\",\"stroke-width\":0}).attr(\"d\",h),_=n.append(\"path\").attr(\"class\",\"zoombox-corners\").attr(\"transform\",Fm(e.x0,e.y0)).style({fill:NT.background,stroke:NT.defaultLine,\"stroke-width\":1,opacity:0}).attr(\"d\",\"M0,0Z\"),e.clearOutline(r)}function E(T,z){return 1-z/e.h}function S(T,z){return 1-(T+(e.h-z)/Math.sqrt(3))/e.w}function L(T,z){return(T-(e.h-z)/Math.sqrt(3))/e.w}function x(T,z){var O=o+T*i,V=s+z*a,G=Math.max(0,Math.min(1,E(o,s),E(O,V))),Z=Math.max(0,Math.min(1,S(o,s),S(O,V))),H=Math.max(0,Math.min(1,L(o,s),L(O,V))),N=(G/2+H)*e.w,j=(1-G/2-Z)*e.w,re=(N+j)/2,oe=j-N,_e=(1-G)*e.h,Ee=_e-oe/BT;oe<T2e.MINZOOM?(c=l,v.attr(\"d\",h),_.attr(\"d\",\"M0,0Z\")):(c={a:l.a+G*u,b:l.b+Z*u,c:l.c+H*u},v.attr(\"d\",h+\"M\"+N+\",\"+_e+\"H\"+j+\"L\"+re+\",\"+Ee+\"L\"+N+\",\"+_e+\"Z\"),_.attr(\"d\",\"M\"+o+\",\"+s+F2t+\"M\"+N+\",\"+_e+I2t+\"M\"+j+\",\"+_e+R2t+\"M\"+re+\",\"+Ee+D2t)),d||(v.transition().style(\"fill\",f>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),_.transition().style(\"opacity\",1).duration(200),d=!0),r.emit(\"plotly_relayouting\",b(c))}function C(){x2e(r),c!==l&&(PG.call(\"_guiRelayout\",r,b(c)),_2e&&r.data&&r._context.showTips&&(By.notifier(I8(r,\"Double-click to zoom back out\"),\"long\"),_2e=!1))}function M(){l={a:e.aaxis.range[0],b:e.baxis.range[1],c:e.caxis.range[1]},c=l}function g(T,z){var O=T/e.xaxis._m,V=z/e.yaxis._m;c={a:l.a-V,b:l.b+(O+V)/2,c:l.c-(O-V)/2};var G=[c.a,c.b,c.c].sort(By.sorterAsc),Z={a:G.indexOf(c.a),b:G.indexOf(c.b),c:G.indexOf(c.c)};G[0]<0&&(G[1]+G[0]/2<0?(G[2]+=G[0]+G[1],G[0]=G[1]=0):(G[2]+=G[0]/2,G[1]+=G[0]/2,G[0]=0),c={a:G[Z.a],b:G[Z.b],c:G[Z.c]},z=(l.a-c.a)*e.yaxis._m,T=(l.c-c.c-l.b+c.b)*e.xaxis._m);var H=Fm(e.x0+T,e.y0+z);e.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",H);var N=Fm(-T,-z);e.clipDefRelative.select(\"path\").attr(\"transform\",N),e.aaxis.range=[c.a,e.sum-c.b-c.c],e.baxis.range=[e.sum-c.a-c.c,c.b],e.caxis.range=[e.sum-c.a-c.b,c.c],e.drawAxes(!1),e._hasClipOnAxisFalse&&e.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(R8.hideOutsideRangePoints,e),r.emit(\"plotly_relayouting\",b(c))}function P(){PG.call(\"_guiRelayout\",r,b(c))}t.onmousemove=function(T){m2e.hover(r,T,e.id),r._fullLayout._lasthover=t,r._fullLayout._hoversubplot=e.id},t.onmouseout=function(T){r._dragging||g2e.unhover(r,T)},g2e.init(this.dragOptions)};function x2e(e){b2e.select(e).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}});var zG=ye((Bcr,E2e)=>{\"use strict\";var z2t=Lh(),O2t=Cc().attributes,su=Rd(),q2t=mc().overrideAll,DG=Ao().extendFlat,FG={title:{text:su.title.text,font:su.title.font},color:su.color,tickmode:su.minor.tickmode,nticks:DG({},su.nticks,{dflt:6,min:1}),tick0:su.tick0,dtick:su.dtick,tickvals:su.tickvals,ticktext:su.ticktext,ticks:su.ticks,ticklen:su.ticklen,tickwidth:su.tickwidth,tickcolor:su.tickcolor,ticklabelstep:su.ticklabelstep,showticklabels:su.showticklabels,labelalias:su.labelalias,showtickprefix:su.showtickprefix,tickprefix:su.tickprefix,showticksuffix:su.showticksuffix,ticksuffix:su.ticksuffix,showexponent:su.showexponent,exponentformat:su.exponentformat,minexponent:su.minexponent,separatethousands:su.separatethousands,tickfont:su.tickfont,tickangle:su.tickangle,tickformat:su.tickformat,tickformatstops:su.tickformatstops,hoverformat:su.hoverformat,showline:DG({},su.showline,{dflt:!0}),linecolor:su.linecolor,linewidth:su.linewidth,showgrid:DG({},su.showgrid,{dflt:!0}),gridcolor:su.gridcolor,gridwidth:su.gridwidth,griddash:su.griddash,layer:su.layer,min:{valType:\"number\",dflt:0,min:0}},D8=E2e.exports=q2t({domain:O2t({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:z2t.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:FG,baxis:FG,caxis:FG},\"plot\",\"from-root\");D8.uirevision={valType:\"any\",editType:\"none\"};D8.aaxis.uirevision=D8.baxis.uirevision=D8.caxis.uirevision={valType:\"any\",editType:\"none\"}});var k_=ye((Ncr,k2e)=>{\"use strict\";var B2t=Dr(),N2t=vl(),U2t=Cc().defaults;k2e.exports=function(t,r,n,i){var a=i.type,o=i.attributes,s=i.handleDefaults,l=i.partition||\"x\",u=r._subplots[a],c=u.length,f=c&&u[0].replace(/\\d+$/,\"\"),h,d;function v(k,E){return B2t.coerce(h,d,o,k,E)}for(var _=0;_<c;_++){var b=u[_];t[b]?h=t[b]:h=t[b]={},d=N2t.newContainer(r,b,f),i.noUirevision||v(\"uirevision\",r.uirevision);var p={};p[l]=[_/c,(_+1)/c],U2t(d,r,v,p),i.id=b,s(h,d,v,i)}}});var I2e=ye((Ucr,P2e)=>{\"use strict\";var V2t=ka(),G2t=vl(),F8=Dr(),H2t=k_(),j2t=e_(),W2t=t_(),X2t=S3(),Z2t=bb(),Y2t=e4(),L2e=zG(),C2e=[\"aaxis\",\"baxis\",\"caxis\"];P2e.exports=function(t,r,n){H2t(t,r,n,{type:\"ternary\",attributes:L2e,handleDefaults:K2t,font:r.font,paper_bgcolor:r.paper_bgcolor})};function K2t(e,t,r,n){var i=r(\"bgcolor\"),a=r(\"sum\");n.bgColor=V2t.combine(i,n.paper_bgcolor);for(var o,s,l,u=0;u<C2e.length;u++)o=C2e[u],s=e[o]||{},l=G2t.newContainer(t,o),l._name=o,J2t(s,l,n,t);var c=t.aaxis,f=t.baxis,h=t.caxis;c.min+f.min+h.min>=a&&(c.min=0,f.min=0,h.min=0,e.aaxis&&delete e.aaxis.min,e.baxis&&delete e.baxis.min,e.caxis&&delete e.caxis.min)}function J2t(e,t,r,n){var i=L2e[t._name];function a(d,v){return F8.coerce(e,t,i,d,v)}a(\"uirevision\",n.uirevision),t.type=\"linear\";var o=a(\"color\"),s=o!==i.color.dflt?o:r.font.color,l=t._name,u=l.charAt(0).toUpperCase(),c=\"Component \"+u,f=a(\"title.text\",c);t._hovertitle=f===c?f:u,F8.coerceFont(a,\"title.font\",r.font,{overrideDflt:{size:F8.bigFont(r.font.size),color:s}}),a(\"min\"),Z2t(e,t,a,\"linear\"),W2t(e,t,a,\"linear\"),j2t(e,t,a,\"linear\",{noAutotickangles:!0,noTicklabelshift:!0,noTicklabelstandoff:!0}),X2t(e,t,a,{outerTicks:!0});var h=a(\"showticklabels\");h&&(F8.coerceFont(a,\"tickfont\",r.font,{overrideDflt:{color:s}}),a(\"tickangle\"),a(\"tickformat\")),Y2t(e,t,a,{dfltColor:o,bgColor:r.bgColor,blend:60,showLine:!0,showGrid:!0,noZeroLine:!0,attributes:i}),a(\"hoverformat\"),a(\"layer\")}});var R2e=ye(W0=>{\"use strict\";var $2t=M2e(),Q2t=Id().getSubplotCalcData,ewt=Dr().counterRegex,UT=\"ternary\";W0.name=UT;var twt=W0.attr=\"subplot\";W0.idRoot=UT;W0.idRegex=W0.attrRegex=ewt(UT);var rwt=W0.attributes={};rwt[twt]={valType:\"subplotid\",dflt:\"ternary\",editType:\"calc\"};W0.layoutAttributes=zG();W0.supplyLayoutDefaults=I2e();W0.plot=function(t){for(var r=t._fullLayout,n=t.calcdata,i=r._subplots[UT],a=0;a<i.length;a++){var o=i[a],s=Q2t(n,UT,o),l=r[o]._subplot;l||(l=new $2t({id:o,graphDiv:t,container:r._ternarylayer.node()},r),r[o]._subplot=l),l.plot(s,r,t._promises)}};W0.clean=function(e,t,r,n){for(var i=n._subplots[UT]||[],a=0;a<i.length;a++){var o=i[a],s=n[o]._subplot;!t[o]&&s&&(s.plotContainer.remove(),s.clipDef.remove(),s.clipDefRelative.remove(),s.layers[\"a-title\"].remove(),s.layers[\"b-title\"].remove(),s.layers[\"c-title\"].remove())}};W0.updateFx=function(e){var t=e._fullLayout;t._ternarylayer.selectAll(\"g.toplevel\").style(\"cursor\",t.dragmode===\"pan\"?\"move\":\"crosshair\")}});var F2e=ye((Gcr,D2e)=>{\"use strict\";D2e.exports={attributes:kG(),supplyDefaults:i2e(),colorbar:$d(),formatLabels:a2e(),calc:u2e(),plot:f2e(),style:op().style,styleOnSelect:op().styleOnSelect,hoverPoints:d2e(),selectPoints:fT(),eventData:p2e(),moduleType:\"trace\",name:\"scatterternary\",basePlotModule:R2e(),categories:[\"ternary\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}});var O2e=ye((Hcr,z2e)=>{\"use strict\";z2e.exports=F2e()});var OG=ye((jcr,B2e)=>{\"use strict\";var Fh=_4(),VT=Ao().extendFlat,q2e=df().axisHoverFormat;B2e.exports={y:Fh.y,x:Fh.x,x0:Fh.x0,y0:Fh.y0,xhoverformat:q2e(\"x\"),yhoverformat:q2e(\"y\"),name:VT({},Fh.name,{}),orientation:VT({},Fh.orientation,{}),bandwidth:{valType:\"number\",min:0,editType:\"calc\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},scalemode:{valType:\"enumerated\",values:[\"width\",\"count\"],dflt:\"width\",editType:\"calc\"},spanmode:{valType:\"enumerated\",values:[\"soft\",\"hard\",\"manual\"],dflt:\"soft\",editType:\"calc\"},span:{valType:\"info_array\",items:[{valType:\"any\",editType:\"calc\"},{valType:\"any\",editType:\"calc\"}],editType:\"calc\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,dflt:2,editType:\"style\"},editType:\"plot\"},fillcolor:Fh.fillcolor,points:VT({},Fh.boxpoints,{}),jitter:VT({},Fh.jitter,{}),pointpos:VT({},Fh.pointpos,{}),width:VT({},Fh.width,{}),marker:Fh.marker,text:Fh.text,hovertext:Fh.hovertext,hovertemplate:Fh.hovertemplate,hovertemplatefallback:Fh.hovertemplatefallback,quartilemethod:Fh.quartilemethod,box:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},width:{valType:\"number\",min:0,max:1,dflt:.25,editType:\"plot\"},fillcolor:{valType:\"color\",editType:\"style\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"style\"},editType:\"plot\"},meanline:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"plot\"},side:{valType:\"enumerated\",values:[\"both\",\"positive\",\"negative\"],dflt:\"both\",editType:\"calc\"},offsetgroup:Fh.offsetgroup,alignmentgroup:Fh.alignmentgroup,selected:Fh.selected,unselected:Fh.unselected,hoveron:{valType:\"flaglist\",flags:[\"violins\",\"points\",\"kde\"],dflt:\"violins+points+kde\",extras:[\"all\"],editType:\"style\"},zorder:Fh.zorder}});var NG=ye((Wcr,N2e)=>{\"use strict\";var qG=x4(),BG=Dr().extendFlat;N2e.exports={violinmode:BG({},qG.boxmode,{}),violingap:BG({},qG.boxgap,{}),violingroupgap:BG({},qG.boxgroupgap,{})}});var j2e=ye((Xcr,H2e)=>{\"use strict\";var U2e=Dr(),iwt=ka(),V2e=w4(),G2e=OG();H2e.exports=function(t,r,n,i){function a(L,x){return U2e.coerce(t,r,G2e,L,x)}function o(L,x){return U2e.coerce2(t,r,G2e,L,x)}if(V2e.handleSampleDefaults(t,r,a,i),r.visible!==!1){a(\"bandwidth\"),a(\"side\");var s=a(\"width\");s||(a(\"scalegroup\",r.name),a(\"scalemode\"));var l=a(\"span\"),u;Array.isArray(l)&&(u=\"manual\"),a(\"spanmode\",u);var c=a(\"line.color\",(t.marker||{}).color||n),f=a(\"line.width\"),h=a(\"fillcolor\",iwt.addOpacity(r.line.color,.5));V2e.handlePointsDefaults(t,r,a,{prefix:\"\"});var d=o(\"box.width\"),v=o(\"box.fillcolor\",h),_=o(\"box.line.color\",c),b=o(\"box.line.width\",f),p=a(\"box.visible\",!!(d||v||_||b));p||(r.box={visible:!1});var k=o(\"meanline.color\",c),E=o(\"meanline.width\",f),S=a(\"meanline.visible\",!!(k||E));S||(r.meanline={visible:!1}),a(\"quartilemethod\"),a(\"zorder\")}}});var X2e=ye((Zcr,W2e)=>{\"use strict\";var nwt=Dr(),awt=NG(),owt=XI();W2e.exports=function(t,r,n){function i(a,o){return nwt.coerce(t,r,awt,a,o)}owt._supply(t,r,n,i,\"violin\")}});var z8=ye(s2=>{\"use strict\";var swt=Dr(),lwt={gaussian:function(e){return 1/Math.sqrt(2*Math.PI)*Math.exp(-.5*e*e)}};s2.makeKDE=function(e,t,r){var n=r.length,i=lwt.gaussian,a=e.bandwidth,o=1/(n*a);return function(s){for(var l=0,u=0;u<n;u++)l+=i((s-r[u])/a);return o*l}};s2.getPositionOnKdePath=function(e,t,r){var n,i;t.orientation===\"h\"?(n=\"y\",i=\"x\"):(n=\"x\",i=\"y\");var a=swt.findPointOnPath(e.path,r,i,{pathLength:e.pathLength}),o=e.posCenterPx,s=a[n],l=t.side===\"both\"?2*o-s:o;return[s,l]};s2.getKdeValue=function(e,t,r){var n=e.pts.map(s2.extractVal),i=s2.makeKDE(e,t,n);return i(r)/e.posDensityScale};s2.extractVal=function(e){return e.v}});var K2e=ye((Kcr,Y2e)=>{\"use strict\";var UG=Dr(),VG=ho(),uwt=RV(),Z2e=z8(),cwt=fs().BADNUM;Y2e.exports=function(t,r){var n=uwt(t,r);if(n[0].t.empty)return n;for(var i=t._fullLayout,a=VG.getFromId(t,r[r.orientation===\"h\"?\"xaxis\":\"yaxis\"]),o=1/0,s=-1/0,l=0,u=0,c=0;c<n.length;c++){var f=n[c],h=f.pts.map(Z2e.extractVal),d=f.bandwidth=hwt(r,f,h),v=f.span=dwt(r,f,a,d);if(f.min===f.max&&d===0)v=f.span=[f.min,f.max],f.density=[{v:1,t:v[0]}],f.bandwidth=d,l=Math.max(l,1);else{var _=v[1]-v[0],b=Math.ceil(_/(d/3)),p=_/b;if(!isFinite(p)||!isFinite(b))return UG.error(\"Something went wrong with computing the violin span\"),n[0].t.empty=!0,n;var k=Z2e.makeKDE(f,r,h);f.density=new Array(b+1);for(var E=0;E<f.density.length;E++){var S=v[0]+E*p,L=k(S);f.density[E]={v:L,t:S},l=Math.max(l,L)}}u=Math.max(u,h.length),o=Math.min(o,v[0]),s=Math.max(s,v[1])}var x=VG.findExtremes(a,[o,s],{padded:!0});if(r._extremes[a._id]=x,r.width)n[0].t.maxKDE=l;else{var 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s=J2e[o],l=s===\"h\"?a:i,u=[],c=0;c<n.length;c++){var f=n[c],h=f[0].t,d=f[0].trace;d.visible===!0&&d.type===\"violin\"&&!h.empty&&d.orientation===s&&d.xaxis===i._id&&d.yaxis===a._id&&u.push(c)}vwt(\"violin\",t,u,l)}}});var twe=ye(($cr,ewe)=>{\"use strict\";var GG=Oa(),HG=Dr(),pwt=So(),jG=KI(),gwt=yU(),mwt=z8();ewe.exports=function(t,r,n,i){var a=t._context.staticPlot,o=t._fullLayout,s=r.xaxis,l=r.yaxis;function u(c,f){var h=gwt(c,{xaxis:s,yaxis:l,trace:f,connectGaps:!0,baseTolerance:.75,shape:\"spline\",simplify:!0,linearized:!0});return pwt.smoothopen(h[0],1)}HG.makeTraceGroups(i,n,\"trace violins\").each(function(c){var f=GG.select(this),h=c[0],d=h.t,v=h.trace;if(v.visible!==!0||d.empty){f.remove();return}var _=d.bPos,b=d.bdPos,p=r[d.valLetter+\"axis\"],k=r[d.posLetter+\"axis\"],E=v.side===\"both\",S=E||v.side===\"positive\",L=E||v.side===\"negative\",x=f.selectAll(\"path.violin\").data(HG.identity);x.enter().append(\"path\").style(\"vector-effect\",a?\"none\":\"non-scaling-stroke\").attr(\"class\",\"violin\"),x.exit().remove(),x.each(function(V){var G=GG.select(this),Z=V.density,H=Z.length,N=k.c2l(V.pos+_,!0),j=k.l2p(N),re;if(v.width)re=d.maxKDE/b;else{var oe=o._violinScaleGroupStats[v.scalegroup];re=v.scalemode===\"count\"?oe.maxKDE/b*(oe.maxCount/V.pts.length):oe.maxKDE/b}var _e,Ee,Ce,me,ie,Se,Le;if(S){for(Se=new Array(H),me=0;me<H;me++)Le=Se[me]={},Le[d.posLetter]=N+Z[me].v/re,Le[d.valLetter]=p.c2l(Z[me].t,!0);_e=u(Se,v)}if(L){for(Se=new Array(H),ie=0,me=H-1;ie<H;ie++,me--)Le=Se[ie]={},Le[d.posLetter]=N-Z[me].v/re,Le[d.valLetter]=p.c2l(Z[me].t,!0);Ee=u(Se,v)}if(E)Ce=_e+\"L\"+Ee.substr(1)+\"Z\";else{var Ae=[j,p.c2p(Z[0].t)],Fe=[j,p.c2p(Z[H-1].t)];v.orientation===\"h\"&&(Ae.reverse(),Fe.reverse()),S?Ce=\"M\"+Ae+\"L\"+_e.substr(1)+\"L\"+Fe:Ce=\"M\"+Fe+\"L\"+Ee.substr(1)+\"L\"+Ae}G.attr(\"d\",Ce),V.posCenterPx=j,V.posDensityScale=re*b,V.path=G.node(),V.pathLength=V.path.getTotalLength()/(E?2:1)});var C=v.box,M=C.width,g=(C.line||{}).width,P,T;E?(P=b*M,T=0):S?(P=[0,b*M/2],T=g*{x:1,y:-1}[d.posLetter]):(P=[b*M/2,0],T=g*{x:-1,y:1}[d.posLetter]),jG.plotBoxAndWhiskers(f,{pos:k,val:p},v,{bPos:_,bdPos:P,bPosPxOffset:T}),jG.plotBoxMean(f,{pos:k,val:p},v,{bPos:_,bdPos:P,bPosPxOffset:T});var z;!v.box.visible&&v.meanline.visible&&(z=HG.identity);var O=f.selectAll(\"path.meanline\").data(z||[]);O.enter().append(\"path\").attr(\"class\",\"meanline\").style(\"fill\",\"none\").style(\"vector-effect\",a?\"none\":\"non-scaling-stroke\"),O.exit().remove(),O.each(function(V){var G=p.c2p(V.mean,!0),Z=mwt.getPositionOnKdePath(V,v,G);GG.select(this).attr(\"d\",v.orientation===\"h\"?\"M\"+G+\",\"+Z[0]+\"V\"+Z[1]:\"M\"+Z[0]+\",\"+G+\"H\"+Z[1])}),jG.plotPoints(f,{x:s,y:l},v,d)})}});var nwe=ye((Qcr,iwe)=>{\"use strict\";var rwe=Oa(),GT=ka(),ywt=op().stylePoints;iwe.exports=function(t){var r=rwe.select(t).selectAll(\"g.trace.violins\");r.style(\"opacity\",function(n){return n[0].trace.opacity}),r.each(function(n){var i=n[0].trace,a=rwe.select(this),o=i.box||{},s=o.line||{},l=i.meanline||{},u=l.width;a.selectAll(\"path.violin\").style(\"stroke-width\",i.line.width+\"px\").call(GT.stroke,i.line.color).call(GT.fill,i.fillcolor),a.selectAll(\"path.box\").style(\"stroke-width\",s.width+\"px\").call(GT.stroke,s.color).call(GT.fill,o.fillcolor);var c={\"stroke-width\":u+\"px\",\"stroke-dasharray\":2*u+\"px,\"+u+\"px\"};a.selectAll(\"path.mean\").style(c).call(GT.stroke,l.color),a.selectAll(\"path.meanline\").style(c).call(GT.stroke,l.color),ywt(a,i,t)})}});var lwe=ye((efr,swe)=>{\"use strict\";var _wt=ka(),WG=Dr(),xwt=ho(),awe=qV(),owe=z8();swe.exports=function(t,r,n,i,a){a||(a={});var o=a.hoverLayer,s=t.cd,l=s[0].trace,u=l.hoveron,c=u.indexOf(\"violins\")!==-1,f=u.indexOf(\"kde\")!==-1,h=[],d,v;if(c||f){var _=awe.hoverOnBoxes(t,r,n,i);if(f&&_.length>0){var b=t.xa,p=t.ya,k,E,S,L,x;l.orientation===\"h\"?(x=r,k=\"y\",S=p,E=\"x\",L=b):(x=n,k=\"x\",S=b,E=\"y\",L=p);var C=s[t.index];if(x>=C.span[0]&&x<=C.span[1]){var M=WG.extendFlat({},t),g=L.c2p(x,!0),P=owe.getKdeValue(C,l,x),T=owe.getPositionOnKdePath(C,l,g),z=S._offset,O=S._length;M[k+\"0\"]=T[0],M[k+\"1\"]=T[1],M[E+\"0\"]=M[E+\"1\"]=g,M[E+\"Label\"]=E+\": \"+xwt.hoverLabelText(L,x,l[E+\"hoverformat\"])+\", \"+s[0].t.labels.kde+\" \"+P.toFixed(3);for(var V=0,G=0;G<_.length;G++)if(_[G].attr===\"med\"){V=G;break}M.spikeDistance=_[V].spikeDistance;var Z=k+\"Spike\";M[Z]=_[V][Z],_[V].spikeDistance=void 0,_[V][Z]=void 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e=Ny({},jc.marker);return delete e.pattern,delete e.cornerradius,e}});var YG=ye((afr,_we)=>{\"use strict\";_we.exports={funnelmode:{valType:\"enumerated\",values:[\"stack\",\"group\",\"overlay\"],dflt:\"stack\",editType:\"calc\"},funnelgap:{valType:\"number\",min:0,max:1,editType:\"calc\"},funnelgroupgap:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"}}});var JG=ye((ofr,bwe)=>{\"use strict\";var O8=Dr(),Mwt=Hb(),Ewt=r0().handleText,kwt=Q3(),Cwt=Pg(),xwe=ZG(),KG=ka();function Lwt(e,t,r,n){function i(f,h){return O8.coerce(e,t,xwe,f,h)}var a=kwt(e,t,n,i);if(!a){t.visible=!1;return}Cwt(e,t,n,i),i(\"xhoverformat\"),i(\"yhoverformat\"),i(\"orientation\",t.y&&!t.x?\"v\":\"h\"),i(\"offset\"),i(\"width\");var o=i(\"text\");i(\"hovertext\"),i(\"hovertemplate\"),i(\"hovertemplatefallback\");var s=i(\"textposition\");Ewt(e,t,n,i,s,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),t.textposition!==\"none\"&&!t.texttemplate&&i(\"textinfo\",O8.isArrayOrTypedArray(o)?\"text+value\":\"value\");var l=i(\"marker.color\",r);i(\"marker.line.color\",KG.defaultLine),i(\"marker.line.width\");var u=i(\"connector.visible\");if(u){i(\"connector.fillcolor\",Pwt(l));var c=i(\"connector.line.width\");c&&(i(\"connector.line.color\"),i(\"connector.line.dash\"))}i(\"zorder\")}function Pwt(e){var t=O8.isArrayOrTypedArray(e)?\"#000\":e;return KG.addOpacity(t,.5*KG.opacity(t))}function Iwt(e,t){var r,n;function i(o){return O8.coerce(n._input,n,xwe,o)}for(var a=0;a<e.length;a++)n=e[a],n.type===\"funnel\"&&(r=n._input,Mwt(r,n,t,i,t.funnelmode))}bwe.exports={supplyDefaults:Lwt,crossTraceDefaults:Iwt}});var Twe=ye((sfr,wwe)=>{\"use strict\";var Rwt=Dr(),Dwt=YG();wwe.exports=function(e,t,r){var n=!1;function 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n=Mwe.getFromId(t,r.xaxis||\"x\"),i=Mwe.getFromId(t,r.yaxis||\"y\"),a,o,s,l,u,c,f,h;r.orientation===\"h\"?(a=n.makeCalcdata(r,\"x\"),s=i.makeCalcdata(r,\"y\"),l=Ewe(r,i,\"y\",s),u=!!r.yperiodalignment,c=\"y\"):(a=i.makeCalcdata(r,\"y\"),s=n.makeCalcdata(r,\"x\"),l=Ewe(r,n,\"x\",s),u=!!r.xperiodalignment,c=\"x\"),o=l.vals;var d=Math.min(o.length,a.length),v=new Array(d);for(r._base=[],f=0;f<d;f++){a[f]<0&&(a[f]=z4);var _=!1;a[f]!==z4&&f+1<d&&a[f+1]!==z4&&(_=!0),h=v[f]={p:o[f],s:a[f],cNext:_},r._base[f]=-.5*h.s,u&&(v[f].orig_p=s[f],v[f][c+\"End\"]=l.ends[f],v[f][c+\"Start\"]=l.starts[f]),r.ids&&(h.id=String(r.ids[f])),f===0&&(v[0].vTotal=0),v[0].vTotal+=$G(h.s),h.begR=$G(h.s)/$G(v[0].s)}var b;for(f=0;f<d;f++)h=v[f],h.s!==z4&&(h.sumR=h.s/v[0].vTotal,h.difR=b!==void 0?h.s/b:1,b=h.s);return Fwt(v,r),zwt(v,r),v};function $G(e){return e===z4?0:e}});var Iwe=ye((cfr,Pwe)=>{\"use strict\";var Lwe=jb().setGroupPositions;Pwe.exports=function(t,r){var n=t._fullLayout,i=t._fullData,a=t.calcdata,o=r.xaxis,s=r.yaxis,l=[],u=[],c=[],f,h;for(h=0;h<i.length;h++){var d=i[h],v=d.orientation===\"h\";d.visible===!0&&d.xaxis===o._id&&d.yaxis===s._id&&d.type===\"funnel\"&&(f=a[h],v?c.push(f):u.push(f),l.push(f))}var _={mode:n.funnelmode,norm:n.funnelnorm,gap:n.funnelgap,groupgap:n.funnelgroupgap};for(Lwe(t,o,s,u,_),Lwe(t,s,o,c,_),h=0;h<l.length;h++){f=l[h];for(var b=0;b<f.length;b++)b+1<f.length&&(f[b].nextP0=f[b+1].p0,f[b].nextS0=f[b+1].s0,f[b].nextP1=f[b+1].p1,f[b].nextS1=f[b+1].s1)}}});var zwe=ye((ffr,Fwe)=>{\"use strict\";var q8=Oa(),L_=Dr(),Rwe=So(),C_=fs().BADNUM,Owt=n2(),qwt=bv().clearMinTextSize;Fwe.exports=function(t,r,n,i){var a=t._fullLayout;qwt(\"funnel\",a),Bwt(t,r,n,i),Nwt(t,r,n,i),Owt.plot(t,r,n,i,{mode:a.funnelmode,norm:a.funnelmode,gap:a.funnelgap,groupgap:a.funnelgroupgap})};function Bwt(e,t,r,n){var i=t.xaxis,a=t.yaxis;L_.makeTraceGroups(n,r,\"trace bars\").each(function(o){var s=q8.select(this),l=o[0].trace,u=L_.ensureSingle(s,\"g\",\"regions\");if(!l.connector||!l.connector.visible){u.remove();return}var c=l.orientation===\"h\",f=u.selectAll(\"g.region\").data(L_.identity);f.enter().append(\"g\").classed(\"region\",!0),f.exit().remove();var h=f.size();f.each(function(d,v){if(!(v!==h-1&&!d.cNext)){var _=Dwe(d,i,a,c),b=_[0],p=_[1],k=\"\";b[0]!==C_&&p[0]!==C_&&b[1]!==C_&&p[1]!==C_&&b[2]!==C_&&p[2]!==C_&&b[3]!==C_&&p[3]!==C_&&(c?k+=\"M\"+b[0]+\",\"+p[1]+\"L\"+b[2]+\",\"+p[2]+\"H\"+b[3]+\"L\"+b[1]+\",\"+p[1]+\"Z\":k+=\"M\"+b[1]+\",\"+p[1]+\"L\"+b[2]+\",\"+p[3]+\"V\"+p[2]+\"L\"+b[1]+\",\"+p[0]+\"Z\"),k===\"\"&&(k=\"M0,0Z\"),L_.ensureSingle(q8.select(this),\"path\").attr(\"d\",k).call(Rwe.setClipUrl,t.layerClipId,e)}})})}function Nwt(e,t,r,n){var i=t.xaxis,a=t.yaxis;L_.makeTraceGroups(n,r,\"trace bars\").each(function(o){var s=q8.select(this),l=o[0].trace,u=L_.ensureSingle(s,\"g\",\"lines\");if(!l.connector||!l.connector.visible||!l.connector.line.width){u.remove();return}var c=l.orientation===\"h\",f=u.selectAll(\"g.line\").data(L_.identity);f.enter().append(\"g\").classed(\"line\",!0),f.exit().remove();var h=f.size();f.each(function(d,v){if(!(v!==h-1&&!d.cNext)){var _=Dwe(d,i,a,c),b=_[0],p=_[1],k=\"\";b[3]!==void 0&&p[3]!==void 0&&(c?(k+=\"M\"+b[0]+\",\"+p[1]+\"L\"+b[2]+\",\"+p[2],k+=\"M\"+b[1]+\",\"+p[1]+\"L\"+b[3]+\",\"+p[2]):(k+=\"M\"+b[1]+\",\"+p[1]+\"L\"+b[2]+\",\"+p[3],k+=\"M\"+b[1]+\",\"+p[0]+\"L\"+b[2]+\",\"+p[2])),k===\"\"&&(k=\"M0,0Z\"),L_.ensureSingle(q8.select(this),\"path\").attr(\"d\",k).call(Rwe.setClipUrl,t.layerClipId,e)}})})}function Dwe(e,t,r,n){var i=[],a=[],o=n?t:r,s=n?r:t;return i[0]=o.c2p(e.s0,!0),a[0]=s.c2p(e.p0,!0),i[1]=o.c2p(e.s1,!0),a[1]=s.c2p(e.p1,!0),i[2]=o.c2p(e.nextS0,!0),a[2]=s.c2p(e.nextP0,!0),i[3]=o.c2p(e.nextS1,!0),a[3]=s.c2p(e.nextP1,!0),n?[i,a]:[a,i]}});var Bwe=ye((hfr,qwe)=>{\"use strict\";var O4=Oa(),Owe=So(),QG=ka(),Uwt=N1().DESELECTDIM,Vwt=N0(),Gwt=bv().resizeText,Hwt=Vwt.styleTextPoints;function jwt(e,t,r){var n=r||O4.select(e).selectAll('g[class^=\"funnellayer\"]').selectAll(\"g.trace\");Gwt(e,n,\"funnel\"),n.style(\"opacity\",function(i){return i[0].trace.opacity}),n.each(function(i){var a=O4.select(this),o=i[0].trace;a.selectAll(\".point > path\").each(function(s){if(!s.isBlank){var l=o.marker;O4.select(this).call(QG.fill,s.mc||l.color).call(QG.stroke,s.mlc||l.line.color).call(Owe.dashLine,l.line.dash,s.mlw||l.line.width).style(\"opacity\",o.selectedpoints&&!s.selected?Uwt:1)}}),Hwt(a,o,e),a.selectAll(\".regions\").each(function(){O4.select(this).selectAll(\"path\").style(\"stroke-width\",0).call(QG.fill,o.connector.fillcolor)}),a.selectAll(\".lines\").each(function(){var s=o.connector.line;Owe.lineGroupStyle(O4.select(this).selectAll(\"path\"),s.width,s.color,s.dash)})})}qwe.exports={style:jwt}});var Vwe=ye((dfr,Uwe)=>{\"use 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_c=Lm(),tH=pf().line,Zwt=Gl(),Jwe=df().axisHoverFormat,{hovertemplateAttrs:Ywt,texttemplateAttrs:Kwt,templatefallbackAttrs:$we}=Ll(),Qwe=Kwe(),jT=Ao().extendFlat,Jwt=ka();function rH(e){return{marker:{color:jT({},_c.marker.color,{arrayOk:!1,editType:\"style\"}),line:{color:jT({},_c.marker.line.color,{arrayOk:!1,editType:\"style\"}),width:jT({},_c.marker.line.width,{arrayOk:!1,editType:\"style\"}),editType:\"style\"},editType:\"style\"},editType:\"style\"}}e3e.exports={measure:{valType:\"data_array\",dflt:[],editType:\"calc\"},base:{valType:\"number\",dflt:null,arrayOk:!1,editType:\"calc\"},x:_c.x,x0:_c.x0,dx:_c.dx,y:_c.y,y0:_c.y0,dy:_c.dy,xperiod:_c.xperiod,yperiod:_c.yperiod,xperiod0:_c.xperiod0,yperiod0:_c.yperiod0,xperiodalignment:_c.xperiodalignment,yperiodalignment:_c.yperiodalignment,xhoverformat:Jwe(\"x\"),yhoverformat:Jwe(\"y\"),hovertext:_c.hovertext,hovertemplate:Ywt({},{keys:Qwe.eventDataKeys}),hovertemplatefallback:$we(),hoverinfo:jT({},Zwt.hoverinfo,{flags:[\"name\",\"x\",\"y\",\"text\",\"initial\",\"delta\",\"final\"]}),textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"initial\",\"delta\",\"final\"],extras:[\"none\"],editType:\"plot\",arrayOk:!1},texttemplate:Kwt({editType:\"plot\"},{keys:Qwe.eventDataKeys.concat([\"label\"])}),texttemplatefallback:$we({editType:\"plot\"}),text:_c.text,textposition:_c.textposition,insidetextanchor:_c.insidetextanchor,textangle:_c.textangle,textfont:_c.textfont,insidetextfont:_c.insidetextfont,outsidetextfont:_c.outsidetextfont,constraintext:_c.constraintext,cliponaxis:_c.cliponaxis,orientation:_c.orientation,offset:_c.offset,width:_c.width,increasing:rH(\"increasing\"),decreasing:rH(\"decreasing\"),totals:rH(\"intermediate 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i3e=Dr(),$wt=Hb(),Qwt=r0().handleText,e3t=Q3(),t3t=Pg(),n3e=iH(),r3t=ka(),a3e=WT(),i3t=a3e.INCREASING.COLOR,n3t=a3e.DECREASING.COLOR,a3t=\"#4499FF\";function aH(e,t,r){e(t+\".marker.color\",r),e(t+\".marker.line.color\",r3t.defaultLine),e(t+\".marker.line.width\")}function o3t(e,t,r,n){function i(u,c){return i3e.coerce(e,t,n3e,u,c)}var a=e3t(e,t,n,i);if(!a){t.visible=!1;return}t3t(e,t,n,i),i(\"xhoverformat\"),i(\"yhoverformat\"),i(\"measure\"),i(\"orientation\",t.x&&!t.y?\"h\":\"v\"),i(\"base\"),i(\"offset\"),i(\"width\"),i(\"text\"),i(\"hovertext\"),i(\"hovertemplate\"),i(\"hovertemplatefallback\");var o=i(\"textposition\");Qwt(e,t,n,i,o,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),t.textposition!==\"none\"&&(i(\"texttemplate\"),i(\"texttemplatefallback\"),t.texttemplate||i(\"textinfo\")),aH(i,\"increasing\",i3t),aH(i,\"decreasing\",n3t),aH(i,\"totals\",a3t);var 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+       "\n",
+       "`).concat(d.join(`\n",
+       "`),`\n",
+       "`))}else{var v=cE(u),_=\"\",b=T2[s];s===\"notDeepEqual\"||s===\"notEqual\"?(v=\"\".concat(T2[s],`\n",
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+       "`).concat(v),v.length>1024&&(v=\"\".concat(v.slice(0,1021),\"...\"))):(_=\"\".concat(cE(c)),v.length>512&&(v=\"\".concat(v.slice(0,509),\"...\")),_.length>512&&(_=\"\".concat(_.slice(0,509),\"...\")),s===\"deepEqual\"||s===\"equal\"?v=\"\".concat(b,`\n",
+       "\n",
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i=e._parserCallback;if(i&&e._parserState===nD&&e._parserBuffers.length>1&&(t=Buffer.concat(e._parserBuffers,e._parserBuffered)),e._parserState!==nD&&(t=null),e._parserCallback=null,e._parserBuffered=0,e._parserState=D4e,e._parserBuffers.splice(0),i){var a=[];t&&a.push(t),r&&a.push(r);var o=i.length>a.length;o&&a.push(q4e(n));var s=i.apply(e,a);if(!o||n===s)return n}}else return n}var O4e=q4e(z4e);function q4e(e){return function(){for(var t=e.apply(this,arguments);typeof t==\"function\";)t=t();return t}}});var rc=ye(Hy=>{\"use strict\";var U4e=RSe().Transform,rkt=N4e();function SE(){U4e.call(this,{readableObjectMode:!0})}SE.prototype=Object.create(U4e.prototype);SE.prototype.constructor=SE;rkt(SE.prototype);Hy.ParserStream=SE;Hy.sliceEq=function(e,t,r){for(var n=t,i=0;i<r.length;)if(e[n++]!==r[i++])return!1;return!0};Hy.str2arr=function(e,t){var r=[],n=0;if(t&&t===\"hex\")for(;n<e.length;)r.push(parseInt(e.slice(n,n+2),16)),n+=2;else 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n=ME(e,r);if(!n)break;switch(n.boxtype){case\"ispe\":t.sizes.push({width:oW(n.data,4),height:oW(n.data,8)});break;case\"irot\":t.transforms.push({type:\"irot\",value:n.data[0]&3});break;case\"imir\":t.transforms.push({type:\"imir\",value:n.data[0]&1});break}r=n.end}}function aW(e,t,r){for(var n=0,i=0;i<r;i++)n=n*256+(e[t+i]||0);return n}function nkt(e,t){for(var r=e[4]>>4&15,n=e[4]&15,i=e[5]>>4&15,a=xA(e,6),o=8,s=0;s<a;s++){var l=xA(e,o);o+=2;var u=xA(e,o);o+=2;var c=aW(e,o,i);o+=i;var f=xA(e,o);if(o+=2,u===0&&f===1){var h=aW(e,o,r),d=aW(e,o+r,n);t.item_loc[l]={length:d,offset:h+c}}o+=f*(r+n)}}function akt(e,t){for(var r=xA(e,4),n=6,i=0;i<r;i++){var a=ME(e,n);if(!a)break;if(a.boxtype===\"infe\"){for(var o=xA(a.data,4),s=\"\",l=8;l<a.data.length&&a.data[l];l++)s+=String.fromCharCode(a.data[l]);t.item_inf[s]=o}n=a.end}}function okt(e,t){for(var r=0;;){var n=ME(e,r);if(!n)break;n.boxtype===\"ipco\"&&ikt(n.data,t),r=n.end}}function skt(e,t){for(var r=4;;){var n=ME(e,r);if(!n)break;n.boxtype===\"iprp\"&&okt(n.data,t),n.boxtype===\"iloc\"&&nkt(n.data,t),n.boxtype===\"iinf\"&&akt(n.data,t),r=n.end}}function lkt(e){var t=e.reduce(function(i,a){return i.width>a.width||i.width===a.width&&i.height>a.height?i:a}),r=e.reduce(function(i,a){return i.height>a.height||i.height===a.height&&i.width>a.width?i:a}),n;return t.width>r.height||t.width===r.height&&t.height>r.width?n=t:n=r,n}oD.exports.readSizeFromMeta=function(e){var t={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(skt(e,t),!!t.sizes.length){var r=lkt(t.sizes),n=1;t.transforms.forEach(function(a){var o={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},s={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(a.type===\"imir\"&&(a.value===0?n=s[n]:(n=s[n],n=o[n],n=o[n])),a.type===\"irot\")for(var l=0;l<a.value;l++)n=o[n]});var i=null;return t.item_inf.Exif&&(i=t.item_loc[t.item_inf.Exif]),{width:r.width,height:r.height,orientation:t.transforms.length?n:null,variants:t.sizes,exif_location:i}}};oD.exports.getMimeType=function(e){var t=String.fromCharCode.apply(null,e.slice(0,4)),r={};r[t]=!0;for(var n=8;n<e.length;n+=4)r[String.fromCharCode.apply(null,e.slice(n,n+4))]=!0;if(!(!r.mif1&&!r.msf1&&!r.miaf))return t===\"avif\"||t===\"avis\"||t===\"avio\"?{type:\"avif\",mime:\"image/avif\"}:t===\"heic\"||t===\"heix\"?{type:\"heic\",mime:\"image/heic\"}:t===\"hevc\"||t===\"hevx\"?{type:\"heic\",mime:\"image/heic-sequence\"}:r.avif||r.avis?{type:\"avif\",mime:\"image/avif\"}:r.heic||r.heix||r.hevc||r.hevx||r.heis?r.msf1?{type:\"heif\",mime:\"image/heif-sequence\"}:{type:\"heif\",mime:\"image/heif\"}:{type:\"avif\",mime:\"image/avif\"}}});var lD=ye((wdr,sW)=>{\"use strict\";function sD(e,t){var r=new Error(e);return r.code=t,r}function ukt(e){try{return decodeURIComponent(escape(e))}catch(t){return e}}function jy(e,t,r){this.input=e.subarray(t,r),this.start=t;var n=String.fromCharCode.apply(null,this.input.subarray(0,4));if(n!==\"II*\\0\"&&n!==\"MM\\0*\")throw sD(\"invalid TIFF signature\",\"EBADDATA\");this.big_endian=n[0]===\"M\"}jy.prototype.each=function(e){this.aborted=!1;var t=this.read_uint32(4);for(this.ifds_to_read=[{id:0,offset:t}];this.ifds_to_read.length>0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,e)}};jy.prototype.read_uint16=function(e){var t=this.input;if(e+2>t.length)throw sD(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?t[e]*256+t[e+1]:t[e]+t[e+1]*256};jy.prototype.read_uint32=function(e){var t=this.input;if(e+4>t.length)throw sD(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?t[e]*16777216+t[e+1]*65536+t[e+2]*256+t[e+3]:t[e]+t[e+1]*256+t[e+2]*65536+t[e+3]*16777216};jy.prototype.is_subifd_link=function(e,t){return e===0&&t===34665||e===0&&t===34853||e===34665&&t===40965};jy.prototype.exif_format_length=function(e){switch(e){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}};jy.prototype.exif_format_read=function(e,t){var r;switch(e){case 1:case 2:return r=this.input[t],r;case 6:return r=this.input[t],r|(r&128)*33554430;case 3:return r=this.read_uint16(t),r;case 8:return r=this.read_uint16(t),r|(r&32768)*131070;case 4:return r=this.read_uint32(t),r;case 9:return r=this.read_uint32(t),r|0;case 5:case 10:case 11:case 12:return null;case 7:return null;default:return null}};jy.prototype.scan_ifd=function(e,t,r){var n=this.read_uint16(t);t+=2;for(var i=0;i<n;i++){var a=this.read_uint16(t),o=this.read_uint16(t+2),s=this.read_uint32(t+4),l=this.exif_format_length(o),u=s*l,c=u<=4?t+8:this.read_uint32(t+8),f=!1;if(c+u>this.input.length)throw sD(\"unexpected EOF\",\"EBADDATA\");for(var h=[],d=c,v=0;v<s;v++,d+=l){var _=this.exif_format_read(o,d);if(_===null){h=null;break}h.push(_)}Array.isArray(h)&&o===2&&(h=ukt(String.fromCharCode.apply(null,h)),h&&h[h.length-1]===\"\\0\"&&(h=h.slice(0,-1))),this.is_subifd_link(e,a)&&Array.isArray(h)&&Number.isInteger(h[0])&&h[0]>0&&(this.ifds_to_read.push({id:a,offset:h[0]}),f=!0);var b={is_big_endian:this.big_endian,ifd:e,tag:a,format:o,count:s,entry_offset:t+this.start,data_length:u,data_offset:c+this.start,value:h,is_subifd_link:f};if(r(b)===!1){this.aborted=!0;return}t+=12}e===0&&this.ifds_to_read.push({id:1,offset:this.read_uint32(t)})};sW.exports.ExifParser=jy;sW.exports.get_orientation=function(e){var t=0;try{return new jy(e,0,e.length).each(function(r){if(r.ifd===0&&r.tag===274&&Array.isArray(r.value))return t=r.value[0],!1}),t}catch(r){return-1}}});var H4e=ye((Tdr,G4e)=>{\"use strict\";var ckt=rc().str2arr,fkt=rc().sliceEq,hkt=rc().readUInt32BE,uD=V4e(),dkt=lD(),vkt=ckt(\"ftyp\");G4e.exports=function(e){if(fkt(e,4,vkt)){var t=uD.unbox(e,0);if(t){var r=uD.getMimeType(t.data);if(r){for(var n,i=t.end;;){var a=uD.unbox(e,i);if(!a)break;if(i=a.end,a.boxtype===\"mdat\")return;if(a.boxtype===\"meta\"){n=a.data;break}}if(n){var o=uD.readSizeFromMeta(n);if(o){var s={width:o.width,height:o.height,type:r.type,mime:r.mime,wUnits:\"px\",hUnits:\"px\"};if(o.variants.length>1&&(s.variants=o.variants),o.orientation&&(s.orientation=o.orientation),o.exif_location&&o.exif_location.offset+o.exif_location.length<=e.length){var l=hkt(e,o.exif_location.offset),u=e.slice(o.exif_location.offset+l+4,o.exif_location.offset+o.exif_location.length),c=dkt.get_orientation(u);c>0&&(s.orientation=c)}return s}}}}}}});var X4e=ye((Adr,W4e)=>{\"use strict\";var pkt=rc().str2arr,gkt=rc().sliceEq,j4e=rc().readUInt16LE,mkt=pkt(\"BM\");W4e.exports=function(e){if(!(e.length<26)&&gkt(e,0,mkt))return{width:j4e(e,18),height:j4e(e,22),type:\"bmp\",mime:\"image/bmp\",wUnits:\"px\",hUnits:\"px\"}}});var $4e=ye((Sdr,J4e)=>{\"use strict\";var K4e=rc().str2arr,Z4e=rc().sliceEq,Y4e=rc().readUInt16LE,ykt=K4e(\"GIF87a\"),_kt=K4e(\"GIF89a\");J4e.exports=function(e){if(!(e.length<10)&&!(!Z4e(e,0,ykt)&&!Z4e(e,0,_kt)))return{width:Y4e(e,6),height:Y4e(e,8),type:\"gif\",mime:\"image/gif\",wUnits:\"px\",hUnits:\"px\"}}});var tEe=ye((Mdr,eEe)=>{\"use strict\";var lW=rc().readUInt16LE,xkt=0,bkt=1,Q4e=16;eEe.exports=function(e){var t=lW(e,0),r=lW(e,2),n=lW(e,4);if(!(t!==xkt||r!==bkt||!n)){for(var i=[],a={width:0,height:0},o=0;o<n;o++){var s=e[6+Q4e*o]||256,l=e[6+Q4e*o+1]||256,u={width:s,height:l};i.push(u),(s>a.width||l>a.height)&&(a=u)}return{width:a.width,height:a.height,variants:i,type:\"ico\",mime:\"image/x-icon\",wUnits:\"px\",hUnits:\"px\"}}}});var iEe=ye((Edr,rEe)=>{\"use strict\";var uW=rc().readUInt16BE,wkt=rc().str2arr,Tkt=rc().sliceEq,Akt=lD(),Skt=wkt(\"Exif\\0\\0\");rEe.exports=function(e){if(!(e.length<2)&&!(e[0]!==255||e[1]!==216||e[2]!==255))for(var t=2;;){for(;;){if(e.length-t<2)return;if(e[t++]===255)break}for(var r=e[t++],n;r===255;)r=e[t++];if(208<=r&&r<=217||r===1)n=0;else if(192<=r&&r<=254){if(e.length-t<2)return;n=uW(e,t)-2,t+=2}else return;if(r===217||r===218)return;var i;if(r===225&&n>=10&&Tkt(e,t,Skt)&&(i=Akt.get_orientation(e.slice(t+6,t+n))),n>=5&&192<=r&&r<=207&&r!==196&&r!==200&&r!==204){if(e.length-t<n)return;var a={width:uW(e,t+3),height:uW(e,t+1),type:\"jpg\",mime:\"image/jpeg\",wUnits:\"px\",hUnits:\"px\"};return i>0&&(a.orientation=i),a}t+=n}}});var lEe=ye((kdr,sEe)=>{\"use strict\";var oEe=rc().str2arr,nEe=rc().sliceEq,aEe=rc().readUInt32BE,Mkt=oEe(`\\x89PNG\\r\n",
+       "\u001a\n",
+       "`),Ekt=oEe(\"IHDR\");sEe.exports=function(e){if(!(e.length<24)&&nEe(e,0,Mkt)&&nEe(e,12,Ekt))return{width:aEe(e,16),height:aEe(e,20),type:\"png\",mime:\"image/png\",wUnits:\"px\",hUnits:\"px\"}}});var fEe=ye((Cdr,cEe)=>{\"use strict\";var kkt=rc().str2arr,Ckt=rc().sliceEq,uEe=rc().readUInt32BE,Lkt=kkt(\"8BPS\\0\u0001\");cEe.exports=function(e){if(!(e.length<22)&&Ckt(e,0,Lkt))return{width:uEe(e,18),height:uEe(e,14),type:\"psd\",mime:\"image/vnd.adobe.photoshop\",wUnits:\"px\",hUnits:\"px\"}}});var vEe=ye((Ldr,dEe)=>{\"use strict\";function Pkt(e){return e===32||e===9||e===13||e===10}function bA(e){return typeof e==\"number\"&&isFinite(e)&&e>0}function Ikt(e){var t=0,r=e.length;for(e[0]===239&&e[1]===187&&e[2]===191&&(t=3);t<r&&Pkt(e[t]);)t++;return t===r?!1:e[t]===60}var Rkt=/<[-_.:a-zA-Z0-9][^>]*>/,Dkt=/^<([-_.:a-zA-Z0-9]+:)?svg\\s/,Fkt=/[^-]\\bwidth=\"([^%]+?)\"|[^-]\\bwidth='([^%]+?)'/,zkt=/\\bheight=\"([^%]+?)\"|\\bheight='([^%]+?)'/,Okt=/\\bview[bB]ox=\"(.+?)\"|\\bview[bB]ox='(.+?)'/,hEe=/in$|mm$|cm$|pt$|pc$|px$|em$|ex$/;function qkt(e){var t=e.match(Fkt),r=e.match(zkt),n=e.match(Okt);return{width:t&&(t[1]||t[2]),height:r&&(r[1]||r[2]),viewbox:n&&(n[1]||n[2])}}function Um(e){return hEe.test(e)?e.match(hEe)[0]:\"px\"}dEe.exports=function(e){if(Ikt(e)){for(var t=\"\",r=0;r<e.length;r++)t+=String.fromCharCode(e[r]);var n=(t.match(Rkt)||[\"\"])[0];if(Dkt.test(n)){var i=qkt(n),a=parseFloat(i.width),o=parseFloat(i.height);if(i.width&&i.height)return!bA(a)||!bA(o)?void 0:{width:a,height:o,type:\"svg\",mime:\"image/svg+xml\",wUnits:Um(i.width),hUnits:Um(i.height)};var s=(i.viewbox||\"\").split(\" \"),l={width:s[2],height:s[3]},u=parseFloat(l.width),c=parseFloat(l.height);if(!(!bA(u)||!bA(c))&&Um(l.width)===Um(l.height)){var f=u/c;return i.width?bA(a)?{width:a,height:a/f,type:\"svg\",mime:\"image/svg+xml\",wUnits:Um(i.width),hUnits:Um(i.width)}:void 0:i.height?bA(o)?{width:o*f,height:o,type:\"svg\",mime:\"image/svg+xml\",wUnits:Um(i.height),hUnits:Um(i.height)}:void 0:{width:u,height:c,type:\"svg\",mime:\"image/svg+xml\",wUnits:Um(l.width),hUnits:Um(l.height)}}}}}});var _Ee=ye((Pdr,yEe)=>{\"use strict\";var mEe=rc().str2arr,pEe=rc().sliceEq,Bkt=rc().readUInt16LE,Nkt=rc().readUInt16BE,Ukt=rc().readUInt32LE,Vkt=rc().readUInt32BE,Gkt=mEe(\"II*\\0\"),Hkt=mEe(\"MM\\0*\");function cD(e,t,r){return r?Nkt(e,t):Bkt(e,t)}function cW(e,t,r){return r?Vkt(e,t):Ukt(e,t)}function gEe(e,t,r){var n=cD(e,t+2,r),i=cW(e,t+4,r);return i!==1||n!==3&&n!==4?null:n===3?cD(e,t+8,r):cW(e,t+8,r)}yEe.exports=function(e){if(!(e.length<8)&&!(!pEe(e,0,Gkt)&&!pEe(e,0,Hkt))){var t=e[0]===77,r=cW(e,4,t)-8;if(!(r<0)){var n=r+8;if(!(e.length-n<2)){var i=cD(e,n+0,t)*12;if(!(i<=0)&&(n+=2,!(e.length-n<i))){var a,o,s,l;for(a=0;a<i;a+=12)l=cD(e,n+a,t),l===256?o=gEe(e,n+a,t):l===257&&(s=gEe(e,n+a,t));if(o&&s)return{width:o,height:s,type:\"tiff\",mime:\"image/tiff\",wUnits:\"px\",hUnits:\"px\"}}}}}}});var AEe=ye((Idr,TEe)=>{\"use strict\";var wEe=rc().str2arr,xEe=rc().sliceEq,bEe=rc().readUInt16LE,fW=rc().readUInt32LE,jkt=lD(),Wkt=wEe(\"RIFF\"),Xkt=wEe(\"WEBP\");function Zkt(e,t){if(!(e[t+3]!==157||e[t+4]!==1||e[t+5]!==42))return{width:bEe(e,t+6)&16383,height:bEe(e,t+8)&16383,type:\"webp\",mime:\"image/webp\",wUnits:\"px\",hUnits:\"px\"}}function Ykt(e,t){if(e[t]===47){var r=fW(e,t+1);return{width:(r&16383)+1,height:(r>>14&16383)+1,type:\"webp\",mime:\"image/webp\",wUnits:\"px\",hUnits:\"px\"}}}function Kkt(e,t){return{width:(e[t+6]<<16|e[t+5]<<8|e[t+4])+1,height:(e[t+9]<<t|e[t+8]<<8|e[t+7])+1,type:\"webp\",mime:\"image/webp\",wUnits:\"px\",hUnits:\"px\"}}TEe.exports=function(e){if(!(e.length<16)&&!(!xEe(e,0,Wkt)&&!xEe(e,8,Xkt))){var t=12,r=null,n=0,i=fW(e,4)+8;if(!(i>e.length)){for(;t+8<i;){if(e[t]===0){t++;continue}var a=String.fromCharCode.apply(null,e.slice(t,t+4)),o=fW(e,t+4);a===\"VP8 \"&&o>=10?r=r||Zkt(e,t+8):a===\"VP8L\"&&o>=9?r=r||Ykt(e,t+8):a===\"VP8X\"&&o>=10?r=r||Kkt(e,t+8):a===\"EXIF\"&&(n=jkt.get_orientation(e.slice(t+8,t+8+o)),t=1/0),t+=8+o}if(r)return n>0&&(r.orientation=n),r}}}});var MEe=ye((Rdr,SEe)=>{\"use strict\";SEe.exports={avif:H4e(),bmp:X4e(),gif:$4e(),ico:tEe(),jpeg:iEe(),png:lEe(),psd:fEe(),svg:vEe(),tiff:_Ee(),webp:AEe()}});var EEe=ye((Ddr,dW)=>{\"use strict\";var hW=MEe();function Jkt(e){for(var t=Object.keys(hW),r=0;r<t.length;r++){var n=hW[t[r]](e);if(n)return n}return null}dW.exports=function(t){return Jkt(t)};dW.exports.parsers=hW});var CEe=ye(kEe=>{\"use strict\";var $kt=EEe(),Qkt=Py().IMAGE_URL_PREFIX,eCt=c2().Buffer;kEe.getImageSize=function(e){var t=e.replace(Qkt,\"\"),r=new eCt(t,\"base64\");return $kt(r)}});var IEe=ye((zdr,PEe)=>{\"use strict\";var 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l=Math.floor((r-i.x0)/a.dx),u=Math.floor(Math.abs(n-i.y0)/a.dy),c;if(a._hasZ?c=i.z[u][l]:a._hasSource&&(c=a._canvas.el.getContext(\"2d\",{willReadFrequently:!0}).getImageData(l,u,1,1).data),!!c){var f=i.hi||a.hoverinfo,h;if(f){var d=f.split(\"+\");d.indexOf(\"all\")!==-1&&(d=[\"color\"]),d.indexOf(\"color\")!==-1&&(h=!0)}var v=vCt.colormodel[a.colormodel],_=v.colormodel||a.colormodel,b=_.length,p=a._scaler(c),k=v.suffix,E=[];(a.hovertemplate||h)&&(E.push(\"[\"+[p[0]+k[0],p[1]+k[1],p[2]+k[2]].join(\", \")),b===4&&E.push(\", \"+p[3]+k[3]),E.push(\"]\"),E=E.join(\"\"),t.extraText=_.toUpperCase()+\": \"+E);var S;hD(a.hovertext)&&hD(a.hovertext[u])?S=a.hovertext[u][l]:hD(a.text)&&hD(a.text[u])&&(S=a.text[u][l]);var L=s.c2p(i.y0+(u+.5)*a.dy),x=i.x0+(l+.5)*a.dx,C=i.y0+(u+.5)*a.dy,M=\"[\"+c.slice(0,a.colormodel.length).join(\", \")+\"]\";return[BEe.extendFlat(t,{index:[u,l],x0:o.c2p(i.x0+l*a.dx),x1:o.c2p(i.x0+(l+1)*a.dx),y0:L,y1:L,color:p,xVal:x,xLabelVal:x,yVal:C,yLabelVal:C,zLabelVal:M,text:S,hovertemplateLabels:{zLabel:M,colorLabel:E,\"color[0]Label\":p[0]+k[0],\"color[1]Label\":p[1]+k[1],\"color[2]Label\":p[2]+k[2],\"color[3]Label\":p[3]+k[3]}})]}}}});var GEe=ye((Ndr,VEe)=>{\"use strict\";VEe.exports=function(t,r){return\"xVal\"in r&&(t.x=r.xVal),\"yVal\"in r&&(t.y=r.yVal),r.xa&&(t.xaxis=r.xa),r.ya&&(t.yaxis=r.ya),t.color=r.color,t.colormodel=r.trace.colormodel,t.z||(t.z=r.color),t}});var jEe=ye((Udr,HEe)=>{\"use strict\";HEe.exports={attributes:uH(),supplyDefaults:U3e(),calc:IEe(),plot:FEe(),style:OEe(),hoverPoints:UEe(),eventData:GEe(),moduleType:\"trace\",name:\"image\",basePlotModule:ph(),categories:[\"cartesian\",\"svg\",\"2dMap\",\"noSortingByValue\"],animatable:!1,meta:{}}});var XEe=ye((Vdr,WEe)=>{\"use strict\";WEe.exports=jEe()});var S2=ye((Gdr,YEe)=>{\"use strict\";var pCt=Gl(),gCt=Cc().attributes,mCt=ec(),yCt=Lh(),{hovertemplateAttrs:_Ct,texttemplateAttrs:xCt,templatefallbackAttrs:ZEe}=Ll(),EE=Ao().extendFlat,bCt=Pd().pattern,dD=mCt({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});YEe.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:yCt.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},pattern:bCt,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:EE({},pCt.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:_Ct({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),hovertemplatefallback:ZEe(),texttemplate:xCt({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplatefallback:ZEe({editType:\"plot\"}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:EE({},dD,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:EE({},dD,{}),outsidetextfont:EE({},dD,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:EE({},dD,{}),position:{valType:\"enumerated\",values:[\"top 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a=n(\"marker.line.width\");a&&n(\"marker.line.color\",i?void 0:r.paper_bgcolor);var o=n(\"marker.colors\");MCt(n,\"marker.pattern\",o),e.marker&&!t.marker.pattern.fgcolor&&(t.marker.pattern.fgcolor=e.marker.colors),t.marker.pattern.bgcolor||(t.marker.pattern.bgcolor=r.paper_bgcolor)}function ECt(e,t,r,n){function i(k,E){return kE.coerce(e,t,TCt,k,E)}var a=i(\"labels\"),o=i(\"values\"),s=KEe(a,o),l=s.len;if(t._hasLabels=s.hasLabels,t._hasValues=s.hasValues,!t._hasLabels&&t._hasValues&&(i(\"label0\"),i(\"dlabel\")),!l){t.visible=!1;return}t._length=l,JEe(e,t,n,i,!0),i(\"scalegroup\");var u=i(\"text\"),c=i(\"texttemplate\");i(\"texttemplatefallback\");var f;if(c||(f=i(\"textinfo\",kE.isArrayOrTypedArray(u)?\"text+percent\":\"percent\")),i(\"hovertext\"),i(\"hovertemplate\"),i(\"hovertemplatefallback\"),c||f&&f!==\"none\"){var h=i(\"textposition\");SCt(e,t,n,i,h,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1});var d=Array.isArray(h)||h===\"auto\",v=d||h===\"outside\";v&&i(\"automargin\"),(h===\"inside\"||h===\"auto\"||Array.isArray(h))&&i(\"insidetextorientation\")}else f===\"none\"&&i(\"textposition\",\"none\");ACt(t,n,i);var _=i(\"hole\"),b=i(\"title.text\");if(b){var p=i(\"title.position\",_?\"middle center\":\"top center\");!_&&p===\"middle center\"&&(t.title.position=\"top center\"),kE.coerceFont(i,\"title.font\",n.font)}i(\"sort\"),i(\"direction\"),i(\"rotation\"),i(\"pull\")}$Ee.exports={handleLabelsAndValues:KEe,handleMarkerDefaults:JEe,supplyDefaults:ECt}});var vD=ye((jdr,QEe)=>{\"use strict\";QEe.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}});var tke=ye((Wdr,eke)=>{\"use 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x.v-L.v}),r[0]&&(r[0].vTotal=v),r}function rke(e){return function(r,n){return!r||(r=vW(r),!r.isValid())?!1:(r=PCt.addOpacity(r,r.getAlpha()),e[n]||(e[n]=r),r)}}function DCt(e,t){var r=(t||{}).type;r||(r=\"pie\");var n=e._fullLayout,i=e.calcdata,a=n[r+\"colorway\"],o=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=ike(a,ICt));for(var s=0,l=0;l<i.length;l++){var u=i[l],c=u[0].trace.type;if(c===r)for(var f=0;f<u.length;f++){var h=u[f];h.color===!1&&(o[h.label]?h.color=o[h.label]:(o[h.label]=h.color=a[s%a.length],s++))}}}function ike(e,t){var r,n=JSON.stringify(e),i=t[n];if(!i){for(i=e.slice(),r=0;r<e.length;r++)i.push(vW(e[r]).lighten(20).toHexString());for(r=0;r<e.length;r++)i.push(vW(e[r]).darken(20).toHexString());t[n]=i}return i}nke.exports={calc:RCt,crossTraceCalc:DCt,makePullColorFn:rke,generateExtendedColors:ike}});var oke=ye((Zdr,ake)=>{\"use strict\";var FCt=ip().appendArrayMultiPointValues;ake.exports=function(t,r){var n={curveNumber:r.index,pointNumbers:t.pts,data:r._input,fullData:r,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return t.pts.length===1&&(n.pointNumber=n.i=t.pts[0]),FCt(n,r,t.pts),r.type===\"funnelarea\"&&(delete n.v,delete n.i),n}});var yD=ye((Ydr,Eke)=>{\"use strict\";var Fp=Oa(),zCt=Mc(),pD=vf(),hke=ka(),Wy=So(),rv=Dr(),OCt=rv.strScale,ske=rv.strTranslate,pW=ru(),dke=bv(),qCt=dke.recordMinTextSize,BCt=dke.clearMinTextSize,vke=e2().TEXTPAD,ns=l_(),gD=oke(),lke=Dr().isValidTextValue;function NCt(e,t){var r=e._context.staticPlot,n=e._fullLayout,i=n._size;BCt(\"pie\",n),mke(t,e),Ake(t,i);var a=rv.makeTraceGroups(n._pielayer,t,\"trace\").each(function(o){var s=Fp.select(this),l=o[0],u=l.trace;YCt(o),s.attr(\"stroke-linejoin\",\"round\"),s.each(function(){var c=Fp.select(this).selectAll(\"g.slice\").data(o);c.enter().append(\"g\").classed(\"slice\",!0),c.exit().remove();var f=[[[],[]],[[],[]]],h=!1;c.each(function(S,L){if(S.hidden){Fp.select(this).selectAll(\"path,g\").remove();return}S.pointNumber=S.i,S.curveNumber=u.index,f[S.pxmid[1]<0?0:1][S.pxmid[0]<0?0:1].push(S);var x=l.cx,C=l.cy,M=Fp.select(this),g=M.selectAll(\"path.surface\").data([S]);if(g.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":r?\"none\":\"all\"}),M.call(pke,e,o),u.pull){var P=+ns.castOption(u.pull,S.pts)||0;P>0&&(x+=P*S.pxmid[0],C+=P*S.pxmid[1])}S.cxFinal=x,S.cyFinal=C;function T(N,j,re,oe){var _e=oe*(j[0]-N[0]),Ee=oe*(j[1]-N[1]);return\"a\"+oe*l.r+\",\"+oe*l.r+\" 0 \"+S.largeArc+(re?\" 1 \":\" 0 \")+_e+\",\"+Ee}var z=u.hole;if(S.v===l.vTotal){var O=\"M\"+(x+S.px0[0])+\",\"+(C+S.px0[1])+T(S.px0,S.pxmid,!0,1)+T(S.pxmid,S.px0,!0,1)+\"Z\";z?g.attr(\"d\",\"M\"+(x+z*S.px0[0])+\",\"+(C+z*S.px0[1])+T(S.px0,S.pxmid,!1,z)+T(S.pxmid,S.px0,!1,z)+\"Z\"+O):g.attr(\"d\",O)}else{var V=T(S.px0,S.px1,!0,1);if(z){var G=1-z;g.attr(\"d\",\"M\"+(x+z*S.px1[0])+\",\"+(C+z*S.px1[1])+T(S.px1,S.px0,!1,z)+\"l\"+G*S.px0[0]+\",\"+G*S.px0[1]+V+\"Z\")}else g.attr(\"d\",\"M\"+x+\",\"+C+\"l\"+S.px0[0]+\",\"+S.px0[1]+V+\"Z\")}Ske(e,S,l);var Z=ns.castOption(u.textposition,S.pts),H=M.selectAll(\"g.slicetext\").data(S.text&&Z!==\"none\"?[0]:[]);H.enter().append(\"g\").classed(\"slicetext\",!0),H.exit().remove(),H.each(function(){var N=rv.ensureSingle(Fp.select(this),\"text\",\"\",function(ie){ie.attr(\"data-notex\",1)}),j=rv.ensureUniformFontSize(e,Z===\"outside\"?VCt(u,S,n.font):gke(u,S,n.font));N.text(S.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(Wy.font,j).call(pW.convertToTspans,e);var re=Wy.bBox(N.node()),oe;if(Z===\"outside\")oe=fke(re,S);else if(oe=yke(re,S,l),Z===\"auto\"&&oe.scale<1){var _e=rv.ensureUniformFontSize(e,u.outsidetextfont);N.call(Wy.font,_e),re=Wy.bBox(N.node()),oe=fke(re,S)}var Ee=oe.textPosAngle,Ce=Ee===void 0?S.pxmid:mD(l.r,Ee);if(oe.targetX=x+Ce[0]*oe.rCenter+(oe.x||0),oe.targetY=C+Ce[1]*oe.rCenter+(oe.y||0),Mke(oe,re),oe.outside){var me=oe.targetY;S.yLabelMin=me-re.height/2,S.yLabelMid=me,S.yLabelMax=me+re.height/2,S.labelExtraX=0,S.labelExtraY=0,h=!0}oe.fontSize=j.size,qCt(u.type,oe,n),o[L].transform=oe,rv.setTransormAndDisplay(N,oe)})});var d=Fp.select(this).selectAll(\"g.titletext\").data(u.title.text?[0]:[]);if(d.enter().append(\"g\").classed(\"titletext\",!0),d.exit().remove(),d.each(function(){var S=rv.ensureSingle(Fp.select(this),\"text\",\"\",function(C){C.attr(\"data-notex\",1)}),L=u.title.text;u._meta&&(L=rv.templateString(L,u._meta)),S.text(L).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(Wy.font,u.title.font).call(pW.convertToTspans,e);var x;u.title.position===\"middle center\"?x=jCt(l):x=wke(l,i),S.attr(\"transform\",ske(x.x,x.y)+OCt(Math.min(1,x.scale))+ske(x.tx,x.ty))}),h&&XCt(f,u),UCt(c,u),h&&u.automargin){var v=Wy.bBox(s.node()),_=u.domain,b=i.w*(_.x[1]-_.x[0]),p=i.h*(_.y[1]-_.y[0]),k=(.5*b-l.r)/i.w,E=(.5*p-l.r)/i.h;zCt.autoMargin(e,\"pie.\"+u.uid+\".automargin\",{xl:_.x[0]-k,xr:_.x[1]+k,yb:_.y[0]-E,yt:_.y[1]+E,l:Math.max(l.cx-l.r-v.left,0),r:Math.max(v.right-(l.cx+l.r),0),b:Math.max(v.bottom-(l.cy+l.r),0),t:Math.max(l.cy-l.r-v.top,0),pad:5})}})});setTimeout(function(){a.selectAll(\"tspan\").each(function(){var o=Fp.select(this);o.attr(\"dy\")&&o.attr(\"dy\",o.attr(\"dy\"))})},0)}function UCt(e,t){e.each(function(r){var n=Fp.select(this);if(!r.labelExtraX&&!r.labelExtraY){n.select(\"path.textline\").remove();return}var i=n.select(\"g.slicetext text\");r.transform.targetX+=r.labelExtraX,r.transform.targetY+=r.labelExtraY,rv.setTransormAndDisplay(i,r.transform);var a=r.cxFinal+r.pxmid[0],o=r.cyFinal+r.pxmid[1],s=\"M\"+a+\",\"+o,l=(r.yLabelMax-r.yLabelMin)*(r.pxmid[0]<0?-1:1)/4;if(r.labelExtraX){var u=r.labelExtraX*r.pxmid[1]/r.pxmid[0],c=r.yLabelMid+r.labelExtraY-(r.cyFinal+r.pxmid[1]);Math.abs(u)>Math.abs(c)?s+=\"l\"+c*r.pxmid[0]/r.pxmid[1]+\",\"+c+\"H\"+(a+r.labelExtraX+l):s+=\"l\"+r.labelExtraX+\",\"+u+\"v\"+(c-u)+\"h\"+l}else s+=\"V\"+(r.yLabelMid+r.labelExtraY)+\"h\"+l;rv.ensureSingle(n,\"path\",\"textline\").call(hke.stroke,t.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,t.outsidetextfont.size/8),d:s,fill:\"none\"})})}function pke(e,t,r){var n=r[0],i=n.cx,a=n.cy,o=n.trace,s=o.type===\"funnelarea\";\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),e.on(\"mouseover\",function(l){var u=t._fullLayout,c=t._fullData[o.index];if(!(t._dragging||u.hovermode===!1)){var f=c.hoverinfo;if(Array.isArray(f)&&(f=pD.castHoverinfo({hoverinfo:[ns.castOption(f,l.pts)],_module:o._module},u,0)),f===\"all\"&&(f=\"label+text+value+percent+name\"),c.hovertemplate||f!==\"none\"&&f!==\"skip\"&&f){var h=l.rInscribed||0,d=i+l.pxmid[0]*(1-h),v=a+l.pxmid[1]*(1-h),_=u.separators,b=[];if(f&&f.indexOf(\"label\")!==-1&&b.push(l.label),l.text=ns.castOption(c.hovertext||c.text,l.pts),f&&f.indexOf(\"text\")!==-1){var p=l.text;rv.isValidTextValue(p)&&b.push(p)}l.value=l.v,l.valueLabel=ns.formatPieValue(l.v,_),f&&f.indexOf(\"value\")!==-1&&b.push(l.valueLabel),l.percent=l.v/n.vTotal,l.percentLabel=ns.formatPiePercent(l.percent,_),f&&f.indexOf(\"percent\")!==-1&&b.push(l.percentLabel);var k=c.hoverlabel,E=k.font,S=[];pD.loneHover({trace:o,x0:d-h*n.r,x1:d+h*n.r,y:v,_x0:s?i+l.TL[0]:d-h*n.r,_x1:s?i+l.TR[0]:d+h*n.r,_y0:s?a+l.TL[1]:v-h*n.r,_y1:s?a+l.BL[1]:v+h*n.r,text:b.join(\"<br>\"),name:c.hovertemplate||f.indexOf(\"name\")!==-1?c.name:void 0,idealAlign:l.pxmid[0]<0?\"left\":\"right\",color:ns.castOption(k.bgcolor,l.pts)||l.color,borderColor:ns.castOption(k.bordercolor,l.pts),fontFamily:ns.castOption(E.family,l.pts),fontSize:ns.castOption(E.size,l.pts),fontColor:ns.castOption(E.color,l.pts),nameLength:ns.castOption(k.namelength,l.pts),textAlign:ns.castOption(k.align,l.pts),hovertemplate:ns.castOption(c.hovertemplate,l.pts),hovertemplateLabels:l,eventData:[gD(l,c)]},{container:u._hoverlayer.node(),outerContainer:u._paper.node(),gd:t,inOut_bbox:S}),l.bbox=S[0],o._hasHoverLabel=!0}o._hasHoverEvent=!0,t.emit(\"plotly_hover\",{points:[gD(l,c)],event:Fp.event})}}),e.on(\"mouseout\",function(l){var u=t._fullLayout,c=t._fullData[o.index],f=Fp.select(this).datum();o._hasHoverEvent&&(l.originalEvent=Fp.event,t.emit(\"plotly_unhover\",{points:[gD(f,c)],event:Fp.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(pD.loneUnhover(u._hoverlayer.node()),o._hasHoverLabel=!1)}),e.on(\"click\",function(l){var u=t._fullLayout,c=t._fullData[o.index];t._dragging||u.hovermode===!1||(t._hoverdata=[gD(l,c)],pD.click(t,Fp.event))})}function VCt(e,t,r){var n=ns.castOption(e.outsidetextfont.color,t.pts)||ns.castOption(e.textfont.color,t.pts)||r.color,i=ns.castOption(e.outsidetextfont.family,t.pts)||ns.castOption(e.textfont.family,t.pts)||r.family,a=ns.castOption(e.outsidetextfont.size,t.pts)||ns.castOption(e.textfont.size,t.pts)||r.size,o=ns.castOption(e.outsidetextfont.weight,t.pts)||ns.castOption(e.textfont.weight,t.pts)||r.weight,s=ns.castOption(e.outsidetextfont.style,t.pts)||ns.castOption(e.textfont.style,t.pts)||r.style,l=ns.castOption(e.outsidetextfont.variant,t.pts)||ns.castOption(e.textfont.variant,t.pts)||r.variant,u=ns.castOption(e.outsidetextfont.textcase,t.pts)||ns.castOption(e.textfont.textcase,t.pts)||r.textcase,c=ns.castOption(e.outsidetextfont.lineposition,t.pts)||ns.castOption(e.textfont.lineposition,t.pts)||r.lineposition,f=ns.castOption(e.outsidetextfont.shadow,t.pts)||ns.castOption(e.textfont.shadow,t.pts)||r.shadow;return{color:n,family:i,size:a,weight:o,style:s,variant:l,textcase:u,lineposition:c,shadow:f}}function gke(e,t,r){var n=ns.castOption(e.insidetextfont.color,t.pts);!n&&e._input.textfont&&(n=ns.castOption(e._input.textfont.color,t.pts));var i=ns.castOption(e.insidetextfont.family,t.pts)||ns.castOption(e.textfont.family,t.pts)||r.family,a=ns.castOption(e.insidetextfont.size,t.pts)||ns.castOption(e.textfont.size,t.pts)||r.size,o=ns.castOption(e.insidetextfont.weight,t.pts)||ns.castOption(e.textfont.weight,t.pts)||r.weight,s=ns.castOption(e.insidetextfont.style,t.pts)||ns.castOption(e.textfont.style,t.pts)||r.style,l=ns.castOption(e.insidetextfont.variant,t.pts)||ns.castOption(e.textfont.variant,t.pts)||r.variant,u=ns.castOption(e.insidetextfont.textcase,t.pts)||ns.castOption(e.textfont.textcase,t.pts)||r.textcase,c=ns.castOption(e.insidetextfont.lineposition,t.pts)||ns.castOption(e.textfont.lineposition,t.pts)||r.lineposition,f=ns.castOption(e.insidetextfont.shadow,t.pts)||ns.castOption(e.textfont.shadow,t.pts)||r.shadow;return{color:n||hke.contrast(t.color),family:i,size:a,weight:o,style:s,variant:l,textcase:u,lineposition:c,shadow:f}}function mke(e,t){for(var r,n,i=0;i<e.length;i++)if(r=e[i][0],n=r.trace,n.title.text){var a=n.title.text;n._meta&&(a=rv.templateString(a,n._meta));var o=Wy.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(Wy.font,n.title.font).call(pW.convertToTspans,t),s=Wy.bBox(o.node(),!0);r.titleBox={width:s.width,height:s.height},o.remove()}}function yke(e,t,r){var n=r.r||t.rpx1,i=t.rInscribed,a=t.startangle===t.stopangle;if(a)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var o=t.ring,s=o===1&&Math.abs(t.startangle-t.stopangle)===Math.PI*2,l=t.halfangle,u=t.midangle,c=r.trace.insidetextorientation,f=c===\"horizontal\",h=c===\"tangential\",d=c===\"radial\",v=c===\"auto\",_=[],b;if(!v){var p=function(M,g){if(GCt(t,M)){var P=Math.abs(M-t.startangle),T=Math.abs(M-t.stopangle),z=P<T?P:T;g===\"tan\"?b=cke(e,n,o,z,0):b=uke(e,n,o,z,Math.PI/2),b.textPosAngle=M,_.push(b)}},k;if(f||h){for(k=4;k>=-4;k-=2)p(Math.PI*k,\"tan\");for(k=4;k>=-4;k-=2)p(Math.PI*(k+1),\"tan\")}if(f||d){for(k=4;k>=-4;k-=2)p(Math.PI*(k+1.5),\"rad\");for(k=4;k>=-4;k-=2)p(Math.PI*(k+.5),\"rad\")}}if(s||v||f){var E=Math.sqrt(e.width*e.width+e.height*e.height);if(b={scale:i*n*2/E,rCenter:1-i,rotate:0},b.textPosAngle=(t.startangle+t.stopangle)/2,b.scale>=1)return b;_.push(b)}(v||d)&&(b=uke(e,n,o,l,u),b.textPosAngle=(t.startangle+t.stopangle)/2,_.push(b)),(v||h)&&(b=cke(e,n,o,l,u),b.textPosAngle=(t.startangle+t.stopangle)/2,_.push(b));for(var S=0,L=0,x=0;x<_.length;x++){var C=_[x].scale;if(L<C&&(L=C,S=x),!v&&L>=1)break}return _[S]}function GCt(e,t){var r=e.startangle,n=e.stopangle;return r>t&&t>n||r<t&&t<n}function uke(e,t,r,n,i){t=Math.max(0,t-2*vke);var a=e.width/e.height,o=bke(a,n,t,r);return{scale:o*2/e.height,rCenter:_ke(a,o/t),rotate:xke(i)}}function cke(e,t,r,n,i){t=Math.max(0,t-2*vke);var a=e.height/e.width,o=bke(a,n,t,r);return{scale:o*2/e.width,rCenter:_ke(a,o/t),rotate:xke(i+Math.PI/2)}}function _ke(e,t){return Math.cos(t)-e*t}function xke(e){return(180/Math.PI*e+720)%180-90}function bke(e,t,r,n){var i=e+1/(2*Math.tan(t));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(e*e+n/2)+e))}function HCt(e,t){return e.v===t.vTotal&&!t.trace.hole?1:Math.min(1/(1+1/Math.sin(e.halfangle)),e.ring/2)}function fke(e,t){var r=t.pxmid[0],n=t.pxmid[1],i=e.width/2,a=e.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function jCt(e){var t=Math.sqrt(e.titleBox.width*e.titleBox.width+e.titleBox.height*e.titleBox.height);return{x:e.cx,y:e.cy,scale:e.trace.hole*e.r*2/t,tx:0,ty:-e.titleBox.height/2+e.trace.title.font.size}}function wke(e,t){var r=1,n=1,i,a=e.trace,o={x:e.cx,y:e.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=Tke(a),a.title.position.indexOf(\"top\")!==-1?(o.y-=(1+i)*e.r,s.ty-=e.titleBox.height):a.title.position.indexOf(\"bottom\")!==-1&&(o.y+=(1+i)*e.r);var l=WCt(e.r,e.trace.aspectratio),u=t.w*(a.domain.x[1]-a.domain.x[0])/2;return a.title.position.indexOf(\"left\")!==-1?(u=u+l,o.x-=(1+i)*l,s.tx+=e.titleBox.width/2):a.title.position.indexOf(\"center\")!==-1?u*=2:a.title.position.indexOf(\"right\")!==-1&&(u=u+l,o.x+=(1+i)*l,s.tx-=e.titleBox.width/2),r=u/e.titleBox.width,n=gW(e,t)/e.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function WCt(e,t){return e/(t===void 0?1:t)}function gW(e,t){var r=e.trace,n=t.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(e.titleBox.height,n/2)}function Tke(e){var t=e.pull;if(!t)return 0;var r;if(rv.isArrayOrTypedArray(t))for(t=0,r=0;r<e.pull.length;r++)e.pull[r]>t&&(t=e.pull[r]);return t}function XCt(e,t){var r,n,i,a,o,s,l,u,c,f,h,d,v;function _(E,S){return E.pxmid[1]-S.pxmid[1]}function b(E,S){return S.pxmid[1]-E.pxmid[1]}function p(E,S){S||(S={});var L=S.labelExtraY+(n?S.yLabelMax:S.yLabelMin),x=n?E.yLabelMin:E.yLabelMax,C=n?E.yLabelMax:E.yLabelMin,M=E.cyFinal+o(E.px0[1],E.px1[1]),g=L-x,P,T,z,O,V,G;if(g*l>0&&(E.labelExtraY=g),!!rv.isArrayOrTypedArray(t.pull))for(T=0;T<f.length;T++)z=f[T],!(z===E||(ns.castOption(t.pull,E.pts)||0)>=(ns.castOption(t.pull,z.pts)||0))&&((E.pxmid[1]-z.pxmid[1])*l>0?(O=z.cyFinal+o(z.px0[1],z.px1[1]),g=O-x-E.labelExtraY,g*l>0&&(E.labelExtraY+=g)):(C+E.labelExtraY-M)*l>0&&(P=3*s*Math.abs(T-f.indexOf(E)),V=z.cxFinal+a(z.px0[0],z.px1[0]),G=V+P-(E.cxFinal+E.pxmid[0])-E.labelExtraX,G*s>0&&(E.labelExtraX+=G)))}for(n=0;n<2;n++)for(i=n?_:b,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,u=e[n][r],u.sort(i),c=e[1-n][r],f=c.concat(u),d=[],h=0;h<u.length;h++)u[h].yLabelMid!==void 0&&d.push(u[h]);for(v=!1,h=0;n&&h<c.length;h++)if(c[h].yLabelMid!==void 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E+b6e(me)[0]*(me.transform.rCenter||0)+(me.transform.x||0)},H=function(me){return S+b6e(me)[1]*(me.transform.rCenter||0)+(me.transform.y||0)};l=l.data(C,Rl.getPtId),l.enter().append(\"g\").classed(\"slice\",!0),o?l.exit().transition().each(function(){var me=jE.select(this),ie=me.select(\"path.surface\");ie.transition().attrTween(\"d\",function(Le){var Ae=oe(Le);return function(Fe){return G(Ae(Fe))}});var Se=me.select(\"g.slicetext\");Se.attr(\"opacity\",0)}).remove():l.exit().remove(),l.order();var N=null;if(o&&L){var j=Rl.getPtId(L);l.each(function(me){N===null&&Rl.getPtId(me)===j&&(N=me.x1)})}var re=l;o&&(re=re.transition().each(\"end\",function(){var me=jE.select(this);Rl.setSliceCursor(me,e,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:!1})})),re.each(function(me){var ie=jE.select(this),Se=Av.ensureSingle(ie,\"path\",\"surface\",function(Re){Re.style(\"pointer-events\",i?\"none\":\"all\")});me.rpx0=O(me.y0),me.rpx1=O(me.y1),me.xmid=(me.x0+me.x1)/2,me.pxmid=V(me.rpx1,me.xmid),me.midangle=-(me.xmid-Math.PI/2),me.startangle=-(me.x0-Math.PI/2),me.stopangle=-(me.x1-Math.PI/2),me.halfangle=.5*Math.min(Av.angleDelta(me.x0,me.x1)||Math.PI,Math.PI),me.ring=1-me.rpx0/me.rpx1,me.rInscribed=uLt(me,c),o?Se.transition().attrTween(\"d\",function(Re){var ce=_e(Re);return function(Ze){return G(ce(Ze))}}):Se.attr(\"d\",G),ie.call(sLt,h,e,t,{eventDataKeys:VW.eventDataKeys,transitionTime:VW.CLICK_TRANSITION_TIME,transitionEasing:VW.CLICK_TRANSITION_EASING}).call(Rl.setSliceCursor,e,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:e._transitioning}),Se.call(aLt,me,c,e);var Le=Av.ensureSingle(ie,\"g\",\"slicetext\"),Ae=Av.ensureSingle(Le,\"text\",\"\",function(Re){Re.attr(\"data-notex\",1)}),Fe=Av.ensureUniformFontSize(e,Rl.determineTextFont(c,me,a.font));Ae.text(ND.formatSliceLabel(me,h,c,t,a)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(y6e.font,Fe).call(eLt.convertToTspans,e);var Pe=y6e.bBox(Ae.node());me.transform=nLt(Pe,me,u),me.transform.targetX=Z(me),me.transform.targetY=H(me);var ge=function(Re,ce){var Ze=Re.transform;return iLt(Ze,ce),Ze.fontSize=Fe.size,_6e(c.type,Ze,a),Av.getTextTransform(Ze)};o?Ae.transition().attrTween(\"transform\",function(Re){var ce=Ee(Re);return function(Ze){return ge(ce(Ze),Pe)}}):Ae.attr(\"transform\",ge(me,Pe))});function oe(me){var ie=Rl.getPtId(me),Se=x[ie],Le=x[Rl.getPtId(h)],Ae;if(Le){var Fe=(me.x1>Le.x1?2*Math.PI:0)+T;Ae=me.rpx1<Le.rpx1?{x0:me.x0,x1:me.x1,rpx0:0,rpx1:0}:{x0:Fe,x1:Fe,rpx0:me.rpx0,rpx1:me.rpx1}}else{var Pe,ge=Rl.getPtId(me.parent);l.each(function(pt){if(Rl.getPtId(pt)===ge)return 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Fe=Zg(Se.transform.textPosAngle,me.transform.textPosAngle),Pe=Zg(Se.rpx1,me.rpx1),ge=Zg(Se.x0,me.x0),Re=Zg(Se.x1,me.x1),ce=Zg(Se.transform.scale,Le.scale),Ze=Zg(Se.transform.rotate,Le.rotate),ut=Le.rCenter===0?3:Se.transform.rCenter===0?1/3:1,pt=Zg(Se.transform.rCenter,Le.rCenter),Zt=function(st){return pt(Math.pow(st,ut))};return function(st){var lt=Pe(st),Gt=ge(st),Nt=Re(st),Jt=Zt(st),sr=V(lt,(Gt+Nt)/2),wr=Fe(st),cr={pxmid:sr,rpx1:lt,transform:{textPosAngle:wr,rCenter:Jt,x:Le.x,y:Le.y}};return _6e(c.type,Le,a),{transform:{targetX:Z(cr),targetY:H(cr),scale:ce(st),rotate:Ze(st),rCenter:Jt}}}}function Ce(me){var ie=me.parent,Se=x[Rl.getPtId(ie)],Le={};if(Se){var Ae=ie.children,Fe=Ae.indexOf(me),Pe=Ae.length,ge=Zg(Se.x0,Se.x1);Le.x0=ge(Fe/Pe),Le.x1=ge(Fe/Pe)}else Le.x0=Le.x1=0;return Le}}function lLt(e){return Q6t.partition().size([2*Math.PI,e.height+1])(e)}ND.formatSliceLabel=function(e,t,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!a&&(!o||o===\"none\"))return\"\";var s=i.separators,l=n[0],u=e.data.data,c=l.hierarchy,f=Rl.isHierarchyRoot(e),h=Rl.getParent(c,e),d=Rl.getValue(e);if(!a){var v=o.split(\"+\"),_=function(g){return v.indexOf(g)!==-1},b=[],p;if(_(\"label\")&&u.label&&b.push(u.label),u.hasOwnProperty(\"v\")&&_(\"value\")&&b.push(Rl.formatValue(u.v,s)),!f){_(\"current path\")&&b.push(Rl.getPath(e.data));var k=0;_(\"percent parent\")&&k++,_(\"percent entry\")&&k++,_(\"percent root\")&&k++;var E=k>1;if(k){var S,L=function(g){p=Rl.formatPercent(S,s),E&&(p+=\" of \"+g),b.push(p)};_(\"percent parent\")&&!f&&(S=d/Rl.getValue(h),L(\"parent\")),_(\"percent entry\")&&(S=d/Rl.getValue(t),L(\"entry\")),_(\"percent root\")&&(S=d/Rl.getValue(c),L(\"root\"))}}return _(\"text\")&&(p=Av.castOption(r,u.i,\"text\"),Av.isValidTextValue(p)&&b.push(p)),b.join(\"<br>\")}var x=Av.castOption(r,u.i,\"texttemplate\");if(!x)return\"\";var C={};u.label&&(C.label=u.label),u.hasOwnProperty(\"v\")&&(C.value=u.v,C.valueLabel=Rl.formatValue(u.v,s)),C.currentPath=Rl.getPath(e.data),f||(C.percentParent=d/Rl.getValue(h),C.percentParentLabel=Rl.formatPercent(C.percentParent,s),C.parent=Rl.getPtLabel(h)),C.percentEntry=d/Rl.getValue(t),C.percentEntryLabel=Rl.formatPercent(C.percentEntry,s),C.entry=Rl.getPtLabel(t),C.percentRoot=d/Rl.getValue(c),C.percentRootLabel=Rl.formatPercent(C.percentRoot,s),C.root=Rl.getPtLabel(c),u.hasOwnProperty(\"color\")&&(C.color=u.color);var M=Av.castOption(r,u.i,\"text\");return(Av.isValidTextValue(M)||M===\"\")&&(C.text=M),C.customdata=Av.castOption(r,u.i,\"customdata\"),Av.texttemplateString({data:[C,r._meta],fallback:r.texttemplatefallback,labels:C,locale:i._d3locale,template:x})};function uLt(e){return e.rpx0===0&&Av.isFullCircle([e.x0,e.x1])?1:Math.max(0,Math.min(1/(1+1/Math.sin(e.halfangle)),e.ring/2))}function b6e(e){return cLt(e.rpx1,e.transform.textPosAngle)}function cLt(e,t){return[e*Math.sin(t),-e*Math.cos(t)]}});var S6e=ye((e0r,A6e)=>{\"use strict\";A6e.exports={moduleType:\"trace\",name:\"sunburst\",basePlotModule:qke(),categories:[],animatable:!0,attributes:LE(),layoutAttributes:yW(),supplyDefaults:Xke(),supplyLayoutDefaults:Yke(),calc:RE().calc,crossTraceCalc:RE().crossTraceCalc,plot:UD().plot,style:UW().style,colorbar:$d(),meta:{}}});var E6e=ye((t0r,M6e)=>{\"use strict\";M6e.exports=S6e()});var C6e=ye(DA=>{\"use strict\";var k6e=Mc();DA.name=\"treemap\";DA.plot=function(e,t,r,n){k6e.plotBasePlot(DA.name,e,t,r,n)};DA.clean=function(e,t,r,n){k6e.cleanBasePlot(DA.name,e,t,r,n)}});var z2=ye((i0r,L6e)=>{\"use strict\";L6e.exports={CLICK_TRANSITION_TIME:750,CLICK_TRANSITION_EASING:\"poly\",eventDataKeys:[\"currentPath\",\"root\",\"entry\",\"percentRoot\",\"percentEntry\",\"percentParent\"],gapWithPathbar:1}});var VD=ye((n0r,R6e)=>{\"use 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u=a(\"tiling.packing\");u===\"squarify\"&&a(\"tiling.squarifyratio\"),a(\"tiling.flip\"),a(\"tiling.pad\");var c=a(\"text\");a(\"texttemplate\"),a(\"texttemplatefallback\"),r.texttemplate||a(\"textinfo\",F6e.isArrayOrTypedArray(c)?\"text+label\":\"label\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\");var f=a(\"pathbar.visible\"),h=\"auto\";_Lt(t,r,i,a,h,{hasPathbar:f,moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),a(\"textposition\");var d=r.textposition.indexOf(\"bottom\")!==-1;bLt(t,r,i,a);var v=r._hasColorscale=wLt(t,\"marker\",\"colors\")||(t.marker||{}).coloraxis;v?TLt(t,r,i,a,{prefix:\"marker.\",cLetter:\"c\"}):a(\"marker.depthfade\",!(r.marker.colors||[]).length);var _=r.textfont.size*2;a(\"marker.pad.t\",d?_/4:_),a(\"marker.pad.l\",_/4),a(\"marker.pad.r\",_/4),a(\"marker.pad.b\",d?_:_/4),a(\"marker.cornerradius\"),r._hovered={marker:{line:{width:2,color:mLt.contrast(i.paper_bgcolor)}}},f&&(a(\"pathbar.thickness\",r.pathbar.textfont.size+2*xLt),a(\"pathbar.side\"),a(\"pathbar.edgeshape\")),a(\"sort\"),a(\"root.color\"),yLt(r,i,a),r._length=null}});var N6e=ye((s0r,B6e)=>{\"use strict\";var ALt=Dr(),SLt=HW();B6e.exports=function(t,r){function n(i,a){return ALt.coerce(t,r,SLt,i,a)}n(\"treemapcolorway\",r.colorway),n(\"extendtreemapcolors\")}});var WW=ye(jW=>{\"use strict\";var U6e=RE();jW.calc=function(e,t){return U6e.calc(e,t)};jW.crossTraceCalc=function(e){return U6e._runCrossTraceCalc(\"treemap\",e)}});var XW=ye((u0r,V6e)=>{\"use strict\";V6e.exports=function e(t,r,n){var i;n.swapXY&&(i=t.x0,t.x0=t.y0,t.y0=i,i=t.x1,t.x1=t.y1,t.y1=i),n.flipX&&(i=t.x0,t.x0=r[0]-t.x1,t.x1=r[0]-i),n.flipY&&(i=t.y0,t.y0=r[1]-t.y1,t.y1=r[1]-i);var a=t.children;if(a)for(var o=0;o<a.length;o++)e(a[o],r,n)}});var ZW=ye((c0r,G6e)=>{\"use strict\";var FA=PE(),MLt=XW();G6e.exports=function(t,r,n){var i=n.flipX,a=n.flipY,o=n.packing===\"dice-slice\",s=n.pad[a?\"bottom\":\"top\"],l=n.pad[i?\"right\":\"left\"],u=n.pad[i?\"left\":\"right\"],c=n.pad[a?\"top\":\"bottom\"],f;o&&(f=l,l=s,s=f,f=u,u=c,c=f);var h=FA.treemap().tile(ELt(n.packing,n.squarifyratio)).paddingInner(n.pad.inner).paddingLeft(l).paddingRight(u).paddingTop(s).paddingBottom(c).size(o?[r[1],r[0]]:r)(t);return(o||i||a)&&MLt(h,r,{swapXY:o,flipX:i,flipY:a}),h};function ELt(e,t){switch(e){case\"squarify\":return FA.treemapSquarify.ratio(t);case\"binary\":return FA.treemapBinary;case\"dice\":return FA.treemapDice;case\"slice\":return FA.treemapSlice;default:return FA.treemapSliceDice}}});var GD=ye((f0r,X6e)=>{\"use strict\";var H6e=Oa(),zA=ka(),j6e=Dr(),YW=Ky(),kLt=bv().resizeText,CLt=BD();function LLt(e){var 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+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "vec3 getOrthogonalVector(vec3 v) {\n",
+       "  // Return up-vector for only-z vector.\n",
+       "  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n",
+       "  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n",
+       "  // Assign z = 0, x = -b, y = a:\n",
+       "  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n",
+       "  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n",
+       "    return normalize(vec3(-v.y, v.x, 0.0));\n",
+       "  } else {\n",
+       "    return normalize(vec3(0.0, v.z, -v.y));\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "// Calculate the cone vertex and normal at the given index.\n",
+       "//\n",
+       "// The returned vertex is for a cone with its top at origin and height of 1.0,\n",
+       "// pointing in the direction of the vector attribute.\n",
+       "//\n",
+       "// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n",
+       "// These vertices are used to make up the triangles of the cone by the following:\n",
+       "//   segment + 0 top vertex\n",
+       "//   segment + 1 perimeter vertex a+1\n",
+       "//   segment + 2 perimeter vertex a\n",
+       "//   segment + 3 center base vertex\n",
+       "//   segment + 4 perimeter vertex a\n",
+       "//   segment + 5 perimeter vertex a+1\n",
+       "// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n",
+       "// To go from index to segment, floor(index / 6)\n",
+       "// To go from segment to angle, 2*pi * (segment/segmentCount)\n",
+       "// To go from index to segment index, index - (segment*6)\n",
+       "//\n",
+       "vec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n",
+       "\n",
+       "  const float segmentCount = 8.0;\n",
+       "\n",
+       "  float index = rawIndex - floor(rawIndex /\n",
+       "    (segmentCount * 6.0)) *\n",
+       "    (segmentCount * 6.0);\n",
+       "\n",
+       "  float segment = floor(0.001 + index/6.0);\n",
+       "  float segmentIndex = index - (segment*6.0);\n",
+       "\n",
+       "  normal = -normalize(d);\n",
+       "\n",
+       "  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n",
+       "    return mix(vec3(0.0), -d, coneOffset);\n",
+       "  }\n",
+       "\n",
+       "  float nextAngle = (\n",
+       "    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\n",
+       "    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\n",
+       "  ) ? 1.0 : 0.0;\n",
+       "  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n",
+       "\n",
+       "  vec3 v1 = mix(d, vec3(0.0), coneOffset);\n",
+       "  vec3 v2 = v1 - d;\n",
+       "\n",
+       "  vec3 u = getOrthogonalVector(d);\n",
+       "  vec3 v = normalize(cross(u, d));\n",
+       "\n",
+       "  vec3 x = u * cos(angle) * length(d)*0.25;\n",
+       "  vec3 y = v * sin(angle) * length(d)*0.25;\n",
+       "  vec3 v3 = v2 + x + y;\n",
+       "  if (segmentIndex < 3.0) {\n",
+       "    vec3 tx = u * sin(angle);\n",
+       "    vec3 ty = v * -cos(angle);\n",
+       "    vec3 tangent = tx + ty;\n",
+       "    normal = normalize(cross(v3 - v1, tangent));\n",
+       "  }\n",
+       "\n",
+       "  if (segmentIndex == 0.0) {\n",
+       "    return mix(d, vec3(0.0), coneOffset);\n",
+       "  }\n",
+       "  return v3;\n",
+       "}\n",
+       "\n",
+       "attribute vec3 vector;\n",
+       "attribute vec4 color, position;\n",
+       "attribute vec2 uv;\n",
+       "\n",
+       "uniform float vectorScale, coneScale, coneOffset;\n",
+       "uniform mat4 model, view, projection, inverseModel;\n",
+       "uniform vec3 eyePosition, lightPosition;\n",
+       "\n",
+       "varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  // Scale the vector magnitude to stay constant with\n",
+       "  // model & view changes.\n",
+       "  vec3 normal;\n",
+       "  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\n",
+       "  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n",
+       "\n",
+       "  //Lighting geometry parameters\n",
+       "  vec4 cameraCoordinate = view * conePosition;\n",
+       "  cameraCoordinate.xyz /= cameraCoordinate.w;\n",
+       "  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n",
+       "  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n",
+       "  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n",
+       "\n",
+       "  // vec4 m_position  = model * vec4(conePosition, 1.0);\n",
+       "  vec4 t_position  = view * conePosition;\n",
+       "  gl_Position      = projection * t_position;\n",
+       "\n",
+       "  f_color          = color;\n",
+       "  f_data           = conePosition.xyz;\n",
+       "  f_position       = position.xyz;\n",
+       "  f_uv             = uv;\n",
+       "}\n",
+       "`]),u=s([`#extension GL_OES_standard_derivatives : enable\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "float beckmannDistribution(float x, float roughness) {\n",
+       "  float NdotH = max(x, 0.0001);\n",
+       "  float cos2Alpha = NdotH * NdotH;\n",
+       "  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n",
+       "  float roughness2 = roughness * roughness;\n",
+       "  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n",
+       "  return exp(tan2Alpha / roughness2) / denom;\n",
+       "}\n",
+       "\n",
+       "float cookTorranceSpecular(\n",
+       "  vec3 lightDirection,\n",
+       "  vec3 viewDirection,\n",
+       "  vec3 surfaceNormal,\n",
+       "  float roughness,\n",
+       "  float fresnel) {\n",
+       "\n",
+       "  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n",
+       "  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n",
+       "\n",
+       "  //Half angle vector\n",
+       "  vec3 H = normalize(lightDirection + viewDirection);\n",
+       "\n",
+       "  //Geometric term\n",
+       "  float NdotH = max(dot(surfaceNormal, H), 0.0);\n",
+       "  float VdotH = max(dot(viewDirection, H), 0.000001);\n",
+       "  float LdotH = max(dot(lightDirection, H), 0.000001);\n",
+       "  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n",
+       "  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n",
+       "  float G = min(1.0, min(G1, G2));\n",
+       "  \n",
+       "  //Distribution term\n",
+       "  float D = beckmannDistribution(NdotH, roughness);\n",
+       "\n",
+       "  //Fresnel term\n",
+       "  float F = pow(1.0 - VdotN, fresnel);\n",
+       "\n",
+       "  //Multiply terms and done\n",
+       "  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\n",
+       "uniform sampler2D texture;\n",
+       "\n",
+       "varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n",
+       "  vec3 N = normalize(f_normal);\n",
+       "  vec3 L = normalize(f_lightDirection);\n",
+       "  vec3 V = normalize(f_eyeDirection);\n",
+       "\n",
+       "  if(gl_FrontFacing) {\n",
+       "    N = -N;\n",
+       "  }\n",
+       "\n",
+       "  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n",
+       "  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n",
+       "\n",
+       "  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n",
+       "  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n",
+       "\n",
+       "  gl_FragColor = litColor * opacity;\n",
+       "}\n",
+       "`]),c=s([`precision highp float;\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "vec3 getOrthogonalVector(vec3 v) {\n",
+       "  // Return up-vector for only-z vector.\n",
+       "  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n",
+       "  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n",
+       "  // Assign z = 0, x = -b, y = a:\n",
+       "  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n",
+       "  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n",
+       "    return normalize(vec3(-v.y, v.x, 0.0));\n",
+       "  } else {\n",
+       "    return normalize(vec3(0.0, v.z, -v.y));\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "// Calculate the cone vertex and normal at the given index.\n",
+       "//\n",
+       "// The returned vertex is for a cone with its top at origin and height of 1.0,\n",
+       "// pointing in the direction of the vector attribute.\n",
+       "//\n",
+       "// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n",
+       "// These vertices are used to make up the triangles of the cone by the following:\n",
+       "//   segment + 0 top vertex\n",
+       "//   segment + 1 perimeter vertex a+1\n",
+       "//   segment + 2 perimeter vertex a\n",
+       "//   segment + 3 center base vertex\n",
+       "//   segment + 4 perimeter vertex a\n",
+       "//   segment + 5 perimeter vertex a+1\n",
+       "// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n",
+       "// To go from index to segment, floor(index / 6)\n",
+       "// To go from segment to angle, 2*pi * (segment/segmentCount)\n",
+       "// To go from index to segment index, index - (segment*6)\n",
+       "//\n",
+       "vec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n",
+       "\n",
+       "  const float segmentCount = 8.0;\n",
+       "\n",
+       "  float index = rawIndex - floor(rawIndex /\n",
+       "    (segmentCount * 6.0)) *\n",
+       "    (segmentCount * 6.0);\n",
+       "\n",
+       "  float segment = floor(0.001 + index/6.0);\n",
+       "  float segmentIndex = index - (segment*6.0);\n",
+       "\n",
+       "  normal = -normalize(d);\n",
+       "\n",
+       "  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n",
+       "    return mix(vec3(0.0), -d, coneOffset);\n",
+       "  }\n",
+       "\n",
+       "  float nextAngle = (\n",
+       "    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\n",
+       "    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\n",
+       "  ) ? 1.0 : 0.0;\n",
+       "  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n",
+       "\n",
+       "  vec3 v1 = mix(d, vec3(0.0), coneOffset);\n",
+       "  vec3 v2 = v1 - d;\n",
+       "\n",
+       "  vec3 u = getOrthogonalVector(d);\n",
+       "  vec3 v = normalize(cross(u, d));\n",
+       "\n",
+       "  vec3 x = u * cos(angle) * length(d)*0.25;\n",
+       "  vec3 y = v * sin(angle) * length(d)*0.25;\n",
+       "  vec3 v3 = v2 + x + y;\n",
+       "  if (segmentIndex < 3.0) {\n",
+       "    vec3 tx = u * sin(angle);\n",
+       "    vec3 ty = v * -cos(angle);\n",
+       "    vec3 tangent = tx + ty;\n",
+       "    normal = normalize(cross(v3 - v1, tangent));\n",
+       "  }\n",
+       "\n",
+       "  if (segmentIndex == 0.0) {\n",
+       "    return mix(d, vec3(0.0), coneOffset);\n",
+       "  }\n",
+       "  return v3;\n",
+       "}\n",
+       "\n",
+       "attribute vec4 vector;\n",
+       "attribute vec4 position;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform float vectorScale, coneScale, coneOffset;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 normal;\n",
+       "  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\n",
+       "  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n",
+       "  gl_Position = projection * (view * conePosition);\n",
+       "  f_id        = id;\n",
+       "  f_position  = position.xyz;\n",
+       "}\n",
+       "`]),f=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3  clipBounds[2];\n",
+       "uniform float pickId;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n",
+       "\n",
+       "  gl_FragColor = vec4(pickId, f_id.xyz);\n",
+       "}`]);a.meshShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},a.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},620:function(i){i.exports=[\"precision\",\"highp\",\"mediump\",\"lowp\",\"attribute\",\"const\",\"uniform\",\"varying\",\"break\",\"continue\",\"do\",\"for\",\"while\",\"if\",\"else\",\"in\",\"out\",\"inout\",\"float\",\"int\",\"uint\",\"void\",\"bool\",\"true\",\"false\",\"discard\",\"return\",\"mat2\",\"mat3\",\"mat4\",\"vec2\",\"vec3\",\"vec4\",\"ivec2\",\"ivec3\",\"ivec4\",\"bvec2\",\"bvec3\",\"bvec4\",\"sampler1D\",\"sampler2D\",\"sampler3D\",\"samplerCube\",\"sampler1DShadow\",\"sampler2DShadow\",\"struct\",\"asm\",\"class\",\"union\",\"enum\",\"typedef\",\"template\",\"this\",\"packed\",\"goto\",\"switch\",\"default\",\"inline\",\"noinline\",\"volatile\",\"public\",\"static\",\"extern\",\"external\",\"interface\",\"long\",\"short\",\"double\",\"half\",\"fixed\",\"unsigned\",\"input\",\"output\",\"hvec2\",\"hvec3\",\"hvec4\",\"dvec2\",\"dvec3\",\"dvec4\",\"fvec2\",\"fvec3\",\"fvec4\",\"sampler2DRect\",\"sampler3DRect\",\"sampler2DRectShadow\",\"sizeof\",\"cast\",\"namespace\",\"using\"]},665:function(i,a,o){\"use 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S=0;S<l;++S)i.exports[S]=p[S]}E()},737:function(i){i.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},781:function(i,a,o){\"use strict\";i.exports=l;var s=o(3349);function l(u,c){var f=[];return c=+c||0,s(u.hi(u.shape[0]-1),f,c),f}},783:function(i){i.exports=a;function a(o,s,l,u){var c=s[0],f=s[1],h=s[2],d=s[3],v=l[0],_=l[1],b=l[2],p=l[3],k,E,S,L,x;return E=c*v+f*_+h*b+d*p,E<0&&(E=-E,v=-v,_=-_,b=-b,p=-p),1-E>1e-6?(k=Math.acos(E),S=Math.sin(k),L=Math.sin((1-u)*k)/S,x=Math.sin(u*k)/S):(L=1-u,x=u),o[0]=L*c+x*v,o[1]=L*f+x*_,o[2]=L*h+x*b,o[3]=L*d+x*p,o}},799:function(i,a,o){var s=o(3236),l=o(9405),u=s([`precision mediump float;\n",
+       "#define GLSLIFY 1\n",
+       "attribute vec2 position;\n",
+       "varying vec2 uv;\n",
+       "void main() {\n",
+       "  uv = position;\n",
+       "  gl_Position = vec4(position, 0, 1);\n",
+       "}`]),c=s([`precision mediump float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform sampler2D accumBuffer;\n",
+       "varying vec2 uv;\n",
+       "\n",
+       "void main() {\n",
+       "  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\n",
+       "  gl_FragColor = min(vec4(1,1,1,1), accum);\n",
+       "}`]);i.exports=function(f){return l(f,u,c,null,[{name:\"position\",type:\"vec2\"}])}},811:function(i){i.exports=a;function a(o,s){return o[0]=1/s[0],o[1]=1/s[1],o[2]=1/s[2],o}},840:function(i,a,o){var s=o(3236),l=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position, normal;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 uv;\n",
+       "\n",
+       "uniform mat4 model\n",
+       "           , view\n",
+       "           , projection\n",
+       "           , inverseModel;\n",
+       "uniform vec3 eyePosition\n",
+       "           , lightPosition;\n",
+       "\n",
+       "varying vec3 f_normal\n",
+       "           , f_lightDirection\n",
+       "           , f_eyeDirection\n",
+       "           , f_data;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "vec4 project(vec3 p) {\n",
+       "  return projection * (view * (model * vec4(p, 1.0)));\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  gl_Position      = project(position);\n",
+       "\n",
+       "  //Lighting geometry parameters\n",
+       "  vec4 cameraCoordinate = view * vec4(position , 1.0);\n",
+       "  cameraCoordinate.xyz /= cameraCoordinate.w;\n",
+       "  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n",
+       "  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n",
+       "  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n",
+       "\n",
+       "  f_color          = color;\n",
+       "  f_data           = position;\n",
+       "  f_uv             = uv;\n",
+       "}\n",
+       "`]),u=s([`#extension GL_OES_standard_derivatives : enable\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "float beckmannDistribution(float x, float roughness) {\n",
+       "  float NdotH = max(x, 0.0001);\n",
+       "  float cos2Alpha = NdotH * NdotH;\n",
+       "  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n",
+       "  float roughness2 = roughness * roughness;\n",
+       "  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n",
+       "  return exp(tan2Alpha / roughness2) / denom;\n",
+       "}\n",
+       "\n",
+       "float cookTorranceSpecular(\n",
+       "  vec3 lightDirection,\n",
+       "  vec3 viewDirection,\n",
+       "  vec3 surfaceNormal,\n",
+       "  float roughness,\n",
+       "  float fresnel) {\n",
+       "\n",
+       "  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n",
+       "  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n",
+       "\n",
+       "  //Half angle vector\n",
+       "  vec3 H = normalize(lightDirection + viewDirection);\n",
+       "\n",
+       "  //Geometric term\n",
+       "  float NdotH = max(dot(surfaceNormal, H), 0.0);\n",
+       "  float VdotH = max(dot(viewDirection, H), 0.000001);\n",
+       "  float LdotH = max(dot(lightDirection, H), 0.000001);\n",
+       "  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n",
+       "  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n",
+       "  float G = min(1.0, min(G1, G2));\n",
+       "  \n",
+       "  //Distribution term\n",
+       "  float D = beckmannDistribution(NdotH, roughness);\n",
+       "\n",
+       "  //Fresnel term\n",
+       "  float F = pow(1.0 - VdotN, fresnel);\n",
+       "\n",
+       "  //Multiply terms and done\n",
+       "  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n",
+       "}\n",
+       "\n",
+       "//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float roughness\n",
+       "            , fresnel\n",
+       "            , kambient\n",
+       "            , kdiffuse\n",
+       "            , kspecular;\n",
+       "uniform sampler2D texture;\n",
+       "\n",
+       "varying vec3 f_normal\n",
+       "           , f_lightDirection\n",
+       "           , f_eyeDirection\n",
+       "           , f_data;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  if (f_color.a == 0.0 ||\n",
+       "    outOfRange(clipBounds[0], clipBounds[1], f_data)\n",
+       "  ) discard;\n",
+       "\n",
+       "  vec3 N = normalize(f_normal);\n",
+       "  vec3 L = normalize(f_lightDirection);\n",
+       "  vec3 V = normalize(f_eyeDirection);\n",
+       "\n",
+       "  if(gl_FrontFacing) {\n",
+       "    N = -N;\n",
+       "  }\n",
+       "\n",
+       "  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n",
+       "  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\n",
+       "\n",
+       "  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n",
+       "\n",
+       "  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\n",
+       "  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n",
+       "\n",
+       "  gl_FragColor = litColor * f_color.a;\n",
+       "}\n",
+       "`]),c=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 uv;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "\n",
+       "varying vec4 f_color;\n",
+       "varying vec3 f_data;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_Position = projection * (view * (model * vec4(position, 1.0)));\n",
+       "  f_color = color;\n",
+       "  f_data  = position;\n",
+       "  f_uv    = uv;\n",
+       "}`]),f=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform sampler2D texture;\n",
+       "uniform float opacity;\n",
+       "\n",
+       "varying vec4 f_color;\n",
+       "varying vec3 f_data;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\n",
+       "\n",
+       "  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n",
+       "}`]),h=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 uv;\n",
+       "attribute float pointSize;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n",
+       "\n",
+       "    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\n",
+       "  } else {\n",
+       "    gl_Position = projection * (view * (model * vec4(position, 1.0)));\n",
+       "  }\n",
+       "  gl_PointSize = pointSize;\n",
+       "  f_color = color;\n",
+       "  f_uv = uv;\n",
+       "}`]),d=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform sampler2D texture;\n",
+       "uniform float opacity;\n",
+       "\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\n",
+       "  if(dot(pointR, pointR) > 0.25) {\n",
+       "    discard;\n",
+       "  }\n",
+       "  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n",
+       "}`]),v=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_Position = projection * (view * (model * vec4(position, 1.0)));\n",
+       "  f_id        = id;\n",
+       "  f_position  = position;\n",
+       "}`]),_=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3  clipBounds[2];\n",
+       "uniform float pickId;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n",
+       "\n",
+       "  gl_FragColor = vec4(pickId, f_id.xyz);\n",
+       "}`]),b=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "attribute vec3  position;\n",
+       "attribute float pointSize;\n",
+       "attribute vec4  id;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n",
+       "\n",
+       "    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\n",
+       "  } else {\n",
+       "    gl_Position  = projection * (view * (model * vec4(position, 1.0)));\n",
+       "    gl_PointSize = pointSize;\n",
+       "  }\n",
+       "  f_id         = id;\n",
+       "  f_position   = position;\n",
+       "}`]),p=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_Position = projection * (view * (model * vec4(position, 1.0)));\n",
+       "}`]),k=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform vec3 contourColor;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_FragColor = vec4(contourColor, 1.0);\n",
+       "}\n",
+       "`]);a.meshShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},a.wireShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},a.pointShader={vertex:h,fragment:d,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},a.pickShader={vertex:v,fragment:_,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},a.pointPickShader={vertex:b,fragment:_,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},a.contourShader={vertex:p,fragment:k,attributes:[{name:\"position\",type:\"vec3\"}]}},855:function(i,a,o){\"use strict\";i.exports={init:E,sweepBipartite:x,sweepComplete:C,scanBipartite:M,scanComplete:g};var s=o(1888),l=o(8828),u=o(4192),c=1<<28,f=1024,h=s.mallocInt32(f),d=s.mallocInt32(f),v=s.mallocInt32(f),_=s.mallocInt32(f),b=s.mallocInt32(f),p=s.mallocInt32(f),k=s.mallocDouble(f*8);function E(P){var T=l.nextPow2(P);h.length<T&&(s.free(h),h=s.mallocInt32(T)),d.length<T&&(s.free(d),d=s.mallocInt32(T)),v.length<T&&(s.free(v),v=s.mallocInt32(T)),_.length<T&&(s.free(_),_=s.mallocInt32(T)),b.length<T&&(s.free(b),b=s.mallocInt32(T)),p.length<T&&(s.free(p),p=s.mallocInt32(T));var z=8*T;k.length<z&&(s.free(k),k=s.mallocDouble(z))}function S(P,T,z,O){var V=T[O],G=P[z-1];P[V]=G,T[G]=V}function L(P,T,z,O){P[z]=O,T[O]=z}function x(P,T,z,O,V,G,Z,H,N,j){for(var re=0,oe=2*P,_e=P-1,Ee=oe-1,Ce=z;Ce<O;++Ce){var me=G[Ce],ie=oe*Ce;k[re++]=V[ie+_e],k[re++]=-(me+1),k[re++]=V[ie+Ee],k[re++]=me}for(var Ce=Z;Ce<H;++Ce){var me=j[Ce]+c,Se=oe*Ce;k[re++]=N[Se+_e],k[re++]=-me,k[re++]=N[Se+Ee],k[re++]=me}var Le=re>>>1;u(k,Le);for(var Ae=0,Fe=0,Ce=0;Ce<Le;++Ce){var Pe=k[2*Ce+1]|0;if(Pe>=c)Pe=Pe-c|0,S(v,_,Fe--,Pe);else if(Pe>=0)S(h,d,Ae--,Pe);else if(Pe<=-c){Pe=-Pe-c|0;for(var ge=0;ge<Ae;++ge){var Re=T(h[ge],Pe);if(Re!==void 0)return Re}L(v,_,Fe++,Pe)}else{Pe=-Pe-1|0;for(var ge=0;ge<Fe;++ge){var Re=T(Pe,v[ge]);if(Re!==void 0)return Re}L(h,d,Ae++,Pe)}}}function C(P,T,z,O,V,G,Z,H,N,j){for(var re=0,oe=2*P,_e=P-1,Ee=oe-1,Ce=z;Ce<O;++Ce){var me=G[Ce]+1<<1,ie=oe*Ce;k[re++]=V[ie+_e],k[re++]=-me,k[re++]=V[ie+Ee],k[re++]=me}for(var Ce=Z;Ce<H;++Ce){var me=j[Ce]+1<<1,Se=oe*Ce;k[re++]=N[Se+_e],k[re++]=-me|1,k[re++]=N[Se+Ee],k[re++]=me|1}var Le=re>>>1;u(k,Le);for(var Ae=0,Fe=0,Pe=0,Ce=0;Ce<Le;++Ce){var ge=k[2*Ce+1]|0,Re=ge&1;if(Ce<Le-1&&ge>>1===k[2*Ce+3]>>1&&(Re=2,Ce+=1),ge<0){for(var ce=-(ge>>1)-1,Ze=0;Ze<Pe;++Ze){var ut=T(b[Ze],ce);if(ut!==void 0)return ut}if(Re!==0)for(var Ze=0;Ze<Ae;++Ze){var ut=T(h[Ze],ce);if(ut!==void 0)return ut}if(Re!==1)for(var Ze=0;Ze<Fe;++Ze){var ut=T(v[Ze],ce);if(ut!==void 0)return ut}Re===0?L(h,d,Ae++,ce):Re===1?L(v,_,Fe++,ce):Re===2&&L(b,p,Pe++,ce)}else{var ce=(ge>>1)-1;Re===0?S(h,d,Ae--,ce):Re===1?S(v,_,Fe--,ce):Re===2&&S(b,p,Pe--,ce)}}}function M(P,T,z,O,V,G,Z,H,N,j,re,oe){var _e=0,Ee=2*P,Ce=T,me=T+P,ie=1,Se=1;O?Se=c:ie=c;for(var Le=V;Le<G;++Le){var Ae=Le+ie,Fe=Ee*Le;k[_e++]=Z[Fe+Ce],k[_e++]=-Ae,k[_e++]=Z[Fe+me],k[_e++]=Ae}for(var Le=N;Le<j;++Le){var Ae=Le+Se,Pe=Ee*Le;k[_e++]=re[Pe+Ce],k[_e++]=-Ae}var ge=_e>>>1;u(k,ge);for(var Re=0,Le=0;Le<ge;++Le){var ce=k[2*Le+1]|0;if(ce<0){var Ae=-ce,Ze=!1;if(Ae>=c?(Ze=!O,Ae-=c):(Ze=!!O,Ae-=1),Ze)L(h,d,Re++,Ae);else{var ut=oe[Ae],pt=Ee*Ae,Zt=re[pt+T+1],st=re[pt+T+1+P];e:for(var lt=0;lt<Re;++lt){var Gt=h[lt],Nt=Ee*Gt;if(!(st<Z[Nt+T+1]||Z[Nt+T+1+P]<Zt)){for(var Jt=T+2;Jt<P;++Jt)if(re[pt+Jt+P]<Z[Nt+Jt]||Z[Nt+Jt+P]<re[pt+Jt])continue e;var sr=H[Gt],wr;if(O?wr=z(ut,sr):wr=z(sr,ut),wr!==void 0)return wr}}}}else S(h,d,Re--,ce-ie)}}function g(P,T,z,O,V,G,Z,H,N,j,re){for(var oe=0,_e=2*P,Ee=T,Ce=T+P,me=O;me<V;++me){var ie=me+c,Se=_e*me;k[oe++]=G[Se+Ee],k[oe++]=-ie,k[oe++]=G[Se+Ce],k[oe++]=ie}for(var me=H;me<N;++me){var ie=me+1,Le=_e*me;k[oe++]=j[Le+Ee],k[oe++]=-ie}var Ae=oe>>>1;u(k,Ae);for(var Fe=0,me=0;me<Ae;++me){var Pe=k[2*me+1]|0;if(Pe<0){var ie=-Pe;if(ie>=c)h[Fe++]=ie-c;else{ie-=1;var ge=re[ie],Re=_e*ie,ce=j[Re+T+1],Ze=j[Re+T+1+P];e:for(var ut=0;ut<Fe;++ut){var pt=h[ut],Zt=Z[pt];if(Zt===ge)break;var st=_e*pt;if(!(Ze<G[st+T+1]||G[st+T+1+P]<ce)){for(var lt=T+2;lt<P;++lt)if(j[Re+lt+P]<G[st+lt]||G[st+lt+P]<j[Re+lt])continue e;var Gt=z(Zt,ge);if(Gt!==void 0)return Gt}}}}else{for(var ie=Pe-c,ut=Fe-1;ut>=0;--ut)if(h[ut]===ie){for(var lt=ut+1;lt<Fe;++lt)h[lt-1]=h[lt];break}--Fe}}}},868:function(i,a,o){i.exports=o(1387)},869:function(i,a,o){\"use strict\";var s=o(2651),l=o(5716);i.exports=u;function u(c,f){var h=l(c),d=l(f);if(h===0)return[s(0),s(1)];if(d===0)return[s(0),s(0)];d<0&&(c=c.neg(),f=f.neg());var v=c.gcd(f);return v.cmpn(1)?[c.div(v),f.div(v)]:[c,f]}},870:function(i,a,o){\"use strict\";var s=o(1433);function l(c){this.gl=c,this._elements=null,this._attributes=null,this._elementsType=c.UNSIGNED_SHORT}l.prototype.bind=function(){s(this.gl,this._elements,this._attributes)},l.prototype.update=function(c,f,h){this._elements=f,this._attributes=c,this._elementsType=h||this.gl.UNSIGNED_SHORT},l.prototype.dispose=function(){},l.prototype.unbind=function(){},l.prototype.draw=function(c,f,h){h=h||0;var d=this.gl;this._elements?d.drawElements(c,f,this._elementsType,h):d.drawArrays(c,h,f)};function u(c){return new l(c)}i.exports=u},946:function(i,a,o){\"use strict\";var s=o(1369),l=o(4025);i.exports=u;function u(c){var f=c[0],h=c[1];if(f.cmpn(0)===0)return 0;var d=f.abs().divmod(h.abs()),v=d.div,_=s(v),b=d.mod,p=f.negative!==h.negative?-1:1;if(b.cmpn(0)===0)return p*_;if(_){var k=l(_)+4,E=s(b.ushln(k).divRound(h));return p*(_+E*Math.pow(2,-k))}else{var S=h.bitLength()-b.bitLength()+53,E=s(b.ushln(S).divRound(h));return S<1023?p*E*Math.pow(2,-S):(E*=Math.pow(2,-1023),p*E*Math.pow(2,1023-S))}}},990:function(i,a,o){var s=o(9405),l=o(3236),u=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec4 uv;\n",
+       "attribute vec3 f;\n",
+       "attribute vec3 normal;\n",
+       "\n",
+       "uniform vec3 objectOffset;\n",
+       "uniform mat4 model, view, projection, inverseModel;\n",
+       "uniform vec3 lightPosition, eyePosition;\n",
+       "uniform sampler2D colormap;\n",
+       "\n",
+       "varying float value, kill;\n",
+       "varying vec3 worldCoordinate;\n",
+       "varying vec2 planeCoordinate;\n",
+       "varying vec3 lightDirection, eyeDirection, surfaceNormal;\n",
+       "varying vec4 vColor;\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 localCoordinate = vec3(uv.zw, f.x);\n",
+       "  worldCoordinate = objectOffset + localCoordinate;\n",
+       "  mat4 objectOffsetTranslation = mat4(1.0) + mat4(vec4(0), vec4(0), vec4(0), vec4(objectOffset, 0));\n",
+       "  vec4 worldPosition = (model * objectOffsetTranslation) * vec4(localCoordinate, 1.0);\n",
+       "  vec4 clipPosition = projection * (view * worldPosition);\n",
+       "  gl_Position = clipPosition;\n",
+       "  kill = f.y;\n",
+       "  value = f.z;\n",
+       "  planeCoordinate = uv.xy;\n",
+       "\n",
+       "  vColor = texture2D(colormap, vec2(value, value));\n",
+       "\n",
+       "  //Lighting geometry parameters\n",
+       "  vec4 cameraCoordinate = view * worldPosition;\n",
+       "  cameraCoordinate.xyz /= cameraCoordinate.w;\n",
+       "  lightDirection = lightPosition - cameraCoordinate.xyz;\n",
+       "  eyeDirection   = eyePosition - cameraCoordinate.xyz;\n",
+       "  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\n",
+       "}\n",
+       "`]),c=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "float beckmannDistribution(float x, float roughness) {\n",
+       "  float NdotH = max(x, 0.0001);\n",
+       "  float cos2Alpha = NdotH * NdotH;\n",
+       "  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n",
+       "  float roughness2 = roughness * roughness;\n",
+       "  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n",
+       "  return exp(tan2Alpha / roughness2) / denom;\n",
+       "}\n",
+       "\n",
+       "float beckmannSpecular(\n",
+       "  vec3 lightDirection,\n",
+       "  vec3 viewDirection,\n",
+       "  vec3 surfaceNormal,\n",
+       "  float roughness) {\n",
+       "  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 lowerBound, upperBound;\n",
+       "uniform float contourTint;\n",
+       "uniform vec4 contourColor;\n",
+       "uniform sampler2D colormap;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\n",
+       "uniform float vertexColor;\n",
+       "\n",
+       "varying float value, kill;\n",
+       "varying vec3 worldCoordinate;\n",
+       "varying vec3 lightDirection, eyeDirection, surfaceNormal;\n",
+       "varying vec4 vColor;\n",
+       "\n",
+       "void main() {\n",
+       "  if (\n",
+       "    kill > 0.0 ||\n",
+       "    vColor.a == 0.0 ||\n",
+       "    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\n",
+       "  ) discard;\n",
+       "\n",
+       "  vec3 N = normalize(surfaceNormal);\n",
+       "  vec3 V = normalize(eyeDirection);\n",
+       "  vec3 L = normalize(lightDirection);\n",
+       "\n",
+       "  if(gl_FrontFacing) {\n",
+       "    N = -N;\n",
+       "  }\n",
+       "\n",
+       "  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\n",
+       "  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n",
+       "\n",
+       "  //decide how to interpolate color \\u2014 in vertex or in fragment\n",
+       "  vec4 surfaceColor =\n",
+       "    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\n",
+       "    step(.5, vertexColor) * vColor;\n",
+       "\n",
+       "  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n",
+       "\n",
+       "  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\n",
+       "}\n",
+       "`]),f=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec4 uv;\n",
+       "attribute float f;\n",
+       "\n",
+       "uniform vec3 objectOffset;\n",
+       "uniform mat3 permutation;\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform float height, zOffset;\n",
+       "uniform sampler2D colormap;\n",
+       "\n",
+       "varying float value, kill;\n",
+       "varying vec3 worldCoordinate;\n",
+       "varying vec2 planeCoordinate;\n",
+       "varying vec3 lightDirection, eyeDirection, surfaceNormal;\n",
+       "varying vec4 vColor;\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\n",
+       "  worldCoordinate = objectOffset + dataCoordinate;\n",
+       "  mat4 objectOffsetTranslation = mat4(1.0) + mat4(vec4(0), vec4(0), vec4(0), vec4(objectOffset, 0));\n",
+       "  vec4 worldPosition = (model * objectOffsetTranslation) * vec4(dataCoordinate, 1.0);\n",
+       "\n",
+       "  vec4 clipPosition = projection * (view * worldPosition);\n",
+       "  clipPosition.z += zOffset;\n",
+       "\n",
+       "  gl_Position = clipPosition;\n",
+       "  value = f + objectOffset.z;\n",
+       "  kill = -1.0;\n",
+       "  planeCoordinate = uv.zw;\n",
+       "\n",
+       "  vColor = texture2D(colormap, vec2(value, value));\n",
+       "\n",
+       "  //Don't do lighting for contours\n",
+       "  surfaceNormal   = vec3(1,0,0);\n",
+       "  eyeDirection    = vec3(0,1,0);\n",
+       "  lightDirection  = vec3(0,0,1);\n",
+       "}\n",
+       "`]),h=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec2 shape;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float pickId;\n",
+       "\n",
+       "varying float value, kill;\n",
+       "varying vec3 worldCoordinate;\n",
+       "varying vec2 planeCoordinate;\n",
+       "varying vec3 surfaceNormal;\n",
+       "\n",
+       "vec2 splitFloat(float v) {\n",
+       "  float vh = 255.0 * v;\n",
+       "  float upper = floor(vh);\n",
+       "  float lower = fract(vh);\n",
+       "  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  if ((kill > 0.0) ||\n",
+       "      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\n",
+       "\n",
+       "  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\n",
+       "  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\n",
+       "  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\n",
+       "}\n",
+       "`]);a.createShader=function(d){var v=s(d,u,c,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v.attributes.normal.location=2,v},a.createPickShader=function(d){var v=s(d,u,h,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v.attributes.normal.location=2,v},a.createContourShader=function(d){var v=s(d,f,c,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v},a.createPickContourShader=function(d){var v=s(d,f,h,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v}},1085:function(i,a,o){var s=o(1371);i.exports=l;function l(u,c,f){c=typeof c==\"number\"?c:1,f=f||\": \";var h=u.split(/\\r?\\n/),d=String(h.length+c-1).length;return h.map(function(v,_){var b=_+c,p=String(b).length,k=s(b,d-p);return k+f+v}).join(`\n",
+       "`)}},1091:function(i){i.exports=a;function a(){var o=new Float32Array(3);return o[0]=0,o[1]=0,o[2]=0,o}},1125:function(i,a,o){\"use strict\";i.exports=u;var s=o(3250)[3];function l(c,f,h,d){for(var v=0;v<2;++v){var _=c[v],b=f[v],p=Math.min(_,b),k=Math.max(_,b),E=h[v],S=d[v],L=Math.min(E,S),x=Math.max(E,S);if(x<p||k<L)return!1}return!0}function u(c,f,h,d){var v=s(c,h,d),_=s(f,h,d);if(v>0&&_>0||v<0&&_<0)return!1;var b=s(h,c,f),p=s(d,c,f);return b>0&&p>0||b<0&&p<0?!1:v===0&&_===0&&b===0&&p===0?l(c,f,h,d):!0}},1278:function(i,a,o){\"use strict\";var s=o(2361),l=Math.pow(2,-1074),u=-1>>>0;i.exports=c;function c(f,h){if(isNaN(f)||isNaN(h))return NaN;if(f===h)return f;if(f===0)return h<0?-l:l;var d=s.hi(f),v=s.lo(f);return h>f==f>0?v===u?(d+=1,v=0):v+=1:v===0?(v=u,d-=1):v-=1,s.pack(v,d)}},1283:function(i,a,o){var s=o(9405),l=o(3236),u=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 glyph;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform vec4 highlightId;\n",
+       "uniform float highlightScale;\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "\n",
+       "varying vec4 interpColor;\n",
+       "varying vec4 pickId;\n",
+       "varying vec3 dataCoordinate;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n",
+       "\n",
+       "    gl_Position = vec4(0,0,0,0);\n",
+       "  } else {\n",
+       "    float scale = 1.0;\n",
+       "    if(distance(highlightId, id) < 0.0001) {\n",
+       "      scale = highlightScale;\n",
+       "    }\n",
+       "\n",
+       "    vec4 worldPosition = model * vec4(position, 1);\n",
+       "    vec4 viewPosition = view * worldPosition;\n",
+       "    viewPosition = viewPosition / viewPosition.w;\n",
+       "    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\n",
+       "\n",
+       "    gl_Position = clipPosition;\n",
+       "    interpColor = color;\n",
+       "    pickId = id;\n",
+       "    dataCoordinate = position;\n",
+       "  }\n",
+       "}`]),c=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 glyph;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec2 screenSize;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float highlightScale, pixelRatio;\n",
+       "uniform vec4 highlightId;\n",
+       "\n",
+       "varying vec4 interpColor;\n",
+       "varying vec4 pickId;\n",
+       "varying vec3 dataCoordinate;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n",
+       "\n",
+       "    gl_Position = vec4(0,0,0,0);\n",
+       "  } else {\n",
+       "    float scale = pixelRatio;\n",
+       "    if(distance(highlightId.bgr, id.bgr) < 0.001) {\n",
+       "      scale *= highlightScale;\n",
+       "    }\n",
+       "\n",
+       "    vec4 worldPosition = model * vec4(position, 1.0);\n",
+       "    vec4 viewPosition = view * worldPosition;\n",
+       "    vec4 clipPosition = projection * viewPosition;\n",
+       "    clipPosition /= clipPosition.w;\n",
+       "\n",
+       "    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\n",
+       "    interpColor = color;\n",
+       "    pickId = id;\n",
+       "    dataCoordinate = position;\n",
+       "  }\n",
+       "}`]),f=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec4 color;\n",
+       "attribute vec2 glyph;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform float highlightScale;\n",
+       "uniform vec4 highlightId;\n",
+       "uniform vec3 axes[2];\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec2 screenSize;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float scale, pixelRatio;\n",
+       "\n",
+       "varying vec4 interpColor;\n",
+       "varying vec4 pickId;\n",
+       "varying vec3 dataCoordinate;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n",
+       "\n",
+       "    gl_Position = vec4(0,0,0,0);\n",
+       "  } else {\n",
+       "    float lscale = pixelRatio * scale;\n",
+       "    if(distance(highlightId, id) < 0.0001) {\n",
+       "      lscale *= highlightScale;\n",
+       "    }\n",
+       "\n",
+       "    vec4 clipCenter   = projection * (view * (model * vec4(position, 1)));\n",
+       "    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\n",
+       "    vec4 clipPosition = projection * (view * (model * vec4(dataPosition, 1)));\n",
+       "\n",
+       "    gl_Position = clipPosition;\n",
+       "    interpColor = color;\n",
+       "    pickId = id;\n",
+       "    dataCoordinate = dataPosition;\n",
+       "  }\n",
+       "}\n",
+       "`]),h=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 fragClipBounds[2];\n",
+       "uniform float opacity;\n",
+       "\n",
+       "varying vec4 interpColor;\n",
+       "varying vec3 dataCoordinate;\n",
+       "\n",
+       "void main() {\n",
+       "  if (\n",
+       "    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\n",
+       "    interpColor.a * opacity == 0.\n",
+       "  ) discard;\n",
+       "  gl_FragColor = interpColor * opacity;\n",
+       "}\n",
+       "`]),d=l([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 fragClipBounds[2];\n",
+       "uniform float pickGroup;\n",
+       "\n",
+       "varying vec4 pickId;\n",
+       "varying vec3 dataCoordinate;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\n",
+       "\n",
+       "  gl_FragColor = vec4(pickGroup, pickId.bgr);\n",
+       "}`]),v=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],_={vertex:u,fragment:h,attributes:v},b={vertex:c,fragment:h,attributes:v},p={vertex:f,fragment:h,attributes:v},k={vertex:u,fragment:d,attributes:v},E={vertex:c,fragment:d,attributes:v},S={vertex:f,fragment:d,attributes:v};function L(x,C){var M=s(x,C),g=M.attributes;return g.position.location=0,g.color.location=1,g.glyph.location=2,g.id.location=3,M}a.createPerspective=function(x){return L(x,_)},a.createOrtho=function(x){return L(x,b)},a.createProject=function(x){return L(x,p)},a.createPickPerspective=function(x){return L(x,k)},a.createPickOrtho=function(x){return L(x,E)},a.createPickProject=function(x){return L(x,S)}},1303:function(i,a,o){\"use strict\";i.exports=u;var s=o(3250);function l(c,f){var h,d;if(f[0][0]<f[1][0])h=f[0],d=f[1];else if(f[0][0]>f[1][0])h=f[1],d=f[0];else{var v=Math.min(c[0][1],c[1][1]),_=Math.max(c[0][1],c[1][1]),b=Math.min(f[0][1],f[1][1]),p=Math.max(f[0][1],f[1][1]);return _<b?_-b:v>p?v-p:_-p}var k,E;c[0][1]<c[1][1]?(k=c[0],E=c[1]):(k=c[1],E=c[0]);var S=s(d,h,k);return S||(S=s(d,h,E),S)?S:E-d}function u(c,f){var h,d;if(f[0][0]<f[1][0])h=f[0],d=f[1];else if(f[0][0]>f[1][0])h=f[1],d=f[0];else return l(f,c);var v,_;if(c[0][0]<c[1][0])v=c[0],_=c[1];else if(c[0][0]>c[1][0])v=c[1],_=c[0];else return-l(c,f);var b=s(h,d,_),p=s(h,d,v);if(b<0){if(p<=0)return b}else if(b>0){if(p>=0)return b}else if(p)return p;if(b=s(_,v,d),p=s(_,v,h),b<0){if(p<=0)return b}else if(b>0){if(p>=0)return b}else if(p)return p;return d[0]-_[0]}},1318:function(i){\"use strict\";i.exports=a;function a(o,s){return o[0].mul(s[1]).cmp(s[0].mul(o[1]))}},1338:function(i){\"use strict\";function a(l,u,c){var f=l[c]|0;if(f<=0)return[];var h=new Array(f),d;if(c===l.length-1)for(d=0;d<f;++d)h[d]=u;else for(d=0;d<f;++d)h[d]=a(l,u,c+1);return h}function o(l,u){var c,f;for(c=new Array(l),f=0;f<l;++f)c[f]=u;return c}function s(l,u){switch(typeof u==\"undefined\"&&(u=0),typeof l){case\"number\":if(l>0)return o(l|0,u);break;case\"object\":if(typeof l.length==\"number\")return a(l,u,0);break}return[]}i.exports=s},1369:function(i,a,o){\"use strict\";var s=o(5716);i.exports=l;function l(u){var c=u.length,f=u.words,h=0;if(c===1)h=f[0];else if(c===2)h=f[0]+f[1]*67108864;else for(var d=0;d<c;d++){var v=f[d];h+=v*Math.pow(67108864,d)}return s(u)*h}},1371:function(i,a,o){\"use strict\";var s=o(3233);i.exports=function(u,c,f){return f=typeof f!=\"undefined\"?f+\"\":\" \",s(f,c)+u}},1373:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]/l[0],o[1]=s[1]/l[1],o[2]=s[2]/l[2],o[3]=s[3]/l[3],o}},1387:function(i){i.exports=a;function a(o){var s=o[0],l=o[1],u=o[2];return Math.sqrt(s*s+l*l+u*u)}},1433:function(i){\"use strict\";function a(o,s,l){s?s.bind():o.bindBuffer(o.ELEMENT_ARRAY_BUFFER,null);var u=o.getParameter(o.MAX_VERTEX_ATTRIBS)|0;if(l){if(l.length>u)throw new Error(\"gl-vao: Too many vertex attributes\");for(var c=0;c<l.length;++c){var f=l[c];if(f.buffer){var h=f.buffer,d=f.size||4,v=f.type||o.FLOAT,_=!!f.normalized,b=f.stride||0,p=f.offset||0;h.bind(),o.enableVertexAttribArray(c),o.vertexAttribPointer(c,d,v,_,b,p)}else{if(typeof f==\"number\")o.vertexAttrib1f(c,f);else if(f.length===1)o.vertexAttrib1f(c,f[0]);else if(f.length===2)o.vertexAttrib2f(c,f[0],f[1]);else if(f.length===3)o.vertexAttrib3f(c,f[0],f[1],f[2]);else if(f.length===4)o.vertexAttrib4f(c,f[0],f[1],f[2],f[3]);else throw new Error(\"gl-vao: Invalid vertex attribute\");o.disableVertexAttribArray(c)}}for(;c<u;++c)o.disableVertexAttribArray(c)}else{o.bindBuffer(o.ARRAY_BUFFER,null);for(var c=0;c<u;++c)o.disableVertexAttribArray(c)}}i.exports=a},1463:function(i){i.exports=a;function a(o,s,l,u){return o[0]=s,o[1]=l,o[2]=u,o}},1493:function(i,a,o){\"use strict\";var s=o(3236),l=o(9405),u=s([`precision mediump float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position, color;\n",
+       "attribute float weight;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 coordinates[3];\n",
+       "uniform vec4 colors[3];\n",
+       "uniform vec2 screenShape;\n",
+       "uniform float lineWidth;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 vertexPosition = mix(coordinates[0],\n",
+       "    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\n",
+       "\n",
+       "  vec4 clipPos = projection * (view * (model * vec4(vertexPosition, 1.0)));\n",
+       "  vec2 clipOffset = (projection * (view * (model * vec4(color, 0.0)))).xy;\n",
+       "  vec2 delta = weight * clipOffset * screenShape;\n",
+       "  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\n",
+       "\n",
+       "  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\n",
+       "  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\n",
+       "}\n",
+       "`]),c=s([`precision mediump float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_FragColor = fragColor;\n",
+       "}`]);i.exports=function(f){return l(f,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},1498:function(i){i.exports=a;function a(o,s){return o[0]=-s[0],o[1]=-s[1],o[2]=-s[2],o[3]=-s[3],o}},1533:function(i,a,o){\"use strict\";var s=o(6859);i.exports=l;function l(u){return u&&typeof u==\"object\"&&!!u.words}},1538:function(i){(function(){\"use strict\";if(typeof ses!=\"undefined\"&&ses.ok&&!ses.ok())return;function o(T){T.permitHostObjects___&&T.permitHostObjects___(o)}typeof ses!=\"undefined\"&&(ses.weakMapPermitHostObjects=o);var s=!1;if(typeof WeakMap==\"function\"){var l=WeakMap;if(!(typeof navigator!=\"undefined\"&&/Firefox/.test(navigator.userAgent))){var u=new l,c=Object.freeze({});if(u.set(c,1),u.get(c)!==1)s=!0;else{i.exports=WeakMap;return}}}var f=Object.prototype.hasOwnProperty,h=Object.getOwnPropertyNames,d=Object.defineProperty,v=Object.isExtensible,_=\"weakmap:\",b=_+\"ident:\"+Math.random()+\"___\";if(typeof crypto!=\"undefined\"&&typeof crypto.getRandomValues==\"function\"&&typeof ArrayBuffer==\"function\"&&typeof Uint8Array==\"function\"){var p=new ArrayBuffer(25),k=new Uint8Array(p);crypto.getRandomValues(k),b=_+\"rand:\"+Array.prototype.map.call(k,function(T){return(T%36).toString(36)}).join(\"\")+\"___\"}function E(T){return!(T.substr(0,_.length)==_&&T.substr(T.length-3)===\"___\")}if(d(Object,\"getOwnPropertyNames\",{value:function(z){return h(z).filter(E)}}),\"getPropertyNames\"in Object){var S=Object.getPropertyNames;d(Object,\"getPropertyNames\",{value:function(z){return S(z).filter(E)}})}function L(T){if(T!==Object(T))throw new TypeError(\"Not an object: \"+T);var z=T[b];if(z&&z.key===T)return z;if(v(T)){z={key:T};try{return d(T,b,{value:z,writable:!1,enumerable:!1,configurable:!1}),z}catch(O){return}}}(function(){var T=Object.freeze;d(Object,\"freeze\",{value:function(G){return L(G),T(G)}});var z=Object.seal;d(Object,\"seal\",{value:function(G){return L(G),z(G)}});var O=Object.preventExtensions;d(Object,\"preventExtensions\",{value:function(G){return L(G),O(G)}})})();function x(T){return T.prototype=null,Object.freeze(T)}var C=!1;function M(){!C&&typeof console!=\"undefined\"&&(C=!0,console.warn(\"WeakMap should be invoked as new WeakMap(), not WeakMap(). 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O=C[M+1]-C[M],T=16*M,V=this.prevMatrix,G=!0,z=0;z<16;++z)V[z]=P[T++];for(var Z=this.nextMatrix,z=0;z<16;++z)Z[z]=P[T++],G=G&&V[z]===Z[z];if(O<1e-6||G)for(var z=0;z<16;++z)g[z]=V[z];else l(g,V,Z,(x-C[M])/O)}var H=this.computedUp;H[0]=g[1],H[1]=g[5],H[2]=g[9],b(H,H);var N=this.computedInverse;u(N,g);var j=this.computedEye,re=N[15];j[0]=N[12]/re,j[1]=N[13]/re,j[2]=N[14]/re;for(var oe=this.computedCenter,_e=Math.exp(this.computedRadius[0]),z=0;z<3;++z)oe[z]=j[z]-g[2+4*z]*_e}},E.idle=function(x){if(!(x<this.lastT())){for(var C=this._components,M=C.length-16,g=0;g<16;++g)C.push(C[M++]);this._time.push(x)}},E.flush=function(x){var C=s.gt(this._time,x)-2;C<0||(this._time.splice(0,C),this._components.splice(0,16*C))},E.lastT=function(){return this._time[this._time.length-1]},E.lookAt=function(x,C,M,g){this.recalcMatrix(x),C=C||this.computedEye,M=M||p,g=g||this.computedUp,this.setMatrix(x,d(this.computedMatrix,C,M,g));for(var P=0,T=0;T<3;++T)P+=Math.pow(M[T]-C[T],2);P=Math.log(Math.sqrt(P)),this.computedRadius[0]=P},E.rotate=function(x,C,M,g){this.recalcMatrix(x);var P=this.computedInverse;C&&f(P,P,C),M&&c(P,P,M),g&&h(P,P,g),this.setMatrix(x,u(this.computedMatrix,P))};var S=[0,0,0];E.pan=function(x,C,M,g){S[0]=-(C||0),S[1]=-(M||0),S[2]=-(g||0),this.recalcMatrix(x);var P=this.computedInverse;v(P,P,S),this.setMatrix(x,u(P,P))},E.translate=function(x,C,M,g){S[0]=C||0,S[1]=M||0,S[2]=g||0,this.recalcMatrix(x);var P=this.computedMatrix;v(P,P,S),this.setMatrix(x,P)},E.setMatrix=function(x,C){if(!(x<this.lastT())){this._time.push(x);for(var M=0;M<16;++M)this._components.push(C[M])}},E.setDistance=function(x,C){this.computedRadius[0]=C},E.setDistanceLimits=function(x,C){var M=this._limits;M[0]=x,M[1]=C},E.getDistanceLimits=function(x){var C=this._limits;return x?(x[0]=C[0],x[1]=C[1],x):C};function L(x){x=x||{};var C=x.matrix||[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];return new k(C)}},1848:function(i,a,o){var s=o(4905),l=o(6468);i.exports=u;function u(c){for(var f=Array.isArray(c)?c:s(c),h=0;h<f.length;h++){var d=f[h];if(d.type===\"preprocessor\"){var v=d.data.match(/\\#define\\s+SHADER_NAME(_B64)?\\s+(.+)$/);if(v&&v[2]){var _=v[1],b=v[2];return(_?l(b):b).trim()}}}}},1879:function(i,a,o){\"use strict\";var s=o(3236),l=o(9405),u=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 offset, majorAxis, minorAxis, screenAxis;\n",
+       "uniform float lineWidth;\n",
+       "uniform vec2 screenShape;\n",
+       "\n",
+       "vec3 project(vec3 p) {\n",
+       "  vec4 pp = projection * (view * (model * vec4(p, 1.0)));\n",
+       "  return pp.xyz / max(pp.w, 0.0001);\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 major = position.x * majorAxis;\n",
+       "  vec3 minor = position.y * minorAxis;\n",
+       "\n",
+       "  vec3 vPosition = major + minor + offset;\n",
+       "  vec3 pPosition = project(vPosition);\n",
+       "  vec3 offset = project(vPosition + screenAxis * position.z);\n",
+       "\n",
+       "  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\n",
+       "\n",
+       "  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\n",
+       "}\n",
+       "`]),c=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform vec4 color;\n",
+       "void main() {\n",
+       "  gl_FragColor = color;\n",
+       "}`]);a.n=function(_){return l(_,u,c,null,[{name:\"position\",type:\"vec3\"}])};var f=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 offset, axis, alignDir, alignOpt;\n",
+       "uniform float scale, angle, pixelScale;\n",
+       "uniform vec2 resolution;\n",
+       "\n",
+       "vec3 project(vec3 p) {\n",
+       "  vec4 pp = projection * (view * (model * vec4(p, 1.0)));\n",
+       "  return pp.xyz / max(pp.w, 0.0001);\n",
+       "}\n",
+       "\n",
+       "float computeViewAngle(vec3 a, vec3 b) {\n",
+       "  vec3 A = project(a);\n",
+       "  vec3 B = project(b);\n",
+       "\n",
+       "  return atan(\n",
+       "    (B.y - A.y) * resolution.y,\n",
+       "    (B.x - A.x) * resolution.x\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "const float PI = 3.141592;\n",
+       "const float TWO_PI = 2.0 * PI;\n",
+       "const float HALF_PI = 0.5 * PI;\n",
+       "const float ONE_AND_HALF_PI = 1.5 * PI;\n",
+       "\n",
+       "int option = int(floor(alignOpt.x + 0.001));\n",
+       "float hv_ratio =       alignOpt.y;\n",
+       "bool enableAlign =    (alignOpt.z != 0.0);\n",
+       "\n",
+       "float mod_angle(float a) {\n",
+       "  return mod(a, PI);\n",
+       "}\n",
+       "\n",
+       "float positive_angle(float a) {\n",
+       "  return mod_angle((a < 0.0) ?\n",
+       "    a + TWO_PI :\n",
+       "    a\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "float look_upwards(float a) {\n",
+       "  float b = positive_angle(a);\n",
+       "  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\n",
+       "    b - PI :\n",
+       "    b;\n",
+       "}\n",
+       "\n",
+       "float look_horizontal_or_vertical(float a, float ratio) {\n",
+       "  // ratio controls the ratio between being horizontal to (vertical + horizontal)\n",
+       "  // if ratio is set to 0.5 then it is 50%, 50%.\n",
+       "  // when using a higher ratio e.g. 0.75 the result would\n",
+       "  // likely be more horizontal than vertical.\n",
+       "\n",
+       "  float b = positive_angle(a);\n",
+       "\n",
+       "  return\n",
+       "    (b < (      ratio) * HALF_PI) ? 0.0 :\n",
+       "    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\n",
+       "    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\n",
+       "    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\n",
+       "                                    0.0;\n",
+       "}\n",
+       "\n",
+       "float roundTo(float a, float b) {\n",
+       "  return float(b * floor((a + 0.5 * b) / b));\n",
+       "}\n",
+       "\n",
+       "float look_round_n_directions(float a, int n) {\n",
+       "  float b = positive_angle(a);\n",
+       "  float div = TWO_PI / float(n);\n",
+       "  float c = roundTo(b, div);\n",
+       "  return look_upwards(c);\n",
+       "}\n",
+       "\n",
+       "float applyAlignOption(float rawAngle, float delta) {\n",
+       "  return\n",
+       "    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\n",
+       "    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\n",
+       "    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\n",
+       "    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\n",
+       "    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\n",
+       "                    rawAngle;                // otherwise return back raw input angle\n",
+       "}\n",
+       "\n",
+       "bool isAxisTitle = (axis.x == 0.0) &&\n",
+       "                   (axis.y == 0.0) &&\n",
+       "                   (axis.z == 0.0);\n",
+       "\n",
+       "void main() {\n",
+       "  //Compute world offset\n",
+       "  float axisDistance = position.z;\n",
+       "  vec3 dataPosition = axisDistance * axis + offset;\n",
+       "\n",
+       "  float beta = angle; // i.e. user defined attributes for each tick\n",
+       "\n",
+       "  float axisAngle;\n",
+       "  float clipAngle;\n",
+       "  float flip;\n",
+       "\n",
+       "  if (enableAlign) {\n",
+       "    axisAngle = (isAxisTitle) ? HALF_PI :\n",
+       "                      computeViewAngle(dataPosition, dataPosition + axis);\n",
+       "    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\n",
+       "\n",
+       "    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\n",
+       "    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\n",
+       "\n",
+       "    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\n",
+       "                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\n",
+       "\n",
+       "    beta += applyAlignOption(clipAngle, flip * PI);\n",
+       "  }\n",
+       "\n",
+       "  //Compute plane offset\n",
+       "  vec2 planeCoord = position.xy * pixelScale;\n",
+       "\n",
+       "  mat2 planeXform = scale * mat2(\n",
+       "     cos(beta), sin(beta),\n",
+       "    -sin(beta), cos(beta)\n",
+       "  );\n",
+       "\n",
+       "  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\n",
+       "\n",
+       "  //Compute clip position\n",
+       "  vec3 clipPosition = project(dataPosition);\n",
+       "\n",
+       "  //Apply text offset in clip coordinates\n",
+       "  clipPosition += vec3(viewOffset, 0.0);\n",
+       "\n",
+       "  //Done\n",
+       "  gl_Position = vec4(clipPosition, 1.0);\n",
+       "}\n",
+       "`]),h=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform vec4 color;\n",
+       "void main() {\n",
+       "  gl_FragColor = color;\n",
+       "}`]);a.Q=function(_){return l(_,f,h,null,[{name:\"position\",type:\"vec3\"}])};var d=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position;\n",
+       "attribute vec3 normal;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform vec3 enable;\n",
+       "uniform vec3 bounds[2];\n",
+       "\n",
+       "varying vec3 colorChannel;\n",
+       "\n",
+       "void main() {\n",
+       "\n",
+       "  vec3 signAxis = sign(bounds[1] - bounds[0]);\n",
+       "\n",
+       "  vec3 realNormal = signAxis * normal;\n",
+       "\n",
+       "  if(dot(realNormal, enable) > 0.0) {\n",
+       "    vec3 minRange = min(bounds[0], bounds[1]);\n",
+       "    vec3 maxRange = max(bounds[0], bounds[1]);\n",
+       "    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\n",
+       "    gl_Position = projection * (view * (model * vec4(nPosition, 1.0)));\n",
+       "  } else {\n",
+       "    gl_Position = vec4(0,0,0,0);\n",
+       "  }\n",
+       "\n",
+       "  colorChannel = abs(realNormal);\n",
+       "}\n",
+       "`]),v=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform vec4 colors[3];\n",
+       "\n",
+       "varying vec3 colorChannel;\n",
+       "\n",
+       "void main() {\n",
+       "  gl_FragColor = colorChannel.x * colors[0] +\n",
+       "                 colorChannel.y * colors[1] +\n",
+       "                 colorChannel.z * colors[2];\n",
+       "}`]);a.bg=function(_){return l(_,d,v,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},1888:function(i,a,o){\"use strict\";var s=o(8828),l=o(1338),u=o(4793).hp;o.g.__TYPEDARRAY_POOL||(o.g.__TYPEDARRAY_POOL={UINT8:l([32,0]),UINT16:l([32,0]),UINT32:l([32,0]),BIGUINT64:l([32,0]),INT8:l([32,0]),INT16:l([32,0]),INT32:l([32,0]),BIGINT64:l([32,0]),FLOAT:l([32,0]),DOUBLE:l([32,0]),DATA:l([32,0]),UINT8C:l([32,0]),BUFFER:l([32,0])});var c=typeof Uint8ClampedArray!=\"undefined\",f=typeof BigUint64Array!=\"undefined\",h=typeof BigInt64Array!=\"undefined\",d=o.g.__TYPEDARRAY_POOL;d.UINT8C||(d.UINT8C=l([32,0])),d.BIGUINT64||(d.BIGUINT64=l([32,0])),d.BIGINT64||(d.BIGINT64=l([32,0])),d.BUFFER||(d.BUFFER=l([32,0]));var v=d.DATA,_=d.BUFFER;a.free=function(H){if(u.isBuffer(H))_[s.log2(H.length)].push(H);else{if(Object.prototype.toString.call(H)!==\"[object ArrayBuffer]\"&&(H=H.buffer),!H)return;var N=H.length||H.byteLength,j=s.log2(N)|0;v[j].push(H)}};function 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+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position, offset;\n",
+       "attribute vec4 color;\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform float capSize;\n",
+       "varying vec4 fragColor;\n",
+       "varying vec3 fragPosition;\n",
+       "\n",
+       "void main() {\n",
+       "  vec4 worldPosition  = model * vec4(position, 1.0);\n",
+       "  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\n",
+       "  gl_Position         = projection * (view * worldPosition);\n",
+       "  fragColor           = color;\n",
+       "  fragPosition        = position;\n",
+       "}`]),c=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float opacity;\n",
+       "varying vec3 fragPosition;\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "  if (\n",
+       "    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\n",
+       "    fragColor.a * opacity == 0.\n",
+       "  ) discard;\n",
+       "\n",
+       "  gl_FragColor = opacity * fragColor;\n",
+       "}`]);i.exports=function(f){return l(f,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},3502:function(i,a,o){i.exports=u;var s=o(5995),l=o(9127);function u(c,f){return l(s(c,f))}},3508:function(i,a,o){var 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o[0]*s[0]+o[1]*s[1]+o[2]*s[2]+o[3]*s[3]}},3778:function(i,a){a.read=function(o,s,l,u,c){var f,h,d=c*8-u-1,v=(1<<d)-1,_=v>>1,b=-7,p=l?c-1:0,k=l?-1:1,E=o[s+p];for(p+=k,f=E&(1<<-b)-1,E>>=-b,b+=d;b>0;f=f*256+o[s+p],p+=k,b-=8);for(h=f&(1<<-b)-1,f>>=-b,b+=u;b>0;h=h*256+o[s+p],p+=k,b-=8);if(f===0)f=1-_;else{if(f===v)return h?NaN:(E?-1:1)*(1/0);h=h+Math.pow(2,u),f=f-_}return(E?-1:1)*h*Math.pow(2,f-u)},a.write=function(o,s,l,u,c,f){var h,d,v,_=f*8-c-1,b=(1<<_)-1,p=b>>1,k=c===23?Math.pow(2,-24)-Math.pow(2,-77):0,E=u?0:f-1,S=u?1:-1,L=s<0||s===0&&1/s<0?1:0;for(s=Math.abs(s),isNaN(s)||s===1/0?(d=isNaN(s)?1:0,h=b):(h=Math.floor(Math.log(s)/Math.LN2),s*(v=Math.pow(2,-h))<1&&(h--,v*=2),h+p>=1?s+=k/v:s+=k*Math.pow(2,1-p),s*v>=2&&(h++,v/=2),h+p>=b?(d=0,h=b):h+p>=1?(d=(s*v-1)*Math.pow(2,c),h=h+p):(d=s*Math.pow(2,p-1)*Math.pow(2,c),h=0));c>=8;o[l+E]=d&255,E+=S,d/=256,c-=8);for(h=h<<c|d,_+=c;_>0;o[l+E]=h&255,E+=S,h/=256,_-=8);o[l+E-S]|=L*128}},3788:function(i,a,o){\"use strict\";var s=o(8507),l=o(2419);i.exports=u;function u(c,f){return s(c,f)||l(c)-l(f)}},3837:function(i,a,o){\"use strict\";i.exports=O;var s=o(4935),l=o(501),u=o(5304),c=o(6429),f=o(6444),h=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),d=ArrayBuffer,v=DataView;function _(V){return d.isView(V)&&!(V instanceof v)}function b(V){return Array.isArray(V)||_(V)}function p(V,G){return V[0]=G[0],V[1]=G[1],V[2]=G[2],V}function k(V){this.gl=V,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickFontStyle=[\"normal\",\"normal\",\"normal\"],this.tickFontWeight=[\"normal\",\"normal\",\"normal\"],this.tickFontVariant=[\"normal\",\"normal\",\"normal\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.labelFontStyle=[\"normal\",\"normal\",\"normal\"],this.labelFontWeight=[\"normal\",\"normal\",\"normal\"],this.labelFontVariant=[\"normal\",\"normal\",\"normal\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=u(V)}var E=k.prototype;E.update=function(V){V=V||{};function G(Ae,Fe,Pe){if(Pe in V){var ge=V[Pe],Re=this[Pe],ce;(Ae?b(ge)&&b(ge[0]):b(ge))?this[Pe]=ce=[Fe(ge[0]),Fe(ge[1]),Fe(ge[2])]:this[Pe]=ce=[Fe(ge),Fe(ge),Fe(ge)];for(var Ze=0;Ze<3;++Ze)if(ce[Ze]!==Re[Ze])return!0}return!1}var Z=G.bind(this,!1,Number),H=G.bind(this,!1,Boolean),N=G.bind(this,!1,String),j=G.bind(this,!0,function(Ae){if(b(Ae)){if(Ae.length===3)return[+Ae[0],+Ae[1],+Ae[2],1];if(Ae.length===4)return[+Ae[0],+Ae[1],+Ae[2],+Ae[3]]}return[0,0,0,1]}),re,oe=!1,_e=!1;if(\"bounds\"in V)for(var Ee=V.bounds,Ce=0;Ce<2;++Ce)for(var me=0;me<3;++me)Ee[Ce][me]!==this.bounds[Ce][me]&&(_e=!0),this.bounds[Ce][me]=Ee[Ce][me];if(\"ticks\"in V){re=V.ticks,oe=!0,this.autoTicks=!1;for(var Ce=0;Ce<3;++Ce)this.tickSpacing[Ce]=0}else Z(\"tickSpacing\")&&(this.autoTicks=!0,_e=!0);if(this._firstInit&&(\"ticks\"in V||\"tickSpacing\"in V||(this.autoTicks=!0),_e=!0,oe=!0,this._firstInit=!1),_e&&this.autoTicks&&(re=f.create(this.bounds,this.tickSpacing),oe=!0),oe){for(var Ce=0;Ce<3;++Ce)re[Ce].sort(function(Fe,Pe){return Fe.x-Pe.x});f.equal(re,this.ticks)?oe=!1:this.ticks=re}H(\"tickEnable\"),N(\"tickFont\")&&(oe=!0),N(\"tickFontStyle\")&&(oe=!0),N(\"tickFontWeight\")&&(oe=!0),N(\"tickFontVariant\")&&(oe=!0),Z(\"tickSize\"),Z(\"tickAngle\"),Z(\"tickPad\"),j(\"tickColor\");var ie=N(\"labels\");N(\"labelFont\")&&(ie=!0),N(\"labelFontStyle\")&&(ie=!0),N(\"labelFontWeight\")&&(ie=!0),N(\"labelFontVariant\")&&(ie=!0),H(\"labelEnable\"),Z(\"labelSize\"),Z(\"labelPad\"),j(\"labelColor\"),H(\"lineEnable\"),H(\"lineMirror\"),Z(\"lineWidth\"),j(\"lineColor\"),H(\"lineTickEnable\"),H(\"lineTickMirror\"),Z(\"lineTickLength\"),Z(\"lineTickWidth\"),j(\"lineTickColor\"),H(\"gridEnable\"),Z(\"gridWidth\"),j(\"gridColor\"),H(\"zeroEnable\"),j(\"zeroLineColor\"),Z(\"zeroLineWidth\"),H(\"backgroundEnable\"),j(\"backgroundColor\");var Se=[{family:this.labelFont[0],style:this.labelFontStyle[0],weight:this.labelFontWeight[0],variant:this.labelFontVariant[0]},{family:this.labelFont[1],style:this.labelFontStyle[1],weight:this.labelFontWeight[1],variant:this.labelFontVariant[1]},{family:this.labelFont[2],style:this.labelFontStyle[2],weight:this.labelFontWeight[2],variant:this.labelFontVariant[2]}],Le=[{family:this.tickFont[0],style:this.tickFontStyle[0],weight:this.tickFontWeight[0],variant:this.tickFontVariant[0]},{family:this.tickFont[1],style:this.tickFontStyle[1],weight:this.tickFontWeight[1],variant:this.tickFontVariant[1]},{family:this.tickFont[2],style:this.tickFontStyle[2],weight:this.tickFontWeight[2],variant:this.tickFontVariant[2]}];this._text?this._text&&(ie||oe)&&this._text.update(this.bounds,this.labels,Se,this.ticks,Le):this._text=s(this.gl,this.bounds,this.labels,Se,this.ticks,Le),this._lines&&oe&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=l(this.gl,this.bounds,this.ticks))};function S(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}var L=[new S,new S,new S];function x(V,G,Z,H,N){for(var j=V.primalOffset,re=V.primalMinor,oe=V.mirrorOffset,_e=V.mirrorMinor,Ee=H[G],Ce=0;Ce<3;++Ce)if(G!==Ce){var me=j,ie=oe,Se=re,Le=_e;Ee&1<<Ce&&(me=oe,ie=j,Se=_e,Le=re),me[Ce]=Z[0][Ce],ie[Ce]=Z[1][Ce],N[Ce]>0?(Se[Ce]=-1,Le[Ce]=0):(Se[Ce]=0,Le[Ce]=1)}}var C=[0,0,0],M={model:h,view:h,projection:h,_ortho:!1};E.isOpaque=function(){return!0},E.isTransparent=function(){return!1},E.drawTransparent=function(V){};var g=0,P=[0,0,0],T=[0,0,0],z=[0,0,0];E.draw=function(V){V=V||M;for(var Pe=this.gl,G=V.model||h,Z=V.view||h,H=V.projection||h,N=this.bounds,j=V._ortho||!1,re=c(G,Z,H,N,j),oe=re.cubeEdges,_e=re.axis,Ee=Z[12],Ce=Z[13],me=Z[14],ie=Z[15],Se=j?2:1,Le=Se*this.pixelRatio*(H[3]*Ee+H[7]*Ce+H[11]*me+H[15]*ie)/Pe.drawingBufferHeight,Ae=0;Ae<3;++Ae)this.lastCubeProps.cubeEdges[Ae]=oe[Ae],this.lastCubeProps.axis[Ae]=_e[Ae];for(var Fe=L,Ae=0;Ae<3;++Ae)x(L[Ae],Ae,this.bounds,oe,_e);for(var Pe=this.gl,ge=C,Ae=0;Ae<3;++Ae)this.backgroundEnable[Ae]?ge[Ae]=_e[Ae]:ge[Ae]=0;this._background.draw(G,Z,H,N,ge,this.backgroundColor),this._lines.bind(G,Z,H,this);for(var Ae=0;Ae<3;++Ae){var Re=[0,0,0];_e[Ae]>0?Re[Ae]=N[1][Ae]:Re[Ae]=N[0][Ae];for(var ce=0;ce<2;++ce){var Ze=(Ae+1+ce)%3,ut=(Ae+1+(ce^1))%3;this.gridEnable[Ze]&&this._lines.drawGrid(Ze,ut,this.bounds,Re,this.gridColor[Ze],this.gridWidth[Ze]*this.pixelRatio)}for(var ce=0;ce<2;++ce){var Ze=(Ae+1+ce)%3,ut=(Ae+1+(ce^1))%3;this.zeroEnable[ut]&&Math.min(N[0][ut],N[1][ut])<=0&&Math.max(N[0][ut],N[1][ut])>=0&&this._lines.drawZero(Ze,ut,this.bounds,Re,this.zeroLineColor[ut],this.zeroLineWidth[ut]*this.pixelRatio)}}for(var Ae=0;Ae<3;++Ae){this.lineEnable[Ae]&&this._lines.drawAxisLine(Ae,this.bounds,Fe[Ae].primalOffset,this.lineColor[Ae],this.lineWidth[Ae]*this.pixelRatio),this.lineMirror[Ae]&&this._lines.drawAxisLine(Ae,this.bounds,Fe[Ae].mirrorOffset,this.lineColor[Ae],this.lineWidth[Ae]*this.pixelRatio);for(var pt=p(P,Fe[Ae].primalMinor),Zt=p(T,Fe[Ae].mirrorMinor),st=this.lineTickLength,ce=0;ce<3;++ce){var lt=Le/G[5*ce];pt[ce]*=st[ce]*lt,Zt[ce]*=st[ce]*lt}this.lineTickEnable[Ae]&&this._lines.drawAxisTicks(Ae,Fe[Ae].primalOffset,pt,this.lineTickColor[Ae],this.lineTickWidth[Ae]*this.pixelRatio),this.lineTickMirror[Ae]&&this._lines.drawAxisTicks(Ae,Fe[Ae].mirrorOffset,Zt,this.lineTickColor[Ae],this.lineTickWidth[Ae]*this.pixelRatio)}this._lines.unbind(),this._text.bind(G,Z,H,this.pixelRatio);var Gt,Nt=.5,Jt,sr;function wr(_t){sr=[0,0,0],sr[_t]=1}function cr(_t,It,mt){var er=(_t+1)%3,lr=(_t+2)%3,Tr=It[er],Lr=It[lr],ti=mt[er],Br=mt[lr];if(Tr>0&&Br>0){wr(er);return}else if(Tr>0&&Br<0){wr(er);return}else if(Tr<0&&Br>0){wr(er);return}else if(Tr<0&&Br<0){wr(er);return}else if(Lr>0&&ti>0){wr(lr);return}else if(Lr>0&&ti<0){wr(lr);return}else if(Lr<0&&ti>0){wr(lr);return}else if(Lr<0&&ti<0){wr(lr);return}}for(var Ae=0;Ae<3;++Ae){for(var $e=Fe[Ae].primalMinor,St=Fe[Ae].mirrorMinor,Qt=p(z,Fe[Ae].primalOffset),ce=0;ce<3;++ce)this.lineTickEnable[Ae]&&(Qt[ce]+=Le*$e[ce]*Math.max(this.lineTickLength[ce],0)/G[5*ce]);var Vt=[0,0,0];if(Vt[Ae]=1,this.tickEnable[Ae]){this.tickAngle[Ae]===-3600?(this.tickAngle[Ae]=0,this.tickAlign[Ae]=\"auto\"):this.tickAlign[Ae]=-1,Jt=1,Gt=[this.tickAlign[Ae],Nt,Jt],Gt[0]===\"auto\"?Gt[0]=g:Gt[0]=parseInt(\"\"+Gt[0]),sr=[0,0,0],cr(Ae,$e,St);for(var ce=0;ce<3;++ce)Qt[ce]+=Le*$e[ce]*this.tickPad[ce]/G[5*ce];this._text.drawTicks(Ae,this.tickSize[Ae],this.tickAngle[Ae],Qt,this.tickColor[Ae],Vt,sr,Gt)}if(this.labelEnable[Ae]){Jt=0,sr=[0,0,0],this.labels[Ae].length>4&&(wr(Ae),Jt=1),Gt=[this.labelAlign[Ae],Nt,Jt],Gt[0]===\"auto\"?Gt[0]=g:Gt[0]=parseInt(\"\"+Gt[0]);for(var ce=0;ce<3;++ce)Qt[ce]+=Le*$e[ce]*this.labelPad[ce]/G[5*ce];Qt[Ae]+=.5*(N[0][Ae]+N[1][Ae]),this._text.drawLabel(Ae,this.labelSize[Ae],this.labelAngle[Ae],Qt,this.labelColor[Ae],[0,0,0],sr,Gt)}}this._text.unbind()},E.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null};function O(V,G){var Z=new k(V);return Z.update(G),Z}},3840:function(i){\"use strict\";i.exports=L;var a=0,o=1;function s(x,C,M,g,P,T){this._color=x,this.key=C,this.value=M,this.left=g,this.right=P,this._count=T}function l(x){return new s(x._color,x.key,x.value,x.left,x.right,x._count)}function u(x,C){return new s(x,C.key,C.value,C.left,C.right,C._count)}function c(x){x._count=1+(x.left?x.left._count:0)+(x.right?x.right._count:0)}function f(x,C){this._compare=x,this.root=C}var h=f.prototype;Object.defineProperty(h,\"keys\",{get:function(){var x=[];return 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ir=ke+this[++xe]*Math.pow(2,8)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,24),ar=this[++xe]+this[++xe]*Math.pow(2,8)+this[++xe]*Math.pow(2,16)+vt*Math.pow(2,24);return BigInt(ir)+(BigInt(ar)<<BigInt(32))}),T.prototype.readBigUInt64BE=tt(function(xe){xe=xe>>>0,mt(xe,\"offset\");var ke=this[xe],vt=this[xe+7];(ke===void 0||vt===void 0)&&er(xe,this.length-8);var ir=ke*Math.pow(2,24)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,8)+this[++xe],ar=this[++xe]*Math.pow(2,24)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,8)+vt;return(BigInt(ir)<<BigInt(32))+BigInt(ar)}),T.prototype.readIntLE=function(xe,ke,vt){xe=xe>>>0,ke=ke>>>0,vt||Gt(xe,ke,this.length);for(var ir=this[xe],ar=1,vr=0;++vr<ke&&(ar*=256);)ir+=this[xe+vr]*ar;return ar*=128,ir>=ar&&(ir-=Math.pow(2,8*ke)),ir},T.prototype.readIntBE=function(xe,ke,vt){xe=xe>>>0,ke=ke>>>0,vt||Gt(xe,ke,this.length);for(var ir=ke,ar=1,vr=this[xe+--ir];ir>0&&(ar*=256);)vr+=this[xe+--ir]*ar;return ar*=128,vr>=ar&&(vr-=Math.pow(2,8*ke)),vr},T.prototype.readInt8=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,1,this.length),this[xe]&128?(255-this[xe]+1)*-1:this[xe]},T.prototype.readInt16LE=function(xe,ke){xe=xe>>>0,ke||Gt(xe,2,this.length);var vt=this[xe]|this[xe+1]<<8;return vt&32768?vt|4294901760:vt},T.prototype.readInt16BE=function(xe,ke){xe=xe>>>0,ke||Gt(xe,2,this.length);var vt=this[xe+1]|this[xe]<<8;return vt&32768?vt|4294901760:vt},T.prototype.readInt32LE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,4,this.length),this[xe]|this[xe+1]<<8|this[xe+2]<<16|this[xe+3]<<24},T.prototype.readInt32BE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,4,this.length),this[xe]<<24|this[xe+1]<<16|this[xe+2]<<8|this[xe+3]},T.prototype.readBigInt64LE=tt(function(xe){xe=xe>>>0,mt(xe,\"offset\");var ke=this[xe],vt=this[xe+7];(ke===void 0||vt===void 0)&&er(xe,this.length-8);var ir=this[xe+4]+this[xe+5]*Math.pow(2,8)+this[xe+6]*Math.pow(2,16)+(vt<<24);return(BigInt(ir)<<BigInt(32))+BigInt(ke+this[++xe]*Math.pow(2,8)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,24))}),T.prototype.readBigInt64BE=tt(function(xe){xe=xe>>>0,mt(xe,\"offset\");var ke=this[xe],vt=this[xe+7];(ke===void 0||vt===void 0)&&er(xe,this.length-8);var ir=(ke<<24)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,8)+this[++xe];return(BigInt(ir)<<BigInt(32))+BigInt(this[++xe]*Math.pow(2,24)+this[++xe]*Math.pow(2,16)+this[++xe]*Math.pow(2,8)+vt)}),T.prototype.readFloatLE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,4,this.length),x.read(this,xe,!0,23,4)},T.prototype.readFloatBE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,4,this.length),x.read(this,xe,!1,23,4)},T.prototype.readDoubleLE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,8,this.length),x.read(this,xe,!0,52,8)},T.prototype.readDoubleBE=function(xe,ke){return xe=xe>>>0,ke||Gt(xe,8,this.length),x.read(this,xe,!1,52,8)};function Nt(Ie,xe,ke,vt,ir,ar){if(!T.isBuffer(Ie))throw new TypeError('\"buffer\" argument must be a Buffer instance');if(xe>ir||xe<ar)throw new RangeError('\"value\" argument is out of bounds');if(ke+vt>Ie.length)throw new RangeError(\"Index out of range\")}T.prototype.writeUintLE=T.prototype.writeUIntLE=function(xe,ke,vt,ir){if(xe=+xe,ke=ke>>>0,vt=vt>>>0,!ir){var ar=Math.pow(2,8*vt)-1;Nt(this,xe,ke,vt,ar,0)}var vr=1,ii=0;for(this[ke]=xe&255;++ii<vt&&(vr*=256);)this[ke+ii]=xe/vr&255;return ke+vt},T.prototype.writeUintBE=T.prototype.writeUIntBE=function(xe,ke,vt,ir){if(xe=+xe,ke=ke>>>0,vt=vt>>>0,!ir){var ar=Math.pow(2,8*vt)-1;Nt(this,xe,ke,vt,ar,0)}var vr=vt-1,ii=1;for(this[ke+vr]=xe&255;--vr>=0&&(ii*=256);)this[ke+vr]=xe/ii&255;return ke+vt},T.prototype.writeUint8=T.prototype.writeUInt8=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,1,255,0),this[ke]=xe&255,ke+1},T.prototype.writeUint16LE=T.prototype.writeUInt16LE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,2,65535,0),this[ke]=xe&255,this[ke+1]=xe>>>8,ke+2},T.prototype.writeUint16BE=T.prototype.writeUInt16BE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,2,65535,0),this[ke]=xe>>>8,this[ke+1]=xe&255,ke+2},T.prototype.writeUint32LE=T.prototype.writeUInt32LE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,4,4294967295,0),this[ke+3]=xe>>>24,this[ke+2]=xe>>>16,this[ke+1]=xe>>>8,this[ke]=xe&255,ke+4},T.prototype.writeUint32BE=T.prototype.writeUInt32BE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,4,4294967295,0),this[ke]=xe>>>24,this[ke+1]=xe>>>16,this[ke+2]=xe>>>8,this[ke+3]=xe&255,ke+4};function Jt(Ie,xe,ke,vt,ir){It(xe,vt,ir,Ie,ke,7);var ar=Number(xe&BigInt(4294967295));Ie[ke++]=ar,ar=ar>>8,Ie[ke++]=ar,ar=ar>>8,Ie[ke++]=ar,ar=ar>>8,Ie[ke++]=ar;var vr=Number(xe>>BigInt(32)&BigInt(4294967295));return Ie[ke++]=vr,vr=vr>>8,Ie[ke++]=vr,vr=vr>>8,Ie[ke++]=vr,vr=vr>>8,Ie[ke++]=vr,ke}function sr(Ie,xe,ke,vt,ir){It(xe,vt,ir,Ie,ke,7);var ar=Number(xe&BigInt(4294967295));Ie[ke+7]=ar,ar=ar>>8,Ie[ke+6]=ar,ar=ar>>8,Ie[ke+5]=ar,ar=ar>>8,Ie[ke+4]=ar;var vr=Number(xe>>BigInt(32)&BigInt(4294967295));return Ie[ke+3]=vr,vr=vr>>8,Ie[ke+2]=vr,vr=vr>>8,Ie[ke+1]=vr,vr=vr>>8,Ie[ke]=vr,ke+8}T.prototype.writeBigUInt64LE=tt(function(xe){var ke=arguments.length>1&&arguments[1]!==void 0?arguments[1]:0;return Jt(this,xe,ke,BigInt(0),BigInt(\"0xffffffffffffffff\"))}),T.prototype.writeBigUInt64BE=tt(function(xe){var ke=arguments.length>1&&arguments[1]!==void 0?arguments[1]:0;return sr(this,xe,ke,BigInt(0),BigInt(\"0xffffffffffffffff\"))}),T.prototype.writeIntLE=function(xe,ke,vt,ir){if(xe=+xe,ke=ke>>>0,!ir){var ar=Math.pow(2,8*vt-1);Nt(this,xe,ke,vt,ar-1,-ar)}var vr=0,ii=1,pi=0;for(this[ke]=xe&255;++vr<vt&&(ii*=256);)xe<0&&pi===0&&this[ke+vr-1]!==0&&(pi=1),this[ke+vr]=(xe/ii>>0)-pi&255;return ke+vt},T.prototype.writeIntBE=function(xe,ke,vt,ir){if(xe=+xe,ke=ke>>>0,!ir){var ar=Math.pow(2,8*vt-1);Nt(this,xe,ke,vt,ar-1,-ar)}var vr=vt-1,ii=1,pi=0;for(this[ke+vr]=xe&255;--vr>=0&&(ii*=256);)xe<0&&pi===0&&this[ke+vr+1]!==0&&(pi=1),this[ke+vr]=(xe/ii>>0)-pi&255;return ke+vt},T.prototype.writeInt8=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,1,127,-128),xe<0&&(xe=255+xe+1),this[ke]=xe&255,ke+1},T.prototype.writeInt16LE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,2,32767,-32768),this[ke]=xe&255,this[ke+1]=xe>>>8,ke+2},T.prototype.writeInt16BE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,2,32767,-32768),this[ke]=xe>>>8,this[ke+1]=xe&255,ke+2},T.prototype.writeInt32LE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,4,2147483647,-2147483648),this[ke]=xe&255,this[ke+1]=xe>>>8,this[ke+2]=xe>>>16,this[ke+3]=xe>>>24,ke+4},T.prototype.writeInt32BE=function(xe,ke,vt){return xe=+xe,ke=ke>>>0,vt||Nt(this,xe,ke,4,2147483647,-2147483648),xe<0&&(xe=4294967295+xe+1),this[ke]=xe>>>24,this[ke+1]=xe>>>16,this[ke+2]=xe>>>8,this[ke+3]=xe&255,ke+4},T.prototype.writeBigInt64LE=tt(function(xe){var ke=arguments.length>1&&arguments[1]!==void 0?arguments[1]:0;return Jt(this,xe,ke,-BigInt(\"0x8000000000000000\"),BigInt(\"0x7fffffffffffffff\"))}),T.prototype.writeBigInt64BE=tt(function(xe){var ke=arguments.length>1&&arguments[1]!==void 0?arguments[1]:0;return sr(this,xe,ke,-BigInt(\"0x8000000000000000\"),BigInt(\"0x7fffffffffffffff\"))});function wr(Ie,xe,ke,vt,ir,ar){if(ke+vt>Ie.length)throw new RangeError(\"Index out of range\");if(ke<0)throw new RangeError(\"Index out of range\")}function cr(Ie,xe,ke,vt,ir){return xe=+xe,ke=ke>>>0,ir||wr(Ie,xe,ke,4,34028234663852886e22,-34028234663852886e22),x.write(Ie,xe,ke,vt,23,4),ke+4}T.prototype.writeFloatLE=function(xe,ke,vt){return cr(this,xe,ke,!0,vt)},T.prototype.writeFloatBE=function(xe,ke,vt){return 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Uint8Array.prototype.copyWithin==\"function\"?this.copyWithin(ke,vt,ir):Uint8Array.prototype.set.call(xe,this.subarray(vt,ir),ke),ar},T.prototype.fill=function(xe,ke,vt,ir){if(typeof xe==\"string\"){if(typeof ke==\"string\"?(ir=ke,ke=0,vt=this.length):typeof vt==\"string\"&&(ir=vt,vt=this.length),ir!==void 0&&typeof ir!=\"string\")throw new TypeError(\"encoding must be a string\");if(typeof ir==\"string\"&&!T.isEncoding(ir))throw new TypeError(\"Unknown encoding: \"+ir);if(xe.length===1){var ar=xe.charCodeAt(0);(ir===\"utf8\"&&ar<128||ir===\"latin1\")&&(xe=ar)}}else typeof xe==\"number\"?xe=xe&255:typeof xe==\"boolean\"&&(xe=Number(xe));if(ke<0||this.length<ke||this.length<vt)throw new RangeError(\"Out of range index\");if(vt<=ke)return this;ke=ke>>>0,vt=vt===void 0?this.length:vt>>>0,xe||(xe=0);var vr;if(typeof xe==\"number\")for(vr=ke;vr<vt;++vr)this[vr]=xe;else{var ii=T.isBuffer(xe)?xe:T.from(xe,ir),pi=ii.length;if(pi===0)throw new TypeError('The value \"'+xe+'\" is invalid for 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o[0]=s[0]+l[0]*u,o[1]=s[1]+l[1]*u,o[2]=s[2]+l[2]*u,o[3]=s[3]+l[3]*u,o}},4905:function(i,a,o){var s=o(5874);i.exports=l;function l(u,c){var f=s(c),h=[];return h=h.concat(f(u)),h=h.concat(f(null)),h}},4935:function(i,a,o){\"use strict\";i.exports=k;var s=o(2762),l=o(8116),u=o(4359),c=o(1879).Q,f=window||process.global||{},h=f.__TEXT_CACHE||{};f.__TEXT_CACHE={};var d=3;function v(E,S,L,x){this.gl=E,this.shader=S,this.buffer=L,this.vao=x,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var _=v.prototype,b=[0,0];_.bind=function(E,S,L,x){this.vao.bind(),this.shader.bind();var C=this.shader.uniforms;C.model=E,C.view=S,C.projection=L,C.pixelScale=x,b[0]=this.gl.drawingBufferWidth,b[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=b},_.unbind=function(){this.vao.unbind()},_.update=function(E,S,L,x,C){var M=[];function g(j,re,oe,_e,Ee,Ce){var me=[oe.style,oe.weight,oe.variant,oe.family].join(\"_\"),ie=h[me];ie||(ie=h[me]={});var 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p(E,S){try{return u(E,S)}catch(L){return console.warn('error vectorizing text:\"'+E+'\" error:',L),{cells:[],positions:[]}}}function k(E,S,L,x,C,M){var g=s(E),P=l(E,[{buffer:g,size:3}]),T=c(E);T.attributes.position.location=0;var z=new v(E,T,g,P);return z.update(S,L,x,C,M),z}},5023:function(i,a,o){\"use strict\";var s=o(2478);i.exports=d;function l(v,_,b,p,k,E,S){this.cells=v,this.neighbor=_,this.flags=p,this.constraint=b,this.active=k,this.next=E,this.boundary=S}var u=l.prototype;function c(v,_){return v[0]-_[0]||v[1]-_[1]||v[2]-_[2]}u.locate=function(){var v=[0,0,0];return function(_,b,p){var k=_,E=b,S=p;return b<p?b<_&&(k=b,E=p,S=_):p<_&&(k=p,E=_,S=b),k<0?-1:(v[0]=k,v[1]=E,v[2]=S,s.eq(this.cells,v,c))}}();function f(v,_){for(var b=v.cells(),p=b.length,k=0;k<p;++k){var E=b[k],S=E[0],L=E[1],x=E[2];L<x?L<S&&(E[0]=L,E[1]=x,E[2]=S):x<S&&(E[0]=x,E[1]=S,E[2]=L)}b.sort(c);for(var C=new Array(p),k=0;k<C.length;++k)C[k]=0;var M=[],g=[],P=new Array(3*p),T=new 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z=f[T],re=z[0],oe=z[1],_e=z[2],Ee=C[T],Ce=s.length(Ee)*H,me=0,ie=8;me<ie;me++){d.positions.push([re,oe,_e,j++]),d.positions.push([re,oe,_e,j++]),d.positions.push([re,oe,_e,j++]),d.positions.push([re,oe,_e,j++]),d.positions.push([re,oe,_e,j++]),d.positions.push([re,oe,_e,j++]),d.vectors.push(Ee),d.vectors.push(Ee),d.vectors.push(Ee),d.vectors.push(Ee),d.vectors.push(Ee),d.vectors.push(Ee),d.vertexIntensity.push(Ce,Ce,Ce),d.vertexIntensity.push(Ce,Ce,Ce);var Se=d.positions.length;d.cells.push([Se-6,Se-5,Se-4],[Se-3,Se-2,Se-1])}return d};var l=o(614);i.exports.createMesh=o(9060),i.exports.createConeMesh=function(u,c){return i.exports.createMesh(u,c,{shaders:l,traceType:\"cone\"})}},6429:function(i,a,o){\"use strict\";i.exports=x;var s=o(8828),l=o(6760),u=o(5202),c=o(3250),f=new Array(16),h=new Array(8),d=new Array(8),v=new Array(3),_=[0,0,0];(function(){for(var C=0;C<8;++C)h[C]=[1,1,1,1],d[C]=[1,1,1]})();function b(C,M,g){for(var P=0;P<4;++P){C[P]=g[12+P];for(var T=0;T<3;++T)C[P]+=M[T]*g[4*T+P]}}var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function k(C){for(var M=0;M<p.length;++M)if(C=u.positive(C,p[M]),C.length<3)return 0;for(var g=C[0],P=g[0]/g[3],T=g[1]/g[3],z=0,M=1;M+1<C.length;++M){var O=C[M],V=C[M+1],G=O[0]/O[3],Z=O[1]/O[3],H=V[0]/V[3],N=V[1]/V[3],j=G-P,re=Z-T,oe=H-P,_e=N-T;z+=Math.abs(j*_e-re*oe)}return z}var E=[1,1,1],S=[0,0,0],L={cubeEdges:E,axis:S};function x(C,M,g,P,T){l(f,M,C),l(f,g,f);for(var z=0,O=0;O<2;++O){v[2]=P[O][2];for(var V=0;V<2;++V){v[1]=P[V][1];for(var G=0;G<2;++G)v[0]=P[G][0],b(h[z],v,f),z+=1}}for(var Z=-1,O=0;O<8;++O){for(var H=h[O][3],N=0;N<3;++N)d[O][N]=h[O][N]/H;T&&(d[O][2]*=-1),H<0&&(Z<0||d[O][2]<d[Z][2])&&(Z=O)}if(Z<0){Z=0;for(var j=0;j<3;++j){for(var re=(j+2)%3,oe=(j+1)%3,_e=-1,Ee=-1,Ce=0;Ce<2;++Ce){var me=Ce<<j,ie=me+(Ce<<re)+(1-Ce<<oe),Se=me+(1-Ce<<re)+(Ce<<oe);c(d[me],d[ie],d[Se],_)<0||(Ce?_e=1:Ee=1)}if(_e<0||Ee<0){Ee>_e&&(Z|=1<<j);continue}for(var Ce=0;Ce<2;++Ce){var me=Ce<<j,ie=me+(Ce<<re)+(1-Ce<<oe),Se=me+(1-Ce<<re)+(Ce<<oe),Le=k([h[me],h[ie],h[Se],h[me+(1<<re)+(1<<oe)]]);Ce?_e=Le:Ee=Le}if(Ee>_e){Z|=1<<j;continue}}}for(var Ae=7^Z,Fe=-1,O=0;O<8;++O)O===Z||O===Ae||(Fe<0||d[Fe][1]>d[O][1])&&(Fe=O);for(var Pe=-1,O=0;O<3;++O){var ge=Fe^1<<O;if(!(ge===Z||ge===Ae)){Pe<0&&(Pe=ge);var oe=d[ge];oe[0]<d[Pe][0]&&(Pe=ge)}}for(var Re=-1,O=0;O<3;++O){var ge=Fe^1<<O;if(!(ge===Z||ge===Ae||ge===Pe)){Re<0&&(Re=ge);var oe=d[ge];oe[0]>d[Re][0]&&(Re=ge)}}var ce=E;ce[0]=ce[1]=ce[2]=0,ce[s.log2(Pe^Fe)]=Fe&Pe,ce[s.log2(Fe^Re)]=Fe&Re;var Ze=Re^7;Ze===Z||Ze===Ae?(Ze=Pe^7,ce[s.log2(Re^Ze)]=Ze&Re):ce[s.log2(Pe^Ze)]=Ze&Pe;for(var ut=S,pt=Z,j=0;j<3;++j)pt&1<<j?ut[j]=-1:ut[j]=1;return L}},6444:function(i,a){\"use strict\";a.create=s,a.equal=l;function o(u,c){var f=u+\"\",h=f.indexOf(\".\"),d=0;h>=0&&(d=f.length-h-1);var v=Math.pow(10,d),_=Math.round(u*c*v),b=_+\"\";if(b.indexOf(\"e\")>=0)return b;var p=_/v,k=_%v;_<0?(p=-Math.ceil(p)|0,k=-k|0):(p=Math.floor(p)|0,k=k|0);var E=\"\"+p;if(_<0&&(E=\"-\"+E),d){for(var S=\"\"+k;S.length<d;)S=\"0\"+S;return E+\".\"+S}else return E}function s(u,c){for(var f=[],h=0;h<3;++h){for(var d=[],v=.5*(u[0][h]+u[1][h]),_=0;_*c[h]<=u[1][h];++_)d.push({x:_*c[h],text:o(c[h],_)});for(var _=-1;_*c[h]>=u[0][h];--_)d.push({x:_*c[h],text:o(c[h],_)});f.push(d)}return f}function l(u,c){for(var f=0;f<3;++f){if(u[f].length!==c[f].length)return!1;for(var h=0;h<u[f].length;++h){var d=u[f][h],v=c[f][h];if(d.x!==v.x||d.text!==v.text||d.font!==v.font||d.fontColor!==v.fontColor||d.fontSize!==v.fontSize||d.dx!==v.dx||d.dy!==v.dy)return!1}}return!0}},6468:function(i){i.exports=function(o){return atob(o)}},6504:function(i,a,o){\"use strict\";var s=o(869);i.exports=l;function l(u,c){return s(u[0].mul(c[0]),u[1].mul(c[1]))}},6582:function(i,a,o){var s=o(7894);i.exports=l;function l(u,c,f,h){var d,v,_,b,p,k,E,S,L,x,C=c[0],M=c[1],g=c[2],P=h[0],T=h[1],z=h[2],O=f[0],V=f[1],G=f[2];return Math.abs(C-O)<1e-6&&Math.abs(M-V)<1e-6&&Math.abs(g-G)<1e-6?s(u):(E=C-O,S=M-V,L=g-G,x=1/Math.sqrt(E*E+S*S+L*L),E*=x,S*=x,L*=x,d=T*L-z*S,v=z*E-P*L,_=P*S-T*E,x=Math.sqrt(d*d+v*v+_*_),x?(x=1/x,d*=x,v*=x,_*=x):(d=0,v=0,_=0),b=S*_-L*v,p=L*d-E*_,k=E*v-S*d,x=Math.sqrt(b*b+p*p+k*k),x?(x=1/x,b*=x,p*=x,k*=x):(b=0,p=0,k=0),u[0]=d,u[1]=b,u[2]=E,u[3]=0,u[4]=v,u[5]=p,u[6]=S,u[7]=0,u[8]=_,u[9]=k,u[10]=L,u[11]=0,u[12]=-(d*C+v*M+_*g),u[13]=-(b*C+p*M+k*g),u[14]=-(E*C+S*M+L*g),u[15]=1,u)}},6621:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]*l,o[1]=s[1]*l,o[2]=s[2]*l,o}},6658:function(i){i.exports=a;function a(o,s,l,u){var c=s[0],f=s[1],h=s[2];return o[0]=c+u*(l[0]-c),o[1]=f+u*(l[1]-f),o[2]=h+u*(l[2]-h),o}},6690:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]/l[0],o[1]=s[1]/l[1],o[2]=s[2]/l[2],o}},6729:function(i,a,o){\"use strict\";var s=o(3642),l=o(395);i.exports=u;function u(d){var v,_,b,p,k,E,S,L,g,x,C;if(d||(d={}),L=(d.nshades||72)-1,S=d.format||\"hex\",E=d.colormap,E||(E=\"jet\"),typeof E==\"string\"){if(E=E.toLowerCase(),!s[E])throw Error(E+\" not a supported colorscale\");k=s[E]}else if(Array.isArray(E))k=E.slice();else throw Error(\"unsupported colormap option\",E);if(k.length>L+1)throw new Error(E+\" map requires nshades to be at least size \"+k.length);Array.isArray(d.alpha)?d.alpha.length!==2?x=[1,1]:x=d.alpha.slice():typeof d.alpha==\"number\"?x=[d.alpha,d.alpha]:x=[1,1],v=k.map(function(z){return Math.round(z.index*L)}),x[0]=Math.min(Math.max(x[0],0),1),x[1]=Math.min(Math.max(x[1],0),1);var M=k.map(function(z,O){var V=k[O].index,G=k[O].rgb.slice();return G.length===4&&G[3]>=0&&G[3]<=1||(G[3]=x[0]+(x[1]-x[0])*V),G}),g=[];for(C=0;C<v.length-1;++C){p=v[C+1]-v[C],_=M[C],b=M[C+1];for(var P=0;P<p;P++){var T=P/p;g.push([Math.round(l(_[0],b[0],T)),Math.round(l(_[1],b[1],T)),Math.round(l(_[2],b[2],T)),l(_[3],b[3],T)])}}return g.push(k[k.length-1].rgb.concat(x[1])),S===\"hex\"?g=g.map(f):S===\"rgbaString\"?g=g.map(h):S===\"float\"&&(g=g.map(c)),g}function c(d){return[d[0]/255,d[1]/255,d[2]/255,d[3]]}function f(d){for(var v,_=\"#\",b=0;b<3;++b)v=d[b],v=v.toString(16),_+=(\"00\"+v).substr(v.length);return _}function h(d){return\"rgba(\"+d.join(\",\")+\")\"}},6740:function(i,a,o){var s=o(3236),l=s([`precision highp float;\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "vec3 getOrthogonalVector(vec3 v) {\n",
+       "  // Return up-vector for only-z vector.\n",
+       "  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n",
+       "  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n",
+       "  // Assign z = 0, x = -b, y = a:\n",
+       "  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n",
+       "  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n",
+       "    return normalize(vec3(-v.y, v.x, 0.0));\n",
+       "  } else {\n",
+       "    return normalize(vec3(0.0, v.z, -v.y));\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "// Calculate the tube vertex and normal at the given index.\n",
+       "//\n",
+       "// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\n",
+       "//\n",
+       "// Each tube segment is made up of a ring of vertices.\n",
+       "// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\n",
+       "// The indexes of tube segments run from 0 to 8.\n",
+       "//\n",
+       "vec3 getTubePosition(vec3 d, float index, out vec3 normal) {\n",
+       "  float segmentCount = 8.0;\n",
+       "\n",
+       "  float angle = 2.0 * 3.14159 * (index / segmentCount);\n",
+       "\n",
+       "  vec3 u = getOrthogonalVector(d);\n",
+       "  vec3 v = normalize(cross(u, d));\n",
+       "\n",
+       "  vec3 x = u * cos(angle) * length(d);\n",
+       "  vec3 y = v * sin(angle) * length(d);\n",
+       "  vec3 v3 = x + y;\n",
+       "\n",
+       "  normal = normalize(v3);\n",
+       "\n",
+       "  return v3;\n",
+       "}\n",
+       "\n",
+       "attribute vec4 vector;\n",
+       "attribute vec4 color, position;\n",
+       "attribute vec2 uv;\n",
+       "\n",
+       "uniform float vectorScale, tubeScale;\n",
+       "uniform mat4 model, view, projection, inverseModel;\n",
+       "uniform vec3 eyePosition, lightPosition;\n",
+       "\n",
+       "varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  // Scale the vector magnitude to stay constant with\n",
+       "  // model & view changes.\n",
+       "  vec3 normal;\n",
+       "  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n",
+       "  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n",
+       "\n",
+       "  //Lighting geometry parameters\n",
+       "  vec4 cameraCoordinate = view * tubePosition;\n",
+       "  cameraCoordinate.xyz /= cameraCoordinate.w;\n",
+       "  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n",
+       "  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n",
+       "  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n",
+       "\n",
+       "  // vec4 m_position  = model * vec4(tubePosition, 1.0);\n",
+       "  vec4 t_position  = view * tubePosition;\n",
+       "  gl_Position      = projection * t_position;\n",
+       "\n",
+       "  f_color          = color;\n",
+       "  f_data           = tubePosition.xyz;\n",
+       "  f_position       = position.xyz;\n",
+       "  f_uv             = uv;\n",
+       "}\n",
+       "`]),u=s([`#extension GL_OES_standard_derivatives : enable\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "float beckmannDistribution(float x, float roughness) {\n",
+       "  float NdotH = max(x, 0.0001);\n",
+       "  float cos2Alpha = NdotH * NdotH;\n",
+       "  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n",
+       "  float roughness2 = roughness * roughness;\n",
+       "  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n",
+       "  return exp(tan2Alpha / roughness2) / denom;\n",
+       "}\n",
+       "\n",
+       "float cookTorranceSpecular(\n",
+       "  vec3 lightDirection,\n",
+       "  vec3 viewDirection,\n",
+       "  vec3 surfaceNormal,\n",
+       "  float roughness,\n",
+       "  float fresnel) {\n",
+       "\n",
+       "  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n",
+       "  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n",
+       "\n",
+       "  //Half angle vector\n",
+       "  vec3 H = normalize(lightDirection + viewDirection);\n",
+       "\n",
+       "  //Geometric term\n",
+       "  float NdotH = max(dot(surfaceNormal, H), 0.0);\n",
+       "  float VdotH = max(dot(viewDirection, H), 0.000001);\n",
+       "  float LdotH = max(dot(lightDirection, H), 0.000001);\n",
+       "  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n",
+       "  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n",
+       "  float G = min(1.0, min(G1, G2));\n",
+       "  \n",
+       "  //Distribution term\n",
+       "  float D = beckmannDistribution(NdotH, roughness);\n",
+       "\n",
+       "  //Fresnel term\n",
+       "  float F = pow(1.0 - VdotN, fresnel);\n",
+       "\n",
+       "  //Multiply terms and done\n",
+       "  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3 clipBounds[2];\n",
+       "uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\n",
+       "uniform sampler2D texture;\n",
+       "\n",
+       "varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\n",
+       "varying vec4 f_color;\n",
+       "varying vec2 f_uv;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n",
+       "  vec3 N = normalize(f_normal);\n",
+       "  vec3 L = normalize(f_lightDirection);\n",
+       "  vec3 V = normalize(f_eyeDirection);\n",
+       "\n",
+       "  if(gl_FrontFacing) {\n",
+       "    N = -N;\n",
+       "  }\n",
+       "\n",
+       "  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n",
+       "  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n",
+       "\n",
+       "  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n",
+       "  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n",
+       "\n",
+       "  gl_FragColor = litColor * opacity;\n",
+       "}\n",
+       "`]),c=s([`precision highp float;\n",
+       "\n",
+       "precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "vec3 getOrthogonalVector(vec3 v) {\n",
+       "  // Return up-vector for only-z vector.\n",
+       "  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n",
+       "  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n",
+       "  // Assign z = 0, x = -b, y = a:\n",
+       "  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n",
+       "  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n",
+       "    return normalize(vec3(-v.y, v.x, 0.0));\n",
+       "  } else {\n",
+       "    return normalize(vec3(0.0, v.z, -v.y));\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "// Calculate the tube vertex and normal at the given index.\n",
+       "//\n",
+       "// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\n",
+       "//\n",
+       "// Each tube segment is made up of a ring of vertices.\n",
+       "// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\n",
+       "// The indexes of tube segments run from 0 to 8.\n",
+       "//\n",
+       "vec3 getTubePosition(vec3 d, float index, out vec3 normal) {\n",
+       "  float segmentCount = 8.0;\n",
+       "\n",
+       "  float angle = 2.0 * 3.14159 * (index / segmentCount);\n",
+       "\n",
+       "  vec3 u = getOrthogonalVector(d);\n",
+       "  vec3 v = normalize(cross(u, d));\n",
+       "\n",
+       "  vec3 x = u * cos(angle) * length(d);\n",
+       "  vec3 y = v * sin(angle) * length(d);\n",
+       "  vec3 v3 = x + y;\n",
+       "\n",
+       "  normal = normalize(v3);\n",
+       "\n",
+       "  return v3;\n",
+       "}\n",
+       "\n",
+       "attribute vec4 vector;\n",
+       "attribute vec4 position;\n",
+       "attribute vec4 id;\n",
+       "\n",
+       "uniform mat4 model, view, projection;\n",
+       "uniform float tubeScale;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  vec3 normal;\n",
+       "  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n",
+       "  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n",
+       "\n",
+       "  gl_Position = projection * (view * tubePosition);\n",
+       "  f_id        = id;\n",
+       "  f_position  = position.xyz;\n",
+       "}\n",
+       "`]),f=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3  clipBounds[2];\n",
+       "uniform float pickId;\n",
+       "\n",
+       "varying vec3 f_position;\n",
+       "varying vec4 f_id;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n",
+       "\n",
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j=N,re=0;return(j&8191)===0&&(re+=13,j>>>=13),(j&127)===0&&(re+=7,j>>>=7),(j&15)===0&&(re+=4,j>>>=4),(j&3)===0&&(re+=2,j>>>=2),(j&1)===0&&re++,re},f.prototype.bitLength=function(){var N=this.words[this.length-1],j=this._countBits(N);return(this.length-1)*26+j};function E(H){for(var N=new Array(H.bitLength()),j=0;j<N.length;j++){var re=j/26|0,oe=j%26;N[j]=(H.words[re]&1<<oe)>>>oe}return N}f.prototype.zeroBits=function(){if(this.isZero())return 0;for(var N=0,j=0;j<this.length;j++){var re=this._zeroBits(this.words[j]);if(N+=re,re!==26)break}return N},f.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},f.prototype.toTwos=function(N){return this.negative!==0?this.abs().inotn(N).iaddn(1):this.clone()},f.prototype.fromTwos=function(N){return this.testn(N-1)?this.notn(N).iaddn(1).ineg():this.clone()},f.prototype.isNeg=function(){return this.negative!==0},f.prototype.neg=function(){return this.clone().ineg()},f.prototype.ineg=function(){return 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j,re;this.length>N.length?(j=this,re=N):(j=N,re=this);for(var oe=0;oe<re.length;oe++)this.words[oe]=j.words[oe]^re.words[oe];if(this!==j)for(;oe<j.length;oe++)this.words[oe]=j.words[oe];return this.length=j.length,this.strip()},f.prototype.ixor=function(N){return u((this.negative|N.negative)===0),this.iuxor(N)},f.prototype.xor=function(N){return this.length>N.length?this.clone().ixor(N):N.clone().ixor(this)},f.prototype.uxor=function(N){return this.length>N.length?this.clone().iuxor(N):N.clone().iuxor(this)},f.prototype.inotn=function(N){u(typeof N==\"number\"&&N>=0);var j=Math.ceil(N/26)|0,re=N%26;this._expand(j),re>0&&j--;for(var oe=0;oe<j;oe++)this.words[oe]=~this.words[oe]&67108863;return re>0&&(this.words[oe]=~this.words[oe]&67108863>>26-re),this.strip()},f.prototype.notn=function(N){return this.clone().inotn(N)},f.prototype.setn=function(N,j){u(typeof N==\"number\"&&N>=0);var re=N/26|0,oe=N%26;return this._expand(re+1),j?this.words[re]=this.words[re]|1<<oe:this.words[re]=this.words[re]&~(1<<oe),this.strip()},f.prototype.iadd=function(N){var j;if(this.negative!==0&&N.negative===0)return this.negative=0,j=this.isub(N),this.negative^=1,this._normSign();if(this.negative===0&&N.negative!==0)return N.negative=0,j=this.isub(N),N.negative=1,j._normSign();var re,oe;this.length>N.length?(re=this,oe=N):(re=N,oe=this);for(var _e=0,Ee=0;Ee<oe.length;Ee++)j=(re.words[Ee]|0)+(oe.words[Ee]|0)+_e,this.words[Ee]=j&67108863,_e=j>>>26;for(;_e!==0&&Ee<re.length;Ee++)j=(re.words[Ee]|0)+_e,this.words[Ee]=j&67108863,_e=j>>>26;if(this.length=re.length,_e!==0)this.words[this.length]=_e,this.length++;else if(re!==this)for(;Ee<re.length;Ee++)this.words[Ee]=re.words[Ee];return this},f.prototype.add=function(N){var j;return N.negative!==0&&this.negative===0?(N.negative=0,j=this.sub(N),N.negative^=1,j):N.negative===0&&this.negative!==0?(this.negative=0,j=N.sub(this),this.negative=1,j):this.length>N.length?this.clone().iadd(N):N.clone().iadd(this)},f.prototype.isub=function(N){if(N.negative!==0){N.negative=0;var j=this.iadd(N);return N.negative=1,j._normSign()}else if(this.negative!==0)return this.negative=0,this.iadd(N),this.negative=1,this._normSign();var re=this.cmp(N);if(re===0)return this.negative=0,this.length=1,this.words[0]=0,this;var oe,_e;re>0?(oe=this,_e=N):(oe=N,_e=this);for(var Ee=0,Ce=0;Ce<_e.length;Ce++)j=(oe.words[Ce]|0)-(_e.words[Ce]|0)+Ee,Ee=j>>26,this.words[Ce]=j&67108863;for(;Ee!==0&&Ce<oe.length;Ce++)j=(oe.words[Ce]|0)+Ee,Ee=j>>26,this.words[Ce]=j&67108863;if(Ee===0&&Ce<oe.length&&oe!==this)for(;Ce<oe.length;Ce++)this.words[Ce]=oe.words[Ce];return this.length=Math.max(this.length,Ce),oe!==this&&(this.negative=1),this.strip()},f.prototype.sub=function(N){return this.clone().isub(N)};function S(H,N,j){j.negative=N.negative^H.negative;var re=H.length+N.length|0;j.length=re,re=re-1|0;var oe=H.words[0]|0,_e=N.words[0]|0,Ee=oe*_e,Ce=Ee&67108863,me=Ee/67108864|0;j.words[0]=Ce;for(var ie=1;ie<re;ie++){for(var Se=me>>>26,Le=me&67108863,Ae=Math.min(ie,N.length-1),Fe=Math.max(0,ie-H.length+1);Fe<=Ae;Fe++){var Pe=ie-Fe|0;oe=H.words[Pe]|0,_e=N.words[Fe]|0,Ee=oe*_e+Le,Se+=Ee/67108864|0,Le=Ee&67108863}j.words[ie]=Le|0,me=Se|0}return me!==0?j.words[ie]=me|0:j.length--,j.strip()}var L=function(N,j,re){var oe=N.words,_e=j.words,Ee=re.words,Ce=0,me,ie,Se,Le=oe[0]|0,Ae=Le&8191,Fe=Le>>>13,Pe=oe[1]|0,ge=Pe&8191,Re=Pe>>>13,ce=oe[2]|0,Ze=ce&8191,ut=ce>>>13,pt=oe[3]|0,Zt=pt&8191,st=pt>>>13,lt=oe[4]|0,Gt=lt&8191,Nt=lt>>>13,Jt=oe[5]|0,sr=Jt&8191,wr=Jt>>>13,cr=oe[6]|0,$e=cr&8191,St=cr>>>13,Qt=oe[7]|0,Vt=Qt&8191,_t=Qt>>>13,It=oe[8]|0,mt=It&8191,er=It>>>13,lr=oe[9]|0,Tr=lr&8191,Lr=lr>>>13,ti=_e[0]|0,Br=ti&8191,Vr=ti>>>13,dt=_e[1]|0,Ge=dt&8191,Je=dt>>>13,je=_e[2]|0,tt=je&8191,xt=je>>>13,Ie=_e[3]|0,xe=Ie&8191,ke=Ie>>>13,vt=_e[4]|0,ir=vt&8191,ar=vt>>>13,vr=_e[5]|0,ii=vr&8191,pi=vr>>>13,$r=_e[6]|0,di=$r&8191,ji=$r>>>13,In=_e[7]|0,wi=In&8191,On=In>>>13,qn=_e[8]|0,Fn=qn&8191,ra=qn>>>13,la=_e[9]|0,Ut=la&8191,wt=la>>>13;re.negative=N.negative^j.negative,re.length=19,me=Math.imul(Ae,Br),ie=Math.imul(Ae,Vr),ie=ie+Math.imul(Fe,Br)|0,Se=Math.imul(Fe,Vr);var rr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(rr>>>26)|0,rr&=67108863,me=Math.imul(ge,Br),ie=Math.imul(ge,Vr),ie=ie+Math.imul(Re,Br)|0,Se=Math.imul(Re,Vr),me=me+Math.imul(Ae,Ge)|0,ie=ie+Math.imul(Ae,Je)|0,ie=ie+Math.imul(Fe,Ge)|0,Se=Se+Math.imul(Fe,Je)|0;var nr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(nr>>>26)|0,nr&=67108863,me=Math.imul(Ze,Br),ie=Math.imul(Ze,Vr),ie=ie+Math.imul(ut,Br)|0,Se=Math.imul(ut,Vr),me=me+Math.imul(ge,Ge)|0,ie=ie+Math.imul(ge,Je)|0,ie=ie+Math.imul(Re,Ge)|0,Se=Se+Math.imul(Re,Je)|0,me=me+Math.imul(Ae,tt)|0,ie=ie+Math.imul(Ae,xt)|0,ie=ie+Math.imul(Fe,tt)|0,Se=Se+Math.imul(Fe,xt)|0;var Er=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Er>>>26)|0,Er&=67108863,me=Math.imul(Zt,Br),ie=Math.imul(Zt,Vr),ie=ie+Math.imul(st,Br)|0,Se=Math.imul(st,Vr),me=me+Math.imul(Ze,Ge)|0,ie=ie+Math.imul(Ze,Je)|0,ie=ie+Math.imul(ut,Ge)|0,Se=Se+Math.imul(ut,Je)|0,me=me+Math.imul(ge,tt)|0,ie=ie+Math.imul(ge,xt)|0,ie=ie+Math.imul(Re,tt)|0,Se=Se+Math.imul(Re,xt)|0,me=me+Math.imul(Ae,xe)|0,ie=ie+Math.imul(Ae,ke)|0,ie=ie+Math.imul(Fe,xe)|0,Se=Se+Math.imul(Fe,ke)|0;var Xr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Xr>>>26)|0,Xr&=67108863,me=Math.imul(Gt,Br),ie=Math.imul(Gt,Vr),ie=ie+Math.imul(Nt,Br)|0,Se=Math.imul(Nt,Vr),me=me+Math.imul(Zt,Ge)|0,ie=ie+Math.imul(Zt,Je)|0,ie=ie+Math.imul(st,Ge)|0,Se=Se+Math.imul(st,Je)|0,me=me+Math.imul(Ze,tt)|0,ie=ie+Math.imul(Ze,xt)|0,ie=ie+Math.imul(ut,tt)|0,Se=Se+Math.imul(ut,xt)|0,me=me+Math.imul(ge,xe)|0,ie=ie+Math.imul(ge,ke)|0,ie=ie+Math.imul(Re,xe)|0,Se=Se+Math.imul(Re,ke)|0,me=me+Math.imul(Ae,ir)|0,ie=ie+Math.imul(Ae,ar)|0,ie=ie+Math.imul(Fe,ir)|0,Se=Se+Math.imul(Fe,ar)|0;var ri=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ri>>>26)|0,ri&=67108863,me=Math.imul(sr,Br),ie=Math.imul(sr,Vr),ie=ie+Math.imul(wr,Br)|0,Se=Math.imul(wr,Vr),me=me+Math.imul(Gt,Ge)|0,ie=ie+Math.imul(Gt,Je)|0,ie=ie+Math.imul(Nt,Ge)|0,Se=Se+Math.imul(Nt,Je)|0,me=me+Math.imul(Zt,tt)|0,ie=ie+Math.imul(Zt,xt)|0,ie=ie+Math.imul(st,tt)|0,Se=Se+Math.imul(st,xt)|0,me=me+Math.imul(Ze,xe)|0,ie=ie+Math.imul(Ze,ke)|0,ie=ie+Math.imul(ut,xe)|0,Se=Se+Math.imul(ut,ke)|0,me=me+Math.imul(ge,ir)|0,ie=ie+Math.imul(ge,ar)|0,ie=ie+Math.imul(Re,ir)|0,Se=Se+Math.imul(Re,ar)|0,me=me+Math.imul(Ae,ii)|0,ie=ie+Math.imul(Ae,pi)|0,ie=ie+Math.imul(Fe,ii)|0,Se=Se+Math.imul(Fe,pi)|0;var Qr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Qr>>>26)|0,Qr&=67108863,me=Math.imul($e,Br),ie=Math.imul($e,Vr),ie=ie+Math.imul(St,Br)|0,Se=Math.imul(St,Vr),me=me+Math.imul(sr,Ge)|0,ie=ie+Math.imul(sr,Je)|0,ie=ie+Math.imul(wr,Ge)|0,Se=Se+Math.imul(wr,Je)|0,me=me+Math.imul(Gt,tt)|0,ie=ie+Math.imul(Gt,xt)|0,ie=ie+Math.imul(Nt,tt)|0,Se=Se+Math.imul(Nt,xt)|0,me=me+Math.imul(Zt,xe)|0,ie=ie+Math.imul(Zt,ke)|0,ie=ie+Math.imul(st,xe)|0,Se=Se+Math.imul(st,ke)|0,me=me+Math.imul(Ze,ir)|0,ie=ie+Math.imul(Ze,ar)|0,ie=ie+Math.imul(ut,ir)|0,Se=Se+Math.imul(ut,ar)|0,me=me+Math.imul(ge,ii)|0,ie=ie+Math.imul(ge,pi)|0,ie=ie+Math.imul(Re,ii)|0,Se=Se+Math.imul(Re,pi)|0,me=me+Math.imul(Ae,di)|0,ie=ie+Math.imul(Ae,ji)|0,ie=ie+Math.imul(Fe,di)|0,Se=Se+Math.imul(Fe,ji)|0;var Oi=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Oi>>>26)|0,Oi&=67108863,me=Math.imul(Vt,Br),ie=Math.imul(Vt,Vr),ie=ie+Math.imul(_t,Br)|0,Se=Math.imul(_t,Vr),me=me+Math.imul($e,Ge)|0,ie=ie+Math.imul($e,Je)|0,ie=ie+Math.imul(St,Ge)|0,Se=Se+Math.imul(St,Je)|0,me=me+Math.imul(sr,tt)|0,ie=ie+Math.imul(sr,xt)|0,ie=ie+Math.imul(wr,tt)|0,Se=Se+Math.imul(wr,xt)|0,me=me+Math.imul(Gt,xe)|0,ie=ie+Math.imul(Gt,ke)|0,ie=ie+Math.imul(Nt,xe)|0,Se=Se+Math.imul(Nt,ke)|0,me=me+Math.imul(Zt,ir)|0,ie=ie+Math.imul(Zt,ar)|0,ie=ie+Math.imul(st,ir)|0,Se=Se+Math.imul(st,ar)|0,me=me+Math.imul(Ze,ii)|0,ie=ie+Math.imul(Ze,pi)|0,ie=ie+Math.imul(ut,ii)|0,Se=Se+Math.imul(ut,pi)|0,me=me+Math.imul(ge,di)|0,ie=ie+Math.imul(ge,ji)|0,ie=ie+Math.imul(Re,di)|0,Se=Se+Math.imul(Re,ji)|0,me=me+Math.imul(Ae,wi)|0,ie=ie+Math.imul(Ae,On)|0,ie=ie+Math.imul(Fe,wi)|0,Se=Se+Math.imul(Fe,On)|0;var $i=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+($i>>>26)|0,$i&=67108863,me=Math.imul(mt,Br),ie=Math.imul(mt,Vr),ie=ie+Math.imul(er,Br)|0,Se=Math.imul(er,Vr),me=me+Math.imul(Vt,Ge)|0,ie=ie+Math.imul(Vt,Je)|0,ie=ie+Math.imul(_t,Ge)|0,Se=Se+Math.imul(_t,Je)|0,me=me+Math.imul($e,tt)|0,ie=ie+Math.imul($e,xt)|0,ie=ie+Math.imul(St,tt)|0,Se=Se+Math.imul(St,xt)|0,me=me+Math.imul(sr,xe)|0,ie=ie+Math.imul(sr,ke)|0,ie=ie+Math.imul(wr,xe)|0,Se=Se+Math.imul(wr,ke)|0,me=me+Math.imul(Gt,ir)|0,ie=ie+Math.imul(Gt,ar)|0,ie=ie+Math.imul(Nt,ir)|0,Se=Se+Math.imul(Nt,ar)|0,me=me+Math.imul(Zt,ii)|0,ie=ie+Math.imul(Zt,pi)|0,ie=ie+Math.imul(st,ii)|0,Se=Se+Math.imul(st,pi)|0,me=me+Math.imul(Ze,di)|0,ie=ie+Math.imul(Ze,ji)|0,ie=ie+Math.imul(ut,di)|0,Se=Se+Math.imul(ut,ji)|0,me=me+Math.imul(ge,wi)|0,ie=ie+Math.imul(ge,On)|0,ie=ie+Math.imul(Re,wi)|0,Se=Se+Math.imul(Re,On)|0,me=me+Math.imul(Ae,Fn)|0,ie=ie+Math.imul(Ae,ra)|0,ie=ie+Math.imul(Fe,Fn)|0,Se=Se+Math.imul(Fe,ra)|0;var tn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(tn>>>26)|0,tn&=67108863,me=Math.imul(Tr,Br),ie=Math.imul(Tr,Vr),ie=ie+Math.imul(Lr,Br)|0,Se=Math.imul(Lr,Vr),me=me+Math.imul(mt,Ge)|0,ie=ie+Math.imul(mt,Je)|0,ie=ie+Math.imul(er,Ge)|0,Se=Se+Math.imul(er,Je)|0,me=me+Math.imul(Vt,tt)|0,ie=ie+Math.imul(Vt,xt)|0,ie=ie+Math.imul(_t,tt)|0,Se=Se+Math.imul(_t,xt)|0,me=me+Math.imul($e,xe)|0,ie=ie+Math.imul($e,ke)|0,ie=ie+Math.imul(St,xe)|0,Se=Se+Math.imul(St,ke)|0,me=me+Math.imul(sr,ir)|0,ie=ie+Math.imul(sr,ar)|0,ie=ie+Math.imul(wr,ir)|0,Se=Se+Math.imul(wr,ar)|0,me=me+Math.imul(Gt,ii)|0,ie=ie+Math.imul(Gt,pi)|0,ie=ie+Math.imul(Nt,ii)|0,Se=Se+Math.imul(Nt,pi)|0,me=me+Math.imul(Zt,di)|0,ie=ie+Math.imul(Zt,ji)|0,ie=ie+Math.imul(st,di)|0,Se=Se+Math.imul(st,ji)|0,me=me+Math.imul(Ze,wi)|0,ie=ie+Math.imul(Ze,On)|0,ie=ie+Math.imul(ut,wi)|0,Se=Se+Math.imul(ut,On)|0,me=me+Math.imul(ge,Fn)|0,ie=ie+Math.imul(ge,ra)|0,ie=ie+Math.imul(Re,Fn)|0,Se=Se+Math.imul(Re,ra)|0,me=me+Math.imul(Ae,Ut)|0,ie=ie+Math.imul(Ae,wt)|0,ie=ie+Math.imul(Fe,Ut)|0,Se=Se+Math.imul(Fe,wt)|0;var fn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(fn>>>26)|0,fn&=67108863,me=Math.imul(Tr,Ge),ie=Math.imul(Tr,Je),ie=ie+Math.imul(Lr,Ge)|0,Se=Math.imul(Lr,Je),me=me+Math.imul(mt,tt)|0,ie=ie+Math.imul(mt,xt)|0,ie=ie+Math.imul(er,tt)|0,Se=Se+Math.imul(er,xt)|0,me=me+Math.imul(Vt,xe)|0,ie=ie+Math.imul(Vt,ke)|0,ie=ie+Math.imul(_t,xe)|0,Se=Se+Math.imul(_t,ke)|0,me=me+Math.imul($e,ir)|0,ie=ie+Math.imul($e,ar)|0,ie=ie+Math.imul(St,ir)|0,Se=Se+Math.imul(St,ar)|0,me=me+Math.imul(sr,ii)|0,ie=ie+Math.imul(sr,pi)|0,ie=ie+Math.imul(wr,ii)|0,Se=Se+Math.imul(wr,pi)|0,me=me+Math.imul(Gt,di)|0,ie=ie+Math.imul(Gt,ji)|0,ie=ie+Math.imul(Nt,di)|0,Se=Se+Math.imul(Nt,ji)|0,me=me+Math.imul(Zt,wi)|0,ie=ie+Math.imul(Zt,On)|0,ie=ie+Math.imul(st,wi)|0,Se=Se+Math.imul(st,On)|0,me=me+Math.imul(Ze,Fn)|0,ie=ie+Math.imul(Ze,ra)|0,ie=ie+Math.imul(ut,Fn)|0,Se=Se+Math.imul(ut,ra)|0,me=me+Math.imul(ge,Ut)|0,ie=ie+Math.imul(ge,wt)|0,ie=ie+Math.imul(Re,Ut)|0,Se=Se+Math.imul(Re,wt)|0;var yn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(yn>>>26)|0,yn&=67108863,me=Math.imul(Tr,tt),ie=Math.imul(Tr,xt),ie=ie+Math.imul(Lr,tt)|0,Se=Math.imul(Lr,xt),me=me+Math.imul(mt,xe)|0,ie=ie+Math.imul(mt,ke)|0,ie=ie+Math.imul(er,xe)|0,Se=Se+Math.imul(er,ke)|0,me=me+Math.imul(Vt,ir)|0,ie=ie+Math.imul(Vt,ar)|0,ie=ie+Math.imul(_t,ir)|0,Se=Se+Math.imul(_t,ar)|0,me=me+Math.imul($e,ii)|0,ie=ie+Math.imul($e,pi)|0,ie=ie+Math.imul(St,ii)|0,Se=Se+Math.imul(St,pi)|0,me=me+Math.imul(sr,di)|0,ie=ie+Math.imul(sr,ji)|0,ie=ie+Math.imul(wr,di)|0,Se=Se+Math.imul(wr,ji)|0,me=me+Math.imul(Gt,wi)|0,ie=ie+Math.imul(Gt,On)|0,ie=ie+Math.imul(Nt,wi)|0,Se=Se+Math.imul(Nt,On)|0,me=me+Math.imul(Zt,Fn)|0,ie=ie+Math.imul(Zt,ra)|0,ie=ie+Math.imul(st,Fn)|0,Se=Se+Math.imul(st,ra)|0,me=me+Math.imul(Ze,Ut)|0,ie=ie+Math.imul(Ze,wt)|0,ie=ie+Math.imul(ut,Ut)|0,Se=Se+Math.imul(ut,wt)|0;var Sn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Sn>>>26)|0,Sn&=67108863,me=Math.imul(Tr,xe),ie=Math.imul(Tr,ke),ie=ie+Math.imul(Lr,xe)|0,Se=Math.imul(Lr,ke),me=me+Math.imul(mt,ir)|0,ie=ie+Math.imul(mt,ar)|0,ie=ie+Math.imul(er,ir)|0,Se=Se+Math.imul(er,ar)|0,me=me+Math.imul(Vt,ii)|0,ie=ie+Math.imul(Vt,pi)|0,ie=ie+Math.imul(_t,ii)|0,Se=Se+Math.imul(_t,pi)|0,me=me+Math.imul($e,di)|0,ie=ie+Math.imul($e,ji)|0,ie=ie+Math.imul(St,di)|0,Se=Se+Math.imul(St,ji)|0,me=me+Math.imul(sr,wi)|0,ie=ie+Math.imul(sr,On)|0,ie=ie+Math.imul(wr,wi)|0,Se=Se+Math.imul(wr,On)|0,me=me+Math.imul(Gt,Fn)|0,ie=ie+Math.imul(Gt,ra)|0,ie=ie+Math.imul(Nt,Fn)|0,Se=Se+Math.imul(Nt,ra)|0,me=me+Math.imul(Zt,Ut)|0,ie=ie+Math.imul(Zt,wt)|0,ie=ie+Math.imul(st,Ut)|0,Se=Se+Math.imul(st,wt)|0;var Ba=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Ba>>>26)|0,Ba&=67108863,me=Math.imul(Tr,ir),ie=Math.imul(Tr,ar),ie=ie+Math.imul(Lr,ir)|0,Se=Math.imul(Lr,ar),me=me+Math.imul(mt,ii)|0,ie=ie+Math.imul(mt,pi)|0,ie=ie+Math.imul(er,ii)|0,Se=Se+Math.imul(er,pi)|0,me=me+Math.imul(Vt,di)|0,ie=ie+Math.imul(Vt,ji)|0,ie=ie+Math.imul(_t,di)|0,Se=Se+Math.imul(_t,ji)|0,me=me+Math.imul($e,wi)|0,ie=ie+Math.imul($e,On)|0,ie=ie+Math.imul(St,wi)|0,Se=Se+Math.imul(St,On)|0,me=me+Math.imul(sr,Fn)|0,ie=ie+Math.imul(sr,ra)|0,ie=ie+Math.imul(wr,Fn)|0,Se=Se+Math.imul(wr,ra)|0,me=me+Math.imul(Gt,Ut)|0,ie=ie+Math.imul(Gt,wt)|0,ie=ie+Math.imul(Nt,Ut)|0,Se=Se+Math.imul(Nt,wt)|0;var ua=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ua>>>26)|0,ua&=67108863,me=Math.imul(Tr,ii),ie=Math.imul(Tr,pi),ie=ie+Math.imul(Lr,ii)|0,Se=Math.imul(Lr,pi),me=me+Math.imul(mt,di)|0,ie=ie+Math.imul(mt,ji)|0,ie=ie+Math.imul(er,di)|0,Se=Se+Math.imul(er,ji)|0,me=me+Math.imul(Vt,wi)|0,ie=ie+Math.imul(Vt,On)|0,ie=ie+Math.imul(_t,wi)|0,Se=Se+Math.imul(_t,On)|0,me=me+Math.imul($e,Fn)|0,ie=ie+Math.imul($e,ra)|0,ie=ie+Math.imul(St,Fn)|0,Se=Se+Math.imul(St,ra)|0,me=me+Math.imul(sr,Ut)|0,ie=ie+Math.imul(sr,wt)|0,ie=ie+Math.imul(wr,Ut)|0,Se=Se+Math.imul(wr,wt)|0;var ma=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ma>>>26)|0,ma&=67108863,me=Math.imul(Tr,di),ie=Math.imul(Tr,ji),ie=ie+Math.imul(Lr,di)|0,Se=Math.imul(Lr,ji),me=me+Math.imul(mt,wi)|0,ie=ie+Math.imul(mt,On)|0,ie=ie+Math.imul(er,wi)|0,Se=Se+Math.imul(er,On)|0,me=me+Math.imul(Vt,Fn)|0,ie=ie+Math.imul(Vt,ra)|0,ie=ie+Math.imul(_t,Fn)|0,Se=Se+Math.imul(_t,ra)|0,me=me+Math.imul($e,Ut)|0,ie=ie+Math.imul($e,wt)|0,ie=ie+Math.imul(St,Ut)|0,Se=Se+Math.imul(St,wt)|0;var Wa=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Wa>>>26)|0,Wa&=67108863,me=Math.imul(Tr,wi),ie=Math.imul(Tr,On),ie=ie+Math.imul(Lr,wi)|0,Se=Math.imul(Lr,On),me=me+Math.imul(mt,Fn)|0,ie=ie+Math.imul(mt,ra)|0,ie=ie+Math.imul(er,Fn)|0,Se=Se+Math.imul(er,ra)|0,me=me+Math.imul(Vt,Ut)|0,ie=ie+Math.imul(Vt,wt)|0,ie=ie+Math.imul(_t,Ut)|0,Se=Se+Math.imul(_t,wt)|0;var Fa=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Fa>>>26)|0,Fa&=67108863,me=Math.imul(Tr,Fn),ie=Math.imul(Tr,ra),ie=ie+Math.imul(Lr,Fn)|0,Se=Math.imul(Lr,ra),me=me+Math.imul(mt,Ut)|0,ie=ie+Math.imul(mt,wt)|0,ie=ie+Math.imul(er,Ut)|0,Se=Se+Math.imul(er,wt)|0;var Wo=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Wo>>>26)|0,Wo&=67108863,me=Math.imul(Tr,Ut),ie=Math.imul(Tr,wt),ie=ie+Math.imul(Lr,Ut)|0,Se=Math.imul(Lr,wt);var da=(Ce+me|0)+((ie&8191)<<13)|0;return Ce=(Se+(ie>>>13)|0)+(da>>>26)|0,da&=67108863,Ee[0]=rr,Ee[1]=nr,Ee[2]=Er,Ee[3]=Xr,Ee[4]=ri,Ee[5]=Qr,Ee[6]=Oi,Ee[7]=$i,Ee[8]=tn,Ee[9]=fn,Ee[10]=yn,Ee[11]=Sn,Ee[12]=Ba,Ee[13]=ua,Ee[14]=ma,Ee[15]=Wa,Ee[16]=Fa,Ee[17]=Wo,Ee[18]=da,Ce!==0&&(Ee[19]=Ce,re.length++),re};Math.imul||(L=S);function x(H,N,j){j.negative=N.negative^H.negative,j.length=H.length+N.length;for(var re=0,oe=0,_e=0;_e<j.length-1;_e++){var Ee=oe;oe=0;for(var Ce=re&67108863,me=Math.min(_e,N.length-1),ie=Math.max(0,_e-H.length+1);ie<=me;ie++){var Se=_e-ie,Le=H.words[Se]|0,Ae=N.words[ie]|0,Fe=Le*Ae,Pe=Fe&67108863;Ee=Ee+(Fe/67108864|0)|0,Pe=Pe+Ce|0,Ce=Pe&67108863,Ee=Ee+(Pe>>>26)|0,oe+=Ee>>>26,Ee&=67108863}j.words[_e]=Ce,re=Ee,Ee=oe}return re!==0?j.words[_e]=re:j.length--,j.strip()}function C(H,N,j){var re=new M;return re.mulp(H,N,j)}f.prototype.mulTo=function(N,j){var re,oe=this.length+N.length;return this.length===10&&N.length===10?re=L(this,N,j):oe<63?re=S(this,N,j):oe<1024?re=x(this,N,j):re=C(this,N,j),re};function M(H,N){this.x=H,this.y=N}M.prototype.makeRBT=function(N){for(var j=new Array(N),re=f.prototype._countBits(N)-1,oe=0;oe<N;oe++)j[oe]=this.revBin(oe,re,N);return j},M.prototype.revBin=function(N,j,re){if(N===0||N===re-1)return N;for(var oe=0,_e=0;_e<j;_e++)oe|=(N&1)<<j-_e-1,N>>=1;return oe},M.prototype.permute=function(N,j,re,oe,_e,Ee){for(var Ce=0;Ce<Ee;Ce++)oe[Ce]=j[N[Ce]],_e[Ce]=re[N[Ce]]},M.prototype.transform=function(N,j,re,oe,_e,Ee){this.permute(Ee,N,j,re,oe,_e);for(var Ce=1;Ce<_e;Ce<<=1)for(var me=Ce<<1,ie=Math.cos(2*Math.PI/me),Se=Math.sin(2*Math.PI/me),Le=0;Le<_e;Le+=me)for(var Ae=ie,Fe=Se,Pe=0;Pe<Ce;Pe++){var ge=re[Le+Pe],Re=oe[Le+Pe],ce=re[Le+Pe+Ce],Ze=oe[Le+Pe+Ce],ut=Ae*ce-Fe*Ze;Ze=Ae*Ze+Fe*ce,ce=ut,re[Le+Pe]=ge+ce,oe[Le+Pe]=Re+Ze,re[Le+Pe+Ce]=ge-ce,oe[Le+Pe+Ce]=Re-Ze,Pe!==me&&(ut=ie*Ae-Se*Fe,Fe=ie*Fe+Se*Ae,Ae=ut)}},M.prototype.guessLen13b=function(N,j){var re=Math.max(j,N)|1,oe=re&1,_e=0;for(re=re/2|0;re;re=re>>>1)_e++;return 1<<_e+1+oe},M.prototype.conjugate=function(N,j,re){if(!(re<=1))for(var oe=0;oe<re/2;oe++){var _e=N[oe];N[oe]=N[re-oe-1],N[re-oe-1]=_e,_e=j[oe],j[oe]=-j[re-oe-1],j[re-oe-1]=-_e}},M.prototype.normalize13b=function(N,j){for(var re=0,oe=0;oe<j/2;oe++){var _e=Math.round(N[2*oe+1]/j)*8192+Math.round(N[2*oe]/j)+re;N[oe]=_e&67108863,_e<67108864?re=0:re=_e/67108864|0}return N},M.prototype.convert13b=function(N,j,re,oe){for(var _e=0,Ee=0;Ee<j;Ee++)_e=_e+(N[Ee]|0),re[2*Ee]=_e&8191,_e=_e>>>13,re[2*Ee+1]=_e&8191,_e=_e>>>13;for(Ee=2*j;Ee<oe;++Ee)re[Ee]=0;u(_e===0),u((_e&-8192)===0)},M.prototype.stub=function(N){for(var j=new Array(N),re=0;re<N;re++)j[re]=0;return j},M.prototype.mulp=function(N,j,re){var oe=2*this.guessLen13b(N.length,j.length),_e=this.makeRBT(oe),Ee=this.stub(oe),Ce=new Array(oe),me=new Array(oe),ie=new Array(oe),Se=new Array(oe),Le=new Array(oe),Ae=new Array(oe),Fe=re.words;Fe.length=oe,this.convert13b(N.words,N.length,Ce,oe),this.convert13b(j.words,j.length,Se,oe),this.transform(Ce,Ee,me,ie,oe,_e),this.transform(Se,Ee,Le,Ae,oe,_e);for(var Pe=0;Pe<oe;Pe++){var ge=me[Pe]*Le[Pe]-ie[Pe]*Ae[Pe];ie[Pe]=me[Pe]*Ae[Pe]+ie[Pe]*Le[Pe],me[Pe]=ge}return this.conjugate(me,ie,oe),this.transform(me,ie,Fe,Ee,oe,_e),this.conjugate(Fe,Ee,oe),this.normalize13b(Fe,oe),re.negative=N.negative^j.negative,re.length=N.length+j.length,re.strip()},f.prototype.mul=function(N){var j=new f(null);return j.words=new Array(this.length+N.length),this.mulTo(N,j)},f.prototype.mulf=function(N){var j=new f(null);return j.words=new Array(this.length+N.length),C(this,N,j)},f.prototype.imul=function(N){return this.clone().mulTo(N,this)},f.prototype.imuln=function(N){u(typeof N==\"number\"),u(N<67108864);for(var j=0,re=0;re<this.length;re++){var oe=(this.words[re]|0)*N,_e=(oe&67108863)+(j&67108863);j>>=26,j+=oe/67108864|0,j+=_e>>>26,this.words[re]=_e&67108863}return j!==0&&(this.words[re]=j,this.length++),this},f.prototype.muln=function(N){return this.clone().imuln(N)},f.prototype.sqr=function(){return this.mul(this)},f.prototype.isqr=function(){return this.imul(this.clone())},f.prototype.pow=function(N){var j=E(N);if(j.length===0)return new f(1);for(var re=this,oe=0;oe<j.length&&j[oe]===0;oe++,re=re.sqr());if(++oe<j.length)for(var _e=re.sqr();oe<j.length;oe++,_e=_e.sqr())j[oe]!==0&&(re=re.mul(_e));return re},f.prototype.iushln=function(N){u(typeof N==\"number\"&&N>=0);var j=N%26,re=(N-j)/26,oe=67108863>>>26-j<<26-j,_e;if(j!==0){var Ee=0;for(_e=0;_e<this.length;_e++){var Ce=this.words[_e]&oe,me=(this.words[_e]|0)-Ce<<j;this.words[_e]=me|Ee,Ee=Ce>>>26-j}Ee&&(this.words[_e]=Ee,this.length++)}if(re!==0){for(_e=this.length-1;_e>=0;_e--)this.words[_e+re]=this.words[_e];for(_e=0;_e<re;_e++)this.words[_e]=0;this.length+=re}return this.strip()},f.prototype.ishln=function(N){return u(this.negative===0),this.iushln(N)},f.prototype.iushrn=function(N,j,re){u(typeof N==\"number\"&&N>=0);var oe;j?oe=(j-j%26)/26:oe=0;var _e=N%26,Ee=Math.min((N-_e)/26,this.length),Ce=67108863^67108863>>>_e<<_e,me=re;if(oe-=Ee,oe=Math.max(0,oe),me){for(var ie=0;ie<Ee;ie++)me.words[ie]=this.words[ie];me.length=Ee}if(Ee!==0)if(this.length>Ee)for(this.length-=Ee,ie=0;ie<this.length;ie++)this.words[ie]=this.words[ie+Ee];else this.words[0]=0,this.length=1;var Se=0;for(ie=this.length-1;ie>=0&&(Se!==0||ie>=oe);ie--){var Le=this.words[ie]|0;this.words[ie]=Se<<26-_e|Le>>>_e,Se=Le&Ce}return me&&Se!==0&&(me.words[me.length++]=Se),this.length===0&&(this.words[0]=0,this.length=1),this.strip()},f.prototype.ishrn=function(N,j,re){return u(this.negative===0),this.iushrn(N,j,re)},f.prototype.shln=function(N){return this.clone().ishln(N)},f.prototype.ushln=function(N){return this.clone().iushln(N)},f.prototype.shrn=function(N){return this.clone().ishrn(N)},f.prototype.ushrn=function(N){return this.clone().iushrn(N)},f.prototype.testn=function(N){u(typeof N==\"number\"&&N>=0);var j=N%26,re=(N-j)/26,oe=1<<j;if(this.length<=re)return!1;var _e=this.words[re];return!!(_e&oe)},f.prototype.imaskn=function(N){u(typeof N==\"number\"&&N>=0);var j=N%26,re=(N-j)/26;if(u(this.negative===0,\"imaskn works only with positive numbers\"),this.length<=re)return this;if(j!==0&&re++,this.length=Math.min(re,this.length),j!==0){var oe=67108863^67108863>>>j<<j;this.words[this.length-1]&=oe}return this.strip()},f.prototype.maskn=function(N){return this.clone().imaskn(N)},f.prototype.iaddn=function(N){return u(typeof N==\"number\"),u(N<67108864),N<0?this.isubn(-N):this.negative!==0?this.length===1&&(this.words[0]|0)<N?(this.words[0]=N-(this.words[0]|0),this.negative=0,this):(this.negative=0,this.isubn(N),this.negative=1,this):this._iaddn(N)},f.prototype._iaddn=function(N){this.words[0]+=N;for(var j=0;j<this.length&&this.words[j]>=67108864;j++)this.words[j]-=67108864,j===this.length-1?this.words[j+1]=1:this.words[j+1]++;return this.length=Math.max(this.length,j+1),this},f.prototype.isubn=function(N){if(u(typeof N==\"number\"),u(N<67108864),N<0)return this.iaddn(-N);if(this.negative!==0)return this.negative=0,this.iaddn(N),this.negative=1,this;if(this.words[0]-=N,this.length===1&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var j=0;j<this.length&&this.words[j]<0;j++)this.words[j]+=67108864,this.words[j+1]-=1;return this.strip()},f.prototype.addn=function(N){return this.clone().iaddn(N)},f.prototype.subn=function(N){return this.clone().isubn(N)},f.prototype.iabs=function(){return this.negative=0,this},f.prototype.abs=function(){return this.clone().iabs()},f.prototype._ishlnsubmul=function(N,j,re){var oe=N.length+re,_e;this._expand(oe);var Ee,Ce=0;for(_e=0;_e<N.length;_e++){Ee=(this.words[_e+re]|0)+Ce;var me=(N.words[_e]|0)*j;Ee-=me&67108863,Ce=(Ee>>26)-(me/67108864|0),this.words[_e+re]=Ee&67108863}for(;_e<this.length-re;_e++)Ee=(this.words[_e+re]|0)+Ce,Ce=Ee>>26,this.words[_e+re]=Ee&67108863;if(Ce===0)return this.strip();for(u(Ce===-1),Ce=0,_e=0;_e<this.length;_e++)Ee=-(this.words[_e]|0)+Ce,Ce=Ee>>26,this.words[_e]=Ee&67108863;return this.negative=1,this.strip()},f.prototype._wordDiv=function(N,j){var re=this.length-N.length,oe=this.clone(),_e=N,Ee=_e.words[_e.length-1]|0,Ce=this._countBits(Ee);re=26-Ce,re!==0&&(_e=_e.ushln(re),oe.iushln(re),Ee=_e.words[_e.length-1]|0);var me=oe.length-_e.length,ie;if(j!==\"mod\"){ie=new f(null),ie.length=me+1,ie.words=new Array(ie.length);for(var Se=0;Se<ie.length;Se++)ie.words[Se]=0}var Le=oe.clone()._ishlnsubmul(_e,1,me);Le.negative===0&&(oe=Le,ie&&(ie.words[me]=1));for(var Ae=me-1;Ae>=0;Ae--){var Fe=(oe.words[_e.length+Ae]|0)*67108864+(oe.words[_e.length+Ae-1]|0);for(Fe=Math.min(Fe/Ee|0,67108863),oe._ishlnsubmul(_e,Fe,Ae);oe.negative!==0;)Fe--,oe.negative=0,oe._ishlnsubmul(_e,1,Ae),oe.isZero()||(oe.negative^=1);ie&&(ie.words[Ae]=Fe)}return ie&&ie.strip(),oe.strip(),j!==\"div\"&&re!==0&&oe.iushrn(re),{div:ie||null,mod:oe}},f.prototype.divmod=function(N,j,re){if(u(!N.isZero()),this.isZero())return{div:new f(0),mod:new f(0)};var oe,_e,Ee;return this.negative!==0&&N.negative===0?(Ee=this.neg().divmod(N,j),j!==\"mod\"&&(oe=Ee.div.neg()),j!==\"div\"&&(_e=Ee.mod.neg(),re&&_e.negative!==0&&_e.iadd(N)),{div:oe,mod:_e}):this.negative===0&&N.negative!==0?(Ee=this.divmod(N.neg(),j),j!==\"mod\"&&(oe=Ee.div.neg()),{div:oe,mod:Ee.mod}):(this.negative&N.negative)!==0?(Ee=this.neg().divmod(N.neg(),j),j!==\"div\"&&(_e=Ee.mod.neg(),re&&_e.negative!==0&&_e.isub(N)),{div:Ee.div,mod:_e}):N.length>this.length||this.cmp(N)<0?{div:new f(0),mod:this}:N.length===1?j===\"div\"?{div:this.divn(N.words[0]),mod:null}:j===\"mod\"?{div:null,mod:new f(this.modn(N.words[0]))}:{div:this.divn(N.words[0]),mod:new f(this.modn(N.words[0]))}:this._wordDiv(N,j)},f.prototype.div=function(N){return this.divmod(N,\"div\",!1).div},f.prototype.mod=function(N){return this.divmod(N,\"mod\",!1).mod},f.prototype.umod=function(N){return this.divmod(N,\"mod\",!0).mod},f.prototype.divRound=function(N){var j=this.divmod(N);if(j.mod.isZero())return j.div;var re=j.div.negative!==0?j.mod.isub(N):j.mod,oe=N.ushrn(1),_e=N.andln(1),Ee=re.cmp(oe);return Ee<0||_e===1&&Ee===0?j.div:j.div.negative!==0?j.div.isubn(1):j.div.iaddn(1)},f.prototype.modn=function(N){u(N<=67108863);for(var j=(1<<26)%N,re=0,oe=this.length-1;oe>=0;oe--)re=(j*re+(this.words[oe]|0))%N;return re},f.prototype.idivn=function(N){u(N<=67108863);for(var j=0,re=this.length-1;re>=0;re--){var oe=(this.words[re]|0)+j*67108864;this.words[re]=oe/N|0,j=oe%N}return this.strip()},f.prototype.divn=function(N){return this.clone().idivn(N)},f.prototype.egcd=function(N){u(N.negative===0),u(!N.isZero());var j=this,re=N.clone();j.negative!==0?j=j.umod(N):j=j.clone();for(var oe=new f(1),_e=new f(0),Ee=new f(0),Ce=new f(1),me=0;j.isEven()&&re.isEven();)j.iushrn(1),re.iushrn(1),++me;for(var ie=re.clone(),Se=j.clone();!j.isZero();){for(var Le=0,Ae=1;(j.words[0]&Ae)===0&&Le<26;++Le,Ae<<=1);if(Le>0)for(j.iushrn(Le);Le-- >0;)(oe.isOdd()||_e.isOdd())&&(oe.iadd(ie),_e.isub(Se)),oe.iushrn(1),_e.iushrn(1);for(var Fe=0,Pe=1;(re.words[0]&Pe)===0&&Fe<26;++Fe,Pe<<=1);if(Fe>0)for(re.iushrn(Fe);Fe-- >0;)(Ee.isOdd()||Ce.isOdd())&&(Ee.iadd(ie),Ce.isub(Se)),Ee.iushrn(1),Ce.iushrn(1);j.cmp(re)>=0?(j.isub(re),oe.isub(Ee),_e.isub(Ce)):(re.isub(j),Ee.isub(oe),Ce.isub(_e))}return{a:Ee,b:Ce,gcd:re.iushln(me)}},f.prototype._invmp=function(N){u(N.negative===0),u(!N.isZero());var j=this,re=N.clone();j.negative!==0?j=j.umod(N):j=j.clone();for(var oe=new f(1),_e=new f(0),Ee=re.clone();j.cmpn(1)>0&&re.cmpn(1)>0;){for(var Ce=0,me=1;(j.words[0]&me)===0&&Ce<26;++Ce,me<<=1);if(Ce>0)for(j.iushrn(Ce);Ce-- >0;)oe.isOdd()&&oe.iadd(Ee),oe.iushrn(1);for(var ie=0,Se=1;(re.words[0]&Se)===0&&ie<26;++ie,Se<<=1);if(ie>0)for(re.iushrn(ie);ie-- >0;)_e.isOdd()&&_e.iadd(Ee),_e.iushrn(1);j.cmp(re)>=0?(j.isub(re),oe.isub(_e)):(re.isub(j),_e.isub(oe))}var Le;return j.cmpn(1)===0?Le=oe:Le=_e,Le.cmpn(0)<0&&Le.iadd(N),Le},f.prototype.gcd=function(N){if(this.isZero())return N.abs();if(N.isZero())return this.abs();var j=this.clone(),re=N.clone();j.negative=0,re.negative=0;for(var oe=0;j.isEven()&&re.isEven();oe++)j.iushrn(1),re.iushrn(1);do{for(;j.isEven();)j.iushrn(1);for(;re.isEven();)re.iushrn(1);var _e=j.cmp(re);if(_e<0){var Ee=j;j=re,re=Ee}else if(_e===0||re.cmpn(1)===0)break;j.isub(re)}while(!0);return re.iushln(oe)},f.prototype.invm=function(N){return this.egcd(N).a.umod(N)},f.prototype.isEven=function(){return(this.words[0]&1)===0},f.prototype.isOdd=function(){return(this.words[0]&1)===1},f.prototype.andln=function(N){return this.words[0]&N},f.prototype.bincn=function(N){u(typeof N==\"number\");var j=N%26,re=(N-j)/26,oe=1<<j;if(this.length<=re)return this._expand(re+1),this.words[re]|=oe,this;for(var _e=oe,Ee=re;_e!==0&&Ee<this.length;Ee++){var Ce=this.words[Ee]|0;Ce+=_e,_e=Ce>>>26,Ce&=67108863,this.words[Ee]=Ce}return _e!==0&&(this.words[Ee]=_e,this.length++),this},f.prototype.isZero=function(){return this.length===1&&this.words[0]===0},f.prototype.cmpn=function(N){var j=N<0;if(this.negative!==0&&!j)return-1;if(this.negative===0&&j)return 1;this.strip();var re;if(this.length>1)re=1;else{j&&(N=-N),u(N<=67108863,\"Number is too big\");var oe=this.words[0]|0;re=oe===N?0:oe<N?-1:1}return this.negative!==0?-re|0:re},f.prototype.cmp=function(N){if(this.negative!==0&&N.negative===0)return-1;if(this.negative===0&&N.negative!==0)return 1;var j=this.ucmp(N);return this.negative!==0?-j|0:j},f.prototype.ucmp=function(N){if(this.length>N.length)return 1;if(this.length<N.length)return-1;for(var j=0,re=this.length-1;re>=0;re--){var oe=this.words[re]|0,_e=N.words[re]|0;if(oe!==_e){oe<_e?j=-1:oe>_e&&(j=1);break}}return j},f.prototype.gtn=function(N){return this.cmpn(N)===1},f.prototype.gt=function(N){return this.cmp(N)===1},f.prototype.gten=function(N){return this.cmpn(N)>=0},f.prototype.gte=function(N){return this.cmp(N)>=0},f.prototype.ltn=function(N){return this.cmpn(N)===-1},f.prototype.lt=function(N){return this.cmp(N)===-1},f.prototype.lten=function(N){return this.cmpn(N)<=0},f.prototype.lte=function(N){return this.cmp(N)<=0},f.prototype.eqn=function(N){return this.cmpn(N)===0},f.prototype.eq=function(N){return this.cmp(N)===0},f.red=function(N){return new G(N)},f.prototype.toRed=function(N){return u(!this.red,\"Already a number in reduction context\"),u(this.negative===0,\"red works only with positives\"),N.convertTo(this)._forceRed(N)},f.prototype.fromRed=function(){return u(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},f.prototype._forceRed=function(N){return this.red=N,this},f.prototype.forceRed=function(N){return u(!this.red,\"Already a number in reduction context\"),this._forceRed(N)},f.prototype.redAdd=function(N){return u(this.red,\"redAdd works only with red numbers\"),this.red.add(this,N)},f.prototype.redIAdd=function(N){return u(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,N)},f.prototype.redSub=function(N){return u(this.red,\"redSub works only with red numbers\"),this.red.sub(this,N)},f.prototype.redISub=function(N){return u(this.red,\"redISub works only with red numbers\"),this.red.isub(this,N)},f.prototype.redShl=function(N){return u(this.red,\"redShl works only with red numbers\"),this.red.shl(this,N)},f.prototype.redMul=function(N){return u(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,N),this.red.mul(this,N)},f.prototype.redIMul=function(N){return u(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,N),this.red.imul(this,N)},f.prototype.redSqr=function(){return u(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},f.prototype.redISqr=function(){return u(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},f.prototype.redSqrt=function(){return u(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},f.prototype.redInvm=function(){return u(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},f.prototype.redNeg=function(){return u(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},f.prototype.redPow=function(N){return u(this.red&&!N.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,N)};var g={k256:null,p224:null,p192:null,p25519:null};function P(H,N){this.name=H,this.p=new f(N,16),this.n=this.p.bitLength(),this.k=new f(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}P.prototype._tmp=function(){var N=new f(null);return N.words=new Array(Math.ceil(this.n/13)),N},P.prototype.ireduce=function(N){var j=N,re;do this.split(j,this.tmp),j=this.imulK(j),j=j.iadd(this.tmp),re=j.bitLength();while(re>this.n);var oe=re<this.n?-1:j.ucmp(this.p);return oe===0?(j.words[0]=0,j.length=1):oe>0?j.isub(this.p):j.strip!==void 0?j.strip():j._strip(),j},P.prototype.split=function(N,j){N.iushrn(this.n,0,j)},P.prototype.imulK=function(N){return N.imul(this.k)};function T(){P.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}c(T,P),T.prototype.split=function(N,j){for(var re=4194303,oe=Math.min(N.length,9),_e=0;_e<oe;_e++)j.words[_e]=N.words[_e];if(j.length=oe,N.length<=9){N.words[0]=0,N.length=1;return}var Ee=N.words[9];for(j.words[j.length++]=Ee&re,_e=10;_e<N.length;_e++){var Ce=N.words[_e]|0;N.words[_e-10]=(Ce&re)<<4|Ee>>>22,Ee=Ce}Ee>>>=22,N.words[_e-10]=Ee,Ee===0&&N.length>10?N.length-=10:N.length-=9},T.prototype.imulK=function(N){N.words[N.length]=0,N.words[N.length+1]=0,N.length+=2;for(var j=0,re=0;re<N.length;re++){var oe=N.words[re]|0;j+=oe*977,N.words[re]=j&67108863,j=oe*64+(j/67108864|0)}return N.words[N.length-1]===0&&(N.length--,N.words[N.length-1]===0&&N.length--),N};function z(){P.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}c(z,P);function O(){P.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}c(O,P);function V(){P.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}c(V,P),V.prototype.imulK=function(N){for(var j=0,re=0;re<N.length;re++){var oe=(N.words[re]|0)*19+j,_e=oe&67108863;oe>>>=26,N.words[re]=_e,j=oe}return j!==0&&(N.words[N.length++]=j),N},f._prime=function(N){if(g[N])return g[N];var j;if(N===\"k256\")j=new T;else if(N===\"p224\")j=new z;else if(N===\"p192\")j=new O;else if(N===\"p25519\")j=new V;else throw new Error(\"Unknown prime \"+N);return g[N]=j,j};function G(H){if(typeof H==\"string\"){var N=f._prime(H);this.m=N.p,this.prime=N}else u(H.gtn(1),\"modulus must be greater than 1\"),this.m=H,this.prime=null}G.prototype._verify1=function(N){u(N.negative===0,\"red works only with positives\"),u(N.red,\"red works only with red numbers\")},G.prototype._verify2=function(N,j){u((N.negative|j.negative)===0,\"red works only with positives\"),u(N.red&&N.red===j.red,\"red works only with red numbers\")},G.prototype.imod=function(N){return this.prime?this.prime.ireduce(N)._forceRed(this):N.umod(this.m)._forceRed(this)},G.prototype.neg=function(N){return N.isZero()?N.clone():this.m.sub(N)._forceRed(this)},G.prototype.add=function(N,j){this._verify2(N,j);var re=N.add(j);return re.cmp(this.m)>=0&&re.isub(this.m),re._forceRed(this)},G.prototype.iadd=function(N,j){this._verify2(N,j);var re=N.iadd(j);return re.cmp(this.m)>=0&&re.isub(this.m),re},G.prototype.sub=function(N,j){this._verify2(N,j);var re=N.sub(j);return re.cmpn(0)<0&&re.iadd(this.m),re._forceRed(this)},G.prototype.isub=function(N,j){this._verify2(N,j);var re=N.isub(j);return re.cmpn(0)<0&&re.iadd(this.m),re},G.prototype.shl=function(N,j){return this._verify1(N),this.imod(N.ushln(j))},G.prototype.imul=function(N,j){return this._verify2(N,j),this.imod(N.imul(j))},G.prototype.mul=function(N,j){return this._verify2(N,j),this.imod(N.mul(j))},G.prototype.isqr=function(N){return this.imul(N,N.clone())},G.prototype.sqr=function(N){return this.mul(N,N)},G.prototype.sqrt=function(N){if(N.isZero())return N.clone();var j=this.m.andln(3);if(u(j%2===1),j===3){var re=this.m.add(new f(1)).iushrn(2);return this.pow(N,re)}for(var oe=this.m.subn(1),_e=0;!oe.isZero()&&oe.andln(1)===0;)_e++,oe.iushrn(1);u(!oe.isZero());var Ee=new f(1).toRed(this),Ce=Ee.redNeg(),me=this.m.subn(1).iushrn(1),ie=this.m.bitLength();for(ie=new f(2*ie*ie).toRed(this);this.pow(ie,me).cmp(Ce)!==0;)ie.redIAdd(Ce);for(var Se=this.pow(ie,oe),Le=this.pow(N,oe.addn(1).iushrn(1)),Ae=this.pow(N,oe),Fe=_e;Ae.cmp(Ee)!==0;){for(var Pe=Ae,ge=0;Pe.cmp(Ee)!==0;ge++)Pe=Pe.redSqr();u(ge<Fe);var Re=this.pow(Se,new f(1).iushln(Fe-ge-1));Le=Le.redMul(Re),Se=Re.redSqr(),Ae=Ae.redMul(Se),Fe=ge}return Le},G.prototype.invm=function(N){var j=N._invmp(this.m);return j.negative!==0?(j.negative=0,this.imod(j).redNeg()):this.imod(j)},G.prototype.pow=function(N,j){if(j.isZero())return new f(1).toRed(this);if(j.cmpn(1)===0)return N.clone();var re=4,oe=new Array(1<<re);oe[0]=new f(1).toRed(this),oe[1]=N;for(var _e=2;_e<oe.length;_e++)oe[_e]=this.mul(oe[_e-1],N);var Ee=oe[0],Ce=0,me=0,ie=j.bitLength()%26;for(ie===0&&(ie=26),_e=j.length-1;_e>=0;_e--){for(var Se=j.words[_e],Le=ie-1;Le>=0;Le--){var Ae=Se>>Le&1;if(Ee!==oe[0]&&(Ee=this.sqr(Ee)),Ae===0&&Ce===0){me=0;continue}Ce<<=1,Ce|=Ae,me++,!(me!==re&&(_e!==0||Le!==0))&&(Ee=this.mul(Ee,oe[Ce]),me=0,Ce=0)}ie=26}return Ee},G.prototype.convertTo=function(N){var j=N.umod(this.m);return j===N?j.clone():j},G.prototype.convertFrom=function(N){var j=N.clone();return j.red=null,j},f.mont=function(N){return new Z(N)};function Z(H){G.call(this,H),this.shift=this.m.bitLength(),this.shift%26!==0&&(this.shift+=26-this.shift%26),this.r=new f(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}c(Z,G),Z.prototype.convertTo=function(N){return this.imod(N.ushln(this.shift))},Z.prototype.convertFrom=function(N){var j=this.imod(N.mul(this.rinv));return j.red=null,j},Z.prototype.imul=function(N,j){if(N.isZero()||j.isZero())return N.words[0]=0,N.length=1,N;var re=N.imul(j),oe=re.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),_e=re.isub(oe).iushrn(this.shift),Ee=_e;return _e.cmp(this.m)>=0?Ee=_e.isub(this.m):_e.cmpn(0)<0&&(Ee=_e.iadd(this.m)),Ee._forceRed(this)},Z.prototype.mul=function(N,j){if(N.isZero()||j.isZero())return new f(0)._forceRed(this);var re=N.mul(j),oe=re.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),_e=re.isub(oe).iushrn(this.shift),Ee=_e;return _e.cmp(this.m)>=0?Ee=_e.isub(this.m):_e.cmpn(0)<0&&(Ee=_e.iadd(this.m)),Ee._forceRed(this)},Z.prototype.invm=function(N){var j=this.imod(N._invmp(this.m).mul(this.r2));return j._forceRed(this)}}(i,this)},6860:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]-l[0],o[1]=s[1]-l[1],o[2]=s[2]-l[2],o[3]=s[3]-l[3],o}},6864:function(i){i.exports=a;function a(){var o=new Float32Array(16);return o[0]=1,o[1]=0,o[2]=0,o[3]=0,o[4]=0,o[5]=1,o[6]=0,o[7]=0,o[8]=0,o[9]=0,o[10]=1,o[11]=0,o[12]=0,o[13]=0,o[14]=0,o[15]=1,o}},6867:function(i,a,o){\"use strict\";i.exports=p;var s=o(1888),l=o(855),u=o(7150);function c(k,E){for(var S=0;S<k;++S)if(!(E[S]<=E[S+k]))return!0;return!1}function f(k,E,S,L){for(var x=0,C=0,M=0,g=k.length;M<g;++M){var P=k[M];if(!c(E,P)){for(var T=0;T<2*E;++T)S[x++]=P[T];L[C++]=M}}return C}function h(k,E,S,L){var x=k.length,C=E.length;if(!(x<=0||C<=0)){var M=k[0].length>>>1;if(!(M<=0)){var g,P=s.mallocDouble(2*M*x),T=s.mallocInt32(x);if(x=f(k,M,P,T),x>0){if(M===1&&L)l.init(x),g=l.sweepComplete(M,S,0,x,P,T,0,x,P,T);else{var z=s.mallocDouble(2*M*C),O=s.mallocInt32(C);C=f(E,M,z,O),C>0&&(l.init(x+C),M===1?g=l.sweepBipartite(M,S,0,x,P,T,0,C,z,O):g=u(M,S,L,x,P,T,C,z,O),s.free(z),s.free(O))}s.free(P),s.free(T)}return g}}}var d;function v(k,E){d.push([k,E])}function _(k){return d=[],h(k,k,v,!0),d}function b(k,E){return d=[],h(k,E,v,!1),d}function p(k,E,S){switch(arguments.length){case 1:return _(k);case 2:return typeof E==\"function\"?h(k,k,E,!0):b(k,E);case 3:return h(k,E,S,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}}},6894:function(i){i.exports=a;function a(o,s,l,u){var c=l[1],f=l[2],h=s[1]-c,d=s[2]-f,v=Math.sin(u),_=Math.cos(u);return o[0]=s[0],o[1]=c+h*_-d*v,o[2]=f+h*v+d*_,o}},7004:function(i){\"use strict\";i.exports=a;function a(o){for(var s=o.length,l=o[o.length-1],u=s,c=s-2;c>=0;--c){var f=l,h=o[c];l=f+h;var d=l-f,v=h-d;v&&(o[--u]=l,l=v)}for(var _=0,c=u;c<s;++c){var f=o[c],h=l;l=f+h;var d=l-f,v=h-d;v&&(o[_++]=v)}return o[_++]=l,o.length=_,o}},7056:function(i){i.exports=a;function a(o,s){var l=s[0]-o[0],u=s[1]-o[1],c=s[2]-o[2];return Math.sqrt(l*l+u*u+c*c)}},7089:function(i){i.exports=a;function a(o,s,l){var u=Math.sin(l),c=Math.cos(l),f=s[0],h=s[1],d=s[2],v=s[3],_=s[4],b=s[5],p=s[6],k=s[7];return s!==o&&(o[8]=s[8],o[9]=s[9],o[10]=s[10],o[11]=s[11],o[12]=s[12],o[13]=s[13],o[14]=s[14],o[15]=s[15]),o[0]=f*c+_*u,o[1]=h*c+b*u,o[2]=d*c+p*u,o[3]=v*c+k*u,o[4]=_*c-f*u,o[5]=b*c-h*u,o[6]=p*c-d*u,o[7]=k*c-v*u,o}},7150:function(i,a,o){\"use strict\";i.exports=H;var s=o(1888),l=o(8828),u=o(2455),c=u.partial,f=u.full,h=o(855),d=o(3545),v=o(8105),_=128,b=1<<22,p=1<<22,k=v(\"!(lo>=p0)&&!(p1>=hi)\"),E=v(\"lo===p0\"),S=v(\"lo<p0\"),L=v(\"hi<=p0\"),x=v(\"lo<=p0&&p0<=hi\"),C=v(\"lo<p0&&p0<=hi\"),M=6,g=2,P=1024,T=s.mallocInt32(P),z=s.mallocDouble(P);function O(N,j){var re=8*l.log2(j+1)*(N+1)|0,oe=l.nextPow2(M*re);T.length<oe&&(s.free(T),T=s.mallocInt32(oe));var _e=l.nextPow2(g*re);z.length<_e&&(s.free(z),z=s.mallocDouble(_e))}function V(N,j,re,oe,_e,Ee,Ce,me,ie){var Se=M*N;T[Se]=j,T[Se+1]=re,T[Se+2]=oe,T[Se+3]=_e,T[Se+4]=Ee,T[Se+5]=Ce;var Le=g*N;z[Le]=me,z[Le+1]=ie}function G(N,j,re,oe,_e,Ee,Ce,me,ie,Se,Le){var Ae=2*N,Fe=ie*Ae,Pe=Se[Fe+j];e:for(var ge=_e,Re=_e*Ae;ge<Ee;++ge,Re+=Ae){var ce=Ce[Re+j],Ze=Ce[Re+j+N];if(!(Pe<ce||Ze<Pe)&&!(oe&&Pe===ce)){for(var ut=me[ge],pt=j+1;pt<N;++pt){var ce=Ce[Re+pt],Ze=Ce[Re+pt+N],Zt=Se[Fe+pt],st=Se[Fe+pt+N];if(Ze<Zt||st<ce)continue e}var lt;if(oe?lt=re(Le,ut):lt=re(ut,Le),lt!==void 0)return lt}}}function Z(N,j,re,oe,_e,Ee,Ce,me,ie,Se){var Le=2*N,Ae=me*Le,Fe=ie[Ae+j];e:for(var Pe=oe,ge=oe*Le;Pe<_e;++Pe,ge+=Le){var Re=Ce[Pe];if(Re!==Se){var ce=Ee[ge+j],Ze=Ee[ge+j+N];if(!(Fe<ce||Ze<Fe)){for(var ut=j+1;ut<N;++ut){var ce=Ee[ge+ut],Ze=Ee[ge+ut+N],pt=ie[Ae+ut],Zt=ie[Ae+ut+N];if(Ze<pt||Zt<ce)continue e}var st=re(Re,Se);if(st!==void 0)return st}}}}function H(N,j,re,oe,_e,Ee,Ce,me,ie){O(N,oe+Ce);var Se=0,Le=2*N,Ae;for(V(Se++,0,0,oe,0,Ce,re?16:0,-1/0,1/0),re||V(Se++,0,0,Ce,0,oe,1,-1/0,1/0);Se>0;){Se-=1;var Fe=Se*M,Pe=T[Fe],ge=T[Fe+1],Re=T[Fe+2],ce=T[Fe+3],Ze=T[Fe+4],ut=T[Fe+5],pt=Se*g,Zt=z[pt],st=z[pt+1],lt=ut&1,Gt=!!(ut&16),Nt=_e,Jt=Ee,sr=me,wr=ie;if(lt&&(Nt=me,Jt=ie,sr=_e,wr=Ee),!(ut&2&&(Re=S(N,Pe,ge,Re,Nt,Jt,st),ge>=Re))&&!(ut&4&&(ge=L(N,Pe,ge,Re,Nt,Jt,Zt),ge>=Re))){var cr=Re-ge,$e=Ze-ce;if(Gt){if(N*cr*(cr+$e)<p){if(Ae=h.scanComplete(N,Pe,j,ge,Re,Nt,Jt,ce,Ze,sr,wr),Ae!==void 0)return Ae;continue}}else if(N*Math.min(cr,$e)<_){if(Ae=c(N,Pe,j,lt,ge,Re,Nt,Jt,ce,Ze,sr,wr),Ae!==void 0)return Ae;continue}else if(N*cr*$e<b){if(Ae=h.scanBipartite(N,Pe,j,lt,ge,Re,Nt,Jt,ce,Ze,sr,wr),Ae!==void 0)return Ae;continue}var St=k(N,Pe,ge,Re,Nt,Jt,Zt,st);if(ge<St)if(N*(St-ge)<_){if(Ae=f(N,Pe+1,j,ge,St,Nt,Jt,ce,Ze,sr,wr),Ae!==void 0)return Ae}else if(Pe===N-2){if(lt?Ae=h.sweepBipartite(N,j,ce,Ze,sr,wr,ge,St,Nt,Jt):Ae=h.sweepBipartite(N,j,ge,St,Nt,Jt,ce,Ze,sr,wr),Ae!==void 0)return Ae}else V(Se++,Pe+1,ge,St,ce,Ze,lt,-1/0,1/0),V(Se++,Pe+1,ce,Ze,ge,St,lt^1,-1/0,1/0);if(St<Re){var Qt=d(N,Pe,ce,Ze,sr,wr),Vt=sr[Le*Qt+Pe],_t=E(N,Pe,Qt,Ze,sr,wr,Vt);if(_t<Ze&&V(Se++,Pe,St,Re,_t,Ze,(lt|4)+(Gt?16:0),Vt,st),ce<Qt&&V(Se++,Pe,St,Re,ce,Qt,(lt|2)+(Gt?16:0),Zt,Vt),Qt+1===_t){if(Gt?Ae=Z(N,Pe,j,St,Re,Nt,Jt,Qt,sr,wr[Qt]):Ae=G(N,Pe,j,lt,St,Re,Nt,Jt,Qt,sr,wr[Qt]),Ae!==void 0)return Ae}else if(Qt<_t){var It;if(Gt){if(It=x(N,Pe,St,Re,Nt,Jt,Vt),St<It){var mt=E(N,Pe,St,It,Nt,Jt,Vt);if(Pe===N-2){if(St<mt&&(Ae=h.sweepComplete(N,j,St,mt,Nt,Jt,Qt,_t,sr,wr),Ae!==void 0)||mt<It&&(Ae=h.sweepBipartite(N,j,mt,It,Nt,Jt,Qt,_t,sr,wr),Ae!==void 0))return Ae}else St<mt&&V(Se++,Pe+1,St,mt,Qt,_t,16,-1/0,1/0),mt<It&&(V(Se++,Pe+1,mt,It,Qt,_t,0,-1/0,1/0),V(Se++,Pe+1,Qt,_t,mt,It,1,-1/0,1/0))}}else lt?It=C(N,Pe,St,Re,Nt,Jt,Vt):It=x(N,Pe,St,Re,Nt,Jt,Vt),St<It&&(Pe===N-2?lt?Ae=h.sweepBipartite(N,j,Qt,_t,sr,wr,St,It,Nt,Jt):Ae=h.sweepBipartite(N,j,St,It,Nt,Jt,Qt,_t,sr,wr):(V(Se++,Pe+1,St,It,Qt,_t,lt,-1/0,1/0),V(Se++,Pe+1,Qt,_t,St,It,lt^1,-1/0,1/0)))}}}}}},7163:function(i){i.exports=function(s){return s!=null&&(a(s)||o(s)||!!s._isBuffer)};function a(s){return!!s.constructor&&typeof s.constructor.isBuffer==\"function\"&&s.constructor.isBuffer(s)}function o(s){return typeof s.readFloatLE==\"function\"&&typeof s.slice==\"function\"&&a(s.slice(0,0))}},7169:function(i,a,o){\"use strict\";var s=typeof WeakMap==\"undefined\"?o(1538):WeakMap,l=o(2762),u=o(8116),c=new s;function f(h){var d=c.get(h),v=d&&(d._triangleBuffer.handle||d._triangleBuffer.buffer);if(!v||!h.isBuffer(v)){var _=l(h,new Float32Array([-1,-1,-1,4,4,-1]));d=u(h,[{buffer:_,type:h.FLOAT,size:2}]),d._triangleBuffer=_,c.set(h,d)}d.bind(),h.drawArrays(h.TRIANGLES,0,3),d.unbind()}i.exports=f},7182:function(i,a,o){var s={identity:o(7894),translate:o(7656),multiply:o(6760),create:o(6864),scale:o(2504),fromRotationTranslation:o(6743)},l=s.create(),u=s.create();i.exports=function(f,h,d,v,_,b){return s.identity(f),s.fromRotationTranslation(f,b,h),f[3]=_[0],f[7]=_[1],f[11]=_[2],f[15]=_[3],s.identity(u),v[2]!==0&&(u[9]=v[2],s.multiply(f,f,u)),v[1]!==0&&(u[9]=0,u[8]=v[1],s.multiply(f,f,u)),v[0]!==0&&(u[8]=0,u[4]=v[0],s.multiply(f,f,u)),s.scale(f,f,d),f}},7201:function(i,a,o){\"use strict\";var s=1e-6,l=1e-6,u=o(9405),c=o(2762),f=o(8116),h=o(7766),d=o(8406),v=o(6760),_=o(7608),b=o(9618),p=o(6729),k=o(7765),E=o(1888),S=o(840),L=o(7626),x=S.meshShader,C=S.wireShader,M=S.pointShader,g=S.pickShader,P=S.pointPickShader,T=S.contourShader,z=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function O(me,ie,Se,Le,Ae,Fe,Pe,ge,Re,ce,Ze,ut,pt,Zt,st,lt,Gt,Nt,Jt,sr,wr,cr,$e,St,Qt,Vt,_t){this.gl=me,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=ie,this.dirty=!0,this.triShader=Se,this.lineShader=Le,this.pointShader=Ae,this.pickShader=Fe,this.pointPickShader=Pe,this.contourShader=ge,this.trianglePositions=Re,this.triangleColors=Ze,this.triangleNormals=pt,this.triangleUVs=ut,this.triangleIds=ce,this.triangleVAO=Zt,this.triangleCount=0,this.lineWidth=1,this.edgePositions=st,this.edgeColors=Gt,this.edgeUVs=Nt,this.edgeIds=lt,this.edgeVAO=Jt,this.edgeCount=0,this.pointPositions=sr,this.pointColors=cr,this.pointUVs=$e,this.pointSizes=St,this.pointIds=wr,this.pointVAO=Qt,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=Vt,this.contourVAO=_t,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=z,this._view=z,this._projection=z,this._resolution=[1,1]}var V=O.prototype;V.isOpaque=function(){return!this.hasAlpha},V.isTransparent=function(){return this.hasAlpha},V.pickSlots=1,V.setPickBase=function(me){this.pickId=me};function G(me,ie){if(!ie||!ie.length)return 1;for(var Se=0;Se<ie.length;++Se){if(ie.length<2)return 1;if(ie[Se][0]===me)return ie[Se][1];if(ie[Se][0]>me&&Se>0){var Le=(ie[Se][0]-me)/(ie[Se][0]-ie[Se-1][0]);return ie[Se][1]*(1-Le)+Le*ie[Se-1][1]}}return 1}function Z(me,ie){for(var Se=p({colormap:me,nshades:256,format:\"rgba\"}),Le=new Uint8Array(256*4),Ae=0;Ae<256;++Ae){for(var Fe=Se[Ae],Pe=0;Pe<3;++Pe)Le[4*Ae+Pe]=Fe[Pe];ie?Le[4*Ae+3]=255*G(Ae/255,ie):Le[4*Ae+3]=255*Fe[3]}return b(Le,[256,256,4],[4,0,1])}function H(me){for(var ie=me.length,Se=new Array(ie),Le=0;Le<ie;++Le)Se[Le]=me[Le][2];return Se}V.highlight=function(me){if(!me||!this.contourEnable){this.contourCount=0;return}for(var ie=k(this.cells,this.intensity,me.intensity),Se=ie.cells,Le=ie.vertexIds,Ae=ie.vertexWeights,Fe=Se.length,Pe=E.mallocFloat32(2*3*Fe),ge=0,Re=0;Re<Fe;++Re)for(var ce=Se[Re],Ze=0;Ze<2;++Ze){var ut=ce[0];ce.length===2&&(ut=ce[Ze]);for(var pt=Le[ut][0],Zt=Le[ut][1],st=Ae[ut],lt=1-st,Gt=this.positions[pt],Nt=this.positions[Zt],Jt=0;Jt<3;++Jt)Pe[ge++]=st*Gt[Jt]+lt*Nt[Jt]}this.contourCount=ge/3|0,this.contourPositions.update(Pe.subarray(0,ge)),E.free(Pe)},V.update=function(me){me=me||{};var ie=this.gl;this.dirty=!0,\"contourEnable\"in me&&(this.contourEnable=me.contourEnable),\"contourColor\"in me&&(this.contourColor=me.contourColor),\"lineWidth\"in me&&(this.lineWidth=me.lineWidth),\"lightPosition\"in me&&(this.lightPosition=me.lightPosition),this.hasAlpha=!1,\"opacity\"in me&&(this.opacity=me.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in me&&(this.opacityscale=me.opacityscale,this.hasAlpha=!0),\"ambient\"in me&&(this.ambientLight=me.ambient),\"diffuse\"in me&&(this.diffuseLight=me.diffuse),\"specular\"in me&&(this.specularLight=me.specular),\"roughness\"in me&&(this.roughness=me.roughness),\"fresnel\"in me&&(this.fresnel=me.fresnel),me.texture?(this.texture.dispose(),this.texture=h(ie,me.texture)):me.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=ie.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=ie.LINEAR,this.texture.setPixels(Z(me.colormap,this.opacityscale)),this.texture.generateMipmap());var Se=me.cells,Le=me.positions;if(!(!Le||!Se)){var Ae=[],Fe=[],Pe=[],ge=[],Re=[],ce=[],Ze=[],ut=[],pt=[],Zt=[],st=[],lt=[],Gt=[],Nt=[];this.cells=Se,this.positions=Le;var Jt=me.vertexNormals,sr=me.cellNormals,wr=me.vertexNormalsEpsilon===void 0?s:me.vertexNormalsEpsilon,cr=me.faceNormalsEpsilon===void 0?l:me.faceNormalsEpsilon;me.useFacetNormals&&!sr&&(sr=d.faceNormals(Se,Le,cr)),!sr&&!Jt&&(Jt=d.vertexNormals(Se,Le,wr));var $e=me.vertexColors,St=me.cellColors,Qt=me.meshColor||[1,1,1,1],Vt=me.vertexUVs,_t=me.vertexIntensity,It=me.cellUVs,mt=me.cellIntensity,er=1/0,lr=-1/0;if(!Vt&&!It)if(_t)if(me.vertexIntensityBounds)er=+me.vertexIntensityBounds[0],lr=+me.vertexIntensityBounds[1];else for(var Tr=0;Tr<_t.length;++Tr){var Lr=_t[Tr];er=Math.min(er,Lr),lr=Math.max(lr,Lr)}else if(mt)if(me.cellIntensityBounds)er=+me.cellIntensityBounds[0],lr=+me.cellIntensityBounds[1];else for(var Tr=0;Tr<mt.length;++Tr){var Lr=mt[Tr];er=Math.min(er,Lr),lr=Math.max(lr,Lr)}else for(var Tr=0;Tr<Le.length;++Tr){var Lr=Le[Tr][2];er=Math.min(er,Lr),lr=Math.max(lr,Lr)}_t?this.intensity=_t:mt?this.intensity=mt:this.intensity=H(Le),this.pickVertex=!(mt||St);var ti=me.pointSizes,Br=me.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(var Tr=0;Tr<Le.length;++Tr)for(var Vr=Le[Tr],dt=0;dt<3;++dt)isNaN(Vr[dt])||!isFinite(Vr[dt])||(this.bounds[0][dt]=Math.min(this.bounds[0][dt],Vr[dt]),this.bounds[1][dt]=Math.max(this.bounds[1][dt],Vr[dt]));var Ge=0,Je=0,je=0;e:for(var Tr=0;Tr<Se.length;++Tr){var tt=Se[Tr];switch(tt.length){case 1:for(var xt=tt[0],Vr=Le[xt],dt=0;dt<3;++dt)if(isNaN(Vr[dt])||!isFinite(Vr[dt]))continue e;Zt.push(Vr[0],Vr[1],Vr[2]);var Ie;$e?Ie=$e[xt]:St?Ie=St[Tr]:Ie=Qt,this.opacityscale&&_t?Fe.push(Ie[0],Ie[1],Ie[2],this.opacity*G((_t[xt]-er)/(lr-er),this.opacityscale)):Ie.length===3?st.push(Ie[0],Ie[1],Ie[2],this.opacity):(st.push(Ie[0],Ie[1],Ie[2],Ie[3]*this.opacity),Ie[3]<1&&(this.hasAlpha=!0));var xe;Vt?xe=Vt[xt]:_t?xe=[(_t[xt]-er)/(lr-er),0]:It?xe=It[Tr]:mt?xe=[(mt[Tr]-er)/(lr-er),0]:xe=[(Vr[2]-er)/(lr-er),0],lt.push(xe[0],xe[1]),ti?Gt.push(ti[xt]):Gt.push(Br),Nt.push(Tr),je+=1;break;case 2:for(var dt=0;dt<2;++dt)for(var xt=tt[dt],Vr=Le[xt],ke=0;ke<3;++ke)if(isNaN(Vr[ke])||!isFinite(Vr[ke]))continue e;for(var dt=0;dt<2;++dt){var xt=tt[dt],Vr=Le[xt];ce.push(Vr[0],Vr[1],Vr[2]);var Ie;$e?Ie=$e[xt]:St?Ie=St[Tr]:Ie=Qt,this.opacityscale&&_t?Fe.push(Ie[0],Ie[1],Ie[2],this.opacity*G((_t[xt]-er)/(lr-er),this.opacityscale)):Ie.length===3?Ze.push(Ie[0],Ie[1],Ie[2],this.opacity):(Ze.push(Ie[0],Ie[1],Ie[2],Ie[3]*this.opacity),Ie[3]<1&&(this.hasAlpha=!0));var xe;Vt?xe=Vt[xt]:_t?xe=[(_t[xt]-er)/(lr-er),0]:It?xe=It[Tr]:mt?xe=[(mt[Tr]-er)/(lr-er),0]:xe=[(Vr[2]-er)/(lr-er),0],ut.push(xe[0],xe[1]),pt.push(Tr)}Je+=1;break;case 3:for(var dt=0;dt<3;++dt)for(var xt=tt[dt],Vr=Le[xt],ke=0;ke<3;++ke)if(isNaN(Vr[ke])||!isFinite(Vr[ke]))continue e;for(var dt=0;dt<3;++dt){var xt=tt[2-dt],Vr=Le[xt];Ae.push(Vr[0],Vr[1],Vr[2]);var Ie;$e?Ie=$e[xt]:St?Ie=St[Tr]:Ie=Qt,Ie?this.opacityscale&&_t?Fe.push(Ie[0],Ie[1],Ie[2],this.opacity*G((_t[xt]-er)/(lr-er),this.opacityscale)):Ie.length===3?Fe.push(Ie[0],Ie[1],Ie[2],this.opacity):(Fe.push(Ie[0],Ie[1],Ie[2],Ie[3]*this.opacity),Ie[3]<1&&(this.hasAlpha=!0)):Fe.push(.5,.5,.5,1);var xe;Vt?xe=Vt[xt]:_t?xe=[(_t[xt]-er)/(lr-er),0]:It?xe=It[Tr]:mt?xe=[(mt[Tr]-er)/(lr-er),0]:xe=[(Vr[2]-er)/(lr-er),0],ge.push(xe[0],xe[1]);var vt;Jt?vt=Jt[xt]:vt=sr[Tr],Pe.push(vt[0],vt[1],vt[2]),Re.push(Tr)}Ge+=1;break;default:break}}this.pointCount=je,this.edgeCount=Je,this.triangleCount=Ge,this.pointPositions.update(Zt),this.pointColors.update(st),this.pointUVs.update(lt),this.pointSizes.update(Gt),this.pointIds.update(new Uint32Array(Nt)),this.edgePositions.update(ce),this.edgeColors.update(Ze),this.edgeUVs.update(ut),this.edgeIds.update(new Uint32Array(pt)),this.trianglePositions.update(Ae),this.triangleColors.update(Fe),this.triangleUVs.update(ge),this.triangleNormals.update(Pe),this.triangleIds.update(new Uint32Array(Re))}},V.drawTransparent=V.draw=function(me){me=me||{};for(var ie=this.gl,Se=me.model||z,Le=me.view||z,Ae=me.projection||z,Fe=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],Pe=0;Pe<3;++Pe)Fe[0][Pe]=Math.max(Fe[0][Pe],this.clipBounds[0][Pe]),Fe[1][Pe]=Math.min(Fe[1][Pe],this.clipBounds[1][Pe]);var ge={model:Se,view:Le,projection:Ae,inverseModel:z.slice(),clipBounds:Fe,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};ge.inverseModel=_(ge.inverseModel,ge.model),ie.disable(ie.CULL_FACE),this.texture.bind(0);var Re=new Array(16);v(Re,ge.view,ge.model),v(Re,ge.projection,Re),_(Re,Re);for(var Pe=0;Pe<3;++Pe)ge.eyePosition[Pe]=Re[12+Pe]/Re[15];for(var ce=Re[15],Pe=0;Pe<3;++Pe)ce+=this.lightPosition[Pe]*Re[4*Pe+3];for(var Pe=0;Pe<3;++Pe){for(var Ze=Re[12+Pe],ut=0;ut<3;++ut)Ze+=Re[4*ut+Pe]*this.lightPosition[ut];ge.lightPosition[Pe]=Ze/ce}if(this.triangleCount>0){var pt=this.triShader;pt.bind(),pt.uniforms=ge,this.triangleVAO.bind(),ie.drawArrays(ie.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var pt=this.lineShader;pt.bind(),pt.uniforms=ge,this.edgeVAO.bind(),ie.lineWidth(this.lineWidth*this.pixelRatio),ie.drawArrays(ie.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()}if(this.pointCount>0){var pt=this.pointShader;pt.bind(),pt.uniforms=ge,this.pointVAO.bind(),ie.drawArrays(ie.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var pt=this.contourShader;pt.bind(),pt.uniforms=ge,this.contourVAO.bind(),ie.drawArrays(ie.LINES,0,this.contourCount),this.contourVAO.unbind()}},V.drawPick=function(me){me=me||{};for(var ie=this.gl,Se=me.model||z,Le=me.view||z,Ae=me.projection||z,Fe=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],Pe=0;Pe<3;++Pe)Fe[0][Pe]=Math.max(Fe[0][Pe],this.clipBounds[0][Pe]),Fe[1][Pe]=Math.min(Fe[1][Pe],this.clipBounds[1][Pe]);this._model=[].slice.call(Se),this._view=[].slice.call(Le),this._projection=[].slice.call(Ae),this._resolution=[ie.drawingBufferWidth,ie.drawingBufferHeight];var ge={model:Se,view:Le,projection:Ae,clipBounds:Fe,pickId:this.pickId/255},Re=this.pickShader;if(Re.bind(),Re.uniforms=ge,this.triangleCount>0&&(this.triangleVAO.bind(),ie.drawArrays(ie.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),ie.lineWidth(this.lineWidth*this.pixelRatio),ie.drawArrays(ie.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()),this.pointCount>0){var Re=this.pointPickShader;Re.bind(),Re.uniforms=ge,this.pointVAO.bind(),ie.drawArrays(ie.POINTS,0,this.pointCount),this.pointVAO.unbind()}},V.pick=function(me){if(!me||me.id!==this.pickId)return null;for(var ie=me.value[0]+256*me.value[1]+65536*me.value[2],Se=this.cells[ie],Le=this.positions,Ae=new Array(Se.length),Fe=0;Fe<Se.length;++Fe)Ae[Fe]=Le[Se[Fe]];var Pe=me.coord[0],ge=me.coord[1];if(!this.pickVertex){var Re=this.positions[Se[0]],ce=this.positions[Se[1]],Ze=this.positions[Se[2]],ut=[(Re[0]+ce[0]+Ze[0])/3,(Re[1]+ce[1]+Ze[1])/3,(Re[2]+ce[2]+Ze[2])/3];return{_cellCenter:!0,position:[Pe,ge],index:ie,cell:Se,cellId:ie,intensity:this.intensity[ie],dataCoordinate:ut}}var pt=L(Ae,[Pe*this.pixelRatio,this._resolution[1]-ge*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!pt)return null;for(var Zt=pt[2],st=0,Fe=0;Fe<Se.length;++Fe)st+=Zt[Fe]*this.intensity[Se[Fe]];return{position:pt[1],index:Se[pt[0]],cell:Se,cellId:ie,intensity:st,dataCoordinate:this.positions[Se[pt[0]]]}},V.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()};function N(me){var ie=u(me,x.vertex,x.fragment);return ie.attributes.position.location=0,ie.attributes.color.location=2,ie.attributes.uv.location=3,ie.attributes.normal.location=4,ie}function j(me){var ie=u(me,C.vertex,C.fragment);return ie.attributes.position.location=0,ie.attributes.color.location=2,ie.attributes.uv.location=3,ie}function re(me){var ie=u(me,M.vertex,M.fragment);return ie.attributes.position.location=0,ie.attributes.color.location=2,ie.attributes.uv.location=3,ie.attributes.pointSize.location=4,ie}function oe(me){var ie=u(me,g.vertex,g.fragment);return ie.attributes.position.location=0,ie.attributes.id.location=1,ie}function _e(me){var ie=u(me,P.vertex,P.fragment);return ie.attributes.position.location=0,ie.attributes.id.location=1,ie.attributes.pointSize.location=4,ie}function Ee(me){var ie=u(me,T.vertex,T.fragment);return ie.attributes.position.location=0,ie}function Ce(me,ie){arguments.length===1&&(ie=me,me=ie.gl);var Se=me.getExtension(\"OES_standard_derivatives\")||me.getExtension(\"MOZ_OES_standard_derivatives\")||me.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!Se)throw new Error(\"derivatives not supported\");var Le=N(me),Ae=j(me),Fe=re(me),Pe=oe(me),ge=_e(me),Re=Ee(me),ce=h(me,b(new Uint8Array([255,255,255,255]),[1,1,4]));ce.generateMipmap(),ce.minFilter=me.LINEAR_MIPMAP_LINEAR,ce.magFilter=me.LINEAR;var Ze=c(me),ut=c(me),pt=c(me),Zt=c(me),st=c(me),lt=f(me,[{buffer:Ze,type:me.FLOAT,size:3},{buffer:st,type:me.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:ut,type:me.FLOAT,size:4},{buffer:pt,type:me.FLOAT,size:2},{buffer:Zt,type:me.FLOAT,size:3}]),Gt=c(me),Nt=c(me),Jt=c(me),sr=c(me),wr=f(me,[{buffer:Gt,type:me.FLOAT,size:3},{buffer:sr,type:me.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:Nt,type:me.FLOAT,size:4},{buffer:Jt,type:me.FLOAT,size:2}]),cr=c(me),$e=c(me),St=c(me),Qt=c(me),Vt=c(me),_t=f(me,[{buffer:cr,type:me.FLOAT,size:3},{buffer:Vt,type:me.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:$e,type:me.FLOAT,size:4},{buffer:St,type:me.FLOAT,size:2},{buffer:Qt,type:me.FLOAT,size:1}]),It=c(me),mt=f(me,[{buffer:It,type:me.FLOAT,size:3}]),er=new O(me,ce,Le,Ae,Fe,Pe,ge,Re,Ze,st,ut,pt,Zt,lt,Gt,sr,Nt,Jt,wr,cr,Vt,$e,St,Qt,_t,It,mt);return er.update(ie),er}i.exports=Ce},7261:function(i,a,o){\"use strict\";i.exports=E;var s=o(9215),l=o(7608),u=o(6079),c=o(5911),f=o(3536),h=o(244);function d(S,L,x){return Math.sqrt(Math.pow(S,2)+Math.pow(L,2)+Math.pow(x,2))}function v(S){return Math.min(1,Math.max(-1,S))}function _(S){var L=Math.abs(S[0]),x=Math.abs(S[1]),C=Math.abs(S[2]),M=[0,0,0];L>Math.max(x,C)?M[2]=1:x>Math.max(L,C)?M[0]=1:M[1]=1;for(var g=0,P=0,T=0;T<3;++T)g+=S[T]*S[T],P+=M[T]*S[T];for(var T=0;T<3;++T)M[T]-=P/g*S[T];return f(M,M),M}function b(S,L,x,C,M,g,P,T){this.center=s(x),this.up=s(C),this.right=s(M),this.radius=s([g]),this.angle=s([P,T]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(S,L),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var z=0;z<16;++z)this.computedMatrix[z]=.5;this.recalcMatrix(0)}var p=b.prototype;p.setDistanceLimits=function(S,L){S>0?S=Math.log(S):S=-1/0,L>0?L=Math.log(L):L=1/0,L=Math.max(L,S),this.radius.bounds[0][0]=S,this.radius.bounds[1][0]=L},p.getDistanceLimits=function(S){var L=this.radius.bounds[0];return S?(S[0]=Math.exp(L[0][0]),S[1]=Math.exp(L[1][0]),S):[Math.exp(L[0][0]),Math.exp(L[1][0])]},p.recalcMatrix=function(S){this.center.curve(S),this.up.curve(S),this.right.curve(S),this.radius.curve(S),this.angle.curve(S);for(var L=this.computedUp,x=this.computedRight,C=0,M=0,g=0;g<3;++g)M+=L[g]*x[g],C+=L[g]*L[g];for(var P=Math.sqrt(C),T=0,g=0;g<3;++g)x[g]-=L[g]*M/C,T+=x[g]*x[g],L[g]/=P;for(var z=Math.sqrt(T),g=0;g<3;++g)x[g]/=z;var O=this.computedToward;c(O,L,x),f(O,O);for(var V=Math.exp(this.computedRadius[0]),G=this.computedAngle[0],Z=this.computedAngle[1],H=Math.cos(G),N=Math.sin(G),j=Math.cos(Z),re=Math.sin(Z),oe=this.computedCenter,_e=H*j,Ee=N*j,Ce=re,me=-H*re,ie=-N*re,Se=j,Le=this.computedEye,Ae=this.computedMatrix,g=0;g<3;++g){var Fe=_e*x[g]+Ee*O[g]+Ce*L[g];Ae[4*g+1]=me*x[g]+ie*O[g]+Se*L[g],Ae[4*g+2]=Fe,Ae[4*g+3]=0}var Pe=Ae[1],ge=Ae[5],Re=Ae[9],ce=Ae[2],Ze=Ae[6],ut=Ae[10],pt=ge*ut-Re*Ze,Zt=Re*ce-Pe*ut,st=Pe*Ze-ge*ce,lt=d(pt,Zt,st);pt/=lt,Zt/=lt,st/=lt,Ae[0]=pt,Ae[4]=Zt,Ae[8]=st;for(var g=0;g<3;++g)Le[g]=oe[g]+Ae[2+4*g]*V;for(var g=0;g<3;++g){for(var T=0,Gt=0;Gt<3;++Gt)T+=Ae[g+4*Gt]*Le[Gt];Ae[12+g]=-T}Ae[15]=1},p.getMatrix=function(S,L){this.recalcMatrix(S);var x=this.computedMatrix;if(L){for(var C=0;C<16;++C)L[C]=x[C];return L}return x};var k=[0,0,0];p.rotate=function(S,L,x,C){if(this.angle.move(S,L,x),C){this.recalcMatrix(S);var M=this.computedMatrix;k[0]=M[2],k[1]=M[6],k[2]=M[10];for(var g=this.computedUp,P=this.computedRight,T=this.computedToward,z=0;z<3;++z)M[4*z]=g[z],M[4*z+1]=P[z],M[4*z+2]=T[z];u(M,M,C,k);for(var z=0;z<3;++z)g[z]=M[4*z],P[z]=M[4*z+1];this.up.set(S,g[0],g[1],g[2]),this.right.set(S,P[0],P[1],P[2])}},p.pan=function(S,L,x,C){L=L||0,x=x||0,C=C||0,this.recalcMatrix(S);var M=this.computedMatrix,g=Math.exp(this.computedRadius[0]),P=M[1],T=M[5],z=M[9],O=d(P,T,z);P/=O,T/=O,z/=O;var V=M[0],G=M[4],Z=M[8],H=V*P+G*T+Z*z;V-=P*H,G-=T*H,Z-=z*H;var N=d(V,G,Z);V/=N,G/=N,Z/=N;var j=V*L+P*x,re=G*L+T*x,oe=Z*L+z*x;this.center.move(S,j,re,oe);var _e=Math.exp(this.computedRadius[0]);_e=Math.max(1e-4,_e+C),this.radius.set(S,Math.log(_e))},p.translate=function(S,L,x,C){this.center.move(S,L||0,x||0,C||0)},p.setMatrix=function(S,L,x,C){var M=1;typeof x==\"number\"&&(M=x|0),(M<0||M>3)&&(M=1);var g=(M+2)%3,P=(M+1)%3;L||(this.recalcMatrix(S),L=this.computedMatrix);var T=L[M],z=L[M+4],O=L[M+8];if(C){var G=Math.abs(T),Z=Math.abs(z),H=Math.abs(O),N=Math.max(G,Z,H);G===N?(T=T<0?-1:1,z=O=0):H===N?(O=O<0?-1:1,T=z=0):(z=z<0?-1:1,T=O=0)}else{var V=d(T,z,O);T/=V,z/=V,O/=V}var j=L[g],re=L[g+4],oe=L[g+8],_e=j*T+re*z+oe*O;j-=T*_e,re-=z*_e,oe-=O*_e;var Ee=d(j,re,oe);j/=Ee,re/=Ee,oe/=Ee;var Ce=z*oe-O*re,me=O*j-T*oe,ie=T*re-z*j,Se=d(Ce,me,ie);Ce/=Se,me/=Se,ie/=Se,this.center.jump(S,cr,$e,St),this.radius.idle(S),this.up.jump(S,T,z,O),this.right.jump(S,j,re,oe);var Le,Ae;if(M===2){var Fe=L[1],Pe=L[5],ge=L[9],Re=Fe*j+Pe*re+ge*oe,ce=Fe*Ce+Pe*me+ge*ie;Zt<0?Le=-Math.PI/2:Le=Math.PI/2,Ae=Math.atan2(ce,Re)}else{var Ze=L[2],ut=L[6],pt=L[10],Zt=Ze*T+ut*z+pt*O,st=Ze*j+ut*re+pt*oe,lt=Ze*Ce+ut*me+pt*ie;Le=Math.asin(v(Zt)),Ae=Math.atan2(lt,st)}this.angle.jump(S,Ae,Le),this.recalcMatrix(S);var Gt=L[2],Nt=L[6],Jt=L[10],sr=this.computedMatrix;l(sr,L);var wr=sr[15],cr=sr[12]/wr,$e=sr[13]/wr,St=sr[14]/wr,Qt=Math.exp(this.computedRadius[0]);this.center.jump(S,cr-Gt*Qt,$e-Nt*Qt,St-Jt*Qt)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(S){this.center.idle(S),this.up.idle(S),this.right.idle(S),this.radius.idle(S),this.angle.idle(S)},p.flush=function(S){this.center.flush(S),this.up.flush(S),this.right.flush(S),this.radius.flush(S),this.angle.flush(S)},p.setDistance=function(S,L){L>0&&this.radius.set(S,Math.log(L))},p.lookAt=function(S,L,x,C){this.recalcMatrix(S),L=L||this.computedEye,x=x||this.computedCenter,C=C||this.computedUp;var M=C[0],g=C[1],P=C[2],T=d(M,g,P);if(!(T<1e-6)){M/=T,g/=T,P/=T;var z=L[0]-x[0],O=L[1]-x[1],V=L[2]-x[2],G=d(z,O,V);if(!(G<1e-6)){z/=G,O/=G,V/=G;var Z=this.computedRight,H=Z[0],N=Z[1],j=Z[2],re=M*H+g*N+P*j;H-=re*M,N-=re*g,j-=re*P;var oe=d(H,N,j);if(!(oe<.01&&(H=g*V-P*O,N=P*z-M*V,j=M*O-g*z,oe=d(H,N,j),oe<1e-6))){H/=oe,N/=oe,j/=oe,this.up.set(S,M,g,P),this.right.set(S,H,N,j),this.center.set(S,x[0],x[1],x[2]),this.radius.set(S,Math.log(G));var _e=g*j-P*N,Ee=P*H-M*j,Ce=M*N-g*H,me=d(_e,Ee,Ce);_e/=me,Ee/=me,Ce/=me;var ie=M*z+g*O+P*V,Se=H*z+N*O+j*V,Le=_e*z+Ee*O+Ce*V,Ae=Math.asin(v(ie)),Fe=Math.atan2(Le,Se),Pe=this.angle._state,ge=Pe[Pe.length-1],Re=Pe[Pe.length-2];ge=ge%(2*Math.PI);var ce=Math.abs(ge+2*Math.PI-Fe),Ze=Math.abs(ge-Fe),ut=Math.abs(ge-2*Math.PI-Fe);ce<Ze&&(ge+=2*Math.PI),ut<Ze&&(ge-=2*Math.PI),this.angle.jump(this.angle.lastT(),ge,Re),this.angle.set(S,Fe,Ae)}}}};function E(S){S=S||{};var L=S.center||[0,0,0],x=S.up||[0,1,0],C=S.right||_(x),M=S.radius||1,g=S.theta||0,P=S.phi||0;if(L=[].slice.call(L,0,3),x=[].slice.call(x,0,3),f(x,x),C=[].slice.call(C,0,3),f(C,C),\"eye\"in S){var T=S.eye,z=[T[0]-L[0],T[1]-L[1],T[2]-L[2]];c(C,z,x),d(C[0],C[1],C[2])<1e-6?C=_(x):f(C,C),M=d(z[0],z[1],z[2]);var O=h(x,z)/M,V=h(C,z)/M;P=Math.acos(O),g=Math.acos(V)}return M=Math.log(M),new b(S.zoomMin,S.zoomMax,L,x,C,M,g,P)}},7319:function(i,a,o){var s=o(3236),l=o(9405),u=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute vec3 position, nextPosition;\n",
+       "attribute float arcLength, lineWidth;\n",
+       "attribute vec4 color;\n",
+       "\n",
+       "uniform vec2 screenShape;\n",
+       "uniform float pixelRatio;\n",
+       "uniform mat4 model, view, projection;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "varying vec3 worldPosition;\n",
+       "varying float pixelArcLength;\n",
+       "\n",
+       "vec4 project(vec3 p) {\n",
+       "  return projection * (view * (model * vec4(p, 1.0)));\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  vec4 startPoint = project(position);\n",
+       "  vec4 endPoint   = project(nextPosition);\n",
+       "\n",
+       "  vec2 A = startPoint.xy / startPoint.w;\n",
+       "  vec2 B =   endPoint.xy /   endPoint.w;\n",
+       "\n",
+       "  float clipAngle = atan(\n",
+       "    (B.y - A.y) * screenShape.y,\n",
+       "    (B.x - A.x) * screenShape.x\n",
+       "  );\n",
+       "\n",
+       "  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\n",
+       "    sin(clipAngle),\n",
+       "    -cos(clipAngle)\n",
+       "  ) / screenShape;\n",
+       "\n",
+       "  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\n",
+       "\n",
+       "  worldPosition = position;\n",
+       "  pixelArcLength = arcLength;\n",
+       "  fragColor = color;\n",
+       "}\n",
+       "`]),c=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform vec3      clipBounds[2];\n",
+       "uniform sampler2D dashTexture;\n",
+       "uniform float     dashScale;\n",
+       "uniform float     opacity;\n",
+       "\n",
+       "varying vec3    worldPosition;\n",
+       "varying float   pixelArcLength;\n",
+       "varying vec4    fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "  if (\n",
+       "    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\n",
+       "    fragColor.a * opacity == 0.\n",
+       "  ) discard;\n",
+       "\n",
+       "  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\n",
+       "  if(dashWeight < 0.5) {\n",
+       "    discard;\n",
+       "  }\n",
+       "  gl_FragColor = fragColor * opacity;\n",
+       "}\n",
+       "`]),f=s([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "#define FLOAT_MAX  1.70141184e38\n",
+       "#define FLOAT_MIN  1.17549435e-38\n",
+       "\n",
+       "// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\n",
+       "vec4 packFloat(float v) {\n",
+       "  float av = abs(v);\n",
+       "\n",
+       "  //Handle special cases\n",
+       "  if(av < FLOAT_MIN) {\n",
+       "    return vec4(0.0, 0.0, 0.0, 0.0);\n",
+       "  } else if(v > FLOAT_MAX) {\n",
+       "    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\n",
+       "  } else if(v < -FLOAT_MAX) {\n",
+       "    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\n",
+       "  }\n",
+       "\n",
+       "  vec4 c = vec4(0,0,0,0);\n",
+       "\n",
+       "  //Compute exponent and mantissa\n",
+       "  float e = floor(log2(av));\n",
+       "  float m = av * pow(2.0, -e) - 1.0;\n",
+       "\n",
+       "  //Unpack mantissa\n",
+       "  c[1] = floor(128.0 * m);\n",
+       "  m -= c[1] / 128.0;\n",
+       "  c[2] = floor(32768.0 * m);\n",
+       "  m -= c[2] / 32768.0;\n",
+       "  c[3] = floor(8388608.0 * m);\n",
+       "\n",
+       "  //Unpack exponent\n",
+       "  float ebias = e + 127.0;\n",
+       "  c[0] = floor(ebias / 2.0);\n",
+       "  ebias -= c[0] * 2.0;\n",
+       "  c[1] += floor(ebias) * 128.0;\n",
+       "\n",
+       "  //Unpack sign bit\n",
+       "  c[0] += 128.0 * step(0.0, -v);\n",
+       "\n",
+       "  //Scale back to range\n",
+       "  return c / 255.0;\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(float a, float b, float p) {\n",
+       "  return ((p > max(a, b)) || \n",
+       "          (p < min(a, b)));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n",
+       "  return (outOfRange(a.x, b.x, p.x) ||\n",
+       "          outOfRange(a.y, b.y, p.y) ||\n",
+       "          outOfRange(a.z, b.z, p.z));\n",
+       "}\n",
+       "\n",
+       "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n",
+       "  return outOfRange(a.xyz, b.xyz, p.xyz);\n",
+       "}\n",
+       "\n",
+       "uniform float pickId;\n",
+       "uniform vec3 clipBounds[2];\n",
+       "\n",
+       "varying vec3 worldPosition;\n",
+       "varying float pixelArcLength;\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\n",
+       "\n",
+       "  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\n",
+       "}`]),h=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];a.createShader=function(d){return l(d,u,c,null,h)},a.createPickShader=function(d){return l(d,u,f,null,h)}},7352:function(i,a,o){\"use strict\";var s=o(5721),l=o(4750),u=o(2690);i.exports=c;function c(f){var h=f.length;if(h===0)return[];if(h===1)return[[0]];var d=f[0].length;return d===0?[]:d===1?s(f):d===2?l(f):u(f,d)}},7399:function(i){i.exports=a;function a(o,s){var l=s[0],u=s[1],c=s[2],f=s[3],h=l+l,d=u+u,v=c+c,_=l*h,b=u*h,p=u*d,k=c*h,E=c*d,S=c*v,L=f*h,x=f*d,C=f*v;return o[0]=1-p-S,o[1]=b+C,o[2]=k-x,o[3]=0,o[4]=b-C,o[5]=1-_-S,o[6]=E+L,o[7]=0,o[8]=k+x,o[9]=E-L,o[10]=1-_-p,o[11]=0,o[12]=0,o[13]=0,o[14]=0,o[15]=1,o}},7417:function(i){i.exports=a;function a(o,s,l){return o[0]=Math.max(s[0],l[0]),o[1]=Math.max(s[1],l[1]),o[2]=Math.max(s[2],l[2]),o}},7442:function(i,a,o){var s=o(6658),l=o(7182),u=o(2652),c=o(9921),f=o(8648),h=b(),d=b(),v=b();i.exports=_;function _(E,S,L,x){if(c(S)===0||c(L)===0)return!1;var C=u(S,h.translate,h.scale,h.skew,h.perspective,h.quaternion),M=u(L,d.translate,d.scale,d.skew,d.perspective,d.quaternion);return!C||!M?!1:(s(v.translate,h.translate,d.translate,x),s(v.skew,h.skew,d.skew,x),s(v.scale,h.scale,d.scale,x),s(v.perspective,h.perspective,d.perspective,x),f(v.quaternion,h.quaternion,d.quaternion,x),l(E,v.translate,v.scale,v.skew,v.perspective,v.quaternion),!0)}function b(){return{translate:p(),scale:p(1),skew:p(),perspective:k(),quaternion:k()}}function p(E){return[E||0,E||0,E||0]}function k(){return[0,0,0,1]}},7507:function(i,a){\"use strict\";a.byteLength=d,a.toByteArray=_,a.fromByteArray=k;for(var o=[],s=[],l=typeof Uint8Array!=\"undefined\"?Uint8Array:Array,u=\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/\",c=0,f=u.length;c<f;++c)o[c]=u[c],s[u.charCodeAt(c)]=c;s[45]=62,s[95]=63;function h(E){var S=E.length;if(S%4>0)throw new Error(\"Invalid string. 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ie=H[me].indexOf(G[0]);ie===-1?H[me]+=G:_e&&(H[me]=H[me].substr(0,ie+1)+(1+parseInt(H[me][ie+1]))+H[me].substr(ie+2))}var Se=Ee+re,Le=Z.substr(Se,Ce-Se),Ae=Le.indexOf(N);Ae!==-1?Ee=Ae:Ee=Ce+oe}return H}function M(V,G,Z){for(var H=G.textAlign||\"start\",N=G.textBaseline||\"alphabetic\",j=[1<<30,1<<30],re=[0,0],oe=V.length,_e=0;_e<oe;++_e)for(var Ee=V[_e],Ce=0;Ce<2;++Ce)j[Ce]=Math.min(j[Ce],Ee[Ce])|0,re[Ce]=Math.max(re[Ce],Ee[Ce])|0;var me=0;switch(H){case\"center\":me=-.5*(j[0]+re[0]);break;case\"right\":case\"end\":me=-re[0];break;case\"left\":case\"start\":me=-j[0];break;default:throw new Error(\"vectorize-text: Unrecognized textAlign: '\"+H+\"'\")}var ie=0;switch(N){case\"hanging\":case\"top\":ie=-j[1];break;case\"middle\":ie=-.5*(j[1]+re[1]);break;case\"alphabetic\":case\"ideographic\":ie=-3*Z;break;case\"bottom\":ie=-re[1];break;default:throw new Error(\"vectorize-text: Unrecoginized textBaseline: '\"+N+\"'\")}var Se=1/Z;return\"lineHeight\"in G?Se*=+G.lineHeight:\"width\"in G?Se=G.width/(re[0]-j[0]):\"height\"in G&&(Se=G.height/(re[1]-j[1])),V.map(function(Le){return[Se*(Le[0]+me),Se*(Le[1]+ie)]})}function g(V,G,Z,H,N,j){Z=Z.replace(/\\n/g,\"\"),j.breaklines===!0?Z=Z.replace(/\\<br\\>/g,`\n",
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+       "`),me=Ce.length,ie=Math.round(N*H),Se=H,Le=H*2,Ae=0,Fe=me*ie+Le;V.height<Fe&&(V.height=Fe),G.fillStyle=\"#000\",G.fillRect(0,0,V.width,V.height),G.fillStyle=\"#fff\";var Pe,ge,Re,ce,Ze,ut=0,pt=\"\";function Zt(){if(pt!==\"\"){var $e=G.measureText(pt).width;G.fillText(pt,Se+Re,Le+ce),Re+=$e}}function st(){return\"\"+Math.round(Ze)+\"px \"}function lt($e,St){var Qt=\"\"+G.font;if(j.subscripts===!0){var Vt=$e.indexOf(L),_t=St.indexOf(L),It=Vt>-1?parseInt($e[1+Vt]):0,mt=_t>-1?parseInt(St[1+_t]):0;It!==mt&&(Qt=Qt.replace(st(),\"?px \"),Ze*=Math.pow(.75,mt-It),Qt=Qt.replace(\"?px \",st())),ce+=.25*ie*(mt-It)}if(j.superscripts===!0){var er=$e.indexOf(k),lr=St.indexOf(k),Tr=er>-1?parseInt($e[1+er]):0,Lr=lr>-1?parseInt(St[1+lr]):0;Tr!==Lr&&(Qt=Qt.replace(st(),\"?px \"),Ze*=Math.pow(.75,Lr-Tr),Qt=Qt.replace(\"?px \",st())),ce-=.25*ie*(Lr-Tr)}if(j.bolds===!0){var ti=$e.indexOf(v)>-1,Br=St.indexOf(v)>-1;!ti&&Br&&(Vr?Qt=Qt.replace(\"italic \",\"italic bold \"):Qt=\"bold \"+Qt),ti&&!Br&&(Qt=Qt.replace(\"bold \",\"\"))}if(j.italics===!0){var Vr=$e.indexOf(b)>-1,dt=St.indexOf(b)>-1;!Vr&&dt&&(Qt=\"italic \"+Qt),Vr&&!dt&&(Qt=Qt.replace(\"italic \",\"\"))}G.font=Qt}for(Pe=0;Pe<me;++Pe){var Gt=Ce[Pe]+`\n",
+       "`;for(Re=0,ce=Pe*ie,Ze=H,pt=\"\",ge=0;ge<Gt.length;++ge){var Nt=ge+ut<_e.length?_e[ge+ut]:_e[_e.length-1];re===Nt?pt+=Gt[ge]:(Zt(),pt=Gt[ge],Nt!==void 0&&(lt(re,Nt),re=Nt))}Zt(),ut+=Gt.length;var Jt=Math.round(Re+2*Se)|0;Ae<Jt&&(Ae=Jt)}var sr=Ae,wr=Le+ie*me,cr=l(G.getImageData(0,0,sr,wr).data,[wr,sr,4]);return cr.pick(-1,-1,0).transpose(1,0)}function P(V,G){var Z=s(V,128);return G?u(Z.cells,Z.positions,.25):{edges:Z.cells,positions:Z.positions}}function T(V,G,Z,H){var N=P(V,H),j=M(N.positions,G,Z),re=N.edges,oe=G.orientation===\"ccw\";if(c(j,re),G.polygons||G.polygon||G.polyline){for(var _e=h(re,j),Ee=new Array(_e.length),Ce=0;Ce<_e.length;++Ce){for(var me=_e[Ce],ie=new Array(me.length),Se=0;Se<me.length;++Se){for(var Le=me[Se],Ae=new Array(Le.length),Fe=0;Fe<Le.length;++Fe)Ae[Fe]=j[Le[Fe]].slice();oe&&Ae.reverse(),ie[Se]=Ae}Ee[Ce]=ie}return Ee}else return G.triangles||G.triangulate||G.triangle?{cells:f(j,re,{delaunay:!1,exterior:!1,interior:!0}),positions:j}:{edges:re,positions:j}}function z(V,G,Z){try{return T(V,G,Z,!0)}catch(H){}try{return T(V,G,Z,!1)}catch(H){}return G.polygons||G.polyline||G.polygon?[]:G.triangles||G.triangulate||G.triangle?{cells:[],positions:[]}:{edges:[],positions:[]}}function O(V,G,Z,H){var N=64,j=1.25,re={breaklines:!1,bolds:!1,italics:!1,subscripts:!1,superscripts:!1};H&&(H.size&&H.size>0&&(N=H.size),H.lineSpacing&&H.lineSpacing>0&&(j=H.lineSpacing),H.styletags&&H.styletags.breaklines&&(re.breaklines=!!H.styletags.breaklines),H.styletags&&H.styletags.bolds&&(re.bolds=!!H.styletags.bolds),H.styletags&&H.styletags.italics&&(re.italics=!!H.styletags.italics),H.styletags&&H.styletags.subscripts&&(re.subscripts=!!H.styletags.subscripts),H.styletags&&H.styletags.superscripts&&(re.superscripts=!!H.styletags.superscripts)),Z.font=[H.fontStyle,H.fontVariant,H.fontWeight,N+\"px\",H.font].filter(function(_e){return _e}).join(\" \"),Z.textAlign=\"start\",Z.textBaseline=\"alphabetic\",Z.direction=\"ltr\";var oe=g(G,Z,V,N,j,re);return z(oe,H,N)}},7721:function(i,a,o){\"use strict\";var s=o(5716);i.exports=l;function l(u){return s(u[0])*s(u[1])}},7765:function(i,a,o){\"use strict\";i.exports=p;var s=o(9618),l=o(1888),u=o(446),c=o(1570);function f(k){for(var E=k.length,S=0,L=0;L<E;++L)S=Math.max(S,k[L].length)|0;return S-1}function h(k,E){for(var S=k.length,L=l.mallocUint8(S),x=0;x<S;++x)L[x]=k[x]<E|0;return L}function d(k,E){for(var S=k.length,L=E*(E+1)/2*S|0,x=l.mallocUint32(L*2),C=0,M=0;M<S;++M)for(var g=k[M],E=g.length,P=0;P<E;++P)for(var T=0;T<P;++T){var z=g[T],O=g[P];x[C++]=Math.min(z,O)|0,x[C++]=Math.max(z,O)|0}var V=C/2|0;u(s(x,[V,2]));for(var G=2,M=2;M<C;M+=2)x[M-2]===x[M]&&x[M-1]===x[M+1]||(x[G++]=x[M],x[G++]=x[M+1]);return s(x,[G/2|0,2])}function v(k,E,S,L){for(var x=k.data,C=k.shape[0],M=l.mallocDouble(C),g=0,P=0;P<C;++P){var T=x[2*P],z=x[2*P+1];if(S[T]!==S[z]){var O=E[T],V=E[z];x[2*g]=T,x[2*g+1]=z,M[g++]=(V-L)/(V-O)}}return k.shape[0]=g,s(M,[g])}function _(k,E){var S=l.mallocInt32(E*2),L=k.shape[0],x=k.data;S[0]=0;for(var C=0,M=0;M<L;++M){var g=x[2*M];if(g!==C){for(S[2*C+1]=M;++C<g;)S[2*C]=M,S[2*C+1]=M;S[2*C]=M}}for(S[2*C+1]=L;++C<E;)S[2*C]=S[2*C+1]=L;return S}function b(k){for(var E=k.shape[0]|0,S=k.data,L=new Array(E),x=0;x<E;++x)L[x]=[S[2*x],S[2*x+1]];return L}function p(k,E,S,L){S=S||0,typeof L==\"undefined\"&&(L=f(k));var x=k.length;if(x===0||L<1)return{cells:[],vertexIds:[],vertexWeights:[]};var C=h(E,+S),M=d(k,L),g=v(M,E,C,+S),P=_(M,E.length|0),T=c(L)(k,M.data,P,C),z=b(M),O=[].slice.call(g.data,0,g.shape[0]);return l.free(C),l.free(M.data),l.free(g.data),l.free(P),{cells:T,vertexIds:z,vertexWeights:O}}},7766:function(i,a,o){\"use strict\";var s=o(9618),l=o(5298),u=o(1888);i.exports=g;var c=null,f=null,h=null;function d(P){c=[P.LINEAR,P.NEAREST_MIPMAP_LINEAR,P.LINEAR_MIPMAP_NEAREST,P.LINEAR_MIPMAP_NEAREST],f=[P.NEAREST,P.LINEAR,P.NEAREST_MIPMAP_NEAREST,P.NEAREST_MIPMAP_LINEAR,P.LINEAR_MIPMAP_NEAREST,P.LINEAR_MIPMAP_LINEAR],h=[P.REPEAT,P.CLAMP_TO_EDGE,P.MIRRORED_REPEAT]}function v(P){return typeof HTMLCanvasElement!=\"undefined\"&&P instanceof HTMLCanvasElement||typeof HTMLImageElement!=\"undefined\"&&P instanceof HTMLImageElement||typeof HTMLVideoElement!=\"undefined\"&&P instanceof HTMLVideoElement||typeof ImageData!=\"undefined\"&&P instanceof ImageData}var _=function(P,T){l.muls(P,T,255)};function b(P,T,z){var O=P.gl,V=O.getParameter(O.MAX_TEXTURE_SIZE);if(T<0||T>V||z<0||z>V)throw new Error(\"gl-texture2d: Invalid texture size\");return P._shape=[T,z],P.bind(),O.texImage2D(O.TEXTURE_2D,0,P.format,T,z,0,P.format,P.type,null),P._mipLevels=[0],P}function p(P,T,z,O,V,G){this.gl=P,this.handle=T,this.format=V,this.type=G,this._shape=[z,O],this._mipLevels=[0],this._magFilter=P.NEAREST,this._minFilter=P.NEAREST,this._wrapS=P.CLAMP_TO_EDGE,this._wrapT=P.CLAMP_TO_EDGE,this._anisoSamples=1;var Z=this,H=[this._wrapS,this._wrapT];Object.defineProperties(H,[{get:function(){return Z._wrapS},set:function(j){return Z.wrapS=j}},{get:function(){return Z._wrapT},set:function(j){return Z.wrapT=j}}]),this._wrapVector=H;var N=[this._shape[0],this._shape[1]];Object.defineProperties(N,[{get:function(){return Z._shape[0]},set:function(j){return Z.width=j}},{get:function(){return Z._shape[1]},set:function(j){return Z.height=j}}]),this._shapeVector=N}var k=p.prototype;Object.defineProperties(k,{minFilter:{get:function(){return this._minFilter},set:function(P){this.bind();var T=this.gl;if(this.type===T.FLOAT&&c.indexOf(P)>=0&&(T.getExtension(\"OES_texture_float_linear\")||(P=T.NEAREST)),f.indexOf(P)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+P);return T.texParameteri(T.TEXTURE_2D,T.TEXTURE_MIN_FILTER,P),this._minFilter=P}},magFilter:{get:function(){return this._magFilter},set:function(P){this.bind();var T=this.gl;if(this.type===T.FLOAT&&c.indexOf(P)>=0&&(T.getExtension(\"OES_texture_float_linear\")||(P=T.NEAREST)),f.indexOf(P)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+P);return T.texParameteri(T.TEXTURE_2D,T.TEXTURE_MAG_FILTER,P),this._magFilter=P}},mipSamples:{get:function(){return this._anisoSamples},set:function(P){var T=this._anisoSamples;if(this._anisoSamples=Math.max(P,1)|0,T!==this._anisoSamples){var z=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");z&&this.gl.texParameterf(this.gl.TEXTURE_2D,z.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(P){if(this.bind(),h.indexOf(P)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+P);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,P),this._wrapS=P}},wrapT:{get:function(){return this._wrapT},set:function(P){if(this.bind(),h.indexOf(P)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+P);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,P),this._wrapT=P}},wrap:{get:function(){return this._wrapVector},set:function(P){if(Array.isArray(P)||(P=[P,P]),P.length!==2)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var T=0;T<2;++T)if(h.indexOf(P[T])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+P);this._wrapS=P[0],this._wrapT=P[1];var z=this.gl;return this.bind(),z.texParameteri(z.TEXTURE_2D,z.TEXTURE_WRAP_S,this._wrapS),z.texParameteri(z.TEXTURE_2D,z.TEXTURE_WRAP_T,this._wrapT),P}},shape:{get:function(){return this._shapeVector},set:function(P){if(!Array.isArray(P))P=[P|0,P|0];else if(P.length!==2)throw new Error(\"gl-texture2d: Invalid texture shape\");return b(this,P[0]|0,P[1]|0),[P[0]|0,P[1]|0]}},width:{get:function(){return this._shape[0]},set:function(P){return P=P|0,b(this,P,this._shape[1]),P}},height:{get:function(){return this._shape[1]},set:function(P){return P=P|0,b(this,this._shape[0],P),P}}}),k.bind=function(P){var T=this.gl;return P!==void 0&&T.activeTexture(T.TEXTURE0+(P|0)),T.bindTexture(T.TEXTURE_2D,this.handle),P!==void 0?P|0:T.getParameter(T.ACTIVE_TEXTURE)-T.TEXTURE0},k.dispose=function(){this.gl.deleteTexture(this.handle)},k.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var P=Math.min(this._shape[0],this._shape[1]),T=0;P>0;++T,P>>>=1)this._mipLevels.indexOf(T)<0&&this._mipLevels.push(T)},k.setPixels=function(P,T,z,O){var V=this.gl;this.bind(),Array.isArray(T)?(O=z,z=T[1]|0,T=T[0]|0):(T=T||0,z=z||0),O=O||0;var G=v(P)?P:P.raw;if(G){var Z=this._mipLevels.indexOf(O)<0;Z?(V.texImage2D(V.TEXTURE_2D,0,this.format,this.format,this.type,G),this._mipLevels.push(O)):V.texSubImage2D(V.TEXTURE_2D,O,T,z,this.format,this.type,G)}else if(P.shape&&P.stride&&P.data){if(P.shape.length<2||T+P.shape[1]>this._shape[1]>>>O||z+P.shape[0]>this._shape[0]>>>O||T<0||z<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");S(V,T,z,O,this.format,this.type,this._mipLevels,P)}else throw new Error(\"gl-texture2d: Unsupported data type\")};function E(P,T){return P.length===3?T[2]===1&&T[1]===P[0]*P[2]&&T[0]===P[2]:T[0]===1&&T[1]===P[0]}function S(P,T,z,O,V,G,Z,H){var N=H.dtype,j=H.shape.slice();if(j.length<2||j.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var re=0,oe=0,_e=E(j,H.stride.slice());N===\"float32\"?re=P.FLOAT:N===\"float64\"?(re=P.FLOAT,_e=!1,N=\"float32\"):N===\"uint8\"?re=P.UNSIGNED_BYTE:(re=P.UNSIGNED_BYTE,_e=!1,N=\"uint8\");var Ee=1;if(j.length===2)oe=P.LUMINANCE,j=[j[0],j[1],1],H=s(H.data,j,[H.stride[0],H.stride[1],1],H.offset);else if(j.length===3){if(j[2]===1)oe=P.ALPHA;else if(j[2]===2)oe=P.LUMINANCE_ALPHA;else if(j[2]===3)oe=P.RGB;else if(j[2]===4)oe=P.RGBA;else throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");Ee=j[2]}else throw new Error(\"gl-texture2d: Invalid shape for texture\");if((oe===P.LUMINANCE||oe===P.ALPHA)&&(V===P.LUMINANCE||V===P.ALPHA)&&(oe=V),oe!==V)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var Ce=H.size,me=Z.indexOf(O)<0;if(me&&Z.push(O),re===G&&_e)H.offset===0&&H.data.length===Ce?me?P.texImage2D(P.TEXTURE_2D,O,V,j[0],j[1],0,V,G,H.data):P.texSubImage2D(P.TEXTURE_2D,O,T,z,j[0],j[1],V,G,H.data):me?P.texImage2D(P.TEXTURE_2D,O,V,j[0],j[1],0,V,G,H.data.subarray(H.offset,H.offset+Ce)):P.texSubImage2D(P.TEXTURE_2D,O,T,z,j[0],j[1],V,G,H.data.subarray(H.offset,H.offset+Ce));else{var ie;G===P.FLOAT?ie=u.mallocFloat32(Ce):ie=u.mallocUint8(Ce);var Se=s(ie,j,[j[2],j[2]*j[0],1]);re===P.FLOAT&&G===P.UNSIGNED_BYTE?_(Se,H):l.assign(Se,H),me?P.texImage2D(P.TEXTURE_2D,O,V,j[0],j[1],0,V,G,ie.subarray(0,Ce)):P.texSubImage2D(P.TEXTURE_2D,O,T,z,j[0],j[1],V,G,ie.subarray(0,Ce)),G===P.FLOAT?u.freeFloat32(ie):u.freeUint8(ie)}}function L(P){var T=P.createTexture();return P.bindTexture(P.TEXTURE_2D,T),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),T}function x(P,T,z,O,V){var G=P.getParameter(P.MAX_TEXTURE_SIZE);if(T<0||T>G||z<0||z>G)throw new Error(\"gl-texture2d: Invalid texture shape\");if(V===P.FLOAT&&!P.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var Z=L(P);return P.texImage2D(P.TEXTURE_2D,0,O,T,z,0,O,V,null),new p(P,Z,T,z,O,V)}function C(P,T,z,O,V,G){var Z=L(P);return P.texImage2D(P.TEXTURE_2D,0,V,V,G,T),new p(P,Z,z,O,V,G)}function M(P,T){var z=T.dtype,O=T.shape.slice(),V=P.getParameter(P.MAX_TEXTURE_SIZE);if(O[0]<0||O[0]>V||O[1]<0||O[1]>V)throw new Error(\"gl-texture2d: Invalid texture size\");var G=E(O,T.stride.slice()),Z=0;z===\"float32\"?Z=P.FLOAT:z===\"float64\"?(Z=P.FLOAT,G=!1,z=\"float32\"):z===\"uint8\"?Z=P.UNSIGNED_BYTE:(Z=P.UNSIGNED_BYTE,G=!1,z=\"uint8\");var H=0;if(O.length===2)H=P.LUMINANCE,O=[O[0],O[1],1],T=s(T.data,O,[T.stride[0],T.stride[1],1],T.offset);else if(O.length===3)if(O[2]===1)H=P.ALPHA;else if(O[2]===2)H=P.LUMINANCE_ALPHA;else if(O[2]===3)H=P.RGB;else if(O[2]===4)H=P.RGBA;else throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");else throw new Error(\"gl-texture2d: Invalid shape for texture\");Z===P.FLOAT&&!P.getExtension(\"OES_texture_float\")&&(Z=P.UNSIGNED_BYTE,G=!1);var N,j,re=T.size;if(G)T.offset===0&&T.data.length===re?N=T.data:N=T.data.subarray(T.offset,T.offset+re);else{var oe=[O[2],O[2]*O[0],1];j=u.malloc(re,z);var _e=s(j,O,oe,0);(z===\"float32\"||z===\"float64\")&&Z===P.UNSIGNED_BYTE?_(_e,T):l.assign(_e,T),N=j.subarray(0,re)}var Ee=L(P);return P.texImage2D(P.TEXTURE_2D,0,H,O[0],O[1],0,H,Z,N),G||u.free(j),new p(P,Ee,O[0],O[1],H,Z)}function g(P){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(c||d(P),typeof arguments[1]==\"number\")return x(P,arguments[1],arguments[2],arguments[3]||P.RGBA,arguments[4]||P.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return x(P,arguments[1][0]|0,arguments[1][1]|0,arguments[2]||P.RGBA,arguments[3]||P.UNSIGNED_BYTE);if(typeof arguments[1]==\"object\"){var T=arguments[1],z=v(T)?T:T.raw;if(z)return C(P,z,T.width|0,T.height|0,arguments[2]||P.RGBA,arguments[3]||P.UNSIGNED_BYTE);if(T.shape&&T.data&&T.stride)return M(P,T)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")}},7790:function(){},7815:function(i,a,o){\"use strict\";var s=o(2931),l=o(9970),u=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],c=function(S,L,x,C){for(var M=S.points,g=S.velocities,P=S.divergences,T=[],z=[],O=[],V=[],G=[],Z=[],H=0,N=0,j=l.create(),re=l.create(),oe=8,_e=0;_e<M.length;_e++){var Ee=M[_e],Ce=g[_e],me=P[_e];L===0&&(me=x*.05),N=s.length(Ce)/C,j=l.create(),s.copy(j,Ce),j[3]=me;for(var ie=0;ie<oe;ie++)G[ie]=[Ee[0],Ee[1],Ee[2],ie];if(V.length>0)for(var ie=0;ie<oe;ie++){var Se=(ie+1)%oe;T.push(V[ie],G[ie],G[Se],G[Se],V[Se],V[ie]),O.push(re,j,j,j,re,re),Z.push(H,N,N,N,H,H);var Le=T.length;z.push([Le-6,Le-5,Le-4],[Le-3,Le-2,Le-1])}var Ae=V;V=G,G=Ae;var Fe=re;re=j,j=Fe;var Pe=H;H=N,N=Pe}return{positions:T,cells:z,vectors:O,vertexIntensity:Z}},f=function(S,L,x,C){for(var M=0,g=0;g<S.length;g++)for(var P=S[g].velocities,T=0;T<P.length;T++)M=Math.max(M,s.length(P[T]));for(var z=S.map(function(_e){return c(_e,x,C,M)}),O=[],V=[],G=[],Z=[],g=0;g<z.length;g++){var H=z[g],N=O.length;O=O.concat(H.positions),G=G.concat(H.vectors),Z=Z.concat(H.vertexIntensity);for(var T=0;T<H.cells.length;T++){var j=H.cells[T],re=[];V.push(re);for(var oe=0;oe<j.length;oe++)re.push(j[oe]+N)}}return{positions:O,cells:V,vectors:G,vertexIntensity:Z,colormap:L}},h=function(S,L){var x=S.length,C;for(C=0;C<x;C++){var M=S[C];if(M===L)return C;if(M>L)return C-1}return C},d=function(S,L,x){return S<L?L:S>x?x:S},v=function(S,L,x){var C=L.vectors,M=L.meshgrid,g=S[0],P=S[1],T=S[2],z=M[0].length,O=M[1].length,V=M[2].length,G=h(M[0],g),Z=h(M[1],P),H=h(M[2],T),N=G+1,j=Z+1,re=H+1;if(G=d(G,0,z-1),N=d(N,0,z-1),Z=d(Z,0,O-1),j=d(j,0,O-1),H=d(H,0,V-1),re=d(re,0,V-1),G<0||Z<0||H<0||N>z-1||j>O-1||re>V-1)return s.create();var oe=M[0][G],_e=M[0][N],Ee=M[1][Z],Ce=M[1][j],me=M[2][H],ie=M[2][re],Se=(g-oe)/(_e-oe),Le=(P-Ee)/(Ce-Ee),Ae=(T-me)/(ie-me);isFinite(Se)||(Se=.5),isFinite(Le)||(Le=.5),isFinite(Ae)||(Ae=.5);var Fe,Pe,ge,Re,ce,Ze;switch(x.reversedX&&(G=z-1-G,N=z-1-N),x.reversedY&&(Z=O-1-Z,j=O-1-j),x.reversedZ&&(H=V-1-H,re=V-1-re),x.filled){case 5:ce=H,Ze=re,ge=Z*V,Re=j*V,Fe=G*V*O,Pe=N*V*O;break;case 4:ce=H,Ze=re,Fe=G*V,Pe=N*V,ge=Z*V*z,Re=j*V*z;break;case 3:ge=Z,Re=j,ce=H*O,Ze=re*O,Fe=G*O*V,Pe=N*O*V;break;case 2:ge=Z,Re=j,Fe=G*O,Pe=N*O,ce=H*O*z,Ze=re*O*z;break;case 1:Fe=G,Pe=N,ce=H*z,Ze=re*z,ge=Z*z*V,Re=j*z*V;break;default:Fe=G,Pe=N,ge=Z*z,Re=j*z,ce=H*z*O,Ze=re*z*O;break}var ut=C[Fe+ge+ce],pt=C[Fe+ge+Ze],Zt=C[Fe+Re+ce],st=C[Fe+Re+Ze],lt=C[Pe+ge+ce],Gt=C[Pe+ge+Ze],Nt=C[Pe+Re+ce],Jt=C[Pe+Re+Ze],sr=s.create(),wr=s.create(),cr=s.create(),$e=s.create();s.lerp(sr,ut,lt,Se),s.lerp(wr,pt,Gt,Se),s.lerp(cr,Zt,Nt,Se),s.lerp($e,st,Jt,Se);var St=s.create(),Qt=s.create();s.lerp(St,sr,cr,Le),s.lerp(Qt,wr,$e,Le);var Vt=s.create();return s.lerp(Vt,St,Qt,Ae),Vt},_=function(S,L){var x=L[0],C=L[1],M=L[2];return S[0]=x<0?-x:x,S[1]=C<0?-C:C,S[2]=M<0?-M:M,S},b=function(S){var L=1/0;S.sort(function(g,P){return 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pt=Ae.uniforms;pt.model=ge.model||_,pt.view=ge.view||_,pt.projection=ge.projection||_,P[0]=2/ut.drawingBufferWidth,P[1]=2/ut.drawingBufferHeight,pt.screenSize=P,pt.highlightId=Pe.highlightId,pt.highlightScale=Pe.highlightScale,pt.fragClipBounds=me,pt.clipBounds=Pe.axes.bounds,pt.opacity=Pe.opacity,pt.pickGroup=Pe.pickId/255,pt.pixelRatio=Re,Pe.vao.bind(),Pe.vao.draw(ut.TRIANGLES,Pe.vertexCount),Pe.lineWidth>0&&(ut.lineWidth(Pe.lineWidth*Re),Pe.vao.draw(ut.LINES,Pe.lineVertexCount,Pe.vertexCount)),Pe.vao.unbind()}}g.draw=function(Ae){var Fe=this.useOrtho?this.orthoShader:this.shader;ie(Fe,this.projectShader,this,Ae,this.pixelRatio,!1,!1)},g.drawTransparent=function(Ae){var Fe=this.useOrtho?this.orthoShader:this.shader;ie(Fe,this.projectShader,this,Ae,this.pixelRatio,!0,!1)},g.drawPick=function(Ae){var Fe=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;ie(Fe,this.pickProjectShader,this,Ae,1,!0,!0)},g.pick=function(Ae){if(!Ae||Ae.id!==this.pickId)return null;var Fe=Ae.value[2]+(Ae.value[1]<<8)+(Ae.value[0]<<16);if(Fe>=this.pointCount||Fe<0)return null;var Pe=this.points[Fe],ge=this._selectResult;ge.index=Fe;for(var Re=0;Re<3;++Re)ge.position[Re]=ge.dataCoordinate[Re]=Pe[Re];return ge},g.highlight=function(Ae){if(!Ae)this.highlightId=[1,1,1,1];else{var Fe=Ae.index,Pe=Fe&255,ge=Fe>>8&255,Re=Fe>>16&255;this.highlightId=[Pe/255,ge/255,Re/255,0]}};function Se(Ae,Fe,Pe,ge){var Re;E(Ae)?Fe<Ae.length?Re=Ae[Fe]:Re=void 0:Re=Ae,Re=v(Re);var ce=!0;s(Re)&&(Re=\"\\u25BC\",ce=!1),Pe||(Pe={});var Ze=Pe.family;E(Ze)&&(Ze=Ze[Fe]),Ze||(Ze=\"normal\");var ut=Pe.weight;E(ut)&&(ut=ut[Fe]),ut||(ut=\"normal\");var pt=Pe.style;E(pt)&&(pt=pt[Fe]),pt||(pt=\"normal\");var Zt=Pe.variant;E(Zt)&&(Zt=Zt[Fe]),Zt||(Zt=\"normal\");var st=d(Re,{family:Ze,weight:ut,style:pt,variant:Zt},ge),st=d(Re,Pe,ge);return{mesh:st[0],lines:st[1],bounds:st[2],visible:ce}}g.update=function(Ae){if(Ae=Ae||{},\"perspective\"in Ae&&(this.useOrtho=!Ae.perspective),\"orthographic\"in Ae&&(this.useOrtho=!!Ae.orthographic),\"lineWidth\"in Ae&&(this.lineWidth=Ae.lineWidth),\"project\"in Ae)if(E(Ae.project))this.axesProject=Ae.project;else{var Fe=!!Ae.project;this.axesProject=[Fe,Fe,Fe]}if(\"projectScale\"in Ae)if(E(Ae.projectScale))this.projectScale=Ae.projectScale.slice();else{var Pe=+Ae.projectScale;this.projectScale=[Pe,Pe,Pe]}if(this.projectHasAlpha=!1,\"projectOpacity\"in Ae){if(E(Ae.projectOpacity))this.projectOpacity=Ae.projectOpacity.slice();else{var Pe=+Ae.projectOpacity;this.projectOpacity=[Pe,Pe,Pe]}for(var ge=0;ge<3;++ge)this.projectOpacity[ge]=C(this.projectOpacity[ge]),this.projectOpacity[ge]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in Ae&&(this.opacity=C(Ae.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var Re=Ae.position,ce={family:Ae.font||\"normal\",style:Ae.fontStyle||\"normal\",weight:Ae.fontWeight||\"normal\",variant:Ae.fontVariant||\"normal\"},Ze=Ae.alignment||[0,0],ut,pt;if(Ze.length===2)ut=Ze[0],pt=Ze[1];else{ut=[],pt=[];for(var ge=0;ge<Ze.length;++ge)ut[ge]=Ze[ge][0],pt[ge]=Ze[ge][1]}var Zt=[1/0,1/0,1/0],st=[-1/0,-1/0,-1/0],lt=Ae.glyph,Gt=Ae.color,Nt=Ae.size,Jt=Ae.angle,sr=Ae.lineColor,wr=-1,cr=0,$e=0,St=0;if(Re.length){St=Re.length;e:for(var ge=0;ge<St;++ge){for(var Qt=Re[ge],Vt=0;Vt<3;++Vt)if(isNaN(Qt[Vt])||!isFinite(Qt[Vt]))continue e;var _t=Se(lt,ge,ce,this.pixelRatio),It=_t.mesh,mt=_t.lines,er=_t.bounds;cr+=It.cells.length*3,$e+=mt.edges.length*2}}var lr=cr+$e,Tr=c.mallocFloat(3*lr),Lr=c.mallocFloat(4*lr),ti=c.mallocFloat(2*lr),Br=c.mallocUint32(lr);if(lr>0){var Vr=0,dt=cr,Ge=[0,0,0,1],Je=[0,0,0,1],je=E(Gt)&&E(Gt[0]),tt=E(sr)&&E(sr[0]);e:for(var ge=0;ge<St;++ge){wr+=1;for(var Qt=Re[ge],Vt=0;Vt<3;++Vt){if(isNaN(Qt[Vt])||!isFinite(Qt[Vt]))continue e;st[Vt]=Math.max(st[Vt],Qt[Vt]),Zt[Vt]=Math.min(Zt[Vt],Qt[Vt])}var _t=Se(lt,ge,ce,this.pixelRatio),It=_t.mesh,mt=_t.lines,er=_t.bounds,xt=_t.visible;if(!xt)Ge=[1,1,1,0];else if(E(Gt)){var Ie;if(je?ge<Gt.length?Ie=Gt[ge]:Ie=[0,0,0,0]:Ie=Gt,Ie.length===3){for(var Vt=0;Vt<3;++Vt)Ge[Vt]=Ie[Vt];Ge[3]=1}else if(Ie.length===4){for(var Vt=0;Vt<4;++Vt)Ge[Vt]=Ie[Vt];!this.hasAlpha&&Ie[3]<1&&(this.hasAlpha=!0)}}else Ge[0]=Ge[1]=Ge[2]=0,Ge[3]=1;if(!xt)Je=[1,1,1,0];else if(E(sr)){var Ie;if(tt?ge<sr.length?Ie=sr[ge]:Ie=[0,0,0,0]:Ie=sr,Ie.length===3){for(var Vt=0;Vt<3;++Vt)Je[Vt]=Ie[Vt];Je[Vt]=1}else if(Ie.length===4){for(var Vt=0;Vt<4;++Vt)Je[Vt]=Ie[Vt];!this.hasAlpha&&Ie[3]<1&&(this.hasAlpha=!0)}}else Je[0]=Je[1]=Je[2]=0,Je[3]=1;var xe=.5;xt?E(Nt)?ge<Nt.length?xe=+Nt[ge]:xe=12:Nt?xe=+Nt:this.useOrtho&&(xe=12):xe=0;var ke=0;E(Jt)?ge<Jt.length?ke=+Jt[ge]:ke=0:Jt&&(ke=+Jt);for(var vt=Math.cos(ke),ir=Math.sin(ke),Qt=Re[ge],Vt=0;Vt<3;++Vt)st[Vt]=Math.max(st[Vt],Qt[Vt]),Zt[Vt]=Math.min(Zt[Vt],Qt[Vt]);var ar=ut,vr=pt,ar=0;E(ut)?ge<ut.length?ar=ut[ge]:ar=0:ut&&(ar=ut);var vr=0;E(pt)?ge<pt.length?vr=pt[ge]:vr=0:pt&&(vr=pt),ar*=ar>0?1-er[0][0]:ar<0?1+er[1][0]:1,vr*=vr>0?1-er[0][1]:vr<0?1+er[1][1]:1;for(var ii=[ar,vr],In=It.cells||[],wi=It.positions||[],Vt=0;Vt<In.length;++Vt)for(var pi=In[Vt],$r=0;$r<3;++$r){for(var di=0;di<3;++di)Tr[3*Vr+di]=Qt[di];for(var di=0;di<4;++di)Lr[4*Vr+di]=Ge[di];Br[Vr]=wr;var ji=wi[pi[$r]];ti[2*Vr]=xe*(vt*ji[0]-ir*ji[1]+ii[0]),ti[2*Vr+1]=xe*(ir*ji[0]+vt*ji[1]+ii[1]),Vr+=1}for(var In=mt.edges,wi=mt.positions,Vt=0;Vt<In.length;++Vt)for(var pi=In[Vt],$r=0;$r<2;++$r){for(var di=0;di<3;++di)Tr[3*dt+di]=Qt[di];for(var di=0;di<4;++di)Lr[4*dt+di]=Je[di];Br[dt]=wr;var ji=wi[pi[$r]];ti[2*dt]=xe*(vt*ji[0]-ir*ji[1]+ii[0]),ti[2*dt+1]=xe*(ir*ji[0]+vt*ji[1]+ii[1]),dt+=1}}}this.bounds=[Zt,st],this.points=Re,this.pointCount=Re.length,this.vertexCount=cr,this.lineVertexCount=$e,this.pointBuffer.update(Tr),this.colorBuffer.update(Lr),this.glyphBuffer.update(ti),this.idBuffer.update(Br),c.free(Tr),c.free(Lr),c.free(ti),c.free(Br)},g.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()};function Le(Ae){var Fe=Ae.gl,Pe=h.createPerspective(Fe),ge=h.createOrtho(Fe),Re=h.createProject(Fe),ce=h.createPickPerspective(Fe),Ze=h.createPickOrtho(Fe),ut=h.createPickProject(Fe),pt=l(Fe),Zt=l(Fe),st=l(Fe),lt=l(Fe),Gt=u(Fe,[{buffer:pt,size:3,type:Fe.FLOAT},{buffer:Zt,size:4,type:Fe.FLOAT},{buffer:st,size:2,type:Fe.FLOAT},{buffer:lt,size:4,type:Fe.UNSIGNED_BYTE,normalized:!0}]),Nt=new M(Fe,Pe,ge,Re,pt,Zt,st,lt,Gt,ce,Ze,ut);return Nt.update(Ae),Nt}},8489:function(i){i.exports=a;function a(o,s,l,u){return o[0]=s[0]+l[0]*u,o[1]=s[1]+l[1]*u,o[2]=s[2]+l[2]*u,o}},8507:function(i){i.exports=s;var a=Math.min;function o(l,u){return l-u}function s(l,u){var c=l.length,f=l.length-u.length;if(f)return f;switch(c){case 0:return 0;case 1:return l[0]-u[0];case 2:return l[0]+l[1]-u[0]-u[1]||a(l[0],l[1])-a(u[0],u[1]);case 3:var h=l[0]+l[1],d=u[0]+u[1];if(f=h+l[2]-(d+u[2]),f)return f;var v=a(l[0],l[1]),_=a(u[0],u[1]);return a(v,l[2])-a(_,u[2])||a(v+l[2],h)-a(_+u[2],d);case 4:var 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k(L,x,C){var M=s.le(L,C,p),g=L[M],P=g.upperIds,T=P[P.length-1];g.upperIds=[T],L.splice(M+1,0,new h(C.a,C.b,C.idx,[T],P))}function E(L,x,C){var M=C.a;C.a=C.b,C.b=M;var g=s.eq(L,C,p),P=L[g],T=L[g-1];T.upperIds=P.upperIds,L.splice(g,1)}function S(L,x){for(var C=L.length,M=x.length,g=[],P=0;P<C;++P)g.push(new d(L[P],null,u,P));for(var P=0;P<M;++P){var T=x[P],z=L[T[0]],O=L[T[1]];z[0]<O[0]?g.push(new d(z,O,f,P),new d(O,z,c,P)):z[0]>O[0]&&g.push(new d(O,z,f,P),new d(z,O,c,P))}g.sort(v);for(var V=g[0].a[0]-(1+Math.abs(g[0].a[0]))*Math.pow(2,-52),G=[new h([V,1],[V,0],-1,[],[],[],[])],Z=[],P=0,H=g.length;P<H;++P){var N=g[P],j=N.type;j===u?b(Z,G,L,N.a,N.idx):j===f?k(G,L,N):E(G,L,N)}return Z}},8954:function(i,a,o){\"use strict\";i.exports=p;var s=o(3250),l=o(6803).Fw;function u(k,E,S){this.vertices=k,this.adjacent=E,this.boundary=S,this.lastVisited=-1}u.prototype.flip=function(){var k=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=k;var E=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=E};function c(k,E,S){this.vertices=k,this.cell=E,this.index=S}function f(k,E){return l(k.vertices,E.vertices)}function h(k){return function(){var E=this.tuple;return k.apply(this,E)}}function d(k){var E=s[k+1];return E||(E=s),h(E)}var v=[];function _(k,E,S){this.dimension=k,this.vertices=E,this.simplices=S,this.interior=S.filter(function(C){return!C.boundary}),this.tuple=new Array(k+1);for(var L=0;L<=k;++L)this.tuple[L]=this.vertices[L];var x=v[k];x||(x=v[k]=d(k)),this.orient=x}var b=_.prototype;b.handleBoundaryDegeneracy=function(k,E){var S=this.dimension,L=this.vertices.length-1,x=this.tuple,C=this.vertices,M=[k];for(k.lastVisited=-L;M.length>0;){k=M.pop();for(var g=k.adjacent,P=0;P<=S;++P){var T=g[P];if(!(!T.boundary||T.lastVisited<=-L)){for(var z=T.vertices,O=0;O<=S;++O){var V=z[O];V<0?x[O]=E:x[O]=C[V]}var G=this.orient();if(G>0)return T;T.lastVisited=-L,G===0&&M.push(T)}}}return null},b.walk=function(k,E){var S=this.vertices.length-1,L=this.dimension,x=this.vertices,C=this.tuple,M=E?this.interior.length*Math.random()|0:this.interior.length-1,g=this.interior[M];e:for(;!g.boundary;){for(var P=g.vertices,T=g.adjacent,z=0;z<=L;++z)C[z]=x[P[z]];g.lastVisited=S;for(var z=0;z<=L;++z){var O=T[z];if(!(O.lastVisited>=S)){var V=C[z];C[z]=k;var G=this.orient();if(C[z]=V,G<0){g=O;continue e}else O.boundary?O.lastVisited=-S:O.lastVisited=S}}return}return g},b.addPeaks=function(k,E){var S=this.vertices.length-1,L=this.dimension,x=this.vertices,C=this.tuple,M=this.interior,g=this.simplices,P=[E];E.lastVisited=S,E.vertices[E.vertices.indexOf(-1)]=S,E.boundary=!1,M.push(E);for(var T=[];P.length>0;){var E=P.pop(),z=E.vertices,O=E.adjacent,V=z.indexOf(S);if(!(V<0)){for(var G=0;G<=L;++G)if(G!==V){var Z=O[G];if(!(!Z.boundary||Z.lastVisited>=S)){var H=Z.vertices;if(Z.lastVisited!==-S){for(var N=0,j=0;j<=L;++j)H[j]<0?(N=j,C[j]=k):C[j]=x[H[j]];var re=this.orient();if(re>0){H[N]=S,Z.boundary=!1,M.push(Z),P.push(Z),Z.lastVisited=S;continue}else Z.lastVisited=-S}var oe=Z.adjacent,_e=z.slice(),Ee=O.slice(),Ce=new u(_e,Ee,!0);g.push(Ce);var me=oe.indexOf(E);if(!(me<0)){oe[me]=Ce,Ee[V]=Z,_e[G]=-1,Ee[G]=E,O[G]=Ce,Ce.flip();for(var j=0;j<=L;++j){var ie=_e[j];if(!(ie<0||ie===S)){for(var Se=new Array(L-1),Le=0,Ae=0;Ae<=L;++Ae){var Fe=_e[Ae];Fe<0||Ae===j||(Se[Le++]=Fe)}T.push(new c(Se,Ce,j))}}}}}}}T.sort(f);for(var G=0;G+1<T.length;G+=2){var Pe=T[G],ge=T[G+1],Re=Pe.index,ce=ge.index;Re<0||ce<0||(Pe.cell.adjacent[Pe.index]=ge.cell,ge.cell.adjacent[ge.index]=Pe.cell)}},b.insert=function(k,E){var S=this.vertices;S.push(k);var L=this.walk(k,E);if(L){for(var x=this.dimension,C=this.tuple,M=0;M<=x;++M){var g=L.vertices[M];g<0?C[M]=k:C[M]=S[g]}var P=this.orient(C);P<0||P===0&&(L=this.handleBoundaryDegeneracy(L,k),!L)||this.addPeaks(k,L)}},b.boundary=function(){for(var k=this.dimension,E=[],S=this.simplices,L=S.length,x=0;x<L;++x){var C=S[x];if(C.boundary){for(var M=new Array(k),g=C.vertices,P=0,T=0,z=0;z<=k;++z)g[z]>=0?M[P++]=g[z]:T=z&1;if(T===(k&1)){var O=M[0];M[0]=M[1],M[1]=O}E.push(M)}}return E};function p(k,E){var S=k.length;if(S===0)throw new Error(\"Must have at least d+1 points\");var L=k[0].length;if(S<=L)throw new Error(\"Must input at least d+1 points\");var x=k.slice(0,L+1),C=s.apply(void 0,x);if(C===0)throw new Error(\"Input not in general position\");for(var M=new Array(L+1),g=0;g<=L;++g)M[g]=g;C<0&&(M[0]=1,M[1]=0);for(var P=new u(M,new Array(L+1),!1),T=P.adjacent,z=new Array(L+2),g=0;g<=L;++g){for(var O=M.slice(),V=0;V<=L;++V)V===g&&(O[V]=-1);var G=O[0];O[0]=O[1],O[1]=G;var Z=new u(O,new Array(L+1),!0);T[g]=Z,z[g]=Z}z[L+1]=P;for(var g=0;g<=L;++g)for(var O=T[g].vertices,H=T[g].adjacent,V=0;V<=L;++V){var N=O[V];if(N<0){H[V]=P;continue}for(var j=0;j<=L;++j)T[j].vertices.indexOf(N)<0&&(H[V]=T[j])}for(var re=new _(L,x,z),oe=!!E,g=L+1;g<S;++g)re.insert(k[g],oe);return re.boundary()}},8987:function(i,a,o){\"use strict\";var s=o(7842),l=o(6504);i.exports=u;function u(c,f){for(var h=s(f),d=c.length,v=new Array(d),_=0;_<d;++_)v[_]=l(c[_],h);return v}},9060:function(i,a,o){\"use strict\";var s=o(9405),l=o(2762),u=o(8116),c=o(7766),f=o(6760),h=o(7608),d=o(9618),v=o(6729),_=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function b(C,M,g,P,T,z,O,V,G,Z,H){this.gl=C,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=M,this.dirty=!0,this.triShader=g,this.pickShader=P,this.trianglePositions=T,this.triangleVectors=z,this.triangleColors=V,this.triangleUVs=G,this.triangleIds=O,this.triangleVAO=Z,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=H,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=_,this._view=_,this._projection=_,this._resolution=[1,1]}var p=b.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(C){this.pickId=C};function k(C){for(var M=v({colormap:C,nshades:256,format:\"rgba\"}),g=new Uint8Array(256*4),P=0;P<256;++P){for(var T=M[P],z=0;z<3;++z)g[4*P+z]=T[z];g[4*P+3]=T[3]*255}return d(g,[256,256,4],[4,0,1])}function E(C){for(var M=C.length,g=new Array(M),P=0;P<M;++P)g[P]=C[P][2];return g}p.update=function(C){C=C||{};var M=this.gl;this.dirty=!0,\"lightPosition\"in C&&(this.lightPosition=C.lightPosition),\"opacity\"in C&&(this.opacity=C.opacity),\"ambient\"in C&&(this.ambientLight=C.ambient),\"diffuse\"in C&&(this.diffuseLight=C.diffuse),\"specular\"in C&&(this.specularLight=C.specular),\"roughness\"in C&&(this.roughness=C.roughness),\"fresnel\"in C&&(this.fresnel=C.fresnel),C.tubeScale!==void 0&&(this.tubeScale=C.tubeScale),C.vectorScale!==void 0&&(this.vectorScale=C.vectorScale),C.coneScale!==void 0&&(this.coneScale=C.coneScale),C.coneOffset!==void 0&&(this.coneOffset=C.coneOffset),C.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=M.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=M.LINEAR,this.texture.setPixels(k(C.colormap)),this.texture.generateMipmap());var g=C.cells,P=C.positions,T=C.vectors;if(!(!P||!g||!T)){var z=[],O=[],V=[],G=[],Z=[];this.cells=g,this.positions=P,this.vectors=T;var H=C.meshColor||[1,1,1,1],N=C.vertexIntensity,j=1/0,re=-1/0;if(N)if(C.vertexIntensityBounds)j=+C.vertexIntensityBounds[0],re=+C.vertexIntensityBounds[1];else for(var oe=0;oe<N.length;++oe){var _e=N[oe];j=Math.min(j,_e),re=Math.max(re,_e)}else for(var oe=0;oe<P.length;++oe){var _e=P[oe][2];j=Math.min(j,_e),re=Math.max(re,_e)}N?this.intensity=N:this.intensity=E(P),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(var oe=0;oe<P.length;++oe)for(var Ee=P[oe],Ce=0;Ce<3;++Ce)isNaN(Ee[Ce])||!isFinite(Ee[Ce])||(this.bounds[0][Ce]=Math.min(this.bounds[0][Ce],Ee[Ce]),this.bounds[1][Ce]=Math.max(this.bounds[1][Ce],Ee[Ce]));var me=0;e:for(var oe=0;oe<g.length;++oe){var ie=g[oe];switch(ie.length){case 3:for(var Ce=0;Ce<3;++Ce)for(var Se=ie[Ce],Ee=P[Se],Le=0;Le<3;++Le)if(isNaN(Ee[Le])||!isFinite(Ee[Le]))continue e;for(var Ce=0;Ce<3;++Ce){var Se=ie[2-Ce],Ee=P[Se];z.push(Ee[0],Ee[1],Ee[2],Ee[3]);var Ae=T[Se];O.push(Ae[0],Ae[1],Ae[2],Ae[3]||0);var Fe=H;Fe.length===3?V.push(Fe[0],Fe[1],Fe[2],1):V.push(Fe[0],Fe[1],Fe[2],Fe[3]);var Pe;N?Pe=[(N[Se]-j)/(re-j),0]:Pe=[(Ee[2]-j)/(re-j),0],G.push(Pe[0],Pe[1]),Z.push(oe)}me+=1;break;default:break}}this.triangleCount=me,this.trianglePositions.update(z),this.triangleVectors.update(O),this.triangleColors.update(V),this.triangleUVs.update(G),this.triangleIds.update(new Uint32Array(Z))}},p.drawTransparent=p.draw=function(C){C=C||{};for(var M=this.gl,g=C.model||_,P=C.view||_,T=C.projection||_,z=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],O=0;O<3;++O)z[0][O]=Math.max(z[0][O],this.clipBounds[0][O]),z[1][O]=Math.min(z[1][O],this.clipBounds[1][O]);var V={model:g,view:P,projection:T,inverseModel:_.slice(),clipBounds:z,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};V.inverseModel=h(V.inverseModel,V.model),M.disable(M.CULL_FACE),this.texture.bind(0);var G=new Array(16);f(G,V.view,V.model),f(G,V.projection,G),h(G,G);for(var O=0;O<3;++O)V.eyePosition[O]=G[12+O]/G[15];for(var Z=G[15],O=0;O<3;++O)Z+=this.lightPosition[O]*G[4*O+3];for(var O=0;O<3;++O){for(var H=G[12+O],N=0;N<3;++N)H+=G[4*N+O]*this.lightPosition[N];V.lightPosition[O]=H/Z}if(this.triangleCount>0){var j=this.triShader;j.bind(),j.uniforms=V,this.triangleVAO.bind(),M.drawArrays(M.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()}},p.drawPick=function(C){C=C||{};for(var M=this.gl,g=C.model||_,P=C.view||_,T=C.projection||_,z=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],O=0;O<3;++O)z[0][O]=Math.max(z[0][O],this.clipBounds[0][O]),z[1][O]=Math.min(z[1][O],this.clipBounds[1][O]);this._model=[].slice.call(g),this._view=[].slice.call(P),this._projection=[].slice.call(T),this._resolution=[M.drawingBufferWidth,M.drawingBufferHeight];var V={model:g,view:P,projection:T,clipBounds:z,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},G=this.pickShader;G.bind(),G.uniforms=V,this.triangleCount>0&&(this.triangleVAO.bind(),M.drawArrays(M.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind())},p.pick=function(C){if(!C||C.id!==this.pickId)return null;var M=C.value[0]+256*C.value[1]+65536*C.value[2],g=this.cells[M],P=this.positions[g[1]].slice(0,3),T={position:P,dataCoordinate:P,index:Math.floor(g[1]/48)};return this.traceType===\"cone\"?T.index=Math.floor(g[1]/48):this.traceType===\"streamtube\"&&(T.intensity=this.intensity[g[1]],T.velocity=this.vectors[g[1]].slice(0,3),T.divergence=this.vectors[g[1]][3],T.index=M),T},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()};function S(C,M){var g=s(C,M.meshShader.vertex,M.meshShader.fragment,null,M.meshShader.attributes);return g.attributes.position.location=0,g.attributes.color.location=2,g.attributes.uv.location=3,g.attributes.vector.location=4,g}function L(C,M){var g=s(C,M.pickShader.vertex,M.pickShader.fragment,null,M.pickShader.attributes);return g.attributes.position.location=0,g.attributes.id.location=1,g.attributes.vector.location=4,g}function x(C,M,g){var P=g.shaders;arguments.length===1&&(M=C,C=M.gl);var T=S(C,P),z=L(C,P),O=c(C,d(new Uint8Array([255,255,255,255]),[1,1,4]));O.generateMipmap(),O.minFilter=C.LINEAR_MIPMAP_LINEAR,O.magFilter=C.LINEAR;var V=l(C),G=l(C),Z=l(C),H=l(C),N=l(C),j=u(C,[{buffer:V,type:C.FLOAT,size:4},{buffer:N,type:C.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:Z,type:C.FLOAT,size:4},{buffer:H,type:C.FLOAT,size:2},{buffer:G,type:C.FLOAT,size:4}]),re=new b(C,O,T,z,V,G,N,Z,H,j,g.traceType||\"cone\");return re.update(M),re}i.exports=x},9127:function(i,a,o){\"use strict\";i.exports=u;var s=o(6204),l=o(5771);function u(c){return l(s(c))}},9131:function(i,a,o){var s=o(5177),l=o(9288);i.exports=u;function u(c,f){return f=f||1,c[0]=Math.random(),c[1]=Math.random(),c[2]=Math.random(),c[3]=Math.random(),s(c,c),l(c,c,f),c}},9165:function(i,a,o){\"use strict\";i.exports=b;var s=o(2762),l=o(8116),u=o(3436),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function f(p,k,E,S){this.gl=p,this.shader=S,this.buffer=k,this.vao=E,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var h=f.prototype;h.isOpaque=function(){return!this.hasAlpha},h.isTransparent=function(){return this.hasAlpha},h.drawTransparent=h.draw=function(p){var k=this.gl,E=this.shader.uniforms;this.shader.bind();var S=E.view=p.view||c,L=E.projection=p.projection||c;E.model=p.model||c,E.clipBounds=this.clipBounds,E.opacity=this.opacity;var x=S[12],C=S[13],M=S[14],g=S[15],P=p._ortho||!1,T=P?2:1,z=T*this.pixelRatio*(L[3]*x+L[7]*C+L[11]*M+L[15]*g)/k.drawingBufferHeight;this.vao.bind();for(var O=0;O<3;++O)k.lineWidth(this.lineWidth[O]*this.pixelRatio),E.capSize=this.capSize[O]*z,this.lineCount[O]&&k.drawArrays(k.LINES,this.lineOffset[O],this.lineCount[O]);this.vao.unbind()};function d(p,k){for(var E=0;E<3;++E)p[0][E]=Math.min(p[0][E],k[E]),p[1][E]=Math.max(p[1][E],k[E])}var v=function(){for(var p=new Array(3),k=0;k<3;++k){for(var E=[],S=1;S<=2;++S)for(var L=-1;L<=1;L+=2){var x=(S+k)%3,C=[0,0,0];C[x]=L,E.push(C)}p[k]=E}return p}();function _(p,k,E,S){for(var L=v[S],x=0;x<L.length;++x){var C=L[x];p.push(k[0],k[1],k[2],E[0],E[1],E[2],E[3],C[0],C[1],C[2])}return L.length}h.update=function(p){p=p||{},\"lineWidth\"in p&&(this.lineWidth=p.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in p&&(this.capSize=p.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),this.hasAlpha=!1,\"opacity\"in p&&(this.opacity=+p.opacity,this.opacity<1&&(this.hasAlpha=!0));var k=p.color||[[0,0,0],[0,0,0],[0,0,0]],E=p.position,S=p.error;if(Array.isArray(k[0])||(k=[k,k,k]),E&&S){var L=[],x=E.length,C=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var M=0;M<3;++M){this.lineOffset[M]=C;e:for(var g=0;g<x;++g){for(var P=E[g],T=0;T<3;++T)if(isNaN(P[T])||!isFinite(P[T]))continue e;var z=S[g],O=k[M];if(Array.isArray(O[0])&&(O=k[g]),O.length===3?O=[O[0],O[1],O[2],1]:O.length===4&&(O=[O[0],O[1],O[2],O[3]],!this.hasAlpha&&O[3]<1&&(this.hasAlpha=!0)),!(isNaN(z[0][M])||isNaN(z[1][M]))){if(z[0][M]<0){var V=P.slice();V[M]+=z[0][M],L.push(P[0],P[1],P[2],O[0],O[1],O[2],O[3],0,0,0,V[0],V[1],V[2],O[0],O[1],O[2],O[3],0,0,0),d(this.bounds,V),C+=2+_(L,V,O,M)}if(z[1][M]>0){var V=P.slice();V[M]+=z[1][M],L.push(P[0],P[1],P[2],O[0],O[1],O[2],O[3],0,0,0,V[0],V[1],V[2],O[0],O[1],O[2],O[3],0,0,0),d(this.bounds,V),C+=2+_(L,V,O,M)}}}this.lineCount[M]=C-this.lineOffset[M]}this.buffer.update(L)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()};function b(p){var k=p.gl,E=s(k),S=l(k,[{buffer:E,type:k.FLOAT,size:3,offset:0,stride:40},{buffer:E,type:k.FLOAT,size:4,offset:12,stride:40},{buffer:E,type:k.FLOAT,size:3,offset:28,stride:40}]),L=u(k);L.attributes.position.location=0,L.attributes.color.location=1,L.attributes.offset.location=2;var x=new f(k,E,S,L);return x.update(p),x}},9215:function(i,a,o){\"use strict\";i.exports=d;var s=o(4769),l=o(2478);function u(v,_,b){return Math.min(_,Math.max(v,b))}function c(v,_,b){this.dimension=v.length,this.bounds=[new Array(this.dimension),new Array(this.dimension)];for(var p=0;p<this.dimension;++p)this.bounds[0][p]=-1/0,this.bounds[1][p]=1/0;this._state=v.slice().reverse(),this._velocity=_.slice().reverse(),this._time=[b],this._scratch=[v.slice(),v.slice(),v.slice(),v.slice(),v.slice()]}var f=c.prototype;f.flush=function(v){var _=l.gt(this._time,v)-1;_<=0||(this._time.splice(0,_),this._state.splice(0,_*this.dimension),this._velocity.splice(0,_*this.dimension))},f.curve=function(v){var _=this._time,b=_.length,p=l.le(_,v),k=this._scratch[0],E=this._state,S=this._velocity,L=this.dimension,x=this.bounds;if(p<0)for(var C=L-1,M=0;M<L;++M,--C)k[M]=E[C];else if(p>=b-1)for(var C=E.length-1,g=v-_[b-1],M=0;M<L;++M,--C)k[M]=E[C]+g*S[C];else{for(var C=L*(p+1)-1,P=_[p],T=_[p+1],z=T-P||1,O=this._scratch[1],V=this._scratch[2],G=this._scratch[3],Z=this._scratch[4],H=!0,M=0;M<L;++M,--C)O[M]=E[C],G[M]=S[C]*z,V[M]=E[C+L],Z[M]=S[C+L]*z,H=H&&O[M]===V[M]&&G[M]===Z[M]&&G[M]===0;if(H)for(var M=0;M<L;++M)k[M]=O[M];else s(O,G,V,Z,(v-P)/z,k)}for(var N=x[0],j=x[1],M=0;M<L;++M)k[M]=u(N[M],j[M],k[M]);return k},f.dcurve=function(v){var _=this._time,b=_.length,p=l.le(_,v),k=this._scratch[0],E=this._state,S=this._velocity,L=this.dimension;if(p>=b-1)for(var x=E.length-1,C=v-_[b-1],M=0;M<L;++M,--x)k[M]=S[x];else{for(var x=L*(p+1)-1,g=_[p],P=_[p+1],T=P-g||1,z=this._scratch[1],O=this._scratch[2],V=this._scratch[3],G=this._scratch[4],Z=!0,M=0;M<L;++M,--x)z[M]=E[x],V[M]=S[x]*T,O[M]=E[x+L],G[M]=S[x+L]*T,Z=Z&&z[M]===O[M]&&V[M]===G[M]&&V[M]===0;if(Z)for(var M=0;M<L;++M)k[M]=0;else{s.derivative(z,V,O,G,(v-g)/T,k);for(var M=0;M<L;++M)k[M]/=T}}return k},f.lastT=function(){var v=this._time;return v[v.length-1]},f.stable=function(){for(var v=this._velocity,_=v.length,b=this.dimension-1;b>=0;--b)if(v[--_])return!1;return!0},f.jump=function(v){var _=this.lastT(),b=this.dimension;if(!(v<_||arguments.length!==b+1)){var p=this._state,k=this._velocity,E=p.length-this.dimension,S=this.bounds,L=S[0],x=S[1];this._time.push(_,v);for(var C=0;C<2;++C)for(var M=0;M<b;++M)p.push(p[E++]),k.push(0);this._time.push(v);for(var M=b;M>0;--M)p.push(u(L[M-1],x[M-1],arguments[M])),k.push(0)}},f.push=function(v){var _=this.lastT(),b=this.dimension;if(!(v<_||arguments.length!==b+1)){var p=this._state,k=this._velocity,E=p.length-this.dimension,S=v-_,L=this.bounds,x=L[0],C=L[1],M=S>1e-6?1/S:0;this._time.push(v);for(var g=b;g>0;--g){var P=u(x[g-1],C[g-1],arguments[g]);p.push(P),k.push((P-p[E++])*M)}}},f.set=function(v){var _=this.dimension;if(!(v<this.lastT()||arguments.length!==_+1)){var b=this._state,p=this._velocity,k=this.bounds,E=k[0],S=k[1];this._time.push(v);for(var L=_;L>0;--L)b.push(u(E[L-1],S[L-1],arguments[L])),p.push(0)}},f.move=function(v){var _=this.lastT(),b=this.dimension;if(!(v<=_||arguments.length!==b+1)){var p=this._state,k=this._velocity,E=p.length-this.dimension,S=this.bounds,L=S[0],x=S[1],C=v-_,M=C>1e-6?1/C:0;this._time.push(v);for(var g=b;g>0;--g){var P=arguments[g];p.push(u(L[g-1],x[g-1],p[E++]+P)),k.push(P*M)}}},f.idle=function(v){var _=this.lastT();if(!(v<_)){var b=this.dimension,p=this._state,k=this._velocity,E=p.length-b,S=this.bounds,L=S[0],x=S[1],C=v-_;this._time.push(v);for(var M=b-1;M>=0;--M)p.push(u(L[M],x[M],p[E]+C*k[E])),k.push(0),E+=1}};function h(v){for(var _=new Array(v),b=0;b<v;++b)_[b]=0;return _}function d(v,_,b){switch(arguments.length){case 0:return new c([0],[0],0);case 1:if(typeof v==\"number\"){var p=h(v);return new c(p,p,0)}else return new c(v,h(v.length),0);case 2:if(typeof _==\"number\"){var p=h(v.length);return new c(v,p,+_)}else b=0;case 3:if(v.length!==_.length)throw new Error(\"state and velocity lengths must match\");return new c(v,_,b)}}},9216:function(i){\"use strict\";i.exports=l,i.exports.isMobile=l,i.exports.default=l;var a=/(android|bb\\d+|meego).+mobile|armv7l|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|samsungbrowser.*mobile|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,o=/CrOS/,s=/android|ipad|playbook|silk/i;function l(u){u||(u={});var c=u.ua;if(!c&&typeof navigator!=\"undefined\"&&(c=navigator.userAgent),c&&c.headers&&typeof c.headers[\"user-agent\"]==\"string\"&&(c=c.headers[\"user-agent\"]),typeof c!=\"string\")return!1;var f=a.test(c)&&!o.test(c)||!!u.tablet&&s.test(c);return!f&&u.tablet&&u.featureDetect&&navigator&&navigator.maxTouchPoints>1&&c.indexOf(\"Macintosh\")!==-1&&c.indexOf(\"Safari\")!==-1&&(f=!0),f}},9226:function(i){i.exports=a;function a(o,s){return o[0]=Math.ceil(s[0]),o[1]=Math.ceil(s[1]),o[2]=Math.ceil(s[2]),o}},9265:function(i){i.exports=a;function a(o,s){return o[0]===s[0]&&o[1]===s[1]&&o[2]===s[2]}},9288:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]*l,o[1]=s[1]*l,o[2]=s[2]*l,o[3]=s[3]*l,o}},9346:function(i){\"use strict\";var a=new Float64Array(4),o=new Float64Array(4),s=new Float64Array(4);function l(u,c,f,h,d){a.length<h.length&&(a=new Float64Array(h.length),o=new Float64Array(h.length),s=new Float64Array(h.length));for(var v=0;v<h.length;++v)a[v]=u[v]-h[v],o[v]=c[v]-u[v],s[v]=f[v]-u[v];for(var _=0,b=0,p=0,k=0,E=0,S=0,v=0;v<h.length;++v){var L=o[v],x=s[v],C=a[v];_+=L*L,b+=L*x,p+=x*x,k+=C*L,E+=C*x,S+=C*C}var M=Math.abs(_*p-b*b),g=b*E-p*k,P=b*k-_*E,T;if(g+P<=M)if(g<0)P<0&&k<0?(P=0,-k>=_?(g=1,T=_+2*k+S):(g=-k/_,T=k*g+S)):(g=0,E>=0?(P=0,T=S):-E>=p?(P=1,T=p+2*E+S):(P=-E/p,T=E*P+S));else if(P<0)P=0,k>=0?(g=0,T=S):-k>=_?(g=1,T=_+2*k+S):(g=-k/_,T=k*g+S);else{var z=1/M;g*=z,P*=z,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S}else{var O,V,G,Z;g<0?(O=b+k,V=p+E,V>O?(G=V-O,Z=_-2*b+p,G>=Z?(g=1,P=0,T=_+2*k+S):(g=G/Z,P=1-g,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)):(g=0,V<=0?(P=1,T=p+2*E+S):E>=0?(P=0,T=S):(P=-E/p,T=E*P+S))):P<0?(O=b+E,V=_+k,V>O?(G=V-O,Z=_-2*b+p,G>=Z?(P=1,g=0,T=p+2*E+S):(P=G/Z,g=1-P,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)):(P=0,V<=0?(g=1,T=_+2*k+S):k>=0?(g=0,T=S):(g=-k/_,T=k*g+S))):(G=p+E-b-k,G<=0?(g=0,P=1,T=p+2*E+S):(Z=_-2*b+p,G>=Z?(g=1,P=0,T=_+2*k+S):(g=G/Z,P=1-g,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)))}for(var H=1-g-P,v=0;v<h.length;++v)d[v]=H*u[v]+g*c[v]+P*f[v];return T<0?0:T}i.exports=l},9362:function(i){\"use strict\";i.exports=a;function a(o,s,l){var u=o+s,c=u-o,f=u-c,h=s-c,d=o-f;return l?(l[0]=d+h,l[1]=u,l):[d+h,u]}},9366:function(i,a,o){\"use strict\";var s=o(4359);i.exports=u;var l={};function u(c,f,h){var d=[f.style,f.weight,f.variant,f.family].join(\"_\"),v=l[d];if(v||(v=l[d]={}),c in v)return v[c];var _={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:f.family,fontStyle:f.style,fontWeight:f.weight,fontVariant:f.variant,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0}};_.triangles=!0;var b=s(c,_);_.triangles=!1;var p=s(c,_),k,E;if(h&&h!==1){for(k=0;k<b.positions.length;++k)for(E=0;E<b.positions[k].length;++E)b.positions[k][E]/=h;for(k=0;k<p.positions.length;++k)for(E=0;E<p.positions[k].length;++E)p.positions[k][E]/=h}var S=[[1/0,1/0],[-1/0,-1/0]],L=p.positions.length;for(k=0;k<L;++k){var x=p.positions[k];for(E=0;E<2;++E)S[0][E]=Math.min(S[0][E],x[E]),S[1][E]=Math.max(S[1][E],x[E])}return v[c]=[b,p,S]}},9405:function(i,a,o){\"use strict\";var s=o(3327),l=o(8731),u=o(216),c=o(5091),f=o(2145),h=o(8866);function d(p){this.gl=p,this.gl.lastAttribCount=0,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}var v=d.prototype;v.bind=function(){this.program||this._relink();var p,k=this.gl.getProgramParameter(this.program,this.gl.ACTIVE_ATTRIBUTES),E=this.gl.lastAttribCount;if(k>E)for(p=E;p<k;p++)this.gl.enableVertexAttribArray(p);else if(E>k)for(p=k;p<E;p++)this.gl.disableVertexAttribArray(p);this.gl.lastAttribCount=k,this.gl.useProgram(this.program)},v.dispose=function(){for(var p=this.gl.lastAttribCount,k=0;k<p;k++)this.gl.disableVertexAttribArray(k);this.gl.lastAttribCount=0,this._fref&&this._fref.dispose(),this._vref&&this._vref.dispose(),this.attributes=this.types=this.vertShader=this.fragShader=this.program=this._relink=this._fref=this._vref=null};function _(p,k){return p.name<k.name?-1:1}v.update=function(p,k,E,S){if(!k||arguments.length===1){var L=p;p=L.vertex,k=L.fragment,E=L.uniforms,S=L.attributes}var x=this,C=x.gl,M=x._vref;x._vref=c.shader(C,C.VERTEX_SHADER,p),M&&M.dispose(),x.vertShader=x._vref.shader;var g=this._fref;if(x._fref=c.shader(C,C.FRAGMENT_SHADER,k),g&&g.dispose(),x.fragShader=x._fref.shader,!E||!S){var P=C.createProgram();if(C.attachShader(P,x.fragShader),C.attachShader(P,x.vertShader),C.linkProgram(P),!C.getProgramParameter(P,C.LINK_STATUS)){var T=C.getProgramInfoLog(P);throw new h(T,\"Error linking program:\"+T)}E=E||f.uniforms(C,P),S=S||f.attributes(C,P),C.deleteProgram(P)}S=S.slice(),S.sort(_);var z=[],O=[],V=[],G;for(G=0;G<S.length;++G){var Z=S[G];if(Z.type.indexOf(\"mat\")>=0){for(var H=Z.type.charAt(Z.type.length-1)|0,N=new Array(H),j=0;j<H;++j)N[j]=V.length,O.push(Z.name+\"[\"+j+\"]\"),typeof Z.location==\"number\"?V.push(Z.location+j):Array.isArray(Z.location)&&Z.location.length===H&&typeof Z.location[j]==\"number\"?V.push(Z.location[j]|0):V.push(-1);z.push({name:Z.name,type:Z.type,locations:N})}else z.push({name:Z.name,type:Z.type,locations:[V.length]}),O.push(Z.name),typeof Z.location==\"number\"?V.push(Z.location|0):V.push(-1)}var re=0;for(G=0;G<V.length;++G)if(V[G]<0){for(;V.indexOf(re)>=0;)re+=1;V[G]=re}var oe=new Array(E.length);function _e(){x.program=c.program(C,x._vref,x._fref,O,V);for(var Ee=0;Ee<E.length;++Ee)oe[Ee]=C.getUniformLocation(x.program,E[Ee].name)}_e(),x._relink=_e,x.types={uniforms:u(E),attributes:u(S)},x.attributes=l(C,x,z,V),Object.defineProperty(x,\"uniforms\",s(C,x,E,oe))};function b(p,k,E,S,L){var x=new d(p);return x.update(k,E,S,L),x}i.exports=b},9499:function(i,a,o){\"use strict\";i.exports=Fe;var s=o(8828),l=o(2762),u=o(8116),c=o(7766),f=o(1888),h=o(6729),d=o(5298),v=o(9994),_=o(9618),b=o(3711),p=o(6760),k=o(7608),E=o(2478),S=o(6199),L=o(990),x=L.createShader,C=L.createContourShader,M=L.createPickShader,g=L.createPickContourShader,P=4*10,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],z=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],O=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];(function(){for(var Pe=0;Pe<3;++Pe){var ge=O[Pe],Re=(Pe+1)%3,ce=(Pe+2)%3;ge[Re+0]=1,ge[ce+3]=1,ge[Pe+6]=1}})();function V(Pe,ge,Re,ce,Ze){this.position=Pe,this.index=ge,this.uv=Re,this.level=ce,this.dataCoordinate=Ze}var G=256;function Z(Pe,ge,Re,ce,Ze,ut,pt,Zt,st,lt,Gt,Nt,Jt,sr,wr){this.gl=Pe,this.shape=ge,this.bounds=Re,this.objectOffset=wr,this.intensityBounds=[],this._shader=ce,this._pickShader=Ze,this._coordinateBuffer=ut,this._vao=pt,this._colorMap=Zt,this._contourShader=st,this._contourPickShader=lt,this._contourBuffer=Gt,this._contourVAO=Nt,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new V([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=Jt,this._dynamicVAO=sr,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(f.mallocFloat(1024),[0,0]),_(f.mallocFloat(1024),[0,0]),_(f.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var H=Z.prototype;H.genColormap=function(Pe,ge){var Re=!1,ce=v([h({colormap:Pe,nshades:G,format:\"rgba\"}).map(function(Ze,ut){var pt=ge?N(ut/255,ge):Ze[3];return pt<1&&(Re=!0),[Ze[0],Ze[1],Ze[2],255*pt]})]);return d.divseq(ce,255),this.hasAlphaScale=Re,ce},H.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},H.isOpaque=function(){return!this.isTransparent()},H.pickSlots=1,H.setPickBase=function(Pe){this.pickId=Pe};function N(Pe,ge){if(!ge||!ge.length)return 1;for(var Re=0;Re<ge.length;++Re){if(ge.length<2)return 1;if(ge[Re][0]===Pe)return ge[Re][1];if(ge[Re][0]>Pe&&Re>0){var ce=(ge[Re][0]-Pe)/(ge[Re][0]-ge[Re-1][0]);return ge[Re][1]*(1-ce)+ce*ge[Re-1][1]}}return 1}var j=[0,0,0],re={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function oe(Pe,ge){var Re,ce,Ze,ut=ge.axes&&ge.axes.lastCubeProps.axis||j,pt=ge.showSurface,Zt=ge.showContour;for(Re=0;Re<3;++Re)for(pt=pt||ge.surfaceProject[Re],ce=0;ce<3;++ce)Zt=Zt||ge.contourProject[Re][ce];for(Re=0;Re<3;++Re){var st=re.projections[Re];for(ce=0;ce<16;++ce)st[ce]=0;for(ce=0;ce<4;++ce)st[5*ce]=1;st[5*Re]=0,st[12+Re]=ge.axesBounds[+(ut[Re]>0)][Re],p(st,Pe.model,st);var lt=re.clipBounds[Re];for(Ze=0;Ze<2;++Ze)for(ce=0;ce<3;++ce)lt[Ze][ce]=Pe.clipBounds[Ze][ce];lt[0][Re]=-1e8,lt[1][Re]=1e8}return re.showSurface=pt,re.showContour=Zt,re}var _e={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},Ee=T.slice(),Ce=[1,0,0,0,1,0,0,0,1];function me(Pe,ge){Pe=Pe||{};var Re=this.gl;Re.disable(Re.CULL_FACE),this._colorMap.bind(0);var ce=_e;ce.model=Pe.model||T,ce.view=Pe.view||T,ce.projection=Pe.projection||T,ce.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],ce.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],ce.objectOffset=this.objectOffset,ce.contourColor=this.contourColor[0],ce.inverseModel=k(ce.inverseModel,ce.model);for(var Ze=0;Ze<2;++Ze)for(var ut=ce.clipBounds[Ze],pt=0;pt<3;++pt)ut[pt]=Math.min(Math.max(this.clipBounds[Ze][pt],-1e8),1e8);ce.kambient=this.ambientLight,ce.kdiffuse=this.diffuseLight,ce.kspecular=this.specularLight,ce.roughness=this.roughness,ce.fresnel=this.fresnel,ce.opacity=this.opacity,ce.height=0,ce.permutation=Ce,ce.vertexColor=this.vertexColor;var Zt=Ee;for(p(Zt,ce.view,ce.model),p(Zt,ce.projection,Zt),k(Zt,Zt),Ze=0;Ze<3;++Ze)ce.eyePosition[Ze]=Zt[12+Ze]/Zt[15];var st=Zt[15];for(Ze=0;Ze<3;++Ze)st+=this.lightPosition[Ze]*Zt[4*Ze+3];for(Ze=0;Ze<3;++Ze){var lt=Zt[12+Ze];for(pt=0;pt<3;++pt)lt+=Zt[4*pt+Ze]*this.lightPosition[pt];ce.lightPosition[Ze]=lt/st}var Gt=oe(ce,this);if(Gt.showSurface){for(this._shader.bind(),this._shader.uniforms=ce,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(Re.TRIANGLES,this._vertexCount),Ze=0;Ze<3;++Ze)!this.surfaceProject[Ze]||!this.vertexCount||(this._shader.uniforms.model=Gt.projections[Ze],this._shader.uniforms.clipBounds=Gt.clipBounds[Ze],this._vao.draw(Re.TRIANGLES,this._vertexCount));this._vao.unbind()}if(Gt.showContour){var Nt=this._contourShader;ce.kambient=1,ce.kdiffuse=0,ce.kspecular=0,ce.opacity=1,Nt.bind(),Nt.uniforms=ce;var Jt=this._contourVAO;for(Jt.bind(),Ze=0;Ze<3;++Ze)for(Nt.uniforms.permutation=O[Ze],Re.lineWidth(this.contourWidth[Ze]*this.pixelRatio),pt=0;pt<this.contourLevels[Ze].length;++pt)pt===this.highlightLevel[Ze]?(Nt.uniforms.contourColor=this.highlightColor[Ze],Nt.uniforms.contourTint=this.highlightTint[Ze]):(pt===0||pt-1===this.highlightLevel[Ze])&&(Nt.uniforms.contourColor=this.contourColor[Ze],Nt.uniforms.contourTint=this.contourTint[Ze]),this._contourCounts[Ze][pt]&&(Nt.uniforms.height=this.contourLevels[Ze][pt],Jt.draw(Re.LINES,this._contourCounts[Ze][pt],this._contourOffsets[Ze][pt]));for(Ze=0;Ze<3;++Ze)for(Nt.uniforms.model=Gt.projections[Ze],Nt.uniforms.clipBounds=Gt.clipBounds[Ze],pt=0;pt<3;++pt)if(this.contourProject[Ze][pt]){Nt.uniforms.permutation=O[pt],Re.lineWidth(this.contourWidth[pt]*this.pixelRatio);for(var sr=0;sr<this.contourLevels[pt].length;++sr)sr===this.highlightLevel[pt]?(Nt.uniforms.contourColor=this.highlightColor[pt],Nt.uniforms.contourTint=this.highlightTint[pt]):(sr===0||sr-1===this.highlightLevel[pt])&&(Nt.uniforms.contourColor=this.contourColor[pt],Nt.uniforms.contourTint=this.contourTint[pt]),this._contourCounts[pt][sr]&&(Nt.uniforms.height=this.contourLevels[pt][sr],Jt.draw(Re.LINES,this._contourCounts[pt][sr],this._contourOffsets[pt][sr]))}for(Jt.unbind(),Jt=this._dynamicVAO,Jt.bind(),Ze=0;Ze<3;++Ze)if(this._dynamicCounts[Ze]!==0)for(Nt.uniforms.model=ce.model,Nt.uniforms.clipBounds=ce.clipBounds,Nt.uniforms.permutation=O[Ze],Re.lineWidth(this.dynamicWidth[Ze]*this.pixelRatio),Nt.uniforms.contourColor=this.dynamicColor[Ze],Nt.uniforms.contourTint=this.dynamicTint[Ze],Nt.uniforms.height=this.dynamicLevel[Ze],Jt.draw(Re.LINES,this._dynamicCounts[Ze],this._dynamicOffsets[Ze]),pt=0;pt<3;++pt)this.contourProject[pt][Ze]&&(Nt.uniforms.model=Gt.projections[pt],Nt.uniforms.clipBounds=Gt.clipBounds[pt],Jt.draw(Re.LINES,this._dynamicCounts[Ze],this._dynamicOffsets[Ze]));Jt.unbind()}}H.draw=function(Pe){return me.call(this,Pe,!1)},H.drawTransparent=function(Pe){return me.call(this,Pe,!0)};var ie={model:T,view:T,projection:T,inverseModel:T,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};H.drawPick=function(Pe){Pe=Pe||{};var ge=this.gl;ge.disable(ge.CULL_FACE);var Re=ie;Re.model=Pe.model||T,Re.view=Pe.view||T,Re.projection=Pe.projection||T,Re.shape=this._field[2].shape,Re.pickId=this.pickId/255,Re.lowerBound=this.bounds[0],Re.upperBound=this.bounds[1],Re.objectOffset=this.objectOffset,Re.permutation=Ce;for(var ce=0;ce<2;++ce)for(var Ze=Re.clipBounds[ce],ut=0;ut<3;++ut)Ze[ut]=Math.min(Math.max(this.clipBounds[ce][ut],-1e8),1e8);var pt=oe(Re,this);if(pt.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=Re,this._vao.bind(),this._vao.draw(ge.TRIANGLES,this._vertexCount),ce=0;ce<3;++ce)this.surfaceProject[ce]&&(this._pickShader.uniforms.model=pt.projections[ce],this._pickShader.uniforms.clipBounds=pt.clipBounds[ce],this._vao.draw(ge.TRIANGLES,this._vertexCount));this._vao.unbind()}if(pt.showContour){var Zt=this._contourPickShader;Zt.bind(),Zt.uniforms=Re;var st=this._contourVAO;for(st.bind(),ut=0;ut<3;++ut)for(ge.lineWidth(this.contourWidth[ut]*this.pixelRatio),Zt.uniforms.permutation=O[ut],ce=0;ce<this.contourLevels[ut].length;++ce)this._contourCounts[ut][ce]&&(Zt.uniforms.height=this.contourLevels[ut][ce],st.draw(ge.LINES,this._contourCounts[ut][ce],this._contourOffsets[ut][ce]));for(ce=0;ce<3;++ce)for(Zt.uniforms.model=pt.projections[ce],Zt.uniforms.clipBounds=pt.clipBounds[ce],ut=0;ut<3;++ut)if(this.contourProject[ce][ut]){Zt.uniforms.permutation=O[ut],ge.lineWidth(this.contourWidth[ut]*this.pixelRatio);for(var lt=0;lt<this.contourLevels[ut].length;++lt)this._contourCounts[ut][lt]&&(Zt.uniforms.height=this.contourLevels[ut][lt],st.draw(ge.LINES,this._contourCounts[ut][lt],this._contourOffsets[ut][lt]))}st.unbind()}},H.pick=function(Pe){if(!Pe||Pe.id!==this.pickId)return null;var ge=this._field[2].shape,Re=this._pickResult,ce=ge[0]*(Pe.value[0]+(Pe.value[2]>>4)/16)/255,Ze=Math.floor(ce),ut=ce-Ze,pt=ge[1]*(Pe.value[1]+(Pe.value[2]&15)/16)/255,Zt=Math.floor(pt),st=pt-Zt;Ze+=1,Zt+=1;var lt=Re.position;lt[0]=lt[1]=lt[2]=0;for(var Gt=0;Gt<2;++Gt)for(var Nt=Gt?ut:1-ut,Jt=0;Jt<2;++Jt)for(var sr=Jt?st:1-st,wr=Ze+Gt,cr=Zt+Jt,$e=Nt*sr,St=0;St<3;++St)lt[St]+=this._field[St].get(wr,cr)*$e;for(var Qt=this._pickResult.level,Vt=0;Vt<3;++Vt)if(Qt[Vt]=E.le(this.contourLevels[Vt],lt[Vt]),Qt[Vt]<0)this.contourLevels[Vt].length>0&&(Qt[Vt]=0);else if(Qt[Vt]<this.contourLevels[Vt].length-1){var _t=this.contourLevels[Vt][Qt[Vt]],It=this.contourLevels[Vt][Qt[Vt]+1];Math.abs(_t-lt[Vt])>Math.abs(It-lt[Vt])&&(Qt[Vt]+=1)}for(Re.index[0]=ut<.5?Ze:Ze+1,Re.index[1]=st<.5?Zt:Zt+1,Re.uv[0]=ce/ge[0],Re.uv[1]=pt/ge[1],St=0;St<3;++St)Re.dataCoordinate[St]=this._field[St].get(Re.index[0],Re.index[1]);return Re},H.padField=function(Pe,ge){var Re=ge.shape.slice(),ce=Pe.shape.slice();d.assign(Pe.lo(1,1).hi(Re[0],Re[1]),ge),d.assign(Pe.lo(1).hi(Re[0],1),ge.hi(Re[0],1)),d.assign(Pe.lo(1,ce[1]-1).hi(Re[0],1),ge.lo(0,Re[1]-1).hi(Re[0],1)),d.assign(Pe.lo(0,1).hi(1,Re[1]),ge.hi(1)),d.assign(Pe.lo(ce[0]-1,1).hi(1,Re[1]),ge.lo(Re[0]-1)),Pe.set(0,0,ge.get(0,0)),Pe.set(0,ce[1]-1,ge.get(0,Re[1]-1)),Pe.set(ce[0]-1,0,ge.get(Re[0]-1,0)),Pe.set(ce[0]-1,ce[1]-1,ge.get(Re[0]-1,Re[1]-1))};function Se(Pe,ge){return Array.isArray(Pe)?[ge(Pe[0]),ge(Pe[1]),ge(Pe[2])]:[ge(Pe),ge(Pe),ge(Pe)]}function Le(Pe){return Array.isArray(Pe)?Pe.length===3?[Pe[0],Pe[1],Pe[2],1]:[Pe[0],Pe[1],Pe[2],Pe[3]]:[0,0,0,1]}function Ae(Pe){if(Array.isArray(Pe)){if(Array.isArray(Pe))return[Le(Pe[0]),Le(Pe[1]),Le(Pe[2])];var ge=Le(Pe);return[ge.slice(),ge.slice(),ge.slice()]}}H.update=function(Pe){Pe=Pe||{},this.objectOffset=Pe.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in Pe&&(this.contourWidth=Se(Pe.contourWidth,Number)),\"showContour\"in Pe&&(this.showContour=Se(Pe.showContour,Boolean)),\"showSurface\"in Pe&&(this.showSurface=!!Pe.showSurface),\"contourTint\"in Pe&&(this.contourTint=Se(Pe.contourTint,Boolean)),\"contourColor\"in Pe&&(this.contourColor=Ae(Pe.contourColor)),\"contourProject\"in Pe&&(this.contourProject=Se(Pe.contourProject,function(yn){return Se(yn,Boolean)})),\"surfaceProject\"in Pe&&(this.surfaceProject=Pe.surfaceProject),\"dynamicColor\"in Pe&&(this.dynamicColor=Ae(Pe.dynamicColor)),\"dynamicTint\"in Pe&&(this.dynamicTint=Se(Pe.dynamicTint,Number)),\"dynamicWidth\"in Pe&&(this.dynamicWidth=Se(Pe.dynamicWidth,Number)),\"opacity\"in Pe&&(this.opacity=Pe.opacity),\"opacityscale\"in Pe&&(this.opacityscale=Pe.opacityscale),\"colorBounds\"in Pe&&(this.colorBounds=Pe.colorBounds),\"vertexColor\"in Pe&&(this.vertexColor=Pe.vertexColor?1:0),\"colormap\"in Pe&&this._colorMap.setPixels(this.genColormap(Pe.colormap,this.opacityscale));var ge=Pe.field||Pe.coords&&Pe.coords[2]||null,Re=!1;if(ge||(this._field[2].shape[0]||this._field[2].shape[2]?ge=this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):ge=this._field[2].hi(0,0)),\"field\"in Pe||\"coords\"in Pe){var ce=(ge.shape[0]+2)*(ge.shape[1]+2);ce>this._field[2].data.length&&(f.freeFloat(this._field[2].data),this._field[2].data=f.mallocFloat(s.nextPow2(ce))),this._field[2]=_(this._field[2].data,[ge.shape[0]+2,ge.shape[1]+2]),this.padField(this._field[2],ge),this.shape=ge.shape.slice();for(var Ze=this.shape,ut=0;ut<2;++ut)this._field[2].size>this._field[ut].data.length&&(f.freeFloat(this._field[ut].data),this._field[ut].data=f.mallocFloat(this._field[2].size)),this._field[ut]=_(this._field[ut].data,[Ze[0]+2,Ze[1]+2]);if(Pe.coords){var pt=Pe.coords;if(!Array.isArray(pt)||pt.length!==3)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(ut=0;ut<2;++ut){var Zt=pt[ut];for(Jt=0;Jt<2;++Jt)if(Zt.shape[Jt]!==Ze[Jt])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[ut],Zt)}}else if(Pe.ticks){var st=Pe.ticks;if(!Array.isArray(st)||st.length!==2)throw new Error(\"gl-surface: invalid ticks\");for(ut=0;ut<2;++ut){var lt=st[ut];if((Array.isArray(lt)||lt.length)&&(lt=_(lt)),lt.shape[0]!==Ze[ut])throw new Error(\"gl-surface: invalid tick length\");var Gt=_(lt.data,Ze);Gt.stride[ut]=lt.stride[0],Gt.stride[ut^1]=0,this.padField(this._field[ut],Gt)}}else{for(ut=0;ut<2;++ut){var Nt=[0,0];Nt[ut]=1,this._field[ut]=_(this._field[ut].data,[Ze[0]+2,Ze[1]+2],Nt,0)}this._field[0].set(0,0,0);for(var Jt=0;Jt<Ze[0];++Jt)this._field[0].set(Jt+1,0,Jt);for(this._field[0].set(Ze[0]+1,0,Ze[0]-1),this._field[1].set(0,0,0),Jt=0;Jt<Ze[1];++Jt)this._field[1].set(0,Jt+1,Jt);this._field[1].set(0,Ze[1]+1,Ze[1]-1)}var sr=this._field,wr=_(f.mallocFloat(sr[2].size*3*2),[3,Ze[0]+2,Ze[1]+2,2]);for(ut=0;ut<3;++ut)S(wr.pick(ut),sr[ut],\"mirror\");var cr=_(f.mallocFloat(sr[2].size*3),[Ze[0]+2,Ze[1]+2,3]);for(ut=0;ut<Ze[0]+2;++ut)for(Jt=0;Jt<Ze[1]+2;++Jt){var $e=wr.get(0,ut,Jt,0),St=wr.get(0,ut,Jt,1),Qt=wr.get(1,ut,Jt,0),Vt=wr.get(1,ut,Jt,1),_t=wr.get(2,ut,Jt,0),It=wr.get(2,ut,Jt,1),mt=Qt*It-Vt*_t,er=_t*St-It*$e,lr=$e*Vt-St*Qt,Tr=Math.sqrt(mt*mt+er*er+lr*lr);Tr<1e-8?(Tr=Math.max(Math.abs(mt),Math.abs(er),Math.abs(lr)),Tr<1e-8?(lr=1,er=mt=0,Tr=1):Tr=1/Tr):Tr=1/Math.sqrt(Tr),cr.set(ut,Jt,0,mt*Tr),cr.set(ut,Jt,1,er*Tr),cr.set(ut,Jt,2,lr*Tr)}f.free(wr.data);var Lr=[1/0,1/0,1/0],ti=[-1/0,-1/0,-1/0],Br=1/0,Vr=-1/0,dt=(Ze[0]-1)*(Ze[1]-1)*6,Ge=f.mallocFloat(s.nextPow2(10*dt)),Je=0,je=0;for(ut=0;ut<Ze[0]-1;++ut)e:for(Jt=0;Jt<Ze[1]-1;++Jt){for(var tt=0;tt<2;++tt)for(var xt=0;xt<2;++xt)for(var Ie=0;Ie<3;++Ie){var xe=this._field[Ie].get(1+ut+tt,1+Jt+xt);if(isNaN(xe)||!isFinite(xe))continue e}for(Ie=0;Ie<6;++Ie){var ke=ut+z[Ie][0],vt=Jt+z[Ie][1],ir=this._field[0].get(ke+1,vt+1),ar=this._field[1].get(ke+1,vt+1);xe=this._field[2].get(ke+1,vt+1),mt=cr.get(ke+1,vt+1,0),er=cr.get(ke+1,vt+1,1),lr=cr.get(ke+1,vt+1,2),Pe.intensity&&(vr=Pe.intensity.get(ke,vt));var vr=Pe.intensity?Pe.intensity.get(ke,vt):xe+this.objectOffset[2];Ge[Je++]=ke,Ge[Je++]=vt,Ge[Je++]=ir,Ge[Je++]=ar,Ge[Je++]=xe,Ge[Je++]=0,Ge[Je++]=vr,Ge[Je++]=mt,Ge[Je++]=er,Ge[Je++]=lr,Lr[0]=Math.min(Lr[0],ir+this.objectOffset[0]),Lr[1]=Math.min(Lr[1],ar+this.objectOffset[1]),Lr[2]=Math.min(Lr[2],xe+this.objectOffset[2]),Br=Math.min(Br,vr),ti[0]=Math.max(ti[0],ir+this.objectOffset[0]),ti[1]=Math.max(ti[1],ar+this.objectOffset[1]),ti[2]=Math.max(ti[2],xe+this.objectOffset[2]),Vr=Math.max(Vr,vr),je+=1}}for(Pe.intensityBounds&&(Br=+Pe.intensityBounds[0],Vr=+Pe.intensityBounds[1]),ut=6;ut<Je;ut+=10)Ge[ut]=(Ge[ut]-Br)/(Vr-Br);this._vertexCount=je,this._coordinateBuffer.update(Ge.subarray(0,Je)),f.freeFloat(Ge),f.free(cr.data),this.bounds=[Lr,ti],this.intensity=Pe.intensity||this._field[2],(this.intensityBounds[0]!==Br||this.intensityBounds[1]!==Vr)&&(Re=!0),this.intensityBounds=[Br,Vr]}if(\"levels\"in Pe){var ii=Pe.levels;for(Array.isArray(ii[0])?ii=ii.slice():ii=[[],[],ii],ut=0;ut<3;++ut)ii[ut]=ii[ut].slice(),ii[ut].sort(function(yn,Sn){return yn-Sn});for(ut=0;ut<3;++ut)for(Jt=0;Jt<ii[ut].length;++Jt)ii[ut][Jt]-=this.objectOffset[ut];e:for(ut=0;ut<3;++ut){if(ii[ut].length!==this.contourLevels[ut].length){Re=!0;break}for(Jt=0;Jt<ii[ut].length;++Jt)if(ii[ut][Jt]!==this.contourLevels[ut][Jt]){Re=!0;break e}}this.contourLevels=ii}if(Re){sr=this._field,Ze=this.shape;for(var pi=[],$r=0;$r<3;++$r){var di=this.contourLevels[$r],ji=[],In=[],wi=[0,0,0];for(ut=0;ut<di.length;++ut){var On=b(this._field[$r],di[ut]);ji.push(pi.length/5|0),je=0;e:for(Jt=0;Jt<On.cells.length;++Jt){var qn=On.cells[Jt];for(Ie=0;Ie<2;++Ie){var Fn=On.positions[qn[Ie]],ra=Fn[0],la=Math.floor(ra)|0,Ut=ra-la,wt=Fn[1],rr=Math.floor(wt)|0,nr=wt-rr,Er=!1;t:for(var Xr=0;Xr<3;++Xr){wi[Xr]=0;var ri=($r+Xr+1)%3;for(tt=0;tt<2;++tt){var Qr=tt?Ut:1-Ut;for(ke=Math.min(Math.max(la+tt,0),Ze[0])|0,xt=0;xt<2;++xt){var Oi=xt?nr:1-nr;if(vt=Math.min(Math.max(rr+xt,0),Ze[1])|0,Xr<2?xe=this._field[ri].get(ke,vt):xe=(this.intensity.get(ke,vt)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(xe)||isNaN(xe)){Er=!0;break t}var $i=Qr*Oi;wi[Xr]+=$i*xe}}}if(!Er)pi.push(wi[0],wi[1],Fn[0],Fn[1],wi[2]),je+=1;else{if(Ie>0){for(var tn=0;tn<5;++tn)pi.pop();je-=1}continue e}}}In.push(je)}this._contourOffsets[$r]=ji,this._contourCounts[$r]=In}var fn=f.mallocFloat(pi.length);for(ut=0;ut<pi.length;++ut)fn[ut]=pi[ut];this._contourBuffer.update(fn),f.freeFloat(fn)}},H.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var Pe=0;Pe<3;++Pe)f.freeFloat(this._field[Pe].data)},H.highlight=function(Pe){var ge;if(!Pe){this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],this.highlightLevel=[-1,-1,-1];return}for(ge=0;ge<3;++ge)this.enableHighlight[ge]?this.highlightLevel[ge]=Pe.level[ge]:this.highlightLevel[ge]=-1;var Re;for(this.snapToData?Re=Pe.dataCoordinate:Re=Pe.position,ge=0;ge<3;++ge)Re[ge]-=this.objectOffset[ge];if(!((!this.enableDynamic[0]||Re[0]===this.dynamicLevel[0])&&(!this.enableDynamic[1]||Re[1]===this.dynamicLevel[1])&&(!this.enableDynamic[2]||Re[2]===this.dynamicLevel[2]))){for(var ce=0,Ze=this.shape,ut=f.mallocFloat(12*Ze[0]*Ze[1]),pt=0;pt<3;++pt){if(!this.enableDynamic[pt]){this.dynamicLevel[pt]=NaN,this._dynamicCounts[pt]=0;continue}this.dynamicLevel[pt]=Re[pt];var Zt=(pt+1)%3,st=(pt+2)%3,lt=this._field[pt],Gt=this._field[Zt],Nt=this._field[st],Jt=b(lt,Re[pt]),sr=Jt.cells,wr=Jt.positions;for(this._dynamicOffsets[pt]=ce,ge=0;ge<sr.length;++ge)for(var cr=sr[ge],$e=0;$e<2;++$e){var St=wr[cr[$e]],Qt=+St[0],Vt=Qt|0,_t=Math.min(Vt+1,Ze[0])|0,It=Qt-Vt,mt=1-It,er=+St[1],lr=er|0,Tr=Math.min(lr+1,Ze[1])|0,Lr=er-lr,ti=1-Lr,Br=mt*ti,Vr=mt*Lr,dt=It*ti,Ge=It*Lr,Je=Br*Gt.get(Vt,lr)+Vr*Gt.get(Vt,Tr)+dt*Gt.get(_t,lr)+Ge*Gt.get(_t,Tr),je=Br*Nt.get(Vt,lr)+Vr*Nt.get(Vt,Tr)+dt*Nt.get(_t,lr)+Ge*Nt.get(_t,Tr);if(isNaN(Je)||isNaN(je)){$e&&(ce-=1);break}ut[2*ce+0]=Je,ut[2*ce+1]=je,ce+=1}this._dynamicCounts[pt]=ce-this._dynamicOffsets[pt]}this._dynamicBuffer.update(ut.subarray(0,2*ce)),f.freeFloat(ut)}};function Fe(Pe){var ge=Pe.gl,Re=x(ge),ce=M(ge),Ze=C(ge),ut=g(ge),pt=l(ge),Zt=u(ge,[{buffer:pt,size:4,stride:P,offset:0},{buffer:pt,size:3,stride:P,offset:16},{buffer:pt,size:3,stride:P,offset:28}]),st=l(ge),lt=u(ge,[{buffer:st,size:4,stride:20,offset:0},{buffer:st,size:1,stride:20,offset:16}]),Gt=l(ge),Nt=u(ge,[{buffer:Gt,size:2,type:ge.FLOAT}]),Jt=c(ge,1,G,ge.RGBA,ge.UNSIGNED_BYTE);Jt.minFilter=ge.LINEAR,Jt.magFilter=ge.LINEAR;var sr=new Z(ge,[0,0],[[0,0,0],[0,0,0]],Re,ce,pt,Zt,Jt,Ze,ut,st,lt,Gt,Nt,[0,0,0]),wr={levels:[[],[],[]]};for(var cr in Pe)wr[cr]=Pe[cr];return wr.colormap=wr.colormap||\"jet\",sr.update(wr),sr}},9507:function(i){i.exports=!0},9618:function(i,a,o){var s=o(7163),l=typeof Float64Array!=\"undefined\";function u(b,p){return b[0]-p[0]}function c(){var b=this.stride,p=new Array(b.length),k;for(k=0;k<p.length;++k)p[k]=[Math.abs(b[k]),k];p.sort(u);var E=new Array(p.length);for(k=0;k<E.length;++k)E[k]=p[k][1];return E}var f={T:function(b){function p(E){this.data=E}var k=p.prototype;return k.dtype=b,k.index=function(){return-1},k.size=0,k.dimension=-1,k.shape=k.stride=k.order=[],k.lo=k.hi=k.transpose=k.step=function(){return new p(this.data)},k.get=k.set=function(){},k.pick=function(){return null},function(S){return new p(S)}},0:function(b,p){function k(S,L){this.data=S,this.offset=L}var E=k.prototype;return E.dtype=b,E.index=function(){return this.offset},E.dimension=0,E.size=1,E.shape=E.stride=E.order=[],E.lo=E.hi=E.transpose=E.step=function(){return new k(this.data,this.offset)},E.pick=function(){return p(this.data)},E.valueOf=E.get=function(){return b===\"generic\"?this.data.get(this.offset):this.data[this.offset]},E.set=function(L){return b===\"generic\"?this.data.set(this.offset,L):this.data[this.offset]=L},function(L,x,C,M){return new k(L,M)}},1:function(b,p,k){function E(L,x,C,M){this.data=L,this.shape=[x],this.stride=[C],this.offset=M|0}var S=E.prototype;return S.dtype=b,S.dimension=1,Object.defineProperty(S,\"size\",{get:function(){return this.shape[0]}}),S.order=[0],S.set=function(x,C){return b===\"generic\"?this.data.set(this.offset+this.stride[0]*x,C):this.data[this.offset+this.stride[0]*x]=C},S.get=function(x){return b===\"generic\"?this.data.get(this.offset+this.stride[0]*x):this.data[this.offset+this.stride[0]*x]},S.index=function(x){return this.offset+this.stride[0]*x},S.hi=function(x){return new E(this.data,typeof x!=\"number\"||x<0?this.shape[0]:x|0,this.stride[0],this.offset)},S.lo=function(x){var C=this.offset,M=0,g=this.shape[0],P=this.stride[0];return typeof x==\"number\"&&x>=0&&(M=x|0,C+=P*M,g-=M),new E(this.data,g,P,C)},S.step=function(x){var C=this.shape[0],M=this.stride[0],g=this.offset,P=0,T=Math.ceil;return typeof x==\"number\"&&(P=x|0,P<0?(g+=M*(C-1),C=T(-C/P)):C=T(C/P),M*=P),new E(this.data,C,M,g)},S.transpose=function(x){x=x===void 0?0:x|0;var C=this.shape,M=this.stride;return new E(this.data,C[x],M[x],this.offset)},S.pick=function(x){var C=[],M=[],g=this.offset;typeof x==\"number\"&&x>=0?g=g+this.stride[0]*x|0:(C.push(this.shape[0]),M.push(this.stride[0]));var P=p[C.length+1];return P(this.data,C,M,g)},function(x,C,M,g){return new E(x,C[0],M[0],g)}},2:function(b,p,k){function E(L,x,C,M,g,P){this.data=L,this.shape=[x,C],this.stride=[M,g],this.offset=P|0}var S=E.prototype;return S.dtype=b,S.dimension=2,Object.defineProperty(S,\"size\",{get:function(){return this.shape[0]*this.shape[1]}}),Object.defineProperty(S,\"order\",{get:function(){return Math.abs(this.stride[0])>Math.abs(this.stride[1])?[1,0]:[0,1]}}),S.set=function(x,C,M){return b===\"generic\"?this.data.set(this.offset+this.stride[0]*x+this.stride[1]*C,M):this.data[this.offset+this.stride[0]*x+this.stride[1]*C]=M},S.get=function(x,C){return b===\"generic\"?this.data.get(this.offset+this.stride[0]*x+this.stride[1]*C):this.data[this.offset+this.stride[0]*x+this.stride[1]*C]},S.index=function(x,C){return this.offset+this.stride[0]*x+this.stride[1]*C},S.hi=function(x,C){return new E(this.data,typeof x!=\"number\"||x<0?this.shape[0]:x|0,typeof C!=\"number\"||C<0?this.shape[1]:C|0,this.stride[0],this.stride[1],this.offset)},S.lo=function(x,C){var M=this.offset,g=0,P=this.shape[0],T=this.shape[1],z=this.stride[0],O=this.stride[1];return typeof x==\"number\"&&x>=0&&(g=x|0,M+=z*g,P-=g),typeof C==\"number\"&&C>=0&&(g=C|0,M+=O*g,T-=g),new E(this.data,P,T,z,O,M)},S.step=function(x,C){var M=this.shape[0],g=this.shape[1],P=this.stride[0],T=this.stride[1],z=this.offset,O=0,V=Math.ceil;return typeof x==\"number\"&&(O=x|0,O<0?(z+=P*(M-1),M=V(-M/O)):M=V(M/O),P*=O),typeof C==\"number\"&&(O=C|0,O<0?(z+=T*(g-1),g=V(-g/O)):g=V(g/O),T*=O),new E(this.data,M,g,P,T,z)},S.transpose=function(x,C){x=x===void 0?0:x|0,C=C===void 0?1:C|0;var M=this.shape,g=this.stride;return new E(this.data,M[x],M[C],g[x],g[C],this.offset)},S.pick=function(x,C){var M=[],g=[],P=this.offset;typeof x==\"number\"&&x>=0?P=P+this.stride[0]*x|0:(M.push(this.shape[0]),g.push(this.stride[0])),typeof C==\"number\"&&C>=0?P=P+this.stride[1]*C|0:(M.push(this.shape[1]),g.push(this.stride[1]));var T=p[M.length+1];return T(this.data,M,g,P)},function(x,C,M,g){return new E(x,C[0],C[1],M[0],M[1],g)}},3:function(b,p,k){function E(L,x,C,M,g,P,T,z){this.data=L,this.shape=[x,C,M],this.stride=[g,P,T],this.offset=z|0}var S=E.prototype;return S.dtype=b,S.dimension=3,Object.defineProperty(S,\"size\",{get:function(){return this.shape[0]*this.shape[1]*this.shape[2]}}),Object.defineProperty(S,\"order\",{get:function(){var x=Math.abs(this.stride[0]),C=Math.abs(this.stride[1]),M=Math.abs(this.stride[2]);return x>C?C>M?[2,1,0]:x>M?[1,2,0]:[1,0,2]:x>M?[2,0,1]:M>C?[0,1,2]:[0,2,1]}}),S.set=function(x,C,M,g){return b===\"generic\"?this.data.set(this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M,g):this.data[this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M]=g},S.get=function(x,C,M){return b===\"generic\"?this.data.get(this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M):this.data[this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M]},S.index=function(x,C,M){return this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M},S.hi=function(x,C,M){return new E(this.data,typeof x!=\"number\"||x<0?this.shape[0]:x|0,typeof C!=\"number\"||C<0?this.shape[1]:C|0,typeof M!=\"number\"||M<0?this.shape[2]:M|0,this.stride[0],this.stride[1],this.stride[2],this.offset)},S.lo=function(x,C,M){var g=this.offset,P=0,T=this.shape[0],z=this.shape[1],O=this.shape[2],V=this.stride[0],G=this.stride[1],Z=this.stride[2];return typeof x==\"number\"&&x>=0&&(P=x|0,g+=V*P,T-=P),typeof C==\"number\"&&C>=0&&(P=C|0,g+=G*P,z-=P),typeof M==\"number\"&&M>=0&&(P=M|0,g+=Z*P,O-=P),new E(this.data,T,z,O,V,G,Z,g)},S.step=function(x,C,M){var g=this.shape[0],P=this.shape[1],T=this.shape[2],z=this.stride[0],O=this.stride[1],V=this.stride[2],G=this.offset,Z=0,H=Math.ceil;return typeof x==\"number\"&&(Z=x|0,Z<0?(G+=z*(g-1),g=H(-g/Z)):g=H(g/Z),z*=Z),typeof C==\"number\"&&(Z=C|0,Z<0?(G+=O*(P-1),P=H(-P/Z)):P=H(P/Z),O*=Z),typeof M==\"number\"&&(Z=M|0,Z<0?(G+=V*(T-1),T=H(-T/Z)):T=H(T/Z),V*=Z),new E(this.data,g,P,T,z,O,V,G)},S.transpose=function(x,C,M){x=x===void 0?0:x|0,C=C===void 0?1:C|0,M=M===void 0?2:M|0;var g=this.shape,P=this.stride;return new 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j=t.projection[N[L]];(S.project[L]=j.show)&&(S.projectOpacity[L]=j.opacity,S.projectScale[L]=j.scale)}S.errorBounds=TIt(t,i,n);var re=SIt([t.error_x,t.error_y,t.error_z]);return S.errorColor=re.color,S.errorLineWidth=re.lineWidth,S.errorCapSize=re.capSize,S.delaunayAxis=t.surfaceaxis,S.delaunayColor=jPe(t.surfacecolor),S}function GPe(e){if(Qy.isArrayOrTypedArray(e)){var t=e[0];return Qy.isArrayOrTypedArray(t)&&(e=t),\"rgb(\"+e.slice(0,3).map(function(r){return Math.round(r*255)})+\")\"}return null}function HPe(e){return Qy.isArrayOrTypedArray(e)?e.length===4&&typeof e[0]==\"number\"?GPe(e):e.map(GPe):null}bX.update=function(e){var t=this.scene.glplot.gl,r,n,i,a,o=_X.solid;this.data=e;var s=CIt(this.scene,e);\"mode\"in s&&(this.mode=s.mode),\"lineDashes\"in s&&s.lineDashes in _X&&(o=_X[s.lineDashes]),this.color=HPe(s.scatterColor)||HPe(s.lineColor),this.dataPoints=s.position,r={gl:this.scene.glplot.gl,position:s.position,color:s.lineColor,lineWidth:s.lineWidth||1,dashes:o[0],dashScale:o[1],opacity:e.opacity,connectGaps:e.connectgaps},this.mode.indexOf(\"lines\")!==-1?this.linePlot?this.linePlot.update(r):(this.linePlot=pIt(r),this.linePlot._trace=this,this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var l=e.opacity;if(e.marker&&e.marker.opacity!==void 0&&(l*=e.marker.opacity),n={gl:this.scene.glplot.gl,position:s.position,color:s.scatterColor,size:s.scatterSize,glyph:s.scatterMarker,opacity:l,orthographic:!0,lineWidth:s.scatterLineWidth,lineColor:s.scatterLineColor,project:s.project,projectScale:s.projectScale,projectOpacity:s.projectOpacity},this.mode.indexOf(\"markers\")!==-1?this.scatterPlot?this.scatterPlot.update(n):(this.scatterPlot=NPe(n),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:this.scene.glplot.gl,position:s.position,glyph:s.text,color:s.textColor,size:s.textSize,angle:s.textAngle,alignment:s.textOffset,font:s.textFontFamily,fontWeight:s.textFontWeight,fontStyle:s.textFontStyle,fontVariant:s.textFontVariant,orthographic:!0,lineWidth:0,project:!1,opacity:e.opacity},this.textLabels=e.hovertext||e.text,this.mode.indexOf(\"text\")!==-1?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=NPe(a),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),i={gl:this.scene.glplot.gl,position:s.position,color:s.errorColor,error:s.errorBounds,lineWidth:s.errorLineWidth,capSize:s.errorCapSize,opacity:e.opacity},this.errorBars?s.errorBounds?this.errorBars.update(i):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):s.errorBounds&&(this.errorBars=gIt(i),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),s.delaunayAxis>=0){var u=AIt(s.position,s.delaunayColor,s.delaunayAxis);u.opacity=e.opacity,this.delaunayMesh?this.delaunayMesh.update(u):(u.gl=t,this.delaunayMesh=mIt(u),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)};bX.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())};function LIt(e,t){var r=new WPe(e,t.uid);return r.update(t),r}XPe.exports=LIt});var MX=ye((egr,$Pe)=>{\"use strict\";var e1=pf(),PIt=ec(),SX=Tu(),wX=df().axisHoverFormat,{hovertemplateAttrs:IIt,texttemplateAttrs:RIt,templatefallbackAttrs:YPe}=Ll(),KPe=Gl(),DIt=mX(),FIt=$D(),Yg=Ao().extendFlat,zIt=mc().overrideAll,JPe=Z1(),OIt=e1.line,U2=e1.marker,qIt=U2.line,BIt=Yg({width:OIt.width,dash:{valType:\"enumerated\",values:JPe(DIt),dflt:\"solid\"}},SX(\"line\"));function TX(e){return{show:{valType:\"boolean\",dflt:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1},scale:{valType:\"number\",min:0,max:10,dflt:2/3}}}var AX=$Pe.exports=zIt({x:e1.x,y:e1.y,z:{valType:\"data_array\"},text:Yg({},e1.text,{}),texttemplate:RIt(),texttemplatefallback:YPe({editType:\"calc\"}),hovertext:Yg({},e1.hovertext,{}),hovertemplate:IIt(),hovertemplatefallback:YPe(),xhoverformat:wX(\"x\"),yhoverformat:wX(\"y\"),zhoverformat:wX(\"z\"),mode:Yg({},e1.mode,{dflt:\"lines+markers\"}),surfaceaxis:{valType:\"enumerated\",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:\"color\"},projection:{x:TX(\"x\"),y:TX(\"y\"),z:TX(\"z\")},connectgaps:e1.connectgaps,line:BIt,marker:Yg({symbol:{valType:\"enumerated\",values:JPe(FIt),dflt:\"circle\",arrayOk:!0},size:Yg({},U2.size,{dflt:8}),sizeref:U2.sizeref,sizemin:U2.sizemin,sizemode:U2.sizemode,opacity:Yg({},U2.opacity,{arrayOk:!1}),colorbar:U2.colorbar,line:Yg({width:Yg({},qIt.width,{arrayOk:!1})},SX(\"marker.line\"))},SX(\"marker\")),textposition:Yg({},e1.textposition,{dflt:\"top center\"}),textfont:PIt({noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0,editType:\"calc\",colorEditType:\"style\",arrayOk:!0,variantValues:[\"normal\",\"small-caps\"]}),opacity:KPe.opacity,hoverinfo:Yg({},KPe.hoverinfo)},\"calc\",\"nested\");AX.x.editType=AX.y.editType=AX.z.editType=\"calc+clearAxisTypes\"});var tIe=ye((tgr,eIe)=>{\"use strict\";var QPe=qa(),NIt=Dr(),EX=Ru(),UIt=$p(),VIt=R0(),GIt=D0(),HIt=MX();eIe.exports=function(t,r,n,i){function a(d,v){return NIt.coerce(t,r,HIt,d,v)}var o=jIt(t,r,a,i);if(!o){r.visible=!1;return}a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),a(\"xhoverformat\"),a(\"yhoverformat\"),a(\"zhoverformat\"),a(\"mode\"),EX.hasMarkers(r)&&UIt(t,r,n,i,a,{noSelect:!0,noAngle:!0}),EX.hasLines(r)&&(a(\"connectgaps\"),VIt(t,r,n,i,a)),EX.hasText(r)&&(a(\"texttemplate\"),a(\"texttemplatefallback\"),GIt(t,r,i,a,{noSelect:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0}));var s=(r.line||{}).color,l=(r.marker||{}).color;a(\"surfaceaxis\")>=0&&a(\"surfacecolor\",s||l);for(var u=[\"x\",\"y\",\"z\"],c=0;c<3;++c){var f=\"projection.\"+u[c];a(f+\".show\")&&(a(f+\".opacity\"),a(f+\".scale\"))}var h=QPe.getComponentMethod(\"errorbars\",\"supplyDefaults\");h(t,r,s||l||n,{axis:\"z\"}),h(t,r,s||l||n,{axis:\"y\",inherit:\"z\"}),h(t,r,s||l||n,{axis:\"x\",inherit:\"z\"})};function jIt(e,t,r,n){var i=0,a=r(\"x\"),o=r(\"y\"),s=r(\"z\"),l=QPe.getComponentMethod(\"calendars\",\"handleTraceDefaults\");return l(e,t,[\"x\",\"y\",\"z\"],n),a&&o&&s&&(i=Math.min(a.length,o.length,s.length),t._length=t._xlength=t._ylength=t._zlength=i),i}});var iIe=ye((rgr,rIe)=>{\"use strict\";var WIt=km(),XIt=F0();rIe.exports=function(t,r){var n=[{x:!1,y:!1,trace:r,t:{}}];return WIt(n,r),XIt(t,r),n}});var aIe=ye((igr,nIe)=>{nIe.exports=ZIt;function ZIt(e,t){if(typeof e!=\"string\")throw new TypeError(\"must specify type string\");if(t=t||{},typeof document==\"undefined\"&&!t.canvas)return null;var r=t.canvas||document.createElement(\"canvas\");typeof t.width==\"number\"&&(r.width=t.width),typeof t.height==\"number\"&&(r.height=t.height);var n=t,i;try{var a=[e];e.indexOf(\"webgl\")===0&&a.push(\"experimental-\"+e);for(var o=0;o<a.length;o++)if(i=r.getContext(a[o],n),i)return i}catch(s){i=null}return i||null}});var sIe=ye((ngr,oIe)=>{var YIt=aIe();oIe.exports=function(t){return YIt(\"webgl\",t)}});var kX=ye((agr,uIe)=>{\"use strict\";var lIe=ka(),KIt=function(){};uIe.exports=function(t){for(var r in t)typeof t[r]==\"function\"&&(t[r]=KIt);t.destroy=function(){t.container.parentNode.removeChild(t.container)};var n=document.createElement(\"div\");n.className=\"no-webgl\",n.style.cursor=\"pointer\",n.style.fontSize=\"24px\",n.style.color=lIe.defaults[0],n.style.position=\"absolute\",n.style.left=n.style.top=\"0px\",n.style.width=n.style.height=\"100%\",n.style[\"background-color\"]=lIe.lightLine,n.style[\"z-index\"]=30;var i=document.createElement(\"p\");return i.textContent=\"WebGL is not supported by your browser - visit https://get.webgl.org for more info\",i.style.position=\"relative\",i.style.top=\"50%\",i.style.left=\"50%\",i.style.height=\"30%\",i.style.width=\"50%\",i.style.margin=\"-15% 0 0 -25%\",n.appendChild(i),t.container.appendChild(n),t.container.style.background=\"#FFFFFF\",t.container.onclick=function(){window.open(\"https://get.webgl.org\")},!1}});var hIe=ye((ogr,fIe)=>{\"use strict\";var V2=Jy(),JIt=Dr(),$It=[\"xaxis\",\"yaxis\",\"zaxis\"];function cIe(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickFontWeight=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickFontStyle=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickFontVariant=[\"normal\",\"normal\",\"normal\",\"normal\"],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelFontWeight=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelFontStyle=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelFontVariant=[\"normal\",\"normal\",\"normal\",\"normal\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}var QIt=cIe.prototype;QIt.merge=function(e,t){for(var r=this,n=0;n<3;++n){var i=t[$It[n]];if(!i.visible){r.tickEnable[n]=!1,r.labelEnable[n]=!1,r.lineEnable[n]=!1,r.lineTickEnable[n]=!1,r.gridEnable[n]=!1,r.zeroEnable[n]=!1,r.backgroundEnable[n]=!1;continue}r.labels[n]=e._meta?JIt.templateString(i.title.text,e._meta):i.title.text,\"font\"in i.title&&(i.title.font.color&&(r.labelColor[n]=V2(i.title.font.color)),i.title.font.family&&(r.labelFont[n]=i.title.font.family),i.title.font.size&&(r.labelSize[n]=i.title.font.size),i.title.font.weight&&(r.labelFontWeight[n]=i.title.font.weight),i.title.font.style&&(r.labelFontStyle[n]=i.title.font.style),i.title.font.variant&&(r.labelFontVariant[n]=i.title.font.variant)),\"showline\"in i&&(r.lineEnable[n]=i.showline),\"linecolor\"in i&&(r.lineColor[n]=V2(i.linecolor)),\"linewidth\"in i&&(r.lineWidth[n]=i.linewidth),\"showgrid\"in i&&(r.gridEnable[n]=i.showgrid),\"gridcolor\"in i&&(r.gridColor[n]=V2(i.gridcolor)),\"gridwidth\"in i&&(r.gridWidth[n]=i.gridwidth),i.type===\"log\"?r.zeroEnable[n]=!1:\"zeroline\"in i&&(r.zeroEnable[n]=i.zeroline),\"zerolinecolor\"in i&&(r.zeroLineColor[n]=V2(i.zerolinecolor)),\"zerolinewidth\"in i&&(r.zeroLineWidth[n]=i.zerolinewidth),\"ticks\"in i&&i.ticks?r.lineTickEnable[n]=!0:r.lineTickEnable[n]=!1,\"ticklen\"in i&&(r.lineTickLength[n]=r._defaultLineTickLength[n]=i.ticklen),\"tickcolor\"in i&&(r.lineTickColor[n]=V2(i.tickcolor)),\"tickwidth\"in i&&(r.lineTickWidth[n]=i.tickwidth),\"tickangle\"in i&&(r.tickAngle[n]=i.tickangle===\"auto\"?-3600:Math.PI*-i.tickangle/180),\"showticklabels\"in i&&(r.tickEnable[n]=i.showticklabels),\"tickfont\"in i&&(i.tickfont.color&&(r.tickColor[n]=V2(i.tickfont.color)),i.tickfont.family&&(r.tickFont[n]=i.tickfont.family),i.tickfont.size&&(r.tickSize[n]=i.tickfont.size),i.tickfont.weight&&(r.tickFontWeight[n]=i.tickfont.weight),i.tickfont.style&&(r.tickFontStyle[n]=i.tickfont.style),i.tickfont.variant&&(r.tickFontVariant[n]=i.tickfont.variant)),\"mirror\"in i?[\"ticks\",\"all\",\"allticks\"].indexOf(i.mirror)!==-1?(r.lineTickMirror[n]=!0,r.lineMirror[n]=!0):i.mirror===!0?(r.lineTickMirror[n]=!1,r.lineMirror[n]=!0):(r.lineTickMirror[n]=!1,r.lineMirror[n]=!1):r.lineMirror[n]=!1,\"showbackground\"in i&&i.showbackground!==!1?(r.backgroundEnable[n]=!0,r.backgroundColor[n]=V2(i.backgroundcolor)):r.backgroundEnable[n]=!1}};function e8t(e,t){var r=new cIe;return r.merge(e,t),r}fIe.exports=e8t});var pIe=ye((sgr,vIe)=>{\"use strict\";var t8t=Jy(),r8t=[\"xaxis\",\"yaxis\",\"zaxis\"];function dIe(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}var i8t=dIe.prototype;i8t.merge=function(e){for(var t=0;t<3;++t){var r=e[r8t[t]];if(!r.visible){this.enabled[t]=!1,this.drawSides[t]=!1;continue}this.enabled[t]=r.showspikes,this.colors[t]=t8t(r.spikecolor),this.drawSides[t]=r.spikesides,this.lineWidth[t]=r.spikethickness}};function n8t(e){var t=new dIe;return t.merge(e),t}vIe.exports=n8t});var yIe=ye((lgr,mIe)=>{\"use strict\";mIe.exports=u8t;var gIe=ho(),a8t=Dr(),o8t=[\"xaxis\",\"yaxis\",\"zaxis\"],s8t=[0,0,0];function l8t(e){for(var t=new Array(3),r=0;r<3;++r){for(var n=e[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;t[r]=i}return t}function u8t(e){for(var t=e.axesOptions,r=e.glplot.axesPixels,n=e.fullSceneLayout,i=[[],[],[]],a=0;a<3;++a){var o=n[o8t[a]];if(o._length=(r[a].hi-r[a].lo)*r[a].pixelsPerDataUnit/e.dataScale[a],Math.abs(o._length)===1/0||isNaN(o._length))i[a]=[];else{o._input_range=o.range.slice(),o.range[0]=r[a].lo/e.dataScale[a],o.range[1]=r[a].hi/e.dataScale[a],o._m=1/(e.dataScale[a]*r[a].pixelsPerDataUnit),o.range[0]===o.range[1]&&(o.range[0]-=1,o.range[1]+=1);var s=o.tickmode;if(o.tickmode===\"auto\"){o.tickmode=\"linear\";var l=o.nticks||a8t.constrain(o._length/40,4,9);gIe.autoTicks(o,Math.abs(o.range[1]-o.range[0])/l)}for(var u=gIe.calcTicks(o,{msUTC:!0}),c=0;c<u.length;++c)u[c].x=u[c].x*e.dataScale[a],o.type===\"date\"&&(u[c].text=u[c].text.replace(/\\<br\\>/g,\" \"));i[a]=u,o.tickmode=s}}t.ticks=i;for(var a=0;a<3;++a){s8t[a]=.5*(e.glplot.bounds[0][a]+e.glplot.bounds[1][a]);for(var c=0;c<2;++c)t.bounds[c][a]=e.glplot.bounds[c][a]}e.contourLevels=l8t(i)}});var SIe=ye((ugr,AIe)=>{\"use strict\";var bIe=Od().gl_plot3d,c8t=bIe.createCamera,_Ie=bIe.createScene,f8t=sIe(),h8t=RL(),rF=qa(),up=Dr(),tF=up.preserveDrawingBuffer(),iF=ho(),Kg=vf(),d8t=Jy(),v8t=kX(),p8t=UU(),g8t=hIe(),m8t=pIe(),y8t=yIe(),_8t=Tg().applyAutorangeOptions,YE,eF,wIe=!1;function TIe(e,t){var r=document.createElement(\"div\"),n=e.container;this.graphDiv=e.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=e.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=t,this.id=e.id||\"scene\",this.fullSceneLayout=t[this.id],this.plotArgs=[[],{},{}],this.axesOptions=g8t(t,t[this.id]),this.spikeOptions=m8t(t[this.id]),this.container=r,this.staticMode=!!e.staticPlot,this.pixelRatio=this.pixelRatio||e.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=rF.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=rF.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var Sv=TIe.prototype;Sv.prepareOptions=function(){var e=this,t={canvas:e.canvas,gl:e.gl,glOptions:{preserveDrawingBuffer:tF,premultipliedAlpha:!0,antialias:!0},container:e.container,axes:e.axesOptions,spikes:e.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:e.camera,pixelRatio:e.pixelRatio};if(e.staticMode){if(!eF&&(YE=document.createElement(\"canvas\"),eF=f8t({canvas:YE,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}),!eF))throw new Error(\"error creating static canvas/context for image server\");t.gl=eF,t.canvas=YE}return t};var xIe=!0;Sv.tryCreatePlot=function(){var e=this,t=e.prepareOptions(),r=!0;try{e.glplot=_Ie(t)}catch(n){if(e.staticMode||!xIe||tF)r=!1;else{up.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{tF=t.glOptions.preserveDrawingBuffer=!0,e.glplot=_Ie(t)}catch(i){tF=t.glOptions.preserveDrawingBuffer=!1,r=!1}}}return xIe=!1,r};Sv.initializeGLCamera=function(){var e=this,t=e.fullSceneLayout.camera,r=t.projection.type===\"orthographic\";e.camera=c8t(e.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:\"orbit\"})};Sv.initializeGLPlot=function(){var e=this;e.initializeGLCamera();var t=e.tryCreatePlot();if(!t)return v8t(e);e.traces={},e.make4thDimension();var r=e.graphDiv,n=r.layout,i=function(){var o={};return e.isCameraChanged(n)&&(o[e.id+\".camera\"]=e.getCamera()),e.isAspectChanged(n)&&(o[e.id+\".aspectratio\"]=e.glplot.getAspectratio(),n[e.id].aspectmode!==\"manual\"&&(e.fullSceneLayout.aspectmode=n[e.id].aspectmode=o[e.id+\".aspectmode\"]=\"manual\")),o},a=function(o){if(o.fullSceneLayout.dragmode!==!1){var s=i();o.saveLayout(n),o.graphDiv.emit(\"plotly_relayout\",s)}};return e.glplot.canvas&&(e.glplot.canvas.addEventListener(\"mouseup\",function(){a(e)}),e.glplot.canvas.addEventListener(\"touchstart\",function(){wIe=!0}),e.glplot.canvas.addEventListener(\"wheel\",function(o){if(r._context._scrollZoom.gl3d){if(e.camera._ortho){var s=o.deltaX>o.deltaY?1.1:.9090909090909091,l=e.glplot.getAspectratio();e.glplot.setAspectratio({x:s*l.x,y:s*l.y,z:s*l.z})}a(e)}},h8t?{passive:!1}:!1),e.glplot.canvas.addEventListener(\"mousemove\",function(){if(e.fullSceneLayout.dragmode!==!1&&e.camera.mouseListener.buttons!==0){var o=i();e.graphDiv.emit(\"plotly_relayouting\",o)}}),e.staticMode||e.glplot.canvas.addEventListener(\"webglcontextlost\",function(o){r&&r.emit&&r.emit(\"plotly_webglcontextlost\",{event:o,layer:e.id})},!1)),e.glplot.oncontextloss=function(){e.recoverContext()},e.glplot.onrender=function(){e.render()},!0};Sv.render=function(){var e=this,t=e.graphDiv,r,n=e.svgContainer,i=e.container.getBoundingClientRect();t._fullLayout._calcInverseTransform(t);var a=t._fullLayout._invScaleX,o=t._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),y8t(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,f=e.glplot.selection,h=0;h<u.length;++h)r=e.traces[u[h]],r.data.hoverinfo!==\"skip\"&&r.handlePick(f)&&(c=r),r.setContourLevels&&r.setContourLevels();function d(P,T,z){var O=e.fullSceneLayout[P+\"axis\"];return O.type!==\"log\"&&(T=O.d2l(T)),iF.hoverLabelText(O,T,z)}if(c!==null){var v=p8t(e.glplot.cameraParams,f.dataCoordinate);r=c.data;var _=t._fullData[r.index],b=f.index,p={xLabel:d(\"x\",f.traceCoordinate[0],r.xhoverformat),yLabel:d(\"y\",f.traceCoordinate[1],r.yhoverformat),zLabel:d(\"z\",f.traceCoordinate[2],r.zhoverformat)},k=Kg.castHoverinfo(_,e.fullLayout,b),E=(k||\"\").split(\"+\"),S=k&&k===\"all\";!_.hovertemplate&&!S&&(E.indexOf(\"x\")===-1&&(p.xLabel=void 0),E.indexOf(\"y\")===-1&&(p.yLabel=void 0),E.indexOf(\"z\")===-1&&(p.zLabel=void 0),E.indexOf(\"text\")===-1&&(f.textLabel=void 0),E.indexOf(\"name\")===-1&&(c.name=void 0));var L,x=[];r.type===\"cone\"||r.type===\"streamtube\"?(p.uLabel=d(\"x\",f.traceCoordinate[3],r.uhoverformat),(S||E.indexOf(\"u\")!==-1)&&x.push(\"u: \"+p.uLabel),p.vLabel=d(\"y\",f.traceCoordinate[4],r.vhoverformat),(S||E.indexOf(\"v\")!==-1)&&x.push(\"v: \"+p.vLabel),p.wLabel=d(\"z\",f.traceCoordinate[5],r.whoverformat),(S||E.indexOf(\"w\")!==-1)&&x.push(\"w: \"+p.wLabel),p.normLabel=f.traceCoordinate[6].toPrecision(3),(S||E.indexOf(\"norm\")!==-1)&&x.push(\"norm: \"+p.normLabel),r.type===\"streamtube\"&&(p.divergenceLabel=f.traceCoordinate[7].toPrecision(3),(S||E.indexOf(\"divergence\")!==-1)&&x.push(\"divergence: \"+p.divergenceLabel)),f.textLabel&&x.push(f.textLabel),L=x.join(\"<br>\")):r.type===\"isosurface\"||r.type===\"volume\"?(p.valueLabel=iF.hoverLabelText(e._mockAxis,e._mockAxis.d2l(f.traceCoordinate[3]),r.valuehoverformat),x.push(\"value: \"+p.valueLabel),f.textLabel&&x.push(f.textLabel),L=x.join(\"<br>\")):L=f.textLabel;var C={x:f.traceCoordinate[0],y:f.traceCoordinate[1],z:f.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:b};Kg.appendArrayPointValue(C,_,b),r._module.eventData&&(C=_._module.eventData(C,f,_,{},b));var M={points:[C]};if(e.fullSceneLayout.hovermode){var g=[];Kg.loneHover({trace:_,x:(.5+.5*v[0]/v[3])*s,y:(.5-.5*v[1]/v[3])*l,xLabel:p.xLabel,yLabel:p.yLabel,zLabel:p.zLabel,text:L,name:c.name,color:Kg.castHoverOption(_,b,\"bgcolor\")||c.color,borderColor:Kg.castHoverOption(_,b,\"bordercolor\"),fontFamily:Kg.castHoverOption(_,b,\"font.family\"),fontSize:Kg.castHoverOption(_,b,\"font.size\"),fontColor:Kg.castHoverOption(_,b,\"font.color\"),nameLength:Kg.castHoverOption(_,b,\"namelength\"),textAlign:Kg.castHoverOption(_,b,\"align\"),hovertemplate:up.castOption(_,b,\"hovertemplate\"),hovertemplateLabels:up.extendFlat({},C,p),eventData:[C]},{container:n,gd:t,inOut_bbox:g}),C.bbox=g[0]}f.distance<5&&(f.buttons||wIe)?t.emit(\"plotly_click\",M):t.emit(\"plotly_hover\",M),this.oldEventData=M}else Kg.loneUnhover(n),this.oldEventData&&t.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)};Sv.recoverContext=function(){var e=this;e.glplot.dispose();var t=function(){if(e.glplot.gl.isContextLost()){requestAnimationFrame(t);return}if(!e.initializeGLPlot()){up.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\");return}e.plot.apply(e,e.plotArgs)};requestAnimationFrame(t)};var KE=[\"xaxis\",\"yaxis\",\"zaxis\"];function x8t(e,t,r){for(var n=e.fullSceneLayout,i=0;i<3;i++){var a=KE[i],o=a.charAt(0),s=n[a],l=t[o],u=t[o+\"calendar\"],c=t[\"_\"+o+\"length\"];if(!up.isArrayOrTypedArray(l))r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],c-1);else for(var f,h=0;h<(c||l.length);h++)if(up.isArrayOrTypedArray(l[h]))for(var d=0;d<l[h].length;++d)f=s.d2l(l[h][d],0,u),!isNaN(f)&&isFinite(f)&&(r[0][i]=Math.min(r[0][i],f),r[1][i]=Math.max(r[1][i],f));else f=s.d2l(l[h],0,u),!isNaN(f)&&isFinite(f)&&(r[0][i]=Math.min(r[0][i],f),r[1][i]=Math.max(r[1][i],f))}}function b8t(e,t){for(var r=e.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=KE[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var u=n[l];if(u.visible){var c=s.r2l(u[o]);!isNaN(c)&&isFinite(c)&&(t[0][i]=Math.min(t[0][i],c),t[1][i]=Math.max(t[1][i],c))}}}Sv.plot=function(e,t,r){var n=this;if(n.plotArgs=[e,t,r],!n.glplot.contextLost){var i,a,o,s,l,u,c=t[n.id],f=r[n.id];n.fullLayout=t,n.fullSceneLayout=c,n.axesOptions.merge(t,c),n.spikeOptions.merge(c),n.setViewport(c),n.updateFx(c.dragmode,c.hovermode),n.camera.enableWheel=n.graphDiv._context._scrollZoom.gl3d,n.glplot.setClearColor(d8t(c.bgcolor)),n.setConvert(l),e?Array.isArray(e)||(e=[e]):e=[];var h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(o=0;o<e.length;++o)i=e[o],!(i.visible!==!0||i._length===0)&&x8t(this,i,h);b8t(this,h);var d=[1,1,1];for(s=0;s<3;++s)h[1][s]===h[0][s]?d[s]=1:d[s]=1/(h[1][s]-h[0][s]);for(n.dataScale=d,n.convertAnnotations(this),o=0;o<e.length;++o)i=e[o],!(i.visible!==!0||i._length===0)&&(a=n.traces[i.uid],a?a.data.type===i.type?a.update(i):(a.dispose(),a=i._module.plot(this,i),n.traces[i.uid]=a):(a=i._module.plot(this,i),n.traces[i.uid]=a),a.name=i.name);var v=Object.keys(n.traces);e:for(o=0;o<v.length;++o){for(s=0;s<e.length;++s)if(e[s].uid===v[o]&&e[s].visible===!0&&e[s]._length!==0)continue e;a=n.traces[v[o]],a.dispose(),delete n.traces[v[o]]}n.glplot.objects.sort(function(oe,_e){return oe._trace.data.index-_e._trace.data.index});var _=[[0,0,0],[0,0,0]],b=[],p={};for(o=0;o<3;++o){l=c[KE[o]],u=l.type,u in p?(p[u].acc*=d[o],p[u].count+=1):p[u]={acc:d[o],count:1};var k;if(l.autorange){_[0][o]=1/0,_[1][o]=-1/0;var E=n.glplot.objects,S=n.fullSceneLayout.annotations||[],L=l._name.charAt(0);for(s=0;s<E.length;s++){var x=E[s],C=x.bounds,M=x._trace.data._pad||0;x.constructor.name===\"ErrorBars\"&&l._lowerLogErrorBound?_[0][o]=Math.min(_[0][o],l._lowerLogErrorBound):_[0][o]=Math.min(_[0][o],C[0][o]/d[o]-M),_[1][o]=Math.max(_[1][o],C[1][o]/d[o]+M)}for(s=0;s<S.length;s++){var g=S[s];if(g.visible){var P=l.r2l(g[L]);_[0][o]=Math.min(_[0][o],P),_[1][o]=Math.max(_[1][o],P)}}if(\"rangemode\"in l&&l.rangemode===\"tozero\"&&(_[0][o]=Math.min(_[0][o],0),_[1][o]=Math.max(_[1][o],0)),_[0][o]>_[1][o])_[0][o]=-1,_[1][o]=1;else{var T=_[1][o]-_[0][o];_[0][o]-=T/32,_[1][o]+=T/32}if(k=[_[0][o],_[1][o]],k=_8t(k,l),_[0][o]=k[0],_[1][o]=k[1],l.isReversed()){var z=_[0][o];_[0][o]=_[1][o],_[1][o]=z}}else k=l.range,_[0][o]=l.r2l(k[0]),_[1][o]=l.r2l(k[1]);_[0][o]===_[1][o]&&(_[0][o]-=1,_[1][o]+=1),b[o]=_[1][o]-_[0][o],l.range=[_[0][o],_[1][o]],l.limitRange(),n.glplot.setBounds(o,{min:l.range[0]*d[o],max:l.range[1]*d[o]})}var O,V=c.aspectmode;if(V===\"cube\")O=[1,1,1];else if(V===\"manual\"){var G=c.aspectratio;O=[G.x,G.y,G.z]}else if(V===\"auto\"||V===\"data\"){var Z=[1,1,1];for(o=0;o<3;++o){l=c[KE[o]],u=l.type;var H=p[u];Z[o]=Math.pow(H.acc,1/H.count)/d[o]}V===\"data\"||Math.max.apply(null,Z)/Math.min.apply(null,Z)<=4?O=Z:O=[1,1,1]}else throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");c.aspectratio.x=f.aspectratio.x=O[0],c.aspectratio.y=f.aspectratio.y=O[1],c.aspectratio.z=f.aspectratio.z=O[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var N=c.domain||null,j=t._size||null;if(N&&j){var re=n.container.style;re.position=\"absolute\",re.left=j.l+N.x[0]*j.w+\"px\",re.top=j.t+(1-N.y[1])*j.h+\"px\",re.width=j.w*(N.x[1]-N.x[0])+\"px\",re.height=j.h*(N.y[1]-N.y[0])+\"px\"}n.glplot.redraw()}};Sv.destroy=function(){var e=this;e.glplot&&(e.camera.mouseListener.enabled=!1,e.container.removeEventListener(\"wheel\",e.camera.wheelListener),e.camera=null,e.glplot.dispose(),e.container.parentNode.removeChild(e.container),e.glplot=null)};function w8t(e){return[[e.eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]}function T8t(e){return{up:{x:e.up[0],y:e.up[1],z:e.up[2]},center:{x:e.center[0],y:e.center[1],z:e.center[2]},eye:{x:e.eye[0],y:e.eye[1],z:e.eye[2]},projection:{type:e._ortho===!0?\"orthographic\":\"perspective\"}}}Sv.getCamera=function(){var e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),T8t(e.camera)};Sv.setViewport=function(e){var t=this,r=e.camera;t.camera.lookAt.apply(this,w8t(r)),t.glplot.setAspectratio(e.aspectratio);var n=r.projection.type===\"orthographic\",i=t.camera._ortho;n!==i&&(t.glplot.redraw(),t.glplot.clearRGBA(),t.glplot.dispose(),t.initializeGLPlot())};Sv.isCameraChanged=function(e){var t=this,r=t.getCamera(),n=up.nestedProperty(e,t.id+\".camera\"),i=n.get();function a(u,c,f,h){var d=[\"up\",\"center\",\"eye\"],v=[\"x\",\"y\",\"z\"];return c[d[f]]&&u[d[f]][v[h]]===c[d[f]][v[h]]}var o=!1;if(i===void 0)o=!0;else{for(var s=0;s<3;s++)for(var l=0;l<3;l++)if(!a(r,i,s,l)){o=!0;break}(!i.projection||r.projection&&r.projection.type!==i.projection.type)&&(o=!0)}return o};Sv.isAspectChanged=function(e){var t=this,r=t.glplot.getAspectratio(),n=up.nestedProperty(e,t.id+\".aspectratio\"),i=n.get();return i===void 0||i.x!==r.x||i.y!==r.y||i.z!==r.z};Sv.saveLayout=function(e){var t=this,r=t.fullLayout,n,i,a,o,s,l,u=t.isCameraChanged(e),c=t.isAspectChanged(e),f=u||c;if(f){var h={};if(u&&(n=t.getCamera(),i=up.nestedProperty(e,t.id+\".camera\"),a=i.get(),h[t.id+\".camera\"]=a),c&&(o=t.glplot.getAspectratio(),s=up.nestedProperty(e,t.id+\".aspectratio\"),l=s.get(),h[t.id+\".aspectratio\"]=l),rF.call(\"_storeDirectGUIEdit\",e,r._preGUI,h),u){i.set(n);var d=up.nestedProperty(r,t.id+\".camera\");d.set(n)}if(c){s.set(o);var v=up.nestedProperty(r,t.id+\".aspectratio\");v.set(o),t.glplot.redraw()}}return f};Sv.updateFx=function(e,t){var r=this,n=r.camera;if(n)if(e===\"orbit\")n.mode=\"orbit\",n.keyBindingMode=\"rotate\";else if(e===\"turntable\"){n.up=[0,0,1],n.mode=\"turntable\",n.keyBindingMode=\"rotate\";var i=r.graphDiv,a=i._fullLayout,o=r.fullSceneLayout.camera,s=o.up.x,l=o.up.y,u=o.up.z;if(u/Math.sqrt(s*s+l*l+u*u)<.999){var c=r.id+\".camera.up\",f={x:0,y:0,z:1},h={};h[c]=f;var d=i.layout;rF.call(\"_storeDirectGUIEdit\",d,a._preGUI,h),o.up=f,up.nestedProperty(d,c).set(f)}}else n.keyBindingMode=e;r.fullSceneLayout.hovermode=t};function A8t(e,t,r){for(var n=0,i=r-1;n<i;++n,--i)for(var a=0;a<t;++a)for(var o=0;o<4;++o){var s=4*(t*n+a)+o,l=4*(t*i+a)+o,u=e[s];e[s]=e[l],e[l]=u}}function S8t(e,t,r){for(var n=0;n<r;++n)for(var i=0;i<t;++i){var a=4*(t*n+i),o=e[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)e[a+l]=Math.min(s*e[a+l],255)}}Sv.toImage=function(e){var t=this;e||(e=\"png\"),t.staticMode&&t.container.appendChild(YE),t.glplot.redraw();var r=t.glplot.gl,n=r.drawingBufferWidth,i=r.drawingBufferHeight;r.bindFramebuffer(r.FRAMEBUFFER,null);var a=new Uint8Array(n*i*4);r.readPixels(0,0,n,i,r.RGBA,r.UNSIGNED_BYTE,a),A8t(a,n,i),S8t(a,n,i);var o=document.createElement(\"canvas\");o.width=n,o.height=i;var s=o.getContext(\"2d\",{willReadFrequently:!0}),l=s.createImageData(n,i);l.data.set(a),s.putImageData(l,0,0);var u;switch(e){case\"jpeg\":u=o.toDataURL(\"image/jpeg\");break;case\"webp\":u=o.toDataURL(\"image/webp\");break;default:u=o.toDataURL(\"image/png\")}return t.staticMode&&t.container.removeChild(YE),u};Sv.setConvert=function(){for(var e=this,t=0;t<3;t++){var r=e.fullSceneLayout[KE[t]];iF.setConvert(r,e.fullLayout),r.setScale=up.noop}};Sv.make4thDimension=function(){var e=this,t=e.graphDiv,r=t._fullLayout;e._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},iF.setConvert(e._mockAxis,r)};AIe.exports=TIe});var EIe=ye((cgr,MIe)=>{\"use strict\";MIe.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}});var LX=ye((fgr,kIe)=>{\"use strict\";var M8t=ka(),xs=Rd(),CX=Ao().extendFlat,E8t=mc().overrideAll;kIe.exports=E8t({visible:xs.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:M8t.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:xs.color,categoryorder:xs.categoryorder,categoryarray:xs.categoryarray,title:{text:xs.title.text,font:xs.title.font},type:CX({},xs.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:xs.autotypenumbers,autorange:xs.autorange,autorangeoptions:{minallowed:xs.autorangeoptions.minallowed,maxallowed:xs.autorangeoptions.maxallowed,clipmin:xs.autorangeoptions.clipmin,clipmax:xs.autorangeoptions.clipmax,include:xs.autorangeoptions.include,editType:\"plot\"},rangemode:xs.rangemode,minallowed:xs.minallowed,maxallowed:xs.maxallowed,range:CX({},xs.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:xs.minor.tickmode,nticks:xs.nticks,tick0:xs.tick0,dtick:xs.dtick,tickvals:xs.tickvals,ticktext:xs.ticktext,ticks:xs.ticks,mirror:xs.mirror,ticklen:xs.ticklen,tickwidth:xs.tickwidth,tickcolor:xs.tickcolor,showticklabels:xs.showticklabels,labelalias:xs.labelalias,tickfont:xs.tickfont,tickangle:xs.tickangle,tickprefix:xs.tickprefix,showtickprefix:xs.showtickprefix,ticksuffix:xs.ticksuffix,showticksuffix:xs.showticksuffix,showexponent:xs.showexponent,exponentformat:xs.exponentformat,minexponent:xs.minexponent,separatethousands:xs.separatethousands,tickformat:xs.tickformat,tickformatstops:xs.tickformatstops,hoverformat:xs.hoverformat,showline:xs.showline,linecolor:xs.linecolor,linewidth:xs.linewidth,showgrid:xs.showgrid,gridcolor:CX({},xs.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:xs.gridwidth,zeroline:xs.zeroline,zerolinecolor:xs.zerolinecolor,zerolinewidth:xs.zerolinewidth},\"plot\",\"from-root\")});var DX=ye((hgr,CIe)=>{\"use strict\";var PX=LX(),k8t=Cc().attributes,IX=Ao().extendFlat,C8t=Dr().counterRegex;function RX(e,t,r){return{x:{valType:\"number\",dflt:e,editType:\"camera\"},y:{valType:\"number\",dflt:t,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}CIe.exports={_arrayAttrRegexps:[C8t(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:IX(RX(0,0,1),{}),center:IX(RX(0,0,0),{}),eye:IX(RX(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:k8t({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:PX,yaxis:PX,zaxis:PX,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\"}});var RIe=ye((dgr,IIe)=>{\"use strict\";var L8t=cd().mix,LIe=Dr(),P8t=vl(),I8t=LX(),R8t=SU(),D8t=r4(),PIe=[\"xaxis\",\"yaxis\",\"zaxis\"],F8t=100*136/187;IIe.exports=function(t,r,n){var i,a;function o(u,c){return LIe.coerce(i,a,I8t,u,c)}for(var s=0;s<PIe.length;s++){var l=PIe[s];i=t[l]||{},a=P8t.newContainer(r,l),a._id=l[0]+n.scene,a._name=l,R8t(i,a,o,n),D8t(i,a,o,{font:n.font,letter:l[0],data:n.data,showGrid:!0,noAutotickangles:!0,noMinorloglabels:!0,noTicklabelindex:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelshift:!0,noTicklabelstandoff:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,noInsiderange:!0,noUnifiedhovertitle:!0,bgColor:n.bgColor,calendar:n.calendar},n.fullLayout),o(\"gridcolor\",L8t(a.color,n.bgColor,F8t).toRgbString()),o(\"title.text\",l[0]),a.setScale=LIe.noop,o(\"showspikes\")&&(o(\"spikesides\"),o(\"spikethickness\"),o(\"spikecolor\",a.color)),o(\"showaxeslabels\"),o(\"showbackground\")&&o(\"backgroundcolor\")}}});var OIe=ye((vgr,zIe)=>{\"use strict\";var z8t=Dr(),O8t=ka(),q8t=qa(),B8t=k_(),N8t=RIe(),DIe=DX(),U8t=Id().getSubplotData,FIe=\"gl3d\";zIe.exports=function(t,r,n){var i=r._basePlotModules.length>1;function a(o){if(!i){var s=z8t.validate(t[o],DIe[o]);if(s)return t[o]}}B8t(t,r,n,{type:FIe,attributes:DIe,handleDefaults:V8t,fullLayout:r,font:r.font,fullData:n,getDfltFromLayout:a,autotypenumbersDflt:r.autotypenumbers,paper_bgcolor:r.paper_bgcolor,calendar:r.calendar})};function V8t(e,t,r,n){for(var i=r(\"bgcolor\"),a=O8t.combine(i,n.paper_bgcolor),o=[\"up\",\"center\",\"eye\"],s=0;s<o.length;s++)r(\"camera.\"+o[s]+\".x\"),r(\"camera.\"+o[s]+\".y\"),r(\"camera.\"+o[s]+\".z\");r(\"camera.projection.type\");var l=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),u=l?\"manual\":\"auto\",c=r(\"aspectmode\",u);l||(e.aspectratio=t.aspectratio={x:1,y:1,z:1},c===\"manual\"&&(t.aspectmode=\"auto\"),e.aspectmode=t.aspectmode);var f=U8t(n.fullData,FIe,n.id);N8t(e,t,{font:n.font,scene:n.id,data:f,bgColor:a,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),q8t.getComponentMethod(\"annotations3d\",\"handleDefaults\")(e,t,n);var h=n.getDfltFromLayout(\"dragmode\");if(h!==!1&&!h)if(h=\"orbit\",e.camera&&e.camera.up){var d=e.camera.up.x,v=e.camera.up.y,_=e.camera.up.z;_!==0&&(!d||!v||!_||_/Math.sqrt(d*d+v*v+_*_)>.999)&&(h=\"turntable\")}else h=\"turntable\";r(\"dragmode\",h),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}});var $_=ye(cp=>{\"use strict\";var G8t=mc().overrideAll,H8t=B1(),j8t=SIe(),W8t=Id().getSubplotData,X8t=Dr(),Z8t=Wp(),VA=\"gl3d\",FX=\"scene\";cp.name=VA;cp.attr=FX;cp.idRoot=FX;cp.idRegex=cp.attrRegex=X8t.counterRegex(\"scene\");cp.attributes=EIe();cp.layoutAttributes=DX();cp.baseLayoutAttrOverrides=G8t({hoverlabel:H8t.hoverlabel},\"plot\",\"nested\");cp.supplyLayoutDefaults=OIe();cp.plot=function(t){for(var r=t._fullLayout,n=t._fullData,i=r._subplots[VA],a=0;a<i.length;a++){var o=i[a],s=W8t(n,VA,o),l=r[o],u=l.camera,c=l._scene;c||(c=new j8t({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},r),l._scene=c),c.viewInitial||(c.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),c.plot(s,r,t.layout)}};cp.clean=function(e,t,r,n){for(var i=n._subplots[VA]||[],a=0;a<i.length;a++){var o=i[a];!t[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}};cp.toSVG=function(e){for(var t=e._fullLayout,r=t._subplots[VA],n=t._size,i=0;i<r.length;i++){var a=t[r[i]],o=a.domain,s=a._scene,l=s.toImage(\"png\"),u=t._glimages.append(\"svg:image\");u.attr({xmlns:Z8t.svg,\"xlink:href\":l,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}};cp.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var r=t.substr(5);return r===\"1\"&&(r=\"\"),FX+r}};cp.updateFx=function(e){for(var t=e._fullLayout,r=t._subplots[VA],n=0;n<r.length;n++){var i=t[r[n]]._scene;i.updateFx(t.dragmode,t.hovermode)}}});var BIe=ye((ggr,qIe)=>{\"use strict\";qIe.exports={plot:ZPe(),attributes:MX(),markerSymbols:$D(),supplyDefaults:tIe(),colorbar:[{container:\"marker\",min:\"cmin\",max:\"cmax\"},{container:\"line\",min:\"cmin\",max:\"cmax\"}],calc:iIe(),moduleType:\"trace\",name:\"scatter3d\",basePlotModule:$_(),categories:[\"gl3d\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}});var UIe=ye((mgr,NIe)=>{\"use strict\";NIe.exports=BIe()});var JE=ye((ygr,HIe)=>{\"use strict\";var VIe=ka(),Y8t=Tu(),zX=df().axisHoverFormat,{hovertemplateAttrs:K8t,templatefallbackAttrs:J8t}=Ll(),GIe=Gl(),OX=Ao().extendFlat,$8t=mc().overrideAll;function qX(e){return{valType:\"boolean\",dflt:!1}}function BX(e){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:qX(\"x\"),y:qX(\"y\"),z:qX(\"z\")},color:{valType:\"color\",dflt:VIe.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:VIe.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var NX=HIe.exports=$8t(OX({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:K8t(),hovertemplatefallback:J8t(),xhoverformat:zX(\"x\"),yhoverformat:zX(\"y\"),zhoverformat:zX(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},Y8t(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:BX(\"x\"),y:BX(\"y\"),z:BX(\"z\")},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05,description:\"Represents the level that incident rays are reflected in a single direction, causing shine.\"},roughness:{valType:\"number\",min:0,max:1,dflt:.5,description:\"Alters specular reflection; the rougher the surface, the wider and less contrasty the shine.\"},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},hoverinfo:OX({},GIe.hoverinfo),showlegend:OX({},GIe.showlegend,{dflt:!1})}),\"calc\",\"nested\");NX.x.editType=NX.y.editType=NX.z.editType=\"calc+clearAxisTypes\"});var VX=ye((_gr,XIe)=>{\"use strict\";var Q8t=qa(),jIe=Dr(),eRt=Qh(),tRt=JE(),UX=.1;function rRt(e,t){for(var r=[],n=32,i=0;i<n;i++){var a=i/(n-1),o=t+(1-t)*(1-Math.pow(Math.sin(e*a*Math.PI),2));r.push([a,Math.max(0,Math.min(1,o))])}return r}function iRt(e){var t=0;if(!Array.isArray(e)||e.length<2||!e[0]||!e[e.length-1]||+e[0][0]!=0||+e[e.length-1][0]!=1)return!1;for(var r=0;r<e.length;r++){var n=e[r];if(n.length!==2||+n[0]<t)return!1;t=+n[0]}return!0}function nRt(e,t,r,n){var i,a;function o(b,p){return jIe.coerce(e,t,tRt,b,p)}var s=o(\"x\"),l=o(\"y\"),u=o(\"z\");if(!u||!u.length||s&&s.length<1||l&&l.length<1){t.visible=!1;return}t._xlength=Array.isArray(s)&&jIe.isArrayOrTypedArray(s[0])?u.length:u[0].length,t._ylength=u.length;var c=Q8t.getComponentMethod(\"calendars\",\"handleTraceDefaults\");c(e,t,[\"x\",\"y\",\"z\"],n),o(\"text\"),o(\"hovertext\"),o(\"hovertemplate\"),o(\"hovertemplatefallback\"),o(\"xhoverformat\"),o(\"yhoverformat\"),o(\"zhoverformat\"),[\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"hidesurface\",\"connectgaps\",\"opacity\"].forEach(function(b){o(b)});var f=o(\"surfacecolor\"),h=[\"x\",\"y\",\"z\"];for(i=0;i<3;++i){var d=\"contours.\"+h[i],v=o(d+\".show\"),_=o(d+\".highlight\");if(v||_)for(a=0;a<3;++a)o(d+\".project.\"+h[a]);v&&(o(d+\".color\"),o(d+\".width\"),o(d+\".usecolormap\")),_&&(o(d+\".highlightcolor\"),o(d+\".highlightwidth\")),o(d+\".start\"),o(d+\".end\"),o(d+\".size\")}eRt(e,t,n,o,{prefix:\"\",cLetter:\"c\"}),WIe(e,t,n,o),t._length=null}function WIe(e,t,r,n){var i=n(\"opacityscale\");i===\"max\"?t.opacityscale=[[0,UX],[1,1]]:i===\"min\"?t.opacityscale=[[0,1],[1,UX]]:i===\"extremes\"?t.opacityscale=rRt(1,UX):iRt(i)||(t.opacityscale=void 0)}XIe.exports={supplyDefaults:nRt,opacityscaleDefaults:WIe}});var KIe=ye((xgr,YIe)=>{\"use strict\";var ZIe=gv();YIe.exports=function(t,r){r.surfacecolor?ZIe(t,r,{vals:r.surfacecolor,containerStr:\"\",cLetter:\"c\"}):ZIe(t,r,{vals:r.z,containerStr:\"\",cLetter:\"c\"})}});var r8e=ye((bgr,t8e)=>{\"use strict\";var aRt=Od().gl_surface3d,GA=Od().ndarray,oRt=Od().ndarray_linear_interpolate.d2,sRt=a8(),lRt=o8(),$E=Dr().isArrayOrTypedArray,uRt=$y().parseColorScale,JIe=Jy(),cRt=tc().extractOpts;function QIe(e,t,r){this.scene=e,this.uid=r,this.surface=t,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var Jg=QIe.prototype;Jg.getXat=function(e,t,r,n){var i=$E(this.data.x)?$E(this.data.x[0])?this.data.x[t][e]:this.data.x[e]:e;return r===void 0?i:n.d2l(i,0,r)};Jg.getYat=function(e,t,r,n){var i=$E(this.data.y)?$E(this.data.y[0])?this.data.y[t][e]:this.data.y[t]:t;return r===void 0?i:n.d2l(i,0,r)};Jg.getZat=function(e,t,r,n){var i=this.data.z[t][e];return i===null&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[t][e]),r===void 0?i:n.d2l(i,0,r)};Jg.handlePick=function(e){if(e.object===this.surface){var t=(e.data.index[0]-1)/this.dataScaleX-1,r=(e.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(t),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);e.index=[n,i],e.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],e.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=e.dataCoordinate[a];o!=null&&(e.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return $E(s)&&s[i]&&s[i][n]!==void 0?e.textLabel=s[i][n]:s?e.textLabel=s:e.textLabel=\"\",e.data.dataCoordinate=e.dataCoordinate.slice(),this.surface.highlight(e.data),this.scene.glplot.spikes.position=e.dataCoordinate,!0}};function fRt(e){var t=e[0].rgb,r=e[e.length-1].rgb;return t[0]===r[0]&&t[1]===r[1]&&t[2]===r[2]&&t[3]===r[3]}var 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hRt(e,t){if(e<t)return 0;for(var r=0;Math.floor(e%t)===0;)e/=t,r++;return r}function GX(e){for(var t=[],r=0;r<HA.length;r++){var n=HA[r];t.push(hRt(e,n))}return t}function dRt(e){for(var t=GX(e),r=e,n=0;n<HA.length;n++)if(t[n]>0){r=HA[n];break}return r}function vRt(e,t){if(!(e<1||t<1)){for(var r=GX(e),n=GX(t),i=1,a=0;a<HA.length;a++)i*=Math.pow(HA[a],Math.max(r[a],n[a]));return i}}function pRt(e){if(e.length!==0){for(var t=1,r=0;r<e.length;r++)t=vRt(t,e[r]);return t}}Jg.calcXnums=function(e){var t,r=[];for(t=1;t<e;t++){var n=this.getXat(t-1,0),i=this.getXat(t,0);i!==n&&n!==void 0&&n!==null&&i!==void 0&&i!==null?r[t-1]=Math.abs(i-n):r[t-1]=0}var a=0;for(t=1;t<e;t++)a+=r[t-1];for(t=1;t<e;t++)r[t-1]===0?r[t-1]=1:r[t-1]=Math.round(a/r[t-1]);return r};Jg.calcYnums=function(e){var t,r=[];for(t=1;t<e;t++){var n=this.getYat(0,t-1),i=this.getYat(0,t);i!==n&&n!==void 0&&n!==null&&i!==void 0&&i!==null?r[t-1]=Math.abs(i-n):r[t-1]=0}var a=0;for(t=1;t<e;t++)a+=r[t-1];for(t=1;t<e;t++)r[t-1]===0?r[t-1]=1:r[t-1]=Math.round(a/r[t-1]);return r};var e8e=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],$Ie=e8e[9],nF=e8e[13];Jg.estimateScale=function(e,t){for(var r=t===0?this.calcXnums(e):this.calcYnums(e),n=1+pRt(r);n<$Ie;)n*=2;for(;n>nF;)n--,n/=dRt(n),n++,n<$Ie&&(n=nF);var i=Math.round(n/e);return i>1?i:1};function gRt(e,t,r){var n=r[8]+r[2]*t[0]+r[5]*t[1];return e[0]=(r[6]+r[0]*t[0]+r[3]*t[1])/n,e[1]=(r[7]+r[1]*t[0]+r[4]*t[1])/n,e}function mRt(e,t,r){return yRt(e,t,gRt,r),e}function yRt(e,t,r,n){for(var i=[0,0],a=e.shape[0],o=e.shape[1],s=0;s<a;s++)for(var l=0;l<o;l++)r(i,[s,l],n),e.set(s,l,oRt(t,i[0],i[1]));return e}Jg.refineCoords=function(e){for(var t=this.dataScaleX,r=this.dataScaleY,n=e[0].shape[0],i=e[0].shape[1],a=Math.floor(e[0].shape[0]*t+1)|0,o=Math.floor(e[0].shape[1]*r+1)|0,s=1+n+1,l=1+i+1,u=GA(new Float32Array(s*l),[s,l]),c=[1/t,0,0,0,1/r,0,0,0,1],f=0;f<e.length;++f){this.surface.padField(u,e[f]);var h=GA(new Float32Array(a*o),[a,o]);mRt(h,u,c),e[f]=h}};function _Rt(e,t){for(var r=!1,n=0;n<e.length;n++)if(t===e[n]){r=!0;break}r===!1&&e.push(t)}Jg.setContourLevels=function(){var e=[[],[],[]],t=[!1,!1,!1],r=!1,n,i,a;for(n=0;n<3;++n)if(this.showContour[n]&&(r=!0,this.contourSize[n]>0&&this.contourStart[n]!==null&&this.contourEnd[n]!==null&&this.contourEnd[n]>this.contourStart[n]))for(t[n]=!0,i=this.contourStart[n];i<this.contourEnd[n];i+=this.contourSize[n])a=i*this.scene.dataScale[n],_Rt(e[n],a);if(r){var o=[[],[],[]];for(n=0;n<3;++n)this.showContour[n]&&(o[n]=t[n]?e[n]:this.scene.contourLevels[n]);this.surface.update({levels:o})}};Jg.update=function(e){var t=this.scene,r=t.fullSceneLayout,n=this.surface,i=uRt(e),a=t.dataScale,o=e.z[0].length,s=e._ylength,l=t.contourLevels;this.data=e;var u,c,f,h,d=[];for(u=0;u<3;u++)for(d[u]=[],c=0;c<o;c++)d[u][c]=[];for(c=0;c<o;c++)for(f=0;f<s;f++)d[0][c][f]=this.getXat(c,f,e.xcalendar,r.xaxis),d[1][c][f]=this.getYat(c,f,e.ycalendar,r.yaxis),d[2][c][f]=this.getZat(c,f,e.zcalendar,r.zaxis);if(e.connectgaps)for(e._emptypoints=lRt(d[2]),sRt(d[2],e._emptypoints),e._interpolatedZ=[],c=0;c<o;c++)for(e._interpolatedZ[c]=[],f=0;f<s;f++)e._interpolatedZ[c][f]=d[2][c][f];for(u=0;u<3;u++)for(c=0;c<o;c++)for(f=0;f<s;f++)h=d[u][c][f],h==null?d[u][c][f]=NaN:h=d[u][c][f]*=a[u];for(u=0;u<3;u++)for(c=0;c<o;c++)for(f=0;f<s;f++)h=d[u][c][f],h!=null&&(this.minValues[u]>h&&(this.minValues[u]=h),this.maxValues[u]<h&&(this.maxValues[u]=h));for(u=0;u<3;u++)this.objectOffset[u]=.5*(this.minValues[u]+this.maxValues[u]);for(u=0;u<3;u++)for(c=0;c<o;c++)for(f=0;f<s;f++)h=d[u][c][f],h!=null&&(d[u][c][f]-=this.objectOffset[u]);var v=[GA(new Float32Array(o*s),[o,s]),GA(new Float32Array(o*s),[o,s]),GA(new Float32Array(o*s),[o,s])];for(u=0;u<3;u++)for(c=0;c<o;c++)for(f=0;f<s;f++)v[u].set(c,f,d[u][c][f]);d=[];var _={colormap:i,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!e.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:e.opacityscale,opacity:e.opacity},b=cRt(e);if(_.intensityBounds=[b.min,b.max],e.surfacecolor){var p=GA(new Float32Array(o*s),[o,s]);for(c=0;c<o;c++)for(f=0;f<s;f++)p.set(c,f,e.surfacecolor[f][c]);v.push(p)}else _.intensityBounds[0]*=a[2],_.intensityBounds[1]*=a[2];(nF<v[0].shape[0]||nF<v[0].shape[1])&&(this.refineData=!1),this.refineData===!0&&(this.dataScaleX=this.estimateScale(v[0].shape[0],0),this.dataScaleY=this.estimateScale(v[0].shape[1],1),(this.dataScaleX!==1||this.dataScaleY!==1)&&this.refineCoords(v)),e.surfacecolor&&(_.intensity=v.pop());var k=[!0,!0,!0],E=[\"x\",\"y\",\"z\"];for(u=0;u<3;++u){var S=e.contours[E[u]];k[u]=S.highlight,_.showContour[u]=S.show||S.highlight,_.showContour[u]&&(_.contourProject[u]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[u]=!0,_.levels[u]=l[u],n.highlightColor[u]=_.contourColor[u]=JIe(S.color),S.usecolormap?n.highlightTint[u]=_.contourTint[u]=0:n.highlightTint[u]=_.contourTint[u]=1,_.contourWidth[u]=S.width,this.contourStart[u]=S.start,this.contourEnd[u]=S.end,this.contourSize[u]=S.size):(this.showContour[u]=!1,this.contourStart[u]=null,this.contourEnd[u]=null,this.contourSize[u]=0),S.highlight&&(_.dynamicColor[u]=JIe(S.highlightcolor),_.dynamicWidth[u]=S.highlightwidth))}fRt(i)&&(_.vertexColor=!0),_.objectOffset=this.objectOffset,_.coords=v,n.update(_),n.visible=e.visible,n.enableDynamic=k,n.enableHighlight=k,n.snapToData=!0,\"lighting\"in e&&(n.ambientLight=e.lighting.ambient,n.diffuseLight=e.lighting.diffuse,n.specularLight=e.lighting.specular,n.roughness=e.lighting.roughness,n.fresnel=e.lighting.fresnel),\"lightposition\"in e&&(n.lightPosition=[e.lightposition.x,e.lightposition.y,e.lightposition.z])};Jg.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()};function xRt(e,t){var r=e.glplot.gl,n=aRt({gl:r}),i=new QIe(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}t8e.exports=xRt});var n8e=ye((wgr,i8e)=>{\"use strict\";i8e.exports={attributes:JE(),supplyDefaults:VX().supplyDefaults,colorbar:{min:\"cmin\",max:\"cmax\"},calc:KIe(),plot:r8e(),moduleType:\"trace\",name:\"surface\",basePlotModule:$_(),categories:[\"gl3d\",\"2dMap\",\"showLegend\"],meta:{}}});var o8e=ye((Tgr,a8e)=>{\"use strict\";a8e.exports=n8e()});var jA=ye((Agr,l8e)=>{\"use strict\";var bRt=Tu(),HX=df().axisHoverFormat,{hovertemplateAttrs:wRt,templatefallbackAttrs:TRt}=Ll(),Q_=JE(),s8e=Gl(),ex=Ao().extendFlat;l8e.exports=ex({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:wRt({editType:\"calc\"}),hovertemplatefallback:TRt({editType:\"calc\"}),xhoverformat:HX(\"x\"),yhoverformat:HX(\"y\"),zhoverformat:HX(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"}},bRt(\"\",{colorAttr:\"`intensity`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:Q_.opacity,flatshading:{valType:\"boolean\",dflt:!1,editType:\"calc\"},contour:{show:ex({},Q_.contours.x.show,{}),color:Q_.contours.x.color,width:Q_.contours.x.width,editType:\"calc\"},lightposition:{x:ex({},Q_.lightposition.x,{dflt:1e5}),y:ex({},Q_.lightposition.y,{dflt:1e5}),z:ex({},Q_.lightposition.z,{dflt:0}),editType:\"calc\"},lighting:ex({vertexnormalsepsilon:{valType:\"number\",min:0,max:1,dflt:1e-12,editType:\"calc\",description:\"Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry.\"},facenormalsepsilon:{valType:\"number\",min:0,max:1,dflt:1e-6,editType:\"calc\",description:\"Epsilon for face normals calculation avoids math issues arising from degenerate geometry.\"},editType:\"calc\"},Q_.lighting),hoverinfo:ex({},s8e.hoverinfo,{editType:\"calc\"}),showlegend:ex({},s8e.showlegend,{dflt:!1})})});var oF=ye((Sgr,c8e)=>{\"use strict\";var ARt=Tu(),aF=df().axisHoverFormat,{hovertemplateAttrs:SRt,templatefallbackAttrs:MRt}=Ll(),QE=jA(),u8e=Gl(),jX=Ao().extendFlat,ERt=mc().overrideAll;function WX(e){return{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}}}function XX(e){return{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}}}var WA=c8e.exports=ERt(jX({x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},value:{valType:\"data_array\"},isomin:{valType:\"number\"},isomax:{valType:\"number\"},surface:{show:{valType:\"boolean\",dflt:!0},count:{valType:\"integer\",dflt:2,min:1},fill:{valType:\"number\",min:0,max:1,dflt:1},pattern:{valType:\"flaglist\",flags:[\"A\",\"B\",\"C\",\"D\",\"E\"],extras:[\"all\",\"odd\",\"even\"],dflt:\"all\"}},spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:.15}},slices:{x:WX(\"x\"),y:WX(\"y\"),z:WX(\"z\")},caps:{x:XX(\"x\"),y:XX(\"y\"),z:XX(\"z\")},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:SRt(),hovertemplatefallback:MRt(),xhoverformat:aF(\"x\"),yhoverformat:aF(\"y\"),zhoverformat:aF(\"z\"),valuehoverformat:aF(\"value\",1),showlegend:jX({},u8e.showlegend,{dflt:!1})},ARt(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:QE.opacity,lightposition:QE.lightposition,lighting:QE.lighting,flatshading:QE.flatshading,contour:QE.contour,hoverinfo:jX({},u8e.hoverinfo)}),\"calc\",\"nested\");WA.flatshading.dflt=!0;WA.lighting.facenormalsepsilon.dflt=0;WA.x.editType=WA.y.editType=WA.z.editType=WA.value.editType=\"calc+clearAxisTypes\"});var ZX=ye((Mgr,h8e)=>{\"use strict\";var kRt=Dr(),CRt=qa(),LRt=oF(),PRt=Qh();function IRt(e,t,r,n){function i(a,o){return kRt.coerce(e,t,LRt,a,o)}f8e(e,t,r,n,i)}function f8e(e,t,r,n,i){var a=i(\"isomin\"),o=i(\"isomax\");o!=null&&a!==void 0&&a!==null&&a>o&&(t.isomin=null,t.isomax=null);var s=i(\"x\"),l=i(\"y\"),u=i(\"z\"),c=i(\"value\");if(!s||!s.length||!l||!l.length||!u||!u.length||!c||!c.length){t.visible=!1;return}var f=CRt.getComponentMethod(\"calendars\",\"handleTraceDefaults\");f(e,t,[\"x\",\"y\",\"z\"],n),i(\"valuehoverformat\"),[\"x\",\"y\",\"z\"].forEach(function(_){i(_+\"hoverformat\");var b=\"caps.\"+_,p=i(b+\".show\");p&&i(b+\".fill\");var k=\"slices.\"+_,E=i(k+\".show\");E&&(i(k+\".fill\"),i(k+\".locations\"))});var h=i(\"spaceframe.show\");h&&i(\"spaceframe.fill\");var d=i(\"surface.show\");d&&(i(\"surface.count\"),i(\"surface.fill\"),i(\"surface.pattern\"));var v=i(\"contour.show\");v&&(i(\"contour.color\"),i(\"contour.width\")),[\"text\",\"hovertext\",\"hovertemplate\",\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"opacity\"].forEach(function(_){i(_)}),PRt(e,t,n,i,{prefix:\"\",cLetter:\"c\"}),t._length=null}h8e.exports={supplyDefaults:IRt,supplyIsoDefaults:f8e}});var sF=ye((Egr,v8e)=>{\"use strict\";var KX=Dr(),RRt=gv();function DRt(e,t){t._len=Math.min(t.u.length,t.v.length,t.w.length,t.x.length,t.y.length,t.z.length),t._u=jm(t.u,t._len),t._v=jm(t.v,t._len),t._w=jm(t.w,t._len),t._x=jm(t.x,t._len),t._y=jm(t.y,t._len),t._z=jm(t.z,t._len);var r=d8e(t);t._gridFill=r.fill,t._Xs=r.Xs,t._Ys=r.Ys,t._Zs=r.Zs,t._len=r.len;var n=0,i,a,o;t.starts&&(i=jm(t.starts.x||[]),a=jm(t.starts.y||[]),o=jm(t.starts.z||[]),n=Math.min(i.length,a.length,o.length)),t._startsX=i||[],t._startsY=a||[],t._startsZ=o||[];var s=0,l=1/0,u;for(u=0;u<t._len;u++){var c=t._u[u],f=t._v[u],h=t._w[u],d=Math.sqrt(c*c+f*f+h*h);s=Math.max(s,d),l=Math.min(l,d)}for(RRt(e,t,{vals:[l,s],containerStr:\"\",cLetter:\"c\"}),u=0;u<n;u++){var v=i[u];r.xMax=Math.max(r.xMax,v),r.xMin=Math.min(r.xMin,v);var _=a[u];r.yMax=Math.max(r.yMax,_),r.yMin=Math.min(r.yMin,_);var b=o[u];r.zMax=Math.max(r.zMax,b),r.zMin=Math.min(r.zMin,b)}t._slen=n,t._normMax=s,t._xbnds=[r.xMin,r.xMax],t._ybnds=[r.yMin,r.yMax],t._zbnds=[r.zMin,r.zMax]}function d8e(e){var t=e._x,r=e._y,n=e._z,i=e._len,a,o,s,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,d=1/0,v=\"\",_,b,p,k,E,S,L,x,C;for(i&&(k=t[0],S=r[0],x=n[0]),i>1&&(E=t[i-1],L=r[i-1],C=n[i-1]),a=0;a<i;a++)l=Math.max(l,t[a]),u=Math.min(u,t[a]),c=Math.max(c,r[a]),f=Math.min(f,r[a]),h=Math.max(h,n[a]),d=Math.min(d,n[a]),!_&&t[a]!==k&&(_=!0,v+=\"x\"),!b&&r[a]!==S&&(b=!0,v+=\"y\"),!p&&n[a]!==x&&(p=!0,v+=\"z\");_||(v+=\"x\"),b||(v+=\"y\"),p||(v+=\"z\");var M=YX(e._x),g=YX(e._y),P=YX(e._z);v=v.replace(\"x\",(k>E?\"-\":\"+\")+\"x\"),v=v.replace(\"y\",(S>L?\"-\":\"+\")+\"y\"),v=v.replace(\"z\",(x>C?\"-\":\"+\")+\"z\");var T=function(){i=0,M=[],g=[],P=[]};(!i||i<M.length*g.length*P.length)&&T();var z=function(Fe){return Fe===\"x\"?t:Fe===\"y\"?r:n},O=function(Fe){return Fe===\"x\"?M:Fe===\"y\"?g:P},V=function(Fe){return Fe[i-1]<Fe[0]?-1:1},G=z(v[1]),Z=z(v[3]),H=z(v[5]),N=O(v[1]).length,j=O(v[3]).length,re=O(v[5]).length,oe=!1,_e=function(Fe,Pe,ge){return N*(j*Fe+Pe)+ge},Ee=V(z(v[1])),Ce=V(z(v[3])),me=V(z(v[5]));for(a=0;a<re-1;a++){for(o=0;o<j-1;o++){for(s=0;s<N-1;s++){var ie=_e(a,o,s),Se=_e(a,o,s+1),Le=_e(a,o+1,s),Ae=_e(a+1,o,s);if((!(G[ie]*Ee<G[Se]*Ee)||!(Z[ie]*Ce<Z[Le]*Ce)||!(H[ie]*me<H[Ae]*me))&&(oe=!0),oe)break}if(oe)break}if(oe)break}return oe&&(KX.warn(\"Encountered arbitrary coordinates! 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XA=ye((Cgr,g8e)=>{\"use strict\";g8e.exports=function(t,r,n,i){i=i||t.length;for(var a=new Array(i),o=0;o<i;o++)a[o]=[t[o],r[o],n[o]];return a}});var uF=ye((Lgr,x8e)=>{\"use strict\";var ORt=Od().gl_mesh3d,qRt=$y().parseColorScale,BRt=Dr().isArrayOrTypedArray,NRt=Jy(),URt=tc().extractOpts,m8e=XA(),ek=function(e,t){for(var r=t.length-1;r>0;r--){var n=Math.min(t[r],t[r-1]),i=Math.max(t[r],t[r-1]);if(i>n&&n<e&&e<=i)return{id:r,distRatio:(i-e)/(i-n)}}return{id:0,distRatio:0}};function y8e(e,t,r){this.scene=e,this.uid=r,this.mesh=t,this.name=\"\",this.data=null,this.showContour=!1}var $X=y8e.prototype;$X.handlePick=function(e){if(e.object===this.mesh){var t=e.data.index,r=this.data._meshX[t],n=this.data._meshY[t],i=this.data._meshZ[t],a=this.data._Ys.length,o=this.data._Zs.length,s=ek(r,this.data._Xs).id,l=ek(n,this.data._Ys).id,u=ek(i,this.data._Zs).id,c=e.index=u+o*l+o*a*s;e.traceCoordinate=[this.data._meshX[c],this.data._meshY[c],this.data._meshZ[c],this.data._value[c]];var f=this.data.hovertext||this.data.text;return BRt(f)&&f[c]!==void 0?e.textLabel=f[c]:f&&(e.textLabel=f),!0}};$X.update=function(e){var t=this.scene,r=t.fullSceneLayout;this.data=_8e(e);function n(l,u,c,f){return u.map(function(h){return l.d2l(h,0,f)*c})}var i=m8e(n(r.xaxis,e._meshX,t.dataScale[0],e.xcalendar),n(r.yaxis,e._meshY,t.dataScale[1],e.ycalendar),n(r.zaxis,e._meshZ,t.dataScale[2],e.zcalendar)),a=m8e(e._meshI,e._meshJ,e._meshK),o={positions:i,cells:a,lightPosition:[e.lightposition.x,e.lightposition.y,e.lightposition.z],ambient:e.lighting.ambient,diffuse:e.lighting.diffuse,specular:e.lighting.specular,roughness:e.lighting.roughness,fresnel:e.lighting.fresnel,vertexNormalsEpsilon:e.lighting.vertexnormalsepsilon,faceNormalsEpsilon:e.lighting.facenormalsepsilon,opacity:e.opacity,contourEnable:e.contour.show,contourColor:NRt(e.contour.color).slice(0,3),contourWidth:e.contour.width,useFacetNormals:e.flatshading},s=URt(e);o.vertexIntensity=e._meshIntensity,o.vertexIntensityBounds=[s.min,s.max],o.colormap=qRt(e),this.mesh.update(o)};$X.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};var VRt=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"];function _8e(e){e._meshI=[],e._meshJ=[],e._meshK=[];var t=e.surface.show,r=e.spaceframe.show,n=e.surface.fill,i=e.spaceframe.fill,a=!1,o=!1,s=0,l,u,c=e._Xs,f=e._Ys,h=e._Zs,d=c.length,v=f.length,_=h.length,b=VRt.indexOf(e._gridFill.replace(/-/g,\"\").replace(/\\+/g,\"\")),p=function(Qt,Vt,_t){switch(b){case 5:return _t+_*Vt+_*v*Qt;case 4:return _t+_*Qt+_*d*Vt;case 3:return Vt+v*_t+v*_*Qt;case 2:return Vt+v*Qt+v*d*_t;case 1:return Qt+d*_t+d*_*Vt;default:return Qt+d*Vt+d*v*_t}},k=e._minValues,E=e._maxValues,S=e._vMin,L=e._vMax,x,C,M,g;function P(Qt,Vt,_t){for(var It=g.length,mt=u;mt<It;mt++)if(Qt===x[mt]&&Vt===C[mt]&&_t===M[mt])return mt;return-1}function T(){u=l}function z(){x=[],C=[],M=[],g=[],l=0,T()}function O(Qt,Vt,_t,It){return x.push(Qt),C.push(Vt),M.push(_t),g.push(It),l++,l-1}function V(Qt,Vt,_t){return e._meshI.push(Qt),e._meshJ.push(Vt),e._meshK.push(_t),s++,s-1}function G(Qt,Vt,_t){for(var It=[],mt=0;mt<Qt.length;mt++)It[mt]=(Qt[mt]+Vt[mt]+_t[mt])/3;return It}function Z(Qt,Vt,_t){for(var It=[],mt=0;mt<Qt.length;mt++)It[mt]=Qt[mt]*(1-_t)+_t*Vt[mt];return It}var H;function N(Qt){H=Qt}function j(Qt,Vt){var _t=Qt[0],It=Qt[1],mt=Qt[2],er=G(_t,It,mt),lr=Math.sqrt(1-H),Tr=Z(er,_t,lr),Lr=Z(er,It,lr),ti=Z(er,mt,lr),Br=Vt[0],Vr=Vt[1],dt=Vt[2];return{xyzv:[[_t,It,Lr],[Lr,Tr,_t],[It,mt,ti],[ti,Lr,It],[mt,_t,Tr],[Tr,ti,mt]],abc:[[Br,Vr,-1],[-1,-1,Br],[Vr,dt,-1],[-1,-1,Vr],[dt,Br,-1],[-1,-1,dt]]}}function re(Qt,Vt){return Qt===\"all\"||Qt===null?!0:Qt.indexOf(Vt)>-1}function oe(Qt,Vt){return Qt===null?Vt:Qt}function _e(Qt,Vt,_t){T();var It=[Vt],mt=[_t];if(H>=1)It=[Vt],mt=[_t];else if(H>0){var er=j(Vt,_t);It=er.xyzv,mt=er.abc}for(var lr=0;lr<It.length;lr++){Vt=It[lr],_t=mt[lr];for(var Tr=[],Lr=0;Lr<3;Lr++){var ti=Vt[Lr][0],Br=Vt[Lr][1],Vr=Vt[Lr][2],dt=Vt[Lr][3],Ge=_t[Lr]>-1?_t[Lr]:P(ti,Br,Vr);Ge>-1?Tr[Lr]=Ge:Tr[Lr]=O(ti,Br,Vr,oe(Qt,dt))}V(Tr[0],Tr[1],Tr[2])}}function Ee(Qt,Vt,_t){var It=function(mt,er,lr){_e(Qt,[Vt[mt],Vt[er],Vt[lr]],[_t[mt],_t[er],_t[lr]])};It(0,1,2),It(2,3,0)}function Ce(Qt,Vt,_t){var It=function(mt,er,lr){_e(Qt,[Vt[mt],Vt[er],Vt[lr]],[_t[mt],_t[er],_t[lr]])};It(0,1,2),It(3,0,1),It(2,3,0),It(1,2,3)}function me(Qt,Vt,_t,It){var mt=Qt[3];mt<_t&&(mt=_t),mt>It&&(mt=It);for(var er=(Qt[3]-mt)/(Qt[3]-Vt[3]+1e-9),lr=[],Tr=0;Tr<4;Tr++)lr[Tr]=(1-er)*Qt[Tr]+er*Vt[Tr];return lr}function ie(Qt,Vt,_t){return Qt>=Vt&&Qt<=_t}function Se(Qt){var Vt=.001*(L-S);return Qt>=S-Vt&&Qt<=L+Vt}function Le(Qt){for(var Vt=[],_t=0;_t<4;_t++){var It=Qt[_t];Vt.push([e._x[It],e._y[It],e._z[It],e._value[It]])}return Vt}var Ae=3;function Fe(Qt,Vt,_t,It,mt,er){er||(er=1),_t=[-1,-1,-1];var lr=!1,Tr=[ie(Vt[0][3],It,mt),ie(Vt[1][3],It,mt),ie(Vt[2][3],It,mt)];if(!Tr[0]&&!Tr[1]&&!Tr[2])return!1;var Lr=function(Br,Vr,dt){return Se(Vr[0][3])&&Se(Vr[1][3])&&Se(Vr[2][3])?(_e(Br,Vr,dt),!0):er<Ae?Fe(Br,Vr,dt,S,L,++er):!1};if(Tr[0]&&Tr[1]&&Tr[2])return Lr(Qt,Vt,_t)||lr;var ti=!1;return[[0,1,2],[2,0,1],[1,2,0]].forEach(function(Br){if(Tr[Br[0]]&&Tr[Br[1]]&&!Tr[Br[2]]){var Vr=Vt[Br[0]],dt=Vt[Br[1]],Ge=Vt[Br[2]],Je=me(Ge,Vr,It,mt),je=me(Ge,dt,It,mt);lr=Lr(Qt,[je,Je,Vr],[-1,-1,_t[Br[0]]])||lr,lr=Lr(Qt,[Vr,dt,je],[_t[Br[0]],_t[Br[1]],-1])||lr,ti=!0}}),ti||[[0,1,2],[1,2,0],[2,0,1]].forEach(function(Br){if(Tr[Br[0]]&&!Tr[Br[1]]&&!Tr[Br[2]]){var Vr=Vt[Br[0]],dt=Vt[Br[1]],Ge=Vt[Br[2]],Je=me(dt,Vr,It,mt),je=me(Ge,Vr,It,mt);lr=Lr(Qt,[je,Je,Vr],[-1,-1,_t[Br[0]]])||lr,ti=!0}}),lr}function Pe(Qt,Vt,_t,It){var mt=!1,er=Le(Vt),lr=[ie(er[0][3],_t,It),ie(er[1][3],_t,It),ie(er[2][3],_t,It),ie(er[3][3],_t,It)];if(!lr[0]&&!lr[1]&&!lr[2]&&!lr[3])return mt;if(lr[0]&&lr[1]&&lr[2]&&lr[3])return o&&(mt=Ce(Qt,er,Vt)||mt),mt;var Tr=!1;return[[0,1,2,3],[3,0,1,2],[2,3,0,1],[1,2,3,0]].forEach(function(Lr){if(lr[Lr[0]]&&lr[Lr[1]]&&lr[Lr[2]]&&!lr[Lr[3]]){var ti=er[Lr[0]],Br=er[Lr[1]],Vr=er[Lr[2]],dt=er[Lr[3]];if(o)mt=_e(Qt,[ti,Br,Vr],[Vt[Lr[0]],Vt[Lr[1]],Vt[Lr[2]]])||mt;else{var Ge=me(dt,ti,_t,It),Je=me(dt,Br,_t,It),je=me(dt,Vr,_t,It);mt=_e(null,[Ge,Je,je],[-1,-1,-1])||mt}Tr=!0}}),Tr||([[0,1,2,3],[1,2,3,0],[2,3,0,1],[3,0,1,2],[0,2,3,1],[1,3,2,0]].forEach(function(Lr){if(lr[Lr[0]]&&lr[Lr[1]]&&!lr[Lr[2]]&&!lr[Lr[3]]){var ti=er[Lr[0]],Br=er[Lr[1]],Vr=er[Lr[2]],dt=er[Lr[3]],Ge=me(Vr,ti,_t,It),Je=me(Vr,Br,_t,It),je=me(dt,Br,_t,It),tt=me(dt,ti,_t,It);o?(mt=_e(Qt,[ti,tt,Ge],[Vt[Lr[0]],-1,-1])||mt,mt=_e(Qt,[Br,Je,je],[Vt[Lr[1]],-1,-1])||mt):mt=Ee(null,[Ge,Je,je,tt],[-1,-1,-1,-1])||mt,Tr=!0}}),Tr)||[[0,1,2,3],[1,2,3,0],[2,3,0,1],[3,0,1,2]].forEach(function(Lr){if(lr[Lr[0]]&&!lr[Lr[1]]&&!lr[Lr[2]]&&!lr[Lr[3]]){var ti=er[Lr[0]],Br=er[Lr[1]],Vr=er[Lr[2]],dt=er[Lr[3]],Ge=me(Br,ti,_t,It),Je=me(Vr,ti,_t,It),je=me(dt,ti,_t,It);o?(mt=_e(Qt,[ti,Ge,Je],[Vt[Lr[0]],-1,-1])||mt,mt=_e(Qt,[ti,Je,je],[Vt[Lr[0]],-1,-1])||mt,mt=_e(Qt,[ti,je,Ge],[Vt[Lr[0]],-1,-1])||mt):mt=_e(null,[Ge,Je,je],[-1,-1,-1])||mt,Tr=!0}}),mt}function ge(Qt,Vt,_t,It,mt,er,lr,Tr,Lr,ti,Br){var Vr=!1;return a&&(re(Qt,\"A\")&&(Vr=Pe(null,[Vt,_t,It,er],ti,Br)||Vr),re(Qt,\"B\")&&(Vr=Pe(null,[_t,It,mt,Lr],ti,Br)||Vr),re(Qt,\"C\")&&(Vr=Pe(null,[_t,er,lr,Lr],ti,Br)||Vr),re(Qt,\"D\")&&(Vr=Pe(null,[It,er,Tr,Lr],ti,Br)||Vr),re(Qt,\"E\")&&(Vr=Pe(null,[_t,It,er,Lr],ti,Br)||Vr)),o&&(Vr=Pe(Qt,[_t,It,er,Lr],ti,Br)||Vr),Vr}function Re(Qt,Vt,_t,It,mt,er,lr,Tr){return[Tr[0]===!0?!0:Fe(Qt,Le([Vt,_t,It]),[Vt,_t,It],er,lr),Tr[1]===!0?!0:Fe(Qt,Le([It,mt,Vt]),[It,mt,Vt],er,lr)]}function ce(Qt,Vt,_t,It,mt,er,lr,Tr,Lr){return Tr?Re(Qt,Vt,_t,mt,It,er,lr,Lr):Re(Qt,_t,mt,It,Vt,er,lr,Lr)}function Ze(Qt,Vt,_t,It,mt,er,lr){var Tr=!1,Lr,ti,Br,Vr,dt=function(){Tr=Fe(Qt,[Lr,ti,Br],[-1,-1,-1],mt,er)||Tr,Tr=Fe(Qt,[Br,Vr,Lr],[-1,-1,-1],mt,er)||Tr},Ge=lr[0],Je=lr[1],je=lr[2];return Ge&&(Lr=Z(Le([p(Vt,_t-0,It-0)])[0],Le([p(Vt-1,_t-0,It-0)])[0],Ge),ti=Z(Le([p(Vt,_t-0,It-1)])[0],Le([p(Vt-1,_t-0,It-1)])[0],Ge),Br=Z(Le([p(Vt,_t-1,It-1)])[0],Le([p(Vt-1,_t-1,It-1)])[0],Ge),Vr=Z(Le([p(Vt,_t-1,It-0)])[0],Le([p(Vt-1,_t-1,It-0)])[0],Ge),dt()),Je&&(Lr=Z(Le([p(Vt-0,_t,It-0)])[0],Le([p(Vt-0,_t-1,It-0)])[0],Je),ti=Z(Le([p(Vt-0,_t,It-1)])[0],Le([p(Vt-0,_t-1,It-1)])[0],Je),Br=Z(Le([p(Vt-1,_t,It-1)])[0],Le([p(Vt-1,_t-1,It-1)])[0],Je),Vr=Z(Le([p(Vt-1,_t,It-0)])[0],Le([p(Vt-1,_t-1,It-0)])[0],Je),dt()),je&&(Lr=Z(Le([p(Vt-0,_t-0,It)])[0],Le([p(Vt-0,_t-0,It-1)])[0],je),ti=Z(Le([p(Vt-0,_t-1,It)])[0],Le([p(Vt-0,_t-1,It-1)])[0],je),Br=Z(Le([p(Vt-1,_t-1,It)])[0],Le([p(Vt-1,_t-1,It-1)])[0],je),Vr=Z(Le([p(Vt-1,_t-0,It)])[0],Le([p(Vt-1,_t-0,It-1)])[0],je),dt()),Tr}function ut(Qt,Vt,_t,It,mt,er,lr,Tr,Lr,ti,Br,Vr){var dt=Qt;return Vr?(a&&Qt===\"even\"&&(dt=null),ge(dt,Vt,_t,It,mt,er,lr,Tr,Lr,ti,Br)):(a&&Qt===\"odd\"&&(dt=null),ge(dt,Lr,Tr,lr,er,mt,It,_t,Vt,ti,Br))}function pt(Qt,Vt,_t,It,mt){for(var er=[],lr=0,Tr=0;Tr<Vt.length;Tr++)for(var Lr=Vt[Tr],ti=1;ti<_;ti++)for(var Br=1;Br<v;Br++)er.push(ce(Qt,p(Lr,Br-1,ti-1),p(Lr,Br-1,ti),p(Lr,Br,ti-1),p(Lr,Br,ti),_t,It,(Lr+Br+ti)%2,mt&&mt[lr]?mt[lr]:[])),lr++;return er}function Zt(Qt,Vt,_t,It,mt){for(var er=[],lr=0,Tr=0;Tr<Vt.length;Tr++)for(var Lr=Vt[Tr],ti=1;ti<d;ti++)for(var Br=1;Br<_;Br++)er.push(ce(Qt,p(ti-1,Lr,Br-1),p(ti,Lr,Br-1),p(ti-1,Lr,Br),p(ti,Lr,Br),_t,It,(ti+Lr+Br)%2,mt&&mt[lr]?mt[lr]:[])),lr++;return er}function st(Qt,Vt,_t,It,mt){for(var er=[],lr=0,Tr=0;Tr<Vt.length;Tr++)for(var Lr=Vt[Tr],ti=1;ti<v;ti++)for(var Br=1;Br<d;Br++)er.push(ce(Qt,p(Br-1,ti-1,Lr),p(Br-1,ti,Lr),p(Br,ti-1,Lr),p(Br,ti,Lr),_t,It,(Br+ti+Lr)%2,mt&&mt[lr]?mt[lr]:[])),lr++;return er}function lt(Qt,Vt,_t){for(var It=1;It<_;It++)for(var mt=1;mt<v;mt++)for(var er=1;er<d;er++)ut(Qt,p(er-1,mt-1,It-1),p(er-1,mt-1,It),p(er-1,mt,It-1),p(er-1,mt,It),p(er,mt-1,It-1),p(er,mt-1,It),p(er,mt,It-1),p(er,mt,It),Vt,_t,(er+mt+It)%2)}function Gt(Qt,Vt,_t){o=!0,lt(Qt,Vt,_t),o=!1}function Nt(Qt,Vt,_t){a=!0,lt(Qt,Vt,_t),a=!1}function Jt(Qt,Vt,_t,It,mt,er){for(var lr=[],Tr=0,Lr=0;Lr<Vt.length;Lr++)for(var ti=Vt[Lr],Br=1;Br<_;Br++)for(var Vr=1;Vr<v;Vr++)lr.push(Ze(Qt,ti,Vr,Br,_t,It,mt[Lr],er&&er[Tr]?er[Tr]:[])),Tr++;return lr}function sr(Qt,Vt,_t,It,mt,er){for(var lr=[],Tr=0,Lr=0;Lr<Vt.length;Lr++)for(var ti=Vt[Lr],Br=1;Br<d;Br++)for(var Vr=1;Vr<_;Vr++)lr.push(Ze(Qt,Br,ti,Vr,_t,It,mt[Lr],er&&er[Tr]?er[Tr]:[])),Tr++;return lr}function wr(Qt,Vt,_t,It,mt,er){for(var lr=[],Tr=0,Lr=0;Lr<Vt.length;Lr++)for(var ti=Vt[Lr],Br=1;Br<v;Br++)for(var Vr=1;Vr<d;Vr++)lr.push(Ze(Qt,Vr,Br,ti,_t,It,mt[Lr],er&&er[Tr]?er[Tr]:[])),Tr++;return lr}function cr(Qt,Vt){for(var _t=[],It=Qt;It<Vt;It++)_t.push(It);return _t}function $e(){for(var Qt=0;Qt<d;Qt++)for(var Vt=0;Vt<v;Vt++)for(var _t=0;_t<_;_t++){var It=p(Qt,Vt,_t);O(e._x[It],e._y[It],e._z[It],e._value[It])}}function St(){z(),$e();var Qt=null;if(r&&i&&(N(i),Gt(Qt,S,L)),t&&n){N(n);for(var Vt=e.surface.pattern,_t=e.surface.count,It=0;It<_t;It++){var mt=_t===1?.5:It/(_t-1),er=(1-mt)*S+mt*L,lr=Math.abs(er-k),Tr=Math.abs(er-E),Lr=lr>Tr?[k,er]:[er,E];Nt(Vt,Lr[0],Lr[1])}}var ti=[[Math.min(S,E),Math.max(S,E)],[Math.min(k,L),Math.max(k,L)]];[\"x\",\"y\",\"z\"].forEach(function(Br){for(var Vr=[],dt=0;dt<ti.length;dt++){var Ge=0,Je=ti[dt][0],je=ti[dt][1],tt=e.slices[Br];if(tt.show&&tt.fill){N(tt.fill);var xt=[],Ie=[],xe=[];if(tt.locations.length)for(var ke=0;ke<tt.locations.length;ke++){var vt=ek(tt.locations[ke],Br===\"x\"?c:Br===\"y\"?f:h);vt.distRatio===0?xt.push(vt.id):vt.id>0&&(Ie.push(vt.id),Br===\"x\"?xe.push([vt.distRatio,0,0]):Br===\"y\"?xe.push([0,vt.distRatio,0]):xe.push([0,0,vt.distRatio]))}else Br===\"x\"?xt=cr(1,d-1):Br===\"y\"?xt=cr(1,v-1):xt=cr(1,_-1);Ie.length>0&&(Br===\"x\"?Vr[Ge]=Jt(Qt,Ie,Je,je,xe,Vr[Ge]):Br===\"y\"?Vr[Ge]=sr(Qt,Ie,Je,je,xe,Vr[Ge]):Vr[Ge]=wr(Qt,Ie,Je,je,xe,Vr[Ge]),Ge++),xt.length>0&&(Br===\"x\"?Vr[Ge]=pt(Qt,xt,Je,je,Vr[Ge]):Br===\"y\"?Vr[Ge]=Zt(Qt,xt,Je,je,Vr[Ge]):Vr[Ge]=st(Qt,xt,Je,je,Vr[Ge]),Ge++)}var ir=e.caps[Br];ir.show&&ir.fill&&(N(ir.fill),Br===\"x\"?Vr[Ge]=pt(Qt,[0,d-1],Je,je,Vr[Ge]):Br===\"y\"?Vr[Ge]=Zt(Qt,[0,v-1],Je,je,Vr[Ge]):Vr[Ge]=st(Qt,[0,_-1],Je,je,Vr[Ge]),Ge++)}}),s===0&&z(),e._meshX=x,e._meshY=C,e._meshZ=M,e._meshIntensity=g,e._Xs=c,e._Ys=f,e._Zs=h}return St(),e}function GRt(e,t){var r=e.glplot.gl,n=ORt({gl:r}),i=new y8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}x8e.exports={findNearestOnAxis:ek,generateIsoMeshes:_8e,createIsosurfaceTrace:GRt}});var w8e=ye((Pgr,b8e)=>{\"use strict\";b8e.exports={attributes:oF(),supplyDefaults:ZX().supplyDefaults,calc:JX(),colorbar:{min:\"cmin\",max:\"cmax\"},plot:uF().createIsosurfaceTrace,moduleType:\"trace\",name:\"isosurface\",basePlotModule:$_(),categories:[\"gl3d\",\"showLegend\"],meta:{}}});var A8e=ye((Igr,T8e)=>{\"use strict\";T8e.exports=w8e()});var eZ=ye((Rgr,M8e)=>{\"use strict\";var HRt=Tu(),yh=oF(),jRt=JE(),S8e=Gl(),QX=Ao().extendFlat,WRt=mc().overrideAll,cF=M8e.exports=WRt(QX({x:yh.x,y:yh.y,z:yh.z,value:yh.value,isomin:yh.isomin,isomax:yh.isomax,surface:yh.surface,spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:1}},slices:yh.slices,caps:yh.caps,text:yh.text,hovertext:yh.hovertext,xhoverformat:yh.xhoverformat,yhoverformat:yh.yhoverformat,zhoverformat:yh.zhoverformat,valuehoverformat:yh.valuehoverformat,hovertemplate:yh.hovertemplate,hovertemplatefallback:yh.hovertemplatefallback},HRt(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{colorbar:yh.colorbar,opacity:yh.opacity,opacityscale:jRt.opacityscale,lightposition:yh.lightposition,lighting:yh.lighting,flatshading:yh.flatshading,contour:yh.contour,hoverinfo:QX({},S8e.hoverinfo),showlegend:QX({},S8e.showlegend,{dflt:!1})}),\"calc\",\"nested\");cF.x.editType=cF.y.editType=cF.z.editType=cF.value.editType=\"calc+clearAxisTypes\"});var k8e=ye((Dgr,E8e)=>{\"use strict\";var XRt=Dr(),ZRt=eZ(),YRt=ZX().supplyIsoDefaults,KRt=VX().opacityscaleDefaults;E8e.exports=function(t,r,n,i){function a(o,s){return XRt.coerce(t,r,ZRt,o,s)}YRt(t,r,n,i,a),KRt(t,r,i,a)}});var I8e=ye((Fgr,P8e)=>{\"use strict\";var JRt=Od().gl_mesh3d,$Rt=$y().parseColorScale,QRt=Dr().isArrayOrTypedArray,eDt=Jy(),tDt=tc().extractOpts,C8e=XA(),tZ=uF().findNearestOnAxis,rDt=uF().generateIsoMeshes;function L8e(e,t,r){this.scene=e,this.uid=r,this.mesh=t,this.name=\"\",this.data=null,this.showContour=!1}var rZ=L8e.prototype;rZ.handlePick=function(e){if(e.object===this.mesh){var t=e.data.index,r=this.data._meshX[t],n=this.data._meshY[t],i=this.data._meshZ[t],a=this.data._Ys.length,o=this.data._Zs.length,s=tZ(r,this.data._Xs).id,l=tZ(n,this.data._Ys).id,u=tZ(i,this.data._Zs).id,c=e.index=u+o*l+o*a*s;e.traceCoordinate=[this.data._meshX[c],this.data._meshY[c],this.data._meshZ[c],this.data._value[c]];var f=this.data.hovertext||this.data.text;return QRt(f)&&f[c]!==void 0?e.textLabel=f[c]:f&&(e.textLabel=f),!0}};rZ.update=function(e){var t=this.scene,r=t.fullSceneLayout;this.data=rDt(e);function n(l,u,c,f){return u.map(function(h){return l.d2l(h,0,f)*c})}var i=C8e(n(r.xaxis,e._meshX,t.dataScale[0],e.xcalendar),n(r.yaxis,e._meshY,t.dataScale[1],e.ycalendar),n(r.zaxis,e._meshZ,t.dataScale[2],e.zcalendar)),a=C8e(e._meshI,e._meshJ,e._meshK),o={positions:i,cells:a,lightPosition:[e.lightposition.x,e.lightposition.y,e.lightposition.z],ambient:e.lighting.ambient,diffuse:e.lighting.diffuse,specular:e.lighting.specular,roughness:e.lighting.roughness,fresnel:e.lighting.fresnel,vertexNormalsEpsilon:e.lighting.vertexnormalsepsilon,faceNormalsEpsilon:e.lighting.facenormalsepsilon,opacity:e.opacity,opacityscale:e.opacityscale,contourEnable:e.contour.show,contourColor:eDt(e.contour.color).slice(0,3),contourWidth:e.contour.width,useFacetNormals:e.flatshading},s=tDt(e);o.vertexIntensity=e._meshIntensity,o.vertexIntensityBounds=[s.min,s.max],o.colormap=$Rt(e),this.mesh.update(o)};rZ.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};function iDt(e,t){var r=e.glplot.gl,n=JRt({gl:r}),i=new L8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}P8e.exports=iDt});var D8e=ye((zgr,R8e)=>{\"use strict\";R8e.exports={attributes:eZ(),supplyDefaults:k8e(),calc:JX(),colorbar:{min:\"cmin\",max:\"cmax\"},plot:I8e(),moduleType:\"trace\",name:\"volume\",basePlotModule:$_(),categories:[\"gl3d\",\"showLegend\"],meta:{}}});var z8e=ye((Ogr,F8e)=>{\"use strict\";F8e.exports=D8e()});var B8e=ye((qgr,q8e)=>{\"use strict\";var nDt=qa(),O8e=Dr(),aDt=Qh(),oDt=jA();q8e.exports=function(t,r,n,i){function a(c,f){return O8e.coerce(t,r,oDt,c,f)}function o(c){var f=c.map(function(h){var d=a(h);return d&&O8e.isArrayOrTypedArray(d)?d:null});return f.every(function(h){return h&&h.length===f[0].length})&&f}var s=o([\"x\",\"y\",\"z\"]);if(!s){r.visible=!1;return}if(o([\"i\",\"j\",\"k\"]),r.i&&(!r.j||!r.k)||r.j&&(!r.k||!r.i)||r.k&&(!r.i||!r.j)){r.visible=!1;return}var l=nDt.getComponentMethod(\"calendars\",\"handleTraceDefaults\");l(t,r,[\"x\",\"y\",\"z\"],i),[\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"alphahull\",\"delaunayaxis\",\"opacity\"].forEach(function(c){a(c)});var u=a(\"contour.show\");u&&(a(\"contour.color\"),a(\"contour.width\")),\"intensity\"in t?(a(\"intensity\"),a(\"intensitymode\"),aDt(t,r,i,a,{prefix:\"\",cLetter:\"c\"})):(r.showscale=!1,\"facecolor\"in t?a(\"facecolor\"):\"vertexcolor\"in t?a(\"vertexcolor\"):a(\"color\",n)),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),a(\"xhoverformat\"),a(\"yhoverformat\"),a(\"zhoverformat\"),r._length=null}});var U8e=ye((Bgr,N8e)=>{\"use strict\";var sDt=gv();N8e.exports=function(t,r){r.intensity&&sDt(t,r,{vals:r.intensity,containerStr:\"\",cLetter:\"c\"})}});var W8e=ye((Ngr,j8e)=>{\"use strict\";var lDt=Od().gl_mesh3d,uDt=Od().delaunay_triangulate,cDt=Od().alpha_shape,fDt=Od().convex_hull,hDt=$y().parseColorScale,dDt=Dr().isArrayOrTypedArray,oZ=Jy(),vDt=tc().extractOpts,V8e=XA();function H8e(e,t,r){this.scene=e,this.uid=r,this.mesh=t,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var sZ=H8e.prototype;sZ.handlePick=function(e){if(e.object===this.mesh){var t=e.index=e.data.index;e.data._cellCenter?e.traceCoordinate=e.data.dataCoordinate:e.traceCoordinate=[this.data.x[t],this.data.y[t],this.data.z[t]];var r=this.data.hovertext||this.data.text;return dDt(r)&&r[t]!==void 0?e.textLabel=r[t]:r&&(e.textLabel=r),!0}};function G8e(e){for(var t=[],r=e.length,n=0;n<r;n++)t[n]=oZ(e[n]);return t}function iZ(e,t,r,n){for(var i=[],a=t.length,o=0;o<a;o++)i[o]=e.d2l(t[o],0,n)*r;return i}function nZ(e){for(var t=[],r=e.length,n=0;n<r;n++)t[n]=Math.round(e[n]);return t}function pDt(e,t){for(var r=[\"x\",\"y\",\"z\"].indexOf(e),n=[],i=t.length,a=0;a<i;a++)n[a]=[t[a][(r+1)%3],t[a][(r+2)%3]];return uDt(n)}function aZ(e,t){for(var r=e.length,n=0;n<r;n++)if(e[n]<=-.5||e[n]>=t-.5)return!1;return!0}sZ.update=function(e){var t=this.scene,r=t.fullSceneLayout;this.data=e;var n=e.x.length,i=V8e(iZ(r.xaxis,e.x,t.dataScale[0],e.xcalendar),iZ(r.yaxis,e.y,t.dataScale[1],e.ycalendar),iZ(r.zaxis,e.z,t.dataScale[2],e.zcalendar)),a;if(e.i&&e.j&&e.k){if(e.i.length!==e.j.length||e.j.length!==e.k.length||!aZ(e.i,n)||!aZ(e.j,n)||!aZ(e.k,n))return;a=V8e(nZ(e.i),nZ(e.j),nZ(e.k))}else e.alphahull===0?a=fDt(i):e.alphahull>0?a=cDt(e.alphahull,i):a=pDt(e.delaunayaxis,i);var o={positions:i,cells:a,lightPosition:[e.lightposition.x,e.lightposition.y,e.lightposition.z],ambient:e.lighting.ambient,diffuse:e.lighting.diffuse,specular:e.lighting.specular,roughness:e.lighting.roughness,fresnel:e.lighting.fresnel,vertexNormalsEpsilon:e.lighting.vertexnormalsepsilon,faceNormalsEpsilon:e.lighting.facenormalsepsilon,opacity:e.opacity,contourEnable:e.contour.show,contourColor:oZ(e.contour.color).slice(0,3),contourWidth:e.contour.width,useFacetNormals:e.flatshading};if(e.intensity){var s=vDt(e);this.color=\"#fff\";var l=e.intensitymode;o[l+\"Intensity\"]=e.intensity,o[l+\"IntensityBounds\"]=[s.min,s.max],o.colormap=hDt(e)}else e.vertexcolor?(this.color=e.vertexcolor[0],o.vertexColors=G8e(e.vertexcolor)):e.facecolor?(this.color=e.facecolor[0],o.cellColors=G8e(e.facecolor)):(this.color=e.color,o.meshColor=oZ(e.color));this.mesh.update(o)};sZ.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};function gDt(e,t){var r=e.glplot.gl,n=lDt({gl:r}),i=new H8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}j8e.exports=gDt});var Z8e=ye((Ugr,X8e)=>{\"use strict\";X8e.exports={attributes:jA(),supplyDefaults:B8e(),calc:U8e(),colorbar:{min:\"cmin\",max:\"cmax\"},plot:W8e(),moduleType:\"trace\",name:\"mesh3d\",basePlotModule:$_(),categories:[\"gl3d\",\"showLegend\"],meta:{}}});var K8e=ye((Vgr,Y8e)=>{\"use strict\";Y8e.exports=Z8e()});var uZ=ye((Ggr,$8e)=>{\"use strict\";var mDt=Tu(),ZA=df().axisHoverFormat,{hovertemplateAttrs:yDt,templatefallbackAttrs:_Dt}=Ll(),xDt=jA(),J8e=Gl(),lZ=Ao().extendFlat,fF={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"scaled\",\"absolute\",\"raw\"],editType:\"calc\",dflt:\"scaled\"},sizeref:{valType:\"number\",editType:\"calc\",min:0},anchor:{valType:\"enumerated\",editType:\"calc\",values:[\"tip\",\"tail\",\"cm\",\"center\"],dflt:\"cm\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:yDt({editType:\"calc\"},{keys:[\"norm\"]}),hovertemplatefallback:_Dt({editType:\"calc\"}),uhoverformat:ZA(\"u\",1),vhoverformat:ZA(\"v\",1),whoverformat:ZA(\"w\",1),xhoverformat:ZA(\"x\"),yhoverformat:ZA(\"y\"),zhoverformat:ZA(\"z\"),showlegend:lZ({},J8e.showlegend,{dflt:!1})};lZ(fF,mDt(\"\",{colorAttr:\"u/v/w 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Be=[[ve[0],ve[1],_(ve[1]),o(ve[1])],[be[0],be[1],_(be[1]),o(be[1])],[De[0],De[1],_(De[1]),o(De[1])]],et=Be[2],We,it=0;it<3;++it,et=We)We=Be[it],et.v=Br(We[1]-et[1],et[3],et[2],We[3],We[2],We[0]-et[0]),et.point=[0,0];var Ft=Vr(Be[0].v[0],Be[2].v[0],Be[1].v[0]),Ht=Vr(Be[0].v[0],Be[1].v[0],Be[2].v[0]),tr=E-Ft;Be[2].point[1]=0,Be[0].point[0]=-(Be[1].point[0]=Be[0].v[0]/2);var dr=[Be[2].point[0]=Be[0].point[0]+Be[2].v[0]*o(Ft),2*(Be[0].point[1]=Be[1].point[1]=Be[2].v[0]*_(Ft))];function Sr(Or,Wr){var ni=_(Wr),Pi=o(Wr),cn=new Array(3),ln;for(ln=0;ln<3;++ln){var Cn=Be[ln];if(cn[ln]=Br(Wr-Cn[1],Cn[3],Cn[2],Pi,ni,Or-Cn[0]),!cn[ln][0])return Cn.point;cn[ln][1]=dt(cn[ln][1]-Cn.v[1])}var Kn=dr.slice();for(ln=0;ln<3;++ln){var Ta=ln==2?0:ln+1,fa=Vr(Be[ln].v[0],cn[ln][0],cn[Ta][0]);cn[ln][1]<0&&(fa=-fa),ln?ln==1?(fa=Ht-fa,Kn[0]-=cn[ln][0]*o(fa),Kn[1]-=cn[ln][0]*_(fa)):(fa=tr-fa,Kn[0]+=cn[ln][0]*o(fa),Kn[1]+=cn[ln][0]*_(fa)):(Kn[0]+=cn[ln][0]*o(fa),Kn[1]-=cn[ln][0]*_(fa))}return 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De=2-n(be)/G(2*E/3);return[ve*G(6*E)/(2*De),v(be)*O((4-De*De)/3)]};function wi(){return t.geoProjection(In).scale(165.664)}function On(ve,be){var De=G(E*(4+E));return[2/De*ve*(1+G(1-4*be*be/(E*E))),4/De*be]}On.invert=function(ve,be){var De=G(E*(4+E))/2;return[ve*De/(1+G(1-be*be*(4+E)/(4*E))),be*De/2]};function qn(){return t.geoProjection(On).scale(180.739)}function Fn(ve,be){var De=(2+S)*_(be);be/=2;for(var Be=0,et=1/0;Be<10&&n(et)>p;Be++){var We=o(be);be-=et=(be+_(be)*(We+2)-De)/(2*We*(1+We))}return[2/G(E*(4+E))*ve*(1+o(be)),2*G(E/(4+E))*_(be)]}Fn.invert=function(ve,be){var De=be*G((4+E)/E)/2,Be=O(De),et=o(Be);return[ve/(2/G(E*(4+E))*(1+et)),O((Be+De*(et+2))/(2+S))]};function ra(){return t.geoProjection(Fn).scale(180.739)}function la(ve,be){return[ve*(1+o(be))/G(2+E),2*be/G(2+E)]}la.invert=function(ve,be){var De=G(2+E),Be=be*De/2;return[De*ve/(1+o(Be)),Be]};function Ut(){return t.geoProjection(la).scale(173.044)}function wt(ve,be){for(var De=(1+S)*_(be),Be=0,et=1/0;Be<10&&n(et)>p;Be++)be-=et=(be+_(be)-De)/(1+o(be));return De=G(2+E),[ve*(1+o(be))/De,2*be/De]}wt.invert=function(ve,be){var De=1+S,Be=G(De/2);return[ve*2*Be/(1+o(be*=Be)),O((be+_(be))/De)]};function rr(){return t.geoProjection(wt).scale(173.044)}var nr=3+2*C;function Er(ve,be){var De=_(ve/=2),Be=o(ve),et=G(o(be)),We=o(be/=2),it=_(be)/(We+C*Be*et),Ft=G(2/(1+it*it)),Ht=G((C*We+(Be+De)*et)/(C*We+(Be-De)*et));return[nr*(Ft*(Ht-1/Ht)-2*u(Ht)),nr*(Ft*it*(Ht+1/Ht)-2*i(it))]}Er.invert=function(ve,be){if(!(We=Se.invert(ve/1.2,be*1.065)))return null;var De=We[0],Be=We[1],et=20,We;ve/=nr,be/=nr;do{var it=De/2,Ft=Be/2,Ht=_(it),tr=o(it),dr=_(Ft),Sr=o(Ft),Or=o(Be),Wr=G(Or),ni=dr/(Sr+C*tr*Wr),Pi=ni*ni,cn=G(2/(1+Pi)),ln=C*Sr+(tr+Ht)*Wr,Cn=C*Sr+(tr-Ht)*Wr,Kn=ln/Cn,Ta=G(Kn),fa=Ta-1/Ta,$a=Ta+1/Ta,Co=cn*fa-2*u(Ta)-ve,Qa=cn*ni*$a-2*i(ni)-be,mo=dr&&x*Wr*Ht*Pi/dr,Bo=(C*tr*Sr+Wr)/(2*(Sr+C*tr*Wr)*(Sr+C*tr*Wr)*Wr),Ps=-.5*ni*cn*cn*cn,Ts=Ps*mo,wo=Ps*Bo,To=(To=2*Sr+C*Wr*(tr-Ht))*To*Ta,hl=(C*tr*Sr*Wr+Or)/To,Ul=-(C*Ht*dr)/(Wr*To),Lu=fa*Ts-2*hl/Ta+cn*(hl+hl/Kn),au=fa*wo-2*Ul/Ta+cn*(Ul+Ul/Kn),Js=ni*$a*Ts-2*mo/(1+Pi)+cn*$a*mo+cn*ni*(hl-hl/Kn),Ql=ni*$a*wo-2*Bo/(1+Pi)+cn*$a*Bo+cn*ni*(Ul-Ul/Kn),dc=au*Js-Ql*Lu;if(!dc)break;var Tl=(Qa*au-Co*Ql)/dc,Al=(Co*Js-Qa*Lu)/dc;De-=Tl,Be=c(-S,f(S,Be-Al))}while((n(Tl)>p||n(Al)>p)&&--et>0);return n(n(Be)-S)<p?[0,Be]:et&&[De,Be]};function Xr(){return t.geoProjection(Er).scale(62.5271)}var ri=o(35*T);function Qr(ve,be){var De=b(be/2);return[ve*ri*G(1-De*De),(1+ri)*De]}Qr.invert=function(ve,be){var De=be/(1+ri);return[ve&&ve/(ri*G(1-De*De)),2*i(De)]};function Oi(){return t.geoProjection(Qr).scale(137.152)}function $i(ve,be){var De=be/2,Be=o(De);return[2*ve/M*o(be)*Be*Be,M*b(De)]}$i.invert=function(ve,be){var De=i(be/M),Be=o(De),et=2*De;return[ve*M/2/(o(et)*Be*Be),et]};function tn(){return t.geoProjection($i).scale(135.264)}function fn(ve){var be=1-ve,De=We(E,0)[0]-We(-E,0)[0],Be=We(0,S)[1]-We(0,-S)[1],et=G(2*Be/De);function We(Ht,tr){var dr=o(tr),Sr=_(tr);return[dr/(be+ve*dr)*Ht,be*tr+ve*Sr]}function it(Ht,tr){var dr=We(Ht,tr);return[dr[0]*et,dr[1]/et]}function Ft(Ht){return it(0,Ht)[1]}return it.invert=function(Ht,tr){var dr=Zt(Ft,tr),Sr=Ht/et*(ve+be/o(dr));return[Sr,dr]},it}function yn(){var ve=.5,be=t.geoProjectionMutator(fn),De=be(ve);return De.alpha=function(Be){return arguments.length?be(ve=+Be):ve},De.scale(168.725)}function Sn(ve){return[ve[0]/2,O(b(ve[1]/2*T))*P]}function Ba(ve){return[ve[0]*2,2*i(_(ve[1]*T))*P]}function ua(ve){ve==null&&(ve=t.geoOrthographic);var be=ve(),De=t.geoEquirectangular().scale(P).precision(0).clipAngle(null).translate([0,0]);function Be(We){return be(Sn(We))}be.invert&&(Be.invert=function(We){return Ba(be.invert(We))}),Be.stream=function(We){var it=be.stream(We),Ft=De.stream({point:function(Ht,tr){it.point(Ht/2,O(b(-tr/2*T))*P)},lineStart:function(){it.lineStart()},lineEnd:function(){it.lineEnd()},polygonStart:function(){it.polygonStart()},polygonEnd:function(){it.polygonEnd()}});return Ft.sphere=it.sphere,Ft};function et(We){Be[We]=function(){return arguments.length?(be[We].apply(be,arguments),Be):be[We]()}}return Be.rotate=function(We){return arguments.length?(De.rotate(We),Be):De.rotate()},Be.center=function(We){return arguments.length?(be.center(Sn(We)),Be):Ba(be.center())},et(\"angle\"),et(\"clipAngle\"),et(\"clipExtent\"),et(\"fitExtent\"),et(\"fitHeight\"),et(\"fitSize\"),et(\"fitWidth\"),et(\"scale\"),et(\"translate\"),et(\"precision\"),Be.scale(249.5)}function ma(ve,be){var De=2*E/be,Be=ve*ve;function et(We,it){var Ft=t.geoAzimuthalEquidistantRaw(We,it),Ht=Ft[0],tr=Ft[1],dr=Ht*Ht+tr*tr;if(dr>Be){var Sr=G(dr),Or=a(tr,Ht),Wr=De*d(Or/De),ni=Or-Wr,Pi=ve*o(ni),cn=(ve*_(ni)-ni*_(Pi))/(S-Pi),ln=Wa(ni,cn),Cn=(E-ve)/Fa(ln,Pi,E);Ht=Sr;var Kn=50,Ta;do Ht-=Ta=(ve+Fa(ln,Pi,Ht)*Cn-Sr)/(ln(Ht)*Cn);while(n(Ta)>p&&--Kn>0);tr=ni*_(Ht),Ht<S&&(tr-=cn*(Ht-S));var fa=_(Wr),$a=o(Wr);Ft[0]=Ht*$a-tr*fa,Ft[1]=Ht*fa+tr*$a}return Ft}return et.invert=function(We,it){var Ft=We*We+it*it;if(Ft>Be){var Ht=G(Ft),tr=a(it,We),dr=De*d(tr/De),Sr=tr-dr;We=Ht*o(Sr),it=Ht*_(Sr);for(var Or=We-S,Wr=_(We),ni=it/Wr,Pi=We<S?1/0:0,cn=10;;){var ln=ve*_(ni),Cn=ve*o(ni),Kn=_(Cn),Ta=S-Cn,fa=(ln-ni*Kn)/Ta,$a=Wa(ni,fa);if(n(Pi)<k||!--cn)break;ni-=Pi=(ni*Wr-fa*Or-it)/(Wr-Or*2*(Ta*(Cn+ni*ln*o(Cn)-Kn)-ln*(ln-ni*Kn))/(Ta*Ta))}Ht=ve+Fa($a,Cn,We)*(E-ve)/Fa($a,Cn,E),tr=dr+ni,We=Ht*o(tr),it=Ht*_(tr)}return t.geoAzimuthalEquidistantRaw.invert(We,it)},et}function Wa(ve,be){return function(De){var Be=ve*o(De);return De<S&&(Be-=be),G(1+Be*Be)}}function Fa(ve,be,De){for(var Be=50,et=(De-be)/Be,We=ve(be)+ve(De),it=1,Ft=be;it<Be;++it)We+=2*ve(Ft+=et);return We*.5*et}function Wo(){var ve=6,be=30*T,De=o(be),Be=_(be),et=t.geoProjectionMutator(ma),We=et(be,ve),it=We.stream,Ft=.01,Ht=-o(Ft*T),tr=_(Ft*T);return We.radius=function(dr){return arguments.length?(De=o(be=dr*T),Be=_(be),et(be,ve)):be*P},We.lobes=function(dr){return arguments.length?et(be,ve=+dr):ve},We.stream=function(dr){var Sr=We.rotate(),Or=it(dr),Wr=(We.rotate([0,0]),it(dr));return We.rotate(Sr),Or.sphere=function(){Wr.polygonStart(),Wr.lineStart();for(var ni=0,Pi=2*E/ve,cn=0;ni<ve;++ni,cn-=Pi)Wr.point(a(tr*o(cn),Ht)*P,O(tr*_(cn))*P),Wr.point(a(Be*o(cn-Pi/2),De)*P,O(Be*_(cn-Pi/2))*P);Wr.lineEnd(),Wr.polygonEnd()},Or},We.rotate([90,-40]).scale(91.7095).clipAngle(180-.001)}function da(ve,be,De,Be,et,We,it,Ft){arguments.length<8&&(Ft=0);function Ht(tr,dr){if(!dr)return[ve*tr/E,0];var Sr=dr*dr,Or=ve+Sr*(be+Sr*(De+Sr*Be)),Wr=dr*(et-1+Sr*(We-Ft+Sr*it)),ni=(Or*Or+Wr*Wr)/(2*Wr),Pi=tr*O(Or/ni)/E;return[ni*_(Pi),dr*(1+Sr*Ft)+ni*(1-o(Pi))]}return Ht.invert=function(tr,dr){var Sr=E*tr/ve,Or=dr,Wr,ni,Pi=50;do{var cn=Or*Or,ln=ve+cn*(be+cn*(De+cn*Be)),Cn=Or*(et-1+cn*(We-Ft+cn*it)),Kn=ln*ln+Cn*Cn,Ta=2*Cn,fa=Kn/Ta,$a=fa*fa,Co=O(ln/fa)/E,Qa=Sr*Co,mo=ln*ln,Bo=(2*be+cn*(4*De+cn*6*Be))*Or,Ps=et+cn*(3*We+cn*5*it),Ts=2*(ln*Bo+Cn*(Ps-1)),wo=2*(Ps-1),To=(Ts*Ta-Kn*wo)/(Ta*Ta),hl=o(Qa),Ul=_(Qa),Lu=fa*hl,au=fa*Ul,Js=Sr/E*(1/G(1-mo/$a))*(Bo*fa-ln*To)/$a,Ql=au-tr,dc=Or*(1+cn*Ft)+fa-Lu-dr,Tl=To*Ul+Lu*Js,Al=Lu*Co,X=1+To-(To*hl-au*Js),se=au*Co,Te=Tl*se-X*Al;if(!Te)break;Sr-=Wr=(dc*Tl-Ql*X)/Te,Or-=ni=(Ql*se-dc*Al)/Te}while((n(Wr)>p||n(ni)>p)&&--Pi>0);return[Sr,Or]},Ht}var Wn=da(2.8284,-1.6988,.75432,-.18071,1.76003,-.38914,.042555);function Ga(){return t.geoProjection(Wn).scale(149.995)}var vo=da(2.583819,-.835827,.170354,-.038094,1.543313,-.411435,.082742);function jn(){return t.geoProjection(vo).scale(153.93)}var Mt=da(5/6*E,-.62636,-.0344,0,1.3493,-.05524,0,.045);function kr(){return t.geoProjection(Mt).scale(130.945)}function Jr(ve,be){var De=ve*ve,Be=be*be;return[ve*(1-.162388*Be)*(.87-952426e-9*De*De),be*(1+Be/12)]}Jr.invert=function(ve,be){var De=ve,Be=be,et=50,We;do{var it=Be*Be;Be-=We=(Be*(1+it/12)-be)/(1+it/4)}while(n(We)>p&&--et>0);et=50,ve/=1-.162388*it;do{var Ft=(Ft=De*De)*Ft;De-=We=(De*(.87-952426e-9*Ft)-ve)/(.87-.00476213*Ft)}while(n(We)>p&&--et>0);return[De,Be]};function vi(){return t.geoProjection(Jr).scale(131.747)}var hn=da(2.6516,-.76534,.19123,-.047094,1.36289,-.13965,.031762);function An(){return t.geoProjection(hn).scale(131.087)}function Mn(ve){var be=ve(S,0)[0]-ve(-S,0)[0];function De(Be,et){var We=Be>0?-.5:.5,it=ve(Be+We*E,et);return it[0]-=We*be,it}return ve.invert&&(De.invert=function(Be,et){var We=Be>0?-.5:.5,it=ve.invert(Be+We*be,et),Ft=it[0]-We*E;return Ft<-E?Ft+=2*E:Ft>E&&(Ft-=2*E),it[0]=Ft,it}),De}function Li(ve,be){var De=v(ve),Be=v(be),et=o(be),We=o(ve)*et,it=_(ve)*et,Ft=_(Be*be);ve=n(a(it,Ft)),be=O(We),n(ve-S)>p&&(ve%=S);var Ht=_n(ve>E/4?S-ve:ve,be);return ve>E/4&&(Ft=Ht[0],Ht[0]=-Ht[1],Ht[1]=-Ft),Ht[0]*=De,Ht[1]*=-Be,Ht}Li.invert=function(ve,be){n(ve)>1&&(ve=v(ve)*2-ve),n(be)>1&&(be=v(be)*2-be);var De=v(ve),Be=v(be),et=-De*ve,We=-Be*be,it=We/et<1,Ft=ya(it?We:et,it?et:We),Ht=Ft[0],tr=Ft[1],dr=o(tr);return it&&(Ht=-S-Ht),[De*(a(_(Ht)*dr,-_(tr))+E),Be*O(o(Ht)*dr)]};function _n(ve,be){if(be===S)return[0,0];var De=_(be),Be=De*De,et=Be*Be,We=1+et,it=1+3*et,Ft=1-et,Ht=O(1/G(We)),tr=Ft+Be*We*Ht,dr=(1-De)/tr,Sr=G(dr),Or=dr*We,Wr=G(Or),ni=Sr*Ft,Pi,cn;if(ve===0)return[0,-(ni+Be*Wr)];var ln=o(be),Cn=1/ln,Kn=2*De*ln,Ta=(-3*Be+Ht*it)*Kn,fa=(-tr*ln-(1-De)*Ta)/(tr*tr),$a=.5*fa/Sr,Co=Ft*$a-2*Be*Sr*Kn,Qa=Be*We*fa+dr*it*Kn,mo=-Cn*Kn,Bo=-Cn*Qa,Ps=-2*Cn*Co,Ts=4*ve/E,wo;if(ve>.222*E||be<E/4&&ve>.175*E){if(Pi=(ni+Be*G(Or*(1+et)-ni*ni))/(1+et),ve>E/4)return[Pi,Pi];var To=Pi,hl=.5*Pi;Pi=.5*(hl+To),cn=50;do{var Ul=G(Or-Pi*Pi),Lu=Pi*(Ps+mo*Ul)+Bo*O(Pi/Wr)-Ts;if(!Lu)break;Lu<0?hl=Pi:To=Pi,Pi=.5*(hl+To)}while(n(To-hl)>p&&--cn>0)}else{Pi=p,cn=25;do{var au=Pi*Pi,Js=G(Or-au),Ql=Ps+mo*Js,dc=Pi*Ql+Bo*O(Pi/Wr)-Ts,Tl=Ql+(Bo-mo*au)/Js;Pi-=wo=Js?dc/Tl:0}while(n(wo)>p&&--cn>0)}return[Pi,-ni-Be*G(Or-Pi*Pi)]}function ya(ve,be){for(var De=0,Be=1,et=.5,We=50;;){var it=et*et,Ft=G(et),Ht=O(1/G(1+it)),tr=1-it+et*(1+it)*Ht,dr=(1-Ft)/tr,Sr=G(dr),Or=dr*(1+it),Wr=Sr*(1-it),ni=Or-ve*ve,Pi=G(ni),cn=be+Wr+et*Pi;if(n(Be-De)<k||--We===0||cn===0)break;cn>0?De=et:Be=et,et=.5*(De+Be)}if(!We)return null;var ln=O(Ft),Cn=o(ln),Kn=1/Cn,Ta=2*Ft*Cn,fa=(-3*et+Ht*(1+3*it))*Ta,$a=(-tr*Cn-(1-Ft)*fa)/(tr*tr),Co=.5*$a/Sr,Qa=(1-it)*Co-2*et*Sr*Ta,mo=-2*Kn*Qa,Bo=-Kn*Ta,Ps=-Kn*(et*(1+it)*$a+dr*(1+3*it)*Ta);return[E/4*(ve*(mo+Bo*Pi)+Ps*O(ve/G(Or))),ln]}function Jn(){return t.geoProjection(Mn(Li)).scale(239.75)}function Ma(ve,be,De){var Be,et,We;return ve?(Be=_o(ve,De),be?(et=_o(be,1-De),We=et[1]*et[1]+De*Be[0]*Be[0]*et[0]*et[0],[[Be[0]*et[2]/We,Be[1]*Be[2]*et[0]*et[1]/We],[Be[1]*et[1]/We,-Be[0]*Be[2]*et[0]*et[2]/We],[Be[2]*et[1]*et[2]/We,-De*Be[0]*Be[1]*et[0]/We]]):[[Be[0],0],[Be[1],0],[Be[2],0]]):(et=_o(be,1-De),[[0,et[0]/et[1]],[1/et[1],0],[et[2]/et[1],0]])}function _o(ve,be){var De,Be,et,We,it;if(be<p)return We=_(ve),Be=o(ve),De=be*(ve-We*Be)/4,[We-De*Be,Be+De*We,1-be*We*We/2,ve-De];if(be>=1-p)return De=(1-be)/4,Be=N(ve),We=Z(ve),et=1/Be,it=Be*H(ve),[We+De*(it-ve)/(Be*Be),et-De*We*et*(it-ve),et+De*We*et*(it+ve),2*i(s(ve))-S+De*(it-ve)/Be];var Ft=[1,0,0,0,0,0,0,0,0],Ht=[G(be),0,0,0,0,0,0,0,0],tr=0;for(Be=G(1-be),it=1;n(Ht[tr]/Ft[tr])>p&&tr<8;)De=Ft[tr++],Ht[tr]=(De-Be)/2,Ft[tr]=(De+Be)/2,Be=G(De*Be),it*=2;et=it*Ft[tr]*ve;do We=Ht[tr]*_(Be=et)/Ft[tr],et=(O(We)+et)/2;while(--tr);return[_(et),We=o(et),We/o(et-Be),et]}function No(ve,be,De){var Be=n(ve),et=n(be),We=H(et);if(Be){var it=1/_(Be),Ft=1/(b(Be)*b(Be)),Ht=-(Ft+De*(We*We*it*it)-1+De),tr=(De-1)*Ft,dr=(-Ht+G(Ht*Ht-4*tr))/2;return[po(i(1/G(dr)),De)*v(ve),po(i(G((dr/Ft-1)/De)),1-De)*v(be)]}return[0,po(i(We),1-De)*v(be)]}function po(ve,be){if(!be)return ve;if(be===1)return u(b(ve/2+L));for(var De=1,Be=G(1-be),et=G(be),We=0;n(et)>p;We++){if(ve%E){var it=i(Be*b(ve)/De);it<0&&(it+=E),ve+=it+~~(ve/E)*E}else ve+=ve;et=(De+Be)/2,Be=G(De*Be),et=((De=et)-Be)/2}return ve/(h(2,We)*De)}function Lo(ve,be){var De=(C-1)/(C+1),Be=G(1-De*De),et=po(S,Be*Be),We=-1,it=u(b(E/4+n(be)/2)),Ft=s(We*it)/G(De),Ht=ko(Ft*o(We*ve),Ft*_(We*ve)),tr=No(Ht[0],Ht[1],Be*Be);return[-tr[1],(be>=0?1:-1)*(.5*et-tr[0])]}function ko(ve,be){var De=ve*ve,Be=be+1,et=1-De-be*be;return[.5*((ve>=0?S:-S)-a(et,2*ve)),-.25*u(et*et+4*De)+.5*u(Be*Be+De)]}function Ds(ve,be){var De=be[0]*be[0]+be[1]*be[1];return[(ve[0]*be[0]+ve[1]*be[1])/De,(ve[1]*be[0]-ve[0]*be[1])/De]}Lo.invert=function(ve,be){var De=(C-1)/(C+1),Be=G(1-De*De),et=po(S,Be*Be),We=-1,it=Ma(.5*et-be,-ve,Be*Be),Ft=Ds(it[0],it[1]),Ht=a(Ft[1],Ft[0])/We;return[Ht,2*i(s(.5/We*u(De*Ft[0]*Ft[0]+De*Ft[1]*Ft[1])))-S]};function Fs(){return t.geoProjection(Mn(Lo)).scale(151.496)}function ll(ve){var be=_(ve),De=o(ve),Be=ul(ve);Be.invert=ul(-ve);function et(We,it){var Ft=Be(We,it);We=Ft[0],it=Ft[1];var Ht=_(it),tr=o(it),dr=o(We),Sr=V(be*Ht+De*tr*dr),Or=_(Sr),Wr=n(Or)>p?Sr/Or:1;return[Wr*De*_(We),(n(We)>S?Wr:-Wr)*(be*tr-De*Ht*dr)]}return et.invert=function(We,it){var Ft=G(We*We+it*it),Ht=-_(Ft),tr=o(Ft),dr=Ft*tr,Sr=-it*Ht,Or=Ft*be,Wr=G(dr*dr+Sr*Sr-Or*Or),ni=a(dr*Or+Sr*Wr,Sr*Or-dr*Wr),Pi=(Ft>S?-1:1)*a(We*Ht,Ft*o(ni)*tr+it*_(ni)*Ht);return Be.invert(Pi,ni)},et}function ul(ve){var be=_(ve),De=o(ve);return function(Be,et){var We=o(et),it=o(Be)*We,Ft=_(Be)*We,Ht=_(et);return[a(Ft,it*De-Ht*be),O(Ht*De+it*be)]}}function zl(){var ve=0,be=t.geoProjectionMutator(ll),De=be(ve),Be=De.rotate,et=De.stream,We=t.geoCircle();return De.parallel=function(it){if(!arguments.length)return ve*P;var Ft=De.rotate();return be(ve=it*T).rotate(Ft)},De.rotate=function(it){return arguments.length?(Be.call(De,[it[0],it[1]-ve*P]),We.center([-it[0],-it[1]]),De):(it=Be.call(De),it[1]+=ve*P,it)},De.stream=function(it){return it=et(it),it.sphere=function(){it.polygonStart();var Ft=.01,Ht=We.radius(90-Ft)().coordinates[0],tr=Ht.length-1,dr=-1,Sr;for(it.lineStart();++dr<tr;)it.point((Sr=Ht[dr])[0],Sr[1]);for(it.lineEnd(),Ht=We.radius(90+Ft)().coordinates[0],tr=Ht.length-1,it.lineStart();--dr>=0;)it.point((Sr=Ht[dr])[0],Sr[1]);it.lineEnd(),it.polygonEnd()},it},De.scale(79.4187).parallel(45).clipAngle(180-.001)}var us=3,il=O(1-1/us)*P,As=vr(0);function cl(ve){var be=il*T,De=xt(E,be)[0]-xt(-E,be)[0],Be=As(0,be)[1],et=xt(0,be)[1],We=M-et,it=g/ve,Ft=4/g,Ht=Be+We*We*4/g;function tr(dr,Sr){var Or,Wr=n(Sr);if(Wr>be){var ni=f(ve-1,c(0,l((dr+E)/it)));dr+=E*(ve-1)/ve-ni*it,Or=xt(dr,Wr),Or[0]=Or[0]*g/De-g*(ve-1)/(2*ve)+ni*g/ve,Or[1]=Be+(Or[1]-et)*4*We/g,Sr<0&&(Or[1]=-Or[1])}else Or=As(dr,Sr);return Or[0]*=Ft,Or[1]/=Ht,Or}return tr.invert=function(dr,Sr){dr/=Ft,Sr*=Ht;var Or=n(Sr);if(Or>Be){var Wr=f(ve-1,c(0,l((dr+E)/it)));dr=(dr+E*(ve-1)/ve-Wr*it)*De/g;var ni=xt.invert(dr,.25*(Or-Be)*g/We+et);return ni[0]-=E*(ve-1)/ve-Wr*it,Sr<0&&(ni[1]=-ni[1]),ni}return As.invert(dr,Sr)},tr}function Ks(ve,be){return[ve,be&1?90-p:il]}function zs(ve,be){return[ve,be&1?-90+p:-il]}function Io(ve){return[ve[0]*(1-p),ve[1]]}function ls(ve){var be=[].concat(r.range(-180,180+ve/2,ve).map(Ks),r.range(180,-180-ve/2,-ve).map(zs));return{type:\"Polygon\",coordinates:[ve===180?be.map(Io):be]}}function Zl(){var ve=4,be=t.geoProjectionMutator(cl),De=be(ve),Be=De.stream;return De.lobes=function(et){return arguments.length?be(ve=+et):ve},De.stream=function(et){var We=De.rotate(),it=Be(et),Ft=(De.rotate([0,0]),Be(et));return De.rotate(We),it.sphere=function(){t.geoStream(ls(180/ve),Ft)},it},De.scale(239.75)}function Su(ve){var be=1+ve,De=_(1/be),Be=O(De),et=2*G(E/(We=E+4*Be*be)),We,it=.5*et*(be+G(ve*(2+ve))),Ft=ve*ve,Ht=be*be;function tr(dr,Sr){var Or=1-_(Sr),Wr,ni;if(Or&&Or<2){var Pi=S-Sr,cn=25,ln;do{var Cn=_(Pi),Kn=o(Pi),Ta=Be+a(Cn,be-Kn),fa=1+Ht-2*be*Kn;Pi-=ln=(Pi-Ft*Be-be*Cn+fa*Ta-.5*Or*We)/(2*be*Cn*Ta)}while(n(ln)>k&&--cn>0);Wr=et*G(fa),ni=dr*Ta/E}else Wr=et*(ve+Or),ni=dr*Be/E;return[Wr*_(ni),it-Wr*o(ni)]}return tr.invert=function(dr,Sr){var Or=dr*dr+(Sr-=it)*Sr,Wr=(1+Ht-Or/(et*et))/(2*be),ni=V(Wr),Pi=_(ni),cn=Be+a(Pi,be-Wr);return[O(dr/G(Or))*E/cn,O(1-2*(ni-Ft*Be-be*Pi+(1+Ht-2*be*Wr)*cn)/We)]},tr}function nc(){var ve=1,be=t.geoProjectionMutator(Su),De=be(ve);return De.ratio=function(Be){return arguments.length?be(ve=+Be):ve},De.scale(167.774).center([0,18.67])}var bs=.7109889596207567,Rn=.0528035274542;function _a(ve,be){return be>-bs?(ve=sr(ve,be),ve[1]+=Rn,ve):_t(ve,be)}_a.invert=function(ve,be){return be>-bs?sr.invert(ve,be-Rn):_t.invert(ve,be)};function Vu(){return t.geoProjection(_a).rotate([-20,-55]).scale(164.263).center([0,-5.4036])}function Ol(ve,be){return n(be)>bs?(ve=sr(ve,be),ve[1]-=be>0?Rn:-Rn,ve):_t(ve,be)}Ol.invert=function(ve,be){return n(be)>bs?sr.invert(ve,be+(be>0?Rn:-Rn)):_t.invert(ve,be)};function xo(){return t.geoProjection(Ol).scale(152.63)}function Yl(ve,be,De,Be){var et=G(4*E/(2*De+(1+ve-be/2)*_(2*De)+(ve+be)/2*_(4*De)+be/2*_(6*De))),We=G(Be*_(De)*G((1+ve*o(2*De)+be*o(4*De))/(1+ve+be))),it=De*Ht(1);function Ft(Sr){return G(1+ve*o(2*Sr)+be*o(4*Sr))}function Ht(Sr){var Or=Sr*De;return(2*Or+(1+ve-be/2)*_(2*Or)+(ve+be)/2*_(4*Or)+be/2*_(6*Or))/De}function tr(Sr){return Ft(Sr)*_(Sr)}var dr=function(Sr,Or){var Wr=De*Zt(Ht,it*_(Or)/De,Or/E);isNaN(Wr)&&(Wr=De*v(Or));var ni=et*Ft(Wr);return[ni*We*Sr/E*o(Wr),ni/We*_(Wr)]};return dr.invert=function(Sr,Or){var Wr=Zt(tr,Or*We/et);return[Sr*E/(o(Wr)*et*We*Ft(Wr)),O(De*Ht(Wr/De)/it)]},De===0&&(et=G(Be/E),dr=function(Sr,Or){return[Sr*et,_(Or)/et]},dr.invert=function(Sr,Or){return[Sr/et,O(Or*et)]}),dr}function Ns(){var ve=1,be=0,De=45*T,Be=2,et=t.geoProjectionMutator(Yl),We=et(ve,be,De,Be);return We.a=function(it){return arguments.length?et(ve=+it,be,De,Be):ve},We.b=function(it){return arguments.length?et(ve,be=+it,De,Be):be},We.psiMax=function(it){return arguments.length?et(ve,be,De=+it*T,Be):De*P},We.ratio=function(it){return arguments.length?et(ve,be,De,Be=+it):Be},We.scale(180.739)}function Hl(ve,be,De,Be,et,We,it,Ft,Ht,tr,dr){if(dr.nanEncountered)return NaN;var Sr,Or,Wr,ni,Pi,cn,ln,Cn,Kn,Ta;if(Sr=De-be,Or=ve(be+Sr*.25),Wr=ve(De-Sr*.25),isNaN(Or)){dr.nanEncountered=!0;return}if(isNaN(Wr)){dr.nanEncountered=!0;return}return ni=Sr*(Be+4*Or+et)/12,Pi=Sr*(et+4*Wr+We)/12,cn=ni+Pi,Ta=(cn-it)/15,tr>Ht?(dr.maxDepthCount++,cn+Ta):Math.abs(Ta)<Ft?cn+Ta:(ln=be+Sr*.5,Cn=Hl(ve,be,ln,Be,Or,et,ni,Ft*.5,Ht,tr+1,dr),isNaN(Cn)?(dr.nanEncountered=!0,NaN):(Kn=Hl(ve,ln,De,et,Wr,We,Pi,Ft*.5,Ht,tr+1,dr),isNaN(Kn)?(dr.nanEncountered=!0,NaN):Cn+Kn))}function ac(ve,be,De,Be,et){var We={maxDepthCount:0,nanEncountered:!1};Be===void 0&&(Be=1e-8),et===void 0&&(et=20);var it=ve(be),Ft=ve(.5*(be+De)),Ht=ve(De),tr=(it+4*Ft+Ht)*(De-be)/6,dr=Hl(ve,be,De,it,Ft,Ht,tr,Be,et,1,We);return dr}function aa(ve,be,De){function Be(Wr){return ve+(1-ve)*h(1-h(Wr,be),1/be)}function et(Wr){return ac(Be,0,Wr,1e-4)}for(var We=1/et(1),it=1e3,Ft=(1+1e-8)*We,Ht=[],tr=0;tr<=it;tr++)Ht.push(et(tr/it)*Ft);function dr(Wr){var ni=0,Pi=it,cn=it>>1;do Ht[cn]>Wr?Pi=cn:ni=cn,cn=ni+Pi>>1;while(cn>ni);var ln=Ht[cn+1]-Ht[cn];return ln&&(ln=(Wr-Ht[cn+1])/ln),(cn+1+ln)/it}var Sr=2*dr(1)/E*We/De,Or=function(Wr,ni){var Pi=dr(n(_(ni))),cn=Be(Pi)*Wr;return Pi/=Sr,[cn,ni>=0?Pi:-Pi]};return Or.invert=function(Wr,ni){var Pi;return ni*=Sr,n(ni)<1&&(Pi=v(ni)*O(et(n(ni))*We)),[Wr/Be(n(ni)),Pi]},Or}function Oo(){var ve=0,be=2.5,De=1.183136,Be=t.geoProjectionMutator(aa),et=Be(ve,be,De);return et.alpha=function(We){return arguments.length?Be(ve=+We,be,De):ve},et.k=function(We){return arguments.length?Be(ve,be=+We,De):be},et.gamma=function(We){return arguments.length?Be(ve,be,De=+We):De},et.scale(152.63)}function qo(ve,be){return n(ve[0]-be[0])<p&&n(ve[1]-be[1])<p}function ql(ve,be){for(var De=-1,Be=ve.length,et=ve[0],We,it,Ft,Ht=[];++De<Be;){We=ve[De],it=(We[0]-et[0])/be,Ft=(We[1]-et[1])/be;for(var tr=0;tr<be;++tr)Ht.push([et[0]+tr*it,et[1]+tr*Ft]);et=We}return Ht.push(We),Ht}function Pc(ve){var be=[],De,Be,et,We,it,Ft,Ht,tr=ve[0].length;for(Ht=0;Ht<tr;++Ht)De=ve[0][Ht],Be=De[0][0],et=De[0][1],We=De[1][1],it=De[2][0],Ft=De[2][1],be.push(ql([[Be+p,et+p],[Be+p,We-p],[it-p,We-p],[it-p,Ft+p]],30));for(Ht=ve[1].length-1;Ht>=0;--Ht)De=ve[1][Ht],Be=De[0][0],et=De[0][1],We=De[1][1],it=De[2][0],Ft=De[2][1],be.push(ql([[it-p,Ft-p],[it-p,We+p],[Be+p,We+p],[Be+p,et-p]],30));return{type:\"Polygon\",coordinates:[r.merge(be)]}}function Do(ve,be,De){var Be,et;function We(Ht,tr){for(var dr=tr<0?-1:1,Sr=be[+(tr<0)],Or=0,Wr=Sr.length-1;Or<Wr&&Ht>Sr[Or][2][0];++Or);var ni=ve(Ht-Sr[Or][1][0],tr);return ni[0]+=ve(Sr[Or][1][0],dr*tr>dr*Sr[Or][0][1]?Sr[Or][0][1]:tr)[0],ni}De?We.invert=De(We):ve.invert&&(We.invert=function(Ht,tr){for(var dr=et[+(tr<0)],Sr=be[+(tr<0)],Or=0,Wr=dr.length;Or<Wr;++Or){var ni=dr[Or];if(ni[0][0]<=Ht&&Ht<ni[1][0]&&ni[0][1]<=tr&&tr<ni[1][1]){var Pi=ve.invert(Ht-ve(Sr[Or][1][0],0)[0],tr);return Pi[0]+=Sr[Or][1][0],qo(We(Pi[0],Pi[1]),[Ht,tr])?Pi:null}}});var it=t.geoProjection(We),Ft=it.stream;return it.stream=function(Ht){var tr=it.rotate(),dr=Ft(Ht),Sr=(it.rotate([0,0]),Ft(Ht));return it.rotate(tr),dr.sphere=function(){t.geoStream(Be,Sr)},dr},it.lobes=function(Ht){return arguments.length?(Be=Pc(Ht),be=Ht.map(function(tr){return tr.map(function(dr){return[[dr[0][0]*T,dr[0][1]*T],[dr[1][0]*T,dr[1][1]*T],[dr[2][0]*T,dr[2][1]*T]]})}),et=be.map(function(tr){return tr.map(function(dr){var Sr=ve(dr[0][0],dr[0][1])[0],Or=ve(dr[2][0],dr[2][1])[0],Wr=ve(dr[1][0],dr[0][1])[1],ni=ve(dr[1][0],dr[1][1])[1],Pi;return Wr>ni&&(Pi=Wr,Wr=ni,ni=Pi),[[Sr,Wr],[Or,ni]]})}),it):be.map(function(tr){return tr.map(function(dr){return[[dr[0][0]*P,dr[0][1]*P],[dr[1][0]*P,dr[1][1]*P],[dr[2][0]*P,dr[2][1]*P]]})})},be!=null&&it.lobes(be),it}var rf=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Uf(){return Do(St,rf).scale(160.857)}var pl=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Zc(){return Do(Ol,pl).scale(152.63)}var Kl=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Os(){return Do(sr,Kl).scale(169.529)}var yu=[[[[-180,0],[-90,90],[0,0]],[[0,0],[90,90],[180,0]]],[[[-180,0],[-90,-90],[0,0]],[[0,0],[90,-90],[180,0]]]];function oc(){return Do(sr,yu).scale(169.529).rotate([20,0])}var Cf=[[[[-180,35],[-30,90],[0,35]],[[0,35],[30,90],[180,35]]],[[[-180,-10],[-102,-90],[-65,-10]],[[-65,-10],[5,-90],[77,-10]],[[77,-10],[103,-90],[180,-10]]]];function sc(){return Do(_a,Cf,st).rotate([-20,-55]).scale(164.263).center([0,-5.4036])}var Vh=[[[[-180,0],[-110,90],[-40,0]],[[-40,0],[0,90],[40,0]],[[40,0],[110,90],[180,0]]],[[[-180,0],[-110,-90],[-40,0]],[[-40,0],[0,-90],[40,0]],[[40,0],[110,-90],[180,0]]]];function Lf(){return Do(_t,Vh).scale(152.63).rotate([-20,0])}function cs(ve,be){return[3/g*ve*G(E*E/3-be*be),be]}cs.invert=function(ve,be){return[g/3*ve/G(E*E/3-be*be),be]};function nf(){return t.geoProjection(cs).scale(158.837)}function Vf(ve){function be(De,Be){if(n(n(Be)-S)<p)return[0,Be<0?-2:2];var et=_(Be),We=h((1+et)/(1-et),ve/2),it=.5*(We+1/We)+o(De*=ve);return[2*_(De)/it,(We-1/We)/it]}return be.invert=function(De,Be){var et=n(Be);if(n(et-2)<p)return De?null:[0,v(Be)*S];if(et>2)return null;De/=2,Be/=2;var We=De*De,it=Be*Be,Ft=2*Be/(1+We+it);return Ft=h((1+Ft)/(1-Ft),1/ve),[a(2*De,1-We-it)/ve,O((Ft-1)/(Ft+1))]},be}function Jl(){var ve=.5,be=t.geoProjectionMutator(Vf),De=be(ve);return De.spacing=function(Be){return arguments.length?be(ve=+Be):ve},De.scale(124.75)}var fl=E/C;function lc(ve,be){return[ve*(1+G(o(be)))/2,be/(o(be/2)*o(ve/6))]}lc.invert=function(ve,be){var De=n(ve),Be=n(be),et=p,We=S;Be<fl?We*=Be/fl:et+=6*V(fl/Be);for(var it=0;it<25;it++){var Ft=_(We),Ht=G(o(We)),tr=_(We/2),dr=o(We/2),Sr=_(et/6),Or=o(et/6),Wr=.5*et*(1+Ht)-De,ni=We/(dr*Or)-Be,Pi=Ht?-.25*et*Ft/Ht:0,cn=.5*(1+Ht),ln=(1+.5*We*tr/dr)/(dr*Or),Cn=We/dr*(Sr/6)/(Or*Or),Kn=Pi*Cn-ln*cn,Ta=(Wr*Cn-ni*cn)/Kn,fa=(ni*Pi-Wr*ln)/Kn;if(We-=Ta,et-=fa,n(Ta)<p&&n(fa)<p)break}return[ve<0?-et:et,be<0?-We:We]};function Fu(){return t.geoProjection(lc).scale(97.2672)}function Es(ve,be){var De=ve*ve,Be=be*be;return[ve*(.975534+Be*(-.119161+De*-.0143059+Be*-.0547009)),be*(1.00384+De*(.0802894+Be*-.02855+De*199025e-9)+Be*(.0998909+Be*-.0491032))]}Es.invert=function(ve,be){var De=v(ve)*E,Be=be/2,et=50;do{var We=De*De,it=Be*Be,Ft=De*Be,Ht=De*(.975534+it*(-.119161+We*-.0143059+it*-.0547009))-ve,tr=Be*(1.00384+We*(.0802894+it*-.02855+We*199025e-9)+it*(.0998909+it*-.0491032))-be,dr=.975534-it*(.119161+3*We*.0143059+it*.0547009),Sr=-Ft*(2*.119161+4*.0547009*it+2*.0143059*We),Or=Ft*(2*.0802894+4*199025e-9*We+2*-.02855*it),Wr=1.00384+We*(.0802894+199025e-9*We)+it*(3*(.0998909-.02855*We)-5*.0491032*it),ni=Sr*Or-Wr*dr,Pi=(tr*Sr-Ht*Wr)/ni,cn=(Ht*Or-tr*dr)/ni;De-=Pi,Be-=cn}while((n(Pi)>p||n(cn)>p)&&--et>0);return et&&[De,Be]};function Hs(){return t.geoProjection(Es).scale(139.98)}function Go(ve,be){return[_(ve)/o(be),b(be)*o(ve)]}Go.invert=function(ve,be){var De=ve*ve,Be=be*be,et=Be+1,We=De+et,it=ve?x*G((We-G(We*We-4*De))/De):1/G(et);return[O(ve*it),v(be)*V(it)]};function ps(){return t.geoProjection(Go).scale(144.049).clipAngle(90-.001)}function uc(ve){var be=o(ve),De=b(L+ve/2);function Be(et,We){var it=We-ve,Ft=n(it)<p?et*be:n(Ft=L+We/2)<p||n(n(Ft)-S)<p?0:et*it/u(b(Ft)/De);return[Ft,it]}return Be.invert=function(et,We){var it,Ft=We+ve;return[n(We)<p?et/be:n(it=L+Ft/2)<p||n(n(it)-S)<p?0:et*u(b(it)/De)/We,Ft]},Be}function xl(){return Vt(uc).parallel(40).scale(158.837)}function Gu(ve,be){return[ve,1.25*u(b(L+.4*be))]}Gu.invert=function(ve,be){return[ve,2.5*i(s(.8*be))-.625*E]};function qs(){return t.geoProjection(Gu).scale(108.318)}function ad(ve){var be=ve.length-1;function De(Be,et){for(var We=o(et),it=2/(1+We*o(Be)),Ft=it*We*_(Be),Ht=it*_(et),tr=be,dr=ve[tr],Sr=dr[0],Or=dr[1],Wr;--tr>=0;)dr=ve[tr],Sr=dr[0]+Ft*(Wr=Sr)-Ht*Or,Or=dr[1]+Ft*Or+Ht*Wr;return Sr=Ft*(Wr=Sr)-Ht*Or,Or=Ft*Or+Ht*Wr,[Sr,Or]}return De.invert=function(Be,et){var We=20,it=Be,Ft=et;do{for(var Ht=be,tr=ve[Ht],dr=tr[0],Sr=tr[1],Or=0,Wr=0,ni;--Ht>=0;)tr=ve[Ht],Or=dr+it*(ni=Or)-Ft*Wr,Wr=Sr+it*Wr+Ft*ni,dr=tr[0]+it*(ni=dr)-Ft*Sr,Sr=tr[1]+it*Sr+Ft*ni;Or=dr+it*(ni=Or)-Ft*Wr,Wr=Sr+it*Wr+Ft*ni,dr=it*(ni=dr)-Ft*Sr-Be,Sr=it*Sr+Ft*ni-et;var Pi=Or*Or+Wr*Wr,cn,ln;it-=cn=(dr*Or+Sr*Wr)/Pi,Ft-=ln=(Sr*Or-dr*Wr)/Pi}while(n(cn)+n(ln)>p*p&&--We>0);if(We){var Cn=G(it*it+Ft*Ft),Kn=2*i(Cn*.5),Ta=_(Kn);return[a(it*Ta,Cn*o(Kn)),Cn?O(Ft*Ta/Cn):0]}},De}var Po=[[.9972523,0],[.0052513,-.0041175],[.0074606,.0048125],[-.0153783,-.1968253],[.0636871,-.1408027],[.3660976,-.2937382]],od=[[.98879,0],[0,0],[-.050909,0],[0,0],[.075528,0]],Yo=[[.984299,0],[.0211642,.0037608],[-.1036018,-.0575102],[-.0329095,-.0320119],[.0499471,.1223335],[.026046,.0899805],[7388e-7,-.1435792],[.0075848,-.1334108],[-.0216473,.0776645],[-.0225161,.0853673]],Pa=[[.9245,0],[0,0],[.01943,0]],af=[[.721316,0],[0,0],[-.00881625,-.00617325]];function Hu(){return Bl(Po,[152,-64]).scale(1400).center([-160.908,62.4864]).clipAngle(30).angle(7.8)}function bl(){return Bl(od,[95,-38]).scale(1e3).clipAngle(55).center([-96.5563,38.8675])}function Gf(){return Bl(Yo,[120,-45]).scale(359.513).clipAngle(55).center([-117.474,53.0628])}function Ic(){return Bl(Pa,[-20,-18]).scale(209.091).center([20,16.7214]).clipAngle(82)}function yf(){return Bl(af,[165,10]).scale(250).clipAngle(130).center([-165,-10])}function Bl(ve,be){var De=t.geoProjection(ad(ve)).rotate(be).clipAngle(90),Be=t.geoRotation(be),et=De.center;return delete De.rotate,De.center=function(We){return arguments.length?et(Be(We)):Be.invert(et())},De}var wh=G(6),Qf=G(7);function _f(ve,be){var De=O(7*_(be)/(3*wh));return[wh*ve*(2*o(2*De/3)-1)/Qf,9*_(De/3)/Qf]}_f.invert=function(ve,be){var De=3*O(be*Qf/9);return[ve*Qf/(wh*(2*o(2*De/3)-1)),O(_(De)*3*wh/7)]};function Yc(){return t.geoProjection(_f).scale(164.859)}function eh(ve,be){for(var De=(1+x)*_(be),Be=be,et=0,We;et<25&&(Be-=We=(_(Be/2)+_(Be)-De)/(.5*o(Be/2)+o(Be)),!(n(We)<p));et++);return[ve*(1+2*o(Be)/o(Be/2))/(3*C),2*G(3)*_(Be/2)/G(2+C)]}eh.invert=function(ve,be){var De=be*G(2+C)/(2*G(3)),Be=2*O(De);return[3*C*ve/(1+2*o(Be)/o(Be/2)),O((De+_(Be))/(1+x))]};function th(){return t.geoProjection(eh).scale(188.209)}function ju(ve,be){for(var De=G(6/(4+E)),Be=(1+E/4)*_(be),et=be/2,We=0,it;We<25&&(et-=it=(et/2+_(et)-Be)/(.5+o(et)),!(n(it)<p));We++);return[De*(.5+o(et))*ve/1.5,De*et]}ju.invert=function(ve,be){var De=G(6/(4+E)),Be=be/De;return n(n(Be)-S)<p&&(Be=Be<0?-S:S),[1.5*ve/(De*(.5+o(Be))),O((Be/2+_(Be))/(1+E/4))]};function Hf(){return t.geoProjection(ju).scale(166.518)}function cc(ve,be){var De=be*be,Be=De*De,et=De*Be;return[ve*(.84719-.13063*De+et*et*(-.04515+.05494*De-.02326*Be+.00331*et)),be*(1.01183+Be*Be*(-.02625+.01926*De-.00396*Be))]}cc.invert=function(ve,be){var De=be,Be=25,et,We,it,Ft;do We=De*De,it=We*We,De-=et=(De*(1.01183+it*it*(-.02625+.01926*We-.00396*it))-be)/(1.01183+it*it*(9*-.02625+11*.01926*We+13*-.00396*it));while(n(et)>k&&--Be>0);return We=De*De,it=We*We,Ft=We*it,[ve/(.84719-.13063*We+Ft*Ft*(-.04515+.05494*We-.02326*it+.00331*Ft)),De]};function of(){return t.geoProjection(cc).scale(175.295)}function Nl(ve,be){return[ve*(1+o(be))/2,2*(be-b(be/2))]}Nl.invert=function(ve,be){for(var De=be/2,Be=0,et=1/0;Be<10&&n(et)>p;++Be){var We=o(be/2);be-=et=(be-b(be/2)-De)/(1-.5/(We*We))}return[2*ve/(1+o(be)),be]};function Kc(){return t.geoProjection(Nl).scale(152.63)}var Rc=[[[[-180,0],[-90,90],[0,0]],[[0,0],[90,90],[180,0]]],[[[-180,0],[-90,-90],[0,0]],[[0,0],[90,-90],[180,0]]]];function gs(){return Do(Ze(1/0),Rc).rotate([20,0]).scale(152.63)}function jf(ve,be){var De=_(be),Be=o(be),et=v(ve);if(ve===0||n(be)===S)return[0,be];if(be===0)return[ve,0];if(n(ve)===S)return[ve*Be,S*De];var We=E/(2*ve)-2*ve/E,it=2*be/E,Ft=(1-it*it)/(De-it),Ht=We*We,tr=Ft*Ft,dr=1+Ht/tr,Sr=1+tr/Ht,Or=(We*De/Ft-We/2)/dr,Wr=(tr*De/Ht+Ft/2)/Sr,ni=Or*Or+Be*Be/dr,Pi=Wr*Wr-(tr*De*De/Ht+Ft*De-1)/Sr;return[S*(Or+G(ni)*et),S*(Wr+G(Pi<0?0:Pi)*v(-be*We)*et)]}jf.invert=function(ve,be){ve/=S,be/=S;var De=ve*ve,Be=be*be,et=De+Be,We=E*E;return[ve?(et-1+G((1-et)*(1-et)+4*De))/(2*ve)*S:0,Zt(function(it){return et*(E*_(it)-2*it)*E+4*it*it*(be-_(it))+2*E*it-We*be},0)]};function Gh(){return t.geoProjection(jf).scale(127.267)}var rh=1.0148,sf=.23185,Th=-.14499,Mu=.02406,ih=rh,js=5*sf,Eu=7*Th,Dc=9*Mu,ks=1.790857183;function bc(ve,be){var De=be*be;return[ve,be*(rh+De*De*(sf+De*(Th+Mu*De)))]}bc.invert=function(ve,be){be>ks?be=ks:be<-ks&&(be=-ks);var De=be,Be;do{var et=De*De;De-=Be=(De*(rh+et*et*(sf+et*(Th+Mu*et)))-be)/(ih+et*et*(js+et*(Eu+Dc*et)))}while(n(Be)>p);return[ve,De]};function hu(){return t.geoProjection(bc).scale(139.319)}function _u(ve,be){if(n(be)<p)return[ve,0];var De=b(be),Be=ve*_(be);return[_(Be)/De,be+(1-o(Be))/De]}_u.invert=function(ve,be){if(n(be)<p)return[ve,0];var De=ve*ve+be*be,Be=be*.5,et=10,We;do{var it=b(Be),Ft=1/o(Be),Ht=De-2*be*Be+Be*Be;Be-=We=(it*Ht+2*(Be-be))/(2+Ht*Ft*Ft+2*(Be-be)*it)}while(n(We)>p&&--et>0);return it=b(Be),[(n(be)<n(Be+1/it)?O(ve*it):v(be)*v(ve)*(V(n(ve*it))+S))/_(Be),Be]};function nl(){return t.geoProjection(_u).scale(103.74)}function nh(ve,be){var De=Fc(ve[1],ve[0]),Be=Fc(be[1],be[0]),et=bd(De,Be),We=wc(De)/wc(Be);return zu([1,0,ve[0][0],0,1,ve[0][1]],zu([We,0,0,0,We,0],zu([o(et),_(et),0,-_(et),o(et),0],[1,0,-be[0][0],0,1,-be[0][1]])))}function Ah(ve){var be=1/(ve[0]*ve[4]-ve[1]*ve[3]);return[be*ve[4],-be*ve[1],be*(ve[1]*ve[5]-ve[2]*ve[4]),-be*ve[3],be*ve[0],be*(ve[2]*ve[3]-ve[0]*ve[5])]}function zu(ve,be){return[ve[0]*be[0]+ve[1]*be[3],ve[0]*be[1]+ve[1]*be[4],ve[0]*be[2]+ve[1]*be[5]+ve[2],ve[3]*be[0]+ve[4]*be[3],ve[3]*be[1]+ve[4]*be[4],ve[3]*be[2]+ve[4]*be[5]+ve[5]]}function Fc(ve,be){return[ve[0]-be[0],ve[1]-be[1]]}function wc(ve){return G(ve[0]*ve[0]+ve[1]*ve[1])}function bd(ve,be){return a(ve[0]*be[1]-ve[1]*be[0],ve[0]*be[0]+ve[1]*be[1])}function xf(ve,be,De){Be(ve,{transform:null});function Be(tr,dr){if(tr.edges=jl(tr.face),dr.face){var Sr=tr.shared=bf(tr.face,dr.face),Or=nh(Sr.map(dr.project),Sr.map(tr.project));tr.transform=dr.transform?zu(dr.transform,Or):Or;for(var Wr=dr.edges,ni=0,Pi=Wr.length;ni<Pi;++ni)Ou(Sr[0],Wr[ni][1])&&Ou(Sr[1],Wr[ni][0])&&(Wr[ni]=tr),Ou(Sr[0],Wr[ni][0])&&Ou(Sr[1],Wr[ni][1])&&(Wr[ni]=tr);for(Wr=tr.edges,ni=0,Pi=Wr.length;ni<Pi;++ni)Ou(Sr[0],Wr[ni][0])&&Ou(Sr[1],Wr[ni][1])&&(Wr[ni]=dr),Ou(Sr[0],Wr[ni][1])&&Ou(Sr[1],Wr[ni][0])&&(Wr[ni]=dr)}else tr.transform=dr.transform;return tr.children&&tr.children.forEach(function(cn){Be(cn,tr)}),tr}function et(tr,dr){var Sr=be(tr,dr),Or=Sr.project([tr*P,dr*P]),Wr;return(Wr=Sr.transform)?[Wr[0]*Or[0]+Wr[1]*Or[1]+Wr[2],-(Wr[3]*Or[0]+Wr[4]*Or[1]+Wr[5])]:(Or[1]=-Or[1],Or)}lf(ve)&&(et.invert=function(tr,dr){var Sr=We(ve,[tr,-dr]);return Sr&&(Sr[0]*=T,Sr[1]*=T,Sr)});function We(tr,dr){var Sr=tr.project.invert,Or=tr.transform,Wr=dr;if(Or&&(Or=Ah(Or),Wr=[Or[0]*Wr[0]+Or[1]*Wr[1]+Or[2],Or[3]*Wr[0]+Or[4]*Wr[1]+Or[5]]),Sr&&tr===it(ni=Sr(Wr)))return ni;for(var ni,Pi=tr.children,cn=0,ln=Pi&&Pi.length;cn<ln;++cn)if(ni=We(Pi[cn],dr))return ni}function it(tr){return be(tr[0]*T,tr[1]*T)}var Ft=t.geoProjection(et),Ht=Ft.stream;return Ft.stream=function(tr){var dr=Ft.rotate(),Sr=Ht(tr),Or=(Ft.rotate([0,0]),Ht(tr));return Ft.rotate(dr),Sr.sphere=function(){Or.polygonStart(),Or.lineStart(),Pf(Or,ve),Or.lineEnd(),Or.polygonEnd()},Sr},Ft.angle(De==null?-30:De*P)}function Pf(ve,be,De){var Be,et=be.edges,We=et.length,it,Ft={type:\"MultiPoint\",coordinates:be.face},Ht=be.face.filter(function(Pi){return n(Pi[1])!==90}),tr=t.geoBounds({type:\"MultiPoint\",coordinates:Ht}),dr=!1,Sr=-1,Or=tr[1][0]-tr[0][0],Wr=Or===180||Or===360?[(tr[0][0]+tr[1][0])/2,(tr[0][1]+tr[1][1])/2]:t.geoCentroid(Ft);if(De)for(;++Sr<We&&et[Sr]!==De;);++Sr;for(var ni=0;ni<We;++ni)it=et[(ni+Sr)%We],Array.isArray(it)?(dr||(ve.point((Be=t.geoInterpolate(it[0],Wr)(p))[0],Be[1]),dr=!0),ve.point((Be=t.geoInterpolate(it[1],Wr)(p))[0],Be[1])):(dr=!1,it!==De&&Pf(ve,it,be))}function Ou(ve,be){return ve&&be&&ve[0]===be[0]&&ve[1]===be[1]}function bf(ve,be){for(var De,Be,et=ve.length,We=null,it=0;it<et;++it){De=ve[it];for(var Ft=be.length;--Ft>=0;)if(Be=be[Ft],De[0]===Be[0]&&De[1]===Be[1]){if(We)return[We,De];We=De}}}function jl(ve){for(var be=ve.length,De=[],Be=ve[be-1],et=0;et<be;++et)De.push([Be,Be=ve[et]]);return De}function lf(ve){return ve.project.invert||ve.children&&ve.children.some(lf)}var Hh=[[0,90],[-90,0],[0,0],[90,0],[180,0],[0,-90]],If=[[0,2,1],[0,3,2],[5,1,2],[5,2,3],[0,1,4],[0,4,3],[5,4,1],[5,3,4]].map(function(ve){return ve.map(function(be){return Hh[be]})});function Cs(ve){ve=ve||function(De){var Be=t.geoCentroid({type:\"MultiPoint\",coordinates:De});return t.geoGnomonic().scale(1).translate([0,0]).rotate([-Be[0],-Be[1]])};var be=If.map(function(De){return{face:De,project:ve(De)}});return[-1,0,0,1,0,1,4,5].forEach(function(De,Be){var et=be[De];et&&(et.children||(et.children=[])).push(be[Be])}),xf(be[0],function(De,Be){return 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Ft=it.map(Rf),Ht=Ft.length,tr=Ft[Ht-1],dr,Sr=[],Or=0;Or<Ht;++Or)dr=Ft[Or],Sr.push(Wu([tr[0]*.9486832980505138+dr[0]*.31622776601683794,tr[1]*.9486832980505138+dr[1]*.31622776601683794,tr[2]*.9486832980505138+dr[2]*.31622776601683794]),Wu([dr[0]*.9486832980505138+tr[0]*.31622776601683794,dr[1]*.9486832980505138+tr[1]*.31622776601683794,dr[2]*.9486832980505138+tr[2]*.31622776601683794])),tr=dr;return Sr}),De=[],Be=[-1,0,0,1,0,1,4,5];be.forEach(function(it,Ft){for(var Ht=If[Ft],tr=Ht.length,dr=De[Ft]=[],Sr=0;Sr<tr;++Sr)be.push([Ht[Sr],it[(Sr*2+2)%(2*tr)],it[(Sr*2+1)%(2*tr)]]),Be.push(Ft),dr.push(zc(Rf(it[(Sr*2+2)%(2*tr)]),Rf(it[(Sr*2+1)%(2*tr)])))});var et=be.map(function(it){return{project:ve(it),face:it}});Be.forEach(function(it,Ft){var Ht=et[it];Ht&&(Ht.children||(Ht.children=[])).push(et[Ft])});function We(it,Ft){var Ht=o(Ft),tr=[Ht*o(it),Ht*_(it),_(Ft)],dr=it<-E/2?Ft<0?6:4:it<0?Ft<0?2:0:it<E/2?Ft<0?3:1:Ft<0?7:5,Sr=De[dr];return 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ve=wl.length?wl.length<2?{type:\"Point\",coordinates:wl[0]}:{type:\"MultiPoint\",coordinates:wl}:null;return wl=[],ve}},cf={lineStart:Xu,point:function(ve,be){wl.push([ve,be])},lineEnd:function(){wl.length&&(vu.push(wl),wl=[])},result:function(){var ve=vu.length?vu.length<2?{type:\"LineString\",coordinates:vu[0]}:{type:\"MultiLineString\",coordinates:vu}:null;return vu=[],ve}},fc={polygonStart:Xu,lineStart:Xu,point:function(ve,be){wl.push([ve,be])},lineEnd:function(){var ve=wl.length;if(ve){do wl.push(wl[0].slice());while(++ve<4);vu.push(wl),wl=[]}},polygonEnd:Xu,result:function(){if(!vu.length)return null;var ve=[],be=[];return vu.forEach(function(De){uf(De)?ve.push([De]):be.push(De)}),be.forEach(function(De){var Be=De[0];ve.some(function(et){if(Xf(et[0],Be))return et.push(De),!0})||ve.push([De])}),vu=[],ve.length?ve.length>1?{type:\"MultiPolygon\",coordinates:ve}:{type:\"Polygon\",coordinates:ve[0]}:null}};function Bc(ve){var be=ve(S,0)[0]-ve(-S,0)[0];function De(Be,et){var We=n(Be)<S,it=ve(We?Be:Be>0?Be-E:Be+E,et),Ft=(it[0]-it[1])*x,Ht=(it[0]+it[1])*x;if(We)return[Ft,Ht];var tr=be*x,dr=Ft>0^Ht>0?-1:1;return[dr*Ft-v(Ht)*tr,dr*Ht-v(Ft)*tr]}return ve.invert&&(De.invert=function(Be,et){var We=(Be+et)*x,it=(et-Be)*x,Ft=n(We)<.5*be&&n(it)<.5*be;if(!Ft){var Ht=be*x,tr=We>0^it>0?-1:1,dr=-tr*Be+(it>0?1:-1)*Ht,Sr=-tr*et+(We>0?1:-1)*Ht;We=(-dr-Sr)*x,it=(dr-Sr)*x}var Or=ve.invert(We,it);return Ft||(Or[0]+=We>0?E:-E),Or}),t.geoProjection(De).rotate([-90,-90,45]).clipAngle(180-.001)}function At(){return Bc(Li).scale(176.423)}function Wt(){return Bc(Lo).scale(111.48)}function Cr(ve,be){if(!(0<=(be=+be)&&be<=20))throw new Error(\"invalid digits\");function De(tr){var dr=tr.length,Sr=2,Or=new Array(dr);for(Or[0]=+tr[0].toFixed(be),Or[1]=+tr[1].toFixed(be);Sr<dr;)Or[Sr]=tr[Sr],++Sr;return Or}function Be(tr){return tr.map(De)}function et(tr){for(var dr=De(tr[0]),Sr=[dr],Or=1;Or<tr.length;Or++){var 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tr.id!=null&&(dr.id=tr.id),tr.bbox!=null&&(dr.bbox=tr.bbox),dr}if(ve!=null)switch(ve.type){case\"Feature\":return Ft(ve);case\"FeatureCollection\":{var Ht={type:\"FeatureCollection\",features:ve.features.map(Ft)};return ve.bbox!=null&&(Ht.bbox=ve.bbox),Ht}default:return it(ve)}return ve}function Ar(ve){var be=_(ve);function De(Be,et){var We=be?b(Be*be/2)/be:Be/2;if(!et)return[2*We,-ve];var it=2*i(We*_(et)),Ft=1/b(et);return[_(it)*Ft,et+(1-o(it))*Ft-ve]}return De.invert=function(Be,et){if(n(et+=ve)<p)return[be?2*i(be*Be/2)/be:Be,0];var We=Be*Be+et*et,it=0,Ft=10,Ht;do{var tr=b(it),dr=1/o(it),Sr=We-2*et*it+it*it;it-=Ht=(tr*Sr+2*(it-et))/(2+Sr*dr*dr+2*(it-et)*tr)}while(n(Ht)>p&&--Ft>0);var Or=Be*(tr=b(it)),Wr=b(n(et)<n(it+1/tr)?O(Or)*.5:V(Or)*.5+E/4)/_(it);return[be?2*i(be*Wr)/be:2*Wr,it]},De}function Kr(){return Vt(Ar).scale(131.215)}var 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tr=Ht*Ht,dr=o(G(tr+(Or=Ft+be)*Or)),Sr=o(G(tr+(Or=Ft+De)*Or)),Or,Wr;return[a(Wr=dr-Sr,Or=(dr+Sr)*et),(Ht<0?-1:1)*V(G(Or*Or+Wr*Wr)*We)]},it}function Nc(){return pu([-158,21.5],[-77,39]).clipAngle(130).scale(122.571)}function pu(ve,be){return ys(Yu,ve,be)}function Uc(ve,be){if(n(be)<p)return[ve,0];var De=n(be/S),Be=O(De);if(n(ve)<p||n(n(be)-S)<p)return[0,v(be)*E*b(Be/2)];var et=o(Be),We=n(E/ve-ve/E)/2,it=We*We,Ft=et/(De+et-1),Ht=Ft*(2/De-1),tr=Ht*Ht,dr=tr+it,Sr=Ft-tr,Or=it+Ft;return[v(ve)*E*(We*Sr+G(it*Sr*Sr-dr*(Ft*Ft-tr)))/dr,v(be)*E*(Ht*Or-We*G((it+1)*dr-Or*Or))/dr]}Uc.invert=function(ve,be){if(n(be)<p)return[ve,0];if(n(ve)<p)return[0,S*_(2*i(be/E))];var De=(ve/=E)*ve,Be=(be/=E)*be,et=De+Be,We=et*et,it=-n(be)*(1+et),Ft=it-2*Be+De,Ht=-2*it+1+2*Be+We,tr=Be/Ht+(2*Ft*Ft*Ft/(Ht*Ht*Ht)-9*it*Ft/(Ht*Ht))/27,dr=(it-Ft*Ft/(3*Ht))/Ht,Sr=2*G(-dr/3),Or=V(3*tr/(dr*Sr))/3;return[E*(et-1+G(1+2*(De-Be)+We))/(2*ve),v(be)*E*(-Sr*o(Or+E/3)-Ft/(3*Ht))]};function xu(){return t.geoProjection(Uc).scale(79.4183)}function Ac(ve,be){if(n(be)<p)return[ve,0];var De=n(be/S),Be=O(De);if(n(ve)<p||n(n(be)-S)<p)return[0,v(be)*E*b(Be/2)];var et=o(Be),We=n(E/ve-ve/E)/2,it=We*We,Ft=et*(G(1+it)-We*et)/(1+it*De*De);return[v(ve)*E*Ft,v(be)*E*G(1-Ft*(2*We+Ft))]}Ac.invert=function(ve,be){if(!ve)return[0,S*_(2*i(be/E))];var De=n(ve/E),Be=(1-De*De-(be/=E)*be)/(2*De),et=Be*Be,We=G(et+1);return[v(ve)*E*(We-Be),v(be)*S*_(2*a(G((1-2*Be*De)*(Be+We)-De),G(We+Be+De)))]};function Ua(){return t.geoProjection(Ac).scale(79.4183)}function oo(ve,be){if(n(be)<p)return[ve,0];var De=be/S,Be=O(De);if(n(ve)<p||n(n(be)-S)<p)return[0,E*b(Be/2)];var et=(E/ve-ve/E)/2,We=De/(1+o(Be));return[E*(v(ve)*G(et*et+1-We*We)-et),E*We]}oo.invert=function(ve,be){if(!be)return[ve,0];var De=be/E,Be=(E*E*(1-De*De)-ve*ve)/(2*E*ve);return[ve?E*(v(ve)*G(Be*Be+1)-Be):0,S*_(2*i(De))]};function Vc(){return t.geoProjection(oo).scale(79.4183)}function hc(ve,be){if(!be)return[ve,0];var De=n(be);if(!ve||De===S)return[0,be];var Be=De/S,et=Be*Be,We=(8*Be-et*(et+2)-5)/(2*et*(Be-1)),it=We*We,Ft=Be*We,Ht=et+it+2*Ft,tr=Be+3*We,dr=ve/S,Sr=dr+1/dr,Or=v(n(ve)-S)*G(Sr*Sr-4),Wr=Or*Or,ni=Ht*(et+it*Wr-1)+(1-et)*(et*(tr*tr+4*it)+12*Ft*it+4*it*it),Pi=(Or*(Ht+it-1)+2*G(ni))/(4*Ht+Wr);return[v(ve)*S*Pi,v(be)*S*G(1+Or*n(Pi)-Pi*Pi)]}hc.invert=function(ve,be){var De;if(!ve||!be)return[ve,be];be/=E;var Be=v(ve)*ve/S,et=(Be*Be-1+4*be*be)/n(Be),We=et*et,it=2*be,Ft=50;do{var Ht=it*it,tr=(8*it-Ht*(Ht+2)-5)/(2*Ht*(it-1)),dr=(3*it-Ht*it-10)/(2*Ht*it),Sr=tr*tr,Or=it*tr,Wr=it+tr,ni=Wr*Wr,Pi=it+3*tr,cn=ni*(Ht+Sr*We-1)+(1-Ht)*(Ht*(Pi*Pi+4*Sr)+Sr*(12*Or+4*Sr)),ln=-2*Wr*(4*Or*Sr+(1-4*Ht+3*Ht*Ht)*(1+dr)+Sr*(-6+14*Ht-We+(-8+8*Ht-2*We)*dr)+Or*(-8+12*Ht+(-10+10*Ht-We)*dr)),Cn=G(cn),Kn=et*(ni+Sr-1)+2*Cn-Be*(4*ni+We),Ta=et*(2*tr*dr+2*Wr*(1+dr))+ln/Cn-8*Wr*(et*(-1+Sr+ni)+2*Cn)*(1+dr)/(We+4*ni);it-=De=Kn/Ta}while(De>p&&--Ft>0);return[v(ve)*(G(et*et+4)+et)*E/4,S*it]};function Ku(){return t.geoProjection(hc).scale(127.16)}function ue(ve,be,De,Be,et){function We(it,Ft){var Ht=De*_(Be*Ft),tr=G(1-Ht*Ht),dr=G(2/(1+tr*o(it*=et)));return[ve*tr*dr*_(it),be*Ht*dr]}return We.invert=function(it,Ft){var Ht=it/ve,tr=Ft/be,dr=G(Ht*Ht+tr*tr),Sr=2*O(dr/2);return[a(it*b(Sr),ve*dr)/et,dr&&O(Ft*_(Sr)/(be*De*dr))/Be]},We}function w(ve,be,De,Be){var et=E/3;ve=c(ve,p),be=c(be,p),ve=f(ve,S),be=f(be,E-p),De=c(De,0),De=f(De,100-p),Be=c(Be,p);var We=De/100+1,it=Be/100,Ft=V(We*o(et))/et,Ht=_(ve)/_(Ft*S),tr=be/E,dr=G(it*_(ve/2)/_(be/2)),Sr=dr/G(tr*Ht*Ft),Or=1/(dr*G(tr*Ht*Ft));return ue(Sr,Or,Ht,Ft,tr)}function B(){var ve=65*T,be=60*T,De=20,Be=200,et=t.geoProjectionMutator(w),We=et(ve,be,De,Be);return We.poleline=function(it){return arguments.length?et(ve=+it*T,be,De,Be):ve*P},We.parallels=function(it){return arguments.length?et(ve,be=+it*T,De,Be):be*P},We.inflation=function(it){return arguments.length?et(ve,be,De=+it,Be):De},We.ratio=function(it){return 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t=.5*e[0]*JA,r=.5*e[1]*JA,n=.5*e[2]*JA,i=Math.sin(t),a=Math.cos(t),o=Math.sin(r),s=Math.cos(r),l=Math.sin(n),u=Math.cos(n);return[a*s*u+i*o*l,i*s*u-a*o*l,a*o*u+i*s*l,a*s*l-i*o*u]}function Izt(e,t){var r=e[0],n=e[1],i=e[2],a=e[3],o=t[0],s=t[1],l=t[2],u=t[3];return[r*o-n*s-i*l-a*u,r*s+n*o+i*u-a*l,r*l-n*u+i*o+a*s,r*u+n*l-i*s+a*o]}function Rzt(e,t){if(!(!e||!t)){var r=Ozt(e,t),n=Math.sqrt(RDe(r,r)),i=.5*Math.acos(Math.max(-1,Math.min(1,RDe(e,t)))),a=Math.sin(i)/n;return n&&[Math.cos(i),r[2]*a,-r[1]*a,r[0]*a]}}function Dzt(e,t,r){var n=DZ(t,2,e[0]);n=DZ(n,1,e[1]),n=DZ(n,0,e[2]-r[2]);var i=t[0],a=t[1],o=t[2],s=n[0],l=n[1],u=n[2],c=Math.atan2(a,i)*j2,f=Math.sqrt(i*i+a*a),h,d;Math.abs(l)>f?(d=(l>0?90:-90)-c,h=0):(d=Math.asin(l/f)*j2-c,h=Math.sqrt(f*f-l*l));var v=180-d-2*c,_=(Math.atan2(u,s)-Math.atan2(o,h))*j2,b=(Math.atan2(u,s)-Math.atan2(o,-h))*j2,p=PDe(r[0],r[1],d,_),k=PDe(r[0],r[1],v,b);return p<=k?[d,_,r[2]]:[v,b,r[2]]}function PDe(e,t,r,n){var i=IDe(r-e),a=IDe(n-t);return 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t1=Oa(),UZ=IZ(),Bzt=UZ.geoPath,Nzt=UZ.geoDistance,Uzt=LDe(),Vzt=qa(),ok=Dr(),Gzt=ok.strTranslate,IF=ka(),ak=So(),zDe=vf(),Hzt=Mc(),NZ=ho(),ODe=Tg().getAutoRange,BZ=yv(),jzt=Of().prepSelect,Wzt=Of().clearOutline,Xzt=Of().selectOnClick,Zzt=FDe(),fp=tk(),Yzt=ix(),BDe=gF(),Kzt=mZ().feature;function NDe(e){this.id=e.id,this.graphDiv=e.graphDiv,this.container=e.container,this.topojsonURL=e.topojsonURL,this.isStatic=e.staticPlot,this.topojsonName=null,this.topojson=null,this.projection=null,this.scope=null,this.viewInitial=null,this.fitScale=null,this.bounds=null,this.midPt=null,this.hasChoropleth=!1,this.traceHash={},this.layers={},this.basePaths={},this.dataPaths={},this.dataPoints={},this.clipDef=null,this.clipRect=null,this.bgRect=null,this.makeFramework()}var $g=NDe.prototype;UDe.exports=function(t){return new NDe(t)};$g.plot=function(e,t,r,n){var i=this;if(n)return i.update(e,t,!0);i._geoCalcData=e,i._fullLayout=t;var a=t[this.id],o=[],s=!1;for(var l in fp.layerNameToAdjective)if(l!==\"frame\"&&a[\"show\"+l]){s=!0;break}for(var u=!1,c=0;c<e.length;c++){var f=e[0][0].trace;f._geo=i,f.locationmode&&(s=!0);var h=f.marker;if(h){var d=h.angle,v=h.angleref;(d||v===\"north\"||v===\"previous\")&&(u=!0)}}if(this._hasMarkerAngles=u,s){var _=BDe.getTopojsonName(a);(i.topojson===null||_!==i.topojsonName)&&(i.topojsonName=_,PlotlyGeoAssets.topojson[i.topojsonName]===void 0&&o.push(i.fetchTopojson()))}o=o.concat(Yzt.fetchTraceGeoData(e)),r.push(new Promise(function(b,p){Promise.all(o).then(function(){i.topojson=PlotlyGeoAssets.topojson[i.topojsonName],i.update(e,t),b()}).catch(p)}))};$g.fetchTopojson=function(){var e=this,t=BDe.getTopojsonPath(e.topojsonURL,e.topojsonName);return new Promise(function(r,n){t1.json(t,function(i,a){if(i)return i.status===404?n(new Error([\"plotly.js could not find topojson file at\",t+\".\",\"Make sure the *topojsonURL* plot config option\",\"is set properly.\"].join(\" \"))):n(new Error([\"unexpected error while 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r=this.graphDiv,n=t[this.id],i=t._size,a=n.domain,o=n.projection,s=n.lonaxis,l=n.lataxis,u=s._ax,c=l._ax,f=this.projection=Jzt(n),h=[[i.l+i.w*a.x[0],i.t+i.h*(1-a.y[1])],[i.l+i.w*a.x[1],i.t+i.h*(1-a.y[0])]],d=n.center||{},v=o.rotation||{},_=s.range||[],b=l.range||[];if(n.fitbounds){u._length=h[1][0]-h[0][0],c._length=h[1][1]-h[0][1],u.range=ODe(r,u),c.range=ODe(r,c);var p=(u.range[0]+u.range[1])/2,k=(c.range[0]+c.range[1])/2;if(n._isScoped)d={lon:p,lat:k};else if(n._isClipped){d={lon:p,lat:k},v={lon:p,lat:k,roll:v.roll};var E=o.type,S=fp.lonaxisSpan[E]/2||180,L=fp.lataxisSpan[E]/2||90;_=[p-S,p+S],b=[k-L,k+L]}else d={lon:p,lat:k},v={lon:p,lat:v.lat,roll:v.roll}}f.center([d.lon-v.lon,d.lat-v.lat]).rotate([-v.lon,-v.lat,v.roll]).parallels(o.parallels);var x=qDe(_,b);f.fitExtent(h,x);var C=this.bounds=f.getBounds(x),M=this.fitScale=f.scale(),g=f.translate();if(n.fitbounds){var P=f.getBounds(qDe(u.range,c.range)),T=Math.min((C[1][0]-C[0][0])/(P[1][0]-P[0][0]),(C[1][1]-C[0][1])/(P[1][1]-P[0][1]));isFinite(T)?f.scale(T*M):ok.warn(\"Something went wrong during\"+this.id+\"fitbounds computations.\")}else f.scale(o.scale*M);var z=this.midPt=[(C[0][0]+C[1][0])/2,(C[0][1]+C[1][1])/2];if(f.translate([g[0]+(z[0]-g[0]),g[1]+(z[1]-g[1])]).clipExtent(C),n._isAlbersUsa){var O=f([d.lon,d.lat]),V=f.translate();f.translate([V[0]-(O[0]-V[0]),V[1]-(O[1]-V[1])])}};$g.updateBaseLayers=function(e,t){var r=this,n=r.topojson,i=r.layers,a=r.basePaths;function o(h){return h===\"lonaxis\"||h===\"lataxis\"}function s(h){return!!fp.lineLayers[h]}function l(h){return!!fp.fillLayers[h]}var u=this.hasChoropleth?fp.layersForChoropleth:fp.layers,c=u.filter(function(h){return s(h)||l(h)?t[\"show\"+h]:o(h)?t[h].showgrid:!0}),f=r.framework.selectAll(\".layer\").data(c,String);f.exit().each(function(h){delete i[h],delete 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r=this.bounds,n=(t.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;ak.setRect(this.clipRect,i,a,o,s),this.bgRect.call(ak.setRect,i,a,o,s).call(IF.fill,t.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s};$g.updateFx=function(e,t){var r=this,n=r.graphDiv,i=r.bgRect,a=e.dragmode,o=e.clickmode;if(r.isStatic)return;function s(){var f=r.viewInitial,h={};for(var d in f)h[r.id+\".\"+d]=f[d];Vzt.call(\"_guiRelayout\",n,h),n.emit(\"plotly_doubleclick\",null)}function l(f){return r.projection.invert([f[0]+r.xaxis._offset,f[1]+r.yaxis._offset])}var u=function(f,h){if(h.isRect){var d=f.range={};d[r.id]=[l([h.xmin,h.ymin]),l([h.xmax,h.ymax])]}else{var 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e=this,t=e.graphDiv,r=t._fullLayout,n=\"clip\"+r._uid+e.id;e.clipDef=r._clips.append(\"clipPath\").attr(\"id\",n),e.clipRect=e.clipDef.append(\"rect\"),e.framework=t1.select(e.container).append(\"g\").attr(\"class\",\"geo \"+e.id).call(ak.setClipUrl,n,t),e.project=function(i){var a=e.projection(i);return a?[a[0]-e.xaxis._offset,a[1]-e.yaxis._offset]:[null,null]},e.xaxis={_id:\"x\",c2p:function(i){return e.project(i)[0]}},e.yaxis={_id:\"y\",c2p:function(i){return e.project(i)[1]}},e.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},NZ.setConvert(e.mockAxis,r)};$g.saveViewInitial=function(e){var t=e.center||{},r=e.projection,n=r.rotation||{};this.viewInitial={fitbounds:e.fitbounds,\"projection.scale\":r.scale};var i;e._isScoped?i={\"center.lon\":t.lon,\"center.lat\":t.lat}:e._isClipped?i={\"projection.rotation.lon\":n.lon,\"projection.rotation.lat\":n.lat}:i={\"center.lon\":t.lon,\"center.lat\":t.lat,\"projection.rotation.lon\":n.lon},ok.extendFlat(this.viewInitial,i)};$g.render=function(e){this._hasMarkerAngles&&e?this.plot(this._geoCalcData,this._fullLayout,[],!0):this._render()};$g._render=function(){var e=this.projection,t=e.getPath(),r;function n(a){var o=e(a.lonlat);return o?Gzt(o[0],o[1]):null}function i(a){return e.isLonLatOverEdges(a.lonlat)?\"none\":null}for(r in this.basePaths)this.basePaths[r].attr(\"d\",t);for(r in this.dataPaths)this.dataPaths[r].attr(\"d\",function(a){return t(a.geojson)});for(r in this.dataPoints)this.dataPoints[r].attr(\"display\",i).attr(\"transform\",n)};function Jzt(e){var t=e.projection,r=t.type,n=fp.projNames[r];n=\"geo\"+ok.titleCase(n);for(var i=UZ[n]||Uzt[n],a=i(),o=e._isSatellite?Math.acos(1/t.distance)*180/Math.PI:e._isClipped?fp.lonaxisSpan[r]/2:null,s=[\"center\",\"rotate\",\"parallels\",\"clipExtent\"],l=function(f){return f?a:[]},u=0;u<s.length;u++){var c=s[u];typeof a[c]!=\"function\"&&(a[c]=l)}return a.isLonLatOverEdges=function(f){if(a(f)===null)return!0;if(o){var h=a.rotate(),d=Nzt(f,[-h[0],-h[1]]),v=o*Math.PI/180;return d>v}else return!1},a.getPath=function(){return Bzt().projection(a)},a.getBounds=function(f){return a.getPath().bounds(f)},a.precision(fp.precision),e._isSatellite&&a.tilt(t.tilt).distance(t.distance),o&&a.clipAngle(o-fp.clipPad),a}function $zt(e,t,r){var n=1e-6,i=2.5,a=t[e],o=fp.scopeDefaults[t.scope],s,l,u;e===\"lonaxis\"?(s=o.lonaxisRange,l=o.lataxisRange,u=function(k,E){return[k,E]}):e===\"lataxis\"&&(s=o.lataxisRange,l=o.lonaxisRange,u=function(k,E){return[E,k]});var c={type:\"linear\",range:[s[0],s[1]-n],tick0:a.tick0,dtick:a.dtick};NZ.setConvert(c,r);var 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QA=Lh(),Qzt=Cc().attributes,e7t=Pd().dash,$A=tk(),t7t=mc().overrideAll,GDe=Z1(),HDe={range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},showgrid:{valType:\"boolean\",dflt:!1},tick0:{valType:\"number\",dflt:0},dtick:{valType:\"number\"},gridcolor:{valType:\"color\",dflt:QA.lightLine},gridwidth:{valType:\"number\",min:0,dflt:1},griddash:e7t},r7t=jDe.exports=t7t({domain:Qzt({name:\"geo\"},{}),fitbounds:{valType:\"enumerated\",values:[!1,\"locations\",\"geojson\"],dflt:!1,editType:\"plot\"},resolution:{valType:\"enumerated\",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:\"enumerated\",values:GDe($A.scopeDefaults),dflt:\"world\"},projection:{type:{valType:\"enumerated\",values:GDe($A.projNames)},rotation:{lon:{valType:\"number\"},lat:{valType:\"number\"},roll:{valType:\"number\"}},tilt:{valType:\"number\",dflt:0},distance:{valType:\"number\",min:1.001,dflt:2},parallels:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},scale:{valType:\"number\",min:0,dflt:1}},center:{lon:{valType:\"number\"},lat:{valType:\"number\"}},visible:{valType:\"boolean\",dflt:!0},showcoastlines:{valType:\"boolean\"},coastlinecolor:{valType:\"color\",dflt:QA.defaultLine},coastlinewidth:{valType:\"number\",min:0,dflt:1},showland:{valType:\"boolean\",dflt:!1},landcolor:{valType:\"color\",dflt:$A.landColor},showocean:{valType:\"boolean\",dflt:!1},oceancolor:{valType:\"color\",dflt:$A.waterColor},showlakes:{valType:\"boolean\",dflt:!1},lakecolor:{valType:\"color\",dflt:$A.waterColor},showrivers:{valType:\"boolean\",dflt:!1},rivercolor:{valType:\"color\",dflt:$A.waterColor},riverwidth:{valType:\"number\",min:0,dflt:1},showcountries:{valType:\"boolean\"},countrycolor:{valType:\"color\",dflt:QA.defaultLine},countrywidth:{valType:\"number\",min:0,dflt:1},showsubunits:{valType:\"boolean\"},subunitcolor:{valType:\"color\",dflt:QA.defaultLine},subunitwidth:{valType:\"number\",min:0,dflt:1},showframe:{valType:\"boolean\"},framecolor:{valType:\"color\",dflt:QA.defaultLine},framewidth:{valType:\"number\",min:0,dflt:1},bgcolor:{valType:\"color\",dflt:QA.background},lonaxis:HDe,lataxis:HDe},\"plot\",\"from-root\");r7t.uirevision={valType:\"any\",editType:\"none\"}});var 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oFe=ye((kmr,aFe)=>{\"use strict\";var sk=Dr(),m7t=Qh(),y7t=e5(),_7t=[\"The library used by the *country names* `locationmode` option is changing in the next major version.\",\"Some country names in existing plots may not work in the new version.\",\"To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.\"].join(\" \");aFe.exports=function(t,r,n,i){function a(h,d){return sk.coerce(t,r,y7t,h,d)}var o=a(\"locations\"),s=a(\"z\");if(!(o&&o.length&&sk.isArrayOrTypedArray(s)&&s.length)){r.visible=!1;return}r._length=Math.min(o.length,s.length);var l=a(\"geojson\"),u;(typeof l==\"string\"&&l!==\"\"||sk.isPlainObject(l))&&(u=\"geojson-id\");var c=a(\"locationmode\",u);c===\"country names\"&&sk.warn(_7t),c===\"geojson-id\"&&a(\"featureidkey\"),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\");var 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r=e[0].trace,n=t[r.geo],i=n._subplot,a=r.locationmode,o=r._length,s=a===\"geojson-id\"?t5.extractTraceFeature(e):L7t(r,i.topojson),l=[],u=[],c=0;c<o;c++){var f=e[c],h=a===\"geojson-id\"?f.fOut:t5.locationToFeature(a,f.loc,s);if(h){f.geojson=h,f.ct=h.properties.ct,f._polygons=t5.feature2polygons(h);var d=t5.computeBbox(h);l.push(d[0],d[2]),u.push(d[1],d[3])}else f.geojson=null}if(n.fitbounds===\"geojson\"&&a===\"geojson-id\"){var v=t5.computeBbox(t5.getTraceGeojson(r));l=[v[0],v[2]],u=[v[1],v[3]]}var _={padded:!0};r._extremes.lon=dFe(n.lonaxis._ax,l,_),r._extremes.lat=dFe(n.lataxis._ax,u,_)}vFe.exports={calcGeoJSON:R7t,plot:I7t}});var OF=ye((Imr,pFe)=>{\"use strict\";var D7t=ho(),F7t=e5(),z7t=Dr().fillText;pFe.exports=function(t,r,n){var i=t.cd,a=i[0].trace,o=t.subplot,s,l,u,c,f=[r,n],h=[r+360,n];for(l=0;l<i.length;l++)if(s=i[l],c=!1,s._polygons){for(u=0;u<s._polygons.length;u++)s._polygons[u].contains(f)&&(c=!c),s._polygons[u].contains(h)&&(c=!c);if(c)break}if(!(!c||!s))return 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e==\"string\")return cY(e,t);var r=Object.prototype.toString.call(e).slice(8,-1);if(r===\"Object\"&&e.constructor&&(r=e.constructor.name),r===\"Map\"||r===\"Set\")return Array.from(e);if(r===\"Arguments\"||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(r))return cY(e,t)}}function cY(e,t){(t==null||t>e.length)&&(t=e.length);for(var r=0,n=new Array(t);r<t;r++)n[r]=e[r];return n}function EOt(){throw new TypeError(`Invalid attempt to spread non-iterable instance.\n",
+       "In order to be iterable, non-array objects must have a [Symbol.iterator]() method.`)}function kOt(){throw new TypeError(`Invalid attempt to destructure non-iterable instance.\n",
+       "In order to be iterable, non-array objects must have a [Symbol.iterator]() method.`)}var COt=J_(),LOt=W2(),POt=e7e(),IOt=GF(),J2=Oh(),ez=n7e(),ROt=Zm(),DOt=uY(),FOt=X2(),u7e=s7e(),tz=QF(),zOt=r5(),OOt=nv;function nv(e,t){var r=this;if(!(this instanceof nv))return new nv(e,t);typeof e==\"function\"?(t||(t={}),t.regl=e):(t=e,e=null),t&&t.length&&(t.positions=t),e=t.regl;var n=e._gl,i,a=[],o={},s=[],l=[null],u=[null],c=255,f=100;this.tooManyColors=u7e,i=e.texture({data:new Uint8Array(c*4),width:c,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),J2(this,{regl:e,gl:n,groups:s,markerCache:u,markerTextures:l,palette:a,paletteIds:o,paletteTexture:i,maxColors:c,maxSize:f,canvas:n.canvas}),this.update(t);var h={uniforms:{constPointSize:!!t.constPointSize,opacity:e.prop(\"opacity\"),paletteSize:function(b,p){return[r.tooManyColors?0:c,i.height]},pixelRatio:e.context(\"pixelRatio\"),scale:e.prop(\"scale\"),scaleFract:e.prop(\"scaleFract\"),translate:e.prop(\"translate\"),translateFract:e.prop(\"translateFract\"),markerTexture:e.prop(\"markerTexture\"),paletteTexture:i},attributes:{x:function(b,p){return p.xAttr||{buffer:p.positionBuffer,stride:8,offset:0}},y:function(b,p){return p.yAttr||{buffer:p.positionBuffer,stride:8,offset:4}},xFract:function(b,p){return p.xAttr?{constant:[0,0]}:{buffer:p.positionFractBuffer,stride:8,offset:0}},yFract:function(b,p){return p.yAttr?{constant:[0,0]}:{buffer:p.positionFractBuffer,stride:8,offset:4}},size:function(b,p){return p.size.length?{buffer:p.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(p.size*255/r.maxSize)]}},borderSize:function(b,p){return p.borderSize.length?{buffer:p.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(p.borderSize*255/r.maxSize)]}},colorId:function(b,p){return p.color.length?{buffer:p.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?a.slice(p.color*4,p.color*4+4):[p.color]}},borderColorId:function(b,p){return p.borderColor.length?{buffer:p.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?a.slice(p.borderColor*4,p.borderColor*4+4):[p.borderColor]}},isActive:function(b,p){return p.activation===!0?{constant:[1]}:p.activation?p.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:e.prop(\"viewport\")},viewport:e.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:e.prop(\"elements\"),count:e.prop(\"count\"),offset:e.prop(\"offset\"),primitive:\"points\"},d=J2({},h);d.frag=ez([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "uniform float opacity;\n",
+       "uniform sampler2D markerTexture;\n",
+       "\n",
+       "varying vec4 fragColor, fragBorderColor;\n",
+       "varying float fragWidth, fragBorderColorLevel, fragColorLevel;\n",
+       "\n",
+       "float smoothStep(float x, float y) {\n",
+       "  return 1.0 / (1.0 + exp(50.0*(x - y)));\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  float dist = texture2D(markerTexture, gl_PointCoord).r, delta = fragWidth;\n",
+       "\n",
+       "  // max-distance alpha\n",
+       "  if (dist < 0.003) discard;\n",
+       "\n",
+       "  // null-border case\n",
+       "  if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\n",
+       "    float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\n",
+       "    gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\n",
+       "  }\n",
+       "  else {\n",
+       "    float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\n",
+       "    float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\n",
+       "\n",
+       "    vec4 color = fragBorderColor;\n",
+       "    color.a *= borderColorAmt;\n",
+       "    color = mix(color, fragColor, colorAmt);\n",
+       "    color.a *= opacity;\n",
+       "\n",
+       "    gl_FragColor = color;\n",
+       "  }\n",
+       "\n",
+       "}\n",
+       "`]),d.vert=ez([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute float x, y, xFract, yFract;\n",
+       "attribute float size, borderSize;\n",
+       "attribute vec4 colorId, borderColorId;\n",
+       "attribute float isActive;\n",
+       "\n",
+       "// \\`invariant\\` effectively turns off optimizations for the position.\n",
+       "// We need this because -fast-math on M1 Macs is re-ordering\n",
+       "// floating point operations in a way that causes floating point\n",
+       "// precision limits to put points in the wrong locations.\n",
+       "invariant gl_Position;\n",
+       "\n",
+       "uniform bool constPointSize;\n",
+       "uniform float pixelRatio;\n",
+       "uniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\n",
+       "uniform sampler2D paletteTexture;\n",
+       "\n",
+       "const float maxSize = 100.;\n",
+       "const float borderLevel = .5;\n",
+       "\n",
+       "varying vec4 fragColor, fragBorderColor;\n",
+       "varying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\n",
+       "\n",
+       "float pointSizeScale = (constPointSize) ? 2. : pixelRatio;\n",
+       "\n",
+       "bool isDirect = (paletteSize.x < 1.);\n",
+       "\n",
+       "vec4 getColor(vec4 id) {\n",
+       "  return isDirect ? id / 255. : texture2D(paletteTexture,\n",
+       "    vec2(\n",
+       "      (id.x + .5) / paletteSize.x,\n",
+       "      (id.y + .5) / paletteSize.y\n",
+       "    )\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  // ignore inactive points\n",
+       "  if (isActive == 0.) return;\n",
+       "\n",
+       "  vec2 position = vec2(x, y);\n",
+       "  vec2 positionFract = vec2(xFract, yFract);\n",
+       "\n",
+       "  vec4 color = getColor(colorId);\n",
+       "  vec4 borderColor = getColor(borderColorId);\n",
+       "\n",
+       "  float size = size * maxSize / 255.;\n",
+       "  float borderSize = borderSize * maxSize / 255.;\n",
+       "\n",
+       "  gl_PointSize = 2. * size * pointSizeScale;\n",
+       "  fragPointSize = size * pixelRatio;\n",
+       "\n",
+       "  vec2 pos = (position + translate) * scale\n",
+       "      + (positionFract + translateFract) * scale\n",
+       "      + (position + translate) * scaleFract\n",
+       "      + (positionFract + translateFract) * scaleFract;\n",
+       "\n",
+       "  gl_Position = vec4(pos * 2. - 1., 0., 1.);\n",
+       "\n",
+       "  fragColor = color;\n",
+       "  fragBorderColor = borderColor;\n",
+       "  fragWidth = 1. / gl_PointSize;\n",
+       "\n",
+       "  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\n",
+       "  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\n",
+       "}\n",
+       "`]),this.drawMarker=e(d);var v=J2({},h);v.frag=ez([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "varying vec4 fragColor, fragBorderColor;\n",
+       "varying float fragBorderRadius, fragWidth;\n",
+       "\n",
+       "uniform float opacity;\n",
+       "\n",
+       "float smoothStep(float edge0, float edge1, float x) {\n",
+       "\tfloat t;\n",
+       "\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\n",
+       "\treturn t * t * (3.0 - 2.0 * t);\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "\tfloat radius, alpha = 1.0, delta = fragWidth;\n",
+       "\n",
+       "\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\n",
+       "\n",
+       "\tif (radius > 1.0 + delta) {\n",
+       "\t\tdiscard;\n",
+       "\t}\n",
+       "\n",
+       "\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\n",
+       "\n",
+       "\tfloat borderRadius = fragBorderRadius;\n",
+       "\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\n",
+       "\tvec4 color = mix(fragColor, fragBorderColor, ratio);\n",
+       "\tcolor.a *= alpha * opacity;\n",
+       "\tgl_FragColor = color;\n",
+       "}\n",
+       "`]),v.vert=ez([`precision highp float;\n",
+       "#define GLSLIFY 1\n",
+       "\n",
+       "attribute float x, y, xFract, yFract;\n",
+       "attribute float size, borderSize;\n",
+       "attribute vec4 colorId, borderColorId;\n",
+       "attribute float isActive;\n",
+       "\n",
+       "// \\`invariant\\` effectively turns off optimizations for the position.\n",
+       "// We need this because -fast-math on M1 Macs is re-ordering\n",
+       "// floating point operations in a way that causes floating point\n",
+       "// precision limits to put points in the wrong locations.\n",
+       "invariant gl_Position;\n",
+       "\n",
+       "uniform bool constPointSize;\n",
+       "uniform float pixelRatio;\n",
+       "uniform vec2 paletteSize, scale, scaleFract, translate, translateFract;\n",
+       "uniform sampler2D paletteTexture;\n",
+       "\n",
+       "const float maxSize = 100.;\n",
+       "\n",
+       "varying vec4 fragColor, fragBorderColor;\n",
+       "varying float fragBorderRadius, fragWidth;\n",
+       "\n",
+       "float pointSizeScale = (constPointSize) ? 2. : pixelRatio;\n",
+       "\n",
+       "bool isDirect = (paletteSize.x < 1.);\n",
+       "\n",
+       "vec4 getColor(vec4 id) {\n",
+       "  return isDirect ? id / 255. : texture2D(paletteTexture,\n",
+       "    vec2(\n",
+       "      (id.x + .5) / paletteSize.x,\n",
+       "      (id.y + .5) / paletteSize.y\n",
+       "    )\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "  // ignore inactive points\n",
+       "  if (isActive == 0.) return;\n",
+       "\n",
+       "  vec2 position = vec2(x, y);\n",
+       "  vec2 positionFract = vec2(xFract, yFract);\n",
+       "\n",
+       "  vec4 color = getColor(colorId);\n",
+       "  vec4 borderColor = getColor(borderColorId);\n",
+       "\n",
+       "  float size = size * maxSize / 255.;\n",
+       "  float borderSize = borderSize * maxSize / 255.;\n",
+       "\n",
+       "  gl_PointSize = (size + borderSize) * pointSizeScale;\n",
+       "\n",
+       "  vec2 pos = (position + translate) * scale\n",
+       "      + (positionFract + translateFract) * scale\n",
+       "      + (position + translate) * scaleFract\n",
+       "      + (positionFract + translateFract) * scaleFract;\n",
+       "\n",
+       "  gl_Position = vec4(pos * 2. - 1., 0., 1.);\n",
+       "\n",
+       "  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\n",
+       "  fragColor = color;\n",
+       "  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\n",
+       "  fragWidth = 1. / gl_PointSize;\n",
+       "}\n",
+       "`]),u7e&&(v.frag=v.frag.replace(\"smoothstep\",\"smoothStep\"),d.frag=d.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=e(v)}nv.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4};nv.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this};nv.prototype.draw=function(){for(var e=this,t=arguments.length,r=new Array(t),n=0;n<t;n++)r[n]=arguments[n];var i=this.groups;if(r.length===1&&Array.isArray(r[0])&&(r[0][0]===null||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach(function(o,s){e.drawItem(s)});return this};nv.prototype.drawItem=function(e,t){var r=this.groups,n=r[e];if(typeof t==\"number\"&&(e=t,n=r[t],t=null),!!(n&&n.count&&n.opacity)){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,t));for(var i=[],a=1;a<n.activation.length;a++)!n.activation[a]||n.activation[a]!==!0&&!n.activation[a].data.length||i.push.apply(i,TOt(this.getMarkerDrawOptions(a,n,t)));i.length&&this.drawMarker(i)}};nv.prototype.getMarkerDrawOptions=function(e,t,r){var n=t.range,i=t.tree,a=t.viewport,o=t.activation,s=t.selectionBuffer,l=t.count,u=this.regl;if(!i)return r?[J2({},t,{markerTexture:this.markerTextures[e],activation:o[e],count:r.length,elements:r,offset:0})]:[J2({},t,{markerTexture:this.markerTextures[e],activation:o[e],offset:0})];var c=[],f=i.range(n,{lod:!0,px:[(n[2]-n[0])/a.width,(n[3]-n[1])/a.height]});if(r){for(var h=o[e],d=h.data,v=new Uint8Array(l),_=0;_<r.length;_++){var b=r[_];v[b]=d?d[b]:1}s.subdata(v)}for(var p=f.length;p--;){var k=wOt(f[p],2),E=k[0],S=k[1];c.push(J2({},t,{markerTexture:this.markerTextures[e],activation:r?s:o[e],offset:E,count:S-E}))}return c};nv.prototype.update=function(){for(var e=this,t=arguments.length,r=new Array(t),n=0;n<t;n++)r[n]=arguments[n];if(r.length){r.length===1&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,l=this.maxColors,u=this.palette;this.groups=i=r.map(function(c,f){var h=i[f];if(c===void 0)return h;c===null?c={positions:null}:typeof c==\"function\"?c={ondraw:c}:typeof c[0]==\"number\"&&(c={positions:c}),c=ROt(c,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"}),c.positions===null&&(c.positions=[]),c.tooManyColors!=null&&(e.tooManyColors=c.tooManyColors),h||(i[f]=h={id:f,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},c=J2({},nv.defaults,c)),c.positions&&!(\"marker\"in c)&&(c.marker=h.marker,delete h.marker),c.marker&&!(\"positions\"in c)&&(c.positions=h.positions,delete h.positions);var d=0,v=0;if(DOt(h,c,[{snap:!0,size:function(H,N){return H==null&&(H=nv.defaults.size),d+=H&&H.length?1:0,H},borderSize:function(H,N){return H==null&&(H=nv.defaults.borderSize),d+=H&&H.length?1:0,H},opacity:parseFloat,color:function(H,N){return H==null&&(H=nv.defaults.color),H=e.updateColor(H),v++,H},borderColor:function(H,N){return H==null&&(H=nv.defaults.borderColor),H=e.updateColor(H),v++,H},bounds:function(H,N,j){return\"range\"in j||(j.range=null),H},positions:function(H,N,j){var re=N.snap,oe=N.positionBuffer,_e=N.positionFractBuffer,Ee=N.selectionBuffer;if(H.x||H.y)return H.x.length?N.xAttr={buffer:o.buffer(H.x),offset:0,stride:4,count:H.x.length}:N.xAttr={buffer:H.x.buffer,offset:H.x.offset*4||0,stride:(H.x.stride||1)*4,count:H.x.count},H.y.length?N.yAttr={buffer:o.buffer(H.y),offset:0,stride:4,count:H.y.length}:N.yAttr={buffer:H.y.buffer,offset:H.y.offset*4||0,stride:(H.y.stride||1)*4,count:H.y.count},N.count=Math.max(N.xAttr.count,N.yAttr.count),H;H=FOt(H,\"float64\");var Ce=N.count=Math.floor(H.length/2),me=N.bounds=Ce?LOt(H,2):null;if(!j.range&&!N.range&&(delete N.range,j.range=me),!j.marker&&!N.marker&&(delete N.marker,j.marker=null),re&&(re===!0||Ce>re)?N.tree=IOt(H,{bounds:me}):re&&re.length&&(N.tree=re),N.tree){var ie={primitive:\"points\",usage:\"static\",data:N.tree,type:\"uint32\"};N.elements?N.elements(ie):N.elements=o.elements(ie)}var Se=tz.float32(H);oe({data:Se,usage:\"dynamic\"});var Le=tz.fract32(H,Se);return _e({data:Le,usage:\"dynamic\"}),Ee({data:new Uint8Array(Ce),type:\"uint8\",usage:\"stream\"}),H}},{marker:function(H,N,j){var re=N.activation;if(re.forEach(function(Le){return Le&&Le.destroy&&Le.destroy()}),re.length=0,!H||typeof H[0]==\"number\"){var oe=e.addMarker(H);re[oe]=!0}else{for(var _e=[],Ee=0,Ce=Math.min(H.length,N.count);Ee<Ce;Ee++){var me=e.addMarker(H[Ee]);_e[me]||(_e[me]=new Uint8Array(N.count)),_e[me][Ee]=1}for(var ie=0;ie<_e.length;ie++)if(_e[ie]){var Se={data:_e[ie],type:\"uint8\",usage:\"static\"};re[ie]?re[ie](Se):re[ie]=o.buffer(Se),re[ie].data=_e[ie]}}return H},range:function(H,N,j){var re=N.bounds;if(re)return H||(H=re),N.scale=[1/(H[2]-H[0]),1/(H[3]-H[1])],N.translate=[-H[0],-H[1]],N.scaleFract=tz.fract(N.scale),N.translateFract=tz.fract(N.translate),H},viewport:function(H){var N=zOt(H||[a.drawingBufferWidth,a.drawingBufferHeight]);return N}}]),d){var _=h,b=_.count,p=_.size,k=_.borderSize,E=_.sizeBuffer,S=new Uint8Array(b*2);if(p.length||k.length)for(var L=0;L<b;L++)S[L*2]=Math.round((p[L]==null?p:p[L])*255/s),S[L*2+1]=Math.round((k[L]==null?k:k[L])*255/s);E({data:S,usage:\"dynamic\"})}if(v){var x=h,C=x.count,M=x.color,g=x.borderColor,P=x.colorBuffer,T;if(e.tooManyColors){if(M.length||g.length){T=new Uint8Array(C*8);for(var z=0;z<C;z++){var O=M[z];T[z*8]=u[O*4],T[z*8+1]=u[O*4+1],T[z*8+2]=u[O*4+2],T[z*8+3]=u[O*4+3];var V=g[z];T[z*8+4]=u[V*4],T[z*8+5]=u[V*4+1],T[z*8+6]=u[V*4+2],T[z*8+7]=u[V*4+3]}}}else if(M.length||g.length){T=new Uint8Array(C*4+2);for(var G=0;G<C;G++)M[G]!=null&&(T[G*4]=M[G]%l,T[G*4+1]=Math.floor(M[G]/l)),g[G]!=null&&(T[G*4+2]=g[G]%l,T[G*4+3]=Math.floor(g[G]/l))}P({data:T||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return h})}};nv.prototype.addMarker=function(e){var t=this.markerTextures,r=this.regl,n=this.markerCache,i=e==null?0:n.indexOf(e);if(i>=0)return i;var a;if(e instanceof Uint8Array||e instanceof Uint8ClampedArray)a=e;else{a=new Uint8Array(e.length);for(var o=0,s=e.length;o<s;o++)a[o]=e[o]*255}var l=Math.floor(Math.sqrt(a.length));return i=t.length,n.push(e),t.push(r.texture({channels:1,data:a,radius:l,mag:\"linear\",min:\"linear\"})),i};nv.prototype.updateColor=function(e){var t=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(e)||(e=[e]);var i=[];if(typeof e[0]==\"number\"){var a=[];if(Array.isArray(e))for(var o=0;o<e.length;o+=4)a.push(e.slice(o,o+4));else for(var s=0;s<e.length;s+=4)a.push(e.subarray(s,s+4));e=a}for(var 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qOe=lz(),BOe=TY(),IY=n1(),HBt=ux(),RY=PY(),NOe=Object.defineProperty,h5;h5=UOe.exports=function(e,t){if(!(this instanceof h5))throw new TypeError(\"Constructor requires 'new'\");RY.call(this,e),t?BOe.call(t,\"key+value\")?t=\"key+value\":BOe.call(t,\"key\")?t=\"key\":t=\"value\":t=\"value\",NOe(this,\"__kind__\",IY(\"\",t))};qOe&&qOe(h5,RY);delete h5.prototype.constructor;h5.prototype=Object.create(RY.prototype,{_resolve:IY(function(e){return this.__kind__===\"value\"?this.__list__[e]:this.__kind__===\"key+value\"?[e,this.__list__[e]]:e})});NOe(h5.prototype,HBt.toStringTag,IY(\"c\",\"Array Iterator\"))});var WOe=ye((I1r,jOe)=>{\"use strict\";var GOe=lz(),vz=n1(),jBt=ux(),DY=PY(),HOe=Object.defineProperty,d5;d5=jOe.exports=function(e){if(!(this instanceof d5))throw new TypeError(\"Constructor requires 'new'\");e=String(e),DY.call(this,e),HOe(this,\"__length__\",vz(\"\",e.length))};GOe&&GOe(d5,DY);delete d5.prototype.constructor;d5.prototype=Object.create(DY.prototype,{_next:vz(function(){if(this.__list__){if(this.__nextIndex__<this.__length__)return this.__nextIndex__++;this._unBind()}}),_resolve:vz(function(e){var t=this.__list__[e],r;return this.__nextIndex__===this.__length__?t:(r=t.charCodeAt(0),r>=55296&&r<=56319?t+this.__list__[this.__nextIndex__++]:t)})});HOe(d5.prototype,jBt.toStringTag,vz(\"c\",\"String Iterator\"))});var ZOe=ye((R1r,XOe)=>{\"use strict\";var WBt=yk(),XBt=lx(),ZBt=_k(),YBt=ux().iterator,KBt=Array.isArray;XOe.exports=function(e){return XBt(e)?KBt(e)||ZBt(e)||WBt(e)?!0:typeof e[YBt]==\"function\":!1}});var KOe=ye((D1r,YOe)=>{\"use strict\";var JBt=ZOe();YOe.exports=function(e){if(!JBt(e))throw new TypeError(e+\" is not iterable\");return e}});var FY=ye((F1r,QOe)=>{\"use strict\";var $Bt=yk(),QBt=_k(),JOe=VOe(),eNt=WOe(),tNt=KOe(),$Oe=ux().iterator;QOe.exports=function(e){return typeof tNt(e)[$Oe]==\"function\"?e[$Oe]():$Bt(e)?new JOe(e):QBt(e)?new eNt(e):new JOe(e)}});var tqe=ye((z1r,eqe)=>{\"use strict\";var rNt=yk(),iNt=f5(),nNt=_k(),aNt=FY(),oNt=Array.isArray,zY=Function.prototype.call,sNt=Array.prototype.some;eqe.exports=function(e,t){var r,n=arguments[2],i,a,o,s,l,u,c;if(oNt(e)||rNt(e)?r=\"array\":nNt(e)?r=\"string\":e=aNt(e),iNt(t),a=function(){o=!0},r===\"array\"){sNt.call(e,function(f){return zY.call(t,n,f,a),o});return}if(r===\"string\"){for(l=e.length,s=0;s<l&&(u=e[s],s+1<l&&(c=u.charCodeAt(0),c>=55296&&c<=56319&&(u+=e[++s])),zY.call(t,n,u,a),!o);++s);return}for(i=e.next();!i.done;){if(zY.call(t,n,i.value,a),o)return;i=e.next()}}});var iqe=ye((O1r,rqe)=>{\"use strict\";rqe.exports=function(){return typeof WeakMap!=\"function\"?!1:Object.prototype.toString.call(new WeakMap)===\"[object WeakMap]\"}()});var oqe=ye((q1r,aqe)=>{\"use strict\";var lNt=lx(),gz=lz(),pz=R7e(),uNt=i1(),cNt=F7e(),a1=n1(),fNt=FY(),hNt=tqe(),dNt=ux().toStringTag,nqe=iqe(),vNt=Array.isArray,qY=Object.defineProperty,OY=Object.prototype.hasOwnProperty,pNt=Object.getPrototypeOf,cx;aqe.exports=cx=function(){var e=arguments[0],t;if(!(this instanceof cx))throw new TypeError(\"Constructor requires 'new'\");return t=nqe&&gz&&WeakMap!==cx?gz(new WeakMap,pNt(this)):this,lNt(e)&&(vNt(e)||(e=fNt(e))),qY(t,\"__weakMapData__\",a1(\"c\",\"$weakMap$\"+cNt())),e&&hNt(e,function(r){uNt(r),t.set(r[0],r[1])}),t};nqe&&(gz&&gz(cx,WeakMap),cx.prototype=Object.create(WeakMap.prototype,{constructor:a1(cx)}));Object.defineProperties(cx.prototype,{delete:a1(function(e){return OY.call(pz(e),this.__weakMapData__)?(delete e[this.__weakMapData__],!0):!1}),get:a1(function(e){if(OY.call(pz(e),this.__weakMapData__))return e[this.__weakMapData__]}),has:a1(function(e){return OY.call(pz(e),this.__weakMapData__)}),set:a1(function(e,t){return qY(pz(e),this.__weakMapData__,a1(\"c\",t)),this}),toString:a1(function(){return\"[object WeakMap]\"})});qY(cx.prototype,dNt,a1(\"c\",\"WeakMap\"))});var BY=ye((B1r,sqe)=>{\"use strict\";sqe.exports=x7e()()?WeakMap:oqe()});var uqe=ye((N1r,lqe)=>{\"use strict\";lqe.exports=function(e,t,r){if(typeof Array.prototype.findIndex==\"function\")return e.findIndex(t,r);if(typeof t!=\"function\")throw new TypeError(\"predicate must be a function\");var n=Object(e),i=n.length;if(i===0)return-1;for(var a=0;a<i;a++)if(t.call(r,n[a],a,n))return a;return-1}});var VY=ye((U1r,hqe)=>{\"use strict\";var mz=J_(),gNt=W2(),UY=Oh(),mNt=Zm(),yNt=X2(),cqe=g7e(),_Nt=y7e(),{float32:xNt,fract32:NY}=QF(),bNt=BY(),fqe=r5(),wNt=uqe(),TNt=`\n",
+       "precision highp float;\n",
+       "\n",
+       "attribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\n",
+       "attribute vec4 color;\n",
+       "attribute float lineEnd, lineTop;\n",
+       "\n",
+       "uniform vec2 scale, scaleFract, translate, translateFract;\n",
+       "uniform float thickness, pixelRatio, id, depth;\n",
+       "uniform vec4 viewport;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "varying vec2 tangent;\n",
+       "\n",
+       "vec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\n",
+       "\t// the order is important\n",
+       "\treturn position * scale + translate\n",
+       "       + positionFract * scale + translateFract\n",
+       "       + position * scaleFract\n",
+       "       + positionFract * scaleFract;\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "\tfloat lineStart = 1. - lineEnd;\n",
+       "\tfloat lineOffset = lineTop * 2. - 1.;\n",
+       "\n",
+       "\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\n",
+       "\ttangent = normalize(diff * scale * viewport.zw);\n",
+       "\tvec2 normal = vec2(-tangent.y, tangent.x);\n",
+       "\n",
+       "\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\n",
+       "\t\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\n",
+       "\n",
+       "\t\t+ thickness * normal * .5 * lineOffset / viewport.zw;\n",
+       "\n",
+       "\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n",
+       "\n",
+       "\tfragColor = color / 255.;\n",
+       "}\n",
+       "`,ANt=`\n",
+       "precision highp float;\n",
+       "\n",
+       "uniform float dashLength, pixelRatio, thickness, opacity, id;\n",
+       "uniform sampler2D dashTexture;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "varying vec2 tangent;\n",
+       "\n",
+       "void main() {\n",
+       "\tfloat alpha = 1.;\n",
+       "\n",
+       "\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\n",
+       "\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\n",
+       "\n",
+       "\tgl_FragColor = fragColor;\n",
+       "\tgl_FragColor.a *= alpha * opacity * dash;\n",
+       "}\n",
+       "`,SNt=`\n",
+       "precision highp float;\n",
+       "\n",
+       "attribute vec2 position, positionFract;\n",
+       "\n",
+       "uniform vec4 color;\n",
+       "uniform vec2 scale, scaleFract, translate, translateFract;\n",
+       "uniform float pixelRatio, id;\n",
+       "uniform vec4 viewport;\n",
+       "uniform float opacity;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "const float MAX_LINES = 256.;\n",
+       "\n",
+       "void main() {\n",
+       "\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\n",
+       "\n",
+       "\tvec2 position = position * scale + translate\n",
+       "       + positionFract * scale + translateFract\n",
+       "       + position * scaleFract\n",
+       "       + positionFract * scaleFract;\n",
+       "\n",
+       "\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n",
+       "\n",
+       "\tfragColor = color / 255.;\n",
+       "\tfragColor.a *= opacity;\n",
+       "}\n",
+       "`,MNt=`\n",
+       "precision highp float;\n",
+       "varying vec4 fragColor;\n",
+       "\n",
+       "void main() {\n",
+       "\tgl_FragColor = fragColor;\n",
+       "}\n",
+       "`,ENt=`\n",
+       "precision highp float;\n",
+       "\n",
+       "attribute vec2 aCoord, bCoord, nextCoord, prevCoord;\n",
+       "attribute vec4 aColor, bColor;\n",
+       "attribute float lineEnd, lineTop;\n",
+       "\n",
+       "uniform vec2 scale, translate;\n",
+       "uniform float thickness, pixelRatio, id, depth;\n",
+       "uniform vec4 viewport;\n",
+       "uniform float miterLimit, miterMode;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "varying vec4 startCutoff, endCutoff;\n",
+       "varying vec2 tangent;\n",
+       "varying vec2 startCoord, endCoord;\n",
+       "varying float enableStartMiter, enableEndMiter;\n",
+       "\n",
+       "const float REVERSE_THRESHOLD = -.875;\n",
+       "const float MIN_DIFF = 1e-6;\n",
+       "\n",
+       "// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\n",
+       "// TODO: precalculate dot products, normalize things beforehead etc.\n",
+       "// TODO: refactor to rectangular algorithm\n",
+       "\n",
+       "float distToLine(vec2 p, vec2 a, vec2 b) {\n",
+       "\tvec2 diff = b - a;\n",
+       "\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n",
+       "\treturn dot(p - a, perp);\n",
+       "}\n",
+       "\n",
+       "bool isNaN( float val ){\n",
+       "  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\n",
+       "\n",
+       "  vec2 adjustedScale;\n",
+       "  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\n",
+       "  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\n",
+       "\n",
+       "  vec2 scaleRatio = adjustedScale * viewport.zw;\n",
+       "\tvec2 normalWidth = thickness / scaleRatio;\n",
+       "\n",
+       "\tfloat lineStart = 1. - lineEnd;\n",
+       "\tfloat lineBot = 1. - lineTop;\n",
+       "\n",
+       "\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\n",
+       "\n",
+       "\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\n",
+       "\n",
+       "\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\n",
+       "\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\n",
+       "\n",
+       "\n",
+       "\tvec2 prevDiff = aCoord - prevCoord;\n",
+       "\tvec2 currDiff = bCoord - aCoord;\n",
+       "\tvec2 nextDiff = nextCoord - bCoord;\n",
+       "\n",
+       "\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\n",
+       "\tvec2 currTangent = normalize(currDiff * scaleRatio);\n",
+       "\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\n",
+       "\n",
+       "\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\n",
+       "\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\n",
+       "\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\n",
+       "\n",
+       "\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\n",
+       "\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\n",
+       "\n",
+       "\t// collapsed/unidirectional segment cases\n",
+       "\t// FIXME: there should be more elegant solution\n",
+       "\tvec2 prevTanDiff = abs(prevTangent - currTangent);\n",
+       "\tvec2 nextTanDiff = abs(nextTangent - currTangent);\n",
+       "\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\n",
+       "\t\tstartJoinDirection = currNormal;\n",
+       "\t}\n",
+       "\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\n",
+       "\t\tendJoinDirection = currNormal;\n",
+       "\t}\n",
+       "\tif (aCoord == bCoord) {\n",
+       "\t\tendJoinDirection = startJoinDirection;\n",
+       "\t\tcurrNormal = prevNormal;\n",
+       "\t\tcurrTangent = prevTangent;\n",
+       "\t}\n",
+       "\n",
+       "\ttangent = currTangent;\n",
+       "\n",
+       "\t//calculate join shifts relative to normals\n",
+       "\tfloat startJoinShift = dot(currNormal, startJoinDirection);\n",
+       "\tfloat endJoinShift = dot(currNormal, endJoinDirection);\n",
+       "\n",
+       "\tfloat startMiterRatio = abs(1. / startJoinShift);\n",
+       "\tfloat endMiterRatio = abs(1. / endJoinShift);\n",
+       "\n",
+       "\tvec2 startJoin = startJoinDirection * startMiterRatio;\n",
+       "\tvec2 endJoin = endJoinDirection * endMiterRatio;\n",
+       "\n",
+       "\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\n",
+       "\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\n",
+       "\tstartBotJoin = -startTopJoin;\n",
+       "\n",
+       "\tendTopJoin = sign(endJoinShift) * endJoin * .5;\n",
+       "\tendBotJoin = -endTopJoin;\n",
+       "\n",
+       "\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\n",
+       "\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\n",
+       "\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\n",
+       "\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\n",
+       "\n",
+       "\t//miter anti-clipping\n",
+       "\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\n",
+       "\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\n",
+       "\n",
+       "\t//prevent close to reverse direction switch\n",
+       "\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\n",
+       "\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\n",
+       "\n",
+       "\tif (prevReverse) {\n",
+       "\t\t//make join rectangular\n",
+       "\t\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\n",
+       "\t\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\n",
+       "\t\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n",
+       "\t\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n",
+       "\t}\n",
+       "\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\n",
+       "\t\t//handle miter clipping\n",
+       "\t\tbTopCoord -= normalWidth * endTopJoin;\n",
+       "\t\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\n",
+       "\t}\n",
+       "\n",
+       "\tif (nextReverse) {\n",
+       "\t\t//make join rectangular\n",
+       "\t\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\n",
+       "\t\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\n",
+       "\t\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n",
+       "\t\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n",
+       "\t}\n",
+       "\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\n",
+       "\t\t//handle miter clipping\n",
+       "\t\taBotCoord -= normalWidth * startBotJoin;\n",
+       "\t\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\n",
+       "\t}\n",
+       "\n",
+       "\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\n",
+       "\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\n",
+       "\n",
+       "\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\n",
+       "\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\n",
+       "\n",
+       "\t//position is normalized 0..1 coord on the screen\n",
+       "\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\n",
+       "\n",
+       "\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n",
+       "\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n",
+       "\n",
+       "\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\n",
+       "\n",
+       "\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\n",
+       "\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\n",
+       "\n",
+       "\t//bevel miter cutoffs\n",
+       "\tif (miterMode == 1.) {\n",
+       "\t\tif (enableStartMiter == 1.) {\n",
+       "\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\n",
+       "\t\t\tstartCutoff = vec4(aCoord, aCoord);\n",
+       "\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n",
+       "\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n",
+       "\t\t\tstartCutoff += viewport.xyxy;\n",
+       "\t\t\tstartCutoff += startMiterWidth.xyxy;\n",
+       "\t\t}\n",
+       "\n",
+       "\t\tif (enableEndMiter == 1.) {\n",
+       "\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\n",
+       "\t\t\tendCutoff = vec4(bCoord, bCoord);\n",
+       "\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\n",
+       "\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n",
+       "\t\t\tendCutoff += viewport.xyxy;\n",
+       "\t\t\tendCutoff += endMiterWidth.xyxy;\n",
+       "\t\t}\n",
+       "\t}\n",
+       "\n",
+       "\t//round miter cutoffs\n",
+       "\telse if (miterMode == 2.) {\n",
+       "\t\tif (enableStartMiter == 1.) {\n",
+       "\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\n",
+       "\t\t\tstartCutoff = vec4(aCoord, aCoord);\n",
+       "\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n",
+       "\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n",
+       "\t\t\tstartCutoff += viewport.xyxy;\n",
+       "\t\t\tstartCutoff += startMiterWidth.xyxy;\n",
+       "\t\t}\n",
+       "\n",
+       "\t\tif (enableEndMiter == 1.) {\n",
+       "\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\n",
+       "\t\t\tendCutoff = vec4(bCoord, bCoord);\n",
+       "\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\n",
+       "\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n",
+       "\t\t\tendCutoff += viewport.xyxy;\n",
+       "\t\t\tendCutoff += endMiterWidth.xyxy;\n",
+       "\t\t}\n",
+       "\t}\n",
+       "}\n",
+       "`,kNt=`\n",
+       "precision highp float;\n",
+       "\n",
+       "uniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\n",
+       "uniform sampler2D dashTexture;\n",
+       "\n",
+       "varying vec4 fragColor;\n",
+       "varying vec2 tangent;\n",
+       "varying vec4 startCutoff, endCutoff;\n",
+       "varying vec2 startCoord, endCoord;\n",
+       "varying float enableStartMiter, enableEndMiter;\n",
+       "\n",
+       "float distToLine(vec2 p, vec2 a, vec2 b) {\n",
+       "\tvec2 diff = b - a;\n",
+       "\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n",
+       "\treturn dot(p - a, perp);\n",
+       "}\n",
+       "\n",
+       "void main() {\n",
+       "\tfloat alpha = 1., distToStart, distToEnd;\n",
+       "\tfloat cutoff = thickness * .5;\n",
+       "\n",
+       "\t//bevel miter\n",
+       "\tif (miterMode == 1.) {\n",
+       "\t\tif (enableStartMiter == 1.) {\n",
+       "\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n",
+       "\t\t\tif (distToStart < -1.) {\n",
+       "\t\t\t\tdiscard;\n",
+       "\t\t\t\treturn;\n",
+       "\t\t\t}\n",
+       "\t\t\talpha *= min(max(distToStart + 1., 0.), 1.);\n",
+       "\t\t}\n",
+       "\n",
+       "\t\tif (enableEndMiter == 1.) {\n",
+       "\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n",
+       "\t\t\tif (distToEnd < -1.) {\n",
+       "\t\t\t\tdiscard;\n",
+       "\t\t\t\treturn;\n",
+       "\t\t\t}\n",
+       "\t\t\talpha *= min(max(distToEnd + 1., 0.), 1.);\n",
+       "\t\t}\n",
+       "\t}\n",
+       "\n",
+       "\t// round miter\n",
+       "\telse if (miterMode == 2.) {\n",
+       "\t\tif (enableStartMiter == 1.) {\n",
+       "\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n",
+       "\t\t\tif (distToStart < 0.) {\n",
+       "\t\t\t\tfloat radius = length(gl_FragCoord.xy - startCoord);\n",
+       "\n",
+       "\t\t\t\tif(radius > cutoff + .5) {\n",
+       "\t\t\t\t\tdiscard;\n",
+       "\t\t\t\t\treturn;\n",
+       "\t\t\t\t}\n",
+       "\n",
+       "\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n",
+       "\t\t\t}\n",
+       "\t\t}\n",
+       "\n",
+       "\t\tif (enableEndMiter == 1.) {\n",
+       "\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n",
+       "\t\t\tif (distToEnd < 0.) {\n",
+       "\t\t\t\tfloat radius = length(gl_FragCoord.xy - endCoord);\n",
+       "\n",
+       "\t\t\t\tif(radius > cutoff + .5) {\n",
+       "\t\t\t\t\tdiscard;\n",
+       "\t\t\t\t\treturn;\n",
+       "\t\t\t\t}\n",
+       "\n",
+       "\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n",
+       "\t\t\t}\n",
+       "\t\t}\n",
+       "\t}\n",
+       "\n",
+       "\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\n",
+       "\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\n",
+       "\n",
+       "\tgl_FragColor = fragColor;\n",
+       "\tgl_FragColor.a *= alpha * opacity * dash;\n",
+       "}\n",
+       "`;hqe.exports=Wc;function Wc(e,t){if(!(this instanceof Wc))return new Wc(e,t);if(typeof e==\"function\"?(t||(t={}),t.regl=e):t=e,t.length&&(t.positions=t),e=t.regl,!e.hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=e._gl,this.regl=e,this.passes=[],this.shaders=Wc.shaders.has(e)?Wc.shaders.get(e):Wc.shaders.set(e,Wc.createShaders(e)).get(e),this.update(t)}Wc.dashMult=2;Wc.maxPatternLength=256;Wc.precisionThreshold=3e6;Wc.maxPoints=1e4;Wc.maxLines=2048;Wc.shaders=new bNt;Wc.createShaders=function(e){let t=e.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),r={primitive:\"triangle strip\",instances:e.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:(o,s)=>s.join===\"round\"?2:1,miterLimit:e.prop(\"miterLimit\"),scale:e.prop(\"scale\"),scaleFract:e.prop(\"scaleFract\"),translateFract:e.prop(\"translateFract\"),translate:e.prop(\"translate\"),thickness:e.prop(\"thickness\"),dashTexture:e.prop(\"dashTexture\"),opacity:e.prop(\"opacity\"),pixelRatio:e.context(\"pixelRatio\"),id:e.prop(\"id\"),dashLength:e.prop(\"dashLength\"),viewport:(o,s)=>[s.viewport.x,s.viewport.y,o.viewportWidth,o.viewportHeight],depth:e.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:(o,s)=>!s.overlay},stencil:{enable:!1},scissor:{enable:!0,box:e.prop(\"viewport\")},viewport:e.prop(\"viewport\")},n=e(UY({vert:TNt,frag:ANt,attributes:{lineEnd:{buffer:t,divisor:0,stride:8,offset:0},lineTop:{buffer:t,divisor:0,stride:8,offset:4},aCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:e.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:e.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:e.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},r)),i;try{i=e(UY({cull:{enable:!0,face:\"back\"},vert:ENt,frag:kNt,attributes:{lineEnd:{buffer:t,divisor:0,stride:8,offset:0},lineTop:{buffer:t,divisor:0,stride:8,offset:4},aColor:{buffer:e.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:e.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},r))}catch(o){i=n}return{fill:e({primitive:\"triangle\",elements:(o,s)=>s.triangles,offset:0,vert:SNt,frag:MNt,uniforms:{scale:e.prop(\"scale\"),color:e.prop(\"fill\"),scaleFract:e.prop(\"scaleFract\"),translateFract:e.prop(\"translateFract\"),translate:e.prop(\"translate\"),opacity:e.prop(\"opacity\"),pixelRatio:e.context(\"pixelRatio\"),id:e.prop(\"id\"),viewport:(o,s)=>[s.viewport.x,s.viewport.y,o.viewportWidth,o.viewportHeight]},attributes:{position:{buffer:e.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:e.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:r.blend,depth:{enable:!1},scissor:r.scissor,stencil:r.stencil,viewport:r.viewport}),rect:n,miter:i}};Wc.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null};Wc.prototype.render=function(...e){e.length&&this.update(...e),this.draw()};Wc.prototype.draw=function(...e){return(e.length?e:this.passes).forEach((t,r)=>{if(t&&Array.isArray(t))return this.draw(...t);typeof t==\"number\"&&(t=this.passes[t]),t&&t.count>1&&t.opacity&&(this.regl._refresh(),t.fill&&t.triangles&&t.triangles.length>2&&this.shaders.fill(t),t.thickness&&(t.scale[0]*t.viewport.width>Wc.precisionThreshold||t.scale[1]*t.viewport.height>Wc.precisionThreshold?this.shaders.rect(t):t.join===\"rect\"||!t.join&&(t.thickness<=2||t.count>=Wc.maxPoints)?this.shaders.rect(t):this.shaders.miter(t)))}),this};Wc.prototype.update=function(e){if(!e)return;e.length!=null?typeof e[0]==\"number\"&&(e=[{positions:e}]):Array.isArray(e)||(e=[e]);let{regl:t,gl:r}=this;if(e.forEach((i,a)=>{let o=this.passes[a];if(i!==void 0){if(i===null){this.passes[a]=null;return}if(typeof i[0]==\"number\"&&(i={positions:i}),i=mNt(i,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin join type mode\",miterLimit:\"miterlimit miterLimit\",dashes:\"dash dashes dasharray dash-array dashArray\",color:\"color colour stroke colors colours stroke-color strokeColor\",fill:\"fill fill-color fillColor\",opacity:\"alpha opacity\",overlay:\"overlay crease overlap intersect\",close:\"closed close closed-path closePath\",range:\"range dataBox\",viewport:\"viewport viewBox\",hole:\"holes hole hollow\",splitNull:\"splitNull\"}),o||(this.passes[a]=o={id:a,scale:null,scaleFract:null,translate:null,translateFract:null,count:0,hole:[],depth:0,dashLength:1,dashTexture:t.texture({channels:1,data:new Uint8Array([255]),width:1,height:1,mag:\"linear\",min:\"linear\"}),colorBuffer:t.buffer({usage:\"dynamic\",type:\"uint8\",data:new Uint8Array}),positionBuffer:t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),positionFractBuffer:t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array})},i=UY({},Wc.defaults,i)),i.thickness!=null&&(o.thickness=parseFloat(i.thickness)),i.opacity!=null&&(o.opacity=parseFloat(i.opacity)),i.miterLimit!=null&&(o.miterLimit=parseFloat(i.miterLimit)),i.overlay!=null&&(o.overlay=!!i.overlay,a<Wc.maxLines&&(o.depth=2*(Wc.maxLines-1-a%Wc.maxLines)/Wc.maxLines-1)),i.join!=null&&(o.join=i.join),i.hole!=null&&(o.hole=i.hole),i.fill!=null&&(o.fill=i.fill?mz(i.fill,\"uint8\"):null),i.viewport!=null&&(o.viewport=fqe(i.viewport)),o.viewport||(o.viewport=fqe([r.drawingBufferWidth,r.drawingBufferHeight])),i.close!=null&&(o.close=i.close),i.positions===null&&(i.positions=[]),i.positions){let u,c;if(i.positions.x&&i.positions.y){let v=i.positions.x,_=i.positions.y;c=o.count=Math.max(v.length,_.length),u=new Float64Array(c*2);for(let b=0;b<c;b++)u[b*2]=v[b],u[b*2+1]=_[b]}else u=yNt(i.positions,\"float64\"),c=o.count=Math.floor(u.length/2);let f=o.bounds=gNt(u,2);if(o.fill){let v=[],_={},b=0;for(let p=0,k=0,E=o.count;p<E;p++){let S=u[p*2],L=u[p*2+1];isNaN(S)||isNaN(L)||S==null||L==null?(S=u[b*2],L=u[b*2+1],_[p]=b):b=p,v[k++]=S,v[k++]=L}if(i.splitNull){o.count-1 in _||(_[o.count]=o.count-1);let p=Object.keys(_).map(Number).sort((L,x)=>L-x),k=[],E=0,S=o.hole!=null?o.hole[0]:null;if(S!=null){let L=wNt(p,x=>x>=S);p=p.slice(0,L),p.push(S)}for(let L=0;L<p.length;L++){let x=v.slice(E*2,p[L]*2).concat(S?v.slice(S*2):[]),C=(o.hole||[]).map(g=>g-S+(p[L]-E)),M=cqe(x,C);M=M.map(g=>g+E+(g+E<p[L]?0:S-p[L])),k.push(...M),E=p[L]+1}for(let L=0,x=k.length;L<x;L++)_[k[L]]!=null&&(k[L]=_[k[L]]);o.triangles=k}else{let p=cqe(v,o.hole||[]);for(let k=0,E=p.length;k<E;k++)_[p[k]]!=null&&(p[k]=_[p[k]]);o.triangles=p}}let h=new Float64Array(u);_Nt(h,2,f);let d=new Float64Array(c*2+6);o.close?u[0]===u[c*2-2]&&u[1]===u[c*2-1]?(d[0]=h[c*2-4],d[1]=h[c*2-3]):(d[0]=h[c*2-2],d[1]=h[c*2-1]):(d[0]=h[0],d[1]=h[1]),d.set(h,2),o.close?u[0]===u[c*2-2]&&u[1]===u[c*2-1]?(d[c*2+2]=h[2],d[c*2+3]=h[3],o.count-=1):(d[c*2+2]=h[0],d[c*2+3]=h[1],d[c*2+4]=h[2],d[c*2+5]=h[3]):(d[c*2+2]=h[c*2-2],d[c*2+3]=h[c*2-1],d[c*2+4]=h[c*2-2],d[c*2+5]=h[c*2-1]);var s=xNt(d);o.positionBuffer(s);var l=NY(d,s);o.positionFractBuffer(l)}if(i.range?o.range=i.range:o.range||(o.range=o.bounds),(i.range||i.positions)&&o.count){let u=o.bounds,c=u[2]-u[0],f=u[3]-u[1],h=o.range[2]-o.range[0],d=o.range[3]-o.range[1];o.scale=[c/h,f/d],o.translate=[-o.range[0]/h+u[0]/h||0,-o.range[1]/d+u[1]/d||0],o.scaleFract=NY(o.scale),o.translateFract=NY(o.translate)}if(i.dashes){let u=0,c;if(!i.dashes||i.dashes.length<2)u=1,c=new Uint8Array([255,255,255,255,255,255,255,255]);else{u=0;for(let d=0;d<i.dashes.length;++d)u+=i.dashes[d];c=new Uint8Array(u*Wc.dashMult);let f=0,h=255;for(let d=0;d<2;d++)for(let v=0;v<i.dashes.length;++v){for(let _=0,b=i.dashes[v]*Wc.dashMult*.5;_<b;++_)c[f++]=h;h^=255}}o.dashLength=u,o.dashTexture({channels:1,data:c,width:c.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(i.color){let u=o.count,c=i.color;c||(c=\"transparent\");let f=new Uint8Array(u*4+4);if(!Array.isArray(c)||typeof c[0]==\"number\"){let h=mz(c,\"uint8\");for(let d=0;d<u+1;d++)f.set(h,d*4)}else{for(let h=0;h<u;h++){let d=mz(c[h],\"uint8\");f.set(d,h*4)}f.set(mz(c[0],\"uint8\"),u*4)}o.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:f})}}}),e.length<this.passes.length){for(let i=e.length;i<this.passes.length;i++){let a=this.passes[i];a&&(a.colorBuffer.destroy(),a.positionBuffer.destroy(),a.dashTexture.destroy())}this.passes.length=e.length}let n=[];for(let i=0;i<this.passes.length;i++)this.passes[i]!==null&&n.push(this.passes[i]);return this.passes=n,this};Wc.prototype.destroy=function(){return this.passes.forEach(e=>{e.colorBuffer.destroy(),e.positionBuffer.destroy(),e.dashTexture.destroy()}),this.passes.length=0,this}});var mqe=ye((V1r,gqe)=>{\"use strict\";var CNt=W2(),LNt=J_(),PNt=uY(),INt=Zm(),dqe=Oh(),vqe=X2(),{float32:RNt,fract32:GY}=QF();gqe.exports=DNt;var pqe=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]];function DNt(e,t){if(typeof e==\"function\"?(t||(t={}),t.regl=e):t=e,t.length&&(t.positions=t),e=t.regl,!e.hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");let r=e._gl,n,i,a,o,s,l,u={color:\"black\",capSize:5,lineWidth:1,opacity:1,viewport:null,range:null,offset:0,count:0,bounds:null,positions:[],errors:[]},c=[];return o=e.buffer({usage:\"dynamic\",type:\"uint8\",data:new Uint8Array(0)}),i=e.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),a=e.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),s=e.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)}),l=e.buffer({usage:\"static\",type:\"float\",data:pqe}),v(t),n=e({vert:`\n",
+       "\t\tprecision highp float;\n",
+       "\n",
+       "\t\tattribute vec2 position, positionFract;\n",
+       "\t\tattribute vec4 error;\n",
+       "\t\tattribute vec4 color;\n",
+       "\n",
+       "\t\tattribute vec2 direction, lineOffset, capOffset;\n",
+       "\n",
+       "\t\tuniform vec4 viewport;\n",
+       "\t\tuniform float lineWidth, capSize;\n",
+       "\t\tuniform vec2 scale, scaleFract, translate, translateFract;\n",
+       "\n",
+       "\t\tvarying vec4 fragColor;\n",
+       "\n",
+       "\t\tvoid main() {\n",
+       "\t\t\tfragColor = color / 255.;\n",
+       "\n",
+       "\t\t\tvec2 pixelOffset = lineWidth * lineOffset + (capSize + lineWidth) * capOffset;\n",
+       "\n",
+       "\t\t\tvec2 dxy = -step(.5, direction.xy) * error.xz + step(direction.xy, vec2(-.5)) * error.yw;\n",
+       "\n",
+       "\t\t\tvec2 position = position + dxy;\n",
+       "\n",
+       "\t\t\tvec2 pos = (position + translate) * scale\n",
+       "\t\t\t\t+ (positionFract + translateFract) * scale\n",
+       "\t\t\t\t+ (position + translate) * scaleFract\n",
+       "\t\t\t\t+ (positionFract + translateFract) * scaleFract;\n",
+       "\n",
+       "\t\t\tpos += pixelOffset / viewport.zw;\n",
+       "\n",
+       "\t\t\tgl_Position = vec4(pos * 2. - 1., 0, 1);\n",
+       "\t\t}\n",
+       "\t\t`,frag:`\n",
+       "\t\tprecision highp float;\n",
+       "\n",
+       "\t\tvarying vec4 fragColor;\n",
+       "\n",
+       "\t\tuniform float opacity;\n",
+       "\n",
+       "\t\tvoid main() {\n",
+       "\t\t\tgl_FragColor = fragColor;\n",
+       "\t\t\tgl_FragColor.a *= opacity;\n",
+       "\t\t}\n",
+       "\t\t`,uniforms:{range:e.prop(\"range\"),lineWidth:e.prop(\"lineWidth\"),capSize:e.prop(\"capSize\"),opacity:e.prop(\"opacity\"),scale:e.prop(\"scale\"),translate:e.prop(\"translate\"),scaleFract:e.prop(\"scaleFract\"),translateFract:e.prop(\"translateFract\"),viewport:(b,p)=>[p.viewport.x,p.viewport.y,b.viewportWidth,b.viewportHeight]},attributes:{color:{buffer:o,offset:(b,p)=>p.offset*4,divisor:1},position:{buffer:i,offset:(b,p)=>p.offset*8,divisor:1},positionFract:{buffer:a,offset:(b,p)=>p.offset*8,divisor:1},error:{buffer:s,offset:(b,p)=>p.offset*16,divisor:1},direction:{buffer:l,stride:24,offset:0},lineOffset:{buffer:l,stride:24,offset:8},capOffset:{buffer:l,stride:24,offset:16}},primitive:\"triangles\",blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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Dt=ne.width||Ue[0].length,yt=ne.height||Ue.length,Pt=ne.channels;Mn(Ue[0][0])?Pt=Pt||Ue[0][0].length:Pt=Pt||1;for(var ht=Ge.shape(Ue),ur=1,br=0;br<ht.length;++br)ur*=ht[br];var Ur=th(ne,ur);Ge.flatten(Ue,ht,\"\",Ur),ju(ne,Ur),ne.alignment=1,ne.width=Dt,ne.height=yt,ne.channels=Pt,ne.format=ne.internalformat=Hs[Pt],ne.needsFree=!0}ne.type===aa||ne.type}function pn(ne,we,Ue){var ft=ne.element,Xt=ne.data,hr=ne.internalformat,qt=ne.format,Ve=ne.type,Qe=ne.width,at=ne.height;Ji(ne),ft?Me.texImage2D(we,Ue,qt,qt,Ve,ft):ne.compressed?Me.compressedTexImage2D(we,Ue,hr,Qe,at,0,Xt):ne.needsCopy?(Rr(),Me.copyTexImage2D(we,Ue,qt,ne.xOffset,ne.yOffset,Qe,at,0)):Me.texImage2D(we,Ue,qt,Qe,at,0,qt,Ve,Xt||null)}function Vn(ne,we,Ue,ft,Xt){var hr=ne.element,qt=ne.data,Ve=ne.internalformat,Qe=ne.format,at=ne.type,Ct=ne.width,Ot=ne.height;Ji(ne),hr?Me.texSubImage2D(we,Xt,Ue,ft,Qe,at,hr):ne.compressed?Me.compressedTexSubImage2D(we,Xt,Ue,ft,Ve,Ct,Ot,qt):ne.needsCopy?(Rr(),Me.copyTexSubImage2D(we,Xt,Ue,ft,ne.xOffset,ne.yOffset,Ct,Ot)):Me.texSubImage2D(we,Xt,Ue,ft,Ct,Ot,Qe,at,qt)}var na=[];function Ki(){return na.pop()||new Vi}function kn(ne){ne.needsFree&&j.freeType(ne.data),Vi.call(ne),na.push(ne)}function ta(){hi.call(this),this.genMipmaps=!1,this.mipmapHint=sc,this.mipmask=0,this.images=Array(16)}function oa(ne,we,Ue){var ft=ne.images[0]=Ki();ne.mipmask=1,ft.width=ne.width=we,ft.height=ne.height=Ue,ft.channels=ne.channels=4}function ba(ne,we){var Ue=null;if(_f(we))Ue=ne.images[0]=Ki(),li(Ue,ne),Ni(Ue,we),ne.mipmask=1;else if(mn(ne,we),Array.isArray(we.mipmap))for(var ft=we.mipmap,Xt=0;Xt<ft.length;++Xt)Ue=ne.images[Xt]=Ki(),li(Ue,ne),Ue.width>>=Xt,Ue.height>>=Xt,Ni(Ue,ft[Xt]),ne.mipmask|=1<<Xt;else Ue=ne.images[0]=Ki(),li(Ue,ne),Ni(Ue,we),ne.mipmask=1;li(ne,ne.images[0]),ne.compressed&&(ne.internalformat===Io||ne.internalformat===ls||ne.internalformat===Zl||ne.internalformat)}function is(ne,we){for(var Ue=ne.images,ft=0;ft<Ue.length;++ft){if(!Ue[ft])return;pn(Ue[ft],we,ft)}}var Zs=[];function Va(){var ne=Zs.pop()||new ta;hi.call(ne),ne.mipmask=0;for(var we=0;we<16;++we)ne.images[we]=null;return ne}function Ml(ne){for(var we=ne.images,Ue=0;Ue<we.length;++Ue)we[Ue]&&kn(we[Ue]),we[Ue]=null;Zs.push(ne)}function zo(){this.minFilter=pl,this.magFilter=pl,this.wrapS=Pc,this.wrapT=Pc,this.anisotropic=1,this.genMipmaps=!1,this.mipmapHint=sc}function Qs(ne,we){if(\"min\"in we){var Ue=we.min;ne.minFilter=Ei[Ue],Es.indexOf(ne.minFilter)>=0&&!(\"faces\"in we)&&(ne.genMipmaps=!0)}if(\"mag\"in we){var ft=we.mag;ne.magFilter=qi[ft]}var Xt=ne.wrapS,hr=ne.wrapT;if(\"wrap\"in we){var qt=we.wrap;typeof qt==\"string\"?Xt=hr=Ui[qt]:Array.isArray(qt)&&(Xt=Ui[qt[0]],hr=Ui[qt[1]])}else{if(\"wrapS\"in we){var Ve=we.wrapS;Xt=Ui[Ve]}if(\"wrapT\"in we){var Qe=we.wrapT;hr=Ui[Qe]}}if(ne.wrapS=Xt,ne.wrapT=hr,\"anisotropic\"in we){var at=we.anisotropic;ne.anisotropic=we.anisotropic}if(\"mipmap\"in we){var Ct=!1;switch(typeof we.mipmap){case\"string\":ne.mipmapHint=mi[we.mipmap],ne.genMipmaps=!0,Ct=!0;break;case\"boolean\":Ct=ne.genMipmaps=we.mipmap;break;case\"object\":ne.genMipmaps=!1,Ct=!0;break;default:}Ct&&!(\"min\"in we)&&(ne.minFilter=Kl)}}function al(ne,we){Me.texParameteri(we,Uf,ne.minFilter),Me.texParameteri(we,rf,ne.magFilter),Me.texParameteri(we,Oo,ne.wrapS),Me.texParameteri(we,qo,ne.wrapT),bt.ext_texture_filter_anisotropic&&Me.texParameteri(we,cs,ne.anisotropic),ne.genMipmaps&&(Me.hint(Cf,ne.mipmapHint),Me.generateMipmap(we))}var Vl=0,ss={},Vs=zt.maxTextureUnits,Ys=Array(Vs).map(function(){return null});function wa(ne){hi.call(this),this.mipmask=0,this.internalformat=Ma,this.id=Vl++,this.refCount=1,this.target=ne,this.texture=Me.createTexture(),this.unit=-1,this.bindCount=0,this.texInfo=new zo,Gr.profile&&(this.stats={size:0})}function ol(ne){Me.activeTexture(Fu),Me.bindTexture(ne.target,ne.texture)}function io(){var ne=Ys[0];ne?Me.bindTexture(ne.target,ne.texture):Me.bindTexture(_n,null)}function Y(ne){var we=ne.texture,Ue=ne.unit,ft=ne.target;Ue>=0&&(Me.activeTexture(Fu+Ue),Me.bindTexture(ft,null),Ys[Ue]=null),Me.deleteTexture(we),ne.texture=null,ne.params=null,ne.pixels=null,ne.refCount=0,delete ss[ne.id],Nr.textureCount--}e(wa.prototype,{bind:function(){var ne=this;ne.bindCount+=1;var we=ne.unit;if(we<0){for(var Ue=0;Ue<Vs;++Ue){var ft=Ys[Ue];if(ft){if(ft.bindCount>0)continue;ft.unit=-1}Ys[Ue]=ne,we=Ue;break}we>=Vs,Gr.profile&&Nr.maxTextureUnits<we+1&&(Nr.maxTextureUnits=we+1),ne.unit=we,Me.activeTexture(Fu+we),Me.bindTexture(ne.target,ne.texture)}return we},unbind:function(){this.bindCount-=1},decRef:function(){--this.refCount<=0&&Y(this)}});function D(ne,we){var Ue=new wa(_n);ss[Ue.id]=Ue,Nr.textureCount++;function ft(qt,Ve){var Qe=Ue.texInfo;zo.call(Qe);var at=Va();return typeof qt==\"number\"?typeof Ve==\"number\"?oa(at,qt|0,Ve|0):oa(at,qt|0,qt|0):qt?(Qs(Qe,qt),ba(at,qt)):oa(at,1,1),Qe.genMipmaps&&(at.mipmask=(at.width<<1)-1),Ue.mipmask=at.mipmask,li(Ue,at),Ue.internalformat=at.internalformat,ft.width=at.width,ft.height=at.height,ol(Ue),is(at,_n),al(Qe,_n),io(),Ml(at),Gr.profile&&(Ue.stats.size=cc(Ue.internalformat,Ue.type,at.width,at.height,Qe.genMipmaps,!1)),ft.format=xi[Ue.internalformat],ft.type=Ri[Ue.type],ft.mag=ci[Qe.magFilter],ft.min=an[Qe.minFilter],ft.wrapS=Zi[Qe.wrapS],ft.wrapT=Zi[Qe.wrapT],ft}function Xt(qt,Ve,Qe,at){var Ct=Ve|0,Ot=Qe|0,Rt=at|0,Bt=Ki();return li(Bt,Ue),Bt.width=0,Bt.height=0,Ni(Bt,qt),Bt.width=Bt.width||(Ue.width>>Rt)-Ct,Bt.height=Bt.height||(Ue.height>>Rt)-Ot,ol(Ue),Vn(Bt,_n,Ct,Ot,Rt),io(),kn(Bt),ft}function hr(qt,Ve){var Qe=qt|0,at=Ve|0||Qe;if(Qe===Ue.width&&at===Ue.height)return ft;ft.width=Ue.width=Qe,ft.height=Ue.height=at,ol(Ue);for(var Ct=0;Ue.mipmask>>Ct;++Ct){var Ot=Qe>>Ct,Rt=at>>Ct;if(!Ot||!Rt)break;Me.texImage2D(_n,Ct,Ue.format,Ot,Rt,0,Ue.format,Ue.type,null)}return io(),Gr.profile&&(Ue.stats.size=cc(Ue.internalformat,Ue.type,Qe,at,!1,!1)),ft}return ft(ne,we),ft.subimage=Xt,ft.resize=hr,ft._reglType=\"texture2d\",ft._texture=Ue,Gr.profile&&(ft.stats=Ue.stats),ft.destroy=function(){Ue.decRef()},ft}function J(ne,we,Ue,ft,Xt,hr){var qt=new wa(ya);ss[qt.id]=qt,Nr.cubeCount++;var Ve=new Array(6);function Qe(Ot,Rt,Bt,Dt,yt,Pt){var ht,ur=qt.texInfo;for(zo.call(ur),ht=0;ht<6;++ht)Ve[ht]=Va();if(typeof Ot==\"number\"||!Ot){var br=Ot|0||1;for(ht=0;ht<6;++ht)oa(Ve[ht],br,br)}else if(typeof Ot==\"object\")if(Rt)ba(Ve[0],Ot),ba(Ve[1],Rt),ba(Ve[2],Bt),ba(Ve[3],Dt),ba(Ve[4],yt),ba(Ve[5],Pt);else if(Qs(ur,Ot),mn(qt,Ot),\"faces\"in Ot){var Ur=Ot.faces;for(ht=0;ht<6;++ht)li(Ve[ht],qt),ba(Ve[ht],Ur[ht])}else for(ht=0;ht<6;++ht)ba(Ve[ht],Ot);for(li(qt,Ve[0]),ur.genMipmaps?qt.mipmask=(Ve[0].width<<1)-1:qt.mipmask=Ve[0].mipmask,qt.internalformat=Ve[0].internalformat,Qe.width=Ve[0].width,Qe.height=Ve[0].height,ol(qt),ht=0;ht<6;++ht)is(Ve[ht],Jn+ht);for(al(ur,ya),io(),Gr.profile&&(qt.stats.size=cc(qt.internalformat,qt.type,Qe.width,Qe.height,ur.genMipmaps,!0)),Qe.format=xi[qt.internalformat],Qe.type=Ri[qt.type],Qe.mag=ci[ur.magFilter],Qe.min=an[ur.minFilter],Qe.wrapS=Zi[ur.wrapS],Qe.wrapT=Zi[ur.wrapT],ht=0;ht<6;++ht)Ml(Ve[ht]);return Qe}function at(Ot,Rt,Bt,Dt,yt){var Pt=Bt|0,ht=Dt|0,ur=yt|0,br=Ki();return li(br,qt),br.width=0,br.height=0,Ni(br,Rt),br.width=br.width||(qt.width>>ur)-Pt,br.height=br.height||(qt.height>>ur)-ht,ol(qt),Vn(br,Jn+Ot,Pt,ht,ur),io(),kn(br),Qe}function Ct(Ot){var Rt=Ot|0;if(Rt!==qt.width){Qe.width=qt.width=Rt,Qe.height=qt.height=Rt,ol(qt);for(var Bt=0;Bt<6;++Bt)for(var Dt=0;qt.mipmask>>Dt;++Dt)Me.texImage2D(Jn+Bt,Dt,qt.format,Rt>>Dt,Rt>>Dt,0,qt.format,qt.type,null);return io(),Gr.profile&&(qt.stats.size=cc(qt.internalformat,qt.type,Qe.width,Qe.height,!1,!0)),Qe}}return Qe(ne,we,Ue,ft,Xt,hr),Qe.subimage=at,Qe.resize=Ct,Qe._reglType=\"textureCube\",Qe._texture=qt,Gr.profile&&(Qe.stats=qt.stats),Qe.destroy=function(){qt.decRef()},Qe}function q(){for(var ne=0;ne<Vs;++ne)Me.activeTexture(Fu+ne),Me.bindTexture(_n,null),Ys[ne]=null;dt(ss).forEach(Y),Nr.cubeCount=0,Nr.textureCount=0}Gr.profile&&(Nr.getTotalTextureSize=function(){var ne=0;return Object.keys(ss).forEach(function(we){ne+=ss[we].stats.size}),ne});function K(){for(var ne=0;ne<Vs;++ne){var we=Ys[ne];we&&(we.bindCount=0,we.unit=-1,Ys[ne]=null)}dt(ss).forEach(function(Ue){Ue.texture=Me.createTexture(),Me.bindTexture(Ue.target,Ue.texture);for(var ft=0;ft<32;++ft)if((Ue.mipmask&1<<ft)!==0)if(Ue.target===_n)Me.texImage2D(_n,ft,Ue.internalformat,Ue.width>>ft,Ue.height>>ft,0,Ue.internalformat,Ue.type,null);else for(var Xt=0;Xt<6;++Xt)Me.texImage2D(Jn+Xt,ft,Ue.internalformat,Ue.width>>ft,Ue.height>>ft,0,Ue.internalformat,Ue.type,null);al(Ue.texInfo,Ue.target)})}function de(){for(var ne=0;ne<Vs;++ne){var we=Ys[ne];we&&(we.bindCount=0,we.unit=-1,Ys[ne]=null),Me.activeTexture(Fu+ne),Me.bindTexture(_n,null),Me.bindTexture(ya,null)}}return{create2D:D,createCube:J,clear:q,getTexture:function(ne){return null},restore:K,refresh:de}}var Nl=36161,Kc=32854,Rc=32855,gs=36194,jf=33189,Gh=36168,rh=34041,sf=35907,Th=34836,Mu=34842,ih=34843,js=[];js[Kc]=2,js[Rc]=2,js[gs]=2,js[jf]=2,js[Gh]=1,js[rh]=4,js[sf]=4,js[Th]=16,js[Mu]=8,js[ih]=6;function Eu(Me,bt,zt){return js[Me]*bt*zt}var Dc=function(Me,bt,zt,Rr,jr){var Nr={rgba4:Kc,rgb565:gs,\"rgb5 a1\":Rc,depth:jf,stencil:Gh,\"depth stencil\":rh};bt.ext_srgb&&(Nr.srgba=sf),bt.ext_color_buffer_half_float&&(Nr.rgba16f=Mu,Nr.rgb16f=ih),bt.webgl_color_buffer_float&&(Nr.rgba32f=Th);var Gr=[];Object.keys(Nr).forEach(function(Wi){var si=Nr[Wi];Gr[si]=Wi});var mi=0,Ui={};function qi(Wi){this.id=mi++,this.refCount=1,this.renderbuffer=Wi,this.format=Kc,this.width=0,this.height=0,jr.profile&&(this.stats={size:0})}qi.prototype.decRef=function(){--this.refCount<=0&&Ei(this)};function Ei(Wi){var si=Wi.renderbuffer;Me.bindRenderbuffer(Nl,null),Me.deleteRenderbuffer(si),Wi.renderbuffer=null,Wi.refCount=0,delete Ui[Wi.id],Rr.renderbufferCount--}function Hn(Wi,si){var Mr=new qi(Me.createRenderbuffer());Ui[Mr.id]=Mr,Rr.renderbufferCount++;function Yr(Ri,ci){var an=0,Zi=0,Bn=Kc;if(typeof Ri==\"object\"&&Ri){var hi=Ri;if(\"shape\"in hi){var li=hi.shape;an=li[0]|0,Zi=li[1]|0}else\"radius\"in hi&&(an=Zi=hi.radius|0),\"width\"in hi&&(an=hi.width|0),\"height\"in hi&&(Zi=hi.height|0);\"format\"in hi&&(Bn=Nr[hi.format])}else typeof Ri==\"number\"?(an=Ri|0,typeof ci==\"number\"?Zi=ci|0:Zi=an):Ri||(an=Zi=1);if(!(an===Mr.width&&Zi===Mr.height&&Bn===Mr.format))return Yr.width=Mr.width=an,Yr.height=Mr.height=Zi,Mr.format=Bn,Me.bindRenderbuffer(Nl,Mr.renderbuffer),Me.renderbufferStorage(Nl,Bn,an,Zi),jr.profile&&(Mr.stats.size=Eu(Mr.format,Mr.width,Mr.height)),Yr.format=Gr[Mr.format],Yr}function xi(Ri,ci){var an=Ri|0,Zi=ci|0||an;return an===Mr.width&&Zi===Mr.height||(Yr.width=Mr.width=an,Yr.height=Mr.height=Zi,Me.bindRenderbuffer(Nl,Mr.renderbuffer),Me.renderbufferStorage(Nl,Mr.format,an,Zi),jr.profile&&(Mr.stats.size=Eu(Mr.format,Mr.width,Mr.height))),Yr}return Yr(Wi,si),Yr.resize=xi,Yr._reglType=\"renderbuffer\",Yr._renderbuffer=Mr,jr.profile&&(Yr.stats=Mr.stats),Yr.destroy=function(){Mr.decRef()},Yr}jr.profile&&(Rr.getTotalRenderbufferSize=function(){var Wi=0;return Object.keys(Ui).forEach(function(si){Wi+=Ui[si].stats.size}),Wi});function en(){dt(Ui).forEach(function(Wi){Wi.renderbuffer=Me.createRenderbuffer(),Me.bindRenderbuffer(Nl,Wi.renderbuffer),Me.renderbufferStorage(Nl,Wi.format,Wi.width,Wi.height)}),Me.bindRenderbuffer(Nl,null)}return{create:Hn,clear:function(){dt(Ui).forEach(Ei)},restore:en}},ks=36160,bc=36161,hu=3553,_u=34069,nl=36064,nh=36096,Ah=36128,zu=33306,Fc=36053,wc=36193,bd=5121,xf=5126,Pf=6407,Ou=6408,bf=[];bf[Ou]=4,bf[Pf]=3;var jl=[];jl[bd]=1,jl[xf]=4,jl[wc]=2;function lf(Me,bt,zt,Rr,jr,Nr){var Gr={cur:null,next:null,dirty:!1,setFBO:null},mi=[\"rgba\"],Ui=[\"rgba4\",\"rgb565\",\"rgb5 a1\"];bt.ext_srgb&&Ui.push(\"srgba\"),bt.ext_color_buffer_half_float&&Ui.push(\"rgba16f\",\"rgb16f\"),bt.webgl_color_buffer_float&&Ui.push(\"rgba32f\");var qi=[\"uint8\"];bt.oes_texture_half_float&&qi.push(\"half float\",\"float16\"),bt.oes_texture_float&&qi.push(\"float\",\"float32\");function Ei(Vi,Ni,pn){this.target=Vi,this.texture=Ni,this.renderbuffer=pn;var 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kn=jr.create({width:Vi,height:Ni,format:Vn});return kn._renderbuffer.refCount=0,new Ei(bc,null,kn)}}function Yr(Vi){return Vi&&(Vi.texture||Vi.renderbuffer)}function xi(Vi,Ni,pn){Vi&&(Vi.texture?Vi.texture.resize(Ni,pn):Vi.renderbuffer&&Vi.renderbuffer.resize(Ni,pn),Vi.width=Ni,Vi.height=pn)}var Ri=0,ci={};function an(){this.id=Ri++,ci[this.id]=this,this.framebuffer=Me.createFramebuffer(),this.width=0,this.height=0,this.colorAttachments=[],this.depthAttachment=null,this.stencilAttachment=null,this.depthStencilAttachment=null}function Zi(Vi){Vi.colorAttachments.forEach(Hn),Hn(Vi.depthAttachment),Hn(Vi.stencilAttachment),Hn(Vi.depthStencilAttachment)}function Bn(Vi){var Ni=Vi.framebuffer;Me.deleteFramebuffer(Ni),Vi.framebuffer=null,Nr.framebufferCount--,delete ci[Vi.id]}function hi(Vi){var Ni;Me.bindFramebuffer(ks,Vi.framebuffer);var 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xi(pn.depthAttachment,ta,oa),xi(pn.stencilAttachment,ta,oa),xi(pn.depthStencilAttachment,ta,oa),pn.width=Vn.width=ta,pn.height=Vn.height=oa,hi(pn),Vn}return Vn(Vi,Ni),e(Vn,{resize:na,_reglType:\"framebuffer\",_framebuffer:pn,destroy:function(){Bn(pn),Zi(pn)},use:function(Ki){Gr.setFBO({framebuffer:Vn},Ki)}})}function mn(Vi){var Ni=Array(6);function pn(na){var Ki,kn={color:null},ta=0,oa=null,ba=\"rgba\",is=\"uint8\",Zs=1;if(typeof na==\"number\")ta=na|0;else if(!na)ta=1;else{var Va=na;if(\"shape\"in Va){var Ml=Va.shape;ta=Ml[0]}else\"radius\"in Va&&(ta=Va.radius|0),\"width\"in Va?(ta=Va.width|0,\"height\"in Va):\"height\"in Va&&(ta=Va.height|0);(\"color\"in Va||\"colors\"in Va)&&(oa=Va.color||Va.colors,Array.isArray(oa)),oa||(\"colorCount\"in Va&&(Zs=Va.colorCount|0),\"colorType\"in Va&&(is=Va.colorType),\"colorFormat\"in Va&&(ba=Va.colorFormat)),\"depth\"in Va&&(kn.depth=Va.depth),\"stencil\"in Va&&(kn.stencil=Va.stencil),\"depthStencil\"in Va&&(kn.depthStencil=Va.depthStencil)}var zo;if(oa)if(Array.isArray(oa))for(zo=[],Ki=0;Ki<oa.length;++Ki)zo[Ki]=oa[Ki];else zo=[oa];else{zo=Array(Zs);var Qs={radius:ta,format:ba,type:is};for(Ki=0;Ki<Zs;++Ki)zo[Ki]=Rr.createCube(Qs)}for(kn.color=Array(zo.length),Ki=0;Ki<zo.length;++Ki){var al=zo[Ki];ta=ta||al.width,kn.color[Ki]={target:_u,data:zo[Ki]}}for(Ki=0;Ki<6;++Ki){for(var Vl=0;Vl<zo.length;++Vl)kn.color[Vl].target=_u+Ki;Ki>0&&(kn.depth=Ni[0].depth,kn.stencil=Ni[0].stencil,kn.depthStencil=Ni[0].depthStencil),Ni[Ki]?Ni[Ki](kn):Ni[Ki]=li(kn)}return e(pn,{width:ta,height:ta,color:zo})}function Vn(na){var Ki,kn=na|0;if(kn===pn.width)return pn;var ta=pn.color;for(Ki=0;Ki<ta.length;++Ki)ta[Ki].resize(kn);for(Ki=0;Ki<6;++Ki)Ni[Ki].resize(kn);return pn.width=pn.height=kn,pn}return pn(Vi),e(pn,{faces:Ni,resize:Vn,_reglType:\"framebufferCube\",destroy:function(){Ni.forEach(function(na){na.destroy()})}})}function Ji(){Gr.cur=null,Gr.next=null,Gr.dirty=!0,dt(ci).forEach(function(Vi){Vi.framebuffer=Me.createFramebuffer(),hi(Vi)})}return e(Gr,{getFramebuffer:function(Vi){if(typeof Vi==\"function\"&&Vi._reglType===\"framebuffer\"){var Ni=Vi._framebuffer;if(Ni instanceof an)return Ni}return null},create:li,createCube:mn,clear:function(){dt(ci).forEach(Bn)},restore:Ji})}var Hh=5126,If=34962,Cs=34963;function du(){this.state=0,this.x=0,this.y=0,this.z=0,this.w=0,this.buffer=null,this.size=0,this.normalized=!1,this.type=Hh,this.offset=0,this.stride=0,this.divisor=0}function ku(Me,bt,zt,Rr,jr,Nr,Gr){for(var mi=zt.maxAttributes,Ui=new Array(mi),qi=0;qi<mi;++qi)Ui[qi]=new du;var Ei=0,Hn={},en={Record:du,scope:{},state:Ui,currentVAO:null,targetVAO:null,restore:si()?Zi:function(){},createVAO:Bn,getVAO:Yr,destroyBuffer:Wi,setVAO:si()?xi:Ri,clear:si()?ci:function(){}};function Wi(hi){for(var li=0;li<Ui.length;++li){var mn=Ui[li];mn.buffer===hi&&(Me.disableVertexAttribArray(li),mn.buffer=null)}}function si(){return bt.oes_vertex_array_object}function Mr(){return bt.angle_instanced_arrays}function Yr(hi){return typeof hi==\"function\"&&hi._vao?hi._vao:null}function xi(hi){if(hi!==en.currentVAO){var li=si();hi?li.bindVertexArrayOES(hi.vao):li.bindVertexArrayOES(null),en.currentVAO=hi}}function Ri(hi){if(hi!==en.currentVAO){if(hi)hi.bindAttrs();else{for(var li=Mr(),mn=0;mn<Ui.length;++mn){var Ji=Ui[mn];Ji.buffer?(Me.enableVertexAttribArray(mn),Ji.buffer.bind(),Me.vertexAttribPointer(mn,Ji.size,Ji.type,Ji.normalized,Ji.stride,Ji.offfset),li&&Ji.divisor&&li.vertexAttribDivisorANGLE(mn,Ji.divisor)):(Me.disableVertexAttribArray(mn),Me.vertexAttrib4f(mn,Ji.x,Ji.y,Ji.z,Ji.w))}Gr.elements?Me.bindBuffer(Cs,Gr.elements.buffer.buffer):Me.bindBuffer(Cs,null)}en.currentVAO=hi}}function ci(){dt(Hn).forEach(function(hi){hi.destroy()})}function an(){this.id=++Ei,this.attributes=[],this.elements=null,this.ownsElements=!1,this.count=0,this.offset=0,this.instances=-1,this.primitive=4;var hi=si();hi?this.vao=hi.createVertexArrayOES():this.vao=null,Hn[this.id]=this,this.buffers=[]}an.prototype.bindAttrs=function(){for(var hi=Mr(),li=this.attributes,mn=0;mn<li.length;++mn){var Ji=li[mn];Ji.buffer?(Me.enableVertexAttribArray(mn),Me.bindBuffer(If,Ji.buffer.buffer),Me.vertexAttribPointer(mn,Ji.size,Ji.type,Ji.normalized,Ji.stride,Ji.offset),hi&&Ji.divisor&&hi.vertexAttribDivisorANGLE(mn,Ji.divisor)):(Me.disableVertexAttribArray(mn),Me.vertexAttrib4f(mn,Ji.x,Ji.y,Ji.z,Ji.w))}for(var Vi=li.length;Vi<mi;++Vi)Me.disableVertexAttribArray(Vi);var Ni=Nr.getElements(this.elements);Ni?Me.bindBuffer(Cs,Ni.buffer.buffer):Me.bindBuffer(Cs,null)},an.prototype.refresh=function(){var hi=si();hi&&(hi.bindVertexArrayOES(this.vao),this.bindAttrs(),en.currentVAO=null,hi.bindVertexArrayOES(null))},an.prototype.destroy=function(){if(this.vao){var hi=si();this===en.currentVAO&&(en.currentVAO=null,hi.bindVertexArrayOES(null)),hi.deleteVertexArrayOES(this.vao),this.vao=null}this.ownsElements&&(this.elements.destroy(),this.elements=null,this.ownsElements=!1),Hn[this.id]&&(delete Hn[this.id],Rr.vaoCount-=1)};function Zi(){var hi=si();hi&&dt(Hn).forEach(function(li){li.refresh()})}function Bn(hi){var li=new an;Rr.vaoCount+=1;function mn(Ji){var Vi;if(Array.isArray(Ji))Vi=Ji,li.elements&&li.ownsElements&&li.elements.destroy(),li.elements=null,li.ownsElements=!1,li.offset=0,li.count=0,li.instances=-1,li.primitive=4;else{if(Ji.elements){var Ni=Ji.elements;li.ownsElements?typeof Ni==\"function\"&&Ni._reglType===\"elements\"?(li.elements.destroy(),li.ownsElements=!1):(li.elements(Ni),li.ownsElements=!1):Nr.getElements(Ji.elements)?(li.elements=Ji.elements,li.ownsElements=!1):(li.elements=Nr.create(Ji.elements),li.ownsElements=!0)}else li.elements=null,li.ownsElements=!1;Vi=Ji.attributes,li.offset=0,li.count=-1,li.instances=-1,li.primitive=4,li.elements&&(li.count=li.elements._elements.vertCount,li.primitive=li.elements._elements.primType),\"offset\"in Ji&&(li.offset=Ji.offset|0),\"count\"in Ji&&(li.count=Ji.count|0),\"instances\"in Ji&&(li.instances=Ji.instances|0),\"primitive\"in Ji&&(li.primitive=Sn[Ji.primitive])}var pn={},Vn=li.attributes;Vn.length=Vi.length;for(var na=0;na<Vi.length;++na){var Ki=Vi[na],kn=Vn[na]=new du,ta=Ki.data||Ki;if(Array.isArray(ta)||Br(ta)||Vr(ta)){var oa;li.buffers[na]&&(oa=li.buffers[na],Br(ta)&&oa._buffer.byteLength>=ta.byteLength?oa.subdata(ta):(oa.destroy(),li.buffers[na]=null)),li.buffers[na]||(oa=li.buffers[na]=jr.create(Ki,If,!1,!0)),kn.buffer=jr.getBuffer(oa),kn.size=kn.buffer.dimension|0,kn.normalized=!1,kn.type=kn.buffer.dtype,kn.offset=0,kn.stride=0,kn.divisor=0,kn.state=1,pn[na]=1}else jr.getBuffer(Ki)?(kn.buffer=jr.getBuffer(Ki),kn.size=kn.buffer.dimension|0,kn.normalized=!1,kn.type=kn.buffer.dtype,kn.offset=0,kn.stride=0,kn.divisor=0,kn.state=1):jr.getBuffer(Ki.buffer)?(kn.buffer=jr.getBuffer(Ki.buffer),kn.size=(+Ki.size||kn.buffer.dimension)|0,kn.normalized=!!Ki.normalized||!1,\"type\"in Ki?kn.type=ji[Ki.type]:kn.type=kn.buffer.dtype,kn.offset=(Ki.offset||0)|0,kn.stride=(Ki.stride||0)|0,kn.divisor=(Ki.divisor||0)|0,kn.state=1):\"x\"in Ki&&(kn.x=+Ki.x||0,kn.y=+Ki.y||0,kn.z=+Ki.z||0,kn.w=+Ki.w||0,kn.state=2)}for(var ba=0;ba<li.buffers.length;++ba)!pn[ba]&&li.buffers[ba]&&(li.buffers[ba].destroy(),li.buffers[ba]=null);return li.refresh(),mn}return mn.destroy=function(){for(var Ji=0;Ji<li.buffers.length;++Ji)li.buffers[Ji]&&li.buffers[Ji].destroy();li.buffers.length=0,li.ownsElements&&(li.elements.destroy(),li.elements=null,li.ownsElements=!1),li.destroy()},mn._vao=li,mn._reglType=\"vao\",mn(hi)}return en}var Wf=35632,Us=35633,wf=35718,zc=35721;function Wu(Me,bt,zt,Rr){var jr={},Nr={};function Gr(Mr,Yr,xi,Ri){this.name=Mr,this.id=Yr,this.location=xi,this.info=Ri}function mi(Mr,Yr){for(var xi=0;xi<Mr.length;++xi)if(Mr[xi].id===Yr.id){Mr[xi].location=Yr.location;return}Mr.push(Yr)}function Ui(Mr,Yr,xi){var Ri=Mr===Wf?jr:Nr,ci=Ri[Yr];if(!ci){var an=bt.str(Yr);ci=Me.createShader(Mr),Me.shaderSource(ci,an),Me.compileShader(ci),Ri[Yr]=ci}return ci}var qi={},Ei=[],Hn=0;function en(Mr,Yr){this.id=Hn++,this.fragId=Mr,this.vertId=Yr,this.program=null,this.uniforms=[],this.attributes=[],this.refCount=1,Rr.profile&&(this.stats={uniformsCount:0,attributesCount:0})}function Wi(Mr,Yr,xi){var Ri,ci,an=Ui(Wf,Mr.fragId),Zi=Ui(Us,Mr.vertId),Bn=Mr.program=Me.createProgram();if(Me.attachShader(Bn,an),Me.attachShader(Bn,Zi),xi)for(Ri=0;Ri<xi.length;++Ri){var hi=xi[Ri];Me.bindAttribLocation(Bn,hi[0],hi[1])}Me.linkProgram(Bn);var li=Me.getProgramParameter(Bn,wf);Rr.profile&&(Mr.stats.uniformsCount=li);var mn=Mr.uniforms;for(Ri=0;Ri<li;++Ri)if(ci=Me.getActiveUniform(Bn,Ri),ci)if(ci.size>1)for(var Ji=0;Ji<ci.size;++Ji){var Vi=ci.name.replace(\"[0]\",\"[\"+Ji+\"]\");mi(mn,new Gr(Vi,bt.id(Vi),Me.getUniformLocation(Bn,Vi),ci))}else mi(mn,new Gr(ci.name,bt.id(ci.name),Me.getUniformLocation(Bn,ci.name),ci));var Ni=Me.getProgramParameter(Bn,zc);Rr.profile&&(Mr.stats.attributesCount=Ni);var pn=Mr.attributes;for(Ri=0;Ri<Ni;++Ri)ci=Me.getActiveAttrib(Bn,Ri),ci&&mi(pn,new Gr(ci.name,bt.id(ci.name),Me.getAttribLocation(Bn,ci.name),ci))}Rr.profile&&(zt.getMaxUniformsCount=function(){var Mr=0;return Ei.forEach(function(Yr){Yr.stats.uniformsCount>Mr&&(Mr=Yr.stats.uniformsCount)}),Mr},zt.getMaxAttributesCount=function(){var Mr=0;return Ei.forEach(function(Yr){Yr.stats.attributesCount>Mr&&(Mr=Yr.stats.attributesCount)}),Mr});function si(){jr={},Nr={};for(var Mr=0;Mr<Ei.length;++Mr)Wi(Ei[Mr],null,Ei[Mr].attributes.map(function(Yr){return[Yr.location,Yr.name]}))}return{clear:function(){var Mr=Me.deleteShader.bind(Me);dt(jr).forEach(Mr),jr={},dt(Nr).forEach(Mr),Nr={},Ei.forEach(function(Yr){Me.deleteProgram(Yr.program)}),Ei.length=0,qi={},zt.shaderCount=0},program:function(Mr,Yr,xi,Ri){var ci=qi[Yr];ci||(ci=qi[Yr]={});var an=ci[Mr];if(an&&(an.refCount++,!Ri))return an;var Zi=new en(Yr,Mr);return zt.shaderCount++,Wi(Zi,xi,Ri),an||(ci[Mr]=Zi),Ei.push(Zi),e(Zi,{destroy:function(){if(Zi.refCount--,Zi.refCount<=0){Me.deleteProgram(Zi.program);var Bn=Ei.indexOf(Zi);Ei.splice(Bn,1),zt.shaderCount--}ci[Zi.vertId].refCount<=0&&(Me.deleteShader(Nr[Zi.vertId]),delete Nr[Zi.vertId],delete qi[Zi.fragId][Zi.vertId]),Object.keys(qi[Zi.fragId]).length||(Me.deleteShader(jr[Zi.fragId]),delete jr[Zi.fragId],delete qi[Zi.fragId])}})},restore:si,shader:Ui,frag:-1,vert:-1}}var Rf=6408,Xu=5121,uf=3333,Xf=5126;function Wl(Me,bt,zt,Rr,jr,Nr,Gr){function mi(Ei){var Hn;bt.next===null?Hn=Xu:Hn=bt.next.colorAttachments[0].texture._texture.type;var 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bt=ah?\"0123456789ABCDEF\":\"0123456789abcdef\",zt=\"\",Rr,jr=0;jr<Me.length;jr++)Rr=Me.charCodeAt(jr),zt+=bt.charAt(Rr>>>4&15)+bt.charAt(Rr&15);return zt}function qc(Me){for(var bt=\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/\",zt=\"\",Rr=Me.length,jr=0;jr<Rr;jr+=3)for(var Nr=Me.charCodeAt(jr)<<16|(jr+1<Rr?Me.charCodeAt(jr+1)<<8:0)|(jr+2<Rr?Me.charCodeAt(jr+2):0),Gr=0;Gr<4;Gr++)jr*8+Gr*6>Me.length*8?zt+=Zu:zt+=bt.charAt(Nr>>>6*(3-Gr)&63);return zt}function cf(Me,bt){var zt=bt.length,Rr=Array(),jr,Nr,Gr,mi,Ui=Array(Math.ceil(Me.length/2));for(jr=0;jr<Ui.length;jr++)Ui[jr]=Me.charCodeAt(jr*2)<<8|Me.charCodeAt(jr*2+1);for(;Ui.length>0;){for(mi=Array(),Gr=0,jr=0;jr<Ui.length;jr++)Gr=(Gr<<16)+Ui[jr],Nr=Math.floor(Gr/zt),Gr-=Nr*zt,(mi.length>0||Nr>0)&&(mi[mi.length]=Nr);Rr[Rr.length]=Gr,Ui=mi}var qi=\"\";for(jr=Rr.length-1;jr>=0;jr--)qi+=bt.charAt(Rr[jr]);var Ei=Math.ceil(Me.length*8/(Math.log(bt.length)/Math.log(2)));for(jr=qi.length;jr<Ei;jr++)qi=bt[0]+qi;return 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+       "`).replace(/{/g,`{\n",
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Ri=zt.angle_instanced_arrays,ci=zt.webgl_draw_buffers,an=zt.oes_vertex_array_object,Zi={dirty:!0,profile:Mr.profile},Bn={},hi=[],li={},mn={};function Ji(Ve){return Ve.replace(\".\",\"_\")}function Vi(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Bn[Ct]=Zi[Ct]=!!at,li[Ct]=Qe}function Ni(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Array.isArray(at)?(Zi[Ct]=at.slice(),Bn[Ct]=at.slice()):Zi[Ct]=Bn[Ct]=at,mn[Ct]=Qe}function pn(Ve){return!!isNaN(Ve)}Vi(ws,Pi),Vi(Ho,ni),Ni(ml,\"blendColor\",[0,0,0,0]),Ni(Ws,\"blendEquationSeparate\",[yr,yr]),Ni(Ls,\"blendFuncSeparate\",[gr,jt,gr,jt]),Vi(va,ln,!0),Ni(no,\"depthFunc\",Hr),Ni(ys,\"depthRange\",[0,1]),Ni(rs,\"depthMask\",!0),Ni($l,$l,[!0,!0,!0,!0]),Vi(Cu,Wr),Ni(Yu,\"cullFace\",se),Ni(Nc,Nc,Ne),Ni(pu,pu,1),Vi(Uc,Kn),Ni(xu,\"polygonOffset\",[0,0]),Vi(Ac,Ta),Vi(Ua,fa),Ni(oo,\"sampleCoverage\",[1,!1]),Vi(Vc,cn),Ni(hc,\"stencilMask\",-1),Ni(Ku,\"stencilFunc\",[kt,0,-1]),Ni(ue,\"stencilOpSeparate\",[X,nt,nt,nt]),Ni(w,\"stencilOpSeparate\",[se,nt,nt,nt]),Vi(B,Cn),Ni(Q,\"scissor\",[0,0,Me.drawingBufferWidth,Me.drawingBufferHeight]),Ni(ee,ee,[0,0,Me.drawingBufferWidth,Me.drawingBufferHeight]);var Vn={gl:Me,context:en,strings:bt,next:Bn,current:Zi,draw:Hn,elements:Nr,buffer:jr,shader:Ei,attributes:qi.state,vao:qi,uniforms:Ui,framebuffer:mi,extensions:zt,timer:Wi,isBufferArgs:Ii},na={primTypes:Sn,compareFuncs:Zr,blendFuncs:bi,blendEquations:xi,stencilOps:ai,glTypes:ji,orientationType:gi};ci&&(na.backBuffer=[se],na.drawBuffer=M(Rr.maxDrawbuffers,function(Ve){return Ve===0?[0]:M(Ve,function(Qe){return _i+Qe})}));var Ki=0;function kn(){var Ve=$n({cache:si}),Qe=Ve.link,at=Ve.global;Ve.id=Ki++,Ve.batchId=\"0\";var Ct=Qe(Vn),Ot=Ve.shared={props:\"a0\"};Object.keys(Vn).forEach(function(Pt){Ot[Pt]=at.def(Ct,\".\",Pt)});var Rt=Ve.next={},Bt=Ve.current={};Object.keys(mn).forEach(function(Pt){Array.isArray(Zi[Pt])&&(Rt[Pt]=at.def(Ot.next,\".\",Pt),Bt[Pt]=at.def(Ot.current,\".\",Pt))});var Dt=Ve.constants={};Object.keys(na).forEach(function(Pt){Dt[Pt]=at.def(JSON.stringify(na[Pt]))}),Ve.invoke=function(Pt,ht){switch(ht.type){case Yn:var ur=[\"this\",Ot.context,Ot.props,Ve.batchId];return Pt.def(Qe(ht.data),\".call(\",ur.slice(0,Math.max(ht.data.length+1,4)),\")\");case Dn:return Pt.def(Ot.props,ht.data);case Ka:return Pt.def(Ot.context,ht.data);case bo:return Pt.def(\"this\",ht.data);case Xo:return ht.data.append(Ve,Pt),ht.data.ref;case Ss:return ht.data.toString();case as:return ht.data.map(function(br){return Ve.invoke(Pt,br)})}},Ve.attribCache={};var yt={};return Ve.scopeAttrib=function(Pt){var ht=bt.id(Pt);if(ht in yt)return yt[ht];var ur=qi.scope[ht];ur||(ur=qi.scope[ht]=new Yr);var br=yt[ht]=Qe(ur);return br},Ve}function ta(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct;if(le in Qe){var Ot=!!Qe[le];Ct=En(function(Bt,Dt){return Ot}),Ct.enable=Ot}else if(le in at){var Rt=at[le];Ct=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}return Ct}function oa(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic;if(qe in at){var Ot=at[qe];return Ot?(Ot=mi.getFramebuffer(Ot),En(function(Bt,Dt){var yt=Bt.link(Ot),Pt=Bt.shared;Dt.set(Pt.framebuffer,\".next\",yt);var ht=Pt.context;return 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at[Xe]==\"string\";if(Ct){if(Object.keys(Qe.dynamic).length>0)return null;var Ot=Qe.static,Rt=Object.keys(Ot);if(Rt.length>0&&typeof Ot[Rt[0]]==\"number\"){for(var Bt=[],Dt=0;Dt<Rt.length;++Dt)Bt.push([Ot[Rt[Dt]]|0,Rt[Dt]]);return Bt}}return null}function Zs(Ve,Qe,at){var Ct=Ve.static,Ot=Ve.dynamic;function Rt(ht){if(ht in Ct){var ur=bt.id(Ct[ht]),br=En(function(){return ur});return br.id=ur,br}else if(ht in Ot){var Ur=Ot[ht];return Un(Ur,function(Di,fi){var Ti=Di.invoke(fi,Ur),gn=fi.def(Di.shared.strings,\".id(\",Ti,\")\");return gn})}return null}var Bt=Rt(ot),Dt=Rt(Xe),yt=null,Pt;return Ln(Bt)&&Ln(Dt)?(yt=Ei.program(Dt.id,Bt.id,null,at),Pt=En(function(ht,ur){return ht.link(yt)})):Pt=new ei(Bt&&Bt.thisDep||Dt&&Dt.thisDep,Bt&&Bt.contextDep||Dt&&Dt.contextDep,Bt&&Bt.propDep||Dt&&Dt.propDep,function(ht,ur){var br=ht.shared.shader,Ur;Bt?Ur=Bt.append(ht,ur):Ur=ur.def(br,\".\",ot);var Di;Dt?Di=Dt.append(ht,ur):Di=ur.def(br,\".\",Xe);var fi=br+\".program(\"+Di+\",\"+Ur;return ur.def(fi+\")\")}),{frag:Bt,vert:Dt,progVar:Pt,program:yt}}function Va(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={},Rt=!1;function Bt(){if(ve in at){var rn=at[ve];return rn!==null&&qi.getVAO(rn)===null&&(rn=qi.createVAO(rn)),Rt=!0,Ot.vao=rn,En(function(Bi){var Gi=qi.getVAO(rn);return Gi?Bi.link(Gi):\"null\"})}else if(ve in Ct){Rt=!0;var Ci=Ct[ve];return Un(Ci,function(Bi,Gi){var sn=Bi.invoke(Gi,Ci);return Gi.def(Bi.shared.vao+\".getVAO(\"+sn+\")\")})}return null}var Dt=Bt(),yt=!1;function Pt(){if(Tt in at){var rn=at[Tt];if(Ot.elements=rn,Ii(rn)){var Ci=Ot.elements=Nr.create(rn,!0);rn=Nr.getElements(Ci),yt=!0}else rn&&(rn=Nr.getElements(rn),yt=!0);var Bi=En(function(sn,zn){if(rn){var Ja=sn.link(rn);return sn.ELEMENTS=Ja,Ja}return sn.ELEMENTS=null,null});return Bi.value=rn,Bi}else if(Tt in Ct){yt=!0;var Gi=Ct[Tt];return Un(Gi,function(sn,zn){var Ja=sn.shared,co=Ja.isBufferArgs,ts=Ja.elements,so=sn.invoke(zn,Gi),Zo=zn.def(\"null\"),ms=zn.def(co,\"(\",so,\")\"),ou=sn.cond(ms).then(Zo,\"=\",ts,\".createStream(\",so,\");\").else(Zo,\"=\",ts,\".getElements(\",so,\");\");return zn.entry(ou),zn.exit(sn.cond(ms).then(ts,\".destroyStream(\",Zo,\");\")),sn.ELEMENTS=Zo,Zo})}else if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.elements+\".getElements(\"+sn.shared.vao+\".currentVAO.elements):null\")});return null}var ht=Pt();function ur(){if(Yt in at){var rn=at[Yt];return Ot.primitive=rn,En(function(Bi,Gi){return Sn[rn]})}else if(Yt in Ct){var Ci=Ct[Yt];return Un(Ci,function(Bi,Gi){var sn=Bi.constants.primTypes,zn=Bi.invoke(Gi,Ci);return Gi.def(sn,\"[\",zn,\"]\")})}else{if(yt)return Ln(ht)?ht.value?En(function(Bi,Gi){return Gi.def(Bi.ELEMENTS,\".primType\")}):En(function(){return Al}):new ei(ht.thisDep,ht.contextDep,ht.propDep,function(Bi,Gi){var sn=Bi.ELEMENTS;return Gi.def(sn,\"?\",sn,\".primType:\",Al)});if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(Bi,Gi){return Gi.def(Bi.shared.vao+\".currentVAO?\"+Bi.shared.vao+\".currentVAO.primitive:\"+Al)})}return null}function br(rn,Ci){if(rn in at){var Bi=at[rn]|0;return Ci?Ot.offset=Bi:Ot.instances=Bi,En(function(sn,zn){return Ci&&(sn.OFFSET=Bi),Bi})}else if(rn in Ct){var Gi=Ct[rn];return Un(Gi,function(sn,zn){var Ja=sn.invoke(zn,Gi);return Ci&&(sn.OFFSET=Ja),Ja})}else if(Ci){if(yt)return En(function(sn,zn){return sn.OFFSET=0,0});if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.vao+\".currentVAO.offset:0\")})}else if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.vao+\".currentVAO.instances:-1\")});return null}var Ur=br(xr,!0);function Di(){if(Kt in at){var rn=at[Kt]|0;return Ot.count=rn,En(function(){return rn})}else if(Kt in Ct){var Ci=Ct[Kt];return Un(Ci,function(zn,Ja){var co=zn.invoke(Ja,Ci);return co})}else if(yt)if(Ln(ht)){if(ht)return Ur?new ei(Ur.thisDep,Ur.contextDep,Ur.propDep,function(zn,Ja){var co=Ja.def(zn.ELEMENTS,\".vertCount-\",zn.OFFSET);return co}):En(function(zn,Ja){return Ja.def(zn.ELEMENTS,\".vertCount\")});var Bi=En(function(){return-1});return Bi}else{var Gi=new ei(ht.thisDep||Ur.thisDep,ht.contextDep||Ur.contextDep,ht.propDep||Ur.propDep,function(zn,Ja){var co=zn.ELEMENTS;return zn.OFFSET?Ja.def(co,\"?\",co,\".vertCount-\",zn.OFFSET,\":-1\"):Ja.def(co,\"?\",co,\".vertCount:-1\")});return Gi}else if(Rt){var sn=new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(zn,Ja){return Ja.def(zn.shared.vao,\".currentVAO?\",zn.shared.vao,\".currentVAO.count:-1\")});return sn}return null}var fi=ur(),Ti=Di(),gn=br(Ir,!1);return{elements:ht,primitive:fi,count:Ti,instances:gn,offset:Ur,vao:Dt,vaoActive:Rt,elementsActive:yt,static:Ot}}function Ml(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return hi.forEach(function(Rt){var Bt=Ji(Rt);function Dt(yt,Pt){if(Rt in at){var ht=yt(at[Rt]);Ot[Bt]=En(function(){return ht})}else if(Rt in Ct){var ur=Ct[Rt];Ot[Bt]=Un(ur,function(br,Ur){return Pt(br,Ur,br.invoke(Ur,ur))})}}switch(Rt){case Cu:case Ho:case ws:case Vc:case va:case B:case Uc:case Ac:case Ua:case rs:return Dt(function(yt){return yt},function(yt,Pt,ht){return ht});case no:return Dt(function(yt){return Zr[yt]},function(yt,Pt,ht){var ur=yt.constants.compareFuncs;return Pt.def(ur,\"[\",ht,\"]\")});case ys:return Dt(function(yt){return yt},function(yt,Pt,ht){var ur=Pt.def(\"+\",ht,\"[0]\"),br=Pt.def(\"+\",ht,\"[1]\");return[ur,br]});case Ls:return Dt(function(yt){var Pt=\"srcRGB\"in yt?yt.srcRGB:yt.src,ht=\"srcAlpha\"in yt?yt.srcAlpha:yt.src,ur=\"dstRGB\"in yt?yt.dstRGB:yt.dst,br=\"dstAlpha\"in yt?yt.dstAlpha:yt.dst;return[bi[Pt],bi[ur],bi[ht],bi[br]]},function(yt,Pt,ht){var ur=yt.constants.blendFuncs;function br(Ci,Bi){var Gi=Pt.def('\"',Ci,Bi,'\" in ',ht,\"?\",ht,\".\",Ci,Bi,\":\",ht,\".\",Ci);return Gi}var Ur=br(\"src\",\"RGB\"),Di=br(\"dst\",\"RGB\"),fi=Pt.def(ur,\"[\",Ur,\"]\"),Ti=Pt.def(ur,\"[\",br(\"src\",\"Alpha\"),\"]\"),gn=Pt.def(ur,\"[\",Di,\"]\"),rn=Pt.def(ur,\"[\",br(\"dst\",\"Alpha\"),\"]\");return[fi,gn,Ti,rn]});case Ws:return Dt(function(yt){if(typeof yt==\"string\")return[xi[yt],xi[yt]];if(typeof yt==\"object\")return[xi[yt.rgb],xi[yt.alpha]]},function(yt,Pt,ht){var ur=yt.constants.blendEquations,br=Pt.def(),Ur=Pt.def(),Di=yt.cond(\"typeof \",ht,'===\"string\"');return Di.then(br,\"=\",Ur,\"=\",ur,\"[\",ht,\"];\"),Di.else(br,\"=\",ur,\"[\",ht,\".rgb];\",Ur,\"=\",ur,\"[\",ht,\".alpha];\"),Pt(Di),[br,Ur]});case ml:return Dt(function(yt){return M(4,function(Pt){return+yt[Pt]})},function(yt,Pt,ht){return M(4,function(ur){return Pt.def(\"+\",ht,\"[\",ur,\"]\")})});case hc:return Dt(function(yt){return yt|0},function(yt,Pt,ht){return Pt.def(ht,\"|0\")});case Ku:return Dt(function(yt){var Pt=yt.cmp||\"keep\",ht=yt.ref||0,ur=\"mask\"in yt?yt.mask:-1;return[Zr[Pt],ht,ur]},function(yt,Pt,ht){var ur=yt.constants.compareFuncs,br=Pt.def('\"cmp\" in ',ht,\"?\",ur,\"[\",ht,\".cmp]\",\":\",nt),Ur=Pt.def(ht,\".ref|0\"),Di=Pt.def('\"mask\" in ',ht,\"?\",ht,\".mask|0:-1\");return[br,Ur,Di]});case ue:case w:return Dt(function(yt){var Pt=yt.fail||\"keep\",ht=yt.zfail||\"keep\",ur=yt.zpass||\"keep\";return[Rt===w?se:X,ai[Pt],ai[ht],ai[ur]]},function(yt,Pt,ht){var ur=yt.constants.stencilOps;function br(Ur){return Pt.def('\"',Ur,'\" in ',ht,\"?\",ur,\"[\",ht,\".\",Ur,\"]:\",nt)}return[Rt===w?se:X,br(\"fail\"),br(\"zfail\"),br(\"zpass\")]});case xu:return Dt(function(yt){var Pt=yt.factor|0,ht=yt.units|0;return[Pt,ht]},function(yt,Pt,ht){var ur=Pt.def(ht,\".factor|0\"),br=Pt.def(ht,\".units|0\");return[ur,br]});case Yu:return Dt(function(yt){var Pt=0;return yt===\"front\"?Pt=X:yt===\"back\"&&(Pt=se),Pt},function(yt,Pt,ht){return Pt.def(ht,'===\"front\"?',X,\":\",se)});case pu:return Dt(function(yt){return yt},function(yt,Pt,ht){return ht});case Nc:return Dt(function(yt){return gi[yt]},function(yt,Pt,ht){return Pt.def(ht+'===\"cw\"?'+Te+\":\"+Ne)});case $l:return Dt(function(yt){return yt.map(function(Pt){return!!Pt})},function(yt,Pt,ht){return M(4,function(ur){return\"!!\"+ht+\"[\"+ur+\"]\"})});case oo:return Dt(function(yt){var Pt=\"value\"in yt?yt.value:1,ht=!!yt.invert;return[Pt,ht]},function(yt,Pt,ht){var ur=Pt.def('\"value\" in ',ht,\"?+\",ht,\".value:1\"),br=Pt.def(\"!!\",ht,\".invert\");return[ur,br]})}}),Ot}function zo(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return Object.keys(at).forEach(function(Rt){var Bt=at[Rt],Dt;if(typeof Bt==\"number\"||typeof Bt==\"boolean\")Dt=En(function(){return Bt});else if(typeof Bt==\"function\"){var yt=Bt._reglType;yt===\"texture2d\"||yt===\"textureCube\"?Dt=En(function(Pt){return Pt.link(Bt)}):(yt===\"framebuffer\"||yt===\"framebufferCube\")&&(Dt=En(function(Pt){return Pt.link(Bt.color[0])}))}else Mn(Bt)&&(Dt=En(function(Pt){var ht=Pt.global.def(\"[\",M(Bt.length,function(ur){return Bt[ur]}),\"]\");return ht}));Dt.value=Bt,Ot[Rt]=Dt}),Object.keys(Ct).forEach(function(Rt){var Bt=Ct[Rt];Ot[Rt]=Un(Bt,function(Dt,yt){return Dt.invoke(yt,Bt)})}),Ot}function Qs(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return Object.keys(at).forEach(function(Rt){var Bt=at[Rt],Dt=bt.id(Rt),yt=new Yr;if(Ii(Bt))yt.state=La,yt.buffer=jr.getBuffer(jr.create(Bt,Sr,!1,!0)),yt.type=0;else{var Pt=jr.getBuffer(Bt);if(Pt)yt.state=La,yt.buffer=Pt,yt.type=0;else if(\"constant\"in Bt){var ht=Bt.constant;yt.buffer=\"null\",yt.state=Na,typeof ht==\"number\"?yt.x=ht:Ca.forEach(function(gn,rn){rn<ht.length&&(yt[gn]=ht[rn])})}else{Ii(Bt.buffer)?Pt=jr.getBuffer(jr.create(Bt.buffer,Sr,!1,!0)):Pt=jr.getBuffer(Bt.buffer);var ur=Bt.offset|0,br=Bt.stride|0,Ur=Bt.size|0,Di=!!Bt.normalized,fi=0;\"type\"in Bt&&(fi=ji[Bt.type]);var Ti=Bt.divisor|0;yt.buffer=Pt,yt.state=La,yt.size=Ur,yt.normalized=Di,yt.type=fi||Pt.dtype,yt.offset=ur,yt.stride=br,yt.divisor=Ti}}Ot[Rt]=En(function(gn,rn){var Ci=gn.attribCache;if(Dt in Ci)return Ci[Dt];var Bi={isStream:!1};return Object.keys(yt).forEach(function(Gi){Bi[Gi]=yt[Gi]}),yt.buffer&&(Bi.buffer=gn.link(yt.buffer),Bi.type=Bi.type||Bi.buffer+\".dtype\"),Ci[Dt]=Bi,Bi})}),Object.keys(Ct).forEach(function(Rt){var Bt=Ct[Rt];function Dt(yt,Pt){var ht=yt.invoke(Pt,Bt),ur=yt.shared,br=yt.constants,Ur=ur.isBufferArgs,Di=ur.buffer,fi={isStream:Pt.def(!1)},Ti=new Yr;Ti.state=La,Object.keys(Ti).forEach(function(Bi){fi[Bi]=Pt.def(\"\"+Ti[Bi])});var gn=fi.buffer,rn=fi.type;Pt(\"if(\",Ur,\"(\",ht,\")){\",fi.isStream,\"=true;\",gn,\"=\",Di,\".createStream(\",Sr,\",\",ht,\");\",rn,\"=\",gn,\".dtype;\",\"}else{\",gn,\"=\",Di,\".getBuffer(\",ht,\");\",\"if(\",gn,\"){\",rn,\"=\",gn,\".dtype;\",'}else if(\"constant\" in ',ht,\"){\",fi.state,\"=\",Na,\";\",\"if(typeof \"+ht+'.constant === \"number\"){',fi[Ca[0]],\"=\",ht,\".constant;\",Ca.slice(1).map(function(Bi){return fi[Bi]}).join(\"=\"),\"=0;\",\"}else{\",Ca.map(function(Bi,Gi){return fi[Bi]+\"=\"+ht+\".constant.length>\"+Gi+\"?\"+ht+\".constant[\"+Gi+\"]:0;\"}).join(\"\"),\"}}else{\",\"if(\",Ur,\"(\",ht,\".buffer)){\",gn,\"=\",Di,\".createStream(\",Sr,\",\",ht,\".buffer);\",\"}else{\",gn,\"=\",Di,\".getBuffer(\",ht,\".buffer);\",\"}\",rn,'=\"type\" in ',ht,\"?\",br.glTypes,\"[\",ht,\".type]:\",gn,\".dtype;\",fi.normalized,\"=!!\",ht,\".normalized;\");function Ci(Bi){Pt(fi[Bi],\"=\",ht,\".\",Bi,\"|0;\")}return Ci(\"size\"),Ci(\"offset\"),Ci(\"stride\"),Ci(\"divisor\"),Pt(\"}}\"),Pt.exit(\"if(\",fi.isStream,\"){\",Di,\".destroyStream(\",gn,\");\",\"}\"),fi}Ot[Rt]=Un(Bt,Dt)}),Ot}function al(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct={};return Object.keys(Qe).forEach(function(Ot){var Rt=Qe[Ot];Ct[Ot]=En(function(Bt,Dt){return typeof Rt==\"number\"||typeof Rt==\"boolean\"?\"\"+Rt:Bt.link(Rt)})}),Object.keys(at).forEach(function(Ot){var Rt=at[Ot];Ct[Ot]=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}),Ct}function Vl(Ve,Qe,at,Ct,Ot){var Rt=Ve.static,Bt=Ve.dynamic,Dt=is(Ve,Qe),yt=oa(Ve,Ot),Pt=ba(Ve,yt,Ot),ht=Va(Ve,Ot),ur=Ml(Ve,Ot),br=Zs(Ve,Ot,Dt);function Ur(Ci){var Bi=Pt[Ci];Bi&&(ur[Ci]=Bi)}Ur(ee),Ur(Ji(Q));var Di=Object.keys(ur).length>0,fi={framebuffer:yt,draw:ht,shader:br,state:ur,dirty:Di,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(fi.profile=ta(Ve,Ot),fi.uniforms=zo(at,Ot),fi.drawVAO=fi.scopeVAO=ht.vao,!fi.drawVAO&&br.program&&!Dt&&zt.angle_instanced_arrays&&ht.static.elements){var Ti=!0,gn=br.program.attributes.map(function(Ci){var Bi=Qe.static[Ci];return Ti=Ti&&!!Bi,Bi});if(Ti&&gn.length>0){var rn=qi.getVAO(qi.createVAO({attributes:gn,elements:ht.static.elements}));fi.drawVAO=new ei(null,null,null,function(Ci,Bi){return Ci.link(rn)}),fi.useVAO=!0}}return Dt?fi.useVAO=!0:fi.attributes=Qs(Qe,Ot),fi.context=al(Ct,Ot),fi}function ss(Ve,Qe,at){var Ct=Ve.shared,Ot=Ct.context,Rt=Ve.scope();Object.keys(at).forEach(function(Bt){Qe.save(Ot,\".\"+Bt);var Dt=at[Bt],yt=Dt.append(Ve,Qe);Array.isArray(yt)?Rt(Ot,\".\",Bt,\"=[\",yt.join(),\"];\"):Rt(Ot,\".\",Bt,\"=\",yt,\";\")}),Qe(Rt)}function Vs(Ve,Qe,at,Ct){var Ot=Ve.shared,Rt=Ot.gl,Bt=Ot.framebuffer,Dt;ci&&(Dt=Qe.def(Ot.extensions,\".webgl_draw_buffers\"));var yt=Ve.constants,Pt=yt.drawBuffer,ht=yt.backBuffer,ur;at?ur=at.append(Ve,Qe):ur=Qe.def(Bt,\".next\"),Ct||Qe(\"if(\",ur,\"!==\",Bt,\".cur){\"),Qe(\"if(\",ur,\"){\",Rt,\".bindFramebuffer(\",qr,\",\",ur,\".framebuffer);\"),ci&&Qe(Dt,\".drawBuffersWEBGL(\",Pt,\"[\",ur,\".colorAttachments.length]);\"),Qe(\"}else{\",Rt,\".bindFramebuffer(\",qr,\",null);\"),ci&&Qe(Dt,\".drawBuffersWEBGL(\",ht,\");\"),Qe(\"}\",Bt,\".cur=\",ur,\";\"),Ct||Qe(\"}\")}function Ys(Ve,Qe,at){var Ct=Ve.shared,Ot=Ct.gl,Rt=Ve.current,Bt=Ve.next,Dt=Ct.current,yt=Ct.next,Pt=Ve.cond(Dt,\".dirty\");hi.forEach(function(ht){var ur=Ji(ht);if(!(ur in at.state)){var br,Ur;if(ur in Bt){br=Bt[ur],Ur=Rt[ur];var Di=M(Zi[ur].length,function(Ti){return Pt.def(br,\"[\",Ti,\"]\")});Pt(Ve.cond(Di.map(function(Ti,gn){return Ti+\"!==\"+Ur+\"[\"+gn+\"]\"}).join(\"||\")).then(Ot,\".\",mn[ur],\"(\",Di,\");\",Di.map(function(Ti,gn){return Ur+\"[\"+gn+\"]=\"+Ti}).join(\";\"),\";\"))}else{br=Pt.def(yt,\".\",ur);var fi=Ve.cond(br,\"!==\",Dt,\".\",ur);Pt(fi),ur in li?fi(Ve.cond(br).then(Ot,\".enable(\",li[ur],\");\").else(Ot,\".disable(\",li[ur],\");\"),Dt,\".\",ur,\"=\",br,\";\"):fi(Ot,\".\",mn[ur],\"(\",br,\");\",Dt,\".\",ur,\"=\",br,\";\")}}}),Object.keys(at.state).length===0&&Pt(Dt,\".dirty=false;\"),Qe(Pt)}function wa(Ve,Qe,at,Ct){var Ot=Ve.shared,Rt=Ve.current,Bt=Ot.current,Dt=Ot.gl,yt;Si(Object.keys(at)).forEach(function(Pt){var ht=at[Pt];if(!(Ct&&!Ct(ht))){var ur=ht.append(Ve,Qe);if(li[Pt]){var br=li[Pt];Ln(ht)?(yt=Ve.link(ur,{stable:!0}),Qe(Ve.cond(yt).then(Dt,\".enable(\",br,\");\").else(Dt,\".disable(\",br,\");\")),Qe(Bt,\".\",Pt,\"=\",yt,\";\")):(Qe(Ve.cond(ur).then(Dt,\".enable(\",br,\");\").else(Dt,\".disable(\",br,\");\")),Qe(Bt,\".\",Pt,\"=\",ur,\";\"))}else if(Mn(ur)){var Ur=Rt[Pt];Qe(Dt,\".\",mn[Pt],\"(\",ur,\");\",ur.map(function(Di,fi){return Ur+\"[\"+fi+\"]=\"+Di}).join(\";\"),\";\")}else Ln(ht)?(yt=Ve.link(ur,{stable:!0}),Qe(Dt,\".\",mn[Pt],\"(\",yt,\");\",Bt,\".\",Pt,\"=\",yt,\";\")):Qe(Dt,\".\",mn[Pt],\"(\",ur,\");\",Bt,\".\",Pt,\"=\",ur,\";\")}})}function ol(Ve,Qe){Ri&&(Ve.instancing=Qe.def(Ve.shared.extensions,\".angle_instanced_arrays\"))}function io(Ve,Qe,at,Ct,Ot){var Rt=Ve.shared,Bt=Ve.stats,Dt=Rt.current,yt=Rt.timer,Pt=at.profile;function ht(){return typeof performance==\"undefined\"?\"Date.now()\":\"performance.now()\"}var ur,br;function Ur(Ci){ur=Qe.def(),Ci(ur,\"=\",ht(),\";\"),typeof Ot==\"string\"?Ci(Bt,\".count+=\",Ot,\";\"):Ci(Bt,\".count++;\"),Wi&&(Ct?(br=Qe.def(),Ci(br,\"=\",yt,\".getNumPendingQueries();\")):Ci(yt,\".beginQuery(\",Bt,\");\"))}function Di(Ci){Ci(Bt,\".cpuTime+=\",ht(),\"-\",ur,\";\"),Wi&&(Ct?Ci(yt,\".pushScopeStats(\",br,\",\",yt,\".getNumPendingQueries(),\",Bt,\");\"):Ci(yt,\".endQuery();\"))}function fi(Ci){var Bi=Qe.def(Dt,\".profile\");Qe(Dt,\".profile=\",Ci,\";\"),Qe.exit(Dt,\".profile=\",Bi,\";\")}var Ti;if(Pt){if(Ln(Pt)){Pt.enable?(Ur(Qe),Di(Qe.exit),fi(\"true\")):fi(\"false\");return}Ti=Pt.append(Ve,Qe),fi(Ti)}else Ti=Qe.def(Dt,\".profile\");var gn=Ve.block();Ur(gn),Qe(\"if(\",Ti,\"){\",gn,\"}\");var rn=Ve.block();Di(rn),Qe.exit(\"if(\",Ti,\"){\",rn,\"}\")}function Y(Ve,Qe,at,Ct,Ot){var Rt=Ve.shared;function Bt(yt){switch(yt){case Co:case Ps:case hl:return 2;case Qa:case Ts:case Ul:return 3;case mo:case wo:case Lu:return 4;default:return 1}}function Dt(yt,Pt,ht){var ur=Rt.gl,br=Qe.def(yt,\".location\"),Ur=Qe.def(Rt.attributes,\"[\",br,\"]\"),Di=ht.state,fi=ht.buffer,Ti=[ht.x,ht.y,ht.z,ht.w],gn=[\"buffer\",\"normalized\",\"offset\",\"stride\"];function rn(){Qe(\"if(!\",Ur,\".buffer){\",ur,\".enableVertexAttribArray(\",br,\");}\");var Bi=ht.type,Gi;if(ht.size?Gi=Qe.def(ht.size,\"||\",Pt):Gi=Pt,Qe(\"if(\",Ur,\".type!==\",Bi,\"||\",Ur,\".size!==\",Gi,\"||\",gn.map(function(zn){return Ur+\".\"+zn+\"!==\"+ht[zn]}).join(\"||\"),\"){\",ur,\".bindBuffer(\",Sr,\",\",fi,\".buffer);\",ur,\".vertexAttribPointer(\",[br,Gi,Bi,ht.normalized,ht.stride,ht.offset],\");\",Ur,\".type=\",Bi,\";\",Ur,\".size=\",Gi,\";\",gn.map(function(zn){return Ur+\".\"+zn+\"=\"+ht[zn]+\";\"}).join(\"\"),\"}\"),Ri){var sn=ht.divisor;Qe(\"if(\",Ur,\".divisor!==\",sn,\"){\",Ve.instancing,\".vertexAttribDivisorANGLE(\",[br,sn],\");\",Ur,\".divisor=\",sn,\";}\")}}function 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Ot=Ve.global,Rt=Object.keys(Ct),Bt=!1,Dt=!1,yt=!1,Pt=Ve.global.def(\"{}\");Rt.forEach(function(ur){var br=Ct[ur];if(h.isDynamic(br)){typeof br==\"function\"&&(br=Ct[ur]=h.unbox(br));var Ur=Un(br,null);Bt=Bt||Ur.thisDep,yt=yt||Ur.propDep,Dt=Dt||Ur.contextDep}else{switch(Ot(Pt,\".\",ur,\"=\"),typeof br){case\"number\":Ot(br);break;case\"string\":Ot('\"',br,'\"');break;case\"object\":Array.isArray(br)&&Ot(\"[\",br.join(),\"]\");break;default:Ot(Ve.link(br));break}Ot(\";\")}});function ht(ur,br){Rt.forEach(function(Ur){var Di=Ct[Ur];if(h.isDynamic(Di)){var fi=ur.invoke(br,Di);br(Pt,\".\",Ur,\"=\",fi,\";\")}})}Qe.dynamic[at]=new h.DynamicVariable(Xo,{thisDep:Bt,contextDep:Dt,propDep:yt,ref:Pt,append:ht}),delete Qe.static[at]}function qt(Ve,Qe,at,Ct,Ot){var Rt=kn();Rt.stats=Rt.link(Ot),Object.keys(Qe.static).forEach(function(Dt){hr(Rt,Qe,Dt)}),dr.forEach(function(Dt){hr(Rt,Ve,Dt)});var Bt=Vl(Ve,Qe,at,Ct,Rt);return Bt.shader.program&&(Bt.shader.program.attributes.sort(function(Dt,yt){return 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lBe(e){e=fx.nextPow2(e);var t=fx.log2(e),r=_z[t];return r.length>0?r.pop():new Yqe(e)}mu.mallocBuffer=lBe;mu.clearCache=function(){for(var t=0;t<32;++t)nd.UINT8[t].length=0,nd.UINT16[t].length=0,nd.UINT32[t].length=0,nd.INT8[t].length=0,nd.INT16[t].length=0,nd.INT32[t].length=0,nd.FLOAT[t].length=0,nd.DOUBLE[t].length=0,nd.BIGUINT64[t].length=0,nd.BIGINT64[t].length=0,nd.UINT8C[t].length=0,yz[t].length=0,_z[t].length=0}});var fBe=ye((s_r,cBe)=>{\"use strict\";var gUt=Object.prototype.toString;cBe.exports=function(e){var t;return gUt.call(e)===\"[object Object]\"&&(t=Object.getPrototypeOf(e),t===null||t===Object.getPrototypeOf({}))}});var aK=ye((l_r,hBe)=>{hBe.exports=function(t,r){r||(r=[0,\"\"]),t=String(t);var n=parseFloat(t,10);return r[0]=n,r[1]=t.match(/[\\d.\\-\\+]*\\s*(.*)/)[1]||\"\",r}});var pBe=ye((u_r,vBe)=>{\"use strict\";var mUt=aK();vBe.exports=dBe;var Ek=96;function oK(e,t){var r=mUt(getComputedStyle(e).getPropertyValue(t));return r[0]*dBe(r[1],e)}function yUt(e,t){var r=document.createElement(\"div\");r.style[\"font-size\"]=\"128\"+e,t.appendChild(r);var n=oK(r,\"font-size\")/128;return t.removeChild(r),n}function dBe(e,t){switch(t=t||document.body,e=(e||\"px\").trim().toLowerCase(),(t===window||t===document)&&(t=document.body),e){case\"%\":return t.clientHeight/100;case\"ch\":case\"ex\":return yUt(e,t);case\"em\":return oK(t,\"font-size\");case\"rem\":return oK(document.body,\"font-size\");case\"vw\":return window.innerWidth/100;case\"vh\":return window.innerHeight/100;case\"vmin\":return Math.min(window.innerWidth,window.innerHeight)/100;case\"vmax\":return Math.max(window.innerWidth,window.innerHeight)/100;case\"in\":return Ek;case\"cm\":return Ek/2.54;case\"mm\":return Ek/25.4;case\"pt\":return Ek/72;case\"pc\":return Ek/6}return 1}});var yBe=ye((c_r,mBe)=>{\"use strict\";mBe.exports=wz;var _Ut=wz.canvas=document.createElement(\"canvas\"),xz=_Ut.getContext(\"2d\"),gBe=bz([32,126]);wz.createPairs=bz;wz.ascii=gBe;function wz(e,t){Array.isArray(e)&&(e=e.join(\", \"));var r={},n,i=16,a=.05;t&&(t.length===2&&typeof t[0]==\"number\"?n=bz(t):Array.isArray(t)?n=t:(t.o?n=bz(t.o):t.pairs&&(n=t.pairs),t.fontSize&&(i=t.fontSize),t.threshold!=null&&(a=t.threshold))),n||(n=gBe),xz.font=i+\"px \"+e;for(var o=0;o<n.length;o++){var s=n[o],l=xz.measureText(s[0]).width+xz.measureText(s[1]).width,u=xz.measureText(s).width;if(Math.abs(l-u)>i*a){var c=(u-l)/i;r[s]=c*1e3}}return r}function bz(e){for(var t=[],r=e[0];r<=e[1];r++)for(var n=String.fromCharCode(r),i=e[0];i<e[1];i++){var a=String.fromCharCode(i),o=n+a;t.push(o)}return t}});var wBe=ye((f_r,bBe)=>{\"use strict\";bBe.exports=hx;hx.canvas=document.createElement(\"canvas\");hx.cache={};function hx(o,t){t||(t={}),(typeof o==\"string\"||Array.isArray(o))&&(t.family=o);var r=Array.isArray(t.family)?t.family.join(\", \"):t.family;if(!r)throw Error(\"`family` must be defined\");var n=t.size||t.fontSize||t.em||48,i=t.weight||t.fontWeight||\"\",a=t.style||t.fontStyle||\"\",o=[a,i,n].join(\" \")+\"px \"+r,s=t.origin||\"top\";if(hx.cache[r]&&n<=hx.cache[r].em)return _Be(hx.cache[r],s);var l=t.canvas||hx.canvas,u=l.getContext(\"2d\"),c={upper:t.upper!==void 0?t.upper:\"H\",lower:t.lower!==void 0?t.lower:\"x\",descent:t.descent!==void 0?t.descent:\"p\",ascent:t.ascent!==void 0?t.ascent:\"h\",tittle:t.tittle!==void 0?t.tittle:\"i\",overshoot:t.overshoot!==void 0?t.overshoot:\"O\"},f=Math.ceil(n*1.5);l.height=f,l.width=f*.5,u.font=o;var h=\"H\",d={top:0};u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillStyle=\"black\",u.fillText(h,0,0);var v=Km(u.getImageData(0,0,f,f));u.clearRect(0,0,f,f),u.textBaseline=\"bottom\",u.fillText(h,0,f);var _=Km(u.getImageData(0,0,f,f));d.lineHeight=d.bottom=f-_+v,u.clearRect(0,0,f,f),u.textBaseline=\"alphabetic\",u.fillText(h,0,f);var b=Km(u.getImageData(0,0,f,f)),p=f-b-1+v;d.baseline=d.alphabetic=p,u.clearRect(0,0,f,f),u.textBaseline=\"middle\",u.fillText(h,0,f*.5);var k=Km(u.getImageData(0,0,f,f));d.median=d.middle=f-k-1+v-f*.5,u.clearRect(0,0,f,f),u.textBaseline=\"hanging\",u.fillText(h,0,f*.5);var E=Km(u.getImageData(0,0,f,f));d.hanging=f-E-1+v-f*.5,u.clearRect(0,0,f,f),u.textBaseline=\"ideographic\",u.fillText(h,0,f);var S=Km(u.getImageData(0,0,f,f));if(d.ideographic=f-S-1+v,c.upper&&(u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.upper,0,0),d.upper=Km(u.getImageData(0,0,f,f)),d.capHeight=d.baseline-d.upper),c.lower&&(u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.lower,0,0),d.lower=Km(u.getImageData(0,0,f,f)),d.xHeight=d.baseline-d.lower),c.tittle&&(u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.tittle,0,0),d.tittle=Km(u.getImageData(0,0,f,f))),c.ascent&&(u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.ascent,0,0),d.ascent=Km(u.getImageData(0,0,f,f))),c.descent&&(u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.descent,0,0),d.descent=xBe(u.getImageData(0,0,f,f))),c.overshoot){u.clearRect(0,0,f,f),u.textBaseline=\"top\",u.fillText(c.overshoot,0,0);var L=xBe(u.getImageData(0,0,f,f));d.overshoot=L-p}for(var x in d)d[x]/=n;return d.em=n,hx.cache[r]=d,_Be(d,s)}function _Be(e,t){var r={};typeof t==\"string\"&&(t=e[t]);for(var n in e)n!==\"em\"&&(r[n]=e[n]-t);return r}function Km(e){for(var t=e.height,r=e.data,n=3;n<r.length;n+=4)if(r[n]!==0)return Math.floor((n-3)*.25/t)}function xBe(e){for(var t=e.height,r=e.data,n=r.length-1;n>0;n-=4)if(r[n]!==0)return Math.floor((n-3)*.25/t)}});var MBe=ye((h_r,SBe)=>{\"use strict\";var v5=zqe(),xUt=Zm(),bUt=Oqe(),wUt=Vqe(),TUt=BY(),sK=J_(),AUt=Hqe(),dx=uBe(),SUt=r5(),MUt=fBe(),EUt=aK(),kUt=pBe(),CUt=yBe(),LUt=Oh(),PUt=wBe(),IUt=X2(),RUt=iK(),TBe=RUt.nextPow2,ABe=new TUt,Az=!1;document.body&&(Tz=document.body.appendChild(document.createElement(\"div\")),Tz.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(Tz).fontStretch&&(Az=!0),document.body.removeChild(Tz));var Tz,xc=function(t){DUt(t)?(t={regl:t},this.gl=t.regl._gl):this.gl=wUt(t),this.shader=ABe.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||bUt({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),ABe.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(MUt(t)?t:{})};xc.prototype.createShader=function(){var t=this.regl,r=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(i,a){return[a.atlas.width,a.atlas.height]},atlasDim:function(i,a){return[a.atlas.cols,a.atlas.rows]},atlas:function(i,a){return a.atlas.texture},charStep:function(i,a){return a.atlas.step},em:function(i,a){return a.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:`\n",
+       "\t\t\tprecision highp float;\n",
+       "\t\t\tattribute float width, charOffset, char;\n",
+       "\t\t\tattribute vec2 position;\n",
+       "\t\t\tuniform float fontSize, charStep, em, align, baseline;\n",
+       "\t\t\tuniform vec4 viewport;\n",
+       "\t\t\tuniform vec4 color;\n",
+       "\t\t\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\n",
+       "\t\t\tvarying vec2 charCoord, charId;\n",
+       "\t\t\tvarying float charWidth;\n",
+       "\t\t\tvarying vec4 fontColor;\n",
+       "\t\t\tvoid main () {\n",
+       "\t\t\t\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\n",
+       "\t\t\t\t\t+ vec2(positionOffset.x, -positionOffset.y)))\n",
+       "\t\t\t\t\t/ (viewport.zw * scale.xy);\n",
+       "\n",
+       "\t\t\t\tvec2 position = (position + translate) * scale;\n",
+       "\t\t\t\tposition += offset * scale;\n",
+       "\n",
+       "\t\t\t\tcharCoord = position * viewport.zw + viewport.xy;\n",
+       "\n",
+       "\t\t\t\tgl_Position = vec4(position * 2. - 1., 0, 1);\n",
+       "\n",
+       "\t\t\t\tgl_PointSize = charStep;\n",
+       "\n",
+       "\t\t\t\tcharId.x = mod(char, atlasDim.x);\n",
+       "\t\t\t\tcharId.y = floor(char / atlasDim.x);\n",
+       "\n",
+       "\t\t\t\tcharWidth = width * em;\n",
+       "\n",
+       "\t\t\t\tfontColor = color / 255.;\n",
+       "\t\t\t}`,frag:`\n",
+       "\t\t\tprecision highp float;\n",
+       "\t\t\tuniform float fontSize, charStep, opacity;\n",
+       "\t\t\tuniform vec2 atlasSize;\n",
+       "\t\t\tuniform vec4 viewport;\n",
+       "\t\t\tuniform sampler2D atlas;\n",
+       "\t\t\tvarying vec4 fontColor;\n",
+       "\t\t\tvarying vec2 charCoord, charId;\n",
+       "\t\t\tvarying float charWidth;\n",
+       "\n",
+       "\t\t\tfloat lightness(vec4 color) {\n",
+       "\t\t\t\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\n",
+       "\t\t\t}\n",
+       "\n",
+       "\t\t\tvoid main () {\n",
+       "\t\t\t\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\n",
+       "\t\t\t\tfloat halfCharStep = floor(charStep * .5 + .5);\n",
+       "\n",
+       "\t\t\t\t// invert y and shift by 1px (FF expecially needs that)\n",
+       "\t\t\t\tuv.y = charStep - uv.y;\n",
+       "\n",
+       "\t\t\t\t// ignore points outside of character bounding box\n",
+       "\t\t\t\tfloat halfCharWidth = ceil(charWidth * .5);\n",
+       "\t\t\t\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\n",
+       "\t\t\t\t\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\n",
+       "\n",
+       "\t\t\t\tuv += charId * charStep;\n",
+       "\t\t\t\tuv = uv / atlasSize;\n",
+       "\n",
+       "\t\t\t\tvec4 color = fontColor;\n",
+       "\t\t\t\tvec4 mask = texture2D(atlas, uv);\n",
+       "\n",
+       "\t\t\t\tfloat maskY = lightness(mask);\n",
+       "\t\t\t\t// float colorY = lightness(color);\n",
+       "\t\t\t\tcolor.a *= maskY;\n",
+       "\t\t\t\tcolor.a *= opacity;\n",
+       "\n",
+       "\t\t\t\t// color.a += .1;\n",
+       "\n",
+       "\t\t\t\t// antialiasing, see yiq color space y-channel formula\n",
+       "\t\t\t\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\n",
+       "\n",
+       "\t\t\t\tgl_FragColor = color;\n",
+       "\t\t\t}`}),n={};return{regl:t,draw:r,atlas:n}};xc.prototype.update=function(t){var r=this;if(typeof t==\"string\")t={text:t};else if(!t)return;t=xUt(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0),t.opacity!=null&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map(function(Ce){return parseFloat(Ce)}):this.opacity=parseFloat(t.opacity)),t.viewport!=null&&(this.viewport=SUt(t.viewport),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),this.viewport==null&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),t.kerning!=null&&(this.kerning=t.kerning),t.offset!=null&&(typeof t.offset==\"number\"&&(t.offset=[t.offset,0]),this.positionOffset=IUt(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),!this.font.length&&!t.font&&(t.font=xc.baseFontSize+\"px sans-serif\");var n=!1,i=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach(function(Ce,me){if(typeof Ce==\"string\")try{Ce=v5.parse(Ce)}catch(Ze){Ce=v5.parse(xc.baseFontSize+\"px \"+Ce)}else{var ie=Ce.style,Se=Ce.weight,Le=Ce.stretch,Ae=Ce.variant;Ce=v5.parse(v5.stringify(Ce)),ie&&(Ce.style=ie),Se&&(Ce.weight=Se),Le&&(Ce.stretch=Le),Ae&&(Ce.variant=Ae)}var Fe=v5.stringify({size:xc.baseFontSize,family:Ce.family,stretch:Az?Ce.stretch:void 0,variant:Ce.variant,weight:Ce.weight,style:Ce.style}),Pe=EUt(Ce.size),ge=Math.round(Pe[0]*kUt(Pe[1]));if(ge!==r.fontSize[me]&&(i=!0,r.fontSize[me]=ge),(!r.font[me]||Fe!=r.font[me].baseString)&&(n=!0,r.font[me]=xc.fonts[Fe],!r.font[me])){var Re=Ce.family.join(\", \"),ce=[Ce.style];Ce.style!=Ce.variant&&ce.push(Ce.variant),Ce.variant!=Ce.weight&&ce.push(Ce.weight),Az&&Ce.weight!=Ce.stretch&&ce.push(Ce.stretch),r.font[me]={baseString:Fe,family:Re,weight:Ce.weight,stretch:Ce.stretch,style:Ce.style,variant:Ce.variant,width:{},kerning:{},metrics:PUt(Re,{origin:\"top\",fontSize:xc.baseFontSize,fontStyle:ce.join(\" \")})},xc.fonts[Fe]=r.font[me]}}),(n||i)&&this.font.forEach(function(Ce,me){var ie=v5.stringify({size:r.fontSize[me],family:Ce.family,stretch:Az?Ce.stretch:void 0,variant:Ce.variant,weight:Ce.weight,style:Ce.style});if(r.fontAtlas[me]=r.shader.atlas[ie],!r.fontAtlas[me]){var Se=Ce.metrics;r.shader.atlas[ie]=r.fontAtlas[me]={fontString:ie,step:Math.ceil(r.fontSize[me]*Se.bottom*.5)*2,em:r.fontSize[me],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:r.regl.texture()}}t.text==null&&(t.text=r.text)}),typeof t.text==\"string\"&&t.position&&t.position.length>2){for(var a=Array(t.position.length*.5),o=0;o<a.length;o++)a[o]=t.text;t.text=a}var s;if(t.text!=null||n){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var l=1;l<t.text.length;l++)this.textOffsets[l]=this.textOffsets[l-1]+t.text[l-1].length,this.count+=t.text[l].length,this.counts.push(t.text[l].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];s=[],this.font.forEach(function(Ce,me){xc.atlasContext.font=Ce.baseString;for(var ie=r.fontAtlas[me],Se=0;Se<r.text.length;Se++){var Le=r.text.charAt(Se);if(ie.ids[Le]==null&&(ie.ids[Le]=ie.chars.length,ie.chars.push(Le),s.push(Le)),Ce.width[Le]==null&&(Ce.width[Le]=xc.atlasContext.measureText(Le).width/xc.baseFontSize,r.kerning)){var Ae=[];for(var Fe in Ce.width)Ae.push(Fe+Le,Le+Fe);LUt(Ce.kerning,CUt(Ce.family,{pairs:Ae}))}}})}if(t.position)if(t.position.length>2){for(var u=!t.position[0].length,c=dx.mallocFloat(this.count*2),f=0,h=0;f<this.counts.length;f++){var d=this.counts[f];if(u)for(var v=0;v<d;v++)c[h++]=t.position[f*2],c[h++]=t.position[f*2+1];else for(var _=0;_<d;_++)c[h++]=t.position[f][0],c[h++]=t.position[f][1]}this.position.call?this.position({type:\"float\",data:c}):this.position=this.regl.buffer({type:\"float\",data:c}),dx.freeFloat(c)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||n){var b=dx.mallocUint8(this.count),p=dx.mallocFloat(this.count*2);this.textWidth=[];for(var k=0,E=0;k<this.counts.length;k++){for(var S=this.counts[k],L=this.font[k]||this.font[0],x=this.fontAtlas[k]||this.fontAtlas[0],C=0;C<S;C++){var M=this.text.charAt(E),g=this.text.charAt(E-1);if(b[E]=x.ids[M],p[E*2]=L.width[M],C){var P=p[E*2-2],T=p[E*2],z=p[E*2-1],O=z+P*.5+T*.5;if(this.kerning){var V=L.kerning[g+M];V&&(O+=V*.001)}p[E*2+1]=O}else 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wa(ne){hi.call(this),this.mipmask=0,this.internalformat=Ma,this.id=Vl++,this.refCount=1,this.target=ne,this.texture=Me.createTexture(),this.unit=-1,this.bindCount=0,this.texInfo=new zo,Gr.profile&&(this.stats={size:0})}function ol(ne){Me.activeTexture(Fu),Me.bindTexture(ne.target,ne.texture)}function io(){var ne=Ys[0];ne?Me.bindTexture(ne.target,ne.texture):Me.bindTexture(_n,null)}function Y(ne){var we=ne.texture,Ue=ne.unit,ft=ne.target;Ue>=0&&(Me.activeTexture(Fu+Ue),Me.bindTexture(ft,null),Ys[Ue]=null),Me.deleteTexture(we),ne.texture=null,ne.params=null,ne.pixels=null,ne.refCount=0,delete ss[ne.id],Nr.textureCount--}e(wa.prototype,{bind:function(){var ne=this;ne.bindCount+=1;var we=ne.unit;if(we<0){for(var Ue=0;Ue<Vs;++Ue){var ft=Ys[Ue];if(ft){if(ft.bindCount>0)continue;ft.unit=-1}Ys[Ue]=ne,we=Ue;break}we>=Vs,Gr.profile&&Nr.maxTextureUnits<we+1&&(Nr.maxTextureUnits=we+1),ne.unit=we,Me.activeTexture(Fu+we),Me.bindTexture(ne.target,ne.texture)}return we},unbind:function(){this.bindCount-=1},decRef:function(){--this.refCount<=0&&Y(this)}});function D(ne,we){var Ue=new wa(_n);ss[Ue.id]=Ue,Nr.textureCount++;function ft(qt,Ve){var Qe=Ue.texInfo;zo.call(Qe);var at=Va();return typeof qt==\"number\"?typeof Ve==\"number\"?oa(at,qt|0,Ve|0):oa(at,qt|0,qt|0):qt?(Qs(Qe,qt),ba(at,qt)):oa(at,1,1),Qe.genMipmaps&&(at.mipmask=(at.width<<1)-1),Ue.mipmask=at.mipmask,li(Ue,at),Ue.internalformat=at.internalformat,ft.width=at.width,ft.height=at.height,ol(Ue),is(at,_n),al(Qe,_n),io(),Ml(at),Gr.profile&&(Ue.stats.size=cc(Ue.internalformat,Ue.type,at.width,at.height,Qe.genMipmaps,!1)),ft.format=xi[Ue.internalformat],ft.type=Ri[Ue.type],ft.mag=ci[Qe.magFilter],ft.min=an[Qe.minFilter],ft.wrapS=Zi[Qe.wrapS],ft.wrapT=Zi[Qe.wrapT],ft}function Xt(qt,Ve,Qe,at){var Ct=Ve|0,Ot=Qe|0,Rt=at|0,Bt=Ki();return li(Bt,Ue),Bt.width=0,Bt.height=0,Ni(Bt,qt),Bt.width=Bt.width||(Ue.width>>Rt)-Ct,Bt.height=Bt.height||(Ue.height>>Rt)-Ot,ol(Ue),Vn(Bt,_n,Ct,Ot,Rt),io(),kn(Bt),ft}function hr(qt,Ve){var Qe=qt|0,at=Ve|0||Qe;if(Qe===Ue.width&&at===Ue.height)return ft;ft.width=Ue.width=Qe,ft.height=Ue.height=at,ol(Ue);for(var Ct=0;Ue.mipmask>>Ct;++Ct){var Ot=Qe>>Ct,Rt=at>>Ct;if(!Ot||!Rt)break;Me.texImage2D(_n,Ct,Ue.format,Ot,Rt,0,Ue.format,Ue.type,null)}return io(),Gr.profile&&(Ue.stats.size=cc(Ue.internalformat,Ue.type,Qe,at,!1,!1)),ft}return ft(ne,we),ft.subimage=Xt,ft.resize=hr,ft._reglType=\"texture2d\",ft._texture=Ue,Gr.profile&&(ft.stats=Ue.stats),ft.destroy=function(){Ue.decRef()},ft}function J(ne,we,Ue,ft,Xt,hr){var qt=new wa(ya);ss[qt.id]=qt,Nr.cubeCount++;var Ve=new Array(6);function Qe(Ot,Rt,Bt,Dt,yt,Pt){var ht,ur=qt.texInfo;for(zo.call(ur),ht=0;ht<6;++ht)Ve[ht]=Va();if(typeof Ot==\"number\"||!Ot){var br=Ot|0||1;for(ht=0;ht<6;++ht)oa(Ve[ht],br,br)}else if(typeof 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Ct(Ot){var Rt=Ot|0;if(Rt!==qt.width){Qe.width=qt.width=Rt,Qe.height=qt.height=Rt,ol(qt);for(var Bt=0;Bt<6;++Bt)for(var Dt=0;qt.mipmask>>Dt;++Dt)Me.texImage2D(Jn+Bt,Dt,qt.format,Rt>>Dt,Rt>>Dt,0,qt.format,qt.type,null);return io(),Gr.profile&&(qt.stats.size=cc(qt.internalformat,qt.type,Qe.width,Qe.height,!1,!0)),Qe}}return Qe(ne,we,Ue,ft,Xt,hr),Qe.subimage=at,Qe.resize=Ct,Qe._reglType=\"textureCube\",Qe._texture=qt,Gr.profile&&(Qe.stats=qt.stats),Qe.destroy=function(){qt.decRef()},Qe}function q(){for(var ne=0;ne<Vs;++ne)Me.activeTexture(Fu+ne),Me.bindTexture(_n,null),Ys[ne]=null;dt(ss).forEach(Y),Nr.cubeCount=0,Nr.textureCount=0}Gr.profile&&(Nr.getTotalTextureSize=function(){var ne=0;return Object.keys(ss).forEach(function(we){ne+=ss[we].stats.size}),ne});function K(){for(var ne=0;ne<Vs;++ne){var we=Ys[ne];we&&(we.bindCount=0,we.unit=-1,Ys[ne]=null)}dt(ss).forEach(function(Ue){Ue.texture=Me.createTexture(),Me.bindTexture(Ue.target,Ue.texture);for(var ft=0;ft<32;++ft)if((Ue.mipmask&1<<ft)!==0)if(Ue.target===_n)Me.texImage2D(_n,ft,Ue.internalformat,Ue.width>>ft,Ue.height>>ft,0,Ue.internalformat,Ue.type,null);else for(var Xt=0;Xt<6;++Xt)Me.texImage2D(Jn+Xt,ft,Ue.internalformat,Ue.width>>ft,Ue.height>>ft,0,Ue.internalformat,Ue.type,null);al(Ue.texInfo,Ue.target)})}function de(){for(var ne=0;ne<Vs;++ne){var we=Ys[ne];we&&(we.bindCount=0,we.unit=-1,Ys[ne]=null),Me.activeTexture(Fu+ne),Me.bindTexture(_n,null),Me.bindTexture(ya,null)}}return{create2D:D,createCube:J,clear:q,getTexture:function(ne){return null},restore:K,refresh:de}}var Nl=36161,Kc=32854,Rc=32855,gs=36194,jf=33189,Gh=36168,rh=34041,sf=35907,Th=34836,Mu=34842,ih=34843,js=[];js[Kc]=2,js[Rc]=2,js[gs]=2,js[jf]=2,js[Gh]=1,js[rh]=4,js[sf]=4,js[Th]=16,js[Mu]=8,js[ih]=6;function Eu(Me,bt,zt){return js[Me]*bt*zt}var Dc=function(Me,bt,zt,Rr,jr){var Nr={rgba4:Kc,rgb565:gs,\"rgb5 a1\":Rc,depth:jf,stencil:Gh,\"depth 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en(){dt(Ui).forEach(function(Wi){Wi.renderbuffer=Me.createRenderbuffer(),Me.bindRenderbuffer(Nl,Wi.renderbuffer),Me.renderbufferStorage(Nl,Wi.format,Wi.width,Wi.height)}),Me.bindRenderbuffer(Nl,null)}return{create:Hn,clear:function(){dt(Ui).forEach(Ei)},restore:en}},ks=36160,bc=36161,hu=3553,_u=34069,nl=36064,nh=36096,Ah=36128,zu=33306,Fc=36053,wc=36193,bd=5121,xf=5126,Pf=6407,Ou=6408,bf=[];bf[Ou]=4,bf[Pf]=3;var jl=[];jl[bd]=1,jl[xf]=4,jl[wc]=2;function lf(Me,bt,zt,Rr,jr,Nr){var Gr={cur:null,next:null,dirty:!1,setFBO:null},mi=[\"rgba\"],Ui=[\"rgba4\",\"rgb565\",\"rgb5 a1\"];bt.ext_srgb&&Ui.push(\"srgba\"),bt.ext_color_buffer_half_float&&Ui.push(\"rgba16f\",\"rgb16f\"),bt.webgl_color_buffer_float&&Ui.push(\"rgba32f\");var qi=[\"uint8\"];bt.oes_texture_half_float&&qi.push(\"half float\",\"float16\"),bt.oes_texture_float&&qi.push(\"float\",\"float32\");function Ei(Vi,Ni,pn){this.target=Vi,this.texture=Ni,this.renderbuffer=pn;var Vn=0,na=0;Ni?(Vn=Ni.width,na=Ni.height):pn&&(Vn=pn.width,na=pn.height),this.width=Vn,this.height=na}function Hn(Vi){Vi&&(Vi.texture&&Vi.texture._texture.decRef(),Vi.renderbuffer&&Vi.renderbuffer._renderbuffer.decRef())}function en(Vi,Ni,pn){if(Vi)if(Vi.texture){var Vn=Vi.texture._texture,na=Math.max(1,Vn.width),Ki=Math.max(1,Vn.height);Vn.refCount+=1}else{var kn=Vi.renderbuffer._renderbuffer;kn.refCount+=1}}function Wi(Vi,Ni){Ni&&(Ni.texture?Me.framebufferTexture2D(ks,Vi,Ni.target,Ni.texture._texture.texture,0):Me.framebufferRenderbuffer(ks,Vi,bc,Ni.renderbuffer._renderbuffer.renderbuffer))}function si(Vi){var Ni=hu,pn=null,Vn=null,na=Vi;typeof Vi==\"object\"&&(na=Vi.data,\"target\"in Vi&&(Ni=Vi.target|0));var Ki=na._reglType;return Ki===\"texture2d\"||Ki===\"textureCube\"?pn=na:Ki===\"renderbuffer\"&&(Vn=na,Ni=bc),new Ei(Ni,pn,Vn)}function Mr(Vi,Ni,pn,Vn,na){if(pn){var Ki=Rr.create2D({width:Vi,height:Ni,format:Vn,type:na});return Ki._texture.refCount=0,new Ei(hu,Ki,null)}else{var kn=jr.create({width:Vi,height:Ni,format:Vn});return kn._renderbuffer.refCount=0,new Ei(bc,null,kn)}}function Yr(Vi){return Vi&&(Vi.texture||Vi.renderbuffer)}function xi(Vi,Ni,pn){Vi&&(Vi.texture?Vi.texture.resize(Ni,pn):Vi.renderbuffer&&Vi.renderbuffer.resize(Ni,pn),Vi.width=Ni,Vi.height=pn)}var Ri=0,ci={};function an(){this.id=Ri++,ci[this.id]=this,this.framebuffer=Me.createFramebuffer(),this.width=0,this.height=0,this.colorAttachments=[],this.depthAttachment=null,this.stencilAttachment=null,this.depthStencilAttachment=null}function Zi(Vi){Vi.colorAttachments.forEach(Hn),Hn(Vi.depthAttachment),Hn(Vi.stencilAttachment),Hn(Vi.depthStencilAttachment)}function Bn(Vi){var Ni=Vi.framebuffer;Me.deleteFramebuffer(Ni),Vi.framebuffer=null,Nr.framebufferCount--,delete ci[Vi.id]}function hi(Vi){var Ni;Me.bindFramebuffer(ks,Vi.framebuffer);var 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xi(pn.depthAttachment,ta,oa),xi(pn.stencilAttachment,ta,oa),xi(pn.depthStencilAttachment,ta,oa),pn.width=Vn.width=ta,pn.height=Vn.height=oa,hi(pn),Vn}return Vn(Vi,Ni),e(Vn,{resize:na,_reglType:\"framebuffer\",_framebuffer:pn,destroy:function(){Bn(pn),Zi(pn)},use:function(Ki){Gr.setFBO({framebuffer:Vn},Ki)}})}function mn(Vi){var Ni=Array(6);function pn(na){var Ki,kn={color:null},ta=0,oa=null,ba=\"rgba\",is=\"uint8\",Zs=1;if(typeof na==\"number\")ta=na|0;else if(!na)ta=1;else{var Va=na;if(\"shape\"in Va){var Ml=Va.shape;ta=Ml[0]}else\"radius\"in Va&&(ta=Va.radius|0),\"width\"in Va?(ta=Va.width|0,\"height\"in Va):\"height\"in Va&&(ta=Va.height|0);(\"color\"in Va||\"colors\"in Va)&&(oa=Va.color||Va.colors,Array.isArray(oa)),oa||(\"colorCount\"in Va&&(Zs=Va.colorCount|0),\"colorType\"in Va&&(is=Va.colorType),\"colorFormat\"in Va&&(ba=Va.colorFormat)),\"depth\"in Va&&(kn.depth=Va.depth),\"stencil\"in Va&&(kn.stencil=Va.stencil),\"depthStencil\"in Va&&(kn.depthStencil=Va.depthStencil)}var zo;if(oa)if(Array.isArray(oa))for(zo=[],Ki=0;Ki<oa.length;++Ki)zo[Ki]=oa[Ki];else zo=[oa];else{zo=Array(Zs);var Qs={radius:ta,format:ba,type:is};for(Ki=0;Ki<Zs;++Ki)zo[Ki]=Rr.createCube(Qs)}for(kn.color=Array(zo.length),Ki=0;Ki<zo.length;++Ki){var al=zo[Ki];ta=ta||al.width,kn.color[Ki]={target:_u,data:zo[Ki]}}for(Ki=0;Ki<6;++Ki){for(var Vl=0;Vl<zo.length;++Vl)kn.color[Vl].target=_u+Ki;Ki>0&&(kn.depth=Ni[0].depth,kn.stencil=Ni[0].stencil,kn.depthStencil=Ni[0].depthStencil),Ni[Ki]?Ni[Ki](kn):Ni[Ki]=li(kn)}return e(pn,{width:ta,height:ta,color:zo})}function Vn(na){var Ki,kn=na|0;if(kn===pn.width)return pn;var ta=pn.color;for(Ki=0;Ki<ta.length;++Ki)ta[Ki].resize(kn);for(Ki=0;Ki<6;++Ki)Ni[Ki].resize(kn);return pn.width=pn.height=kn,pn}return pn(Vi),e(pn,{faces:Ni,resize:Vn,_reglType:\"framebufferCube\",destroy:function(){Ni.forEach(function(na){na.destroy()})}})}function Ji(){Gr.cur=null,Gr.next=null,Gr.dirty=!0,dt(ci).forEach(function(Vi){Vi.framebuffer=Me.createFramebuffer(),hi(Vi)})}return e(Gr,{getFramebuffer:function(Vi){if(typeof Vi==\"function\"&&Vi._reglType===\"framebuffer\"){var Ni=Vi._framebuffer;if(Ni instanceof an)return Ni}return null},create:li,createCube:mn,clear:function(){dt(ci).forEach(Bn)},restore:Ji})}var Hh=5126,If=34962,Cs=34963;function du(){this.state=0,this.x=0,this.y=0,this.z=0,this.w=0,this.buffer=null,this.size=0,this.normalized=!1,this.type=Hh,this.offset=0,this.stride=0,this.divisor=0}function ku(Me,bt,zt,Rr,jr,Nr,Gr){for(var mi=zt.maxAttributes,Ui=new Array(mi),qi=0;qi<mi;++qi)Ui[qi]=new du;var Ei=0,Hn={},en={Record:du,scope:{},state:Ui,currentVAO:null,targetVAO:null,restore:si()?Zi:function(){},createVAO:Bn,getVAO:Yr,destroyBuffer:Wi,setVAO:si()?xi:Ri,clear:si()?ci:function(){}};function Wi(hi){for(var li=0;li<Ui.length;++li){var mn=Ui[li];mn.buffer===hi&&(Me.disableVertexAttribArray(li),mn.buffer=null)}}function si(){return bt.oes_vertex_array_object}function Mr(){return bt.angle_instanced_arrays}function Yr(hi){return typeof hi==\"function\"&&hi._vao?hi._vao:null}function xi(hi){if(hi!==en.currentVAO){var li=si();hi?li.bindVertexArrayOES(hi.vao):li.bindVertexArrayOES(null),en.currentVAO=hi}}function Ri(hi){if(hi!==en.currentVAO){if(hi)hi.bindAttrs();else{for(var li=Mr(),mn=0;mn<Ui.length;++mn){var Ji=Ui[mn];Ji.buffer?(Me.enableVertexAttribArray(mn),Ji.buffer.bind(),Me.vertexAttribPointer(mn,Ji.size,Ji.type,Ji.normalized,Ji.stride,Ji.offfset),li&&Ji.divisor&&li.vertexAttribDivisorANGLE(mn,Ji.divisor)):(Me.disableVertexAttribArray(mn),Me.vertexAttrib4f(mn,Ji.x,Ji.y,Ji.z,Ji.w))}Gr.elements?Me.bindBuffer(Cs,Gr.elements.buffer.buffer):Me.bindBuffer(Cs,null)}en.currentVAO=hi}}function ci(){dt(Hn).forEach(function(hi){hi.destroy()})}function an(){this.id=++Ei,this.attributes=[],this.elements=null,this.ownsElements=!1,this.count=0,this.offset=0,this.instances=-1,this.primitive=4;var hi=si();hi?this.vao=hi.createVertexArrayOES():this.vao=null,Hn[this.id]=this,this.buffers=[]}an.prototype.bindAttrs=function(){for(var hi=Mr(),li=this.attributes,mn=0;mn<li.length;++mn){var Ji=li[mn];Ji.buffer?(Me.enableVertexAttribArray(mn),Me.bindBuffer(If,Ji.buffer.buffer),Me.vertexAttribPointer(mn,Ji.size,Ji.type,Ji.normalized,Ji.stride,Ji.offset),hi&&Ji.divisor&&hi.vertexAttribDivisorANGLE(mn,Ji.divisor)):(Me.disableVertexAttribArray(mn),Me.vertexAttrib4f(mn,Ji.x,Ji.y,Ji.z,Ji.w))}for(var Vi=li.length;Vi<mi;++Vi)Me.disableVertexAttribArray(Vi);var Ni=Nr.getElements(this.elements);Ni?Me.bindBuffer(Cs,Ni.buffer.buffer):Me.bindBuffer(Cs,null)},an.prototype.refresh=function(){var hi=si();hi&&(hi.bindVertexArrayOES(this.vao),this.bindAttrs(),en.currentVAO=null,hi.bindVertexArrayOES(null))},an.prototype.destroy=function(){if(this.vao){var hi=si();this===en.currentVAO&&(en.currentVAO=null,hi.bindVertexArrayOES(null)),hi.deleteVertexArrayOES(this.vao),this.vao=null}this.ownsElements&&(this.elements.destroy(),this.elements=null,this.ownsElements=!1),Hn[this.id]&&(delete Hn[this.id],Rr.vaoCount-=1)};function Zi(){var hi=si();hi&&dt(Hn).forEach(function(li){li.refresh()})}function Bn(hi){var li=new an;Rr.vaoCount+=1;function mn(Ji){var Vi;if(Array.isArray(Ji))Vi=Ji,li.elements&&li.ownsElements&&li.elements.destroy(),li.elements=null,li.ownsElements=!1,li.offset=0,li.count=0,li.instances=-1,li.primitive=4;else{if(Ji.elements){var Ni=Ji.elements;li.ownsElements?typeof Ni==\"function\"&&Ni._reglType===\"elements\"?(li.elements.destroy(),li.ownsElements=!1):(li.elements(Ni),li.ownsElements=!1):Nr.getElements(Ji.elements)?(li.elements=Ji.elements,li.ownsElements=!1):(li.elements=Nr.create(Ji.elements),li.ownsElements=!0)}else li.elements=null,li.ownsElements=!1;Vi=Ji.attributes,li.offset=0,li.count=-1,li.instances=-1,li.primitive=4,li.elements&&(li.count=li.elements._elements.vertCount,li.primitive=li.elements._elements.primType),\"offset\"in Ji&&(li.offset=Ji.offset|0),\"count\"in Ji&&(li.count=Ji.count|0),\"instances\"in Ji&&(li.instances=Ji.instances|0),\"primitive\"in Ji&&(li.primitive=Sn[Ji.primitive])}var pn={},Vn=li.attributes;Vn.length=Vi.length;for(var na=0;na<Vi.length;++na){var Ki=Vi[na],kn=Vn[na]=new du,ta=Ki.data||Ki;if(Array.isArray(ta)||Br(ta)||Vr(ta)){var oa;li.buffers[na]&&(oa=li.buffers[na],Br(ta)&&oa._buffer.byteLength>=ta.byteLength?oa.subdata(ta):(oa.destroy(),li.buffers[na]=null)),li.buffers[na]||(oa=li.buffers[na]=jr.create(Ki,If,!1,!0)),kn.buffer=jr.getBuffer(oa),kn.size=kn.buffer.dimension|0,kn.normalized=!1,kn.type=kn.buffer.dtype,kn.offset=0,kn.stride=0,kn.divisor=0,kn.state=1,pn[na]=1}else 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Wu(Me,bt,zt,Rr){var jr={},Nr={};function Gr(Mr,Yr,xi,Ri){this.name=Mr,this.id=Yr,this.location=xi,this.info=Ri}function mi(Mr,Yr){for(var xi=0;xi<Mr.length;++xi)if(Mr[xi].id===Yr.id){Mr[xi].location=Yr.location;return}Mr.push(Yr)}function Ui(Mr,Yr,xi){var Ri=Mr===Wf?jr:Nr,ci=Ri[Yr];if(!ci){var an=bt.str(Yr);ci=Me.createShader(Mr),Me.shaderSource(ci,an),Me.compileShader(ci),Ri[Yr]=ci}return ci}var qi={},Ei=[],Hn=0;function en(Mr,Yr){this.id=Hn++,this.fragId=Mr,this.vertId=Yr,this.program=null,this.uniforms=[],this.attributes=[],this.refCount=1,Rr.profile&&(this.stats={uniformsCount:0,attributesCount:0})}function Wi(Mr,Yr,xi){var Ri,ci,an=Ui(Wf,Mr.fragId),Zi=Ui(Us,Mr.vertId),Bn=Mr.program=Me.createProgram();if(Me.attachShader(Bn,an),Me.attachShader(Bn,Zi),xi)for(Ri=0;Ri<xi.length;++Ri){var hi=xi[Ri];Me.bindAttribLocation(Bn,hi[0],hi[1])}Me.linkProgram(Bn);var li=Me.getProgramParameter(Bn,wf);Rr.profile&&(Mr.stats.uniformsCount=li);var mn=Mr.uniforms;for(Ri=0;Ri<li;++Ri)if(ci=Me.getActiveUniform(Bn,Ri),ci)if(ci.size>1)for(var Ji=0;Ji<ci.size;++Ji){var Vi=ci.name.replace(\"[0]\",\"[\"+Ji+\"]\");mi(mn,new Gr(Vi,bt.id(Vi),Me.getUniformLocation(Bn,Vi),ci))}else mi(mn,new Gr(ci.name,bt.id(ci.name),Me.getUniformLocation(Bn,ci.name),ci));var Ni=Me.getProgramParameter(Bn,zc);Rr.profile&&(Mr.stats.attributesCount=Ni);var pn=Mr.attributes;for(Ri=0;Ri<Ni;++Ri)ci=Me.getActiveAttrib(Bn,Ri),ci&&mi(pn,new Gr(ci.name,bt.id(ci.name),Me.getAttribLocation(Bn,ci.name),ci))}Rr.profile&&(zt.getMaxUniformsCount=function(){var Mr=0;return Ei.forEach(function(Yr){Yr.stats.uniformsCount>Mr&&(Mr=Yr.stats.uniformsCount)}),Mr},zt.getMaxAttributesCount=function(){var Mr=0;return Ei.forEach(function(Yr){Yr.stats.attributesCount>Mr&&(Mr=Yr.stats.attributesCount)}),Mr});function si(){jr={},Nr={};for(var Mr=0;Mr<Ei.length;++Mr)Wi(Ei[Mr],null,Ei[Mr].attributes.map(function(Yr){return[Yr.location,Yr.name]}))}return{clear:function(){var Mr=Me.deleteShader.bind(Me);dt(jr).forEach(Mr),jr={},dt(Nr).forEach(Mr),Nr={},Ei.forEach(function(Yr){Me.deleteProgram(Yr.program)}),Ei.length=0,qi={},zt.shaderCount=0},program:function(Mr,Yr,xi,Ri){var ci=qi[Yr];ci||(ci=qi[Yr]={});var an=ci[Mr];if(an&&(an.refCount++,!Ri))return an;var Zi=new en(Yr,Mr);return zt.shaderCount++,Wi(Zi,xi,Ri),an||(ci[Mr]=Zi),Ei.push(Zi),e(Zi,{destroy:function(){if(Zi.refCount--,Zi.refCount<=0){Me.deleteProgram(Zi.program);var Bn=Ei.indexOf(Zi);Ei.splice(Bn,1),zt.shaderCount--}ci[Zi.vertId].refCount<=0&&(Me.deleteShader(Nr[Zi.vertId]),delete Nr[Zi.vertId],delete qi[Zi.fragId][Zi.vertId]),Object.keys(qi[Zi.fragId]).length||(Me.deleteShader(jr[Zi.fragId]),delete jr[Zi.fragId],delete qi[Zi.fragId])}})},restore:si,shader:Ui,frag:-1,vert:-1}}var Rf=6408,Xu=5121,uf=3333,Xf=5126;function Wl(Me,bt,zt,Rr,jr,Nr,Gr){function mi(Ei){var Hn;bt.next===null?Hn=Xu:Hn=bt.next.colorAttachments[0].texture._texture.type;var 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bt=ah?\"0123456789ABCDEF\":\"0123456789abcdef\",zt=\"\",Rr,jr=0;jr<Me.length;jr++)Rr=Me.charCodeAt(jr),zt+=bt.charAt(Rr>>>4&15)+bt.charAt(Rr&15);return zt}function qc(Me){for(var bt=\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/\",zt=\"\",Rr=Me.length,jr=0;jr<Rr;jr+=3)for(var Nr=Me.charCodeAt(jr)<<16|(jr+1<Rr?Me.charCodeAt(jr+1)<<8:0)|(jr+2<Rr?Me.charCodeAt(jr+2):0),Gr=0;Gr<4;Gr++)jr*8+Gr*6>Me.length*8?zt+=Zu:zt+=bt.charAt(Nr>>>6*(3-Gr)&63);return zt}function cf(Me,bt){var zt=bt.length,Rr=Array(),jr,Nr,Gr,mi,Ui=Array(Math.ceil(Me.length/2));for(jr=0;jr<Ui.length;jr++)Ui[jr]=Me.charCodeAt(jr*2)<<8|Me.charCodeAt(jr*2+1);for(;Ui.length>0;){for(mi=Array(),Gr=0,jr=0;jr<Ui.length;jr++)Gr=(Gr<<16)+Ui[jr],Nr=Math.floor(Gr/zt),Gr-=Nr*zt,(mi.length>0||Nr>0)&&(mi[mi.length]=Nr);Rr[Rr.length]=Gr,Ui=mi}var qi=\"\";for(jr=Rr.length-1;jr>=0;jr--)qi+=bt.charAt(Rr[jr]);var Ei=Math.ceil(Me.length*8/(Math.log(bt.length)/Math.log(2)));for(jr=qi.length;jr<Ei;jr++)qi=bt[0]+qi;return qi}function fc(Me){for(var bt=\"\",zt=-1,Rr,jr;++zt<Me.length;)Rr=Me.charCodeAt(zt),jr=zt+1<Me.length?Me.charCodeAt(zt+1):0,55296<=Rr&&Rr<=56319&&56320<=jr&&jr<=57343&&(Rr=65536+((Rr&1023)<<10)+(jr&1023),zt++),Rr<=127?bt+=String.fromCharCode(Rr):Rr<=2047?bt+=String.fromCharCode(192|Rr>>>6&31,128|Rr&63):Rr<=65535?bt+=String.fromCharCode(224|Rr>>>12&15,128|Rr>>>6&63,128|Rr&63):Rr<=2097151&&(bt+=String.fromCharCode(240|Rr>>>18&7,128|Rr>>>12&63,128|Rr>>>6&63,128|Rr&63));return bt}function Bc(Me){for(var bt=Array(Me.length>>2),zt=0;zt<bt.length;zt++)bt[zt]=0;for(var zt=0;zt<Me.length*8;zt+=8)bt[zt>>5]|=(Me.charCodeAt(zt/8)&255)<<24-zt%32;return bt}function At(Me){for(var bt=\"\",zt=0;zt<Me.length*32;zt+=8)bt+=String.fromCharCode(Me[zt>>5]>>>24-zt%32&255);return bt}function Wt(Me,bt){return Me>>>bt|Me<<32-bt}function Cr(Me,bt){return Me>>>bt}function Ar(Me,bt,zt){return Me&bt^~Me&zt}function Kr(Me,bt,zt){return Me&bt^Me&zt^bt&zt}function ki(Me){return Wt(Me,2)^Wt(Me,13)^Wt(Me,22)}function 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ei(!1,!1,!1,Me)}function Un(Me,bt){var zt=Me.type;if(zt===Yn){var Rr=Me.data.length;return new ei(!0,Rr>=1,Rr>=2,bt)}else if(zt===Xo){var jr=Me.data;return new ei(jr.thisDep,jr.contextDep,jr.propDep,bt)}else{if(zt===Ss)return new ei(!1,!1,!1,bt);if(zt===as){for(var Nr=!1,Gr=!1,mi=!1,Ui=0;Ui<Me.data.length;++Ui){var qi=Me.data[Ui];if(qi.type===Dn)mi=!0;else if(qi.type===Ka)Gr=!0;else if(qi.type===bo)Nr=!0;else if(qi.type===Yn){Nr=!0;var Ei=qi.data;Ei>=1&&(Gr=!0),Ei>=2&&(mi=!0)}else qi.type===Xo&&(Nr=Nr||qi.data.thisDep,Gr=Gr||qi.data.contextDep,mi=mi||qi.data.propDep)}return new ei(Nr,Gr,mi,bt)}else return new ei(zt===bo,zt===Ka,zt===Dn,bt)}}var ia=new ei(!1,!1,!1,function(){});function Ea(Me,bt,zt,Rr,jr,Nr,Gr,mi,Ui,qi,Ei,Hn,en,Wi,si,Mr){var Yr=qi.Record,xi={add:32774,subtract:32778,\"reverse subtract\":32779};zt.ext_blend_minmax&&(xi.min=He,xi.max=Ye);var Ri=zt.angle_instanced_arrays,ci=zt.webgl_draw_buffers,an=zt.oes_vertex_array_object,Zi={dirty:!0,profile:Mr.profile},Bn={},hi=[],li={},mn={};function Ji(Ve){return Ve.replace(\".\",\"_\")}function Vi(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Bn[Ct]=Zi[Ct]=!!at,li[Ct]=Qe}function Ni(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Array.isArray(at)?(Zi[Ct]=at.slice(),Bn[Ct]=at.slice()):Zi[Ct]=Bn[Ct]=at,mn[Ct]=Qe}function pn(Ve){return!!isNaN(Ve)}Vi(ws,Pi),Vi(Ho,ni),Ni(ml,\"blendColor\",[0,0,0,0]),Ni(Ws,\"blendEquationSeparate\",[yr,yr]),Ni(Ls,\"blendFuncSeparate\",[gr,jt,gr,jt]),Vi(va,ln,!0),Ni(no,\"depthFunc\",Hr),Ni(ys,\"depthRange\",[0,1]),Ni(rs,\"depthMask\",!0),Ni($l,$l,[!0,!0,!0,!0]),Vi(Cu,Wr),Ni(Yu,\"cullFace\",se),Ni(Nc,Nc,Ne),Ni(pu,pu,1),Vi(Uc,Kn),Ni(xu,\"polygonOffset\",[0,0]),Vi(Ac,Ta),Vi(Ua,fa),Ni(oo,\"sampleCoverage\",[1,!1]),Vi(Vc,cn),Ni(hc,\"stencilMask\",-1),Ni(Ku,\"stencilFunc\",[kt,0,-1]),Ni(ue,\"stencilOpSeparate\",[X,nt,nt,nt]),Ni(w,\"stencilOpSeparate\",[se,nt,nt,nt]),Vi(B,Cn),Ni(Q,\"scissor\",[0,0,Me.drawingBufferWidth,Me.drawingBufferHeight]),Ni(ee,ee,[0,0,Me.drawingBufferWidth,Me.drawingBufferHeight]);var Vn={gl:Me,context:en,strings:bt,next:Bn,current:Zi,draw:Hn,elements:Nr,buffer:jr,shader:Ei,attributes:qi.state,vao:qi,uniforms:Ui,framebuffer:mi,extensions:zt,timer:Wi,isBufferArgs:Ii},na={primTypes:Sn,compareFuncs:Zr,blendFuncs:bi,blendEquations:xi,stencilOps:ai,glTypes:ji,orientationType:gi};ci&&(na.backBuffer=[se],na.drawBuffer=M(Rr.maxDrawbuffers,function(Ve){return Ve===0?[0]:M(Ve,function(Qe){return _i+Qe})}));var Ki=0;function kn(){var Ve=$n({cache:si}),Qe=Ve.link,at=Ve.global;Ve.id=Ki++,Ve.batchId=\"0\";var Ct=Qe(Vn),Ot=Ve.shared={props:\"a0\"};Object.keys(Vn).forEach(function(Pt){Ot[Pt]=at.def(Ct,\".\",Pt)});var Rt=Ve.next={},Bt=Ve.current={};Object.keys(mn).forEach(function(Pt){Array.isArray(Zi[Pt])&&(Rt[Pt]=at.def(Ot.next,\".\",Pt),Bt[Pt]=at.def(Ot.current,\".\",Pt))});var Dt=Ve.constants={};Object.keys(na).forEach(function(Pt){Dt[Pt]=at.def(JSON.stringify(na[Pt]))}),Ve.invoke=function(Pt,ht){switch(ht.type){case Yn:var ur=[\"this\",Ot.context,Ot.props,Ve.batchId];return Pt.def(Qe(ht.data),\".call(\",ur.slice(0,Math.max(ht.data.length+1,4)),\")\");case Dn:return Pt.def(Ot.props,ht.data);case Ka:return Pt.def(Ot.context,ht.data);case bo:return Pt.def(\"this\",ht.data);case Xo:return ht.data.append(Ve,Pt),ht.data.ref;case Ss:return ht.data.toString();case as:return ht.data.map(function(br){return Ve.invoke(Pt,br)})}},Ve.attribCache={};var yt={};return Ve.scopeAttrib=function(Pt){var ht=bt.id(Pt);if(ht in yt)return yt[ht];var ur=qi.scope[ht];ur||(ur=qi.scope[ht]=new Yr);var br=yt[ht]=Qe(ur);return br},Ve}function ta(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct;if(le in Qe){var Ot=!!Qe[le];Ct=En(function(Bt,Dt){return Ot}),Ct.enable=Ot}else if(le in at){var Rt=at[le];Ct=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}return Ct}function oa(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic;if(qe in at){var Ot=at[qe];return Ot?(Ot=mi.getFramebuffer(Ot),En(function(Bt,Dt){var yt=Bt.link(Ot),Pt=Bt.shared;Dt.set(Pt.framebuffer,\".next\",yt);var ht=Pt.context;return Dt.set(ht,\".\"+Be,yt+\".width\"),Dt.set(ht,\".\"+et,yt+\".height\"),yt})):En(function(Bt,Dt){var yt=Bt.shared;Dt.set(yt.framebuffer,\".next\",\"null\");var Pt=yt.context;return Dt.set(Pt,\".\"+Be,Pt+\".\"+Ht),Dt.set(Pt,\".\"+et,Pt+\".\"+tr),\"null\"})}else if(qe in Ct){var Rt=Ct[qe];return Un(Rt,function(Bt,Dt){var yt=Bt.invoke(Dt,Rt),Pt=Bt.shared,ht=Pt.framebuffer,ur=Dt.def(ht,\".getFramebuffer(\",yt,\")\");Dt.set(ht,\".next\",ur);var br=Pt.context;return Dt.set(br,\".\"+Be,ur+\"?\"+ur+\".width:\"+br+\".\"+Ht),Dt.set(br,\".\"+et,ur+\"?\"+ur+\".height:\"+br+\".\"+tr),ur})}else return null}function ba(Ve,Qe,at){var Ct=Ve.static,Ot=Ve.dynamic;function Rt(yt){if(yt in Ct){var Pt=Ct[yt],ht=!0,ur=Pt.x|0,br=Pt.y|0,Ur,Di;return\"width\"in Pt?Ur=Pt.width|0:ht=!1,\"height\"in Pt?Di=Pt.height|0:ht=!1,new ei(!ht&&Qe&&Qe.thisDep,!ht&&Qe&&Qe.contextDep,!ht&&Qe&&Qe.propDep,function(gn,rn){var Ci=gn.shared.context,Bi=Ur;\"width\"in Pt||(Bi=rn.def(Ci,\".\",Be,\"-\",ur));var Gi=Di;return\"height\"in Pt||(Gi=rn.def(Ci,\".\",et,\"-\",br)),[ur,br,Bi,Gi]})}else if(yt in Ot){var fi=Ot[yt],Ti=Un(fi,function(gn,rn){var Ci=gn.invoke(rn,fi),Bi=gn.shared.context,Gi=rn.def(Ci,\".x|0\"),sn=rn.def(Ci,\".y|0\"),zn=rn.def('\"width\" in ',Ci,\"?\",Ci,\".width|0:\",\"(\",Bi,\".\",Be,\"-\",Gi,\")\"),Ja=rn.def('\"height\" in ',Ci,\"?\",Ci,\".height|0:\",\"(\",Bi,\".\",et,\"-\",sn,\")\");return[Gi,sn,zn,Ja]});return Qe&&(Ti.thisDep=Ti.thisDep||Qe.thisDep,Ti.contextDep=Ti.contextDep||Qe.contextDep,Ti.propDep=Ti.propDep||Qe.propDep),Ti}else return Qe?new ei(Qe.thisDep,Qe.contextDep,Qe.propDep,function(gn,rn){var Ci=gn.shared.context;return[0,0,rn.def(Ci,\".\",Be),rn.def(Ci,\".\",et)]}):null}var Bt=Rt(ee);if(Bt){var Dt=Bt;Bt=new ei(Bt.thisDep,Bt.contextDep,Bt.propDep,function(yt,Pt){var ht=Dt.append(yt,Pt),ur=yt.shared.context;return Pt.set(ur,\".\"+We,ht[2]),Pt.set(ur,\".\"+it,ht[3]),ht})}return{viewport:Bt,scissor_box:Rt(Q)}}function is(Ve,Qe){var at=Ve.static,Ct=typeof at[ot]==\"string\"&&typeof at[Xe]==\"string\";if(Ct){if(Object.keys(Qe.dynamic).length>0)return null;var Ot=Qe.static,Rt=Object.keys(Ot);if(Rt.length>0&&typeof Ot[Rt[0]]==\"number\"){for(var Bt=[],Dt=0;Dt<Rt.length;++Dt)Bt.push([Ot[Rt[Dt]]|0,Rt[Dt]]);return Bt}}return null}function Zs(Ve,Qe,at){var Ct=Ve.static,Ot=Ve.dynamic;function Rt(ht){if(ht in Ct){var ur=bt.id(Ct[ht]),br=En(function(){return ur});return br.id=ur,br}else if(ht in Ot){var Ur=Ot[ht];return Un(Ur,function(Di,fi){var Ti=Di.invoke(fi,Ur),gn=fi.def(Di.shared.strings,\".id(\",Ti,\")\");return gn})}return null}var Bt=Rt(ot),Dt=Rt(Xe),yt=null,Pt;return Ln(Bt)&&Ln(Dt)?(yt=Ei.program(Dt.id,Bt.id,null,at),Pt=En(function(ht,ur){return ht.link(yt)})):Pt=new ei(Bt&&Bt.thisDep||Dt&&Dt.thisDep,Bt&&Bt.contextDep||Dt&&Dt.contextDep,Bt&&Bt.propDep||Dt&&Dt.propDep,function(ht,ur){var br=ht.shared.shader,Ur;Bt?Ur=Bt.append(ht,ur):Ur=ur.def(br,\".\",ot);var Di;Dt?Di=Dt.append(ht,ur):Di=ur.def(br,\".\",Xe);var fi=br+\".program(\"+Di+\",\"+Ur;return ur.def(fi+\")\")}),{frag:Bt,vert:Dt,progVar:Pt,program:yt}}function Va(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={},Rt=!1;function Bt(){if(ve in at){var rn=at[ve];return rn!==null&&qi.getVAO(rn)===null&&(rn=qi.createVAO(rn)),Rt=!0,Ot.vao=rn,En(function(Bi){var Gi=qi.getVAO(rn);return Gi?Bi.link(Gi):\"null\"})}else if(ve in Ct){Rt=!0;var Ci=Ct[ve];return Un(Ci,function(Bi,Gi){var sn=Bi.invoke(Gi,Ci);return Gi.def(Bi.shared.vao+\".getVAO(\"+sn+\")\")})}return null}var Dt=Bt(),yt=!1;function Pt(){if(Tt in at){var rn=at[Tt];if(Ot.elements=rn,Ii(rn)){var Ci=Ot.elements=Nr.create(rn,!0);rn=Nr.getElements(Ci),yt=!0}else rn&&(rn=Nr.getElements(rn),yt=!0);var Bi=En(function(sn,zn){if(rn){var Ja=sn.link(rn);return sn.ELEMENTS=Ja,Ja}return sn.ELEMENTS=null,null});return Bi.value=rn,Bi}else if(Tt in Ct){yt=!0;var Gi=Ct[Tt];return Un(Gi,function(sn,zn){var Ja=sn.shared,co=Ja.isBufferArgs,ts=Ja.elements,so=sn.invoke(zn,Gi),Zo=zn.def(\"null\"),ms=zn.def(co,\"(\",so,\")\"),ou=sn.cond(ms).then(Zo,\"=\",ts,\".createStream(\",so,\");\").else(Zo,\"=\",ts,\".getElements(\",so,\");\");return zn.entry(ou),zn.exit(sn.cond(ms).then(ts,\".destroyStream(\",Zo,\");\")),sn.ELEMENTS=Zo,Zo})}else if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.elements+\".getElements(\"+sn.shared.vao+\".currentVAO.elements):null\")});return null}var ht=Pt();function ur(){if(Yt in at){var rn=at[Yt];return Ot.primitive=rn,En(function(Bi,Gi){return Sn[rn]})}else if(Yt in Ct){var Ci=Ct[Yt];return Un(Ci,function(Bi,Gi){var sn=Bi.constants.primTypes,zn=Bi.invoke(Gi,Ci);return Gi.def(sn,\"[\",zn,\"]\")})}else{if(yt)return Ln(ht)?ht.value?En(function(Bi,Gi){return Gi.def(Bi.ELEMENTS,\".primType\")}):En(function(){return Al}):new ei(ht.thisDep,ht.contextDep,ht.propDep,function(Bi,Gi){var sn=Bi.ELEMENTS;return Gi.def(sn,\"?\",sn,\".primType:\",Al)});if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(Bi,Gi){return Gi.def(Bi.shared.vao+\".currentVAO?\"+Bi.shared.vao+\".currentVAO.primitive:\"+Al)})}return null}function br(rn,Ci){if(rn in at){var Bi=at[rn]|0;return Ci?Ot.offset=Bi:Ot.instances=Bi,En(function(sn,zn){return Ci&&(sn.OFFSET=Bi),Bi})}else if(rn in Ct){var Gi=Ct[rn];return Un(Gi,function(sn,zn){var Ja=sn.invoke(zn,Gi);return Ci&&(sn.OFFSET=Ja),Ja})}else if(Ci){if(yt)return En(function(sn,zn){return sn.OFFSET=0,0});if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.vao+\".currentVAO.offset:0\")})}else if(Rt)return new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(sn,zn){return zn.def(sn.shared.vao+\".currentVAO?\"+sn.shared.vao+\".currentVAO.instances:-1\")});return null}var Ur=br(xr,!0);function Di(){if(Kt in at){var rn=at[Kt]|0;return Ot.count=rn,En(function(){return rn})}else if(Kt in Ct){var Ci=Ct[Kt];return Un(Ci,function(zn,Ja){var co=zn.invoke(Ja,Ci);return co})}else if(yt)if(Ln(ht)){if(ht)return Ur?new ei(Ur.thisDep,Ur.contextDep,Ur.propDep,function(zn,Ja){var co=Ja.def(zn.ELEMENTS,\".vertCount-\",zn.OFFSET);return co}):En(function(zn,Ja){return Ja.def(zn.ELEMENTS,\".vertCount\")});var Bi=En(function(){return-1});return Bi}else{var Gi=new ei(ht.thisDep||Ur.thisDep,ht.contextDep||Ur.contextDep,ht.propDep||Ur.propDep,function(zn,Ja){var co=zn.ELEMENTS;return zn.OFFSET?Ja.def(co,\"?\",co,\".vertCount-\",zn.OFFSET,\":-1\"):Ja.def(co,\"?\",co,\".vertCount:-1\")});return Gi}else if(Rt){var sn=new ei(Dt.thisDep,Dt.contextDep,Dt.propDep,function(zn,Ja){return Ja.def(zn.shared.vao,\".currentVAO?\",zn.shared.vao,\".currentVAO.count:-1\")});return sn}return null}var fi=ur(),Ti=Di(),gn=br(Ir,!1);return{elements:ht,primitive:fi,count:Ti,instances:gn,offset:Ur,vao:Dt,vaoActive:Rt,elementsActive:yt,static:Ot}}function Ml(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return hi.forEach(function(Rt){var Bt=Ji(Rt);function Dt(yt,Pt){if(Rt in at){var ht=yt(at[Rt]);Ot[Bt]=En(function(){return ht})}else if(Rt in Ct){var ur=Ct[Rt];Ot[Bt]=Un(ur,function(br,Ur){return Pt(br,Ur,br.invoke(Ur,ur))})}}switch(Rt){case Cu:case Ho:case ws:case Vc:case va:case B:case Uc:case Ac:case Ua:case rs:return Dt(function(yt){return yt},function(yt,Pt,ht){return ht});case no:return Dt(function(yt){return Zr[yt]},function(yt,Pt,ht){var ur=yt.constants.compareFuncs;return Pt.def(ur,\"[\",ht,\"]\")});case ys:return Dt(function(yt){return yt},function(yt,Pt,ht){var ur=Pt.def(\"+\",ht,\"[0]\"),br=Pt.def(\"+\",ht,\"[1]\");return[ur,br]});case Ls:return Dt(function(yt){var Pt=\"srcRGB\"in yt?yt.srcRGB:yt.src,ht=\"srcAlpha\"in yt?yt.srcAlpha:yt.src,ur=\"dstRGB\"in yt?yt.dstRGB:yt.dst,br=\"dstAlpha\"in yt?yt.dstAlpha:yt.dst;return[bi[Pt],bi[ur],bi[ht],bi[br]]},function(yt,Pt,ht){var ur=yt.constants.blendFuncs;function br(Ci,Bi){var Gi=Pt.def('\"',Ci,Bi,'\" in ',ht,\"?\",ht,\".\",Ci,Bi,\":\",ht,\".\",Ci);return Gi}var Ur=br(\"src\",\"RGB\"),Di=br(\"dst\",\"RGB\"),fi=Pt.def(ur,\"[\",Ur,\"]\"),Ti=Pt.def(ur,\"[\",br(\"src\",\"Alpha\"),\"]\"),gn=Pt.def(ur,\"[\",Di,\"]\"),rn=Pt.def(ur,\"[\",br(\"dst\",\"Alpha\"),\"]\");return[fi,gn,Ti,rn]});case Ws:return Dt(function(yt){if(typeof yt==\"string\")return[xi[yt],xi[yt]];if(typeof yt==\"object\")return[xi[yt.rgb],xi[yt.alpha]]},function(yt,Pt,ht){var ur=yt.constants.blendEquations,br=Pt.def(),Ur=Pt.def(),Di=yt.cond(\"typeof \",ht,'===\"string\"');return Di.then(br,\"=\",Ur,\"=\",ur,\"[\",ht,\"];\"),Di.else(br,\"=\",ur,\"[\",ht,\".rgb];\",Ur,\"=\",ur,\"[\",ht,\".alpha];\"),Pt(Di),[br,Ur]});case ml:return Dt(function(yt){return M(4,function(Pt){return+yt[Pt]})},function(yt,Pt,ht){return M(4,function(ur){return Pt.def(\"+\",ht,\"[\",ur,\"]\")})});case hc:return Dt(function(yt){return yt|0},function(yt,Pt,ht){return Pt.def(ht,\"|0\")});case Ku:return Dt(function(yt){var Pt=yt.cmp||\"keep\",ht=yt.ref||0,ur=\"mask\"in yt?yt.mask:-1;return[Zr[Pt],ht,ur]},function(yt,Pt,ht){var ur=yt.constants.compareFuncs,br=Pt.def('\"cmp\" in ',ht,\"?\",ur,\"[\",ht,\".cmp]\",\":\",nt),Ur=Pt.def(ht,\".ref|0\"),Di=Pt.def('\"mask\" in ',ht,\"?\",ht,\".mask|0:-1\");return[br,Ur,Di]});case ue:case w:return Dt(function(yt){var Pt=yt.fail||\"keep\",ht=yt.zfail||\"keep\",ur=yt.zpass||\"keep\";return[Rt===w?se:X,ai[Pt],ai[ht],ai[ur]]},function(yt,Pt,ht){var ur=yt.constants.stencilOps;function br(Ur){return Pt.def('\"',Ur,'\" in ',ht,\"?\",ur,\"[\",ht,\".\",Ur,\"]:\",nt)}return[Rt===w?se:X,br(\"fail\"),br(\"zfail\"),br(\"zpass\")]});case xu:return Dt(function(yt){var Pt=yt.factor|0,ht=yt.units|0;return[Pt,ht]},function(yt,Pt,ht){var ur=Pt.def(ht,\".factor|0\"),br=Pt.def(ht,\".units|0\");return[ur,br]});case Yu:return Dt(function(yt){var Pt=0;return yt===\"front\"?Pt=X:yt===\"back\"&&(Pt=se),Pt},function(yt,Pt,ht){return Pt.def(ht,'===\"front\"?',X,\":\",se)});case pu:return Dt(function(yt){return yt},function(yt,Pt,ht){return ht});case Nc:return Dt(function(yt){return gi[yt]},function(yt,Pt,ht){return Pt.def(ht+'===\"cw\"?'+Te+\":\"+Ne)});case $l:return Dt(function(yt){return yt.map(function(Pt){return!!Pt})},function(yt,Pt,ht){return M(4,function(ur){return\"!!\"+ht+\"[\"+ur+\"]\"})});case oo:return Dt(function(yt){var Pt=\"value\"in yt?yt.value:1,ht=!!yt.invert;return[Pt,ht]},function(yt,Pt,ht){var ur=Pt.def('\"value\" in ',ht,\"?+\",ht,\".value:1\"),br=Pt.def(\"!!\",ht,\".invert\");return[ur,br]})}}),Ot}function zo(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return Object.keys(at).forEach(function(Rt){var Bt=at[Rt],Dt;if(typeof Bt==\"number\"||typeof Bt==\"boolean\")Dt=En(function(){return Bt});else if(typeof Bt==\"function\"){var yt=Bt._reglType;yt===\"texture2d\"||yt===\"textureCube\"?Dt=En(function(Pt){return Pt.link(Bt)}):(yt===\"framebuffer\"||yt===\"framebufferCube\")&&(Dt=En(function(Pt){return Pt.link(Bt.color[0])}))}else Mn(Bt)&&(Dt=En(function(Pt){var ht=Pt.global.def(\"[\",M(Bt.length,function(ur){return Bt[ur]}),\"]\");return ht}));Dt.value=Bt,Ot[Rt]=Dt}),Object.keys(Ct).forEach(function(Rt){var Bt=Ct[Rt];Ot[Rt]=Un(Bt,function(Dt,yt){return Dt.invoke(yt,Bt)})}),Ot}function Qs(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic,Ot={};return Object.keys(at).forEach(function(Rt){var Bt=at[Rt],Dt=bt.id(Rt),yt=new Yr;if(Ii(Bt))yt.state=La,yt.buffer=jr.getBuffer(jr.create(Bt,Sr,!1,!0)),yt.type=0;else{var Pt=jr.getBuffer(Bt);if(Pt)yt.state=La,yt.buffer=Pt,yt.type=0;else if(\"constant\"in Bt){var ht=Bt.constant;yt.buffer=\"null\",yt.state=Na,typeof ht==\"number\"?yt.x=ht:Ca.forEach(function(gn,rn){rn<ht.length&&(yt[gn]=ht[rn])})}else{Ii(Bt.buffer)?Pt=jr.getBuffer(jr.create(Bt.buffer,Sr,!1,!0)):Pt=jr.getBuffer(Bt.buffer);var ur=Bt.offset|0,br=Bt.stride|0,Ur=Bt.size|0,Di=!!Bt.normalized,fi=0;\"type\"in Bt&&(fi=ji[Bt.type]);var Ti=Bt.divisor|0;yt.buffer=Pt,yt.state=La,yt.size=Ur,yt.normalized=Di,yt.type=fi||Pt.dtype,yt.offset=ur,yt.stride=br,yt.divisor=Ti}}Ot[Rt]=En(function(gn,rn){var Ci=gn.attribCache;if(Dt in Ci)return Ci[Dt];var Bi={isStream:!1};return Object.keys(yt).forEach(function(Gi){Bi[Gi]=yt[Gi]}),yt.buffer&&(Bi.buffer=gn.link(yt.buffer),Bi.type=Bi.type||Bi.buffer+\".dtype\"),Ci[Dt]=Bi,Bi})}),Object.keys(Ct).forEach(function(Rt){var Bt=Ct[Rt];function Dt(yt,Pt){var ht=yt.invoke(Pt,Bt),ur=yt.shared,br=yt.constants,Ur=ur.isBufferArgs,Di=ur.buffer,fi={isStream:Pt.def(!1)},Ti=new Yr;Ti.state=La,Object.keys(Ti).forEach(function(Bi){fi[Bi]=Pt.def(\"\"+Ti[Bi])});var gn=fi.buffer,rn=fi.type;Pt(\"if(\",Ur,\"(\",ht,\")){\",fi.isStream,\"=true;\",gn,\"=\",Di,\".createStream(\",Sr,\",\",ht,\");\",rn,\"=\",gn,\".dtype;\",\"}else{\",gn,\"=\",Di,\".getBuffer(\",ht,\");\",\"if(\",gn,\"){\",rn,\"=\",gn,\".dtype;\",'}else if(\"constant\" in ',ht,\"){\",fi.state,\"=\",Na,\";\",\"if(typeof \"+ht+'.constant === \"number\"){',fi[Ca[0]],\"=\",ht,\".constant;\",Ca.slice(1).map(function(Bi){return fi[Bi]}).join(\"=\"),\"=0;\",\"}else{\",Ca.map(function(Bi,Gi){return fi[Bi]+\"=\"+ht+\".constant.length>\"+Gi+\"?\"+ht+\".constant[\"+Gi+\"]:0;\"}).join(\"\"),\"}}else{\",\"if(\",Ur,\"(\",ht,\".buffer)){\",gn,\"=\",Di,\".createStream(\",Sr,\",\",ht,\".buffer);\",\"}else{\",gn,\"=\",Di,\".getBuffer(\",ht,\".buffer);\",\"}\",rn,'=\"type\" in ',ht,\"?\",br.glTypes,\"[\",ht,\".type]:\",gn,\".dtype;\",fi.normalized,\"=!!\",ht,\".normalized;\");function Ci(Bi){Pt(fi[Bi],\"=\",ht,\".\",Bi,\"|0;\")}return Ci(\"size\"),Ci(\"offset\"),Ci(\"stride\"),Ci(\"divisor\"),Pt(\"}}\"),Pt.exit(\"if(\",fi.isStream,\"){\",Di,\".destroyStream(\",gn,\");\",\"}\"),fi}Ot[Rt]=Un(Bt,Dt)}),Ot}function al(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct={};return Object.keys(Qe).forEach(function(Ot){var Rt=Qe[Ot];Ct[Ot]=En(function(Bt,Dt){return typeof Rt==\"number\"||typeof Rt==\"boolean\"?\"\"+Rt:Bt.link(Rt)})}),Object.keys(at).forEach(function(Ot){var Rt=at[Ot];Ct[Ot]=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}),Ct}function Vl(Ve,Qe,at,Ct,Ot){var Rt=Ve.static,Bt=Ve.dynamic,Dt=is(Ve,Qe),yt=oa(Ve,Ot),Pt=ba(Ve,yt,Ot),ht=Va(Ve,Ot),ur=Ml(Ve,Ot),br=Zs(Ve,Ot,Dt);function Ur(Ci){var Bi=Pt[Ci];Bi&&(ur[Ci]=Bi)}Ur(ee),Ur(Ji(Q));var Di=Object.keys(ur).length>0,fi={framebuffer:yt,draw:ht,shader:br,state:ur,dirty:Di,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(fi.profile=ta(Ve,Ot),fi.uniforms=zo(at,Ot),fi.drawVAO=fi.scopeVAO=ht.vao,!fi.drawVAO&&br.program&&!Dt&&zt.angle_instanced_arrays&&ht.static.elements){var Ti=!0,gn=br.program.attributes.map(function(Ci){var Bi=Qe.static[Ci];return Ti=Ti&&!!Bi,Bi});if(Ti&&gn.length>0){var rn=qi.getVAO(qi.createVAO({attributes:gn,elements:ht.static.elements}));fi.drawVAO=new ei(null,null,null,function(Ci,Bi){return Ci.link(rn)}),fi.useVAO=!0}}return Dt?fi.useVAO=!0:fi.attributes=Qs(Qe,Ot),fi.context=al(Ct,Ot),fi}function ss(Ve,Qe,at){var Ct=Ve.shared,Ot=Ct.context,Rt=Ve.scope();Object.keys(at).forEach(function(Bt){Qe.save(Ot,\".\"+Bt);var Dt=at[Bt],yt=Dt.append(Ve,Qe);Array.isArray(yt)?Rt(Ot,\".\",Bt,\"=[\",yt.join(),\"];\"):Rt(Ot,\".\",Bt,\"=\",yt,\";\")}),Qe(Rt)}function Vs(Ve,Qe,at,Ct){var Ot=Ve.shared,Rt=Ot.gl,Bt=Ot.framebuffer,Dt;ci&&(Dt=Qe.def(Ot.extensions,\".webgl_draw_buffers\"));var yt=Ve.constants,Pt=yt.drawBuffer,ht=yt.backBuffer,ur;at?ur=at.append(Ve,Qe):ur=Qe.def(Bt,\".next\"),Ct||Qe(\"if(\",ur,\"!==\",Bt,\".cur){\"),Qe(\"if(\",ur,\"){\",Rt,\".bindFramebuffer(\",qr,\",\",ur,\".framebuffer);\"),ci&&Qe(Dt,\".drawBuffersWEBGL(\",Pt,\"[\",ur,\".colorAttachments.length]);\"),Qe(\"}else{\",Rt,\".bindFramebuffer(\",qr,\",null);\"),ci&&Qe(Dt,\".drawBuffersWEBGL(\",ht,\");\"),Qe(\"}\",Bt,\".cur=\",ur,\";\"),Ct||Qe(\"}\")}function Ys(Ve,Qe,at){var Ct=Ve.shared,Ot=Ct.gl,Rt=Ve.current,Bt=Ve.next,Dt=Ct.current,yt=Ct.next,Pt=Ve.cond(Dt,\".dirty\");hi.forEach(function(ht){var ur=Ji(ht);if(!(ur in at.state)){var br,Ur;if(ur in Bt){br=Bt[ur],Ur=Rt[ur];var Di=M(Zi[ur].length,function(Ti){return Pt.def(br,\"[\",Ti,\"]\")});Pt(Ve.cond(Di.map(function(Ti,gn){return Ti+\"!==\"+Ur+\"[\"+gn+\"]\"}).join(\"||\")).then(Ot,\".\",mn[ur],\"(\",Di,\");\",Di.map(function(Ti,gn){return Ur+\"[\"+gn+\"]=\"+Ti}).join(\";\"),\";\"))}else{br=Pt.def(yt,\".\",ur);var fi=Ve.cond(br,\"!==\",Dt,\".\",ur);Pt(fi),ur in li?fi(Ve.cond(br).then(Ot,\".enable(\",li[ur],\");\").else(Ot,\".disable(\",li[ur],\");\"),Dt,\".\",ur,\"=\",br,\";\"):fi(Ot,\".\",mn[ur],\"(\",br,\");\",Dt,\".\",ur,\"=\",br,\";\")}}}),Object.keys(at.state).length===0&&Pt(Dt,\".dirty=false;\"),Qe(Pt)}function wa(Ve,Qe,at,Ct){var Ot=Ve.shared,Rt=Ve.current,Bt=Ot.current,Dt=Ot.gl,yt;Si(Object.keys(at)).forEach(function(Pt){var ht=at[Pt];if(!(Ct&&!Ct(ht))){var ur=ht.append(Ve,Qe);if(li[Pt]){var br=li[Pt];Ln(ht)?(yt=Ve.link(ur,{stable:!0}),Qe(Ve.cond(yt).then(Dt,\".enable(\",br,\");\").else(Dt,\".disable(\",br,\");\")),Qe(Bt,\".\",Pt,\"=\",yt,\";\")):(Qe(Ve.cond(ur).then(Dt,\".enable(\",br,\");\").else(Dt,\".disable(\",br,\");\")),Qe(Bt,\".\",Pt,\"=\",ur,\";\"))}else if(Mn(ur)){var Ur=Rt[Pt];Qe(Dt,\".\",mn[Pt],\"(\",ur,\");\",ur.map(function(Di,fi){return Ur+\"[\"+fi+\"]=\"+Di}).join(\";\"),\";\")}else Ln(ht)?(yt=Ve.link(ur,{stable:!0}),Qe(Dt,\".\",mn[Pt],\"(\",yt,\");\",Bt,\".\",Pt,\"=\",yt,\";\")):Qe(Dt,\".\",mn[Pt],\"(\",ur,\");\",Bt,\".\",Pt,\"=\",ur,\";\")}})}function ol(Ve,Qe){Ri&&(Ve.instancing=Qe.def(Ve.shared.extensions,\".angle_instanced_arrays\"))}function io(Ve,Qe,at,Ct,Ot){var Rt=Ve.shared,Bt=Ve.stats,Dt=Rt.current,yt=Rt.timer,Pt=at.profile;function ht(){return typeof performance==\"undefined\"?\"Date.now()\":\"performance.now()\"}var ur,br;function Ur(Ci){ur=Qe.def(),Ci(ur,\"=\",ht(),\";\"),typeof Ot==\"string\"?Ci(Bt,\".count+=\",Ot,\";\"):Ci(Bt,\".count++;\"),Wi&&(Ct?(br=Qe.def(),Ci(br,\"=\",yt,\".getNumPendingQueries();\")):Ci(yt,\".beginQuery(\",Bt,\");\"))}function Di(Ci){Ci(Bt,\".cpuTime+=\",ht(),\"-\",ur,\";\"),Wi&&(Ct?Ci(yt,\".pushScopeStats(\",br,\",\",yt,\".getNumPendingQueries(),\",Bt,\");\"):Ci(yt,\".endQuery();\"))}function fi(Ci){var Bi=Qe.def(Dt,\".profile\");Qe(Dt,\".profile=\",Ci,\";\"),Qe.exit(Dt,\".profile=\",Bi,\";\")}var Ti;if(Pt){if(Ln(Pt)){Pt.enable?(Ur(Qe),Di(Qe.exit),fi(\"true\")):fi(\"false\");return}Ti=Pt.append(Ve,Qe),fi(Ti)}else Ti=Qe.def(Dt,\".profile\");var gn=Ve.block();Ur(gn),Qe(\"if(\",Ti,\"){\",gn,\"}\");var rn=Ve.block();Di(rn),Qe.exit(\"if(\",Ti,\"){\",rn,\"}\")}function Y(Ve,Qe,at,Ct,Ot){var Rt=Ve.shared;function Bt(yt){switch(yt){case Co:case Ps:case hl:return 2;case Qa:case Ts:case Ul:return 3;case mo:case wo:case Lu:return 4;default:return 1}}function Dt(yt,Pt,ht){var ur=Rt.gl,br=Qe.def(yt,\".location\"),Ur=Qe.def(Rt.attributes,\"[\",br,\"]\"),Di=ht.state,fi=ht.buffer,Ti=[ht.x,ht.y,ht.z,ht.w],gn=[\"buffer\",\"normalized\",\"offset\",\"stride\"];function rn(){Qe(\"if(!\",Ur,\".buffer){\",ur,\".enableVertexAttribArray(\",br,\");}\");var Bi=ht.type,Gi;if(ht.size?Gi=Qe.def(ht.size,\"||\",Pt):Gi=Pt,Qe(\"if(\",Ur,\".type!==\",Bi,\"||\",Ur,\".size!==\",Gi,\"||\",gn.map(function(zn){return Ur+\".\"+zn+\"!==\"+ht[zn]}).join(\"||\"),\"){\",ur,\".bindBuffer(\",Sr,\",\",fi,\".buffer);\",ur,\".vertexAttribPointer(\",[br,Gi,Bi,ht.normalized,ht.stride,ht.offset],\");\",Ur,\".type=\",Bi,\";\",Ur,\".size=\",Gi,\";\",gn.map(function(zn){return Ur+\".\"+zn+\"=\"+ht[zn]+\";\"}).join(\"\"),\"}\"),Ri){var sn=ht.divisor;Qe(\"if(\",Ur,\".divisor!==\",sn,\"){\",Ve.instancing,\".vertexAttribDivisorANGLE(\",[br,sn],\");\",Ur,\".divisor=\",sn,\";}\")}}function Ci(){Qe(\"if(\",Ur,\".buffer){\",ur,\".disableVertexAttribArray(\",br,\");\",Ur,\".buffer=null;\",\"}if(\",Ca.map(function(Bi,Gi){return Ur+\".\"+Bi+\"!==\"+Ti[Gi]}).join(\"||\"),\"){\",ur,\".vertexAttrib4f(\",br,\",\",Ti,\");\",Ca.map(function(Bi,Gi){return Ur+\".\"+Bi+\"=\"+Ti[Gi]+\";\"}).join(\"\"),\"}\")}Di===La?rn():Di===Na?Ci():(Qe(\"if(\",Di,\"===\",La,\"){\"),rn(),Qe(\"}else{\"),Ci(),Qe(\"}\"))}Ct.forEach(function(yt){var Pt=yt.name,ht=at.attributes[Pt],ur;if(ht){if(!Ot(ht))return;ur=ht.append(Ve,Qe)}else{if(!Ot(ia))return;var br=Ve.scopeAttrib(Pt);ur={},Object.keys(new Yr).forEach(function(Ur){ur[Ur]=Qe.def(br,\".\",Ur)})}Dt(Ve.link(yt),Bt(yt.info.type),ur)})}function D(Ve,Qe,at,Ct,Ot,Rt){for(var Bt=Ve.shared,Dt=Bt.gl,yt,Pt=0;Pt<Ct.length;++Pt){var ht=Ct[Pt],ur=ht.name,br=ht.info.type,Ur=at.uniforms[ur],Di=Ve.link(ht),fi=Di+\".location\",Ti;if(Ur){if(!Ot(Ur))continue;if(Ln(Ur)){var gn=Ur.value;if(br===dc||br===Tl){var rn=Ve.link(gn._texture||gn.color[0]._texture);Qe(Dt,\".uniform1i(\",fi,\",\",rn+\".bind());\"),Qe.exit(rn,\".unbind();\")}else if(br===au||br===Js||br===Ql){var Ci=Ve.global.def(\"new Float32Array([\"+Array.prototype.slice.call(gn)+\"])\"),Bi=2;br===Js?Bi=3:br===Ql&&(Bi=4),Qe(Dt,\".uniformMatrix\",Bi,\"fv(\",fi,\",false,\",Ci,\");\")}else{switch(br){case $a:yt=\"1f\";break;case Co:yt=\"2f\";break;case Qa:yt=\"3f\";break;case mo:yt=\"4f\";break;case To:yt=\"1i\";break;case Bo:yt=\"1i\";break;case hl:yt=\"2i\";break;case Ps:yt=\"2i\";break;case Ul:yt=\"3i\";break;case Ts:yt=\"3i\";break;case Lu:yt=\"4i\";break;case wo:yt=\"4i\";break}Qe(Dt,\".uniform\",yt,\"(\",fi,\",\",Mn(gn)?Array.prototype.slice.call(gn):gn,\");\")}continue}else 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a=TNe.extendFlat({},i.matrixOptions,i.viewOpts);i.matrix.update(a,null)}}});var ENe=ye((C_r,MNe)=>{\"use strict\";var MVt=qa(),EVt=fV();MNe.exports={moduleType:\"trace\",name:\"splom\",categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:dK(),supplyDefaults:WBe(),colorbar:$d(),calc:$Be(),plot:cNe(),hoverPoints:gNe().hoverPoints,selectPoints:wNe(),editStyle:SNe(),meta:{}};MVt.register(EVt)});var RNe=ye((L_r,INe)=>{\"use strict\";var kVt=VY(),CVt=qa(),LVt=Sz(),PVt=Id().getModuleCalcData,gx=ph(),kNe=hf().getFromId,CNe=ho().shouldShowZeroLine,LNe=\"splom\",PNe={};function IVt(e){var t=e._fullLayout,r=CVt.getModule(LNe),n=PVt(e.calcdata,r)[0],i=LVt(e,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"],PNe);i&&(t._hasOnlyLargeSploms&&xK(e),r.plot(e,{},n))}function RVt(e){var t=e.calcdata,r=e._fullLayout;r._hasOnlyLargeSploms&&xK(e);for(var n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=r._splomScenes[a.uid];a.type===\"splom\"&&o&&o.matrix&&DVt(e,a,o)}}function DVt(e,t,r){for(var n=r.matrixOptions.data.length,i=t._visibleDims,a=r.viewOpts.ranges=new Array(n),o=0;o<i.length;o++){var s=i[o],l=a[o]=new Array(4),u=kNe(e,t._diag[s][0]);u&&(l[0]=u.r2l(u.range[0]),l[2]=u.r2l(u.range[1]));var c=kNe(e,t._diag[s][1]);c&&(l[1]=c.r2l(c.range[0]),l[3]=c.r2l(c.range[1]))}r.selectBatch.length||r.unselectBatch.length?r.matrix.update({ranges:a},{ranges:a}):r.matrix.update({ranges:a})}function xK(e){var t=e._fullLayout,r=t._glcanvas.data()[0].regl,n=t._splomGrid;n||(n=t._splomGrid=kVt(r)),n.update(FVt(e))}function FVt(e){var t=e._context.plotGlPixelRatio,r=e._fullLayout,n=r._size,i=[0,0,r.width*t,r.height*t],a={},o;function s(x,C,M,g,P,T){M*=t,g*=t,P*=t,T*=t;var z=C[x+\"color\"],O=C[x+\"width\"],V=String(z+O);V in a?a[V].data.push(NaN,NaN,M,g,P,T):a[V]={data:[M,g,P,T],join:\"rect\",thickness:O*t,color:z,viewport:i,range:i,overlay:!1}}for(o in r._splomSubplots){var 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OVt=Tu(),bK=Rd(),wK=ec(),qVt=Cc().attributes,Dz=Ao().extendFlat,BVt=vl().templatedArray;BNe.exports={domain:qVt({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:wK({editType:\"plot\"}),tickfont:wK({autoShadowDflt:!0,editType:\"plot\"}),rangefont:wK({editType:\"plot\"}),dimensions:BVt(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:Dz({},bK.tickvals,{editType:\"plot\"}),ticktext:Dz({},bK.ticktext,{editType:\"plot\"}),tickformat:Dz({},bK.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:Dz({editType:\"calc\"},OVt(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"})),unselected:{line:{color:{valType:\"color\",dflt:\"#7f7f7f\",editType:\"plot\"},opacity:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"plot\"},editType:\"plot\"},editType:\"plot\"}}});var Pk=ye((D_r,NNe)=>{\"use 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Jm=ye((F_r,VNe)=>{\"use strict\";var NVt=GS();function UNe(e){return[e]}VNe.exports={keyFun:function(e){return e.key},repeat:UNe,descend:NVt,wrap:UNe,unwrap:function(e){return e[0]}}});var MK=ye((z_r,QNe)=>{\"use strict\";var bh=Pk(),em=Oa(),UVt=Jm().keyFun,Fz=Jm().repeat,_5=Dr().sorterAsc,VVt=Dr().strTranslate,GNe=bh.bar.snapRatio;function HNe(e,t){return e*(1-GNe)+t*GNe}var jNe=bh.bar.snapClose;function GVt(e,t){return e*(1-jNe)+t*jNe}function Oz(e,t,r,n){if(HVt(r,n))return r;var i=e?-1:1,a=0,o=t.length-1;if(i<0){var s=a;a=o,o=s}for(var l=t[a],u=l,c=a;i*c<i*o;c+=i){var f=c+i,h=t[f];if(i*r<i*GVt(l,h))return HNe(l,u);if(i*r<i*h||f===o)return HNe(h,l);u=l,l=h}}function HVt(e,t){for(var r=0;r<t.length;r++)if(e>=t[r][0]&&e<=t[r][1])return!0;return!1}function jVt(e){e.attr(\"x\",-bh.bar.captureWidth/2).attr(\"width\",bh.bar.captureWidth)}function WVt(e){e.attr(\"visibility\",\"visible\").style(\"visibility\",\"visible\").attr(\"fill\",\"yellow\").attr(\"opacity\",0)}function XVt(e){if(!e.brush.filterSpecified)return\"0,\"+e.height;for(var t=WNe(e.brush.filter.getConsolidated(),e.height),r=[0],n,i,a,o=t.length?t[0][0]:null,s=0;s<t.length;s++)n=t[s],i=n[1]-n[0],r.push(o),r.push(i),a=s+1,a<t.length&&(o=t[a][0]-n[1]);return r.push(e.height),r}function WNe(e,t){return e.map(function(r){return r.map(function(n){return Math.max(0,n*t)}).sort(_5)})}function ZVt(e,t){var r=bh.bar.handleHeight;if(!(t>e[1]+r||t<e[0]-r))return t>=.9*e[1]+.1*e[0]?\"n\":t<=.9*e[0]+.1*e[1]?\"s\":\"ns\"}function XNe(){em.select(document.body).style(\"cursor\",null)}function SK(e){e.attr(\"stroke-dasharray\",XVt)}function zz(e,t){var r=em.select(e).selectAll(\".highlight, .highlight-shadow\"),n=t?r.transition().duration(bh.bar.snapDuration).each(\"end\",t):r;SK(n)}function ZNe(e,t){var r=e.brush,n=r.filterSpecified,i=NaN,a={},o;if(n){var s=e.height,l=r.filter.getConsolidated(),u=WNe(l,s),c=NaN,f=NaN,h=NaN;for(o=0;o<=u.length;o++){var d=u[o];if(d&&d[0]<=t&&t<=d[1]){c=o;break}else 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r=t.height-em.mouse(e)[1]-2*bh.verticalPadding,n=ZNe(t,r),i=\"crosshair\";n.clickableOrdinalRange?i=\"pointer\":n.region&&(i=n.region+\"-resize\"),em.select(document.body).style(\"cursor\",i)}function JVt(e){e.on(\"mousemove\",function(t){em.event.preventDefault(),t.parent.inBrushDrag||KNe(this,t)}).on(\"mouseleave\",function(t){t.parent.inBrushDrag||XNe()}).call(em.behavior.drag().on(\"dragstart\",function(t){YVt(this,t)}).on(\"drag\",function(t){YNe(this,t)}).on(\"dragend\",function(t){KVt(this,t)}))}function JNe(e,t){return e[0]-t[0]}function $Vt(e,t,r){var n=r._context.staticPlot,i=e.selectAll(\".background\").data(Fz);i.enter().append(\"rect\").classed(\"background\",!0).call(jVt).call(WVt).style(\"pointer-events\",n?\"none\":\"auto\").attr(\"transform\",VVt(0,bh.verticalPadding)),i.call(JVt).attr(\"height\",function(s){return s.height-bh.verticalPadding});var a=e.selectAll(\".highlight-shadow\").data(Fz);a.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-bh.bar.width/2).attr(\"stroke-width\",bh.bar.width+bh.bar.strokeWidth).attr(\"stroke\",t).attr(\"opacity\",bh.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),a.attr(\"y1\",function(s){return s.height}).call(SK);var o=e.selectAll(\".highlight\").data(Fz);o.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-bh.bar.width/2).attr(\"stroke-width\",bh.bar.width-bh.bar.strokeWidth).attr(\"stroke\",bh.bar.fillColor).attr(\"opacity\",bh.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),o.attr(\"y1\",function(s){return s.height}).call(SK)}function QVt(e,t,r){var n=e.selectAll(\".\"+bh.cn.axisBrush).data(Fz,UVt);n.enter().append(\"g\").classed(bh.cn.axisBrush,!0),$Vt(n,t,r)}function eGt(e){return e.svgBrush.extent.map(function(t){return t.slice()})}function AK(e){e.filterSpecified=!1,e.svgBrush.extent=[[-1/0,1/0]]}function tGt(e){return function(r){var n=r.brush,i=eGt(n),a=i.slice();n.filter.set(a),e()}}function $Ne(e){for(var t=e.slice(),r=[],n,i=t.shift();i;){for(n=i.slice();(i=t.shift())&&i[0]<=n[1];)n[1]=Math.max(n[1],i[1]);r.push(n)}return r.length===1&&r[0][0]>r[0][1]&&(r=[]),r}function rGt(){var e=[],t,r;return{set:function(n){e=n.map(function(i){return i.slice().sort(_5)}).sort(JNe),e.length===1&&e[0][0]===-1/0&&e[0][1]===1/0&&(e=[[0,-1]]),t=$Ne(e),r=e.reduce(function(i,a){return[Math.min(i[0],a[0]),Math.max(i[1],a[1])]},[1/0,-1/0])},get:function(){return e.slice()},getConsolidated:function(){return t},getBounds:function(){return r}}}function iGt(e,t,r,n,i,a){var o=rGt();return o.set(r),{filter:o,filterSpecified:t,svgBrush:{extent:[],brushStartCallback:n,brushCallback:tGt(i),brushEndCallback:a}}}function nGt(e,t){if(Array.isArray(e[0])?(e=e.map(function(n){return n.sort(_5)}),t.multiselect?e=$Ne(e.sort(JNe)):e=[e[0]]):e=[e.sort(_5)],t.tickvals){var r=t.tickvals.slice().sort(_5);if(e=e.map(function(n){var 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vOutside(p[0], lo[0], hi[0]) ||\",\"        vOutside(p[1], lo[1], hi[1]) ||\",\"        vOutside(p[2], lo[2], hi[2]) ||\",\"        vOutside(p[3], lo[3], hi[3])\",\"    );\",\"}\",\"\",\"bool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    return mOutside(A, loA, hiA) ||\",\"           mOutside(B, loB, hiB) ||\",\"           mOutside(C, loC, hiC) ||\",\"           mOutside(D, loD, hiD);\",\"}\",\"\",\"bool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    mat4 pnts[4];\",\"    pnts[0] = A;\",\"    pnts[1] = B;\",\"    pnts[2] = C;\",\"    pnts[3] = D;\",\"\",\"    for(int i = 0; i < 4; ++i) {\",\"        for(int j = 0; j < 4; ++j) {\",\"            for(int k = 0; k < 4; ++k) {\",\"                if(0 == iMod(\",\"                    int(255.0 * texture2D(maskTexture,\",\"                        vec2(\",\"                            (float(i * 2 + j / 2) + 0.5) / 8.0,\",\"                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\",\"                        ))[3]\",\"                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\",\"                    2\",\"                )) return true;\",\"            }\",\"        }\",\"    }\",\"    return false;\",\"}\",\"\",\"vec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\",\"    float x = 0.5 * sign(v) + 0.5;\",\"    float y = axisY(x, A, B, C, D);\",\"    float z = 1.0 - abs(v);\",\"\",\"    z += isContext ? 0.0 : 2.0 * float(\",\"        outsideBoundingBox(A, B, C, D) ||\",\"        outsideRasterMask(A, B, C, D)\",\"    );\",\"\",\"    return vec4(\",\"        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\",\"        z,\",\"        1.0\",\"    );\",\"}\",\"\",\"void main() {\",\"    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\",\"    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\",\"    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\",\"    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\",\"\",\"    float v = colors[3];\",\"\",\"    gl_Position = position(isContext, v, A, B, C, D);\",\"\",\"    fragColor =\",\"        isContext ? vec4(contextColor) :\",\"        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\",\"}\"].join(`\n",
+       "`),xGt=[\"precision highp float;\",\"\",\"varying vec4 fragColor;\",\"\",\"void main() {\",\"    gl_FragColor = fragColor;\",\"}\"].join(`\n",
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b=e.lines.canvasOverdrag*d,p=e.domain,k=e.canvasWidth*d,E=e.canvasHeight*d,S=e.pad.l*d,L=e.pad.b*d,x=e.layoutHeight*d,C=e.layoutWidth*d,M=e.deselectedLines.color,g=e.deselectedLines.opacity,P=mUe.extendFlat({key:c,resolution:[k,E],viewBoxPos:[o+b,s],viewBoxSize:[l,u],i0:i,i1:a,dim0A:v[0].slice(0,16),dim0B:v[0].slice(16,32),dim0C:v[0].slice(32,48),dim0D:v[0].slice(48,64),dim1A:v[1].slice(0,16),dim1B:v[1].slice(16,32),dim1C:v[1].slice(32,48),dim1D:v[1].slice(48,64),drwLayer:f,contextColor:[M[0]/255,M[1]/255,M[2]/255,g!==\"auto\"?M[3]*g:Math.max(1/255,Math.pow(1/e.lines.color.length,1/3))],scissorX:(n===t?0:o+b)+(S-b)+C*p.x[0],scissorWidth:(n===r?k-o+b:l+.5)+(n===t?o+b:0),scissorY:s+L+x*p.y[0],scissorHeight:u,viewportX:S-b+C*p.x[0],viewportY:L+x*p.y[0],viewportWidth:k,viewportHeight:E},h);return P}function gUe(e){var t=Nz-1,r=Math.max(0,Math.floor(e[0]*t),0),n=Math.min(t,Math.ceil(e[1]*t),t);return[Math.min(r,n),Math.max(r,n)]}xUe.exports=function(e,t){var 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O.val-V.val}if(RK(x)&&x.length){l1.isTypedArray(x)&&(x=Array.from(x)),C=h.ticktext,!RK(C)||!C.length?C=x.map(EUe(h.tickformat)):C.length>x.length?C=C.slice(0,x.length):x.length>C.length&&(x=x.slice(0,C.length));for(var P=1;P<x.length;P++)if(x[P]<x[P-1]){for(var T=x.map(M).sort(g),z=0;z<x.length;z++)x[z]=T[z].val,C[z]=T[z].text;break}}else x=void 0;return L=x5.convertTypedArray(L),{key:b,label:h.label,tickFormat:h.tickformat,tickvals:x,ticktext:C,ordinal:x5.isOrdinal(h),multiselect:h.multiselect,xIndex:d,crossfilterDimensionIndex:d,visibleIndex:h._index,height:i,values:L,paddedUnitValues:L.map(v),unitTickvals:x&&x.map(v),xScale:s,x:s(d),canvasX:s(d)*o,unitToPaddedPx:u,domainScale:FGt(i,Dl.verticalPadding,h,x,C),ordinalScale:qGt(h),parent:c,model:r,brush:PUe.makeBrush(e,k,E,function(){e.linePickActive(!1)},S,function(O){if(c.focusLayer.render(c.panels,!0),c.pickLayer&&c.pickLayer.render(c.panels,!0),e.linePickActive(!0),t&&t.filterChanged){var V=v.invert,G=O.map(function(Z){return 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p=b.selectAll(\".\"+Dl.cn.parcoordsControlView).data(Qm,tg);p.enter().append(\"g\").classed(Dl.cn.parcoordsControlView,!0),p.attr(\"transform\",function(z){return $m(z.model.pad.l,z.model.pad.t)});var k=p.selectAll(\".\"+Dl.cn.yAxis).data(function(z){return z.dimensions},tg);k.enter().append(\"g\").classed(Dl.cn.yAxis,!0),p.each(function(z){DK(k,z,u)}),d.each(function(z){if(z.viewModel){!z.lineLayer||i?z.lineLayer=RGt(this,z):z.lineLayer.update(z),(z.key||z.key===0)&&(z.viewModel[z.key]=z.lineLayer);var O=!z.context||i;z.lineLayer.render(z.viewModel.panels,O)}}),k.attr(\"transform\",function(z){return $m(z.xScale(z.xIndex),0)}),k.call(Bd.behavior.drag().origin(function(z){return z}).on(\"drag\",function(z){var O=z.parent;f.linePickActive(!1),z.x=Math.max(-Dl.overdrag,Math.min(z.model.width+Dl.overdrag,Bd.event.x)),z.canvasX=z.x*z.model.canvasPixelRatio,k.sort(function(V,G){return V.x-G.x}).each(function(V,G){V.xIndex=G,V.x=z===V?V.x:V.xScale(V.xIndex),V.canvasX=V.x*V.model.canvasPixelRatio}),DK(k,O,u),k.filter(function(V){return Math.abs(z.xIndex-V.xIndex)!==0}).attr(\"transform\",function(V){return $m(V.xScale(V.xIndex),0)}),Bd.select(this).attr(\"transform\",$m(z.x,0)),k.each(function(V,G,Z){Z===z.parent.key&&(O.dimensions[G]=V)}),O.contextLayer&&O.contextLayer.render(O.panels,!1,!FK(O)),O.focusLayer.render&&O.focusLayer.render(O.panels)}).on(\"dragend\",function(z){var O=z.parent;z.x=z.xScale(z.xIndex),z.canvasX=z.x*z.model.canvasPixelRatio,DK(k,O,u),Bd.select(this).attr(\"transform\",function(V){return $m(V.x,0)}),O.contextLayer&&O.contextLayer.render(O.panels,!1,!FK(O)),O.focusLayer&&O.focusLayer.render(O.panels),O.pickLayer&&O.pickLayer.render(O.panels,!0),f.linePickActive(!0),i&&i.axesMoved&&i.axesMoved(O.key,O.dimensions.map(function(V){return V.crossfilterDimensionIndex}))})),k.exit().remove();var E=k.selectAll(\".\"+Dl.cn.axisOverlays).data(Qm,tg);E.enter().append(\"g\").classed(Dl.cn.axisOverlays,!0),E.selectAll(\".\"+Dl.cn.axis).remove();var S=E.selectAll(\".\"+Dl.cn.axis).data(Qm,tg);S.enter().append(\"g\").classed(Dl.cn.axis,!0),S.each(function(z){var O=z.model.height/z.model.tickDistance,V=z.domainScale,G=V.domain();Bd.select(this).call(Bd.svg.axis().orient(\"left\").tickSize(4).outerTickSize(2).ticks(O,z.tickFormat).tickValues(z.ordinal?G:null).tickFormat(function(Z){return x5.isOrdinal(z)?Z:RUe(z.model.dimensions[z.visibleIndex],Z)}).scale(V)),Uz.font(S.selectAll(\"text\"),z.model.tickFont)}),S.selectAll(\".domain, .tick>line\").attr(\"fill\",\"none\").attr(\"stroke\",\"black\").attr(\"stroke-opacity\",.25).attr(\"stroke-width\",\"1px\"),S.selectAll(\"text\").style(\"cursor\",\"default\");var L=E.selectAll(\".\"+Dl.cn.axisHeading).data(Qm,tg);L.enter().append(\"g\").classed(Dl.cn.axisHeading,!0);var x=L.selectAll(\".\"+Dl.cn.axisTitle).data(Qm,tg);x.enter().append(\"text\").classed(Dl.cn.axisTitle,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"ew-resize\").style(\"pointer-events\",a?\"none\":\"auto\"),x.text(function(z){return z.label}).each(function(z){var O=Bd.select(this);Uz.font(O,z.model.labelFont),IGt.convertToTspans(O,t)}).attr(\"transform\",function(z){var O=SUe(z.model.labelAngle,z.model.labelSide),V=Dl.axisTitleOffset;return(O.dir>0?\"\":$m(0,2*V+z.model.height))+PGt(O.degrees)+$m(-V*O.dx,-V*O.dy)}).attr(\"text-anchor\",function(z){var O=SUe(z.model.labelAngle,z.model.labelSide),V=Math.abs(O.dx),G=Math.abs(O.dy);return 2*V>G?O.dir*O.dx<0?\"start\":\"end\":\"middle\"});var C=E.selectAll(\".\"+Dl.cn.axisExtent).data(Qm,tg);C.enter().append(\"g\").classed(Dl.cn.axisExtent,!0);var M=C.selectAll(\".\"+Dl.cn.axisExtentTop).data(Qm,tg);M.enter().append(\"g\").classed(Dl.cn.axisExtentTop,!0),M.attr(\"transform\",$m(0,-Dl.axisExtentOffset));var g=M.selectAll(\".\"+Dl.cn.axisExtentTopText).data(Qm,tg);g.enter().append(\"text\").classed(Dl.cn.axisExtentTopText,!0).call(AUe),g.text(function(z){return MUe(z,!0)}).each(function(z){Uz.font(Bd.select(this),z.model.rangeFont)});var P=C.selectAll(\".\"+Dl.cn.axisExtentBottom).data(Qm,tg);P.enter().append(\"g\").classed(Dl.cn.axisExtentBottom,!0),P.attr(\"transform\",function(z){return $m(0,z.model.height+Dl.axisExtentOffset)});var T=P.selectAll(\".\"+Dl.cn.axisExtentBottomText).data(Qm,tg);T.enter().append(\"text\").classed(Dl.cn.axisExtentBottomText,!0).attr(\"dy\",\"0.75em\").call(AUe),T.text(function(z){return MUe(z,!1)}).each(function(z){Uz.font(Bd.select(this),z.model.rangeFont)}),PUe.ensureAxisBrush(E,c,t)}});var BK=ye((qK,BUe)=>{\"use strict\";var HGt=FUe(),jGt=Sz(),zUe=PK().isVisible,qUe={};function OUe(e,t,r){var n=t.indexOf(r),i=e.indexOf(n);return i===-1&&(i+=t.length),i}function WGt(e,t){return function(n,i){return OUe(e,t,n)-OUe(e,t,i)}}var 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i(\"line.colorscale\"),tHt(e,t,n,i,{prefix:\"line.\",cLetter:\"c\"}),a.length;t.line.color=r}return 1/0}function sHt(e,t){function r(u,c){return b5.coerce(e,t,eVe.dimensions,u,c)}var n=r(\"values\"),i=r(\"visible\");if(n&&n.length||(i=t.visible=!1),i){r(\"label\"),r(\"displayindex\",t._index);var a=e.categoryarray,o=b5.isArrayOrTypedArray(a)&&a.length>0||aHt(a),s;o&&(s=\"array\");var l=r(\"categoryorder\",s);l===\"array\"?(r(\"categoryarray\"),r(\"ticktext\")):(delete e.categoryarray,delete e.ticktext),!o&&l===\"array\"&&(t.categoryorder=\"trace\")}}tVe.exports=function(t,r,n,i){function a(u,c){return b5.coerce(t,r,eVe,u,c)}var o=iHt(t,r,{name:\"dimensions\",handleItemDefaults:sHt}),s=oHt(t,r,n,i,a);rHt(r,i,a),(!Array.isArray(o)||!o.length)&&(r.visible=!1),nHt(r,o,\"values\",s),a(\"hoveron\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),a(\"arrangement\"),a(\"bundlecolors\"),a(\"sortpaths\"),a(\"counts\");var l=i.font;b5.coerceFont(a,\"labelfont\",l,{overrideDflt:{size:Math.round(l.size)}}),b5.coerceFont(a,\"tickfont\",l,{autoShadowDflt:!0,overrideDflt:{size:Math.round(l.size/1.2)}})}});var nVe=ye((txr,iVe)=>{\"use strict\";var lHt=Jm().wrap,uHt=pv().hasColorscale,cHt=gv(),fHt=KO(),hHt=So(),Fk=Dr(),dHt=Eo();iVe.exports=function(t,r){var n=Fk.filterVisible(r.dimensions);if(n.length===0)return[];var i=n.map(function(g){var P;if(g.categoryorder===\"trace\")P=null;else if(g.categoryorder===\"array\")P=g.categoryarray;else{P=fHt(g.values);for(var T=!0,z=0;z<P.length;z++)if(!dHt(P[z])){T=!1;break}P.sort(T?Fk.sorterAsc:void 0),g.categoryorder===\"category descending\"&&(P=P.reverse())}return xHt(g.values,P)}),a,o,s;Fk.isArrayOrTypedArray(r.counts)?a=r.counts:a=[r.counts],bHt(n),n.forEach(function(g,P){wHt(g,i[P])});var l=r.line,u;l?(uHt(r,\"line\")&&cHt(t,r,{vals:r.line.color,containerStr:\"line\",cLetter:\"c\"}),u=hHt.tryColorscale(l)):u=Fk.identity;function c(g){var P,T;return Fk.isArrayOrTypedArray(l.color)?(P=l.color[g%l.color.length],T=P):P=l.color,{color:u(P),rawColor:T}}var f=n[0].values.length,h={},d=i.map(function(g){return g.inds});s=0;var v,_;for(v=0;v<f;v++){var b=[];for(_=0;_<d.length;_++)b.push(d[_][v]);o=a[v%a.length],s+=o;var p=c(v),k=b+\"-\"+p.rawColor;h[k]===void 0&&(h[k]=yHt(b,p.color,p.rawColor)),_Ht(h[k],v,o)}var E=n.map(function(g,P){return pHt(P,g._index,g._displayindex,g.label,s)});for(v=0;v<f;v++)for(o=a[v%a.length],_=0;_<E.length;_++){var S=E[_].containerInd,L=i[_].inds[v],x=E[_].categories;if(x[L]===void 0){var C=r.dimensions[S]._categoryarray[L],M=r.dimensions[S]._ticktext[L];x[L]=gHt(_,L,C,M)}mHt(x[L],v,o)}return lHt(vHt(E,h,s))};function vHt(e,t,r){var n=e.map(function(i){return i.categories.length}).reduce(function(i,a){return Math.max(i,a)});return{dimensions:e,paths:t,trace:void 0,maxCats:n,count:r}}function pHt(e,t,r,n,i){return{dimensionInd:e,containerInd:t,displayInd:r,dimensionLabel:n,count:i,categories:[],dragX:null}}function gHt(e,t,r,n){return{dimensionInd:e,categoryInd:t,categoryValue:r,displayInd:t,categoryLabel:n,valueInds:[],count:0,dragY:null}}function mHt(e,t,r){e.valueInds.push(t),e.count+=r}function yHt(e,t,r){return{categoryInds:e,color:t,rawColor:r,valueInds:[],count:0}}function _Ht(e,t,r){e.valueInds.push(t),e.count+=r}function xHt(e,t){t==null?t=[]:t=t.map(function(u){return u});var r={},n={},i=[];t.forEach(function(u,c){r[u]=0,n[u]=c});for(var a=0;a<e.length;a++){var o=e[a],s;r[o]===void 0?(r[o]=1,s=t.push(o)-1,n[o]=s):(r[o]++,s=n[o]),i.push(s)}var l=t.map(function(u){return r[u]});return{uniqueValues:t,uniqueCounts:l,inds:i}}function bHt(e){var t=e.map(function(n){return n.displayindex}),r;if(THt(t))for(r=0;r<e.length;r++)e[r]._displayindex=e[r].displayindex;else for(r=0;r<e.length;r++)e[r]._displayindex=r}function wHt(e,t){e._categoryarray=t.uniqueValues,e.ticktext===null||e.ticktext===void 0?e._ticktext=[]:e._ticktext=e.ticktext.slice();for(var r=e._ticktext.length;r<t.uniqueValues.length;r++)e._ticktext.push(t.uniqueValues[r])}function THt(e){for(var t=new Array(e.length),r=0;r<e.length;r++){if(e[r]<0||e[r]>=e.length||t[e[r]]!==void 0)return!1;t[e[r]]=!0}return!0}});var dVe=ye((rxr,hVe)=>{\"use strict\";var Fl=Oa(),AHt=(D2(),ob(R2)).interpolateNumber,SHt=GP(),qk=vf(),yx=Dr(),zk=yx.strTranslate,aVe=So(),UK=cd(),MHt=ru();function EHt(e,t,r,n){var i=t._context.staticPlot,a=e.map(VHt.bind(0,t,r)),o=n.selectAll(\"g.parcatslayer\").data([null]);o.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",i?\"none\":\"all\");var s=o.selectAll(\"g.trace.parcats\").data(a,u1),l=s.enter().append(\"g\").attr(\"class\",\"trace parcats\");s.attr(\"transform\",function(k){return zk(k.x,k.y)}),l.append(\"g\").attr(\"class\",\"paths\");var u=s.select(\"g.paths\"),c=u.selectAll(\"path.path\").data(function(k){return k.paths},u1);c.attr(\"fill\",function(k){return k.model.color});var f=c.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",function(k){return k.model.color}).attr(\"fill-opacity\",0);HK(f),c.attr(\"d\",function(k){return k.svgD}),f.empty()||c.sort(VK),c.exit().remove(),c.on(\"mouseover\",kHt).on(\"mouseout\",CHt).on(\"click\",LHt),l.append(\"g\").attr(\"class\",\"dimensions\");var h=s.select(\"g.dimensions\"),d=h.selectAll(\"g.dimension\").data(function(k){return k.dimensions},u1);d.enter().append(\"g\").attr(\"class\",\"dimension\"),d.attr(\"transform\",function(k){return zk(k.x,0)}),d.exit().remove();var v=d.selectAll(\"g.category\").data(function(k){return k.categories},u1),_=v.enter().append(\"g\").attr(\"class\",\"category\");v.attr(\"transform\",function(k){return zk(0,k.y)}),_.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),v.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",function(k){return k.width}).attr(\"height\",function(k){return k.height}),sVe(_);var b=v.selectAll(\"rect.bandrect\").data(function(k){return k.bands},u1);b.each(function(){yx.raiseToTop(this)}),b.attr(\"fill\",function(k){return k.color});var p=b.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",function(k){return k.color}).attr(\"fill-opacity\",0);b.attr(\"fill\",function(k){return k.color}).attr(\"width\",function(k){return k.width}).attr(\"height\",function(k){return k.height}).attr(\"y\",function(k){return k.y}).attr(\"cursor\",function(k){return k.parcatsViewModel.arrangement===\"fixed\"?\"default\":k.parcatsViewModel.arrangement===\"perpendicular\"?\"ns-resize\":\"move\"}),WK(p),b.exit().remove(),_.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\"),v.select(\"text.catlabel\").attr(\"text-anchor\",function(k){return Ok(k)?\"start\":\"end\"}).attr(\"alignment-baseline\",\"middle\").style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",function(k){return Ok(k)?k.width+5:-5}).attr(\"y\",function(k){return k.height/2}).text(function(k){return k.model.categoryLabel}).each(function(k){aVe.font(Fl.select(this),k.parcatsViewModel.categorylabelfont),MHt.convertToTspans(Fl.select(this),t)}),_.append(\"text\").attr(\"class\",\"dimlabel\"),v.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",function(k){return k.parcatsViewModel.arrangement===\"fixed\"?\"default\":\"ew-resize\"}).attr(\"x\",function(k){return k.width/2}).attr(\"y\",-5).text(function(k,E){return E===0?k.parcatsViewModel.model.dimensions[k.model.dimensionInd].dimensionLabel:null}).each(function(k){aVe.font(Fl.select(this),k.parcatsViewModel.labelfont)}),v.selectAll(\"rect.bandrect\").on(\"mouseover\",OHt).on(\"mouseout\",qHt),v.exit().remove(),d.call(Fl.behavior.drag().origin(function(k){return{x:k.x,y:0}}).on(\"dragstart\",BHt).on(\"drag\",NHt).on(\"dragend\",UHt)),s.each(function(k){k.traceSelection=Fl.select(this),k.pathSelection=Fl.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),k.dimensionSelection=Fl.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")}),s.exit().remove()}hVe.exports=function(e,t,r,n){EHt(r,e,n,t)};function u1(e){return e.key}function Ok(e){var t=e.parcatsViewModel.dimensions.length,r=e.parcatsViewModel.dimensions[t-1].model.dimensionInd;return e.model.dimensionInd===r}function VK(e,t){return e.model.rawColor>t.model.rawColor?1:e.model.rawColor<t.model.rawColor?-1:0}function kHt(e){if(!e.parcatsViewModel.dragDimension&&e.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")===-1){yx.raiseToTop(this),jK(Fl.select(this));var t=Bk(e),r=GK(e);if(e.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:t,event:Fl.event,constraints:r}),e.parcatsViewModel.hoverinfoItems.indexOf(\"none\")===-1){var n=Fl.mouse(this)[0],i=e.parcatsViewModel.graphDiv,a=e.parcatsViewModel.trace,o=i._fullLayout,s=o._paperdiv.node().getBoundingClientRect(),l=e.parcatsViewModel.graphDiv.getBoundingClientRect(),u,c,f;for(f=0;f<e.leftXs.length-1;f++)if(e.leftXs[f]+e.dimWidths[f]-2<=n&&n<=e.leftXs[f+1]+2){var h=e.parcatsViewModel.dimensions[f],d=e.parcatsViewModel.dimensions[f+1];u=(h.x+h.width+d.x)/2,c=(e.topYs[f]+e.topYs[f+1]+e.height)/2;break}var v=e.parcatsViewModel.x+u,_=e.parcatsViewModel.y+c,b=UK.mostReadable(e.model.color,[\"black\",\"white\"]),p=e.model.count,k=p/e.parcatsViewModel.model.count,E={countLabel:p,probabilityLabel:k.toFixed(3)},S=[];e.parcatsViewModel.hoverinfoItems.indexOf(\"count\")!==-1&&S.push([\"Count:\",E.countLabel].join(\" \")),e.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")!==-1&&S.push([\"P:\",E.probabilityLabel].join(\" \"));var L=S.join(\"<br>\"),x=Fl.mouse(i)[0];qk.loneHover({trace:a,x:v-s.left+l.left,y:_-s.top+l.top,text:L,color:e.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:b,idealAlign:x<v?\"right\":\"left\",hovertemplate:(a.line||{}).hovertemplate,hovertemplateLabels:E,eventData:[{data:a._input,fullData:a,count:p,probability:k}]},{container:o._hoverlayer.node(),outerContainer:o._paper.node(),gd:i})}}}function CHt(e){if(!e.parcatsViewModel.dragDimension&&(HK(Fl.select(this)),qk.loneUnhover(e.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),e.parcatsViewModel.pathSelection.sort(VK),e.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")===-1)){var t=Bk(e),r=GK(e);e.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:t,event:Fl.event,constraints:r})}}function Bk(e){for(var t=[],r=uVe(e.parcatsViewModel),n=0;n<e.model.valueInds.length;n++){var i=e.model.valueInds[n];t.push({curveNumber:r,pointNumber:i})}return t}function GK(e){for(var t={},r=e.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[e.model.categoryInds[n]];t[i.containerInd]=a.categoryValue}return e.model.rawColor!==void 0&&(t.color=e.model.rawColor),t}function LHt(e){if(e.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")===-1){var t=Bk(e),r=GK(e);e.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:t,event:Fl.event,constraints:r})}}function HK(e){e.attr(\"fill\",function(t){return t.model.color}).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function jK(e){e.attr(\"fill-opacity\",.8).attr(\"stroke\",function(t){return UK.mostReadable(t.model.color,[\"black\",\"white\"])}).attr(\"stroke-width\",.3)}function PHt(e){e.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}function sVe(e){e.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function IHt(e){e.attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}function WK(e){e.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function Gz(e){var t=e.parcatsViewModel.pathSelection,r=e.categoryViewModel.model.dimensionInd,n=e.categoryViewModel.model.categoryInd;return t.filter(function(i){return i.model.categoryInds[r]===n&&i.model.color===e.color})}function RHt(e){var t=Fl.select(e.parentNode).selectAll(\"rect.bandrect\");t.each(function(r){var n=Gz(r);jK(n),n.each(function(){yx.raiseToTop(this)})}),PHt(Fl.select(e.parentNode))}function DHt(e){var t=Fl.select(e).datum(),r=Gz(t);jK(r),r.each(function(){yx.raiseToTop(this)}),Fl.select(e.parentNode).selectAll(\"rect.bandrect\").filter(function(n){return n.color===t.color}).each(function(){yx.raiseToTop(this),IHt(Fl.select(this))})}function XK(e,t,r){var n=Fl.select(e).datum(),i=n.categoryViewModel.model,a=n.parcatsViewModel.graphDiv,o=Fl.select(e.parentNode).selectAll(\"rect.bandrect\"),s=[];o.each(function(u){var c=Gz(u);c.each(function(f){Array.prototype.push.apply(s,Bk(f))})});var l={};l[i.dimensionInd]=i.categoryValue,a.emit(t,{points:s,event:r,constraints:l})}function ZK(e,t,r){var n=Fl.select(e).datum(),i=n.categoryViewModel.model,a=n.parcatsViewModel.graphDiv,o=Gz(n),s=[];o.each(function(u){Array.prototype.push.apply(s,Bk(u))});var l={};l[i.dimensionInd]=i.categoryValue,n.rawColor!==void 0&&(l.color=n.rawColor),a.emit(t,{points:s,event:r,constraints:l})}function lVe(e,t,r){e._fullLayout._calcInverseTransform(e);var n=e._fullLayout._invScaleX,i=e._fullLayout._invScaleY,a=Fl.select(r.parentNode).select(\"rect.catrect\"),o=a.node().getBoundingClientRect(),s=a.datum(),l=s.parcatsViewModel,u=l.model.dimensions[s.model.dimensionInd],c=l.trace,f=o.top+o.height/2,h,d;l.dimensions.length>1&&u.displayInd===l.dimensions.length-1?(h=o.left,d=\"left\"):(h=o.left+o.width,d=\"right\");var v=s.model.count,_=s.model.categoryLabel,b=v/s.parcatsViewModel.model.count,p={countLabel:v,categoryLabel:_,probabilityLabel:b.toFixed(3)},k=[];s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")!==-1&&k.push([\"Count:\",p.countLabel].join(\" \")),s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")!==-1&&k.push([\"P(\"+p.categoryLabel+\"):\",p.probabilityLabel].join(\" \"));var E=k.join(\"<br>\");return{trace:c,x:n*(h-t.left),y:i*(f-t.top),text:E,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:d,hovertemplate:c.hovertemplate,hovertemplateLabels:p,eventData:[{data:c._input,fullData:c,count:v,category:_,probability:b}]}}function FHt(e,t,r){var n=[];return Fl.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each(function(){var i=this;n.push(lVe(e,t,i))}),n}function zHt(e,t,r){e._fullLayout._calcInverseTransform(e);var n=e._fullLayout._invScaleX,i=e._fullLayout._invScaleY,a=r.getBoundingClientRect(),o=Fl.select(r).datum(),s=o.categoryViewModel,l=s.parcatsViewModel,u=l.model.dimensions[s.model.dimensionInd],c=l.trace,f=a.y+a.height/2,h,d;l.dimensions.length>1&&u.displayInd===l.dimensions.length-1?(h=a.left,d=\"left\"):(h=a.left+a.width,d=\"right\");var v=s.model.categoryLabel,_=o.parcatsViewModel.model.count,b=0;o.categoryViewModel.bands.forEach(function(P){P.color===o.color&&(b+=P.count)});var p=s.model.count,k=0;l.pathSelection.each(function(P){P.model.color===o.color&&(k+=P.model.count)});var E=b/_,S=b/k,L=b/p,x={countLabel:b,categoryLabel:v,probabilityLabel:E.toFixed(3)},C=[];s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")!==-1&&C.push([\"Count:\",x.countLabel].join(\" \")),s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")!==-1&&(C.push(\"P(color \\u2229 \"+v+\"): \"+x.probabilityLabel),C.push(\"P(\"+v+\" | color): \"+S.toFixed(3)),C.push(\"P(color | \"+v+\"): \"+L.toFixed(3)));var M=C.join(\"<br>\"),g=UK.mostReadable(o.color,[\"black\",\"white\"]);return{trace:c,x:n*(h-t.left),y:i*(f-t.top),text:M,color:o.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:g,fontSize:10,idealAlign:d,hovertemplate:c.hovertemplate,hovertemplateLabels:x,eventData:[{data:c._input,fullData:c,category:v,count:_,probability:E,categorycount:p,colorcount:k,bandcolorcount:b}]}}function OHt(e){if(!e.parcatsViewModel.dragDimension&&e.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")===-1){var t=Fl.mouse(this)[1];if(t<-1)return;var r=e.parcatsViewModel.graphDiv,n=r._fullLayout,i=n._paperdiv.node().getBoundingClientRect(),a=e.parcatsViewModel.hoveron,o=this;if(a===\"color\"?(DHt(o),ZK(o,\"plotly_hover\",Fl.event)):(RHt(o),XK(o,\"plotly_hover\",Fl.event)),e.parcatsViewModel.hoverinfoItems.indexOf(\"none\")===-1){var s;a===\"category\"?s=lVe(r,i,o):a===\"color\"?s=zHt(r,i,o):a===\"dimension\"&&(s=FHt(r,i,o)),s&&qk.loneHover(s,{container:n._hoverlayer.node(),outerContainer:n._paper.node(),gd:r})}}}function qHt(e){var t=e.parcatsViewModel;if(!t.dragDimension&&(HK(t.pathSelection),sVe(t.dimensionSelection.selectAll(\"g.category\")),WK(t.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),qk.loneUnhover(t.graphDiv._fullLayout._hoverlayer.node()),t.pathSelection.sort(VK),t.hoverinfoItems.indexOf(\"skip\")===-1)){var r=e.parcatsViewModel.hoveron,n=this;r===\"color\"?ZK(n,\"plotly_unhover\",Fl.event):XK(n,\"plotly_unhover\",Fl.event)}}function BHt(e){e.parcatsViewModel.arrangement!==\"fixed\"&&(e.dragDimensionDisplayInd=e.model.displayInd,e.initialDragDimensionDisplayInds=e.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),e.dragHasMoved=!1,e.dragCategoryDisplayInd=null,Fl.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each(function(t){var r=Fl.mouse(this)[0],n=Fl.mouse(this)[1];-2<=r&&r<=t.width+2&&-2<=n&&n<=t.height+2&&(e.dragCategoryDisplayInd=t.model.displayInd,e.initialDragCategoryDisplayInds=e.model.categories.map(function(i){return i.displayInd}),t.model.dragY=t.y,yx.raiseToTop(this.parentNode),Fl.select(this.parentNode).selectAll(\"rect.bandrect\").each(function(i){i.y<n&&n<=i.y+i.height&&(e.potentialClickBand=this)}))}),e.parcatsViewModel.dragDimension=e,qk.loneUnhover(e.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function NHt(e){if(e.parcatsViewModel.arrangement!==\"fixed\"&&(e.dragHasMoved=!0,e.dragDimensionDisplayInd!==null)){var t=e.dragDimensionDisplayInd,r=t-1,n=t+1,i=e.parcatsViewModel.dimensions[t];if(e.dragCategoryDisplayInd!==null){var a=i.categories[e.dragCategoryDisplayInd];a.model.dragY+=Fl.event.dy;var o=a.model.dragY,s=a.model.displayInd,l=i.categories,u=l[s-1],c=l[s+1];u!==void 0&&o<u.y+u.height/2&&(a.model.displayInd=u.model.displayInd,u.model.displayInd=s),c!==void 0&&o+a.height>c.y+c.height/2&&(a.model.displayInd=c.model.displayInd,c.model.displayInd=s),e.dragCategoryDisplayInd=a.model.displayInd}if(e.dragCategoryDisplayInd===null||e.parcatsViewModel.arrangement===\"freeform\"){i.model.dragX=Fl.event.x;var f=e.parcatsViewModel.dimensions[r],h=e.parcatsViewModel.dimensions[n];f!==void 0&&i.model.dragX<f.x+f.width&&(i.model.displayInd=f.model.displayInd,f.model.displayInd=t),h!==void 0&&i.model.dragX+i.width>h.x&&(i.model.displayInd=h.model.displayInd,h.model.displayInd=e.dragDimensionDisplayInd),e.dragDimensionDisplayInd=i.model.displayInd}KK(e.parcatsViewModel),YK(e.parcatsViewModel),fVe(e.parcatsViewModel),cVe(e.parcatsViewModel)}}function UHt(e){if(e.parcatsViewModel.arrangement!==\"fixed\"&&e.dragDimensionDisplayInd!==null){Fl.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var t={},r=uVe(e.parcatsViewModel),n=e.parcatsViewModel.model.dimensions.map(function(h){return h.displayInd}),i=e.initialDragDimensionDisplayInds.some(function(h,d){return h!==n[d]});i&&n.forEach(function(h,d){var v=e.parcatsViewModel.model.dimensions[d].containerInd;t[\"dimensions[\"+v+\"].displayindex\"]=h});var a=!1;if(e.dragCategoryDisplayInd!==null){var o=e.model.categories.map(function(h){return h.displayInd});if(a=e.initialDragCategoryDisplayInds.some(function(h,d){return h!==o[d]}),a){var s=e.model.categories.slice().sort(function(h,d){return h.displayInd-d.displayInd}),l=s.map(function(h){return h.categoryValue}),u=s.map(function(h){return h.categoryLabel});t[\"dimensions[\"+e.model.containerInd+\"].categoryarray\"]=[l],t[\"dimensions[\"+e.model.containerInd+\"].ticktext\"]=[u],t[\"dimensions[\"+e.model.containerInd+\"].categoryorder\"]=\"array\"}}if(e.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")===-1&&!e.dragHasMoved&&e.potentialClickBand&&(e.parcatsViewModel.hoveron===\"color\"?ZK(e.potentialClickBand,\"plotly_click\",Fl.event.sourceEvent):XK(e.potentialClickBand,\"plotly_click\",Fl.event.sourceEvent)),e.model.dragX=null,e.dragCategoryDisplayInd!==null){var c=e.parcatsViewModel.dimensions[e.dragDimensionDisplayInd].categories[e.dragCategoryDisplayInd];c.model.dragY=null,e.dragCategoryDisplayInd=null}e.dragDimensionDisplayInd=null,e.parcatsViewModel.dragDimension=null,e.dragHasMoved=null,e.potentialClickBand=null,KK(e.parcatsViewModel),YK(e.parcatsViewModel);var f=Fl.transition().duration(300).ease(\"cubic-in-out\");f.each(function(){fVe(e.parcatsViewModel,!0),cVe(e.parcatsViewModel,!0)}).each(\"end\",function(){(i||a)&&SHt.restyle(e.parcatsViewModel.graphDiv,t,[r])})}}function uVe(e){for(var t,r=e.graphDiv._fullData,n=0;n<r.length;n++)if(e.key===r[n].uid){t=n;break}return t}function cVe(e,t){t===void 0&&(t=!1);function r(n){return t?n.transition():n}e.pathSelection.data(function(n){return n.paths},u1),r(e.pathSelection).attr(\"d\",function(n){return n.svgD})}function fVe(e,t){t===void 0&&(t=!1);function r(l){return t?l.transition():l}e.dimensionSelection.data(function(l){return l.dimensions},u1);var n=e.dimensionSelection.selectAll(\"g.category\").data(function(l){return l.categories},u1);r(e.dimensionSelection).attr(\"transform\",function(l){return zk(l.x,0)}),r(n).attr(\"transform\",function(l){return zk(0,l.y)});var i=n.select(\".dimlabel\");i.text(function(l,u){return u===0?l.parcatsViewModel.model.dimensions[l.model.dimensionInd].dimensionLabel:null});var a=n.select(\".catlabel\");a.attr(\"text-anchor\",function(l){return Ok(l)?\"start\":\"end\"}).attr(\"x\",function(l){return Ok(l)?l.width+5:-5}).each(function(l){var u,c;Ok(l)?(u=l.width+5,c=\"start\"):(u=-5,c=\"end\"),Fl.select(this).selectAll(\"tspan\").attr(\"x\",u).attr(\"text-anchor\",c)});var o=n.selectAll(\"rect.bandrect\").data(function(l){return l.bands},u1),s=o.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",function(l){return l.color}).attr(\"fill-opacity\",0);o.attr(\"fill\",function(l){return l.color}).attr(\"width\",function(l){return l.width}).attr(\"height\",function(l){return l.height}).attr(\"y\",function(l){return l.y}),WK(s),o.each(function(){yx.raiseToTop(this)}),o.exit().remove()}function VHt(e,t,r){var n=r[0],i=t.margin||{l:80,r:80,t:100,b:80},a=n.trace,o=a.domain,s=t.width,l=t.height,u=Math.floor(s*(o.x[1]-o.x[0])),c=Math.floor(l*(o.y[1]-o.y[0])),f=o.x[0]*s+i.l,h=t.height-o.y[1]*t.height+i.t,d=a.line.shape,v;a.hoverinfo===\"all\"?v=[\"count\",\"probability\"]:v=(a.hoverinfo||\"\").split(\"+\");var _={trace:a,key:a.uid,model:n,x:f,y:h,width:u,height:c,hoveron:a.hoveron,hoverinfoItems:v,arrangement:a.arrangement,bundlecolors:a.bundlecolors,sortpaths:a.sortpaths,labelfont:a.labelfont,categorylabelfont:a.tickfont,pathShape:d,dragDimension:null,margin:i,paths:[],dimensions:[],graphDiv:e,traceSelection:null,pathSelection:null,dimensionSelection:null};return n.dimensions&&(KK(_),YK(_)),_}function oVe(e,t,r,n,i){var a=[],o=[],s,l;for(l=0;l<r.length-1;l++)s=AHt(r[l]+e[l],e[l+1]),a.push(s(i)),o.push(s(1-i));var u=\"M \"+e[0]+\",\"+t[0];for(u+=\"l\"+r[0]+\",0 \",l=1;l<r.length;l++)u+=\"C\"+a[l-1]+\",\"+t[l-1]+\" \"+o[l-1]+\",\"+t[l]+\" \"+e[l]+\",\"+t[l],u+=\"l\"+r[l]+\",0 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e.sortpaths===\"backward\"&&(G.reverse(),Z.reverse()),G.push(O.valueInds[0]),Z.push(V.valueInds[0]),e.bundlecolors&&(G.unshift(O.rawColor),Z.unshift(V.rawColor)),G<Z?-1:G>Z?1:0});for(var h=new Array(u.length),d=t[0].model.count,v=t[0].categories.map(function(O){return O.height}).reduce(function(O,V){return O+V}),_=0;_<u.length;_++){var b=u[_],p;d>0?p=v*(b.count/d):p=0;for(var k=new Array(n.length),E=0;E<b.categoryInds.length;E++){var S=b.categoryInds[E],L=i[E][S],x=a[E];k[x]=n[x][L],n[x][L]+=p;var C=e.dimensions[x].categories[L],M=C.bands.length,g=C.bands[M-1];if(g===void 0||b.rawColor!==g.rawColor){var P=g===void 0?0:g.y+g.height;C.bands.push({key:P,color:b.color,rawColor:b.rawColor,height:p,width:C.width,count:b.count,y:P,categoryViewModel:C,parcatsViewModel:e})}else{var T=C.bands[M-1];T.height+=p,T.count+=b.count}}var z;e.pathShape===\"hspline\"?z=oVe(s,k,l,p,.5):z=oVe(s,k,l,p,0),h[_]={key:b.valueInds[0],model:b,height:p,leftXs:s,topYs:k,dimWidths:l,svgD:z,parcatsViewModel:e}}e.paths=h}function KK(e){var t=e.model.dimensions.map(function(o){return{displayInd:o.displayInd,dimensionInd:o.dimensionInd}});t.sort(function(o,s){return o.displayInd-s.displayInd});var r=[];for(var n in t){var i=t[n].dimensionInd,a=e.model.dimensions[i];r.push(GHt(e,a))}e.dimensions=r}function GHt(e,t){var r=40,n=16,i=e.model.dimensions.length,a=t.displayInd,o,s,l;i>1?o=(e.width-2*r-n)/(i-1):o=0,s=r,l=s+o*a;var u=[],c=e.model.maxCats,f=t.categories.length,h=8,d=t.count,v=e.height-h*(c-1),_,b,p,k,E,S=(c-f)*h/2,L=t.categories.map(function(x){return{displayInd:x.displayInd,categoryInd:x.categoryInd}});for(L.sort(function(x,C){return x.displayInd-C.displayInd}),E=0;E<f;E++)k=L[E].categoryInd,b=t.categories[k],d>0?_=b.count/d*v:_=0,p={key:b.valueInds[0],model:b,width:n,height:_,y:b.dragY!==null?b.dragY:S,bands:[],parcatsViewModel:e},S=S+_+h,u.push(p);return{key:t.dimensionInd,x:t.dragX!==null?t.dragX:l,y:0,width:n,model:t,categories:u,parcatsViewModel:e,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}});var JK=ye((ixr,vVe)=>{\"use strict\";var HHt=dVe();vVe.exports=function(t,r,n,i){var a=t._fullLayout,o=a._paper,s=a._size;HHt(t,o,r,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},n,i)}});var gVe=ye(Hz=>{\"use strict\";var jHt=Id().getModuleCalcData,WHt=JK(),pVe=\"parcats\";Hz.name=pVe;Hz.plot=function(e,t,r,n){var i=jHt(e.calcdata,pVe);if(i.length){var a=i[0];WHt(e,a,r,n)}};Hz.clean=function(e,t,r,n){var i=n._has&&n._has(\"parcats\"),a=t._has&&t._has(\"parcats\");i&&!a&&n._paperdiv.selectAll(\".parcats\").remove()}});var yVe=ye((axr,mVe)=>{\"use strict\";mVe.exports={attributes:NK(),supplyDefaults:rVe(),calc:nVe(),plot:JK(),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcats\",basePlotModule:gVe(),categories:[\"noOpacity\"],meta:{}}});var xVe=ye((oxr,_Ve)=>{\"use strict\";_Ve.exports=yVe()});var c1=ye((sxr,EVe)=>{\"use strict\";var XHt=Z1(),bVe=\"1.13.4\",SVe='\\xA9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',wVe=['\\xA9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',SVe].join(\" \"),TVe=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a 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\"),MVe={\"open-street-map\":{id:\"osm\",version:8,sources:{\"plotly-osm-tiles\":{type:\"raster\",attribution:SVe,tiles:[\"https://a.tile.openstreetmap.org/{z}/{x}/{y}.png\",\"https://b.tile.openstreetmap.org/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-osm-tiles\",type:\"raster\",source:\"plotly-osm-tiles\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"white-bg\":{id:\"white-bg\",version:8,sources:{},layers:[{id:\"white-bg\",type:\"background\",paint:{\"background-color\":\"#FFFFFF\"},minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"carto-positron\":{id:\"carto-positron\",version:8,sources:{\"plotly-carto-positron\":{type:\"raster\",attribution:wVe,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-positron\",type:\"raster\",source:\"plotly-carto-positron\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"carto-darkmatter\":{id:\"carto-darkmatter\",version:8,sources:{\"plotly-carto-darkmatter\":{type:\"raster\",attribution:wVe,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-darkmatter\",type:\"raster\",source:\"plotly-carto-darkmatter\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"stamen-terrain\":{id:\"stamen-terrain\",version:8,sources:{\"plotly-stamen-terrain\":{type:\"raster\",attribution:TVe,tiles:[\"https://tiles.stadiamaps.com/tiles/stamen_terrain/{z}/{x}/{y}.png?api_key=\"],tileSize:256}},layers:[{id:\"plotly-stamen-terrain\",type:\"raster\",source:\"plotly-stamen-terrain\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"stamen-toner\":{id:\"stamen-toner\",version:8,sources:{\"plotly-stamen-toner\":{type:\"raster\",attribution:TVe,tiles:[\"https://tiles.stadiamaps.com/tiles/stamen_toner/{z}/{x}/{y}.png?api_key=\"],tileSize:256}},layers:[{id:\"plotly-stamen-toner\",type:\"raster\",source:\"plotly-stamen-toner\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"},\"stamen-watercolor\":{id:\"stamen-watercolor\",version:8,sources:{\"plotly-stamen-watercolor\":{type:\"raster\",attribution:ZHt,tiles:[\"https://tiles.stadiamaps.com/tiles/stamen_watercolor/{z}/{x}/{y}.jpg?api_key=\"],tileSize:256}},layers:[{id:\"plotly-stamen-watercolor\",type:\"raster\",source:\"plotly-stamen-watercolor\",minzoom:0,maxzoom:22}],glyphs:\"https://fonts.openmaptiles.org/{fontstack}/{range}.pbf\"}},AVe=XHt(MVe);EVe.exports={requiredVersion:bVe,styleUrlPrefix:\"mapbox://styles/mapbox/\",styleUrlSuffix:\"v9\",styleValuesMapbox:[\"basic\",\"streets\",\"outdoors\",\"light\",\"dark\",\"satellite\",\"satellite-streets\"],styleValueDflt:\"basic\",stylesNonMapbox:MVe,styleValuesNonMapbox:AVe,traceLayerPrefix:\"plotly-trace-layer-\",layoutLayerPrefix:\"plotly-layout-layer-\",wrongVersionErrorMsg:[\"Your custom plotly.js bundle is not using the correct mapbox-gl version\",\"Please install @plotly/mapbox-gl@\"+bVe+\".\"].join(`\n",
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kVe=Dr(),CVe=ka().defaultLine,YHt=Cc().attributes,KHt=ec(),JHt=pf().textposition,$Ht=mc().overrideAll,QHt=vl().templatedArray,$K=c1(),LVe=KHt({noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0});LVe.family.dflt=\"Open Sans Regular, Arial Unicode MS Regular\";var 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jz=ye((uxr,FVe)=>{\"use 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QK=ye((cxr,zVe)=>{\"use strict\";var ljt=[\"Metropolis Black Italic\",\"Metropolis Black\",\"Metropolis Bold Italic\",\"Metropolis Bold\",\"Metropolis Extra Bold Italic\",\"Metropolis Extra Bold\",\"Metropolis Extra Light Italic\",\"Metropolis Extra Light\",\"Metropolis Light Italic\",\"Metropolis Light\",\"Metropolis Medium Italic\",\"Metropolis Medium\",\"Metropolis Regular Italic\",\"Metropolis Regular\",\"Metropolis Semi Bold Italic\",\"Metropolis Semi Bold\",\"Metropolis Thin Italic\",\"Metropolis Thin\",\"Open Sans Bold Italic\",\"Open Sans Bold\",\"Open Sans Extrabold Italic\",\"Open Sans Extrabold\",\"Open Sans Italic\",\"Open Sans Light Italic\",\"Open Sans Light\",\"Open Sans Regular\",\"Open Sans Semibold Italic\",\"Open Sans Semibold\",\"Klokantech Noto Sans Bold\",\"Klokantech Noto Sans CJK Bold\",\"Klokantech Noto Sans CJK Regular\",\"Klokantech Noto Sans Italic\",\"Klokantech Noto Sans Regular\"];zVe.exports={isSupportedFont:function(e){return ljt.indexOf(e)!==-1}}});var 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r=t._fullLayout,n=e[0].trace,i=n.marker||{},a=i.symbol,o=i.angle,s=a!==\"circle\"?iJ(a):Yz,l=o!==\"auto\"?iJ(o,!0):Yz,u=Zz.hasText(n)?iJ(n.text):Yz,c=[],f=0;f<e.length;f++){var h=e[f];if(!XVe(h.lonlat)){var d=n.texttemplate,v;if(d){var _=Array.isArray(d)?d[f]||\"\":d,b=n._module.formatLabels(h,n,r),p={};xjt(p,n,h.i),v=av.texttemplateString({data:[p,h,n._meta],fallback:n.texttemplatefallback,labels:b,locale:r._d3locale,template:_})}else v=u(f);v&&(v=v.replace(bjt,\"\").replace(wjt,`\n",
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JVe(e,t,r,n){this.type=\"scattermapbox\",this.subplot=e,this.uid=t,this.clusterEnabled=r,this.isHidden=n,this.sourceIds={fill:\"source-\"+t+\"-fill\",line:\"source-\"+t+\"-line\",circle:\"source-\"+t+\"-circle\",symbol:\"source-\"+t+\"-symbol\",cluster:\"source-\"+t+\"-circle\",clusterCount:\"source-\"+t+\"-circle\"},this.layerIds={fill:A5+t+\"-fill\",line:A5+t+\"-line\",circle:A5+t+\"-circle\",symbol:A5+t+\"-symbol\",cluster:A5+t+\"-cluster\",clusterCount:A5+t+\"-cluster-count\"},this.below=null}var Gk=JVe.prototype;Gk.addSource=function(e,t,r){var n={type:\"geojson\",data:t.geojson};r&&r.enabled&&Sjt.extendFlat(n,{cluster:!0,clusterMaxZoom:r.maxzoom});var i=this.subplot.map.getSource(this.sourceIds[e]);i?i.setData(t.geojson):this.subplot.map.addSource(this.sourceIds[e],n)};Gk.setSourceData=function(e,t){this.subplot.map.getSource(this.sourceIds[e]).setData(t.geojson)};Gk.addLayer=function(e,t,r){var n={type:t.type,id:this.layerIds[e],source:this.sourceIds[e],layout:t.layout,paint:t.paint};t.filter&&(n.filter=t.filter);for(var i=this.layerIds[e],a,o=this.subplot.getMapLayers(),s=0;s<o.length;s++)if(o[s].id===i){a=!0;break}a?(this.subplot.setOptions(i,\"setLayoutProperty\",n.layout),n.layout.visibility===\"visible\"&&this.subplot.setOptions(i,\"setPaintProperty\",n.paint)):this.subplot.addLayer(n,r)};Gk.update=function(t){var r=t[0].trace,n=this.subplot,i=n.map,a=KVe(n.gd,t),o=n.belowLookup[\"trace-\"+this.uid],s=!!(r.cluster&&r.cluster.enabled),l=!!this.clusterEnabled,u=this;function c(E){E||u.addSource(\"circle\",a.circle,r.cluster);for(var S=rg.cluster,L=0;L<S.length;L++){var x=S[L],C=a[x];u.addLayer(x,C,o)}}function f(E){for(var S=rg.cluster,L=S.length-1;L>=0;L--){var x=S[L];i.removeLayer(u.layerIds[x])}E||i.removeSource(u.sourceIds.circle)}function h(E){for(var S=rg.nonCluster,L=0;L<S.length;L++){var x=S[L],C=a[x];E||u.addSource(x,C),u.addLayer(x,C,o)}}function d(E){for(var 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Math.max(Math.sqrt(O*O+V*V)-G,1-3/G)}if(Mjt.getClosest(n,_,e),e.index!==!1){var b=n[e.index],p=b.lonlat,k=[aJ.modHalf(p[0],360)+d,p[1]],E=a.c2p(k),S=o.c2p(k),L=b.mrc||1;e.x0=E-L,e.x1=E+L,e.y0=S-L,e.y1=S+L;var x={};x[i.subplot]={_subplot:s};var C=i._module.formatLabels(b,i,x);return e.lonLabel=C.lonLabel,e.latLabel=C.latLabel,e.color=Ejt(i,b),e.extraText=eGe(i,b,n[0].t.labels),e.hovertemplate=i.hovertemplate,[e]}}function eGe(e,t,r){if(e.hovertemplate)return;var n=t.hi||e.hoverinfo,i=n.split(\"+\"),a=i.indexOf(\"all\")!==-1,o=i.indexOf(\"lon\")!==-1,s=i.indexOf(\"lat\")!==-1,l=t.lonlat,u=[];function c(f){return f+\"\\xB0\"}return a||o&&s?u.push(\"(\"+c(l[1])+\", \"+c(l[0])+\")\"):o?u.push(r.lon+c(l[0])):s&&u.push(r.lat+c(l[1])),(a||i.indexOf(\"text\")!==-1)&&kjt(t,e,u),u.join(\"<br>\")}tGe.exports={hoverPoints:Pjt,getExtraText:eGe}});var iGe=ye((mxr,rGe)=>{\"use strict\";rGe.exports=function(t,r){return t.lon=r.lon,t.lat=r.lat,t}});var aGe=ye((yxr,nGe)=>{\"use strict\";var Ijt=Dr(),Rjt=Ru(),Djt=fs().BADNUM;nGe.exports=function(t,r){var n=t.cd,i=t.xaxis,a=t.yaxis,o=[],s=n[0].trace,l;if(!Rjt.hasMarkers(s))return[];if(r===!1)for(l=0;l<n.length;l++)n[l].selected=0;else for(l=0;l<n.length;l++){var u=n[l],c=u.lonlat;if(c[0]!==Djt){var f=[Ijt.modHalf(c[0],360),c[1]],h=[i.c2p(f),a.c2p(f)];r.contains(h,null,l,t)?(o.push({pointNumber:l,lon:c[0],lat:c[1]}),u.selected=1):u.selected=0}}return o}});var lJ=ye((oJ,sJ)=>{(function(e,t){typeof oJ==\"object\"&&typeof sJ!=\"undefined\"?sJ.exports=t():(e=e||self,e.mapboxgl=t())})(oJ,function(){\"use strict\";var e,t,r;function n(i,a){if(!e)e=a;else if(!t)t=a;else{var o=\"var sharedChunk = {}; (\"+e+\")(sharedChunk); (\"+t+\")(sharedChunk);\",s={};e(s),r=a(s),typeof window!=\"undefined\"&&(r.workerUrl=window.URL.createObjectURL(new Blob([o],{type:\"text/javascript\"})))}}return n([\"exports\"],function(i){\"use strict\";function a(m,y){return y={exports:{}},m(y,y.exports),y.exports}var o=\"1.13.4\",s=l;function 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Cu(m.default,y.default);var U=m.stops.length;if(U===1||I<=m.stops[0][0])return m.stops[0][1];if(I>=m.stops[U-1][0])return m.stops[U-1][1];var $=hu(m.stops.map(function(ae){return ae[0]}),I);return m.stops[$][1]}function pu(m,y,I){var U=m.base!==void 0?m.base:1;if(no(I)!==\"number\")return Cu(m.default,y.default);var $=m.stops.length;if($===1||I<=m.stops[0][0])return m.stops[0][1];if(I>=m.stops[$-1][0])return m.stops[$-1][1];var ae=hu(m.stops.map(function(or){return or[0]}),I),he=xu(I,U,m.stops[ae][0],m.stops[ae+1][0]),Oe=m.stops[ae][1],rt=m.stops[ae+1][1],gt=zu[y.type]||rs;if(m.colorSpace&&m.colorSpace!==\"rgb\"){var Et=Xf[m.colorSpace];gt=function(or,_r){return Et.reverse(Et.interpolate(Et.forward(or),Et.forward(_r),he))}}return typeof Oe.evaluate==\"function\"?{evaluate:function(){for(var _r=[],pr=arguments.length;pr--;)_r[pr]=arguments[pr];var Fr=Oe.evaluate.apply(void 0,_r),oi=rt.evaluate.apply(void 0,_r);if(!(Fr===void 0||oi===void 0))return gt(Fr,oi,he)}}:gt(Oe,rt,he)}function Uc(m,y,I){return y.type===\"color\"?I=cs.parse(I):y.type===\"formatted\"?I=Jl.fromString(I.toString()):y.type===\"resolvedImage\"?I=fl.fromString(I.toString()):no(I)!==y.type&&(y.type!==\"enum\"||!y.values[I])&&(I=void 0),Cu(I,m.default,y.default)}function xu(m,y,I,U){var $=U-I,ae=m-I;return $===0?0:y===1?ae/$:(Math.pow(y,ae)-1)/(Math.pow(y,$)-1)}var Ac=function(y,I){this.expression=y,this._warningHistory={},this._evaluator=new Yo,this._defaultValue=I?ee(I):null,this._enumValues=I&&I.type===\"enum\"?I.values:null};Ac.prototype.evaluateWithoutErrorHandling=function(y,I,U,$,ae,he){return this._evaluator.globals=y,this._evaluator.feature=I,this._evaluator.featureState=U,this._evaluator.canonical=$,this._evaluator.availableImages=ae||null,this._evaluator.formattedSection=he,this.expression.evaluate(this._evaluator)},Ac.prototype.evaluate=function(y,I,U,$,ae,he){this._evaluator.globals=y,this._evaluator.feature=I||null,this._evaluator.featureState=U||null,this._evaluator.canonical=$,this._evaluator.availableImages=ae||null,this._evaluator.formattedSection=he||null;try{var Oe=this.expression.evaluate(this._evaluator);if(Oe==null||typeof Oe==\"number\"&&Oe!==Oe)return this._defaultValue;if(this._enumValues&&!(Oe in this._enumValues))throw new ps(\"Expected value to be one of \"+Object.keys(this._enumValues).map(function(rt){return JSON.stringify(rt)}).join(\", \")+\", but found \"+JSON.stringify(Oe)+\" instead.\");return Oe}catch(rt){return this._warningHistory[rt.message]||(this._warningHistory[rt.message]=!0,typeof console!=\"undefined\"&&console.warn(rt.message)),this._defaultValue}};function Ua(m){return Array.isArray(m)&&m.length>0&&typeof m[0]==\"string\"&&m[0]in Ka}function oo(m,y){var I=new ks(Ka,[],y?Q(y):void 0),U=I.parse(m,void 0,void 0,void 0,y&&y.type===\"string\"?{typeAnnotation:\"coerce\"}:void 0);return U?Ho(new Ac(U,y)):ml(I.errors)}var Vc=function(y,I){this.kind=y,this._styleExpression=I,this.isStateDependent=y!==\"constant\"&&!js(I.expression)};Vc.prototype.evaluateWithoutErrorHandling=function(y,I,U,$,ae,he){return this._styleExpression.evaluateWithoutErrorHandling(y,I,U,$,ae,he)},Vc.prototype.evaluate=function(y,I,U,$,ae,he){return this._styleExpression.evaluate(y,I,U,$,ae,he)};var hc=function(y,I,U,$){this.kind=y,this.zoomStops=U,this._styleExpression=I,this.isStateDependent=y!==\"camera\"&&!js(I.expression),this.interpolationType=$};hc.prototype.evaluateWithoutErrorHandling=function(y,I,U,$,ae,he){return this._styleExpression.evaluateWithoutErrorHandling(y,I,U,$,ae,he)},hc.prototype.evaluate=function(y,I,U,$,ae,he){return this._styleExpression.evaluate(y,I,U,$,ae,he)},hc.prototype.interpolationFactor=function(y,I,U){return this.interpolationType?Wl.interpolationFactor(this.interpolationType,y,I,U):0};function Ku(m,y){if(m=oo(m,y),m.result===\"error\")return m;var I=m.value.expression,U=ih(I);if(!U&&!Ws(y))return ml([new Ns(\"\",\"data expressions not supported\")]);var $=Eu(I,[\"zoom\"]);if(!$&&!Ls(y))return ml([new Ns(\"\",\"zoom expressions not supported\")]);var ae=B(I);if(!ae&&!$)return ml([new Ns(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.')]);if(ae instanceof Ns)return ml([ae]);if(ae instanceof Wl&&!va(y))return ml([new Ns(\"\",'\"interpolate\" expressions cannot be used with this property')]);if(!ae)return Ho(U?new Vc(\"constant\",m.value):new Vc(\"source\",m.value));var he=ae instanceof Wl?ae.interpolation:void 0;return Ho(U?new hc(\"camera\",m.value,ae.labels,he):new hc(\"composite\",m.value,ae.labels,he))}var ue=function(y,I){this._parameters=y,this._specification=I,Ol(this,$l(this._parameters,this._specification))};ue.deserialize=function(y){return new ue(y._parameters,y._specification)},ue.serialize=function(y){return{_parameters:y._parameters,_specification:y._specification}};function w(m,y){if(ys(m))return new ue(m,y);if(Ua(m)){var I=Ku(m,y);if(I.result===\"error\")throw new Error(I.value.map(function($){return $.key+\": \"+$.message}).join(\", \"));return I.value}else{var U=m;return typeof m==\"string\"&&y.type===\"color\"&&(U=cs.parse(m)),{kind:\"constant\",evaluate:function(){return U}}}}function B(m){var y=null;if(m instanceof Oc)y=B(m.result);else if(m instanceof Zu)for(var I=0,U=m.args;I<U.length;I+=1){var $=U[I];if(y=B($),y)break}else(m instanceof _u||m instanceof Wl)&&m.input instanceof Pa&&m.input.name===\"zoom\"&&(y=m);return y instanceof Ns||m.eachChild(function(ae){var he=B(ae);he instanceof Ns?y=he:!y&&he?y=new Ns(\"\",'\"zoom\" expression may only be used as input to a top-level \"step\" or \"interpolate\" expression.'):y&&he&&y!==he&&(y=new Ns(\"\",'Only one zoom-based \"step\" or \"interpolate\" subexpression may be used in an expression.'))}),y}function Q(m){var y={color:ql,string:Oo,number:aa,enum:Oo,boolean:qo,formatted:pl,resolvedImage:Zc};return m.type===\"array\"?Kl(y[m.value]||Do,m.length):y[m.type]}function ee(m){return m.type===\"color\"&&ys(m.default)?new cs(0,0,0,0):m.type===\"color\"?cs.parse(m.default)||null:m.default===void 0?null:m.default}function le(m){var y=m.key,I=m.value,U=m.valueSpec||{},$=m.objectElementValidators||{},ae=m.style,he=m.styleSpec,Oe=[],rt=no(I);if(rt!==\"object\")return[new _a(y,I,\"object expected, \"+rt+\" found\")];for(var gt in I){var Et=gt.split(\".\")[0],or=U[Et]||U[\"*\"],_r=void 0;if($[Et])_r=$[Et];else if(U[Et])_r=Qa;else if($[\"*\"])_r=$[\"*\"];else if(U[\"*\"])_r=Qa;else{Oe.push(new 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rt=[],gt=0;gt<y.length;gt++)rt=rt.concat(he({array:y,arrayIndex:gt,value:y[gt],valueSpec:Oe,style:U,styleSpec:$,key:ae+\"[\"+gt+\"]\"}));return rt}function Xe(m){var y=m.key,I=m.value,U=m.valueSpec,$=no(I);return $===\"number\"&&I!==I&&($=\"NaN\"),$!==\"number\"?[new _a(y,I,\"number expected, \"+$+\" found\")]:\"minimum\"in U&&I<U.minimum?[new _a(y,I,I+\" is less than the minimum value \"+U.minimum)]:\"maximum\"in U&&I>U.maximum?[new _a(y,I,I+\" is greater than the maximum value \"+U.maximum)]:[]}function ot(m){var y=m.valueSpec,I=xo(m.value.type),U,$={},ae,he,Oe=I!==\"categorical\"&&m.value.property===void 0,rt=!Oe,gt=no(m.value.stops)===\"array\"&&no(m.value.stops[0])===\"array\"&&no(m.value.stops[0][0])===\"object\",Et=le({key:m.key,value:m.value,valueSpec:m.styleSpec.function,style:m.style,styleSpec:m.styleSpec,objectElementValidators:{stops:or,default:Fr}});return I===\"identity\"&&Oe&&Et.push(new _a(m.key,m.value,'missing required property 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Hi=[],Ai=oi.value,bn=oi.key;if(no(Ai)!==\"array\")return[new _a(bn,Ai,\"array expected, \"+no(Ai)+\" found\")];if(Ai.length!==2)return[new _a(bn,Ai,\"array length 2 expected, length \"+Ai.length+\" found\")];if(gt){if(no(Ai[0])!==\"object\")return[new _a(bn,Ai,\"object expected, \"+no(Ai[0])+\" found\")];if(Ai[0].zoom===void 0)return[new _a(bn,Ai,\"object stop key must have zoom\")];if(Ai[0].value===void 0)return[new _a(bn,Ai,\"object stop key must have value\")];if(he&&he>xo(Ai[0].zoom))return[new _a(bn,Ai[0].zoom,\"stop zoom values must appear in ascending order\")];xo(Ai[0].zoom)!==he&&(he=xo(Ai[0].zoom),ae=void 0,$={}),Hi=Hi.concat(le({key:bn+\"[0]\",value:Ai[0],valueSpec:{zoom:{}},style:oi.style,styleSpec:oi.styleSpec,objectElementValidators:{zoom:Xe,value:pr}}))}else Hi=Hi.concat(pr({key:bn+\"[0]\",value:Ai[0],valueSpec:{},style:oi.style,styleSpec:oi.styleSpec},Ai));return Ua(Yl(Ai[1]))?Hi.concat([new _a(bn+\"[1]\",Ai[1],\"expressions are not allowed in function stops.\")]):Hi.concat(Qa({key:bn+\"[1]\",value:Ai[1],valueSpec:y,style:oi.style,styleSpec:oi.styleSpec}))}function pr(oi,Hi){var Ai=no(oi.value),bn=xo(oi.value),nn=oi.value!==null?oi.value:Hi;if(!U)U=Ai;else if(Ai!==U)return[new _a(oi.key,nn,Ai+\" stop domain type must match previous stop domain type \"+U)];if(Ai!==\"number\"&&Ai!==\"string\"&&Ai!==\"boolean\")return[new _a(oi.key,nn,\"stop domain value must be a number, string, or boolean\")];if(Ai!==\"number\"&&I!==\"categorical\"){var xn=\"number expected, \"+Ai+\" found\";return Ws(y)&&I===void 0&&(xn+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new _a(oi.key,nn,xn)]}return I===\"categorical\"&&Ai===\"number\"&&(!isFinite(bn)||Math.floor(bn)!==bn)?[new _a(oi.key,nn,\"integer expected, found \"+bn)]:I!==\"categorical\"&&Ai===\"number\"&&ae!==void 0&&bn<ae?[new _a(oi.key,nn,\"stop domain values must appear in ascending order\")]:(ae=bn,I===\"categorical\"&&bn in $?[new _a(oi.key,nn,\"stop domain values must be unique\")]:($[bn]=!0,[]))}function Fr(oi){return Qa({key:oi.key,value:oi.value,valueSpec:y,style:oi.style,styleSpec:oi.styleSpec})}}function Tt(m){var y=(m.expressionContext===\"property\"?Ku:oo)(Yl(m.value),m.valueSpec);if(y.result===\"error\")return y.value.map(function(U){return new _a(\"\"+m.key+U.key,m.value,U.message)});var I=y.value.expression||y.value._styleExpression.expression;if(m.expressionContext===\"property\"&&m.propertyKey===\"text-font\"&&!I.outputDefined())return[new _a(m.key,m.value,'Invalid data expression for \"'+m.propertyKey+'\". Output values must be contained as literals within the expression.')];if(m.expressionContext===\"property\"&&m.propertyType===\"layout\"&&!js(I))return[new _a(m.key,m.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(m.expressionContext===\"filter\"&&!js(I))return[new _a(m.key,m.value,'\"feature-state\" data expressions are not supported with filters.')];if(m.expressionContext&&m.expressionContext.indexOf(\"cluster\")===0){if(!Eu(I,[\"zoom\",\"feature-state\"]))return[new _a(m.key,m.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(m.expressionContext===\"cluster-initial\"&&!ih(I))return[new _a(m.key,m.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function Yt(m){var y=m.value,I=m.key,U=no(y);return U!==\"boolean\"?[new _a(I,y,\"boolean expected, \"+U+\" found\")]:[]}function Kt(m){var y=m.key,I=m.value,U=no(I);return U!==\"string\"?[new _a(y,I,\"color expected, \"+U+\" found\")]:Lf(I)===null?[new _a(y,I,'color expected, \"'+I+'\" found')]:[]}function xr(m){var y=m.key,I=m.value,U=m.valueSpec,$=[];return Array.isArray(U.values)?U.values.indexOf(xo(I))===-1&&$.push(new _a(y,I,\"expected one of [\"+U.values.join(\", \")+\"], \"+JSON.stringify(I)+\" found\")):Object.keys(U.values).indexOf(xo(I))===-1&&$.push(new _a(y,I,\"expected one of [\"+Object.keys(U.values).join(\", \")+\"], \"+JSON.stringify(I)+\" found\")),$}function Ir(m){if(m===!0||m===!1)return!0;if(!Array.isArray(m)||m.length===0)return!1;switch(m[0]){case\"has\":return m.length>=2&&m[1]!==\"$id\"&&m[1]!==\"$type\";case\"in\":return m.length>=3&&(typeof m[1]!=\"string\"||Array.isArray(m[2]));case\"!in\":case\"!has\":case\"none\":return!1;case\"==\":case\"!=\":case\">\":case\">=\":case\"<\":case\"<=\":return m.length!==3||Array.isArray(m[1])||Array.isArray(m[2]);case\"any\":case\"all\":for(var y=0,I=m.slice(1);y<I.length;y+=1){var U=I[y];if(!Ir(U)&&typeof U!=\"boolean\")return!1}return!0;default:return!0}}var ve={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function be(m){if(m==null)return{filter:function(){return!0},needGeometry:!1};Ir(m)||(m=et(m));var y=oo(m,ve);if(y.result===\"error\")throw new Error(y.value.map(function(U){return U.key+\": \"+U.message}).join(\", \"));var I=Be(m);return{filter:function(U,$,ae){return y.value.evaluate(U,$,{},ae)},needGeometry:I}}function De(m,y){return m<y?-1:m>y?1:0}function Be(m){if(!Array.isArray(m))return!1;if(m[0]===\"within\")return!0;for(var y=1;y<m.length;y++)if(Be(m[y]))return!0;return!1}function et(m){if(!m)return!0;var y=m[0];if(m.length<=1)return y!==\"any\";var I=y===\"==\"?We(m[1],m[2],\"==\"):y===\"!=\"?tr(We(m[1],m[2],\"==\")):y===\"<\"||y===\">\"||y===\"<=\"||y===\">=\"?We(m[1],m[2],y):y===\"any\"?it(m.slice(1)):y===\"all\"?[\"all\"].concat(m.slice(1).map(et)):y===\"none\"?[\"all\"].concat(m.slice(1).map(et).map(tr)):y===\"in\"?Ft(m[1],m.slice(2)):y===\"!in\"?tr(Ft(m[1],m.slice(2))):y===\"has\"?Ht(m[1]):y===\"!has\"?tr(Ht(m[1])):y===\"within\"?m:!0;return I}function We(m,y,I){switch(m){case\"$type\":return[\"filter-type-\"+I,y];case\"$id\":return[\"filter-id-\"+I,y];default:return[\"filter-\"+I,m,y]}}function it(m){return[\"any\"].concat(m.map(et))}function Ft(m,y){if(y.length===0)return!1;switch(m){case\"$type\":return[\"filter-type-in\",[\"literal\",y]];case\"$id\":return[\"filter-id-in\",[\"literal\",y]];default:return y.length>200&&!y.some(function(I){return typeof I!=typeof y[0]})?[\"filter-in-large\",m,[\"literal\",y.sort(De)]]:[\"filter-in-small\",m,[\"literal\",y]]}}function 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y.paint._values)if(U(ae)){var he=y.paint.get(ae);if(!(!(he instanceof dl)||!Ws(he.property.specification))){var Oe=Ti(ae,y.type),rt=he.value,gt=he.property.specification.type,Et=he.property.useIntegerZoom,or=he.property.specification[\"property-type\"],_r=or===\"cross-faded\"||or===\"cross-faded-data-driven\";if(rt.kind===\"constant\")this.binders[ae]=_r?new ht(rt.value,Oe):new Pt(rt.value,Oe,gt),$.push(\"/u_\"+ae);else if(rt.kind===\"source\"||_r){var pr=rn(ae,gt,\"source\");this.binders[ae]=_r?new Ur(rt,gt,Et,I,pr,y.id):new ur(rt,Oe,gt,pr),$.push(\"/a_\"+ae)}else{var Fr=rn(ae,gt,\"composite\");this.binders[ae]=new br(rt,Oe,gt,Et,I,Fr),$.push(\"/z_\"+ae)}}}this.cacheKey=$.sort().join(\"\")};Di.prototype.getMaxValue=function(y){var I=this.binders[y];return I instanceof ur||I instanceof br?I.maxValue:0},Di.prototype.populatePaintArrays=function(y,I,U,$,ae){for(var he in this.binders){var Oe=this.binders[he];(Oe instanceof ur||Oe instanceof br||Oe instanceof 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vg(I,I.readVarint()+I.pos);U.length&&(y[U.name]=U)}}var BC=qC,k1=pS,NC=vg,pg={VectorTile:BC,VectorTileFeature:k1,VectorTileLayer:NC},UC=pg.VectorTileFeature.types,qw=500,C1=Math.pow(2,13);function cm(m,y,I,U,$,ae,he,Oe){m.emplaceBack(y,I,Math.floor(U*C1)*2+he,$*C1*2,ae*C1*2,Math.round(Oe))}var Vp=function(y){this.zoom=y.zoom,this.overscaling=y.overscaling,this.layers=y.layers,this.layerIds=this.layers.map(function(I){return I.id}),this.index=y.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new pn,this.programConfigurations=new fi(y.layers,y.zoom),this.segments=new io,this.stateDependentLayerIds=this.layers.filter(function(I){return I.isStateDependent()}).map(function(I){return I.id})};Vp.prototype.populate=function(y,I,U){this.features=[],this.hasPattern=Ow(\"fill-extrusion\",this.layers,I);for(var $=0,ae=y;$<ae.length;$+=1){var he=ae[$],Oe=he.feature,rt=he.id,gt=he.index,Et=he.sourceLayerIndex,or=this.layers[0]._featureFilter.needGeometry,_r=Ja(Oe,or);if(this.layers[0]._featureFilter.filter(new Gn(this.zoom),_r,U)){var pr={id:rt,sourceLayerIndex:Et,index:gt,geometry:or?_r.geometry:zn(Oe),properties:Oe.properties,type:Oe.type,patterns:{}};this.hasPattern?this.features.push(Jx(\"fill-extrusion\",this.layers,pr,this.zoom,I)):this.addFeature(pr,pr.geometry,gt,U,{}),I.featureIndex.insert(Oe,pr.geometry,gt,Et,this.index,!0)}}},Vp.prototype.addFeatures=function(y,I,U){for(var $=0,ae=this.features;$<ae.length;$+=1){var he=ae[$],Oe=he.geometry;this.addFeature(he,Oe,he.index,I,U)}},Vp.prototype.update=function(y,I,U){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(y,I,this.stateDependentLayers,U)},Vp.prototype.isEmpty=function(){return 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xn=Hi[bn-1];if(!eO(nn,xn)){pr.vertexLength+4>io.MAX_VERTEX_ARRAY_LENGTH&&(pr=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var Pn=nn.sub(xn)._perp()._unit(),Zn=xn.dist(nn);Ai+Zn>32768&&(Ai=0),cm(this.layoutVertexArray,nn.x,nn.y,Pn.x,Pn.y,0,0,Ai),cm(this.layoutVertexArray,nn.x,nn.y,Pn.x,Pn.y,0,1,Ai),Ai+=Zn,cm(this.layoutVertexArray,xn.x,xn.y,Pn.x,Pn.y,0,0,Ai),cm(this.layoutVertexArray,xn.x,xn.y,Pn.x,Pn.y,0,1,Ai);var ga=pr.vertexLength;this.indexArray.emplaceBack(ga,ga+2,ga+1),this.indexArray.emplaceBack(ga+1,ga+2,ga+3),pr.vertexLength+=4,pr.primitiveLength+=2}}}}if(pr.vertexLength+gt>io.MAX_VERTEX_ARRAY_LENGTH&&(pr=this.segments.prepareSegment(gt,this.layoutVertexArray,this.indexArray)),UC[y.type]===\"Polygon\"){for(var ha=[],eo=[],za=pr.vertexLength,Za=0,Ko=rt;Za<Ko.length;Za+=1){var to=Ko[Za];if(to.length!==0){to!==rt[0]&&eo.push(ha.length/2);for(var ao=0;ao<to.length;ao++){var _s=to[ao];cm(this.layoutVertexArray,_s.x,_s.y,0,0,1,1,0),ha.push(_s.x),ha.push(_s.y)}}}for(var jo=Iw(ha,eo),El=0;El<jo.length;El+=3)this.indexArray.emplaceBack(za+jo[El],za+jo[El+2],za+jo[El+1]);pr.primitiveLength+=jo.length/3,pr.vertexLength+=gt}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,y,U,ae,$)},X(\"FillExtrusionBucket\",Vp,{omit:[\"layers\",\"features\"]});function eO(m,y){return m.x===y.x&&(m.x<0||m.x>Ci)||m.y===y.y&&(m.y<0||m.y>Ci)}function tO(m){return m.every(function(y){return y.x<0})||m.every(function(y){return y.x>Ci})||m.every(function(y){return y.y<0})||m.every(function(y){return y.y>Ci})}var L1=new Nr({\"fill-extrusion-opacity\":new Me(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new bt(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new Me(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new Me(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new zt(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new bt(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new bt(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new Me(Rn[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])}),sd={paint:L1},fm=function(m){function y(I){m.call(this,I,sd)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.createBucket=function(U){return new Vp(U)},y.prototype.queryRadius=function(){return Pv(this.paint.get(\"fill-extrusion-translate\"))},y.prototype.is3D=function(){return!0},y.prototype.queryIntersectsFeature=function(U,$,ae,he,Oe,rt,gt,Et){var or=Jv(U,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),rt.angle,gt),_r=this.paint.get(\"fill-extrusion-height\").evaluate($,ae),pr=this.paint.get(\"fill-extrusion-base\").evaluate($,ae),Fr=rO(or,Et,rt,0),oi=yS(he,pr,_r,Et),Hi=oi[0],Ai=oi[1];return VC(Hi,Ai,Fr)},y}(mi);function hy(m,y){return m.x*y.x+m.y*y.y}function mS(m,y){if(m.length===1){for(var I=0,U=y[I++],$;!$||U.equals($);)if($=y[I++],!$)return 1/0;for(;I<y.length;I++){var ae=y[I],he=m[0],Oe=$.sub(U),rt=ae.sub(U),gt=he.sub(U),Et=hy(Oe,Oe),or=hy(Oe,rt),_r=hy(rt,rt),pr=hy(gt,Oe),Fr=hy(gt,rt),oi=Et*_r-or*or,Hi=(_r*pr-or*Fr)/oi,Ai=(Et*Fr-or*pr)/oi,bn=1-Hi-Ai,nn=U.z*bn+$.z*Hi+ae.z*Ai;if(isFinite(nn))return nn}return 1/0}else{for(var xn=1/0,Pn=0,Zn=y;Pn<Zn.length;Pn+=1){var ga=Zn[Pn];xn=Math.min(xn,ga.z)}return xn}}function VC(m,y,I){var U=1/0;ms(I,y)&&(U=mS(I,y[0]));for(var $=0;$<y.length;$++)for(var ae=y[$],he=m[$],Oe=0;Oe<ae.length-1;Oe++){var rt=ae[Oe],gt=ae[Oe+1],Et=he[Oe],or=he[Oe+1],_r=[rt,gt,or,Et,rt];so(I,_r)&&(U=Math.min(U,mS(I,_r)))}return U===1/0?!1:U}function yS(m,y,I,U){for(var $=[],ae=[],he=U[8]*y,Oe=U[9]*y,rt=U[10]*y,gt=U[11]*y,Et=U[8]*I,or=U[9]*I,_r=U[10]*I,pr=U[11]*I,Fr=0,oi=m;Fr<oi.length;Fr+=1){for(var Hi=oi[Fr],Ai=[],bn=[],nn=0,xn=Hi;nn<xn.length;nn+=1){var Pn=xn[nn],Zn=Pn.x,ga=Pn.y,ha=U[0]*Zn+U[4]*ga+U[12],eo=U[1]*Zn+U[5]*ga+U[13],za=U[2]*Zn+U[6]*ga+U[14],Za=U[3]*Zn+U[7]*ga+U[15],Ko=ha+he,to=eo+Oe,ao=za+rt,_s=Za+gt,jo=ha+Et,El=eo+or,Iu=za+_r,kl=Za+pr,Cl=new u(Ko/_s,to/_s);Cl.z=ao/_s,Ai.push(Cl);var yl=new u(jo/kl,El/kl);yl.z=Iu/kl,bn.push(yl)}$.push(Ai),ae.push(bn)}return[$,ae]}function rO(m,y,I,U){for(var $=[],ae=0,he=m;ae<he.length;ae+=1){var Oe=he[ae],rt=[Oe.x,Oe.y,U,1];uy(rt,rt,y),$.push(new u(rt[0]/rt[3],rt[1]/rt[3]))}return $}var GC=Wi([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4),HC=GC.members,iO=Wi([{name:\"a_uv_x\",components:1,type:\"Float32\"},{name:\"a_split_index\",components:1,type:\"Float32\"}]),jC=iO.members,_S=pg.VectorTileFeature.types,Bw=63,WC=Math.cos(75/2*(Math.PI/180)),eb=15,xS=20,XC=15,Nw=1/2,tb=Math.pow(2,XC-1)/Nw,sh=function(y){var I=this;this.zoom=y.zoom,this.overscaling=y.overscaling,this.layers=y.layers,this.layerIds=this.layers.map(function(U){return U.id}),this.index=y.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach(function(U){I.gradients[U.id]={}}),this.layoutVertexArray=new ci,this.layoutVertexArray2=new an,this.indexArray=new pn,this.programConfigurations=new fi(y.layers,y.zoom),this.segments=new io,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter(function(U){return U.isStateDependent()}).map(function(U){return U.id})};sh.prototype.populate=function(y,I,U){this.hasPattern=Ow(\"line\",this.layers,I);for(var $=this.layers[0].layout.get(\"line-sort-key\"),ae=[],he=0,Oe=y;he<Oe.length;he+=1){var rt=Oe[he],gt=rt.feature,Et=rt.id,or=rt.index,_r=rt.sourceLayerIndex,pr=this.layers[0]._featureFilter.needGeometry,Fr=Ja(gt,pr);if(this.layers[0]._featureFilter.filter(new Gn(this.zoom),Fr,U)){var oi=$?$.evaluate(Fr,{},U):void 0,Hi={id:Et,properties:gt.properties,type:gt.type,sourceLayerIndex:_r,index:or,geometry:pr?Fr.geometry:zn(gt),patterns:{},sortKey:oi};ae.push(Hi)}}$&&ae.sort(function(za,Za){return za.sortKey-Za.sortKey});for(var Ai=0,bn=ae;Ai<bn.length;Ai+=1){var nn=bn[Ai],xn=nn,Pn=xn.geometry,Zn=xn.index,ga=xn.sourceLayerIndex;if(this.hasPattern){var ha=Jx(\"line\",this.layers,nn,this.zoom,I);this.patternFeatures.push(ha)}else this.addFeature(nn,Pn,Zn,U,{});var eo=y[Zn].feature;I.featureIndex.insert(eo,Pn,Zn,ga,this.index)}},sh.prototype.update=function(y,I,U){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(y,I,this.stateDependentLayers,U)},sh.prototype.addFeatures=function(y,I,U){for(var $=0,ae=this.patternFeatures;$<ae.length;$+=1){var he=ae[$];this.addFeature(he,he.geometry,he.index,I,U)}},sh.prototype.isEmpty=function(){return this.layoutVertexArray.length===0},sh.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},sh.prototype.upload=function(y){this.uploaded||(this.layoutVertexArray2.length!==0&&(this.layoutVertexBuffer2=y.createVertexBuffer(this.layoutVertexArray2,jC)),this.layoutVertexBuffer=y.createVertexBuffer(this.layoutVertexArray,HC),this.indexBuffer=y.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(y),this.uploaded=!0},sh.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},sh.prototype.lineFeatureClips=function(y){if(y.properties&&y.properties.hasOwnProperty(\"mapbox_clip_start\")&&y.properties.hasOwnProperty(\"mapbox_clip_end\")){var I=+y.properties.mapbox_clip_start,U=+y.properties.mapbox_clip_end;return{start:I,end:U}}},sh.prototype.addFeature=function(y,I,U,$,ae){var he=this.layers[0].layout,Oe=he.get(\"line-join\").evaluate(y,{}),rt=he.get(\"line-cap\"),gt=he.get(\"line-miter-limit\"),Et=he.get(\"line-round-limit\");this.lineClips=this.lineFeatureClips(y);for(var or=0,_r=I;or<_r.length;or+=1){var pr=_r[or];this.addLine(pr,y,Oe,rt,gt,Et)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,y,U,ae,$)},sh.prototype.addLine=function(y,I,U,$,ae,he){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(var Oe=0;Oe<y.length-1;Oe++)this.totalDistance+=y[Oe].dist(y[Oe+1]);this.updateScaledDistance(),this.maxLineLength=Math.max(this.maxLineLength,this.totalDistance)}for(var rt=_S[I.type]===\"Polygon\",gt=y.length;gt>=2&&y[gt-1].equals(y[gt-2]);)gt--;for(var Et=0;Et<gt-1&&y[Et].equals(y[Et+1]);)Et++;if(!(gt<(rt?3:2))){U===\"bevel\"&&(ae=1.05);var or=this.overscaling<=16?eb*Ci/(512*this.overscaling):0,_r=this.segments.prepareSegment(gt*10,this.layoutVertexArray,this.indexArray),pr,Fr=void 0,oi=void 0,Hi=void 0,Ai=void 0;this.e1=this.e2=-1,rt&&(pr=y[gt-2],Ai=y[Et].sub(pr)._unit()._perp());for(var bn=Et;bn<gt;bn++)if(oi=bn===gt-1?rt?y[Et+1]:void 0:y[bn+1],!(oi&&y[bn].equals(oi))){Ai&&(Hi=Ai),pr&&(Fr=pr),pr=y[bn],Ai=oi?oi.sub(pr)._unit()._perp():Hi,Hi=Hi||Ai;var nn=Hi.add(Ai);(nn.x!==0||nn.y!==0)&&nn._unit();var xn=Hi.x*Ai.x+Hi.y*Ai.y,Pn=nn.x*Ai.x+nn.y*Ai.y,Zn=Pn!==0?1/Pn:1/0,ga=2*Math.sqrt(2-2*Pn),ha=Pn<WC&&Fr&&oi,eo=Hi.x*Ai.y-Hi.y*Ai.x>0;if(ha&&bn>Et){var za=pr.dist(Fr);if(za>2*or){var Za=pr.sub(pr.sub(Fr)._mult(or/za)._round());this.updateDistance(Fr,Za),this.addCurrentVertex(Za,Hi,0,0,_r),Fr=Za}}var Ko=Fr&&oi,to=Ko?U:rt?\"butt\":$;if(Ko&&to===\"round\"&&(Zn<he?to=\"miter\":Zn<=2&&(to=\"fakeround\")),to===\"miter\"&&Zn>ae&&(to=\"bevel\"),to===\"bevel\"&&(Zn>2&&(to=\"flipbevel\"),Zn<ae&&(to=\"miter\")),Fr&&this.updateDistance(Fr,pr),to===\"miter\")nn._mult(Zn),this.addCurrentVertex(pr,nn,0,0,_r);else if(to===\"flipbevel\"){if(Zn>100)nn=Ai.mult(-1);else{var ao=Zn*Hi.add(Ai).mag()/Hi.sub(Ai).mag();nn._perp()._mult(ao*(eo?-1:1))}this.addCurrentVertex(pr,nn,0,0,_r),this.addCurrentVertex(pr,nn.mult(-1),0,0,_r)}else if(to===\"bevel\"||to===\"fakeround\"){var _s=-Math.sqrt(Zn*Zn-1),jo=eo?_s:0,El=eo?0:_s;if(Fr&&this.addCurrentVertex(pr,Hi,jo,El,_r),to===\"fakeround\")for(var Iu=Math.round(ga*180/Math.PI/xS),kl=1;kl<Iu;kl++){var Cl=kl/Iu;if(Cl!==.5){var yl=Cl-.5,Qu=1.0904+xn*(-3.2452+xn*(3.55645-xn*1.43519)),gc=.848013+xn*(-1.06021+xn*.215638);Cl=Cl+Cl*yl*(Cl-1)*(Qu*yl*yl+gc)}var Sf=Ai.sub(Hi)._mult(Cl)._add(Hi)._unit()._mult(eo?-1:1);this.addHalfVertex(pr,Sf.x,Sf.y,!1,eo,0,_r)}oi&&this.addCurrentVertex(pr,Ai,-jo,-El,_r)}else if(to===\"butt\")this.addCurrentVertex(pr,nn,0,0,_r);else if(to===\"square\"){var Ff=Fr?1:-1;this.addCurrentVertex(pr,nn,Ff,Ff,_r)}else to===\"round\"&&(Fr&&(this.addCurrentVertex(pr,Hi,0,0,_r),this.addCurrentVertex(pr,Hi,1,1,_r,!0)),oi&&(this.addCurrentVertex(pr,Ai,-1,-1,_r,!0),this.addCurrentVertex(pr,Ai,0,0,_r)));if(ha&&bn<gt-1){var Yh=pr.dist(oi);if(Yh>2*or){var ch=pr.add(oi.sub(pr)._mult(or/Yh)._round());this.updateDistance(pr,ch),this.addCurrentVertex(ch,Ai,0,0,_r),pr=ch}}}}},sh.prototype.addCurrentVertex=function(y,I,U,$,ae,he){he===void 0&&(he=!1);var Oe=I.x+I.y*U,rt=I.y-I.x*U,gt=-I.x+I.y*$,Et=-I.y-I.x*$;this.addHalfVertex(y,Oe,rt,he,!1,U,ae),this.addHalfVertex(y,gt,Et,he,!0,-$,ae),this.distance>tb/2&&this.totalDistance===0&&(this.distance=0,this.addCurrentVertex(y,I,U,$,ae,he))},sh.prototype.addHalfVertex=function(y,I,U,$,ae,he,Oe){var rt=y.x,gt=y.y,Et=this.lineClips?this.scaledDistance*(tb-1):this.scaledDistance,or=Et*Nw;if(this.layoutVertexArray.emplaceBack((rt<<1)+($?1:0),(gt<<1)+(ae?1:0),Math.round(Bw*I)+128,Math.round(Bw*U)+128,(he===0?0:he<0?-1:1)+1|(or&63)<<2,or>>6),this.lineClips){var _r=this.scaledDistance-this.lineClips.start,pr=this.lineClips.end-this.lineClips.start,Fr=_r/pr;this.layoutVertexArray2.emplaceBack(Fr,this.lineClipsArray.length)}var 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yl=rt.get(\"text-radial-offset\").evaluate(ha,{},he);yl?_s=UQ(kl,[yl*Tn,cO]):_s=rt.get(\"text-offset\").evaluate(ha,{},he).map(function(gy){return gy*Tn})}var Qu=bn?\"center\":rt.get(\"text-justify\").evaluate(ha,{},he),gc=rt.get(\"symbol-placement\"),Sf=gc===\"point\"?rt.get(\"text-max-width\").evaluate(ha,{},he)*Tn:0,Ff=function(){m.allowVerticalPlacement&&jt(jo)&&(to.vertical=Gw(ao,y,I,$,eo,Sf,Ai,kl,\"left\",Iu,_s,uv.vertical,!0,gc,Za,za))};if(!bn&&Cl){for(var Yh=Qu===\"auto\"?Cl.map(function(gy){return fO(gy)}):[Qu],ch=!1,Xd=0;Xd<Yh.length;Xd++){var Zd=Yh[Xd];if(!to.horizontal[Zd])if(ch)to.horizontal[Zd]=to.horizontal[0];else{var Kh=Gw(ao,y,I,$,eo,Sf,Ai,\"center\",Zd,Iu,_s,uv.horizontal,!1,gc,Za,za);Kh&&(to.horizontal[Zd]=Kh,ch=Kh.positionedLines.length===1)}}Ff()}else{Qu===\"auto\"&&(Qu=fO(kl));var fv=Gw(ao,y,I,$,eo,Sf,Ai,kl,Qu,Iu,_s,uv.horizontal,!1,gc,Za,za);fv&&(to.horizontal[Qu]=fv),Ff(),jt(jo)&&bn&&nn&&(to.vertical=Gw(ao,y,I,$,eo,Sf,Ai,kl,Qu,Iu,_s,uv.vertical,!1,gc,Za,za))}}var hv=void 0,Ch=!1;if(ha.icon&&ha.icon.name){var dv=U[ha.icon.name];dv&&(hv=rp($[ha.icon.name],rt.get(\"icon-offset\").evaluate(ha,{},he),rt.get(\"icon-anchor\").evaluate(ha,{},he)),Ch=dv.sdf,m.sdfIcons===void 0?m.sdfIcons=dv.sdf:m.sdfIcons!==dv.sdf&&re(\"Style sheet warning: Cannot mix SDF and non-SDF icons in one buffer\"),(dv.pixelRatio!==m.pixelRatio||rt.get(\"icon-rotate\").constantOr(1)!==0)&&(m.iconsNeedLinear=!0))}var xp=GQ(to.horizontal)||to.vertical;m.iconsInText=xp?xp.iconsInText:!1,(xp||hv)&&Det(m,ha,to,hv,U,Et,Za,Ko,_s,Ch,he)},Zn=0,ga=m.features;Zn<ga.length;Zn+=1)Pn();ae&&m.generateCollisionDebugBuffers()}function fO(m){switch(m){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function Det(m,y,I,U,$,ae,he,Oe,rt,gt,Et){var or=ae.textMaxSize.evaluate(y,{});or===void 0&&(or=he);var _r=m.layers[0].layout,pr=_r.get(\"icon-offset\").evaluate(y,{},Et),Fr=GQ(I.horizontal),oi=24,Hi=he/oi,Ai=m.tilePixelRatio*Hi,bn=m.tilePixelRatio*or/oi,nn=m.tilePixelRatio*Oe,xn=m.tilePixelRatio*_r.get(\"symbol-spacing\"),Pn=_r.get(\"text-padding\")*m.tilePixelRatio,Zn=_r.get(\"icon-padding\")*m.tilePixelRatio,ga=_r.get(\"text-max-angle\")/180*Math.PI,ha=_r.get(\"text-rotation-alignment\")===\"map\"&&_r.get(\"symbol-placement\")!==\"point\",eo=_r.get(\"icon-rotation-alignment\")===\"map\"&&_r.get(\"symbol-placement\")!==\"point\",za=_r.get(\"symbol-placement\"),Za=xn/2,Ko=_r.get(\"icon-text-fit\"),to;U&&Ko!==\"none\"&&(m.allowVerticalPlacement&&I.vertical&&(to=hm(U,I.vertical,Ko,_r.get(\"icon-text-fit-padding\"),pr,Hi)),Fr&&(U=hm(U,Fr,Ko,_r.get(\"icon-text-fit-padding\"),pr,Hi)));var ao=function(Qw,m0){m0.x<0||m0.x>=Ci||m0.y<0||m0.y>=Ci||Fet(m,m0,Qw,I,U,$,to,m.layers[0],m.collisionBoxArray,y.index,y.sourceLayerIndex,m.index,Ai,Pn,ha,rt,nn,Zn,eo,pr,y,ae,gt,Et,he)};if(za===\"line\")for(var _s=0,jo=qQ(y.geometry,0,0,Ci,Ci);_s<jo.length;_s+=1)for(var El=jo[_s],Iu=Met(El,xn,ga,I.vertical||Fr,U,oi,bn,m.overscaling,Ci),kl=0,Cl=Iu;kl<Cl.length;kl+=1){var yl=Cl[kl],Qu=Fr;(!Qu||!zet(m,Qu.text,Za,yl))&&ao(El,yl)}else if(za===\"line-center\")for(var gc=0,Sf=y.geometry;gc<Sf.length;gc+=1){var Ff=Sf[gc];if(Ff.length>1){var Yh=Aet(Ff,ga,I.vertical||Fr,U,oi,bn);Yh&&ao(Ff,Yh)}}else if(y.type===\"Polygon\")for(var ch=0,Xd=zw(y.geometry,0);ch<Xd.length;ch+=1){var Zd=Xd[ch],Kh=Cet(Zd,16);ao(Zd[0],new Wd(Kh.x,Kh.y,0))}else if(y.type===\"LineString\")for(var fv=0,hv=y.geometry;fv<hv.length;fv+=1){var Ch=hv[fv];ao(Ch,new Wd(Ch[0].x,Ch[0].y,0))}else if(y.type===\"Point\")for(var dv=0,xp=y.geometry;dv<xp.length;dv+=1)for(var gy=xp[dv],F1=0,z1=gy;F1<z1.length;F1+=1){var O1=z1[F1];ao([O1],new Wd(O1.x,O1.y,0))}}var SS=255,R1=SS*Cd;function VQ(m,y,I,U,$,ae,he,Oe,rt,gt,Et,or,_r,pr,Fr){var oi=Eet(y,I,Oe,$,ae,he,U,m.allowVerticalPlacement),Hi=m.textSizeData,Ai=null;Hi.kind===\"source\"?(Ai=[Cd*$.layout.get(\"text-size\").evaluate(he,{})],Ai[0]>R1&&re(m.layerIds[0]+': Value for \"text-size\" is >= '+SS+'. Reduce your \"text-size\".')):Hi.kind===\"composite\"&&(Ai=[Cd*pr.compositeTextSizes[0].evaluate(he,{},Fr),Cd*pr.compositeTextSizes[1].evaluate(he,{},Fr)],(Ai[0]>R1||Ai[1]>R1)&&re(m.layerIds[0]+': Value for \"text-size\" is >= '+SS+'. Reduce your \"text-size\".')),m.addSymbols(m.text,oi,Ai,Oe,ae,he,gt,y,rt.lineStartIndex,rt.lineLength,_r,Fr);for(var bn=0,nn=Et;bn<nn.length;bn+=1){var xn=nn[bn];or[xn]=m.text.placedSymbolArray.length-1}return oi.length*4}function GQ(m){for(var y in m)return m[y];return null}function Fet(m,y,I,U,$,ae,he,Oe,rt,gt,Et,or,_r,pr,Fr,oi,Hi,Ai,bn,nn,xn,Pn,Zn,ga,ha){var eo,za=m.addToLineVertexArray(y,I),Za,Ko,to,ao,_s=0,jo=0,El=0,Iu=0,kl=-1,Cl=-1,yl={},Qu=K(\"\"),gc=0,Sf=0;if(Oe._unevaluatedLayout.getValue(\"text-radial-offset\")===void 0?(eo=Oe.layout.get(\"text-offset\").evaluate(xn,{},ga).map(function(kS){return kS*Tn}),gc=eo[0],Sf=eo[1]):(gc=Oe.layout.get(\"text-radial-offset\").evaluate(xn,{},ga)*Tn,Sf=cO),m.allowVerticalPlacement&&U.vertical){var Ff=Oe.layout.get(\"text-rotate\").evaluate(xn,{},ga),Yh=Ff+90,ch=U.vertical;to=new QC(rt,y,gt,Et,or,ch,_r,pr,Fr,Yh),he&&(ao=new QC(rt,y,gt,Et,or,he,Hi,Ai,Fr,Yh))}if($){var Xd=Oe.layout.get(\"icon-rotate\").evaluate(xn,{}),Zd=Oe.layout.get(\"icon-text-fit\")!==\"none\",Kh=BQ($,Xd,Zn,Zd),fv=he?BQ(he,Xd,Zn,Zd):void 0;Ko=new QC(rt,y,gt,Et,or,$,Hi,Ai,!1,Xd),_s=Kh.length*4;var hv=m.iconSizeData,Ch=null;hv.kind===\"source\"?(Ch=[Cd*Oe.layout.get(\"icon-size\").evaluate(xn,{})],Ch[0]>R1&&re(m.layerIds[0]+': Value for \"icon-size\" is >= '+SS+'. Reduce your \"icon-size\".')):hv.kind===\"composite\"&&(Ch=[Cd*Pn.compositeIconSizes[0].evaluate(xn,{},ga),Cd*Pn.compositeIconSizes[1].evaluate(xn,{},ga)],(Ch[0]>R1||Ch[1]>R1)&&re(m.layerIds[0]+': Value for \"icon-size\" is >= '+SS+'. Reduce your \"icon-size\".')),m.addSymbols(m.icon,Kh,Ch,nn,bn,xn,!1,y,za.lineStartIndex,za.lineLength,-1,ga),kl=m.icon.placedSymbolArray.length-1,fv&&(jo=fv.length*4,m.addSymbols(m.icon,fv,Ch,nn,bn,xn,uv.vertical,y,za.lineStartIndex,za.lineLength,-1,ga),Cl=m.icon.placedSymbolArray.length-1)}for(var dv in U.horizontal){var xp=U.horizontal[dv];if(!Za){Qu=K(xp.text);var gy=Oe.layout.get(\"text-rotate\").evaluate(xn,{},ga);Za=new QC(rt,y,gt,Et,or,xp,_r,pr,Fr,gy)}var F1=xp.positionedLines.length===1;if(El+=VQ(m,y,xp,ae,Oe,Fr,xn,oi,za,U.vertical?uv.horizontal:uv.horizontalOnly,F1?Object.keys(U.horizontal):[dv],yl,kl,Pn,ga),F1)break}U.vertical&&(Iu+=VQ(m,y,U.vertical,ae,Oe,Fr,xn,oi,za,uv.vertical,[\"vertical\"],yl,Cl,Pn,ga));var z1=Za?Za.boxStartIndex:m.collisionBoxArray.length,O1=Za?Za.boxEndIndex:m.collisionBoxArray.length,Qw=to?to.boxStartIndex:m.collisionBoxArray.length,m0=to?to.boxEndIndex:m.collisionBoxArray.length,n6=Ko?Ko.boxStartIndex:m.collisionBoxArray.length,mO=Ko?Ko.boxEndIndex:m.collisionBoxArray.length,a6=ao?ao.boxStartIndex:m.collisionBoxArray.length,yO=ao?ao.boxEndIndex:m.collisionBoxArray.length,Hp=-1,e3=function(kS,aee){return kS&&kS.circleDiameter?Math.max(kS.circleDiameter,aee):aee};Hp=e3(Za,Hp),Hp=e3(to,Hp),Hp=e3(Ko,Hp),Hp=e3(ao,Hp);var o6=Hp>-1?1:0;o6&&(Hp*=ha/Tn),m.glyphOffsetArray.length>=Pu.MAX_GLYPHS&&re(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),xn.sortKey!==void 0&&m.addToSortKeyRanges(m.symbolInstances.length,xn.sortKey),m.symbolInstances.emplaceBack(y.x,y.y,yl.right>=0?yl.right:-1,yl.center>=0?yl.center:-1,yl.left>=0?yl.left:-1,yl.vertical||-1,kl,Cl,Qu,z1,O1,Qw,m0,n6,mO,a6,yO,gt,El,Iu,_s,jo,o6,0,_r,gc,Sf,Hp)}function zet(m,y,I,U){var $=m.compareText;if(!(y in $))$[y]=[];else for(var ae=$[y],he=ae.length-1;he>=0;he--)if(U.dist(ae[he])<I)return!0;return $[y].push(U),!1}var Oet=pg.VectorTileFeature.types,qet=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function e6(m,y,I,U,$,ae,he,Oe,rt,gt,Et,or,_r){var pr=Oe?Math.min(R1,Math.round(Oe[0])):0,Fr=Oe?Math.min(R1,Math.round(Oe[1])):0;m.emplaceBack(y,I,Math.round(U*32),Math.round($*32),ae,he,(pr<<1)+(rt?1:0),Fr,gt*16,Et*16,or*256,_r*256)}function hO(m,y,I){m.emplaceBack(y.x,y.y,I),m.emplaceBack(y.x,y.y,I),m.emplaceBack(y.x,y.y,I),m.emplaceBack(y.x,y.y,I)}function Bet(m){for(var y=0,I=m.sections;y<I.length;y+=1){var U=I[y];if(Ii(U.text))return!0}return!1}var Yw=function(y){this.layoutVertexArray=new Bn,this.indexArray=new pn,this.programConfigurations=y,this.segments=new io,this.dynamicLayoutVertexArray=new hi,this.opacityVertexArray=new li,this.placedSymbolArray=new zo};Yw.prototype.isEmpty=function(){return this.layoutVertexArray.length===0&&this.indexArray.length===0&&this.dynamicLayoutVertexArray.length===0&&this.opacityVertexArray.length===0},Yw.prototype.upload=function(y,I,U,$){this.isEmpty()||(U&&(this.layoutVertexBuffer=y.createVertexBuffer(this.layoutVertexArray,te.members),this.indexBuffer=y.createIndexBuffer(this.indexArray,I),this.dynamicLayoutVertexBuffer=y.createVertexBuffer(this.dynamicLayoutVertexArray,fe.members,!0),this.opacityVertexBuffer=y.createVertexBuffer(this.opacityVertexArray,qet,!0),this.opacityVertexBuffer.itemSize=1),(U||$)&&this.programConfigurations.upload(y))},Yw.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},X(\"SymbolBuffers\",Yw);var MS=function(y,I,U){this.layoutVertexArray=new y,this.layoutAttributes=I,this.indexArray=new U,this.segments=new io,this.collisionVertexArray=new Ni};MS.prototype.upload=function(y){this.layoutVertexBuffer=y.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=y.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=y.createVertexBuffer(this.collisionVertexArray,ze.members,!0)},MS.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},X(\"CollisionBuffers\",MS);var Pu=function(y){this.collisionBoxArray=y.collisionBoxArray,this.zoom=y.zoom,this.overscaling=y.overscaling,this.layers=y.layers,this.layerIds=this.layers.map(function(rt){return rt.id}),this.index=y.index,this.pixelRatio=y.pixelRatio,this.sourceLayerIndex=y.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=sy([]),this.placementViewportMatrix=sy([]);var I=this.layers[0],U=I._unevaluatedLayout._values;this.textSizeData=_p(this.zoom,U[\"text-size\"]),this.iconSizeData=_p(this.zoom,U[\"icon-size\"]);var $=this.layers[0].layout,ae=$.get(\"symbol-sort-key\"),he=$.get(\"symbol-z-order\");this.canOverlap=$.get(\"text-allow-overlap\")||$.get(\"icon-allow-overlap\")||$.get(\"text-ignore-placement\")||$.get(\"icon-ignore-placement\"),this.sortFeaturesByKey=he!==\"viewport-y\"&&ae.constantOr(1)!==void 0;var Oe=he===\"viewport-y\"||he===\"auto\"&&!this.sortFeaturesByKey;this.sortFeaturesByY=Oe&&this.canOverlap,$.get(\"symbol-placement\")===\"point\"&&(this.writingModes=$.get(\"text-writing-mode\").map(function(rt){return uv[rt]})),this.stateDependentLayerIds=this.layers.filter(function(rt){return rt.isStateDependent()}).map(function(rt){return rt.id}),this.sourceID=y.sourceID};Pu.prototype.createArrays=function(){this.text=new Yw(new fi(this.layers,this.zoom,function(y){return/^text/.test(y)})),this.icon=new Yw(new fi(this.layers,this.zoom,function(y){return/^icon/.test(y)})),this.glyphOffsetArray=new Vl,this.lineVertexArray=new ss,this.symbolInstances=new al},Pu.prototype.calculateGlyphDependencies=function(y,I,U,$,ae){for(var he=0;he<y.length;he++)if(I[y.charCodeAt(he)]=!0,(U||$)&&ae){var Oe=zi[y.charAt(he)];Oe&&(I[Oe.charCodeAt(0)]=!0)}},Pu.prototype.populate=function(y,I,U){var $=this.layers[0],ae=$.layout,he=ae.get(\"text-font\"),Oe=ae.get(\"text-field\"),rt=ae.get(\"icon-image\"),gt=(Oe.value.kind!==\"constant\"||Oe.value.value instanceof Jl&&!Oe.value.value.isEmpty()||Oe.value.value.toString().length>0)&&(he.value.kind!==\"constant\"||he.value.value.length>0),Et=rt.value.kind!==\"constant\"||!!rt.value.value||Object.keys(rt.parameters).length>0,or=ae.get(\"symbol-sort-key\");if(this.features=[],!(!gt&&!Et)){for(var _r=I.iconDependencies,pr=I.glyphDependencies,Fr=I.availableImages,oi=new Gn(this.zoom),Hi=0,Ai=y;Hi<Ai.length;Hi+=1){var bn=Ai[Hi],nn=bn.feature,xn=bn.id,Pn=bn.index,Zn=bn.sourceLayerIndex,ga=$._featureFilter.needGeometry,ha=Ja(nn,ga);if($._featureFilter.filter(oi,ha,U)){ga||(ha.geometry=zn(nn));var eo=void 0;if(gt){var za=$.getValueAndResolveTokens(\"text-field\",ha,U,Fr),Za=Jl.factory(za);Bet(Za)&&(this.hasRTLText=!0),(!this.hasRTLText||yo()===\"unavailable\"||this.hasRTLText&&Ms.isParsed())&&(eo=yi(Za,$,ha))}var Ko=void 0;if(Et){var to=$.getValueAndResolveTokens(\"icon-image\",ha,U,Fr);to instanceof fl?Ko=to:Ko=fl.fromString(to)}if(!(!eo&&!Ko)){var ao=this.sortFeaturesByKey?or.evaluate(ha,{},U):void 0,_s={id:xn,text:eo,icon:Ko,index:Pn,sourceLayerIndex:Zn,geometry:ha.geometry,properties:nn.properties,type:Oet[nn.type],sortKey:ao};if(this.features.push(_s),Ko&&(_r[Ko.name]=!0),eo){var jo=he.evaluate(ha,{},U).join(\",\"),El=ae.get(\"text-rotation-alignment\")===\"map\"&&ae.get(\"symbol-placement\")!==\"point\";this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(uv.vertical)>=0;for(var Iu=0,kl=eo.sections;Iu<kl.length;Iu+=1){var Cl=kl[Iu];if(Cl.image)_r[Cl.image.name]=!0;else{var yl=jt(eo.toString()),Qu=Cl.fontStack||jo,gc=pr[Qu]=pr[Qu]||{};this.calculateGlyphDependencies(Cl.text,gc,El,this.allowVerticalPlacement,yl)}}}}}}ae.get(\"symbol-placement\")===\"line\"&&(this.features=vn(this.features)),this.sortFeaturesByKey&&this.features.sort(function(Sf,Ff){return Sf.sortKey-Ff.sortKey})}},Pu.prototype.update=function(y,I,U){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(y,I,this.layers,U),this.icon.programConfigurations.updatePaintArrays(y,I,this.layers,U))},Pu.prototype.isEmpty=function(){return this.symbolInstances.length===0&&!this.hasRTLText},Pu.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Pu.prototype.upload=function(y){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(y),this.iconCollisionBox.upload(y)),this.text.upload(y,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(y,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Pu.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Pu.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Pu.prototype.addToLineVertexArray=function(y,I){var U=this.lineVertexArray.length;if(y.segment!==void 0){for(var $=y.dist(I[y.segment+1]),ae=y.dist(I[y.segment]),he={},Oe=y.segment+1;Oe<I.length;Oe++)he[Oe]={x:I[Oe].x,y:I[Oe].y,tileUnitDistanceFromAnchor:$},Oe<I.length-1&&($+=I[Oe+1].dist(I[Oe]));for(var rt=y.segment||0;rt>=0;rt--)he[rt]={x:I[rt].x,y:I[rt].y,tileUnitDistanceFromAnchor:ae},rt>0&&(ae+=I[rt-1].dist(I[rt]));for(var gt=0;gt<I.length;gt++){var Et=he[gt];this.lineVertexArray.emplaceBack(Et.x,Et.y,Et.tileUnitDistanceFromAnchor)}}return{lineStartIndex:U,lineLength:this.lineVertexArray.length-U}},Pu.prototype.addSymbols=function(y,I,U,$,ae,he,Oe,rt,gt,Et,or,_r){for(var pr=y.indexArray,Fr=y.layoutVertexArray,oi=y.segments.prepareSegment(4*I.length,Fr,pr,this.canOverlap?he.sortKey:void 0),Hi=this.glyphOffsetArray.length,Ai=oi.vertexLength,bn=this.allowVerticalPlacement&&Oe===uv.vertical?Math.PI/2:0,nn=he.text&&he.text.sections,xn=0;xn<I.length;xn++){var Pn=I[xn],Zn=Pn.tl,ga=Pn.tr,ha=Pn.bl,eo=Pn.br,za=Pn.tex,Za=Pn.pixelOffsetTL,Ko=Pn.pixelOffsetBR,to=Pn.minFontScaleX,ao=Pn.minFontScaleY,_s=Pn.glyphOffset,jo=Pn.isSDF,El=Pn.sectionIndex,Iu=oi.vertexLength,kl=_s[1];e6(Fr,rt.x,rt.y,Zn.x,kl+Zn.y,za.x,za.y,U,jo,Za.x,Za.y,to,ao),e6(Fr,rt.x,rt.y,ga.x,kl+ga.y,za.x+za.w,za.y,U,jo,Ko.x,Za.y,to,ao),e6(Fr,rt.x,rt.y,ha.x,kl+ha.y,za.x,za.y+za.h,U,jo,Za.x,Ko.y,to,ao),e6(Fr,rt.x,rt.y,eo.x,kl+eo.y,za.x+za.w,za.y+za.h,U,jo,Ko.x,Ko.y,to,ao),hO(y.dynamicLayoutVertexArray,rt,bn),pr.emplaceBack(Iu,Iu+1,Iu+2),pr.emplaceBack(Iu+1,Iu+2,Iu+3),oi.vertexLength+=4,oi.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(_s[0]),(xn===I.length-1||El!==I[xn+1].sectionIndex)&&y.programConfigurations.populatePaintArrays(Fr.length,he,he.index,{},_r,nn&&nn[El])}y.placedSymbolArray.emplaceBack(rt.x,rt.y,Hi,this.glyphOffsetArray.length-Hi,Ai,gt,Et,rt.segment,U?U[0]:0,U?U[1]:0,$[0],$[1],Oe,0,!1,0,or)},Pu.prototype._addCollisionDebugVertex=function(y,I,U,$,ae,he){return I.emplaceBack(0,0),y.emplaceBack(U.x,U.y,$,ae,Math.round(he.x),Math.round(he.y))},Pu.prototype.addCollisionDebugVertices=function(y,I,U,$,ae,he,Oe){var rt=ae.segments.prepareSegment(4,ae.layoutVertexArray,ae.indexArray),gt=rt.vertexLength,Et=ae.layoutVertexArray,or=ae.collisionVertexArray,_r=Oe.anchorX,pr=Oe.anchorY;this._addCollisionDebugVertex(Et,or,he,_r,pr,new u(y,I)),this._addCollisionDebugVertex(Et,or,he,_r,pr,new u(U,I)),this._addCollisionDebugVertex(Et,or,he,_r,pr,new u(U,$)),this._addCollisionDebugVertex(Et,or,he,_r,pr,new u(y,$)),rt.vertexLength+=4;var Fr=ae.indexArray;Fr.emplaceBack(gt,gt+1),Fr.emplaceBack(gt+1,gt+2),Fr.emplaceBack(gt+2,gt+3),Fr.emplaceBack(gt+3,gt),rt.primitiveLength+=4},Pu.prototype.addDebugCollisionBoxes=function(y,I,U,$){for(var ae=y;ae<I;ae++){var he=this.collisionBoxArray.get(ae),Oe=he.x1,rt=he.y1,gt=he.x2,Et=he.y2;this.addCollisionDebugVertices(Oe,rt,gt,Et,$?this.textCollisionBox:this.iconCollisionBox,he.anchorPoint,U)}},Pu.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new MS(Ji,ct.members,oa),this.iconCollisionBox=new MS(Ji,ct.members,oa);for(var y=0;y<this.symbolInstances.length;y++){var I=this.symbolInstances.get(y);this.addDebugCollisionBoxes(I.textBoxStartIndex,I.textBoxEndIndex,I,!0),this.addDebugCollisionBoxes(I.verticalTextBoxStartIndex,I.verticalTextBoxEndIndex,I,!0),this.addDebugCollisionBoxes(I.iconBoxStartIndex,I.iconBoxEndIndex,I,!1),this.addDebugCollisionBoxes(I.verticalIconBoxStartIndex,I.verticalIconBoxEndIndex,I,!1)}},Pu.prototype._deserializeCollisionBoxesForSymbol=function(y,I,U,$,ae,he,Oe,rt,gt){for(var Et={},or=I;or<U;or++){var _r=y.get(or);Et.textBox={x1:_r.x1,y1:_r.y1,x2:_r.x2,y2:_r.y2,anchorPointX:_r.anchorPointX,anchorPointY:_r.anchorPointY},Et.textFeatureIndex=_r.featureIndex;break}for(var pr=$;pr<ae;pr++){var Fr=y.get(pr);Et.verticalTextBox={x1:Fr.x1,y1:Fr.y1,x2:Fr.x2,y2:Fr.y2,anchorPointX:Fr.anchorPointX,anchorPointY:Fr.anchorPointY},Et.verticalTextFeatureIndex=Fr.featureIndex;break}for(var oi=he;oi<Oe;oi++){var Hi=y.get(oi);Et.iconBox={x1:Hi.x1,y1:Hi.y1,x2:Hi.x2,y2:Hi.y2,anchorPointX:Hi.anchorPointX,anchorPointY:Hi.anchorPointY},Et.iconFeatureIndex=Hi.featureIndex;break}for(var Ai=rt;Ai<gt;Ai++){var bn=y.get(Ai);Et.verticalIconBox={x1:bn.x1,y1:bn.y1,x2:bn.x2,y2:bn.y2,anchorPointX:bn.anchorPointX,anchorPointY:bn.anchorPointY},Et.verticalIconFeatureIndex=bn.featureIndex;break}return Et},Pu.prototype.deserializeCollisionBoxes=function(y){this.collisionArrays=[];for(var I=0;I<this.symbolInstances.length;I++){var U=this.symbolInstances.get(I);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(y,U.textBoxStartIndex,U.textBoxEndIndex,U.verticalTextBoxStartIndex,U.verticalTextBoxEndIndex,U.iconBoxStartIndex,U.iconBoxEndIndex,U.verticalIconBoxStartIndex,U.verticalIconBoxEndIndex))}},Pu.prototype.hasTextData=function(){return this.text.segments.get().length>0},Pu.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Pu.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Pu.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Pu.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Pu.prototype.addIndicesForPlacedSymbol=function(y,I){for(var U=y.placedSymbolArray.get(I),$=U.vertexStartIndex+U.numGlyphs*4,ae=U.vertexStartIndex;ae<$;ae+=4)y.indexArray.emplaceBack(ae,ae+1,ae+2),y.indexArray.emplaceBack(ae+1,ae+2,ae+3)},Pu.prototype.getSortedSymbolIndexes=function(y){if(this.sortedAngle===y&&this.symbolInstanceIndexes!==void 0)return this.symbolInstanceIndexes;for(var I=Math.sin(y),U=Math.cos(y),$=[],ae=[],he=[],Oe=0;Oe<this.symbolInstances.length;++Oe){he.push(Oe);var rt=this.symbolInstances.get(Oe);$.push(Math.round(I*rt.anchorX+U*rt.anchorY)|0),ae.push(rt.featureIndex)}return he.sort(function(gt,Et){return $[gt]-$[Et]||ae[Et]-ae[gt]}),he},Pu.prototype.addToSortKeyRanges=function(y,I){var U=this.sortKeyRanges[this.sortKeyRanges.length-1];U&&U.sortKey===I?U.symbolInstanceEnd=y+1:this.sortKeyRanges.push({sortKey:I,symbolInstanceStart:y,symbolInstanceEnd:y+1})},Pu.prototype.sortFeatures=function(y){var I=this;if(this.sortFeaturesByY&&this.sortedAngle!==y&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(y),this.sortedAngle=y,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var U=0,$=this.symbolInstanceIndexes;U<$.length;U+=1){var ae=$[U],he=this.symbolInstances.get(ae);this.featureSortOrder.push(he.featureIndex),[he.rightJustifiedTextSymbolIndex,he.centerJustifiedTextSymbolIndex,he.leftJustifiedTextSymbolIndex].forEach(function(Oe,rt,gt){Oe>=0&&gt.indexOf(Oe)===rt&&I.addIndicesForPlacedSymbol(I.text,Oe)}),he.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,he.verticalPlacedTextSymbolIndex),he.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,he.placedIconSymbolIndex),he.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,he.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},X(\"SymbolBucket\",Pu,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Pu.MAX_GLYPHS=65535,Pu.addDynamicAttributes=hO;function Net(m,y){return y.replace(/{([^{}]+)}/g,function(I,U){return U in m?String(m[U]):\"\"})}var Uet=new Nr({\"symbol-placement\":new Me(Rn.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new Me(Rn.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new Me(Rn.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new bt(Rn.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new Me(Rn.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new Me(Rn.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new Me(Rn.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new Me(Rn.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new Me(Rn.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new bt(Rn.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new Me(Rn.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new Me(Rn.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new bt(Rn.layout_symbol[\"icon-image\"]),\"icon-rotate\":new bt(Rn.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new Me(Rn.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new Me(Rn.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new bt(Rn.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new bt(Rn.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new Me(Rn.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new Me(Rn.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new Me(Rn.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new bt(Rn.layout_symbol[\"text-field\"]),\"text-font\":new bt(Rn.layout_symbol[\"text-font\"]),\"text-size\":new bt(Rn.layout_symbol[\"text-size\"]),\"text-max-width\":new bt(Rn.layout_symbol[\"text-max-width\"]),\"text-line-height\":new Me(Rn.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new bt(Rn.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new bt(Rn.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new bt(Rn.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new Me(Rn.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new bt(Rn.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new Me(Rn.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new Me(Rn.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new bt(Rn.layout_symbol[\"text-rotate\"]),\"text-padding\":new Me(Rn.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new Me(Rn.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new bt(Rn.layout_symbol[\"text-transform\"]),\"text-offset\":new bt(Rn.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new Me(Rn.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new Me(Rn.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new Me(Rn.layout_symbol[\"text-optional\"])}),Vet=new Nr({\"icon-opacity\":new bt(Rn.paint_symbol[\"icon-opacity\"]),\"icon-color\":new bt(Rn.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new bt(Rn.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new bt(Rn.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new bt(Rn.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new Me(Rn.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new Me(Rn.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new bt(Rn.paint_symbol[\"text-opacity\"]),\"text-color\":new bt(Rn.paint_symbol[\"text-color\"],{runtimeType:ql,getOverride:function(m){return m.textColor},hasOverride:function(m){return!!m.textColor}}),\"text-halo-color\":new bt(Rn.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new bt(Rn.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new bt(Rn.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new Me(Rn.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new Me(Rn.paint_symbol[\"text-translate-anchor\"])}),dO={paint:Vet,layout:Uet},Kw=function(y){this.type=y.property.overrides?y.property.overrides.runtimeType:ac,this.defaultValue=y};Kw.prototype.evaluate=function(y){if(y.formattedSection){var I=this.defaultValue.property.overrides;if(I&&I.hasOverride(y.formattedSection))return I.getOverride(y.formattedSection)}return y.feature&&y.featureState?this.defaultValue.evaluate(y.feature,y.featureState):this.defaultValue.property.specification.default},Kw.prototype.eachChild=function(y){if(!this.defaultValue.isConstant()){var I=this.defaultValue.value;y(I._styleExpression.expression)}},Kw.prototype.outputDefined=function(){return!1},Kw.prototype.serialize=function(){return null},X(\"FormatSectionOverride\",Kw,{omit:[\"defaultValue\"]});var Get=function(m){function y(I){m.call(this,I,dO)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.recalculate=function(U,$){if(m.prototype.recalculate.call(this,U,$),this.layout.get(\"icon-rotation-alignment\")===\"auto\"&&(this.layout.get(\"symbol-placement\")!==\"point\"?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),this.layout.get(\"text-rotation-alignment\")===\"auto\"&&(this.layout.get(\"symbol-placement\")!==\"point\"?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),this.layout.get(\"text-pitch-alignment\")===\"auto\"&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),this.layout.get(\"icon-pitch-alignment\")===\"auto\"&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),this.layout.get(\"symbol-placement\")===\"point\"){var ae=this.layout.get(\"text-writing-mode\");if(ae){for(var he=[],Oe=0,rt=ae;Oe<rt.length;Oe+=1){var gt=rt[Oe];he.indexOf(gt)<0&&he.push(gt)}this.layout._values[\"text-writing-mode\"]=he}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},y.prototype.getValueAndResolveTokens=function(U,$,ae,he){var Oe=this.layout.get(U).evaluate($,{},ae,he),rt=this._unevaluatedLayout._values[U];return!rt.isDataDriven()&&!Ua(rt.value)&&Oe?Net($.properties,Oe):Oe},y.prototype.createBucket=function(U){return new Pu(U)},y.prototype.queryRadius=function(){return 0},y.prototype.queryIntersectsFeature=function(){return!1},y.prototype._setPaintOverrides=function(){for(var U=0,$=dO.paint.overridableProperties;U<$.length;U+=1){var ae=$[U];if(y.hasPaintOverride(this.layout,ae)){var he=this.paint.get(ae),Oe=new Kw(he),rt=new Ac(Oe,he.property.specification),gt=null;he.value.kind===\"constant\"||he.value.kind===\"source\"?gt=new Vc(\"source\",rt):gt=new hc(\"composite\",rt,he.value.zoomStops,he.value._interpolationType),this.paint._values[ae]=new dl(he.property,gt,he.parameters)}}},y.prototype._handleOverridablePaintPropertyUpdate=function(U,$,ae){return!this.layout||$.isDataDriven()||ae.isDataDriven()?!1:y.hasPaintOverride(this.layout,U)},y.hasPaintOverride=function(U,$){var ae=U.get(\"text-field\"),he=dO.paint.properties[$],Oe=!1,rt=function(or){for(var _r=0,pr=or;_r<pr.length;_r+=1){var Fr=pr[_r];if(he.overrides&&he.overrides.hasOverride(Fr)){Oe=!0;return}}};if(ae.value.kind===\"constant\"&&ae.value.value instanceof Jl)rt(ae.value.value.sections);else if(ae.value.kind===\"source\"){var gt=function(or){if(!Oe)if(or instanceof Go&&Es(or.value)===pl){var _r=or.value;rt(_r.sections)}else or instanceof Gu?rt(or.sections):or.eachChild(gt)},Et=ae.value;Et._styleExpression&&gt(Et._styleExpression.expression)}return Oe},y}(mi),Het=new Nr({\"background-color\":new Me(Rn.paint_background[\"background-color\"]),\"background-pattern\":new Rr(Rn.paint_background[\"background-pattern\"]),\"background-opacity\":new Me(Rn.paint_background[\"background-opacity\"])}),jet={paint:Het},Wet=function(m){function y(I){m.call(this,I,jet)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y}(mi),Xet=new Nr({\"raster-opacity\":new Me(Rn.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new Me(Rn.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new Me(Rn.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new Me(Rn.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new Me(Rn.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new Me(Rn.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new Me(Rn.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new Me(Rn.paint_raster[\"raster-fade-duration\"])}),Zet={paint:Xet},Yet=function(m){function y(I){m.call(this,I,Zet)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y}(mi);function Ket(m){var y=[],I=m.id;return I===void 0&&y.push({message:\"layers.\"+I+': missing required property \"id\"'}),m.render===void 0&&y.push({message:\"layers.\"+I+': missing required method \"render\"'}),m.renderingMode&&m.renderingMode!==\"2d\"&&m.renderingMode!==\"3d\"&&y.push({message:\"layers.\"+I+': property \"renderingMode\" must be either \"2d\" or \"3d\"'}),y}var Jet=function(m){function y(I){m.call(this,I,{}),this.implementation=I}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.is3D=function(){return this.implementation.renderingMode===\"3d\"},y.prototype.hasOffscreenPass=function(){return this.implementation.prerender!==void 0},y.prototype.recalculate=function(){},y.prototype.updateTransitions=function(){},y.prototype.hasTransition=function(){},y.prototype.serialize=function(){},y.prototype.onAdd=function(U){this.implementation.onAdd&&this.implementation.onAdd(U,U.painter.context.gl)},y.prototype.onRemove=function(U){this.implementation.onRemove&&this.implementation.onRemove(U,U.painter.context.gl)},y}(mi),$et={circle:H9,heatmap:Pw,hillshade:xC,fill:Qx,\"fill-extrusion\":fm,line:A,symbol:Get,background:Wet,raster:Yet};function Qet(m){return m.type===\"custom\"?new Jet(m):new $et[m.type](m)}var HQ=f.HTMLImageElement,jQ=f.HTMLCanvasElement,WQ=f.HTMLVideoElement,XQ=f.ImageData,t6=f.ImageBitmap,ib=function(y,I,U,$){this.context=y,this.format=U,this.texture=y.gl.createTexture(),this.update(I,$)};ib.prototype.update=function(y,I,U){var $=y.width,ae=y.height,he=(!this.size||this.size[0]!==$||this.size[1]!==ae)&&!U,Oe=this,rt=Oe.context,gt=rt.gl;if(this.useMipmap=!!(I&&I.useMipmap),gt.bindTexture(gt.TEXTURE_2D,this.texture),rt.pixelStoreUnpackFlipY.set(!1),rt.pixelStoreUnpack.set(1),rt.pixelStoreUnpackPremultiplyAlpha.set(this.format===gt.RGBA&&(!I||I.premultiply!==!1)),he)this.size=[$,ae],y instanceof HQ||y instanceof jQ||y instanceof WQ||y instanceof XQ||t6&&y instanceof t6?gt.texImage2D(gt.TEXTURE_2D,0,this.format,this.format,gt.UNSIGNED_BYTE,y):gt.texImage2D(gt.TEXTURE_2D,0,this.format,$,ae,0,this.format,gt.UNSIGNED_BYTE,y.data);else{var Et=U||{x:0,y:0},or=Et.x,_r=Et.y;y instanceof HQ||y instanceof jQ||y instanceof WQ||y instanceof XQ||t6&&y instanceof t6?gt.texSubImage2D(gt.TEXTURE_2D,0,or,_r,gt.RGBA,gt.UNSIGNED_BYTE,y):gt.texSubImage2D(gt.TEXTURE_2D,0,or,_r,$,ae,gt.RGBA,gt.UNSIGNED_BYTE,y.data)}this.useMipmap&&this.isSizePowerOfTwo()&&gt.generateMipmap(gt.TEXTURE_2D)},ib.prototype.bind=function(y,I,U){var $=this,ae=$.context,he=ae.gl;he.bindTexture(he.TEXTURE_2D,this.texture),U===he.LINEAR_MIPMAP_NEAREST&&!this.isSizePowerOfTwo()&&(U=he.LINEAR),y!==this.filter&&(he.texParameteri(he.TEXTURE_2D,he.TEXTURE_MAG_FILTER,y),he.texParameteri(he.TEXTURE_2D,he.TEXTURE_MIN_FILTER,U||y),this.filter=y),I!==this.wrap&&(he.texParameteri(he.TEXTURE_2D,he.TEXTURE_WRAP_S,I),he.texParameteri(he.TEXTURE_2D,he.TEXTURE_WRAP_T,I),this.wrap=I)},ib.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1===0},ib.prototype.destroy=function(){var y=this.context,I=y.gl;I.deleteTexture(this.texture),this.texture=null};var vO=function(y){var I=this;this._callback=y,this._triggered=!1,typeof MessageChannel!=\"undefined\"&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){I._triggered=!1,I._callback()})};vO.prototype.trigger=function(){var y=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout(function(){y._triggered=!1,y._callback()},0))},vO.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Jw=function(y,I,U){this.target=y,this.parent=I,this.mapId=U,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},O([\"receive\",\"process\"],this),this.invoker=new vO(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=Ce()?y:f};Jw.prototype.send=function(y,I,U,$,ae){var he=this;ae===void 0&&(ae=!1);var Oe=Math.round(Math.random()*1e18).toString(36).substring(0,10);U&&(this.callbacks[Oe]=U);var rt=Se(this.globalScope)?void 0:[];return this.target.postMessage({id:Oe,type:y,hasCallback:!!U,targetMapId:$,mustQueue:ae,sourceMapId:this.mapId,data:He(I,rt)},rt),{cancel:function(){U&&delete he.callbacks[Oe],he.target.postMessage({id:Oe,type:\"<cancel>\",targetMapId:$,sourceMapId:he.mapId})}}},Jw.prototype.receive=function(y){var I=y.data,U=I.id;if(U&&!(I.targetMapId&&this.mapId!==I.targetMapId))if(I.type===\"<cancel>\"){delete this.tasks[U];var $=this.cancelCallbacks[U];delete this.cancelCallbacks[U],$&&$()}else Ce()||I.mustQueue?(this.tasks[U]=I,this.taskQueue.push(U),this.invoker.trigger()):this.processTask(U,I)},Jw.prototype.process=function(){if(this.taskQueue.length){var y=this.taskQueue.shift(),I=this.tasks[y];delete this.tasks[y],this.taskQueue.length&&this.invoker.trigger(),I&&this.processTask(y,I)}},Jw.prototype.processTask=function(y,I){var U=this;if(I.type===\"<response>\"){var $=this.callbacks[y];delete this.callbacks[y],$&&(I.error?$(Ye(I.error)):$(null,Ye(I.data)))}else{var ae=!1,he=Se(this.globalScope)?void 0:[],Oe=I.hasCallback?function(_r,pr){ae=!0,delete U.cancelCallbacks[y],U.target.postMessage({id:y,type:\"<response>\",sourceMapId:U.mapId,error:_r?He(_r):null,data:He(pr,he)},he)}:function(_r){ae=!0},rt=null,gt=Ye(I.data);if(this.parent[I.type])rt=this.parent[I.type](I.sourceMapId,gt,Oe);else if(this.parent.getWorkerSource){var Et=I.type.split(\".\"),or=this.parent.getWorkerSource(I.sourceMapId,Et[0],gt.source);rt=or[Et[1]](gt,Oe)}else Oe(new Error(\"Could not find function \"+I.type));!ae&&rt&&rt.cancel&&(this.cancelCallbacks[y]=rt.cancel)}},Jw.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};function ett(m,y,I){y=Math.pow(2,I)-y-1;var U=ZQ(m*256,y*256,I),$=ZQ((m+1)*256,(y+1)*256,I);return U[0]+\",\"+U[1]+\",\"+$[0]+\",\"+$[1]}function ZQ(m,y,I){var U=2*Math.PI*6378137/256/Math.pow(2,I),$=m*U-2*Math.PI*6378137/2,ae=y*U-2*Math.PI*6378137/2;return[$,ae]}var lh=function(y,I){y&&(I?this.setSouthWest(y).setNorthEast(I):y.length===4?this.setSouthWest([y[0],y[1]]).setNorthEast([y[2],y[3]]):this.setSouthWest(y[0]).setNorthEast(y[1]))};lh.prototype.setNorthEast=function(y){return this._ne=y instanceof Hc?new Hc(y.lng,y.lat):Hc.convert(y),this},lh.prototype.setSouthWest=function(y){return this._sw=y instanceof Hc?new Hc(y.lng,y.lat):Hc.convert(y),this},lh.prototype.extend=function(y){var I=this._sw,U=this._ne,$,ae;if(y instanceof Hc)$=y,ae=y;else if(y instanceof lh){if($=y._sw,ae=y._ne,!$||!ae)return this}else{if(Array.isArray(y))if(y.length===4||y.every(Array.isArray)){var he=y;return this.extend(lh.convert(he))}else{var Oe=y;return this.extend(Hc.convert(Oe))}return this}return!I&&!U?(this._sw=new Hc($.lng,$.lat),this._ne=new Hc(ae.lng,ae.lat)):(I.lng=Math.min($.lng,I.lng),I.lat=Math.min($.lat,I.lat),U.lng=Math.max(ae.lng,U.lng),U.lat=Math.max(ae.lat,U.lat)),this},lh.prototype.getCenter=function(){return new Hc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},lh.prototype.getSouthWest=function(){return this._sw},lh.prototype.getNorthEast=function(){return this._ne},lh.prototype.getNorthWest=function(){return new Hc(this.getWest(),this.getNorth())},lh.prototype.getSouthEast=function(){return new Hc(this.getEast(),this.getSouth())},lh.prototype.getWest=function(){return this._sw.lng},lh.prototype.getSouth=function(){return this._sw.lat},lh.prototype.getEast=function(){return this._ne.lng},lh.prototype.getNorth=function(){return this._ne.lat},lh.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},lh.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},lh.prototype.isEmpty=function(){return!(this._sw&&this._ne)},lh.prototype.contains=function(y){var I=Hc.convert(y),U=I.lng,$=I.lat,ae=this._sw.lat<=$&&$<=this._ne.lat,he=this._sw.lng<=U&&U<=this._ne.lng;return this._sw.lng>this._ne.lng&&(he=this._sw.lng>=U&&U>=this._ne.lng),ae&&he},lh.convert=function(y){return!y||y instanceof lh?y:new lh(y)};var YQ=63710088e-1,Hc=function(y,I){if(isNaN(y)||isNaN(I))throw new Error(\"Invalid LngLat object: (\"+y+\", \"+I+\")\");if(this.lng=+y,this.lat=+I,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Hc.prototype.wrap=function(){return new Hc(k(this.lng,-180,180),this.lat)},Hc.prototype.toArray=function(){return[this.lng,this.lat]},Hc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Hc.prototype.distanceTo=function(y){var I=Math.PI/180,U=this.lat*I,$=y.lat*I,ae=Math.sin(U)*Math.sin($)+Math.cos(U)*Math.cos($)*Math.cos((y.lng-this.lng)*I),he=YQ*Math.acos(Math.min(ae,1));return he},Hc.prototype.toBounds=function(y){y===void 0&&(y=0);var I=40075017,U=360*y/I,$=U/Math.cos(Math.PI/180*this.lat);return new lh(new Hc(this.lng-$,this.lat-U),new Hc(this.lng+$,this.lat+U))},Hc.convert=function(y){if(y instanceof Hc)return y;if(Array.isArray(y)&&(y.length===2||y.length===3))return new Hc(Number(y[0]),Number(y[1]));if(!Array.isArray(y)&&typeof y==\"object\"&&y!==null)return new Hc(Number(\"lng\"in y?y.lng:y.lon),Number(y.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var KQ=2*Math.PI*YQ;function JQ(m){return KQ*Math.cos(m*Math.PI/180)}function $Q(m){return(180+m)/360}function QQ(m){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+m*Math.PI/360)))/360}function eee(m,y){return m/JQ(y)}function ttt(m){return m*360-180}function pO(m){var y=180-m*360;return 360/Math.PI*Math.atan(Math.exp(y*Math.PI/180))-90}function rtt(m,y){return m*JQ(pO(y))}function itt(m){return 1/Math.cos(m*Math.PI/180)}var nb=function(y,I,U){U===void 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u((y.x*I-this.x)*Ci,(y.y*I-this.y)*Ci)},ab.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var tee=function(y,I){this.wrap=y,this.canonical=I,this.key=ES(y,I.z,I.z,I.x,I.y)},uh=function(y,I,U,$,ae){this.overscaledZ=y,this.wrap=I,this.canonical=new ab(U,+$,+ae),this.key=ES(I,y,U,$,ae)};uh.prototype.equals=function(y){return this.overscaledZ===y.overscaledZ&&this.wrap===y.wrap&&this.canonical.equals(y.canonical)},uh.prototype.scaledTo=function(y){var I=this.canonical.z-y;return y>this.canonical.z?new uh(y,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new uh(y,this.wrap,y,this.canonical.x>>I,this.canonical.y>>I)},uh.prototype.calculateScaledKey=function(y,I){var U=this.canonical.z-y;return y>this.canonical.z?ES(this.wrap*+I,y,this.canonical.z,this.canonical.x,this.canonical.y):ES(this.wrap*+I,y,y,this.canonical.x>>U,this.canonical.y>>U)},uh.prototype.isChildOf=function(y){if(y.wrap!==this.wrap)return!1;var I=this.canonical.z-y.canonical.z;return y.overscaledZ===0||y.overscaledZ<this.overscaledZ&&y.canonical.x===this.canonical.x>>I&&y.canonical.y===this.canonical.y>>I},uh.prototype.children=function(y){if(this.overscaledZ>=y)return[new uh(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var I=this.canonical.z+1,U=this.canonical.x*2,$=this.canonical.y*2;return[new uh(I,this.wrap,I,U,$),new uh(I,this.wrap,I,U+1,$),new uh(I,this.wrap,I,U,$+1),new uh(I,this.wrap,I,U+1,$+1)]},uh.prototype.isLessThan=function(y){return this.wrap<y.wrap?!0:this.wrap>y.wrap?!1:this.overscaledZ<y.overscaledZ?!0:this.overscaledZ>y.overscaledZ?!1:this.canonical.x<y.canonical.x?!0:this.canonical.x>y.canonical.x?!1:this.canonical.y<y.canonical.y},uh.prototype.wrapped=function(){return new uh(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},uh.prototype.unwrapTo=function(y){return new uh(this.overscaledZ,y,this.canonical.z,this.canonical.x,this.canonical.y)},uh.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},uh.prototype.toUnwrapped=function(){return new tee(this.wrap,this.canonical)},uh.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},uh.prototype.getTilePoint=function(y){return this.canonical.getTilePoint(new nb(y.x-this.wrap,y.y))};function ES(m,y,I,U,$){m*=2,m<0&&(m=m*-1-1);var ae=1<<I;return(ae*ae*m+ae*$+U).toString(36)+I.toString(36)+y.toString(36)}function ntt(m,y,I){for(var U=\"\",$,ae=m;ae>0;ae--)$=1<<ae-1,U+=(y&$?1:0)+(I&$?2:0);return U}X(\"CanonicalTileID\",ab),X(\"OverscaledTileID\",uh,{omit:[\"posMatrix\"]});var vy=function(y,I,U){if(this.uid=y,I.height!==I.width)throw new RangeError(\"DEM tiles must be square\");if(U&&U!==\"mapbox\"&&U!==\"terrarium\")return re('\"'+U+'\" is not a valid encoding type. 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this.encoding===\"terrarium\"?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},vy.prototype._idx=function(y,I){if(y<-1||y>=this.dim+1||I<-1||I>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(I+1)*this.stride+(y+1)},vy.prototype._unpackMapbox=function(y,I,U){return(y*256*256+I*256+U)/10-1e4},vy.prototype._unpackTerrarium=function(y,I,U){return y*256+I+U/256-32768},vy.prototype.getPixels=function(){return new Sh({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},vy.prototype.backfillBorder=function(y,I,U){if(this.dim!==y.dim)throw new Error(\"dem dimension mismatch\");var $=I*this.dim,ae=I*this.dim+this.dim,he=U*this.dim,Oe=U*this.dim+this.dim;switch(I){case-1:$=ae-1;break;case 1:ae=$+1;break}switch(U){case-1:he=Oe-1;break;case 1:Oe=he+1;break}for(var rt=-I*this.dim,gt=-U*this.dim,Et=he;Et<Oe;Et++)for(var or=$;or<ae;or++)this.data[this._idx(or,Et)]=y.data[this._idx(or+rt,Et+gt)]},X(\"DEMData\",vy);function att(m,y){var I={};if(!y)return I;for(var U=function(){var he=ae[$],Oe=he.layerIds.map(function(or){return y.getLayer(or)}).filter(Boolean);if(Oe.length!==0){he.layers=Oe,he.stateDependentLayerIds&&(he.stateDependentLayers=he.stateDependentLayerIds.map(function(or){return Oe.filter(function(_r){return _r.id===or})[0]}));for(var rt=0,gt=Oe;rt<gt.length;rt+=1){var Et=gt[rt];I[Et.id]=he}}},$=0,ae=m;$<ae.length;$+=1)U();return I}var r6=function(y){this._stringToNumber={},this._numberToString=[];for(var I=0;I<y.length;I++){var U=y[I];this._stringToNumber[U]=I,this._numberToString[I]=U}};r6.prototype.encode=function(y){return this._stringToNumber[y]},r6.prototype.decode=function(y){return this._numberToString[y]};var i6=function(y,I,U,$,ae){this.type=\"Feature\",this._vectorTileFeature=y,y._z=I,y._x=U,y._y=$,this.properties=y.properties,this.id=ae},gO={geometry:{configurable:!0}};gO.geometry.get=function(){return this._geometry===void 0&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},gO.geometry.set=function(m){this._geometry=m},i6.prototype.toJSON=function(){var y={geometry:this.geometry};for(var I in this)I===\"_geometry\"||I===\"_vectorTileFeature\"||(y[I]=this[I]);return y},Object.defineProperties(i6.prototype,gO);var $w=function(){this.state={},this.stateChanges={},this.deletedStates={}};$w.prototype.updateState=function(y,I,U){var $=String(I);if(this.stateChanges[y]=this.stateChanges[y]||{},this.stateChanges[y][$]=this.stateChanges[y][$]||{},x(this.stateChanges[y][$],U),this.deletedStates[y]===null){this.deletedStates[y]={};for(var ae in this.state[y])ae!==$&&(this.deletedStates[y][ae]=null)}else{var he=this.deletedStates[y]&&this.deletedStates[y][$]===null;if(he){this.deletedStates[y][$]={};for(var Oe in this.state[y][$])U[Oe]||(this.deletedStates[y][$][Oe]=null)}else for(var rt in U){var gt=this.deletedStates[y]&&this.deletedStates[y][$]&&this.deletedStates[y][$][rt]===null;gt&&delete this.deletedStates[y][$][rt]}}},$w.prototype.removeFeatureState=function(y,I,U){var $=this.deletedStates[y]===null;if(!$){var ae=String(I);if(this.deletedStates[y]=this.deletedStates[y]||{},U&&I!==void 0)this.deletedStates[y][ae]!==null&&(this.deletedStates[y][ae]=this.deletedStates[y][ae]||{},this.deletedStates[y][ae][U]=null);else if(I!==void 0){var he=this.stateChanges[y]&&this.stateChanges[y][ae];if(he){this.deletedStates[y][ae]={};for(U in this.stateChanges[y][ae])this.deletedStates[y][ae][U]=null}else this.deletedStates[y][ae]=null}else this.deletedStates[y]=null}},$w.prototype.getState=function(y,I){var U=String(I),$=this.state[y]||{},ae=this.stateChanges[y]||{},he=x({},$[U],ae[U]);if(this.deletedStates[y]===null)return{};if(this.deletedStates[y]){var Oe=this.deletedStates[y][I];if(Oe===null)return{};for(var rt in Oe)delete he[rt]}return he},$w.prototype.initializeTileState=function(y,I){y.setFeatureState(this.state,I)},$w.prototype.coalesceChanges=function(y,I){var U={};for(var $ in this.stateChanges){this.state[$]=this.state[$]||{};var ae={};for(var he in this.stateChanges[$])this.state[$][he]||(this.state[$][he]={}),x(this.state[$][he],this.stateChanges[$][he]),ae[he]=this.state[$][he];U[$]=ae}for(var Oe in this.deletedStates){this.state[Oe]=this.state[Oe]||{};var rt={};if(this.deletedStates[Oe]===null)for(var gt in this.state[Oe])rt[gt]={},this.state[Oe][gt]={};else for(var Et in this.deletedStates[Oe]){var or=this.deletedStates[Oe][Et]===null;if(or)this.state[Oe][Et]={};else for(var _r=0,pr=Object.keys(this.deletedStates[Oe][Et]);_r<pr.length;_r+=1){var Fr=pr[_r];delete this.state[Oe][Et][Fr]}rt[Et]=this.state[Oe][Et]}U[Oe]=U[Oe]||{},x(U[Oe],rt)}if(this.stateChanges={},this.deletedStates={},Object.keys(U).length!==0)for(var oi in y){var Hi=y[oi];Hi.setFeatureState(U,I)}};var py=function(y,I){this.tileID=y,this.x=y.canonical.x,this.y=y.canonical.y,this.z=y.canonical.z,this.grid=new au(Ci,16,0),this.grid3D=new au(Ci,16,0),this.featureIndexArray=new Ys,this.promoteId=I};py.prototype.insert=function(y,I,U,$,ae,he){var Oe=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(U,$,ae);for(var rt=he?this.grid3D:this.grid,gt=0;gt<I.length;gt++){for(var Et=I[gt],or=[1/0,1/0,-1/0,-1/0],_r=0;_r<Et.length;_r++){var pr=Et[_r];or[0]=Math.min(or[0],pr.x),or[1]=Math.min(or[1],pr.y),or[2]=Math.max(or[2],pr.x),or[3]=Math.max(or[3],pr.y)}or[0]<Ci&&or[1]<Ci&&or[2]>=0&&or[3]>=0&&rt.insert(Oe,or[0],or[1],or[2],or[3])}},py.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new pg.VectorTile(new Xa(this.rawTileData)).layers,this.sourceLayerCoder=new r6(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},py.prototype.query=function(y,I,U,$){var ae=this;this.loadVTLayers();for(var he=y.params||{},Oe=Ci/y.tileSize/y.scale,rt=be(he.filter),gt=y.queryGeometry,Et=y.queryPadding*Oe,or=iee(gt),_r=this.grid.query(or.minX-Et,or.minY-Et,or.maxX+Et,or.maxY+Et),pr=iee(y.cameraQueryGeometry),Fr=this.grid3D.query(pr.minX-Et,pr.minY-Et,pr.maxX+Et,pr.maxY+Et,function(Zn,ga,ha,eo){return gp(y.cameraQueryGeometry,Zn-Et,ga-Et,ha+Et,eo+Et)}),oi=0,Hi=Fr;oi<Hi.length;oi+=1){var Ai=Hi[oi];_r.push(Ai)}_r.sort(ott);for(var bn={},nn,xn=function(Zn){var ga=_r[Zn];if(ga!==nn){nn=ga;var ha=ae.featureIndexArray.get(ga),eo=null;ae.loadMatchingFeature(bn,ha.bucketIndex,ha.sourceLayerIndex,ha.featureIndex,rt,he.layers,he.availableImages,I,U,$,function(za,Za,Ko){return eo||(eo=zn(za)),Za.queryIntersectsFeature(gt,za,Ko,eo,ae.z,y.transform,Oe,y.pixelPosMatrix)})}},Pn=0;Pn<_r.length;Pn++)xn(Pn);return bn},py.prototype.loadMatchingFeature=function(y,I,U,$,ae,he,Oe,rt,gt,Et,or){var _r=this.bucketLayerIDs[I];if(!(he&&!N(he,_r))){var pr=this.sourceLayerCoder.decode(U),Fr=this.vtLayers[pr],oi=Fr.feature($);if(ae.needGeometry){var Hi=Ja(oi,!0);if(!ae.filter(new Gn(this.tileID.overscaledZ),Hi,this.tileID.canonical))return}else if(!ae.filter(new Gn(this.tileID.overscaledZ),oi))return;for(var Ai=this.getId(oi,pr),bn=0;bn<_r.length;bn++){var nn=_r[bn];if(!(he&&he.indexOf(nn)<0)){var xn=rt[nn];if(xn){var Pn={};Ai!==void 0&&Et&&(Pn=Et.getState(xn.sourceLayer||\"_geojsonTileLayer\",Ai));var Zn=x({},gt[nn]);Zn.paint=ree(Zn.paint,xn.paint,oi,Pn,Oe),Zn.layout=ree(Zn.layout,xn.layout,oi,Pn,Oe);var ga=!or||or(oi,xn,Pn);if(ga){var ha=new i6(oi,this.z,this.x,this.y,Ai);ha.layer=Zn;var eo=y[nn];eo===void 0&&(eo=y[nn]=[]),eo.push({featureIndex:$,feature:ha,intersectionZ:ga})}}}}}},py.prototype.lookupSymbolFeatures=function(y,I,U,$,ae,he,Oe,rt){var gt={};this.loadVTLayers();for(var Et=be(ae),or=0,_r=y;or<_r.length;or+=1){var pr=_r[or];this.loadMatchingFeature(gt,U,$,pr,Et,he,Oe,rt,I)}return gt},py.prototype.hasLayer=function(y){for(var I=0,U=this.bucketLayerIDs;I<U.length;I+=1)for(var $=U[I],ae=0,he=$;ae<he.length;ae+=1){var Oe=he[ae];if(y===Oe)return!0}return!1},py.prototype.getId=function(y,I){var U=y.id;if(this.promoteId){var $=typeof this.promoteId==\"string\"?this.promoteId:this.promoteId[I];U=y.properties[$],typeof U==\"boolean\"&&(U=Number(U))}return U},X(\"FeatureIndex\",py,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});function ree(m,y,I,U,$){return G(m,function(ae,he){var Oe=y instanceof Sc?y.get(he):null;return Oe&&Oe.evaluate?Oe.evaluate(I,U,$):Oe})}function iee(m){for(var y=1/0,I=1/0,U=-1/0,$=-1/0,ae=0,he=m;ae<he.length;ae+=1){var Oe=he[ae];y=Math.min(y,Oe.x),I=Math.min(I,Oe.y),U=Math.max(U,Oe.x),$=Math.max($,Oe.y)}return{minX:y,minY:I,maxX:U,maxY:$}}function ott(m,y){return y-m}var stt=3e4,Zh=function(y,I){this.tileID=y,this.uid=g(),this.uses=0,this.tileSize=I,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};Zh.prototype.registerFadeDuration=function(y){var I=y+this.timeAdded;I<ut.now()||this.fadeEndTime&&I<this.fadeEndTime||(this.fadeEndTime=I)},Zh.prototype.wasRequested=function(){return this.state===\"errored\"||this.state===\"loaded\"||this.state===\"reloading\"},Zh.prototype.loadVectorData=function(y,I,U){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",!y){this.collisionBoxArray=new Va;return}y.featureIndex&&(this.latestFeatureIndex=y.featureIndex,y.rawTileData?(this.latestRawTileData=y.rawTileData,this.latestFeatureIndex.rawTileData=y.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=y.collisionBoxArray,this.buckets=att(y.buckets,I.style),this.hasSymbolBuckets=!1;for(var $ in this.buckets){var ae=this.buckets[$];if(ae instanceof Pu)if(this.hasSymbolBuckets=!0,U)ae.justReloaded=!0;else break}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var he in this.buckets){var Oe=this.buckets[he];if(Oe instanceof Pu&&Oe.hasRTLText){this.hasRTLText=!0,Xs();break}}this.queryPadding=0;for(var rt in this.buckets){var gt=this.buckets[rt];this.queryPadding=Math.max(this.queryPadding,I.style.getLayer(rt).queryRadius(gt))}y.imageAtlas&&(this.imageAtlas=y.imageAtlas),y.glyphAtlasImage&&(this.glyphAtlasImage=y.glyphAtlasImage)},Zh.prototype.unloadVectorData=function(){for(var y in this.buckets)this.buckets[y].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},Zh.prototype.getBucket=function(y){return this.buckets[y.id]},Zh.prototype.upload=function(y){for(var I in this.buckets){var U=this.buckets[I];U.uploadPending()&&U.upload(y)}var $=y.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new ib(y,this.imageAtlas.image,$.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new ib(y,this.glyphAtlasImage,$.ALPHA),this.glyphAtlasImage=null)},Zh.prototype.prepare=function(y){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(y,this.imageAtlasTexture)},Zh.prototype.queryRenderedFeatures=function(y,I,U,$,ae,he,Oe,rt,gt,Et){return!this.latestFeatureIndex||!this.latestFeatureIndex.rawTileData?{}:this.latestFeatureIndex.query({queryGeometry:$,cameraQueryGeometry:ae,scale:he,tileSize:this.tileSize,pixelPosMatrix:Et,transform:rt,params:Oe,queryPadding:this.queryPadding*gt},y,I,U)},Zh.prototype.querySourceFeatures=function(y,I){var U=this.latestFeatureIndex;if(!(!U||!U.rawTileData)){var $=U.loadVTLayers(),ae=I?I.sourceLayer:\"\",he=$._geojsonTileLayer||$[ae];if(he)for(var Oe=be(I&&I.filter),rt=this.tileID.canonical,gt=rt.z,Et=rt.x,or=rt.y,_r={z:gt,x:Et,y:or},pr=0;pr<he.length;pr++){var Fr=he.feature(pr);if(Oe.needGeometry){var oi=Ja(Fr,!0);if(!Oe.filter(new Gn(this.tileID.overscaledZ),oi,this.tileID.canonical))continue}else if(!Oe.filter(new Gn(this.tileID.overscaledZ),Fr))continue;var Hi=U.getId(Fr,ae),Ai=new i6(Fr,gt,Et,or,Hi);Ai.tile=_r,y.push(Ai)}}},Zh.prototype.hasData=function(){return this.state===\"loaded\"||this.state===\"reloading\"||this.state===\"expired\"},Zh.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},Zh.prototype.setExpiryData=function(y){var I=this.expirationTime;if(y.cacheControl){var U=me(y.cacheControl);U[\"max-age\"]&&(this.expirationTime=Date.now()+U[\"max-age\"]*1e3)}else y.expires&&(this.expirationTime=new Date(y.expires).getTime());if(this.expirationTime){var $=Date.now(),ae=!1;if(this.expirationTime>$)ae=!1;else if(!I)ae=!0;else if(this.expirationTime<I)ae=!0;else{var he=this.expirationTime-I;he?this.expirationTime=$+Math.max(he,stt):ae=!0}ae?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},Zh.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-new Date().getTime(),Math.pow(2,31)-1)},Zh.prototype.setFeatureState=function(y,I){if(!(!this.latestFeatureIndex||!this.latestFeatureIndex.rawTileData||Object.keys(y).length===0)){var U=this.latestFeatureIndex.loadVTLayers();for(var $ in this.buckets)if(I.style.hasLayer($)){var ae=this.buckets[$],he=ae.layers[0].sourceLayer||\"_geojsonTileLayer\",Oe=U[he],rt=y[he];if(!(!Oe||!rt||Object.keys(rt).length===0)){ae.update(rt,Oe,this.imageAtlas&&this.imageAtlas.patternPositions||{});var gt=I&&I.style&&I.style.getLayer($);gt&&(this.queryPadding=Math.max(this.queryPadding,gt.queryRadius(ae)))}}}},Zh.prototype.holdingForFade=function(){return this.symbolFadeHoldUntil!==void 0},Zh.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<ut.now()},Zh.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},Zh.prototype.setHoldDuration=function(y){this.symbolFadeHoldUntil=ut.now()+y},Zh.prototype.setDependencies=function(y,I){for(var U={},$=0,ae=I;$<ae.length;$+=1){var he=ae[$];U[he]=!0}this.dependencies[y]=U},Zh.prototype.hasDependency=function(y,I){for(var U=0,$=y;U<$.length;U+=1){var ae=$[U],he=this.dependencies[ae];if(he)for(var Oe=0,rt=I;Oe<rt.length;Oe+=1){var gt=rt[Oe];if(he[gt])return!0}}return!1};var ltt=[\"type\",\"source\",\"source-layer\",\"minzoom\",\"maxzoom\",\"filter\",\"layout\"],D1=f.performance,nee=function(y){this._marks={start:[y.url,\"start\"].join(\"#\"),end:[y.url,\"end\"].join(\"#\"),measure:y.url.toString()},D1.mark(this._marks.start)};nee.prototype.finish=function(){D1.mark(this._marks.end);var y=D1.getEntriesByName(this._marks.measure);return y.length===0&&(D1.measure(this._marks.measure,this._marks.start,this._marks.end),y=D1.getEntriesByName(this._marks.measure),D1.clearMarks(this._marks.start),D1.clearMarks(this._marks.end),D1.clearMeasures(this._marks.measure)),y},i.Actor=Jw,i.AlphaImage=Dv,i.CanonicalTileID=ab,i.CollisionBoxArray=Va,i.Color=cs,i.DEMData=vy,i.DataConstantProperty=Me,i.DictionaryCoder=r6,i.EXTENT=Ci,i.ErrorEvent=da,i.EvaluationParameters=Gn,i.Event=Wo,i.Evented=Wn,i.FeatureIndex=py,i.FillBucket=mp,i.FillExtrusionBucket=Vp,i.ImageAtlas=gg,i.ImagePosition=Zf,i.LineBucket=sh,i.LngLat=Hc,i.LngLatBounds=lh,i.MercatorCoordinate=nb,i.ONE_EM=Tn,i.OverscaledTileID=uh,i.Point=u,i.Point$1=u,i.Properties=Nr,i.Protobuf=Xa,i.RGBAImage=Sh,i.RequestManager=$e,i.RequestPerformance=nee,i.ResourceType=ra,i.SegmentVector=io,i.SourceFeatureState=$w,i.StructArrayLayout1ui2=ba,i.StructArrayLayout2f1f2i16=Vi,i.StructArrayLayout2i4=Yr,i.StructArrayLayout3ui6=pn,i.StructArrayLayout4i8=xi,i.SymbolBucket=Pu,i.Texture=ib,i.Tile=Zh,i.Transitionable=Uo,i.Uniform1f=Qe,i.Uniform1i=Ve,i.Uniform2f=at,i.Uniform3f=Ct,i.Uniform4f=Ot,i.UniformColor=Rt,i.UniformMatrix4f=Dt,i.UnwrappedTileID=tee,i.ValidationError=_a,i.WritingMode=uv,i.ZoomHistory=kt,i.add=Rv,i.addDynamicAttributes=hO,i.asyncAll=E,i.bezier=_,i.bindAll=O,i.browser=ut,i.cacheEntryPossiblyAdded=ji,i.clamp=p,i.clearTileCache=wi,i.clipLine=qQ,i.clone=w1,i.clone$1=H,i.clone$2=Ew,i.collisionCircleLayout=Lt,i.config=pt,i.create=b1,i.create$1=jh,i.create$2=hg,i.createCommonjsModule=a,i.createExpression=oo,i.createLayout=Wi,i.createStyleLayer=Qet,i.cross=q9,i.deepEqual=h,i.dot=O9,i.dot$1=G9,i.ease=b,i.emitValidationErrors=Lu,i.endsWith=V,i.enforceCacheSizeLimit=In,i.evaluateSizeForFeature=PQ,i.evaluateSizeForZoom=IQ,i.evaluateVariableOffset=UQ,i.evented=Ia,i.extend=x,i.featureFilter=be,i.filterObject=Z,i.fromRotation=rm,i.getAnchorAlignment=AS,i.getAnchorJustification=fO,i.getArrayBuffer=ri,i.getImage=ua,i.getJSON=Xr,i.getRTLTextPluginStatus=yo,i.getReferrer=Ut,i.getVideo=ma,i.identity=sy,i.invert=im,i.isChar=nt,i.isMapboxURL=St,i.keysDifference=L,i.makeRequest=Er,i.mapObject=G,i.mercatorXfromLng=$Q,i.mercatorYfromLat=QQ,i.mercatorZfromAltitude=eee,i.mul=Nx,i.multiply=nm,i.mvt=pg,i.nextPowerOfTwo=T,i.normalize=Ux,i.number=nl,i.offscreenCanvasSupported=Fn,i.ortho=wu,i.parseGlyphPBF=v0,i.pbf=Xa,i.performSymbolLayout=Ret,i.perspective=T1,i.pick=C,i.plugin=Ms,i.polygonIntersectsPolygon=so,i.postMapLoadEvent=je,i.postTurnstileEvent=Ge,i.potpack=ep,i.refProperties=ltt,i.register=X,i.registerForPluginStateChange=Da,i.renderColorRamp=Hx,i.rotate=oy,i.rotateX=Sd,i.rotateZ=ly,i.scale=eu,i.scale$1=V9,i.scale$2=kw,i.setCacheLimits=On,i.setRTLTextPlugin=go,i.sphericalToCartesian=Ee,i.sqrLen=nS,i.styleSpec=Rn,i.sub=N9,i.symbolSize=Tet,i.transformMat3=B9,i.transformMat4=uy,i.translate=vc,i.triggerPluginCompletionEvent=ia,i.uniqueId=g,i.validateCustomStyleLayer=Ket,i.validateLight=To,i.validateStyle=wo,i.values=S,i.vectorTile=pg,i.version=o,i.warnOnce=re,i.webpSupported=Zt,i.window=f,i.wrap=k}),n([\"./shared\"],function(i){\"use strict\";function a(Ut){var wt=typeof Ut;if(wt===\"number\"||wt===\"boolean\"||wt===\"string\"||Ut===void 0||Ut===null)return JSON.stringify(Ut);if(Array.isArray(Ut)){for(var rr=\"[\",nr=0,Er=Ut;nr<Er.length;nr+=1){var Xr=Er[nr];rr+=a(Xr)+\",\"}return rr+\"]\"}for(var ri=Object.keys(Ut).sort(),Qr=\"{\",Oi=0;Oi<ri.length;Oi++)Qr+=JSON.stringify(ri[Oi])+\":\"+a(Ut[ri[Oi]])+\",\";return Qr+\"}\"}function o(Ut){for(var wt=\"\",rr=0,nr=i.refProperties;rr<nr.length;rr+=1){var Er=nr[rr];wt+=\"/\"+a(Ut[Er])}return wt}function s(Ut,wt){for(var rr={},nr=0;nr<Ut.length;nr++){var Er=wt&&wt[Ut[nr].id]||o(Ut[nr]);wt&&(wt[Ut[nr].id]=Er);var Xr=rr[Er];Xr||(Xr=rr[Er]=[]),Xr.push(Ut[nr])}var ri=[];for(var Qr in rr)ri.push(rr[Qr]);return ri}var l=function(wt){this.keyCache={},wt&&this.replace(wt)};l.prototype.replace=function(wt){this._layerConfigs={},this._layers={},this.update(wt,[])},l.prototype.update=function(wt,rr){for(var nr=this,Er=0,Xr=wt;Er<Xr.length;Er+=1){var ri=Xr[Er];this._layerConfigs[ri.id]=ri;var Qr=this._layers[ri.id]=i.createStyleLayer(ri);Qr._featureFilter=i.featureFilter(Qr.filter),this.keyCache[ri.id]&&delete this.keyCache[ri.id]}for(var Oi=0,$i=rr;Oi<$i.length;Oi+=1){var tn=$i[Oi];delete this.keyCache[tn],delete this._layerConfigs[tn],delete this._layers[tn]}this.familiesBySource={};for(var fn=s(i.values(this._layerConfigs),this.keyCache),yn=0,Sn=fn;yn<Sn.length;yn+=1){var Ba=Sn[yn],ua=Ba.map(function(Wn){return nr._layers[Wn.id]}),ma=ua[0];if(ma.visibility!==\"none\"){var Wa=ma.source||\"\",Fa=this.familiesBySource[Wa];Fa||(Fa=this.familiesBySource[Wa]={});var Wo=ma.sourceLayer||\"_geojsonTileLayer\",da=Fa[Wo];da||(da=Fa[Wo]=[]),da.push(ua)}}};var u=1,c=function(wt){var rr={},nr=[];for(var Er in wt){var Xr=wt[Er],ri=rr[Er]={};for(var Qr in Xr){var Oi=Xr[+Qr];if(!(!Oi||Oi.bitmap.width===0||Oi.bitmap.height===0)){var $i={x:0,y:0,w:Oi.bitmap.width+2*u,h:Oi.bitmap.height+2*u};nr.push($i),ri[Qr]={rect:$i,metrics:Oi.metrics}}}}var tn=i.potpack(nr),fn=tn.w,yn=tn.h,Sn=new i.AlphaImage({width:fn||1,height:yn||1});for(var Ba in wt){var ua=wt[Ba];for(var ma in ua){var Wa=ua[+ma];if(!(!Wa||Wa.bitmap.width===0||Wa.bitmap.height===0)){var Fa=rr[Ba][ma].rect;i.AlphaImage.copy(Wa.bitmap,Sn,{x:0,y:0},{x:Fa.x+u,y:Fa.y+u},Wa.bitmap)}}}this.image=Sn,this.positions=rr};i.register(\"GlyphAtlas\",c);var f=function(wt){this.tileID=new i.OverscaledTileID(wt.tileID.overscaledZ,wt.tileID.wrap,wt.tileID.canonical.z,wt.tileID.canonical.x,wt.tileID.canonical.y),this.uid=wt.uid,this.zoom=wt.zoom,this.pixelRatio=wt.pixelRatio,this.tileSize=wt.tileSize,this.source=wt.source,this.overscaling=this.tileID.overscaleFactor(),this.showCollisionBoxes=wt.showCollisionBoxes,this.collectResourceTiming=!!wt.collectResourceTiming,this.returnDependencies=!!wt.returnDependencies,this.promoteId=wt.promoteId};f.prototype.parse=function(wt,rr,nr,Er,Xr){var ri=this;this.status=\"parsing\",this.data=wt,this.collisionBoxArray=new i.CollisionBoxArray;var Qr=new i.DictionaryCoder(Object.keys(wt.layers).sort()),Oi=new i.FeatureIndex(this.tileID,this.promoteId);Oi.bucketLayerIDs=[];var $i={},tn={featureIndex:Oi,iconDependencies:{},patternDependencies:{},glyphDependencies:{},availableImages:nr},fn=rr.familiesBySource[this.source];for(var yn in fn){var Sn=wt.layers[yn];if(Sn){Sn.version===1&&i.warnOnce('Vector tile source \"'+this.source+'\" layer \"'+yn+'\" does not use vector tile spec v2 and therefore may have some rendering errors.');for(var Ba=Qr.encode(yn),ua=[],ma=0;ma<Sn.length;ma++){var Wa=Sn.feature(ma),Fa=Oi.getId(Wa,yn);ua.push({feature:Wa,id:Fa,index:ma,sourceLayerIndex:Ba})}for(var Wo=0,da=fn[yn];Wo<da.length;Wo+=1){var Wn=da[Wo],Ga=Wn[0];if(!(Ga.minzoom&&this.zoom<Math.floor(Ga.minzoom))&&!(Ga.maxzoom&&this.zoom>=Ga.maxzoom)&&Ga.visibility!==\"none\"){h(Wn,this.zoom,nr);var vo=$i[Ga.id]=Ga.createBucket({index:Oi.bucketLayerIDs.length,layers:Wn,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:Ba,sourceID:this.source});vo.populate(ua,tn,this.tileID.canonical),Oi.bucketLayerIDs.push(Wn.map(function(Li){return Li.id}))}}}}var jn,Mt,kr,Jr,vi=i.mapObject(tn.glyphDependencies,function(Li){return Object.keys(Li).map(Number)});Object.keys(vi).length?Er.send(\"getGlyphs\",{uid:this.uid,stacks:vi},function(Li,_n){jn||(jn=Li,Mt=_n,Mn.call(ri))}):Mt={};var hn=Object.keys(tn.iconDependencies);hn.length?Er.send(\"getImages\",{icons:hn,source:this.source,tileID:this.tileID,type:\"icons\"},function(Li,_n){jn||(jn=Li,kr=_n,Mn.call(ri))}):kr={};var An=Object.keys(tn.patternDependencies);An.length?Er.send(\"getImages\",{icons:An,source:this.source,tileID:this.tileID,type:\"patterns\"},function(Li,_n){jn||(jn=Li,Jr=_n,Mn.call(ri))}):Jr={},Mn.call(this);function Mn(){if(jn)return Xr(jn);if(Mt&&kr&&Jr){var Li=new c(Mt),_n=new i.ImageAtlas(kr,Jr);for(var ya in $i){var Jn=$i[ya];Jn instanceof i.SymbolBucket?(h(Jn.layers,this.zoom,nr),i.performSymbolLayout(Jn,Mt,Li.positions,kr,_n.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):Jn.hasPattern&&(Jn instanceof i.LineBucket||Jn instanceof i.FillBucket||Jn instanceof i.FillExtrusionBucket)&&(h(Jn.layers,this.zoom,nr),Jn.addFeatures(tn,this.tileID.canonical,_n.patternPositions))}this.status=\"done\",Xr(null,{buckets:i.values($i).filter(function(Ma){return!Ma.isEmpty()}),featureIndex:Oi,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:Li.image,imageAtlas:_n,glyphMap:this.returnDependencies?Mt:null,iconMap:this.returnDependencies?kr:null,glyphPositions:this.returnDependencies?Li.positions:null})}}};function h(Ut,wt,rr){for(var nr=new i.EvaluationParameters(wt),Er=0,Xr=Ut;Er<Xr.length;Er+=1){var ri=Xr[Er];ri.recalculate(nr,rr)}}function d(Ut,wt){var rr=i.getArrayBuffer(Ut.request,function(nr,Er,Xr,ri){nr?wt(nr):Er&&wt(null,{vectorTile:new i.vectorTile.VectorTile(new i.pbf(Er)),rawData:Er,cacheControl:Xr,expires:ri})});return function(){rr.cancel(),wt()}}var v=function(wt,rr,nr,Er){this.actor=wt,this.layerIndex=rr,this.availableImages=nr,this.loadVectorData=Er||d,this.loading={},this.loaded={}};v.prototype.loadTile=function(wt,rr){var nr=this,Er=wt.uid;this.loading||(this.loading={});var Xr=wt&&wt.request&&wt.request.collectResourceTiming?new i.RequestPerformance(wt.request):!1,ri=this.loading[Er]=new f(wt);ri.abort=this.loadVectorData(wt,function(Qr,Oi){if(delete nr.loading[Er],Qr||!Oi)return ri.status=\"done\",nr.loaded[Er]=ri,rr(Qr);var $i=Oi.rawData,tn={};Oi.expires&&(tn.expires=Oi.expires),Oi.cacheControl&&(tn.cacheControl=Oi.cacheControl);var fn={};if(Xr){var yn=Xr.finish();yn&&(fn.resourceTiming=JSON.parse(JSON.stringify(yn)))}ri.vectorTile=Oi.vectorTile,ri.parse(Oi.vectorTile,nr.layerIndex,nr.availableImages,nr.actor,function(Sn,Ba){if(Sn||!Ba)return rr(Sn);rr(null,i.extend({rawTileData:$i.slice(0)},Ba,tn,fn))}),nr.loaded=nr.loaded||{},nr.loaded[Er]=ri})},v.prototype.reloadTile=function(wt,rr){var nr=this,Er=this.loaded,Xr=wt.uid,ri=this;if(Er&&Er[Xr]){var Qr=Er[Xr];Qr.showCollisionBoxes=wt.showCollisionBoxes;var Oi=function($i,tn){var fn=Qr.reloadCallback;fn&&(delete Qr.reloadCallback,Qr.parse(Qr.vectorTile,ri.layerIndex,nr.availableImages,ri.actor,fn)),rr($i,tn)};Qr.status===\"parsing\"?Qr.reloadCallback=Oi:Qr.status===\"done\"&&(Qr.vectorTile?Qr.parse(Qr.vectorTile,this.layerIndex,this.availableImages,this.actor,Oi):Oi())}},v.prototype.abortTile=function(wt,rr){var nr=this.loading,Er=wt.uid;nr&&nr[Er]&&nr[Er].abort&&(nr[Er].abort(),delete nr[Er]),rr()},v.prototype.removeTile=function(wt,rr){var nr=this.loaded,Er=wt.uid;nr&&nr[Er]&&delete nr[Er],rr()};var _=i.window.ImageBitmap,b=function(){this.loaded={}};b.prototype.loadTile=function(wt,rr){var nr=wt.uid,Er=wt.encoding,Xr=wt.rawImageData,ri=_&&Xr instanceof _?this.getImageData(Xr):Xr,Qr=new i.DEMData(nr,ri,Er);this.loaded=this.loaded||{},this.loaded[nr]=Qr,rr(null,Qr)},b.prototype.getImageData=function(wt){(!this.offscreenCanvas||!this.offscreenCanvasContext)&&(this.offscreenCanvas=new OffscreenCanvas(wt.width,wt.height),this.offscreenCanvasContext=this.offscreenCanvas.getContext(\"2d\")),this.offscreenCanvas.width=wt.width,this.offscreenCanvas.height=wt.height,this.offscreenCanvasContext.drawImage(wt,0,0,wt.width,wt.height);var rr=this.offscreenCanvasContext.getImageData(-1,-1,wt.width+2,wt.height+2);return this.offscreenCanvasContext.clearRect(0,0,this.offscreenCanvas.width,this.offscreenCanvas.height),new i.RGBAImage({width:rr.width,height:rr.height},rr.data)},b.prototype.removeTile=function(wt){var rr=this.loaded,nr=wt.uid;rr&&rr[nr]&&delete rr[nr]};var p=k;function k(Ut,wt){var rr=Ut&&Ut.type,nr;if(rr===\"FeatureCollection\")for(nr=0;nr<Ut.features.length;nr++)k(Ut.features[nr],wt);else if(rr===\"GeometryCollection\")for(nr=0;nr<Ut.geometries.length;nr++)k(Ut.geometries[nr],wt);else if(rr===\"Feature\")k(Ut.geometry,wt);else if(rr===\"Polygon\")E(Ut.coordinates,wt);else if(rr===\"MultiPolygon\")for(nr=0;nr<Ut.coordinates.length;nr++)E(Ut.coordinates[nr],wt);return Ut}function E(Ut,wt){if(Ut.length!==0){S(Ut[0],wt);for(var rr=1;rr<Ut.length;rr++)S(Ut[rr],!wt)}}function S(Ut,wt){for(var rr=0,nr=0,Er=Ut.length,Xr=Er-1;nr<Er;Xr=nr++)rr+=(Ut[nr][0]-Ut[Xr][0])*(Ut[Xr][1]+Ut[nr][1]);rr>=0!=!!wt&&Ut.reverse()}var L=i.vectorTile.VectorTileFeature.prototype.toGeoJSON,x=function(wt){this._feature=wt,this.extent=i.EXTENT,this.type=wt.type,this.properties=wt.tags,\"id\"in wt&&!isNaN(wt.id)&&(this.id=parseInt(wt.id,10))};x.prototype.loadGeometry=function(){if(this._feature.type===1){for(var wt=[],rr=0,nr=this._feature.geometry;rr<nr.length;rr+=1){var Er=nr[rr];wt.push([new i.Point$1(Er[0],Er[1])])}return wt}else{for(var Xr=[],ri=0,Qr=this._feature.geometry;ri<Qr.length;ri+=1){for(var Oi=Qr[ri],$i=[],tn=0,fn=Oi;tn<fn.length;tn+=1){var yn=fn[tn];$i.push(new i.Point$1(yn[0],yn[1]))}Xr.push($i)}return Xr}},x.prototype.toGeoJSON=function(wt,rr,nr){return L.call(this,wt,rr,nr)};var C=function(wt){this.layers={_geojsonTileLayer:this},this.name=\"_geojsonTileLayer\",this.extent=i.EXTENT,this.length=wt.length,this._features=wt};C.prototype.feature=function(wt){return new x(this._features[wt])};var M=i.vectorTile.VectorTileFeature,g=P;function P(Ut,wt){this.options=wt||{},this.features=Ut,this.length=Ut.length}P.prototype.feature=function(Ut){return new T(this.features[Ut],this.options.extent)};function T(Ut,wt){this.id=typeof Ut.id==\"number\"?Ut.id:void 0,this.type=Ut.type,this.rawGeometry=Ut.type===1?[Ut.geometry]:Ut.geometry,this.properties=Ut.tags,this.extent=wt||4096}T.prototype.loadGeometry=function(){var Ut=this.rawGeometry;this.geometry=[];for(var wt=0;wt<Ut.length;wt++){for(var rr=Ut[wt],nr=[],Er=0;Er<rr.length;Er++)nr.push(new i.Point$1(rr[Er][0],rr[Er][1]));this.geometry.push(nr)}return this.geometry},T.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var Ut=this.geometry,wt=1/0,rr=-1/0,nr=1/0,Er=-1/0,Xr=0;Xr<Ut.length;Xr++)for(var ri=Ut[Xr],Qr=0;Qr<ri.length;Qr++){var Oi=ri[Qr];wt=Math.min(wt,Oi.x),rr=Math.max(rr,Oi.x),nr=Math.min(nr,Oi.y),Er=Math.max(Er,Oi.y)}return[wt,nr,rr,Er]},T.prototype.toGeoJSON=M.prototype.toGeoJSON;var z=Z,O=Z,V=H,G=g;function Z(Ut){var wt=new i.pbf;return N(Ut,wt),wt.finish()}function H(Ut,wt){wt=wt||{};var rr={};for(var nr in Ut)rr[nr]=new g(Ut[nr].features,wt),rr[nr].name=nr,rr[nr].version=wt.version,rr[nr].extent=wt.extent;return Z({layers:rr})}function N(Ut,wt){for(var rr in Ut.layers)wt.writeMessage(3,j,Ut.layers[rr])}function j(Ut,wt){wt.writeVarintField(15,Ut.version||1),wt.writeStringField(1,Ut.name||\"\"),wt.writeVarintField(5,Ut.extent||4096);var rr,nr={keys:[],values:[],keycache:{},valuecache:{}};for(rr=0;rr<Ut.length;rr++)nr.feature=Ut.feature(rr),wt.writeMessage(2,re,nr);var Er=nr.keys;for(rr=0;rr<Er.length;rr++)wt.writeStringField(3,Er[rr]);var Xr=nr.values;for(rr=0;rr<Xr.length;rr++)wt.writeMessage(4,me,Xr[rr])}function re(Ut,wt){var rr=Ut.feature;rr.id!==void 0&&wt.writeVarintField(1,rr.id),wt.writeMessage(2,oe,Ut),wt.writeVarintField(3,rr.type),wt.writeMessage(4,Ce,rr)}function oe(Ut,wt){var rr=Ut.feature,nr=Ut.keys,Er=Ut.values,Xr=Ut.keycache,ri=Ut.valuecache;for(var Qr in rr.properties){var Oi=Xr[Qr];typeof Oi==\"undefined\"&&(nr.push(Qr),Oi=nr.length-1,Xr[Qr]=Oi),wt.writeVarint(Oi);var $i=rr.properties[Qr],tn=typeof $i;tn!==\"string\"&&tn!==\"boolean\"&&tn!==\"number\"&&($i=JSON.stringify($i));var fn=tn+\":\"+$i,yn=ri[fn];typeof yn==\"undefined\"&&(Er.push($i),yn=Er.length-1,ri[fn]=yn),wt.writeVarint(yn)}}function _e(Ut,wt){return(wt<<3)+(Ut&7)}function Ee(Ut){return Ut<<1^Ut>>31}function Ce(Ut,wt){for(var rr=Ut.loadGeometry(),nr=Ut.type,Er=0,Xr=0,ri=rr.length,Qr=0;Qr<ri;Qr++){var Oi=rr[Qr],$i=1;nr===1&&($i=Oi.length),wt.writeVarint(_e(1,$i));for(var tn=nr===3?Oi.length-1:Oi.length,fn=0;fn<tn;fn++){fn===1&&nr!==1&&wt.writeVarint(_e(2,tn-1));var yn=Oi[fn].x-Er,Sn=Oi[fn].y-Xr;wt.writeVarint(Ee(yn)),wt.writeVarint(Ee(Sn)),Er+=yn,Xr+=Sn}nr===3&&wt.writeVarint(_e(7,1))}}function me(Ut,wt){var rr=typeof Ut;rr===\"string\"?wt.writeStringField(1,Ut):rr===\"boolean\"?wt.writeBooleanField(7,Ut):rr===\"number\"&&(Ut%1!==0?wt.writeDoubleField(3,Ut):Ut<0?wt.writeSVarintField(6,Ut):wt.writeVarintField(5,Ut))}z.fromVectorTileJs=O,z.fromGeojsonVt=V,z.GeoJSONWrapper=G;function ie(Ut,wt,rr,nr,Er,Xr){if(!(Er-nr<=rr)){var ri=nr+Er>>1;Se(Ut,wt,ri,nr,Er,Xr%2),ie(Ut,wt,rr,nr,ri-1,Xr+1),ie(Ut,wt,rr,ri+1,Er,Xr+1)}}function Se(Ut,wt,rr,nr,Er,Xr){for(;Er>nr;){if(Er-nr>600){var ri=Er-nr+1,Qr=rr-nr+1,Oi=Math.log(ri),$i=.5*Math.exp(2*Oi/3),tn=.5*Math.sqrt(Oi*$i*(ri-$i)/ri)*(Qr-ri/2<0?-1:1),fn=Math.max(nr,Math.floor(rr-Qr*$i/ri+tn)),yn=Math.min(Er,Math.floor(rr+(ri-Qr)*$i/ri+tn));Se(Ut,wt,rr,fn,yn,Xr)}var Sn=wt[2*rr+Xr],Ba=nr,ua=Er;for(Le(Ut,wt,nr,rr),wt[2*Er+Xr]>Sn&&Le(Ut,wt,nr,Er);Ba<ua;){for(Le(Ut,wt,Ba,ua),Ba++,ua--;wt[2*Ba+Xr]<Sn;)Ba++;for(;wt[2*ua+Xr]>Sn;)ua--}wt[2*nr+Xr]===Sn?Le(Ut,wt,nr,ua):(ua++,Le(Ut,wt,ua,Er)),ua<=rr&&(nr=ua+1),rr<=ua&&(Er=ua-1)}}function Le(Ut,wt,rr,nr){Ae(Ut,rr,nr),Ae(wt,2*rr,2*nr),Ae(wt,2*rr+1,2*nr+1)}function Ae(Ut,wt,rr){var nr=Ut[wt];Ut[wt]=Ut[rr],Ut[rr]=nr}function Fe(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=[0,Ut.length-1,0],Oi=[],$i,tn;Qr.length;){var fn=Qr.pop(),yn=Qr.pop(),Sn=Qr.pop();if(yn-Sn<=ri){for(var Ba=Sn;Ba<=yn;Ba++)$i=wt[2*Ba],tn=wt[2*Ba+1],$i>=rr&&$i<=Er&&tn>=nr&&tn<=Xr&&Oi.push(Ut[Ba]);continue}var ua=Math.floor((Sn+yn)/2);$i=wt[2*ua],tn=wt[2*ua+1],$i>=rr&&$i<=Er&&tn>=nr&&tn<=Xr&&Oi.push(Ut[ua]);var ma=(fn+1)%2;(fn===0?rr<=$i:nr<=tn)&&(Qr.push(Sn),Qr.push(ua-1),Qr.push(ma)),(fn===0?Er>=$i:Xr>=tn)&&(Qr.push(ua+1),Qr.push(yn),Qr.push(ma))}return Oi}function Pe(Ut,wt,rr,nr,Er,Xr){for(var ri=[0,Ut.length-1,0],Qr=[],Oi=Er*Er;ri.length;){var $i=ri.pop(),tn=ri.pop(),fn=ri.pop();if(tn-fn<=Xr){for(var yn=fn;yn<=tn;yn++)ge(wt[2*yn],wt[2*yn+1],rr,nr)<=Oi&&Qr.push(Ut[yn]);continue}var Sn=Math.floor((fn+tn)/2),Ba=wt[2*Sn],ua=wt[2*Sn+1];ge(Ba,ua,rr,nr)<=Oi&&Qr.push(Ut[Sn]);var ma=($i+1)%2;($i===0?rr-Er<=Ba:nr-Er<=ua)&&(ri.push(fn),ri.push(Sn-1),ri.push(ma)),($i===0?rr+Er>=Ba:nr+Er>=ua)&&(ri.push(Sn+1),ri.push(tn),ri.push(ma))}return Qr}function ge(Ut,wt,rr,nr){var Er=Ut-rr,Xr=wt-nr;return Er*Er+Xr*Xr}var Re=function(Ut){return Ut[0]},ce=function(Ut){return Ut[1]},Ze=function(wt,rr,nr,Er,Xr){rr===void 0&&(rr=Re),nr===void 0&&(nr=ce),Er===void 0&&(Er=64),Xr===void 0&&(Xr=Float64Array),this.nodeSize=Er,this.points=wt;for(var ri=wt.length<65536?Uint16Array:Uint32Array,Qr=this.ids=new ri(wt.length),Oi=this.coords=new Xr(wt.length*2),$i=0;$i<wt.length;$i++)Qr[$i]=$i,Oi[2*$i]=rr(wt[$i]),Oi[2*$i+1]=nr(wt[$i]);ie(Qr,Oi,Er,0,Qr.length-1,0)};Ze.prototype.range=function(wt,rr,nr,Er){return Fe(this.ids,this.coords,wt,rr,nr,Er,this.nodeSize)},Ze.prototype.within=function(wt,rr,nr){return Pe(this.ids,this.coords,wt,rr,nr,this.nodeSize)};var ut={minZoom:0,maxZoom:16,minPoints:2,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(Ut){return Ut}},pt=function(wt){this.options=cr(Object.create(ut),wt),this.trees=new Array(this.options.maxZoom+1)};pt.prototype.load=function(wt){var rr=this.options,nr=rr.log,Er=rr.minZoom,Xr=rr.maxZoom,ri=rr.nodeSize;nr&&console.time(\"total time\");var Qr=\"prepare \"+wt.length+\" points\";nr&&console.time(Qr),this.points=wt;for(var Oi=[],$i=0;$i<wt.length;$i++)wt[$i].geometry&&Oi.push(st(wt[$i],$i));this.trees[Xr+1]=new Ze(Oi,$e,St,ri,Float32Array),nr&&console.timeEnd(Qr);for(var tn=Xr;tn>=Er;tn--){var fn=+Date.now();Oi=this._cluster(Oi,tn),this.trees[tn]=new Ze(Oi,$e,St,ri,Float32Array),nr&&console.log(\"z%d: %d clusters in %dms\",tn,Oi.length,+Date.now()-fn)}return nr&&console.timeEnd(\"total time\"),this},pt.prototype.getClusters=function(wt,rr){var nr=((wt[0]+180)%360+360)%360-180,Er=Math.max(-90,Math.min(90,wt[1])),Xr=wt[2]===180?180:((wt[2]+180)%360+360)%360-180,ri=Math.max(-90,Math.min(90,wt[3]));if(wt[2]-wt[0]>=360)nr=-180,Xr=180;else if(nr>Xr){var Qr=this.getClusters([nr,Er,180,ri],rr),Oi=this.getClusters([-180,Er,Xr,ri],rr);return Qr.concat(Oi)}for(var $i=this.trees[this._limitZoom(rr)],tn=$i.range(Nt(nr),Jt(ri),Nt(Xr),Jt(Er)),fn=[],yn=0,Sn=tn;yn<Sn.length;yn+=1){var Ba=Sn[yn],ua=$i.points[Ba];fn.push(ua.numPoints?lt(ua):this.points[ua.index])}return fn},pt.prototype.getChildren=function(wt){var rr=this._getOriginId(wt),nr=this._getOriginZoom(wt),Er=\"No cluster with the specified id.\",Xr=this.trees[nr];if(!Xr)throw new Error(Er);var ri=Xr.points[rr];if(!ri)throw new Error(Er);for(var Qr=this.options.radius/(this.options.extent*Math.pow(2,nr-1)),Oi=Xr.within(ri.x,ri.y,Qr),$i=[],tn=0,fn=Oi;tn<fn.length;tn+=1){var yn=fn[tn],Sn=Xr.points[yn];Sn.parentId===wt&&$i.push(Sn.numPoints?lt(Sn):this.points[Sn.index])}if($i.length===0)throw new Error(Er);return $i},pt.prototype.getLeaves=function(wt,rr,nr){rr=rr||10,nr=nr||0;var Er=[];return this._appendLeaves(Er,wt,rr,nr,0),Er},pt.prototype.getTile=function(wt,rr,nr){var Er=this.trees[this._limitZoom(wt)],Xr=Math.pow(2,wt),ri=this.options,Qr=ri.extent,Oi=ri.radius,$i=Oi/Qr,tn=(nr-$i)/Xr,fn=(nr+1+$i)/Xr,yn={features:[]};return this._addTileFeatures(Er.range((rr-$i)/Xr,tn,(rr+1+$i)/Xr,fn),Er.points,rr,nr,Xr,yn),rr===0&&this._addTileFeatures(Er.range(1-$i/Xr,tn,1,fn),Er.points,Xr,nr,Xr,yn),rr===Xr-1&&this._addTileFeatures(Er.range(0,tn,$i/Xr,fn),Er.points,-1,nr,Xr,yn),yn.features.length?yn:null},pt.prototype.getClusterExpansionZoom=function(wt){for(var rr=this._getOriginZoom(wt)-1;rr<=this.options.maxZoom;){var nr=this.getChildren(wt);if(rr++,nr.length!==1)break;wt=nr[0].properties.cluster_id}return rr},pt.prototype._appendLeaves=function(wt,rr,nr,Er,Xr){for(var ri=this.getChildren(rr),Qr=0,Oi=ri;Qr<Oi.length;Qr+=1){var $i=Oi[Qr],tn=$i.properties;if(tn&&tn.cluster?Xr+tn.point_count<=Er?Xr+=tn.point_count:Xr=this._appendLeaves(wt,tn.cluster_id,nr,Er,Xr):Xr<Er?Xr++:wt.push($i),wt.length===nr)break}return Xr},pt.prototype._addTileFeatures=function(wt,rr,nr,Er,Xr,ri){for(var Qr=0,Oi=wt;Qr<Oi.length;Qr+=1){var $i=Oi[Qr],tn=rr[$i],fn=tn.numPoints,yn={type:1,geometry:[[Math.round(this.options.extent*(tn.x*Xr-nr)),Math.round(this.options.extent*(tn.y*Xr-Er))]],tags:fn?Gt(tn):this.points[tn.index].properties},Sn=void 0;fn?Sn=tn.id:this.options.generateId?Sn=tn.index:this.points[tn.index].id&&(Sn=this.points[tn.index].id),Sn!==void 0&&(yn.id=Sn),ri.features.push(yn)}},pt.prototype._limitZoom=function(wt){return Math.max(this.options.minZoom,Math.min(+wt,this.options.maxZoom+1))},pt.prototype._cluster=function(wt,rr){for(var nr=[],Er=this.options,Xr=Er.radius,ri=Er.extent,Qr=Er.reduce,Oi=Er.minPoints,$i=Xr/(ri*Math.pow(2,rr)),tn=0;tn<wt.length;tn++){var fn=wt[tn];if(!(fn.zoom<=rr)){fn.zoom=rr;for(var yn=this.trees[rr+1],Sn=yn.within(fn.x,fn.y,$i),Ba=fn.numPoints||1,ua=Ba,ma=0,Wa=Sn;ma<Wa.length;ma+=1){var Fa=Wa[ma],Wo=yn.points[Fa];Wo.zoom>rr&&(ua+=Wo.numPoints||1)}if(ua>=Oi){for(var da=fn.x*Ba,Wn=fn.y*Ba,Ga=Qr&&Ba>1?this._map(fn,!0):null,vo=(tn<<5)+(rr+1)+this.points.length,jn=0,Mt=Sn;jn<Mt.length;jn+=1){var kr=Mt[jn],Jr=yn.points[kr];if(!(Jr.zoom<=rr)){Jr.zoom=rr;var vi=Jr.numPoints||1;da+=Jr.x*vi,Wn+=Jr.y*vi,Jr.parentId=vo,Qr&&(Ga||(Ga=this._map(fn,!0)),Qr(Ga,this._map(Jr)))}}fn.parentId=vo,nr.push(Zt(da/ua,Wn/ua,vo,ua,Ga))}else if(nr.push(fn),ua>1)for(var hn=0,An=Sn;hn<An.length;hn+=1){var Mn=An[hn],Li=yn.points[Mn];Li.zoom<=rr||(Li.zoom=rr,nr.push(Li))}}}return nr},pt.prototype._getOriginId=function(wt){return wt-this.points.length>>5},pt.prototype._getOriginZoom=function(wt){return(wt-this.points.length)%32},pt.prototype._map=function(wt,rr){if(wt.numPoints)return rr?cr({},wt.properties):wt.properties;var nr=this.points[wt.index].properties,Er=this.options.map(nr);return rr&&Er===nr?cr({},Er):Er};function Zt(Ut,wt,rr,nr,Er){return{x:Ut,y:wt,zoom:1/0,id:rr,parentId:-1,numPoints:nr,properties:Er}}function st(Ut,wt){var rr=Ut.geometry.coordinates,nr=rr[0],Er=rr[1];return{x:Nt(nr),y:Jt(Er),zoom:1/0,index:wt,parentId:-1}}function lt(Ut){return{type:\"Feature\",id:Ut.id,properties:Gt(Ut),geometry:{type:\"Point\",coordinates:[sr(Ut.x),wr(Ut.y)]}}}function Gt(Ut){var wt=Ut.numPoints,rr=wt>=1e4?Math.round(wt/1e3)+\"k\":wt>=1e3?Math.round(wt/100)/10+\"k\":wt;return cr(cr({},Ut.properties),{cluster:!0,cluster_id:Ut.id,point_count:wt,point_count_abbreviated:rr})}function Nt(Ut){return Ut/360+.5}function Jt(Ut){var wt=Math.sin(Ut*Math.PI/180),rr=.5-.25*Math.log((1+wt)/(1-wt))/Math.PI;return rr<0?0:rr>1?1:rr}function sr(Ut){return(Ut-.5)*360}function wr(Ut){var wt=(180-Ut*360)*Math.PI/180;return 360*Math.atan(Math.exp(wt))/Math.PI-90}function cr(Ut,wt){for(var rr in wt)Ut[rr]=wt[rr];return Ut}function $e(Ut){return Ut.x}function St(Ut){return Ut.y}function Qt(Ut,wt,rr,nr){for(var Er=nr,Xr=rr-wt>>1,ri=rr-wt,Qr,Oi=Ut[wt],$i=Ut[wt+1],tn=Ut[rr],fn=Ut[rr+1],yn=wt+3;yn<rr;yn+=3){var Sn=Vt(Ut[yn],Ut[yn+1],Oi,$i,tn,fn);if(Sn>Er)Qr=yn,Er=Sn;else if(Sn===Er){var Ba=Math.abs(yn-Xr);Ba<ri&&(Qr=yn,ri=Ba)}}Er>nr&&(Qr-wt>3&&Qt(Ut,wt,Qr,nr),Ut[Qr+2]=Er,rr-Qr>3&&Qt(Ut,Qr,rr,nr))}function Vt(Ut,wt,rr,nr,Er,Xr){var ri=Er-rr,Qr=Xr-nr;if(ri!==0||Qr!==0){var Oi=((Ut-rr)*ri+(wt-nr)*Qr)/(ri*ri+Qr*Qr);Oi>1?(rr=Er,nr=Xr):Oi>0&&(rr+=ri*Oi,nr+=Qr*Oi)}return ri=Ut-rr,Qr=wt-nr,ri*ri+Qr*Qr}function _t(Ut,wt,rr,nr){var Er={id:typeof Ut==\"undefined\"?null:Ut,type:wt,geometry:rr,tags:nr,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return It(Er),Er}function It(Ut){var wt=Ut.geometry,rr=Ut.type;if(rr===\"Point\"||rr===\"MultiPoint\"||rr===\"LineString\")mt(Ut,wt);else if(rr===\"Polygon\"||rr===\"MultiLineString\")for(var nr=0;nr<wt.length;nr++)mt(Ut,wt[nr]);else if(rr===\"MultiPolygon\")for(nr=0;nr<wt.length;nr++)for(var Er=0;Er<wt[nr].length;Er++)mt(Ut,wt[nr][Er])}function mt(Ut,wt){for(var rr=0;rr<wt.length;rr+=3)Ut.minX=Math.min(Ut.minX,wt[rr]),Ut.minY=Math.min(Ut.minY,wt[rr+1]),Ut.maxX=Math.max(Ut.maxX,wt[rr]),Ut.maxY=Math.max(Ut.maxY,wt[rr+1])}function er(Ut,wt){var rr=[];if(Ut.type===\"FeatureCollection\")for(var nr=0;nr<Ut.features.length;nr++)lr(rr,Ut.features[nr],wt,nr);else Ut.type===\"Feature\"?lr(rr,Ut,wt):lr(rr,{geometry:Ut},wt);return rr}function lr(Ut,wt,rr,nr){if(wt.geometry){var Er=wt.geometry.coordinates,Xr=wt.geometry.type,ri=Math.pow(rr.tolerance/((1<<rr.maxZoom)*rr.extent),2),Qr=[],Oi=wt.id;if(rr.promoteId?Oi=wt.properties[rr.promoteId]:rr.generateId&&(Oi=nr||0),Xr===\"Point\")Tr(Er,Qr);else if(Xr===\"MultiPoint\")for(var $i=0;$i<Er.length;$i++)Tr(Er[$i],Qr);else if(Xr===\"LineString\")Lr(Er,Qr,ri,!1);else if(Xr===\"MultiLineString\")if(rr.lineMetrics){for($i=0;$i<Er.length;$i++)Qr=[],Lr(Er[$i],Qr,ri,!1),Ut.push(_t(Oi,\"LineString\",Qr,wt.properties));return}else ti(Er,Qr,ri,!1);else if(Xr===\"Polygon\")ti(Er,Qr,ri,!0);else if(Xr===\"MultiPolygon\")for($i=0;$i<Er.length;$i++){var tn=[];ti(Er[$i],tn,ri,!0),Qr.push(tn)}else if(Xr===\"GeometryCollection\"){for($i=0;$i<wt.geometry.geometries.length;$i++)lr(Ut,{id:Oi,geometry:wt.geometry.geometries[$i],properties:wt.properties},rr,nr);return}else throw new Error(\"Input data is not a valid GeoJSON object.\");Ut.push(_t(Oi,Xr,Qr,wt.properties))}}function Tr(Ut,wt){wt.push(Br(Ut[0])),wt.push(Vr(Ut[1])),wt.push(0)}function Lr(Ut,wt,rr,nr){for(var Er,Xr,ri=0,Qr=0;Qr<Ut.length;Qr++){var Oi=Br(Ut[Qr][0]),$i=Vr(Ut[Qr][1]);wt.push(Oi),wt.push($i),wt.push(0),Qr>0&&(nr?ri+=(Er*$i-Oi*Xr)/2:ri+=Math.sqrt(Math.pow(Oi-Er,2)+Math.pow($i-Xr,2))),Er=Oi,Xr=$i}var tn=wt.length-3;wt[2]=1,Qt(wt,0,tn,rr),wt[tn+2]=1,wt.size=Math.abs(ri),wt.start=0,wt.end=wt.size}function ti(Ut,wt,rr,nr){for(var Er=0;Er<Ut.length;Er++){var Xr=[];Lr(Ut[Er],Xr,rr,nr),wt.push(Xr)}}function Br(Ut){return Ut/360+.5}function Vr(Ut){var wt=Math.sin(Ut*Math.PI/180),rr=.5-.25*Math.log((1+wt)/(1-wt))/Math.PI;return rr<0?0:rr>1?1:rr}function dt(Ut,wt,rr,nr,Er,Xr,ri,Qr){if(rr/=wt,nr/=wt,Xr>=rr&&ri<nr)return Ut;if(ri<rr||Xr>=nr)return null;for(var Oi=[],$i=0;$i<Ut.length;$i++){var tn=Ut[$i],fn=tn.geometry,yn=tn.type,Sn=Er===0?tn.minX:tn.minY,Ba=Er===0?tn.maxX:tn.maxY;if(Sn>=rr&&Ba<nr){Oi.push(tn);continue}else if(Ba<rr||Sn>=nr)continue;var ua=[];if(yn===\"Point\"||yn===\"MultiPoint\")Ge(fn,ua,rr,nr,Er);else if(yn===\"LineString\")Je(fn,ua,rr,nr,Er,!1,Qr.lineMetrics);else if(yn===\"MultiLineString\")tt(fn,ua,rr,nr,Er,!1);else if(yn===\"Polygon\")tt(fn,ua,rr,nr,Er,!0);else if(yn===\"MultiPolygon\")for(var ma=0;ma<fn.length;ma++){var Wa=[];tt(fn[ma],Wa,rr,nr,Er,!0),Wa.length&&ua.push(Wa)}if(ua.length){if(Qr.lineMetrics&&yn===\"LineString\"){for(ma=0;ma<ua.length;ma++)Oi.push(_t(tn.id,yn,ua[ma],tn.tags));continue}(yn===\"LineString\"||yn===\"MultiLineString\")&&(ua.length===1?(yn=\"LineString\",ua=ua[0]):yn=\"MultiLineString\"),(yn===\"Point\"||yn===\"MultiPoint\")&&(yn=ua.length===3?\"Point\":\"MultiPoint\"),Oi.push(_t(tn.id,yn,ua,tn.tags))}}return Oi.length?Oi:null}function Ge(Ut,wt,rr,nr,Er){for(var Xr=0;Xr<Ut.length;Xr+=3){var ri=Ut[Xr+Er];ri>=rr&&ri<=nr&&(wt.push(Ut[Xr]),wt.push(Ut[Xr+1]),wt.push(Ut[Xr+2]))}}function Je(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=je(Ut),Oi=Er===0?Ie:xe,$i=Ut.start,tn,fn,yn=0;yn<Ut.length-3;yn+=3){var Sn=Ut[yn],Ba=Ut[yn+1],ua=Ut[yn+2],ma=Ut[yn+3],Wa=Ut[yn+4],Fa=Er===0?Sn:Ba,Wo=Er===0?ma:Wa,da=!1;ri&&(tn=Math.sqrt(Math.pow(Sn-ma,2)+Math.pow(Ba-Wa,2))),Fa<rr?Wo>rr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,rr),ri&&(Qr.start=$i+tn*fn)):Fa>nr?Wo<nr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,nr),ri&&(Qr.start=$i+tn*fn)):xt(Qr,Sn,Ba,ua),Wo<rr&&Fa>=rr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,rr),da=!0),Wo>nr&&Fa<=nr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,nr),da=!0),!Xr&&da&&(ri&&(Qr.end=$i+tn*fn),wt.push(Qr),Qr=je(Ut)),ri&&($i+=tn)}var Wn=Ut.length-3;Sn=Ut[Wn],Ba=Ut[Wn+1],ua=Ut[Wn+2],Fa=Er===0?Sn:Ba,Fa>=rr&&Fa<=nr&&xt(Qr,Sn,Ba,ua),Wn=Qr.length-3,Xr&&Wn>=3&&(Qr[Wn]!==Qr[0]||Qr[Wn+1]!==Qr[1])&&xt(Qr,Qr[0],Qr[1],Qr[2]),Qr.length&&wt.push(Qr)}function je(Ut){var wt=[];return wt.size=Ut.size,wt.start=Ut.start,wt.end=Ut.end,wt}function tt(Ut,wt,rr,nr,Er,Xr){for(var ri=0;ri<Ut.length;ri++)Je(Ut[ri],wt,rr,nr,Er,Xr,!1)}function xt(Ut,wt,rr,nr){Ut.push(wt),Ut.push(rr),Ut.push(nr)}function Ie(Ut,wt,rr,nr,Er,Xr){var ri=(Xr-wt)/(nr-wt);return Ut.push(Xr),Ut.push(rr+(Er-rr)*ri),Ut.push(1),ri}function xe(Ut,wt,rr,nr,Er,Xr){var ri=(Xr-rr)/(Er-rr);return Ut.push(wt+(nr-wt)*ri),Ut.push(Xr),Ut.push(1),ri}function ke(Ut,wt){var rr=wt.buffer/wt.extent,nr=Ut,Er=dt(Ut,1,-1-rr,rr,0,-1,2,wt),Xr=dt(Ut,1,1-rr,2+rr,0,-1,2,wt);return(Er||Xr)&&(nr=dt(Ut,1,-rr,1+rr,0,-1,2,wt)||[],Er&&(nr=vt(Er,1).concat(nr)),Xr&&(nr=nr.concat(vt(Xr,-1)))),nr}function vt(Ut,wt){for(var rr=[],nr=0;nr<Ut.length;nr++){var Er=Ut[nr],Xr=Er.type,ri;if(Xr===\"Point\"||Xr===\"MultiPoint\"||Xr===\"LineString\")ri=ir(Er.geometry,wt);else if(Xr===\"MultiLineString\"||Xr===\"Polygon\"){ri=[];for(var Qr=0;Qr<Er.geometry.length;Qr++)ri.push(ir(Er.geometry[Qr],wt))}else if(Xr===\"MultiPolygon\")for(ri=[],Qr=0;Qr<Er.geometry.length;Qr++){for(var Oi=[],$i=0;$i<Er.geometry[Qr].length;$i++)Oi.push(ir(Er.geometry[Qr][$i],wt));ri.push(Oi)}rr.push(_t(Er.id,Xr,ri,Er.tags))}return rr}function ir(Ut,wt){var rr=[];rr.size=Ut.size,Ut.start!==void 0&&(rr.start=Ut.start,rr.end=Ut.end);for(var nr=0;nr<Ut.length;nr+=3)rr.push(Ut[nr]+wt,Ut[nr+1],Ut[nr+2]);return rr}function ar(Ut,wt){if(Ut.transformed)return Ut;var rr=1<<Ut.z,nr=Ut.x,Er=Ut.y,Xr,ri,Qr;for(Xr=0;Xr<Ut.features.length;Xr++){var Oi=Ut.features[Xr],$i=Oi.geometry,tn=Oi.type;if(Oi.geometry=[],tn===1)for(ri=0;ri<$i.length;ri+=2)Oi.geometry.push(vr($i[ri],$i[ri+1],wt,rr,nr,Er));else for(ri=0;ri<$i.length;ri++){var fn=[];for(Qr=0;Qr<$i[ri].length;Qr+=2)fn.push(vr($i[ri][Qr],$i[ri][Qr+1],wt,rr,nr,Er));Oi.geometry.push(fn)}}return Ut.transformed=!0,Ut}function vr(Ut,wt,rr,nr,Er,Xr){return[Math.round(rr*(Ut*nr-Er)),Math.round(rr*(wt*nr-Xr))]}function ii(Ut,wt,rr,nr,Er){for(var Xr=wt===Er.maxZoom?0:Er.tolerance/((1<<wt)*Er.extent),ri={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:rr,y:nr,z:wt,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},Qr=0;Qr<Ut.length;Qr++){ri.numFeatures++,pi(ri,Ut[Qr],Xr,Er);var Oi=Ut[Qr].minX,$i=Ut[Qr].minY,tn=Ut[Qr].maxX,fn=Ut[Qr].maxY;Oi<ri.minX&&(ri.minX=Oi),$i<ri.minY&&(ri.minY=$i),tn>ri.maxX&&(ri.maxX=tn),fn>ri.maxY&&(ri.maxY=fn)}return ri}function pi(Ut,wt,rr,nr){var Er=wt.geometry,Xr=wt.type,ri=[];if(Xr===\"Point\"||Xr===\"MultiPoint\")for(var Qr=0;Qr<Er.length;Qr+=3)ri.push(Er[Qr]),ri.push(Er[Qr+1]),Ut.numPoints++,Ut.numSimplified++;else if(Xr===\"LineString\")$r(ri,Er,Ut,rr,!1,!1);else if(Xr===\"MultiLineString\"||Xr===\"Polygon\")for(Qr=0;Qr<Er.length;Qr++)$r(ri,Er[Qr],Ut,rr,Xr===\"Polygon\",Qr===0);else if(Xr===\"MultiPolygon\")for(var Oi=0;Oi<Er.length;Oi++){var $i=Er[Oi];for(Qr=0;Qr<$i.length;Qr++)$r(ri,$i[Qr],Ut,rr,!0,Qr===0)}if(ri.length){var tn=wt.tags||null;if(Xr===\"LineString\"&&nr.lineMetrics){tn={};for(var fn in wt.tags)tn[fn]=wt.tags[fn];tn.mapbox_clip_start=Er.start/Er.size,tn.mapbox_clip_end=Er.end/Er.size}var yn={geometry:ri,type:Xr===\"Polygon\"||Xr===\"MultiPolygon\"?3:Xr===\"LineString\"||Xr===\"MultiLineString\"?2:1,tags:tn};wt.id!==null&&(yn.id=wt.id),Ut.features.push(yn)}}function $r(Ut,wt,rr,nr,Er,Xr){var ri=nr*nr;if(nr>0&&wt.size<(Er?ri:nr)){rr.numPoints+=wt.length/3;return}for(var Qr=[],Oi=0;Oi<wt.length;Oi+=3)(nr===0||wt[Oi+2]>ri)&&(rr.numSimplified++,Qr.push(wt[Oi]),Qr.push(wt[Oi+1])),rr.numPoints++;Er&&di(Qr,Xr),Ut.push(Qr)}function di(Ut,wt){for(var rr=0,nr=0,Er=Ut.length,Xr=Er-2;nr<Er;Xr=nr,nr+=2)rr+=(Ut[nr]-Ut[Xr])*(Ut[nr+1]+Ut[Xr+1]);if(rr>0===wt)for(nr=0,Er=Ut.length;nr<Er/2;nr+=2){var ri=Ut[nr],Qr=Ut[nr+1];Ut[nr]=Ut[Er-2-nr],Ut[nr+1]=Ut[Er-1-nr],Ut[Er-2-nr]=ri,Ut[Er-1-nr]=Qr}}function ji(Ut,wt){return new In(Ut,wt)}function In(Ut,wt){wt=this.options=On(Object.create(this.options),wt);var rr=wt.debug;if(rr&&console.time(\"preprocess data\"),wt.maxZoom<0||wt.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(wt.promoteId&&wt.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var nr=er(Ut,wt);this.tiles={},this.tileCoords=[],rr&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",wt.indexMaxZoom,wt.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),nr=ke(nr,wt),nr.length&&this.splitTile(nr,0,0,0),rr&&(nr.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}In.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},In.prototype.splitTile=function(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=[Ut,wt,rr,nr],Oi=this.options,$i=Oi.debug;Qr.length;){nr=Qr.pop(),rr=Qr.pop(),wt=Qr.pop(),Ut=Qr.pop();var tn=1<<wt,fn=wi(wt,rr,nr),yn=this.tiles[fn];if(!yn&&($i>1&&console.time(\"creation\"),yn=this.tiles[fn]=ii(Ut,wt,rr,nr,Oi),this.tileCoords.push({z:wt,x:rr,y:nr}),$i)){$i>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",wt,rr,nr,yn.numFeatures,yn.numPoints,yn.numSimplified),console.timeEnd(\"creation\"));var Sn=\"z\"+wt;this.stats[Sn]=(this.stats[Sn]||0)+1,this.total++}if(yn.source=Ut,Er){if(wt===Oi.maxZoom||wt===Er)continue;var Ba=1<<Er-wt;if(rr!==Math.floor(Xr/Ba)||nr!==Math.floor(ri/Ba))continue}else if(wt===Oi.indexMaxZoom||yn.numPoints<=Oi.indexMaxPoints)continue;if(yn.source=null,Ut.length!==0){$i>1&&console.time(\"clipping\");var ua=.5*Oi.buffer/Oi.extent,ma=.5-ua,Wa=.5+ua,Fa=1+ua,Wo,da,Wn,Ga,vo,jn;Wo=da=Wn=Ga=null,vo=dt(Ut,tn,rr-ua,rr+Wa,0,yn.minX,yn.maxX,Oi),jn=dt(Ut,tn,rr+ma,rr+Fa,0,yn.minX,yn.maxX,Oi),Ut=null,vo&&(Wo=dt(vo,tn,nr-ua,nr+Wa,1,yn.minY,yn.maxY,Oi),da=dt(vo,tn,nr+ma,nr+Fa,1,yn.minY,yn.maxY,Oi),vo=null),jn&&(Wn=dt(jn,tn,nr-ua,nr+Wa,1,yn.minY,yn.maxY,Oi),Ga=dt(jn,tn,nr+ma,nr+Fa,1,yn.minY,yn.maxY,Oi),jn=null),$i>1&&console.timeEnd(\"clipping\"),Qr.push(Wo||[],wt+1,rr*2,nr*2),Qr.push(da||[],wt+1,rr*2,nr*2+1),Qr.push(Wn||[],wt+1,rr*2+1,nr*2),Qr.push(Ga||[],wt+1,rr*2+1,nr*2+1)}}},In.prototype.getTile=function(Ut,wt,rr){var nr=this.options,Er=nr.extent,Xr=nr.debug;if(Ut<0||Ut>24)return null;var ri=1<<Ut;wt=(wt%ri+ri)%ri;var Qr=wi(Ut,wt,rr);if(this.tiles[Qr])return ar(this.tiles[Qr],Er);Xr>1&&console.log(\"drilling down to z%d-%d-%d\",Ut,wt,rr);for(var Oi=Ut,$i=wt,tn=rr,fn;!fn&&Oi>0;)Oi--,$i=Math.floor($i/2),tn=Math.floor(tn/2),fn=this.tiles[wi(Oi,$i,tn)];return!fn||!fn.source?null:(Xr>1&&console.log(\"found parent tile z%d-%d-%d\",Oi,$i,tn),Xr>1&&console.time(\"drilling down\"),this.splitTile(fn.source,Oi,$i,tn,Ut,wt,rr),Xr>1&&console.timeEnd(\"drilling down\"),this.tiles[Qr]?ar(this.tiles[Qr],Er):null)};function wi(Ut,wt,rr){return((1<<Ut)*rr+wt)*32+Ut}function On(Ut,wt){for(var rr in wt)Ut[rr]=wt[rr];return Ut}function qn(Ut,wt){var rr=Ut.tileID.canonical;if(!this._geoJSONIndex)return wt(null,null);var nr=this._geoJSONIndex.getTile(rr.z,rr.x,rr.y);if(!nr)return wt(null,null);var Er=new C(nr.features),Xr=z(Er);(Xr.byteOffset!==0||Xr.byteLength!==Xr.buffer.byteLength)&&(Xr=new Uint8Array(Xr)),wt(null,{vectorTile:Er,rawData:Xr.buffer})}var Fn=function(Ut){function wt(rr,nr,Er,Xr){Ut.call(this,rr,nr,Er,qn),Xr&&(this.loadGeoJSON=Xr)}return Ut&&(wt.__proto__=Ut),wt.prototype=Object.create(Ut&&Ut.prototype),wt.prototype.constructor=wt,wt.prototype.loadData=function(nr,Er){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=Er,this._pendingLoadDataParams=nr,this._state&&this._state!==\"Idle\"?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},wt.prototype._loadData=function(){var nr=this;if(!(!this._pendingCallback||!this._pendingLoadDataParams)){var Er=this._pendingCallback,Xr=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var ri=Xr&&Xr.request&&Xr.request.collectResourceTiming?new i.RequestPerformance(Xr.request):!1;this.loadGeoJSON(Xr,function(Qr,Oi){if(Qr||!Oi)return Er(Qr);if(typeof Oi!=\"object\")return Er(new Error(\"Input data given to '\"+Xr.source+\"' is not a valid GeoJSON object.\"));p(Oi,!0);try{if(Xr.filter){var $i=i.createExpression(Xr.filter,{type:\"boolean\",\"property-type\":\"data-driven\",overridable:!1,transition:!1});if($i.result===\"error\")throw new Error($i.value.map(function(Sn){return Sn.key+\": \"+Sn.message}).join(\", \"));var tn=Oi.features.filter(function(Sn){return $i.value.evaluate({zoom:0},Sn)});Oi={type:\"FeatureCollection\",features:tn}}nr._geoJSONIndex=Xr.cluster?new pt(ra(Xr)).load(Oi.features):ji(Oi,Xr.geojsonVtOptions)}catch(Sn){return Er(Sn)}nr.loaded={};var fn={};if(ri){var yn=ri.finish();yn&&(fn.resourceTiming={},fn.resourceTiming[Xr.source]=JSON.parse(JSON.stringify(yn)))}Er(null,fn)})}},wt.prototype.coalesce=function(){this._state===\"Coalescing\"?this._state=\"Idle\":this._state===\"NeedsLoadData\"&&(this._state=\"Coalescing\",this._loadData())},wt.prototype.reloadTile=function(nr,Er){var Xr=this.loaded,ri=nr.uid;return Xr&&Xr[ri]?Ut.prototype.reloadTile.call(this,nr,Er):this.loadTile(nr,Er)},wt.prototype.loadGeoJSON=function(nr,Er){if(nr.request)i.getJSON(nr.request,Er);else if(typeof nr.data==\"string\")try{return Er(null,JSON.parse(nr.data))}catch(Xr){return Er(new Error(\"Input data given to '\"+nr.source+\"' is not a valid GeoJSON object.\"))}else return Er(new Error(\"Input data given to '\"+nr.source+\"' is not a valid GeoJSON object.\"))},wt.prototype.removeSource=function(nr,Er){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),Er()},wt.prototype.getClusterExpansionZoom=function(nr,Er){try{Er(null,this._geoJSONIndex.getClusterExpansionZoom(nr.clusterId))}catch(Xr){Er(Xr)}},wt.prototype.getClusterChildren=function(nr,Er){try{Er(null,this._geoJSONIndex.getChildren(nr.clusterId))}catch(Xr){Er(Xr)}},wt.prototype.getClusterLeaves=function(nr,Er){try{Er(null,this._geoJSONIndex.getLeaves(nr.clusterId,nr.limit,nr.offset))}catch(Xr){Er(Xr)}},wt}(v);function ra(Ut){var wt=Ut.superclusterOptions,rr=Ut.clusterProperties;if(!rr||!wt)return wt;for(var nr={},Er={},Xr={accumulated:null,zoom:0},ri={properties:null},Qr=Object.keys(rr),Oi=0,$i=Qr;Oi<$i.length;Oi+=1){var tn=$i[Oi],fn=rr[tn],yn=fn[0],Sn=fn[1],Ba=i.createExpression(Sn),ua=i.createExpression(typeof yn==\"string\"?[yn,[\"accumulated\"],[\"get\",tn]]:yn);nr[tn]=Ba.value,Er[tn]=ua.value}return wt.map=function(ma){ri.properties=ma;for(var Wa={},Fa=0,Wo=Qr;Fa<Wo.length;Fa+=1){var da=Wo[Fa];Wa[da]=nr[da].evaluate(Xr,ri)}return Wa},wt.reduce=function(ma,Wa){ri.properties=Wa;for(var Fa=0,Wo=Qr;Fa<Wo.length;Fa+=1){var da=Wo[Fa];Xr.accumulated=ma[da],ma[da]=Er[da].evaluate(Xr,ri)}},wt}var la=function(wt){var rr=this;this.self=wt,this.actor=new i.Actor(wt,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:v,geojson:Fn},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(nr,Er){if(rr.workerSourceTypes[nr])throw new Error('Worker source with name \"'+nr+'\" already registered.');rr.workerSourceTypes[nr]=Er},this.self.registerRTLTextPlugin=function(nr){if(i.plugin.isParsed())throw new Error(\"RTL text plugin already registered.\");i.plugin.applyArabicShaping=nr.applyArabicShaping,i.plugin.processBidirectionalText=nr.processBidirectionalText,i.plugin.processStyledBidirectionalText=nr.processStyledBidirectionalText}};return la.prototype.setReferrer=function(wt,rr){this.referrer=rr},la.prototype.setImages=function(wt,rr,nr){this.availableImages[wt]=rr;for(var Er in this.workerSources[wt]){var Xr=this.workerSources[wt][Er];for(var ri in 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Er=this.workerSources[wt][rr.type][rr.source];delete this.workerSources[wt][rr.type][rr.source],Er.removeSource!==void 0?Er.removeSource(rr,nr):nr()}},la.prototype.loadWorkerSource=function(wt,rr,nr){try{this.self.importScripts(rr.url),nr()}catch(Er){nr(Er.toString())}},la.prototype.syncRTLPluginState=function(wt,rr,nr){try{i.plugin.setState(rr);var Er=i.plugin.getPluginURL();if(i.plugin.isLoaded()&&!i.plugin.isParsed()&&Er!=null){this.self.importScripts(Er);var Xr=i.plugin.isParsed(),ri=Xr?void 0:new Error(\"RTL Text Plugin failed to import scripts from \"+Er);nr(ri,Xr)}}catch(Qr){nr(Qr.toString())}},la.prototype.getAvailableImages=function(wt){var rr=this.availableImages[wt];return rr||(rr=[]),rr},la.prototype.getLayerIndex=function(wt){var rr=this.layerIndexes[wt];return rr||(rr=this.layerIndexes[wt]=new l),rr},la.prototype.getWorkerSource=function(wt,rr,nr){var Er=this;if(this.workerSources[wt]||(this.workerSources[wt]={}),this.workerSources[wt][rr]||(this.workerSources[wt][rr]={}),!this.workerSources[wt][rr][nr]){var Xr={send:function(ri,Qr,Oi){Er.actor.send(ri,Qr,Oi,wt)}};this.workerSources[wt][rr][nr]=new this.workerSourceTypes[rr](Xr,this.getLayerIndex(wt),this.getAvailableImages(wt))}return this.workerSources[wt][rr][nr]},la.prototype.getDEMWorkerSource=function(wt,rr){return this.demWorkerSources[wt]||(this.demWorkerSources[wt]={}),this.demWorkerSources[wt][rr]||(this.demWorkerSources[wt][rr]=new b),this.demWorkerSources[wt][rr]},la.prototype.enforceCacheSizeLimit=function(wt,rr){i.enforceCacheSizeLimit(rr)},typeof WorkerGlobalScope!=\"undefined\"&&typeof self!=\"undefined\"&&self instanceof WorkerGlobalScope&&(self.worker=new la(self)),la}),n([\"./shared\"],function(i){\"use strict\";var 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Array.prototype&&Array.prototype.every&&Array.prototype.filter&&Array.prototype.forEach&&Array.prototype.indexOf&&Array.prototype.lastIndexOf&&Array.prototype.map&&Array.prototype.some&&Array.prototype.reduce&&Array.prototype.reduceRight&&Array.isArray}function de(){return Function.prototype&&Function.prototype.bind}function ne(){return Object.keys&&Object.create&&Object.getPrototypeOf&&Object.getOwnPropertyNames&&Object.isSealed&&Object.isFrozen&&Object.isExtensible&&Object.getOwnPropertyDescriptor&&Object.defineProperty&&Object.defineProperties&&Object.seal&&Object.freeze&&Object.preventExtensions}function we(){return\"JSON\"in window&&\"parse\"in JSON&&\"stringify\"in JSON}function Ue(){if(!(\"Worker\"in window&&\"Blob\"in window&&\"URL\"in window))return!1;var Ct=new Blob([\"\"],{type:\"text/javascript\"}),Ot=URL.createObjectURL(Ct),Rt,Bt;try{Bt=new Worker(Ot),Rt=!0}catch(Dt){Rt=!1}return Bt&&Bt.terminate(),URL.revokeObjectURL(Ot),Rt}function ft(){return\"Uint8ClampedArray\"in 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q&&h?Y.addEventListener(D,J,q):Y.addEventListener(D,J,q.capture)},o.removeEventListener=function(Y,D,J,q){q===void 0&&(q={}),\"passive\"in q&&h?Y.removeEventListener(D,J,q):Y.removeEventListener(D,J,q.capture)};var v=function(Y){Y.preventDefault(),Y.stopPropagation(),i.window.removeEventListener(\"click\",v,!0)};o.suppressClick=function(){i.window.addEventListener(\"click\",v,!0),i.window.setTimeout(function(){i.window.removeEventListener(\"click\",v,!0)},0)},o.mousePos=function(Y,D){var J=Y.getBoundingClientRect();return new i.Point(D.clientX-J.left-Y.clientLeft,D.clientY-J.top-Y.clientTop)},o.touchPos=function(Y,D){for(var J=Y.getBoundingClientRect(),q=[],K=0;K<D.length;K++)q.push(new i.Point(D[K].clientX-J.left-Y.clientLeft,D[K].clientY-J.top-Y.clientTop));return q},o.mouseButton=function(Y){return typeof i.window.InstallTrigger!=\"undefined\"&&Y.button===2&&Y.ctrlKey&&i.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:Y.button},o.remove=function(Y){Y.parentNode&&Y.parentNode.removeChild(Y)};function _(Y,D,J){var q,K,de,ne=i.browser.devicePixelRatio>1?\"@2x\":\"\",we=i.getJSON(D.transformRequest(D.normalizeSpriteURL(Y,ne,\".json\"),i.ResourceType.SpriteJSON),function(Xt,hr){we=null,de||(de=Xt,q=hr,ft())}),Ue=i.getImage(D.transformRequest(D.normalizeSpriteURL(Y,ne,\".png\"),i.ResourceType.SpriteImage),function(Xt,hr){Ue=null,de||(de=Xt,K=hr,ft())});function ft(){if(de)J(de);else if(q&&K){var Xt=i.browser.getImageData(K),hr={};for(var qt in q){var Ve=q[qt],Qe=Ve.width,at=Ve.height,Ct=Ve.x,Ot=Ve.y,Rt=Ve.sdf,Bt=Ve.pixelRatio,Dt=Ve.stretchX,yt=Ve.stretchY,Pt=Ve.content,ht=new i.RGBAImage({width:Qe,height:at});i.RGBAImage.copy(Xt,ht,{x:Ct,y:Ot},{x:0,y:0},{width:Qe,height:at}),hr[qt]={data:ht,pixelRatio:Bt,sdf:Rt,stretchX:Dt,stretchY:yt,content:Pt}}J(null,hr)}}return{cancel:function(){we&&(we.cancel(),we=null),Ue&&(Ue.cancel(),Ue=null)}}}function b(Y){var D=Y.userImage;if(D&&D.render){var J=D.render();if(J)return Y.data.replace(new Uint8Array(D.data.buffer)),!0}return!1}var p=1,k=function(Y){function D(){Y.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new i.RGBAImage({width:1,height:1}),this.dirty=!0}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.isLoaded=function(){return this.loaded},D.prototype.setLoaded=function(q){if(this.loaded!==q&&(this.loaded=q,q)){for(var K=0,de=this.requestors;K<de.length;K+=1){var ne=de[K],we=ne.ids,Ue=ne.callback;this._notify(we,Ue)}this.requestors=[]}},D.prototype.getImage=function(q){return this.images[q]},D.prototype.addImage=function(q,K){this._validate(q,K)&&(this.images[q]=K)},D.prototype._validate=function(q,K){var de=!0;return this._validateStretch(K.stretchX,K.data&&K.data.width)||(this.fire(new i.ErrorEvent(new Error('Image \"'+q+'\" has invalid \"stretchX\" value'))),de=!1),this._validateStretch(K.stretchY,K.data&&K.data.height)||(this.fire(new i.ErrorEvent(new Error('Image \"'+q+'\" has invalid \"stretchY\" value'))),de=!1),this._validateContent(K.content,K)||(this.fire(new i.ErrorEvent(new Error('Image \"'+q+'\" has invalid \"content\" value'))),de=!1),de},D.prototype._validateStretch=function(q,K){if(!q)return!0;for(var de=0,ne=0,we=q;ne<we.length;ne+=1){var Ue=we[ne];if(Ue[0]<de||Ue[1]<Ue[0]||K<Ue[1])return!1;de=Ue[1]}return!0},D.prototype._validateContent=function(q,K){return q?!(q.length!==4||q[0]<0||K.data.width<q[0]||q[1]<0||K.data.height<q[1]||q[2]<0||K.data.width<q[2]||q[3]<0||K.data.height<q[3]||q[2]<q[0]||q[3]<q[1]):!0},D.prototype.updateImage=function(q,K){var de=this.images[q];K.version=de.version+1,this.images[q]=K,this.updatedImages[q]=!0},D.prototype.removeImage=function(q){var K=this.images[q];delete this.images[q],delete this.patterns[q],K.userImage&&K.userImage.onRemove&&K.userImage.onRemove()},D.prototype.listImages=function(){return Object.keys(this.images)},D.prototype.getImages=function(q,K){var de=!0;if(!this.isLoaded())for(var ne=0,we=q;ne<we.length;ne+=1){var Ue=we[ne];this.images[Ue]||(de=!1)}this.isLoaded()||de?this._notify(q,K):this.requestors.push({ids:q,callback:K})},D.prototype._notify=function(q,K){for(var de={},ne=0,we=q;ne<we.length;ne+=1){var Ue=we[ne];this.images[Ue]||this.fire(new i.Event(\"styleimagemissing\",{id:Ue}));var ft=this.images[Ue];ft?de[Ue]={data:ft.data.clone(),pixelRatio:ft.pixelRatio,sdf:ft.sdf,version:ft.version,stretchX:ft.stretchX,stretchY:ft.stretchY,content:ft.content,hasRenderCallback:!!(ft.userImage&&ft.userImage.render)}:i.warnOnce('Image \"'+Ue+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}K(null,de)},D.prototype.getPixelSize=function(){var q=this.atlasImage,K=q.width,de=q.height;return{width:K,height:de}},D.prototype.getPattern=function(q){var K=this.patterns[q],de=this.getImage(q);if(!de)return null;if(K&&K.position.version===de.version)return K.position;if(K)K.position.version=de.version;else{var ne=de.data.width+p*2,we=de.data.height+p*2,Ue={w:ne,h:we,x:0,y:0},ft=new i.ImagePosition(Ue,de);this.patterns[q]={bin:Ue,position:ft}}return this._updatePatternAtlas(),this.patterns[q].position},D.prototype.bind=function(q){var K=q.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new i.Texture(q,this.atlasImage,K.RGBA),this.atlasTexture.bind(K.LINEAR,K.CLAMP_TO_EDGE)},D.prototype._updatePatternAtlas=function(){var q=[];for(var K in this.patterns)q.push(this.patterns[K].bin);var de=i.potpack(q),ne=de.w,we=de.h,Ue=this.atlasImage;Ue.resize({width:ne||1,height:we||1});for(var ft in this.patterns){var Xt=this.patterns[ft],hr=Xt.bin,qt=hr.x+p,Ve=hr.y+p,Qe=this.images[ft].data,at=Qe.width,Ct=Qe.height;i.RGBAImage.copy(Qe,Ue,{x:0,y:0},{x:qt,y:Ve},{width:at,height:Ct}),i.RGBAImage.copy(Qe,Ue,{x:0,y:Ct-1},{x:qt,y:Ve-1},{width:at,height:1}),i.RGBAImage.copy(Qe,Ue,{x:0,y:0},{x:qt,y:Ve+Ct},{width:at,height:1}),i.RGBAImage.copy(Qe,Ue,{x:at-1,y:0},{x:qt-1,y:Ve},{width:1,height:Ct}),i.RGBAImage.copy(Qe,Ue,{x:0,y:0},{x:qt+at,y:Ve},{width:1,height:Ct})}this.dirty=!0},D.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},D.prototype.dispatchRenderCallbacks=function(q){for(var K=0,de=q;K<de.length;K+=1){var ne=de[K];if(!this.callbackDispatchedThisFrame[ne]){this.callbackDispatchedThisFrame[ne]=!0;var we=this.images[ne],Ue=b(we);Ue&&this.updateImage(ne,we)}}},D}(i.Evented);function E(Y,D,J,q,K){var de=D*256,ne=de+255,we=q.transformRequest(q.normalizeGlyphsURL(J).replace(\"{fontstack}\",Y).replace(\"{range}\",de+\"-\"+ne),i.ResourceType.Glyphs);i.getArrayBuffer(we,function(Ue,ft){if(Ue)K(Ue);else if(ft){for(var Xt={},hr=0,qt=i.parseGlyphPBF(ft);hr<qt.length;hr+=1){var Ve=qt[hr];Xt[Ve.id]=Ve}K(null,Xt)}})}var S=C,L=C,x=1e20;function C(Y,D,J,q,K,de){this.fontSize=Y||24,this.buffer=D===void 0?3:D,this.cutoff=q||.25,this.fontFamily=K||\"sans-serif\",this.fontWeight=de||\"normal\",this.radius=J||8;var ne=this.size=this.fontSize+this.buffer*2;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=ne,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(ne*ne),this.gridInner=new Float64Array(ne*ne),this.f=new Float64Array(ne),this.d=new Float64Array(ne),this.z=new Float64Array(ne+1),this.v=new Int16Array(ne),this.middle=Math.round(ne/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}C.prototype.draw=function(Y){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(Y,this.buffer,this.middle);for(var D=this.ctx.getImageData(0,0,this.size,this.size),J=new Uint8ClampedArray(this.size*this.size),q=0;q<this.size*this.size;q++){var K=D.data[q*4+3]/255;this.gridOuter[q]=K===1?0:K===0?x:Math.pow(Math.max(0,.5-K),2),this.gridInner[q]=K===1?x:K===0?0:Math.pow(Math.max(0,K-.5),2)}for(M(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),M(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),q=0;q<this.size*this.size;q++){var de=this.gridOuter[q]-this.gridInner[q];J[q]=Math.max(0,Math.min(255,Math.round(255-255*(de/this.radius+this.cutoff))))}return J};function M(Y,D,J,q,K,de,ne){for(var we=0;we<D;we++){for(var Ue=0;Ue<J;Ue++)q[Ue]=Y[Ue*D+we];for(g(q,K,de,ne,J),Ue=0;Ue<J;Ue++)Y[Ue*D+we]=K[Ue]}for(Ue=0;Ue<J;Ue++){for(we=0;we<D;we++)q[we]=Y[Ue*D+we];for(g(q,K,de,ne,D),we=0;we<D;we++)Y[Ue*D+we]=Math.sqrt(K[we])}}function g(Y,D,J,q,K){J[0]=0,q[0]=-x,q[1]=+x;for(var de=1,ne=0;de<K;de++){for(var we=(Y[de]+de*de-(Y[J[ne]]+J[ne]*J[ne]))/(2*de-2*J[ne]);we<=q[ne];)ne--,we=(Y[de]+de*de-(Y[J[ne]]+J[ne]*J[ne]))/(2*de-2*J[ne]);ne++,J[ne]=de,q[ne]=we,q[ne+1]=+x}for(de=0,ne=0;de<K;de++){for(;q[ne+1]<de;)ne++;D[de]=(de-J[ne])*(de-J[ne])+Y[J[ne]]}}S.default=L;var P=function(D,J){this.requestManager=D,this.localIdeographFontFamily=J,this.entries={}};P.prototype.setURL=function(D){this.url=D},P.prototype.getGlyphs=function(D,J){var q=this,K=[];for(var de in D)for(var ne=0,we=D[de];ne<we.length;ne+=1){var Ue=we[ne];K.push({stack:de,id:Ue})}i.asyncAll(K,function(ft,Xt){var hr=ft.stack,qt=ft.id,Ve=q.entries[hr];Ve||(Ve=q.entries[hr]={glyphs:{},requests:{},ranges:{}});var Qe=Ve.glyphs[qt];if(Qe!==void 0){Xt(null,{stack:hr,id:qt,glyph:Qe});return}if(Qe=q._tinySDF(Ve,hr,qt),Qe){Ve.glyphs[qt]=Qe,Xt(null,{stack:hr,id:qt,glyph:Qe});return}var at=Math.floor(qt/256);if(at*256>65535){Xt(new Error(\"glyphs > 65535 not supported\"));return}if(Ve.ranges[at]){Xt(null,{stack:hr,id:qt,glyph:Qe});return}var Ct=Ve.requests[at];Ct||(Ct=Ve.requests[at]=[],P.loadGlyphRange(hr,at,q.url,q.requestManager,function(Ot,Rt){if(Rt){for(var Bt in Rt)q._doesCharSupportLocalGlyph(+Bt)||(Ve.glyphs[+Bt]=Rt[+Bt]);Ve.ranges[at]=!0}for(var Dt=0,yt=Ct;Dt<yt.length;Dt+=1){var Pt=yt[Dt];Pt(Ot,Rt)}delete Ve.requests[at]})),Ct.push(function(Ot,Rt){Ot?Xt(Ot):Rt&&Xt(null,{stack:hr,id:qt,glyph:Rt[qt]||null})})},function(ft,Xt){if(ft)J(ft);else if(Xt){for(var hr={},qt=0,Ve=Xt;qt<Ve.length;qt+=1){var Qe=Ve[qt],at=Qe.stack,Ct=Qe.id,Ot=Qe.glyph;(hr[at]||(hr[at]={}))[Ct]=Ot&&{id:Ot.id,bitmap:Ot.bitmap.clone(),metrics:Ot.metrics}}J(null,hr)}})},P.prototype._doesCharSupportLocalGlyph=function(D){return!!this.localIdeographFontFamily&&(i.isChar[\"CJK Unified Ideographs\"](D)||i.isChar[\"Hangul Syllables\"](D)||i.isChar.Hiragana(D)||i.isChar.Katakana(D))},P.prototype._tinySDF=function(D,J,q){var K=this.localIdeographFontFamily;if(K&&this._doesCharSupportLocalGlyph(q)){var de=D.tinySDF;if(!de){var ne=\"400\";/bold/i.test(J)?ne=\"900\":/medium/i.test(J)?ne=\"500\":/light/i.test(J)&&(ne=\"200\"),de=D.tinySDF=new P.TinySDF(24,3,8,.25,K,ne)}return{id:q,bitmap:new i.AlphaImage({width:30,height:30},de.draw(String.fromCharCode(q))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},P.loadGlyphRange=E,P.TinySDF=S;var T=function(){this.specification=i.styleSpec.light.position};T.prototype.possiblyEvaluate=function(D,J){return i.sphericalToCartesian(D.expression.evaluate(J))},T.prototype.interpolate=function(D,J,q){return{x:i.number(D.x,J.x,q),y:i.number(D.y,J.y,q),z:i.number(D.z,J.z,q)}};var z=new i.Properties({anchor:new i.DataConstantProperty(i.styleSpec.light.anchor),position:new T,color:new i.DataConstantProperty(i.styleSpec.light.color),intensity:new i.DataConstantProperty(i.styleSpec.light.intensity)}),O=\"-transition\",V=function(Y){function D(J){Y.call(this),this._transitionable=new i.Transitionable(z),this.setLight(J),this._transitioning=this._transitionable.untransitioned()}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.getLight=function(){return this._transitionable.serialize()},D.prototype.setLight=function(q,K){if(K===void 0&&(K={}),!this._validate(i.validateLight,q,K))for(var de in q){var ne=q[de];i.endsWith(de,O)?this._transitionable.setTransition(de.slice(0,-O.length),ne):this._transitionable.setValue(de,ne)}},D.prototype.updateTransitions=function(q){this._transitioning=this._transitionable.transitioned(q,this._transitioning)},D.prototype.hasTransition=function(){return this._transitioning.hasTransition()},D.prototype.recalculate=function(q){this.properties=this._transitioning.possiblyEvaluate(q)},D.prototype._validate=function(q,K,de){return de&&de.validate===!1?!1:i.emitValidationErrors(this,q.call(i.validateStyle,i.extend({value:K,style:{glyphs:!0,sprite:!0},styleSpec:i.styleSpec})))},D}(i.Evented),G=function(D,J){this.width=D,this.height=J,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};G.prototype.getDash=function(D,J){var q=D.join(\",\")+String(J);return this.dashEntry[q]||(this.dashEntry[q]=this.addDash(D,J)),this.dashEntry[q]},G.prototype.getDashRanges=function(D,J,q){var K=D.length%2===1,de=[],ne=K?-D[D.length-1]*q:0,we=D[0]*q,Ue=!0;de.push({left:ne,right:we,isDash:Ue,zeroLength:D[0]===0});for(var ft=D[0],Xt=1;Xt<D.length;Xt++){Ue=!Ue;var hr=D[Xt];ne=ft*q,ft+=hr,we=ft*q,de.push({left:ne,right:we,isDash:Ue,zeroLength:hr===0})}return de},G.prototype.addRoundDash=function(D,J,q){for(var K=J/2,de=-q;de<=q;de++)for(var ne=this.nextRow+q+de,we=this.width*ne,Ue=0,ft=D[Ue],Xt=0;Xt<this.width;Xt++){Xt/ft.right>1&&(ft=D[++Ue]);var hr=Math.abs(Xt-ft.left),qt=Math.abs(Xt-ft.right),Ve=Math.min(hr,qt),Qe=void 0,at=de/q*(K+1);if(ft.isDash){var Ct=K-Math.abs(at);Qe=Math.sqrt(Ve*Ve+Ct*Ct)}else Qe=K-Math.sqrt(Ve*Ve+at*at);this.data[we+Xt]=Math.max(0,Math.min(255,Qe+128))}},G.prototype.addRegularDash=function(D){for(var J=D.length-1;J>=0;--J){var q=D[J],K=D[J+1];q.zeroLength?D.splice(J,1):K&&K.isDash===q.isDash&&(K.left=q.left,D.splice(J,1))}var de=D[0],ne=D[D.length-1];de.isDash===ne.isDash&&(de.left=ne.left-this.width,ne.right=de.right+this.width);for(var we=this.width*this.nextRow,Ue=0,ft=D[Ue],Xt=0;Xt<this.width;Xt++){Xt/ft.right>1&&(ft=D[++Ue]);var hr=Math.abs(Xt-ft.left),qt=Math.abs(Xt-ft.right),Ve=Math.min(hr,qt),Qe=ft.isDash?Ve:-Ve;this.data[we+Xt]=Math.max(0,Math.min(255,Qe+128))}},G.prototype.addDash=function(D,J){var q=J?7:0,K=2*q+1;if(this.nextRow+K>this.height)return i.warnOnce(\"LineAtlas out of space\"),null;for(var de=0,ne=0;ne<D.length;ne++)de+=D[ne];if(de!==0){var we=this.width/de,Ue=this.getDashRanges(D,this.width,we);J?this.addRoundDash(Ue,we,q):this.addRegularDash(Ue)}var ft={y:(this.nextRow+q+.5)/this.height,height:2*q/this.height,width:de};return this.nextRow+=K,this.dirty=!0,ft},G.prototype.bind=function(D){var J=D.gl;this.texture?(J.bindTexture(J.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,J.texSubImage2D(J.TEXTURE_2D,0,0,0,this.width,this.height,J.ALPHA,J.UNSIGNED_BYTE,this.data))):(this.texture=J.createTexture(),J.bindTexture(J.TEXTURE_2D,this.texture),J.texParameteri(J.TEXTURE_2D,J.TEXTURE_WRAP_S,J.REPEAT),J.texParameteri(J.TEXTURE_2D,J.TEXTURE_WRAP_T,J.REPEAT),J.texParameteri(J.TEXTURE_2D,J.TEXTURE_MIN_FILTER,J.LINEAR),J.texParameteri(J.TEXTURE_2D,J.TEXTURE_MAG_FILTER,J.LINEAR),J.texImage2D(J.TEXTURE_2D,0,J.ALPHA,this.width,this.height,0,J.ALPHA,J.UNSIGNED_BYTE,this.data))};var Z=function Y(D,J){this.workerPool=D,this.actors=[],this.currentActor=0,this.id=i.uniqueId();for(var q=this.workerPool.acquire(this.id),K=0;K<q.length;K++){var de=q[K],ne=new Y.Actor(de,J,this.id);ne.name=\"Worker \"+K,this.actors.push(ne)}};Z.prototype.broadcast=function(D,J,q){q=q||function(){},i.asyncAll(this.actors,function(K,de){K.send(D,J,de)},q)},Z.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},Z.prototype.remove=function(){this.actors.forEach(function(D){D.remove()}),this.actors=[],this.workerPool.release(this.id)},Z.Actor=i.Actor;function H(Y,D,J){var q=function(K,de){if(K)return J(K);if(de){var ne=i.pick(i.extend(de,Y),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);de.vector_layers&&(ne.vectorLayers=de.vector_layers,ne.vectorLayerIds=ne.vectorLayers.map(function(we){return we.id})),ne.tiles=D.canonicalizeTileset(ne,Y.url),J(null,ne)}};return Y.url?i.getJSON(D.transformRequest(D.normalizeSourceURL(Y.url),i.ResourceType.Source),q):i.browser.frame(function(){return q(null,Y)})}var N=function(D,J,q){this.bounds=i.LngLatBounds.convert(this.validateBounds(D)),this.minzoom=J||0,this.maxzoom=q||24};N.prototype.validateBounds=function(D){return!Array.isArray(D)||D.length!==4?[-180,-90,180,90]:[Math.max(-180,D[0]),Math.max(-90,D[1]),Math.min(180,D[2]),Math.min(90,D[3])]},N.prototype.contains=function(D){var J=Math.pow(2,D.z),q={minX:Math.floor(i.mercatorXfromLng(this.bounds.getWest())*J),minY:Math.floor(i.mercatorYfromLat(this.bounds.getNorth())*J),maxX:Math.ceil(i.mercatorXfromLng(this.bounds.getEast())*J),maxY:Math.ceil(i.mercatorYfromLat(this.bounds.getSouth())*J)},K=D.x>=q.minX&&D.x<q.maxX&&D.y>=q.minY&&D.y<q.maxY;return K};var j=function(Y){function D(J,q,K,de){if(Y.call(this),this.id=J,this.dispatcher=K,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,i.extend(this,i.pick(q,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=i.extend({type:\"vector\"},q),this._collectResourceTiming=q.collectResourceTiming,this.tileSize!==512)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(de)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){var q=this;this._loaded=!1,this.fire(new i.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=H(this._options,this.map._requestManager,function(K,de){q._tileJSONRequest=null,q._loaded=!0,K?q.fire(new i.ErrorEvent(K)):de&&(i.extend(q,de),de.bounds&&(q.tileBounds=new N(de.bounds,q.minzoom,q.maxzoom)),i.postTurnstileEvent(de.tiles,q.map._requestManager._customAccessToken),i.postMapLoadEvent(de.tiles,q.map._getMapId(),q.map._requestManager._skuToken,q.map._requestManager._customAccessToken),q.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),q.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},D.prototype.loaded=function(){return this._loaded},D.prototype.hasTile=function(q){return!this.tileBounds||this.tileBounds.contains(q.canonical)},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.setSourceProperty=function(q){this._tileJSONRequest&&this._tileJSONRequest.cancel(),q();var K=this.map.style.sourceCaches[this.id];K.clearTiles(),this.load()},D.prototype.setTiles=function(q){var K=this;return this.setSourceProperty(function(){K._options.tiles=q}),this},D.prototype.setUrl=function(q){var K=this;return this.setSourceProperty(function(){K.url=q,K._options.url=q}),this},D.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},D.prototype.serialize=function(){return i.extend({},this._options)},D.prototype.loadTile=function(q,K){var de=this.map._requestManager.normalizeTileURL(q.tileID.canonical.url(this.tiles,this.scheme)),ne={request:this.map._requestManager.transformRequest(de,i.ResourceType.Tile),uid:q.uid,tileID:q.tileID,zoom:q.tileID.overscaledZ,tileSize:this.tileSize*q.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:i.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};ne.request.collectResourceTiming=this._collectResourceTiming,!q.actor||q.state===\"expired\"?(q.actor=this.dispatcher.getActor(),q.request=q.actor.send(\"loadTile\",ne,we.bind(this))):q.state===\"loading\"?q.reloadCallback=K:q.request=q.actor.send(\"reloadTile\",ne,we.bind(this));function we(Ue,ft){if(delete q.request,q.aborted)return K(null);if(Ue&&Ue.status!==404)return K(Ue);ft&&ft.resourceTiming&&(q.resourceTiming=ft.resourceTiming),this.map._refreshExpiredTiles&&ft&&q.setExpiryData(ft),q.loadVectorData(ft,this.map.painter),i.cacheEntryPossiblyAdded(this.dispatcher),K(null),q.reloadCallback&&(this.loadTile(q,q.reloadCallback),q.reloadCallback=null)}},D.prototype.abortTile=function(q){q.request&&(q.request.cancel(),delete q.request),q.actor&&q.actor.send(\"abortTile\",{uid:q.uid,type:this.type,source:this.id},void 0)},D.prototype.unloadTile=function(q){q.unloadVectorData(),q.actor&&q.actor.send(\"removeTile\",{uid:q.uid,type:this.type,source:this.id},void 0)},D.prototype.hasTransition=function(){return!1},D}(i.Evented),re=function(Y){function D(J,q,K,de){Y.call(this),this.id=J,this.dispatcher=K,this.setEventedParent(de),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=i.extend({type:\"raster\"},q),i.extend(this,i.pick(q,[\"url\",\"scheme\",\"tileSize\"]))}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){var q=this;this._loaded=!1,this.fire(new i.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=H(this._options,this.map._requestManager,function(K,de){q._tileJSONRequest=null,q._loaded=!0,K?q.fire(new i.ErrorEvent(K)):de&&(i.extend(q,de),de.bounds&&(q.tileBounds=new N(de.bounds,q.minzoom,q.maxzoom)),i.postTurnstileEvent(de.tiles),i.postMapLoadEvent(de.tiles,q.map._getMapId(),q.map._requestManager._skuToken),q.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),q.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},D.prototype.loaded=function(){return this._loaded},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},D.prototype.serialize=function(){return i.extend({},this._options)},D.prototype.hasTile=function(q){return!this.tileBounds||this.tileBounds.contains(q.canonical)},D.prototype.loadTile=function(q,K){var de=this,ne=this.map._requestManager.normalizeTileURL(q.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);q.request=i.getImage(this.map._requestManager.transformRequest(ne,i.ResourceType.Tile),function(we,Ue){if(delete q.request,q.aborted)q.state=\"unloaded\",K(null);else if(we)q.state=\"errored\",K(we);else if(Ue){de.map._refreshExpiredTiles&&q.setExpiryData(Ue),delete Ue.cacheControl,delete Ue.expires;var ft=de.map.painter.context,Xt=ft.gl;q.texture=de.map.painter.getTileTexture(Ue.width),q.texture?q.texture.update(Ue,{useMipmap:!0}):(q.texture=new i.Texture(ft,Ue,Xt.RGBA,{useMipmap:!0}),q.texture.bind(Xt.LINEAR,Xt.CLAMP_TO_EDGE,Xt.LINEAR_MIPMAP_NEAREST),ft.extTextureFilterAnisotropic&&Xt.texParameterf(Xt.TEXTURE_2D,ft.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,ft.extTextureFilterAnisotropicMax)),q.state=\"loaded\",i.cacheEntryPossiblyAdded(de.dispatcher),K(null)}})},D.prototype.abortTile=function(q,K){q.request&&(q.request.cancel(),delete q.request),K()},D.prototype.unloadTile=function(q,K){q.texture&&this.map.painter.saveTileTexture(q.texture),K()},D.prototype.hasTransition=function(){return!1},D}(i.Evented),oe=function(Y){function D(J,q,K,de){Y.call(this,J,q,K,de),this.type=\"raster-dem\",this.maxzoom=22,this._options=i.extend({type:\"raster-dem\"},q),this.encoding=q.encoding||\"mapbox\"}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},D.prototype.loadTile=function(q,K){var de=this.map._requestManager.normalizeTileURL(q.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);q.request=i.getImage(this.map._requestManager.transformRequest(de,i.ResourceType.Tile),ne.bind(this)),q.neighboringTiles=this._getNeighboringTiles(q.tileID);function ne(Ue,ft){if(delete q.request,q.aborted)q.state=\"unloaded\",K(null);else if(Ue)q.state=\"errored\",K(Ue);else if(ft){this.map._refreshExpiredTiles&&q.setExpiryData(ft),delete ft.cacheControl,delete ft.expires;var Xt=i.window.ImageBitmap&&ft instanceof i.window.ImageBitmap&&i.offscreenCanvasSupported(),hr=Xt?ft:i.browser.getImageData(ft,1),qt={uid:q.uid,coord:q.tileID,source:this.id,rawImageData:hr,encoding:this.encoding};(!q.actor||q.state===\"expired\")&&(q.actor=this.dispatcher.getActor(),q.actor.send(\"loadDEMTile\",qt,we.bind(this)))}}function we(Ue,ft){Ue&&(q.state=\"errored\",K(Ue)),ft&&(q.dem=ft,q.needsHillshadePrepare=!0,q.state=\"loaded\",K(null))}},D.prototype._getNeighboringTiles=function(q){var K=q.canonical,de=Math.pow(2,K.z),ne=(K.x-1+de)%de,we=K.x===0?q.wrap-1:q.wrap,Ue=(K.x+1+de)%de,ft=K.x+1===de?q.wrap+1:q.wrap,Xt={};return Xt[new i.OverscaledTileID(q.overscaledZ,we,K.z,ne,K.y).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,ft,K.z,Ue,K.y).key]={backfilled:!1},K.y>0&&(Xt[new i.OverscaledTileID(q.overscaledZ,we,K.z,ne,K.y-1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,q.wrap,K.z,K.x,K.y-1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,ft,K.z,Ue,K.y-1).key]={backfilled:!1}),K.y+1<de&&(Xt[new i.OverscaledTileID(q.overscaledZ,we,K.z,ne,K.y+1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,q.wrap,K.z,K.x,K.y+1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,ft,K.z,Ue,K.y+1).key]={backfilled:!1}),Xt},D.prototype.unloadTile=function(q){q.demTexture&&this.map.painter.saveTileTexture(q.demTexture),q.fbo&&(q.fbo.destroy(),delete q.fbo),q.dem&&delete q.dem,delete q.neighboringTiles,q.state=\"unloaded\",q.actor&&q.actor.send(\"removeDEMTile\",{uid:q.uid,source:this.id})},D}(re),_e=function(Y){function D(J,q,K,de){Y.call(this),this.id=J,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=K.getActor(),this.setEventedParent(de),this._data=q.data,this._options=i.extend({},q),this._collectResourceTiming=q.collectResourceTiming,this._resourceTiming=[],q.maxzoom!==void 0&&(this.maxzoom=q.maxzoom),q.type&&(this.type=q.type),q.attribution&&(this.attribution=q.attribution),this.promoteId=q.promoteId;var ne=i.EXTENT/this.tileSize;this.workerOptions=i.extend({source:this.id,cluster:q.cluster||!1,geojsonVtOptions:{buffer:(q.buffer!==void 0?q.buffer:128)*ne,tolerance:(q.tolerance!==void 0?q.tolerance:.375)*ne,extent:i.EXTENT,maxZoom:this.maxzoom,lineMetrics:q.lineMetrics||!1,generateId:q.generateId||!1},superclusterOptions:{maxZoom:q.clusterMaxZoom!==void 0?Math.min(q.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,minPoints:Math.max(2,q.clusterMinPoints||2),extent:i.EXTENT,radius:(q.clusterRadius||50)*ne,log:!1,generateId:q.generateId||!1},clusterProperties:q.clusterProperties,filter:q.filter},q.workerOptions)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){var q=this;this.fire(new i.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(K){if(K){q.fire(new i.ErrorEvent(K));return}var de={dataType:\"source\",sourceDataType:\"metadata\"};q._collectResourceTiming&&q._resourceTiming&&q._resourceTiming.length>0&&(de.resourceTiming=q._resourceTiming,q._resourceTiming=[]),q.fire(new i.Event(\"data\",de))})},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.setData=function(q){var K=this;return this._data=q,this.fire(new i.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(de){if(de){K.fire(new i.ErrorEvent(de));return}var ne={dataType:\"source\",sourceDataType:\"content\"};K._collectResourceTiming&&K._resourceTiming&&K._resourceTiming.length>0&&(ne.resourceTiming=K._resourceTiming,K._resourceTiming=[]),K.fire(new i.Event(\"data\",ne))}),this},D.prototype.getClusterExpansionZoom=function(q,K){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:q,source:this.id},K),this},D.prototype.getClusterChildren=function(q,K){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:q,source:this.id},K),this},D.prototype.getClusterLeaves=function(q,K,de,ne){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:q,limit:K,offset:de},ne),this},D.prototype._updateWorkerData=function(q){var K=this;this._loaded=!1;var de=i.extend({},this.workerOptions),ne=this._data;typeof ne==\"string\"?(de.request=this.map._requestManager.transformRequest(i.browser.resolveURL(ne),i.ResourceType.Source),de.request.collectResourceTiming=this._collectResourceTiming):de.data=JSON.stringify(ne),this.actor.send(this.type+\".loadData\",de,function(we,Ue){K._removed||Ue&&Ue.abandoned||(K._loaded=!0,Ue&&Ue.resourceTiming&&Ue.resourceTiming[K.id]&&(K._resourceTiming=Ue.resourceTiming[K.id].slice(0)),K.actor.send(K.type+\".coalesce\",{source:de.source},null),q(we))})},D.prototype.loaded=function(){return this._loaded},D.prototype.loadTile=function(q,K){var de=this,ne=q.actor?\"reloadTile\":\"loadTile\";q.actor=this.actor;var we={type:this.type,uid:q.uid,tileID:q.tileID,zoom:q.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:i.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};q.request=this.actor.send(ne,we,function(Ue,ft){return delete q.request,q.unloadVectorData(),q.aborted?K(null):Ue?K(Ue):(q.loadVectorData(ft,de.map.painter,ne===\"reloadTile\"),K(null))})},D.prototype.abortTile=function(q){q.request&&(q.request.cancel(),delete q.request),q.aborted=!0},D.prototype.unloadTile=function(q){q.unloadVectorData(),this.actor.send(\"removeTile\",{uid:q.uid,type:this.type,source:this.id})},D.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},D.prototype.serialize=function(){return i.extend({},this._options,{type:this.type,data:this._data})},D.prototype.hasTransition=function(){return!1},D}(i.Evented),Ee=i.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),Ce=function(Y){function D(J,q,K,de){Y.call(this),this.id=J,this.dispatcher=K,this.coordinates=q.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(de),this.options=q}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(q,K){var de=this;this._loaded=!1,this.fire(new i.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,i.getImage(this.map._requestManager.transformRequest(this.url,i.ResourceType.Image),function(ne,we){de._loaded=!0,ne?de.fire(new i.ErrorEvent(ne)):we&&(de.image=we,q&&(de.coordinates=q),K&&K(),de._finishLoading())})},D.prototype.loaded=function(){return this._loaded},D.prototype.updateImage=function(q){var K=this;return!this.image||!q.url?this:(this.options.url=q.url,this.load(q.coordinates,function(){K.texture=null}),this)},D.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.setCoordinates=function(q){var K=this;this.coordinates=q;var de=q.map(i.MercatorCoordinate.fromLngLat);this.tileID=me(de),this.minzoom=this.maxzoom=this.tileID.z;var ne=de.map(function(we){return K.tileID.getTilePoint(we)._round()});return this._boundsArray=new i.StructArrayLayout4i8,this._boundsArray.emplaceBack(ne[0].x,ne[0].y,0,0),this._boundsArray.emplaceBack(ne[1].x,ne[1].y,i.EXTENT,0),this._boundsArray.emplaceBack(ne[3].x,ne[3].y,0,i.EXTENT),this._boundsArray.emplaceBack(ne[2].x,ne[2].y,i.EXTENT,i.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new i.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},D.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||!this.image)){var q=this.map.painter.context,K=q.gl;this.boundsBuffer||(this.boundsBuffer=q.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new i.Texture(q,this.image,K.RGBA),this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE));for(var de in this.tiles){var ne=this.tiles[de];ne.state!==\"loaded\"&&(ne.state=\"loaded\",ne.texture=this.texture)}}},D.prototype.loadTile=function(q,K){this.tileID&&this.tileID.equals(q.tileID.canonical)?(this.tiles[String(q.tileID.wrap)]=q,q.buckets={},K(null)):(q.state=\"errored\",K(null))},D.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},D.prototype.hasTransition=function(){return!1},D}(i.Evented);function me(Y){for(var D=1/0,J=1/0,q=-1/0,K=-1/0,de=0,ne=Y;de<ne.length;de+=1){var we=ne[de];D=Math.min(D,we.x),J=Math.min(J,we.y),q=Math.max(q,we.x),K=Math.max(K,we.y)}var Ue=q-D,ft=K-J,Xt=Math.max(Ue,ft),hr=Math.max(0,Math.floor(-Math.log(Xt)/Math.LN2)),qt=Math.pow(2,hr);return new i.CanonicalTileID(hr,Math.floor((D+q)/2*qt),Math.floor((J+K)/2*qt))}var ie=function(Y){function D(J,q,K,de){Y.call(this,J,q,K,de),this.roundZoom=!0,this.type=\"video\",this.options=q}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){var q=this;this._loaded=!1;var K=this.options;this.urls=[];for(var de=0,ne=K.urls;de<ne.length;de+=1){var we=ne[de];this.urls.push(this.map._requestManager.transformRequest(we,i.ResourceType.Source).url)}i.getVideo(this.urls,function(Ue,ft){q._loaded=!0,Ue?q.fire(new i.ErrorEvent(Ue)):ft&&(q.video=ft,q.video.loop=!0,q.video.addEventListener(\"playing\",function(){q.map.triggerRepaint()}),q.map&&q.video.play(),q._finishLoading())})},D.prototype.pause=function(){this.video&&this.video.pause()},D.prototype.play=function(){this.video&&this.video.play()},D.prototype.seek=function(q){if(this.video){var K=this.video.seekable;q<K.start(0)||q>K.end(0)?this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+K.start(0)+\" and \"+K.end(0)+\"-second mark.\"))):this.video.currentTime=q}},D.prototype.getVideo=function(){return this.video},D.prototype.onAdd=function(q){this.map||(this.map=q,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},D.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||this.video.readyState<2)){var q=this.map.painter.context,K=q.gl;this.boundsBuffer||(this.boundsBuffer=q.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE),K.texSubImage2D(K.TEXTURE_2D,0,0,0,K.RGBA,K.UNSIGNED_BYTE,this.video)):(this.texture=new i.Texture(q,this.video,K.RGBA),this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE));for(var de in this.tiles){var ne=this.tiles[de];ne.state!==\"loaded\"&&(ne.state=\"loaded\",ne.texture=this.texture)}}},D.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},D.prototype.hasTransition=function(){return this.video&&!this.video.paused},D}(Ce),Se=function(Y){function D(J,q,K,de){Y.call(this,J,q,K,de),q.coordinates?(!Array.isArray(q.coordinates)||q.coordinates.length!==4||q.coordinates.some(function(ne){return!Array.isArray(ne)||ne.length!==2||ne.some(function(we){return typeof we!=\"number\"})}))&&this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+J,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+J,null,'missing required property \"coordinates\"'))),q.animate&&typeof q.animate!=\"boolean\"&&this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+J,null,'optional \"animate\" property must be a boolean value'))),q.canvas?typeof q.canvas!=\"string\"&&!(q.canvas instanceof i.window.HTMLCanvasElement)&&this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+J,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new i.ErrorEvent(new i.ValidationError(\"sources.\"+J,null,'missing required property \"canvas\"'))),this.options=q,this.animate=q.animate!==void 0?q.animate:!0}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){if(this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof i.window.HTMLCanvasElement?this.options.canvas:i.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()){this.fire(new i.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\")));return}this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading()},D.prototype.getCanvas=function(){return this.canvas},D.prototype.onAdd=function(q){this.map=q,this.load(),this.canvas&&this.animate&&this.play()},D.prototype.onRemove=function(){this.pause()},D.prototype.prepare=function(){var q=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,q=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,q=!0),!this._hasInvalidDimensions()&&Object.keys(this.tiles).length!==0){var K=this.map.painter.context,de=K.gl;this.boundsBuffer||(this.boundsBuffer=K.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(q||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new i.Texture(K,this.canvas,de.RGBA,{premultiply:!0});for(var ne in this.tiles){var we=this.tiles[ne];we.state!==\"loaded\"&&(we.state=\"loaded\",we.texture=this.texture)}}},D.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},D.prototype.hasTransition=function(){return this._playing},D.prototype._hasInvalidDimensions=function(){for(var q=0,K=[this.canvas.width,this.canvas.height];q<K.length;q+=1){var de=K[q];if(isNaN(de)||de<=0)return!0}return!1},D}(Ce),Le={vector:j,raster:re,\"raster-dem\":oe,geojson:_e,video:ie,image:Ce,canvas:Se},Ae=function(Y,D,J,q){var K=new Le[D.type](Y,D,J,q);if(K.id!==Y)throw new Error(\"Expected Source id to be \"+Y+\" instead of \"+K.id);return i.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],K),K},Fe=function(Y){return Le[Y]},Pe=function(Y,D){Le[Y]=D};function ge(Y,D){var J=i.identity([]);return i.translate(J,J,[1,1,0]),i.scale(J,J,[Y.width*.5,Y.height*.5,1]),i.multiply(J,J,Y.calculatePosMatrix(D.toUnwrapped()))}function Re(Y,D,J){if(Y)for(var q=0,K=Y;q<K.length;q+=1){var de=K[q],ne=D[de];if(ne&&ne.source===J&&ne.type===\"fill-extrusion\")return!0}else for(var we in D){var Ue=D[we];if(Ue.source===J&&Ue.type===\"fill-extrusion\")return!0}return!1}function ce(Y,D,J,q,K,de){var ne=Re(K&&K.layers,D,Y.id),we=de.maxPitchScaleFactor(),Ue=Y.tilesIn(q,we,ne);Ue.sort(pt);for(var ft=[],Xt=0,hr=Ue;Xt<hr.length;Xt+=1){var qt=hr[Xt];ft.push({wrappedTileID:qt.tileID.wrapped().key,queryResults:qt.tile.queryRenderedFeatures(D,J,Y._state,qt.queryGeometry,qt.cameraQueryGeometry,qt.scale,K,de,we,ge(Y.transform,qt.tileID))})}var Ve=Zt(ft);for(var Qe in Ve)Ve[Qe].forEach(function(at){var Ct=at.feature,Ot=Y.getFeatureState(Ct.layer[\"source-layer\"],Ct.id);Ct.source=Ct.layer.source,Ct.layer[\"source-layer\"]&&(Ct.sourceLayer=Ct.layer[\"source-layer\"]),Ct.state=Ot});return Ve}function Ze(Y,D,J,q,K,de,ne){for(var we={},Ue=de.queryRenderedSymbols(q),ft=[],Xt=0,hr=Object.keys(Ue).map(Number);Xt<hr.length;Xt+=1){var qt=hr[Xt];ft.push(ne[qt])}ft.sort(pt);for(var Ve=function(){var Rt=at[Qe],Bt=Rt.featureIndex.lookupSymbolFeatures(Ue[Rt.bucketInstanceId],D,Rt.bucketIndex,Rt.sourceLayerIndex,K.filter,K.layers,K.availableImages,Y);for(var Dt in Bt){var yt=we[Dt]=we[Dt]||[],Pt=Bt[Dt];Pt.sort(function(Ur,Di){var fi=Rt.featureSortOrder;if(fi){var Ti=fi.indexOf(Ur.featureIndex),gn=fi.indexOf(Di.featureIndex);return gn-Ti}else return Di.featureIndex-Ur.featureIndex});for(var ht=0,ur=Pt;ht<ur.length;ht+=1){var br=ur[ht];yt.push(br)}}},Qe=0,at=ft;Qe<at.length;Qe+=1)Ve();var Ct=function(Rt){we[Rt].forEach(function(Bt){var Dt=Bt.feature,yt=Y[Rt],Pt=J[yt.source],ht=Pt.getFeatureState(Dt.layer[\"source-layer\"],Dt.id);Dt.source=Dt.layer.source,Dt.layer[\"source-layer\"]&&(Dt.sourceLayer=Dt.layer[\"source-layer\"]),Dt.state=ht})};for(var Ot in we)Ct(Ot);return we}function ut(Y,D){for(var J=Y.getRenderableIds().map(function(Ue){return Y.getTileByID(Ue)}),q=[],K={},de=0;de<J.length;de++){var ne=J[de],we=ne.tileID.canonical.key;K[we]||(K[we]=!0,ne.querySourceFeatures(q,D))}return q}function pt(Y,D){var J=Y.tileID,q=D.tileID;return J.overscaledZ-q.overscaledZ||J.canonical.y-q.canonical.y||J.wrap-q.wrap||J.canonical.x-q.canonical.x}function Zt(Y){for(var D={},J={},q=0,K=Y;q<K.length;q+=1){var de=K[q],ne=de.queryResults,we=de.wrappedTileID,Ue=J[we]=J[we]||{};for(var ft in ne)for(var Xt=ne[ft],hr=Ue[ft]=Ue[ft]||{},qt=D[ft]=D[ft]||[],Ve=0,Qe=Xt;Ve<Qe.length;Ve+=1){var at=Qe[Ve];hr[at.featureIndex]||(hr[at.featureIndex]=!0,qt.push(at))}}return D}var st=function(D,J){this.max=D,this.onRemove=J,this.reset()};st.prototype.reset=function(){for(var D in this.data)for(var J=0,q=this.data[D];J<q.length;J+=1){var K=q[J];K.timeout&&clearTimeout(K.timeout),this.onRemove(K.value)}return this.data={},this.order=[],this},st.prototype.add=function(D,J,q){var K=this,de=D.wrapped().key;this.data[de]===void 0&&(this.data[de]=[]);var ne={value:J,timeout:void 0};if(q!==void 0&&(ne.timeout=setTimeout(function(){K.remove(D,ne)},q)),this.data[de].push(ne),this.order.push(de),this.order.length>this.max){var we=this._getAndRemoveByKey(this.order[0]);we&&this.onRemove(we)}return this},st.prototype.has=function(D){return D.wrapped().key in this.data},st.prototype.getAndRemove=function(D){return this.has(D)?this._getAndRemoveByKey(D.wrapped().key):null},st.prototype._getAndRemoveByKey=function(D){var J=this.data[D].shift();return J.timeout&&clearTimeout(J.timeout),this.data[D].length===0&&delete this.data[D],this.order.splice(this.order.indexOf(D),1),J.value},st.prototype.getByKey=function(D){var J=this.data[D];return J?J[0].value:null},st.prototype.get=function(D){if(!this.has(D))return null;var J=this.data[D.wrapped().key][0];return J.value},st.prototype.remove=function(D,J){if(!this.has(D))return this;var q=D.wrapped().key,K=J===void 0?0:this.data[q].indexOf(J),de=this.data[q][K];return this.data[q].splice(K,1),de.timeout&&clearTimeout(de.timeout),this.data[q].length===0&&delete this.data[q],this.onRemove(de.value),this.order.splice(this.order.indexOf(q),1),this},st.prototype.setMaxSize=function(D){for(this.max=D;this.order.length>this.max;){var J=this._getAndRemoveByKey(this.order[0]);J&&this.onRemove(J)}return this},st.prototype.filter=function(D){var J=[];for(var q in this.data)for(var K=0,de=this.data[q];K<de.length;K+=1){var ne=de[K];D(ne.value)||J.push(ne)}for(var we=0,Ue=J;we<Ue.length;we+=1){var ft=Ue[we];this.remove(ft.value.tileID,ft)}};var lt=function(D,J,q){this.context=D;var K=D.gl;this.buffer=K.createBuffer(),this.dynamicDraw=!!q,this.context.unbindVAO(),D.bindElementBuffer.set(this.buffer),K.bufferData(K.ELEMENT_ARRAY_BUFFER,J.arrayBuffer,this.dynamicDraw?K.DYNAMIC_DRAW:K.STATIC_DRAW),this.dynamicDraw||delete J.arrayBuffer};lt.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},lt.prototype.updateData=function(D){var J=this.context.gl;this.context.unbindVAO(),this.bind(),J.bufferSubData(J.ELEMENT_ARRAY_BUFFER,0,D.arrayBuffer)},lt.prototype.destroy=function(){var D=this.context.gl;this.buffer&&(D.deleteBuffer(this.buffer),delete this.buffer)};var 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ii(this),this.extTextureFilterAnisotropic=D.getExtension(\"EXT_texture_filter_anisotropic\")||D.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||D.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=D.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=D.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(D.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=D.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=D.getExtension(\"EXT_disjoint_timer_query\"),this.maxTextureSize=D.getParameter(D.MAX_TEXTURE_SIZE)};Xr.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Xr.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Xr.prototype.createIndexBuffer=function(D,J){return new lt(this,D,J)},Xr.prototype.createVertexBuffer=function(D,J,q){return new Nt(this,D,J,q)},Xr.prototype.createRenderbuffer=function(D,J,q){var K=this.gl,de=K.createRenderbuffer();return this.bindRenderbuffer.set(de),K.renderbufferStorage(K.RENDERBUFFER,D,J,q),this.bindRenderbuffer.set(null),de},Xr.prototype.createFramebuffer=function(D,J,q){return new ji(this,D,J,q)},Xr.prototype.clear=function(D){var J=D.color,q=D.depth,K=this.gl,de=0;J&&(de|=K.COLOR_BUFFER_BIT,this.clearColor.set(J),this.colorMask.set([!0,!0,!0,!0])),typeof q!=\"undefined\"&&(de|=K.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(q),this.depthMask.set(!0)),K.clear(de)},Xr.prototype.setCullFace=function(D){D.enable===!1?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(D.mode),this.frontFace.set(D.frontFace))},Xr.prototype.setDepthMode=function(D){D.func===this.gl.ALWAYS&&!D.mask?this.depthTest.set(!1):(this.depthTest.set(!0),this.depthFunc.set(D.func),this.depthMask.set(D.mask),this.depthRange.set(D.range))},Xr.prototype.setStencilMode=function(D){D.test.func===this.gl.ALWAYS&&!D.mask?this.stencilTest.set(!1):(this.stencilTest.set(!0),this.stencilMask.set(D.mask),this.stencilOp.set([D.fail,D.depthFail,D.pass]),this.stencilFunc.set({func:D.test.func,ref:D.ref,mask:D.test.mask}))},Xr.prototype.setColorMode=function(D){i.deepEqual(D.blendFunction,wt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(D.blendFunction),this.blendColor.set(D.blendColor)),this.colorMask.set(D.mask)},Xr.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var ri=function(Y){function D(J,q,K){var de=this;Y.call(this),this.id=J,this.dispatcher=K,this.on(\"data\",function(ne){ne.dataType===\"source\"&&ne.sourceDataType===\"metadata\"&&(de._sourceLoaded=!0),de._sourceLoaded&&!de._paused&&ne.dataType===\"source\"&&ne.sourceDataType===\"content\"&&(de.reload(),de.transform&&de.update(de.transform))}),this.on(\"error\",function(){de._sourceErrored=!0}),this._source=Ae(J,q,K,this),this._tiles={},this._cache=new st(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new i.SourceFeatureState}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.onAdd=function(q){this.map=q,this._maxTileCacheSize=q?q._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(q)},D.prototype.onRemove=function(q){this._source&&this._source.onRemove&&this._source.onRemove(q)},D.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded||!this._source.loaded())return!1;for(var q in this._tiles){var K=this._tiles[q];if(K.state!==\"loaded\"&&K.state!==\"errored\")return!1}return!0},D.prototype.getSource=function(){return this._source},D.prototype.pause=function(){this._paused=!0},D.prototype.resume=function(){if(this._paused){var q=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,q&&this.reload(),this.transform&&this.update(this.transform)}},D.prototype._loadTile=function(q,K){return this._source.loadTile(q,K)},D.prototype._unloadTile=function(q){if(this._source.unloadTile)return this._source.unloadTile(q,function(){})},D.prototype._abortTile=function(q){if(this._source.abortTile)return this._source.abortTile(q,function(){})},D.prototype.serialize=function(){return this._source.serialize()},D.prototype.prepare=function(q){this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null);for(var K in this._tiles){var de=this._tiles[K];de.upload(q),de.prepare(this.map.style.imageManager)}},D.prototype.getIds=function(){return i.values(this._tiles).map(function(q){return q.tileID}).sort(Qr).map(function(q){return q.key})},D.prototype.getRenderableIds=function(q){var K=this,de=[];for(var ne in this._tiles)this._isIdRenderable(ne,q)&&de.push(this._tiles[ne]);return q?de.sort(function(we,Ue){var ft=we.tileID,Xt=Ue.tileID,hr=new i.Point(ft.canonical.x,ft.canonical.y)._rotate(K.transform.angle),qt=new i.Point(Xt.canonical.x,Xt.canonical.y)._rotate(K.transform.angle);return ft.overscaledZ-Xt.overscaledZ||qt.y-hr.y||qt.x-hr.x}).map(function(we){return we.tileID.key}):de.map(function(we){return we.tileID}).sort(Qr).map(function(we){return we.key})},D.prototype.hasRenderableParent=function(q){var K=this.findLoadedParent(q,0);return K?this._isIdRenderable(K.tileID.key):!1},D.prototype._isIdRenderable=function(q,K){return this._tiles[q]&&this._tiles[q].hasData()&&!this._coveredTiles[q]&&(K||!this._tiles[q].holdingForFade())},D.prototype.reload=function(){if(this._paused){this._shouldReloadOnResume=!0;return}this._cache.reset();for(var q in this._tiles)this._tiles[q].state!==\"errored\"&&this._reloadTile(q,\"reloading\")},D.prototype._reloadTile=function(q,K){var de=this._tiles[q];de&&(de.state!==\"loading\"&&(de.state=K),this._loadTile(de,this._tileLoaded.bind(this,de,q,K)))},D.prototype._tileLoaded=function(q,K,de,ne){if(ne){q.state=\"errored\",ne.status!==404?this._source.fire(new i.ErrorEvent(ne,{tile:q})):this.update(this.transform);return}q.timeAdded=i.browser.now(),de===\"expired\"&&(q.refreshedUponExpiration=!0),this._setTileReloadTimer(K,q),this.getSource().type===\"raster-dem\"&&q.dem&&this._backfillDEM(q),this._state.initializeTileState(q,this.map?this.map.painter:null),this._source.fire(new i.Event(\"data\",{dataType:\"source\",tile:q,coord:q.tileID}))},D.prototype._backfillDEM=function(q){for(var K=this.getRenderableIds(),de=0;de<K.length;de++){var ne=K[de];if(q.neighboringTiles&&q.neighboringTiles[ne]){var we=this.getTileByID(ne);Ue(q,we),Ue(we,q)}}function Ue(ft,Xt){ft.needsHillshadePrepare=!0;var hr=Xt.tileID.canonical.x-ft.tileID.canonical.x,qt=Xt.tileID.canonical.y-ft.tileID.canonical.y,Ve=Math.pow(2,ft.tileID.canonical.z),Qe=Xt.tileID.key;hr===0&&qt===0||Math.abs(qt)>1||(Math.abs(hr)>1&&(Math.abs(hr+Ve)===1?hr+=Ve:Math.abs(hr-Ve)===1&&(hr-=Ve)),!(!Xt.dem||!ft.dem)&&(ft.dem.backfillBorder(Xt.dem,hr,qt),ft.neighboringTiles&&ft.neighboringTiles[Qe]&&(ft.neighboringTiles[Qe].backfilled=!0)))}},D.prototype.getTile=function(q){return this.getTileByID(q.key)},D.prototype.getTileByID=function(q){return this._tiles[q]},D.prototype._retainLoadedChildren=function(q,K,de,ne){for(var we in this._tiles){var Ue=this._tiles[we];if(!(ne[we]||!Ue.hasData()||Ue.tileID.overscaledZ<=K||Ue.tileID.overscaledZ>de)){for(var ft=Ue.tileID;Ue&&Ue.tileID.overscaledZ>K+1;){var Xt=Ue.tileID.scaledTo(Ue.tileID.overscaledZ-1);Ue=this._tiles[Xt.key],Ue&&Ue.hasData()&&(ft=Xt)}for(var hr=ft;hr.overscaledZ>K;)if(hr=hr.scaledTo(hr.overscaledZ-1),q[hr.key]){ne[ft.key]=ft;break}}}},D.prototype.findLoadedParent=function(q,K){if(q.key in this._loadedParentTiles){var de=this._loadedParentTiles[q.key];return de&&de.tileID.overscaledZ>=K?de:null}for(var ne=q.overscaledZ-1;ne>=K;ne--){var we=q.scaledTo(ne),Ue=this._getLoadedTile(we);if(Ue)return Ue}},D.prototype._getLoadedTile=function(q){var K=this._tiles[q.key];if(K&&K.hasData())return K;var de=this._cache.getByKey(q.wrapped().key);return de},D.prototype.updateCacheSize=function(q){var K=Math.ceil(q.width/this._source.tileSize)+1,de=Math.ceil(q.height/this._source.tileSize)+1,ne=K*de,we=5,Ue=Math.floor(ne*we),ft=typeof this._maxTileCacheSize==\"number\"?Math.min(this._maxTileCacheSize,Ue):Ue;this._cache.setMaxSize(ft)},D.prototype.handleWrapJump=function(q){var K=this._prevLng===void 0?q:this._prevLng,de=q-K,ne=de/360,we=Math.round(ne);if(this._prevLng=q,we){var Ue={};for(var ft in this._tiles){var Xt=this._tiles[ft];Xt.tileID=Xt.tileID.unwrapTo(Xt.tileID.wrap+we),Ue[Xt.tileID.key]=Xt}this._tiles=Ue;for(var hr in this._timers)clearTimeout(this._timers[hr]),delete this._timers[hr];for(var qt in this._tiles){var Ve=this._tiles[qt];this._setTileReloadTimer(qt,Ve)}}},D.prototype.update=function(q){var K=this;if(this.transform=q,!(!this._sourceLoaded||this._paused)){this.updateCacheSize(q),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={};var de;this.used?this._source.tileID?de=q.getVisibleUnwrappedCoordinates(this._source.tileID).map(function(Ur){return new i.OverscaledTileID(Ur.canonical.z,Ur.wrap,Ur.canonical.z,Ur.canonical.x,Ur.canonical.y)}):(de=q.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(de=de.filter(function(Ur){return K._source.hasTile(Ur)}))):de=[];var ne=q.coveringZoomLevel(this._source),we=Math.max(ne-D.maxOverzooming,this._source.minzoom),Ue=Math.max(ne+D.maxUnderzooming,this._source.minzoom),ft=this._updateRetainedTiles(de,ne);if(Oi(this._source.type)){for(var Xt={},hr={},qt=Object.keys(ft),Ve=0,Qe=qt;Ve<Qe.length;Ve+=1){var at=Qe[Ve],Ct=ft[at],Ot=this._tiles[at];if(!(!Ot||Ot.fadeEndTime&&Ot.fadeEndTime<=i.browser.now())){var Rt=this.findLoadedParent(Ct,we);Rt&&(this._addTile(Rt.tileID),Xt[Rt.tileID.key]=Rt.tileID),hr[at]=Ct}}this._retainLoadedChildren(hr,ne,Ue,ft);for(var Bt in Xt)ft[Bt]||(this._coveredTiles[Bt]=!0,ft[Bt]=Xt[Bt])}for(var Dt in ft)this._tiles[Dt].clearFadeHold();for(var yt=i.keysDifference(this._tiles,ft),Pt=0,ht=yt;Pt<ht.length;Pt+=1){var ur=ht[Pt],br=this._tiles[ur];br.hasSymbolBuckets&&!br.holdingForFade()?br.setHoldDuration(this.map._fadeDuration):(!br.hasSymbolBuckets||br.symbolFadeFinished())&&this._removeTile(ur)}this._updateLoadedParentTileCache()}},D.prototype.releaseSymbolFadeTiles=function(){for(var q in this._tiles)this._tiles[q].holdingForFade()&&this._removeTile(q)},D.prototype._updateRetainedTiles=function(q,K){for(var de={},ne={},we=Math.max(K-D.maxOverzooming,this._source.minzoom),Ue=Math.max(K+D.maxUnderzooming,this._source.minzoom),ft={},Xt=0,hr=q;Xt<hr.length;Xt+=1){var qt=hr[Xt],Ve=this._addTile(qt);de[qt.key]=qt,!Ve.hasData()&&K<this._source.maxzoom&&(ft[qt.key]=qt)}this._retainLoadedChildren(ft,K,Ue,de);for(var Qe=0,at=q;Qe<at.length;Qe+=1){var Ct=at[Qe],Ot=this._tiles[Ct.key];if(!Ot.hasData()){if(K+1>this._source.maxzoom){var Rt=Ct.children(this._source.maxzoom)[0],Bt=this.getTile(Rt);if(Bt&&Bt.hasData()){de[Rt.key]=Rt;continue}}else{var Dt=Ct.children(this._source.maxzoom);if(de[Dt[0].key]&&de[Dt[1].key]&&de[Dt[2].key]&&de[Dt[3].key])continue}for(var yt=Ot.wasRequested(),Pt=Ct.overscaledZ-1;Pt>=we;--Pt){var ht=Ct.scaledTo(Pt);if(ne[ht.key]||(ne[ht.key]=!0,Ot=this.getTile(ht),!Ot&&yt&&(Ot=this._addTile(ht)),Ot&&(de[ht.key]=ht,yt=Ot.wasRequested(),Ot.hasData())))break}}}return de},D.prototype._updateLoadedParentTileCache=function(){this._loadedParentTiles={};for(var q in this._tiles){for(var K=[],de=void 0,ne=this._tiles[q].tileID;ne.overscaledZ>0;){if(ne.key in this._loadedParentTiles){de=this._loadedParentTiles[ne.key];break}K.push(ne.key);var we=ne.scaledTo(ne.overscaledZ-1);if(de=this._getLoadedTile(we),de)break;ne=we}for(var Ue=0,ft=K;Ue<ft.length;Ue+=1){var Xt=ft[Ue];this._loadedParentTiles[Xt]=de}}},D.prototype._addTile=function(q){var K=this._tiles[q.key];if(K)return K;K=this._cache.getAndRemove(q),K&&(this._setTileReloadTimer(q.key,K),K.tileID=q,this._state.initializeTileState(K,this.map?this.map.painter:null),this._cacheTimers[q.key]&&(clearTimeout(this._cacheTimers[q.key]),delete this._cacheTimers[q.key],this._setTileReloadTimer(q.key,K)));var de=!!K;return de||(K=new i.Tile(q,this._source.tileSize*q.overscaleFactor()),this._loadTile(K,this._tileLoaded.bind(this,K,q.key,K.state))),K?(K.uses++,this._tiles[q.key]=K,de||this._source.fire(new i.Event(\"dataloading\",{tile:K,coord:K.tileID,dataType:\"source\"})),K):null},D.prototype._setTileReloadTimer=function(q,K){var de=this;q in this._timers&&(clearTimeout(this._timers[q]),delete this._timers[q]);var ne=K.getExpiryTimeout();ne&&(this._timers[q]=setTimeout(function(){de._reloadTile(q,\"expired\"),delete de._timers[q]},ne))},D.prototype._removeTile=function(q){var K=this._tiles[q];K&&(K.uses--,delete this._tiles[q],this._timers[q]&&(clearTimeout(this._timers[q]),delete this._timers[q]),!(K.uses>0)&&(K.hasData()&&K.state!==\"reloading\"?this._cache.add(K.tileID,K,K.getExpiryTimeout()):(K.aborted=!0,this._abortTile(K),this._unloadTile(K))))},D.prototype.clearTiles=function(){this._shouldReloadOnResume=!1,this._paused=!1;for(var q in this._tiles)this._removeTile(q);this._cache.reset()},D.prototype.tilesIn=function(q,K,de){var ne=this,we=[],Ue=this.transform;if(!Ue)return we;for(var ft=de?Ue.getCameraQueryGeometry(q):q,Xt=q.map(function(Pt){return Ue.pointCoordinate(Pt)}),hr=ft.map(function(Pt){return Ue.pointCoordinate(Pt)}),qt=this.getIds(),Ve=1/0,Qe=1/0,at=-1/0,Ct=-1/0,Ot=0,Rt=hr;Ot<Rt.length;Ot+=1){var Bt=Rt[Ot];Ve=Math.min(Ve,Bt.x),Qe=Math.min(Qe,Bt.y),at=Math.max(at,Bt.x),Ct=Math.max(Ct,Bt.y)}for(var Dt=function(Pt){var ht=ne._tiles[qt[Pt]];if(!ht.holdingForFade()){var ur=ht.tileID,br=Math.pow(2,Ue.zoom-ht.tileID.overscaledZ),Ur=K*ht.queryPadding*i.EXTENT/ht.tileSize/br,Di=[ur.getTilePoint(new i.MercatorCoordinate(Ve,Qe)),ur.getTilePoint(new i.MercatorCoordinate(at,Ct))];if(Di[0].x-Ur<i.EXTENT&&Di[0].y-Ur<i.EXTENT&&Di[1].x+Ur>=0&&Di[1].y+Ur>=0){var fi=Xt.map(function(gn){return ur.getTilePoint(gn)}),Ti=hr.map(function(gn){return ur.getTilePoint(gn)});we.push({tile:ht,tileID:ur,queryGeometry:fi,cameraQueryGeometry:Ti,scale:br})}}},yt=0;yt<qt.length;yt++)Dt(yt);return we},D.prototype.getVisibleCoordinates=function(q){for(var K=this,de=this.getRenderableIds(q).map(function(ft){return K._tiles[ft].tileID}),ne=0,we=de;ne<we.length;ne+=1){var Ue=we[ne];Ue.posMatrix=this.transform.calculatePosMatrix(Ue.toUnwrapped())}return de},D.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Oi(this._source.type))for(var q in this._tiles){var K=this._tiles[q];if(K.fadeEndTime!==void 0&&K.fadeEndTime>=i.browser.now())return!0}return!1},D.prototype.setFeatureState=function(q,K,de){q=q||\"_geojsonTileLayer\",this._state.updateState(q,K,de)},D.prototype.removeFeatureState=function(q,K,de){q=q||\"_geojsonTileLayer\",this._state.removeFeatureState(q,K,de)},D.prototype.getFeatureState=function(q,K){return q=q||\"_geojsonTileLayer\",this._state.getState(q,K)},D.prototype.setDependencies=function(q,K,de){var ne=this._tiles[q];ne&&ne.setDependencies(K,de)},D.prototype.reloadTilesForDependencies=function(q,K){for(var de in this._tiles){var ne=this._tiles[de];ne.hasDependency(q,K)&&this._reloadTile(de,\"reloading\")}this._cache.filter(function(we){return!we.hasDependency(q,K)})},D}(i.Evented);ri.maxOverzooming=10,ri.maxUnderzooming=3;function Qr(Y,D){var J=Math.abs(Y.wrap*2)-+(Y.wrap<0),q=Math.abs(D.wrap*2)-+(D.wrap<0);return Y.overscaledZ-D.overscaledZ||q-J||D.canonical.y-Y.canonical.y||D.canonical.x-Y.canonical.x}function Oi(Y){return Y===\"raster\"||Y===\"image\"||Y===\"video\"}function $i(){return new i.window.Worker(io.workerUrl)}var tn=\"mapboxgl_preloaded_worker_pool\",fn=function(){this.active={}};fn.prototype.acquire=function(D){if(!this.workers)for(this.workers=[];this.workers.length<fn.workerCount;)this.workers.push(new $i);return this.active[D]=!0,this.workers.slice()},fn.prototype.release=function(D){delete this.active[D],this.numActive()===0&&(this.workers.forEach(function(J){J.terminate()}),this.workers=null)},fn.prototype.isPreloaded=function(){return!!this.active[tn]},fn.prototype.numActive=function(){return Object.keys(this.active).length};var yn=Math.floor(i.browser.hardwareConcurrency/2);fn.workerCount=Math.max(Math.min(yn,6),1);var Sn;function Ba(){return Sn||(Sn=new fn),Sn}function ua(){var Y=Ba();Y.acquire(tn)}function ma(){var Y=Sn;Y&&(Y.isPreloaded()&&Y.numActive()===1?(Y.release(tn),Sn=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))}function Wa(Y,D){var J={};for(var q in Y)q!==\"ref\"&&(J[q]=Y[q]);return i.refProperties.forEach(function(K){K in D&&(J[K]=D[K])}),J}function Fa(Y){Y=Y.slice();for(var D=Object.create(null),J=0;J<Y.length;J++)D[Y[J].id]=Y[J];for(var q=0;q<Y.length;q++)\"ref\"in Y[q]&&(Y[q]=Wa(Y[q],D[Y[q].ref]));return Y}function Wo(){var Y={},D=i.styleSpec.$version;for(var J in i.styleSpec.$root){var q=i.styleSpec.$root[J];if(q.required){var K=null;J===\"version\"?K=D:q.type===\"array\"?K=[]:K={},K!=null&&(Y[J]=K)}}return Y}var da={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Wn(Y,D,J){J.push({command:da.addSource,args:[Y,D[Y]]})}function Ga(Y,D,J){D.push({command:da.removeSource,args:[Y]}),J[Y]=!0}function vo(Y,D,J,q){Ga(Y,J,q),Wn(Y,D,J)}function jn(Y,D,J){var q;for(q in Y[J])if(Y[J].hasOwnProperty(q)&&q!==\"data\"&&!i.deepEqual(Y[J][q],D[J][q]))return!1;for(q in D[J])if(D[J].hasOwnProperty(q)&&q!==\"data\"&&!i.deepEqual(Y[J][q],D[J][q]))return!1;return!0}function Mt(Y,D,J,q){Y=Y||{},D=D||{};var K;for(K in 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q=Y.map(Jr),K=D.map(Jr),de=Y.reduce(vi,{}),ne=D.reduce(vi,{}),we=q.slice(),Ue=Object.create(null),ft,Xt,hr,qt,Ve,Qe,at;for(ft=0,Xt=0;ft<q.length;ft++)hr=q[ft],ne.hasOwnProperty(hr)?Xt++:(J.push({command:da.removeLayer,args:[hr]}),we.splice(we.indexOf(hr,Xt),1));for(ft=0,Xt=0;ft<K.length;ft++)hr=K[K.length-1-ft],we[we.length-1-ft]!==hr&&(de.hasOwnProperty(hr)?(J.push({command:da.removeLayer,args:[hr]}),we.splice(we.lastIndexOf(hr,we.length-Xt),1)):Xt++,Qe=we[we.length-ft],J.push({command:da.addLayer,args:[ne[hr],Qe]}),we.splice(we.length-ft,0,hr),Ue[hr]=!0);for(ft=0;ft<K.length;ft++)if(hr=K[ft],qt=de[hr],Ve=ne[hr],!(Ue[hr]||i.deepEqual(qt,Ve))){if(!i.deepEqual(qt.source,Ve.source)||!i.deepEqual(qt[\"source-layer\"],Ve[\"source-layer\"])||!i.deepEqual(qt.type,Ve.type)){J.push({command:da.removeLayer,args:[hr]}),Qe=we[we.lastIndexOf(hr)+1],J.push({command:da.addLayer,args:[Ve,Qe]});continue}kr(qt.layout,Ve.layout,J,hr,null,da.setLayoutProperty),kr(qt.paint,Ve.paint,J,hr,null,da.setPaintProperty),i.deepEqual(qt.filter,Ve.filter)||J.push({command:da.setFilter,args:[hr,Ve.filter]}),(!i.deepEqual(qt.minzoom,Ve.minzoom)||!i.deepEqual(qt.maxzoom,Ve.maxzoom))&&J.push({command:da.setLayerZoomRange,args:[hr,Ve.minzoom,Ve.maxzoom]});for(at in qt)qt.hasOwnProperty(at)&&(at===\"layout\"||at===\"paint\"||at===\"filter\"||at===\"metadata\"||at===\"minzoom\"||at===\"maxzoom\"||(at.indexOf(\"paint.\")===0?kr(qt[at],Ve[at],J,hr,at.slice(6),da.setPaintProperty):i.deepEqual(qt[at],Ve[at])||J.push({command:da.setLayerProperty,args:[hr,at,Ve[at]]})));for(at in Ve)!Ve.hasOwnProperty(at)||qt.hasOwnProperty(at)||at===\"layout\"||at===\"paint\"||at===\"filter\"||at===\"metadata\"||at===\"minzoom\"||at===\"maxzoom\"||(at.indexOf(\"paint.\")===0?kr(qt[at],Ve[at],J,hr,at.slice(6),da.setPaintProperty):i.deepEqual(qt[at],Ve[at])||J.push({command:da.setLayerProperty,args:[hr,at,Ve[at]]}))}}function An(Y,D){if(!Y)return[{command:da.setStyle,args:[D]}];var J=[];try{if(!i.deepEqual(Y.version,D.version))return[{command:da.setStyle,args:[D]}];i.deepEqual(Y.center,D.center)||J.push({command:da.setCenter,args:[D.center]}),i.deepEqual(Y.zoom,D.zoom)||J.push({command:da.setZoom,args:[D.zoom]}),i.deepEqual(Y.bearing,D.bearing)||J.push({command:da.setBearing,args:[D.bearing]}),i.deepEqual(Y.pitch,D.pitch)||J.push({command:da.setPitch,args:[D.pitch]}),i.deepEqual(Y.sprite,D.sprite)||J.push({command:da.setSprite,args:[D.sprite]}),i.deepEqual(Y.glyphs,D.glyphs)||J.push({command:da.setGlyphs,args:[D.glyphs]}),i.deepEqual(Y.transition,D.transition)||J.push({command:da.setTransition,args:[D.transition]}),i.deepEqual(Y.light,D.light)||J.push({command:da.setLight,args:[D.light]});var q={},K=[];Mt(Y.sources,D.sources,K,q);var de=[];Y.layers&&Y.layers.forEach(function(ne){q[ne.source]?J.push({command:da.removeLayer,args:[ne.id]}):de.push(ne)}),J=J.concat(K),hn(de,D.layers,J)}catch(ne){console.warn(\"Unable to compute style diff:\",ne),J=[{command:da.setStyle,args:[D]}]}return J}var Mn=function(D,J){this.reset(D,J)};Mn.prototype.reset=function(D,J){this.points=D||[],this._distances=[0];for(var q=1;q<this.points.length;q++)this._distances[q]=this._distances[q-1]+this.points[q].dist(this.points[q-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(J||0,this.length*.5),this.paddedLength=this.length-this.padding*2},Mn.prototype.lerp=function(D){if(this.points.length===1)return this.points[0];D=i.clamp(D,0,1);for(var J=1,q=this._distances[J],K=D*this.paddedLength+this.padding;q<K&&J<this._distances.length;)q=this._distances[++J];var de=J-1,ne=this._distances[de],we=q-ne,Ue=we>0?(K-ne)/we:0;return this.points[de].mult(1-Ue).add(this.points[J].mult(Ue))};var Li=function(D,J,q){var K=this.boxCells=[],de=this.circleCells=[];this.xCellCount=Math.ceil(D/q),this.yCellCount=Math.ceil(J/q);for(var ne=0;ne<this.xCellCount*this.yCellCount;ne++)K.push([]),de.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=D,this.height=J,this.xScale=this.xCellCount/D,this.yScale=this.yCellCount/J,this.boxUid=0,this.circleUid=0};Li.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Li.prototype.insert=function(D,J,q,K,de){this._forEachCell(J,q,K,de,this._insertBoxCell,this.boxUid++),this.boxKeys.push(D),this.bboxes.push(J),this.bboxes.push(q),this.bboxes.push(K),this.bboxes.push(de)},Li.prototype.insertCircle=function(D,J,q,K){this._forEachCell(J-K,q-K,J+K,q+K,this._insertCircleCell,this.circleUid++),this.circleKeys.push(D),this.circles.push(J),this.circles.push(q),this.circles.push(K)},Li.prototype._insertBoxCell=function(D,J,q,K,de,ne){this.boxCells[de].push(ne)},Li.prototype._insertCircleCell=function(D,J,q,K,de,ne){this.circleCells[de].push(ne)},Li.prototype._query=function(D,J,q,K,de,ne){if(q<0||D>this.width||K<0||J>this.height)return de?!1:[];var we=[];if(D<=0&&J<=0&&this.width<=q&&this.height<=K){if(de)return!0;for(var Ue=0;Ue<this.boxKeys.length;Ue++)we.push({key:this.boxKeys[Ue],x1:this.bboxes[Ue*4],y1:this.bboxes[Ue*4+1],x2:this.bboxes[Ue*4+2],y2:this.bboxes[Ue*4+3]});for(var ft=0;ft<this.circleKeys.length;ft++){var Xt=this.circles[ft*3],hr=this.circles[ft*3+1],qt=this.circles[ft*3+2];we.push({key:this.circleKeys[ft],x1:Xt-qt,y1:hr-qt,x2:Xt+qt,y2:hr+qt})}return ne?we.filter(ne):we}else{var Ve={hitTest:de,seenUids:{box:{},circle:{}}};return this._forEachCell(D,J,q,K,this._queryCell,we,Ve,ne),de?we.length>0:we}},Li.prototype._queryCircle=function(D,J,q,K,de){var ne=D-q,we=D+q,Ue=J-q,ft=J+q;if(we<0||ne>this.width||ft<0||Ue>this.height)return K?!1:[];var Xt=[],hr={hitTest:K,circle:{x:D,y:J,radius:q},seenUids:{box:{},circle:{}}};return this._forEachCell(ne,Ue,we,ft,this._queryCellCircle,Xt,hr,de),K?Xt.length>0:Xt},Li.prototype.query=function(D,J,q,K,de){return this._query(D,J,q,K,!1,de)},Li.prototype.hitTest=function(D,J,q,K,de){return this._query(D,J,q,K,!0,de)},Li.prototype.hitTestCircle=function(D,J,q,K){return this._queryCircle(D,J,q,!0,K)},Li.prototype._queryCell=function(D,J,q,K,de,ne,we,Ue){var ft=we.seenUids,Xt=this.boxCells[de];if(Xt!==null)for(var hr=this.bboxes,qt=0,Ve=Xt;qt<Ve.length;qt+=1){var Qe=Ve[qt];if(!ft.box[Qe]){ft.box[Qe]=!0;var at=Qe*4;if(D<=hr[at+2]&&J<=hr[at+3]&&q>=hr[at+0]&&K>=hr[at+1]&&(!Ue||Ue(this.boxKeys[Qe]))){if(we.hitTest)return ne.push(!0),!0;ne.push({key:this.boxKeys[Qe],x1:hr[at],y1:hr[at+1],x2:hr[at+2],y2:hr[at+3]})}}}var Ct=this.circleCells[de];if(Ct!==null)for(var Ot=this.circles,Rt=0,Bt=Ct;Rt<Bt.length;Rt+=1){var Dt=Bt[Rt];if(!ft.circle[Dt]){ft.circle[Dt]=!0;var yt=Dt*3;if(this._circleAndRectCollide(Ot[yt],Ot[yt+1],Ot[yt+2],D,J,q,K)&&(!Ue||Ue(this.circleKeys[Dt]))){if(we.hitTest)return ne.push(!0),!0;var Pt=Ot[yt],ht=Ot[yt+1],ur=Ot[yt+2];ne.push({key:this.circleKeys[Dt],x1:Pt-ur,y1:ht-ur,x2:Pt+ur,y2:ht+ur})}}}},Li.prototype._queryCellCircle=function(D,J,q,K,de,ne,we,Ue){var ft=we.circle,Xt=we.seenUids,hr=this.boxCells[de];if(hr!==null)for(var qt=this.bboxes,Ve=0,Qe=hr;Ve<Qe.length;Ve+=1){var at=Qe[Ve];if(!Xt.box[at]){Xt.box[at]=!0;var Ct=at*4;if(this._circleAndRectCollide(ft.x,ft.y,ft.radius,qt[Ct+0],qt[Ct+1],qt[Ct+2],qt[Ct+3])&&(!Ue||Ue(this.boxKeys[at])))return ne.push(!0),!0}}var Ot=this.circleCells[de];if(Ot!==null)for(var Rt=this.circles,Bt=0,Dt=Ot;Bt<Dt.length;Bt+=1){var yt=Dt[Bt];if(!Xt.circle[yt]){Xt.circle[yt]=!0;var Pt=yt*3;if(this._circlesCollide(Rt[Pt],Rt[Pt+1],Rt[Pt+2],ft.x,ft.y,ft.radius)&&(!Ue||Ue(this.circleKeys[yt])))return ne.push(!0),!0}}},Li.prototype._forEachCell=function(D,J,q,K,de,ne,we,Ue){for(var ft=this._convertToXCellCoord(D),Xt=this._convertToYCellCoord(J),hr=this._convertToXCellCoord(q),qt=this._convertToYCellCoord(K),Ve=ft;Ve<=hr;Ve++)for(var Qe=Xt;Qe<=qt;Qe++){var at=this.xCellCount*Qe+Ve;if(de.call(this,D,J,q,K,at,ne,we,Ue))return}},Li.prototype._convertToXCellCoord=function(D){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(D*this.xScale)))},Li.prototype._convertToYCellCoord=function(D){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(D*this.yScale)))},Li.prototype._circlesCollide=function(D,J,q,K,de,ne){var we=K-D,Ue=de-J,ft=q+ne;return ft*ft>we*we+Ue*Ue},Li.prototype._circleAndRectCollide=function(D,J,q,K,de,ne,we){var Ue=(ne-K)/2,ft=Math.abs(D-(K+Ue));if(ft>Ue+q)return!1;var Xt=(we-de)/2,hr=Math.abs(J-(de+Xt));if(hr>Xt+q)return!1;if(ft<=Ue||hr<=Xt)return!0;var qt=ft-Ue,Ve=hr-Xt;return qt*qt+Ve*Ve<=q*q};function _n(Y,D,J,q,K){var de=i.create();return D?(i.scale(de,de,[1/K,1/K,1]),J||i.rotateZ(de,de,q.angle)):i.multiply(de,q.labelPlaneMatrix,Y),de}function ya(Y,D,J,q,K){if(D){var de=i.clone(Y);return i.scale(de,de,[K,K,1]),J||i.rotateZ(de,de,-q.angle),de}else return q.glCoordMatrix}function Jn(Y,D){var J=[Y.x,Y.y,0,1];zl(J,J,D);var q=J[3];return{point:new i.Point(J[0]/q,J[1]/q),signedDistanceFromCamera:q}}function Ma(Y,D){return .5+.5*(Y/D)}function _o(Y,D){var J=Y[0]/Y[3],q=Y[1]/Y[3],K=J>=-D[0]&&J<=D[0]&&q>=-D[1]&&q<=D[1];return K}function No(Y,D,J,q,K,de,ne,we){var Ue=q?Y.textSizeData:Y.iconSizeData,ft=i.evaluateSizeForZoom(Ue,J.transform.zoom),Xt=[256/J.width*2+1,256/J.height*2+1],hr=q?Y.text.dynamicLayoutVertexArray:Y.icon.dynamicLayoutVertexArray;hr.clear();for(var qt=Y.lineVertexArray,Ve=q?Y.text.placedSymbolArray:Y.icon.placedSymbolArray,Qe=J.transform.width/J.transform.height,at=!1,Ct=0;Ct<Ve.length;Ct++){var Ot=Ve.get(Ct);if(Ot.hidden||Ot.writingMode===i.WritingMode.vertical&&!at){ul(Ot.numGlyphs,hr);continue}at=!1;var Rt=[Ot.anchorX,Ot.anchorY,0,1];if(i.transformMat4(Rt,Rt,D),!_o(Rt,Xt)){ul(Ot.numGlyphs,hr);continue}var Bt=Rt[3],Dt=Ma(J.transform.cameraToCenterDistance,Bt),yt=i.evaluateSizeForFeature(Ue,ft,Ot),Pt=ne?yt/Dt:yt*Dt,ht=new i.Point(Ot.anchorX,Ot.anchorY),ur=Jn(ht,K).point,br={},Ur=ko(Ot,Pt,!1,we,D,K,de,Y.glyphOffsetArray,qt,hr,ur,ht,br,Qe);at=Ur.useVertical,(Ur.notEnoughRoom||at||Ur.needsFlipping&&ko(Ot,Pt,!0,we,D,K,de,Y.glyphOffsetArray,qt,hr,ur,ht,br,Qe).notEnoughRoom)&&ul(Ot.numGlyphs,hr)}q?Y.text.dynamicLayoutVertexBuffer.updateData(hr):Y.icon.dynamicLayoutVertexBuffer.updateData(hr)}function po(Y,D,J,q,K,de,ne,we,Ue,ft,Xt){var hr=we.glyphStartIndex+we.numGlyphs,qt=we.lineStartIndex,Ve=we.lineStartIndex+we.lineLength,Qe=D.getoffsetX(we.glyphStartIndex),at=D.getoffsetX(hr-1),Ct=Fs(Y*Qe,J,q,K,de,ne,we.segment,qt,Ve,Ue,ft,Xt);if(!Ct)return null;var Ot=Fs(Y*at,J,q,K,de,ne,we.segment,qt,Ve,Ue,ft,Xt);return Ot?{first:Ct,last:Ot}:null}function Lo(Y,D,J,q){if(Y===i.WritingMode.horizontal){var K=Math.abs(J.y-D.y),de=Math.abs(J.x-D.x)*q;if(K>de)return{useVertical:!0}}return(Y===i.WritingMode.vertical?D.y<J.y:D.x>J.x)?{needsFlipping:!0}:null}function ko(Y,D,J,q,K,de,ne,we,Ue,ft,Xt,hr,qt,Ve){var Qe=D/24,at=Y.lineOffsetX*Qe,Ct=Y.lineOffsetY*Qe,Ot;if(Y.numGlyphs>1){var Rt=Y.glyphStartIndex+Y.numGlyphs,Bt=Y.lineStartIndex,Dt=Y.lineStartIndex+Y.lineLength,yt=po(Qe,we,at,Ct,J,Xt,hr,Y,Ue,de,qt);if(!yt)return{notEnoughRoom:!0};var Pt=Jn(yt.first.point,ne).point,ht=Jn(yt.last.point,ne).point;if(q&&!J){var ur=Lo(Y.writingMode,Pt,ht,Ve);if(ur)return ur}Ot=[yt.first];for(var br=Y.glyphStartIndex+1;br<Rt-1;br++)Ot.push(Fs(Qe*we.getoffsetX(br),at,Ct,J,Xt,hr,Y.segment,Bt,Dt,Ue,de,qt));Ot.push(yt.last)}else{if(q&&!J){var Ur=Jn(hr,K).point,Di=Y.lineStartIndex+Y.segment+1,fi=new i.Point(Ue.getx(Di),Ue.gety(Di)),Ti=Jn(fi,K),gn=Ti.signedDistanceFromCamera>0?Ti.point:Ds(hr,fi,Ur,1,K),rn=Lo(Y.writingMode,Ur,gn,Ve);if(rn)return rn}var Ci=Fs(Qe*we.getoffsetX(Y.glyphStartIndex),at,Ct,J,Xt,hr,Y.segment,Y.lineStartIndex,Y.lineStartIndex+Y.lineLength,Ue,de,qt);if(!Ci)return{notEnoughRoom:!0};Ot=[Ci]}for(var Bi=0,Gi=Ot;Bi<Gi.length;Bi+=1){var sn=Gi[Bi];i.addDynamicAttributes(ft,sn.point,sn.angle)}return{}}function Ds(Y,D,J,q,K){var de=Jn(Y.add(Y.sub(D)._unit()),K).point,ne=J.sub(de);return J.add(ne._mult(q/ne.mag()))}function Fs(Y,D,J,q,K,de,ne,we,Ue,ft,Xt,hr){var qt=q?Y-D:Y+D,Ve=qt>0?1:-1,Qe=0;q&&(Ve*=-1,Qe=Math.PI),Ve<0&&(Qe+=Math.PI);for(var at=Ve>0?we+ne:we+ne+1,Ct=K,Ot=K,Rt=0,Bt=0,Dt=Math.abs(qt),yt=[];Rt+Bt<=Dt;){if(at+=Ve,at<we||at>=Ue)return null;if(Ot=Ct,yt.push(Ct),Ct=hr[at],Ct===void 0){var Pt=new i.Point(ft.getx(at),ft.gety(at)),ht=Jn(Pt,Xt);if(ht.signedDistanceFromCamera>0)Ct=hr[at]=ht.point;else{var ur=at-Ve,br=Rt===0?de:new i.Point(ft.getx(ur),ft.gety(ur));Ct=Ds(br,Pt,Ot,Dt-Rt+1,Xt)}}Rt+=Bt,Bt=Ot.dist(Ct)}var Ur=(Dt-Rt)/Bt,Di=Ct.sub(Ot),fi=Di.mult(Ur)._add(Ot);fi._add(Di._unit()._perp()._mult(J*Ve));var Ti=Qe+Math.atan2(Ct.y-Ot.y,Ct.x-Ot.x);return yt.push(fi),{point:fi,angle:Ti,path:yt}}var ll=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ul(Y,D){for(var J=0;J<Y;J++){var q=D.length;D.resize(q+4),D.float32.set(ll,q*3)}}function zl(Y,D,J){var q=D[0],K=D[1];return Y[0]=J[0]*q+J[4]*K+J[12],Y[1]=J[1]*q+J[5]*K+J[13],Y[3]=J[3]*q+J[7]*K+J[15],Y}var us=100,il=function(D,J,q){J===void 0&&(J=new Li(D.width+2*us,D.height+2*us,25)),q===void 0&&(q=new Li(D.width+2*us,D.height+2*us,25)),this.transform=D,this.grid=J,this.ignoredGrid=q,this.pitchfactor=Math.cos(D._pitch)*D.cameraToCenterDistance,this.screenRightBoundary=D.width+us,this.screenBottomBoundary=D.height+us,this.gridRightBoundary=D.width+2*us,this.gridBottomBoundary=D.height+2*us};il.prototype.placeCollisionBox=function(D,J,q,K,de){var ne=this.projectAndGetPerspectiveRatio(K,D.anchorPointX,D.anchorPointY),we=q*ne.perspectiveRatio,Ue=D.x1*we+ne.point.x,ft=D.y1*we+ne.point.y,Xt=D.x2*we+ne.point.x,hr=D.y2*we+ne.point.y;return!this.isInsideGrid(Ue,ft,Xt,hr)||!J&&this.grid.hitTest(Ue,ft,Xt,hr,de)?{box:[],offscreen:!1}:{box:[Ue,ft,Xt,hr],offscreen:this.isOffscreen(Ue,ft,Xt,hr)}},il.prototype.placeCollisionCircles=function(D,J,q,K,de,ne,we,Ue,ft,Xt,hr,qt,Ve){var Qe=[],at=new i.Point(J.anchorX,J.anchorY),Ct=Jn(at,ne),Ot=Ma(this.transform.cameraToCenterDistance,Ct.signedDistanceFromCamera),Rt=Xt?de/Ot:de*Ot,Bt=Rt/i.ONE_EM,Dt=Jn(at,we).point,yt={},Pt=J.lineOffsetX*Bt,ht=J.lineOffsetY*Bt,ur=po(Bt,K,Pt,ht,!1,Dt,at,J,q,we,yt),br=!1,Ur=!1,Di=!0;if(ur){for(var fi=qt*.5*Ot+Ve,Ti=new i.Point(-us,-us),gn=new i.Point(this.screenRightBoundary,this.screenBottomBoundary),rn=new Mn,Ci=ur.first,Bi=ur.last,Gi=[],sn=Ci.path.length-1;sn>=1;sn--)Gi.push(Ci.path[sn]);for(var zn=1;zn<Bi.path.length;zn++)Gi.push(Bi.path[zn]);var Ja=fi*2.5;if(Ue){var co=Gi.map(function(Iv){return Jn(Iv,Ue)});co.some(function(Iv){return Iv.signedDistanceFromCamera<=0})?Gi=[]:Gi=co.map(function(Iv){return Iv.point})}var ts=[];if(Gi.length>0){for(var so=Gi[0].clone(),Zo=Gi[0].clone(),ms=1;ms<Gi.length;ms++)so.x=Math.min(so.x,Gi[ms].x),so.y=Math.min(so.y,Gi[ms].y),Zo.x=Math.max(Zo.x,Gi[ms].x),Zo.y=Math.max(Zo.y,Gi[ms].y);so.x>=Ti.x&&Zo.x<=gn.x&&so.y>=Ti.y&&Zo.y<=gn.y?ts=[Gi]:Zo.x<Ti.x||so.x>gn.x||Zo.y<Ti.y||so.y>gn.y?ts=[]:ts=i.clipLine([Gi],Ti.x,Ti.y,gn.x,gn.y)}for(var ou=0,Cv=ts;ou<Cv.length;ou+=1){var Lv=Cv[ou];rn.reset(Lv,fi*.25);var wd=0;rn.length<=.5*fi?wd=1:wd=Math.ceil(rn.paddedLength/Ja)+1;for(var Kv=0;Kv<wd;Kv++){var cg=Kv/Math.max(wd-1,1),pp=rn.lerp(cg),Td=pp.x+us,gp=pp.y+us;Qe.push(Td,gp,fi,0);var Vd=Td-fi,Ad=gp-fi,Pv=Td+fi,Jv=gp+fi;if(Di=Di&&this.isOffscreen(Vd,Ad,Pv,Jv),Ur=Ur||this.isInsideGrid(Vd,Ad,Pv,Jv),!D&&this.grid.hitTestCircle(Td,gp,fi,hr)&&(br=!0,!ft))return{circles:[],offscreen:!1,collisionDetected:br}}}}return{circles:!ft&&br||!Ur?[]:Qe,offscreen:Di,collisionDetected:br}},il.prototype.queryRenderedSymbols=function(D){if(D.length===0||this.grid.keysLength()===0&&this.ignoredGrid.keysLength()===0)return{};for(var J=[],q=1/0,K=1/0,de=-1/0,ne=-1/0,we=0,Ue=D;we<Ue.length;we+=1){var ft=Ue[we],Xt=new i.Point(ft.x+us,ft.y+us);q=Math.min(q,Xt.x),K=Math.min(K,Xt.y),de=Math.max(de,Xt.x),ne=Math.max(ne,Xt.y),J.push(Xt)}for(var hr=this.grid.query(q,K,de,ne).concat(this.ignoredGrid.query(q,K,de,ne)),qt={},Ve={},Qe=0,at=hr;Qe<at.length;Qe+=1){var Ct=at[Qe],Ot=Ct.key;if(qt[Ot.bucketInstanceId]===void 0&&(qt[Ot.bucketInstanceId]={}),!qt[Ot.bucketInstanceId][Ot.featureIndex]){var Rt=[new i.Point(Ct.x1,Ct.y1),new i.Point(Ct.x2,Ct.y1),new i.Point(Ct.x2,Ct.y2),new i.Point(Ct.x1,Ct.y2)];i.polygonIntersectsPolygon(J,Rt)&&(qt[Ot.bucketInstanceId][Ot.featureIndex]=!0,Ve[Ot.bucketInstanceId]===void 0&&(Ve[Ot.bucketInstanceId]=[]),Ve[Ot.bucketInstanceId].push(Ot.featureIndex))}}return Ve},il.prototype.insertCollisionBox=function(D,J,q,K,de){var ne=J?this.ignoredGrid:this.grid,we={bucketInstanceId:q,featureIndex:K,collisionGroupID:de};ne.insert(we,D[0],D[1],D[2],D[3])},il.prototype.insertCollisionCircles=function(D,J,q,K,de){for(var ne=J?this.ignoredGrid:this.grid,we={bucketInstanceId:q,featureIndex:K,collisionGroupID:de},Ue=0;Ue<D.length;Ue+=4)ne.insertCircle(we,D[Ue],D[Ue+1],D[Ue+2])},il.prototype.projectAndGetPerspectiveRatio=function(D,J,q){var K=[J,q,0,1];zl(K,K,D);var de=new i.Point((K[0]/K[3]+1)/2*this.transform.width+us,(-K[1]/K[3]+1)/2*this.transform.height+us);return{point:de,perspectiveRatio:.5+.5*(this.transform.cameraToCenterDistance/K[3])}},il.prototype.isOffscreen=function(D,J,q,K){return q<us||D>=this.screenRightBoundary||K<us||J>this.screenBottomBoundary},il.prototype.isInsideGrid=function(D,J,q,K){return q>=0&&D<this.gridRightBoundary&&K>=0&&J<this.gridBottomBoundary},il.prototype.getViewportMatrix=function(){var D=i.identity([]);return i.translate(D,D,[-us,-us,0]),D};function As(Y,D,J){return D*(i.EXTENT/(Y.tileSize*Math.pow(2,J-Y.tileID.overscaledZ)))}var cl=function(D,J,q,K){D?this.opacity=Math.max(0,Math.min(1,D.opacity+(D.placed?J:-J))):this.opacity=K&&q?1:0,this.placed=q};cl.prototype.isHidden=function(){return this.opacity===0&&!this.placed};var Ks=function(D,J,q,K,de){this.text=new cl(D?D.text:null,J,q,de),this.icon=new cl(D?D.icon:null,J,K,de)};Ks.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var zs=function(D,J,q){this.text=D,this.icon=J,this.skipFade=q},Io=function(){this.invProjMatrix=i.create(),this.viewportMatrix=i.create(),this.circles=[]},ls=function(D,J,q,K,de){this.bucketInstanceId=D,this.featureIndex=J,this.sourceLayerIndex=q,this.bucketIndex=K,this.tileID=de},Zl=function(D){this.crossSourceCollisions=D,this.maxGroupID=0,this.collisionGroups={}};Zl.prototype.get=function(D){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[D]){var J=++this.maxGroupID;this.collisionGroups[D]={ID:J,predicate:function(q){return q.collisionGroupID===J}}}return this.collisionGroups[D]};function Su(Y,D,J,q,K){var de=i.getAnchorAlignment(Y),ne=de.horizontalAlign,we=de.verticalAlign,Ue=-(ne-.5)*D,ft=-(we-.5)*J,Xt=i.evaluateVariableOffset(Y,q);return new i.Point(Ue+Xt[0]*K,ft+Xt[1]*K)}function nc(Y,D,J,q,K,de){var ne=Y.x1,we=Y.x2,Ue=Y.y1,ft=Y.y2,Xt=Y.anchorPointX,hr=Y.anchorPointY,qt=new i.Point(D,J);return q&&qt._rotate(K?de:-de),{x1:ne+qt.x,y1:Ue+qt.y,x2:we+qt.x,y2:ft+qt.y,anchorPointX:Xt,anchorPointY:hr}}var bs=function(D,J,q,K){this.transform=D.clone(),this.collisionIndex=new il(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=J,this.retainedQueryData={},this.collisionGroups=new Zl(q),this.collisionCircleArrays={},this.prevPlacement=K,K&&(K.prevPlacement=void 0),this.placedOrientations={}};bs.prototype.getBucketParts=function(D,J,q,K){var de=q.getBucket(J),ne=q.latestFeatureIndex;if(!(!de||!ne||J.id!==de.layerIds[0])){var we=q.collisionBoxArray,Ue=de.layers[0].layout,ft=Math.pow(2,this.transform.zoom-q.tileID.overscaledZ),Xt=q.tileSize/i.EXTENT,hr=this.transform.calculatePosMatrix(q.tileID.toUnwrapped()),qt=Ue.get(\"text-pitch-alignment\")===\"map\",Ve=Ue.get(\"text-rotation-alignment\")===\"map\",Qe=As(q,1,this.transform.zoom),at=_n(hr,qt,Ve,this.transform,Qe),Ct=null;if(qt){var Ot=ya(hr,qt,Ve,this.transform,Qe);Ct=i.multiply([],this.transform.labelPlaneMatrix,Ot)}this.retainedQueryData[de.bucketInstanceId]=new ls(de.bucketInstanceId,ne,de.sourceLayerIndex,de.index,q.tileID);var Rt={bucket:de,layout:Ue,posMatrix:hr,textLabelPlaneMatrix:at,labelToScreenMatrix:Ct,scale:ft,textPixelRatio:Xt,holdingForFade:q.holdingForFade(),collisionBoxArray:we,partiallyEvaluatedTextSize:i.evaluateSizeForZoom(de.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(de.sourceID)};if(K)for(var Bt=0,Dt=de.sortKeyRanges;Bt<Dt.length;Bt+=1){var yt=Dt[Bt],Pt=yt.sortKey,ht=yt.symbolInstanceStart,ur=yt.symbolInstanceEnd;D.push({sortKey:Pt,symbolInstanceStart:ht,symbolInstanceEnd:ur,parameters:Rt})}else D.push({symbolInstanceStart:0,symbolInstanceEnd:de.symbolInstances.length,parameters:Rt})}},bs.prototype.attemptAnchorPlacement=function(D,J,q,K,de,ne,we,Ue,ft,Xt,hr,qt,Ve,Qe,at){var Ct=[qt.textOffset0,qt.textOffset1],Ot=Su(D,q,K,Ct,de),Rt=this.collisionIndex.placeCollisionBox(nc(J,Ot.x,Ot.y,ne,we,this.transform.angle),hr,Ue,ft,Xt.predicate);if(at){var Bt=this.collisionIndex.placeCollisionBox(nc(at,Ot.x,Ot.y,ne,we,this.transform.angle),hr,Ue,ft,Xt.predicate);if(Bt.box.length===0)return}if(Rt.box.length>0){var Dt;return this.prevPlacement&&this.prevPlacement.variableOffsets[qt.crossTileID]&&this.prevPlacement.placements[qt.crossTileID]&&this.prevPlacement.placements[qt.crossTileID].text&&(Dt=this.prevPlacement.variableOffsets[qt.crossTileID].anchor),this.variableOffsets[qt.crossTileID]={textOffset:Ct,width:q,height:K,anchor:D,textBoxScale:de,prevAnchor:Dt},this.markUsedJustification(Ve,D,qt,Qe),Ve.allowVerticalPlacement&&(this.markUsedOrientation(Ve,Qe,qt),this.placedOrientations[qt.crossTileID]=Qe),{shift:Ot,placedGlyphBoxes:Rt}}},bs.prototype.placeLayerBucketPart=function(D,J,q){var K=this,de=D.parameters,ne=de.bucket,we=de.layout,Ue=de.posMatrix,ft=de.textLabelPlaneMatrix,Xt=de.labelToScreenMatrix,hr=de.textPixelRatio,qt=de.holdingForFade,Ve=de.collisionBoxArray,Qe=de.partiallyEvaluatedTextSize,at=de.collisionGroup,Ct=we.get(\"text-optional\"),Ot=we.get(\"icon-optional\"),Rt=we.get(\"text-allow-overlap\"),Bt=we.get(\"icon-allow-overlap\"),Dt=we.get(\"text-rotation-alignment\")===\"map\",yt=we.get(\"text-pitch-alignment\")===\"map\",Pt=we.get(\"icon-text-fit\")!==\"none\",ht=we.get(\"symbol-z-order\")===\"viewport-y\",ur=Rt&&(Bt||!ne.hasIconData()||Ot),br=Bt&&(Rt||!ne.hasTextData()||Ct);!ne.collisionArrays&&Ve&&ne.deserializeCollisionBoxes(Ve);var Ur=function(Ci,Bi){if(!J[Ci.crossTileID]){if(qt){K.placements[Ci.crossTileID]=new zs(!1,!1,!1);return}var Gi=!1,sn=!1,zn=!0,Ja=null,co={box:null,offscreen:null},ts={box:null,offscreen:null},so=null,Zo=null,ms=null,ou=0,Cv=0,Lv=0;Bi.textFeatureIndex?ou=Bi.textFeatureIndex:Ci.useRuntimeCollisionCircles&&(ou=Ci.featureIndex),Bi.verticalTextFeatureIndex&&(Cv=Bi.verticalTextFeatureIndex);var wd=Bi.textBox;if(wd){var Kv=function(vc){var eu=i.WritingMode.horizontal;if(ne.allowVerticalPlacement&&!vc&&K.prevPlacement){var Sd=K.prevPlacement.placedOrientations[Ci.crossTileID];Sd&&(K.placedOrientations[Ci.crossTileID]=Sd,eu=Sd,K.markUsedOrientation(ne,eu,Ci))}return eu},cg=function(vc,eu){if(ne.allowVerticalPlacement&&Ci.numVerticalGlyphVertices>0&&Bi.verticalTextBox)for(var Sd=0,ly=ne.writingModes;Sd<ly.length;Sd+=1){var T1=ly[Sd];if(T1===i.WritingMode.vertical?(co=eu(),ts=co):co=vc(),co&&co.box&&co.box.length)break}else co=vc()};if(we.get(\"text-variable-anchor\")){var Vd=we.get(\"text-variable-anchor\");if(K.prevPlacement&&K.prevPlacement.variableOffsets[Ci.crossTileID]){var Ad=K.prevPlacement.variableOffsets[Ci.crossTileID];Vd.indexOf(Ad.anchor)>0&&(Vd=Vd.filter(function(vc){return vc!==Ad.anchor}),Vd.unshift(Ad.anchor))}var Pv=function(vc,eu,Sd){for(var ly=vc.x2-vc.x1,T1=vc.y2-vc.y1,wu=Ci.textBoxScale,Nx=Pt&&!Bt?eu:null,am={box:[],offscreen:!1},Ew=Rt?Vd.length*2:Vd.length,Rv=0;Rv<Ew;++Rv){var om=Vd[Rv%Vd.length],kw=Rv>=Vd.length,Ux=K.attemptAnchorPlacement(om,vc,ly,T1,wu,Dt,yt,hr,Ue,at,kw,Ci,ne,Sd,Nx);if(Ux&&(am=Ux.placedGlyphBoxes,am&&am.box&&am.box.length)){Gi=!0,Ja=Ux.shift;break}}return am},Jv=function(){return Pv(wd,Bi.iconBox,i.WritingMode.horizontal)},Iv=function(){var vc=Bi.verticalTextBox,eu=co&&co.box&&co.box.length;return ne.allowVerticalPlacement&&!eu&&Ci.numVerticalGlyphVertices>0&&vc?Pv(vc,Bi.verticalIconBox,i.WritingMode.vertical):{box:null,offscreen:null}};cg(Jv,Iv),co&&(Gi=co.box,zn=co.offscreen);var ay=Kv(co&&co.box);if(!Gi&&K.prevPlacement){var fg=K.prevPlacement.variableOffsets[Ci.crossTileID];fg&&(K.variableOffsets[Ci.crossTileID]=fg,K.markUsedJustification(ne,fg.anchor,Ci,ay))}}else{var pp=function(vc,eu){var Sd=K.collisionIndex.placeCollisionBox(vc,Rt,hr,Ue,at.predicate);return Sd&&Sd.box&&Sd.box.length&&(K.markUsedOrientation(ne,eu,Ci),K.placedOrientations[Ci.crossTileID]=eu),Sd},Td=function(){return pp(wd,i.WritingMode.horizontal)},gp=function(){var vc=Bi.verticalTextBox;return ne.allowVerticalPlacement&&Ci.numVerticalGlyphVertices>0&&vc?pp(vc,i.WritingMode.vertical):{box:null,offscreen:null}};cg(Td,gp),Kv(co&&co.box&&co.box.length)}}if(so=co,Gi=so&&so.box&&so.box.length>0,zn=so&&so.offscreen,Ci.useRuntimeCollisionCircles){var oh=ne.text.placedSymbolArray.get(Ci.centerJustifiedTextSymbolIndex),hg=i.evaluateSizeForFeature(ne.textSizeData,Qe,oh),oy=we.get(\"text-padding\"),jh=Ci.collisionCircleDiameter;Zo=K.collisionIndex.placeCollisionCircles(Rt,oh,ne.lineVertexArray,ne.glyphOffsetArray,hg,Ue,ft,Xt,q,yt,at.predicate,jh,oy),Gi=Rt||Zo.circles.length>0&&!Zo.collisionDetected,zn=zn&&Zo.offscreen}if(Bi.iconFeatureIndex&&(Lv=Bi.iconFeatureIndex),Bi.iconBox){var rm=function(vc){var eu=Pt&&Ja?nc(vc,Ja.x,Ja.y,Dt,yt,K.transform.angle):vc;return K.collisionIndex.placeCollisionBox(eu,Bt,hr,Ue,at.predicate)};ts&&ts.box&&ts.box.length&&Bi.verticalIconBox?(ms=rm(Bi.verticalIconBox),sn=ms.box.length>0):(ms=rm(Bi.iconBox),sn=ms.box.length>0),zn=zn&&ms.offscreen}var b1=Ct||Ci.numHorizontalGlyphVertices===0&&Ci.numVerticalGlyphVertices===0,w1=Ot||Ci.numIconVertices===0;if(!b1&&!w1?sn=Gi=sn&&Gi:w1?b1||(sn=sn&&Gi):Gi=sn&&Gi,Gi&&so&&so.box&&(ts&&ts.box&&Cv?K.collisionIndex.insertCollisionBox(so.box,we.get(\"text-ignore-placement\"),ne.bucketInstanceId,Cv,at.ID):K.collisionIndex.insertCollisionBox(so.box,we.get(\"text-ignore-placement\"),ne.bucketInstanceId,ou,at.ID)),sn&&ms&&K.collisionIndex.insertCollisionBox(ms.box,we.get(\"icon-ignore-placement\"),ne.bucketInstanceId,Lv,at.ID),Zo&&(Gi&&K.collisionIndex.insertCollisionCircles(Zo.circles,we.get(\"text-ignore-placement\"),ne.bucketInstanceId,ou,at.ID),q)){var sy=ne.bucketInstanceId,im=K.collisionCircleArrays[sy];im===void 0&&(im=K.collisionCircleArrays[sy]=new Io);for(var nm=0;nm<Zo.circles.length;nm+=4)im.circles.push(Zo.circles[nm+0]),im.circles.push(Zo.circles[nm+1]),im.circles.push(Zo.circles[nm+2]),im.circles.push(Zo.collisionDetected?1:0)}K.placements[Ci.crossTileID]=new zs(Gi||ur,sn||br,zn||ne.justReloaded),J[Ci.crossTileID]=!0}};if(ht)for(var Di=ne.getSortedSymbolIndexes(this.transform.angle),fi=Di.length-1;fi>=0;--fi){var Ti=Di[fi];Ur(ne.symbolInstances.get(Ti),ne.collisionArrays[Ti])}else for(var gn=D.symbolInstanceStart;gn<D.symbolInstanceEnd;gn++)Ur(ne.symbolInstances.get(gn),ne.collisionArrays[gn]);if(q&&ne.bucketInstanceId in this.collisionCircleArrays){var rn=this.collisionCircleArrays[ne.bucketInstanceId];i.invert(rn.invProjMatrix,Ue),rn.viewportMatrix=this.collisionIndex.getViewportMatrix()}ne.justReloaded=!1},bs.prototype.markUsedJustification=function(D,J,q,K){var de={left:q.leftJustifiedTextSymbolIndex,center:q.centerJustifiedTextSymbolIndex,right:q.rightJustifiedTextSymbolIndex},ne;K===i.WritingMode.vertical?ne=q.verticalPlacedTextSymbolIndex:ne=de[i.getAnchorJustification(J)];for(var we=[q.leftJustifiedTextSymbolIndex,q.centerJustifiedTextSymbolIndex,q.rightJustifiedTextSymbolIndex,q.verticalPlacedTextSymbolIndex],Ue=0,ft=we;Ue<ft.length;Ue+=1){var Xt=ft[Ue];Xt>=0&&(ne>=0&&Xt!==ne?D.text.placedSymbolArray.get(Xt).crossTileID=0:D.text.placedSymbolArray.get(Xt).crossTileID=q.crossTileID)}},bs.prototype.markUsedOrientation=function(D,J,q){for(var K=J===i.WritingMode.horizontal||J===i.WritingMode.horizontalOnly?J:0,de=J===i.WritingMode.vertical?J:0,ne=[q.leftJustifiedTextSymbolIndex,q.centerJustifiedTextSymbolIndex,q.rightJustifiedTextSymbolIndex],we=0,Ue=ne;we<Ue.length;we+=1){var ft=Ue[we];D.text.placedSymbolArray.get(ft).placedOrientation=K}q.verticalPlacedTextSymbolIndex&&(D.text.placedSymbolArray.get(q.verticalPlacedTextSymbolIndex).placedOrientation=de)},bs.prototype.commit=function(D){this.commitTime=D,this.zoomAtLastRecencyCheck=this.transform.zoom;var J=this.prevPlacement,q=!1;this.prevZoomAdjustment=J?J.zoomAdjustment(this.transform.zoom):0;var K=J?J.symbolFadeChange(D):1,de=J?J.opacities:{},ne=J?J.variableOffsets:{},we=J?J.placedOrientations:{};for(var Ue in this.placements){var ft=this.placements[Ue],Xt=de[Ue];Xt?(this.opacities[Ue]=new Ks(Xt,K,ft.text,ft.icon),q=q||ft.text!==Xt.text.placed||ft.icon!==Xt.icon.placed):(this.opacities[Ue]=new Ks(null,K,ft.text,ft.icon,ft.skipFade),q=q||ft.text||ft.icon)}for(var hr in de){var qt=de[hr];if(!this.opacities[hr]){var Ve=new Ks(qt,K,!1,!1);Ve.isHidden()||(this.opacities[hr]=Ve,q=q||qt.text.placed||qt.icon.placed)}}for(var Qe in ne)!this.variableOffsets[Qe]&&this.opacities[Qe]&&!this.opacities[Qe].isHidden()&&(this.variableOffsets[Qe]=ne[Qe]);for(var at in we)!this.placedOrientations[at]&&this.opacities[at]&&!this.opacities[at].isHidden()&&(this.placedOrientations[at]=we[at]);q?this.lastPlacementChangeTime=D:typeof this.lastPlacementChangeTime!=\"number\"&&(this.lastPlacementChangeTime=J?J.lastPlacementChangeTime:D)},bs.prototype.updateLayerOpacities=function(D,J){for(var q={},K=0,de=J;K<de.length;K+=1){var ne=de[K],we=ne.getBucket(D);we&&ne.latestFeatureIndex&&D.id===we.layerIds[0]&&this.updateBucketOpacities(we,q,ne.collisionBoxArray)}},bs.prototype.updateBucketOpacities=function(D,J,q){var K=this;D.hasTextData()&&D.text.opacityVertexArray.clear(),D.hasIconData()&&D.icon.opacityVertexArray.clear(),D.hasIconCollisionBoxData()&&D.iconCollisionBox.collisionVertexArray.clear(),D.hasTextCollisionBoxData()&&D.textCollisionBox.collisionVertexArray.clear();var de=D.layers[0].layout,ne=new Ks(null,0,!1,!1,!0),we=de.get(\"text-allow-overlap\"),Ue=de.get(\"icon-allow-overlap\"),ft=de.get(\"text-variable-anchor\"),Xt=de.get(\"text-rotation-alignment\")===\"map\",hr=de.get(\"text-pitch-alignment\")===\"map\",qt=de.get(\"icon-text-fit\")!==\"none\",Ve=new Ks(null,0,we&&(Ue||!D.hasIconData()||de.get(\"icon-optional\")),Ue&&(we||!D.hasTextData()||de.get(\"text-optional\")),!0);!D.collisionArrays&&q&&(D.hasIconCollisionBoxData()||D.hasTextCollisionBoxData())&&D.deserializeCollisionBoxes(q);for(var Qe=function(Rt,Bt,Dt){for(var yt=0;yt<Bt/4;yt++)Rt.opacityVertexArray.emplaceBack(Dt)},at=function(Rt){var Bt=D.symbolInstances.get(Rt),Dt=Bt.numHorizontalGlyphVertices,yt=Bt.numVerticalGlyphVertices,Pt=Bt.crossTileID,ht=J[Pt],ur=K.opacities[Pt];ht?ur=ne:ur||(ur=Ve,K.opacities[Pt]=ur),J[Pt]=!0;var br=Dt>0||yt>0,Ur=Bt.numIconVertices>0,Di=K.placedOrientations[Bt.crossTileID],fi=Di===i.WritingMode.vertical,Ti=Di===i.WritingMode.horizontal||Di===i.WritingMode.horizontalOnly;if(br){var gn=ac(ur.text),rn=fi?aa:gn;Qe(D.text,Dt,rn);var Ci=Ti?aa:gn;Qe(D.text,yt,Ci);var Bi=ur.text.isHidden();[Bt.rightJustifiedTextSymbolIndex,Bt.centerJustifiedTextSymbolIndex,Bt.leftJustifiedTextSymbolIndex].forEach(function(Lv){Lv>=0&&(D.text.placedSymbolArray.get(Lv).hidden=Bi||fi?1:0)}),Bt.verticalPlacedTextSymbolIndex>=0&&(D.text.placedSymbolArray.get(Bt.verticalPlacedTextSymbolIndex).hidden=Bi||Ti?1:0);var Gi=K.variableOffsets[Bt.crossTileID];Gi&&K.markUsedJustification(D,Gi.anchor,Bt,Di);var sn=K.placedOrientations[Bt.crossTileID];sn&&(K.markUsedJustification(D,\"left\",Bt,sn),K.markUsedOrientation(D,sn,Bt))}if(Ur){var zn=ac(ur.icon),Ja=!(qt&&Bt.verticalPlacedIconSymbolIndex&&fi);if(Bt.placedIconSymbolIndex>=0){var co=Ja?zn:aa;Qe(D.icon,Bt.numIconVertices,co),D.icon.placedSymbolArray.get(Bt.placedIconSymbolIndex).hidden=ur.icon.isHidden()}if(Bt.verticalPlacedIconSymbolIndex>=0){var ts=Ja?aa:zn;Qe(D.icon,Bt.numVerticalIconVertices,ts),D.icon.placedSymbolArray.get(Bt.verticalPlacedIconSymbolIndex).hidden=ur.icon.isHidden()}}if(D.hasIconCollisionBoxData()||D.hasTextCollisionBoxData()){var so=D.collisionArrays[Rt];if(so){var Zo=new i.Point(0,0);if(so.textBox||so.verticalTextBox){var ms=!0;if(ft){var ou=K.variableOffsets[Pt];ou?(Zo=Su(ou.anchor,ou.width,ou.height,ou.textOffset,ou.textBoxScale),Xt&&Zo._rotate(hr?K.transform.angle:-K.transform.angle)):ms=!1}so.textBox&&Rn(D.textCollisionBox.collisionVertexArray,ur.text.placed,!ms||fi,Zo.x,Zo.y),so.verticalTextBox&&Rn(D.textCollisionBox.collisionVertexArray,ur.text.placed,!ms||Ti,Zo.x,Zo.y)}var Cv=!!(!Ti&&so.verticalIconBox);so.iconBox&&Rn(D.iconCollisionBox.collisionVertexArray,ur.icon.placed,Cv,qt?Zo.x:0,qt?Zo.y:0),so.verticalIconBox&&Rn(D.iconCollisionBox.collisionVertexArray,ur.icon.placed,!Cv,qt?Zo.x:0,qt?Zo.y:0)}}},Ct=0;Ct<D.symbolInstances.length;Ct++)at(Ct);if(D.sortFeatures(this.transform.angle),this.retainedQueryData[D.bucketInstanceId]&&(this.retainedQueryData[D.bucketInstanceId].featureSortOrder=D.featureSortOrder),D.hasTextData()&&D.text.opacityVertexBuffer&&D.text.opacityVertexBuffer.updateData(D.text.opacityVertexArray),D.hasIconData()&&D.icon.opacityVertexBuffer&&D.icon.opacityVertexBuffer.updateData(D.icon.opacityVertexArray),D.hasIconCollisionBoxData()&&D.iconCollisionBox.collisionVertexBuffer&&D.iconCollisionBox.collisionVertexBuffer.updateData(D.iconCollisionBox.collisionVertexArray),D.hasTextCollisionBoxData()&&D.textCollisionBox.collisionVertexBuffer&&D.textCollisionBox.collisionVertexBuffer.updateData(D.textCollisionBox.collisionVertexArray),D.bucketInstanceId in this.collisionCircleArrays){var Ot=this.collisionCircleArrays[D.bucketInstanceId];D.placementInvProjMatrix=Ot.invProjMatrix,D.placementViewportMatrix=Ot.viewportMatrix,D.collisionCircleArray=Ot.circles,delete this.collisionCircleArrays[D.bucketInstanceId]}},bs.prototype.symbolFadeChange=function(D){return this.fadeDuration===0?1:(D-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},bs.prototype.zoomAdjustment=function(D){return Math.max(0,(this.transform.zoom-D)/1.5)},bs.prototype.hasTransitions=function(D){return this.stale||D-this.lastPlacementChangeTime<this.fadeDuration},bs.prototype.stillRecent=function(D,J){var q=this.zoomAtLastRecencyCheck===J?1-this.zoomAdjustment(J):1;return this.zoomAtLastRecencyCheck=J,this.commitTime+this.fadeDuration*q>D},bs.prototype.setStale=function(){this.stale=!0};function Rn(Y,D,J,q,K){Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0)}var _a=Math.pow(2,25),Vu=Math.pow(2,24),Ol=Math.pow(2,17),xo=Math.pow(2,16),Yl=Math.pow(2,9),Ns=Math.pow(2,8),Hl=Math.pow(2,1);function ac(Y){if(Y.opacity===0&&!Y.placed)return 0;if(Y.opacity===1&&Y.placed)return 4294967295;var D=Y.placed?1:0,J=Math.floor(Y.opacity*127);return J*_a+D*Vu+J*Ol+D*xo+J*Yl+D*Ns+J*Hl+D}var aa=0,Oo=function(D){this._sortAcrossTiles=D.layout.get(\"symbol-z-order\")!==\"viewport-y\"&&D.layout.get(\"symbol-sort-key\").constantOr(1)!==void 0,this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oo.prototype.continuePlacement=function(D,J,q,K,de){for(var ne=this._bucketParts;this._currentTileIndex<D.length;){var we=D[this._currentTileIndex];if(J.getBucketParts(ne,K,we,this._sortAcrossTiles),this._currentTileIndex++,de())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,ne.sort(function(ft,Xt){return ft.sortKey-Xt.sortKey}));this._currentPartIndex<ne.length;){var Ue=ne[this._currentPartIndex];if(J.placeLayerBucketPart(Ue,this._seenCrossTileIDs,q),this._currentPartIndex++,de())return!0}return!1};var qo=function(D,J,q,K,de,ne,we){this.placement=new bs(D,de,ne,we),this._currentPlacementIndex=J.length-1,this._forceFullPlacement=q,this._showCollisionBoxes=K,this._done=!1};qo.prototype.isDone=function(){return this._done},qo.prototype.continuePlacement=function(D,J,q){for(var K=this,de=i.browser.now(),ne=function(){var hr=i.browser.now()-de;return K._forceFullPlacement?!1:hr>2};this._currentPlacementIndex>=0;){var we=D[this._currentPlacementIndex],Ue=J[we],ft=this.placement.collisionIndex.transform.zoom;if(Ue.type===\"symbol\"&&(!Ue.minzoom||Ue.minzoom<=ft)&&(!Ue.maxzoom||Ue.maxzoom>ft)){this._inProgressLayer||(this._inProgressLayer=new Oo(Ue));var Xt=this._inProgressLayer.continuePlacement(q[Ue.source],this.placement,this._showCollisionBoxes,Ue,ne);if(Xt)return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},qo.prototype.commit=function(D){return this.placement.commit(D),this.placement};var ql=512/i.EXTENT/2,Pc=function(D,J,q){this.tileID=D,this.indexedSymbolInstances={},this.bucketInstanceId=q;for(var K=0;K<J.length;K++){var de=J.get(K),ne=de.key;this.indexedSymbolInstances[ne]||(this.indexedSymbolInstances[ne]=[]),this.indexedSymbolInstances[ne].push({crossTileID:de.crossTileID,coord:this.getScaledCoordinates(de,D)})}};Pc.prototype.getScaledCoordinates=function(D,J){var q=J.canonical.z-this.tileID.canonical.z,K=ql/Math.pow(2,q);return{x:Math.floor((J.canonical.x*i.EXTENT+D.anchorX)*K),y:Math.floor((J.canonical.y*i.EXTENT+D.anchorY)*K)}},Pc.prototype.findMatches=function(D,J,q){for(var K=this.tileID.canonical.z<J.canonical.z?1:Math.pow(2,this.tileID.canonical.z-J.canonical.z),de=0;de<D.length;de++){var ne=D.get(de);if(!ne.crossTileID){var we=this.indexedSymbolInstances[ne.key];if(we)for(var Ue=this.getScaledCoordinates(ne,J),ft=0,Xt=we;ft<Xt.length;ft+=1){var hr=Xt[ft];if(Math.abs(hr.coord.x-Ue.x)<=K&&Math.abs(hr.coord.y-Ue.y)<=K&&!q[hr.crossTileID]){q[hr.crossTileID]=!0,ne.crossTileID=hr.crossTileID;break}}}}};var Do=function(){this.maxCrossTileID=0};Do.prototype.generate=function(){return++this.maxCrossTileID};var rf=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};rf.prototype.handleWrapJump=function(D){var J=Math.round((D-this.lng)/360);if(J!==0)for(var q in this.indexes){var K=this.indexes[q],de={};for(var ne in K){var we=K[ne];we.tileID=we.tileID.unwrapTo(we.tileID.wrap+J),de[we.tileID.key]=we}this.indexes[q]=de}this.lng=D},rf.prototype.addBucket=function(D,J,q){if(this.indexes[D.overscaledZ]&&this.indexes[D.overscaledZ][D.key]){if(this.indexes[D.overscaledZ][D.key].bucketInstanceId===J.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(D.overscaledZ,this.indexes[D.overscaledZ][D.key])}for(var K=0;K<J.symbolInstances.length;K++){var de=J.symbolInstances.get(K);de.crossTileID=0}this.usedCrossTileIDs[D.overscaledZ]||(this.usedCrossTileIDs[D.overscaledZ]={});var ne=this.usedCrossTileIDs[D.overscaledZ];for(var we in this.indexes){var Ue=this.indexes[we];if(Number(we)>D.overscaledZ)for(var ft in Ue){var Xt=Ue[ft];Xt.tileID.isChildOf(D)&&Xt.findMatches(J.symbolInstances,D,ne)}else{var hr=D.scaledTo(Number(we)),qt=Ue[hr.key];qt&&qt.findMatches(J.symbolInstances,D,ne)}}for(var Ve=0;Ve<J.symbolInstances.length;Ve++){var Qe=J.symbolInstances.get(Ve);Qe.crossTileID||(Qe.crossTileID=q.generate(),ne[Qe.crossTileID]=!0)}return this.indexes[D.overscaledZ]===void 0&&(this.indexes[D.overscaledZ]={}),this.indexes[D.overscaledZ][D.key]=new Pc(D,J.symbolInstances,J.bucketInstanceId),!0},rf.prototype.removeBucketCrossTileIDs=function(D,J){for(var q in J.indexedSymbolInstances)for(var K=0,de=J.indexedSymbolInstances[q];K<de.length;K+=1){var ne=de[K];delete this.usedCrossTileIDs[D][ne.crossTileID]}},rf.prototype.removeStaleBuckets=function(D){var J=!1;for(var q in this.indexes){var K=this.indexes[q];for(var de in K)D[K[de].bucketInstanceId]||(this.removeBucketCrossTileIDs(q,K[de]),delete K[de],J=!0)}return J};var Uf=function(){this.layerIndexes={},this.crossTileIDs=new Do,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Uf.prototype.addLayer=function(D,J,q){var K=this.layerIndexes[D.id];K===void 0&&(K=this.layerIndexes[D.id]=new rf);var de=!1,ne={};K.handleWrapJump(q);for(var we=0,Ue=J;we<Ue.length;we+=1){var ft=Ue[we],Xt=ft.getBucket(D);!Xt||D.id!==Xt.layerIds[0]||(Xt.bucketInstanceId||(Xt.bucketInstanceId=++this.maxBucketInstanceId),K.addBucket(ft.tileID,Xt,this.crossTileIDs)&&(de=!0),ne[Xt.bucketInstanceId]=!0)}return K.removeStaleBuckets(ne)&&(de=!0),de},Uf.prototype.pruneUnusedLayers=function(D){var J={};D.forEach(function(K){J[K]=!0});for(var q in this.layerIndexes)J[q]||delete this.layerIndexes[q]};var pl=function(Y,D){return i.emitValidationErrors(Y,D&&D.filter(function(J){return J.identifier!==\"source.canvas\"}))},Zc=i.pick(da,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Kl=i.pick(da,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Os=Wo(),yu=function(Y){function D(J,q){var K=this;q===void 0&&(q={}),Y.call(this),this.map=J,this.dispatcher=new Z(Ba(),this),this.imageManager=new k,this.imageManager.setEventedParent(this),this.glyphManager=new P(J._requestManager,q.localIdeographFontFamily),this.lineAtlas=new G(256,512),this.crossTileSymbolIndex=new Uf,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new i.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",i.getReferrer());var de=this;this._rtlTextPluginCallback=D.registerForPluginStateChange(function(ne){var we={pluginStatus:ne.pluginStatus,pluginURL:ne.pluginURL};de.dispatcher.broadcast(\"syncRTLPluginState\",we,function(Ue,ft){if(i.triggerPluginCompletionEvent(Ue),ft){var Xt=ft.every(function(qt){return qt});if(Xt)for(var hr in de.sourceCaches)de.sourceCaches[hr].reload()}})}),this.on(\"data\",function(ne){if(!(ne.dataType!==\"source\"||ne.sourceDataType!==\"metadata\")){var we=K.sourceCaches[ne.sourceId];if(we){var Ue=we.getSource();if(!(!Ue||!Ue.vectorLayerIds))for(var ft in K._layers){var Xt=K._layers[ft];Xt.source===Ue.id&&K._validateLayer(Xt)}}}})}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.loadURL=function(q,K){var de=this;K===void 0&&(K={}),this.fire(new i.Event(\"dataloading\",{dataType:\"style\"}));var ne=typeof K.validate==\"boolean\"?K.validate:!i.isMapboxURL(q);q=this.map._requestManager.normalizeStyleURL(q,K.accessToken);var we=this.map._requestManager.transformRequest(q,i.ResourceType.Style);this._request=i.getJSON(we,function(Ue,ft){de._request=null,Ue?de.fire(new i.ErrorEvent(Ue)):ft&&de._load(ft,ne)})},D.prototype.loadJSON=function(q,K){var de=this;K===void 0&&(K={}),this.fire(new i.Event(\"dataloading\",{dataType:\"style\"})),this._request=i.browser.frame(function(){de._request=null,de._load(q,K.validate!==!1)})},D.prototype.loadEmpty=function(){this.fire(new i.Event(\"dataloading\",{dataType:\"style\"})),this._load(Os,!1)},D.prototype._load=function(q,K){if(!(K&&pl(this,i.validateStyle(q)))){this._loaded=!0,this.stylesheet=q;for(var de in q.sources)this.addSource(de,q.sources[de],{validate:!1});q.sprite?this._loadSprite(q.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(q.glyphs);var ne=Fa(this.stylesheet.layers);this._order=ne.map(function(Xt){return Xt.id}),this._layers={},this._serializedLayers={};for(var we=0,Ue=ne;we<Ue.length;we+=1){var ft=Ue[we];ft=i.createStyleLayer(ft),ft.setEventedParent(this,{layer:{id:ft.id}}),this._layers[ft.id]=ft,this._serializedLayers[ft.id]=ft.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new V(this.stylesheet.light),this.fire(new i.Event(\"data\",{dataType:\"style\"})),this.fire(new i.Event(\"style.load\"))}},D.prototype._loadSprite=function(q){var K=this;this._spriteRequest=_(q,this.map._requestManager,function(de,ne){if(K._spriteRequest=null,de)K.fire(new i.ErrorEvent(de));else if(ne)for(var we in ne)K.imageManager.addImage(we,ne[we]);K.imageManager.setLoaded(!0),K._availableImages=K.imageManager.listImages(),K.dispatcher.broadcast(\"setImages\",K._availableImages),K.fire(new i.Event(\"data\",{dataType:\"style\"}))})},D.prototype._validateLayer=function(q){var K=this.sourceCaches[q.source];if(K){var de=q.sourceLayer;if(de){var ne=K.getSource();(ne.type===\"geojson\"||ne.vectorLayerIds&&ne.vectorLayerIds.indexOf(de)===-1)&&this.fire(new i.ErrorEvent(new Error('Source layer \"'+de+'\" does not exist on source \"'+ne.id+'\" as specified by style layer \"'+q.id+'\"')))}}},D.prototype.loaded=function(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(var q in this.sourceCaches)if(!this.sourceCaches[q].loaded())return!1;return!!this.imageManager.isLoaded()},D.prototype._serializeLayers=function(q){for(var K=[],de=0,ne=q;de<ne.length;de+=1){var we=ne[de],Ue=this._layers[we];Ue.type!==\"custom\"&&K.push(Ue.serialize())}return K},D.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var q in this.sourceCaches)if(this.sourceCaches[q].hasTransition())return!0;for(var K in this._layers)if(this._layers[K].hasTransition())return!0;return!1},D.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},D.prototype.update=function(q){if(this._loaded){var K=this._changed;if(this._changed){var de=Object.keys(this._updatedLayers),ne=Object.keys(this._removedLayers);(de.length||ne.length)&&this._updateWorkerLayers(de,ne);for(var we in this._updatedSources){var Ue=this._updatedSources[we];Ue===\"reload\"?this._reloadSource(we):Ue===\"clear\"&&this._clearSource(we)}this._updateTilesForChangedImages();for(var ft in this._updatedPaintProps)this._layers[ft].updateTransitions(q);this.light.updateTransitions(q),this._resetUpdates()}var Xt={};for(var hr in this.sourceCaches){var qt=this.sourceCaches[hr];Xt[hr]=qt.used,qt.used=!1}for(var Ve=0,Qe=this._order;Ve<Qe.length;Ve+=1){var at=Qe[Ve],Ct=this._layers[at];Ct.recalculate(q,this._availableImages),!Ct.isHidden(q.zoom)&&Ct.source&&(this.sourceCaches[Ct.source].used=!0)}for(var Ot in Xt){var Rt=this.sourceCaches[Ot];Xt[Ot]!==Rt.used&&Rt.fire(new i.Event(\"data\",{sourceDataType:\"visibility\",dataType:\"source\",sourceId:Ot}))}this.light.recalculate(q),this.z=q.zoom,K&&this.fire(new i.Event(\"data\",{dataType:\"style\"}))}},D.prototype._updateTilesForChangedImages=function(){var q=Object.keys(this._changedImages);if(q.length){for(var K in this.sourceCaches)this.sourceCaches[K].reloadTilesForDependencies([\"icons\",\"patterns\"],q);this._changedImages={}}},D.prototype._updateWorkerLayers=function(q,K){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(q),removedIds:K})},D.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},D.prototype.setState=function(q){var K=this;if(this._checkLoaded(),pl(this,i.validateStyle(q)))return!1;q=i.clone$1(q),q.layers=Fa(q.layers);var de=An(this.serialize(),q).filter(function(we){return!(we.command in Kl)});if(de.length===0)return!1;var ne=de.filter(function(we){return!(we.command in Zc)});if(ne.length>0)throw new Error(\"Unimplemented: \"+ne.map(function(we){return we.command}).join(\", \")+\".\");return de.forEach(function(we){we.command!==\"setTransition\"&&K[we.command].apply(K,we.args)}),this.stylesheet=q,!0},D.prototype.addImage=function(q,K){if(this.getImage(q))return this.fire(new i.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(q,K),this._afterImageUpdated(q)},D.prototype.updateImage=function(q,K){this.imageManager.updateImage(q,K)},D.prototype.getImage=function(q){return this.imageManager.getImage(q)},D.prototype.removeImage=function(q){if(!this.getImage(q))return this.fire(new i.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(q),this._afterImageUpdated(q)},D.prototype._afterImageUpdated=function(q){this._availableImages=this.imageManager.listImages(),this._changedImages[q]=!0,this._changed=!0,this.dispatcher.broadcast(\"setImages\",this._availableImages),this.fire(new i.Event(\"data\",{dataType:\"style\"}))},D.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},D.prototype.addSource=function(q,K,de){var ne=this;if(de===void 0&&(de={}),this._checkLoaded(),this.sourceCaches[q]!==void 0)throw new Error(\"There is already a source with this ID\");if(!K.type)throw new Error(\"The type property must be defined, but only the following properties were given: \"+Object.keys(K).join(\", \")+\".\");var we=[\"vector\",\"raster\",\"geojson\",\"video\",\"image\"],Ue=we.indexOf(K.type)>=0;if(!(Ue&&this._validate(i.validateStyle.source,\"sources.\"+q,K,null,de))){this.map&&this.map._collectResourceTiming&&(K.collectResourceTiming=!0);var ft=this.sourceCaches[q]=new ri(q,K,this.dispatcher);ft.style=this,ft.setEventedParent(this,function(){return{isSourceLoaded:ne.loaded(),source:ft.serialize(),sourceId:q}}),ft.onAdd(this.map),this._changed=!0}},D.prototype.removeSource=function(q){if(this._checkLoaded(),this.sourceCaches[q]===void 0)throw new Error(\"There is no source with this ID\");for(var K in this._layers)if(this._layers[K].source===q)return this.fire(new i.ErrorEvent(new Error('Source \"'+q+'\" cannot be removed while layer \"'+K+'\" is using it.')));var de=this.sourceCaches[q];delete this.sourceCaches[q],delete this._updatedSources[q],de.fire(new i.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:q})),de.setEventedParent(null),de.clearTiles(),de.onRemove&&de.onRemove(this.map),this._changed=!0},D.prototype.setGeoJSONSourceData=function(q,K){this._checkLoaded();var de=this.sourceCaches[q].getSource();de.setData(K),this._changed=!0},D.prototype.getSource=function(q){return this.sourceCaches[q]&&this.sourceCaches[q].getSource()},D.prototype.addLayer=function(q,K,de){de===void 0&&(de={}),this._checkLoaded();var ne=q.id;if(this.getLayer(ne)){this.fire(new i.ErrorEvent(new Error('Layer with id \"'+ne+'\" already exists on this map')));return}var we;if(q.type===\"custom\"){if(pl(this,i.validateCustomStyleLayer(q)))return;we=i.createStyleLayer(q)}else{if(typeof q.source==\"object\"&&(this.addSource(ne,q.source),q=i.clone$1(q),q=i.extend(q,{source:ne})),this._validate(i.validateStyle.layer,\"layers.\"+ne,q,{arrayIndex:-1},de))return;we=i.createStyleLayer(q),this._validateLayer(we),we.setEventedParent(this,{layer:{id:ne}}),this._serializedLayers[we.id]=we.serialize()}var Ue=K?this._order.indexOf(K):this._order.length;if(K&&Ue===-1){this.fire(new i.ErrorEvent(new Error('Layer with id \"'+K+'\" does not exist on this map.')));return}if(this._order.splice(Ue,0,ne),this._layerOrderChanged=!0,this._layers[ne]=we,this._removedLayers[ne]&&we.source&&we.type!==\"custom\"){var ft=this._removedLayers[ne];delete this._removedLayers[ne],ft.type!==we.type?this._updatedSources[we.source]=\"clear\":(this._updatedSources[we.source]=\"reload\",this.sourceCaches[we.source].pause())}this._updateLayer(we),we.onAdd&&we.onAdd(this.map)},D.prototype.moveLayer=function(q,K){this._checkLoaded(),this._changed=!0;var de=this._layers[q];if(!de){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot be moved.\")));return}if(q!==K){var ne=this._order.indexOf(q);this._order.splice(ne,1);var we=K?this._order.indexOf(K):this._order.length;if(K&&we===-1){this.fire(new i.ErrorEvent(new Error('Layer with id \"'+K+'\" does not exist on this map.')));return}this._order.splice(we,0,q),this._layerOrderChanged=!0}},D.prototype.removeLayer=function(q){this._checkLoaded();var K=this._layers[q];if(!K){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot be removed.\")));return}K.setEventedParent(null);var de=this._order.indexOf(q);this._order.splice(de,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[q]=K,delete this._layers[q],delete this._serializedLayers[q],delete this._updatedLayers[q],delete this._updatedPaintProps[q],K.onRemove&&K.onRemove(this.map)},D.prototype.getLayer=function(q){return this._layers[q]},D.prototype.hasLayer=function(q){return q in this._layers},D.prototype.setLayerZoomRange=function(q,K,de){this._checkLoaded();var ne=this.getLayer(q);if(!ne){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot have zoom extent.\")));return}ne.minzoom===K&&ne.maxzoom===de||(K!=null&&(ne.minzoom=K),de!=null&&(ne.maxzoom=de),this._updateLayer(ne))},D.prototype.setFilter=function(q,K,de){de===void 0&&(de={}),this._checkLoaded();var ne=this.getLayer(q);if(!ne){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot be filtered.\")));return}if(!i.deepEqual(ne.filter,K)){if(K==null){ne.filter=void 0,this._updateLayer(ne);return}this._validate(i.validateStyle.filter,\"layers.\"+ne.id+\".filter\",K,null,de)||(ne.filter=i.clone$1(K),this._updateLayer(ne))}},D.prototype.getFilter=function(q){return i.clone$1(this.getLayer(q).filter)},D.prototype.setLayoutProperty=function(q,K,de,ne){ne===void 0&&(ne={}),this._checkLoaded();var we=this.getLayer(q);if(!we){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot be styled.\")));return}i.deepEqual(we.getLayoutProperty(K),de)||(we.setLayoutProperty(K,de,ne),this._updateLayer(we))},D.prototype.getLayoutProperty=function(q,K){var de=this.getLayer(q);if(!de){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style.\")));return}return de.getLayoutProperty(K)},D.prototype.setPaintProperty=function(q,K,de,ne){ne===void 0&&(ne={}),this._checkLoaded();var we=this.getLayer(q);if(!we){this.fire(new i.ErrorEvent(new Error(\"The layer '\"+q+\"' does not exist in the map's style and cannot be styled.\")));return}if(!i.deepEqual(we.getPaintProperty(K),de)){var Ue=we.setPaintProperty(K,de,ne);Ue&&this._updateLayer(we),this._changed=!0,this._updatedPaintProps[q]=!0}},D.prototype.getPaintProperty=function(q,K){return this.getLayer(q).getPaintProperty(K)},D.prototype.setFeatureState=function(q,K){this._checkLoaded();var de=q.source,ne=q.sourceLayer,we=this.sourceCaches[de];if(we===void 0){this.fire(new i.ErrorEvent(new Error(\"The source '\"+de+\"' does not exist in the map's style.\")));return}var Ue=we.getSource().type;if(Ue===\"geojson\"&&ne){this.fire(new i.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\")));return}if(Ue===\"vector\"&&!ne){this.fire(new i.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")));return}q.id===void 0&&this.fire(new i.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),we.setFeatureState(ne,q.id,K)},D.prototype.removeFeatureState=function(q,K){this._checkLoaded();var de=q.source,ne=this.sourceCaches[de];if(ne===void 0){this.fire(new i.ErrorEvent(new Error(\"The source '\"+de+\"' does not exist in the map's style.\")));return}var we=ne.getSource().type,Ue=we===\"vector\"?q.sourceLayer:void 0;if(we===\"vector\"&&!Ue){this.fire(new i.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")));return}if(K&&typeof q.id!=\"string\"&&typeof q.id!=\"number\"){this.fire(new i.ErrorEvent(new Error(\"A feature id is required to remove its specific state property.\")));return}ne.removeFeatureState(Ue,q.id,K)},D.prototype.getFeatureState=function(q){this._checkLoaded();var K=q.source,de=q.sourceLayer,ne=this.sourceCaches[K];if(ne===void 0){this.fire(new i.ErrorEvent(new Error(\"The source '\"+K+\"' does not exist in the map's style.\")));return}var we=ne.getSource().type;if(we===\"vector\"&&!de){this.fire(new i.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")));return}return q.id===void 0&&this.fire(new i.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),ne.getFeatureState(de,q.id)},D.prototype.getTransition=function(){return i.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},D.prototype.serialize=function(){return i.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:i.mapObject(this.sourceCaches,function(q){return q.serialize()}),layers:this._serializeLayers(this._order)},function(q){return q!==void 0})},D.prototype._updateLayer=function(q){this._updatedLayers[q.id]=!0,q.source&&!this._updatedSources[q.source]&&this.sourceCaches[q.source].getSource().type!==\"raster\"&&(this._updatedSources[q.source]=\"reload\",this.sourceCaches[q.source].pause()),this._changed=!0},D.prototype._flattenAndSortRenderedFeatures=function(q){for(var K=this,de=function(Ti){return K._layers[Ti].type===\"fill-extrusion\"},ne={},we=[],Ue=this._order.length-1;Ue>=0;Ue--){var ft=this._order[Ue];if(de(ft)){ne[ft]=Ue;for(var Xt=0,hr=q;Xt<hr.length;Xt+=1){var qt=hr[Xt],Ve=qt[ft];if(Ve)for(var Qe=0,at=Ve;Qe<at.length;Qe+=1){var Ct=at[Qe];we.push(Ct)}}}}we.sort(function(Ti,gn){return gn.intersectionZ-Ti.intersectionZ});for(var Ot=[],Rt=this._order.length-1;Rt>=0;Rt--){var Bt=this._order[Rt];if(de(Bt))for(var Dt=we.length-1;Dt>=0;Dt--){var yt=we[Dt].feature;if(ne[yt.layer.id]<Rt)break;Ot.push(yt),we.pop()}else for(var Pt=0,ht=q;Pt<ht.length;Pt+=1){var ur=ht[Pt],br=ur[Bt];if(br)for(var Ur=0,Di=br;Ur<Di.length;Ur+=1){var fi=Di[Ur];Ot.push(fi.feature)}}}return Ot},D.prototype.queryRenderedFeatures=function(q,K,de){K&&K.filter&&this._validate(i.validateStyle.filter,\"queryRenderedFeatures.filter\",K.filter,null,K);var ne={};if(K&&K.layers){if(!Array.isArray(K.layers))return this.fire(new i.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var we=0,Ue=K.layers;we<Ue.length;we+=1){var ft=Ue[we],Xt=this._layers[ft];if(!Xt)return this.fire(new i.ErrorEvent(new Error(\"The layer '\"+ft+\"' does not exist in the map's style and cannot be queried for features.\"))),[];ne[Xt.source]=!0}}var hr=[];K.availableImages=this._availableImages;for(var qt in this.sourceCaches)K.layers&&!ne[qt]||hr.push(ce(this.sourceCaches[qt],this._layers,this._serializedLayers,q,K,de));return this.placement&&hr.push(Ze(this._layers,this._serializedLayers,this.sourceCaches,q,K,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(hr)},D.prototype.querySourceFeatures=function(q,K){K&&K.filter&&this._validate(i.validateStyle.filter,\"querySourceFeatures.filter\",K.filter,null,K);var de=this.sourceCaches[q];return de?ut(de,K):[]},D.prototype.addSourceType=function(q,K,de){if(D.getSourceType(q))return de(new Error('A source type called \"'+q+'\" already exists.'));if(D.setSourceType(q,K),!K.workerSourceURL)return de(null,null);this.dispatcher.broadcast(\"loadWorkerSource\",{name:q,url:K.workerSourceURL},de)},D.prototype.getLight=function(){return this.light.getLight()},D.prototype.setLight=function(q,K){K===void 0&&(K={}),this._checkLoaded();var de=this.light.getLight(),ne=!1;for(var we in q)if(!i.deepEqual(q[we],de[we])){ne=!0;break}if(ne){var Ue={now:i.browser.now(),transition:i.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(q,K),this.light.updateTransitions(Ue)}},D.prototype._validate=function(q,K,de,ne,we){return we===void 0&&(we={}),we&&we.validate===!1?!1:pl(this,q.call(i.validateStyle,i.extend({key:K,style:this.serialize(),value:de,styleSpec:i.styleSpec},ne)))},D.prototype._remove=function(){this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),i.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback);for(var q in this._layers){var K=this._layers[q];K.setEventedParent(null)}for(var de in this.sourceCaches)this.sourceCaches[de].clearTiles(),this.sourceCaches[de].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},D.prototype._clearSource=function(q){this.sourceCaches[q].clearTiles()},D.prototype._reloadSource=function(q){this.sourceCaches[q].resume(),this.sourceCaches[q].reload()},D.prototype._updateSources=function(q){for(var K in this.sourceCaches)this.sourceCaches[K].update(q)},D.prototype._generateCollisionBoxes=function(){for(var q in this.sourceCaches)this._reloadSource(q)},D.prototype._updatePlacement=function(q,K,de,ne,we){we===void 0&&(we=!1);for(var Ue=!1,ft=!1,Xt={},hr=0,qt=this._order;hr<qt.length;hr+=1){var Ve=qt[hr],Qe=this._layers[Ve];if(Qe.type===\"symbol\"){if(!Xt[Qe.source]){var at=this.sourceCaches[Qe.source];Xt[Qe.source]=at.getRenderableIds(!0).map(function(Pt){return at.getTileByID(Pt)}).sort(function(Pt,ht){return ht.tileID.overscaledZ-Pt.tileID.overscaledZ||(Pt.tileID.isLessThan(ht.tileID)?-1:1)})}var Ct=this.crossTileSymbolIndex.addLayer(Qe,Xt[Qe.source],q.center.lng);Ue=Ue||Ct}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),we=we||this._layerOrderChanged||de===0,(we||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(i.browser.now(),q.zoom))&&(this.pauseablePlacement=new qo(q,this._order,we,K,de,ne,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,Xt),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(i.browser.now()),ft=!0),Ue&&this.pauseablePlacement.placement.setStale()),ft||Ue)for(var Ot=0,Rt=this._order;Ot<Rt.length;Ot+=1){var Bt=Rt[Ot],Dt=this._layers[Bt];Dt.type===\"symbol\"&&this.placement.updateLayerOpacities(Dt,Xt[Dt.source])}var yt=!this.pauseablePlacement.isDone()||this.placement.hasTransitions(i.browser.now());return yt},D.prototype._releaseSymbolFadeTiles=function(){for(var q in this.sourceCaches)this.sourceCaches[q].releaseSymbolFadeTiles()},D.prototype.getImages=function(q,K,de){this.imageManager.getImages(K.icons,de),this._updateTilesForChangedImages();var ne=this.sourceCaches[K.source];ne&&ne.setDependencies(K.tileID.key,K.type,K.icons)},D.prototype.getGlyphs=function(q,K,de){this.glyphManager.getGlyphs(K.stacks,de)},D.prototype.getResource=function(q,K,de){return i.makeRequest(K,de)},D}(i.Evented);yu.getSourceType=Fe,yu.setSourceType=Pe,yu.registerForPluginStateChange=i.registerForPluginStateChange;var oc=i.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Cf=`#ifdef GL_ES\n",
+       "precision mediump float;\n",
+       "#else\n",
+       "#if !defined(lowp)\n",
+       "#define lowp\n",
+       "#endif\n",
+       "#if !defined(mediump)\n",
+       "#define mediump\n",
+       "#endif\n",
+       "#if !defined(highp)\n",
+       "#define highp\n",
+       "#endif\n",
+       "#endif`,sc=`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#else\n",
+       "#if !defined(lowp)\n",
+       "#define lowp\n",
+       "#endif\n",
+       "#if !defined(mediump)\n",
+       "#define mediump\n",
+       "#endif\n",
+       "#if !defined(highp)\n",
+       "#define highp\n",
+       "#endif\n",
+       "#endif\n",
+       "vec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\n",
+       ");}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}`,Vh=`uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Lf=\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\",cs=`uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,nf=\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\",Vf=`varying vec3 v_data;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define highp vec4 stroke_color\n",
+       "#pragma mapbox: define mediump float stroke_width\n",
+       "#pragma mapbox: define lowp float stroke_opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize highp vec4 stroke_color\n",
+       "#pragma mapbox: initialize mediump float stroke_width\n",
+       "#pragma mapbox: initialize lowp float stroke_opacity\n",
+       "vec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Jl=`uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define highp vec4 stroke_color\n",
+       "#pragma mapbox: define mediump float stroke_width\n",
+       "#pragma mapbox: define lowp float stroke_opacity\n",
+       "void main(void) {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize highp vec4 stroke_color\n",
+       "#pragma mapbox: initialize mediump float stroke_width\n",
+       "#pragma mapbox: initialize lowp float stroke_opacity\n",
+       "vec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}`,fl=\"void main() {gl_FragColor=vec4(1.0);}\",lc=\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\",Fu=`uniform highp float u_intensity;varying vec2 v_extrude;\n",
+       "#pragma mapbox: define highp float weight\n",
+       "#define GAUSS_COEF 0.3989422804014327\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp float weight\n",
+       "float d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Es=`uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\n",
+       "#pragma mapbox: define highp float weight\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "const highp float ZERO=1.0/255.0/16.0;\n",
+       "#define GAUSS_COEF 0.3989422804014327\n",
+       "void main(void) {\n",
+       "#pragma mapbox: initialize highp float weight\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "vec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}`,Hs=`uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(0.0);\n",
+       "#endif\n",
+       "}`,Go=\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\",ps=\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",uc=\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\",xl=\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",Gu=\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\",qs=\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",ad=\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\",Po=`#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_FragColor=color*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,od=`attribute vec2 a_pos;uniform mat4 u_matrix;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_Position=u_matrix*vec4(a_pos,0,1);}`,Yo=`varying vec2 v_pos;\n",
+       "#pragma mapbox: define highp vec4 outline_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 outline_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Pa=`attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n",
+       "#pragma mapbox: define highp vec4 outline_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 outline_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`,af=`uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Hu=`uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`,bl=`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Gf=`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}`,Ic=`varying vec4 v_color;void main() {gl_FragColor=v_color;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,yf=`uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\n",
+       "#pragma mapbox: define highp float base\n",
+       "#pragma mapbox: define highp float height\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp float base\n",
+       "#pragma mapbox: initialize highp float height\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "vec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`,Bl=`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n",
+       "#pragma mapbox: define lowp float base\n",
+       "#pragma mapbox: define lowp float height\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float base\n",
+       "#pragma mapbox: initialize lowp float height\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,wh=`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n",
+       "#pragma mapbox: define lowp float base\n",
+       "#pragma mapbox: define lowp float height\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float base\n",
+       "#pragma mapbox: initialize lowp float height\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n",
+       "? a_pos\n",
+       ": vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`,Qf=`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#endif\n",
+       "uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,_f=\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\",Yc=`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n",
+       "#define PI 3.141592653589793\n",
+       "void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,eh=\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\",th=`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,ju=`\n",
+       "#define scale 0.015873016\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,Hf=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,cc=`\n",
+       "#define scale 0.015873016\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,of=`uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Nl=`\n",
+       "#define scale 0.015873016\n",
+       "#define LINE_DISTANCE_SCALE 2.0\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`,Kc=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Rc=`\n",
+       "#define scale 0.015873016\n",
+       "#define LINE_DISTANCE_SCALE 2.0\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`,gs=`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,jf=\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\",Gh=`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,rh=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}`,sf=`#define SDF_PX 8.0\n",
+       "uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,Th=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`,Mu=`#define SDF_PX 8.0\n",
+       "#define SDF 1.0\n",
+       "#define ICON 0.0\n",
+       "uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,ih=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`,js=Us(Cf,sc),Eu=Us(Vh,Lf),Dc=Us(cs,nf),ks=Us(Vf,Jl),bc=Us(fl,lc),hu=Us(Fu,Es),_u=Us(Hs,Go),nl=Us(ps,uc),nh=Us(xl,Gu),Ah=Us(qs,ad),zu=Us(Po,od),Fc=Us(Yo,Pa),wc=Us(af,Hu),bd=Us(bl,Gf),xf=Us(Ic,yf),Pf=Us(Bl,wh),Ou=Us(Qf,_f),bf=Us(Yc,eh),jl=Us(th,ju),lf=Us(Hf,cc),Hh=Us(of,Nl),If=Us(Kc,Rc),Cs=Us(gs,jf),du=Us(Gh,rh),ku=Us(sf,Th),Wf=Us(Mu,ih);function Us(Y,D){var J=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,q=D.match(/attribute ([\\w]+) ([\\w]+)/g),K=Y.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),de=D.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),ne=de?de.concat(K):K,we={};return Y=Y.replace(J,function(Ue,ft,Xt,hr,qt){return we[qt]=!0,ft===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "varying `+Xt+\" \"+hr+\" \"+qt+`;\n",
+       "#else\n",
+       "uniform `+Xt+\" \"+hr+\" u_\"+qt+`;\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifdef HAS_UNIFORM_u_`+qt+`\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = u_\"+qt+`;\n",
+       "#endif\n",
+       "`}),D=D.replace(J,function(Ue,ft,Xt,hr,qt){var Ve=hr===\"float\"?\"vec2\":\"vec4\",Qe=qt.match(/color/)?\"color\":Ve;return we[qt]?ft===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "uniform lowp float u_`+qt+`_t;\n",
+       "attribute `+Xt+\" \"+Ve+\" a_\"+qt+`;\n",
+       "varying `+Xt+\" \"+hr+\" \"+qt+`;\n",
+       "#else\n",
+       "uniform `+Xt+\" \"+hr+\" u_\"+qt+`;\n",
+       "#endif\n",
+       "`:Qe===\"vec4\"?`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "    `+qt+\" = a_\"+qt+`;\n",
+       "#else\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = u_\"+qt+`;\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "    `+qt+\" = unpack_mix_\"+Qe+\"(a_\"+qt+\", u_\"+qt+`_t);\n",
+       "#else\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = u_\"+qt+`;\n",
+       "#endif\n",
+       "`:ft===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "uniform lowp float u_`+qt+`_t;\n",
+       "attribute `+Xt+\" \"+Ve+\" a_\"+qt+`;\n",
+       "#else\n",
+       "uniform `+Xt+\" \"+hr+\" u_\"+qt+`;\n",
+       "#endif\n",
+       "`:Qe===\"vec4\"?`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = a_\"+qt+`;\n",
+       "#else\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = u_\"+qt+`;\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifndef HAS_UNIFORM_u_`+qt+`\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = unpack_mix_\"+Qe+\"(a_\"+qt+\", u_\"+qt+`_t);\n",
+       "#else\n",
+       "    `+Xt+\" \"+hr+\" \"+qt+\" = u_\"+qt+`;\n",
+       "#endif\n",
+       "`}),{fragmentSource:Y,vertexSource:D,staticAttributes:q,staticUniforms:ne}}var wf=Object.freeze({__proto__:null,prelude:js,background:Eu,backgroundPattern:Dc,circle:ks,clippingMask:bc,heatmap:hu,heatmapTexture:_u,collisionBox:nl,collisionCircle:nh,debug:Ah,fill:zu,fillOutline:Fc,fillOutlinePattern:wc,fillPattern:bd,fillExtrusion:xf,fillExtrusionPattern:Pf,hillshadePrepare:Ou,hillshade:bf,line:jl,lineGradient:lf,linePattern:Hh,lineSDF:If,raster:Cs,symbolIcon:du,symbolSDF:ku,symbolTextAndIcon:Wf}),zc=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};zc.prototype.bind=function(D,J,q,K,de,ne,we,Ue){this.context=D;for(var ft=this.boundPaintVertexBuffers.length!==K.length,Xt=0;!ft&&Xt<K.length;Xt++)this.boundPaintVertexBuffers[Xt]!==K[Xt]&&(ft=!0);var hr=!this.vao||this.boundProgram!==J||this.boundLayoutVertexBuffer!==q||ft||this.boundIndexBuffer!==de||this.boundVertexOffset!==ne||this.boundDynamicVertexBuffer!==we||this.boundDynamicVertexBuffer2!==Ue;!D.extVertexArrayObject||hr?this.freshBind(J,q,K,de,ne,we,Ue):(D.bindVertexArrayOES.set(this.vao),we&&we.bind(),de&&de.dynamicDraw&&de.bind(),Ue&&Ue.bind())},zc.prototype.freshBind=function(D,J,q,K,de,ne,we){var Ue,ft=D.numAttributes,Xt=this.context,hr=Xt.gl;if(Xt.extVertexArrayObject)this.vao&&this.destroy(),this.vao=Xt.extVertexArrayObject.createVertexArrayOES(),Xt.bindVertexArrayOES.set(this.vao),Ue=0,this.boundProgram=D,this.boundLayoutVertexBuffer=J,this.boundPaintVertexBuffers=q,this.boundIndexBuffer=K,this.boundVertexOffset=de,this.boundDynamicVertexBuffer=ne,this.boundDynamicVertexBuffer2=we;else{Ue=Xt.currentNumAttributes||0;for(var qt=ft;qt<Ue;qt++)hr.disableVertexAttribArray(qt)}J.enableAttributes(hr,D);for(var Ve=0,Qe=q;Ve<Qe.length;Ve+=1){var at=Qe[Ve];at.enableAttributes(hr,D)}ne&&ne.enableAttributes(hr,D),we&&we.enableAttributes(hr,D),J.bind(),J.setVertexAttribPointers(hr,D,de);for(var Ct=0,Ot=q;Ct<Ot.length;Ct+=1){var Rt=Ot[Ct];Rt.bind(),Rt.setVertexAttribPointers(hr,D,de)}ne&&(ne.bind(),ne.setVertexAttribPointers(hr,D,de)),K&&K.bind(),we&&(we.bind(),we.setVertexAttribPointers(hr,D,de)),Xt.currentNumAttributes=ft},zc.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};function Wu(Y){for(var D=[],J=0;J<Y.length;J++)if(Y[J]!==null){var q=Y[J].split(\" \");D.push(q.pop())}return D}var Rf=function(D,J,q,K,de,ne){var we=D.gl;this.program=we.createProgram();for(var Ue=Wu(q.staticAttributes),ft=K?K.getBinderAttributes():[],Xt=Ue.concat(ft),hr=q.staticUniforms?Wu(q.staticUniforms):[],qt=K?K.getBinderUniforms():[],Ve=hr.concat(qt),Qe=[],at=0,Ct=Ve;at<Ct.length;at+=1){var Ot=Ct[at];Qe.indexOf(Ot)<0&&Qe.push(Ot)}var Rt=K?K.defines():[];ne&&Rt.push(\"#define OVERDRAW_INSPECTOR;\");var Bt=Rt.concat(js.fragmentSource,q.fragmentSource).join(`\n",
+       "`),Dt=Rt.concat(js.vertexSource,q.vertexSource).join(`\n",
+       "`),yt=we.createShader(we.FRAGMENT_SHADER);if(we.isContextLost()){this.failedToCreate=!0;return}we.shaderSource(yt,Bt),we.compileShader(yt),we.attachShader(this.program,yt);var Pt=we.createShader(we.VERTEX_SHADER);if(we.isContextLost()){this.failedToCreate=!0;return}we.shaderSource(Pt,Dt),we.compileShader(Pt),we.attachShader(this.program,Pt),this.attributes={};var ht={};this.numAttributes=Xt.length;for(var ur=0;ur<this.numAttributes;ur++)Xt[ur]&&(we.bindAttribLocation(this.program,ur,Xt[ur]),this.attributes[Xt[ur]]=ur);we.linkProgram(this.program),we.deleteShader(Pt),we.deleteShader(yt);for(var br=0;br<Qe.length;br++){var Ur=Qe[br];if(Ur&&!ht[Ur]){var Di=we.getUniformLocation(this.program,Ur);Di&&(ht[Ur]=Di)}}this.fixedUniforms=de(D,ht),this.binderUniforms=K?K.getUniforms(D,ht):[]};Rf.prototype.draw=function(D,J,q,K,de,ne,we,Ue,ft,Xt,hr,qt,Ve,Qe,at,Ct){var Ot,Rt=D.gl;if(!this.failedToCreate){D.program.set(this.program),D.setDepthMode(q),D.setStencilMode(K),D.setColorMode(de),D.setCullFace(ne);for(var Bt in this.fixedUniforms)this.fixedUniforms[Bt].set(we[Bt]);Qe&&Qe.setUniforms(D,this.binderUniforms,qt,{zoom:Ve});for(var Dt=(Ot={},Ot[Rt.LINES]=2,Ot[Rt.TRIANGLES]=3,Ot[Rt.LINE_STRIP]=1,Ot)[J],yt=0,Pt=hr.get();yt<Pt.length;yt+=1){var ht=Pt[yt],ur=ht.vaos||(ht.vaos={}),br=ur[Ue]||(ur[Ue]=new zc);br.bind(D,this,ft,Qe?Qe.getPaintVertexBuffers():[],Xt,ht.vertexOffset,at,Ct),Rt.drawElements(J,ht.primitiveLength*Dt,Rt.UNSIGNED_SHORT,ht.primitiveOffset*Dt*2)}}};function Xu(Y,D,J){var q=1/As(J,1,D.transform.tileZoom),K=Math.pow(2,J.tileID.overscaledZ),de=J.tileSize*Math.pow(2,D.transform.tileZoom)/K,ne=de*(J.tileID.canonical.x+J.tileID.wrap*K),we=de*J.tileID.canonical.y;return{u_image:0,u_texsize:J.imageAtlasTexture.size,u_scale:[q,Y.fromScale,Y.toScale],u_fade:Y.t,u_pixel_coord_upper:[ne>>16,we>>16],u_pixel_coord_lower:[ne&65535,we&65535]}}function uf(Y,D,J,q){var K=J.imageManager.getPattern(Y.from.toString()),de=J.imageManager.getPattern(Y.to.toString()),ne=J.imageManager.getPixelSize(),we=ne.width,Ue=ne.height,ft=Math.pow(2,q.tileID.overscaledZ),Xt=q.tileSize*Math.pow(2,J.transform.tileZoom)/ft,hr=Xt*(q.tileID.canonical.x+q.tileID.wrap*ft),qt=Xt*q.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:K.tl,u_pattern_br_a:K.br,u_pattern_tl_b:de.tl,u_pattern_br_b:de.br,u_texsize:[we,Ue],u_mix:D.t,u_pattern_size_a:K.displaySize,u_pattern_size_b:de.displaySize,u_scale_a:D.fromScale,u_scale_b:D.toScale,u_tile_units_to_pixels:1/As(q,1,J.transform.tileZoom),u_pixel_coord_upper:[hr>>16,qt>>16],u_pixel_coord_lower:[hr&65535,qt&65535]}}var Xf=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_lightpos:new i.Uniform3f(Y,D.u_lightpos),u_lightintensity:new i.Uniform1f(Y,D.u_lightintensity),u_lightcolor:new i.Uniform3f(Y,D.u_lightcolor),u_vertical_gradient:new i.Uniform1f(Y,D.u_vertical_gradient),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},Wl=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_lightpos:new i.Uniform3f(Y,D.u_lightpos),u_lightintensity:new i.Uniform1f(Y,D.u_lightintensity),u_lightcolor:new i.Uniform3f(Y,D.u_lightcolor),u_vertical_gradient:new i.Uniform1f(Y,D.u_vertical_gradient),u_height_factor:new i.Uniform1f(Y,D.u_height_factor),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},ah=function(Y,D,J,q){var K=D.style.light,de=K.properties.get(\"position\"),ne=[de.x,de.y,de.z],we=i.create$1();K.properties.get(\"anchor\")===\"viewport\"&&i.fromRotation(we,-D.transform.angle),i.transformMat3(ne,ne,we);var Ue=K.properties.get(\"color\");return{u_matrix:Y,u_lightpos:ne,u_lightintensity:K.properties.get(\"intensity\"),u_lightcolor:[Ue.r,Ue.g,Ue.b],u_vertical_gradient:+J,u_opacity:q}},Zu=function(Y,D,J,q,K,de,ne){return i.extend(ah(Y,D,J,q),Xu(de,D,ne),{u_height_factor:-Math.pow(2,K.overscaledZ)/ne.tileSize/8})},Oc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Tc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},wl=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world)}},vu=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},qc=function(Y){return{u_matrix:Y}},cf=function(Y,D,J,q){return i.extend(qc(Y),Xu(J,D,q))},fc=function(Y,D){return{u_matrix:Y,u_world:D}},Bc=function(Y,D,J,q,K){return i.extend(cf(Y,D,J,q),{u_world:K})},At=function(Y,D){return{u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_scale_with_map:new i.Uniform1i(Y,D.u_scale_with_map),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_extrude_scale:new i.Uniform2f(Y,D.u_extrude_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Wt=function(Y,D,J,q){var K=Y.transform,de,ne;if(q.paint.get(\"circle-pitch-alignment\")===\"map\"){var we=As(J,1,K.zoom);de=!0,ne=[we,we]}else de=!1,ne=K.pixelsToGLUnits;return{u_camera_to_center_distance:K.cameraToCenterDistance,u_scale_with_map:+(q.paint.get(\"circle-pitch-scale\")===\"map\"),u_matrix:Y.translatePosMatrix(D.posMatrix,J,q.paint.get(\"circle-translate\"),q.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+de,u_device_pixel_ratio:i.browser.devicePixelRatio,u_extrude_scale:ne}},Cr=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pixels_to_tile_units:new i.Uniform1f(Y,D.u_pixels_to_tile_units),u_extrude_scale:new i.Uniform2f(Y,D.u_extrude_scale),u_overscale_factor:new i.Uniform1f(Y,D.u_overscale_factor)}},Ar=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_inv_matrix:new i.UniformMatrix4f(Y,D.u_inv_matrix),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_viewport_size:new i.Uniform2f(Y,D.u_viewport_size)}},Kr=function(Y,D,J){var q=As(J,1,D.zoom),K=Math.pow(2,D.zoom-J.tileID.overscaledZ),de=J.tileID.overscaleFactor();return{u_matrix:Y,u_camera_to_center_distance:D.cameraToCenterDistance,u_pixels_to_tile_units:q,u_extrude_scale:[D.pixelsToGLUnits[0]/(q*K),D.pixelsToGLUnits[1]/(q*K)],u_overscale_factor:de}},ki=function(Y,D,J){return{u_matrix:Y,u_inv_matrix:D,u_camera_to_center_distance:J.cameraToCenterDistance,u_viewport_size:[J.width,J.height]}},Xi=function(Y,D){return{u_color:new i.UniformColor(Y,D.u_color),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_overlay:new i.Uniform1i(Y,D.u_overlay),u_overlay_scale:new i.Uniform1f(Y,D.u_overlay_scale)}},dn=function(Y,D,J){return J===void 0&&(J=1),{u_matrix:Y,u_color:D,u_overlay:0,u_overlay_scale:J}},wn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Nn=function(Y){return{u_matrix:Y}},Yi=function(Y,D){return{u_extrude_scale:new i.Uniform1f(Y,D.u_extrude_scale),u_intensity:new i.Uniform1f(Y,D.u_intensity),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Qi=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world),u_image:new i.Uniform1i(Y,D.u_image),u_color_ramp:new i.Uniform1i(Y,D.u_color_ramp),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},on=function(Y,D,J,q){return{u_matrix:Y,u_extrude_scale:As(D,1,J),u_intensity:q}},Fi=function(Y,D,J,q){var K=i.create();i.ortho(K,0,Y.width,Y.height,0,0,1);var de=Y.context.gl;return{u_matrix:K,u_world:[de.drawingBufferWidth,de.drawingBufferHeight],u_image:J,u_color_ramp:q,u_opacity:D.paint.get(\"heatmap-opacity\")}},$n=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_latrange:new i.Uniform2f(Y,D.u_latrange),u_light:new i.Uniform2f(Y,D.u_light),u_shadow:new i.UniformColor(Y,D.u_shadow),u_highlight:new i.UniformColor(Y,D.u_highlight),u_accent:new i.UniformColor(Y,D.u_accent)}},Ca=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_dimension:new i.Uniform2f(Y,D.u_dimension),u_zoom:new i.Uniform1f(Y,D.u_zoom),u_unpack:new i.Uniform4f(Y,D.u_unpack)}},Ra=function(Y,D,J){var q=J.paint.get(\"hillshade-shadow-color\"),K=J.paint.get(\"hillshade-highlight-color\"),de=J.paint.get(\"hillshade-accent-color\"),ne=J.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);J.paint.get(\"hillshade-illumination-anchor\")===\"viewport\"&&(ne-=Y.transform.angle);var we=!Y.options.moving;return{u_matrix:Y.transform.calculatePosMatrix(D.tileID.toUnwrapped(),we),u_image:0,u_latrange:Na(Y,D.tileID),u_light:[J.paint.get(\"hillshade-exaggeration\"),ne],u_shadow:q,u_highlight:K,u_accent:de}},La=function(Y,D){var J=D.stride,q=i.create();return i.ortho(q,0,i.EXTENT,-i.EXTENT,0,0,1),i.translate(q,q,[0,-i.EXTENT,0]),{u_matrix:q,u_image:1,u_dimension:[J,J],u_zoom:Y.overscaledZ,u_unpack:D.getUnpackVector()}};function Na(Y,D){var J=Math.pow(2,D.canonical.z),q=D.canonical.y;return[new i.MercatorCoordinate(0,q/J).toLngLat().lat,new i.MercatorCoordinate(0,(q+1)/J).toLngLat().lat]}var Yn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels)}},Dn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_image:new i.Uniform1i(Y,D.u_image),u_image_height:new i.Uniform1f(Y,D.u_image_height)}},Ka=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_image:new i.Uniform1i(Y,D.u_image),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},bo=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_patternscale_a:new i.Uniform2f(Y,D.u_patternscale_a),u_patternscale_b:new i.Uniform2f(Y,D.u_patternscale_b),u_sdfgamma:new i.Uniform1f(Y,D.u_sdfgamma),u_image:new i.Uniform1i(Y,D.u_image),u_tex_y_a:new i.Uniform1f(Y,D.u_tex_y_a),u_tex_y_b:new i.Uniform1f(Y,D.u_tex_y_b),u_mix:new i.Uniform1f(Y,D.u_mix)}},Xo=function(Y,D,J){var q=Y.transform;return{u_matrix:ml(Y,D,J),u_ratio:1/As(D,1,q.zoom),u_device_pixel_ratio:i.browser.devicePixelRatio,u_units_to_pixels:[1/q.pixelsToGLUnits[0],1/q.pixelsToGLUnits[1]]}},Ss=function(Y,D,J,q){return i.extend(Xo(Y,D,J),{u_image:0,u_image_height:q})},as=function(Y,D,J,q){var K=Y.transform,de=Ho(D,K);return{u_matrix:ml(Y,D,J),u_texsize:D.imageAtlasTexture.size,u_ratio:1/As(D,1,K.zoom),u_device_pixel_ratio:i.browser.devicePixelRatio,u_image:0,u_scale:[de,q.fromScale,q.toScale],u_fade:q.t,u_units_to_pixels:[1/K.pixelsToGLUnits[0],1/K.pixelsToGLUnits[1]]}},ws=function(Y,D,J,q,K){var de=Y.transform,ne=Y.lineAtlas,we=Ho(D,de),Ue=J.layout.get(\"line-cap\")===\"round\",ft=ne.getDash(q.from,Ue),Xt=ne.getDash(q.to,Ue),hr=ft.width*K.fromScale,qt=Xt.width*K.toScale;return i.extend(Xo(Y,D,J),{u_patternscale_a:[we/hr,-ft.height/2],u_patternscale_b:[we/qt,-Xt.height/2],u_sdfgamma:ne.width/(Math.min(hr,qt)*256*i.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:ft.y,u_tex_y_b:Xt.y,u_mix:K.t})};function Ho(Y,D){return 1/As(Y,1,D.tileZoom)}function ml(Y,D,J){return Y.translatePosMatrix(D.tileID.posMatrix,D,J.paint.get(\"line-translate\"),J.paint.get(\"line-translate-anchor\"))}var Ws=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_tl_parent:new i.Uniform2f(Y,D.u_tl_parent),u_scale_parent:new i.Uniform1f(Y,D.u_scale_parent),u_buffer_scale:new i.Uniform1f(Y,D.u_buffer_scale),u_fade_t:new i.Uniform1f(Y,D.u_fade_t),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_image0:new i.Uniform1i(Y,D.u_image0),u_image1:new i.Uniform1i(Y,D.u_image1),u_brightness_low:new i.Uniform1f(Y,D.u_brightness_low),u_brightness_high:new i.Uniform1f(Y,D.u_brightness_high),u_saturation_factor:new i.Uniform1f(Y,D.u_saturation_factor),u_contrast_factor:new i.Uniform1f(Y,D.u_contrast_factor),u_spin_weights:new i.Uniform3f(Y,D.u_spin_weights)}},Ls=function(Y,D,J,q,K){return{u_matrix:Y,u_tl_parent:D,u_scale_parent:J,u_buffer_scale:1,u_fade_t:q.mix,u_opacity:q.opacity*K.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:K.paint.get(\"raster-brightness-min\"),u_brightness_high:K.paint.get(\"raster-brightness-max\"),u_saturation_factor:ys(K.paint.get(\"raster-saturation\")),u_contrast_factor:no(K.paint.get(\"raster-contrast\")),u_spin_weights:va(K.paint.get(\"raster-hue-rotate\"))}};function va(Y){Y*=Math.PI/180;var D=Math.sin(Y),J=Math.cos(Y);return[(2*J+1)/3,(-Math.sqrt(3)*D-J+1)/3,(Math.sqrt(3)*D-J+1)/3]}function no(Y){return Y>0?1/(1-Y):1+Y}function ys(Y){return Y>0?1-1/(1.001-Y):-Y}var rs=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texture:new i.Uniform1i(Y,D.u_texture)}},$l=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texture:new i.Uniform1i(Y,D.u_texture),u_gamma_scale:new i.Uniform1f(Y,D.u_gamma_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_is_halo:new i.Uniform1i(Y,D.u_is_halo)}},Cu=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texsize_icon:new i.Uniform2f(Y,D.u_texsize_icon),u_texture:new i.Uniform1i(Y,D.u_texture),u_texture_icon:new i.Uniform1i(Y,D.u_texture_icon),u_gamma_scale:new i.Uniform1f(Y,D.u_gamma_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_is_halo:new i.Uniform1i(Y,D.u_is_halo)}},Yu=function(Y,D,J,q,K,de,ne,we,Ue,ft){var Xt=K.transform;return{u_is_size_zoom_constant:+(Y===\"constant\"||Y===\"source\"),u_is_size_feature_constant:+(Y===\"constant\"||Y===\"camera\"),u_size_t:D?D.uSizeT:0,u_size:D?D.uSize:0,u_camera_to_center_distance:Xt.cameraToCenterDistance,u_pitch:Xt.pitch/360*2*Math.PI,u_rotate_symbol:+J,u_aspect_ratio:Xt.width/Xt.height,u_fade_change:K.options.fadeDuration?K.symbolFadeChange:1,u_matrix:de,u_label_plane_matrix:ne,u_coord_matrix:we,u_is_text:+Ue,u_pitch_with_map:+q,u_texsize:ft,u_texture:0}},Nc=function(Y,D,J,q,K,de,ne,we,Ue,ft,Xt){var hr=K.transform;return i.extend(Yu(Y,D,J,q,K,de,ne,we,Ue,ft),{u_gamma_scale:q?Math.cos(hr._pitch)*hr.cameraToCenterDistance:1,u_device_pixel_ratio:i.browser.devicePixelRatio,u_is_halo:+Xt})},pu=function(Y,D,J,q,K,de,ne,we,Ue,ft){return i.extend(Nc(Y,D,J,q,K,de,ne,we,!0,Ue,!0),{u_texsize_icon:ft,u_texture_icon:1})},Uc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_color:new i.UniformColor(Y,D.u_color)}},xu=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_image:new i.Uniform1i(Y,D.u_image),u_pattern_tl_a:new i.Uniform2f(Y,D.u_pattern_tl_a),u_pattern_br_a:new i.Uniform2f(Y,D.u_pattern_br_a),u_pattern_tl_b:new i.Uniform2f(Y,D.u_pattern_tl_b),u_pattern_br_b:new i.Uniform2f(Y,D.u_pattern_br_b),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_mix:new i.Uniform1f(Y,D.u_mix),u_pattern_size_a:new i.Uniform2f(Y,D.u_pattern_size_a),u_pattern_size_b:new i.Uniform2f(Y,D.u_pattern_size_b),u_scale_a:new i.Uniform1f(Y,D.u_scale_a),u_scale_b:new i.Uniform1f(Y,D.u_scale_b),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_tile_units_to_pixels:new i.Uniform1f(Y,D.u_tile_units_to_pixels)}},Ac=function(Y,D,J){return{u_matrix:Y,u_opacity:D,u_color:J}},Ua=function(Y,D,J,q,K,de){return i.extend(uf(q,de,J,K),{u_matrix:Y,u_opacity:D})},oo={fillExtrusion:Xf,fillExtrusionPattern:Wl,fill:Oc,fillPattern:Tc,fillOutline:wl,fillOutlinePattern:vu,circle:At,collisionBox:Cr,collisionCircle:Ar,debug:Xi,clippingMask:wn,heatmap:Yi,heatmapTexture:Qi,hillshade:$n,hillshadePrepare:Ca,line:Yn,lineGradient:Dn,linePattern:Ka,lineSDF:bo,raster:Ws,symbolIcon:rs,symbolSDF:$l,symbolTextAndIcon:Cu,background:Uc,backgroundPattern:xu},Vc;function hc(Y,D,J,q,K,de,ne){for(var we=Y.context,Ue=we.gl,ft=Y.useProgram(\"collisionBox\"),Xt=[],hr=0,qt=0,Ve=0;Ve<q.length;Ve++){var Qe=q[Ve],at=D.getTile(Qe),Ct=at.getBucket(J);if(Ct){var Ot=Qe.posMatrix;(K[0]!==0||K[1]!==0)&&(Ot=Y.translatePosMatrix(Qe.posMatrix,at,K,de));var Rt=ne?Ct.textCollisionBox:Ct.iconCollisionBox,Bt=Ct.collisionCircleArray;if(Bt.length>0){var Dt=i.create(),yt=Ot;i.mul(Dt,Ct.placementInvProjMatrix,Y.transform.glCoordMatrix),i.mul(Dt,Dt,Ct.placementViewportMatrix),Xt.push({circleArray:Bt,circleOffset:qt,transform:yt,invTransform:Dt}),hr+=Bt.length/4,qt=hr}Rt&&ft.draw(we,Ue.LINES,wi.disabled,Fn.disabled,Y.colorModeForRenderPass(),Er.disabled,Kr(Ot,Y.transform,at),J.id,Rt.layoutVertexBuffer,Rt.indexBuffer,Rt.segments,null,Y.transform.zoom,null,null,Rt.collisionVertexBuffer)}}if(!(!ne||!Xt.length)){var Pt=Y.useProgram(\"collisionCircle\"),ht=new i.StructArrayLayout2f1f2i16;ht.resize(hr*4),ht._trim();for(var ur=0,br=0,Ur=Xt;br<Ur.length;br+=1)for(var Di=Ur[br],fi=0;fi<Di.circleArray.length/4;fi++){var Ti=fi*4,gn=Di.circleArray[Ti+0],rn=Di.circleArray[Ti+1],Ci=Di.circleArray[Ti+2],Bi=Di.circleArray[Ti+3];ht.emplace(ur++,gn,rn,Ci,Bi,0),ht.emplace(ur++,gn,rn,Ci,Bi,1),ht.emplace(ur++,gn,rn,Ci,Bi,2),ht.emplace(ur++,gn,rn,Ci,Bi,3)}(!Vc||Vc.length<hr*2)&&(Vc=Ku(hr));for(var Gi=we.createIndexBuffer(Vc,!0),sn=we.createVertexBuffer(ht,i.collisionCircleLayout.members,!0),zn=0,Ja=Xt;zn<Ja.length;zn+=1){var co=Ja[zn],ts=ki(co.transform,co.invTransform,Y.transform);Pt.draw(we,Ue.TRIANGLES,wi.disabled,Fn.disabled,Y.colorModeForRenderPass(),Er.disabled,ts,J.id,sn,Gi,i.SegmentVector.simpleSegment(0,co.circleOffset*2,co.circleArray.length,co.circleArray.length/2),null,Y.transform.zoom,null,null,null)}sn.destroy(),Gi.destroy()}}function Ku(Y){var D=Y*2,J=new i.StructArrayLayout3ui6;J.resize(D),J._trim();for(var q=0;q<D;q++){var K=q*6;J.uint16[K+0]=q*4+0,J.uint16[K+1]=q*4+1,J.uint16[K+2]=q*4+2,J.uint16[K+3]=q*4+2,J.uint16[K+4]=q*4+3,J.uint16[K+5]=q*4+0}return J}var ue=i.identity(new Float32Array(16));function w(Y,D,J,q,K){if(Y.renderPass===\"translucent\"){var de=Fn.disabled,ne=Y.colorModeForRenderPass(),we=J.layout.get(\"text-variable-anchor\");we&&Q(q,Y,J,D,J.layout.get(\"text-rotation-alignment\"),J.layout.get(\"text-pitch-alignment\"),K),J.paint.get(\"icon-opacity\").constantOr(1)!==0&&qe(Y,D,J,q,!1,J.paint.get(\"icon-translate\"),J.paint.get(\"icon-translate-anchor\"),J.layout.get(\"icon-rotation-alignment\"),J.layout.get(\"icon-pitch-alignment\"),J.layout.get(\"icon-keep-upright\"),de,ne),J.paint.get(\"text-opacity\").constantOr(1)!==0&&qe(Y,D,J,q,!0,J.paint.get(\"text-translate\"),J.paint.get(\"text-translate-anchor\"),J.layout.get(\"text-rotation-alignment\"),J.layout.get(\"text-pitch-alignment\"),J.layout.get(\"text-keep-upright\"),de,ne),D.map.showCollisionBoxes&&(hc(Y,D,J,q,J.paint.get(\"text-translate\"),J.paint.get(\"text-translate-anchor\"),!0),hc(Y,D,J,q,J.paint.get(\"icon-translate\"),J.paint.get(\"icon-translate-anchor\"),!1))}}function B(Y,D,J,q,K,de){var ne=i.getAnchorAlignment(Y),we=ne.horizontalAlign,Ue=ne.verticalAlign,ft=-(we-.5)*D,Xt=-(Ue-.5)*J,hr=i.evaluateVariableOffset(Y,q);return new i.Point((ft/K+hr[0])*de,(Xt/K+hr[1])*de)}function Q(Y,D,J,q,K,de,ne){for(var we=D.transform,Ue=K===\"map\",ft=de===\"map\",Xt=0,hr=Y;Xt<hr.length;Xt+=1){var qt=hr[Xt],Ve=q.getTile(qt),Qe=Ve.getBucket(J);if(!(!Qe||!Qe.text||!Qe.text.segments.get().length)){var at=Qe.textSizeData,Ct=i.evaluateSizeForZoom(at,we.zoom),Ot=As(Ve,1,D.transform.zoom),Rt=_n(qt.posMatrix,ft,Ue,D.transform,Ot),Bt=J.layout.get(\"icon-text-fit\")!==\"none\"&&Qe.hasIconData();if(Ct){var Dt=Math.pow(2,we.zoom-Ve.tileID.overscaledZ);ee(Qe,Ue,ft,ne,i.symbolSize,we,Rt,qt.posMatrix,Dt,Ct,Bt)}}}}function ee(Y,D,J,q,K,de,ne,we,Ue,ft,Xt){var hr=Y.text.placedSymbolArray,qt=Y.text.dynamicLayoutVertexArray,Ve=Y.icon.dynamicLayoutVertexArray,Qe={};qt.clear();for(var at=0;at<hr.length;at++){var Ct=hr.get(at),Ot=Y.allowVerticalPlacement&&!Ct.placedOrientation,Rt=!Ct.hidden&&Ct.crossTileID&&!Ot?q[Ct.crossTileID]:null;if(!Rt)ul(Ct.numGlyphs,qt);else{var Bt=new i.Point(Ct.anchorX,Ct.anchorY),Dt=Jn(Bt,J?we:ne),yt=Ma(de.cameraToCenterDistance,Dt.signedDistanceFromCamera),Pt=K.evaluateSizeForFeature(Y.textSizeData,ft,Ct)*yt/i.ONE_EM;J&&(Pt*=Y.tilePixelRatio/Ue);for(var ht=Rt.width,ur=Rt.height,br=Rt.anchor,Ur=Rt.textOffset,Di=Rt.textBoxScale,fi=B(br,ht,ur,Ur,Di,Pt),Ti=J?Jn(Bt.add(fi),ne).point:Dt.point.add(D?fi.rotate(-de.angle):fi),gn=Y.allowVerticalPlacement&&Ct.placedOrientation===i.WritingMode.vertical?Math.PI/2:0,rn=0;rn<Ct.numGlyphs;rn++)i.addDynamicAttributes(qt,Ti,gn);Xt&&Ct.associatedIconIndex>=0&&(Qe[Ct.associatedIconIndex]={shiftedAnchor:Ti,angle:gn})}}if(Xt){Ve.clear();for(var Ci=Y.icon.placedSymbolArray,Bi=0;Bi<Ci.length;Bi++){var Gi=Ci.get(Bi);if(Gi.hidden)ul(Gi.numGlyphs,Ve);else{var sn=Qe[Bi];if(!sn)ul(Gi.numGlyphs,Ve);else for(var zn=0;zn<Gi.numGlyphs;zn++)i.addDynamicAttributes(Ve,sn.shiftedAnchor,sn.angle)}}Y.icon.dynamicLayoutVertexBuffer.updateData(Ve)}Y.text.dynamicLayoutVertexBuffer.updateData(qt)}function le(Y,D,J){return J.iconsInText&&D?\"symbolTextAndIcon\":Y?\"symbolSDF\":\"symbolIcon\"}function qe(Y,D,J,q,K,de,ne,we,Ue,ft,Xt,hr){for(var qt=Y.context,Ve=qt.gl,Qe=Y.transform,at=we===\"map\",Ct=Ue===\"map\",Ot=at&&J.layout.get(\"symbol-placement\")!==\"point\",Rt=at&&!Ct&&!Ot,Bt=J.layout.get(\"symbol-sort-key\").constantOr(1)!==void 0,Dt=!1,yt=Y.depthModeForSublayer(0,wi.ReadOnly),Pt=J.layout.get(\"text-variable-anchor\"),ht=[],ur=0,br=q;ur<br.length;ur+=1){var Ur=br[ur],Di=D.getTile(Ur),fi=Di.getBucket(J);if(fi){var Ti=K?fi.text:fi.icon;if(!(!Ti||!Ti.segments.get().length)){var gn=Ti.programConfigurations.get(J.id),rn=K||fi.sdfIcons,Ci=K?fi.textSizeData:fi.iconSizeData,Bi=Ct||Qe.pitch!==0,Gi=Y.useProgram(le(rn,K,fi),gn),sn=i.evaluateSizeForZoom(Ci,Qe.zoom),zn=void 0,Ja=[0,0],co=void 0,ts=void 0,so=null,Zo=void 0;if(K){if(co=Di.glyphAtlasTexture,ts=Ve.LINEAR,zn=Di.glyphAtlasTexture.size,fi.iconsInText){Ja=Di.imageAtlasTexture.size,so=Di.imageAtlasTexture;var ms=Ci.kind===\"composite\"||Ci.kind===\"camera\";Zo=Bi||Y.options.rotating||Y.options.zooming||ms?Ve.LINEAR:Ve.NEAREST}}else{var ou=J.layout.get(\"icon-size\").constantOr(0)!==1||fi.iconsNeedLinear;co=Di.imageAtlasTexture,ts=rn||Y.options.rotating||Y.options.zooming||ou||Bi?Ve.LINEAR:Ve.NEAREST,zn=Di.imageAtlasTexture.size}var Cv=As(Di,1,Y.transform.zoom),Lv=_n(Ur.posMatrix,Ct,at,Y.transform,Cv),wd=ya(Ur.posMatrix,Ct,at,Y.transform,Cv),Kv=Pt&&fi.hasTextData(),cg=J.layout.get(\"icon-text-fit\")!==\"none\"&&Kv&&fi.hasIconData();Ot&&No(fi,Ur.posMatrix,Y,K,Lv,wd,Ct,ft);var pp=Y.translatePosMatrix(Ur.posMatrix,Di,de,ne),Td=Ot||K&&Pt||cg?ue:Lv,gp=Y.translatePosMatrix(wd,Di,de,ne,!0),Vd=rn&&J.paint.get(K?\"text-halo-width\":\"icon-halo-width\").constantOr(1)!==0,Ad=void 0;rn?fi.iconsInText?Ad=pu(Ci.kind,sn,Rt,Ct,Y,pp,Td,gp,zn,Ja):Ad=Nc(Ci.kind,sn,Rt,Ct,Y,pp,Td,gp,K,zn,!0):Ad=Yu(Ci.kind,sn,Rt,Ct,Y,pp,Td,gp,K,zn);var Pv={program:Gi,buffers:Ti,uniformValues:Ad,atlasTexture:co,atlasTextureIcon:so,atlasInterpolation:ts,atlasInterpolationIcon:Zo,isSDF:rn,hasHalo:Vd};if(Bt&&fi.canOverlap){Dt=!0;for(var Jv=Ti.segments.get(),Iv=0,ay=Jv;Iv<ay.length;Iv+=1){var fg=ay[Iv];ht.push({segments:new i.SegmentVector([fg]),sortKey:fg.sortKey,state:Pv})}}else ht.push({segments:Ti.segments,sortKey:0,state:Pv})}}}Dt&&ht.sort(function(b1,w1){return b1.sortKey-w1.sortKey});for(var oh=0,hg=ht;oh<hg.length;oh+=1){var oy=hg[oh],jh=oy.state;if(qt.activeTexture.set(Ve.TEXTURE0),jh.atlasTexture.bind(jh.atlasInterpolation,Ve.CLAMP_TO_EDGE),jh.atlasTextureIcon&&(qt.activeTexture.set(Ve.TEXTURE1),jh.atlasTextureIcon&&jh.atlasTextureIcon.bind(jh.atlasInterpolationIcon,Ve.CLAMP_TO_EDGE)),jh.isSDF){var rm=jh.uniformValues;jh.hasHalo&&(rm.u_is_halo=1,Xe(jh.buffers,oy.segments,J,Y,jh.program,yt,Xt,hr,rm)),rm.u_is_halo=0}Xe(jh.buffers,oy.segments,J,Y,jh.program,yt,Xt,hr,jh.uniformValues)}}function Xe(Y,D,J,q,K,de,ne,we,Ue){var ft=q.context,Xt=ft.gl;K.draw(ft,Xt.TRIANGLES,de,ne,we,Er.disabled,Ue,J.id,Y.layoutVertexBuffer,Y.indexBuffer,D,J.paint,q.transform.zoom,Y.programConfigurations.get(J.id),Y.dynamicLayoutVertexBuffer,Y.opacityVertexBuffer)}function ot(Y,D,J,q){if(Y.renderPass===\"translucent\"){var K=J.paint.get(\"circle-opacity\"),de=J.paint.get(\"circle-stroke-width\"),ne=J.paint.get(\"circle-stroke-opacity\"),we=J.layout.get(\"circle-sort-key\").constantOr(1)!==void 0;if(!(K.constantOr(1)===0&&(de.constantOr(1)===0||ne.constantOr(1)===0))){for(var Ue=Y.context,ft=Ue.gl,Xt=Y.depthModeForSublayer(0,wi.ReadOnly),hr=Fn.disabled,qt=Y.colorModeForRenderPass(),Ve=[],Qe=0;Qe<q.length;Qe++){var at=q[Qe],Ct=D.getTile(at),Ot=Ct.getBucket(J);if(Ot){var Rt=Ot.programConfigurations.get(J.id),Bt=Y.useProgram(\"circle\",Rt),Dt=Ot.layoutVertexBuffer,yt=Ot.indexBuffer,Pt=Wt(Y,at,Ct,J),ht={programConfiguration:Rt,program:Bt,layoutVertexBuffer:Dt,indexBuffer:yt,uniformValues:Pt};if(we)for(var ur=Ot.segments.get(),br=0,Ur=ur;br<Ur.length;br+=1){var Di=Ur[br];Ve.push({segments:new i.SegmentVector([Di]),sortKey:Di.sortKey,state:ht})}else Ve.push({segments:Ot.segments,sortKey:0,state:ht})}}we&&Ve.sort(function(co,ts){return co.sortKey-ts.sortKey});for(var fi=0,Ti=Ve;fi<Ti.length;fi+=1){var gn=Ti[fi],rn=gn.state,Ci=rn.programConfiguration,Bi=rn.program,Gi=rn.layoutVertexBuffer,sn=rn.indexBuffer,zn=rn.uniformValues,Ja=gn.segments;Bi.draw(Ue,ft.TRIANGLES,Xt,hr,qt,Er.disabled,zn,J.id,Gi,sn,Ja,J.paint,Y.transform.zoom,Ci)}}}}function Tt(Y,D,J,q){if(J.paint.get(\"heatmap-opacity\")!==0)if(Y.renderPass===\"offscreen\"){var K=Y.context,de=K.gl,ne=Fn.disabled,we=new wt([de.ONE,de.ONE],i.Color.transparent,[!0,!0,!0,!0]);Yt(K,Y,J),K.clear({color:i.Color.transparent});for(var Ue=0;Ue<q.length;Ue++){var ft=q[Ue];if(!D.hasRenderableParent(ft)){var Xt=D.getTile(ft),hr=Xt.getBucket(J);if(hr){var qt=hr.programConfigurations.get(J.id),Ve=Y.useProgram(\"heatmap\",qt),Qe=Y.transform,at=Qe.zoom;Ve.draw(K,de.TRIANGLES,wi.disabled,ne,we,Er.disabled,on(ft.posMatrix,Xt,at,J.paint.get(\"heatmap-intensity\")),J.id,hr.layoutVertexBuffer,hr.indexBuffer,hr.segments,J.paint,Y.transform.zoom,qt)}}}K.viewport.set([0,0,Y.width,Y.height])}else Y.renderPass===\"translucent\"&&(Y.context.setColorMode(Y.colorModeForRenderPass()),xr(Y,J))}function Yt(Y,D,J){var q=Y.gl;Y.activeTexture.set(q.TEXTURE1),Y.viewport.set([0,0,D.width/4,D.height/4]);var K=J.heatmapFbo;if(K)q.bindTexture(q.TEXTURE_2D,K.colorAttachment.get()),Y.bindFramebuffer.set(K.framebuffer);else{var de=q.createTexture();q.bindTexture(q.TEXTURE_2D,de),q.texParameteri(q.TEXTURE_2D,q.TEXTURE_WRAP_S,q.CLAMP_TO_EDGE),q.texParameteri(q.TEXTURE_2D,q.TEXTURE_WRAP_T,q.CLAMP_TO_EDGE),q.texParameteri(q.TEXTURE_2D,q.TEXTURE_MIN_FILTER,q.LINEAR),q.texParameteri(q.TEXTURE_2D,q.TEXTURE_MAG_FILTER,q.LINEAR),K=J.heatmapFbo=Y.createFramebuffer(D.width/4,D.height/4,!1),Kt(Y,D,de,K)}}function Kt(Y,D,J,q){var K=Y.gl,de=Y.extRenderToTextureHalfFloat?Y.extTextureHalfFloat.HALF_FLOAT_OES:K.UNSIGNED_BYTE;K.texImage2D(K.TEXTURE_2D,0,K.RGBA,D.width/4,D.height/4,0,K.RGBA,de,null),q.colorAttachment.set(J)}function xr(Y,D){var J=Y.context,q=J.gl,K=D.heatmapFbo;if(K){J.activeTexture.set(q.TEXTURE0),q.bindTexture(q.TEXTURE_2D,K.colorAttachment.get()),J.activeTexture.set(q.TEXTURE1);var de=D.colorRampTexture;de||(de=D.colorRampTexture=new i.Texture(J,D.colorRamp,q.RGBA)),de.bind(q.LINEAR,q.CLAMP_TO_EDGE),Y.useProgram(\"heatmapTexture\").draw(J,q.TRIANGLES,wi.disabled,Fn.disabled,Y.colorModeForRenderPass(),Er.disabled,Fi(Y,D,0,1),D.id,Y.viewportBuffer,Y.quadTriangleIndexBuffer,Y.viewportSegments,D.paint,Y.transform.zoom)}}function Ir(Y,D,J,q){if(Y.renderPass===\"translucent\"){var K=J.paint.get(\"line-opacity\"),de=J.paint.get(\"line-width\");if(!(K.constantOr(1)===0||de.constantOr(1)===0))for(var ne=Y.depthModeForSublayer(0,wi.ReadOnly),we=Y.colorModeForRenderPass(),Ue=J.paint.get(\"line-dasharray\"),ft=J.paint.get(\"line-pattern\"),Xt=ft.constantOr(1),hr=J.paint.get(\"line-gradient\"),qt=J.getCrossfadeParameters(),Ve=Xt?\"linePattern\":Ue?\"lineSDF\":hr?\"lineGradient\":\"line\",Qe=Y.context,at=Qe.gl,Ct=!0,Ot=0,Rt=q;Ot<Rt.length;Ot+=1){var Bt=Rt[Ot],Dt=D.getTile(Bt);if(!(Xt&&!Dt.patternsLoaded())){var yt=Dt.getBucket(J);if(yt){var Pt=yt.programConfigurations.get(J.id),ht=Y.context.program.get(),ur=Y.useProgram(Ve,Pt),br=Ct||ur.program!==ht,Ur=ft.constantOr(null);if(Ur&&Dt.imageAtlas){var Di=Dt.imageAtlas,fi=Di.patternPositions[Ur.to.toString()],Ti=Di.patternPositions[Ur.from.toString()];fi&&Ti&&Pt.setConstantPatternPositions(fi,Ti)}var gn=Xt?as(Y,Dt,J,qt):Ue?ws(Y,Dt,J,Ue,qt):hr?Ss(Y,Dt,J,yt.lineClipsArray.length):Xo(Y,Dt,J);if(Xt)Qe.activeTexture.set(at.TEXTURE0),Dt.imageAtlasTexture.bind(at.LINEAR,at.CLAMP_TO_EDGE),Pt.updatePaintBuffers(qt);else if(Ue&&(br||Y.lineAtlas.dirty))Qe.activeTexture.set(at.TEXTURE0),Y.lineAtlas.bind(Qe);else if(hr){var rn=yt.gradients[J.id],Ci=rn.texture;if(J.gradientVersion!==rn.version){var Bi=256;if(J.stepInterpolant){var Gi=D.getSource().maxzoom,sn=Bt.canonical.z===Gi?Math.ceil(1<<Y.transform.maxZoom-Bt.canonical.z):1,zn=yt.maxLineLength/i.EXTENT,Ja=1024,co=zn*Ja*sn;Bi=i.clamp(i.nextPowerOfTwo(co),256,Qe.maxTextureSize)}rn.gradient=i.renderColorRamp({expression:J.gradientExpression(),evaluationKey:\"lineProgress\",resolution:Bi,image:rn.gradient||void 0,clips:yt.lineClipsArray}),rn.texture?rn.texture.update(rn.gradient):rn.texture=new i.Texture(Qe,rn.gradient,at.RGBA),rn.version=J.gradientVersion,Ci=rn.texture}Qe.activeTexture.set(at.TEXTURE0),Ci.bind(J.stepInterpolant?at.NEAREST:at.LINEAR,at.CLAMP_TO_EDGE)}ur.draw(Qe,at.TRIANGLES,ne,Y.stencilModeForClipping(Bt),we,Er.disabled,gn,J.id,yt.layoutVertexBuffer,yt.indexBuffer,yt.segments,J.paint,Y.transform.zoom,Pt,yt.layoutVertexBuffer2),Ct=!1}}}}}function ve(Y,D,J,q){var K=J.paint.get(\"fill-color\"),de=J.paint.get(\"fill-opacity\");if(de.constantOr(1)!==0){var ne=Y.colorModeForRenderPass(),we=J.paint.get(\"fill-pattern\"),Ue=Y.opaquePassEnabledForLayer()&&!we.constantOr(1)&&K.constantOr(i.Color.transparent).a===1&&de.constantOr(0)===1?\"opaque\":\"translucent\";if(Y.renderPass===Ue){var ft=Y.depthModeForSublayer(1,Y.renderPass===\"opaque\"?wi.ReadWrite:wi.ReadOnly);be(Y,D,J,q,ft,ne,!1)}if(Y.renderPass===\"translucent\"&&J.paint.get(\"fill-antialias\")){var Xt=Y.depthModeForSublayer(J.getPaintProperty(\"fill-outline-color\")?2:0,wi.ReadOnly);be(Y,D,J,q,Xt,ne,!0)}}}function be(Y,D,J,q,K,de,ne){var we=Y.context.gl,Ue=J.paint.get(\"fill-pattern\"),ft=Ue&&Ue.constantOr(1),Xt=J.getCrossfadeParameters(),hr,qt,Ve,Qe,at;ne?(qt=ft&&!J.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",hr=we.LINES):(qt=ft?\"fillPattern\":\"fill\",hr=we.TRIANGLES);for(var Ct=0,Ot=q;Ct<Ot.length;Ct+=1){var Rt=Ot[Ct],Bt=D.getTile(Rt);if(!(ft&&!Bt.patternsLoaded())){var Dt=Bt.getBucket(J);if(Dt){var yt=Dt.programConfigurations.get(J.id),Pt=Y.useProgram(qt,yt);ft&&(Y.context.activeTexture.set(we.TEXTURE0),Bt.imageAtlasTexture.bind(we.LINEAR,we.CLAMP_TO_EDGE),yt.updatePaintBuffers(Xt));var ht=Ue.constantOr(null);if(ht&&Bt.imageAtlas){var ur=Bt.imageAtlas,br=ur.patternPositions[ht.to.toString()],Ur=ur.patternPositions[ht.from.toString()];br&&Ur&&yt.setConstantPatternPositions(br,Ur)}var Di=Y.translatePosMatrix(Rt.posMatrix,Bt,J.paint.get(\"fill-translate\"),J.paint.get(\"fill-translate-anchor\"));if(!ne)Qe=Dt.indexBuffer,at=Dt.segments,Ve=ft?cf(Di,Y,Xt,Bt):qc(Di);else{Qe=Dt.indexBuffer2,at=Dt.segments2;var fi=[we.drawingBufferWidth,we.drawingBufferHeight];Ve=qt===\"fillOutlinePattern\"&&ft?Bc(Di,Y,Xt,Bt,fi):fc(Di,fi)}Pt.draw(Y.context,hr,K,Y.stencilModeForClipping(Rt),de,Er.disabled,Ve,J.id,Dt.layoutVertexBuffer,Qe,at,J.paint,Y.transform.zoom,yt)}}}}function De(Y,D,J,q){var K=J.paint.get(\"fill-extrusion-opacity\");if(K!==0&&Y.renderPass===\"translucent\"){var de=new wi(Y.context.gl.LEQUAL,wi.ReadWrite,Y.depthRangeFor3D);if(K===1&&!J.paint.get(\"fill-extrusion-pattern\").constantOr(1)){var ne=Y.colorModeForRenderPass();Be(Y,D,J,q,de,Fn.disabled,ne)}else Be(Y,D,J,q,de,Fn.disabled,wt.disabled),Be(Y,D,J,q,de,Y.stencilModeFor3D(),Y.colorModeForRenderPass())}}function Be(Y,D,J,q,K,de,ne){for(var we=Y.context,Ue=we.gl,ft=J.paint.get(\"fill-extrusion-pattern\"),Xt=ft.constantOr(1),hr=J.getCrossfadeParameters(),qt=J.paint.get(\"fill-extrusion-opacity\"),Ve=0,Qe=q;Ve<Qe.length;Ve+=1){var at=Qe[Ve],Ct=D.getTile(at),Ot=Ct.getBucket(J);if(Ot){var Rt=Ot.programConfigurations.get(J.id),Bt=Y.useProgram(Xt?\"fillExtrusionPattern\":\"fillExtrusion\",Rt);Xt&&(Y.context.activeTexture.set(Ue.TEXTURE0),Ct.imageAtlasTexture.bind(Ue.LINEAR,Ue.CLAMP_TO_EDGE),Rt.updatePaintBuffers(hr));var Dt=ft.constantOr(null);if(Dt&&Ct.imageAtlas){var yt=Ct.imageAtlas,Pt=yt.patternPositions[Dt.to.toString()],ht=yt.patternPositions[Dt.from.toString()];Pt&&ht&&Rt.setConstantPatternPositions(Pt,ht)}var ur=Y.translatePosMatrix(at.posMatrix,Ct,J.paint.get(\"fill-extrusion-translate\"),J.paint.get(\"fill-extrusion-translate-anchor\")),br=J.paint.get(\"fill-extrusion-vertical-gradient\"),Ur=Xt?Zu(ur,Y,br,qt,at,hr,Ct):ah(ur,Y,br,qt);Bt.draw(we,we.gl.TRIANGLES,K,de,ne,Er.backCCW,Ur,J.id,Ot.layoutVertexBuffer,Ot.indexBuffer,Ot.segments,J.paint,Y.transform.zoom,Rt)}}}function et(Y,D,J,q){if(!(Y.renderPass!==\"offscreen\"&&Y.renderPass!==\"translucent\")){for(var K=Y.context,de=Y.depthModeForSublayer(0,wi.ReadOnly),ne=Y.colorModeForRenderPass(),we=Y.renderPass===\"translucent\"?Y.stencilConfigForOverlap(q):[{},q],Ue=we[0],ft=we[1],Xt=0,hr=ft;Xt<hr.length;Xt+=1){var qt=hr[Xt],Ve=D.getTile(qt);Ve.needsHillshadePrepare&&Y.renderPass===\"offscreen\"?it(Y,Ve,J,de,Fn.disabled,ne):Y.renderPass===\"translucent\"&&We(Y,Ve,J,de,Ue[qt.overscaledZ],ne)}K.viewport.set([0,0,Y.width,Y.height])}}function We(Y,D,J,q,K,de){var ne=Y.context,we=ne.gl,Ue=D.fbo;if(Ue){var ft=Y.useProgram(\"hillshade\");ne.activeTexture.set(we.TEXTURE0),we.bindTexture(we.TEXTURE_2D,Ue.colorAttachment.get());var Xt=Ra(Y,D,J);ft.draw(ne,we.TRIANGLES,q,K,de,Er.disabled,Xt,J.id,Y.rasterBoundsBuffer,Y.quadTriangleIndexBuffer,Y.rasterBoundsSegments)}}function it(Y,D,J,q,K,de){var ne=Y.context,we=ne.gl,Ue=D.dem;if(Ue&&Ue.data){var ft=Ue.dim,Xt=Ue.stride,hr=Ue.getPixels();if(ne.activeTexture.set(we.TEXTURE1),ne.pixelStoreUnpackPremultiplyAlpha.set(!1),D.demTexture=D.demTexture||Y.getTileTexture(Xt),D.demTexture){var qt=D.demTexture;qt.update(hr,{premultiply:!1}),qt.bind(we.NEAREST,we.CLAMP_TO_EDGE)}else D.demTexture=new i.Texture(ne,hr,we.RGBA,{premultiply:!1}),D.demTexture.bind(we.NEAREST,we.CLAMP_TO_EDGE);ne.activeTexture.set(we.TEXTURE0);var Ve=D.fbo;if(!Ve){var Qe=new i.Texture(ne,{width:ft,height:ft,data:null},we.RGBA);Qe.bind(we.LINEAR,we.CLAMP_TO_EDGE),Ve=D.fbo=ne.createFramebuffer(ft,ft,!0),Ve.colorAttachment.set(Qe.texture)}ne.bindFramebuffer.set(Ve.framebuffer),ne.viewport.set([0,0,ft,ft]),Y.useProgram(\"hillshadePrepare\").draw(ne,we.TRIANGLES,q,K,de,Er.disabled,La(D.tileID,Ue),J.id,Y.rasterBoundsBuffer,Y.quadTriangleIndexBuffer,Y.rasterBoundsSegments),D.needsHillshadePrepare=!1}}function Ft(Y,D,J,q){if(Y.renderPass===\"translucent\"&&J.paint.get(\"raster-opacity\")!==0&&q.length)for(var K=Y.context,de=K.gl,ne=D.getSource(),we=Y.useProgram(\"raster\"),Ue=Y.colorModeForRenderPass(),ft=ne instanceof Ce?[{},q]:Y.stencilConfigForOverlap(q),Xt=ft[0],hr=ft[1],qt=hr[hr.length-1].overscaledZ,Ve=!Y.options.moving,Qe=0,at=hr;Qe<at.length;Qe+=1){var Ct=at[Qe],Ot=Y.depthModeForSublayer(Ct.overscaledZ-qt,J.paint.get(\"raster-opacity\")===1?wi.ReadWrite:wi.ReadOnly,de.LESS),Rt=D.getTile(Ct),Bt=Y.transform.calculatePosMatrix(Ct.toUnwrapped(),Ve);Rt.registerFadeDuration(J.paint.get(\"raster-fade-duration\"));var Dt=D.findLoadedParent(Ct,0),yt=Ht(Rt,Dt,D,J,Y.transform),Pt=void 0,ht=void 0,ur=J.paint.get(\"raster-resampling\")===\"nearest\"?de.NEAREST:de.LINEAR;K.activeTexture.set(de.TEXTURE0),Rt.texture.bind(ur,de.CLAMP_TO_EDGE,de.LINEAR_MIPMAP_NEAREST),K.activeTexture.set(de.TEXTURE1),Dt?(Dt.texture.bind(ur,de.CLAMP_TO_EDGE,de.LINEAR_MIPMAP_NEAREST),Pt=Math.pow(2,Dt.tileID.overscaledZ-Rt.tileID.overscaledZ),ht=[Rt.tileID.canonical.x*Pt%1,Rt.tileID.canonical.y*Pt%1]):Rt.texture.bind(ur,de.CLAMP_TO_EDGE,de.LINEAR_MIPMAP_NEAREST);var br=Ls(Bt,ht||[0,0],Pt||1,yt,J);ne instanceof Ce?we.draw(K,de.TRIANGLES,Ot,Fn.disabled,Ue,Er.disabled,br,J.id,ne.boundsBuffer,Y.quadTriangleIndexBuffer,ne.boundsSegments):we.draw(K,de.TRIANGLES,Ot,Xt[Ct.overscaledZ],Ue,Er.disabled,br,J.id,Y.rasterBoundsBuffer,Y.quadTriangleIndexBuffer,Y.rasterBoundsSegments)}}function Ht(Y,D,J,q,K){var de=q.paint.get(\"raster-fade-duration\");if(de>0){var ne=i.browser.now(),we=(ne-Y.timeAdded)/de,Ue=D?(ne-D.timeAdded)/de:-1,ft=J.getSource(),Xt=K.coveringZoomLevel({tileSize:ft.tileSize,roundZoom:ft.roundZoom}),hr=!D||Math.abs(D.tileID.overscaledZ-Xt)>Math.abs(Y.tileID.overscaledZ-Xt),qt=hr&&Y.refreshedUponExpiration?1:i.clamp(hr?we:1-Ue,0,1);return Y.refreshedUponExpiration&&we>=1&&(Y.refreshedUponExpiration=!1),D?{opacity:1,mix:1-qt}:{opacity:qt,mix:0}}else return{opacity:1,mix:0}}function tr(Y,D,J){var q=J.paint.get(\"background-color\"),K=J.paint.get(\"background-opacity\");if(K!==0){var de=Y.context,ne=de.gl,we=Y.transform,Ue=we.tileSize,ft=J.paint.get(\"background-pattern\");if(!Y.isPatternMissing(ft)){var Xt=!ft&&q.a===1&&K===1&&Y.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(Y.renderPass===Xt){var hr=Fn.disabled,qt=Y.depthModeForSublayer(0,Xt===\"opaque\"?wi.ReadWrite:wi.ReadOnly),Ve=Y.colorModeForRenderPass(),Qe=Y.useProgram(ft?\"backgroundPattern\":\"background\"),at=we.coveringTiles({tileSize:Ue});ft&&(de.activeTexture.set(ne.TEXTURE0),Y.imageManager.bind(Y.context));for(var Ct=J.getCrossfadeParameters(),Ot=0,Rt=at;Ot<Rt.length;Ot+=1){var Bt=Rt[Ot],Dt=Y.transform.calculatePosMatrix(Bt.toUnwrapped()),yt=ft?Ua(Dt,K,Y,ft,{tileID:Bt,tileSize:Ue},Ct):Ac(Dt,K,q);Qe.draw(de,ne.TRIANGLES,qt,hr,Ve,Er.disabled,yt,J.id,Y.tileExtentBuffer,Y.quadTriangleIndexBuffer,Y.tileExtentSegments)}}}}}var dr=new i.Color(1,0,0,1),Sr=new i.Color(0,1,0,1),Or=new i.Color(0,0,1,1),Wr=new i.Color(1,0,1,1),ni=new i.Color(0,1,1,1);function Pi(Y){var D=Y.transform.padding,J=3;ln(Y,Y.transform.height-(D.top||0),J,dr),ln(Y,D.bottom||0,J,Sr),Cn(Y,D.left||0,J,Or),Cn(Y,Y.transform.width-(D.right||0),J,Wr);var q=Y.transform.centerPoint;cn(Y,q.x,Y.transform.height-q.y,ni)}function cn(Y,D,J,q){var K=20,de=2;Kn(Y,D-de/2,J-K/2,de,K,q),Kn(Y,D-K/2,J-de/2,K,de,q)}function ln(Y,D,J,q){Kn(Y,0,D+J/2,Y.transform.width,J,q)}function Cn(Y,D,J,q){Kn(Y,D-J/2,0,J,Y.transform.height,q)}function Kn(Y,D,J,q,K,de){var ne=Y.context,we=ne.gl;we.enable(we.SCISSOR_TEST),we.scissor(D*i.browser.devicePixelRatio,J*i.browser.devicePixelRatio,q*i.browser.devicePixelRatio,K*i.browser.devicePixelRatio),ne.clear({color:de}),we.disable(we.SCISSOR_TEST)}function Ta(Y,D,J){for(var q=0;q<J.length;q++)fa(Y,D,J[q])}function fa(Y,D,J){var q=Y.context,K=q.gl,de=J.posMatrix,ne=Y.useProgram(\"debug\"),we=wi.disabled,Ue=Fn.disabled,ft=Y.colorModeForRenderPass(),Xt=\"$debug\";q.activeTexture.set(K.TEXTURE0),Y.emptyTexture.bind(K.LINEAR,K.CLAMP_TO_EDGE),ne.draw(q,K.LINE_STRIP,we,Ue,ft,Er.disabled,dn(de,i.Color.red),Xt,Y.debugBuffer,Y.tileBorderIndexBuffer,Y.debugSegments);var hr=D.getTileByID(J.key).latestRawTileData,qt=hr&&hr.byteLength||0,Ve=Math.floor(qt/1024),Qe=D.getTile(J).tileSize,at=512/Math.min(Qe,512)*(J.overscaledZ/Y.transform.zoom)*.5,Ct=J.canonical.toString();J.overscaledZ!==J.canonical.z&&(Ct+=\" => \"+J.overscaledZ);var Ot=Ct+\" \"+Ve+\"kb\";$a(Y,Ot),ne.draw(q,K.TRIANGLES,we,Ue,wt.alphaBlended,Er.disabled,dn(de,i.Color.transparent,at),Xt,Y.debugBuffer,Y.quadTriangleIndexBuffer,Y.debugSegments)}function $a(Y,D){Y.initDebugOverlayCanvas();var J=Y.debugOverlayCanvas,q=Y.context.gl,K=Y.debugOverlayCanvas.getContext(\"2d\");K.clearRect(0,0,J.width,J.height),K.shadowColor=\"white\",K.shadowBlur=2,K.lineWidth=1.5,K.strokeStyle=\"white\",K.textBaseline=\"top\",K.font=\"bold 36px Open Sans, sans-serif\",K.fillText(D,5,5),K.strokeText(D,5,5),Y.debugOverlayTexture.update(J),Y.debugOverlayTexture.bind(q.LINEAR,q.CLAMP_TO_EDGE)}function Co(Y,D,J){var q=Y.context,K=J.implementation;if(Y.renderPass===\"offscreen\"){var de=K.prerender;de&&(Y.setCustomLayerDefaults(),q.setColorMode(Y.colorModeForRenderPass()),de.call(K,q.gl,Y.transform.customLayerMatrix()),q.setDirty(),Y.setBaseState())}else if(Y.renderPass===\"translucent\"){Y.setCustomLayerDefaults(),q.setColorMode(Y.colorModeForRenderPass()),q.setStencilMode(Fn.disabled);var ne=K.renderingMode===\"3d\"?new wi(Y.context.gl.LEQUAL,wi.ReadWrite,Y.depthRangeFor3D):Y.depthModeForSublayer(0,wi.ReadOnly);q.setDepthMode(ne),K.render(q.gl,Y.transform.customLayerMatrix()),q.setDirty(),Y.setBaseState(),q.bindFramebuffer.set(null)}}var Qa={symbol:w,circle:ot,heatmap:Tt,line:Ir,fill:ve,\"fill-extrusion\":De,hillshade:et,raster:Ft,background:tr,debug:Ta,custom:Co},mo=function(D,J){this.context=new Xr(D),this.transform=J,this._tileTextures={},this.setup(),this.numSublayers=ri.maxUnderzooming+ri.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Uf,this.gpuTimers={}};mo.prototype.resize=function(D,J){if(this.width=D*i.browser.devicePixelRatio,this.height=J*i.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var q=0,K=this.style._order;q<K.length;q+=1){var de=K[q];this.style._layers[de].resize()}},mo.prototype.setup=function(){var D=this.context,J=new i.StructArrayLayout2i4;J.emplaceBack(0,0),J.emplaceBack(i.EXTENT,0),J.emplaceBack(0,i.EXTENT),J.emplaceBack(i.EXTENT,i.EXTENT),this.tileExtentBuffer=D.createVertexBuffer(J,oc.members),this.tileExtentSegments=i.SegmentVector.simpleSegment(0,0,4,2);var q=new i.StructArrayLayout2i4;q.emplaceBack(0,0),q.emplaceBack(i.EXTENT,0),q.emplaceBack(0,i.EXTENT),q.emplaceBack(i.EXTENT,i.EXTENT),this.debugBuffer=D.createVertexBuffer(q,oc.members),this.debugSegments=i.SegmentVector.simpleSegment(0,0,4,5);var K=new i.StructArrayLayout4i8;K.emplaceBack(0,0,0,0),K.emplaceBack(i.EXTENT,0,i.EXTENT,0),K.emplaceBack(0,i.EXTENT,0,i.EXTENT),K.emplaceBack(i.EXTENT,i.EXTENT,i.EXTENT,i.EXTENT),this.rasterBoundsBuffer=D.createVertexBuffer(K,Ee.members),this.rasterBoundsSegments=i.SegmentVector.simpleSegment(0,0,4,2);var de=new i.StructArrayLayout2i4;de.emplaceBack(0,0),de.emplaceBack(1,0),de.emplaceBack(0,1),de.emplaceBack(1,1),this.viewportBuffer=D.createVertexBuffer(de,oc.members),this.viewportSegments=i.SegmentVector.simpleSegment(0,0,4,2);var ne=new i.StructArrayLayout1ui2;ne.emplaceBack(0),ne.emplaceBack(1),ne.emplaceBack(3),ne.emplaceBack(2),ne.emplaceBack(0),this.tileBorderIndexBuffer=D.createIndexBuffer(ne);var we=new i.StructArrayLayout3ui6;we.emplaceBack(0,1,2),we.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=D.createIndexBuffer(we),this.emptyTexture=new i.Texture(D,{width:1,height:1,data:new Uint8Array([0,0,0,0])},D.gl.RGBA);var Ue=this.context.gl;this.stencilClearMode=new Fn({func:Ue.ALWAYS,mask:0},0,255,Ue.ZERO,Ue.ZERO,Ue.ZERO)},mo.prototype.clearStencil=function(){var D=this.context,J=D.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var q=i.create();i.ortho(q,0,this.width,this.height,0,0,1),i.scale(q,q,[J.drawingBufferWidth,J.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(D,J.TRIANGLES,wi.disabled,this.stencilClearMode,wt.disabled,Er.disabled,Nn(q),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},mo.prototype._renderTileClippingMasks=function(D,J){if(!(this.currentStencilSource===D.source||!D.isTileClipped()||!J||!J.length)){this.currentStencilSource=D.source;var q=this.context,K=q.gl;this.nextStencilID+J.length>256&&this.clearStencil(),q.setColorMode(wt.disabled),q.setDepthMode(wi.disabled);var de=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var ne=0,we=J;ne<we.length;ne+=1){var Ue=we[ne],ft=this._tileClippingMaskIDs[Ue.key]=this.nextStencilID++;de.draw(q,K.TRIANGLES,wi.disabled,new Fn({func:K.ALWAYS,mask:0},ft,255,K.KEEP,K.KEEP,K.REPLACE),wt.disabled,Er.disabled,Nn(Ue.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},mo.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var D=this.nextStencilID++,J=this.context.gl;return new Fn({func:J.NOTEQUAL,mask:255},D,255,J.KEEP,J.KEEP,J.REPLACE)},mo.prototype.stencilModeForClipping=function(D){var J=this.context.gl;return new Fn({func:J.EQUAL,mask:255},this._tileClippingMaskIDs[D.key],0,J.KEEP,J.KEEP,J.REPLACE)},mo.prototype.stencilConfigForOverlap=function(D){var J,q=this.context.gl,K=D.sort(function(ft,Xt){return Xt.overscaledZ-ft.overscaledZ}),de=K[K.length-1].overscaledZ,ne=K[0].overscaledZ-de+1;if(ne>1){this.currentStencilSource=void 0,this.nextStencilID+ne>256&&this.clearStencil();for(var we={},Ue=0;Ue<ne;Ue++)we[Ue+de]=new Fn({func:q.GEQUAL,mask:255},Ue+this.nextStencilID,255,q.KEEP,q.KEEP,q.REPLACE);return this.nextStencilID+=ne,[we,K]}return[(J={},J[de]=Fn.disabled,J),K]},mo.prototype.colorModeForRenderPass=function(){var D=this.context.gl;if(this._showOverdrawInspector){var J=8,q=1/J;return new wt([D.CONSTANT_COLOR,D.ONE],new i.Color(q,q,q,0),[!0,!0,!0,!0])}else return this.renderPass===\"opaque\"?wt.unblended:wt.alphaBlended},mo.prototype.depthModeForSublayer=function(D,J,q){if(!this.opaquePassEnabledForLayer())return wi.disabled;var K=1-((1+this.currentLayer)*this.numSublayers+D)*this.depthEpsilon;return new wi(q||this.context.gl.LEQUAL,J,[K,K])},mo.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},mo.prototype.render=function(D,J){var q=this;this.style=D,this.options=J,this.lineAtlas=D.lineAtlas,this.imageManager=D.imageManager,this.glyphManager=D.glyphManager,this.symbolFadeChange=D.placement.symbolFadeChange(i.browser.now()),this.imageManager.beginFrame();var K=this.style._order,de=this.style.sourceCaches;for(var ne in de){var we=de[ne];we.used&&we.prepare(this.context)}var Ue={},ft={},Xt={};for(var hr in de){var qt=de[hr];Ue[hr]=qt.getVisibleCoordinates(),ft[hr]=Ue[hr].slice().reverse(),Xt[hr]=qt.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var Ve=0;Ve<K.length;Ve++){var Qe=K[Ve];if(this.style._layers[Qe].is3D()){this.opaquePassCutoff=Ve;break}}this.renderPass=\"offscreen\";for(var at=0,Ct=K;at<Ct.length;at+=1){var Ot=Ct[at],Rt=this.style._layers[Ot];if(!(!Rt.hasOffscreenPass()||Rt.isHidden(this.transform.zoom))){var Bt=ft[Rt.source];Rt.type!==\"custom\"&&!Bt.length||this.renderLayer(this,de[Rt.source],Rt,Bt)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:J.showOverdrawInspector?i.Color.black:i.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=J.showOverdrawInspector,this.depthRangeFor3D=[0,1-(D._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=K.length-1;this.currentLayer>=0;this.currentLayer--){var Dt=this.style._layers[K[this.currentLayer]],yt=de[Dt.source],Pt=Ue[Dt.source];this._renderTileClippingMasks(Dt,Pt),this.renderLayer(this,yt,Dt,Pt)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<K.length;this.currentLayer++){var ht=this.style._layers[K[this.currentLayer]],ur=de[ht.source],br=(ht.type===\"symbol\"?Xt:ft)[ht.source];this._renderTileClippingMasks(ht,Ue[ht.source]),this.renderLayer(this,ur,ht,br)}if(this.options.showTileBoundaries){var Ur,Di,fi=i.values(this.style._layers);fi.forEach(function(Ti){Ti.source&&!Ti.isHidden(q.transform.zoom)&&(Ti.source!==(Di&&Di.id)&&(Di=q.style.sourceCaches[Ti.source]),(!Ur||Ur.getSource().maxzoom<Di.getSource().maxzoom)&&(Ur=Di))}),Ur&&Qa.debug(this,Ur,Ur.getVisibleCoordinates())}this.options.showPadding&&Pi(this),this.context.setDefault()},mo.prototype.renderLayer=function(D,J,q,K){q.isHidden(this.transform.zoom)||q.type!==\"background\"&&q.type!==\"custom\"&&!K.length||(this.id=q.id,this.gpuTimingStart(q),Qa[q.type](D,J,q,K,this.style.placement.variableOffsets),this.gpuTimingEnd())},mo.prototype.gpuTimingStart=function(D){if(this.options.gpuTiming){var J=this.context.extTimerQuery,q=this.gpuTimers[D.id];q||(q=this.gpuTimers[D.id]={calls:0,cpuTime:0,query:J.createQueryEXT()}),q.calls++,J.beginQueryEXT(J.TIME_ELAPSED_EXT,q.query)}},mo.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var D=this.context.extTimerQuery;D.endQueryEXT(D.TIME_ELAPSED_EXT)}},mo.prototype.collectGpuTimers=function(){var D=this.gpuTimers;return this.gpuTimers={},D},mo.prototype.queryGpuTimers=function(D){var J={};for(var q in D){var K=D[q],de=this.context.extTimerQuery,ne=de.getQueryObjectEXT(K.query,de.QUERY_RESULT_EXT)/(1e3*1e3);de.deleteQueryEXT(K.query),J[q]=ne}return J},mo.prototype.translatePosMatrix=function(D,J,q,K,de){if(!q[0]&&!q[1])return D;var ne=de?K===\"map\"?this.transform.angle:0:K===\"viewport\"?-this.transform.angle:0;if(ne){var we=Math.sin(ne),Ue=Math.cos(ne);q=[q[0]*Ue-q[1]*we,q[0]*we+q[1]*Ue]}var ft=[de?q[0]:As(J,q[0],this.transform.zoom),de?q[1]:As(J,q[1],this.transform.zoom),0],Xt=new Float32Array(16);return i.translate(Xt,D,ft),Xt},mo.prototype.saveTileTexture=function(D){var J=this._tileTextures[D.size[0]];J?J.push(D):this._tileTextures[D.size[0]]=[D]},mo.prototype.getTileTexture=function(D){var J=this._tileTextures[D];return J&&J.length>0?J.pop():null},mo.prototype.isPatternMissing=function(D){if(!D)return!1;if(!D.from||!D.to)return!0;var J=this.imageManager.getPattern(D.from.toString()),q=this.imageManager.getPattern(D.to.toString());return!J||!q},mo.prototype.useProgram=function(D,J){this.cache=this.cache||{};var q=\"\"+D+(J?J.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[q]||(this.cache[q]=new Rf(this.context,D,wf[D],J,oo[D],this._showOverdrawInspector)),this.cache[q]},mo.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},mo.prototype.setBaseState=function(){var D=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(D.FUNC_ADD)},mo.prototype.initDebugOverlayCanvas=function(){if(this.debugOverlayCanvas==null){this.debugOverlayCanvas=i.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var D=this.context.gl;this.debugOverlayTexture=new i.Texture(this.context,this.debugOverlayCanvas,D.RGBA)}},mo.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Bo=function(D,J){this.points=D,this.planes=J};Bo.fromInvProjectionMatrix=function(D,J,q){var K=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]],de=Math.pow(2,q),ne=K.map(function(ft){return i.transformMat4([],ft,D)}).map(function(ft){return i.scale$1([],ft,1/ft[3]/J*de)}),we=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]],Ue=we.map(function(ft){var Xt=i.sub([],ne[ft[0]],ne[ft[1]]),hr=i.sub([],ne[ft[2]],ne[ft[1]]),qt=i.normalize([],i.cross([],Xt,hr)),Ve=-i.dot(qt,ne[ft[1]]);return qt.concat(Ve)});return new Bo(ne,Ue)};var Ps=function(D,J){this.min=D,this.max=J,this.center=i.scale$2([],i.add([],this.min,this.max),.5)};Ps.prototype.quadrant=function(D){for(var J=[D%2===0,D<2],q=i.clone$2(this.min),K=i.clone$2(this.max),de=0;de<J.length;de++)q[de]=J[de]?this.min[de]:this.center[de],K[de]=J[de]?this.center[de]:this.max[de];return K[2]=this.max[2],new Ps(q,K)},Ps.prototype.distanceX=function(D){var J=Math.max(Math.min(this.max[0],D[0]),this.min[0]);return J-D[0]},Ps.prototype.distanceY=function(D){var J=Math.max(Math.min(this.max[1],D[1]),this.min[1]);return J-D[1]},Ps.prototype.intersects=function(D){for(var J=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],q=!0,K=0;K<D.planes.length;K++){for(var de=D.planes[K],ne=0,we=0;we<J.length;we++)ne+=i.dot$1(de,J[we])>=0;if(ne===0)return 0;ne!==J.length&&(q=!1)}if(q)return 2;for(var Ue=0;Ue<3;Ue++){for(var ft=Number.MAX_VALUE,Xt=-Number.MAX_VALUE,hr=0;hr<D.points.length;hr++){var qt=D.points[hr][Ue]-this.min[Ue];ft=Math.min(ft,qt),Xt=Math.max(Xt,qt)}if(Xt<0||ft>this.max[Ue]-this.min[Ue])return 0}return 1};var Ts=function(D,J,q,K){if(D===void 0&&(D=0),J===void 0&&(J=0),q===void 0&&(q=0),K===void 0&&(K=0),isNaN(D)||D<0||isNaN(J)||J<0||isNaN(q)||q<0||isNaN(K)||K<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=D,this.bottom=J,this.left=q,this.right=K};Ts.prototype.interpolate=function(D,J,q){return J.top!=null&&D.top!=null&&(this.top=i.number(D.top,J.top,q)),J.bottom!=null&&D.bottom!=null&&(this.bottom=i.number(D.bottom,J.bottom,q)),J.left!=null&&D.left!=null&&(this.left=i.number(D.left,J.left,q)),J.right!=null&&D.right!=null&&(this.right=i.number(D.right,J.right,q)),this},Ts.prototype.getCenter=function(D,J){var q=i.clamp((this.left+D-this.right)/2,0,D),K=i.clamp((this.top+J-this.bottom)/2,0,J);return new i.Point(q,K)},Ts.prototype.equals=function(D){return this.top===D.top&&this.bottom===D.bottom&&this.left===D.left&&this.right===D.right},Ts.prototype.clone=function(){return new Ts(this.top,this.bottom,this.left,this.right)},Ts.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var wo=function(D,J,q,K,de){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=de===void 0?!0:de,this._minZoom=D||0,this._maxZoom=J||22,this._minPitch=q==null?0:q,this._maxPitch=K==null?60:K,this.setMaxBounds(),this.width=0,this.height=0,this._center=new i.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ts,this._posMatrixCache={},this._alignedPosMatrixCache={}},To={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};wo.prototype.clone=function(){var D=new wo(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return D.tileSize=this.tileSize,D.latRange=this.latRange,D.width=this.width,D.height=this.height,D._center=this._center,D.zoom=this.zoom,D.angle=this.angle,D._fov=this._fov,D._pitch=this._pitch,D._unmodified=this._unmodified,D._edgeInsets=this._edgeInsets.clone(),D._calcMatrices(),D},To.minZoom.get=function(){return this._minZoom},To.minZoom.set=function(Y){this._minZoom!==Y&&(this._minZoom=Y,this.zoom=Math.max(this.zoom,Y))},To.maxZoom.get=function(){return this._maxZoom},To.maxZoom.set=function(Y){this._maxZoom!==Y&&(this._maxZoom=Y,this.zoom=Math.min(this.zoom,Y))},To.minPitch.get=function(){return this._minPitch},To.minPitch.set=function(Y){this._minPitch!==Y&&(this._minPitch=Y,this.pitch=Math.max(this.pitch,Y))},To.maxPitch.get=function(){return this._maxPitch},To.maxPitch.set=function(Y){this._maxPitch!==Y&&(this._maxPitch=Y,this.pitch=Math.min(this.pitch,Y))},To.renderWorldCopies.get=function(){return this._renderWorldCopies},To.renderWorldCopies.set=function(Y){Y===void 0?Y=!0:Y===null&&(Y=!1),this._renderWorldCopies=Y},To.worldSize.get=function(){return this.tileSize*this.scale},To.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},To.size.get=function(){return new i.Point(this.width,this.height)},To.bearing.get=function(){return-this.angle/Math.PI*180},To.bearing.set=function(Y){var D=-i.wrap(Y,-180,180)*Math.PI/180;this.angle!==D&&(this._unmodified=!1,this.angle=D,this._calcMatrices(),this.rotationMatrix=i.create$2(),i.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},To.pitch.get=function(){return this._pitch/Math.PI*180},To.pitch.set=function(Y){var D=i.clamp(Y,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==D&&(this._unmodified=!1,this._pitch=D,this._calcMatrices())},To.fov.get=function(){return this._fov/Math.PI*180},To.fov.set=function(Y){Y=Math.max(.01,Math.min(60,Y)),this._fov!==Y&&(this._unmodified=!1,this._fov=Y/180*Math.PI,this._calcMatrices())},To.zoom.get=function(){return this._zoom},To.zoom.set=function(Y){var D=Math.min(Math.max(Y,this.minZoom),this.maxZoom);this._zoom!==D&&(this._unmodified=!1,this._zoom=D,this.scale=this.zoomScale(D),this.tileZoom=Math.floor(D),this.zoomFraction=D-this.tileZoom,this._constrain(),this._calcMatrices())},To.center.get=function(){return this._center},To.center.set=function(Y){Y.lat===this._center.lat&&Y.lng===this._center.lng||(this._unmodified=!1,this._center=Y,this._constrain(),this._calcMatrices())},To.padding.get=function(){return this._edgeInsets.toJSON()},To.padding.set=function(Y){this._edgeInsets.equals(Y)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,Y,1),this._calcMatrices())},To.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},wo.prototype.isPaddingEqual=function(D){return this._edgeInsets.equals(D)},wo.prototype.interpolatePadding=function(D,J,q){this._unmodified=!1,this._edgeInsets.interpolate(D,J,q),this._constrain(),this._calcMatrices()},wo.prototype.coveringZoomLevel=function(D){var J=(D.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/D.tileSize));return Math.max(0,J)},wo.prototype.getVisibleUnwrappedCoordinates=function(D){var J=[new i.UnwrappedTileID(0,D)];if(this._renderWorldCopies)for(var q=this.pointCoordinate(new i.Point(0,0)),K=this.pointCoordinate(new i.Point(this.width,0)),de=this.pointCoordinate(new i.Point(this.width,this.height)),ne=this.pointCoordinate(new i.Point(0,this.height)),we=Math.floor(Math.min(q.x,K.x,de.x,ne.x)),Ue=Math.floor(Math.max(q.x,K.x,de.x,ne.x)),ft=1,Xt=we-ft;Xt<=Ue+ft;Xt++)Xt!==0&&J.push(new i.UnwrappedTileID(Xt,D));return J},wo.prototype.coveringTiles=function(D){var J=this.coveringZoomLevel(D),q=J;if(D.minzoom!==void 0&&J<D.minzoom)return[];D.maxzoom!==void 0&&J>D.maxzoom&&(J=D.maxzoom);var K=i.MercatorCoordinate.fromLngLat(this.center),de=Math.pow(2,J),ne=[de*K.x,de*K.y,0],we=Bo.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,J),Ue=D.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(Ue=J);var ft=3,Xt=function(fi){return{aabb:new Ps([fi*de,0,0],[(fi+1)*de,de,0]),zoom:0,x:0,y:0,wrap:fi,fullyVisible:!1}},hr=[],qt=[],Ve=J,Qe=D.reparseOverscaled?q:J;if(this._renderWorldCopies)for(var at=1;at<=3;at++)hr.push(Xt(-at)),hr.push(Xt(at));for(hr.push(Xt(0));hr.length>0;){var Ct=hr.pop(),Ot=Ct.x,Rt=Ct.y,Bt=Ct.fullyVisible;if(!Bt){var Dt=Ct.aabb.intersects(we);if(Dt===0)continue;Bt=Dt===2}var yt=Ct.aabb.distanceX(ne),Pt=Ct.aabb.distanceY(ne),ht=Math.max(Math.abs(yt),Math.abs(Pt)),ur=ft+(1<<Ve-Ct.zoom)-2;if(Ct.zoom===Ve||ht>ur&&Ct.zoom>=Ue){qt.push({tileID:new i.OverscaledTileID(Ct.zoom===Ve?Qe:Ct.zoom,Ct.wrap,Ct.zoom,Ot,Rt),distanceSq:i.sqrLen([ne[0]-.5-Ot,ne[1]-.5-Rt])});continue}for(var br=0;br<4;br++){var Ur=(Ot<<1)+br%2,Di=(Rt<<1)+(br>>1);hr.push({aabb:Ct.aabb.quadrant(br),zoom:Ct.zoom+1,x:Ur,y:Di,wrap:Ct.wrap,fullyVisible:Bt})}}return qt.sort(function(fi,Ti){return fi.distanceSq-Ti.distanceSq}).map(function(fi){return fi.tileID})},wo.prototype.resize=function(D,J){this.width=D,this.height=J,this.pixelsToGLUnits=[2/D,-2/J],this._constrain(),this._calcMatrices()},To.unmodified.get=function(){return this._unmodified},wo.prototype.zoomScale=function(D){return Math.pow(2,D)},wo.prototype.scaleZoom=function(D){return Math.log(D)/Math.LN2},wo.prototype.project=function(D){var J=i.clamp(D.lat,-this.maxValidLatitude,this.maxValidLatitude);return new i.Point(i.mercatorXfromLng(D.lng)*this.worldSize,i.mercatorYfromLat(J)*this.worldSize)},wo.prototype.unproject=function(D){return new i.MercatorCoordinate(D.x/this.worldSize,D.y/this.worldSize).toLngLat()},To.point.get=function(){return this.project(this.center)},wo.prototype.setLocationAtPoint=function(D,J){var q=this.pointCoordinate(J),K=this.pointCoordinate(this.centerPoint),de=this.locationCoordinate(D),ne=new i.MercatorCoordinate(de.x-(q.x-K.x),de.y-(q.y-K.y));this.center=this.coordinateLocation(ne),this._renderWorldCopies&&(this.center=this.center.wrap())},wo.prototype.locationPoint=function(D){return this.coordinatePoint(this.locationCoordinate(D))},wo.prototype.pointLocation=function(D){return this.coordinateLocation(this.pointCoordinate(D))},wo.prototype.locationCoordinate=function(D){return i.MercatorCoordinate.fromLngLat(D)},wo.prototype.coordinateLocation=function(D){return D.toLngLat()},wo.prototype.pointCoordinate=function(D){var J=0,q=[D.x,D.y,0,1],K=[D.x,D.y,1,1];i.transformMat4(q,q,this.pixelMatrixInverse),i.transformMat4(K,K,this.pixelMatrixInverse);var de=q[3],ne=K[3],we=q[0]/de,Ue=K[0]/ne,ft=q[1]/de,Xt=K[1]/ne,hr=q[2]/de,qt=K[2]/ne,Ve=hr===qt?0:(J-hr)/(qt-hr);return new i.MercatorCoordinate(i.number(we,Ue,Ve)/this.worldSize,i.number(ft,Xt,Ve)/this.worldSize)},wo.prototype.coordinatePoint=function(D){var J=[D.x*this.worldSize,D.y*this.worldSize,0,1];return i.transformMat4(J,J,this.pixelMatrix),new i.Point(J[0]/J[3],J[1]/J[3])},wo.prototype.getBounds=function(){return new i.LngLatBounds().extend(this.pointLocation(new i.Point(0,0))).extend(this.pointLocation(new i.Point(this.width,0))).extend(this.pointLocation(new i.Point(this.width,this.height))).extend(this.pointLocation(new i.Point(0,this.height)))},wo.prototype.getMaxBounds=function(){return!this.latRange||this.latRange.length!==2||!this.lngRange||this.lngRange.length!==2?null:new i.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]])},wo.prototype.setMaxBounds=function(D){D?(this.lngRange=[D.getWest(),D.getEast()],this.latRange=[D.getSouth(),D.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},wo.prototype.calculatePosMatrix=function(D,J){J===void 0&&(J=!1);var q=D.key,K=J?this._alignedPosMatrixCache:this._posMatrixCache;if(K[q])return K[q];var de=D.canonical,ne=this.worldSize/this.zoomScale(de.z),we=de.x+Math.pow(2,de.z)*D.wrap,Ue=i.identity(new Float64Array(16));return i.translate(Ue,Ue,[we*ne,de.y*ne,0]),i.scale(Ue,Ue,[ne/i.EXTENT,ne/i.EXTENT,1]),i.multiply(Ue,J?this.alignedProjMatrix:this.projMatrix,Ue),K[q]=new Float32Array(Ue),K[q]},wo.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},wo.prototype._constrain=function(){if(!(!this.center||!this.width||!this.height||this._constraining)){this._constraining=!0;var D=-90,J=90,q=-180,K=180,de,ne,we,Ue,ft=this.size,Xt=this._unmodified;if(this.latRange){var hr=this.latRange;D=i.mercatorYfromLat(hr[1])*this.worldSize,J=i.mercatorYfromLat(hr[0])*this.worldSize,de=J-D<ft.y?ft.y/(J-D):0}if(this.lngRange){var qt=this.lngRange;q=i.mercatorXfromLng(qt[0])*this.worldSize,K=i.mercatorXfromLng(qt[1])*this.worldSize,ne=K-q<ft.x?ft.x/(K-q):0}var Ve=this.point,Qe=Math.max(ne||0,de||0);if(Qe){this.center=this.unproject(new i.Point(ne?(K+q)/2:Ve.x,de?(J+D)/2:Ve.y)),this.zoom+=this.scaleZoom(Qe),this._unmodified=Xt,this._constraining=!1;return}if(this.latRange){var at=Ve.y,Ct=ft.y/2;at-Ct<D&&(Ue=D+Ct),at+Ct>J&&(Ue=J-Ct)}if(this.lngRange){var Ot=Ve.x,Rt=ft.x/2;Ot-Rt<q&&(we=q+Rt),Ot+Rt>K&&(we=K-Rt)}(we!==void 0||Ue!==void 0)&&(this.center=this.unproject(new i.Point(we!==void 0?we:Ve.x,Ue!==void 0?Ue:Ve.y))),this._unmodified=Xt,this._constraining=!1}},wo.prototype._calcMatrices=function(){if(this.height){var D=this._fov/2,J=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(D)*this.height;var q=Math.PI/2+this._pitch,K=this._fov*(.5+J.y/this.height),de=Math.sin(K)*this.cameraToCenterDistance/Math.sin(i.clamp(Math.PI-q-K,.01,Math.PI-.01)),ne=this.point,we=ne.x,Ue=ne.y,ft=Math.cos(Math.PI/2-this._pitch)*de+this.cameraToCenterDistance,Xt=ft*1.01,hr=this.height/50,qt=new Float64Array(16);i.perspective(qt,this._fov,this.width/this.height,hr,Xt),qt[8]=-J.x*2/this.width,qt[9]=J.y*2/this.height,i.scale(qt,qt,[1,-1,1]),i.translate(qt,qt,[0,0,-this.cameraToCenterDistance]),i.rotateX(qt,qt,this._pitch),i.rotateZ(qt,qt,this.angle),i.translate(qt,qt,[-we,-Ue,0]),this.mercatorMatrix=i.scale([],qt,[this.worldSize,this.worldSize,this.worldSize]),i.scale(qt,qt,[1,1,i.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=qt,this.invProjMatrix=i.invert([],this.projMatrix);var Ve=this.width%2/2,Qe=this.height%2/2,at=Math.cos(this.angle),Ct=Math.sin(this.angle),Ot=we-Math.round(we)+at*Ve+Ct*Qe,Rt=Ue-Math.round(Ue)+at*Qe+Ct*Ve,Bt=new Float64Array(qt);if(i.translate(Bt,Bt,[Ot>.5?Ot-1:Ot,Rt>.5?Rt-1:Rt,0]),this.alignedProjMatrix=Bt,qt=i.create(),i.scale(qt,qt,[this.width/2,-this.height/2,1]),i.translate(qt,qt,[1,-1,0]),this.labelPlaneMatrix=qt,qt=i.create(),i.scale(qt,qt,[1,-1,1]),i.translate(qt,qt,[-1,-1,0]),i.scale(qt,qt,[2/this.width,2/this.height,1]),this.glCoordMatrix=qt,this.pixelMatrix=i.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),qt=i.invert(new Float64Array(16),this.pixelMatrix),!qt)throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=qt,this._posMatrixCache={},this._alignedPosMatrixCache={}}},wo.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var D=this.pointCoordinate(new i.Point(0,0)),J=[D.x*this.worldSize,D.y*this.worldSize,0,1],q=i.transformMat4(J,J,this.pixelMatrix);return q[3]/this.cameraToCenterDistance},wo.prototype.getCameraPoint=function(){var D=this._pitch,J=Math.tan(D)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new i.Point(0,J))},wo.prototype.getCameraQueryGeometry=function(D){var J=this.getCameraPoint();if(D.length===1)return[D[0],J];for(var q=J.x,K=J.y,de=J.x,ne=J.y,we=0,Ue=D;we<Ue.length;we+=1){var ft=Ue[we];q=Math.min(q,ft.x),K=Math.min(K,ft.y),de=Math.max(de,ft.x),ne=Math.max(ne,ft.y)}return[new i.Point(q,K),new i.Point(de,K),new i.Point(de,ne),new i.Point(q,ne),new i.Point(q,K)]},Object.defineProperties(wo.prototype,To);function hl(Y,D){var J=!1,q=null,K=function(){q=null,J&&(Y(),q=setTimeout(K,D),J=!1)};return function(){return J=!0,q||K(),q}}var Ul=function(D){this._hashName=D&&encodeURIComponent(D),i.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=hl(this._updateHashUnthrottled.bind(this),30*1e3/100)};Ul.prototype.addTo=function(D){return this._map=D,i.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Ul.prototype.remove=function(){return i.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Ul.prototype.getHashString=function(D){var J=this._map.getCenter(),q=Math.round(this._map.getZoom()*100)/100,K=Math.ceil((q*Math.LN2+Math.log(512/360/.5))/Math.LN10),de=Math.pow(10,K),ne=Math.round(J.lng*de)/de,we=Math.round(J.lat*de)/de,Ue=this._map.getBearing(),ft=this._map.getPitch(),Xt=\"\";if(D?Xt+=\"/\"+ne+\"/\"+we+\"/\"+q:Xt+=q+\"/\"+we+\"/\"+ne,(Ue||ft)&&(Xt+=\"/\"+Math.round(Ue*10)/10),ft&&(Xt+=\"/\"+Math.round(ft)),this._hashName){var hr=this._hashName,qt=!1,Ve=i.window.location.hash.slice(1).split(\"&\").map(function(Qe){var at=Qe.split(\"=\")[0];return at===hr?(qt=!0,at+\"=\"+Xt):Qe}).filter(function(Qe){return Qe});return qt||Ve.push(hr+\"=\"+Xt),\"#\"+Ve.join(\"&\")}return\"#\"+Xt},Ul.prototype._getCurrentHash=function(){var D=this,J=i.window.location.hash.replace(\"#\",\"\");if(this._hashName){var q;return J.split(\"&\").map(function(K){return K.split(\"=\")}).forEach(function(K){K[0]===D._hashName&&(q=K)}),(q&&q[1]||\"\").split(\"/\")}return J.split(\"/\")},Ul.prototype._onHashChange=function(){var D=this._getCurrentHash();if(D.length>=3&&!D.some(function(q){return isNaN(q)})){var J=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(D[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+D[2],+D[1]],zoom:+D[0],bearing:J,pitch:+(D[4]||0)}),!0}return!1},Ul.prototype._updateHashUnthrottled=function(){var D=i.window.location.href.replace(/(#.+)?$/,this.getHashString());try{i.window.history.replaceState(i.window.history.state,null,D)}catch(J){}};var Lu={linearity:.3,easing:i.bezier(0,0,.3,1)},au=i.extend({deceleration:2500,maxSpeed:1400},Lu),Js=i.extend({deceleration:20,maxSpeed:1400},Lu),Ql=i.extend({deceleration:1e3,maxSpeed:360},Lu),dc=i.extend({deceleration:1e3,maxSpeed:90},Lu),Tl=function(D){this._map=D,this.clear()};Tl.prototype.clear=function(){this._inertiaBuffer=[]},Tl.prototype.record=function(D){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:i.browser.now(),settings:D})},Tl.prototype._drainInertiaBuffer=function(){for(var D=this._inertiaBuffer,J=i.browser.now(),q=160;D.length>0&&J-D[0].time>q;)D.shift()},Tl.prototype._onMoveEnd=function(D){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var J={zoom:0,bearing:0,pitch:0,pan:new i.Point(0,0),pinchAround:void 0,around:void 0},q=0,K=this._inertiaBuffer;q<K.length;q+=1){var de=K[q],ne=de.settings;J.zoom+=ne.zoomDelta||0,J.bearing+=ne.bearingDelta||0,J.pitch+=ne.pitchDelta||0,ne.panDelta&&J.pan._add(ne.panDelta),ne.around&&(J.around=ne.around),ne.pinchAround&&(J.pinchAround=ne.pinchAround)}var we=this._inertiaBuffer[this._inertiaBuffer.length-1],Ue=we.time-this._inertiaBuffer[0].time,ft={};if(J.pan.mag()){var Xt=X(J.pan.mag(),Ue,i.extend({},au,D||{}));ft.offset=J.pan.mult(Xt.amount/J.pan.mag()),ft.center=this._map.transform.center,Al(ft,Xt)}if(J.zoom){var hr=X(J.zoom,Ue,Js);ft.zoom=this._map.transform.zoom+hr.amount,Al(ft,hr)}if(J.bearing){var qt=X(J.bearing,Ue,Ql);ft.bearing=this._map.transform.bearing+i.clamp(qt.amount,-179,179),Al(ft,qt)}if(J.pitch){var Ve=X(J.pitch,Ue,dc);ft.pitch=this._map.transform.pitch+Ve.amount,Al(ft,Ve)}if(ft.zoom||ft.bearing){var Qe=J.pinchAround===void 0?J.around:J.pinchAround;ft.around=Qe?this._map.unproject(Qe):this._map.getCenter()}return this.clear(),i.extend(ft,{noMoveStart:!0})}};function Al(Y,D){(!Y.duration||Y.duration<D.duration)&&(Y.duration=D.duration,Y.easing=D.easing)}function X(Y,D,J){var q=J.maxSpeed,K=J.linearity,de=J.deceleration,ne=i.clamp(Y*K/(D/1e3),-q,q),we=Math.abs(ne)/(de*K);return{easing:J.easing,duration:we*1e3,amount:ne*(we/2)}}var se=function(Y){function D(q,K,de,ne){ne===void 0&&(ne={});var we=o.mousePos(K.getCanvasContainer(),de),Ue=K.unproject(we);Y.call(this,q,i.extend({point:we,lngLat:Ue,originalEvent:de},ne)),this._defaultPrevented=!1,this.target=K}Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D;var J={defaultPrevented:{configurable:!0}};return D.prototype.preventDefault=function(){this._defaultPrevented=!0},J.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(D.prototype,J),D}(i.Event),Te=function(Y){function D(q,K,de){var ne=q===\"touchend\"?de.changedTouches:de.touches,we=o.touchPos(K.getCanvasContainer(),ne),Ue=we.map(function(hr){return K.unproject(hr)}),ft=we.reduce(function(hr,qt,Ve,Qe){return hr.add(qt.div(Qe.length))},new i.Point(0,0)),Xt=K.unproject(ft);Y.call(this,q,{points:we,point:ft,lngLats:Ue,lngLat:Xt,originalEvent:de}),this._defaultPrevented=!1}Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D;var J={defaultPrevented:{configurable:!0}};return D.prototype.preventDefault=function(){this._defaultPrevented=!0},J.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(D.prototype,J),D}(i.Event),Ne=function(Y){function D(q,K,de){Y.call(this,q,{originalEvent:de}),this._defaultPrevented=!1}Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D;var J={defaultPrevented:{configurable:!0}};return D.prototype.preventDefault=function(){this._defaultPrevented=!0},J.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(D.prototype,J),D}(i.Event),He=function(D,J){this._map=D,this._clickTolerance=J.clickTolerance};He.prototype.reset=function(){delete this._mousedownPos},He.prototype.wheel=function(D){return this._firePreventable(new Ne(D.type,this._map,D))},He.prototype.mousedown=function(D,J){return this._mousedownPos=J,this._firePreventable(new se(D.type,this._map,D))},He.prototype.mouseup=function(D){this._map.fire(new se(D.type,this._map,D))},He.prototype.click=function(D,J){this._mousedownPos&&this._mousedownPos.dist(J)>=this._clickTolerance||this._map.fire(new se(D.type,this._map,D))},He.prototype.dblclick=function(D){return this._firePreventable(new se(D.type,this._map,D))},He.prototype.mouseover=function(D){this._map.fire(new se(D.type,this._map,D))},He.prototype.mouseout=function(D){this._map.fire(new se(D.type,this._map,D))},He.prototype.touchstart=function(D){return this._firePreventable(new Te(D.type,this._map,D))},He.prototype.touchmove=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype.touchend=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype.touchcancel=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype._firePreventable=function(D){if(this._map.fire(D),D.defaultPrevented)return{}},He.prototype.isEnabled=function(){return!0},He.prototype.isActive=function(){return!1},He.prototype.enable=function(){},He.prototype.disable=function(){};var Ye=function(D){this._map=D};Ye.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Ye.prototype.mousemove=function(D){this._map.fire(new se(D.type,this._map,D))},Ye.prototype.mousedown=function(){this._delayContextMenu=!0},Ye.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new se(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Ye.prototype.contextmenu=function(D){this._delayContextMenu?this._contextMenuEvent=D:this._map.fire(new se(D.type,this._map,D)),this._map.listens(\"contextmenu\")&&D.preventDefault()},Ye.prototype.isEnabled=function(){return!0},Ye.prototype.isActive=function(){return!1},Ye.prototype.enable=function(){},Ye.prototype.disable=function(){};var kt=function(D,J){this._map=D,this._el=D.getCanvasContainer(),this._container=D.getContainer(),this._clickTolerance=J.clickTolerance||1};kt.prototype.isEnabled=function(){return!!this._enabled},kt.prototype.isActive=function(){return!!this._active},kt.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},kt.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},kt.prototype.mousedown=function(D,J){this.isEnabled()&&D.shiftKey&&D.button===0&&(o.disableDrag(),this._startPos=this._lastPos=J,this._active=!0)},kt.prototype.mousemoveWindow=function(D,J){if(this._active){var q=J;if(!(this._lastPos.equals(q)||!this._box&&q.dist(this._startPos)<this._clickTolerance)){var K=this._startPos;this._lastPos=q,this._box||(this._box=o.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",D));var de=Math.min(K.x,q.x),ne=Math.max(K.x,q.x),we=Math.min(K.y,q.y),Ue=Math.max(K.y,q.y);o.setTransform(this._box,\"translate(\"+de+\"px,\"+we+\"px)\"),this._box.style.width=ne-de+\"px\",this._box.style.height=Ue-we+\"px\"}}},kt.prototype.mouseupWindow=function(D,J){var q=this;if(this._active&&D.button===0){var K=this._startPos,de=J;if(this.reset(),o.suppressClick(),K.x===de.x&&K.y===de.y)this._fireEvent(\"boxzoomcancel\",D);else return this._map.fire(new i.Event(\"boxzoomend\",{originalEvent:D})),{cameraAnimation:function(ne){return ne.fitScreenCoordinates(K,de,q._map.getBearing(),{linear:!0})}}}},kt.prototype.keydown=function(D){this._active&&D.keyCode===27&&(this.reset(),this._fireEvent(\"boxzoomcancel\",D))},kt.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(o.remove(this._box),this._box=null),o.enableDrag(),delete this._startPos,delete this._lastPos},kt.prototype._fireEvent=function(D,J){return this._map.fire(new i.Event(D,{originalEvent:J}))};function nt(Y,D){for(var J={},q=0;q<Y.length;q++)J[Y[q].identifier]=D[q];return J}function jt(Y){for(var D=new i.Point(0,0),J=0,q=Y;J<q.length;J+=1){var K=q[J];D._add(K)}return D.div(Y.length)}var gr=500,yr=500,Hr=30,qr=function(D){this.reset(),this.numTouches=D.numTouches};qr.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},qr.prototype.touchstart=function(D,J,q){(this.centroid||q.length>this.numTouches)&&(this.aborted=!0),!this.aborted&&(this.startTime===void 0&&(this.startTime=D.timeStamp),q.length===this.numTouches&&(this.centroid=jt(J),this.touches=nt(q,J)))},qr.prototype.touchmove=function(D,J,q){if(!(this.aborted||!this.centroid)){var K=nt(q,J);for(var de in this.touches){var ne=this.touches[de],we=K[de];(!we||we.dist(ne)>Hr)&&(this.aborted=!0)}}},qr.prototype.touchend=function(D,J,q){if((!this.centroid||D.timeStamp-this.startTime>yr)&&(this.aborted=!0),q.length===0){var K=!this.aborted&&this.centroid;if(this.reset(),K)return K}};var _i=function(D){this.singleTap=new qr(D),this.numTaps=D.numTaps,this.reset()};_i.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},_i.prototype.touchstart=function(D,J,q){this.singleTap.touchstart(D,J,q)},_i.prototype.touchmove=function(D,J,q){this.singleTap.touchmove(D,J,q)},_i.prototype.touchend=function(D,J,q){var K=this.singleTap.touchend(D,J,q);if(K){var de=D.timeStamp-this.lastTime<gr,ne=!this.lastTap||this.lastTap.dist(K)<Hr;if((!de||!ne)&&this.reset(),this.count++,this.lastTime=D.timeStamp,this.lastTap=K,this.count===this.numTaps)return this.reset(),K}};var bi=function(){this._zoomIn=new _i({numTouches:1,numTaps:2}),this._zoomOut=new _i({numTouches:2,numTaps:1}),this.reset()};bi.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},bi.prototype.touchstart=function(D,J,q){this._zoomIn.touchstart(D,J,q),this._zoomOut.touchstart(D,J,q)},bi.prototype.touchmove=function(D,J,q){this._zoomIn.touchmove(D,J,q),this._zoomOut.touchmove(D,J,q)},bi.prototype.touchend=function(D,J,q){var K=this,de=this._zoomIn.touchend(D,J,q),ne=this._zoomOut.touchend(D,J,q);if(de)return this._active=!0,D.preventDefault(),setTimeout(function(){return K.reset()},0),{cameraAnimation:function(we){return we.easeTo({duration:300,zoom:we.getZoom()+1,around:we.unproject(de)},{originalEvent:D})}};if(ne)return this._active=!0,D.preventDefault(),setTimeout(function(){return K.reset()},0),{cameraAnimation:function(we){return we.easeTo({duration:300,zoom:we.getZoom()-1,around:we.unproject(ne)},{originalEvent:D})}}},bi.prototype.touchcancel=function(){this.reset()},bi.prototype.enable=function(){this._enabled=!0},bi.prototype.disable=function(){this._enabled=!1,this.reset()},bi.prototype.isEnabled=function(){return this._enabled},bi.prototype.isActive=function(){return this._active};var Zr=0,ai=2,gi={};gi[Zr]=1,gi[ai]=2;function Ii(Y,D){var J=gi[D];return Y.buttons===void 0||(Y.buttons&J)!==J}var Si=function(D){this.reset(),this._clickTolerance=D.clickTolerance||1};Si.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Si.prototype._correctButton=function(D,J){return!1},Si.prototype._move=function(D,J){return{}},Si.prototype.mousedown=function(D,J){if(!this._lastPoint){var q=o.mouseButton(D);this._correctButton(D,q)&&(this._lastPoint=J,this._eventButton=q)}},Si.prototype.mousemoveWindow=function(D,J){var q=this._lastPoint;if(q){if(D.preventDefault(),Ii(D,this._eventButton)){this.reset();return}if(!(!this._moved&&J.dist(q)<this._clickTolerance))return this._moved=!0,this._lastPoint=J,this._move(q,J)}},Si.prototype.mouseupWindow=function(D){if(this._lastPoint){var J=o.mouseButton(D);J===this._eventButton&&(this._moved&&o.suppressClick(),this.reset())}},Si.prototype.enable=function(){this._enabled=!0},Si.prototype.disable=function(){this._enabled=!1,this.reset()},Si.prototype.isEnabled=function(){return this._enabled},Si.prototype.isActive=function(){return this._active};var ei=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.mousedown=function(q,K){Y.prototype.mousedown.call(this,q,K),this._lastPoint&&(this._active=!0)},D.prototype._correctButton=function(q,K){return K===Zr&&!q.ctrlKey},D.prototype._move=function(q,K){return{around:K,panDelta:K.sub(q)}},D}(Si),Ln=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype._correctButton=function(q,K){return K===Zr&&q.ctrlKey||K===ai},D.prototype._move=function(q,K){var de=.8,ne=(K.x-q.x)*de;if(ne)return this._active=!0,{bearingDelta:ne}},D.prototype.contextmenu=function(q){q.preventDefault()},D}(Si),En=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype._correctButton=function(q,K){return K===Zr&&q.ctrlKey||K===ai},D.prototype._move=function(q,K){var de=-.5,ne=(K.y-q.y)*de;if(ne)return this._active=!0,{pitchDelta:ne}},D.prototype.contextmenu=function(q){q.preventDefault()},D}(Si),Un=function(D){this._minTouches=1,this._clickTolerance=D.clickTolerance||1,this.reset()};Un.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new i.Point(0,0)},Un.prototype.touchstart=function(D,J,q){return this._calculateTransform(D,J,q)},Un.prototype.touchmove=function(D,J,q){if(!(!this._active||q.length<this._minTouches))return D.preventDefault(),this._calculateTransform(D,J,q)},Un.prototype.touchend=function(D,J,q){this._calculateTransform(D,J,q),this._active&&q.length<this._minTouches&&this.reset()},Un.prototype.touchcancel=function(){this.reset()},Un.prototype._calculateTransform=function(D,J,q){q.length>0&&(this._active=!0);var K=nt(q,J),de=new i.Point(0,0),ne=new i.Point(0,0),we=0;for(var Ue in K){var ft=K[Ue],Xt=this._touches[Ue];Xt&&(de._add(ft),ne._add(ft.sub(Xt)),we++,K[Ue]=ft)}if(this._touches=K,!(we<this._minTouches||!ne.mag())){var hr=ne.div(we);if(this._sum._add(hr),!(this._sum.mag()<this._clickTolerance)){var qt=de.div(we);return{around:qt,panDelta:hr}}}},Un.prototype.enable=function(){this._enabled=!0},Un.prototype.disable=function(){this._enabled=!1,this.reset()},Un.prototype.isEnabled=function(){return this._enabled},Un.prototype.isActive=function(){return this._active};var ia=function(){this.reset()};ia.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},ia.prototype._start=function(D){},ia.prototype._move=function(D,J,q){return{}},ia.prototype.touchstart=function(D,J,q){this._firstTwoTouches||q.length<2||(this._firstTwoTouches=[q[0].identifier,q[1].identifier],this._start([J[0],J[1]]))},ia.prototype.touchmove=function(D,J,q){if(this._firstTwoTouches){D.preventDefault();var K=this._firstTwoTouches,de=K[0],ne=K[1],we=Ea(q,J,de),Ue=Ea(q,J,ne);if(!(!we||!Ue)){var ft=this._aroundCenter?null:we.add(Ue).div(2);return this._move([we,Ue],ft,D)}}},ia.prototype.touchend=function(D,J,q){if(this._firstTwoTouches){var K=this._firstTwoTouches,de=K[0],ne=K[1],we=Ea(q,J,de),Ue=Ea(q,J,ne);we&&Ue||(this._active&&o.suppressClick(),this.reset())}},ia.prototype.touchcancel=function(){this.reset()},ia.prototype.enable=function(D){this._enabled=!0,this._aroundCenter=!!D&&D.around===\"center\"},ia.prototype.disable=function(){this._enabled=!1,this.reset()},ia.prototype.isEnabled=function(){return this._enabled},ia.prototype.isActive=function(){return this._active};function Ea(Y,D,J){for(var q=0;q<Y.length;q++)if(Y[q].identifier===J)return D[q]}var Ia=.1;function yo(Y,D){return Math.log(Y/D)/Math.LN2}var Da=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.reset=function(){Y.prototype.reset.call(this),delete this._distance,delete this._startDistance},D.prototype._start=function(q){this._startDistance=this._distance=q[0].dist(q[1])},D.prototype._move=function(q,K){var de=this._distance;if(this._distance=q[0].dist(q[1]),!(!this._active&&Math.abs(yo(this._distance,this._startDistance))<Ia))return this._active=!0,{zoomDelta:yo(this._distance,de),pinchAround:K}},D}(ia),go=25;function Is(Y,D){return Y.angleWith(D)*180/Math.PI}var Ms=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.reset=function(){Y.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},D.prototype._start=function(q){this._startVector=this._vector=q[0].sub(q[1]),this._minDiameter=q[0].dist(q[1])},D.prototype._move=function(q,K){var de=this._vector;if(this._vector=q[0].sub(q[1]),!(!this._active&&this._isBelowThreshold(this._vector)))return this._active=!0,{bearingDelta:Is(this._vector,de),pinchAround:K}},D.prototype._isBelowThreshold=function(q){this._minDiameter=Math.min(this._minDiameter,q.mag());var K=Math.PI*this._minDiameter,de=go/K*360,ne=Is(q,this._startVector);return Math.abs(ne)<de},D}(ia);function Xs(Y){return Math.abs(Y.y)>Math.abs(Y.x)}var Gn=100,Ha=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.reset=function(){Y.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},D.prototype._start=function(q){this._lastPoints=q,Xs(q[0].sub(q[1]))&&(this._valid=!1)},D.prototype._move=function(q,K,de){var ne=q[0].sub(this._lastPoints[0]),we=q[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(ne,we,de.timeStamp),!!this._valid){this._lastPoints=q,this._active=!0;var Ue=(ne.y+we.y)/2,ft=-.5;return{pitchDelta:Ue*ft}}},D.prototype.gestureBeginsVertically=function(q,K,de){if(this._valid!==void 0)return this._valid;var ne=2,we=q.mag()>=ne,Ue=K.mag()>=ne;if(!(!we&&!Ue)){if(!we||!Ue)return this._firstMove===void 0&&(this._firstMove=de),de-this._firstMove<Gn?void 0:!1;var ft=q.y>0==K.y>0;return Xs(q)&&Xs(K)&&ft}},D}(ia),Fo={panStep:100,bearingStep:15,pitchStep:10},Uo=function(){var D=Fo;this._panStep=D.panStep,this._bearingStep=D.bearingStep,this._pitchStep=D.pitchStep,this._rotationDisabled=!1};Uo.prototype.reset=function(){this._active=!1},Uo.prototype.keydown=function(D){var J=this;if(!(D.altKey||D.ctrlKey||D.metaKey)){var q=0,K=0,de=0,ne=0,we=0;switch(D.keyCode){case 61:case 107:case 171:case 187:q=1;break;case 189:case 109:case 173:q=-1;break;case 37:D.shiftKey?K=-1:(D.preventDefault(),ne=-1);break;case 39:D.shiftKey?K=1:(D.preventDefault(),ne=1);break;case 38:D.shiftKey?de=1:(D.preventDefault(),we=-1);break;case 40:D.shiftKey?de=-1:(D.preventDefault(),we=1);break;default:return}return this._rotationDisabled&&(K=0,de=0),{cameraAnimation:function(Ue){var ft=Ue.getZoom();Ue.easeTo({duration:300,easeId:\"keyboardHandler\",easing:$s,zoom:q?Math.round(ft)+q*(D.shiftKey?2:1):ft,bearing:Ue.getBearing()+K*J._bearingStep,pitch:Ue.getPitch()+de*J._pitchStep,offset:[-ne*J._panStep,-we*J._panStep],center:Ue.getCenter()},{originalEvent:D})}}}},Uo.prototype.enable=function(){this._enabled=!0},Uo.prototype.disable=function(){this._enabled=!1,this.reset()},Uo.prototype.isEnabled=function(){return this._enabled},Uo.prototype.isActive=function(){return this._active},Uo.prototype.disableRotation=function(){this._rotationDisabled=!0},Uo.prototype.enableRotation=function(){this._rotationDisabled=!1};function $s(Y){return Y*(2-Y)}var Sl=4.000244140625,bu=1/100,dl=1/450,Sc=2,Me=function(D,J){this._map=D,this._el=D.getCanvasContainer(),this._handler=J,this._delta=0,this._defaultZoomRate=bu,this._wheelZoomRate=dl,i.bindAll([\"_onTimeout\"],this)};Me.prototype.setZoomRate=function(D){this._defaultZoomRate=D},Me.prototype.setWheelZoomRate=function(D){this._wheelZoomRate=D},Me.prototype.isEnabled=function(){return!!this._enabled},Me.prototype.isActive=function(){return!!this._active||this._finishTimeout!==void 0},Me.prototype.isZooming=function(){return!!this._zooming},Me.prototype.enable=function(D){this.isEnabled()||(this._enabled=!0,this._aroundCenter=D&&D.around===\"center\")},Me.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Me.prototype.wheel=function(D){if(this.isEnabled()){var J=D.deltaMode===i.window.WheelEvent.DOM_DELTA_LINE?D.deltaY*40:D.deltaY,q=i.browser.now(),K=q-(this._lastWheelEventTime||0);this._lastWheelEventTime=q,J!==0&&J%Sl===0?this._type=\"wheel\":J!==0&&Math.abs(J)<4?this._type=\"trackpad\":K>400?(this._type=null,this._lastValue=J,this._timeout=setTimeout(this._onTimeout,40,D)):this._type||(this._type=Math.abs(K*J)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,J+=this._lastValue)),D.shiftKey&&J&&(J=J/4),this._type&&(this._lastWheelEvent=D,this._delta-=J,this._active||this._start(D)),D.preventDefault()}},Me.prototype._onTimeout=function(D){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(D)},Me.prototype._start=function(D){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var J=o.mousePos(this._el,D);this._around=i.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(J)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},Me.prototype.renderFrame=function(){var D=this;if(this._frameId&&(this._frameId=null,!!this.isActive())){var J=this._map.transform;if(this._delta!==0){var q=this._type===\"wheel\"&&Math.abs(this._delta)>Sl?this._wheelZoomRate:this._defaultZoomRate,K=Sc/(1+Math.exp(-Math.abs(this._delta*q)));this._delta<0&&K!==0&&(K=1/K);var de=typeof this._targetZoom==\"number\"?J.zoomScale(this._targetZoom):J.scale;this._targetZoom=Math.min(J.maxZoom,Math.max(J.minZoom,J.scaleZoom(de*K))),this._type===\"wheel\"&&(this._startZoom=J.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var ne=typeof this._targetZoom==\"number\"?this._targetZoom:J.zoom,we=this._startZoom,Ue=this._easing,ft=!1,Xt;if(this._type===\"wheel\"&&we&&Ue){var hr=Math.min((i.browser.now()-this._lastWheelEventTime)/200,1),qt=Ue(hr);Xt=i.number(we,ne,qt),hr<1?this._frameId||(this._frameId=!0):ft=!0}else Xt=ne,ft=!0;return this._active=!0,ft&&(this._active=!1,this._finishTimeout=setTimeout(function(){D._zooming=!1,D._handler._triggerRenderFrame(),delete D._targetZoom,delete D._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!ft,zoomDelta:Xt-J.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},Me.prototype._smoothOutEasing=function(D){var J=i.ease;if(this._prevEase){var q=this._prevEase,K=(i.browser.now()-q.start)/q.duration,de=q.easing(K+.01)-q.easing(K),ne=.27/Math.sqrt(de*de+1e-4)*.01,we=Math.sqrt(.27*.27-ne*ne);J=i.bezier(ne,we,.25,1)}return this._prevEase={start:i.browser.now(),duration:D,easing:J},J},Me.prototype.reset=function(){this._active=!1};var bt=function(D,J){this._clickZoom=D,this._tapZoom=J};bt.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},bt.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},bt.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},bt.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var zt=function(){this.reset()};zt.prototype.reset=function(){this._active=!1},zt.prototype.dblclick=function(D,J){return D.preventDefault(),{cameraAnimation:function(q){q.easeTo({duration:300,zoom:q.getZoom()+(D.shiftKey?-1:1),around:q.unproject(J)},{originalEvent:D})}}},zt.prototype.enable=function(){this._enabled=!0},zt.prototype.disable=function(){this._enabled=!1,this.reset()},zt.prototype.isEnabled=function(){return this._enabled},zt.prototype.isActive=function(){return this._active};var Rr=function(){this._tap=new _i({numTouches:1,numTaps:1}),this.reset()};Rr.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},Rr.prototype.touchstart=function(D,J,q){this._swipePoint||(this._tapTime&&D.timeStamp-this._tapTime>gr&&this.reset(),this._tapTime?q.length>0&&(this._swipePoint=J[0],this._swipeTouch=q[0].identifier):this._tap.touchstart(D,J,q))},Rr.prototype.touchmove=function(D,J,q){if(!this._tapTime)this._tap.touchmove(D,J,q);else if(this._swipePoint){if(q[0].identifier!==this._swipeTouch)return;var K=J[0],de=K.y-this._swipePoint.y;return this._swipePoint=K,D.preventDefault(),this._active=!0,{zoomDelta:de/128}}},Rr.prototype.touchend=function(D,J,q){if(this._tapTime)this._swipePoint&&q.length===0&&this.reset();else{var K=this._tap.touchend(D,J,q);K&&(this._tapTime=D.timeStamp)}},Rr.prototype.touchcancel=function(){this.reset()},Rr.prototype.enable=function(){this._enabled=!0},Rr.prototype.disable=function(){this._enabled=!1,this.reset()},Rr.prototype.isEnabled=function(){return this._enabled},Rr.prototype.isActive=function(){return this._active};var jr=function(D,J,q){this._el=D,this._mousePan=J,this._touchPan=q};jr.prototype.enable=function(D){this._inertiaOptions=D||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},jr.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},jr.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},jr.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var Nr=function(D,J,q){this._pitchWithRotate=D.pitchWithRotate,this._mouseRotate=J,this._mousePitch=q};Nr.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},Nr.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},Nr.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},Nr.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var Gr=function(D,J,q,K){this._el=D,this._touchZoom=J,this._touchRotate=q,this._tapDragZoom=K,this._rotationDisabled=!1,this._enabled=!0};Gr.prototype.enable=function(D){this._touchZoom.enable(D),this._rotationDisabled||this._touchRotate.enable(D),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},Gr.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},Gr.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},Gr.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},Gr.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},Gr.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var mi=function(Y){return Y.zoom||Y.drag||Y.pitch||Y.rotate},Ui=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D}(i.Event);function qi(Y){return Y.panDelta&&Y.panDelta.mag()||Y.zoomDelta||Y.bearingDelta||Y.pitchDelta}var Ei=function(D,J){this._map=D,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Tl(D),this._bearingSnap=J.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(J),i.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var q=this._el;this._listeners=[[q,\"touchstart\",{passive:!0}],[q,\"touchmove\",{passive:!1}],[q,\"touchend\",void 0],[q,\"touchcancel\",void 0],[q,\"mousedown\",void 0],[q,\"mousemove\",void 0],[q,\"mouseup\",void 0],[i.window.document,\"mousemove\",{capture:!0}],[i.window.document,\"mouseup\",void 0],[q,\"mouseover\",void 0],[q,\"mouseout\",void 0],[q,\"dblclick\",void 0],[q,\"click\",void 0],[q,\"keydown\",{capture:!1}],[q,\"keyup\",void 0],[q,\"wheel\",{passive:!1}],[q,\"contextmenu\",void 0],[i.window,\"blur\",void 0]];for(var K=0,de=this._listeners;K<de.length;K+=1){var ne=de[K],we=ne[0],Ue=ne[1],ft=ne[2];o.addEventListener(we,Ue,we===i.window.document?this.handleWindowEvent:this.handleEvent,ft)}};Ei.prototype.destroy=function(){for(var D=0,J=this._listeners;D<J.length;D+=1){var q=J[D],K=q[0],de=q[1],ne=q[2];o.removeEventListener(K,de,K===i.window.document?this.handleWindowEvent:this.handleEvent,ne)}},Ei.prototype._addDefaultHandlers=function(D){var J=this._map,q=J.getCanvasContainer();this._add(\"mapEvent\",new He(J,D));var K=J.boxZoom=new kt(J,D);this._add(\"boxZoom\",K);var de=new bi,ne=new zt;J.doubleClickZoom=new bt(ne,de),this._add(\"tapZoom\",de),this._add(\"clickZoom\",ne);var we=new Rr;this._add(\"tapDragZoom\",we);var Ue=J.touchPitch=new Ha;this._add(\"touchPitch\",Ue);var ft=new Ln(D),Xt=new En(D);J.dragRotate=new Nr(D,ft,Xt),this._add(\"mouseRotate\",ft,[\"mousePitch\"]),this._add(\"mousePitch\",Xt,[\"mouseRotate\"]);var hr=new ei(D),qt=new Un(D);J.dragPan=new jr(q,hr,qt),this._add(\"mousePan\",hr),this._add(\"touchPan\",qt,[\"touchZoom\",\"touchRotate\"]);var Ve=new Ms,Qe=new Da;J.touchZoomRotate=new Gr(q,Qe,Ve,we),this._add(\"touchRotate\",Ve,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",Qe,[\"touchPan\",\"touchRotate\"]);var at=J.scrollZoom=new Me(J,this);this._add(\"scrollZoom\",at,[\"mousePan\"]);var Ct=J.keyboard=new Uo;this._add(\"keyboard\",Ct),this._add(\"blockableMapEvent\",new Ye(J));for(var Ot=0,Rt=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];Ot<Rt.length;Ot+=1){var Bt=Rt[Ot];D.interactive&&D[Bt]&&J[Bt].enable(D[Bt])}},Ei.prototype._add=function(D,J,q){this._handlers.push({handlerName:D,handler:J,allowed:q}),this._handlersById[D]=J},Ei.prototype.stop=function(D){if(!this._updatingCamera){for(var J=0,q=this._handlers;J<q.length;J+=1){var K=q[J],de=K.handler;de.reset()}this._inertia.clear(),this._fireEvents({},{},D),this._changes=[]}},Ei.prototype.isActive=function(){for(var D=0,J=this._handlers;D<J.length;D+=1){var q=J[D],K=q.handler;if(K.isActive())return!0}return!1},Ei.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},Ei.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},Ei.prototype.isMoving=function(){return!!mi(this._eventsInProgress)||this.isZooming()},Ei.prototype._blockedByActive=function(D,J,q){for(var K in D)if(K!==q&&(!J||J.indexOf(K)<0))return!0;return!1},Ei.prototype.handleWindowEvent=function(D){this.handleEvent(D,D.type+\"Window\")},Ei.prototype._getMapTouches=function(D){for(var J=[],q=0,K=D;q<K.length;q+=1){var de=K[q],ne=de.target;this._el.contains(ne)&&J.push(de)}return J},Ei.prototype.handleEvent=function(D,J){if(D.type===\"blur\"){this.stop(!0);return}this._updatingCamera=!0;for(var q=D.type===\"renderFrame\"?void 0:D,K={needsRenderFrame:!1},de={},ne={},we=D.touches?this._getMapTouches(D.touches):void 0,Ue=we?o.touchPos(this._el,we):o.mousePos(this._el,D),ft=0,Xt=this._handlers;ft<Xt.length;ft+=1){var hr=Xt[ft],qt=hr.handlerName,Ve=hr.handler,Qe=hr.allowed;if(Ve.isEnabled()){var at=void 0;this._blockedByActive(ne,Qe,qt)?Ve.reset():Ve[J||D.type]&&(at=Ve[J||D.type](D,Ue,we),this.mergeHandlerResult(K,de,at,qt,q),at&&at.needsRenderFrame&&this._triggerRenderFrame()),(at||Ve.isActive())&&(ne[qt]=Ve)}}var Ct={};for(var Ot in this._previousActiveHandlers)ne[Ot]||(Ct[Ot]=q);this._previousActiveHandlers=ne,(Object.keys(Ct).length||qi(K))&&(this._changes.push([K,de,Ct]),this._triggerRenderFrame()),(Object.keys(ne).length||qi(K))&&this._map._stop(!0),this._updatingCamera=!1;var Rt=K.cameraAnimation;Rt&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],Rt(this._map))},Ei.prototype.mergeHandlerResult=function(D,J,q,K,de){if(q){i.extend(D,q);var ne={handlerName:K,originalEvent:q.originalEvent||de};q.zoomDelta!==void 0&&(J.zoom=ne),q.panDelta!==void 0&&(J.drag=ne),q.pitchDelta!==void 0&&(J.pitch=ne),q.bearingDelta!==void 0&&(J.rotate=ne)}},Ei.prototype._applyChanges=function(){for(var D={},J={},q={},K=0,de=this._changes;K<de.length;K+=1){var ne=de[K],we=ne[0],Ue=ne[1],ft=ne[2];we.panDelta&&(D.panDelta=(D.panDelta||new i.Point(0,0))._add(we.panDelta)),we.zoomDelta&&(D.zoomDelta=(D.zoomDelta||0)+we.zoomDelta),we.bearingDelta&&(D.bearingDelta=(D.bearingDelta||0)+we.bearingDelta),we.pitchDelta&&(D.pitchDelta=(D.pitchDelta||0)+we.pitchDelta),we.around!==void 0&&(D.around=we.around),we.pinchAround!==void 0&&(D.pinchAround=we.pinchAround),we.noInertia&&(D.noInertia=we.noInertia),i.extend(J,Ue),i.extend(q,ft)}this._updateMapTransform(D,J,q),this._changes=[]},Ei.prototype._updateMapTransform=function(D,J,q){var K=this._map,de=K.transform;if(!qi(D))return this._fireEvents(J,q,!0);var ne=D.panDelta,we=D.zoomDelta,Ue=D.bearingDelta,ft=D.pitchDelta,Xt=D.around,hr=D.pinchAround;hr!==void 0&&(Xt=hr),K._stop(!0),Xt=Xt||K.transform.centerPoint;var qt=de.pointLocation(ne?Xt.sub(ne):Xt);Ue&&(de.bearing+=Ue),ft&&(de.pitch+=ft),we&&(de.zoom+=we),de.setLocationAtPoint(qt,Xt),this._map._update(),D.noInertia||this._inertia.record(D),this._fireEvents(J,q,!0)},Ei.prototype._fireEvents=function(D,J,q){var K=this,de=mi(this._eventsInProgress),ne=mi(D),we={};for(var Ue in D){var ft=D[Ue],Xt=ft.originalEvent;this._eventsInProgress[Ue]||(we[Ue+\"start\"]=Xt),this._eventsInProgress[Ue]=D[Ue]}!de&&ne&&this._fireEvent(\"movestart\",ne.originalEvent);for(var hr in we)this._fireEvent(hr,we[hr]);ne&&this._fireEvent(\"move\",ne.originalEvent);for(var qt in D){var Ve=D[qt],Qe=Ve.originalEvent;this._fireEvent(qt,Qe)}var at={},Ct;for(var Ot in this._eventsInProgress){var Rt=this._eventsInProgress[Ot],Bt=Rt.handlerName,Dt=Rt.originalEvent;this._handlersById[Bt].isActive()||(delete this._eventsInProgress[Ot],Ct=J[Bt]||Dt,at[Ot+\"end\"]=Ct)}for(var yt in at)this._fireEvent(yt,at[yt]);var Pt=mi(this._eventsInProgress);if(q&&(de||ne)&&!Pt){this._updatingCamera=!0;var ht=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),ur=function(br){return br!==0&&-K._bearingSnap<br&&br<K._bearingSnap};ht?(ur(ht.bearing||this._map.getBearing())&&(ht.bearing=0),this._map.easeTo(ht,{originalEvent:Ct})):(this._map.fire(new i.Event(\"moveend\",{originalEvent:Ct})),ur(this._map.getBearing())&&this._map.resetNorth()),this._updatingCamera=!1}},Ei.prototype._fireEvent=function(D,J){this._map.fire(new i.Event(D,J?{originalEvent:J}:{}))},Ei.prototype._requestFrame=function(){var D=this;return this._map.triggerRepaint(),this._map._renderTaskQueue.add(function(J){delete D._frameId,D.handleEvent(new Ui(\"renderFrame\",{timeStamp:J})),D._applyChanges()})},Ei.prototype._triggerRenderFrame=function(){this._frameId===void 0&&(this._frameId=this._requestFrame())};var Hn=function(Y){function D(J,q){Y.call(this),this._moving=!1,this._zooming=!1,this.transform=J,this._bearingSnap=q.bearingSnap,i.bindAll([\"_renderFrameCallback\"],this)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.getCenter=function(){return new i.LngLat(this.transform.center.lng,this.transform.center.lat)},D.prototype.setCenter=function(q,K){return this.jumpTo({center:q},K)},D.prototype.panBy=function(q,K,de){return q=i.Point.convert(q).mult(-1),this.panTo(this.transform.center,i.extend({offset:q},K),de)},D.prototype.panTo=function(q,K,de){return this.easeTo(i.extend({center:q},K),de)},D.prototype.getZoom=function(){return this.transform.zoom},D.prototype.setZoom=function(q,K){return this.jumpTo({zoom:q},K),this},D.prototype.zoomTo=function(q,K,de){return this.easeTo(i.extend({zoom:q},K),de)},D.prototype.zoomIn=function(q,K){return this.zoomTo(this.getZoom()+1,q,K),this},D.prototype.zoomOut=function(q,K){return this.zoomTo(this.getZoom()-1,q,K),this},D.prototype.getBearing=function(){return this.transform.bearing},D.prototype.setBearing=function(q,K){return this.jumpTo({bearing:q},K),this},D.prototype.getPadding=function(){return this.transform.padding},D.prototype.setPadding=function(q,K){return this.jumpTo({padding:q},K),this},D.prototype.rotateTo=function(q,K,de){return this.easeTo(i.extend({bearing:q},K),de)},D.prototype.resetNorth=function(q,K){return this.rotateTo(0,i.extend({duration:1e3},q),K),this},D.prototype.resetNorthPitch=function(q,K){return this.easeTo(i.extend({bearing:0,pitch:0,duration:1e3},q),K),this},D.prototype.snapToNorth=function(q,K){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(q,K):this},D.prototype.getPitch=function(){return this.transform.pitch},D.prototype.setPitch=function(q,K){return this.jumpTo({pitch:q},K),this},D.prototype.cameraForBounds=function(q,K){q=i.LngLatBounds.convert(q);var de=K&&K.bearing||0;return this._cameraForBoxAndBearing(q.getNorthWest(),q.getSouthEast(),de,K)},D.prototype._cameraForBoxAndBearing=function(q,K,de,ne){var we={top:0,bottom:0,right:0,left:0};if(ne=i.extend({padding:we,offset:[0,0],maxZoom:this.transform.maxZoom},ne),typeof ne.padding==\"number\"){var Ue=ne.padding;ne.padding={top:Ue,bottom:Ue,right:Ue,left:Ue}}ne.padding=i.extend(we,ne.padding);var ft=this.transform,Xt=ft.padding,hr=ft.project(i.LngLat.convert(q)),qt=ft.project(i.LngLat.convert(K)),Ve=hr.rotate(-de*Math.PI/180),Qe=qt.rotate(-de*Math.PI/180),at=new i.Point(Math.max(Ve.x,Qe.x),Math.max(Ve.y,Qe.y)),Ct=new i.Point(Math.min(Ve.x,Qe.x),Math.min(Ve.y,Qe.y)),Ot=at.sub(Ct),Rt=(ft.width-(Xt.left+Xt.right+ne.padding.left+ne.padding.right))/Ot.x,Bt=(ft.height-(Xt.top+Xt.bottom+ne.padding.top+ne.padding.bottom))/Ot.y;if(Bt<0||Rt<0){i.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\");return}var Dt=Math.min(ft.scaleZoom(ft.scale*Math.min(Rt,Bt)),ne.maxZoom),yt=typeof ne.offset.x==\"number\"?new i.Point(ne.offset.x,ne.offset.y):i.Point.convert(ne.offset),Pt=(ne.padding.left-ne.padding.right)/2,ht=(ne.padding.top-ne.padding.bottom)/2,ur=new i.Point(Pt,ht),br=ur.rotate(de*Math.PI/180),Ur=yt.add(br),Di=Ur.mult(ft.scale/ft.zoomScale(Dt)),fi=ft.unproject(hr.add(qt).div(2).sub(Di));return{center:fi,zoom:Dt,bearing:de}},D.prototype.fitBounds=function(q,K,de){return this._fitInternal(this.cameraForBounds(q,K),K,de)},D.prototype.fitScreenCoordinates=function(q,K,de,ne,we){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(i.Point.convert(q)),this.transform.pointLocation(i.Point.convert(K)),de,ne),ne,we)},D.prototype._fitInternal=function(q,K,de){return q?(K=i.extend(q,K),delete K.padding,K.linear?this.easeTo(K,de):this.flyTo(K,de)):this},D.prototype.jumpTo=function(q,K){this.stop();var de=this.transform,ne=!1,we=!1,Ue=!1;return\"zoom\"in q&&de.zoom!==+q.zoom&&(ne=!0,de.zoom=+q.zoom),q.center!==void 0&&(de.center=i.LngLat.convert(q.center)),\"bearing\"in q&&de.bearing!==+q.bearing&&(we=!0,de.bearing=+q.bearing),\"pitch\"in q&&de.pitch!==+q.pitch&&(Ue=!0,de.pitch=+q.pitch),q.padding!=null&&!de.isPaddingEqual(q.padding)&&(de.padding=q.padding),this.fire(new i.Event(\"movestart\",K)).fire(new i.Event(\"move\",K)),ne&&this.fire(new i.Event(\"zoomstart\",K)).fire(new i.Event(\"zoom\",K)).fire(new i.Event(\"zoomend\",K)),we&&this.fire(new i.Event(\"rotatestart\",K)).fire(new i.Event(\"rotate\",K)).fire(new i.Event(\"rotateend\",K)),Ue&&this.fire(new i.Event(\"pitchstart\",K)).fire(new i.Event(\"pitch\",K)).fire(new i.Event(\"pitchend\",K)),this.fire(new i.Event(\"moveend\",K))},D.prototype.easeTo=function(q,K){var de=this;this._stop(!1,q.easeId),q=i.extend({offset:[0,0],duration:500,easing:i.ease},q),(q.animate===!1||!q.essential&&i.browser.prefersReducedMotion)&&(q.duration=0);var ne=this.transform,we=this.getZoom(),Ue=this.getBearing(),ft=this.getPitch(),Xt=this.getPadding(),hr=\"zoom\"in q?+q.zoom:we,qt=\"bearing\"in q?this._normalizeBearing(q.bearing,Ue):Ue,Ve=\"pitch\"in q?+q.pitch:ft,Qe=\"padding\"in q?q.padding:ne.padding,at=i.Point.convert(q.offset),Ct=ne.centerPoint.add(at),Ot=ne.pointLocation(Ct),Rt=i.LngLat.convert(q.center||Ot);this._normalizeCenter(Rt);var Bt=ne.project(Ot),Dt=ne.project(Rt).sub(Bt),yt=ne.zoomScale(hr-we),Pt,ht;q.around&&(Pt=i.LngLat.convert(q.around),ht=ne.locationPoint(Pt));var ur={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||hr!==we,this._rotating=this._rotating||Ue!==qt,this._pitching=this._pitching||Ve!==ft,this._padding=!ne.isPaddingEqual(Qe),this._easeId=q.easeId,this._prepareEase(K,q.noMoveStart,ur),this._ease(function(br){if(de._zooming&&(ne.zoom=i.number(we,hr,br)),de._rotating&&(ne.bearing=i.number(Ue,qt,br)),de._pitching&&(ne.pitch=i.number(ft,Ve,br)),de._padding&&(ne.interpolatePadding(Xt,Qe,br),Ct=ne.centerPoint.add(at)),Pt)ne.setLocationAtPoint(Pt,ht);else{var Ur=ne.zoomScale(ne.zoom-we),Di=hr>we?Math.min(2,yt):Math.max(.5,yt),fi=Math.pow(Di,1-br),Ti=ne.unproject(Bt.add(Dt.mult(br*fi)).mult(Ur));ne.setLocationAtPoint(ne.renderWorldCopies?Ti.wrap():Ti,Ct)}de._fireMoveEvents(K)},function(br){de._afterEase(K,br)},q),this},D.prototype._prepareEase=function(q,K,de){de===void 0&&(de={}),this._moving=!0,!K&&!de.moving&&this.fire(new i.Event(\"movestart\",q)),this._zooming&&!de.zooming&&this.fire(new i.Event(\"zoomstart\",q)),this._rotating&&!de.rotating&&this.fire(new i.Event(\"rotatestart\",q)),this._pitching&&!de.pitching&&this.fire(new i.Event(\"pitchstart\",q))},D.prototype._fireMoveEvents=function(q){this.fire(new i.Event(\"move\",q)),this._zooming&&this.fire(new i.Event(\"zoom\",q)),this._rotating&&this.fire(new i.Event(\"rotate\",q)),this._pitching&&this.fire(new i.Event(\"pitch\",q))},D.prototype._afterEase=function(q,K){if(!(this._easeId&&K&&this._easeId===K)){delete this._easeId;var de=this._zooming,ne=this._rotating,we=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,de&&this.fire(new i.Event(\"zoomend\",q)),ne&&this.fire(new i.Event(\"rotateend\",q)),we&&this.fire(new i.Event(\"pitchend\",q)),this.fire(new i.Event(\"moveend\",q))}},D.prototype.flyTo=function(q,K){var de=this;if(!q.essential&&i.browser.prefersReducedMotion){var ne=i.pick(q,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(ne,K)}this.stop(),q=i.extend({offset:[0,0],speed:1.2,curve:1.42,easing:i.ease},q);var we=this.transform,Ue=this.getZoom(),ft=this.getBearing(),Xt=this.getPitch(),hr=this.getPadding(),qt=\"zoom\"in q?i.clamp(+q.zoom,we.minZoom,we.maxZoom):Ue,Ve=\"bearing\"in q?this._normalizeBearing(q.bearing,ft):ft,Qe=\"pitch\"in q?+q.pitch:Xt,at=\"padding\"in q?q.padding:we.padding,Ct=we.zoomScale(qt-Ue),Ot=i.Point.convert(q.offset),Rt=we.centerPoint.add(Ot),Bt=we.pointLocation(Rt),Dt=i.LngLat.convert(q.center||Bt);this._normalizeCenter(Dt);var yt=we.project(Bt),Pt=we.project(Dt).sub(yt),ht=q.curve,ur=Math.max(we.width,we.height),br=ur/Ct,Ur=Pt.mag();if(\"minZoom\"in q){var Di=i.clamp(Math.min(q.minZoom,Ue,qt),we.minZoom,we.maxZoom),fi=ur/we.zoomScale(Di-Ue);ht=Math.sqrt(fi/Ur*2)}var Ti=ht*ht;function gn(so){var Zo=(br*br-ur*ur+(so?-1:1)*Ti*Ti*Ur*Ur)/(2*(so?br:ur)*Ti*Ur);return Math.log(Math.sqrt(Zo*Zo+1)-Zo)}function rn(so){return(Math.exp(so)-Math.exp(-so))/2}function Ci(so){return(Math.exp(so)+Math.exp(-so))/2}function Bi(so){return rn(so)/Ci(so)}var Gi=gn(0),sn=function(so){return Ci(Gi)/Ci(Gi+ht*so)},zn=function(so){return ur*((Ci(Gi)*Bi(Gi+ht*so)-rn(Gi))/Ti)/Ur},Ja=(gn(1)-Gi)/ht;if(Math.abs(Ur)<1e-6||!isFinite(Ja)){if(Math.abs(ur-br)<1e-6)return this.easeTo(q,K);var co=br<ur?-1:1;Ja=Math.abs(Math.log(br/ur))/ht,zn=function(){return 0},sn=function(so){return Math.exp(co*ht*so)}}if(\"duration\"in q)q.duration=+q.duration;else{var ts=\"screenSpeed\"in q?+q.screenSpeed/ht:+q.speed;q.duration=1e3*Ja/ts}return q.maxDuration&&q.duration>q.maxDuration&&(q.duration=0),this._zooming=!0,this._rotating=ft!==Ve,this._pitching=Qe!==Xt,this._padding=!we.isPaddingEqual(at),this._prepareEase(K,!1),this._ease(function(so){var Zo=so*Ja,ms=1/sn(Zo);we.zoom=so===1?qt:Ue+we.scaleZoom(ms),de._rotating&&(we.bearing=i.number(ft,Ve,so)),de._pitching&&(we.pitch=i.number(Xt,Qe,so)),de._padding&&(we.interpolatePadding(hr,at,so),Rt=we.centerPoint.add(Ot));var ou=so===1?Dt:we.unproject(yt.add(Pt.mult(zn(Zo))).mult(ms));we.setLocationAtPoint(we.renderWorldCopies?ou.wrap():ou,Rt),de._fireMoveEvents(K)},function(){return de._afterEase(K)},q),this},D.prototype.isEasing=function(){return!!this._easeFrameId},D.prototype.stop=function(){return this._stop()},D.prototype._stop=function(q,K){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var de=this._onEaseEnd;delete this._onEaseEnd,de.call(this,K)}if(!q){var ne=this.handlers;ne&&ne.stop(!1)}return this},D.prototype._ease=function(q,K,de){de.animate===!1||de.duration===0?(q(1),K()):(this._easeStart=i.browser.now(),this._easeOptions=de,this._onEaseFrame=q,this._onEaseEnd=K,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},D.prototype._renderFrameCallback=function(){var q=Math.min((i.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(q)),q<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},D.prototype._normalizeBearing=function(q,K){q=i.wrap(q,-180,180);var de=Math.abs(q-K);return Math.abs(q-360-K)<de&&(q-=360),Math.abs(q+360-K)<de&&(q+=360),q},D.prototype._normalizeCenter=function(q){var K=this.transform;if(!(!K.renderWorldCopies||K.lngRange)){var de=q.lng-K.center.lng;q.lng+=de>180?-360:de<-180?360:0}},D}(i.Evented),en=function(D){D===void 0&&(D={}),this.options=D,i.bindAll([\"_toggleAttribution\",\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};en.prototype.getDefaultPosition=function(){return\"bottom-right\"},en.prototype.onAdd=function(D){var J=this.options&&this.options.compact;return this._map=D,this._container=o.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._compactButton=o.create(\"button\",\"mapboxgl-ctrl-attrib-button\",this._container),this._compactButton.addEventListener(\"click\",this._toggleAttribution),this._setElementTitle(this._compactButton,\"ToggleAttribution\"),this._innerContainer=o.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),this._innerContainer.setAttribute(\"role\",\"list\"),J&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),J===void 0&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},en.prototype.onRemove=function(){o.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},en.prototype._setElementTitle=function(D,J){var q=this._map._getUIString(\"AttributionControl.\"+J);D.title=q,D.setAttribute(\"aria-label\",q)},en.prototype._toggleAttribution=function(){this._container.classList.contains(\"mapboxgl-compact-show\")?(this._container.classList.remove(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"false\")):(this._container.classList.add(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"true\"))},en.prototype._updateEditLink=function(){var D=this._editLink;D||(D=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var J=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||i.config.ACCESS_TOKEN}];if(D){var q=J.reduce(function(K,de,ne){return de.value&&(K+=de.key+\"=\"+de.value+(ne<J.length-1?\"&\":\"\")),K},\"?\");D.href=i.config.FEEDBACK_URL+\"/\"+q+(this._map._hash?this._map._hash.getHashString(!0):\"\"),D.rel=\"noopener nofollow\",this._setElementTitle(D,\"MapFeedback\")}},en.prototype._updateData=function(D){D&&(D.sourceDataType===\"metadata\"||D.sourceDataType===\"visibility\"||D.dataType===\"style\")&&(this._updateAttributions(),this._updateEditLink())},en.prototype._updateAttributions=function(){if(this._map.style){var D=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?D=D.concat(this.options.customAttribution.map(function(Ue){return typeof Ue!=\"string\"?\"\":Ue})):typeof this.options.customAttribution==\"string\"&&D.push(this.options.customAttribution)),this._map.style.stylesheet){var J=this._map.style.stylesheet;this.styleOwner=J.owner,this.styleId=J.id}var q=this._map.style.sourceCaches;for(var K in q){var de=q[K];if(de.used){var ne=de.getSource();ne.attribution&&D.indexOf(ne.attribution)<0&&D.push(ne.attribution)}}D.sort(function(Ue,ft){return Ue.length-ft.length}),D=D.filter(function(Ue,ft){for(var Xt=ft+1;Xt<D.length;Xt++)if(D[Xt].indexOf(Ue)>=0)return!1;return!0});var we=D.join(\" | \");we!==this._attribHTML&&(this._attribHTML=we,D.length?(this._innerContainer.innerHTML=we,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},en.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\",\"mapboxgl-compact-show\")};var Wi=function(){i.bindAll([\"_updateLogo\"],this),i.bindAll([\"_updateCompact\"],this)};Wi.prototype.onAdd=function(D){this._map=D,this._container=o.create(\"div\",\"mapboxgl-ctrl\");var J=o.create(\"a\",\"mapboxgl-ctrl-logo\");return J.target=\"_blank\",J.rel=\"noopener nofollow\",J.href=\"https://www.mapbox.com/\",J.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),J.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(J),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Wi.prototype.onRemove=function(){o.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Wi.prototype.getDefaultPosition=function(){return\"bottom-left\"},Wi.prototype._updateLogo=function(D){(!D||D.sourceDataType===\"metadata\")&&(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Wi.prototype._logoRequired=function(){if(this._map.style){var D=this._map.style.sourceCaches;for(var J in D){var q=D[J].getSource();if(q.mapbox_logo)return!0}return!1}},Wi.prototype._updateCompact=function(){var D=this._container.children;if(D.length){var J=D[0];this._map.getCanvasContainer().offsetWidth<250?J.classList.add(\"mapboxgl-compact\"):J.classList.remove(\"mapboxgl-compact\")}};var si=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};si.prototype.add=function(D){var J=++this._id,q=this._queue;return q.push({callback:D,id:J,cancelled:!1}),J},si.prototype.remove=function(D){for(var J=this._currentlyRunning,q=J?this._queue.concat(J):this._queue,K=0,de=q;K<de.length;K+=1){var ne=de[K];if(ne.id===D){ne.cancelled=!0;return}}},si.prototype.run=function(D){D===void 0&&(D=0);var J=this._currentlyRunning=this._queue;this._queue=[];for(var q=0,K=J;q<K.length;q+=1){var de=K[q];if(!de.cancelled&&(de.callback(D),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},si.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Mr={\"AttributionControl.ToggleAttribution\":\"Toggle attribution\",\"AttributionControl.MapFeedback\":\"Map feedback\",\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},Yr=i.window.HTMLImageElement,xi=i.window.HTMLElement,Ri=i.window.ImageBitmap,ci=-2,an=22,Zi=0,Bn=60,hi={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:ci,maxZoom:an,minPitch:Zi,maxPitch:Bn,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},li=function(Y){function D(q){var K=this;if(q=i.extend({},hi,q),q.minZoom!=null&&q.maxZoom!=null&&q.minZoom>q.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(q.minPitch!=null&&q.maxPitch!=null&&q.minPitch>q.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(q.minPitch!=null&&q.minPitch<Zi)throw new Error(\"minPitch must be greater than or equal to \"+Zi);if(q.maxPitch!=null&&q.maxPitch>Bn)throw new Error(\"maxPitch must be less than or equal to \"+Bn);var de=new wo(q.minZoom,q.maxZoom,q.minPitch,q.maxPitch,q.renderWorldCopies);if(Y.call(this,de,q),this._interactive=q.interactive,this._maxTileCacheSize=q.maxTileCacheSize,this._failIfMajorPerformanceCaveat=q.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=q.preserveDrawingBuffer,this._antialias=q.antialias,this._trackResize=q.trackResize,this._bearingSnap=q.bearingSnap,this._refreshExpiredTiles=q.refreshExpiredTiles,this._fadeDuration=q.fadeDuration,this._crossSourceCollisions=q.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=q.collectResourceTiming,this._renderTaskQueue=new si,this._controls=[],this._mapId=i.uniqueId(),this._locale=i.extend({},Mr,q.locale),this._clickTolerance=q.clickTolerance,this._requestManager=new i.RequestManager(q.transformRequest,q.accessToken),typeof q.container==\"string\"){if(this._container=i.window.document.getElementById(q.container),!this._container)throw new Error(\"Container '\"+q.container+\"' not found.\")}else if(q.container instanceof xi)this._container=q.container;else throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");if(q.maxBounds&&this.setMaxBounds(q.maxBounds),i.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_onMapScroll\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),this.painter===void 0)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",function(){return K._update(!1)}),this.on(\"moveend\",function(){return K._update(!1)}),this.on(\"zoom\",function(){return K._update(!0)}),typeof i.window!=\"undefined\"&&(i.window.addEventListener(\"online\",this._onWindowOnline,!1),i.window.addEventListener(\"resize\",this._onWindowResize,!1),i.window.addEventListener(\"orientationchange\",this._onWindowResize,!1)),this.handlers=new Ei(this,q);var ne=typeof q.hash==\"string\"&&q.hash||void 0;this._hash=q.hash&&new Ul(ne).addTo(this),(!this._hash||!this._hash._onHashChange())&&(this.jumpTo({center:q.center,zoom:q.zoom,bearing:q.bearing,pitch:q.pitch}),q.bounds&&(this.resize(),this.fitBounds(q.bounds,i.extend({},q.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=q.localIdeographFontFamily,q.style&&this.setStyle(q.style,{localIdeographFontFamily:q.localIdeographFontFamily}),q.attributionControl&&this.addControl(new en({customAttribution:q.customAttribution})),this.addControl(new Wi,q.logoPosition),this.on(\"style.load\",function(){K.transform.unmodified&&K.jumpTo(K.style.stylesheet)}),this.on(\"data\",function(we){K._update(we.dataType===\"style\"),K.fire(new i.Event(we.dataType+\"data\",we))}),this.on(\"dataloading\",function(we){K.fire(new i.Event(we.dataType+\"dataloading\",we))})}Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D;var J={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return D.prototype._getMapId=function(){return this._mapId},D.prototype.addControl=function(K,de){if(de===void 0&&(K.getDefaultPosition?de=K.getDefaultPosition():de=\"top-right\"),!K||!K.onAdd)return this.fire(new i.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var ne=K.onAdd(this);this._controls.push(K);var we=this._controlPositions[de];return de.indexOf(\"bottom\")!==-1?we.insertBefore(ne,we.firstChild):we.appendChild(ne),this},D.prototype.removeControl=function(K){if(!K||!K.onRemove)return this.fire(new i.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var de=this._controls.indexOf(K);return de>-1&&this._controls.splice(de,1),K.onRemove(this),this},D.prototype.hasControl=function(K){return this._controls.indexOf(K)>-1},D.prototype.resize=function(K){var de=this._containerDimensions(),ne=de[0],we=de[1];this._resizeCanvas(ne,we),this.transform.resize(ne,we),this.painter.resize(ne,we);var Ue=!this._moving;return Ue&&(this.stop(),this.fire(new i.Event(\"movestart\",K)).fire(new i.Event(\"move\",K))),this.fire(new i.Event(\"resize\",K)),Ue&&this.fire(new i.Event(\"moveend\",K)),this},D.prototype.getBounds=function(){return this.transform.getBounds()},D.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},D.prototype.setMaxBounds=function(K){return this.transform.setMaxBounds(i.LngLatBounds.convert(K)),this._update()},D.prototype.setMinZoom=function(K){if(K=K==null?ci:K,K>=ci&&K<=this.transform.maxZoom)return this.transform.minZoom=K,this._update(),this.getZoom()<K&&this.setZoom(K),this;throw new Error(\"minZoom must be between \"+ci+\" and the current maxZoom, inclusive\")},D.prototype.getMinZoom=function(){return this.transform.minZoom},D.prototype.setMaxZoom=function(K){if(K=K==null?an:K,K>=this.transform.minZoom)return this.transform.maxZoom=K,this._update(),this.getZoom()>K&&this.setZoom(K),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},D.prototype.getMaxZoom=function(){return this.transform.maxZoom},D.prototype.setMinPitch=function(K){if(K=K==null?Zi:K,K<Zi)throw new Error(\"minPitch must be greater than or equal to \"+Zi);if(K>=Zi&&K<=this.transform.maxPitch)return this.transform.minPitch=K,this._update(),this.getPitch()<K&&this.setPitch(K),this;throw new Error(\"minPitch must be between \"+Zi+\" and the current maxPitch, inclusive\")},D.prototype.getMinPitch=function(){return this.transform.minPitch},D.prototype.setMaxPitch=function(K){if(K=K==null?Bn:K,K>Bn)throw new Error(\"maxPitch must be less than or equal to \"+Bn);if(K>=this.transform.minPitch)return this.transform.maxPitch=K,this._update(),this.getPitch()>K&&this.setPitch(K),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},D.prototype.getMaxPitch=function(){return this.transform.maxPitch},D.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},D.prototype.setRenderWorldCopies=function(K){return this.transform.renderWorldCopies=K,this._update()},D.prototype.project=function(K){return this.transform.locationPoint(i.LngLat.convert(K))},D.prototype.unproject=function(K){return this.transform.pointLocation(i.Point.convert(K))},D.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},D.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},D.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},D.prototype._createDelegatedListener=function(K,de,ne){var we=this,Ue;if(K===\"mouseenter\"||K===\"mouseover\"){var ft=!1,Xt=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length?ft||(ft=!0,ne.call(we,new se(K,we,Ct.originalEvent,{features:Ot}))):ft=!1},hr=function(){ft=!1};return{layer:de,listener:ne,delegates:{mousemove:Xt,mouseout:hr}}}else if(K===\"mouseleave\"||K===\"mouseout\"){var qt=!1,Ve=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length?qt=!0:qt&&(qt=!1,ne.call(we,new se(K,we,Ct.originalEvent)))},Qe=function(Ct){qt&&(qt=!1,ne.call(we,new se(K,we,Ct.originalEvent)))};return{layer:de,listener:ne,delegates:{mousemove:Ve,mouseout:Qe}}}else{var at=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length&&(Ct.features=Ot,ne.call(we,Ct),delete Ct.features)};return{layer:de,listener:ne,delegates:(Ue={},Ue[K]=at,Ue)}}},D.prototype.on=function(K,de,ne){if(ne===void 0)return Y.prototype.on.call(this,K,de);var we=this._createDelegatedListener(K,de,ne);this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[K]=this._delegatedListeners[K]||[],this._delegatedListeners[K].push(we);for(var Ue in we.delegates)this.on(Ue,we.delegates[Ue]);return this},D.prototype.once=function(K,de,ne){if(ne===void 0)return Y.prototype.once.call(this,K,de);var we=this._createDelegatedListener(K,de,ne);for(var Ue in we.delegates)this.once(Ue,we.delegates[Ue]);return this},D.prototype.off=function(K,de,ne){var we=this;if(ne===void 0)return Y.prototype.off.call(this,K,de);var Ue=function(ft){for(var Xt=ft[K],hr=0;hr<Xt.length;hr++){var qt=Xt[hr];if(qt.layer===de&&qt.listener===ne){for(var Ve in qt.delegates)we.off(Ve,qt.delegates[Ve]);return Xt.splice(hr,1),we}}};return this._delegatedListeners&&this._delegatedListeners[K]&&Ue(this._delegatedListeners),this},D.prototype.queryRenderedFeatures=function(K,de){if(!this.style)return[];de===void 0&&K!==void 0&&!(K instanceof i.Point)&&!Array.isArray(K)&&(de=K,K=void 0),de=de||{},K=K||[[0,0],[this.transform.width,this.transform.height]];var ne;if(K instanceof i.Point||typeof K[0]==\"number\")ne=[i.Point.convert(K)];else{var we=i.Point.convert(K[0]),Ue=i.Point.convert(K[1]);ne=[we,new i.Point(Ue.x,we.y),Ue,new i.Point(we.x,Ue.y),we]}return this.style.queryRenderedFeatures(ne,de,this.transform)},D.prototype.querySourceFeatures=function(K,de){return this.style.querySourceFeatures(K,de)},D.prototype.setStyle=function(K,de){return de=i.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},de),de.diff!==!1&&de.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&K?(this._diffStyle(K,de),this):(this._localIdeographFontFamily=de.localIdeographFontFamily,this._updateStyle(K,de))},D.prototype._getUIString=function(K){var de=this._locale[K];if(de==null)throw new Error(\"Missing UI string '\"+K+\"'\");return de},D.prototype._updateStyle=function(K,de){if(this.style&&(this.style.setEventedParent(null),this.style._remove()),K)this.style=new yu(this,de||{});else return delete this.style,this;return this.style.setEventedParent(this,{style:this.style}),typeof K==\"string\"?this.style.loadURL(K):this.style.loadJSON(K),this},D.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new yu(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},D.prototype._diffStyle=function(K,de){var ne=this;if(typeof K==\"string\"){var we=this._requestManager.normalizeStyleURL(K),Ue=this._requestManager.transformRequest(we,i.ResourceType.Style);i.getJSON(Ue,function(ft,Xt){ft?ne.fire(new i.ErrorEvent(ft)):Xt&&ne._updateDiff(Xt,de)})}else typeof K==\"object\"&&this._updateDiff(K,de)},D.prototype._updateDiff=function(K,de){try{this.style.setState(K)&&this._update(!0)}catch(ne){i.warnOnce(\"Unable to perform style diff: \"+(ne.message||ne.error||ne)+\".  Rebuilding the style from scratch.\"),this._updateStyle(K,de)}},D.prototype.getStyle=function(){if(this.style)return this.style.serialize()},D.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():i.warnOnce(\"There is no style added to the map.\")},D.prototype.addSource=function(K,de){return this._lazyInitEmptyStyle(),this.style.addSource(K,de),this._update(!0)},D.prototype.isSourceLoaded=function(K){var de=this.style&&this.style.sourceCaches[K];if(de===void 0){this.fire(new i.ErrorEvent(new Error(\"There is no source with ID '\"+K+\"'\")));return}return de.loaded()},D.prototype.areTilesLoaded=function(){var K=this.style&&this.style.sourceCaches;for(var de in K){var ne=K[de],we=ne._tiles;for(var Ue in we){var ft=we[Ue];if(!(ft.state===\"loaded\"||ft.state===\"errored\"))return!1}}return!0},D.prototype.addSourceType=function(K,de,ne){return this._lazyInitEmptyStyle(),this.style.addSourceType(K,de,ne)},D.prototype.removeSource=function(K){return this.style.removeSource(K),this._update(!0)},D.prototype.getSource=function(K){return this.style.getSource(K)},D.prototype.addImage=function(K,de,ne){ne===void 0&&(ne={});var we=ne.pixelRatio;we===void 0&&(we=1);var Ue=ne.sdf;Ue===void 0&&(Ue=!1);var ft=ne.stretchX,Xt=ne.stretchY,hr=ne.content;this._lazyInitEmptyStyle();var qt=0;if(de instanceof Yr||Ri&&de instanceof Ri){var Ve=i.browser.getImageData(de),Qe=Ve.width,at=Ve.height,Ct=Ve.data;this.style.addImage(K,{data:new i.RGBAImage({width:Qe,height:at},Ct),pixelRatio:we,stretchX:ft,stretchY:Xt,content:hr,sdf:Ue,version:qt})}else{if(de.width===void 0||de.height===void 0)return this.fire(new i.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var Ot=de.width,Rt=de.height,Bt=de.data,Dt=de;this.style.addImage(K,{data:new i.RGBAImage({width:Ot,height:Rt},new Uint8Array(Bt)),pixelRatio:we,stretchX:ft,stretchY:Xt,content:hr,sdf:Ue,version:qt,userImage:Dt}),Dt.onAdd&&Dt.onAdd(this,K)}},D.prototype.updateImage=function(K,de){var ne=this.style.getImage(K);if(!ne)return this.fire(new i.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var we=de instanceof Yr||Ri&&de instanceof Ri?i.browser.getImageData(de):de,Ue=we.width,ft=we.height,Xt=we.data;if(Ue===void 0||ft===void 0)return this.fire(new i.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(Ue!==ne.data.width||ft!==ne.data.height)return this.fire(new i.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var hr=!(de instanceof Yr||Ri&&de instanceof Ri);ne.data.replace(Xt,hr),this.style.updateImage(K,ne)},D.prototype.hasImage=function(K){return K?!!this.style.getImage(K):(this.fire(new i.ErrorEvent(new Error(\"Missing required image id\"))),!1)},D.prototype.removeImage=function(K){this.style.removeImage(K)},D.prototype.loadImage=function(K,de){i.getImage(this._requestManager.transformRequest(K,i.ResourceType.Image),de)},D.prototype.listImages=function(){return this.style.listImages()},D.prototype.addLayer=function(K,de){return this._lazyInitEmptyStyle(),this.style.addLayer(K,de),this._update(!0)},D.prototype.moveLayer=function(K,de){return this.style.moveLayer(K,de),this._update(!0)},D.prototype.removeLayer=function(K){return this.style.removeLayer(K),this._update(!0)},D.prototype.getLayer=function(K){return this.style.getLayer(K)},D.prototype.setLayerZoomRange=function(K,de,ne){return this.style.setLayerZoomRange(K,de,ne),this._update(!0)},D.prototype.setFilter=function(K,de,ne){return ne===void 0&&(ne={}),this.style.setFilter(K,de,ne),this._update(!0)},D.prototype.getFilter=function(K){return this.style.getFilter(K)},D.prototype.setPaintProperty=function(K,de,ne,we){return we===void 0&&(we={}),this.style.setPaintProperty(K,de,ne,we),this._update(!0)},D.prototype.getPaintProperty=function(K,de){return this.style.getPaintProperty(K,de)},D.prototype.setLayoutProperty=function(K,de,ne,we){return we===void 0&&(we={}),this.style.setLayoutProperty(K,de,ne,we),this._update(!0)},D.prototype.getLayoutProperty=function(K,de){return this.style.getLayoutProperty(K,de)},D.prototype.setLight=function(K,de){return de===void 0&&(de={}),this._lazyInitEmptyStyle(),this.style.setLight(K,de),this._update(!0)},D.prototype.getLight=function(){return this.style.getLight()},D.prototype.setFeatureState=function(K,de){return this.style.setFeatureState(K,de),this._update()},D.prototype.removeFeatureState=function(K,de){return this.style.removeFeatureState(K,de),this._update()},D.prototype.getFeatureState=function(K){return this.style.getFeatureState(K)},D.prototype.getContainer=function(){return this._container},D.prototype.getCanvasContainer=function(){return this._canvasContainer},D.prototype.getCanvas=function(){return this._canvas},D.prototype._containerDimensions=function(){var K=0,de=0;return this._container&&(K=this._container.clientWidth||400,de=this._container.clientHeight||300),[K,de]},D.prototype._detectMissingCSS=function(){var K=i.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\");K!==\"rgb(250, 128, 114)\"&&i.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},D.prototype._setupContainer=function(){var K=this._container;K.classList.add(\"mapboxgl-map\");var de=this._missingCSSCanary=o.create(\"div\",\"mapboxgl-canary\",K);de.style.visibility=\"hidden\",this._detectMissingCSS();var ne=this._canvasContainer=o.create(\"div\",\"mapboxgl-canvas-container\",K);this._interactive&&ne.classList.add(\"mapboxgl-interactive\"),this._canvas=o.create(\"canvas\",\"mapboxgl-canvas\",ne),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\"),this._canvas.setAttribute(\"role\",\"region\");var we=this._containerDimensions();this._resizeCanvas(we[0],we[1]);var Ue=this._controlContainer=o.create(\"div\",\"mapboxgl-control-container\",K),ft=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(function(Xt){ft[Xt]=o.create(\"div\",\"mapboxgl-ctrl-\"+Xt,Ue)}),this._container.addEventListener(\"scroll\",this._onMapScroll,!1)},D.prototype._resizeCanvas=function(K,de){var ne=i.browser.devicePixelRatio||1;this._canvas.width=ne*K,this._canvas.height=ne*de,this._canvas.style.width=K+\"px\",this._canvas.style.height=de+\"px\"},D.prototype._setupPainter=function(){var K=i.extend({},a.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),de=this._canvas.getContext(\"webgl\",K)||this._canvas.getContext(\"experimental-webgl\",K);if(!de){this.fire(new i.ErrorEvent(new Error(\"Failed to initialize WebGL\")));return}this.painter=new mo(de,this.transform),i.webpSupported.testSupport(de)},D.prototype._contextLost=function(K){K.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new i.Event(\"webglcontextlost\",{originalEvent:K}))},D.prototype._contextRestored=function(K){this._setupPainter(),this.resize(),this._update(),this.fire(new i.Event(\"webglcontextrestored\",{originalEvent:K}))},D.prototype._onMapScroll=function(K){if(K.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},D.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},D.prototype._update=function(K){return this.style?(this._styleDirty=this._styleDirty||K,this._sourcesDirty=!0,this.triggerRepaint(),this):this},D.prototype._requestRenderFrame=function(K){return this._update(),this._renderTaskQueue.add(K)},D.prototype._cancelRenderFrame=function(K){this._renderTaskQueue.remove(K)},D.prototype._render=function(K){var de=this,ne,we=0,Ue=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(ne=Ue.createQueryEXT(),Ue.beginQueryEXT(Ue.TIME_ELAPSED_EXT,ne),we=i.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(K),!this._removed){var ft=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var Xt=this.transform.zoom,hr=i.browser.now();this.style.zoomHistory.update(Xt,hr);var qt=new i.EvaluationParameters(Xt,{now:hr,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),Ve=qt.crossFadingFactor();(Ve!==1||Ve!==this._crossFadingFactor)&&(ft=!0,this._crossFadingFactor=Ve),this.style.update(qt)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new i.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new i.Event(\"load\"))),this.style&&(this.style.hasTransitions()||ft)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var Qe=i.browser.now()-we;Ue.endQueryEXT(Ue.TIME_ELAPSED_EXT,ne),setTimeout(function(){var Ot=Ue.getQueryObjectEXT(ne,Ue.QUERY_RESULT_EXT)/1e6;Ue.deleteQueryEXT(ne),de.fire(new i.Event(\"gpu-timing-frame\",{cpuTime:Qe,gpuTime:Ot}))},50)}if(this.listens(\"gpu-timing-layer\")){var at=this.painter.collectGpuTimers();setTimeout(function(){var Ot=de.painter.queryGpuTimers(at);de.fire(new i.Event(\"gpu-timing-layer\",{layerTimes:Ot}))},50)}var Ct=this._sourcesDirty||this._styleDirty||this._placementDirty;return Ct||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new i.Event(\"idle\")),this._loaded&&!this._fullyLoaded&&!Ct&&(this._fullyLoaded=!0),this}},D.prototype.remove=function(){this._hash&&this._hash.remove();for(var K=0,de=this._controls;K<de.length;K+=1){var ne=de[K];ne.onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),typeof i.window!=\"undefined\"&&(i.window.removeEventListener(\"resize\",this._onWindowResize,!1),i.window.removeEventListener(\"orientationchange\",this._onWindowResize,!1),i.window.removeEventListener(\"online\",this._onWindowOnline,!1));var we=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");we&&we.loseContext&&we.loseContext(),mn(this._canvasContainer),mn(this._controlContainer),mn(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new i.Event(\"remove\"))},D.prototype.triggerRepaint=function(){var K=this;this.style&&!this._frame&&(this._frame=i.browser.frame(function(de){K._frame=null,K._render(de)}))},D.prototype._onWindowOnline=function(){this._update()},D.prototype._onWindowResize=function(K){this._trackResize&&this.resize({originalEvent:K})._update()},J.showTileBoundaries.get=function(){return!!this._showTileBoundaries},J.showTileBoundaries.set=function(q){this._showTileBoundaries!==q&&(this._showTileBoundaries=q,this._update())},J.showPadding.get=function(){return!!this._showPadding},J.showPadding.set=function(q){this._showPadding!==q&&(this._showPadding=q,this._update())},J.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},J.showCollisionBoxes.set=function(q){this._showCollisionBoxes!==q&&(this._showCollisionBoxes=q,q?this.style._generateCollisionBoxes():this._update())},J.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},J.showOverdrawInspector.set=function(q){this._showOverdrawInspector!==q&&(this._showOverdrawInspector=q,this._update())},J.repaint.get=function(){return!!this._repaint},J.repaint.set=function(q){this._repaint!==q&&(this._repaint=q,this.triggerRepaint())},J.vertices.get=function(){return!!this._vertices},J.vertices.set=function(q){this._vertices=q,this._update()},D.prototype._setCacheLimits=function(K,de){i.setCacheLimits(K,de)},J.version.get=function(){return i.version},Object.defineProperties(D.prototype,J),D}(Hn);function mn(Y){Y.parentNode&&Y.parentNode.removeChild(Y)}var Ji={showCompass:!0,showZoom:!0,visualizePitch:!1},Vi=function(D){var J=this;this.options=i.extend({},Ji,D),this._container=o.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",function(q){return q.preventDefault()}),this.options.showZoom&&(i.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",function(q){return J._map.zoomIn({},{originalEvent:q})}),o.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",function(q){return J._map.zoomOut({},{originalEvent:q})}),o.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(i.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",function(q){J.options.visualizePitch?J._map.resetNorthPitch({},{originalEvent:q}):J._map.resetNorth({},{originalEvent:q})}),this._compassIcon=o.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Vi.prototype._updateZoomButtons=function(){var D=this._map.getZoom(),J=D===this._map.getMaxZoom(),q=D===this._map.getMinZoom();this._zoomInButton.disabled=J,this._zoomOutButton.disabled=q,this._zoomInButton.setAttribute(\"aria-disabled\",J.toString()),this._zoomOutButton.setAttribute(\"aria-disabled\",q.toString())},Vi.prototype._rotateCompassArrow=function(){var D=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=D},Vi.prototype.onAdd=function(D){return this._map=D,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ni(this._map,this._compass,this.options.visualizePitch)),this._container},Vi.prototype.onRemove=function(){o.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Vi.prototype._createButton=function(D,J){var q=o.create(\"button\",D,this._container);return q.type=\"button\",q.addEventListener(\"click\",J),q},Vi.prototype._setButtonTitle=function(D,J){var q=this._map._getUIString(\"NavigationControl.\"+J);D.title=q,D.setAttribute(\"aria-label\",q)};var Ni=function(D,J,q){q===void 0&&(q=!1),this._clickTolerance=10,this.element=J,this.mouseRotate=new Ln({clickTolerance:D.dragRotate._mouseRotate._clickTolerance}),this.map=D,q&&(this.mousePitch=new En({clickTolerance:D.dragRotate._mousePitch._clickTolerance})),i.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),o.addEventListener(J,\"mousedown\",this.mousedown),o.addEventListener(J,\"touchstart\",this.touchstart,{passive:!1}),o.addEventListener(J,\"touchmove\",this.touchmove),o.addEventListener(J,\"touchend\",this.touchend),o.addEventListener(J,\"touchcancel\",this.reset)};Ni.prototype.down=function(D,J){this.mouseRotate.mousedown(D,J),this.mousePitch&&this.mousePitch.mousedown(D,J),o.disableDrag()},Ni.prototype.move=function(D,J){var q=this.map,K=this.mouseRotate.mousemoveWindow(D,J);if(K&&K.bearingDelta&&q.setBearing(q.getBearing()+K.bearingDelta),this.mousePitch){var de=this.mousePitch.mousemoveWindow(D,J);de&&de.pitchDelta&&q.setPitch(q.getPitch()+de.pitchDelta)}},Ni.prototype.off=function(){var D=this.element;o.removeEventListener(D,\"mousedown\",this.mousedown),o.removeEventListener(D,\"touchstart\",this.touchstart,{passive:!1}),o.removeEventListener(D,\"touchmove\",this.touchmove),o.removeEventListener(D,\"touchend\",this.touchend),o.removeEventListener(D,\"touchcancel\",this.reset),this.offTemp()},Ni.prototype.offTemp=function(){o.enableDrag(),o.removeEventListener(i.window,\"mousemove\",this.mousemove),o.removeEventListener(i.window,\"mouseup\",this.mouseup)},Ni.prototype.mousedown=function(D){this.down(i.extend({},D,{ctrlKey:!0,preventDefault:function(){return D.preventDefault()}}),o.mousePos(this.element,D)),o.addEventListener(i.window,\"mousemove\",this.mousemove),o.addEventListener(i.window,\"mouseup\",this.mouseup)},Ni.prototype.mousemove=function(D){this.move(D,o.mousePos(this.element,D))},Ni.prototype.mouseup=function(D){this.mouseRotate.mouseupWindow(D),this.mousePitch&&this.mousePitch.mouseupWindow(D),this.offTemp()},Ni.prototype.touchstart=function(D){D.targetTouches.length!==1?this.reset():(this._startPos=this._lastPos=o.touchPos(this.element,D.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return D.preventDefault()}},this._startPos))},Ni.prototype.touchmove=function(D){D.targetTouches.length!==1?this.reset():(this._lastPos=o.touchPos(this.element,D.targetTouches)[0],this.move({preventDefault:function(){return D.preventDefault()}},this._lastPos))},Ni.prototype.touchend=function(D){D.targetTouches.length===0&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ni.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};function pn(Y,D,J){if(Y=new i.LngLat(Y.lng,Y.lat),D){var q=new i.LngLat(Y.lng-360,Y.lat),K=new i.LngLat(Y.lng+360,Y.lat),de=J.locationPoint(Y).distSqr(D);J.locationPoint(q).distSqr(D)<de?Y=q:J.locationPoint(K).distSqr(D)<de&&(Y=K)}for(;Math.abs(Y.lng-J.center.lng)>180;){var ne=J.locationPoint(Y);if(ne.x>=0&&ne.y>=0&&ne.x<=J.width&&ne.y<=J.height)break;Y.lng>J.center.lng?Y.lng-=360:Y.lng+=360}return Y}var Vn={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function na(Y,D,J){var q=Y.classList;for(var K in Vn)q.remove(\"mapboxgl-\"+J+\"-anchor-\"+K);q.add(\"mapboxgl-\"+J+\"-anchor-\"+D)}var Ki=function(Y){function D(J,q){if(Y.call(this),(J instanceof i.window.HTMLElement||q)&&(J=i.extend({element:J},q)),i.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=J&&J.anchor||\"center\",this._color=J&&J.color||\"#3FB1CE\",this._scale=J&&J.scale||1,this._draggable=J&&J.draggable||!1,this._clickTolerance=J&&J.clickTolerance||0,this._isDragging=!1,this._state=\"inactive\",this._rotation=J&&J.rotation||0,this._rotationAlignment=J&&J.rotationAlignment||\"auto\",this._pitchAlignment=J&&J.pitchAlignment&&J.pitchAlignment!==\"auto\"?J.pitchAlignment:this._rotationAlignment,!J||!J.element){this._defaultMarker=!0,this._element=o.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var K=o.createNS(\"http://www.w3.org/2000/svg\",\"svg\"),de=41,ne=27;K.setAttributeNS(null,\"display\",\"block\"),K.setAttributeNS(null,\"height\",de+\"px\"),K.setAttributeNS(null,\"width\",ne+\"px\"),K.setAttributeNS(null,\"viewBox\",\"0 0 \"+ne+\" \"+de);var we=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");we.setAttributeNS(null,\"stroke\",\"none\"),we.setAttributeNS(null,\"stroke-width\",\"1\"),we.setAttributeNS(null,\"fill\",\"none\"),we.setAttributeNS(null,\"fill-rule\",\"evenodd\");var Ue=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");Ue.setAttributeNS(null,\"fill-rule\",\"nonzero\");var ft=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");ft.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),ft.setAttributeNS(null,\"fill\",\"#000000\");for(var Xt=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}],hr=0,qt=Xt;hr<qt.length;hr+=1){var Ve=qt[hr],Qe=o.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");Qe.setAttributeNS(null,\"opacity\",\"0.04\"),Qe.setAttributeNS(null,\"cx\",\"10.5\"),Qe.setAttributeNS(null,\"cy\",\"5.80029008\"),Qe.setAttributeNS(null,\"rx\",Ve.rx),Qe.setAttributeNS(null,\"ry\",Ve.ry),ft.appendChild(Qe)}var at=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");at.setAttributeNS(null,\"fill\",this._color);var Ct=o.createNS(\"http://www.w3.org/2000/svg\",\"path\");Ct.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),at.appendChild(Ct);var Ot=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");Ot.setAttributeNS(null,\"opacity\",\"0.25\"),Ot.setAttributeNS(null,\"fill\",\"#000000\");var Rt=o.createNS(\"http://www.w3.org/2000/svg\",\"path\");Rt.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),Ot.appendChild(Rt);var Bt=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");Bt.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),Bt.setAttributeNS(null,\"fill\",\"#FFFFFF\");var Dt=o.createNS(\"http://www.w3.org/2000/svg\",\"g\");Dt.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var yt=o.createNS(\"http://www.w3.org/2000/svg\",\"circle\");yt.setAttributeNS(null,\"fill\",\"#000000\"),yt.setAttributeNS(null,\"opacity\",\"0.25\"),yt.setAttributeNS(null,\"cx\",\"5.5\"),yt.setAttributeNS(null,\"cy\",\"5.5\"),yt.setAttributeNS(null,\"r\",\"5.4999962\");var Pt=o.createNS(\"http://www.w3.org/2000/svg\",\"circle\");Pt.setAttributeNS(null,\"fill\",\"#FFFFFF\"),Pt.setAttributeNS(null,\"cx\",\"5.5\"),Pt.setAttributeNS(null,\"cy\",\"5.5\"),Pt.setAttributeNS(null,\"r\",\"5.4999962\"),Dt.appendChild(yt),Dt.appendChild(Pt),Ue.appendChild(ft),Ue.appendChild(at),Ue.appendChild(Ot),Ue.appendChild(Bt),Ue.appendChild(Dt),K.appendChild(Ue),K.setAttributeNS(null,\"height\",de*this._scale+\"px\"),K.setAttributeNS(null,\"width\",ne*this._scale+\"px\"),this._element.appendChild(K),this._offset=i.Point.convert(J&&J.offset||[0,-14])}else this._element=J.element,this._offset=i.Point.convert(J&&J.offset||[0,0]);this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",function(ht){ht.preventDefault()}),this._element.addEventListener(\"mousedown\",function(ht){ht.preventDefault()}),na(this._element,this._anchor,\"marker\"),this._popup=null}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.addTo=function(q){return this.remove(),this._map=q,q.getCanvasContainer().appendChild(this._element),q.on(\"move\",this._update),q.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},D.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),o.remove(this._element),this._popup&&this._popup.remove(),this},D.prototype.getLngLat=function(){return this._lngLat},D.prototype.setLngLat=function(q){return this._lngLat=i.LngLat.convert(q),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},D.prototype.getElement=function(){return this._element},D.prototype.setPopup=function(q){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),q){if(!(\"offset\"in q.options)){var K=38.1,de=13.5,ne=Math.sqrt(Math.pow(de,2)/2);q.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-K],\"bottom-left\":[ne,(K-de+ne)*-1],\"bottom-right\":[-ne,(K-de+ne)*-1],left:[de,(K-de)*-1],right:[-de,(K-de)*-1]}:this._offset}this._popup=q,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},D.prototype._onKeyPress=function(q){var K=q.code,de=q.charCode||q.keyCode;(K===\"Space\"||K===\"Enter\"||de===32||de===13)&&this.togglePopup()},D.prototype._onMapClick=function(q){var K=q.originalEvent.target,de=this._element;this._popup&&(K===de||de.contains(K))&&this.togglePopup()},D.prototype.getPopup=function(){return this._popup},D.prototype.togglePopup=function(){var q=this._popup;if(q)q.isOpen()?q.remove():q.addTo(this._map);else return this;return this},D.prototype._update=function(q){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=pn(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var K=\"\";this._rotationAlignment===\"viewport\"||this._rotationAlignment===\"auto\"?K=\"rotateZ(\"+this._rotation+\"deg)\":this._rotationAlignment===\"map\"&&(K=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var de=\"\";this._pitchAlignment===\"viewport\"||this._pitchAlignment===\"auto\"?de=\"rotateX(0deg)\":this._pitchAlignment===\"map\"&&(de=\"rotateX(\"+this._map.getPitch()+\"deg)\"),(!q||q.type===\"moveend\")&&(this._pos=this._pos.round()),o.setTransform(this._element,Vn[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+de+\" \"+K)}},D.prototype.getOffset=function(){return this._offset},D.prototype.setOffset=function(q){return this._offset=i.Point.convert(q),this._update(),this},D.prototype._onMove=function(q){if(!this._isDragging){var K=this._clickTolerance||this._map._clickTolerance;this._isDragging=q.point.dist(this._pointerdownPos)>=K}this._isDragging&&(this._pos=q.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",this._state===\"pending\"&&(this._state=\"active\",this.fire(new i.Event(\"dragstart\"))),this.fire(new i.Event(\"drag\")))},D.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),this._state===\"active\"&&this.fire(new i.Event(\"dragend\")),this._state=\"inactive\"},D.prototype._addDragHandler=function(q){this._element.contains(q.originalEvent.target)&&(q.preventDefault(),this._positionDelta=q.point.sub(this._pos).add(this._offset),this._pointerdownPos=q.point,this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},D.prototype.setDraggable=function(q){return this._draggable=!!q,this._map&&(q?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},D.prototype.isDraggable=function(){return this._draggable},D.prototype.setRotation=function(q){return this._rotation=q||0,this._update(),this},D.prototype.getRotation=function(){return this._rotation},D.prototype.setRotationAlignment=function(q){return this._rotationAlignment=q||\"auto\",this._update(),this},D.prototype.getRotationAlignment=function(){return this._rotationAlignment},D.prototype.setPitchAlignment=function(q){return this._pitchAlignment=q&&q!==\"auto\"?q:this._rotationAlignment,this._update(),this},D.prototype.getPitchAlignment=function(){return this._pitchAlignment},D}(i.Evented),kn={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},ta;function oa(Y){ta!==void 0?Y(ta):i.window.navigator.permissions!==void 0?i.window.navigator.permissions.query({name:\"geolocation\"}).then(function(D){ta=D.state!==\"denied\",Y(ta)}):(ta=!!i.window.navigator.geolocation,Y(ta))}var ba=0,is=!1,Zs=function(Y){function D(J){Y.call(this),this.options=i.extend({},kn,J),i.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.onAdd=function(q){return this._map=q,this._container=o.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),oa(this._setupUI),this._container},D.prototype.onRemove=function(){this._geolocationWatchID!==void 0&&(i.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),o.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,ba=0,is=!1},D.prototype._isOutOfMapMaxBounds=function(q){var K=this._map.getMaxBounds(),de=q.coords;return K&&(de.longitude<K.getWest()||de.longitude>K.getEast()||de.latitude<K.getSouth()||de.latitude>K.getNorth())},D.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break}},D.prototype._onSuccess=function(q){if(this._map){if(this._isOutOfMapMaxBounds(q)){this._setErrorState(),this.fire(new i.Event(\"outofmaxbounds\",q)),this._updateMarker(),this._finish();return}if(this.options.trackUserLocation)switch(this._lastKnownPosition=q,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break}this.options.showUserLocation&&this._watchState!==\"OFF\"&&this._updateMarker(q),(!this.options.trackUserLocation||this._watchState===\"ACTIVE_LOCK\")&&this._updateCamera(q),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new i.Event(\"geolocate\",q)),this._finish()}},D.prototype._updateCamera=function(q){var K=new i.LngLat(q.coords.longitude,q.coords.latitude),de=q.coords.accuracy,ne=this._map.getBearing(),we=i.extend({bearing:ne},this.options.fitBoundsOptions);this._map.fitBounds(K.toBounds(de),we,{geolocateSource:!0})},D.prototype._updateMarker=function(q){if(q){var K=new i.LngLat(q.coords.longitude,q.coords.latitude);this._accuracyCircleMarker.setLngLat(K).addTo(this._map),this._userLocationDotMarker.setLngLat(K).addTo(this._map),this._accuracy=q.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},D.prototype._updateCircleRadius=function(){var q=this._map._container.clientHeight/2,K=this._map.unproject([0,q]),de=this._map.unproject([1,q]),ne=K.distanceTo(de),we=Math.ceil(2*this._accuracy/ne);this._circleElement.style.width=we+\"px\",this._circleElement.style.height=we+\"px\"},D.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},D.prototype._onError=function(q){if(this._map){if(this.options.trackUserLocation)if(q.code===1){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var K=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=K,this._geolocateButton.setAttribute(\"aria-label\",K),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(q.code===3&&is)return;this._setErrorState()}this._watchState!==\"OFF\"&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new i.Event(\"error\",q)),this._finish()}},D.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},D.prototype._setupUI=function(q){var K=this;if(this._container.addEventListener(\"contextmenu\",function(we){return we.preventDefault()}),this._geolocateButton=o.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),o.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",q===!1){i.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var de=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=de,this._geolocateButton.setAttribute(\"aria-label\",de)}else{var ne=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=ne,this._geolocateButton.setAttribute(\"aria-label\",ne)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=o.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Ki(this._dotElement),this._circleElement=o.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Ki({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",function(we){var Ue=we.originalEvent&&we.originalEvent.type===\"resize\";!we.geolocateSource&&K._watchState===\"ACTIVE_LOCK\"&&!Ue&&(K._watchState=\"BACKGROUND\",K._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),K._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),K.fire(new i.Event(\"trackuserlocationend\")))})},D.prototype.trigger=function(){if(!this._setup)return i.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new i.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":ba--,is=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new i.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new i.Event(\"trackuserlocationstart\"));break}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\");break}if(this._watchState===\"OFF\"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),ba++;var q;ba>1?(q={maximumAge:6e5,timeout:0},is=!0):(q=this.options.positionOptions,is=!1),this._geolocationWatchID=i.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,q)}}else i.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},D.prototype._clearWatch=function(){i.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},D}(i.Evented),Va={maxWidth:100,unit:\"metric\"},Ml=function(D){this.options=i.extend({},Va,D),i.bindAll([\"_onMove\",\"setUnit\"],this)};Ml.prototype.getDefaultPosition=function(){return\"bottom-left\"},Ml.prototype._onMove=function(){zo(this._map,this._container,this.options)},Ml.prototype.onAdd=function(D){return this._map=D,this._container=o.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",D.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},Ml.prototype.onRemove=function(){o.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},Ml.prototype.setUnit=function(D){this.options.unit=D,zo(this._map,this._container,this.options)};function zo(Y,D,J){var q=J&&J.maxWidth||100,K=Y._container.clientHeight/2,de=Y.unproject([0,K]),ne=Y.unproject([q,K]),we=de.distanceTo(ne);if(J&&J.unit===\"imperial\"){var Ue=3.2808*we;if(Ue>5280){var ft=Ue/5280;Qs(D,q,ft,Y._getUIString(\"ScaleControl.Miles\"))}else Qs(D,q,Ue,Y._getUIString(\"ScaleControl.Feet\"))}else if(J&&J.unit===\"nautical\"){var Xt=we/1852;Qs(D,q,Xt,Y._getUIString(\"ScaleControl.NauticalMiles\"))}else we>=1e3?Qs(D,q,we/1e3,Y._getUIString(\"ScaleControl.Kilometers\")):Qs(D,q,we,Y._getUIString(\"ScaleControl.Meters\"))}function Qs(Y,D,J,q){var K=Vl(J),de=K/J;Y.style.width=D*de+\"px\",Y.innerHTML=K+\"&nbsp;\"+q}function al(Y){var D=Math.pow(10,Math.ceil(-Math.log(Y)/Math.LN10));return Math.round(Y*D)/D}function Vl(Y){var D=Math.pow(10,(\"\"+Math.floor(Y)).length-1),J=Y/D;return J=J>=10?10:J>=5?5:J>=3?3:J>=2?2:J>=1?1:al(J),D*J}var ss=function(D){this._fullscreen=!1,D&&D.container&&(D.container instanceof i.window.HTMLElement?this._container=D.container:i.warnOnce(\"Full screen control 'container' must be a DOM element.\")),i.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in i.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in i.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in i.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in i.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};ss.prototype.onAdd=function(D){return this._map=D,this._container||(this._container=this._map.getContainer()),this._controlContainer=o.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",i.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},ss.prototype.onRemove=function(){o.remove(this._controlContainer),this._map=null,i.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},ss.prototype._checkFullscreenSupport=function(){return!!(i.window.document.fullscreenEnabled||i.window.document.mozFullScreenEnabled||i.window.document.msFullscreenEnabled||i.window.document.webkitFullscreenEnabled)},ss.prototype._setupUI=function(){var D=this._fullscreenButton=o.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);o.create(\"span\",\"mapboxgl-ctrl-icon\",D).setAttribute(\"aria-hidden\",!0),D.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),i.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},ss.prototype._updateTitle=function(){var D=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",D),this._fullscreenButton.title=D},ss.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},ss.prototype._isFullscreen=function(){return this._fullscreen},ss.prototype._changeIcon=function(){var D=i.window.document.fullscreenElement||i.window.document.mozFullScreenElement||i.window.document.webkitFullscreenElement||i.window.document.msFullscreenElement;D===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},ss.prototype._onClickFullscreen=function(){this._isFullscreen()?i.window.document.exitFullscreen?i.window.document.exitFullscreen():i.window.document.mozCancelFullScreen?i.window.document.mozCancelFullScreen():i.window.document.msExitFullscreen?i.window.document.msExitFullscreen():i.window.document.webkitCancelFullScreen&&i.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Vs={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:\"\",maxWidth:\"240px\"},Ys=[\"a[href]\",\"[tabindex]:not([tabindex='-1'])\",\"[contenteditable]:not([contenteditable='false'])\",\"button:not([disabled])\",\"input:not([disabled])\",\"select:not([disabled])\",\"textarea:not([disabled])\"].join(\", \"),wa=function(Y){function D(J){Y.call(this),this.options=i.extend(Object.create(Vs),J),i.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.addTo=function(q){return this._map&&this.remove(),this._map=q,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new i.Event(\"open\")),this},D.prototype.isOpen=function(){return!!this._map},D.prototype.remove=function(){return this._content&&o.remove(this._content),this._container&&(o.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new i.Event(\"close\")),this},D.prototype.getLngLat=function(){return this._lngLat},D.prototype.setLngLat=function(q){return this._lngLat=i.LngLat.convert(q),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},D.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},D.prototype.getElement=function(){return this._container},D.prototype.setText=function(q){return this.setDOMContent(i.window.document.createTextNode(q))},D.prototype.setHTML=function(q){var K=i.window.document.createDocumentFragment(),de=i.window.document.createElement(\"body\"),ne;for(de.innerHTML=q;ne=de.firstChild,!!ne;)K.appendChild(ne);return this.setDOMContent(K)},D.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},D.prototype.setMaxWidth=function(q){return this.options.maxWidth=q,this._update(),this},D.prototype.setDOMContent=function(q){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=o.create(\"div\",\"mapboxgl-popup-content\",this._container);return this._content.appendChild(q),this._createCloseButton(),this._update(),this._focusFirstElement(),this},D.prototype.addClassName=function(q){this._container&&this._container.classList.add(q)},D.prototype.removeClassName=function(q){this._container&&this._container.classList.remove(q)},D.prototype.setOffset=function(q){return this.options.offset=q,this._update(),this},D.prototype.toggleClassName=function(q){if(this._container)return this._container.classList.toggle(q)},D.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=o.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},D.prototype._onMouseUp=function(q){this._update(q.point)},D.prototype._onMouseMove=function(q){this._update(q.point)},D.prototype._onDrag=function(q){this._update(q.point)},D.prototype._update=function(q){var K=this,de=this._lngLat||this._trackPointer;if(!(!this._map||!de||!this._content)&&(this._container||(this._container=o.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=o.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach(function(Ve){return K._container.classList.add(Ve)}),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=pn(this._lngLat,this._pos,this._map.transform)),!(this._trackPointer&&!q))){var ne=this._pos=this._trackPointer&&q?q:this._map.project(this._lngLat),we=this.options.anchor,Ue=ol(this.options.offset);if(!we){var ft=this._container.offsetWidth,Xt=this._container.offsetHeight,hr;ne.y+Ue.bottom.y<Xt?hr=[\"top\"]:ne.y>this._map.transform.height-Xt?hr=[\"bottom\"]:hr=[],ne.x<ft/2?hr.push(\"left\"):ne.x>this._map.transform.width-ft/2&&hr.push(\"right\"),hr.length===0?we=\"bottom\":we=hr.join(\"-\")}var qt=ne.add(Ue[we]).round();o.setTransform(this._container,Vn[we]+\" translate(\"+qt.x+\"px,\"+qt.y+\"px)\"),na(this._container,we,\"popup\")}},D.prototype._focusFirstElement=function(){if(!(!this.options.focusAfterOpen||!this._container)){var q=this._container.querySelector(Ys);q&&q.focus()}},D.prototype._onClose=function(){this.remove()},D}(i.Evented);function ol(Y){if(Y)if(typeof Y==\"number\"){var D=Math.round(Math.sqrt(.5*Math.pow(Y,2)));return{center:new i.Point(0,0),top:new i.Point(0,Y),\"top-left\":new i.Point(D,D),\"top-right\":new i.Point(-D,D),bottom:new i.Point(0,-Y),\"bottom-left\":new i.Point(D,-D),\"bottom-right\":new i.Point(-D,-D),left:new i.Point(Y,0),right:new i.Point(-Y,0)}}else if(Y instanceof i.Point||Array.isArray(Y)){var J=i.Point.convert(Y);return{center:J,top:J,\"top-left\":J,\"top-right\":J,bottom:J,\"bottom-left\":J,\"bottom-right\":J,left:J,right:J}}else return{center:i.Point.convert(Y.center||[0,0]),top:i.Point.convert(Y.top||[0,0]),\"top-left\":i.Point.convert(Y[\"top-left\"]||[0,0]),\"top-right\":i.Point.convert(Y[\"top-right\"]||[0,0]),bottom:i.Point.convert(Y.bottom||[0,0]),\"bottom-left\":i.Point.convert(Y[\"bottom-left\"]||[0,0]),\"bottom-right\":i.Point.convert(Y[\"bottom-right\"]||[0,0]),left:i.Point.convert(Y.left||[0,0]),right:i.Point.convert(Y.right||[0,0])};else return ol(new i.Point(0,0))}var io={version:i.version,supported:a,setRTLTextPlugin:i.setRTLTextPlugin,getRTLTextPluginStatus:i.getRTLTextPluginStatus,Map:li,NavigationControl:Vi,GeolocateControl:Zs,AttributionControl:en,ScaleControl:Ml,FullscreenControl:ss,Popup:wa,Marker:Ki,Style:yu,LngLat:i.LngLat,LngLatBounds:i.LngLatBounds,Point:i.Point,MercatorCoordinate:i.MercatorCoordinate,Evented:i.Evented,config:i.config,prewarm:ua,clearPrewarmedResources:ma,get accessToken(){return i.config.ACCESS_TOKEN},set accessToken(Y){i.config.ACCESS_TOKEN=Y},get baseApiUrl(){return i.config.API_URL},set baseApiUrl(Y){i.config.API_URL=Y},get workerCount(){return fn.workerCount},set workerCount(Y){fn.workerCount=Y},get maxParallelImageRequests(){return i.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(Y){i.config.MAX_PARALLEL_IMAGE_REQUESTS=Y},clearStorage:function(D){i.clearTileCache(D)},workerUrl:\"\"};return io}),r})});var cGe=ye((_xr,uGe)=>{\"use strict\";var rw=Dr(),Fjt=ru().sanitizeHTML,zjt=rJ(),oGe=c1();function sGe(e,t){this.subplot=e,this.uid=e.uid+\"-\"+t,this.index=t,this.idSource=\"source-\"+this.uid,this.idLayer=oGe.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var ig=sGe.prototype;ig.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=Jz(t)};ig.needsNewImage=function(e){var t=this.subplot.map;return t.getSource(this.idSource)&&this.sourceType===\"image\"&&e.sourcetype===\"image\"&&(this.source!==e.source||JSON.stringify(this.coordinates)!==JSON.stringify(e.coordinates))};ig.needsNewSource=function(e){return this.sourceType!==e.sourcetype||JSON.stringify(this.source)!==JSON.stringify(e.source)||this.layerType!==e.type};ig.needsNewLayer=function(e){return this.layerType!==e.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]};ig.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]};ig.updateImage=function(e){var t=this.subplot.map;t.getSource(this.idSource).updateImage({url:e.source,coordinates:e.coordinates});var r=this.findFollowingMapboxLayerId(this.lookupBelow());r!==null&&this.subplot.map.moveLayer(this.idLayer,r)};ig.updateSource=function(e){var t=this.subplot.map;if(t.getSource(this.idSource)&&t.removeSource(this.idSource),this.sourceType=e.sourcetype,this.source=e.source,!!Jz(e)){var r=Ojt(e);t.addSource(this.idSource,r)}};ig.findFollowingMapboxLayerId=function(e){if(e===\"traces\")for(var t=this.subplot.getMapLayers(),r=0;r<t.length;r++){var n=t[r].id;if(typeof n==\"string\"&&n.indexOf(oGe.traceLayerPrefix)===0){e=n;break}}return e};ig.updateLayer=function(e){var t=this.subplot,r=lGe(e),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),Jz(e)&&t.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":e.sourcelayer||\"\",type:e.type,minzoom:e.minzoom,maxzoom:e.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=e.type,this.below=n};ig.updateStyle=function(e){if(Jz(e)){var t=lGe(e);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",t.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",t.paint)}};ig.removeLayer=function(){var e=this.subplot.map;e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer)};ig.dispose=function(){var e=this.subplot.map;e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer),e.getSource(this.idSource)&&e.removeSource(this.idSource)};function Jz(e){if(!e.visible)return!1;var t=e.source;if(Array.isArray(t)&&t.length>0){for(var r=0;r<t.length;r++)if(typeof t[r]!=\"string\"||t[r].length===0)return!1;return!0}return rw.isPlainObject(t)||typeof t==\"string\"&&t.length>0}function lGe(e){var t={},r={};switch(e.type){case\"circle\":rw.extendFlat(r,{\"circle-radius\":e.circle.radius,\"circle-color\":e.color,\"circle-opacity\":e.opacity});break;case\"line\":rw.extendFlat(r,{\"line-width\":e.line.width,\"line-color\":e.color,\"line-opacity\":e.opacity,\"line-dasharray\":e.line.dash});break;case\"fill\":rw.extendFlat(r,{\"fill-color\":e.color,\"fill-outline-color\":e.fill.outlinecolor,\"fill-opacity\":e.opacity});break;case\"symbol\":var n=e.symbol,i=zjt(n.textposition,n.iconsize);rw.extendFlat(t,{\"icon-image\":n.icon+\"-15\",\"icon-size\":n.iconsize/10,\"text-field\":n.text,\"text-size\":n.textfont.size,\"text-anchor\":i.anchor,\"text-offset\":i.offset,\"symbol-placement\":n.placement}),rw.extendFlat(r,{\"icon-color\":e.color,\"text-color\":n.textfont.color,\"text-opacity\":e.opacity});break;case\"raster\":rw.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":e.opacity});break}return{layout:t,paint:r}}function Ojt(e){var t=e.sourcetype,r=e.source,n={type:t},i;return t===\"geojson\"?i=\"data\":t===\"vector\"?i=typeof r==\"string\"?\"url\":\"tiles\":t===\"raster\"?(i=\"tiles\",n.tileSize=256):t===\"image\"&&(i=\"url\",n.coordinates=e.coordinates),n[i]=r,e.sourceattribution&&(n.attribution=Fjt(e.sourceattribution)),n}uGe.exports=function(t,r,n){var i=new sGe(t,r);return i.update(n),i}});var _Ge=ye((xxr,yGe)=>{\"use strict\";var uJ=lJ(),cJ=Dr(),vGe=ix(),fGe=qa(),qjt=ho(),Bjt=yv(),$z=vf(),pGe=Mg(),Njt=pGe.drawMode,Ujt=pGe.selectMode,Vjt=Of().prepSelect,Gjt=Of().clearOutline,Hjt=Of().clearSelectionsCache,jjt=Of().selectOnClick,_x=c1(),Wjt=cGe();function gGe(e,t){this.id=t,this.gd=e;var r=e._fullLayout,n=e._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var Nh=gGe.prototype;Nh.plot=function(e,t,r){var n=this,i=t[n.id];n.map&&i.accesstoken!==n.accessToken&&(n.map.remove(),n.map=null,n.styleObj=null,n.traceHash={},n.layerList=[]);var a;n.map?a=new Promise(function(o,s){n.updateMap(e,t,o,s)}):a=new Promise(function(o,s){n.createMap(e,t,o,s)}),r.push(a)};Nh.createMap=function(e,t,r,n){var i=this,a=t[i.id],o=i.styleObj=mGe(a.style,t);i.accessToken=a.accesstoken;var s=a.bounds,l=s?[[s.west,s.south],[s.east,s.north]]:null,u=i.map=new uJ.Map({container:i.div,style:o.style,center:fJ(a.center),zoom:a.zoom,bearing:a.bearing,pitch:a.pitch,maxBounds:l,interactive:!i.isStatic,preserveDrawingBuffer:i.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new uJ.AttributionControl({compact:!0}));u._canvas.style.left=\"0px\",u._canvas.style.top=\"0px\",i.rejectOnError(n),i.isStatic||i.initFx(e,t);var c=[];c.push(new Promise(function(f){u.once(\"load\",f)})),c=c.concat(vGe.fetchTraceGeoData(e)),Promise.all(c).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Nh.updateMap=function(e,t,r,n){var i=this,a=i.map,o=t[this.id];i.rejectOnError(n);var s=[],l=mGe(o.style,t);JSON.stringify(i.styleObj)!==JSON.stringify(l)&&(i.styleObj=l,a.setStyle(l.style),i.traceHash={},s.push(new Promise(function(u){a.once(\"styledata\",u)}))),s=s.concat(vGe.fetchTraceGeoData(e)),Promise.all(s).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Nh.fillBelowLookup=function(e,t){var r=t[this.id],n=r.layers,i,a,o=this.belowLookup={},s=!1;for(i=0;i<e.length;i++){var l=e[i][0].trace,u=l._module;typeof l.below==\"string\"?a=l.below:u.getBelow&&(a=u.getBelow(l,this)),a===\"\"&&(s=!0),o[\"trace-\"+l.uid]=a||\"\"}for(i=0;i<n.length;i++){var c=n[i];typeof c.below==\"string\"?a=c.below:s?a=\"traces\":a=\"\",o[\"layout-\"+i]=a}var f={},h,d;for(h in o)a=o[h],f[a]?f[a].push(h):f[a]=[h];for(a in f){var v=f[a];if(v.length>1)for(i=0;i<v.length;i++)h=v[i],h.indexOf(\"trace-\")===0?(d=h.split(\"trace-\")[1],this.traceHash[d]&&(this.traceHash[d].below=null)):h.indexOf(\"layout-\")===0&&(d=h.split(\"layout-\")[1],this.layerList[d]&&(this.layerList[d].below=null))}};var hGe={choroplethmapbox:0,densitymapbox:1,scattermapbox:2};Nh.updateData=function(e){var t=this.traceHash,r,n,i,a,o=e.slice().sort(function(f,h){return hGe[f[0].trace.type]-hGe[h[0].trace.type]});for(i=0;i<o.length;i++){var s=o[i];n=s[0].trace,r=t[n.uid];var l=!1;r&&(r.type===n.type?(r.update(s),l=!0):r.dispose()),!l&&n._module&&(t[n.uid]=n._module.plot(this,s))}var u=Object.keys(t);e:for(i=0;i<u.length;i++){var c=u[i];for(a=0;a<e.length;a++)if(n=e[a][0].trace,c===n.uid)continue e;r=t[c],r.dispose(),delete t[c]}};Nh.updateLayout=function(e){var t=this.map,r=e[this.id];!this.dragging&&!this.wheeling&&(t.setCenter(fJ(r.center)),t.setZoom(r.zoom),t.setBearing(r.bearing),t.setPitch(r.pitch)),this.updateLayers(e),this.updateFramework(e),this.updateFx(e),this.map.resize(),this.gd._context._scrollZoom.mapbox?t.scrollZoom.enable():t.scrollZoom.disable()};Nh.resolveOnRender=function(e){var t=this.map;t.on(\"render\",function r(){t.loaded()&&(t.off(\"render\",r),setTimeout(e,10))})};Nh.rejectOnError=function(e){var t=this.map;function r(){e(new Error(_x.mapOnErrorMsg))}t.once(\"error\",r),t.once(\"style.error\",r),t.once(\"source.error\",r),t.once(\"tile.error\",r),t.once(\"layer.error\",r)};Nh.createFramework=function(e){var t=this,r=t.div=document.createElement(\"div\");r.id=t.uid,r.style.position=\"absolute\",t.container.appendChild(r),t.xaxis={_id:\"x\",c2p:function(n){return t.project(n).x}},t.yaxis={_id:\"y\",c2p:function(n){return t.project(n).y}},t.updateFramework(e),t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},qjt.setConvert(t.mockAxis,e)};Nh.initFx=function(e,t){var r=this,n=r.gd,i=r.map;i.on(\"moveend\",function(s){if(r.map){var l=n._fullLayout;if(s.originalEvent||r.wheeling){var u=l[r.id];fGe.call(\"_storeDirectGUIEdit\",n.layout,l._preGUI,r.getViewEdits(u));var c=r.getView();u._input.center=u.center=c.center,u._input.zoom=u.zoom=c.zoom,u._input.bearing=u.bearing=c.bearing,u._input.pitch=u.pitch=c.pitch,n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(c))}s.originalEvent&&s.originalEvent.type===\"mouseup\"?r.dragging=!1:r.wheeling&&(r.wheeling=!1),l._rehover&&l._rehover()}}),i.on(\"wheel\",function(){r.wheeling=!0}),i.on(\"mousemove\",function(s){var l=r.div.getBoundingClientRect(),u=[s.originalEvent.offsetX,s.originalEvent.offsetY];s.target.getBoundingClientRect=function(){return l},r.xaxis.p2c=function(){return i.unproject(u).lng},r.yaxis.p2c=function(){return i.unproject(u).lat},n._fullLayout._rehover=function(){n._fullLayout._hoversubplot===r.id&&n._fullLayout[r.id]&&$z.hover(n,s,r.id)},$z.hover(n,s,r.id),n._fullLayout._hoversubplot=r.id});function a(){$z.loneUnhover(t._hoverlayer)}i.on(\"dragstart\",function(){r.dragging=!0,a()}),i.on(\"zoomstart\",a),i.on(\"mouseout\",function(){n._fullLayout._hoversubplot=null});function o(){var s=r.getView();n.emit(\"plotly_relayouting\",r.getViewEditsWithDerived(s))}i.on(\"drag\",o),i.on(\"zoom\",o),i.on(\"dblclick\",function(){var s=n._fullLayout[r.id];fGe.call(\"_storeDirectGUIEdit\",n.layout,n._fullLayout._preGUI,r.getViewEdits(s));var l=r.viewInitial;i.setCenter(fJ(l.center)),i.setZoom(l.zoom),i.setBearing(l.bearing),i.setPitch(l.pitch);var u=r.getView();s._input.center=s.center=u.center,s._input.zoom=s.zoom=u.zoom,s._input.bearing=s.bearing=u.bearing,s._input.pitch=s.pitch=u.pitch,n.emit(\"plotly_doubleclick\",null),n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(u))}),r.clearOutline=function(){Hjt(r.dragOptions),Gjt(r.dragOptions.gd)},r.onClickInPanFn=function(s){return function(l){var u=n._fullLayout.clickmode;u.indexOf(\"select\")>-1&&jjt(l.originalEvent,n,[r.xaxis],[r.yaxis],r.id,s),u.indexOf(\"event\")>-1&&$z.click(n,l.originalEvent)}}};Nh.updateFx=function(e){var t=this,r=t.map,n=t.gd;if(t.isStatic)return;function i(l){var u=t.map.unproject(l);return[u.lng,u.lat]}var a=e.dragmode,o;o=function(l,u){if(u.isRect){var c=l.range={};c[t.id]=[i([u.xmin,u.ymin]),i([u.xmax,u.ymax])]}else{var f=l.lassoPoints={};f[t.id]=u.map(i)}};var s=t.dragOptions;t.dragOptions=cJ.extendDeep(s||{},{dragmode:e.dragmode,element:t.div,gd:n,plotinfo:{id:t.id,domain:e[t.id].domain,xaxis:t.xaxis,yaxis:t.yaxis,fillRangeItems:o},xaxes:[t.xaxis],yaxes:[t.yaxis],subplot:t.id}),r.off(\"click\",t.onClickInPanHandler),Ujt(a)||Njt(a)?(r.dragPan.disable(),r.on(\"zoomstart\",t.clearOutline),t.dragOptions.prepFn=function(l,u,c){Vjt(l,u,c,t.dragOptions,a)},Bjt.init(t.dragOptions)):(r.dragPan.enable(),r.off(\"zoomstart\",t.clearOutline),t.div.onmousedown=null,t.div.ontouchstart=null,t.div.removeEventListener(\"touchstart\",t.div._ontouchstart),t.onClickInPanHandler=t.onClickInPanFn(t.dragOptions),r.on(\"click\",t.onClickInPanHandler))};Nh.updateFramework=function(e){var t=e[this.id].domain,r=e._size,n=this.div.style;n.width=r.w*(t.x[1]-t.x[0])+\"px\",n.height=r.h*(t.y[1]-t.y[0])+\"px\",n.left=r.l+t.x[0]*r.w+\"px\",n.top=r.t+(1-t.y[1])*r.h+\"px\",this.xaxis._offset=r.l+t.x[0]*r.w,this.xaxis._length=r.w*(t.x[1]-t.x[0]),this.yaxis._offset=r.t+(1-t.y[1])*r.h,this.yaxis._length=r.h*(t.y[1]-t.y[0])};Nh.updateLayers=function(e){var t=e[this.id],r=t.layers,n=this.layerList,i;if(r.length!==n.length){for(i=0;i<n.length;i++)n[i].dispose();for(n=this.layerList=[],i=0;i<r.length;i++)n.push(Wjt(this,i,r[i]))}else for(i=0;i<r.length;i++)n[i].update(r[i])};Nh.destroy=function(){this.map&&(this.map.remove(),this.map=null,this.container.removeChild(this.div))};Nh.toImage=function(){return this.map.stop(),this.map.getCanvas().toDataURL()};Nh.setOptions=function(e,t,r){for(var n in r)this.map[t](e,n,r[n])};Nh.getMapLayers=function(){return this.map.getStyle().layers};Nh.addLayer=function(e,t){var r=this.map;if(typeof t==\"string\"){if(t===\"\"){r.addLayer(e,t);return}for(var n=this.getMapLayers(),i=0;i<n.length;i++)if(t===n[i].id){r.addLayer(e,t);return}cJ.warn([\"Trying to add layer with *below* value\",t,\"referencing a layer that does not exist\",\"or that does not yet exist.\"].join(\" \"))}r.addLayer(e)};Nh.project=function(e){return this.map.project(new uJ.LngLat(e[0],e[1]))};Nh.getView=function(){var e=this.map,t=e.getCenter(),r=t.lng,n=t.lat,i={lon:r,lat:n},a=e.getCanvas(),o=parseInt(a.style.width),s=parseInt(a.style.height);return{center:i,zoom:e.getZoom(),bearing:e.getBearing(),pitch:e.getPitch(),_derived:{coordinates:[e.unproject([0,0]).toArray(),e.unproject([o,0]).toArray(),e.unproject([o,s]).toArray(),e.unproject([0,s]).toArray()]}}};Nh.getViewEdits=function(e){for(var t=this.id,r=[\"center\",\"zoom\",\"bearing\",\"pitch\"],n={},i=0;i<r.length;i++){var a=r[i];n[t+\".\"+a]=e[a]}return n};Nh.getViewEditsWithDerived=function(e){var t=this.id,r=this.getViewEdits(e);return r[t+\"._derived\"]=e._derived,r};function mGe(e,t){var r={};if(cJ.isPlainObject(e))r.id=e.id,r.style=e;else if(typeof e==\"string\")if(r.id=e,_x.styleValuesMapbox.indexOf(e)!==-1)r.style=dGe(e);else if(_x.stylesNonMapbox[e]){r.style=_x.stylesNonMapbox[e];var n=r.style.sources[\"plotly-\"+e],i=n?n.tiles:void 0;i&&i[0]&&i[0].slice(-9)===\"?api_key=\"&&(i[0]+=t._mapboxAccessToken)}else r.style=e;else r.id=_x.styleValueDflt,r.style=dGe(_x.styleValueDflt);return r.transition={duration:0,delay:0},r}function dGe(e){return _x.styleUrlPrefix+e+\"-\"+_x.styleUrlSuffix}function fJ(e){return[e.lon,e.lat]}yGe.exports=gGe});var wGe=ye((bxr,bGe)=>{\"use strict\";var hJ=Dr(),Xjt=k_(),Zjt=Yd(),xGe=Nk();bGe.exports=function(t,r,n){Xjt(t,r,n,{type:\"mapbox\",attributes:xGe,handleDefaults:Yjt,partition:\"y\",accessToken:r._mapboxAccessToken})};function Yjt(e,t,r,n){r(\"accesstoken\",n.accessToken),r(\"style\"),r(\"center.lon\"),r(\"center.lat\"),r(\"zoom\"),r(\"bearing\"),r(\"pitch\");var i=r(\"bounds.west\"),a=r(\"bounds.east\"),o=r(\"bounds.south\"),s=r(\"bounds.north\");(i===void 0||a===void 0||o===void 0||s===void 0)&&delete t.bounds,Zjt(e,t,{name:\"layers\",handleItemDefaults:Kjt}),t._input=e}function Kjt(e,t){function r(l,u){return hJ.coerce(e,t,xGe.layers,l,u)}var n=r(\"visible\");if(n){var i=r(\"sourcetype\"),a=i===\"raster\"||i===\"image\";r(\"source\"),r(\"sourceattribution\"),i===\"vector\"&&r(\"sourcelayer\"),i===\"image\"&&r(\"coordinates\");var o;a&&(o=\"raster\");var s=r(\"type\",o);a&&s!==\"raster\"&&(s=t.type=\"raster\",hJ.log(\"Source types *raster* and *image* must drawn *raster* layer type.\")),r(\"below\"),r(\"color\"),r(\"opacity\"),r(\"minzoom\"),r(\"maxzoom\"),s===\"circle\"&&r(\"circle.radius\"),s===\"line\"&&(r(\"line.width\"),r(\"line.dash\")),s===\"fill\"&&r(\"fill.outlinecolor\"),s===\"symbol\"&&(r(\"symbol.icon\"),r(\"symbol.iconsize\"),r(\"symbol.text\"),hJ.coerceFont(r,\"symbol.textfont\",void 0,{noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0}),r(\"symbol.textposition\"),r(\"symbol.placement\"))}}});var Qz=ye(Np=>{\"use strict\";var TGe=lJ(),tm=Dr(),dJ=tm.strTranslate,Jjt=tm.strScale,$jt=Id().getSubplotCalcData,Qjt=Wp(),eWt=Oa(),AGe=So(),tWt=ru(),rWt=_Ge(),xx=\"mapbox\",ey=Np.constants=c1();Np.name=xx;Np.attr=\"subplot\";Np.idRoot=xx;Np.idRegex=Np.attrRegex=tm.counterRegex(xx);var iWt=[\"mapbox subplots and traces are deprecated!\",\"Please consider switching to `map` subplots and traces.\",\"Learn more at: https://plotly.com/python/maplibre-migration/\",\"as well as https://plotly.com/javascript/maplibre-migration/\"].join(\" \");Np.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}};Np.layoutAttributes=Nk();Np.supplyLayoutDefaults=wGe();var SGe=!0;Np.plot=function(t){SGe&&(SGe=!1,tm.warn(iWt));var r=t._fullLayout,n=t.calcdata,i=r._subplots[xx];if(TGe.version!==ey.requiredVersion)throw new Error(ey.wrongVersionErrorMsg);var a=nWt(t,i);TGe.accessToken=a;for(var o=0;o<i.length;o++){var s=i[o],l=$jt(n,xx,s),u=r[s],c=u._subplot;c||(c=new rWt(t,s),r[s]._subplot=c),c.viewInitial||(c.viewInitial={center:tm.extendFlat({},u.center),zoom:u.zoom,bearing:u.bearing,pitch:u.pitch}),c.plot(l,r,t._promises)}};Np.clean=function(e,t,r,n){for(var i=n._subplots[xx]||[],a=0;a<i.length;a++){var o=i[a];!t[o]&&n[o]._subplot&&n[o]._subplot.destroy()}};Np.toSVG=function(e){for(var t=e._fullLayout,r=t._subplots[xx],n=t._size,i=0;i<r.length;i++){var a=t[r[i]],o=a.domain,s=a._subplot,l=s.toImage(\"png\"),u=t._glimages.append(\"svg:image\");u.attr({xmlns:Qjt.svg,\"xlink:href\":l,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"});var c=eWt.select(a._subplot.div),f=c.select(\".mapboxgl-ctrl-logo\").node().offsetParent===null;if(!f){var h=t._glimages.append(\"g\");h.attr(\"transform\",dJ(n.l+n.w*o.x[0]+10,n.t+n.h*(1-o.y[0])-31)),h.append(\"path\").attr(\"d\",ey.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),h.append(\"path\").attr(\"d\",ey.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),h.append(\"path\").attr(\"d\",ey.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),h.append(\"polygon\").attr(\"points\",ey.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var d=c.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),v=t._glimages.append(\"g\"),_=v.append(\"text\");_.text(d).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":d});var b=AGe.bBox(_.node()),p=n.w*(o.x[1]-o.x[0]);if(b.width>p/2){var k=d.split(\"|\").join(\"<br>\");_.text(k).attr(\"data-unformatted\",k).call(tWt.convertToTspans,e),b=AGe.bBox(_.node())}_.attr(\"transform\",dJ(-3,-b.height+8)),v.insert(\"rect\",\".static-attribution\").attr({x:-b.width-6,y:-b.height-3,width:b.width+6,height:b.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var E=1;b.width+6>p&&(E=p/(b.width+6));var S=[n.l+n.w*o.x[1],n.t+n.h*(1-o.y[0])];v.attr(\"transform\",dJ(S[0],S[1])+Jjt(E))}};function nWt(e,t){var r=e._fullLayout,n=e._context;if(n.mapboxAccessToken===\"\")return\"\";for(var i=[],a=[],o=!1,s=!1,l=0;l<t.length;l++){var u=r[t[l]],c=u.accesstoken;MGe(u.style)&&(c?tm.pushUnique(i,c):(MGe(u._input.style)&&(tm.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),c&&tm.pushUnique(a,c)}if(s){var f=o?ey.noAccessTokenErrorMsg:ey.missingStyleErrorMsg;throw tm.error(f),new Error(f)}return i.length?(i.length>1&&tm.warn(ey.multipleTokensErrorMsg),i[0]):(a.length&&tm.log([\"Listed mapbox access token(s)\",a.join(\",\"),\"but did not use a Mapbox map style, ignoring token(s).\"].join(\" \")),\"\")}function MGe(e){return typeof e==\"string\"&&(ey.styleValuesMapbox.indexOf(e)!==-1||e.indexOf(\"mapbox://\")===0||e.indexOf(\"stamen\")===0)}Np.updateFx=function(e){for(var t=e._fullLayout,r=t._subplots[xx],n=0;n<r.length;n++){var i=t[r[n]]._subplot;i.updateFx(t)}}});var kGe=ye((Axr,EGe)=>{\"use strict\";var Txr=[\"*scattermapbox* trace is deprecated!\",\"Please consider switching to the *scattermap* trace type and `map` subplots.\",\"Learn more at: https://plotly.com/python/maplibre-migration/\",\"as well as https://plotly.com/javascript/maplibre-migration/\"].join(\" \");EGe.exports={attributes:jz(),supplyDefaults:BVe(),colorbar:$d(),formatLabels:tJ(),calc:vF(),plot:QVe(),hoverPoints:Kz().hoverPoints,eventData:iGe(),selectPoints:aGe(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.update(t)}},moduleType:\"trace\",name:\"scattermapbox\",basePlotModule:Qz(),categories:[\"mapbox\",\"gl\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}});var LGe=ye((Sxr,CGe)=>{\"use strict\";CGe.exports=kGe()});var vJ=ye((Mxr,PGe)=>{\"use strict\";var f1=e5(),aWt=Tu(),{hovertemplateAttrs:oWt,templatefallbackAttrs:sWt}=Ll(),lWt=Gl(),bx=Ao().extendFlat;PGe.exports=bx({locations:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},geojson:{valType:\"any\",editType:\"calc\"},featureidkey:bx({},f1.featureidkey,{}),below:{valType:\"string\",editType:\"plot\"},text:f1.text,hovertext:f1.hovertext,marker:{line:{color:bx({},f1.marker.line.color,{editType:\"plot\"}),width:bx({},f1.marker.line.width,{editType:\"plot\"}),editType:\"calc\"},opacity:bx({},f1.marker.opacity,{editType:\"plot\"}),editType:\"calc\"},selected:{marker:{opacity:bx({},f1.selected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},unselected:{marker:{opacity:bx({},f1.unselected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},hoverinfo:f1.hoverinfo,hovertemplate:oWt({},{keys:[\"properties\"]}),hovertemplatefallback:sWt(),showlegend:bx({},lWt.showlegend,{dflt:!1})},aWt(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))});var RGe=ye((Exr,IGe)=>{\"use strict\";var Hk=Dr(),uWt=Qh(),cWt=vJ();IGe.exports=function(t,r,n,i){function a(c,f){return Hk.coerce(t,r,cWt,c,f)}var o=a(\"locations\"),s=a(\"z\"),l=a(\"geojson\");if(!Hk.isArrayOrTypedArray(o)||!o.length||!Hk.isArrayOrTypedArray(s)||!s.length||!(typeof l==\"string\"&&l!==\"\"||Hk.isPlainObject(l))){r.visible=!1;return}a(\"featureidkey\"),r._length=Math.min(o.length,s.length),a(\"below\"),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\");var u=a(\"marker.line.width\");u&&a(\"marker.line.color\"),a(\"marker.opacity\"),uWt(t,r,i,a,{prefix:\"\",cLetter:\"z\"}),Hk.coerceSelectionMarkerOpacity(r,a)}});var pJ=ye((kxr,zGe)=>{\"use strict\";var fWt=Eo(),h1=Dr(),hWt=tc(),dWt=So(),vWt=tx().makeBlank,DGe=ix();function pWt(e){var t=e[0].trace,r=t.visible===!0&&t._length!==0,n={layout:{visibility:\"none\"},paint:{}},i={layout:{visibility:\"none\"},paint:{}},a=t._opts={fill:n,line:i,geojson:vWt()};if(!r)return a;var o=DGe.extractTraceFeature(e);if(!o)return a;var s=hWt.makeColorScaleFuncFromTrace(t),l=t.marker,u=l.line||{},c;h1.isArrayOrTypedArray(l.opacity)&&(c=function(k){var E=k.mo;return fWt(E)?+h1.constrain(E,0,1):0});var f;h1.isArrayOrTypedArray(u.color)&&(f=function(k){return k.mlc});var h;h1.isArrayOrTypedArray(u.width)&&(h=function(k){return k.mlw});for(var d=0;d<e.length;d++){var v=e[d],_=v.fOut;if(_){var b=_.properties;b.fc=s(v.z),c&&(b.mo=c(v)),f&&(b.mlc=f(v)),h&&(b.mlw=h(v)),v.ct=b.ct,v._polygons=DGe.feature2polygons(_)}}var p=c?{type:\"identity\",property:\"mo\"}:l.opacity;return h1.extendFlat(n.paint,{\"fill-color\":{type:\"identity\",property:\"fc\"},\"fill-opacity\":p}),h1.extendFlat(i.paint,{\"line-color\":f?{type:\"identity\",property:\"mlc\"}:u.color,\"line-width\":h?{type:\"identity\",property:\"mlw\"}:u.width,\"line-opacity\":p}),n.layout.visibility=\"visible\",i.layout.visibility=\"visible\",a.geojson={type:\"FeatureCollection\",features:o},FGe(e),a}function FGe(e){var t=e[0].trace,r=t._opts,n;if(t.selectedpoints){for(var i=dWt.makeSelectedPointStyleFns(t),a=0;a<e.length;a++){var o=e[a];o.fOut&&(o.fOut.properties.mo2=i.selectedOpacityFn(o))}n={type:\"identity\",property:\"mo2\"}}else n=h1.isArrayOrTypedArray(t.marker.opacity)?{type:\"identity\",property:\"mo\"}:t.marker.opacity;return h1.extendFlat(r.fill.paint,{\"fill-opacity\":n}),h1.extendFlat(r.line.paint,{\"line-opacity\":n}),r}zGe.exports={convert:pWt,convertOnSelect:FGe}});var UGe=ye((Cxr,NGe)=>{\"use strict\";var qGe=pJ().convert,gWt=pJ().convertOnSelect,OGe=c1().traceLayerPrefix;function BGe(e,t){this.type=\"choroplethmapbox\",this.subplot=e,this.uid=t,this.sourceId=\"source-\"+t,this.layerList=[[\"fill\",OGe+t+\"-fill\"],[\"line\",OGe+t+\"-line\"]],this.below=null}var S5=BGe.prototype;S5.update=function(e){this._update(qGe(e)),e[0].trace._glTrace=this};S5.updateOnSelect=function(e){this._update(gWt(e))};S5._update=function(e){var t=this.subplot,r=this.layerList,n=t.belowLookup[\"trace-\"+this.uid];t.map.getSource(this.sourceId).setData(e.geojson),n!==this.below&&(this._removeLayers(),this._addLayers(e,n),this.below=n);for(var i=0;i<r.length;i++){var a=r[i],o=a[0],s=a[1],l=e[o];t.setOptions(s,\"setLayoutProperty\",l.layout),l.layout.visibility===\"visible\"&&t.setOptions(s,\"setPaintProperty\",l.paint)}};S5._addLayers=function(e,t){for(var r=this.subplot,n=this.layerList,i=this.sourceId,a=0;a<n.length;a++){var o=n[a],s=o[0],l=e[s];r.addLayer({type:s,id:o[1],source:i,layout:l.layout,paint:l.paint},t)}};S5._removeLayers=function(){for(var e=this.subplot.map,t=this.layerList,r=t.length-1;r>=0;r--)e.removeLayer(t[r][1])};S5.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};NGe.exports=function(t,r){var n=r[0].trace,i=new BGe(t,n.uid),a=i.sourceId,o=qGe(r),s=i.below=t.belowLookup[\"trace-\"+n.uid];return t.map.addSource(a,{type:\"geojson\",data:o.geojson}),i._addLayers(o,s),r[0].trace._glTrace=i,i}});var GGe=ye((Pxr,VGe)=>{\"use strict\";var Lxr=[\"*choroplethmapbox* trace is deprecated!\",\"Please consider switching to the *choroplethmap* trace type and `map` subplots.\",\"Learn more at: https://plotly.com/python/maplibre-migration/\",\"as well as https://plotly.com/javascript/maplibre-migration/\"].join(\" \");VGe.exports={attributes:vJ(),supplyDefaults:RGe(),colorbar:S_(),calc:FF(),plot:UGe(),hoverPoints:OF(),eventData:qF(),selectPoints:BF(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.updateOnSelect(t)}},getBelow:function(e,t){for(var r=t.getMapLayers(),n=r.length-2;n>=0;n--){var i=r[n].id;if(typeof i==\"string\"&&i.indexOf(\"water\")===0){for(var a=n+1;a<r.length;a++)if(i=r[a].id,typeof i==\"string\"&&i.indexOf(\"plotly-\")===-1)return i}}},moduleType:\"trace\",name:\"choroplethmapbox\",basePlotModule:Qz(),categories:[\"mapbox\",\"gl\",\"noOpacity\",\"showLegend\"],meta:{hr_name:\"choropleth_mapbox\"}}});var jGe=ye((Ixr,HGe)=>{\"use strict\";HGe.exports=GGe()});var mJ=ye((Rxr,XGe)=>{\"use strict\";var mWt=Tu(),{hovertemplateAttrs:yWt,templatefallbackAttrs:_Wt}=Ll(),WGe=Gl(),e7=jz(),gJ=Ao().extendFlat;XGe.exports=gJ({lon:e7.lon,lat:e7.lat,z:{valType:\"data_array\",editType:\"calc\"},radius:{valType:\"number\",editType:\"plot\",arrayOk:!0,min:1,dflt:30},below:{valType:\"string\",editType:\"plot\"},text:e7.text,hovertext:e7.hovertext,hoverinfo:gJ({},WGe.hoverinfo,{flags:[\"lon\",\"lat\",\"z\",\"text\",\"name\"]}),hovertemplate:yWt(),hovertemplatefallback:_Wt(),showlegend:gJ({},WGe.showlegend,{dflt:!1})},mWt(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))});var YGe=ye((Dxr,ZGe)=>{\"use strict\";var xWt=Dr(),bWt=Qh(),wWt=mJ();ZGe.exports=function(t,r,n,i){function a(u,c){return xWt.coerce(t,r,wWt,u,c)}var o=a(\"lon\")||[],s=a(\"lat\")||[],l=Math.min(o.length,s.length);if(!l){r.visible=!1;return}r._length=l,a(\"z\"),a(\"radius\"),a(\"below\"),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),bWt(t,r,i,a,{prefix:\"\",cLetter:\"z\"})}});var $Ge=ye((Fxr,JGe)=>{\"use strict\";var yJ=Eo(),TWt=Dr().isArrayOrTypedArray,_J=fs().BADNUM,AWt=gv(),KGe=Dr()._;JGe.exports=function(t,r){for(var n=r._length,i=new Array(n),a=r.z,o=TWt(a)&&a.length,s=0;s<n;s++){var l=i[s]={},u=r.lon[s],c=r.lat[s];if(l.lonlat=yJ(u)&&yJ(c)?[+u,+c]:[_J,_J],o){var f=a[s];l.z=yJ(f)?f:_J}}return AWt(t,r,{vals:o?a:[0,1],containerStr:\"\",cLetter:\"z\"}),n&&(i[0].t={labels:{lat:KGe(t,\"lat:\")+\" \",lon:KGe(t,\"lon:\")+\" \"}}),i}});var iHe=ye((zxr,rHe)=>{\"use strict\";var SWt=Eo(),xJ=Dr(),QGe=ka(),eHe=tc(),tHe=fs().BADNUM,MWt=tx().makeBlank;rHe.exports=function(t){var r=t[0].trace,n=r.visible===!0&&r._length!==0,i={layout:{visibility:\"none\"},paint:{}},a=r._opts={heatmap:i,geojson:MWt()};if(!n)return a;var o=[],s,l=r.z,u=r.radius,c=xJ.isArrayOrTypedArray(l)&&l.length,f=xJ.isArrayOrTypedArray(u);for(s=0;s<t.length;s++){var h=t[s],d=h.lonlat;if(d[0]!==tHe){var v={};if(c){var _=h.z;v.z=_!==tHe?_:0}f&&(v.r=SWt(u[s])&&u[s]>0?+u[s]:0),o.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:d},properties:v})}}var b=eHe.extractOpts(r),p=b.reversescale?eHe.flipScale(b.colorscale):b.colorscale,k=p[0][1],E=QGe.opacity(k)<1?k:QGe.addOpacity(k,0),S=[\"interpolate\",[\"linear\"],[\"heatmap-density\"],0,E];for(s=1;s<p.length;s++)S.push(p[s][0],p[s][1]);var L=[\"interpolate\",[\"linear\"],[\"get\",\"z\"],b.min,0,b.max,1];return xJ.extendFlat(a.heatmap.paint,{\"heatmap-weight\":c?L:1/(b.max-b.min),\"heatmap-color\":S,\"heatmap-radius\":f?{type:\"identity\",property:\"r\"}:r.radius,\"heatmap-opacity\":r.opacity}),a.geojson={type:\"FeatureCollection\",features:o},a.heatmap.layout.visibility=\"visible\",a}});var sHe=ye((Oxr,oHe)=>{\"use strict\";var nHe=iHe(),EWt=c1().traceLayerPrefix;function aHe(e,t){this.type=\"densitymapbox\",this.subplot=e,this.uid=t,this.sourceId=\"source-\"+t,this.layerList=[[\"heatmap\",EWt+t+\"-heatmap\"]],this.below=null}var t7=aHe.prototype;t7.update=function(e){var t=this.subplot,r=this.layerList,n=nHe(e),i=t.belowLookup[\"trace-\"+this.uid];t.map.getSource(this.sourceId).setData(n.geojson),i!==this.below&&(this._removeLayers(),this._addLayers(n,i),this.below=i);for(var a=0;a<r.length;a++){var o=r[a],s=o[0],l=o[1],u=n[s];t.setOptions(l,\"setLayoutProperty\",u.layout),u.layout.visibility===\"visible\"&&t.setOptions(l,\"setPaintProperty\",u.paint)}};t7._addLayers=function(e,t){for(var r=this.subplot,n=this.layerList,i=this.sourceId,a=0;a<n.length;a++){var o=n[a],s=o[0],l=e[s];r.addLayer({type:s,id:o[1],source:i,layout:l.layout,paint:l.paint},t)}};t7._removeLayers=function(){for(var e=this.subplot.map,t=this.layerList,r=t.length-1;r>=0;r--)e.removeLayer(t[r][1])};t7.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};oHe.exports=function(t,r){var n=r[0].trace,i=new aHe(t,n.uid),a=i.sourceId,o=nHe(r),s=i.below=t.belowLookup[\"trace-\"+n.uid];return t.map.addSource(a,{type:\"geojson\",data:o.geojson}),i._addLayers(o,s),i}});var uHe=ye((qxr,lHe)=>{\"use strict\";var kWt=ho(),CWt=Kz().hoverPoints,LWt=Kz().getExtraText;lHe.exports=function(t,r,n){var i=CWt(t,r,n);if(i){var a=i[0],o=a.cd,s=o[0].trace,l=o[a.index];if(delete a.color,\"z\"in l){var u=a.subplot.mockAxis;a.z=l.z,a.zLabel=kWt.tickText(u,u.c2l(l.z),\"hover\").text}return a.extraText=LWt(s,l,o[0].t.labels),[a]}}});var fHe=ye((Bxr,cHe)=>{\"use 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i7=ye((Xxr,RHe)=>{\"use 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bJ=ye((Zxr,DHe)=>{\"use strict\";var JWt=[\"Metropolis Black Italic\",\"Metropolis Black\",\"Metropolis Bold Italic\",\"Metropolis Bold\",\"Metropolis Extra Bold Italic\",\"Metropolis Extra Bold\",\"Metropolis Extra Light Italic\",\"Metropolis Extra Light\",\"Metropolis Light Italic\",\"Metropolis Light\",\"Metropolis Medium Italic\",\"Metropolis Medium\",\"Metropolis Regular Italic\",\"Metropolis Regular\",\"Metropolis Semi Bold Italic\",\"Metropolis Semi Bold\",\"Metropolis Thin Italic\",\"Metropolis Thin\",\"Open Sans Bold Italic\",\"Open Sans Bold\",\"Open Sans Extrabold Italic\",\"Open Sans Extrabold\",\"Open Sans Italic\",\"Open Sans Light Italic\",\"Open Sans Light\",\"Open Sans Regular\",\"Open Sans Semibold Italic\",\"Open Sans Semibold\",\"Klokantech Noto Sans Bold\",\"Klokantech Noto Sans CJK Bold\",\"Klokantech Noto Sans CJK Regular\",\"Klokantech Noto Sans Italic\",\"Klokantech Noto Sans Regular\"];DHe.exports={isSupportedFont:function(e){return JWt.indexOf(e)!==-1}}});var OHe=ye((Yxr,zHe)=>{\"use strict\";var Xk=Dr(),wJ=Ru(),$Wt=$p(),QWt=R0(),eXt=D0(),tXt=Ig(),FHe=i7(),rXt=bJ().isSupportedFont;zHe.exports=function(t,r,n,i){function a(p,k){return Xk.coerce(t,r,FHe,p,k)}function o(p,k){return Xk.coerce2(t,r,FHe,p,k)}var s=iXt(t,r,a);if(!s){r.visible=!1;return}if(a(\"text\"),a(\"texttemplate\"),a(\"texttemplatefallback\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),a(\"mode\"),a(\"below\"),wJ.hasMarkers(r)){$Wt(t,r,n,i,a,{noLine:!0,noAngle:!0}),a(\"marker.allowoverlap\"),a(\"marker.angle\");var l=r.marker;l.symbol!==\"circle\"&&(Xk.isArrayOrTypedArray(l.size)&&(l.size=l.size[0]),Xk.isArrayOrTypedArray(l.color)&&(l.color=l.color[0]))}wJ.hasLines(r)&&(QWt(t,r,n,i,a,{noDash:!0}),a(\"connectgaps\"));var u=o(\"cluster.maxzoom\"),c=o(\"cluster.step\"),f=o(\"cluster.color\",r.marker&&r.marker.color||n),h=o(\"cluster.size\"),d=o(\"cluster.opacity\"),v=u!==!1||c!==!1||f!==!1||h!==!1||d!==!1,_=a(\"cluster.enabled\",v);if(_||wJ.hasText(r)){var b=i.font.family;eXt(t,r,i,a,{noSelect:!0,noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0,font:{family:rXt(b)?b:\"Open Sans Regular\",weight:i.font.weight,style:i.font.style,size:i.font.size,color:i.font.color}})}a(\"fill\"),r.fill!==\"none\"&&tXt(t,r,n,a),Xk.coerceSelectionMarkerOpacity(r,a)};function iXt(e,t,r){var n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length);return t._length=a,a}});var TJ=ye((Kxr,BHe)=>{\"use strict\";var qHe=ho();BHe.exports=function(t,r,n){var i={},a=n[r.subplot]._subplot,o=a.mockAxis,s=t.lonlat;return i.lonLabel=qHe.tickText(o,o.c2l(s[0]),!0).text,i.latLabel=qHe.tickText(o,o.c2l(s[1]),!0).text,i}});var AJ=ye((Jxr,UHe)=>{\"use strict\";var NHe=Dr();UHe.exports=function(t,r){var n=t.split(\" 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p;if((a||o)&&(p=a7.calcTraceToLineCoords(r)),a&&(h.geojson=a7.makePolygon(p),h.layout.visibility=\"visible\",ov.extendFlat(h.paint,{\"fill-color\":n.fillcolor})),o&&(d.geojson=a7.makeLine(p),d.layout.visibility=\"visible\",ov.extendFlat(d.paint,{\"line-width\":n.line.width,\"line-color\":n.line.color,\"line-opacity\":n.opacity})),u){var k=hXt(r);v.geojson=k.geojson,v.layout.visibility=\"visible\",f&&(v.filter=[\"!\",[\"has\",\"point_count\"]],b.cluster={type:\"circle\",filter:[\"has\",\"point_count\"],layout:{visibility:\"visible\"},paint:{\"circle-color\":MJ(n.cluster.color,n.cluster.step),\"circle-radius\":MJ(n.cluster.size,n.cluster.step),\"circle-opacity\":MJ(n.cluster.opacity,n.cluster.step)}},b.clusterCount={type:\"symbol\",filter:[\"has\",\"point_count\"],paint:{},layout:{\"text-field\":\"{point_count_abbreviated}\",\"text-font\":GHe(n),\"text-size\":12}}),ov.extendFlat(v.paint,{\"circle-color\":k.mcc,\"circle-radius\":k.mrc,\"circle-opacity\":k.mo})}if(u&&f&&(v.filter=[\"!\",[\"has\",\"point_count\"]]),(c||l)&&(_.geojson=dXt(r,t),ov.extendFlat(_.layout,{visibility:\"visible\",\"icon-image\":\"{symbol}-15\",\"text-field\":\"{text}\"}),c&&(ov.extendFlat(_.layout,{\"icon-size\":n.marker.size/10}),\"angle\"in 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r=t._fullLayout,n=e[0].trace,i=n.marker||{},a=i.symbol,o=i.angle,s=a!==\"circle\"?SJ(a):s7,l=o!==\"auto\"?SJ(o,!0):s7,u=o7.hasText(n)?SJ(n.text):s7,c=[],f=0;f<e.length;f++){var h=e[f];if(!jHe(h.lonlat)){var d=n.texttemplate,v;if(d){var _=Array.isArray(d)?d[f]||\"\":d,b=n._module.formatLabels(h,n,r),p={};uXt(p,n,h.i),v=ov.texttemplateString({data:[p,h,n._meta],fallback:n.texttemplatefallback,labels:b,locale:r._d3locale,template:_})}else v=u(f);v&&(v=v.replace(cXt,\"\").replace(fXt,`\n",
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YHe(e,t,r,n){this.type=\"scattermap\",this.subplot=e,this.uid=t,this.clusterEnabled=r,this.isHidden=n,this.sourceIds={fill:\"source-\"+t+\"-fill\",line:\"source-\"+t+\"-line\",circle:\"source-\"+t+\"-circle\",symbol:\"source-\"+t+\"-symbol\",cluster:\"source-\"+t+\"-circle\",clusterCount:\"source-\"+t+\"-circle\"},this.layerIds={fill:k5+t+\"-fill\",line:k5+t+\"-line\",circle:k5+t+\"-circle\",symbol:k5+t+\"-symbol\",cluster:k5+t+\"-cluster\",clusterCount:k5+t+\"-cluster-count\"},this.below=null}var Zk=YHe.prototype;Zk.addSource=function(e,t,r){var n={type:\"geojson\",data:t.geojson};r&&r.enabled&&vXt.extendFlat(n,{cluster:!0,clusterMaxZoom:r.maxzoom});var i=this.subplot.map.getSource(this.sourceIds[e]);i?i.setData(t.geojson):this.subplot.map.addSource(this.sourceIds[e],n)};Zk.setSourceData=function(e,t){this.subplot.map.getSource(this.sourceIds[e]).setData(t.geojson)};Zk.addLayer=function(e,t,r){var n={type:t.type,id:this.layerIds[e],source:this.sourceIds[e],layout:t.layout,paint:t.paint};t.filter&&(n.filter=t.filter);for(var i=this.layerIds[e],a,o=this.subplot.getMapLayers(),s=0;s<o.length;s++)if(o[s].id===i){a=!0;break}a?(this.subplot.setOptions(i,\"setLayoutProperty\",n.layout),n.layout.visibility===\"visible\"&&this.subplot.setOptions(i,\"setPaintProperty\",n.paint)):this.subplot.addLayer(n,r)};Zk.update=function(t){var r=t[0].trace,n=this.subplot,i=n.map,a=ZHe(n.gd,t),o=n.belowLookup[\"trace-\"+this.uid],s=!!(r.cluster&&r.cluster.enabled),l=!!this.clusterEnabled,u=this;function c(E){E||u.addSource(\"circle\",a.circle,r.cluster);for(var S=ng.cluster,L=0;L<S.length;L++){var x=S[L],C=a[x];u.addLayer(x,C,o)}}function f(E){for(var S=ng.cluster,L=S.length-1;L>=0;L--){var x=S[L];i.removeLayer(u.layerIds[x])}E||i.removeSource(u.sourceIds.circle)}function h(E){for(var S=ng.nonCluster,L=0;L<S.length;L++){var x=S[L],C=a[x];E||u.addSource(x,C),u.addLayer(x,C,o)}}function d(E){for(var 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YHe(t,n.uid,i,a),s=ZHe(t.gd,r),l=o.below=t.belowLookup[\"trace-\"+n.uid],u,c,f;if(i)for(o.addSource(\"circle\",s.circle,n.cluster),u=0;u<ng.cluster.length;u++)c=ng.cluster[u],f=s[c],o.addLayer(c,f,l);else for(u=0;u<ng.nonCluster.length;u++)c=ng.nonCluster[u],f=s[c],o.addSource(c,f,n.cluster),o.addLayer(c,f,l);return r[0].trace._glTrace=o,o}});var l7=ye((ebr,QHe)=>{\"use strict\";var pXt=vf(),EJ=Dr(),gXt=uT(),mXt=EJ.fillText,yXt=fs().BADNUM,_Xt=wx().traceLayerPrefix;function xXt(e,t,r){var n=e.cd,i=n[0].trace,a=e.xa,o=e.ya,s=e.subplot,l=[],u=_Xt+i.uid+\"-circle\",c=i.cluster&&i.cluster.enabled;if(c){var f=s.map.queryRenderedFeatures(null,{layers:[u]});l=f.map(function(M){return M.id})}var h=t>=0?Math.floor((t+180)/360):Math.ceil((t-180)/360),d=h*360,v=t-d;function _(M){var g=M.lonlat;if(g[0]===yXt||c&&l.indexOf(M.i+1)===-1)return 1/0;var P=EJ.modHalf(g[0],360),T=g[1],z=s.project([P,T]),O=z.x-a.c2p([v,T]),V=z.y-o.c2p([P,r]),G=Math.max(3,M.mrc||0);return Math.max(Math.sqrt(O*O+V*V)-G,1-3/G)}if(pXt.getClosest(n,_,e),e.index!==!1){var b=n[e.index],p=b.lonlat,k=[EJ.modHalf(p[0],360)+d,p[1]],E=a.c2p(k),S=o.c2p(k),L=b.mrc||1;e.x0=E-L,e.x1=E+L,e.y0=S-L,e.y1=S+L;var x={};x[i.subplot]={_subplot:s};var C=i._module.formatLabels(b,i,x);return e.lonLabel=C.lonLabel,e.latLabel=C.latLabel,e.color=gXt(i,b),e.extraText=$He(i,b,n[0].t.labels),e.hovertemplate=i.hovertemplate,[e]}}function $He(e,t,r){if(e.hovertemplate)return;var n=t.hi||e.hoverinfo,i=n.split(\"+\"),a=i.indexOf(\"all\")!==-1,o=i.indexOf(\"lon\")!==-1,s=i.indexOf(\"lat\")!==-1,l=t.lonlat,u=[];function c(f){return f+\"\\xB0\"}return a||o&&s?u.push(\"(\"+c(l[1])+\", \"+c(l[0])+\")\"):o?u.push(r.lon+c(l[0])):s&&u.push(r.lat+c(l[1])),(a||i.indexOf(\"text\")!==-1)&&mXt(t,e,u),u.join(\"<br>\")}QHe.exports={hoverPoints:xXt,getExtraText:$He}});var tje=ye((tbr,eje)=>{\"use strict\";eje.exports=function(t,r){return t.lon=r.lon,t.lat=r.lat,t}});var ije=ye((rbr,rje)=>{\"use strict\";var 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F=Math.pow(2,A.z);return[(te=(R[0]/bs+A.x)/F,360*te-180),(W=(R[1]/bs+A.y)/F,360/Math.PI*Math.atan(Math.exp((180-360*W)*Math.PI/180))-90)];var W,te}function Vu(R,A){R[0]=Math.min(R[0],A[0]),R[1]=Math.min(R[1],A[1]),R[2]=Math.max(R[2],A[0]),R[3]=Math.max(R[3],A[1])}function Ol(R,A){return!(R[0]<=A[0]||R[2]>=A[2]||R[1]<=A[1]||R[3]>=A[3])}function xo(R,A,F){let W=R[0]-A[0],te=R[1]-A[1],fe=R[0]-F[0],pe=R[1]-F[1];return W*pe-fe*te==0&&W*fe<=0&&te*pe<=0}function Yl(R,A,F,W){return(te=[W[0]-F[0],W[1]-F[1]])[0]*(fe=[A[0]-R[0],A[1]-R[1]])[1]-te[1]*fe[0]!=0&&!(!qo(R,A,F,W)||!qo(F,W,R,A));var te,fe}function Ns(R,A,F){for(let W of F)for(let te=0;te<W.length-1;++te)if(Yl(R,A,W[te],W[te+1]))return!0;return!1}function Hl(R,A,F=!1){let W=!1;for(let ze of A)for(let Ke=0;Ke<ze.length-1;Ke++){if(xo(R,ze[Ke],ze[Ke+1]))return F;(fe=ze[Ke])[1]>(te=R)[1]!=(pe=ze[Ke+1])[1]>te[1]&&te[0]<(pe[0]-fe[0])*(te[1]-fe[1])/(pe[1]-fe[1])+fe[0]&&(W=!W)}var te,fe,pe;return W}function ac(R,A){for(let F of 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this.first?(this.first=!1,this.lastIntegerZoom=W,this.lastIntegerZoomTime=0,this.lastZoom=A,this.lastFloorZoom=W,!0):(this.lastFloorZoom>W?(this.lastIntegerZoom=W+1,this.lastIntegerZoomTime=F):this.lastFloorZoom<W&&(this.lastIntegerZoom=W,this.lastIntegerZoomTime=F),A!==this.lastZoom&&(this.lastZoom=A,this.lastFloorZoom=W,!0))}}let Dn={\"Latin-1 Supplement\":R=>R>=128&&R<=255,\"Hangul Jamo\":R=>R>=4352&&R<=4607,Khmer:R=>R>=6016&&R<=6143,\"General Punctuation\":R=>R>=8192&&R<=8303,\"Letterlike Symbols\":R=>R>=8448&&R<=8527,\"Number Forms\":R=>R>=8528&&R<=8591,\"Miscellaneous Technical\":R=>R>=8960&&R<=9215,\"Control Pictures\":R=>R>=9216&&R<=9279,\"Optical Character Recognition\":R=>R>=9280&&R<=9311,\"Enclosed Alphanumerics\":R=>R>=9312&&R<=9471,\"Geometric Shapes\":R=>R>=9632&&R<=9727,\"Miscellaneous Symbols\":R=>R>=9728&&R<=9983,\"Miscellaneous Symbols and Arrows\":R=>R>=11008&&R<=11263,\"Ideographic Description Characters\":R=>R>=12272&&R<=12287,\"CJK Symbols and 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ws=Xo([\"Bopo\",\"Hani\",\"Hira\",\"Kana\",\"Kits\",\"Nshu\",\"Tang\",\"Yiii\"]);function Ho(R){return!(R!==746&&R!==747&&(R<4352||!(Dn[\"CJK Compatibility Forms\"](R)&&!(R>=65097&&R<=65103)||Dn[\"CJK Compatibility\"](R)||Dn[\"CJK Strokes\"](R)||!(!Dn[\"CJK Symbols and Punctuation\"](R)||R>=12296&&R<=12305||R>=12308&&R<=12319||R===12336)||Dn[\"Enclosed CJK Letters and Months\"](R)||Dn[\"Ideographic Description Characters\"](R)||Dn.Kanbun(R)||Dn.Katakana(R)&&R!==12540||!(!Dn[\"Halfwidth and Fullwidth Forms\"](R)||R===65288||R===65289||R===65293||R>=65306&&R<=65310||R===65339||R===65341||R===65343||R>=65371&&R<=65503||R===65507||R>=65512&&R<=65519)||!(!Dn[\"Small Form Variants\"](R)||R>=65112&&R<=65118||R>=65123&&R<=65126)||Dn[\"Vertical Forms\"](R)||Dn[\"Yijing Hexagram Symbols\"](R)||new RegExp(\"\\\\p{sc=Cans}\",\"u\").test(String.fromCodePoint(R))||new RegExp(\"\\\\p{sc=Hang}\",\"u\").test(String.fromCodePoint(R))||ws.test(String.fromCodePoint(R)))))}function ml(R){return!(Ho(R)||function(A){return!!(Dn[\"Latin-1 Supplement\"](A)&&(A===167||A===169||A===174||A===177||A===188||A===189||A===190||A===215||A===247)||Dn[\"General Punctuation\"](A)&&(A===8214||A===8224||A===8225||A===8240||A===8241||A===8251||A===8252||A===8258||A===8263||A===8264||A===8265||A===8273)||Dn[\"Letterlike Symbols\"](A)||Dn[\"Number Forms\"](A)||Dn[\"Miscellaneous Technical\"](A)&&(A>=8960&&A<=8967||A>=8972&&A<=8991||A>=8996&&A<=9e3||A===9003||A>=9085&&A<=9114||A>=9150&&A<=9165||A===9167||A>=9169&&A<=9179||A>=9186&&A<=9215)||Dn[\"Control Pictures\"](A)&&A!==9251||Dn[\"Optical Character Recognition\"](A)||Dn[\"Enclosed Alphanumerics\"](A)||Dn[\"Geometric Shapes\"](A)||Dn[\"Miscellaneous Symbols\"](A)&&!(A>=9754&&A<=9759)||Dn[\"Miscellaneous Symbols and Arrows\"](A)&&(A>=11026&&A<=11055||A>=11088&&A<=11097||A>=11192&&A<=11243)||Dn[\"CJK Symbols and Punctuation\"](A)||Dn.Katakana(A)||Dn[\"Private Use Area\"](A)||Dn[\"CJK Compatibility Forms\"](A)||Dn[\"Small Form 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class{constructor(){this.applyArabicShaping=null,this.processBidirectionalText=null,this.processStyledBidirectionalText=null,this.pluginStatus=\"unavailable\",this.pluginURL=null}setState(R){this.pluginStatus=R.pluginStatus,this.pluginURL=R.pluginURL}getState(){return{pluginStatus:this.pluginStatus,pluginURL:this.pluginURL}}setMethods(R){this.applyArabicShaping=R.applyArabicShaping,this.processBidirectionalText=R.processBidirectionalText,this.processStyledBidirectionalText=R.processStyledBidirectionalText}isParsed(){return this.applyArabicShaping!=null&&this.processBidirectionalText!=null&&this.processStyledBidirectionalText!=null}getPluginURL(){return this.pluginURL}getRTLTextPluginStatus(){return this.pluginStatus}};class rs{constructor(A,F){this.zoom=A,F?(this.now=F.now,this.fadeDuration=F.fadeDuration,this.zoomHistory=F.zoomHistory,this.transition=F.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Yn,this.transition={})}isSupportedScript(A){return function(F,W){for(let te of F)if(!va(te.charCodeAt(0),W))return!1;return!0}(A,ys.getRTLTextPluginStatus()===\"loaded\")}crossFadingFactor(){return this.fadeDuration===0?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)}getCrossfadeParameters(){let A=this.zoom,F=A-Math.floor(A),W=this.crossFadingFactor();return A>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:F+(1-F)*W}:{fromScale:.5,toScale:1,t:1-(1-W)*F}}}class $l{constructor(A,F){this.property=A,this.value=F,this.expression=function(W,te){if(jf(W))return new nl(W,te);if(Dc(W)){let fe=_u(W,te);if(fe.result===\"error\")throw new Error(fe.value.map(pe=>`${pe.key}: ${pe.message}`).join(\", \"));return fe.value}{let fe=W;return te.type===\"color\"&&typeof W==\"string\"?fe=nr.parse(W):te.type!==\"padding\"||typeof W!=\"number\"&&!Array.isArray(W)?te.type===\"variableAnchorOffsetCollection\"&&Array.isArray(W)&&(fe=$i.parse(W)):fe=Qr.parse(W),{kind:\"constant\",evaluate:()=>fe}}}(F===void 0?A.specification.default:F,A.specification)}isDataDriven(){return this.expression.kind===\"source\"||this.expression.kind===\"composite\"}possiblyEvaluate(A,F,W){return this.property.possiblyEvaluate(this,A,F,W)}}class Cu{constructor(A){this.property=A,this.value=new $l(A,void 0)}transitioned(A,F){return new Nc(this.property,this.value,F,L({},A.transition,this.transition),A.now)}untransitioned(){return new Nc(this.property,this.value,null,{},0)}}class Yu{constructor(A){this._properties=A,this._values=Object.create(A.defaultTransitionablePropertyValues)}getValue(A){return g(this._values[A].value.value)}setValue(A,F){Object.prototype.hasOwnProperty.call(this._values,A)||(this._values[A]=new Cu(this._values[A].property)),this._values[A].value=new $l(this._values[A].property,F===null?void 0:g(F))}getTransition(A){return g(this._values[A].transition)}setTransition(A,F){Object.prototype.hasOwnProperty.call(this._values,A)||(this._values[A]=new Cu(this._values[A].property)),this._values[A].transition=g(F)||void 0}serialize(){let A={};for(let F of Object.keys(this._values)){let W=this.getValue(F);W!==void 0&&(A[F]=W);let te=this.getTransition(F);te!==void 0&&(A[`${F}-transition`]=te)}return A}transitioned(A,F){let W=new pu(this._properties);for(let te of Object.keys(this._values))W._values[te]=this._values[te].transitioned(A,F._values[te]);return W}untransitioned(){let A=new pu(this._properties);for(let F of Object.keys(this._values))A._values[F]=this._values[F].untransitioned();return A}}class Nc{constructor(A,F,W,te,fe){this.property=A,this.value=F,this.begin=fe+te.delay||0,this.end=this.begin+te.duration||0,A.specification.transition&&(te.delay||te.duration)&&(this.prior=W)}possiblyEvaluate(A,F,W){let te=A.now||0,fe=this.value.possiblyEvaluate(A,F,W),pe=this.prior;if(pe){if(te>this.end)return this.prior=null,fe;if(this.value.isDataDriven())return this.prior=null,fe;if(te<this.begin)return pe.possiblyEvaluate(A,F,W);{let ze=(te-this.begin)/(this.end-this.begin);return this.property.interpolate(pe.possiblyEvaluate(A,F,W),fe,function(Ke){if(Ke<=0)return 0;if(Ke>=1)return 1;let ct=Ke*Ke,Lt=ct*Ke;return 4*(Ke<.5?Lt:3*(Ke-ct)+Lt-.75)}(ze))}}return fe}}class pu{constructor(A){this._properties=A,this._values=Object.create(A.defaultTransitioningPropertyValues)}possiblyEvaluate(A,F,W){let te=new Ac(this._properties);for(let fe of Object.keys(this._values))te._values[fe]=this._values[fe].possiblyEvaluate(A,F,W);return te}hasTransition(){for(let A of Object.keys(this._values))if(this._values[A].prior)return!0;return!1}}class Uc{constructor(A){this._properties=A,this._values=Object.create(A.defaultPropertyValues)}hasValue(A){return this._values[A].value!==void 0}getValue(A){return g(this._values[A].value)}setValue(A,F){this._values[A]=new $l(this._values[A].property,F===null?void 0:g(F))}serialize(){let A={};for(let F of Object.keys(this._values)){let W=this.getValue(F);W!==void 0&&(A[F]=W)}return A}possiblyEvaluate(A,F,W){let te=new Ac(this._properties);for(let fe of Object.keys(this._values))te._values[fe]=this._values[fe].possiblyEvaluate(A,F,W);return te}}class xu{constructor(A,F,W){this.property=A,this.value=F,this.parameters=W}isConstant(){return this.value.kind===\"constant\"}constantOr(A){return this.value.kind===\"constant\"?this.value.value:A}evaluate(A,F,W,te){return this.property.evaluate(this.value,this.parameters,A,F,W,te)}}class Ac{constructor(A){this._properties=A,this._values=Object.create(A.defaultPossiblyEvaluatedValues)}get(A){return this._values[A]}}class Ua{constructor(A){this.specification=A}possiblyEvaluate(A,F){if(A.isDataDriven())throw new Error(\"Value should not be data driven\");return A.expression.evaluate(F)}interpolate(A,F,W){let te=Lo[this.specification.type];return te?te(A,F,W):A}}class oo{constructor(A,F){this.specification=A,this.overrides=F}possiblyEvaluate(A,F,W,te){return new xu(this,A.expression.kind===\"constant\"||A.expression.kind===\"camera\"?{kind:\"constant\",value:A.expression.evaluate(F,null,{},W,te)}:A.expression,F)}interpolate(A,F,W){if(A.value.kind!==\"constant\"||F.value.kind!==\"constant\")return A;if(A.value.value===void 0||F.value.value===void 0)return new xu(this,{kind:\"constant\",value:void 0},A.parameters);let te=Lo[this.specification.type];if(te){let fe=te(A.value.value,F.value.value,W);return new xu(this,{kind:\"constant\",value:fe},A.parameters)}return A}evaluate(A,F,W,te,fe,pe){return A.kind===\"constant\"?A.value:A.evaluate(F,W,te,fe,pe)}}class Vc extends oo{possiblyEvaluate(A,F,W,te){if(A.value===void 0)return new xu(this,{kind:\"constant\",value:void 0},F);if(A.expression.kind===\"constant\"){let fe=A.expression.evaluate(F,null,{},W,te),pe=A.property.specification.type===\"resolvedImage\"&&typeof fe!=\"string\"?fe.name:fe,ze=this._calculate(pe,pe,pe,F);return new xu(this,{kind:\"constant\",value:ze},F)}if(A.expression.kind===\"camera\"){let fe=this._calculate(A.expression.evaluate({zoom:F.zoom-1}),A.expression.evaluate({zoom:F.zoom}),A.expression.evaluate({zoom:F.zoom+1}),F);return new xu(this,{kind:\"constant\",value:fe},F)}return new xu(this,A.expression,F)}evaluate(A,F,W,te,fe,pe){if(A.kind===\"source\"){let ze=A.evaluate(F,W,te,fe,pe);return this._calculate(ze,ze,ze,F)}return A.kind===\"composite\"?this._calculate(A.evaluate({zoom:Math.floor(F.zoom)-1},W,te),A.evaluate({zoom:Math.floor(F.zoom)},W,te),A.evaluate({zoom:Math.floor(F.zoom)+1},W,te),F):A.value}_calculate(A,F,W,te){return te.zoom>te.zoomHistory.lastIntegerZoom?{from:A,to:F}:{from:W,to:F}}interpolate(A){return A}}class hc{constructor(A){this.specification=A}possiblyEvaluate(A,F,W,te){if(A.value!==void 0){if(A.expression.kind===\"constant\"){let fe=A.expression.evaluate(F,null,{},W,te);return this._calculate(fe,fe,fe,F)}return this._calculate(A.expression.evaluate(new rs(Math.floor(F.zoom-1),F)),A.expression.evaluate(new rs(Math.floor(F.zoom),F)),A.expression.evaluate(new rs(Math.floor(F.zoom+1),F)),F)}}_calculate(A,F,W,te){return te.zoom>te.zoomHistory.lastIntegerZoom?{from:A,to:F}:{from:W,to:F}}interpolate(A){return A}}class Ku{constructor(A){this.specification=A}possiblyEvaluate(A,F,W,te){return!!A.expression.evaluate(F,null,{},W,te)}interpolate(){return!1}}class ue{constructor(A){this.properties=A,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[];for(let F in A){let W=A[F];W.specification.overridable&&this.overridableProperties.push(F);let te=this.defaultPropertyValues[F]=new $l(W,void 0),fe=this.defaultTransitionablePropertyValues[F]=new Cu(W);this.defaultTransitioningPropertyValues[F]=fe.untransitioned(),this.defaultPossiblyEvaluatedValues[F]=te.possiblyEvaluate({})}}}Fi(\"DataDrivenProperty\",oo),Fi(\"DataConstantProperty\",Ua),Fi(\"CrossFadedDataDrivenProperty\",Vc),Fi(\"CrossFadedProperty\",hc),Fi(\"ColorRampProperty\",Ku);let w=\"-transition\";class B extends Re{constructor(A,F){if(super(),this.id=A.id,this.type=A.type,this._featureFilter={filter:()=>!0,needGeometry:!1},A.type!==\"custom\"&&(this.metadata=A.metadata,this.minzoom=A.minzoom,this.maxzoom=A.maxzoom,A.type!==\"background\"&&(this.source=A.source,this.sourceLayer=A[\"source-layer\"],this.filter=A.filter),F.layout&&(this._unevaluatedLayout=new Uc(F.layout)),F.paint)){this._transitionablePaint=new Yu(F.paint);for(let W in A.paint)this.setPaintProperty(W,A.paint[W],{validate:!1});for(let W in A.layout)this.setLayoutProperty(W,A.layout[W],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new Ac(F.paint)}}getCrossfadeParameters(){return this._crossfadeParameters}getLayoutProperty(A){return A===\"visibility\"?this.visibility:this._unevaluatedLayout.getValue(A)}setLayoutProperty(A,F,W={}){F!=null&&this._validate(Nn,`layers.${this.id}.layout.${A}`,A,F,W)||(A!==\"visibility\"?this._unevaluatedLayout.setValue(A,F):this.visibility=F)}getPaintProperty(A){return A.endsWith(w)?this._transitionablePaint.getTransition(A.slice(0,-11)):this._transitionablePaint.getValue(A)}setPaintProperty(A,F,W={}){if(F!=null&&this._validate(wn,`layers.${this.id}.paint.${A}`,A,F,W))return!1;if(A.endsWith(w))return this._transitionablePaint.setTransition(A.slice(0,-11),F||void 0),!1;{let te=this._transitionablePaint._values[A],fe=te.property.specification[\"property-type\"]===\"cross-faded-data-driven\",pe=te.value.isDataDriven(),ze=te.value;this._transitionablePaint.setValue(A,F),this._handleSpecialPaintPropertyUpdate(A);let Ke=this._transitionablePaint._values[A].value;return Ke.isDataDriven()||pe||fe||this._handleOverridablePaintPropertyUpdate(A,ze,Ke)}}_handleSpecialPaintPropertyUpdate(A){}_handleOverridablePaintPropertyUpdate(A,F,W){return!1}isHidden(A){return!!(this.minzoom&&A<this.minzoom)||!!(this.maxzoom&&A>=this.maxzoom)||this.visibility===\"none\"}updateTransitions(A){this._transitioningPaint=this._transitionablePaint.transitioned(A,this._transitioningPaint)}hasTransition(){return this._transitioningPaint.hasTransition()}recalculate(A,F){A.getCrossfadeParameters&&(this._crossfadeParameters=A.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(A,void 0,F)),this.paint=this._transitioningPaint.possiblyEvaluate(A,void 0,F)}serialize(){let A={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(A.layout=A.layout||{},A.layout.visibility=this.visibility),M(A,(F,W)=>!(F===void 0||W===\"layout\"&&!Object.keys(F).length||W===\"paint\"&&!Object.keys(F).length))}_validate(A,F,W,te,fe={}){return(!fe||fe.validate!==!1)&&Yi(this,A.call(ki,{key:F,layerType:this.type,objectKey:W,value:te,styleSpec:ce,style:{glyphs:!0,sprite:!0}}))}is3D(){return!1}isTileClipped(){return!1}hasOffscreenPass(){return!1}resize(){}isStateDependent(){for(let A in this.paint._values){let F=this.paint.get(A);if(F instanceof xu&&Nl(F.property.specification)&&(F.value.kind===\"source\"||F.value.kind===\"composite\")&&F.value.isStateDependent)return!0}return!1}}let Q={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array};class ee{constructor(A,F){this._structArray=A,this._pos1=F*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8}}class le{constructor(){this.isTransferred=!1,this.capacity=-1,this.resize(0)}static serialize(A,F){return A._trim(),F&&(A.isTransferred=!0,F.push(A.arrayBuffer)),{length:A.length,arrayBuffer:A.arrayBuffer}}static deserialize(A){let F=Object.create(this.prototype);return F.arrayBuffer=A.arrayBuffer,F.length=A.length,F.capacity=A.arrayBuffer.byteLength/F.bytesPerElement,F._refreshViews(),F}_trim(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())}clear(){this.length=0}resize(A){this.reserve(A),this.length=A}reserve(A){if(A>this.capacity){this.capacity=Math.max(A,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);let F=this.uint8;this._refreshViews(),F&&this.uint8.set(F)}}_refreshViews(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")}}function qe(R,A=1){let F=0,W=0;return{members:R.map(te=>{let fe=Q[te.type].BYTES_PER_ELEMENT,pe=F=Xe(F,Math.max(A,fe)),ze=te.components||1;return W=Math.max(W,fe),F+=fe*ze,{name:te.name,type:te.type,components:ze,offset:pe}}),size:Xe(F,Math.max(W,A)),alignment:A}}function Xe(R,A){return Math.ceil(R/A)*A}class ot extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let te=2*A;return this.int16[te+0]=F,this.int16[te+1]=W,A}}ot.prototype.bytesPerElement=4,Fi(\"StructArrayLayout2i4\",ot);class Tt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W){let te=this.length;return this.resize(te+1),this.emplace(te,A,F,W)}emplace(A,F,W,te){let fe=3*A;return this.int16[fe+0]=F,this.int16[fe+1]=W,this.int16[fe+2]=te,A}}Tt.prototype.bytesPerElement=6,Fi(\"StructArrayLayout3i6\",Tt);class Yt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te){let fe=this.length;return this.resize(fe+1),this.emplace(fe,A,F,W,te)}emplace(A,F,W,te,fe){let pe=4*A;return this.int16[pe+0]=F,this.int16[pe+1]=W,this.int16[pe+2]=te,this.int16[pe+3]=fe,A}}Yt.prototype.bytesPerElement=8,Fi(\"StructArrayLayout4i8\",Yt);class Kt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,te,fe,pe)}emplace(A,F,W,te,fe,pe,ze){let Ke=6*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.int16[Ke+2]=te,this.int16[Ke+3]=fe,this.int16[Ke+4]=pe,this.int16[Ke+5]=ze,A}}Kt.prototype.bytesPerElement=12,Fi(\"StructArrayLayout2i4i12\",Kt);class xr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,te,fe,pe)}emplace(A,F,W,te,fe,pe,ze){let Ke=4*A,ct=8*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.uint8[ct+4]=te,this.uint8[ct+5]=fe,this.uint8[ct+6]=pe,this.uint8[ct+7]=ze,A}}xr.prototype.bytesPerElement=8,Fi(\"StructArrayLayout2i4ub8\",xr);class Ir extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let te=2*A;return this.float32[te+0]=F,this.float32[te+1]=W,A}}Ir.prototype.bytesPerElement=8,Fi(\"StructArrayLayout2f8\",Ir);class ve extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe,ze,Ke,ct,Lt){let $t=this.length;return this.resize($t+1),this.emplace($t,A,F,W,te,fe,pe,ze,Ke,ct,Lt)}emplace(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t){let fr=10*A;return this.uint16[fr+0]=F,this.uint16[fr+1]=W,this.uint16[fr+2]=te,this.uint16[fr+3]=fe,this.uint16[fr+4]=pe,this.uint16[fr+5]=ze,this.uint16[fr+6]=Ke,this.uint16[fr+7]=ct,this.uint16[fr+8]=Lt,this.uint16[fr+9]=$t,A}}ve.prototype.bytesPerElement=20,Fi(\"StructArrayLayout10ui20\",ve);class be extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr){let mr=this.length;return this.resize(mr+1),this.emplace(mr,A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr)}emplace(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr){let Pr=12*A;return this.int16[Pr+0]=F,this.int16[Pr+1]=W,this.int16[Pr+2]=te,this.int16[Pr+3]=fe,this.uint16[Pr+4]=pe,this.uint16[Pr+5]=ze,this.uint16[Pr+6]=Ke,this.uint16[Pr+7]=ct,this.int16[Pr+8]=Lt,this.int16[Pr+9]=$t,this.int16[Pr+10]=fr,this.int16[Pr+11]=mr,A}}be.prototype.bytesPerElement=24,Fi(\"StructArrayLayout4i4ui4i24\",be);class De extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W){let te=this.length;return this.resize(te+1),this.emplace(te,A,F,W)}emplace(A,F,W,te){let fe=3*A;return this.float32[fe+0]=F,this.float32[fe+1]=W,this.float32[fe+2]=te,A}}De.prototype.bytesPerElement=12,Fi(\"StructArrayLayout3f12\",De);class Be extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.uint32[1*A+0]=F,A}}Be.prototype.bytesPerElement=4,Fi(\"StructArrayLayout1ul4\",Be);class et extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe,ze,Ke,ct){let Lt=this.length;return this.resize(Lt+1),this.emplace(Lt,A,F,W,te,fe,pe,ze,Ke,ct)}emplace(A,F,W,te,fe,pe,ze,Ke,ct,Lt){let $t=10*A,fr=5*A;return this.int16[$t+0]=F,this.int16[$t+1]=W,this.int16[$t+2]=te,this.int16[$t+3]=fe,this.int16[$t+4]=pe,this.int16[$t+5]=ze,this.uint32[fr+3]=Ke,this.uint16[$t+8]=ct,this.uint16[$t+9]=Lt,A}}et.prototype.bytesPerElement=20,Fi(\"StructArrayLayout6i1ul2ui20\",et);class We extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,te,fe,pe)}emplace(A,F,W,te,fe,pe,ze){let Ke=6*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.int16[Ke+2]=te,this.int16[Ke+3]=fe,this.int16[Ke+4]=pe,this.int16[Ke+5]=ze,A}}We.prototype.bytesPerElement=12,Fi(\"StructArrayLayout2i2i2i12\",We);class it extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe){let pe=this.length;return this.resize(pe+1),this.emplace(pe,A,F,W,te,fe)}emplace(A,F,W,te,fe,pe){let ze=4*A,Ke=8*A;return this.float32[ze+0]=F,this.float32[ze+1]=W,this.float32[ze+2]=te,this.int16[Ke+6]=fe,this.int16[Ke+7]=pe,A}}it.prototype.bytesPerElement=16,Fi(\"StructArrayLayout2f1f2i16\",it);class Ft extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,te,fe,pe)}emplace(A,F,W,te,fe,pe,ze){let Ke=16*A,ct=4*A,Lt=8*A;return this.uint8[Ke+0]=F,this.uint8[Ke+1]=W,this.float32[ct+1]=te,this.float32[ct+2]=fe,this.int16[Lt+6]=pe,this.int16[Lt+7]=ze,A}}Ft.prototype.bytesPerElement=16,Fi(\"StructArrayLayout2ub2f2i16\",Ft);class Ht extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W){let te=this.length;return this.resize(te+1),this.emplace(te,A,F,W)}emplace(A,F,W,te){let fe=3*A;return this.uint16[fe+0]=F,this.uint16[fe+1]=W,this.uint16[fe+2]=te,A}}Ht.prototype.bytesPerElement=6,Fi(\"StructArrayLayout3ui6\",Ht);class tr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi){let vn=this.length;return this.resize(vn+1),this.emplace(vn,A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi)}emplace(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn){let zi=24*A,un=12*A,Tn=48*A;return this.int16[zi+0]=F,this.int16[zi+1]=W,this.uint16[zi+2]=te,this.uint16[zi+3]=fe,this.uint32[un+2]=pe,this.uint32[un+3]=ze,this.uint32[un+4]=Ke,this.uint16[zi+10]=ct,this.uint16[zi+11]=Lt,this.uint16[zi+12]=$t,this.float32[un+7]=fr,this.float32[un+8]=mr,this.uint8[Tn+36]=Pr,this.uint8[Tn+37]=zr,this.uint8[Tn+38]=ui,this.uint32[un+10]=yi,this.int16[zi+22]=vn,A}}tr.prototype.bytesPerElement=48,Fi(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",tr);class dr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo){let lo=this.length;return this.resize(lo+1),this.emplace(lo,A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo)}emplace(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo,lo){let Xn=32*A,Ro=16*A;return this.int16[Xn+0]=F,this.int16[Xn+1]=W,this.int16[Xn+2]=te,this.int16[Xn+3]=fe,this.int16[Xn+4]=pe,this.int16[Xn+5]=ze,this.int16[Xn+6]=Ke,this.int16[Xn+7]=ct,this.uint16[Xn+8]=Lt,this.uint16[Xn+9]=$t,this.uint16[Xn+10]=fr,this.uint16[Xn+11]=mr,this.uint16[Xn+12]=Pr,this.uint16[Xn+13]=zr,this.uint16[Xn+14]=ui,this.uint16[Xn+15]=yi,this.uint16[Xn+16]=vn,this.uint16[Xn+17]=zi,this.uint16[Xn+18]=un,this.uint16[Xn+19]=Tn,this.uint16[Xn+20]=pa,this.uint16[Xn+21]=ro,this.uint16[Xn+22]=Vo,this.uint32[Ro+12]=Xa,this.float32[Ro+13]=sa,this.float32[Ro+14]=Mo,this.uint16[Xn+30]=fo,this.uint16[Xn+31]=lo,A}}dr.prototype.bytesPerElement=64,Fi(\"StructArrayLayout8i15ui1ul2f2ui64\",dr);class Sr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.float32[1*A+0]=F,A}}Sr.prototype.bytesPerElement=4,Fi(\"StructArrayLayout1f4\",Sr);class Or extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W){let te=this.length;return this.resize(te+1),this.emplace(te,A,F,W)}emplace(A,F,W,te){let fe=3*A;return this.uint16[6*A+0]=F,this.float32[fe+1]=W,this.float32[fe+2]=te,A}}Or.prototype.bytesPerElement=12,Fi(\"StructArrayLayout1ui2f12\",Or);class Wr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W){let te=this.length;return this.resize(te+1),this.emplace(te,A,F,W)}emplace(A,F,W,te){let fe=4*A;return this.uint32[2*A+0]=F,this.uint16[fe+2]=W,this.uint16[fe+3]=te,A}}Wr.prototype.bytesPerElement=8,Fi(\"StructArrayLayout1ul2ui8\",Wr);class ni extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let te=2*A;return this.uint16[te+0]=F,this.uint16[te+1]=W,A}}ni.prototype.bytesPerElement=4,Fi(\"StructArrayLayout2ui4\",ni);class Pi extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.uint16[1*A+0]=F,A}}Pi.prototype.bytesPerElement=2,Fi(\"StructArrayLayout1ui2\",Pi);class cn extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,te){let fe=this.length;return this.resize(fe+1),this.emplace(fe,A,F,W,te)}emplace(A,F,W,te,fe){let pe=4*A;return this.float32[pe+0]=F,this.float32[pe+1]=W,this.float32[pe+2]=te,this.float32[pe+3]=fe,A}}cn.prototype.bytesPerElement=16,Fi(\"StructArrayLayout4f16\",cn);class ln extends ee{get anchorPointX(){return this._structArray.int16[this._pos2+0]}get anchorPointY(){return this._structArray.int16[this._pos2+1]}get x1(){return this._structArray.int16[this._pos2+2]}get y1(){return this._structArray.int16[this._pos2+3]}get x2(){return this._structArray.int16[this._pos2+4]}get y2(){return this._structArray.int16[this._pos2+5]}get featureIndex(){return this._structArray.uint32[this._pos4+3]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+8]}get bucketIndex(){return this._structArray.uint16[this._pos2+9]}get anchorPoint(){return new u(this.anchorPointX,this.anchorPointY)}}ln.prototype.size=20;class Cn extends et{get(A){return new ln(this,A)}}Fi(\"CollisionBoxArray\",Cn);class Kn extends ee{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get glyphStartIndex(){return this._structArray.uint16[this._pos2+2]}get numGlyphs(){return this._structArray.uint16[this._pos2+3]}get vertexStartIndex(){return this._structArray.uint32[this._pos4+2]}get lineStartIndex(){return this._structArray.uint32[this._pos4+3]}get lineLength(){return this._structArray.uint32[this._pos4+4]}get segment(){return this._structArray.uint16[this._pos2+10]}get lowerSize(){return this._structArray.uint16[this._pos2+11]}get upperSize(){return this._structArray.uint16[this._pos2+12]}get lineOffsetX(){return this._structArray.float32[this._pos4+7]}get lineOffsetY(){return this._structArray.float32[this._pos4+8]}get writingMode(){return this._structArray.uint8[this._pos1+36]}get placedOrientation(){return this._structArray.uint8[this._pos1+37]}set placedOrientation(A){this._structArray.uint8[this._pos1+37]=A}get hidden(){return this._structArray.uint8[this._pos1+38]}set hidden(A){this._structArray.uint8[this._pos1+38]=A}get crossTileID(){return this._structArray.uint32[this._pos4+10]}set crossTileID(A){this._structArray.uint32[this._pos4+10]=A}get associatedIconIndex(){return this._structArray.int16[this._pos2+22]}}Kn.prototype.size=48;class Ta extends tr{get(A){return new Kn(this,A)}}Fi(\"PlacedSymbolArray\",Ta);class fa extends ee{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get rightJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+2]}get centerJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+3]}get leftJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+4]}get verticalPlacedTextSymbolIndex(){return this._structArray.int16[this._pos2+5]}get placedIconSymbolIndex(){return this._structArray.int16[this._pos2+6]}get verticalPlacedIconSymbolIndex(){return this._structArray.int16[this._pos2+7]}get key(){return this._structArray.uint16[this._pos2+8]}get textBoxStartIndex(){return this._structArray.uint16[this._pos2+9]}get textBoxEndIndex(){return this._structArray.uint16[this._pos2+10]}get verticalTextBoxStartIndex(){return this._structArray.uint16[this._pos2+11]}get verticalTextBoxEndIndex(){return this._structArray.uint16[this._pos2+12]}get iconBoxStartIndex(){return this._structArray.uint16[this._pos2+13]}get iconBoxEndIndex(){return this._structArray.uint16[this._pos2+14]}get verticalIconBoxStartIndex(){return this._structArray.uint16[this._pos2+15]}get verticalIconBoxEndIndex(){return this._structArray.uint16[this._pos2+16]}get featureIndex(){return this._structArray.uint16[this._pos2+17]}get numHorizontalGlyphVertices(){return this._structArray.uint16[this._pos2+18]}get numVerticalGlyphVertices(){return this._structArray.uint16[this._pos2+19]}get numIconVertices(){return this._structArray.uint16[this._pos2+20]}get numVerticalIconVertices(){return this._structArray.uint16[this._pos2+21]}get useRuntimeCollisionCircles(){return this._structArray.uint16[this._pos2+22]}get crossTileID(){return this._structArray.uint32[this._pos4+12]}set crossTileID(A){this._structArray.uint32[this._pos4+12]=A}get textBoxScale(){return this._structArray.float32[this._pos4+13]}get collisionCircleDiameter(){return this._structArray.float32[this._pos4+14]}get textAnchorOffsetStartIndex(){return this._structArray.uint16[this._pos2+30]}get textAnchorOffsetEndIndex(){return this._structArray.uint16[this._pos2+31]}}fa.prototype.size=64;class $a extends dr{get(A){return new fa(this,A)}}Fi(\"SymbolInstanceArray\",$a);class Co extends Sr{getoffsetX(A){return this.float32[1*A+0]}}Fi(\"GlyphOffsetArray\",Co);class Qa extends Tt{getx(A){return this.int16[3*A+0]}gety(A){return this.int16[3*A+1]}gettileUnitDistanceFromAnchor(A){return this.int16[3*A+2]}}Fi(\"SymbolLineVertexArray\",Qa);class mo extends ee{get textAnchor(){return this._structArray.uint16[this._pos2+0]}get textOffset0(){return this._structArray.float32[this._pos4+1]}get textOffset1(){return this._structArray.float32[this._pos4+2]}}mo.prototype.size=12;class Bo extends Or{get(A){return new mo(this,A)}}Fi(\"TextAnchorOffsetArray\",Bo);class Ps extends ee{get featureIndex(){return this._structArray.uint32[this._pos4+0]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+2]}get bucketIndex(){return this._structArray.uint16[this._pos2+3]}}Ps.prototype.size=8;class Ts extends Wr{get(A){return new Ps(this,A)}}Fi(\"FeatureIndexArray\",Ts);class wo extends ot{}class To extends ot{}class hl extends ot{}class Ul extends Kt{}class Lu extends xr{}class au extends Ir{}class Js extends ve{}class Ql extends be{}class dc extends De{}class Tl extends Be{}class Al extends We{}class X extends Ft{}class se extends Ht{}class Te extends ni{}let Ne=qe([{name:\"a_pos\",components:2,type:\"Int16\"}],4),{members:He}=Ne;class Ye{constructor(A=[]){this.segments=A}prepareSegment(A,F,W,te){let fe=this.segments[this.segments.length-1];return A>Ye.MAX_VERTEX_ARRAY_LENGTH&&T(`Max vertices per segment is ${Ye.MAX_VERTEX_ARRAY_LENGTH}: bucket requested ${A}`),(!fe||fe.vertexLength+A>Ye.MAX_VERTEX_ARRAY_LENGTH||fe.sortKey!==te)&&(fe={vertexOffset:F.length,primitiveOffset:W.length,vertexLength:0,primitiveLength:0},te!==void 0&&(fe.sortKey=te),this.segments.push(fe)),fe}get(){return this.segments}destroy(){for(let A of this.segments)for(let F in A.vaos)A.vaos[F].destroy()}static simpleSegment(A,F,W,te){return new Ye([{vertexOffset:A,primitiveOffset:F,vertexLength:W,primitiveLength:te,vaos:{},sortKey:0}])}}function kt(R,A){return 256*(R=E(Math.floor(R),0,255))+E(Math.floor(A),0,255)}Ye.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,Fi(\"SegmentVector\",Ye);let nt=qe([{name:\"a_pattern_from\",components:4,type:\"Uint16\"},{name:\"a_pattern_to\",components:4,type:\"Uint16\"},{name:\"a_pixel_ratio_from\",components:1,type:\"Uint16\"},{name:\"a_pixel_ratio_to\",components:1,type:\"Uint16\"}]);var jt={exports:{}},gr={exports:{}};gr.exports=function(R,A){var F,W,te,fe,pe,ze,Ke,ct;for(W=R.length-(F=3&R.length),te=A,pe=3432918353,ze=461845907,ct=0;ct<W;)Ke=255&R.charCodeAt(ct)|(255&R.charCodeAt(++ct))<<8|(255&R.charCodeAt(++ct))<<16|(255&R.charCodeAt(++ct))<<24,++ct,te=27492+(65535&(fe=5*(65535&(te=(te^=Ke=(65535&(Ke=(Ke=(65535&Ke)*pe+(((Ke>>>16)*pe&65535)<<16)&4294967295)<<15|Ke>>>17))*ze+(((Ke>>>16)*ze&65535)<<16)&4294967295)<<13|te>>>19))+((5*(te>>>16)&65535)<<16)&4294967295))+((58964+(fe>>>16)&65535)<<16);switch(Ke=0,F){case 3:Ke^=(255&R.charCodeAt(ct+2))<<16;case 2:Ke^=(255&R.charCodeAt(ct+1))<<8;case 1:te^=Ke=(65535&(Ke=(Ke=(65535&(Ke^=255&R.charCodeAt(ct)))*pe+(((Ke>>>16)*pe&65535)<<16)&4294967295)<<15|Ke>>>17))*ze+(((Ke>>>16)*ze&65535)<<16)&4294967295}return te^=R.length,te=2246822507*(65535&(te^=te>>>16))+((2246822507*(te>>>16)&65535)<<16)&4294967295,te=3266489909*(65535&(te^=te>>>13))+((3266489909*(te>>>16)&65535)<<16)&4294967295,(te^=te>>>16)>>>0};var yr=gr.exports,Hr={exports:{}};Hr.exports=function(R,A){for(var F,W=R.length,te=A^W,fe=0;W>=4;)F=1540483477*(65535&(F=255&R.charCodeAt(fe)|(255&R.charCodeAt(++fe))<<8|(255&R.charCodeAt(++fe))<<16|(255&R.charCodeAt(++fe))<<24))+((1540483477*(F>>>16)&65535)<<16),te=1540483477*(65535&te)+((1540483477*(te>>>16)&65535)<<16)^(F=1540483477*(65535&(F^=F>>>24))+((1540483477*(F>>>16)&65535)<<16)),W-=4,++fe;switch(W){case 3:te^=(255&R.charCodeAt(fe+2))<<16;case 2:te^=(255&R.charCodeAt(fe+1))<<8;case 1:te=1540483477*(65535&(te^=255&R.charCodeAt(fe)))+((1540483477*(te>>>16)&65535)<<16)}return te=1540483477*(65535&(te^=te>>>13))+((1540483477*(te>>>16)&65535)<<16),(te^=te>>>15)>>>0};var qr=yr,_i=Hr.exports;jt.exports=qr,jt.exports.murmur3=qr,jt.exports.murmur2=_i;var bi=o(jt.exports);class Zr{constructor(){this.ids=[],this.positions=[],this.indexed=!1}add(A,F,W,te){this.ids.push(ai(A)),this.positions.push(F,W,te)}getPositions(A){if(!this.indexed)throw new Error(\"Trying to get index, but feature positions are not indexed\");let F=ai(A),W=0,te=this.ids.length-1;for(;W<te;){let pe=W+te>>1;this.ids[pe]>=F?te=pe:W=pe+1}let fe=[];for(;this.ids[W]===F;)fe.push({index:this.positions[3*W],start:this.positions[3*W+1],end:this.positions[3*W+2]}),W++;return fe}static serialize(A,F){let W=new Float64Array(A.ids),te=new Uint32Array(A.positions);return gi(W,te,0,W.length-1),F&&F.push(W.buffer,te.buffer),{ids:W,positions:te}}static deserialize(A){let F=new Zr;return F.ids=A.ids,F.positions=A.positions,F.indexed=!0,F}}function ai(R){let A=+R;return!isNaN(A)&&A<=Number.MAX_SAFE_INTEGER?A:bi(String(R))}function gi(R,A,F,W){for(;F<W;){let te=R[F+W>>1],fe=F-1,pe=W+1;for(;;){do fe++;while(R[fe]<te);do pe--;while(R[pe]>te);if(fe>=pe)break;Ii(R,fe,pe),Ii(A,3*fe,3*pe),Ii(A,3*fe+1,3*pe+1),Ii(A,3*fe+2,3*pe+2)}pe-F<W-pe?(gi(R,A,F,pe),F=pe+1):(gi(R,A,pe+1,W),W=pe)}}function Ii(R,A,F){let W=R[A];R[A]=R[F],R[F]=W}Fi(\"FeaturePositionMap\",Zr);class Si{constructor(A,F){this.gl=A.gl,this.location=F}}class ei extends Si{constructor(A,F){super(A,F),this.current=0}set(A){this.current!==A&&(this.current=A,this.gl.uniform1f(this.location,A))}}class Ln extends Si{constructor(A,F){super(A,F),this.current=[0,0,0,0]}set(A){A[0]===this.current[0]&&A[1]===this.current[1]&&A[2]===this.current[2]&&A[3]===this.current[3]||(this.current=A,this.gl.uniform4f(this.location,A[0],A[1],A[2],A[3]))}}class En extends Si{constructor(A,F){super(A,F),this.current=nr.transparent}set(A){A.r===this.current.r&&A.g===this.current.g&&A.b===this.current.b&&A.a===this.current.a||(this.current=A,this.gl.uniform4f(this.location,A.r,A.g,A.b,A.a))}}let Un=new Float32Array(16);function ia(R){return[kt(255*R.r,255*R.g),kt(255*R.b,255*R.a)]}class Ea{constructor(A,F,W){this.value=A,this.uniformNames=F.map(te=>`u_${te}`),this.type=W}setUniform(A,F,W){A.set(W.constantOr(this.value))}getBinding(A,F,W){return this.type===\"color\"?new En(A,F):new ei(A,F)}}class Ia{constructor(A,F){this.uniformNames=F.map(W=>`u_${W}`),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1}setConstantPatternPositions(A,F){this.pixelRatioFrom=F.pixelRatio,this.pixelRatioTo=A.pixelRatio,this.patternFrom=F.tlbr,this.patternTo=A.tlbr}setUniform(A,F,W,te){let fe=te===\"u_pattern_to\"?this.patternTo:te===\"u_pattern_from\"?this.patternFrom:te===\"u_pixel_ratio_to\"?this.pixelRatioTo:te===\"u_pixel_ratio_from\"?this.pixelRatioFrom:null;fe&&A.set(fe)}getBinding(A,F,W){return W.substr(0,9)===\"u_pattern\"?new Ln(A,F):new ei(A,F)}}class yo{constructor(A,F,W,te){this.expression=A,this.type=W,this.maxValue=0,this.paintVertexAttributes=F.map(fe=>({name:`a_${fe}`,type:\"Float32\",components:W===\"color\"?2:1,offset:0})),this.paintVertexArray=new te}populatePaintArray(A,F,W,te,fe){let pe=this.paintVertexArray.length,ze=this.expression.evaluate(new rs(0),F,{},te,[],fe);this.paintVertexArray.resize(A),this._setPaintValue(pe,A,ze)}updatePaintArray(A,F,W,te){let fe=this.expression.evaluate({zoom:0},W,te);this._setPaintValue(A,F,fe)}_setPaintValue(A,F,W){if(this.type===\"color\"){let te=ia(W);for(let fe=A;fe<F;fe++)this.paintVertexArray.emplace(fe,te[0],te[1])}else{for(let te=A;te<F;te++)this.paintVertexArray.emplace(te,W);this.maxValue=Math.max(this.maxValue,Math.abs(W))}}upload(A){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=A.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))}destroy(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()}}class Da{constructor(A,F,W,te,fe,pe){this.expression=A,this.uniformNames=F.map(ze=>`u_${ze}_t`),this.type=W,this.useIntegerZoom=te,this.zoom=fe,this.maxValue=0,this.paintVertexAttributes=F.map(ze=>({name:`a_${ze}`,type:\"Float32\",components:W===\"color\"?4:2,offset:0})),this.paintVertexArray=new pe}populatePaintArray(A,F,W,te,fe){let pe=this.expression.evaluate(new rs(this.zoom),F,{},te,[],fe),ze=this.expression.evaluate(new rs(this.zoom+1),F,{},te,[],fe),Ke=this.paintVertexArray.length;this.paintVertexArray.resize(A),this._setPaintValue(Ke,A,pe,ze)}updatePaintArray(A,F,W,te){let fe=this.expression.evaluate({zoom:this.zoom},W,te),pe=this.expression.evaluate({zoom:this.zoom+1},W,te);this._setPaintValue(A,F,fe,pe)}_setPaintValue(A,F,W,te){if(this.type===\"color\"){let fe=ia(W),pe=ia(te);for(let ze=A;ze<F;ze++)this.paintVertexArray.emplace(ze,fe[0],fe[1],pe[0],pe[1])}else{for(let fe=A;fe<F;fe++)this.paintVertexArray.emplace(fe,W,te);this.maxValue=Math.max(this.maxValue,Math.abs(W),Math.abs(te))}}upload(A){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=A.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))}destroy(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()}setUniform(A,F){let W=this.useIntegerZoom?Math.floor(F.zoom):F.zoom,te=E(this.expression.interpolationFactor(W,this.zoom,this.zoom+1),0,1);A.set(te)}getBinding(A,F,W){return new ei(A,F)}}class go{constructor(A,F,W,te,fe,pe){this.expression=A,this.type=F,this.useIntegerZoom=W,this.zoom=te,this.layerId=pe,this.zoomInPaintVertexArray=new fe,this.zoomOutPaintVertexArray=new fe}populatePaintArray(A,F,W){let te=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(A),this.zoomOutPaintVertexArray.resize(A),this._setPaintValues(te,A,F.patterns&&F.patterns[this.layerId],W)}updatePaintArray(A,F,W,te,fe){this._setPaintValues(A,F,W.patterns&&W.patterns[this.layerId],fe)}_setPaintValues(A,F,W,te){if(!te||!W)return;let{min:fe,mid:pe,max:ze}=W,Ke=te[fe],ct=te[pe],Lt=te[ze];if(Ke&&ct&&Lt)for(let $t=A;$t<F;$t++)this.zoomInPaintVertexArray.emplace($t,ct.tl[0],ct.tl[1],ct.br[0],ct.br[1],Ke.tl[0],Ke.tl[1],Ke.br[0],Ke.br[1],ct.pixelRatio,Ke.pixelRatio),this.zoomOutPaintVertexArray.emplace($t,ct.tl[0],ct.tl[1],ct.br[0],ct.br[1],Lt.tl[0],Lt.tl[1],Lt.br[0],Lt.br[1],ct.pixelRatio,Lt.pixelRatio)}upload(A){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=A.createVertexBuffer(this.zoomInPaintVertexArray,nt.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=A.createVertexBuffer(this.zoomOutPaintVertexArray,nt.members,this.expression.isStateDependent))}destroy(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()}}class Is{constructor(A,F,W){this.binders={},this._buffers=[];let te=[];for(let fe in A.paint._values){if(!W(fe))continue;let pe=A.paint.get(fe);if(!(pe instanceof xu&&Nl(pe.property.specification)))continue;let ze=Xs(fe,A.type),Ke=pe.value,ct=pe.property.specification.type,Lt=pe.property.useIntegerZoom,$t=pe.property.specification[\"property-type\"],fr=$t===\"cross-faded\"||$t===\"cross-faded-data-driven\";if(Ke.kind===\"constant\")this.binders[fe]=fr?new Ia(Ke.value,ze):new Ea(Ke.value,ze,ct),te.push(`/u_${fe}`);else if(Ke.kind===\"source\"||fr){let mr=Gn(fe,ct,\"source\");this.binders[fe]=fr?new go(Ke,ct,Lt,F,mr,A.id):new yo(Ke,ze,ct,mr),te.push(`/a_${fe}`)}else{let mr=Gn(fe,ct,\"composite\");this.binders[fe]=new Da(Ke,ze,ct,Lt,F,mr),te.push(`/z_${fe}`)}}this.cacheKey=te.sort().join(\"\")}getMaxValue(A){let F=this.binders[A];return F instanceof yo||F instanceof Da?F.maxValue:0}populatePaintArrays(A,F,W,te,fe){for(let pe in this.binders){let ze=this.binders[pe];(ze instanceof yo||ze instanceof Da||ze instanceof go)&&ze.populatePaintArray(A,F,W,te,fe)}}setConstantPatternPositions(A,F){for(let W in this.binders){let te=this.binders[W];te instanceof Ia&&te.setConstantPatternPositions(A,F)}}updatePaintArrays(A,F,W,te,fe){let pe=!1;for(let ze in A){let Ke=F.getPositions(ze);for(let ct of Ke){let Lt=W.feature(ct.index);for(let $t in this.binders){let fr=this.binders[$t];if((fr instanceof yo||fr instanceof Da||fr instanceof go)&&fr.expression.isStateDependent===!0){let mr=te.paint.get($t);fr.expression=mr.value,fr.updatePaintArray(ct.start,ct.end,Lt,A[ze],fe),pe=!0}}}}return pe}defines(){let A=[];for(let F in this.binders){let W=this.binders[F];(W instanceof Ea||W instanceof Ia)&&A.push(...W.uniformNames.map(te=>`#define HAS_UNIFORM_${te}`))}return A}getBinderAttributes(){let A=[];for(let F in this.binders){let W=this.binders[F];if(W instanceof yo||W instanceof Da)for(let te=0;te<W.paintVertexAttributes.length;te++)A.push(W.paintVertexAttributes[te].name);else if(W instanceof go)for(let te=0;te<nt.members.length;te++)A.push(nt.members[te].name)}return A}getBinderUniforms(){let A=[];for(let F in this.binders){let W=this.binders[F];if(W instanceof Ea||W instanceof Ia||W instanceof Da)for(let te of W.uniformNames)A.push(te)}return A}getPaintVertexBuffers(){return this._buffers}getUniforms(A,F){let W=[];for(let te in this.binders){let fe=this.binders[te];if(fe instanceof Ea||fe instanceof Ia||fe instanceof Da){for(let pe of fe.uniformNames)if(F[pe]){let ze=fe.getBinding(A,F[pe],pe);W.push({name:pe,property:te,binding:ze})}}}return W}setUniforms(A,F,W,te){for(let{name:fe,property:pe,binding:ze}of F)this.binders[pe].setUniform(ze,te,W.get(pe),fe)}updatePaintBuffers(A){this._buffers=[];for(let F in this.binders){let W=this.binders[F];if(A&&W instanceof go){let te=A.fromScale===2?W.zoomInPaintVertexBuffer:W.zoomOutPaintVertexBuffer;te&&this._buffers.push(te)}else(W instanceof yo||W instanceof Da)&&W.paintVertexBuffer&&this._buffers.push(W.paintVertexBuffer)}}upload(A){for(let F in this.binders){let W=this.binders[F];(W instanceof yo||W instanceof Da||W instanceof go)&&W.upload(A)}this.updatePaintBuffers()}destroy(){for(let A in this.binders){let F=this.binders[A];(F instanceof yo||F instanceof Da||F instanceof go)&&F.destroy()}}}class Ms{constructor(A,F,W=()=>!0){this.programConfigurations={};for(let te of A)this.programConfigurations[te.id]=new Is(te,F,W);this.needsUpload=!1,this._featureMap=new Zr,this._bufferOffset=0}populatePaintArrays(A,F,W,te,fe,pe){for(let ze in this.programConfigurations)this.programConfigurations[ze].populatePaintArrays(A,F,te,fe,pe);F.id!==void 0&&this._featureMap.add(F.id,W,this._bufferOffset,A),this._bufferOffset=A,this.needsUpload=!0}updatePaintArrays(A,F,W,te){for(let fe of W)this.needsUpload=this.programConfigurations[fe.id].updatePaintArrays(A,this._featureMap,F,fe,te)||this.needsUpload}get(A){return this.programConfigurations[A]}upload(A){if(this.needsUpload){for(let F in this.programConfigurations)this.programConfigurations[F].upload(A);this.needsUpload=!1}}destroy(){for(let A in 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$t=[];for(W=0;W<Ke.length;W++)$t[W]=Ke[W][0];Lt(Ke=$t);break;case 2:for(W=0;W<Ke.length;W++)Lt(Ke[W]);break;case 3:for(Ke=function(mr){var Pr=mr.length;if(Pr<=1)return[mr];for(var zr,ui,yi=[],vn=0;vn<Pr;vn++){var zi=gn(mr[vn]);zi!==0&&(ui===void 0&&(ui=zi<0),ui===zi<0?(zr&&yi.push(zr),zr=[mr[vn]]):zr.push(mr[vn]))}return zr&&yi.push(zr),yi}(Ke),W=0;W<Ke.length;W++)for(te=0;te<Ke[W].length;te++)Lt(Ke[W][te])}Ke.length===1?Ke=Ke[0]:ct=\"Multi\"+ct;var fr={type:\"Feature\",geometry:{type:ct,coordinates:Ke},properties:this.properties};return\"id\"in this&&(fr.id=this.id),fr};var rn=Di,Ci=Bi;function Bi(R,A){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=R,this._keys=[],this._values=[],this._features=[],R.readFields(Gi,this,A),this.length=this._features.length}function Gi(R,A,F){R===15?A.version=F.readVarint():R===1?A.name=F.readString():R===5?A.extent=F.readVarint():R===2?A._features.push(F.pos):R===3?A._keys.push(F.readString()):R===4&&A._values.push(function(W){for(var te=null,fe=W.readVarint()+W.pos;W.pos<fe;){var pe=W.readVarint()>>3;te=pe===1?W.readString():pe===2?W.readFloat():pe===3?W.readDouble():pe===4?W.readVarint64():pe===5?W.readVarint():pe===6?W.readSVarint():pe===7?W.readBoolean():null}return te}(F))}Bi.prototype.feature=function(R){if(R<0||R>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[R];var A=this._pbf.readVarint()+this._pbf.pos;return new rn(this._pbf,A,this.extent,this._keys,this._values)};var sn=Ci;function zn(R,A,F){if(R===3){var W=new sn(F,F.readVarint()+F.pos);W.length&&(A[W.name]=W)}}br.VectorTile=function(R,A){this.layers=R.readFields(zn,{},A)},br.VectorTileFeature=Di,br.VectorTileLayer=Ci;let Ja=br.VectorTileFeature.types,co=Math.pow(2,13);function ts(R,A,F,W,te,fe,pe,ze){R.emplaceBack(A,F,2*Math.floor(W*co)+pe,te*co*2,fe*co*2,Math.round(ze))}class so{constructor(A){this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(F=>F.id),this.index=A.index,this.hasPattern=!1,this.layoutVertexArray=new Ul,this.centroidVertexArray=new wo,this.indexArray=new se,this.programConfigurations=new Ms(A.layers,A.zoom),this.segments=new Ye,this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){this.features=[],this.hasPattern=at(\"fill-extrusion\",this.layers,F);for(let{feature:te,id:fe,index:pe,sourceLayerIndex:ze}of A){let Ke=this.layers[0]._featureFilter.needGeometry,ct=Sl(te,Ke);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),ct,W))continue;let Lt={id:fe,sourceLayerIndex:ze,index:pe,geometry:Ke?ct.geometry:$s(te),properties:te.properties,type:te.type,patterns:{}};this.hasPattern?this.features.push(Ct(\"fill-extrusion\",this.layers,Lt,this.zoom,F)):this.addFeature(Lt,Lt.geometry,pe,W,{}),F.featureIndex.insert(te,Lt.geometry,pe,ze,this.index,!0)}}addFeatures(A,F,W){for(let te of this.features){let{geometry:fe}=te;this.addFeature(te,fe,te.index,F,W)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}isEmpty(){return this.layoutVertexArray.length===0&&this.centroidVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,ur),this.centroidVertexBuffer=A.createVertexBuffer(this.centroidVertexArray,ht.members,!0),this.indexBuffer=A.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.centroidVertexBuffer.destroy())}addFeature(A,F,W,te,fe){for(let pe of Cf(F,500)){let ze={x:0,y:0,vertexCount:0},Ke=0;for(let Pr of pe)Ke+=Pr.length;let ct=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray);for(let Pr of pe){if(Pr.length===0||ms(Pr))continue;let zr=0;for(let ui=0;ui<Pr.length;ui++){let yi=Pr[ui];if(ui>=1){let vn=Pr[ui-1];if(!Zo(yi,vn)){ct.vertexLength+4>Ye.MAX_VERTEX_ARRAY_LENGTH&&(ct=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));let zi=yi.sub(vn)._perp()._unit(),un=vn.dist(yi);zr+un>32768&&(zr=0),ts(this.layoutVertexArray,yi.x,yi.y,zi.x,zi.y,0,0,zr),ts(this.layoutVertexArray,yi.x,yi.y,zi.x,zi.y,0,1,zr),ze.x+=2*yi.x,ze.y+=2*yi.y,ze.vertexCount+=2,zr+=un,ts(this.layoutVertexArray,vn.x,vn.y,zi.x,zi.y,0,0,zr),ts(this.layoutVertexArray,vn.x,vn.y,zi.x,zi.y,0,1,zr),ze.x+=2*vn.x,ze.y+=2*vn.y,ze.vertexCount+=2;let Tn=ct.vertexLength;this.indexArray.emplaceBack(Tn,Tn+2,Tn+1),this.indexArray.emplaceBack(Tn+1,Tn+2,Tn+3),ct.vertexLength+=4,ct.primitiveLength+=2}}}}if(ct.vertexLength+Ke>Ye.MAX_VERTEX_ARRAY_LENGTH&&(ct=this.segments.prepareSegment(Ke,this.layoutVertexArray,this.indexArray)),Ja[A.type]!==\"Polygon\")continue;let Lt=[],$t=[],fr=ct.vertexLength;for(let Pr of pe)if(Pr.length!==0){Pr!==pe[0]&&$t.push(Lt.length/2);for(let zr=0;zr<Pr.length;zr++){let ui=Pr[zr];ts(this.layoutVertexArray,ui.x,ui.y,0,0,1,1,0),ze.x+=ui.x,ze.y+=ui.y,ze.vertexCount+=1,Lt.push(ui.x),Lt.push(ui.y)}}let mr=zo(Lt,$t);for(let Pr=0;Pr<mr.length;Pr+=3)this.indexArray.emplaceBack(fr+mr[Pr],fr+mr[Pr+2],fr+mr[Pr+1]);ct.primitiveLength+=mr.length/3,ct.vertexLength+=Ke;for(let Pr=0;Pr<ze.vertexCount;Pr++){let zr=Math.floor(ze.x/ze.vertexCount),ui=Math.floor(ze.y/ze.vertexCount);this.centroidVertexArray.emplaceBack(zr,ui)}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,A,W,fe,te)}}function Zo(R,A){return R.x===A.x&&(R.x<0||R.x>Ha)||R.y===A.y&&(R.y<0||R.y>Ha)}function ms(R){return R.every(A=>A.x<0)||R.every(A=>A.x>Ha)||R.every(A=>A.y<0)||R.every(A=>A.y>Ha)}let ou;Fi(\"FillExtrusionBucket\",so,{omit:[\"layers\",\"features\"]});var Cv={get paint(){return ou=ou||new ue({\"fill-extrusion-opacity\":new Ua(ce[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new oo(ce[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new Ua(ce[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new Ua(ce[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new Vc(ce[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new oo(ce[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new oo(ce[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new Ua(ce[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})}};class Lv extends B{constructor(A){super(A,Cv)}createBucket(A){return new so(A)}queryRadius(){return Hn(this.paint.get(\"fill-extrusion-translate\"))}is3D(){return!0}queryIntersectsFeature(A,F,W,te,fe,pe,ze,Ke){let ct=en(A,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),pe.angle,ze),Lt=this.paint.get(\"fill-extrusion-height\").evaluate(F,W),$t=this.paint.get(\"fill-extrusion-base\").evaluate(F,W),fr=function(Pr,zr,ui,yi){let vn=[];for(let zi of Pr){let un=[zi.x,zi.y,0,1];Bn(un,un,zr),vn.push(new u(un[0]/un[3],un[1]/un[3]))}return vn}(ct,Ke),mr=function(Pr,zr,ui,yi){let vn=[],zi=[],un=yi[8]*zr,Tn=yi[9]*zr,pa=yi[10]*zr,ro=yi[11]*zr,Vo=yi[8]*ui,Xa=yi[9]*ui,sa=yi[10]*ui,Mo=yi[11]*ui;for(let fo of Pr){let lo=[],Xn=[];for(let Ro of fo){let uo=Ro.x,$o=Ro.y,Ju=yi[0]*uo+yi[4]*$o+yi[12],qu=yi[1]*uo+yi[5]*$o+yi[13],Mh=yi[2]*uo+yi[6]*$o+yi[14],Qv=yi[3]*uo+yi[7]*$o+yi[15],ld=Mh+pa,Eh=Qv+ro,Gd=Ju+Vo,Hd=qu+Xa,jd=Mh+sa,Af=Qv+Mo,kh=new u((Ju+un)/Eh,(qu+Tn)/Eh);kh.z=ld/Eh,lo.push(kh);let Ed=new u(Gd/Af,Hd/Af);Ed.z=jd/Af,Xn.push(Ed)}vn.push(lo),zi.push(Xn)}return[vn,zi]}(te,$t,Lt,Ke);return function(Pr,zr,ui){let yi=1/0;bt(ui,zr)&&(yi=Kv(ui,zr[0]));for(let vn=0;vn<zr.length;vn++){let zi=zr[vn],un=Pr[vn];for(let Tn=0;Tn<zi.length-1;Tn++){let pa=zi[Tn],ro=[pa,zi[Tn+1],un[Tn+1],un[Tn],pa];Sc(ui,ro)&&(yi=Math.min(yi,Kv(ui,ro)))}}return yi!==1/0&&yi}(mr[0],mr[1],fr)}}function wd(R,A){return R.x*A.x+R.y*A.y}function Kv(R,A){if(R.length===1){let F=0,W=A[F++],te;for(;!te||W.equals(te);)if(te=A[F++],!te)return 1/0;for(;F<A.length;F++){let fe=A[F],pe=R[0],ze=te.sub(W),Ke=fe.sub(W),ct=pe.sub(W),Lt=wd(ze,ze),$t=wd(ze,Ke),fr=wd(Ke,Ke),mr=wd(ct,ze),Pr=wd(ct,Ke),zr=Lt*fr-$t*$t,ui=(fr*mr-$t*Pr)/zr,yi=(Lt*Pr-$t*mr)/zr,vn=W.z*(1-ui-yi)+te.z*ui+fe.z*yi;if(isFinite(vn))return vn}return 1/0}{let F=1/0;for(let W of A)F=Math.min(F,W.z);return F}}let cg=qe([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4),{members:pp}=cg,Td=qe([{name:\"a_uv_x\",components:1,type:\"Float32\"},{name:\"a_split_index\",components:1,type:\"Float32\"}]),{members:gp}=Td,Vd=br.VectorTileFeature.types,Ad=Math.cos(Math.PI/180*37.5),Pv=Math.pow(2,14)/.5;class Jv{constructor(A){this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(F=>F.id),this.index=A.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach(F=>{this.gradients[F.id]={}}),this.layoutVertexArray=new Lu,this.layoutVertexArray2=new au,this.indexArray=new se,this.programConfigurations=new Ms(A.layers,A.zoom),this.segments=new Ye,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){this.hasPattern=at(\"line\",this.layers,F);let te=this.layers[0].layout.get(\"line-sort-key\"),fe=!te.isConstant(),pe=[];for(let{feature:ze,id:Ke,index:ct,sourceLayerIndex:Lt}of A){let $t=this.layers[0]._featureFilter.needGeometry,fr=Sl(ze,$t);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),fr,W))continue;let mr=fe?te.evaluate(fr,{},W):void 0,Pr={id:Ke,properties:ze.properties,type:ze.type,sourceLayerIndex:Lt,index:ct,geometry:$t?fr.geometry:$s(ze),patterns:{},sortKey:mr};pe.push(Pr)}fe&&pe.sort((ze,Ke)=>ze.sortKey-Ke.sortKey);for(let ze of pe){let{geometry:Ke,index:ct,sourceLayerIndex:Lt}=ze;if(this.hasPattern){let $t=Ct(\"line\",this.layers,ze,this.zoom,F);this.patternFeatures.push($t)}else this.addFeature(ze,Ke,ct,W,{});F.featureIndex.insert(A[ct].feature,Ke,ct,Lt,this.index)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}addFeatures(A,F,W){for(let te of this.patternFeatures)this.addFeature(te,te.geometry,te.index,F,W)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexArray2.length!==0&&(this.layoutVertexBuffer2=A.createVertexBuffer(this.layoutVertexArray2,gp)),this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,pp),this.indexBuffer=A.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}lineFeatureClips(A){if(A.properties&&Object.prototype.hasOwnProperty.call(A.properties,\"mapbox_clip_start\")&&Object.prototype.hasOwnProperty.call(A.properties,\"mapbox_clip_end\"))return{start:+A.properties.mapbox_clip_start,end:+A.properties.mapbox_clip_end}}addFeature(A,F,W,te,fe){let pe=this.layers[0].layout,ze=pe.get(\"line-join\").evaluate(A,{}),Ke=pe.get(\"line-cap\"),ct=pe.get(\"line-miter-limit\"),Lt=pe.get(\"line-round-limit\");this.lineClips=this.lineFeatureClips(A);for(let $t of F)this.addLine($t,A,ze,Ke,ct,Lt);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,A,W,fe,te)}addLine(A,F,W,te,fe,pe){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(let yi=0;yi<A.length-1;yi++)this.totalDistance+=A[yi].dist(A[yi+1]);this.updateScaledDistance(),this.maxLineLength=Math.max(this.maxLineLength,this.totalDistance)}let ze=Vd[F.type]===\"Polygon\",Ke=A.length;for(;Ke>=2&&A[Ke-1].equals(A[Ke-2]);)Ke--;let ct=0;for(;ct<Ke-1&&A[ct].equals(A[ct+1]);)ct++;if(Ke<(ze?3:2))return;W===\"bevel\"&&(fe=1.05);let Lt=this.overscaling<=16?15*Ha/(512*this.overscaling):0,$t=this.segments.prepareSegment(10*Ke,this.layoutVertexArray,this.indexArray),fr,mr,Pr,zr,ui;this.e1=this.e2=-1,ze&&(fr=A[Ke-2],ui=A[ct].sub(fr)._unit()._perp());for(let yi=ct;yi<Ke;yi++){if(Pr=yi===Ke-1?ze?A[ct+1]:void 0:A[yi+1],Pr&&A[yi].equals(Pr))continue;ui&&(zr=ui),fr&&(mr=fr),fr=A[yi],ui=Pr?Pr.sub(fr)._unit()._perp():zr,zr=zr||ui;let vn=zr.add(ui);vn.x===0&&vn.y===0||vn._unit();let zi=zr.x*ui.x+zr.y*ui.y,un=vn.x*ui.x+vn.y*ui.y,Tn=un!==0?1/un:1/0,pa=2*Math.sqrt(2-2*un),ro=un<Ad&&mr&&Pr,Vo=zr.x*ui.y-zr.y*ui.x>0;if(ro&&yi>ct){let Mo=fr.dist(mr);if(Mo>2*Lt){let fo=fr.sub(fr.sub(mr)._mult(Lt/Mo)._round());this.updateDistance(mr,fo),this.addCurrentVertex(fo,zr,0,0,$t),mr=fo}}let Xa=mr&&Pr,sa=Xa?W:ze?\"butt\":te;if(Xa&&sa===\"round\"&&(Tn<pe?sa=\"miter\":Tn<=2&&(sa=\"fakeround\")),sa===\"miter\"&&Tn>fe&&(sa=\"bevel\"),sa===\"bevel\"&&(Tn>2&&(sa=\"flipbevel\"),Tn<fe&&(sa=\"miter\")),mr&&this.updateDistance(mr,fr),sa===\"miter\")vn._mult(Tn),this.addCurrentVertex(fr,vn,0,0,$t);else if(sa===\"flipbevel\"){if(Tn>100)vn=ui.mult(-1);else{let Mo=Tn*zr.add(ui).mag()/zr.sub(ui).mag();vn._perp()._mult(Mo*(Vo?-1:1))}this.addCurrentVertex(fr,vn,0,0,$t),this.addCurrentVertex(fr,vn.mult(-1),0,0,$t)}else if(sa===\"bevel\"||sa===\"fakeround\"){let Mo=-Math.sqrt(Tn*Tn-1),fo=Vo?Mo:0,lo=Vo?0:Mo;if(mr&&this.addCurrentVertex(fr,zr,fo,lo,$t),sa===\"fakeround\"){let Xn=Math.round(180*pa/Math.PI/20);for(let Ro=1;Ro<Xn;Ro++){let uo=Ro/Xn;if(uo!==.5){let Ju=uo-.5;uo+=uo*Ju*(uo-1)*((1.0904+zi*(zi*(3.55645-1.43519*zi)-3.2452))*Ju*Ju+(.848013+zi*(.215638*zi-1.06021)))}let $o=ui.sub(zr)._mult(uo)._add(zr)._unit()._mult(Vo?-1:1);this.addHalfVertex(fr,$o.x,$o.y,!1,Vo,0,$t)}}Pr&&this.addCurrentVertex(fr,ui,-fo,-lo,$t)}else if(sa===\"butt\")this.addCurrentVertex(fr,vn,0,0,$t);else if(sa===\"square\"){let Mo=mr?1:-1;this.addCurrentVertex(fr,vn,Mo,Mo,$t)}else sa===\"round\"&&(mr&&(this.addCurrentVertex(fr,zr,0,0,$t),this.addCurrentVertex(fr,zr,1,1,$t,!0)),Pr&&(this.addCurrentVertex(fr,ui,-1,-1,$t,!0),this.addCurrentVertex(fr,ui,0,0,$t)));if(ro&&yi<Ke-1){let Mo=fr.dist(Pr);if(Mo>2*Lt){let fo=fr.add(Pr.sub(fr)._mult(Lt/Mo)._round());this.updateDistance(fr,fo),this.addCurrentVertex(fo,ui,0,0,$t),fr=fo}}}}addCurrentVertex(A,F,W,te,fe,pe=!1){let ze=F.y*te-F.x,Ke=-F.y-F.x*te;this.addHalfVertex(A,F.x+F.y*W,F.y-F.x*W,pe,!1,W,fe),this.addHalfVertex(A,ze,Ke,pe,!0,-te,fe),this.distance>Pv/2&&this.totalDistance===0&&(this.distance=0,this.updateScaledDistance(),this.addCurrentVertex(A,F,W,te,fe,pe))}addHalfVertex({x:A,y:F},W,te,fe,pe,ze,Ke){let ct=.5*(this.lineClips?this.scaledDistance*(Pv-1):this.scaledDistance);this.layoutVertexArray.emplaceBack((A<<1)+(fe?1:0),(F<<1)+(pe?1:0),Math.round(63*W)+128,Math.round(63*te)+128,1+(ze===0?0:ze<0?-1:1)|(63&ct)<<2,ct>>6),this.lineClips&&this.layoutVertexArray2.emplaceBack((this.scaledDistance-this.lineClips.start)/(this.lineClips.end-this.lineClips.start),this.lineClipsArray.length);let Lt=Ke.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,Lt),Ke.primitiveLength++),pe?this.e2=Lt:this.e1=Lt}updateScaledDistance(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance}updateDistance(A,F){this.distance+=A.dist(F),this.updateScaledDistance()}}let Iv,ay;Fi(\"LineBucket\",Jv,{omit:[\"layers\",\"patternFeatures\"]});var fg={get paint(){return ay=ay||new ue({\"line-opacity\":new oo(ce.paint_line[\"line-opacity\"]),\"line-color\":new oo(ce.paint_line[\"line-color\"]),\"line-translate\":new Ua(ce.paint_line[\"line-translate\"]),\"line-translate-anchor\":new Ua(ce.paint_line[\"line-translate-anchor\"]),\"line-width\":new oo(ce.paint_line[\"line-width\"]),\"line-gap-width\":new oo(ce.paint_line[\"line-gap-width\"]),\"line-offset\":new oo(ce.paint_line[\"line-offset\"]),\"line-blur\":new oo(ce.paint_line[\"line-blur\"]),\"line-dasharray\":new hc(ce.paint_line[\"line-dasharray\"]),\"line-pattern\":new Vc(ce.paint_line[\"line-pattern\"]),\"line-gradient\":new Ku(ce.paint_line[\"line-gradient\"])})},get layout(){return Iv=Iv||new ue({\"line-cap\":new Ua(ce.layout_line[\"line-cap\"]),\"line-join\":new oo(ce.layout_line[\"line-join\"]),\"line-miter-limit\":new Ua(ce.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new Ua(ce.layout_line[\"line-round-limit\"]),\"line-sort-key\":new oo(ce.layout_line[\"line-sort-key\"])})}};class oh extends oo{possiblyEvaluate(A,F){return F=new rs(Math.floor(F.zoom),{now:F.now,fadeDuration:F.fadeDuration,zoomHistory:F.zoomHistory,transition:F.transition}),super.possiblyEvaluate(A,F)}evaluate(A,F,W,te){return F=L({},F,{zoom:Math.floor(F.zoom)}),super.evaluate(A,F,W,te)}}let hg;class oy extends B{constructor(A){super(A,fg),this.gradientVersion=0,hg||(hg=new oh(fg.paint.properties[\"line-width\"].specification),hg.useIntegerZoom=!0)}_handleSpecialPaintPropertyUpdate(A){if(A===\"line-gradient\"){let F=this.gradientExpression();this.stepInterpolant=!!function(W){return W._styleExpression!==void 0}(F)&&F._styleExpression.expression instanceof _n,this.gradientVersion=(this.gradientVersion+1)%Number.MAX_SAFE_INTEGER}}gradientExpression(){return this._transitionablePaint._values[\"line-gradient\"].value.expression}recalculate(A,F){super.recalculate(A,F),this.paint._values[\"line-floorwidth\"]=hg.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,A)}createBucket(A){return new Jv(A)}queryRadius(A){let F=A,W=jh(Ei(\"line-width\",this,F),Ei(\"line-gap-width\",this,F)),te=Ei(\"line-offset\",this,F);return W/2+Math.abs(te)+Hn(this.paint.get(\"line-translate\"))}queryIntersectsFeature(A,F,W,te,fe,pe,ze){let Ke=en(A,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),pe.angle,ze),ct=ze/2*jh(this.paint.get(\"line-width\").evaluate(F,W),this.paint.get(\"line-gap-width\").evaluate(F,W)),Lt=this.paint.get(\"line-offset\").evaluate(F,W);return Lt&&(te=function($t,fr){let mr=[];for(let Pr=0;Pr<$t.length;Pr++){let zr=$t[Pr],ui=[];for(let yi=0;yi<zr.length;yi++){let vn=zr[yi-1],zi=zr[yi],un=zr[yi+1],Tn=yi===0?new u(0,0):zi.sub(vn)._unit()._perp(),pa=yi===zr.length-1?new u(0,0):un.sub(zi)._unit()._perp(),ro=Tn._add(pa)._unit(),Vo=ro.x*pa.x+ro.y*pa.y;Vo!==0&&ro._mult(1/Vo),ui.push(ro._mult(fr)._add(zi))}mr.push(ui)}return mr}(te,Lt*ze)),function($t,fr,mr){for(let Pr=0;Pr<fr.length;Pr++){let zr=fr[Pr];if($t.length>=3){for(let 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SC(R,A){let{expression:F}=A;if(F.kind===\"constant\")return{kind:\"constant\",layoutSize:F.evaluate(new rs(R+1))};if(F.kind===\"source\")return{kind:\"source\"};{let{zoomStops:W,interpolationType:te}=F,fe=0;for(;fe<W.length&&W[fe]<=R;)fe++;fe=Math.max(0,fe-1);let pe=fe;for(;pe<W.length&&W[pe]<R+1;)pe++;pe=Math.min(W.length-1,pe);let ze=W[fe],Ke=W[pe];return F.kind===\"composite\"?{kind:\"composite\",minZoom:ze,maxZoom:Ke,interpolationType:te}:{kind:\"camera\",minZoom:ze,maxZoom:Ke,minSize:F.evaluate(new rs(ze)),maxSize:F.evaluate(new rs(Ke)),interpolationType:te}}}function oS(R,A,F){let W=\"never\",te=R.get(A);return te?W=te:R.get(F)&&(W=\"always\"),W}let Z9=br.VectorTileFeature.types,Y9=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function Dw(R,A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr){let mr=ze?Math.min(lm,Math.round(ze[0])):0,Pr=ze?Math.min(lm,Math.round(ze[1])):0;R.emplaceBack(A,F,Math.round(32*W),Math.round(32*te),fe,pe,(mr<<1)+(Ke?1:0),Pr,16*ct,16*Lt,256*$t,256*fr)}function sS(R,A,F){R.emplaceBack(A.x,A.y,F),R.emplaceBack(A.x,A.y,F),R.emplaceBack(A.x,A.y,F),R.emplaceBack(A.x,A.y,F)}function lS(R){for(let A of R.sections)if(no(A.text))return!0;return!1}class uS{constructor(A){this.layoutVertexArray=new Ql,this.indexArray=new se,this.programConfigurations=A,this.segments=new Ye,this.dynamicLayoutVertexArray=new dc,this.opacityVertexArray=new Tl,this.hasVisibleVertices=!1,this.placedSymbolArray=new Ta}isEmpty(){return this.layoutVertexArray.length===0&&this.indexArray.length===0&&this.dynamicLayoutVertexArray.length===0&&this.opacityVertexArray.length===0}upload(A,F,W,te){this.isEmpty()||(W&&(this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,rm.members),this.indexBuffer=A.createIndexBuffer(this.indexArray,F),this.dynamicLayoutVertexBuffer=A.createVertexBuffer(this.dynamicLayoutVertexArray,b1.members,!0),this.opacityVertexBuffer=A.createVertexBuffer(this.opacityVertexArray,Y9,!0),this.opacityVertexBuffer.itemSize=1),(W||te)&&this.programConfigurations.upload(A))}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())}}Fi(\"SymbolBuffers\",uS);class um{constructor(A,F,W){this.layoutVertexArray=new A,this.layoutAttributes=F,this.indexArray=new W,this.segments=new Ye,this.collisionVertexArray=new X}upload(A){this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=A.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=A.createVertexBuffer(this.collisionVertexArray,w1.members,!0)}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())}}Fi(\"CollisionBuffers\",um);class M1{constructor(A){this.collisionBoxArray=A.collisionBoxArray,this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(pe=>pe.id),this.index=A.index,this.pixelRatio=A.pixelRatio,this.sourceLayerIndex=A.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=Ri([]),this.placementViewportMatrix=Ri([]);let F=this.layers[0]._unevaluatedLayout._values;this.textSizeData=SC(this.zoom,F[\"text-size\"]),this.iconSizeData=SC(this.zoom,F[\"icon-size\"]);let W=this.layers[0].layout,te=W.get(\"symbol-sort-key\"),fe=W.get(\"symbol-z-order\");this.canOverlap=oS(W,\"text-overlap\",\"text-allow-overlap\")!==\"never\"||oS(W,\"icon-overlap\",\"icon-allow-overlap\")!==\"never\"||W.get(\"text-ignore-placement\")||W.get(\"icon-ignore-placement\"),this.sortFeaturesByKey=fe!==\"viewport-y\"&&!te.isConstant(),this.sortFeaturesByY=(fe===\"viewport-y\"||fe===\"auto\"&&!this.sortFeaturesByKey)&&this.canOverlap,W.get(\"symbol-placement\")===\"point\"&&(this.writingModes=W.get(\"text-writing-mode\").map(pe=>i.ah[pe])),this.stateDependentLayerIds=this.layers.filter(pe=>pe.isStateDependent()).map(pe=>pe.id),this.sourceID=A.sourceID}createArrays(){this.text=new uS(new Ms(this.layers,this.zoom,A=>/^text/.test(A))),this.icon=new uS(new Ms(this.layers,this.zoom,A=>/^icon/.test(A))),this.glyphOffsetArray=new Co,this.lineVertexArray=new Qa,this.symbolInstances=new $a,this.textAnchorOffsets=new Bo}calculateGlyphDependencies(A,F,W,te,fe){for(let pe=0;pe<A.length;pe++)if(F[A.charCodeAt(pe)]=!0,(W||te)&&fe){let ze=vc[A.charAt(pe)];ze&&(F[ze.charCodeAt(0)]=!0)}}populate(A,F,W){let te=this.layers[0],fe=te.layout,pe=fe.get(\"text-font\"),ze=fe.get(\"text-field\"),Ke=fe.get(\"icon-image\"),ct=(ze.value.kind!==\"constant\"||ze.value.value instanceof ri&&!ze.value.value.isEmpty()||ze.value.value.toString().length>0)&&(pe.value.kind!==\"constant\"||pe.value.value.length>0),Lt=Ke.value.kind!==\"constant\"||!!Ke.value.value||Object.keys(Ke.parameters).length>0,$t=fe.get(\"symbol-sort-key\");if(this.features=[],!ct&&!Lt)return;let fr=F.iconDependencies,mr=F.glyphDependencies,Pr=F.availableImages,zr=new rs(this.zoom);for(let{feature:ui,id:yi,index:vn,sourceLayerIndex:zi}of A){let un=te._featureFilter.needGeometry,Tn=Sl(ui,un);if(!te._featureFilter.filter(zr,Tn,W))continue;let pa,ro;if(un||(Tn.geometry=$s(ui)),ct){let Xa=te.getValueAndResolveTokens(\"text-field\",Tn,W,Pr),sa=ri.factory(Xa),Mo=this.hasRTLText=this.hasRTLText||lS(sa);(!Mo||ys.getRTLTextPluginStatus()===\"unavailable\"||Mo&&ys.isParsed())&&(pa=nm(sa,te,Tn))}if(Lt){let Xa=te.getValueAndResolveTokens(\"icon-image\",Tn,W,Pr);ro=Xa instanceof tn?Xa:tn.fromString(Xa)}if(!pa&&!ro)continue;let Vo=this.sortFeaturesByKey?$t.evaluate(Tn,{},W):void 0;if(this.features.push({id:yi,text:pa,icon:ro,index:vn,sourceLayerIndex:zi,geometry:Tn.geometry,properties:ui.properties,type:Z9[ui.type],sortKey:Vo}),ro&&(fr[ro.name]=!0),pa){let Xa=pe.evaluate(Tn,{},W).join(\",\"),sa=fe.get(\"text-rotation-alignment\")!==\"viewport\"&&fe.get(\"symbol-placement\")!==\"point\";this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(i.ah.vertical)>=0;for(let Mo of pa.sections)if(Mo.image)fr[Mo.image.name]=!0;else{let fo=Ka(pa.toString()),lo=Mo.fontStack||Xa,Xn=mr[lo]=mr[lo]||{};this.calculateGlyphDependencies(Mo.text,Xn,sa,this.allowVerticalPlacement,fo)}}}fe.get(\"symbol-placement\")===\"line\"&&(this.features=function(ui){let yi={},vn={},zi=[],un=0;function Tn(Xa){zi.push(ui[Xa]),un++}function pa(Xa,sa,Mo){let fo=vn[Xa];return delete vn[Xa],vn[sa]=fo,zi[fo].geometry[0].pop(),zi[fo].geometry[0]=zi[fo].geometry[0].concat(Mo[0]),fo}function ro(Xa,sa,Mo){let fo=yi[sa];return delete yi[sa],yi[Xa]=fo,zi[fo].geometry[0].shift(),zi[fo].geometry[0]=Mo[0].concat(zi[fo].geometry[0]),fo}function Vo(Xa,sa,Mo){let fo=Mo?sa[0][sa[0].length-1]:sa[0][0];return`${Xa}:${fo.x}:${fo.y}`}for(let Xa=0;Xa<ui.length;Xa++){let sa=ui[Xa],Mo=sa.geometry,fo=sa.text?sa.text.toString():null;if(!fo){Tn(Xa);continue}let lo=Vo(fo,Mo),Xn=Vo(fo,Mo,!0);if(lo in vn&&Xn in yi&&vn[lo]!==yi[Xn]){let Ro=ro(lo,Xn,Mo),uo=pa(lo,Xn,zi[Ro].geometry);delete yi[lo],delete vn[Xn],vn[Vo(fo,zi[uo].geometry,!0)]=uo,zi[Ro].geometry=null}else lo in vn?pa(lo,Xn,Mo):Xn in yi?ro(lo,Xn,Mo):(Tn(Xa),yi[lo]=un-1,vn[Xn]=un-1)}return zi.filter(Xa=>Xa.geometry)}(this.features)),this.sortFeaturesByKey&&this.features.sort((ui,yi)=>ui.sortKey-yi.sortKey)}update(A,F,W){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(A,F,this.layers,W),this.icon.programConfigurations.updatePaintArrays(A,F,this.layers,W))}isEmpty(){return this.symbolInstances.length===0&&!this.hasRTLText}uploadPending(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload}upload(A){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(A),this.iconCollisionBox.upload(A)),this.text.upload(A,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(A,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0}destroyDebugData(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()}destroy(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()}addToLineVertexArray(A,F){let W=this.lineVertexArray.length;if(A.segment!==void 0){let te=A.dist(F[A.segment+1]),fe=A.dist(F[A.segment]),pe={};for(let ze=A.segment+1;ze<F.length;ze++)pe[ze]={x:F[ze].x,y:F[ze].y,tileUnitDistanceFromAnchor:te},ze<F.length-1&&(te+=F[ze+1].dist(F[ze]));for(let ze=A.segment||0;ze>=0;ze--)pe[ze]={x:F[ze].x,y:F[ze].y,tileUnitDistanceFromAnchor:fe},ze>0&&(fe+=F[ze-1].dist(F[ze]));for(let ze=0;ze<F.length;ze++){let Ke=pe[ze];this.lineVertexArray.emplaceBack(Ke.x,Ke.y,Ke.tileUnitDistanceFromAnchor)}}return{lineStartIndex:W,lineLength:this.lineVertexArray.length-W}}addSymbols(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t,fr){let mr=A.indexArray,Pr=A.layoutVertexArray,zr=A.segments.prepareSegment(4*F.length,Pr,mr,this.canOverlap?pe.sortKey:void 0),ui=this.glyphOffsetArray.length,yi=zr.vertexLength,vn=this.allowVerticalPlacement&&ze===i.ah.vertical?Math.PI/2:0,zi=pe.text&&pe.text.sections;for(let un=0;un<F.length;un++){let{tl:Tn,tr:pa,bl:ro,br:Vo,tex:Xa,pixelOffsetTL:sa,pixelOffsetBR:Mo,minFontScaleX:fo,minFontScaleY:lo,glyphOffset:Xn,isSDF:Ro,sectionIndex:uo}=F[un],$o=zr.vertexLength,Ju=Xn[1];Dw(Pr,Ke.x,Ke.y,Tn.x,Ju+Tn.y,Xa.x,Xa.y,W,Ro,sa.x,sa.y,fo,lo),Dw(Pr,Ke.x,Ke.y,pa.x,Ju+pa.y,Xa.x+Xa.w,Xa.y,W,Ro,Mo.x,sa.y,fo,lo),Dw(Pr,Ke.x,Ke.y,ro.x,Ju+ro.y,Xa.x,Xa.y+Xa.h,W,Ro,sa.x,Mo.y,fo,lo),Dw(Pr,Ke.x,Ke.y,Vo.x,Ju+Vo.y,Xa.x+Xa.w,Xa.y+Xa.h,W,Ro,Mo.x,Mo.y,fo,lo),sS(A.dynamicLayoutVertexArray,Ke,vn),mr.emplaceBack($o,$o+1,$o+2),mr.emplaceBack($o+1,$o+2,$o+3),zr.vertexLength+=4,zr.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(Xn[0]),un!==F.length-1&&uo===F[un+1].sectionIndex||A.programConfigurations.populatePaintArrays(Pr.length,pe,pe.index,{},fr,zi&&zi[uo])}A.placedSymbolArray.emplaceBack(Ke.x,Ke.y,ui,this.glyphOffsetArray.length-ui,yi,ct,Lt,Ke.segment,W?W[0]:0,W?W[1]:0,te[0],te[1],ze,0,!1,0,$t)}_addCollisionDebugVertex(A,F,W,te,fe,pe){return F.emplaceBack(0,0),A.emplaceBack(W.x,W.y,te,fe,Math.round(pe.x),Math.round(pe.y))}addCollisionDebugVertices(A,F,W,te,fe,pe,ze){let Ke=fe.segments.prepareSegment(4,fe.layoutVertexArray,fe.indexArray),ct=Ke.vertexLength,Lt=fe.layoutVertexArray,$t=fe.collisionVertexArray,fr=ze.anchorX,mr=ze.anchorY;this._addCollisionDebugVertex(Lt,$t,pe,fr,mr,new u(A,F)),this._addCollisionDebugVertex(Lt,$t,pe,fr,mr,new u(W,F)),this._addCollisionDebugVertex(Lt,$t,pe,fr,mr,new u(W,te)),this._addCollisionDebugVertex(Lt,$t,pe,fr,mr,new u(A,te)),Ke.vertexLength+=4;let Pr=fe.indexArray;Pr.emplaceBack(ct,ct+1),Pr.emplaceBack(ct+1,ct+2),Pr.emplaceBack(ct+2,ct+3),Pr.emplaceBack(ct+3,ct),Ke.primitiveLength+=4}addDebugCollisionBoxes(A,F,W,te){for(let fe=A;fe<F;fe++){let pe=this.collisionBoxArray.get(fe);this.addCollisionDebugVertices(pe.x1,pe.y1,pe.x2,pe.y2,te?this.textCollisionBox:this.iconCollisionBox,pe.anchorPoint,W)}}generateCollisionDebugBuffers(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new um(Al,sy.members,Te),this.iconCollisionBox=new um(Al,sy.members,Te);for(let A=0;A<this.symbolInstances.length;A++){let F=this.symbolInstances.get(A);this.addDebugCollisionBoxes(F.textBoxStartIndex,F.textBoxEndIndex,F,!0),this.addDebugCollisionBoxes(F.verticalTextBoxStartIndex,F.verticalTextBoxEndIndex,F,!0),this.addDebugCollisionBoxes(F.iconBoxStartIndex,F.iconBoxEndIndex,F,!1),this.addDebugCollisionBoxes(F.verticalIconBoxStartIndex,F.verticalIconBoxEndIndex,F,!1)}}_deserializeCollisionBoxesForSymbol(A,F,W,te,fe,pe,ze,Ke,ct){let Lt={};for(let $t=F;$t<W;$t++){let fr=A.get($t);Lt.textBox={x1:fr.x1,y1:fr.y1,x2:fr.x2,y2:fr.y2,anchorPointX:fr.anchorPointX,anchorPointY:fr.anchorPointY},Lt.textFeatureIndex=fr.featureIndex;break}for(let $t=te;$t<fe;$t++){let fr=A.get($t);Lt.verticalTextBox={x1:fr.x1,y1:fr.y1,x2:fr.x2,y2:fr.y2,anchorPointX:fr.anchorPointX,anchorPointY:fr.anchorPointY},Lt.verticalTextFeatureIndex=fr.featureIndex;break}for(let $t=pe;$t<ze;$t++){let fr=A.get($t);Lt.iconBox={x1:fr.x1,y1:fr.y1,x2:fr.x2,y2:fr.y2,anchorPointX:fr.anchorPointX,anchorPointY:fr.anchorPointY},Lt.iconFeatureIndex=fr.featureIndex;break}for(let $t=Ke;$t<ct;$t++){let fr=A.get($t);Lt.verticalIconBox={x1:fr.x1,y1:fr.y1,x2:fr.x2,y2:fr.y2,anchorPointX:fr.anchorPointX,anchorPointY:fr.anchorPointY},Lt.verticalIconFeatureIndex=fr.featureIndex;break}return Lt}deserializeCollisionBoxes(A){this.collisionArrays=[];for(let F=0;F<this.symbolInstances.length;F++){let W=this.symbolInstances.get(F);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(A,W.textBoxStartIndex,W.textBoxEndIndex,W.verticalTextBoxStartIndex,W.verticalTextBoxEndIndex,W.iconBoxStartIndex,W.iconBoxEndIndex,W.verticalIconBoxStartIndex,W.verticalIconBoxEndIndex))}}hasTextData(){return this.text.segments.get().length>0}hasIconData(){return this.icon.segments.get().length>0}hasDebugData(){return this.textCollisionBox&&this.iconCollisionBox}hasTextCollisionBoxData(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0}hasIconCollisionBoxData(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0}addIndicesForPlacedSymbol(A,F){let W=A.placedSymbolArray.get(F),te=W.vertexStartIndex+4*W.numGlyphs;for(let fe=W.vertexStartIndex;fe<te;fe+=4)A.indexArray.emplaceBack(fe,fe+1,fe+2),A.indexArray.emplaceBack(fe+1,fe+2,fe+3)}getSortedSymbolIndexes(A){if(this.sortedAngle===A&&this.symbolInstanceIndexes!==void 0)return this.symbolInstanceIndexes;let F=Math.sin(A),W=Math.cos(A),te=[],fe=[],pe=[];for(let ze=0;ze<this.symbolInstances.length;++ze){pe.push(ze);let Ke=this.symbolInstances.get(ze);te.push(0|Math.round(F*Ke.anchorX+W*Ke.anchorY)),fe.push(Ke.featureIndex)}return pe.sort((ze,Ke)=>te[ze]-te[Ke]||fe[Ke]-fe[ze]),pe}addToSortKeyRanges(A,F){let W=this.sortKeyRanges[this.sortKeyRanges.length-1];W&&W.sortKey===F?W.symbolInstanceEnd=A+1:this.sortKeyRanges.push({sortKey:F,symbolInstanceStart:A,symbolInstanceEnd:A+1})}sortFeatures(A){if(this.sortFeaturesByY&&this.sortedAngle!==A&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(A),this.sortedAngle=A,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(let F of this.symbolInstanceIndexes){let W=this.symbolInstances.get(F);this.featureSortOrder.push(W.featureIndex),[W.rightJustifiedTextSymbolIndex,W.centerJustifiedTextSymbolIndex,W.leftJustifiedTextSymbolIndex].forEach((te,fe,pe)=>{te>=0&&pe.indexOf(te)===fe&&this.addIndicesForPlacedSymbol(this.text,te)}),W.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,W.verticalPlacedTextSymbolIndex),W.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,W.placedIconSymbolIndex),W.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,W.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}}}let Tf,Xx;Fi(\"SymbolBucket\",M1,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),M1.MAX_GLYPHS=65535,M1.addDynamicAttributes=sS;var Fw={get paint(){return Xx=Xx||new ue({\"icon-opacity\":new oo(ce.paint_symbol[\"icon-opacity\"]),\"icon-color\":new oo(ce.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new oo(ce.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new oo(ce.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new oo(ce.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new Ua(ce.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new Ua(ce.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new oo(ce.paint_symbol[\"text-opacity\"]),\"text-color\":new oo(ce.paint_symbol[\"text-color\"],{runtimeType:er,getOverride:R=>R.textColor,hasOverride:R=>!!R.textColor}),\"text-halo-color\":new oo(ce.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new oo(ce.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new oo(ce.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new Ua(ce.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new Ua(ce.paint_symbol[\"text-translate-anchor\"])})},get layout(){return Tf=Tf||new ue({\"symbol-placement\":new Ua(ce.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new Ua(ce.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new Ua(ce.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new oo(ce.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new Ua(ce.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new Ua(ce.layout_symbol[\"icon-allow-overlap\"]),\"icon-overlap\":new Ua(ce.layout_symbol[\"icon-overlap\"]),\"icon-ignore-placement\":new Ua(ce.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new Ua(ce.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new Ua(ce.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new oo(ce.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new Ua(ce.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new Ua(ce.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new oo(ce.layout_symbol[\"icon-image\"]),\"icon-rotate\":new oo(ce.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new oo(ce.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new Ua(ce.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new oo(ce.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new oo(ce.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new Ua(ce.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new Ua(ce.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new Ua(ce.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new oo(ce.layout_symbol[\"text-field\"]),\"text-font\":new oo(ce.layout_symbol[\"text-font\"]),\"text-size\":new oo(ce.layout_symbol[\"text-size\"]),\"text-max-width\":new oo(ce.layout_symbol[\"text-max-width\"]),\"text-line-height\":new Ua(ce.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new oo(ce.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new oo(ce.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new oo(ce.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new Ua(ce.layout_symbol[\"text-variable-anchor\"]),\"text-variable-anchor-offset\":new oo(ce.layout_symbol[\"text-variable-anchor-offset\"]),\"text-anchor\":new oo(ce.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new Ua(ce.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new Ua(ce.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new oo(ce.layout_symbol[\"text-rotate\"]),\"text-padding\":new Ua(ce.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new Ua(ce.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new oo(ce.layout_symbol[\"text-transform\"]),\"text-offset\":new oo(ce.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new Ua(ce.layout_symbol[\"text-allow-overlap\"]),\"text-overlap\":new Ua(ce.layout_symbol[\"text-overlap\"]),\"text-ignore-placement\":new Ua(ce.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new Ua(ce.layout_symbol[\"text-optional\"])})}};class Zx{constructor(A){if(A.property.overrides===void 0)throw new Error(\"overrides must be provided to instantiate FormatSectionOverride class\");this.type=A.property.overrides?A.property.overrides.runtimeType:Vt,this.defaultValue=A}evaluate(A){if(A.formattedSection){let F=this.defaultValue.property.overrides;if(F&&F.hasOverride(A.formattedSection))return F.getOverride(A.formattedSection)}return A.feature&&A.featureState?this.defaultValue.evaluate(A.feature,A.featureState):this.defaultValue.property.specification.default}eachChild(A){this.defaultValue.isConstant()||A(this.defaultValue.value._styleExpression.expression)}outputDefined(){return!1}serialize(){return null}}Fi(\"FormatSectionOverride\",Zx,{omit:[\"defaultValue\"]});class cy extends B{constructor(A){super(A,Fw)}recalculate(A,F){if(super.recalculate(A,F),this.layout.get(\"icon-rotation-alignment\")===\"auto\"&&(this.layout._values[\"icon-rotation-alignment\"]=this.layout.get(\"symbol-placement\")!==\"point\"?\"map\":\"viewport\"),this.layout.get(\"text-rotation-alignment\")===\"auto\"&&(this.layout._values[\"text-rotation-alignment\"]=this.layout.get(\"symbol-placement\")!==\"point\"?\"map\":\"viewport\"),this.layout.get(\"text-pitch-alignment\")===\"auto\"&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")===\"map\"?\"map\":\"viewport\"),this.layout.get(\"icon-pitch-alignment\")===\"auto\"&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),this.layout.get(\"symbol-placement\")===\"point\"){let W=this.layout.get(\"text-writing-mode\");if(W){let te=[];for(let fe of W)te.indexOf(fe)<0&&te.push(fe);this.layout._values[\"text-writing-mode\"]=te}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()}getValueAndResolveTokens(A,F,W,te){let fe=this.layout.get(A).evaluate(F,{},W,te),pe=this._unevaluatedLayout._values[A];return pe.isDataDriven()||Dc(pe.value)||!fe?fe:function(ze,Ke){return Ke.replace(/{([^{}]+)}/g,(ct,Lt)=>ze&&Lt in ze?String(ze[Lt]):\"\")}(F.properties,fe)}createBucket(A){return new M1(A)}queryRadius(){return 0}queryIntersectsFeature(){throw new Error(\"Should take a different path in FeatureIndex\")}_setPaintOverrides(){for(let A of Fw.paint.overridableProperties){if(!cy.hasPaintOverride(this.layout,A))continue;let F=this.paint.get(A),W=new Zx(F),te=new Eu(W,F.property.specification),fe=null;fe=F.value.kind===\"constant\"||F.value.kind===\"source\"?new bc(\"source\",te):new hu(\"composite\",te,F.value.zoomStops),this.paint._values[A]=new xu(F.property,fe,F.parameters)}}_handleOverridablePaintPropertyUpdate(A,F,W){return!(!this.layout||F.isDataDriven()||W.isDataDriven())&&cy.hasPaintOverride(this.layout,A)}static hasPaintOverride(A,F){let W=A.get(\"text-field\"),te=Fw.paint.properties[F],fe=!1,pe=ze=>{for(let Ke of ze)if(te.overrides&&te.overrides.hasOverride(Ke))return void(fe=!0)};if(W.value.kind===\"constant\"&&W.value.value instanceof ri)pe(W.value.value.sections);else if(W.value.kind===\"source\"){let ze=ct=>{fe||(ct instanceof ua&&Sn(ct.value)===ti?pe(ct.value.sections):ct instanceof Zl?pe(ct.sections):ct.eachChild(ze))},Ke=W.value;Ke._styleExpression&&ze(Ke._styleExpression.expression)}return fe}}let MC;var Yx={get paint(){return MC=MC||new ue({\"background-color\":new Ua(ce.paint_background[\"background-color\"]),\"background-pattern\":new hc(ce.paint_background[\"background-pattern\"]),\"background-opacity\":new Ua(ce.paint_background[\"background-opacity\"])})}};class K9 extends B{constructor(A){super(A,Yx)}}let cS;var EC={get paint(){return cS=cS||new ue({\"raster-opacity\":new Ua(ce.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new Ua(ce.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new Ua(ce.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new Ua(ce.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new Ua(ce.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new Ua(ce.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new Ua(ce.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new Ua(ce.paint_raster[\"raster-fade-duration\"])})}};class Kx extends B{constructor(A){super(A,EC)}}class fS extends B{constructor(A){super(A,{}),this.onAdd=F=>{this.implementation.onAdd&&this.implementation.onAdd(F,F.painter.context.gl)},this.onRemove=F=>{this.implementation.onRemove&&this.implementation.onRemove(F,F.painter.context.gl)},this.implementation=A}is3D(){return this.implementation.renderingMode===\"3d\"}hasOffscreenPass(){return this.implementation.prerender!==void 0}recalculate(){}updateTransitions(){}hasTransition(){return!1}serialize(){throw new Error(\"Custom layers cannot be serialized\")}}class hS{constructor(A){this._methodToThrottle=A,this._triggered=!1,typeof MessageChannel!=\"undefined\"&&(this._channel=new MessageChannel,this._channel.port2.onmessage=()=>{this._triggered=!1,this._methodToThrottle()})}trigger(){this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout(()=>{this._triggered=!1,this._methodToThrottle()},0))}remove(){delete this._channel,this._methodToThrottle=()=>{}}}let dS=63710088e-1;class dg{constructor(A,F){if(isNaN(A)||isNaN(F))throw new Error(`Invalid LngLat object: (${A}, ${F})`);if(this.lng=+A,this.lat=+F,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")}wrap(){return new dg(S(this.lng,-180,180),this.lat)}toArray(){return[this.lng,this.lat]}toString(){return`LngLat(${this.lng}, ${this.lat})`}distanceTo(A){let F=Math.PI/180,W=this.lat*F,te=A.lat*F,fe=Math.sin(W)*Math.sin(te)+Math.cos(W)*Math.cos(te)*Math.cos((A.lng-this.lng)*F);return dS*Math.acos(Math.min(fe,1))}static convert(A){if(A instanceof dg)return A;if(Array.isArray(A)&&(A.length===2||A.length===3))return new dg(Number(A[0]),Number(A[1]));if(!Array.isArray(A)&&typeof A==\"object\"&&A!==null)return new dg(Number(\"lng\"in A?A.lng:A.lon),Number(A.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")}}let E1=2*Math.PI*dS;function kC(R){return E1*Math.cos(R*Math.PI/180)}function zw(R){return(180+R)/360}function CC(R){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+R*Math.PI/360)))/360}function Ow(R,A){return R/kC(A)}function Jx(R){return 360/Math.PI*Math.atan(Math.exp((180-360*R)*Math.PI/180))-90}class $x{constructor(A,F,W=0){this.x=+A,this.y=+F,this.z=+W}static fromLngLat(A,F=0){let W=dg.convert(A);return new $x(zw(W.lng),CC(W.lat),Ow(F,W.lat))}toLngLat(){return new dg(360*this.x-180,Jx(this.y))}toAltitude(){return this.z*kC(Jx(this.y))}meterInMercatorCoordinateUnits(){return 1/E1*(A=Jx(this.y),1/Math.cos(A*Math.PI/180));var A}}function mp(R,A,F){var W=2*Math.PI*6378137/256/Math.pow(2,F);return[R*W-2*Math.PI*6378137/2,A*W-2*Math.PI*6378137/2]}class vS{constructor(A,F,W){if(!function(te,fe,pe){return!(te<0||te>25||pe<0||pe>=Math.pow(2,te)||fe<0||fe>=Math.pow(2,te))}(A,F,W))throw new Error(`x=${F}, y=${W}, z=${A} outside of bounds. 0<=x<${Math.pow(2,A)}, 0<=y<${Math.pow(2,A)} 0<=z<=25 `);this.z=A,this.x=F,this.y=W,this.key=Qx(0,A,A,F,W)}equals(A){return this.z===A.z&&this.x===A.x&&this.y===A.y}url(A,F,W){let te=(pe=this.y,ze=this.z,Ke=mp(256*(fe=this.x),256*(pe=Math.pow(2,ze)-pe-1),ze),ct=mp(256*(fe+1),256*(pe+1),ze),Ke[0]+\",\"+Ke[1]+\",\"+ct[0]+\",\"+ct[1]);var fe,pe,ze,Ke,ct;let Lt=function($t,fr,mr){let Pr,zr=\"\";for(let ui=$t;ui>0;ui--)Pr=1<<ui-1,zr+=(fr&Pr?1:0)+(mr&Pr?2:0);return zr}(this.z,this.x,this.y);return A[(this.x+this.y)%A.length].replace(/{prefix}/g,(this.x%16).toString(16)+(this.y%16).toString(16)).replace(/{z}/g,String(this.z)).replace(/{x}/g,String(this.x)).replace(/{y}/g,String(W===\"tms\"?Math.pow(2,this.z)-this.y-1:this.y)).replace(/{ratio}/g,F>1?\"@2x\":\"\").replace(/{quadkey}/g,Lt).replace(/{bbox-epsg-3857}/g,te)}isChildOf(A){let F=this.z-A.z;return F>0&&A.x===this.x>>F&&A.y===this.y>>F}getTilePoint(A){let F=Math.pow(2,this.z);return new u((A.x*F-this.x)*Ha,(A.y*F-this.y)*Ha)}toString(){return`${this.z}/${this.x}/${this.y}`}}class LC{constructor(A,F){this.wrap=A,this.canonical=F,this.key=Qx(A,F.z,F.z,F.x,F.y)}}class $v{constructor(A,F,W,te,fe){if(A<W)throw new Error(`overscaledZ should be >= z; overscaledZ = ${A}; z = ${W}`);this.overscaledZ=A,this.wrap=F,this.canonical=new vS(W,+te,+fe),this.key=Qx(F,A,W,te,fe)}clone(){return new $v(this.overscaledZ,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)}equals(A){return this.overscaledZ===A.overscaledZ&&this.wrap===A.wrap&&this.canonical.equals(A.canonical)}scaledTo(A){if(A>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${A}; overscaledZ = ${this.overscaledZ}`);let F=this.canonical.z-A;return A>this.canonical.z?new $v(A,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new $v(A,this.wrap,A,this.canonical.x>>F,this.canonical.y>>F)}calculateScaledKey(A,F){if(A>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${A}; overscaledZ = ${this.overscaledZ}`);let W=this.canonical.z-A;return A>this.canonical.z?Qx(this.wrap*+F,A,this.canonical.z,this.canonical.x,this.canonical.y):Qx(this.wrap*+F,A,A,this.canonical.x>>W,this.canonical.y>>W)}isChildOf(A){if(A.wrap!==this.wrap)return!1;let F=this.canonical.z-A.canonical.z;return A.overscaledZ===0||A.overscaledZ<this.overscaledZ&&A.canonical.x===this.canonical.x>>F&&A.canonical.y===this.canonical.y>>F}children(A){if(this.overscaledZ>=A)return[new $v(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];let F=this.canonical.z+1,W=2*this.canonical.x,te=2*this.canonical.y;return[new $v(F,this.wrap,F,W,te),new $v(F,this.wrap,F,W+1,te),new $v(F,this.wrap,F,W,te+1),new $v(F,this.wrap,F,W+1,te+1)]}isLessThan(A){return this.wrap<A.wrap||!(this.wrap>A.wrap)&&(this.overscaledZ<A.overscaledZ||!(this.overscaledZ>A.overscaledZ)&&(this.canonical.x<A.canonical.x||!(this.canonical.x>A.canonical.x)&&this.canonical.y<A.canonical.y))}wrapped(){return new $v(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)}unwrapTo(A){return new $v(this.overscaledZ,A,this.canonical.z,this.canonical.x,this.canonical.y)}overscaleFactor(){return Math.pow(2,this.overscaledZ-this.canonical.z)}toUnwrapped(){return new LC(this.wrap,this.canonical)}toString(){return`${this.overscaledZ}/${this.canonical.x}/${this.canonical.y}`}getTilePoint(A){return this.canonical.getTilePoint(new $x(A.x-this.wrap,A.y))}}function Qx(R,A,F,W,te){(R*=2)<0&&(R=-1*R-1);let fe=1<<F;return(fe*fe*R+fe*te+W).toString(36)+F.toString(36)+A.toString(36)}Fi(\"CanonicalTileID\",vS),Fi(\"OverscaledTileID\",$v,{omit:[\"posMatrix\"]});class PC{constructor(A,F,W,te=1,fe=1,pe=1,ze=0){if(this.uid=A,F.height!==F.width)throw new RangeError(\"DEM tiles must be square\");if(W&&![\"mapbox\",\"terrarium\",\"custom\"].includes(W))return void T(`\"${W}\" is not a valid encoding type. Valid types include \"mapbox\", \"terrarium\" and \"custom\".`);this.stride=F.height;let Ke=this.dim=F.height-2;switch(this.data=new Uint32Array(F.data.buffer),W){case\"terrarium\":this.redFactor=256,this.greenFactor=1,this.blueFactor=1/256,this.baseShift=32768;break;case\"custom\":this.redFactor=te,this.greenFactor=fe,this.blueFactor=pe,this.baseShift=ze;break;default:this.redFactor=6553.6,this.greenFactor=25.6,this.blueFactor=.1,this.baseShift=1e4}for(let ct=0;ct<Ke;ct++)this.data[this._idx(-1,ct)]=this.data[this._idx(0,ct)],this.data[this._idx(Ke,ct)]=this.data[this._idx(Ke-1,ct)],this.data[this._idx(ct,-1)]=this.data[this._idx(ct,0)],this.data[this._idx(ct,Ke)]=this.data[this._idx(ct,Ke-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(Ke,-1)]=this.data[this._idx(Ke-1,0)],this.data[this._idx(-1,Ke)]=this.data[this._idx(0,Ke-1)],this.data[this._idx(Ke,Ke)]=this.data[this._idx(Ke-1,Ke-1)],this.min=Number.MAX_SAFE_INTEGER,this.max=Number.MIN_SAFE_INTEGER;for(let ct=0;ct<Ke;ct++)for(let Lt=0;Lt<Ke;Lt++){let $t=this.get(ct,Lt);$t>this.max&&(this.max=$t),$t<this.min&&(this.min=$t)}}get(A,F){let W=new Uint8Array(this.data.buffer),te=4*this._idx(A,F);return this.unpack(W[te],W[te+1],W[te+2])}getUnpackVector(){return[this.redFactor,this.greenFactor,this.blueFactor,this.baseShift]}_idx(A,F){if(A<-1||A>=this.dim+1||F<-1||F>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(F+1)*this.stride+(A+1)}unpack(A,F,W){return A*this.redFactor+F*this.greenFactor+W*this.blueFactor-this.baseShift}getPixels(){return new Ki({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))}backfillBorder(A,F,W){if(this.dim!==A.dim)throw new Error(\"dem dimension mismatch\");let te=F*this.dim,fe=F*this.dim+this.dim,pe=W*this.dim,ze=W*this.dim+this.dim;switch(F){case-1:te=fe-1;break;case 1:fe=te+1}switch(W){case-1:pe=ze-1;break;case 1:ze=pe+1}let Ke=-F*this.dim,ct=-W*this.dim;for(let Lt=pe;Lt<ze;Lt++)for(let $t=te;$t<fe;$t++)this.data[this._idx($t,Lt)]=A.data[this._idx($t+Ke,Lt+ct)]}}Fi(\"DEMData\",PC);class IC{constructor(A){this._stringToNumber={},this._numberToString=[];for(let F=0;F<A.length;F++){let W=A[F];this._stringToNumber[W]=F,this._numberToString[F]=W}}encode(A){return this._stringToNumber[A]}decode(A){if(A>=this._numberToString.length)throw new Error(`Out of bounds. Index requested n=${A} can't be >= this._numberToString.length ${this._numberToString.length}`);return this._numberToString[A]}}class pS{constructor(A,F,W,te,fe){this.type=\"Feature\",this._vectorTileFeature=A,A._z=F,A._x=W,A._y=te,this.properties=A.properties,this.id=fe}get geometry(){return this._geometry===void 0&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry}set geometry(A){this._geometry=A}toJSON(){let A={geometry:this.geometry};for(let F in this)F!==\"_geometry\"&&F!==\"_vectorTileFeature\"&&(A[F]=this[F]);return A}}class fy{constructor(A,F){this.tileID=A,this.x=A.canonical.x,this.y=A.canonical.y,this.z=A.canonical.z,this.grid=new Qi(Ha,16,0),this.grid3D=new Qi(Ha,16,0),this.featureIndexArray=new Ts,this.promoteId=F}insert(A,F,W,te,fe,pe){let ze=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(W,te,fe);let Ke=pe?this.grid3D:this.grid;for(let ct=0;ct<F.length;ct++){let Lt=F[ct],$t=[1/0,1/0,-1/0,-1/0];for(let fr=0;fr<Lt.length;fr++){let mr=Lt[fr];$t[0]=Math.min($t[0],mr.x),$t[1]=Math.min($t[1],mr.y),$t[2]=Math.max($t[2],mr.x),$t[3]=Math.max($t[3],mr.y)}$t[0]<Ha&&$t[1]<Ha&&$t[2]>=0&&$t[3]>=0&&Ke.insert(ze,$t[0],$t[1],$t[2],$t[3])}}loadVTLayers(){return this.vtLayers||(this.vtLayers=new br.VectorTile(new iS(this.rawTileData)).layers,this.sourceLayerCoder=new IC(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers}query(A,F,W,te){this.loadVTLayers();let fe=A.params||{},pe=Ha/A.tileSize/A.scale,ze=Fc(fe.filter),Ke=A.queryGeometry,ct=A.queryPadding*pe,Lt=DC(Ke),$t=this.grid.query(Lt.minX-ct,Lt.minY-ct,Lt.maxX+ct,Lt.maxY+ct),fr=DC(A.cameraQueryGeometry),mr=this.grid3D.query(fr.minX-ct,fr.minY-ct,fr.maxX+ct,fr.maxY+ct,(ui,yi,vn,zi)=>function(un,Tn,pa,ro,Vo){for(let sa of un)if(Tn<=sa.x&&pa<=sa.y&&ro>=sa.x&&Vo>=sa.y)return!0;let Xa=[new u(Tn,pa),new u(Tn,Vo),new u(ro,Vo),new u(ro,pa)];if(un.length>2){for(let sa of Xa)if(Ui(un,sa))return!0}for(let sa=0;sa<un.length-1;sa++)if(qi(un[sa],un[sa+1],Xa))return!0;return!1}(A.cameraQueryGeometry,ui-ct,yi-ct,vn+ct,zi+ct));for(let ui of mr)$t.push(ui);$t.sort(J9);let Pr={},zr;for(let ui=0;ui<$t.length;ui++){let yi=$t[ui];if(yi===zr)continue;zr=yi;let vn=this.featureIndexArray.get(yi),zi=null;this.loadMatchingFeature(Pr,vn.bucketIndex,vn.sourceLayerIndex,vn.featureIndex,ze,fe.layers,fe.availableImages,F,W,te,(un,Tn,pa)=>(zi||(zi=$s(un)),Tn.queryIntersectsFeature(Ke,un,pa,zi,this.z,A.transform,pe,A.pixelPosMatrix)))}return Pr}loadMatchingFeature(A,F,W,te,fe,pe,ze,Ke,ct,Lt,$t){let fr=this.bucketLayerIDs[F];if(pe&&!function(ui,yi){for(let vn=0;vn<ui.length;vn++)if(yi.indexOf(ui[vn])>=0)return!0;return!1}(pe,fr))return;let mr=this.sourceLayerCoder.decode(W),Pr=this.vtLayers[mr].feature(te);if(fe.needGeometry){let ui=Sl(Pr,!0);if(!fe.filter(new rs(this.tileID.overscaledZ),ui,this.tileID.canonical))return}else if(!fe.filter(new rs(this.tileID.overscaledZ),Pr))return;let zr=this.getId(Pr,mr);for(let ui=0;ui<fr.length;ui++){let yi=fr[ui];if(pe&&pe.indexOf(yi)<0)continue;let vn=Ke[yi];if(!vn)continue;let zi={};zr&&Lt&&(zi=Lt.getState(vn.sourceLayer||\"_geojsonTileLayer\",zr));let un=L({},ct[yi]);un.paint=RC(un.paint,vn.paint,Pr,zi,ze),un.layout=RC(un.layout,vn.layout,Pr,zi,ze);let Tn=!$t||$t(Pr,vn,zi);if(!Tn)continue;let pa=new pS(Pr,this.z,this.x,this.y,zr);pa.layer=un;let ro=A[yi];ro===void 0&&(ro=A[yi]=[]),ro.push({featureIndex:te,feature:pa,intersectionZ:Tn})}}lookupSymbolFeatures(A,F,W,te,fe,pe,ze,Ke){let ct={};this.loadVTLayers();let Lt=Fc(fe);for(let $t of A)this.loadMatchingFeature(ct,W,te,$t,Lt,pe,ze,Ke,F);return ct}hasLayer(A){for(let F of this.bucketLayerIDs)for(let W of F)if(A===W)return!0;return!1}getId(A,F){let W=A.id;return this.promoteId&&(W=A.properties[typeof this.promoteId==\"string\"?this.promoteId:this.promoteId[F]],typeof W==\"boolean\"&&(W=Number(W))),W}}function 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xe={},ke={featureIndex:Ie,iconDependencies:{},patternDependencies:{},glyphDependencies:{},availableImages:je},vt=Je.familiesBySource[this.source];for(let qn in vt){let Fn=Ge.layers[qn];if(!Fn)continue;Fn.version===1&&i.w(`Vector tile source \"${this.source}\" layer \"${qn}\" does not use vector tile spec v2 and therefore may have some rendering errors.`);let ra=xt.encode(qn),la=[];for(let Ut=0;Ut<Fn.length;Ut++){let wt=Fn.feature(Ut),rr=Ie.getId(wt,qn);la.push({feature:wt,id:rr,index:Ut,sourceLayerIndex:ra})}for(let Ut of vt[qn]){let wt=Ut[0];wt.source!==this.source&&i.w(`layer.source = ${wt.source} does not equal this.source = 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this.status=\"done\",{buckets:Object.values(xe).filter(qn=>!qn.isEmpty()),featureIndex:Ie,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:wi.image,imageAtlas:On,glyphMap:this.returnDependencies?di:null,iconMap:this.returnDependencies?ji:null,glyphPositions:this.returnDependencies?wi.positions:null}})}}function l(dt,Ge,Je){let je=new i.z(Ge);for(let tt of dt)tt.recalculate(je,Je)}class u{constructor(Ge,Je,je){this.actor=Ge,this.layerIndex=Je,this.availableImages=je,this.fetching={},this.loading={},this.loaded={}}loadVectorTile(Ge,Je){return i._(this,void 0,void 0,function*(){let je=yield i.l(Ge.request,Je);try{return{vectorTile:new i.bt.VectorTile(new i.bu(je.data)),rawData:je.data,cacheControl:je.cacheControl,expires:je.expires}}catch(tt){let xt=new Uint8Array(je.data),Ie=`Unable to parse the tile at ${Ge.request.url}, `;throw Ie+=xt[0]===31&&xt[1]===139?\"please make sure the data is not gzipped and that you have configured the relevant header in the server\":`got error: ${tt.message}`,new Error(Ie)}})}loadTile(Ge){return i._(this,void 0,void 0,function*(){let Je=Ge.uid,je=!!(Ge&&Ge.request&&Ge.request.collectResourceTiming)&&new i.bv(Ge.request),tt=new s(Ge);this.loading[Je]=tt;let xt=new AbortController;tt.abort=xt;try{let Ie=yield this.loadVectorTile(Ge,xt);if(delete this.loading[Je],!Ie)return null;let xe=Ie.rawData,ke={};Ie.expires&&(ke.expires=Ie.expires),Ie.cacheControl&&(ke.cacheControl=Ie.cacheControl);let vt={};if(je){let ar=je.finish();ar&&(vt.resourceTiming=JSON.parse(JSON.stringify(ar)))}tt.vectorTile=Ie.vectorTile;let ir=tt.parse(Ie.vectorTile,this.layerIndex,this.availableImages,this.actor);this.loaded[Je]=tt,this.fetching[Je]={rawTileData:xe,cacheControl:ke,resourceTiming:vt};try{let ar=yield ir;return i.e({rawTileData:xe.slice(0)},ar,ke,vt)}finally{delete this.fetching[Je]}}catch(Ie){throw delete this.loading[Je],tt.status=\"done\",this.loaded[Je]=tt,Ie}})}reloadTile(Ge){return i._(this,void 0,void 0,function*(){let Je=Ge.uid;if(!this.loaded||!this.loaded[Je])throw new Error(\"Should not be trying to reload a tile that was never loaded or has been removed\");let je=this.loaded[Je];if(je.showCollisionBoxes=Ge.showCollisionBoxes,je.status===\"parsing\"){let tt=yield je.parse(je.vectorTile,this.layerIndex,this.availableImages,this.actor),xt;if(this.fetching[Je]){let{rawTileData:Ie,cacheControl:xe,resourceTiming:ke}=this.fetching[Je];delete this.fetching[Je],xt=i.e({rawTileData:Ie.slice(0)},tt,xe,ke)}else xt=tt;return xt}if(je.status===\"done\"&&je.vectorTile)return je.parse(je.vectorTile,this.layerIndex,this.availableImages,this.actor)})}abortTile(Ge){return i._(this,void 0,void 0,function*(){let Je=this.loading,je=Ge.uid;Je&&Je[je]&&Je[je].abort&&(Je[je].abort.abort(),delete Je[je])})}removeTile(Ge){return i._(this,void 0,void 0,function*(){this.loaded&&this.loaded[Ge.uid]&&delete this.loaded[Ge.uid]})}}class c{constructor(){this.loaded={}}loadTile(Ge){return i._(this,void 0,void 0,function*(){let{uid:Je,encoding:je,rawImageData:tt,redFactor:xt,greenFactor:Ie,blueFactor:xe,baseShift:ke}=Ge,vt=tt.width+2,ir=tt.height+2,ar=i.b(tt)?new i.R({width:vt,height:ir},yield i.bw(tt,-1,-1,vt,ir)):tt,vr=new i.bx(Je,ar,je,xt,Ie,xe,ke);return this.loaded=this.loaded||{},this.loaded[Je]=vr,vr})}removeTile(Ge){let Je=this.loaded,je=Ge.uid;Je&&Je[je]&&delete Je[je]}}function f(dt,Ge){if(dt.length!==0){h(dt[0],Ge);for(var Je=1;Je<dt.length;Je++)h(dt[Je],!Ge)}}function h(dt,Ge){for(var Je=0,je=0,tt=0,xt=dt.length,Ie=xt-1;tt<xt;Ie=tt++){var xe=(dt[tt][0]-dt[Ie][0])*(dt[Ie][1]+dt[tt][1]),ke=Je+xe;je+=Math.abs(Je)>=Math.abs(xe)?Je-ke+xe:xe-ke+Je,Je=ke}Je+je>=0!=!!Ge&&dt.reverse()}var d=i.by(function dt(Ge,Je){var je,tt=Ge&&Ge.type;if(tt===\"FeatureCollection\")for(je=0;je<Ge.features.length;je++)dt(Ge.features[je],Je);else if(tt===\"GeometryCollection\")for(je=0;je<Ge.geometries.length;je++)dt(Ge.geometries[je],Je);else if(tt===\"Feature\")dt(Ge.geometry,Je);else if(tt===\"Polygon\")f(Ge.coordinates,Je);else if(tt===\"MultiPolygon\")for(je=0;je<Ge.coordinates.length;je++)f(Ge.coordinates[je],Je);return Ge});let v=i.bt.VectorTileFeature.prototype.toGeoJSON;var _={exports:{}},b=i.bz,p=i.bt.VectorTileFeature,k=E;function E(dt,Ge){this.options=Ge||{},this.features=dt,this.length=dt.length}function S(dt,Ge){this.id=typeof dt.id==\"number\"?dt.id:void 0,this.type=dt.type,this.rawGeometry=dt.type===1?[dt.geometry]:dt.geometry,this.properties=dt.tags,this.extent=Ge||4096}E.prototype.feature=function(dt){return new S(this.features[dt],this.options.extent)},S.prototype.loadGeometry=function(){var dt=this.rawGeometry;this.geometry=[];for(var Ge=0;Ge<dt.length;Ge++){for(var Je=dt[Ge],je=[],tt=0;tt<Je.length;tt++)je.push(new b(Je[tt][0],Je[tt][1]));this.geometry.push(je)}return this.geometry},S.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var dt=this.geometry,Ge=1/0,Je=-1/0,je=1/0,tt=-1/0,xt=0;xt<dt.length;xt++)for(var Ie=dt[xt],xe=0;xe<Ie.length;xe++){var ke=Ie[xe];Ge=Math.min(Ge,ke.x),Je=Math.max(Je,ke.x),je=Math.min(je,ke.y),tt=Math.max(tt,ke.y)}return[Ge,je,Je,tt]},S.prototype.toGeoJSON=p.prototype.toGeoJSON;var L=i.bA,x=k;function C(dt){var Ge=new L;return function(Je,je){for(var tt in Je.layers)je.writeMessage(3,M,Je.layers[tt])}(dt,Ge),Ge.finish()}function M(dt,Ge){var Je;Ge.writeVarintField(15,dt.version||1),Ge.writeStringField(1,dt.name||\"\"),Ge.writeVarintField(5,dt.extent||4096);var je={keys:[],values:[],keycache:{},valuecache:{}};for(Je=0;Je<dt.length;Je++)je.feature=dt.feature(Je),Ge.writeMessage(2,g,je);var tt=je.keys;for(Je=0;Je<tt.length;Je++)Ge.writeStringField(3,tt[Je]);var xt=je.values;for(Je=0;Je<xt.length;Je++)Ge.writeMessage(4,V,xt[Je])}function g(dt,Ge){var Je=dt.feature;Je.id!==void 0&&Ge.writeVarintField(1,Je.id),Ge.writeMessage(2,P,dt),Ge.writeVarintField(3,Je.type),Ge.writeMessage(4,O,Je)}function P(dt,Ge){var Je=dt.feature,je=dt.keys,tt=dt.values,xt=dt.keycache,Ie=dt.valuecache;for(var xe in Je.properties){var ke=Je.properties[xe],vt=xt[xe];if(ke!==null){vt===void 0&&(je.push(xe),xt[xe]=vt=je.length-1),Ge.writeVarint(vt);var ir=typeof ke;ir!==\"string\"&&ir!==\"boolean\"&&ir!==\"number\"&&(ke=JSON.stringify(ke));var ar=ir+\":\"+ke,vr=Ie[ar];vr===void 0&&(tt.push(ke),Ie[ar]=vr=tt.length-1),Ge.writeVarint(vr)}}}function T(dt,Ge){return(Ge<<3)+(7&dt)}function z(dt){return dt<<1^dt>>31}function O(dt,Ge){for(var Je=dt.loadGeometry(),je=dt.type,tt=0,xt=0,Ie=Je.length,xe=0;xe<Ie;xe++){var ke=Je[xe],vt=1;je===1&&(vt=ke.length),Ge.writeVarint(T(1,vt));for(var ir=je===3?ke.length-1:ke.length,ar=0;ar<ir;ar++){ar===1&&je!==1&&Ge.writeVarint(T(2,ir-1));var vr=ke[ar].x-tt,ii=ke[ar].y-xt;Ge.writeVarint(z(vr)),Ge.writeVarint(z(ii)),tt+=vr,xt+=ii}je===3&&Ge.writeVarint(T(7,1))}}function V(dt,Ge){var Je=typeof dt;Je===\"string\"?Ge.writeStringField(1,dt):Je===\"boolean\"?Ge.writeBooleanField(7,dt):Je===\"number\"&&(dt%1!=0?Ge.writeDoubleField(3,dt):dt<0?Ge.writeSVarintField(6,dt):Ge.writeVarintField(5,dt))}_.exports=C,_.exports.fromVectorTileJs=C,_.exports.fromGeojsonVt=function(dt,Ge){Ge=Ge||{};var Je={};for(var je in dt)Je[je]=new x(dt[je].features,Ge),Je[je].name=je,Je[je].version=Ge.version,Je[je].extent=Ge.extent;return C({layers:Je})},_.exports.GeoJSONWrapper=x;var G=i.by(_.exports);let Z={minZoom:0,maxZoom:16,minPoints:2,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:dt=>dt},H=Math.fround||(N=new Float32Array(1),dt=>(N[0]=+dt,N[0]));var N;let j=3,re=5,oe=6;class _e{constructor(Ge){this.options=Object.assign(Object.create(Z),Ge),this.trees=new Array(this.options.maxZoom+1),this.stride=this.options.reduce?7:6,this.clusterProps=[]}load(Ge){let{log:Je,minZoom:je,maxZoom:tt}=this.options;Je&&console.time(\"total time\");let xt=`prepare ${Ge.length} points`;Je&&console.time(xt),this.points=Ge;let Ie=[];for(let ke=0;ke<Ge.length;ke++){let vt=Ge[ke];if(!vt.geometry)continue;let[ir,ar]=vt.geometry.coordinates,vr=H(me(ir)),ii=H(ie(ar));Ie.push(vr,ii,1/0,ke,-1,1),this.options.reduce&&Ie.push(0)}let xe=this.trees[tt+1]=this._createTree(Ie);Je&&console.timeEnd(xt);for(let ke=tt;ke>=je;ke--){let vt=+Date.now();xe=this.trees[ke]=this._createTree(this._cluster(xe,ke)),Je&&console.log(\"z%d: %d clusters in %dms\",ke,xe.numItems,+Date.now()-vt)}return Je&&console.timeEnd(\"total time\"),this}getClusters(Ge,Je){let je=((Ge[0]+180)%360+360)%360-180,tt=Math.max(-90,Math.min(90,Ge[1])),xt=Ge[2]===180?180:((Ge[2]+180)%360+360)%360-180,Ie=Math.max(-90,Math.min(90,Ge[3]));if(Ge[2]-Ge[0]>=360)je=-180,xt=180;else if(je>xt){let ar=this.getClusters([je,tt,180,Ie],Je),vr=this.getClusters([-180,tt,xt,Ie],Je);return ar.concat(vr)}let xe=this.trees[this._limitZoom(Je)],ke=xe.range(me(je),ie(Ie),me(xt),ie(tt)),vt=xe.data,ir=[];for(let ar of ke){let vr=this.stride*ar;ir.push(vt[vr+re]>1?Ee(vt,vr,this.clusterProps):this.points[vt[vr+j]])}return ir}getChildren(Ge){let Je=this._getOriginId(Ge),je=this._getOriginZoom(Ge),tt=\"No cluster with the specified id.\",xt=this.trees[je];if(!xt)throw new Error(tt);let Ie=xt.data;if(Je*this.stride>=Ie.length)throw new Error(tt);let xe=this.options.radius/(this.options.extent*Math.pow(2,je-1)),ke=xt.within(Ie[Je*this.stride],Ie[Je*this.stride+1],xe),vt=[];for(let ir of ke){let ar=ir*this.stride;Ie[ar+4]===Ge&&vt.push(Ie[ar+re]>1?Ee(Ie,ar,this.clusterProps):this.points[Ie[ar+j]])}if(vt.length===0)throw new Error(tt);return vt}getLeaves(Ge,Je,je){let tt=[];return this._appendLeaves(tt,Ge,Je=Je||10,je=je||0,0),tt}getTile(Ge,Je,je){let tt=this.trees[this._limitZoom(Ge)],xt=Math.pow(2,Ge),{extent:Ie,radius:xe}=this.options,ke=xe/Ie,vt=(je-ke)/xt,ir=(je+1+ke)/xt,ar={features:[]};return this._addTileFeatures(tt.range((Je-ke)/xt,vt,(Je+1+ke)/xt,ir),tt.data,Je,je,xt,ar),Je===0&&this._addTileFeatures(tt.range(1-ke/xt,vt,1,ir),tt.data,xt,je,xt,ar),Je===xt-1&&this._addTileFeatures(tt.range(0,vt,ke/xt,ir),tt.data,-1,je,xt,ar),ar.features.length?ar:null}getClusterExpansionZoom(Ge){let Je=this._getOriginZoom(Ge)-1;for(;Je<=this.options.maxZoom;){let je=this.getChildren(Ge);if(Je++,je.length!==1)break;Ge=je[0].properties.cluster_id}return Je}_appendLeaves(Ge,Je,je,tt,xt){let Ie=this.getChildren(Je);for(let xe of Ie){let ke=xe.properties;if(ke&&ke.cluster?xt+ke.point_count<=tt?xt+=ke.point_count:xt=this._appendLeaves(Ge,ke.cluster_id,je,tt,xt):xt<tt?xt++:Ge.push(xe),Ge.length===je)break}return xt}_createTree(Ge){let Je=new i.av(Ge.length/this.stride|0,this.options.nodeSize,Float32Array);for(let je=0;je<Ge.length;je+=this.stride)Je.add(Ge[je],Ge[je+1]);return Je.finish(),Je.data=Ge,Je}_addTileFeatures(Ge,Je,je,tt,xt,Ie){for(let xe of Ge){let ke=xe*this.stride,vt=Je[ke+re]>1,ir,ar,vr;if(vt)ir=Ce(Je,ke,this.clusterProps),ar=Je[ke],vr=Je[ke+1];else{let $r=this.points[Je[ke+j]];ir=$r.properties;let[di,ji]=$r.geometry.coordinates;ar=me(di),vr=ie(ji)}let ii={type:1,geometry:[[Math.round(this.options.extent*(ar*xt-je)),Math.round(this.options.extent*(vr*xt-tt))]],tags:ir},pi;pi=vt||this.options.generateId?Je[ke+j]:this.points[Je[ke+j]].id,pi!==void 0&&(ii.id=pi),Ie.features.push(ii)}}_limitZoom(Ge){return Math.max(this.options.minZoom,Math.min(Math.floor(+Ge),this.options.maxZoom+1))}_cluster(Ge,Je){let{radius:je,extent:tt,reduce:xt,minPoints:Ie}=this.options,xe=je/(tt*Math.pow(2,Je)),ke=Ge.data,vt=[],ir=this.stride;for(let ar=0;ar<ke.length;ar+=ir){if(ke[ar+2]<=Je)continue;ke[ar+2]=Je;let vr=ke[ar],ii=ke[ar+1],pi=Ge.within(ke[ar],ke[ar+1],xe),$r=ke[ar+re],di=$r;for(let ji of pi){let In=ji*ir;ke[In+2]>Je&&(di+=ke[In+re])}if(di>$r&&di>=Ie){let ji,In=vr*$r,wi=ii*$r,On=-1,qn=((ar/ir|0)<<5)+(Je+1)+this.points.length;for(let Fn of pi){let ra=Fn*ir;if(ke[ra+2]<=Je)continue;ke[ra+2]=Je;let la=ke[ra+re];In+=ke[ra]*la,wi+=ke[ra+1]*la,ke[ra+4]=qn,xt&&(ji||(ji=this._map(ke,ar,!0),On=this.clusterProps.length,this.clusterProps.push(ji)),xt(ji,this._map(ke,ra)))}ke[ar+4]=qn,vt.push(In/di,wi/di,1/0,qn,-1,di),xt&&vt.push(On)}else{for(let ji=0;ji<ir;ji++)vt.push(ke[ar+ji]);if(di>1)for(let ji of pi){let In=ji*ir;if(!(ke[In+2]<=Je)){ke[In+2]=Je;for(let wi=0;wi<ir;wi++)vt.push(ke[In+wi])}}}}return vt}_getOriginId(Ge){return Ge-this.points.length>>5}_getOriginZoom(Ge){return(Ge-this.points.length)%32}_map(Ge,Je,je){if(Ge[Je+re]>1){let Ie=this.clusterProps[Ge[Je+oe]];return je?Object.assign({},Ie):Ie}let tt=this.points[Ge[Je+j]].properties,xt=this.options.map(tt);return je&&xt===tt?Object.assign({},xt):xt}}function Ee(dt,Ge,Je){return{type:\"Feature\",id:dt[Ge+j],properties:Ce(dt,Ge,Je),geometry:{type:\"Point\",coordinates:[(je=dt[Ge],360*(je-.5)),Se(dt[Ge+1])]}};var je}function Ce(dt,Ge,Je){let je=dt[Ge+re],tt=je>=1e4?`${Math.round(je/1e3)}k`:je>=1e3?Math.round(je/100)/10+\"k\":je,xt=dt[Ge+oe],Ie=xt===-1?{}:Object.assign({},Je[xt]);return Object.assign(Ie,{cluster:!0,cluster_id:dt[Ge+j],point_count:je,point_count_abbreviated:tt})}function me(dt){return dt/360+.5}function ie(dt){let Ge=Math.sin(dt*Math.PI/180),Je=.5-.25*Math.log((1+Ge)/(1-Ge))/Math.PI;return Je<0?0:Je>1?1:Je}function Se(dt){let Ge=(180-360*dt)*Math.PI/180;return 360*Math.atan(Math.exp(Ge))/Math.PI-90}function Le(dt,Ge,Je,je){let tt=je,xt=Ge+(Je-Ge>>1),Ie,xe=Je-Ge,ke=dt[Ge],vt=dt[Ge+1],ir=dt[Je],ar=dt[Je+1];for(let vr=Ge+3;vr<Je;vr+=3){let ii=Ae(dt[vr],dt[vr+1],ke,vt,ir,ar);if(ii>tt)Ie=vr,tt=ii;else if(ii===tt){let pi=Math.abs(vr-xt);pi<xe&&(Ie=vr,xe=pi)}}tt>je&&(Ie-Ge>3&&Le(dt,Ge,Ie,je),dt[Ie+2]=tt,Je-Ie>3&&Le(dt,Ie,Je,je))}function Ae(dt,Ge,Je,je,tt,xt){let Ie=tt-Je,xe=xt-je;if(Ie!==0||xe!==0){let ke=((dt-Je)*Ie+(Ge-je)*xe)/(Ie*Ie+xe*xe);ke>1?(Je=tt,je=xt):ke>0&&(Je+=Ie*ke,je+=xe*ke)}return Ie=dt-Je,xe=Ge-je,Ie*Ie+xe*xe}function Fe(dt,Ge,Je,je){let tt={id:dt==null?null:dt,type:Ge,geometry:Je,tags:je,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};if(Ge===\"Point\"||Ge===\"MultiPoint\"||Ge===\"LineString\")Pe(tt,Je);else if(Ge===\"Polygon\")Pe(tt,Je[0]);else if(Ge===\"MultiLineString\")for(let xt of Je)Pe(tt,xt);else if(Ge===\"MultiPolygon\")for(let xt of Je)Pe(tt,xt[0]);return tt}function Pe(dt,Ge){for(let Je=0;Je<Ge.length;Je+=3)dt.minX=Math.min(dt.minX,Ge[Je]),dt.minY=Math.min(dt.minY,Ge[Je+1]),dt.maxX=Math.max(dt.maxX,Ge[Je]),dt.maxY=Math.max(dt.maxY,Ge[Je+1])}function ge(dt,Ge,Je,je){if(!Ge.geometry)return;let tt=Ge.geometry.coordinates;if(tt&&tt.length===0)return;let xt=Ge.geometry.type,Ie=Math.pow(Je.tolerance/((1<<Je.maxZoom)*Je.extent),2),xe=[],ke=Ge.id;if(Je.promoteId?ke=Ge.properties[Je.promoteId]:Je.generateId&&(ke=je||0),xt===\"Point\")Re(tt,xe);else if(xt===\"MultiPoint\")for(let vt of tt)Re(vt,xe);else if(xt===\"LineString\")ce(tt,xe,Ie,!1);else if(xt===\"MultiLineString\"){if(Je.lineMetrics){for(let vt of tt)xe=[],ce(vt,xe,Ie,!1),dt.push(Fe(ke,\"LineString\",xe,Ge.properties));return}Ze(tt,xe,Ie,!1)}else if(xt===\"Polygon\")Ze(tt,xe,Ie,!0);else{if(xt!==\"MultiPolygon\"){if(xt===\"GeometryCollection\"){for(let vt of Ge.geometry.geometries)ge(dt,{id:ke,geometry:vt,properties:Ge.properties},Je,je);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(let vt of tt){let ir=[];Ze(vt,ir,Ie,!0),xe.push(ir)}}dt.push(Fe(ke,xt,xe,Ge.properties))}function Re(dt,Ge){Ge.push(ut(dt[0]),pt(dt[1]),0)}function ce(dt,Ge,Je,je){let tt,xt,Ie=0;for(let ke=0;ke<dt.length;ke++){let vt=ut(dt[ke][0]),ir=pt(dt[ke][1]);Ge.push(vt,ir,0),ke>0&&(Ie+=je?(tt*ir-vt*xt)/2:Math.sqrt(Math.pow(vt-tt,2)+Math.pow(ir-xt,2))),tt=vt,xt=ir}let xe=Ge.length-3;Ge[2]=1,Le(Ge,0,xe,Je),Ge[xe+2]=1,Ge.size=Math.abs(Ie),Ge.start=0,Ge.end=Ge.size}function Ze(dt,Ge,Je,je){for(let tt=0;tt<dt.length;tt++){let xt=[];ce(dt[tt],xt,Je,je),Ge.push(xt)}}function ut(dt){return dt/360+.5}function pt(dt){let Ge=Math.sin(dt*Math.PI/180),Je=.5-.25*Math.log((1+Ge)/(1-Ge))/Math.PI;return Je<0?0:Je>1?1:Je}function Zt(dt,Ge,Je,je,tt,xt,Ie,xe){if(je/=Ge,xt>=(Je/=Ge)&&Ie<je)return dt;if(Ie<Je||xt>=je)return null;let ke=[];for(let vt of dt){let ir=vt.geometry,ar=vt.type,vr=tt===0?vt.minX:vt.minY,ii=tt===0?vt.maxX:vt.maxY;if(vr>=Je&&ii<je){ke.push(vt);continue}if(ii<Je||vr>=je)continue;let pi=[];if(ar===\"Point\"||ar===\"MultiPoint\")st(ir,pi,Je,je,tt);else if(ar===\"LineString\")lt(ir,pi,Je,je,tt,!1,xe.lineMetrics);else if(ar===\"MultiLineString\")Nt(ir,pi,Je,je,tt,!1);else if(ar===\"Polygon\")Nt(ir,pi,Je,je,tt,!0);else if(ar===\"MultiPolygon\")for(let $r of ir){let di=[];Nt($r,di,Je,je,tt,!0),di.length&&pi.push(di)}if(pi.length){if(xe.lineMetrics&&ar===\"LineString\"){for(let $r of pi)ke.push(Fe(vt.id,ar,$r,vt.tags));continue}ar!==\"LineString\"&&ar!==\"MultiLineString\"||(pi.length===1?(ar=\"LineString\",pi=pi[0]):ar=\"MultiLineString\"),ar!==\"Point\"&&ar!==\"MultiPoint\"||(ar=pi.length===3?\"Point\":\"MultiPoint\"),ke.push(Fe(vt.id,ar,pi,vt.tags))}}return ke.length?ke:null}function st(dt,Ge,Je,je,tt){for(let xt=0;xt<dt.length;xt+=3){let Ie=dt[xt+tt];Ie>=Je&&Ie<=je&&Jt(Ge,dt[xt],dt[xt+1],dt[xt+2])}}function lt(dt,Ge,Je,je,tt,xt,Ie){let xe=Gt(dt),ke=tt===0?sr:wr,vt,ir,ar=dt.start;for(let di=0;di<dt.length-3;di+=3){let ji=dt[di],In=dt[di+1],wi=dt[di+2],On=dt[di+3],qn=dt[di+4],Fn=tt===0?ji:In,ra=tt===0?On:qn,la=!1;Ie&&(vt=Math.sqrt(Math.pow(ji-On,2)+Math.pow(In-qn,2))),Fn<Je?ra>Je&&(ir=ke(xe,ji,In,On,qn,Je),Ie&&(xe.start=ar+vt*ir)):Fn>je?ra<je&&(ir=ke(xe,ji,In,On,qn,je),Ie&&(xe.start=ar+vt*ir)):Jt(xe,ji,In,wi),ra<Je&&Fn>=Je&&(ir=ke(xe,ji,In,On,qn,Je),la=!0),ra>je&&Fn<=je&&(ir=ke(xe,ji,In,On,qn,je),la=!0),!xt&&la&&(Ie&&(xe.end=ar+vt*ir),Ge.push(xe),xe=Gt(dt)),Ie&&(ar+=vt)}let vr=dt.length-3,ii=dt[vr],pi=dt[vr+1],$r=tt===0?ii:pi;$r>=Je&&$r<=je&&Jt(xe,ii,pi,dt[vr+2]),vr=xe.length-3,xt&&vr>=3&&(xe[vr]!==xe[0]||xe[vr+1]!==xe[1])&&Jt(xe,xe[0],xe[1],xe[2]),xe.length&&Ge.push(xe)}function Gt(dt){let Ge=[];return Ge.size=dt.size,Ge.start=dt.start,Ge.end=dt.end,Ge}function Nt(dt,Ge,Je,je,tt,xt){for(let Ie of dt)lt(Ie,Ge,Je,je,tt,xt,!1)}function Jt(dt,Ge,Je,je){dt.push(Ge,Je,je)}function sr(dt,Ge,Je,je,tt,xt){let Ie=(xt-Ge)/(je-Ge);return Jt(dt,xt,Je+(tt-Je)*Ie,1),Ie}function wr(dt,Ge,Je,je,tt,xt){let Ie=(xt-Je)/(tt-Je);return Jt(dt,Ge+(je-Ge)*Ie,xt,1),Ie}function cr(dt,Ge){let Je=[];for(let je=0;je<dt.length;je++){let tt=dt[je],xt=tt.type,Ie;if(xt===\"Point\"||xt===\"MultiPoint\"||xt===\"LineString\")Ie=$e(tt.geometry,Ge);else if(xt===\"MultiLineString\"||xt===\"Polygon\"){Ie=[];for(let xe of tt.geometry)Ie.push($e(xe,Ge))}else if(xt===\"MultiPolygon\"){Ie=[];for(let xe of tt.geometry){let ke=[];for(let vt of xe)ke.push($e(vt,Ge));Ie.push(ke)}}Je.push(Fe(tt.id,xt,Ie,tt.tags))}return Je}function $e(dt,Ge){let Je=[];Je.size=dt.size,dt.start!==void 0&&(Je.start=dt.start,Je.end=dt.end);for(let je=0;je<dt.length;je+=3)Je.push(dt[je]+Ge,dt[je+1],dt[je+2]);return Je}function St(dt,Ge){if(dt.transformed)return dt;let Je=1<<dt.z,je=dt.x,tt=dt.y;for(let xt of dt.features){let Ie=xt.geometry,xe=xt.type;if(xt.geometry=[],xe===1)for(let ke=0;ke<Ie.length;ke+=2)xt.geometry.push(Qt(Ie[ke],Ie[ke+1],Ge,Je,je,tt));else for(let ke=0;ke<Ie.length;ke++){let vt=[];for(let ir=0;ir<Ie[ke].length;ir+=2)vt.push(Qt(Ie[ke][ir],Ie[ke][ir+1],Ge,Je,je,tt));xt.geometry.push(vt)}}return dt.transformed=!0,dt}function Qt(dt,Ge,Je,je,tt,xt){return[Math.round(Je*(dt*je-tt)),Math.round(Je*(Ge*je-xt))]}function Vt(dt,Ge,Je,je,tt){let xt=Ge===tt.maxZoom?0:tt.tolerance/((1<<Ge)*tt.extent),Ie={features:[],numPoints:0,numSimplified:0,numFeatures:dt.length,source:null,x:Je,y:je,z:Ge,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0};for(let xe of dt)_t(Ie,xe,xt,tt);return Ie}function _t(dt,Ge,Je,je){let tt=Ge.geometry,xt=Ge.type,Ie=[];if(dt.minX=Math.min(dt.minX,Ge.minX),dt.minY=Math.min(dt.minY,Ge.minY),dt.maxX=Math.max(dt.maxX,Ge.maxX),dt.maxY=Math.max(dt.maxY,Ge.maxY),xt===\"Point\"||xt===\"MultiPoint\")for(let xe=0;xe<tt.length;xe+=3)Ie.push(tt[xe],tt[xe+1]),dt.numPoints++,dt.numSimplified++;else if(xt===\"LineString\")It(Ie,tt,dt,Je,!1,!1);else if(xt===\"MultiLineString\"||xt===\"Polygon\")for(let xe=0;xe<tt.length;xe++)It(Ie,tt[xe],dt,Je,xt===\"Polygon\",xe===0);else if(xt===\"MultiPolygon\")for(let xe=0;xe<tt.length;xe++){let ke=tt[xe];for(let vt=0;vt<ke.length;vt++)It(Ie,ke[vt],dt,Je,!0,vt===0)}if(Ie.length){let xe=Ge.tags||null;if(xt===\"LineString\"&&je.lineMetrics){xe={};for(let vt in Ge.tags)xe[vt]=Ge.tags[vt];xe.mapbox_clip_start=tt.start/tt.size,xe.mapbox_clip_end=tt.end/tt.size}let ke={geometry:Ie,type:xt===\"Polygon\"||xt===\"MultiPolygon\"?3:xt===\"LineString\"||xt===\"MultiLineString\"?2:1,tags:xe};Ge.id!==null&&(ke.id=Ge.id),dt.features.push(ke)}}function It(dt,Ge,Je,je,tt,xt){let Ie=je*je;if(je>0&&Ge.size<(tt?Ie:je))return void(Je.numPoints+=Ge.length/3);let xe=[];for(let ke=0;ke<Ge.length;ke+=3)(je===0||Ge[ke+2]>Ie)&&(Je.numSimplified++,xe.push(Ge[ke],Ge[ke+1])),Je.numPoints++;tt&&function(ke,vt){let ir=0;for(let ar=0,vr=ke.length,ii=vr-2;ar<vr;ii=ar,ar+=2)ir+=(ke[ar]-ke[ii])*(ke[ar+1]+ke[ii+1]);if(ir>0===vt)for(let ar=0,vr=ke.length;ar<vr/2;ar+=2){let ii=ke[ar],pi=ke[ar+1];ke[ar]=ke[vr-2-ar],ke[ar+1]=ke[vr-1-ar],ke[vr-2-ar]=ii,ke[vr-1-ar]=pi}}(xe,xt),dt.push(xe)}let mt={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0};class er{constructor(Ge,Je){let je=(Je=this.options=function(xt,Ie){for(let xe in Ie)xt[xe]=Ie[xe];return xt}(Object.create(mt),Je)).debug;if(je&&console.time(\"preprocess data\"),Je.maxZoom<0||Je.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(Je.promoteId&&Je.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");let tt=function(xt,Ie){let xe=[];if(xt.type===\"FeatureCollection\")for(let ke=0;ke<xt.features.length;ke++)ge(xe,xt.features[ke],Ie,ke);else ge(xe,xt.type===\"Feature\"?xt:{geometry:xt},Ie);return xe}(Ge,Je);this.tiles={},this.tileCoords=[],je&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",Je.indexMaxZoom,Je.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),tt=function(xt,Ie){let xe=Ie.buffer/Ie.extent,ke=xt,vt=Zt(xt,1,-1-xe,xe,0,-1,2,Ie),ir=Zt(xt,1,1-xe,2+xe,0,-1,2,Ie);return(vt||ir)&&(ke=Zt(xt,1,-xe,1+xe,0,-1,2,Ie)||[],vt&&(ke=cr(vt,1).concat(ke)),ir&&(ke=ke.concat(cr(ir,-1)))),ke}(tt,Je),tt.length&&this.splitTile(tt,0,0,0),je&&(tt.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}splitTile(Ge,Je,je,tt,xt,Ie,xe){let ke=[Ge,Je,je,tt],vt=this.options,ir=vt.debug;for(;ke.length;){tt=ke.pop(),je=ke.pop(),Je=ke.pop(),Ge=ke.pop();let ar=1<<Je,vr=lr(Je,je,tt),ii=this.tiles[vr];if(!ii&&(ir>1&&console.time(\"creation\"),ii=this.tiles[vr]=Vt(Ge,Je,je,tt,vt),this.tileCoords.push({z:Je,x:je,y:tt}),ir)){ir>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",Je,je,tt,ii.numFeatures,ii.numPoints,ii.numSimplified),console.timeEnd(\"creation\"));let la=`z${Je}`;this.stats[la]=(this.stats[la]||0)+1,this.total++}if(ii.source=Ge,xt==null){if(Je===vt.indexMaxZoom||ii.numPoints<=vt.indexMaxPoints)continue}else{if(Je===vt.maxZoom||Je===xt)continue;if(xt!=null){let la=xt-Je;if(je!==Ie>>la||tt!==xe>>la)continue}}if(ii.source=null,Ge.length===0)continue;ir>1&&console.time(\"clipping\");let pi=.5*vt.buffer/vt.extent,$r=.5-pi,di=.5+pi,ji=1+pi,In=null,wi=null,On=null,qn=null,Fn=Zt(Ge,ar,je-pi,je+di,0,ii.minX,ii.maxX,vt),ra=Zt(Ge,ar,je+$r,je+ji,0,ii.minX,ii.maxX,vt);Ge=null,Fn&&(In=Zt(Fn,ar,tt-pi,tt+di,1,ii.minY,ii.maxY,vt),wi=Zt(Fn,ar,tt+$r,tt+ji,1,ii.minY,ii.maxY,vt),Fn=null),ra&&(On=Zt(ra,ar,tt-pi,tt+di,1,ii.minY,ii.maxY,vt),qn=Zt(ra,ar,tt+$r,tt+ji,1,ii.minY,ii.maxY,vt),ra=null),ir>1&&console.timeEnd(\"clipping\"),ke.push(In||[],Je+1,2*je,2*tt),ke.push(wi||[],Je+1,2*je,2*tt+1),ke.push(On||[],Je+1,2*je+1,2*tt),ke.push(qn||[],Je+1,2*je+1,2*tt+1)}}getTile(Ge,Je,je){Ge=+Ge,Je=+Je,je=+je;let tt=this.options,{extent:xt,debug:Ie}=tt;if(Ge<0||Ge>24)return null;let xe=1<<Ge,ke=lr(Ge,Je=Je+xe&xe-1,je);if(this.tiles[ke])return St(this.tiles[ke],xt);Ie>1&&console.log(\"drilling down to z%d-%d-%d\",Ge,Je,je);let vt,ir=Ge,ar=Je,vr=je;for(;!vt&&ir>0;)ir--,ar>>=1,vr>>=1,vt=this.tiles[lr(ir,ar,vr)];return vt&&vt.source?(Ie>1&&(console.log(\"found parent tile z%d-%d-%d\",ir,ar,vr),console.time(\"drilling down\")),this.splitTile(vt.source,ir,ar,vr,Ge,Je,je),Ie>1&&console.timeEnd(\"drilling down\"),this.tiles[ke]?St(this.tiles[ke],xt):null):null}}function lr(dt,Ge,Je){return 32*((1<<dt)*Je+Ge)+dt}function Tr(dt,Ge){return Ge?dt.properties[Ge]:dt.id}function Lr(dt,Ge){if(dt==null)return!0;if(dt.type===\"Feature\")return Tr(dt,Ge)!=null;if(dt.type===\"FeatureCollection\"){let Je=new Set;for(let je of dt.features){let tt=Tr(je,Ge);if(tt==null||Je.has(tt))return!1;Je.add(tt)}return!0}return!1}function ti(dt,Ge){let Je=new Map;if(dt!=null)if(dt.type===\"Feature\")Je.set(Tr(dt,Ge),dt);else for(let je of dt.features)Je.set(Tr(je,Ge),je);return Je}class Br extends u{constructor(){super(...arguments),this._dataUpdateable=new Map}loadVectorTile(Ge,Je){return i._(this,void 0,void 0,function*(){let je=Ge.tileID.canonical;if(!this._geoJSONIndex)throw new Error(\"Unable to parse the data into a cluster or geojson\");let tt=this._geoJSONIndex.getTile(je.z,je.x,je.y);if(!tt)return null;let xt=new class{constructor(xe){this.layers={_geojsonTileLayer:this},this.name=\"_geojsonTileLayer\",this.extent=i.X,this.length=xe.length,this._features=xe}feature(xe){return new class{constructor(ke){this._feature=ke,this.extent=i.X,this.type=ke.type,this.properties=ke.tags,\"id\"in ke&&!isNaN(ke.id)&&(this.id=parseInt(ke.id,10))}loadGeometry(){if(this._feature.type===1){let ke=[];for(let vt of this._feature.geometry)ke.push([new i.P(vt[0],vt[1])]);return ke}{let ke=[];for(let vt of this._feature.geometry){let ir=[];for(let ar of vt)ir.push(new i.P(ar[0],ar[1]));ke.push(ir)}return ke}}toGeoJSON(ke,vt,ir){return v.call(this,ke,vt,ir)}}(this._features[xe])}}(tt.features),Ie=G(xt);return Ie.byteOffset===0&&Ie.byteLength===Ie.buffer.byteLength||(Ie=new Uint8Array(Ie)),{vectorTile:xt,rawData:Ie.buffer}})}loadData(Ge){return i._(this,void 0,void 0,function*(){var Je;(Je=this._pendingRequest)===null||Je===void 0||Je.abort();let je=!!(Ge&&Ge.request&&Ge.request.collectResourceTiming)&&new i.bv(Ge.request);this._pendingRequest=new AbortController;try{this._pendingData=this.loadAndProcessGeoJSON(Ge,this._pendingRequest),this._geoJSONIndex=Ge.cluster?new _e(function({superclusterOptions:Ie,clusterProperties:xe}){if(!xe||!Ie)return Ie;let ke={},vt={},ir={accumulated:null,zoom:0},ar={properties:null},vr=Object.keys(xe);for(let ii of vr){let[pi,$r]=xe[ii],di=i.bC($r),ji=i.bC(typeof pi==\"string\"?[pi,[\"accumulated\"],[\"get\",ii]]:pi);ke[ii]=di.value,vt[ii]=ji.value}return Ie.map=ii=>{ar.properties=ii;let pi={};for(let $r of vr)pi[$r]=ke[$r].evaluate(ir,ar);return pi},Ie.reduce=(ii,pi)=>{ar.properties=pi;for(let $r of vr)ir.accumulated=ii[$r],ii[$r]=vt[$r].evaluate(ir,ar)},Ie}(Ge)).load((yield this._pendingData).features):(tt=yield this._pendingData,new er(tt,Ge.geojsonVtOptions)),this.loaded={};let xt={};if(je){let Ie=je.finish();Ie&&(xt.resourceTiming={},xt.resourceTiming[Ge.source]=JSON.parse(JSON.stringify(Ie)))}return xt}catch(xt){if(delete this._pendingRequest,i.bB(xt))return{abandoned:!0};throw xt}var tt})}getData(){return i._(this,void 0,void 0,function*(){return this._pendingData})}reloadTile(Ge){let Je=this.loaded;return Je&&Je[Ge.uid]?super.reloadTile(Ge):this.loadTile(Ge)}loadAndProcessGeoJSON(Ge,Je){return i._(this,void 0,void 0,function*(){let je=yield this.loadGeoJSON(Ge,Je);if(delete this._pendingRequest,typeof je!=\"object\")throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`);if(d(je,!0),Ge.filter){let tt=i.bC(Ge.filter,{type:\"boolean\",\"property-type\":\"data-driven\",overridable:!1,transition:!1});if(tt.result===\"error\")throw new Error(tt.value.map(Ie=>`${Ie.key}: ${Ie.message}`).join(\", \"));je={type:\"FeatureCollection\",features:je.features.filter(Ie=>tt.value.evaluate({zoom:0},Ie))}}return je})}loadGeoJSON(Ge,Je){return i._(this,void 0,void 0,function*(){let{promoteId:je}=Ge;if(Ge.request){let tt=yield i.h(Ge.request,Je);return this._dataUpdateable=Lr(tt.data,je)?ti(tt.data,je):void 0,tt.data}if(typeof Ge.data==\"string\")try{let tt=JSON.parse(Ge.data);return this._dataUpdateable=Lr(tt,je)?ti(tt,je):void 0,tt}catch(tt){throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`)}if(!Ge.dataDiff)throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`);if(!this._dataUpdateable)throw new Error(`Cannot update existing geojson data in ${Ge.source}`);return function(tt,xt,Ie){var xe,ke,vt,ir;if(xt.removeAll&&tt.clear(),xt.remove)for(let ar of xt.remove)tt.delete(ar);if(xt.add)for(let ar of xt.add){let vr=Tr(ar,Ie);vr!=null&&tt.set(vr,ar)}if(xt.update)for(let ar of xt.update){let vr=tt.get(ar.id);if(vr==null)continue;let ii=!ar.removeAllProperties&&(((xe=ar.removeProperties)===null||xe===void 0?void 0:xe.length)>0||((ke=ar.addOrUpdateProperties)===null||ke===void 0?void 0:ke.length)>0);if((ar.newGeometry||ar.removeAllProperties||ii)&&(vr=Object.assign({},vr),tt.set(ar.id,vr),ii&&(vr.properties=Object.assign({},vr.properties))),ar.newGeometry&&(vr.geometry=ar.newGeometry),ar.removeAllProperties)vr.properties={};else if(((vt=ar.removeProperties)===null||vt===void 0?void 0:vt.length)>0)for(let pi of ar.removeProperties)Object.prototype.hasOwnProperty.call(vr.properties,pi)&&delete vr.properties[pi];if(((ir=ar.addOrUpdateProperties)===null||ir===void 0?void 0:ir.length)>0)for(let{key:pi,value:$r}of ar.addOrUpdateProperties)vr.properties[pi]=$r}}(this._dataUpdateable,Ge.dataDiff,je),{type:\"FeatureCollection\",features:Array.from(this._dataUpdateable.values())}})}removeSource(Ge){return i._(this,void 0,void 0,function*(){this._pendingRequest&&this._pendingRequest.abort()})}getClusterExpansionZoom(Ge){return this._geoJSONIndex.getClusterExpansionZoom(Ge.clusterId)}getClusterChildren(Ge){return this._geoJSONIndex.getChildren(Ge.clusterId)}getClusterLeaves(Ge){return this._geoJSONIndex.getLeaves(Ge.clusterId,Ge.limit,Ge.offset)}}class Vr{constructor(Ge){this.self=Ge,this.actor=new i.F(Ge),this.layerIndexes={},this.availableImages={},this.workerSources={},this.demWorkerSources={},this.externalWorkerSourceTypes={},this.self.registerWorkerSource=(Je,je)=>{if(this.externalWorkerSourceTypes[Je])throw new Error(`Worker source with name \"${Je}\" already registered.`);this.externalWorkerSourceTypes[Je]=je},this.self.addProtocol=i.bi,this.self.removeProtocol=i.bj,this.self.registerRTLTextPlugin=Je=>{if(i.bD.isParsed())throw new Error(\"RTL text plugin already registered.\");i.bD.setMethods(Je)},this.actor.registerMessageHandler(\"LDT\",(Je,je)=>this._getDEMWorkerSource(Je,je.source).loadTile(je)),this.actor.registerMessageHandler(\"RDT\",(Je,je)=>i._(this,void 0,void 0,function*(){this._getDEMWorkerSource(Je,je.source).removeTile(je)})),this.actor.registerMessageHandler(\"GCEZ\",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterExpansionZoom(je)})),this.actor.registerMessageHandler(\"GCC\",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterChildren(je)})),this.actor.registerMessageHandler(\"GCL\",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterLeaves(je)})),this.actor.registerMessageHandler(\"LD\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).loadData(je)),this.actor.registerMessageHandler(\"GD\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).getData()),this.actor.registerMessageHandler(\"LT\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).loadTile(je)),this.actor.registerMessageHandler(\"RT\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).reloadTile(je)),this.actor.registerMessageHandler(\"AT\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).abortTile(je)),this.actor.registerMessageHandler(\"RMT\",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).removeTile(je)),this.actor.registerMessageHandler(\"RS\",(Je,je)=>i._(this,void 0,void 0,function*(){if(!this.workerSources[Je]||!this.workerSources[Je][je.type]||!this.workerSources[Je][je.type][je.source])return;let tt=this.workerSources[Je][je.type][je.source];delete this.workerSources[Je][je.type][je.source],tt.removeSource!==void 0&&tt.removeSource(je)})),this.actor.registerMessageHandler(\"RM\",Je=>i._(this,void 0,void 0,function*(){delete this.layerIndexes[Je],delete this.availableImages[Je],delete this.workerSources[Je],delete this.demWorkerSources[Je]})),this.actor.registerMessageHandler(\"SR\",(Je,je)=>i._(this,void 0,void 0,function*(){this.referrer=je})),this.actor.registerMessageHandler(\"SRPS\",(Je,je)=>this._syncRTLPluginState(Je,je)),this.actor.registerMessageHandler(\"IS\",(Je,je)=>i._(this,void 0,void 0,function*(){this.self.importScripts(je)})),this.actor.registerMessageHandler(\"SI\",(Je,je)=>this._setImages(Je,je)),this.actor.registerMessageHandler(\"UL\",(Je,je)=>i._(this,void 0,void 0,function*(){this._getLayerIndex(Je).update(je.layers,je.removedIds)})),this.actor.registerMessageHandler(\"SL\",(Je,je)=>i._(this,void 0,void 0,function*(){this._getLayerIndex(Je).replace(je)}))}_setImages(Ge,Je){return i._(this,void 0,void 0,function*(){this.availableImages[Ge]=Je;for(let je in this.workerSources[Ge]){let tt=this.workerSources[Ge][je];for(let xt in tt)tt[xt].availableImages=Je}})}_syncRTLPluginState(Ge,Je){return i._(this,void 0,void 0,function*(){if(i.bD.isParsed())return i.bD.getState();if(Je.pluginStatus!==\"loading\")return i.bD.setState(Je),Je;let je=Je.pluginURL;if(this.self.importScripts(je),i.bD.isParsed()){let tt={pluginStatus:\"loaded\",pluginURL:je};return i.bD.setState(tt),tt}throw i.bD.setState({pluginStatus:\"error\",pluginURL:\"\"}),new Error(`RTL Text Plugin failed to import scripts from ${je}`)})}_getAvailableImages(Ge){let Je=this.availableImages[Ge];return Je||(Je=[]),Je}_getLayerIndex(Ge){let Je=this.layerIndexes[Ge];return Je||(Je=this.layerIndexes[Ge]=new a),Je}_getWorkerSource(Ge,Je,je){if(this.workerSources[Ge]||(this.workerSources[Ge]={}),this.workerSources[Ge][Je]||(this.workerSources[Ge][Je]={}),!this.workerSources[Ge][Je][je]){let tt={sendAsync:(xt,Ie)=>(xt.targetMapId=Ge,this.actor.sendAsync(xt,Ie))};switch(Je){case\"vector\":this.workerSources[Ge][Je][je]=new u(tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge));break;case\"geojson\":this.workerSources[Ge][Je][je]=new Br(tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge));break;default:this.workerSources[Ge][Je][je]=new this.externalWorkerSourceTypes[Je](tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge))}}return this.workerSources[Ge][Je][je]}_getDEMWorkerSource(Ge,Je){return this.demWorkerSources[Ge]||(this.demWorkerSources[Ge]={}),this.demWorkerSources[Ge][Je]||(this.demWorkerSources[Ge][Je]=new c),this.demWorkerSources[Ge][Je]}}return i.i(self)&&(self.worker=new Vr(self)),Vr}),r(\"index\",[\"exports\",\"./shared\"],function(i,a){\"use strict\";var o=\"4.7.1\";let s,l,u={now:typeof performance!=\"undefined\"&&performance&&performance.now?performance.now.bind(performance):Date.now.bind(Date),frameAsync:ue=>new Promise((w,B)=>{let 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0&&(ee.className=B),Q&&Q.appendChild(ee),ee}static createNS(w,B){return window.document.createElementNS(w,B)}static disableDrag(){c.docStyle&&c.selectProp&&(c.userSelect=c.docStyle[c.selectProp],c.docStyle[c.selectProp]=\"none\")}static enableDrag(){c.docStyle&&c.selectProp&&(c.docStyle[c.selectProp]=c.userSelect)}static setTransform(w,B){w.style[c.transformProp]=B}static addEventListener(w,B,Q,ee={}){w.addEventListener(B,Q,\"passive\"in ee?ee:ee.capture)}static removeEventListener(w,B,Q,ee={}){w.removeEventListener(B,Q,\"passive\"in ee?ee:ee.capture)}static suppressClickInternal(w){w.preventDefault(),w.stopPropagation(),window.removeEventListener(\"click\",c.suppressClickInternal,!0)}static suppressClick(){window.addEventListener(\"click\",c.suppressClickInternal,!0),window.setTimeout(()=>{window.removeEventListener(\"click\",c.suppressClickInternal,!0)},0)}static getScale(w){let B=w.getBoundingClientRect();return{x:B.width/w.offsetWidth||1,y:B.height/w.offsetHeight||1,boundingClientRect:B}}static getPoint(w,B,Q){let ee=B.boundingClientRect;return new a.P((Q.clientX-ee.left)/B.x-w.clientLeft,(Q.clientY-ee.top)/B.y-w.clientTop)}static mousePos(w,B){let Q=c.getScale(w);return c.getPoint(w,Q,B)}static touchPos(w,B){let Q=[],ee=c.getScale(w);for(let le=0;le<B.length;le++)Q.push(c.getPoint(w,ee,B[le]));return Q}static mouseButton(w){return w.button}static remove(w){w.parentNode&&w.parentNode.removeChild(w)}}c.docStyle=typeof window!=\"undefined\"&&window.document&&window.document.documentElement.style,c.selectProp=c.testProp([\"userSelect\",\"MozUserSelect\",\"WebkitUserSelect\",\"msUserSelect\"]),c.transformProp=c.testProp([\"transform\",\"WebkitTransform\"]);let f={supported:!1,testSupport:function(ue){!v&&d&&(_?b(ue):h=ue)}},h,d,v=!1,_=!1;function b(ue){let w=ue.createTexture();ue.bindTexture(ue.TEXTURE_2D,w);try{if(ue.texImage2D(ue.TEXTURE_2D,0,ue.RGBA,ue.RGBA,ue.UNSIGNED_BYTE,d),ue.isContextLost())return;f.supported=!0}catch(B){}ue.deleteTexture(w),v=!0}var p;typeof document!=\"undefined\"&&(d=document.createElement(\"img\"),d.onload=()=>{h&&b(h),h=null,_=!0},d.onerror=()=>{v=!0,h=null},d.src=\"data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA=\"),function(ue){let w,B,Q,ee;ue.resetRequestQueue=()=>{w=[],B=0,Q=0,ee={}},ue.addThrottleControl=ot=>{let Tt=Q++;return ee[Tt]=ot,Tt},ue.removeThrottleControl=ot=>{delete ee[ot],qe()},ue.getImage=(ot,Tt,Yt=!0)=>new Promise((Kt,xr)=>{f.supported&&(ot.headers||(ot.headers={}),ot.headers.accept=\"image/webp,*/*\"),a.e(ot,{type:\"image\"}),w.push({abortController:Tt,requestParameters:ot,supportImageRefresh:Yt,state:\"queued\",onError:Ir=>{xr(Ir)},onSuccess:Ir=>{Kt(Ir)}}),qe()});let le=ot=>a._(this,void 0,void 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Image,Ir=ot.url,ve=ot.credentials;ve&&ve===\"include\"?xr.crossOrigin=\"use-credentials\":(ve&&ve===\"same-origin\"||!a.s(Ir))&&(xr.crossOrigin=\"anonymous\"),Tt.signal.addEventListener(\"abort\",()=>{xr.src=\"\",Kt(a.c())}),xr.fetchPriority=\"high\",xr.onload=()=>{xr.onerror=xr.onload=null,Yt({data:xr})},xr.onerror=()=>{xr.onerror=xr.onload=null,Tt.signal.aborted||Kt(new Error(\"Could not load image. 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Note that SVGs are not supported.\"))},xr.src=Ir})}(p||(p={})),p.resetRequestQueue();class k{constructor(w){this._transformRequestFn=w}transformRequest(w,B){return this._transformRequestFn&&this._transformRequestFn(w,B)||{url:w}}setTransformRequest(w){this._transformRequestFn=w}}function E(ue){var w=new a.A(3);return w[0]=ue[0],w[1]=ue[1],w[2]=ue[2],w}var S,L=function(ue,w,B){return ue[0]=w[0]-B[0],ue[1]=w[1]-B[1],ue[2]=w[2]-B[2],ue};S=new a.A(3),a.A!=Float32Array&&(S[0]=0,S[1]=0,S[2]=0);var x=function(ue){var w=ue[0],B=ue[1];return w*w+B*B};function C(ue){let w=[];if(typeof ue==\"string\")w.push({id:\"default\",url:ue});else if(ue&&ue.length>0){let B=[];for(let{id:Q,url:ee}of ue){let le=`${Q}${ee}`;B.indexOf(le)===-1&&(B.push(le),w.push({id:Q,url:ee}))}}return w}function M(ue,w,B){let Q=ue.split(\"?\");return Q[0]+=`${w}${B}`,Q.join(\"?\")}(function(){var ue=new a.A(2);a.A!=Float32Array&&(ue[0]=0,ue[1]=0)})();class g{constructor(w,B,Q,ee){this.context=w,this.format=Q,this.texture=w.gl.createTexture(),this.update(B,ee)}update(w,B,Q){let{width:ee,height:le}=w,qe=!(this.size&&this.size[0]===ee&&this.size[1]===le||Q),{context:Xe}=this,{gl:ot}=Xe;if(this.useMipmap=!!(B&&B.useMipmap),ot.bindTexture(ot.TEXTURE_2D,this.texture),Xe.pixelStoreUnpackFlipY.set(!1),Xe.pixelStoreUnpack.set(1),Xe.pixelStoreUnpackPremultiplyAlpha.set(this.format===ot.RGBA&&(!B||B.premultiply!==!1)),qe)this.size=[ee,le],w instanceof HTMLImageElement||w instanceof HTMLCanvasElement||w instanceof HTMLVideoElement||w instanceof ImageData||a.b(w)?ot.texImage2D(ot.TEXTURE_2D,0,this.format,this.format,ot.UNSIGNED_BYTE,w):ot.texImage2D(ot.TEXTURE_2D,0,this.format,ee,le,0,this.format,ot.UNSIGNED_BYTE,w.data);else{let{x:Tt,y:Yt}=Q||{x:0,y:0};w instanceof HTMLImageElement||w instanceof HTMLCanvasElement||w instanceof HTMLVideoElement||w instanceof ImageData||a.b(w)?ot.texSubImage2D(ot.TEXTURE_2D,0,Tt,Yt,ot.RGBA,ot.UNSIGNED_BYTE,w):ot.texSubImage2D(ot.TEXTURE_2D,0,Tt,Yt,ee,le,ot.RGBA,ot.UNSIGNED_BYTE,w.data)}this.useMipmap&&this.isSizePowerOfTwo()&&ot.generateMipmap(ot.TEXTURE_2D)}bind(w,B,Q){let{context:ee}=this,{gl:le}=ee;le.bindTexture(le.TEXTURE_2D,this.texture),Q!==le.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(Q=le.LINEAR),w!==this.filter&&(le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MAG_FILTER,w),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MIN_FILTER,Q||w),this.filter=w),B!==this.wrap&&(le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_S,B),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_T,B),this.wrap=B)}isSizePowerOfTwo(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0}destroy(){let{gl:w}=this.context;w.deleteTexture(this.texture),this.texture=null}}function P(ue){let{userImage:w}=ue;return!!(w&&w.render&&w.render())&&(ue.data.replace(new Uint8Array(w.data.buffer)),!0)}class T extends a.E{constructor(){super(),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new a.R({width:1,height:1}),this.dirty=!0}isLoaded(){return this.loaded}setLoaded(w){if(this.loaded!==w&&(this.loaded=w,w)){for(let{ids:B,promiseResolve:Q}of this.requestors)Q(this._getImagesForIds(B));this.requestors=[]}}getImage(w){let B=this.images[w];if(B&&!B.data&&B.spriteData){let Q=B.spriteData;B.data=new a.R({width:Q.width,height:Q.height},Q.context.getImageData(Q.x,Q.y,Q.width,Q.height).data),B.spriteData=null}return B}addImage(w,B){if(this.images[w])throw new Error(`Image id ${w} already exist, use updateImage instead`);this._validate(w,B)&&(this.images[w]=B)}_validate(w,B){let Q=!0,ee=B.data||B.spriteData;return this._validateStretch(B.stretchX,ee&&ee.width)||(this.fire(new a.j(new Error(`Image \"${w}\" has invalid \"stretchX\" value`))),Q=!1),this._validateStretch(B.stretchY,ee&&ee.height)||(this.fire(new a.j(new Error(`Image \"${w}\" has invalid \"stretchY\" value`))),Q=!1),this._validateContent(B.content,B)||(this.fire(new a.j(new Error(`Image \"${w}\" has invalid \"content\" value`))),Q=!1),Q}_validateStretch(w,B){if(!w)return!0;let Q=0;for(let ee of w){if(ee[0]<Q||ee[1]<ee[0]||B<ee[1])return!1;Q=ee[1]}return!0}_validateContent(w,B){if(!w)return!0;if(w.length!==4)return!1;let Q=B.spriteData,ee=Q&&Q.width||B.data.width,le=Q&&Q.height||B.data.height;return!(w[0]<0||ee<w[0]||w[1]<0||le<w[1]||w[2]<0||ee<w[2]||w[3]<0||le<w[3]||w[2]<w[0]||w[3]<w[1])}updateImage(w,B,Q=!0){let ee=this.getImage(w);if(Q&&(ee.data.width!==B.data.width||ee.data.height!==B.data.height))throw new Error(`size mismatch between old image (${ee.data.width}x${ee.data.height}) and new image (${B.data.width}x${B.data.height}).`);B.version=ee.version+1,this.images[w]=B,this.updatedImages[w]=!0}removeImage(w){let B=this.images[w];delete this.images[w],delete this.patterns[w],B.userImage&&B.userImage.onRemove&&B.userImage.onRemove()}listImages(){return Object.keys(this.images)}getImages(w){return new Promise((B,Q)=>{let ee=!0;if(!this.isLoaded())for(let le of w)this.images[le]||(ee=!1);this.isLoaded()||ee?B(this._getImagesForIds(w)):this.requestors.push({ids:w,promiseResolve:B})})}_getImagesForIds(w){let B={};for(let Q of w){let ee=this.getImage(Q);ee||(this.fire(new a.k(\"styleimagemissing\",{id:Q})),ee=this.getImage(Q)),ee?B[Q]={data:ee.data.clone(),pixelRatio:ee.pixelRatio,sdf:ee.sdf,version:ee.version,stretchX:ee.stretchX,stretchY:ee.stretchY,content:ee.content,textFitWidth:ee.textFitWidth,textFitHeight:ee.textFitHeight,hasRenderCallback:!!(ee.userImage&&ee.userImage.render)}:a.w(`Image \"${Q}\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.`)}return B}getPixelSize(){let{width:w,height:B}=this.atlasImage;return{width:w,height:B}}getPattern(w){let B=this.patterns[w],Q=this.getImage(w);if(!Q)return null;if(B&&B.position.version===Q.version)return B.position;if(B)B.position.version=Q.version;else{let ee={w:Q.data.width+2,h:Q.data.height+2,x:0,y:0},le=new a.I(ee,Q);this.patterns[w]={bin:ee,position:le}}return this._updatePatternAtlas(),this.patterns[w].position}bind(w){let B=w.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new g(w,this.atlasImage,B.RGBA),this.atlasTexture.bind(B.LINEAR,B.CLAMP_TO_EDGE)}_updatePatternAtlas(){let w=[];for(let le in this.patterns)w.push(this.patterns[le].bin);let{w:B,h:Q}=a.p(w),ee=this.atlasImage;ee.resize({width:B||1,height:Q||1});for(let le in this.patterns){let{bin:qe}=this.patterns[le],Xe=qe.x+1,ot=qe.y+1,Tt=this.getImage(le).data,Yt=Tt.width,Kt=Tt.height;a.R.copy(Tt,ee,{x:0,y:0},{x:Xe,y:ot},{width:Yt,height:Kt}),a.R.copy(Tt,ee,{x:0,y:Kt-1},{x:Xe,y:ot-1},{width:Yt,height:1}),a.R.copy(Tt,ee,{x:0,y:0},{x:Xe,y:ot+Kt},{width:Yt,height:1}),a.R.copy(Tt,ee,{x:Yt-1,y:0},{x:Xe-1,y:ot},{width:1,height:Kt}),a.R.copy(Tt,ee,{x:0,y:0},{x:Xe+Yt,y:ot},{width:1,height:Kt})}this.dirty=!0}beginFrame(){this.callbackDispatchedThisFrame={}}dispatchRenderCallbacks(w){for(let B of w){if(this.callbackDispatchedThisFrame[B])continue;this.callbackDispatchedThisFrame[B]=!0;let Q=this.getImage(B);Q||a.w(`Image with ID: \"${B}\" was not found`),P(Q)&&this.updateImage(B,Q)}}}let z=1e20;function O(ue,w,B,Q,ee,le,qe,Xe,ot){for(let Tt=w;Tt<w+Q;Tt++)V(ue,B*le+Tt,le,ee,qe,Xe,ot);for(let Tt=B;Tt<B+ee;Tt++)V(ue,Tt*le+w,1,Q,qe,Xe,ot)}function V(ue,w,B,Q,ee,le,qe){le[0]=0,qe[0]=-z,qe[1]=z,ee[0]=ue[w];for(let Xe=1,ot=0,Tt=0;Xe<Q;Xe++){ee[Xe]=ue[w+Xe*B];let Yt=Xe*Xe;do{let Kt=le[ot];Tt=(ee[Xe]-ee[Kt]+Yt-Kt*Kt)/(Xe-Kt)/2}while(Tt<=qe[ot]&&--ot>-1);ot++,le[ot]=Xe,qe[ot]=Tt,qe[ot+1]=z}for(let Xe=0,ot=0;Xe<Q;Xe++){for(;qe[ot+1]<Xe;)ot++;let Tt=le[ot],Yt=Xe-Tt;ue[w+Xe*B]=ee[Tt]+Yt*Yt}}class G{constructor(w,B){this.requestManager=w,this.localIdeographFontFamily=B,this.entries={}}setURL(w){this.url=w}getGlyphs(w){return a._(this,void 0,void 0,function*(){let B=[];for(let le in w)for(let qe of w[le])B.push(this._getAndCacheGlyphsPromise(le,qe));let Q=yield Promise.all(B),ee={};for(let{stack:le,id:qe,glyph:Xe}of Q)ee[le]||(ee[le]={}),ee[le][qe]=Xe&&{id:Xe.id,bitmap:Xe.bitmap.clone(),metrics:Xe.metrics};return ee})}_getAndCacheGlyphsPromise(w,B){return a._(this,void 0,void 0,function*(){let Q=this.entries[w];Q||(Q=this.entries[w]={glyphs:{},requests:{},ranges:{}});let ee=Q.glyphs[B];if(ee!==void 0)return{stack:w,id:B,glyph:ee};if(ee=this._tinySDF(Q,w,B),ee)return Q.glyphs[B]=ee,{stack:w,id:B,glyph:ee};let le=Math.floor(B/256);if(256*le>65535)throw new Error(\"glyphs > 65535 not supported\");if(Q.ranges[le])return{stack:w,id:B,glyph:ee};if(!this.url)throw new Error(\"glyphsUrl is not set\");if(!Q.requests[le]){let Xe=G.loadGlyphRange(w,le,this.url,this.requestManager);Q.requests[le]=Xe}let qe=yield Q.requests[le];for(let Xe in qe)this._doesCharSupportLocalGlyph(+Xe)||(Q.glyphs[+Xe]=qe[+Xe]);return Q.ranges[le]=!0,{stack:w,id:B,glyph:qe[B]||null}})}_doesCharSupportLocalGlyph(w){return!!this.localIdeographFontFamily&&new RegExp(\"\\\\p{Ideo}|\\\\p{sc=Hang}|\\\\p{sc=Hira}|\\\\p{sc=Kana}\",\"u\").test(String.fromCodePoint(w))}_tinySDF(w,B,Q){let ee=this.localIdeographFontFamily;if(!ee||!this._doesCharSupportLocalGlyph(Q))return;let le=w.tinySDF;if(!le){let Xe=\"400\";/bold/i.test(B)?Xe=\"900\":/medium/i.test(B)?Xe=\"500\":/light/i.test(B)&&(Xe=\"200\"),le=w.tinySDF=new G.TinySDF({fontSize:48,buffer:6,radius:16,cutoff:.25,fontFamily:ee,fontWeight:Xe})}let qe=le.draw(String.fromCharCode(Q));return{id:Q,bitmap:new a.o({width:qe.width||60,height:qe.height||60},qe.data),metrics:{width:qe.glyphWidth/2||24,height:qe.glyphHeight/2||24,left:qe.glyphLeft/2+.5||0,top:qe.glyphTop/2-27.5||-8,advance:qe.glyphAdvance/2||24,isDoubleResolution:!0}}}}G.loadGlyphRange=function(ue,w,B,Q){return a._(this,void 0,void 0,function*(){let ee=256*w,le=ee+255,qe=Q.transformRequest(B.replace(\"{fontstack}\",ue).replace(\"{range}\",`${ee}-${le}`),\"Glyphs\"),Xe=yield a.l(qe,new AbortController);if(!Xe||!Xe.data)throw new Error(`Could not load glyph range. range: ${w}, ${ee}-${le}`);let ot={};for(let Tt of a.n(Xe.data))ot[Tt.id]=Tt;return ot})},G.TinySDF=class{constructor({fontSize:ue=24,buffer:w=3,radius:B=8,cutoff:Q=.25,fontFamily:ee=\"sans-serif\",fontWeight:le=\"normal\",fontStyle:qe=\"normal\"}={}){this.buffer=w,this.cutoff=Q,this.radius=B;let Xe=this.size=ue+4*w,ot=this._createCanvas(Xe),Tt=this.ctx=ot.getContext(\"2d\",{willReadFrequently:!0});Tt.font=`${qe} ${le} ${ue}px ${ee}`,Tt.textBaseline=\"alphabetic\",Tt.textAlign=\"left\",Tt.fillStyle=\"black\",this.gridOuter=new Float64Array(Xe*Xe),this.gridInner=new Float64Array(Xe*Xe),this.f=new Float64Array(Xe),this.z=new Float64Array(Xe+1),this.v=new Uint16Array(Xe)}_createCanvas(ue){let w=document.createElement(\"canvas\");return w.width=w.height=ue,w}draw(ue){let{width:w,actualBoundingBoxAscent:B,actualBoundingBoxDescent:Q,actualBoundingBoxLeft:ee,actualBoundingBoxRight:le}=this.ctx.measureText(ue),qe=Math.ceil(B),Xe=Math.max(0,Math.min(this.size-this.buffer,Math.ceil(le-ee))),ot=Math.min(this.size-this.buffer,qe+Math.ceil(Q)),Tt=Xe+2*this.buffer,Yt=ot+2*this.buffer,Kt=Math.max(Tt*Yt,0),xr=new Uint8ClampedArray(Kt),Ir={data:xr,width:Tt,height:Yt,glyphWidth:Xe,glyphHeight:ot,glyphTop:qe,glyphLeft:0,glyphAdvance:w};if(Xe===0||ot===0)return Ir;let{ctx:ve,buffer:be,gridInner:De,gridOuter:Be}=this;ve.clearRect(be,be,Xe,ot),ve.fillText(ue,be,be+qe);let et=ve.getImageData(be,be,Xe,ot);Be.fill(z,0,Kt),De.fill(0,0,Kt);for(let We=0;We<ot;We++)for(let it=0;it<Xe;it++){let Ft=et.data[4*(We*Xe+it)+3]/255;if(Ft===0)continue;let Ht=(We+be)*Tt+it+be;if(Ft===1)Be[Ht]=0,De[Ht]=z;else{let tr=.5-Ft;Be[Ht]=tr>0?tr*tr:0,De[Ht]=tr<0?tr*tr:0}}O(Be,0,0,Tt,Yt,Tt,this.f,this.v,this.z),O(De,be,be,Xe,ot,Tt,this.f,this.v,this.z);for(let We=0;We<Kt;We++){let it=Math.sqrt(Be[We])-Math.sqrt(De[We]);xr[We]=Math.round(255-255*(it/this.radius+this.cutoff))}return Ir}};class Z{constructor(){this.specification=a.v.light.position}possiblyEvaluate(w,B){return a.x(w.expression.evaluate(B))}interpolate(w,B,Q){return{x:a.y.number(w.x,B.x,Q),y:a.y.number(w.y,B.y,Q),z:a.y.number(w.z,B.z,Q)}}}let H;class N extends a.E{constructor(w){super(),H=H||new a.q({anchor:new a.D(a.v.light.anchor),position:new Z,color:new a.D(a.v.light.color),intensity:new a.D(a.v.light.intensity)}),this._transitionable=new a.T(H),this.setLight(w),this._transitioning=this._transitionable.untransitioned()}getLight(){return this._transitionable.serialize()}setLight(w,B={}){if(!this._validate(a.r,w,B))for(let Q in w){let ee=w[Q];Q.endsWith(\"-transition\")?this._transitionable.setTransition(Q.slice(0,-11),ee):this._transitionable.setValue(Q,ee)}}updateTransitions(w){this._transitioning=this._transitionable.transitioned(w,this._transitioning)}hasTransition(){return this._transitioning.hasTransition()}recalculate(w){this.properties=this._transitioning.possiblyEvaluate(w)}_validate(w,B,Q){return(!Q||Q.validate!==!1)&&a.t(this,w.call(a.u,{value:B,style:{glyphs:!0,sprite:!0},styleSpec:a.v}))}}let j=new a.q({\"sky-color\":new a.D(a.v.sky[\"sky-color\"]),\"horizon-color\":new a.D(a.v.sky[\"horizon-color\"]),\"fog-color\":new a.D(a.v.sky[\"fog-color\"]),\"fog-ground-blend\":new a.D(a.v.sky[\"fog-ground-blend\"]),\"horizon-fog-blend\":new a.D(a.v.sky[\"horizon-fog-blend\"]),\"sky-horizon-blend\":new a.D(a.v.sky[\"sky-horizon-blend\"]),\"atmosphere-blend\":new a.D(a.v.sky[\"atmosphere-blend\"])});class re extends a.E{constructor(w){super(),this._transitionable=new a.T(j),this.setSky(w),this._transitioning=this._transitionable.untransitioned(),this.recalculate(new a.z(0))}setSky(w,B={}){if(!this._validate(a.B,w,B)){w||(w={\"sky-color\":\"transparent\",\"horizon-color\":\"transparent\",\"fog-color\":\"transparent\",\"fog-ground-blend\":1,\"atmosphere-blend\":0});for(let Q in w){let ee=w[Q];Q.endsWith(\"-transition\")?this._transitionable.setTransition(Q.slice(0,-11),ee):this._transitionable.setValue(Q,ee)}}}getSky(){return this._transitionable.serialize()}updateTransitions(w){this._transitioning=this._transitionable.transitioned(w,this._transitioning)}hasTransition(){return this._transitioning.hasTransition()}recalculate(w){this.properties=this._transitioning.possiblyEvaluate(w)}_validate(w,B,Q={}){return(Q==null?void 0:Q.validate)!==!1&&a.t(this,w.call(a.u,a.e({value:B,style:{glyphs:!0,sprite:!0},styleSpec:a.v})))}calculateFogBlendOpacity(w){return w<60?0:w<70?(w-60)/10:1}}class oe{constructor(w,B){this.width=w,this.height=B,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}}getDash(w,B){let Q=w.join(\",\")+String(B);return this.dashEntry[Q]||(this.dashEntry[Q]=this.addDash(w,B)),this.dashEntry[Q]}getDashRanges(w,B,Q){let ee=[],le=w.length%2==1?-w[w.length-1]*Q:0,qe=w[0]*Q,Xe=!0;ee.push({left:le,right:qe,isDash:Xe,zeroLength:w[0]===0});let ot=w[0];for(let Tt=1;Tt<w.length;Tt++){Xe=!Xe;let Yt=w[Tt];le=ot*Q,ot+=Yt,qe=ot*Q,ee.push({left:le,right:qe,isDash:Xe,zeroLength:Yt===0})}return ee}addRoundDash(w,B,Q){let ee=B/2;for(let le=-Q;le<=Q;le++){let qe=this.width*(this.nextRow+Q+le),Xe=0,ot=w[Xe];for(let Tt=0;Tt<this.width;Tt++){Tt/ot.right>1&&(ot=w[++Xe]);let Yt=Math.abs(Tt-ot.left),Kt=Math.abs(Tt-ot.right),xr=Math.min(Yt,Kt),Ir,ve=le/Q*(ee+1);if(ot.isDash){let be=ee-Math.abs(ve);Ir=Math.sqrt(xr*xr+be*be)}else Ir=ee-Math.sqrt(xr*xr+ve*ve);this.data[qe+Tt]=Math.max(0,Math.min(255,Ir+128))}}}addRegularDash(w){for(let Xe=w.length-1;Xe>=0;--Xe){let ot=w[Xe],Tt=w[Xe+1];ot.zeroLength?w.splice(Xe,1):Tt&&Tt.isDash===ot.isDash&&(Tt.left=ot.left,w.splice(Xe,1))}let B=w[0],Q=w[w.length-1];B.isDash===Q.isDash&&(B.left=Q.left-this.width,Q.right=B.right+this.width);let ee=this.width*this.nextRow,le=0,qe=w[le];for(let Xe=0;Xe<this.width;Xe++){Xe/qe.right>1&&(qe=w[++le]);let ot=Math.abs(Xe-qe.left),Tt=Math.abs(Xe-qe.right),Yt=Math.min(ot,Tt);this.data[ee+Xe]=Math.max(0,Math.min(255,(qe.isDash?Yt:-Yt)+128))}}addDash(w,B){let Q=B?7:0,ee=2*Q+1;if(this.nextRow+ee>this.height)return a.w(\"LineAtlas out of space\"),null;let le=0;for(let Xe=0;Xe<w.length;Xe++)le+=w[Xe];if(le!==0){let Xe=this.width/le,ot=this.getDashRanges(w,this.width,Xe);B?this.addRoundDash(ot,Xe,Q):this.addRegularDash(ot)}let qe={y:(this.nextRow+Q+.5)/this.height,height:2*Q/this.height,width:le};return this.nextRow+=ee,this.dirty=!0,qe}bind(w){let B=w.gl;this.texture?(B.bindTexture(B.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,B.texSubImage2D(B.TEXTURE_2D,0,0,0,this.width,this.height,B.ALPHA,B.UNSIGNED_BYTE,this.data))):(this.texture=B.createTexture(),B.bindTexture(B.TEXTURE_2D,this.texture),B.texParameteri(B.TEXTURE_2D,B.TEXTURE_WRAP_S,B.REPEAT),B.texParameteri(B.TEXTURE_2D,B.TEXTURE_WRAP_T,B.REPEAT),B.texParameteri(B.TEXTURE_2D,B.TEXTURE_MIN_FILTER,B.LINEAR),B.texParameteri(B.TEXTURE_2D,B.TEXTURE_MAG_FILTER,B.LINEAR),B.texImage2D(B.TEXTURE_2D,0,B.ALPHA,this.width,this.height,0,B.ALPHA,B.UNSIGNED_BYTE,this.data))}}let _e=\"maplibre_preloaded_worker_pool\";class Ee{constructor(){this.active={}}acquire(w){if(!this.workers)for(this.workers=[];this.workers.length<Ee.workerCount;)this.workers.push(new Worker(a.a.WORKER_URL));return this.active[w]=!0,this.workers.slice()}release(w){delete this.active[w],this.numActive()===0&&(this.workers.forEach(B=>{B.terminate()}),this.workers=null)}isPreloaded(){return!!this.active[_e]}numActive(){return Object.keys(this.active).length}}let Ce=Math.floor(u.hardwareConcurrency/2),me,ie;function Se(){return me||(me=new Ee),me}Ee.workerCount=a.C(globalThis)?Math.max(Math.min(Ce,3),1):1;class Le{constructor(w,B){this.workerPool=w,this.actors=[],this.currentActor=0,this.id=B;let Q=this.workerPool.acquire(B);for(let ee=0;ee<Q.length;ee++){let le=new a.F(Q[ee],B);le.name=`Worker ${ee}`,this.actors.push(le)}if(!this.actors.length)throw new Error(\"No actors found\")}broadcast(w,B){let Q=[];for(let ee of this.actors)Q.push(ee.sendAsync({type:w,data:B}));return Promise.all(Q)}getActor(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]}remove(w=!0){this.actors.forEach(B=>{B.remove()}),this.actors=[],w&&this.workerPool.release(this.id)}registerMessageHandler(w,B){for(let Q of this.actors)Q.registerMessageHandler(w,B)}}function Ae(){return ie||(ie=new Le(Se(),a.G),ie.registerMessageHandler(\"GR\",(ue,w,B)=>a.m(w,B))),ie}function Fe(ue,w){let B=a.H();return a.J(B,B,[1,1,0]),a.K(B,B,[.5*ue.width,.5*ue.height,1]),a.L(B,B,ue.calculatePosMatrix(w.toUnwrapped()))}function Pe(ue,w,B,Q,ee,le){let qe=function(Kt,xr,Ir){if(Kt)for(let ve of Kt){let be=xr[ve];if(be&&be.source===Ir&&be.type===\"fill-extrusion\")return!0}else for(let ve in xr){let be=xr[ve];if(be.source===Ir&&be.type===\"fill-extrusion\")return!0}return!1}(ee&&ee.layers,w,ue.id),Xe=le.maxPitchScaleFactor(),ot=ue.tilesIn(Q,Xe,qe);ot.sort(ge);let Tt=[];for(let Kt of ot)Tt.push({wrappedTileID:Kt.tileID.wrapped().key,queryResults:Kt.tile.queryRenderedFeatures(w,B,ue._state,Kt.queryGeometry,Kt.cameraQueryGeometry,Kt.scale,ee,le,Xe,Fe(ue.transform,Kt.tileID))});let Yt=function(Kt){let xr={},Ir={};for(let ve of Kt){let be=ve.queryResults,De=ve.wrappedTileID,Be=Ir[De]=Ir[De]||{};for(let et in be){let We=be[et],it=Be[et]=Be[et]||{},Ft=xr[et]=xr[et]||[];for(let Ht of We)it[Ht.featureIndex]||(it[Ht.featureIndex]=!0,Ft.push(Ht))}}return xr}(Tt);for(let Kt in Yt)Yt[Kt].forEach(xr=>{let Ir=xr.feature,ve=ue.getFeatureState(Ir.layer[\"source-layer\"],Ir.id);Ir.source=Ir.layer.source,Ir.layer[\"source-layer\"]&&(Ir.sourceLayer=Ir.layer[\"source-layer\"]),Ir.state=ve});return Yt}function ge(ue,w){let B=ue.tileID,Q=w.tileID;return B.overscaledZ-Q.overscaledZ||B.canonical.y-Q.canonical.y||B.wrap-Q.wrap||B.canonical.x-Q.canonical.x}function Re(ue,w,B){return a._(this,void 0,void 0,function*(){let Q=ue;if(ue.url?Q=(yield a.h(w.transformRequest(ue.url,\"Source\"),B)).data:yield u.frameAsync(B),!Q)return null;let ee=a.M(a.e(Q,ue),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);return\"vector_layers\"in Q&&Q.vector_layers&&(ee.vectorLayerIds=Q.vector_layers.map(le=>le.id)),ee})}class ce{constructor(w,B){w&&(B?this.setSouthWest(w).setNorthEast(B):Array.isArray(w)&&(w.length===4?this.setSouthWest([w[0],w[1]]).setNorthEast([w[2],w[3]]):this.setSouthWest(w[0]).setNorthEast(w[1])))}setNorthEast(w){return this._ne=w instanceof a.N?new a.N(w.lng,w.lat):a.N.convert(w),this}setSouthWest(w){return this._sw=w instanceof a.N?new a.N(w.lng,w.lat):a.N.convert(w),this}extend(w){let B=this._sw,Q=this._ne,ee,le;if(w instanceof a.N)ee=w,le=w;else{if(!(w instanceof ce))return Array.isArray(w)?w.length===4||w.every(Array.isArray)?this.extend(ce.convert(w)):this.extend(a.N.convert(w)):w&&(\"lng\"in w||\"lon\"in w)&&\"lat\"in w?this.extend(a.N.convert(w)):this;if(ee=w._sw,le=w._ne,!ee||!le)return this}return B||Q?(B.lng=Math.min(ee.lng,B.lng),B.lat=Math.min(ee.lat,B.lat),Q.lng=Math.max(le.lng,Q.lng),Q.lat=Math.max(le.lat,Q.lat)):(this._sw=new a.N(ee.lng,ee.lat),this._ne=new a.N(le.lng,le.lat)),this}getCenter(){return new a.N((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)}getSouthWest(){return this._sw}getNorthEast(){return this._ne}getNorthWest(){return new a.N(this.getWest(),this.getNorth())}getSouthEast(){return new a.N(this.getEast(),this.getSouth())}getWest(){return this._sw.lng}getSouth(){return this._sw.lat}getEast(){return this._ne.lng}getNorth(){return this._ne.lat}toArray(){return[this._sw.toArray(),this._ne.toArray()]}toString(){return`LngLatBounds(${this._sw.toString()}, ${this._ne.toString()})`}isEmpty(){return!(this._sw&&this._ne)}contains(w){let{lng:B,lat:Q}=a.N.convert(w),ee=this._sw.lng<=B&&B<=this._ne.lng;return this._sw.lng>this._ne.lng&&(ee=this._sw.lng>=B&&B>=this._ne.lng),this._sw.lat<=Q&&Q<=this._ne.lat&&ee}static convert(w){return w instanceof ce?w:w&&new ce(w)}static fromLngLat(w,B=0){let Q=360*B/40075017,ee=Q/Math.cos(Math.PI/180*w.lat);return new ce(new a.N(w.lng-ee,w.lat-Q),new a.N(w.lng+ee,w.lat+Q))}adjustAntiMeridian(){let w=new a.N(this._sw.lng,this._sw.lat),B=new a.N(this._ne.lng,this._ne.lat);return new ce(w,w.lng>B.lng?new a.N(B.lng+360,B.lat):B)}}class Ze{constructor(w,B,Q){this.bounds=ce.convert(this.validateBounds(w)),this.minzoom=B||0,this.maxzoom=Q||24}validateBounds(w){return Array.isArray(w)&&w.length===4?[Math.max(-180,w[0]),Math.max(-90,w[1]),Math.min(180,w[2]),Math.min(90,w[3])]:[-180,-90,180,90]}contains(w){let B=Math.pow(2,w.z),Q=Math.floor(a.O(this.bounds.getWest())*B),ee=Math.floor(a.Q(this.bounds.getNorth())*B),le=Math.ceil(a.O(this.bounds.getEast())*B),qe=Math.ceil(a.Q(this.bounds.getSouth())*B);return w.x>=Q&&w.x<le&&w.y>=ee&&w.y<qe}}class ut extends a.E{constructor(w,B,Q,ee){if(super(),this.id=w,this.dispatcher=Q,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,a.e(this,a.M(B,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=a.e({type:\"vector\"},B),this._collectResourceTiming=B.collectResourceTiming,this.tileSize!==512)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(ee)}load(){return a._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new a.k(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=new AbortController;try{let w=yield Re(this._options,this.map._requestManager,this._tileJSONRequest);this._tileJSONRequest=null,this._loaded=!0,this.map.style.sourceCaches[this.id].clearTiles(),w&&(a.e(this,w),w.bounds&&(this.tileBounds=new Ze(w.bounds,this.minzoom,this.maxzoom)),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}catch(w){this._tileJSONRequest=null,this.fire(new a.j(w))}})}loaded(){return this._loaded}hasTile(w){return!this.tileBounds||this.tileBounds.contains(w.canonical)}onAdd(w){this.map=w,this.load()}setSourceProperty(w){this._tileJSONRequest&&this._tileJSONRequest.abort(),w(),this.load()}setTiles(w){return this.setSourceProperty(()=>{this._options.tiles=w}),this}setUrl(w){return this.setSourceProperty(()=>{this.url=w,this._options.url=w}),this}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}serialize(){return a.e({},this._options)}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),Q={request:this.map._requestManager.transformRequest(B,\"Tile\"),uid:w.uid,tileID:w.tileID,zoom:w.tileID.overscaledZ,tileSize:this.tileSize*w.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};Q.request.collectResourceTiming=this._collectResourceTiming;let ee=\"RT\";if(w.actor&&w.state!==\"expired\"){if(w.state===\"loading\")return new Promise((le,qe)=>{w.reloadPromise={resolve:le,reject:qe}})}else w.actor=this.dispatcher.getActor(),ee=\"LT\";w.abortController=new AbortController;try{let le=yield w.actor.sendAsync({type:ee,data:Q},w.abortController);if(delete w.abortController,w.aborted)return;this._afterTileLoadWorkerResponse(w,le)}catch(le){if(delete w.abortController,w.aborted)return;if(le&&le.status!==404)throw le;this._afterTileLoadWorkerResponse(w,null)}})}_afterTileLoadWorkerResponse(w,B){if(B&&B.resourceTiming&&(w.resourceTiming=B.resourceTiming),B&&this.map._refreshExpiredTiles&&w.setExpiryData(B),w.loadVectorData(B,this.map.painter),w.reloadPromise){let Q=w.reloadPromise;w.reloadPromise=null,this.loadTile(w).then(Q.resolve).catch(Q.reject)}}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController),w.actor&&(yield w.actor.sendAsync({type:\"AT\",data:{uid:w.uid,type:this.type,source:this.id}}))})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.unloadVectorData(),w.actor&&(yield w.actor.sendAsync({type:\"RMT\",data:{uid:w.uid,type:this.type,source:this.id}}))})}hasTransition(){return!1}}class pt extends a.E{constructor(w,B,Q,ee){super(),this.id=w,this.dispatcher=Q,this.setEventedParent(ee),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=a.e({type:\"raster\"},B),a.e(this,a.M(B,[\"url\",\"scheme\",\"tileSize\"]))}load(){return a._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new a.k(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=new AbortController;try{let w=yield Re(this._options,this.map._requestManager,this._tileJSONRequest);this._tileJSONRequest=null,this._loaded=!0,w&&(a.e(this,w),w.bounds&&(this.tileBounds=new Ze(w.bounds,this.minzoom,this.maxzoom)),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}catch(w){this._tileJSONRequest=null,this.fire(new a.j(w))}})}loaded(){return this._loaded}onAdd(w){this.map=w,this.load()}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}setSourceProperty(w){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null),w(),this.load()}setTiles(w){return this.setSourceProperty(()=>{this._options.tiles=w}),this}setUrl(w){return this.setSourceProperty(()=>{this.url=w,this._options.url=w}),this}serialize(){return a.e({},this._options)}hasTile(w){return!this.tileBounds||this.tileBounds.contains(w.canonical)}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme);w.abortController=new AbortController;try{let Q=yield p.getImage(this.map._requestManager.transformRequest(B,\"Tile\"),w.abortController,this.map._refreshExpiredTiles);if(delete w.abortController,w.aborted)return void(w.state=\"unloaded\");if(Q&&Q.data){this.map._refreshExpiredTiles&&Q.cacheControl&&Q.expires&&w.setExpiryData({cacheControl:Q.cacheControl,expires:Q.expires});let ee=this.map.painter.context,le=ee.gl,qe=Q.data;w.texture=this.map.painter.getTileTexture(qe.width),w.texture?w.texture.update(qe,{useMipmap:!0}):(w.texture=new g(ee,qe,le.RGBA,{useMipmap:!0}),w.texture.bind(le.LINEAR,le.CLAMP_TO_EDGE,le.LINEAR_MIPMAP_NEAREST)),w.state=\"loaded\"}}catch(Q){if(delete w.abortController,w.aborted)w.state=\"unloaded\";else if(Q)throw w.state=\"errored\",Q}})}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController)})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.texture&&this.map.painter.saveTileTexture(w.texture)})}hasTransition(){return!1}}class Zt extends pt{constructor(w,B,Q,ee){super(w,B,Q,ee),this.type=\"raster-dem\",this.maxzoom=22,this._options=a.e({type:\"raster-dem\"},B),this.encoding=B.encoding||\"mapbox\",this.redFactor=B.redFactor,this.greenFactor=B.greenFactor,this.blueFactor=B.blueFactor,this.baseShift=B.baseShift}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),Q=this.map._requestManager.transformRequest(B,\"Tile\");w.neighboringTiles=this._getNeighboringTiles(w.tileID),w.abortController=new AbortController;try{let ee=yield p.getImage(Q,w.abortController,this.map._refreshExpiredTiles);if(delete w.abortController,w.aborted)return void(w.state=\"unloaded\");if(ee&&ee.data){let le=ee.data;this.map._refreshExpiredTiles&&ee.cacheControl&&ee.expires&&w.setExpiryData({cacheControl:ee.cacheControl,expires:ee.expires});let qe=a.b(le)&&a.U()?le:yield this.readImageNow(le),Xe={type:this.type,uid:w.uid,source:this.id,rawImageData:qe,encoding:this.encoding,redFactor:this.redFactor,greenFactor:this.greenFactor,blueFactor:this.blueFactor,baseShift:this.baseShift};if(!w.actor||w.state===\"expired\"){w.actor=this.dispatcher.getActor();let ot=yield w.actor.sendAsync({type:\"LDT\",data:Xe});w.dem=ot,w.needsHillshadePrepare=!0,w.needsTerrainPrepare=!0,w.state=\"loaded\"}}}catch(ee){if(delete w.abortController,w.aborted)w.state=\"unloaded\";else if(ee)throw w.state=\"errored\",ee}})}readImageNow(w){return a._(this,void 0,void 0,function*(){if(typeof VideoFrame!=\"undefined\"&&a.V()){let B=w.width+2,Q=w.height+2;try{return new a.R({width:B,height:Q},yield a.W(w,-1,-1,B,Q))}catch(ee){}}return u.getImageData(w,1)})}_getNeighboringTiles(w){let B=w.canonical,Q=Math.pow(2,B.z),ee=(B.x-1+Q)%Q,le=B.x===0?w.wrap-1:w.wrap,qe=(B.x+1+Q)%Q,Xe=B.x+1===Q?w.wrap+1:w.wrap,ot={};return ot[new a.S(w.overscaledZ,le,B.z,ee,B.y).key]={backfilled:!1},ot[new a.S(w.overscaledZ,Xe,B.z,qe,B.y).key]={backfilled:!1},B.y>0&&(ot[new a.S(w.overscaledZ,le,B.z,ee,B.y-1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,w.wrap,B.z,B.x,B.y-1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,Xe,B.z,qe,B.y-1).key]={backfilled:!1}),B.y+1<Q&&(ot[new a.S(w.overscaledZ,le,B.z,ee,B.y+1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,w.wrap,B.z,B.x,B.y+1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,Xe,B.z,qe,B.y+1).key]={backfilled:!1}),ot}unloadTile(w){return a._(this,void 0,void 0,function*(){w.demTexture&&this.map.painter.saveTileTexture(w.demTexture),w.fbo&&(w.fbo.destroy(),delete w.fbo),w.dem&&delete w.dem,delete w.neighboringTiles,w.state=\"unloaded\",w.actor&&(yield w.actor.sendAsync({type:\"RDT\",data:{type:this.type,uid:w.uid,source:this.id}}))})}}class st extends a.E{constructor(w,B,Q,ee){super(),this.id=w,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._pendingLoads=0,this.actor=Q.getActor(),this.setEventedParent(ee),this._data=B.data,this._options=a.e({},B),this._collectResourceTiming=B.collectResourceTiming,B.maxzoom!==void 0&&(this.maxzoom=B.maxzoom),B.type&&(this.type=B.type),B.attribution&&(this.attribution=B.attribution),this.promoteId=B.promoteId;let le=a.X/this.tileSize;B.clusterMaxZoom!==void 0&&this.maxzoom<=B.clusterMaxZoom&&a.w(`The maxzoom value \"${this.maxzoom}\" is expected to be greater than the clusterMaxZoom value \"${B.clusterMaxZoom}\".`),this.workerOptions=a.e({source:this.id,cluster:B.cluster||!1,geojsonVtOptions:{buffer:(B.buffer!==void 0?B.buffer:128)*le,tolerance:(B.tolerance!==void 0?B.tolerance:.375)*le,extent:a.X,maxZoom:this.maxzoom,lineMetrics:B.lineMetrics||!1,generateId:B.generateId||!1},superclusterOptions:{maxZoom:B.clusterMaxZoom!==void 0?B.clusterMaxZoom:this.maxzoom-1,minPoints:Math.max(2,B.clusterMinPoints||2),extent:a.X,radius:(B.clusterRadius||50)*le,log:!1,generateId:B.generateId||!1},clusterProperties:B.clusterProperties,filter:B.filter},B.workerOptions),typeof this.promoteId==\"string\"&&(this.workerOptions.promoteId=this.promoteId)}load(){return a._(this,void 0,void 0,function*(){yield this._updateWorkerData()})}onAdd(w){this.map=w,this.load()}setData(w){return this._data=w,this._updateWorkerData(),this}updateData(w){return this._updateWorkerData(w),this}getData(){return a._(this,void 0,void 0,function*(){let w=a.e({type:this.type},this.workerOptions);return this.actor.sendAsync({type:\"GD\",data:w})})}setClusterOptions(w){return this.workerOptions.cluster=w.cluster,w&&(w.clusterRadius!==void 0&&(this.workerOptions.superclusterOptions.radius=w.clusterRadius),w.clusterMaxZoom!==void 0&&(this.workerOptions.superclusterOptions.maxZoom=w.clusterMaxZoom)),this._updateWorkerData(),this}getClusterExpansionZoom(w){return this.actor.sendAsync({type:\"GCEZ\",data:{type:this.type,clusterId:w,source:this.id}})}getClusterChildren(w){return this.actor.sendAsync({type:\"GCC\",data:{type:this.type,clusterId:w,source:this.id}})}getClusterLeaves(w,B,Q){return this.actor.sendAsync({type:\"GCL\",data:{type:this.type,source:this.id,clusterId:w,limit:B,offset:Q}})}_updateWorkerData(w){return a._(this,void 0,void 0,function*(){let B=a.e({type:this.type},this.workerOptions);w?B.dataDiff=w:typeof this._data==\"string\"?(B.request=this.map._requestManager.transformRequest(u.resolveURL(this._data),\"Source\"),B.request.collectResourceTiming=this._collectResourceTiming):B.data=JSON.stringify(this._data),this._pendingLoads++,this.fire(new a.k(\"dataloading\",{dataType:\"source\"}));try{let Q=yield this.actor.sendAsync({type:\"LD\",data:B});if(this._pendingLoads--,this._removed||Q.abandoned)return void this.fire(new a.k(\"dataabort\",{dataType:\"source\"}));let ee=null;Q.resourceTiming&&Q.resourceTiming[this.id]&&(ee=Q.resourceTiming[this.id].slice(0));let le={dataType:\"source\"};this._collectResourceTiming&&ee&&ee.length>0&&a.e(le,{resourceTiming:ee}),this.fire(new a.k(\"data\",Object.assign(Object.assign({},le),{sourceDataType:\"metadata\"}))),this.fire(new a.k(\"data\",Object.assign(Object.assign({},le),{sourceDataType:\"content\"})))}catch(Q){if(this._pendingLoads--,this._removed)return void this.fire(new a.k(\"dataabort\",{dataType:\"source\"}));this.fire(new a.j(Q))}})}loaded(){return this._pendingLoads===0}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.actor?\"RT\":\"LT\";w.actor=this.actor;let Q={type:this.type,uid:w.uid,tileID:w.tileID,zoom:w.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};w.abortController=new AbortController;let ee=yield this.actor.sendAsync({type:B,data:Q},w.abortController);delete w.abortController,w.unloadVectorData(),w.aborted||w.loadVectorData(ee,this.map.painter,B===\"RT\")})}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController),w.aborted=!0})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.unloadVectorData(),yield this.actor.sendAsync({type:\"RMT\",data:{uid:w.uid,type:this.type,source:this.id}})})}onRemove(){this._removed=!0,this.actor.sendAsync({type:\"RS\",data:{type:this.type,source:this.id}})}serialize(){return a.e({},this._options,{type:this.type,data:this._data})}hasTransition(){return!1}}var lt=a.Y([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]);class Gt extends a.E{constructor(w,B,Q,ee){super(),this.id=w,this.dispatcher=Q,this.coordinates=B.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(ee),this.options=B}load(w){return a._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new a.k(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,this._request=new AbortController;try{let B=yield p.getImage(this.map._requestManager.transformRequest(this.url,\"Image\"),this._request);this._request=null,this._loaded=!0,B&&B.data&&(this.image=B.data,w&&(this.coordinates=w),this._finishLoading())}catch(B){this._request=null,this._loaded=!0,this.fire(new a.j(B))}})}loaded(){return this._loaded}updateImage(w){return w.url?(this._request&&(this._request.abort(),this._request=null),this.options.url=w.url,this.load(w.coordinates).finally(()=>{this.texture=null}),this):this}_finishLoading(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))}onAdd(w){this.map=w,this.load()}onRemove(){this._request&&(this._request.abort(),this._request=null)}setCoordinates(w){this.coordinates=w;let B=w.map(a.Z.fromLngLat);this.tileID=function(ee){let le=1/0,qe=1/0,Xe=-1/0,ot=-1/0;for(let xr of ee)le=Math.min(le,xr.x),qe=Math.min(qe,xr.y),Xe=Math.max(Xe,xr.x),ot=Math.max(ot,xr.y);let Tt=Math.max(Xe-le,ot-qe),Yt=Math.max(0,Math.floor(-Math.log(Tt)/Math.LN2)),Kt=Math.pow(2,Yt);return new a.a1(Yt,Math.floor((le+Xe)/2*Kt),Math.floor((qe+ot)/2*Kt))}(B),this.minzoom=this.maxzoom=this.tileID.z;let Q=B.map(ee=>this.tileID.getTilePoint(ee)._round());return this._boundsArray=new a.$,this._boundsArray.emplaceBack(Q[0].x,Q[0].y,0,0),this._boundsArray.emplaceBack(Q[1].x,Q[1].y,a.X,0),this._boundsArray.emplaceBack(Q[3].x,Q[3].y,0,a.X),this._boundsArray.emplaceBack(Q[2].x,Q[2].y,a.X,a.X),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this}prepare(){if(Object.keys(this.tiles).length===0||!this.image)return;let w=this.map.painter.context,B=w.gl;this.boundsBuffer||(this.boundsBuffer=w.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture||(this.texture=new g(w,this.image,B.RGBA),this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE));let Q=!1;for(let ee in this.tiles){let le=this.tiles[ee];le.state!==\"loaded\"&&(le.state=\"loaded\",le.texture=this.texture,Q=!0)}Q&&this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"idle\",sourceId:this.id}))}loadTile(w){return a._(this,void 0,void 0,function*(){this.tileID&&this.tileID.equals(w.tileID.canonical)?(this.tiles[String(w.tileID.wrap)]=w,w.buckets={}):w.state=\"errored\"})}serialize(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}}hasTransition(){return!1}}class Nt extends Gt{constructor(w,B,Q,ee){super(w,B,Q,ee),this.roundZoom=!0,this.type=\"video\",this.options=B}load(){return a._(this,void 0,void 0,function*(){this._loaded=!1;let w=this.options;this.urls=[];for(let B of w.urls)this.urls.push(this.map._requestManager.transformRequest(B,\"Source\").url);try{let B=yield a.a3(this.urls);if(this._loaded=!0,!B)return;this.video=B,this.video.loop=!0,this.video.addEventListener(\"playing\",()=>{this.map.triggerRepaint()}),this.map&&this.video.play(),this._finishLoading()}catch(B){this.fire(new a.j(B))}})}pause(){this.video&&this.video.pause()}play(){this.video&&this.video.play()}seek(w){if(this.video){let B=this.video.seekable;w<B.start(0)||w>B.end(0)?this.fire(new a.j(new a.a2(`sources.${this.id}`,null,`Playback for this video can be set only between the ${B.start(0)} and ${B.end(0)}-second mark.`))):this.video.currentTime=w}}getVideo(){return this.video}onAdd(w){this.map||(this.map=w,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))}prepare(){if(Object.keys(this.tiles).length===0||this.video.readyState<2)return;let w=this.map.painter.context,B=w.gl;this.boundsBuffer||(this.boundsBuffer=w.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE),B.texSubImage2D(B.TEXTURE_2D,0,0,0,B.RGBA,B.UNSIGNED_BYTE,this.video)):(this.texture=new g(w,this.video,B.RGBA),this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE));let Q=!1;for(let ee in this.tiles){let le=this.tiles[ee];le.state!==\"loaded\"&&(le.state=\"loaded\",le.texture=this.texture,Q=!0)}Q&&this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"idle\",sourceId:this.id}))}serialize(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}}hasTransition(){return this.video&&!this.video.paused}}class Jt extends Gt{constructor(w,B,Q,ee){super(w,B,Q,ee),B.coordinates?Array.isArray(B.coordinates)&&B.coordinates.length===4&&!B.coordinates.some(le=>!Array.isArray(le)||le.length!==2||le.some(qe=>typeof qe!=\"number\"))||this.fire(new a.j(new a.a2(`sources.${w}`,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new a.j(new a.a2(`sources.${w}`,null,'missing required property \"coordinates\"'))),B.animate&&typeof B.animate!=\"boolean\"&&this.fire(new a.j(new a.a2(`sources.${w}`,null,'optional \"animate\" property must be a boolean value'))),B.canvas?typeof B.canvas==\"string\"||B.canvas instanceof HTMLCanvasElement||this.fire(new a.j(new a.a2(`sources.${w}`,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new a.j(new a.a2(`sources.${w}`,null,'missing required property \"canvas\"'))),this.options=B,this.animate=B.animate===void 0||B.animate}load(){return a._(this,void 0,void 0,function*(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof HTMLCanvasElement?this.options.canvas:document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new a.j(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())})}getCanvas(){return this.canvas}onAdd(w){this.map=w,this.load(),this.canvas&&this.animate&&this.play()}onRemove(){this.pause()}prepare(){let w=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,w=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,w=!0),this._hasInvalidDimensions()||Object.keys(this.tiles).length===0)return;let B=this.map.painter.context,Q=B.gl;this.boundsBuffer||(this.boundsBuffer=B.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture?(w||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new g(B,this.canvas,Q.RGBA,{premultiply:!0});let ee=!1;for(let le in this.tiles){let qe=this.tiles[le];qe.state!==\"loaded\"&&(qe.state=\"loaded\",qe.texture=this.texture,ee=!0)}ee&&this.fire(new a.k(\"data\",{dataType:\"source\",sourceDataType:\"idle\",sourceId:this.id}))}serialize(){return{type:\"canvas\",coordinates:this.coordinates}}hasTransition(){return this._playing}_hasInvalidDimensions(){for(let w of[this.canvas.width,this.canvas.height])if(isNaN(w)||w<=0)return!0;return!1}}let sr={},wr=ue=>{switch(ue){case\"geojson\":return st;case\"image\":return Gt;case\"raster\":return pt;case\"raster-dem\":return Zt;case\"vector\":return ut;case\"video\":return Nt;case\"canvas\":return Jt}return sr[ue]},cr=\"RTLPluginLoaded\";class $e extends a.E{constructor(){super(...arguments),this.status=\"unavailable\",this.url=null,this.dispatcher=Ae()}_syncState(w){return this.status=w,this.dispatcher.broadcast(\"SRPS\",{pluginStatus:w,pluginURL:this.url}).catch(B=>{throw this.status=\"error\",B})}getRTLTextPluginStatus(){return this.status}clearRTLTextPlugin(){this.status=\"unavailable\",this.url=null}setRTLTextPlugin(w){return a._(this,arguments,void 0,function*(B,Q=!1){if(this.url)throw new Error(\"setRTLTextPlugin cannot be called multiple times.\");if(this.url=u.resolveURL(B),!this.url)throw new Error(`requested url ${B} is invalid`);if(this.status===\"unavailable\"){if(!Q)return this._requestImport();this.status=\"deferred\",this._syncState(this.status)}else if(this.status===\"requested\")return this._requestImport()})}_requestImport(){return a._(this,void 0,void 0,function*(){yield this._syncState(\"loading\"),this.status=\"loaded\",this.fire(new a.k(cr))})}lazyLoad(){this.status===\"unavailable\"?this.status=\"requested\":this.status===\"deferred\"&&this._requestImport()}}let St=null;function Qt(){return St||(St=new $e),St}class Vt{constructor(w,B){this.timeAdded=0,this.fadeEndTime=0,this.tileID=w,this.uid=a.a4(),this.uses=0,this.tileSize=B,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.rtt=[],this.rttCoords={},this.expiredRequestCount=0,this.state=\"loading\"}registerFadeDuration(w){let B=w+this.timeAdded;B<this.fadeEndTime||(this.fadeEndTime=B)}wasRequested(){return this.state===\"errored\"||this.state===\"loaded\"||this.state===\"reloading\"}clearTextures(w){this.demTexture&&w.saveTileTexture(this.demTexture),this.demTexture=null}loadVectorData(w,B,Q){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",w){w.featureIndex&&(this.latestFeatureIndex=w.featureIndex,w.rawTileData?(this.latestRawTileData=w.rawTileData,this.latestFeatureIndex.rawTileData=w.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=w.collisionBoxArray,this.buckets=function(ee,le){let qe={};if(!le)return qe;for(let Xe of ee){let ot=Xe.layerIds.map(Tt=>le.getLayer(Tt)).filter(Boolean);if(ot.length!==0){Xe.layers=ot,Xe.stateDependentLayerIds&&(Xe.stateDependentLayers=Xe.stateDependentLayerIds.map(Tt=>ot.filter(Yt=>Yt.id===Tt)[0]));for(let Tt of ot)qe[Tt.id]=Xe}}return qe}(w.buckets,B.style),this.hasSymbolBuckets=!1;for(let ee in this.buckets){let le=this.buckets[ee];if(le instanceof a.a6){if(this.hasSymbolBuckets=!0,!Q)break;le.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(let ee in this.buckets){let le=this.buckets[ee];if(le instanceof a.a6&&le.hasRTLText){this.hasRTLText=!0,Qt().lazyLoad();break}}this.queryPadding=0;for(let ee in this.buckets){let le=this.buckets[ee];this.queryPadding=Math.max(this.queryPadding,B.style.getLayer(ee).queryRadius(le))}w.imageAtlas&&(this.imageAtlas=w.imageAtlas),w.glyphAtlasImage&&(this.glyphAtlasImage=w.glyphAtlasImage)}else this.collisionBoxArray=new a.a5}unloadVectorData(){for(let w in this.buckets)this.buckets[w].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"}getBucket(w){return this.buckets[w.id]}upload(w){for(let Q in this.buckets){let ee=this.buckets[Q];ee.uploadPending()&&ee.upload(w)}let B=w.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new g(w,this.imageAtlas.image,B.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new g(w,this.glyphAtlasImage,B.ALPHA),this.glyphAtlasImage=null)}prepare(w){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(w,this.imageAtlasTexture)}queryRenderedFeatures(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:ee,cameraQueryGeometry:le,scale:qe,tileSize:this.tileSize,pixelPosMatrix:Yt,transform:ot,params:Xe,queryPadding:this.queryPadding*Tt},w,B,Q):{}}querySourceFeatures(w,B){let Q=this.latestFeatureIndex;if(!Q||!Q.rawTileData)return;let ee=Q.loadVTLayers(),le=B&&B.sourceLayer?B.sourceLayer:\"\",qe=ee._geojsonTileLayer||ee[le];if(!qe)return;let Xe=a.a7(B&&B.filter),{z:ot,x:Tt,y:Yt}=this.tileID.canonical,Kt={z:ot,x:Tt,y:Yt};for(let xr=0;xr<qe.length;xr++){let Ir=qe.feature(xr);if(Xe.needGeometry){let De=a.a8(Ir,!0);if(!Xe.filter(new a.z(this.tileID.overscaledZ),De,this.tileID.canonical))continue}else if(!Xe.filter(new a.z(this.tileID.overscaledZ),Ir))continue;let ve=Q.getId(Ir,le),be=new a.a9(Ir,ot,Tt,Yt,ve);be.tile=Kt,w.push(be)}}hasData(){return this.state===\"loaded\"||this.state===\"reloading\"||this.state===\"expired\"}patternsLoaded(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length}setExpiryData(w){let B=this.expirationTime;if(w.cacheControl){let Q=a.aa(w.cacheControl);Q[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*Q[\"max-age\"])}else w.expires&&(this.expirationTime=new Date(w.expires).getTime());if(this.expirationTime){let Q=Date.now(),ee=!1;if(this.expirationTime>Q)ee=!1;else if(B)if(this.expirationTime<B)ee=!0;else{let le=this.expirationTime-B;le?this.expirationTime=Q+Math.max(le,3e4):ee=!0}else ee=!0;ee?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}}getExpiryTimeout(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-new Date().getTime(),Math.pow(2,31)-1)}setFeatureState(w,B){if(!this.latestFeatureIndex||!this.latestFeatureIndex.rawTileData||Object.keys(w).length===0)return;let Q=this.latestFeatureIndex.loadVTLayers();for(let ee in this.buckets){if(!B.style.hasLayer(ee))continue;let le=this.buckets[ee],qe=le.layers[0].sourceLayer||\"_geojsonTileLayer\",Xe=Q[qe],ot=w[qe];if(!Xe||!ot||Object.keys(ot).length===0)continue;le.update(ot,Xe,this.imageAtlas&&this.imageAtlas.patternPositions||{});let Tt=B&&B.style&&B.style.getLayer(ee);Tt&&(this.queryPadding=Math.max(this.queryPadding,Tt.queryRadius(le)))}}holdingForFade(){return this.symbolFadeHoldUntil!==void 0}symbolFadeFinished(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<u.now()}clearFadeHold(){this.symbolFadeHoldUntil=void 0}setHoldDuration(w){this.symbolFadeHoldUntil=u.now()+w}setDependencies(w,B){let Q={};for(let ee of B)Q[ee]=!0;this.dependencies[w]=Q}hasDependency(w,B){for(let Q of w){let ee=this.dependencies[Q];if(ee){for(let le of B)if(ee[le])return!0}}return!1}}class _t{constructor(w,B){this.max=w,this.onRemove=B,this.reset()}reset(){for(let w in this.data)for(let B of this.data[w])B.timeout&&clearTimeout(B.timeout),this.onRemove(B.value);return this.data={},this.order=[],this}add(w,B,Q){let ee=w.wrapped().key;this.data[ee]===void 0&&(this.data[ee]=[]);let le={value:B,timeout:void 0};if(Q!==void 0&&(le.timeout=setTimeout(()=>{this.remove(w,le)},Q)),this.data[ee].push(le),this.order.push(ee),this.order.length>this.max){let qe=this._getAndRemoveByKey(this.order[0]);qe&&this.onRemove(qe)}return this}has(w){return w.wrapped().key in this.data}getAndRemove(w){return this.has(w)?this._getAndRemoveByKey(w.wrapped().key):null}_getAndRemoveByKey(w){let B=this.data[w].shift();return B.timeout&&clearTimeout(B.timeout),this.data[w].length===0&&delete this.data[w],this.order.splice(this.order.indexOf(w),1),B.value}getByKey(w){let B=this.data[w];return B?B[0].value:null}get(w){return this.has(w)?this.data[w.wrapped().key][0].value:null}remove(w,B){if(!this.has(w))return this;let Q=w.wrapped().key,ee=B===void 0?0:this.data[Q].indexOf(B),le=this.data[Q][ee];return this.data[Q].splice(ee,1),le.timeout&&clearTimeout(le.timeout),this.data[Q].length===0&&delete this.data[Q],this.onRemove(le.value),this.order.splice(this.order.indexOf(Q),1),this}setMaxSize(w){for(this.max=w;this.order.length>this.max;){let B=this._getAndRemoveByKey(this.order[0]);B&&this.onRemove(B)}return this}filter(w){let B=[];for(let Q in this.data)for(let ee of this.data[Q])w(ee.value)||B.push(ee);for(let Q of B)this.remove(Q.value.tileID,Q)}}class It{constructor(){this.state={},this.stateChanges={},this.deletedStates={}}updateState(w,B,Q){let ee=String(B);if(this.stateChanges[w]=this.stateChanges[w]||{},this.stateChanges[w][ee]=this.stateChanges[w][ee]||{},a.e(this.stateChanges[w][ee],Q),this.deletedStates[w]===null){this.deletedStates[w]={};for(let le in this.state[w])le!==ee&&(this.deletedStates[w][le]=null)}else if(this.deletedStates[w]&&this.deletedStates[w][ee]===null){this.deletedStates[w][ee]={};for(let le in this.state[w][ee])Q[le]||(this.deletedStates[w][ee][le]=null)}else for(let le in Q)this.deletedStates[w]&&this.deletedStates[w][ee]&&this.deletedStates[w][ee][le]===null&&delete this.deletedStates[w][ee][le]}removeFeatureState(w,B,Q){if(this.deletedStates[w]===null)return;let ee=String(B);if(this.deletedStates[w]=this.deletedStates[w]||{},Q&&B!==void 0)this.deletedStates[w][ee]!==null&&(this.deletedStates[w][ee]=this.deletedStates[w][ee]||{},this.deletedStates[w][ee][Q]=null);else if(B!==void 0)if(this.stateChanges[w]&&this.stateChanges[w][ee])for(Q in this.deletedStates[w][ee]={},this.stateChanges[w][ee])this.deletedStates[w][ee][Q]=null;else this.deletedStates[w][ee]=null;else this.deletedStates[w]=null}getState(w,B){let Q=String(B),ee=a.e({},(this.state[w]||{})[Q],(this.stateChanges[w]||{})[Q]);if(this.deletedStates[w]===null)return{};if(this.deletedStates[w]){let le=this.deletedStates[w][B];if(le===null)return{};for(let qe in le)delete ee[qe]}return ee}initializeTileState(w,B){w.setFeatureState(this.state,B)}coalesceChanges(w,B){let Q={};for(let ee in this.stateChanges){this.state[ee]=this.state[ee]||{};let le={};for(let qe in this.stateChanges[ee])this.state[ee][qe]||(this.state[ee][qe]={}),a.e(this.state[ee][qe],this.stateChanges[ee][qe]),le[qe]=this.state[ee][qe];Q[ee]=le}for(let ee in this.deletedStates){this.state[ee]=this.state[ee]||{};let le={};if(this.deletedStates[ee]===null)for(let qe in this.state[ee])le[qe]={},this.state[ee][qe]={};else for(let qe in this.deletedStates[ee]){if(this.deletedStates[ee][qe]===null)this.state[ee][qe]={};else for(let Xe of Object.keys(this.deletedStates[ee][qe]))delete this.state[ee][qe][Xe];le[qe]=this.state[ee][qe]}Q[ee]=Q[ee]||{},a.e(Q[ee],le)}if(this.stateChanges={},this.deletedStates={},Object.keys(Q).length!==0)for(let ee in w)w[ee].setFeatureState(Q,B)}}class mt extends a.E{constructor(w,B,Q){super(),this.id=w,this.dispatcher=Q,this.on(\"data\",ee=>this._dataHandler(ee)),this.on(\"dataloading\",()=>{this._sourceErrored=!1}),this.on(\"error\",()=>{this._sourceErrored=this._source.loaded()}),this._source=((ee,le,qe,Xe)=>{let ot=new(wr(le.type))(ee,le,qe,Xe);if(ot.id!==ee)throw new Error(`Expected Source id to be ${ee} instead of ${ot.id}`);return ot})(w,B,Q,this),this._tiles={},this._cache=new _t(0,ee=>this._unloadTile(ee)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._maxTileCacheZoomLevels=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new It,this._didEmitContent=!1,this._updated=!1}onAdd(w){this.map=w,this._maxTileCacheSize=w?w._maxTileCacheSize:null,this._maxTileCacheZoomLevels=w?w._maxTileCacheZoomLevels:null,this._source&&this._source.onAdd&&this._source.onAdd(w)}onRemove(w){this.clearTiles(),this._source&&this._source.onRemove&&this._source.onRemove(w)}loaded(){if(this._sourceErrored)return!0;if(!this._sourceLoaded||!this._source.loaded())return!1;if(!(this.used===void 0&&this.usedForTerrain===void 0||this.used||this.usedForTerrain))return!0;if(!this._updated)return!1;for(let w in this._tiles){let B=this._tiles[w];if(B.state!==\"loaded\"&&B.state!==\"errored\")return!1}return!0}getSource(){return this._source}pause(){this._paused=!0}resume(){if(!this._paused)return;let w=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,w&&this.reload(),this.transform&&this.update(this.transform,this.terrain)}_loadTile(w,B,Q){return a._(this,void 0,void 0,function*(){try{yield this._source.loadTile(w),this._tileLoaded(w,B,Q)}catch(ee){w.state=\"errored\",ee.status!==404?this._source.fire(new a.j(ee,{tile:w})):this.update(this.transform,this.terrain)}})}_unloadTile(w){this._source.unloadTile&&this._source.unloadTile(w)}_abortTile(w){this._source.abortTile&&this._source.abortTile(w),this._source.fire(new a.k(\"dataabort\",{tile:w,coord:w.tileID,dataType:\"source\"}))}serialize(){return this._source.serialize()}prepare(w){this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null);for(let B in this._tiles){let Q=this._tiles[B];Q.upload(w),Q.prepare(this.map.style.imageManager)}}getIds(){return Object.values(this._tiles).map(w=>w.tileID).sort(er).map(w=>w.key)}getRenderableIds(w){let B=[];for(let Q in this._tiles)this._isIdRenderable(Q,w)&&B.push(this._tiles[Q]);return w?B.sort((Q,ee)=>{let le=Q.tileID,qe=ee.tileID,Xe=new a.P(le.canonical.x,le.canonical.y)._rotate(this.transform.angle),ot=new a.P(qe.canonical.x,qe.canonical.y)._rotate(this.transform.angle);return le.overscaledZ-qe.overscaledZ||ot.y-Xe.y||ot.x-Xe.x}).map(Q=>Q.tileID.key):B.map(Q=>Q.tileID).sort(er).map(Q=>Q.key)}hasRenderableParent(w){let B=this.findLoadedParent(w,0);return!!B&&this._isIdRenderable(B.tileID.key)}_isIdRenderable(w,B){return this._tiles[w]&&this._tiles[w].hasData()&&!this._coveredTiles[w]&&(B||!this._tiles[w].holdingForFade())}reload(){if(this._paused)this._shouldReloadOnResume=!0;else{this._cache.reset();for(let w in this._tiles)this._tiles[w].state!==\"errored\"&&this._reloadTile(w,\"reloading\")}}_reloadTile(w,B){return a._(this,void 0,void 0,function*(){let Q=this._tiles[w];Q&&(Q.state!==\"loading\"&&(Q.state=B),yield this._loadTile(Q,w,B))})}_tileLoaded(w,B,Q){w.timeAdded=u.now(),Q===\"expired\"&&(w.refreshedUponExpiration=!0),this._setTileReloadTimer(B,w),this.getSource().type===\"raster-dem\"&&w.dem&&this._backfillDEM(w),this._state.initializeTileState(w,this.map?this.map.painter:null),w.aborted||this._source.fire(new a.k(\"data\",{dataType:\"source\",tile:w,coord:w.tileID}))}_backfillDEM(w){let B=this.getRenderableIds();for(let ee=0;ee<B.length;ee++){let le=B[ee];if(w.neighboringTiles&&w.neighboringTiles[le]){let qe=this.getTileByID(le);Q(w,qe),Q(qe,w)}}function Q(ee,le){ee.needsHillshadePrepare=!0,ee.needsTerrainPrepare=!0;let qe=le.tileID.canonical.x-ee.tileID.canonical.x,Xe=le.tileID.canonical.y-ee.tileID.canonical.y,ot=Math.pow(2,ee.tileID.canonical.z),Tt=le.tileID.key;qe===0&&Xe===0||Math.abs(Xe)>1||(Math.abs(qe)>1&&(Math.abs(qe+ot)===1?qe+=ot:Math.abs(qe-ot)===1&&(qe-=ot)),le.dem&&ee.dem&&(ee.dem.backfillBorder(le.dem,qe,Xe),ee.neighboringTiles&&ee.neighboringTiles[Tt]&&(ee.neighboringTiles[Tt].backfilled=!0)))}}getTile(w){return this.getTileByID(w.key)}getTileByID(w){return this._tiles[w]}_retainLoadedChildren(w,B,Q,ee){for(let le in this._tiles){let qe=this._tiles[le];if(ee[le]||!qe.hasData()||qe.tileID.overscaledZ<=B||qe.tileID.overscaledZ>Q)continue;let Xe=qe.tileID;for(;qe&&qe.tileID.overscaledZ>B+1;){let Tt=qe.tileID.scaledTo(qe.tileID.overscaledZ-1);qe=this._tiles[Tt.key],qe&&qe.hasData()&&(Xe=Tt)}let ot=Xe;for(;ot.overscaledZ>B;)if(ot=ot.scaledTo(ot.overscaledZ-1),w[ot.key]){ee[Xe.key]=Xe;break}}}findLoadedParent(w,B){if(w.key in this._loadedParentTiles){let Q=this._loadedParentTiles[w.key];return Q&&Q.tileID.overscaledZ>=B?Q:null}for(let Q=w.overscaledZ-1;Q>=B;Q--){let ee=w.scaledTo(Q),le=this._getLoadedTile(ee);if(le)return le}}findLoadedSibling(w){return this._getLoadedTile(w)}_getLoadedTile(w){let B=this._tiles[w.key];return B&&B.hasData()?B:this._cache.getByKey(w.wrapped().key)}updateCacheSize(w){let B=Math.ceil(w.width/this._source.tileSize)+1,Q=Math.ceil(w.height/this._source.tileSize)+1,ee=Math.floor(B*Q*(this._maxTileCacheZoomLevels===null?a.a.MAX_TILE_CACHE_ZOOM_LEVELS:this._maxTileCacheZoomLevels)),le=typeof this._maxTileCacheSize==\"number\"?Math.min(this._maxTileCacheSize,ee):ee;this._cache.setMaxSize(le)}handleWrapJump(w){let B=Math.round((w-(this._prevLng===void 0?w:this._prevLng))/360);if(this._prevLng=w,B){let Q={};for(let ee in this._tiles){let le=this._tiles[ee];le.tileID=le.tileID.unwrapTo(le.tileID.wrap+B),Q[le.tileID.key]=le}this._tiles=Q;for(let ee in this._timers)clearTimeout(this._timers[ee]),delete this._timers[ee];for(let ee in this._tiles)this._setTileReloadTimer(ee,this._tiles[ee])}}_updateCoveredAndRetainedTiles(w,B,Q,ee,le,qe){let Xe={},ot={},Tt=Object.keys(w),Yt=u.now();for(let Kt of Tt){let xr=w[Kt],Ir=this._tiles[Kt];if(!Ir||Ir.fadeEndTime!==0&&Ir.fadeEndTime<=Yt)continue;let ve=this.findLoadedParent(xr,B),be=this.findLoadedSibling(xr),De=ve||be||null;De&&(this._addTile(De.tileID),Xe[De.tileID.key]=De.tileID),ot[Kt]=xr}this._retainLoadedChildren(ot,ee,Q,w);for(let Kt in Xe)w[Kt]||(this._coveredTiles[Kt]=!0,w[Kt]=Xe[Kt]);if(qe){let Kt={},xr={};for(let Ir of le)this._tiles[Ir.key].hasData()?Kt[Ir.key]=Ir:xr[Ir.key]=Ir;for(let Ir in xr){let ve=xr[Ir].children(this._source.maxzoom);this._tiles[ve[0].key]&&this._tiles[ve[1].key]&&this._tiles[ve[2].key]&&this._tiles[ve[3].key]&&(Kt[ve[0].key]=w[ve[0].key]=ve[0],Kt[ve[1].key]=w[ve[1].key]=ve[1],Kt[ve[2].key]=w[ve[2].key]=ve[2],Kt[ve[3].key]=w[ve[3].key]=ve[3],delete xr[Ir])}for(let Ir in xr){let ve=xr[Ir],be=this.findLoadedParent(ve,this._source.minzoom),De=this.findLoadedSibling(ve),Be=be||De||null;if(Be){Kt[Be.tileID.key]=w[Be.tileID.key]=Be.tileID;for(let et in Kt)Kt[et].isChildOf(Be.tileID)&&delete Kt[et]}}for(let Ir in this._tiles)Kt[Ir]||(this._coveredTiles[Ir]=!0)}}update(w,B){if(!this._sourceLoaded||this._paused)return;let Q;this.transform=w,this.terrain=B,this.updateCacheSize(w),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used||this.usedForTerrain?this._source.tileID?Q=w.getVisibleUnwrappedCoordinates(this._source.tileID).map(Yt=>new a.S(Yt.canonical.z,Yt.wrap,Yt.canonical.z,Yt.canonical.x,Yt.canonical.y)):(Q=w.coveringTiles({tileSize:this.usedForTerrain?this.tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:!this.usedForTerrain&&this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled,terrain:B}),this._source.hasTile&&(Q=Q.filter(Yt=>this._source.hasTile(Yt)))):Q=[];let ee=w.coveringZoomLevel(this._source),le=Math.max(ee-mt.maxOverzooming,this._source.minzoom),qe=Math.max(ee+mt.maxUnderzooming,this._source.minzoom);if(this.usedForTerrain){let Yt={};for(let Kt of Q)if(Kt.canonical.z>this._source.minzoom){let xr=Kt.scaledTo(Kt.canonical.z-1);Yt[xr.key]=xr;let Ir=Kt.scaledTo(Math.max(this._source.minzoom,Math.min(Kt.canonical.z,5)));Yt[Ir.key]=Ir}Q=Q.concat(Object.values(Yt))}let Xe=Q.length===0&&!this._updated&&this._didEmitContent;this._updated=!0,Xe&&this.fire(new a.k(\"data\",{sourceDataType:\"idle\",dataType:\"source\",sourceId:this.id}));let ot=this._updateRetainedTiles(Q,ee);lr(this._source.type)&&this._updateCoveredAndRetainedTiles(ot,le,qe,ee,Q,B);for(let Yt in ot)this._tiles[Yt].clearFadeHold();let Tt=a.ab(this._tiles,ot);for(let Yt of Tt){let Kt=this._tiles[Yt];Kt.hasSymbolBuckets&&!Kt.holdingForFade()?Kt.setHoldDuration(this.map._fadeDuration):Kt.hasSymbolBuckets&&!Kt.symbolFadeFinished()||this._removeTile(Yt)}this._updateLoadedParentTileCache(),this._updateLoadedSiblingTileCache()}releaseSymbolFadeTiles(){for(let w in this._tiles)this._tiles[w].holdingForFade()&&this._removeTile(w)}_updateRetainedTiles(w,B){var Q;let ee={},le={},qe=Math.max(B-mt.maxOverzooming,this._source.minzoom),Xe=Math.max(B+mt.maxUnderzooming,this._source.minzoom),ot={};for(let Tt of w){let Yt=this._addTile(Tt);ee[Tt.key]=Tt,Yt.hasData()||B<this._source.maxzoom&&(ot[Tt.key]=Tt)}this._retainLoadedChildren(ot,B,Xe,ee);for(let Tt of w){let Yt=this._tiles[Tt.key];if(Yt.hasData())continue;if(B+1>this._source.maxzoom){let xr=Tt.children(this._source.maxzoom)[0],Ir=this.getTile(xr);if(Ir&&Ir.hasData()){ee[xr.key]=xr;continue}}else{let xr=Tt.children(this._source.maxzoom);if(ee[xr[0].key]&&ee[xr[1].key]&&ee[xr[2].key]&&ee[xr[3].key])continue}let Kt=Yt.wasRequested();for(let xr=Tt.overscaledZ-1;xr>=qe;--xr){let Ir=Tt.scaledTo(xr);if(le[Ir.key])break;if(le[Ir.key]=!0,Yt=this.getTile(Ir),!Yt&&Kt&&(Yt=this._addTile(Ir)),Yt){let ve=Yt.hasData();if((ve||!(!((Q=this.map)===null||Q===void 0)&&Q.cancelPendingTileRequestsWhileZooming)||Kt)&&(ee[Ir.key]=Ir),Kt=Yt.wasRequested(),ve)break}}}return ee}_updateLoadedParentTileCache(){this._loadedParentTiles={};for(let w in this._tiles){let B=[],Q,ee=this._tiles[w].tileID;for(;ee.overscaledZ>0;){if(ee.key in this._loadedParentTiles){Q=this._loadedParentTiles[ee.key];break}B.push(ee.key);let le=ee.scaledTo(ee.overscaledZ-1);if(Q=this._getLoadedTile(le),Q)break;ee=le}for(let le of B)this._loadedParentTiles[le]=Q}}_updateLoadedSiblingTileCache(){this._loadedSiblingTiles={};for(let w in this._tiles){let B=this._tiles[w].tileID,Q=this._getLoadedTile(B);this._loadedSiblingTiles[B.key]=Q}}_addTile(w){let B=this._tiles[w.key];if(B)return B;B=this._cache.getAndRemove(w),B&&(this._setTileReloadTimer(w.key,B),B.tileID=w,this._state.initializeTileState(B,this.map?this.map.painter:null),this._cacheTimers[w.key]&&(clearTimeout(this._cacheTimers[w.key]),delete this._cacheTimers[w.key],this._setTileReloadTimer(w.key,B)));let Q=B;return B||(B=new Vt(w,this._source.tileSize*w.overscaleFactor()),this._loadTile(B,w.key,B.state)),B.uses++,this._tiles[w.key]=B,Q||this._source.fire(new a.k(\"dataloading\",{tile:B,coord:B.tileID,dataType:\"source\"})),B}_setTileReloadTimer(w,B){w in this._timers&&(clearTimeout(this._timers[w]),delete this._timers[w]);let Q=B.getExpiryTimeout();Q&&(this._timers[w]=setTimeout(()=>{this._reloadTile(w,\"expired\"),delete this._timers[w]},Q))}_removeTile(w){let B=this._tiles[w];B&&(B.uses--,delete this._tiles[w],this._timers[w]&&(clearTimeout(this._timers[w]),delete this._timers[w]),B.uses>0||(B.hasData()&&B.state!==\"reloading\"?this._cache.add(B.tileID,B,B.getExpiryTimeout()):(B.aborted=!0,this._abortTile(B),this._unloadTile(B))))}_dataHandler(w){let B=w.sourceDataType;w.dataType===\"source\"&&B===\"metadata\"&&(this._sourceLoaded=!0),this._sourceLoaded&&!this._paused&&w.dataType===\"source\"&&B===\"content\"&&(this.reload(),this.transform&&this.update(this.transform,this.terrain),this._didEmitContent=!0)}clearTiles(){this._shouldReloadOnResume=!1,this._paused=!1;for(let w in this._tiles)this._removeTile(w);this._cache.reset()}tilesIn(w,B,Q){let ee=[],le=this.transform;if(!le)return ee;let qe=Q?le.getCameraQueryGeometry(w):w,Xe=w.map(ve=>le.pointCoordinate(ve,this.terrain)),ot=qe.map(ve=>le.pointCoordinate(ve,this.terrain)),Tt=this.getIds(),Yt=1/0,Kt=1/0,xr=-1/0,Ir=-1/0;for(let ve of ot)Yt=Math.min(Yt,ve.x),Kt=Math.min(Kt,ve.y),xr=Math.max(xr,ve.x),Ir=Math.max(Ir,ve.y);for(let ve=0;ve<Tt.length;ve++){let be=this._tiles[Tt[ve]];if(be.holdingForFade())continue;let De=be.tileID,Be=Math.pow(2,le.zoom-be.tileID.overscaledZ),et=B*be.queryPadding*a.X/be.tileSize/Be,We=[De.getTilePoint(new a.Z(Yt,Kt)),De.getTilePoint(new a.Z(xr,Ir))];if(We[0].x-et<a.X&&We[0].y-et<a.X&&We[1].x+et>=0&&We[1].y+et>=0){let it=Xe.map(Ht=>De.getTilePoint(Ht)),Ft=ot.map(Ht=>De.getTilePoint(Ht));ee.push({tile:be,tileID:De,queryGeometry:it,cameraQueryGeometry:Ft,scale:Be})}}return ee}getVisibleCoordinates(w){let B=this.getRenderableIds(w).map(Q=>this._tiles[Q].tileID);for(let Q of B)Q.posMatrix=this.transform.calculatePosMatrix(Q.toUnwrapped());return B}hasTransition(){if(this._source.hasTransition())return!0;if(lr(this._source.type)){let w=u.now();for(let B in this._tiles)if(this._tiles[B].fadeEndTime>=w)return!0}return!1}setFeatureState(w,B,Q){this._state.updateState(w=w||\"_geojsonTileLayer\",B,Q)}removeFeatureState(w,B,Q){this._state.removeFeatureState(w=w||\"_geojsonTileLayer\",B,Q)}getFeatureState(w,B){return this._state.getState(w=w||\"_geojsonTileLayer\",B)}setDependencies(w,B,Q){let ee=this._tiles[w];ee&&ee.setDependencies(B,Q)}reloadTilesForDependencies(w,B){for(let Q in this._tiles)this._tiles[Q].hasDependency(w,B)&&this._reloadTile(Q,\"reloading\");this._cache.filter(Q=>!Q.hasDependency(w,B))}}function er(ue,w){let B=Math.abs(2*ue.wrap)-+(ue.wrap<0),Q=Math.abs(2*w.wrap)-+(w.wrap<0);return ue.overscaledZ-w.overscaledZ||Q-B||w.canonical.y-ue.canonical.y||w.canonical.x-ue.canonical.x}function lr(ue){return ue===\"raster\"||ue===\"image\"||ue===\"video\"}mt.maxOverzooming=10,mt.maxUnderzooming=3;class Tr{constructor(w,B){this.reset(w,B)}reset(w,B){this.points=w||[],this._distances=[0];for(let Q=1;Q<this.points.length;Q++)this._distances[Q]=this._distances[Q-1]+this.points[Q].dist(this.points[Q-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(B||0,.5*this.length),this.paddedLength=this.length-2*this.padding}lerp(w){if(this.points.length===1)return this.points[0];w=a.ac(w,0,1);let B=1,Q=this._distances[B],ee=w*this.paddedLength+this.padding;for(;Q<ee&&B<this._distances.length;)Q=this._distances[++B];let le=B-1,qe=this._distances[le],Xe=Q-qe,ot=Xe>0?(ee-qe)/Xe:0;return this.points[le].mult(1-ot).add(this.points[B].mult(ot))}}function Lr(ue,w){let B=!0;return ue===\"always\"||ue!==\"never\"&&w!==\"never\"||(B=!1),B}class ti{constructor(w,B,Q){let ee=this.boxCells=[],le=this.circleCells=[];this.xCellCount=Math.ceil(w/Q),this.yCellCount=Math.ceil(B/Q);for(let qe=0;qe<this.xCellCount*this.yCellCount;qe++)ee.push([]),le.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=w,this.height=B,this.xScale=this.xCellCount/w,this.yScale=this.yCellCount/B,this.boxUid=0,this.circleUid=0}keysLength(){return this.boxKeys.length+this.circleKeys.length}insert(w,B,Q,ee,le){this._forEachCell(B,Q,ee,le,this._insertBoxCell,this.boxUid++),this.boxKeys.push(w),this.bboxes.push(B),this.bboxes.push(Q),this.bboxes.push(ee),this.bboxes.push(le)}insertCircle(w,B,Q,ee){this._forEachCell(B-ee,Q-ee,B+ee,Q+ee,this._insertCircleCell,this.circleUid++),this.circleKeys.push(w),this.circles.push(B),this.circles.push(Q),this.circles.push(ee)}_insertBoxCell(w,B,Q,ee,le,qe){this.boxCells[le].push(qe)}_insertCircleCell(w,B,Q,ee,le,qe){this.circleCells[le].push(qe)}_query(w,B,Q,ee,le,qe,Xe){if(Q<0||w>this.width||ee<0||B>this.height)return[];let ot=[];if(w<=0&&B<=0&&this.width<=Q&&this.height<=ee){if(le)return[{key:null,x1:w,y1:B,x2:Q,y2:ee}];for(let Tt=0;Tt<this.boxKeys.length;Tt++)ot.push({key:this.boxKeys[Tt],x1:this.bboxes[4*Tt],y1:this.bboxes[4*Tt+1],x2:this.bboxes[4*Tt+2],y2:this.bboxes[4*Tt+3]});for(let Tt=0;Tt<this.circleKeys.length;Tt++){let Yt=this.circles[3*Tt],Kt=this.circles[3*Tt+1],xr=this.circles[3*Tt+2];ot.push({key:this.circleKeys[Tt],x1:Yt-xr,y1:Kt-xr,x2:Yt+xr,y2:Kt+xr})}}else this._forEachCell(w,B,Q,ee,this._queryCell,ot,{hitTest:le,overlapMode:qe,seenUids:{box:{},circle:{}}},Xe);return ot}query(w,B,Q,ee){return this._query(w,B,Q,ee,!1,null)}hitTest(w,B,Q,ee,le,qe){return this._query(w,B,Q,ee,!0,le,qe).length>0}hitTestCircle(w,B,Q,ee,le){let qe=w-Q,Xe=w+Q,ot=B-Q,Tt=B+Q;if(Xe<0||qe>this.width||Tt<0||ot>this.height)return!1;let Yt=[];return this._forEachCell(qe,ot,Xe,Tt,this._queryCellCircle,Yt,{hitTest:!0,overlapMode:ee,circle:{x:w,y:B,radius:Q},seenUids:{box:{},circle:{}}},le),Yt.length>0}_queryCell(w,B,Q,ee,le,qe,Xe,ot){let{seenUids:Tt,hitTest:Yt,overlapMode:Kt}=Xe,xr=this.boxCells[le];if(xr!==null){let ve=this.bboxes;for(let be of xr)if(!Tt.box[be]){Tt.box[be]=!0;let De=4*be,Be=this.boxKeys[be];if(w<=ve[De+2]&&B<=ve[De+3]&&Q>=ve[De+0]&&ee>=ve[De+1]&&(!ot||ot(Be))&&(!Yt||!Lr(Kt,Be.overlapMode))&&(qe.push({key:Be,x1:ve[De],y1:ve[De+1],x2:ve[De+2],y2:ve[De+3]}),Yt))return!0}}let Ir=this.circleCells[le];if(Ir!==null){let ve=this.circles;for(let be of Ir)if(!Tt.circle[be]){Tt.circle[be]=!0;let De=3*be,Be=this.circleKeys[be];if(this._circleAndRectCollide(ve[De],ve[De+1],ve[De+2],w,B,Q,ee)&&(!ot||ot(Be))&&(!Yt||!Lr(Kt,Be.overlapMode))){let et=ve[De],We=ve[De+1],it=ve[De+2];if(qe.push({key:Be,x1:et-it,y1:We-it,x2:et+it,y2:We+it}),Yt)return!0}}}return!1}_queryCellCircle(w,B,Q,ee,le,qe,Xe,ot){let{circle:Tt,seenUids:Yt,overlapMode:Kt}=Xe,xr=this.boxCells[le];if(xr!==null){let ve=this.bboxes;for(let be of xr)if(!Yt.box[be]){Yt.box[be]=!0;let De=4*be,Be=this.boxKeys[be];if(this._circleAndRectCollide(Tt.x,Tt.y,Tt.radius,ve[De+0],ve[De+1],ve[De+2],ve[De+3])&&(!ot||ot(Be))&&!Lr(Kt,Be.overlapMode))return qe.push(!0),!0}}let Ir=this.circleCells[le];if(Ir!==null){let ve=this.circles;for(let be of Ir)if(!Yt.circle[be]){Yt.circle[be]=!0;let De=3*be,Be=this.circleKeys[be];if(this._circlesCollide(ve[De],ve[De+1],ve[De+2],Tt.x,Tt.y,Tt.radius)&&(!ot||ot(Be))&&!Lr(Kt,Be.overlapMode))return qe.push(!0),!0}}}_forEachCell(w,B,Q,ee,le,qe,Xe,ot){let Tt=this._convertToXCellCoord(w),Yt=this._convertToYCellCoord(B),Kt=this._convertToXCellCoord(Q),xr=this._convertToYCellCoord(ee);for(let Ir=Tt;Ir<=Kt;Ir++)for(let ve=Yt;ve<=xr;ve++)if(le.call(this,w,B,Q,ee,this.xCellCount*ve+Ir,qe,Xe,ot))return}_convertToXCellCoord(w){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(w*this.xScale)))}_convertToYCellCoord(w){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(w*this.yScale)))}_circlesCollide(w,B,Q,ee,le,qe){let Xe=ee-w,ot=le-B,Tt=Q+qe;return Tt*Tt>Xe*Xe+ot*ot}_circleAndRectCollide(w,B,Q,ee,le,qe,Xe){let ot=(qe-ee)/2,Tt=Math.abs(w-(ee+ot));if(Tt>ot+Q)return!1;let Yt=(Xe-le)/2,Kt=Math.abs(B-(le+Yt));if(Kt>Yt+Q)return!1;if(Tt<=ot||Kt<=Yt)return!0;let xr=Tt-ot,Ir=Kt-Yt;return xr*xr+Ir*Ir<=Q*Q}}function Br(ue,w,B,Q,ee){let le=a.H();return w?(a.K(le,le,[1/ee,1/ee,1]),B||a.ad(le,le,Q.angle)):a.L(le,Q.labelPlaneMatrix,ue),le}function Vr(ue,w,B,Q,ee){if(w){let le=a.ae(ue);return a.K(le,le,[ee,ee,1]),B||a.ad(le,le,-Q.angle),le}return Q.glCoordMatrix}function dt(ue,w,B,Q){let ee;Q?(ee=[ue,w,Q(ue,w),1],a.af(ee,ee,B)):(ee=[ue,w,0,1],$r(ee,ee,B));let le=ee[3];return{point:new a.P(ee[0]/le,ee[1]/le),signedDistanceFromCamera:le,isOccluded:!1}}function Ge(ue,w){return .5+ue/w*.5}function Je(ue,w){return ue.x>=-w[0]&&ue.x<=w[0]&&ue.y>=-w[1]&&ue.y<=w[1]}function je(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve){let be=Q?ue.textSizeData:ue.iconSizeData,De=a.ag(be,B.transform.zoom),Be=[256/B.width*2+1,256/B.height*2+1],et=Q?ue.text.dynamicLayoutVertexArray:ue.icon.dynamicLayoutVertexArray;et.clear();let We=ue.lineVertexArray,it=Q?ue.text.placedSymbolArray:ue.icon.placedSymbolArray,Ft=B.transform.width/B.transform.height,Ht=!1;for(let tr=0;tr<it.length;tr++){let dr=it.get(tr);if(dr.hidden||dr.writingMode===a.ah.vertical&&!Ht){pi(dr.numGlyphs,et);continue}Ht=!1;let Sr=dt(dr.anchorX,dr.anchorY,w,ve);if(!Je(Sr.point,Be)){pi(dr.numGlyphs,et);continue}let Or=Ge(B.transform.cameraToCenterDistance,Sr.signedDistanceFromCamera),Wr=a.ai(be,De,dr),ni=qe?Wr/Or:Wr*Or,Pi={getElevation:ve,labelPlaneMatrix:ee,lineVertexArray:We,pitchWithMap:qe,projectionCache:{projections:{},offsets:{},cachedAnchorPoint:void 0,anyProjectionOccluded:!1},projection:Tt,tileAnchorPoint:new a.P(dr.anchorX,dr.anchorY),unwrappedTileID:Yt,width:Kt,height:xr,translation:Ir},cn=Ie(Pi,dr,ni,!1,Xe,w,le,ue.glyphOffsetArray,et,Ft,ot);Ht=cn.useVertical,(cn.notEnoughRoom||Ht||cn.needsFlipping&&Ie(Pi,dr,ni,!0,Xe,w,le,ue.glyphOffsetArray,et,Ft,ot).notEnoughRoom)&&pi(dr.numGlyphs,et)}Q?ue.text.dynamicLayoutVertexBuffer.updateData(et):ue.icon.dynamicLayoutVertexBuffer.updateData(et)}function tt(ue,w,B,Q,ee,le,qe,Xe){let ot=le.glyphStartIndex+le.numGlyphs,Tt=le.lineStartIndex,Yt=le.lineStartIndex+le.lineLength,Kt=w.getoffsetX(le.glyphStartIndex),xr=w.getoffsetX(ot-1),Ir=vr(ue*Kt,B,Q,ee,le.segment,Tt,Yt,Xe,qe);if(!Ir)return null;let ve=vr(ue*xr,B,Q,ee,le.segment,Tt,Yt,Xe,qe);return ve?Xe.projectionCache.anyProjectionOccluded?null:{first:Ir,last:ve}:null}function xt(ue,w,B,Q){return ue===a.ah.horizontal&&Math.abs(B.y-w.y)>Math.abs(B.x-w.x)*Q?{useVertical:!0}:(ue===a.ah.vertical?w.y<B.y:w.x>B.x)?{needsFlipping:!0}:null}function Ie(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt){let Kt=B/24,xr=w.lineOffsetX*Kt,Ir=w.lineOffsetY*Kt,ve;if(w.numGlyphs>1){let be=w.glyphStartIndex+w.numGlyphs,De=w.lineStartIndex,Be=w.lineStartIndex+w.lineLength,et=tt(Kt,Xe,xr,Ir,Q,w,Yt,ue);if(!et)return{notEnoughRoom:!0};let We=dt(et.first.point.x,et.first.point.y,qe,ue.getElevation).point,it=dt(et.last.point.x,et.last.point.y,qe,ue.getElevation).point;if(ee&&!Q){let Ft=xt(w.writingMode,We,it,Tt);if(Ft)return Ft}ve=[et.first];for(let Ft=w.glyphStartIndex+1;Ft<be-1;Ft++)ve.push(vr(Kt*Xe.getoffsetX(Ft),xr,Ir,Q,w.segment,De,Be,ue,Yt));ve.push(et.last)}else{if(ee&&!Q){let De=dt(ue.tileAnchorPoint.x,ue.tileAnchorPoint.y,le,ue.getElevation).point,Be=w.lineStartIndex+w.segment+1,et=new a.P(ue.lineVertexArray.getx(Be),ue.lineVertexArray.gety(Be)),We=dt(et.x,et.y,le,ue.getElevation),it=We.signedDistanceFromCamera>0?We.point:function(Ht,tr,dr,Sr,Or,Wr){return xe(Ht,tr,dr,1,Or,Wr)}(ue.tileAnchorPoint,et,De,0,le,ue),Ft=xt(w.writingMode,De,it,Tt);if(Ft)return Ft}let be=vr(Kt*Xe.getoffsetX(w.glyphStartIndex),xr,Ir,Q,w.segment,w.lineStartIndex,w.lineStartIndex+w.lineLength,ue,Yt);if(!be||ue.projectionCache.anyProjectionOccluded)return{notEnoughRoom:!0};ve=[be]}for(let be of ve)a.aj(ot,be.point,be.angle);return{}}function xe(ue,w,B,Q,ee,le){let qe=ue.add(ue.sub(w)._unit()),Xe=ee!==void 0?dt(qe.x,qe.y,ee,le.getElevation).point:vt(qe.x,qe.y,le).point,ot=B.sub(Xe);return B.add(ot._mult(Q/ot.mag()))}function ke(ue,w,B){let Q=w.projectionCache;if(Q.projections[ue])return Q.projections[ue];let ee=new a.P(w.lineVertexArray.getx(ue),w.lineVertexArray.gety(ue)),le=vt(ee.x,ee.y,w);if(le.signedDistanceFromCamera>0)return Q.projections[ue]=le.point,Q.anyProjectionOccluded=Q.anyProjectionOccluded||le.isOccluded,le.point;let qe=ue-B.direction;return function(Xe,ot,Tt,Yt,Kt){return xe(Xe,ot,Tt,Yt,void 0,Kt)}(B.distanceFromAnchor===0?w.tileAnchorPoint:new a.P(w.lineVertexArray.getx(qe),w.lineVertexArray.gety(qe)),ee,B.previousVertex,B.absOffsetX-B.distanceFromAnchor+1,w)}function vt(ue,w,B){let Q=ue+B.translation[0],ee=w+B.translation[1],le;return!B.pitchWithMap&&B.projection.useSpecialProjectionForSymbols?(le=B.projection.projectTileCoordinates(Q,ee,B.unwrappedTileID,B.getElevation),le.point.x=(.5*le.point.x+.5)*B.width,le.point.y=(.5*-le.point.y+.5)*B.height):(le=dt(Q,ee,B.labelPlaneMatrix,B.getElevation),le.isOccluded=!1),le}function ir(ue,w,B){return ue._unit()._perp()._mult(w*B)}function ar(ue,w,B,Q,ee,le,qe,Xe,ot){if(Xe.projectionCache.offsets[ue])return Xe.projectionCache.offsets[ue];let Tt=B.add(w);if(ue+ot.direction<Q||ue+ot.direction>=ee)return Xe.projectionCache.offsets[ue]=Tt,Tt;let Yt=ke(ue+ot.direction,Xe,ot),Kt=ir(Yt.sub(B),qe,ot.direction),xr=B.add(Kt),Ir=Yt.add(Kt);return Xe.projectionCache.offsets[ue]=a.ak(le,Tt,xr,Ir)||Tt,Xe.projectionCache.offsets[ue]}function vr(ue,w,B,Q,ee,le,qe,Xe,ot){let Tt=Q?ue-w:ue+w,Yt=Tt>0?1:-1,Kt=0;Q&&(Yt*=-1,Kt=Math.PI),Yt<0&&(Kt+=Math.PI);let xr,Ir=Yt>0?le+ee:le+ee+1;Xe.projectionCache.cachedAnchorPoint?xr=Xe.projectionCache.cachedAnchorPoint:(xr=vt(Xe.tileAnchorPoint.x,Xe.tileAnchorPoint.y,Xe).point,Xe.projectionCache.cachedAnchorPoint=xr);let ve,be,De=xr,Be=xr,et=0,We=0,it=Math.abs(Tt),Ft=[],Ht;for(;et+We<=it;){if(Ir+=Yt,Ir<le||Ir>=qe)return null;et+=We,Be=De,be=ve;let Sr={absOffsetX:it,direction:Yt,distanceFromAnchor:et,previousVertex:Be};if(De=ke(Ir,Xe,Sr),B===0)Ft.push(Be),Ht=De.sub(Be);else{let Or,Wr=De.sub(Be);Or=Wr.mag()===0?ir(ke(Ir+Yt,Xe,Sr).sub(De),B,Yt):ir(Wr,B,Yt),be||(be=Be.add(Or)),ve=ar(Ir,Or,De,le,qe,be,B,Xe,Sr),Ft.push(be),Ht=ve.sub(be)}We=Ht.mag()}let tr=Ht._mult((it-et)/We)._add(be||Be),dr=Kt+Math.atan2(De.y-Be.y,De.x-Be.x);return Ft.push(tr),{point:tr,angle:ot?dr:0,path:Ft}}let ii=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function pi(ue,w){for(let B=0;B<ue;B++){let Q=w.length;w.resize(Q+4),w.float32.set(ii,3*Q)}}function $r(ue,w,B){let Q=w[0],ee=w[1];return ue[0]=B[0]*Q+B[4]*ee+B[12],ue[1]=B[1]*Q+B[5]*ee+B[13],ue[3]=B[3]*Q+B[7]*ee+B[15],ue}let di=100;class ji{constructor(w,B,Q=new ti(w.width+200,w.height+200,25),ee=new ti(w.width+200,w.height+200,25)){this.transform=w,this.mapProjection=B,this.grid=Q,this.ignoredGrid=ee,this.pitchFactor=Math.cos(w._pitch)*w.cameraToCenterDistance,this.screenRightBoundary=w.width+di,this.screenBottomBoundary=w.height+di,this.gridRightBoundary=w.width+200,this.gridBottomBoundary=w.height+200,this.perspectiveRatioCutoff=.6}placeCollisionBox(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt){let xr=w.anchorPointX+ot[0],Ir=w.anchorPointY+ot[1],ve=this.projectAndGetPerspectiveRatio(ee,xr,Ir,le,Yt),be=Q*ve.perspectiveRatio,De;if(qe||Xe)De=this._projectCollisionBox(w,be,ee,le,qe,Xe,ot,ve,Yt,Kt);else{let Ft=ve.point.x+(Kt?Kt.x*be:0),Ht=ve.point.y+(Kt?Kt.y*be:0);De={allPointsOccluded:!1,box:[Ft+w.x1*be,Ht+w.y1*be,Ft+w.x2*be,Ht+w.y2*be]}}let[Be,et,We,it]=De.box;return this.mapProjection.useSpecialProjectionForSymbols&&(qe?De.allPointsOccluded:this.mapProjection.isOccluded(xr,Ir,le))||ve.perspectiveRatio<this.perspectiveRatioCutoff||!this.isInsideGrid(Be,et,We,it)||B!==\"always\"&&this.grid.hitTest(Be,et,We,it,B,Tt)?{box:[Be,et,We,it],placeable:!1,offscreen:!1}:{box:[Be,et,We,it],placeable:!0,offscreen:this.isOffscreen(Be,et,We,it)}}placeCollisionCircles(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve,be,De){let Be=[],et=new a.P(B.anchorX,B.anchorY),We=this.getPerspectiveRatio(qe,et.x,et.y,Xe,De),it=(Kt?le/We:le*We)/a.ap,Ft={getElevation:De,labelPlaneMatrix:ot,lineVertexArray:Q,pitchWithMap:Kt,projectionCache:{projections:{},offsets:{},cachedAnchorPoint:void 0,anyProjectionOccluded:!1},projection:this.mapProjection,tileAnchorPoint:et,unwrappedTileID:Xe,width:this.transform.width,height:this.transform.height,translation:be},Ht=tt(it,ee,B.lineOffsetX*it,B.lineOffsetY*it,!1,B,!1,Ft),tr=!1,dr=!1,Sr=!0;if(Ht){let Or=.5*Ir*We+ve,Wr=new a.P(-100,-100),ni=new a.P(this.screenRightBoundary,this.screenBottomBoundary),Pi=new Tr,cn=Ht.first,ln=Ht.last,Cn=[];for(let fa=cn.path.length-1;fa>=1;fa--)Cn.push(cn.path[fa]);for(let fa=1;fa<ln.path.length;fa++)Cn.push(ln.path[fa]);let Kn=2.5*Or;if(Tt){let fa=this.projectPathToScreenSpace(Cn,Ft,Tt);Cn=fa.some($a=>$a.signedDistanceFromCamera<=0)?[]:fa.map($a=>$a.point)}let Ta=[];if(Cn.length>0){let fa=Cn[0].clone(),$a=Cn[0].clone();for(let Co=1;Co<Cn.length;Co++)fa.x=Math.min(fa.x,Cn[Co].x),fa.y=Math.min(fa.y,Cn[Co].y),$a.x=Math.max($a.x,Cn[Co].x),$a.y=Math.max($a.y,Cn[Co].y);Ta=fa.x>=Wr.x&&$a.x<=ni.x&&fa.y>=Wr.y&&$a.y<=ni.y?[Cn]:$a.x<Wr.x||fa.x>ni.x||$a.y<Wr.y||fa.y>ni.y?[]:a.al([Cn],Wr.x,Wr.y,ni.x,ni.y)}for(let fa of Ta){Pi.reset(fa,.25*Or);let $a=0;$a=Pi.length<=.5*Or?1:Math.ceil(Pi.paddedLength/Kn)+1;for(let Co=0;Co<$a;Co++){let Qa=Co/Math.max($a-1,1),mo=Pi.lerp(Qa),Bo=mo.x+di,Ps=mo.y+di;Be.push(Bo,Ps,Or,0);let Ts=Bo-Or,wo=Ps-Or,To=Bo+Or,hl=Ps+Or;if(Sr=Sr&&this.isOffscreen(Ts,wo,To,hl),dr=dr||this.isInsideGrid(Ts,wo,To,hl),w!==\"always\"&&this.grid.hitTestCircle(Bo,Ps,Or,w,xr)&&(tr=!0,!Yt))return{circles:[],offscreen:!1,collisionDetected:tr}}}}return{circles:!Yt&&tr||!dr||We<this.perspectiveRatioCutoff?[]:Be,offscreen:Sr,collisionDetected:tr}}projectPathToScreenSpace(w,B,Q){return w.map(ee=>dt(ee.x,ee.y,Q,B.getElevation))}queryRenderedSymbols(w){if(w.length===0||this.grid.keysLength()===0&&this.ignoredGrid.keysLength()===0)return{};let B=[],Q=1/0,ee=1/0,le=-1/0,qe=-1/0;for(let Yt of w){let Kt=new a.P(Yt.x+di,Yt.y+di);Q=Math.min(Q,Kt.x),ee=Math.min(ee,Kt.y),le=Math.max(le,Kt.x),qe=Math.max(qe,Kt.y),B.push(Kt)}let Xe=this.grid.query(Q,ee,le,qe).concat(this.ignoredGrid.query(Q,ee,le,qe)),ot={},Tt={};for(let Yt of Xe){let Kt=Yt.key;if(ot[Kt.bucketInstanceId]===void 0&&(ot[Kt.bucketInstanceId]={}),ot[Kt.bucketInstanceId][Kt.featureIndex])continue;let xr=[new a.P(Yt.x1,Yt.y1),new a.P(Yt.x2,Yt.y1),new a.P(Yt.x2,Yt.y2),new a.P(Yt.x1,Yt.y2)];a.am(B,xr)&&(ot[Kt.bucketInstanceId][Kt.featureIndex]=!0,Tt[Kt.bucketInstanceId]===void 0&&(Tt[Kt.bucketInstanceId]=[]),Tt[Kt.bucketInstanceId].push(Kt.featureIndex))}return Tt}insertCollisionBox(w,B,Q,ee,le,qe){(Q?this.ignoredGrid:this.grid).insert({bucketInstanceId:ee,featureIndex:le,collisionGroupID:qe,overlapMode:B},w[0],w[1],w[2],w[3])}insertCollisionCircles(w,B,Q,ee,le,qe){let Xe=Q?this.ignoredGrid:this.grid,ot={bucketInstanceId:ee,featureIndex:le,collisionGroupID:qe,overlapMode:B};for(let Tt=0;Tt<w.length;Tt+=4)Xe.insertCircle(ot,w[Tt],w[Tt+1],w[Tt+2])}projectAndGetPerspectiveRatio(w,B,Q,ee,le){let qe;le?(qe=[B,Q,le(B,Q),1],a.af(qe,qe,w)):(qe=[B,Q,0,1],$r(qe,qe,w));let Xe=qe[3];return{point:new a.P((qe[0]/Xe+1)/2*this.transform.width+di,(-qe[1]/Xe+1)/2*this.transform.height+di),perspectiveRatio:.5+this.transform.cameraToCenterDistance/Xe*.5,isOccluded:!1,signedDistanceFromCamera:Xe}}getPerspectiveRatio(w,B,Q,ee,le){let qe=this.mapProjection.useSpecialProjectionForSymbols?this.mapProjection.projectTileCoordinates(B,Q,ee,le):dt(B,Q,w,le);return .5+this.transform.cameraToCenterDistance/qe.signedDistanceFromCamera*.5}isOffscreen(w,B,Q,ee){return Q<di||w>=this.screenRightBoundary||ee<di||B>this.screenBottomBoundary}isInsideGrid(w,B,Q,ee){return Q>=0&&w<this.gridRightBoundary&&ee>=0&&B<this.gridBottomBoundary}getViewportMatrix(){let w=a.an([]);return a.J(w,w,[-100,-100,0]),w}_projectCollisionBox(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt){let Kt=new a.P(1,0),xr=new a.P(0,1),Ir=new a.P(w.anchorPointX+Xe[0],w.anchorPointY+Xe[1]);if(qe&&!le){let Sr=this.projectAndGetPerspectiveRatio(Q,Ir.x+1,Ir.y,ee,Tt).point.sub(ot.point).unit(),Or=Math.atan(Sr.y/Sr.x)+(Sr.x<0?Math.PI:0),Wr=Math.sin(Or),ni=Math.cos(Or);Kt=new a.P(ni,Wr),xr=new a.P(-Wr,ni)}else if(!qe&&le){let Sr=-this.transform.angle,Or=Math.sin(Sr),Wr=Math.cos(Sr);Kt=new a.P(Wr,Or),xr=new a.P(-Or,Wr)}let ve=ot.point,be=B;if(le){ve=Ir;let Sr=this.transform.zoom-Math.floor(this.transform.zoom);be=Math.pow(2,-Sr),be*=this.mapProjection.getPitchedTextCorrection(this.transform,Ir,ee),Yt||(be*=a.ac(.5+ot.signedDistanceFromCamera/this.transform.cameraToCenterDistance*.5,0,4))}Yt&&(ve=ve.add(Kt.mult(Yt.x*be)).add(xr.mult(Yt.y*be)));let De=w.x1*be,Be=w.x2*be,et=(De+Be)/2,We=w.y1*be,it=w.y2*be,Ft=(We+it)/2,Ht=[{offsetX:De,offsetY:We},{offsetX:et,offsetY:We},{offsetX:Be,offsetY:We},{offsetX:Be,offsetY:Ft},{offsetX:Be,offsetY:it},{offsetX:et,offsetY:it},{offsetX:De,offsetY:it},{offsetX:De,offsetY:Ft}],tr=[];for(let{offsetX:Sr,offsetY:Or}of Ht)tr.push(new a.P(ve.x+Kt.x*Sr+xr.x*Or,ve.y+Kt.y*Sr+xr.y*Or));let dr=!1;if(le){let Sr=tr.map(Or=>this.projectAndGetPerspectiveRatio(Q,Or.x,Or.y,ee,Tt));dr=Sr.some(Or=>!Or.isOccluded),tr=Sr.map(Or=>Or.point)}else dr=!0;return{box:a.ao(tr),allPointsOccluded:!dr}}}function In(ue,w,B){return w*(a.X/(ue.tileSize*Math.pow(2,B-ue.tileID.overscaledZ)))}class wi{constructor(w,B,Q,ee){this.opacity=w?Math.max(0,Math.min(1,w.opacity+(w.placed?B:-B))):ee&&Q?1:0,this.placed=Q}isHidden(){return this.opacity===0&&!this.placed}}class On{constructor(w,B,Q,ee,le){this.text=new wi(w?w.text:null,B,Q,le),this.icon=new wi(w?w.icon:null,B,ee,le)}isHidden(){return this.text.isHidden()&&this.icon.isHidden()}}class qn{constructor(w,B,Q){this.text=w,this.icon=B,this.skipFade=Q}}class Fn{constructor(){this.invProjMatrix=a.H(),this.viewportMatrix=a.H(),this.circles=[]}}class ra{constructor(w,B,Q,ee,le){this.bucketInstanceId=w,this.featureIndex=B,this.sourceLayerIndex=Q,this.bucketIndex=ee,this.tileID=le}}class la{constructor(w){this.crossSourceCollisions=w,this.maxGroupID=0,this.collisionGroups={}}get(w){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[w]){let B=++this.maxGroupID;this.collisionGroups[w]={ID:B,predicate:Q=>Q.collisionGroupID===B}}return this.collisionGroups[w]}}function Ut(ue,w,B,Q,ee){let{horizontalAlign:le,verticalAlign:qe}=a.au(ue);return new a.P(-(le-.5)*w+Q[0]*ee,-(qe-.5)*B+Q[1]*ee)}class wt{constructor(w,B,Q,ee,le,qe){this.transform=w.clone(),this.terrain=Q,this.collisionIndex=new ji(this.transform,B),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=ee,this.retainedQueryData={},this.collisionGroups=new la(le),this.collisionCircleArrays={},this.collisionBoxArrays=new Map,this.prevPlacement=qe,qe&&(qe.prevPlacement=void 0),this.placedOrientations={}}_getTerrainElevationFunc(w){let B=this.terrain;return B?(Q,ee)=>B.getElevation(w,Q,ee):null}getBucketParts(w,B,Q,ee){let le=Q.getBucket(B),qe=Q.latestFeatureIndex;if(!le||!qe||B.id!==le.layerIds[0])return;let Xe=Q.collisionBoxArray,ot=le.layers[0].layout,Tt=le.layers[0].paint,Yt=Math.pow(2,this.transform.zoom-Q.tileID.overscaledZ),Kt=Q.tileSize/a.X,xr=Q.tileID.toUnwrapped(),Ir=this.transform.calculatePosMatrix(xr),ve=ot.get(\"text-pitch-alignment\")===\"map\",be=ot.get(\"text-rotation-alignment\")===\"map\",De=In(Q,1,this.transform.zoom),Be=this.collisionIndex.mapProjection.translatePosition(this.transform,Q,Tt.get(\"text-translate\"),Tt.get(\"text-translate-anchor\")),et=this.collisionIndex.mapProjection.translatePosition(this.transform,Q,Tt.get(\"icon-translate\"),Tt.get(\"icon-translate-anchor\")),We=Br(Ir,ve,be,this.transform,De),it=null;if(ve){let Ht=Vr(Ir,ve,be,this.transform,De);it=a.L([],this.transform.labelPlaneMatrix,Ht)}this.retainedQueryData[le.bucketInstanceId]=new ra(le.bucketInstanceId,qe,le.sourceLayerIndex,le.index,Q.tileID);let Ft={bucket:le,layout:ot,translationText:Be,translationIcon:et,posMatrix:Ir,unwrappedTileID:xr,textLabelPlaneMatrix:We,labelToScreenMatrix:it,scale:Yt,textPixelRatio:Kt,holdingForFade:Q.holdingForFade(),collisionBoxArray:Xe,partiallyEvaluatedTextSize:a.ag(le.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(le.sourceID)};if(ee)for(let Ht of le.sortKeyRanges){let{sortKey:tr,symbolInstanceStart:dr,symbolInstanceEnd:Sr}=Ht;w.push({sortKey:tr,symbolInstanceStart:dr,symbolInstanceEnd:Sr,parameters:Ft})}else w.push({symbolInstanceStart:0,symbolInstanceEnd:le.symbolInstances.length,parameters:Ft})}attemptAnchorPlacement(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve,be,De,Be,et,We){let it=a.aq[w.textAnchor],Ft=[w.textOffset0,w.textOffset1],Ht=Ut(it,Q,ee,Ft,le),tr=this.collisionIndex.placeCollisionBox(B,xr,ot,Tt,Yt,Xe,qe,De,Kt.predicate,We,Ht);if((!et||this.collisionIndex.placeCollisionBox(et,xr,ot,Tt,Yt,Xe,qe,Be,Kt.predicate,We,Ht).placeable)&&tr.placeable){let dr;if(this.prevPlacement&&this.prevPlacement.variableOffsets[Ir.crossTileID]&&this.prevPlacement.placements[Ir.crossTileID]&&this.prevPlacement.placements[Ir.crossTileID].text&&(dr=this.prevPlacement.variableOffsets[Ir.crossTileID].anchor),Ir.crossTileID===0)throw new Error(\"symbolInstance.crossTileID can't be 0\");return this.variableOffsets[Ir.crossTileID]={textOffset:Ft,width:Q,height:ee,anchor:it,textBoxScale:le,prevAnchor:dr},this.markUsedJustification(ve,it,Ir,be),ve.allowVerticalPlacement&&(this.markUsedOrientation(ve,be,Ir),this.placedOrientations[Ir.crossTileID]=be),{shift:Ht,placedGlyphBoxes:tr}}}placeLayerBucketPart(w,B,Q){let{bucket:ee,layout:le,translationText:qe,translationIcon:Xe,posMatrix:ot,unwrappedTileID:Tt,textLabelPlaneMatrix:Yt,labelToScreenMatrix:Kt,textPixelRatio:xr,holdingForFade:Ir,collisionBoxArray:ve,partiallyEvaluatedTextSize:be,collisionGroup:De}=w.parameters,Be=le.get(\"text-optional\"),et=le.get(\"icon-optional\"),We=a.ar(le,\"text-overlap\",\"text-allow-overlap\"),it=We===\"always\",Ft=a.ar(le,\"icon-overlap\",\"icon-allow-overlap\"),Ht=Ft===\"always\",tr=le.get(\"text-rotation-alignment\")===\"map\",dr=le.get(\"text-pitch-alignment\")===\"map\",Sr=le.get(\"icon-text-fit\")!==\"none\",Or=le.get(\"symbol-z-order\")===\"viewport-y\",Wr=it&&(Ht||!ee.hasIconData()||et),ni=Ht&&(it||!ee.hasTextData()||Be);!ee.collisionArrays&&ve&&ee.deserializeCollisionBoxes(ve);let Pi=this._getTerrainElevationFunc(this.retainedQueryData[ee.bucketInstanceId].tileID),cn=(ln,Cn,Kn)=>{var Ta,fa;if(B[ln.crossTileID])return;if(Ir)return void(this.placements[ln.crossTileID]=new qn(!1,!1,!1));let $a=!1,Co=!1,Qa=!0,mo=null,Bo={box:null,placeable:!1,offscreen:null},Ps={box:null,placeable:!1,offscreen:null},Ts=null,wo=null,To=null,hl=0,Ul=0,Lu=0;Cn.textFeatureIndex?hl=Cn.textFeatureIndex:ln.useRuntimeCollisionCircles&&(hl=ln.featureIndex),Cn.verticalTextFeatureIndex&&(Ul=Cn.verticalTextFeatureIndex);let au=Cn.textBox;if(au){let Tl=Te=>{let Ne=a.ah.horizontal;if(ee.allowVerticalPlacement&&!Te&&this.prevPlacement){let He=this.prevPlacement.placedOrientations[ln.crossTileID];He&&(this.placedOrientations[ln.crossTileID]=He,Ne=He,this.markUsedOrientation(ee,Ne,ln))}return Ne},Al=(Te,Ne)=>{if(ee.allowVerticalPlacement&&ln.numVerticalGlyphVertices>0&&Cn.verticalTextBox){for(let He of ee.writingModes)if(He===a.ah.vertical?(Bo=Ne(),Ps=Bo):Bo=Te(),Bo&&Bo.placeable)break}else Bo=Te()},X=ln.textAnchorOffsetStartIndex,se=ln.textAnchorOffsetEndIndex;if(se===X){let Te=(Ne,He)=>{let Ye=this.collisionIndex.placeCollisionBox(Ne,We,xr,ot,Tt,dr,tr,qe,De.predicate,Pi);return Ye&&Ye.placeable&&(this.markUsedOrientation(ee,He,ln),this.placedOrientations[ln.crossTileID]=He),Ye};Al(()=>Te(au,a.ah.horizontal),()=>{let Ne=Cn.verticalTextBox;return ee.allowVerticalPlacement&&ln.numVerticalGlyphVertices>0&&Ne?Te(Ne,a.ah.vertical):{box:null,offscreen:null}}),Tl(Bo&&Bo.placeable)}else{let Te=a.aq[(fa=(Ta=this.prevPlacement)===null||Ta===void 0?void 0:Ta.variableOffsets[ln.crossTileID])===null||fa===void 0?void 0:fa.anchor],Ne=(Ye,kt,nt)=>{let jt=Ye.x2-Ye.x1,gr=Ye.y2-Ye.y1,yr=ln.textBoxScale,Hr=Sr&&Ft===\"never\"?kt:null,qr=null,_i=We===\"never\"?1:2,bi=\"never\";Te&&_i++;for(let Zr=0;Zr<_i;Zr++){for(let ai=X;ai<se;ai++){let gi=ee.textAnchorOffsets.get(ai);if(Te&&gi.textAnchor!==Te)continue;let Ii=this.attemptAnchorPlacement(gi,Ye,jt,gr,yr,tr,dr,xr,ot,Tt,De,bi,ln,ee,nt,qe,Xe,Hr,Pi);if(Ii&&(qr=Ii.placedGlyphBoxes,qr&&qr.placeable))return $a=!0,mo=Ii.shift,qr}Te?Te=null:bi=We}return Q&&!qr&&(qr={box:this.collisionIndex.placeCollisionBox(au,\"always\",xr,ot,Tt,dr,tr,qe,De.predicate,Pi,new a.P(0,0)).box,offscreen:!1,placeable:!1}),qr};Al(()=>Ne(au,Cn.iconBox,a.ah.horizontal),()=>{let Ye=Cn.verticalTextBox;return ee.allowVerticalPlacement&&(!Bo||!Bo.placeable)&&ln.numVerticalGlyphVertices>0&&Ye?Ne(Ye,Cn.verticalIconBox,a.ah.vertical):{box:null,occluded:!0,offscreen:null}}),Bo&&($a=Bo.placeable,Qa=Bo.offscreen);let He=Tl(Bo&&Bo.placeable);if(!$a&&this.prevPlacement){let Ye=this.prevPlacement.variableOffsets[ln.crossTileID];Ye&&(this.variableOffsets[ln.crossTileID]=Ye,this.markUsedJustification(ee,Ye.anchor,ln,He))}}}if(Ts=Bo,$a=Ts&&Ts.placeable,Qa=Ts&&Ts.offscreen,ln.useRuntimeCollisionCircles){let Tl=ee.text.placedSymbolArray.get(ln.centerJustifiedTextSymbolIndex),Al=a.ai(ee.textSizeData,be,Tl),X=le.get(\"text-padding\");wo=this.collisionIndex.placeCollisionCircles(We,Tl,ee.lineVertexArray,ee.glyphOffsetArray,Al,ot,Tt,Yt,Kt,Q,dr,De.predicate,ln.collisionCircleDiameter,X,qe,Pi),wo.circles.length&&wo.collisionDetected&&!Q&&a.w(\"Collisions detected, but collision boxes are not shown\"),$a=it||wo.circles.length>0&&!wo.collisionDetected,Qa=Qa&&wo.offscreen}if(Cn.iconFeatureIndex&&(Lu=Cn.iconFeatureIndex),Cn.iconBox){let Tl=Al=>this.collisionIndex.placeCollisionBox(Al,Ft,xr,ot,Tt,dr,tr,Xe,De.predicate,Pi,Sr&&mo?mo:void 0);Ps&&Ps.placeable&&Cn.verticalIconBox?(To=Tl(Cn.verticalIconBox),Co=To.placeable):(To=Tl(Cn.iconBox),Co=To.placeable),Qa=Qa&&To.offscreen}let Js=Be||ln.numHorizontalGlyphVertices===0&&ln.numVerticalGlyphVertices===0,Ql=et||ln.numIconVertices===0;Js||Ql?Ql?Js||(Co=Co&&$a):$a=Co&&$a:Co=$a=Co&&$a;let dc=Co&&To.placeable;if($a&&Ts.placeable&&this.collisionIndex.insertCollisionBox(Ts.box,We,le.get(\"text-ignore-placement\"),ee.bucketInstanceId,Ps&&Ps.placeable&&Ul?Ul:hl,De.ID),dc&&this.collisionIndex.insertCollisionBox(To.box,Ft,le.get(\"icon-ignore-placement\"),ee.bucketInstanceId,Lu,De.ID),wo&&$a&&this.collisionIndex.insertCollisionCircles(wo.circles,We,le.get(\"text-ignore-placement\"),ee.bucketInstanceId,hl,De.ID),Q&&this.storeCollisionData(ee.bucketInstanceId,Kn,Cn,Ts,To,wo),ln.crossTileID===0)throw new Error(\"symbolInstance.crossTileID can't be 0\");if(ee.bucketInstanceId===0)throw new Error(\"bucket.bucketInstanceId can't be 0\");this.placements[ln.crossTileID]=new qn($a||Wr,Co||ni,Qa||ee.justReloaded),B[ln.crossTileID]=!0};if(Or){if(w.symbolInstanceStart!==0)throw new Error(\"bucket.bucketInstanceId should be 0\");let ln=ee.getSortedSymbolIndexes(this.transform.angle);for(let Cn=ln.length-1;Cn>=0;--Cn){let Kn=ln[Cn];cn(ee.symbolInstances.get(Kn),ee.collisionArrays[Kn],Kn)}}else for(let ln=w.symbolInstanceStart;ln<w.symbolInstanceEnd;ln++)cn(ee.symbolInstances.get(ln),ee.collisionArrays[ln],ln);if(Q&&ee.bucketInstanceId in this.collisionCircleArrays){let ln=this.collisionCircleArrays[ee.bucketInstanceId];a.as(ln.invProjMatrix,ot),ln.viewportMatrix=this.collisionIndex.getViewportMatrix()}ee.justReloaded=!1}storeCollisionData(w,B,Q,ee,le,qe){if(Q.textBox||Q.iconBox){let Xe,ot;this.collisionBoxArrays.has(w)?Xe=this.collisionBoxArrays.get(w):(Xe=new Map,this.collisionBoxArrays.set(w,Xe)),Xe.has(B)?ot=Xe.get(B):(ot={text:null,icon:null},Xe.set(B,ot)),Q.textBox&&(ot.text=ee.box),Q.iconBox&&(ot.icon=le.box)}if(qe){let Xe=this.collisionCircleArrays[w];Xe===void 0&&(Xe=this.collisionCircleArrays[w]=new Fn);for(let ot=0;ot<qe.circles.length;ot+=4)Xe.circles.push(qe.circles[ot+0]),Xe.circles.push(qe.circles[ot+1]),Xe.circles.push(qe.circles[ot+2]),Xe.circles.push(qe.collisionDetected?1:0)}}markUsedJustification(w,B,Q,ee){let le;le=ee===a.ah.vertical?Q.verticalPlacedTextSymbolIndex:{left:Q.leftJustifiedTextSymbolIndex,center:Q.centerJustifiedTextSymbolIndex,right:Q.rightJustifiedTextSymbolIndex}[a.at(B)];let qe=[Q.leftJustifiedTextSymbolIndex,Q.centerJustifiedTextSymbolIndex,Q.rightJustifiedTextSymbolIndex,Q.verticalPlacedTextSymbolIndex];for(let Xe of qe)Xe>=0&&(w.text.placedSymbolArray.get(Xe).crossTileID=le>=0&&Xe!==le?0:Q.crossTileID)}markUsedOrientation(w,B,Q){let ee=B===a.ah.horizontal||B===a.ah.horizontalOnly?B:0,le=B===a.ah.vertical?B:0,qe=[Q.leftJustifiedTextSymbolIndex,Q.centerJustifiedTextSymbolIndex,Q.rightJustifiedTextSymbolIndex];for(let Xe of qe)w.text.placedSymbolArray.get(Xe).placedOrientation=ee;Q.verticalPlacedTextSymbolIndex&&(w.text.placedSymbolArray.get(Q.verticalPlacedTextSymbolIndex).placedOrientation=le)}commit(w){this.commitTime=w,this.zoomAtLastRecencyCheck=this.transform.zoom;let B=this.prevPlacement,Q=!1;this.prevZoomAdjustment=B?B.zoomAdjustment(this.transform.zoom):0;let ee=B?B.symbolFadeChange(w):1,le=B?B.opacities:{},qe=B?B.variableOffsets:{},Xe=B?B.placedOrientations:{};for(let ot in this.placements){let Tt=this.placements[ot],Yt=le[ot];Yt?(this.opacities[ot]=new On(Yt,ee,Tt.text,Tt.icon),Q=Q||Tt.text!==Yt.text.placed||Tt.icon!==Yt.icon.placed):(this.opacities[ot]=new On(null,ee,Tt.text,Tt.icon,Tt.skipFade),Q=Q||Tt.text||Tt.icon)}for(let ot in le){let Tt=le[ot];if(!this.opacities[ot]){let Yt=new On(Tt,ee,!1,!1);Yt.isHidden()||(this.opacities[ot]=Yt,Q=Q||Tt.text.placed||Tt.icon.placed)}}for(let ot in qe)this.variableOffsets[ot]||!this.opacities[ot]||this.opacities[ot].isHidden()||(this.variableOffsets[ot]=qe[ot]);for(let ot in Xe)this.placedOrientations[ot]||!this.opacities[ot]||this.opacities[ot].isHidden()||(this.placedOrientations[ot]=Xe[ot]);if(B&&B.lastPlacementChangeTime===void 0)throw new Error(\"Last placement time for previous placement is not defined\");Q?this.lastPlacementChangeTime=w:typeof this.lastPlacementChangeTime!=\"number\"&&(this.lastPlacementChangeTime=B?B.lastPlacementChangeTime:w)}updateLayerOpacities(w,B){let Q={};for(let ee of B){let le=ee.getBucket(w);le&&ee.latestFeatureIndex&&w.id===le.layerIds[0]&&this.updateBucketOpacities(le,ee.tileID,Q,ee.collisionBoxArray)}}updateBucketOpacities(w,B,Q,ee){w.hasTextData()&&(w.text.opacityVertexArray.clear(),w.text.hasVisibleVertices=!1),w.hasIconData()&&(w.icon.opacityVertexArray.clear(),w.icon.hasVisibleVertices=!1),w.hasIconCollisionBoxData()&&w.iconCollisionBox.collisionVertexArray.clear(),w.hasTextCollisionBoxData()&&w.textCollisionBox.collisionVertexArray.clear();let le=w.layers[0],qe=le.layout,Xe=new On(null,0,!1,!1,!0),ot=qe.get(\"text-allow-overlap\"),Tt=qe.get(\"icon-allow-overlap\"),Yt=le._unevaluatedLayout.hasValue(\"text-variable-anchor\")||le._unevaluatedLayout.hasValue(\"text-variable-anchor-offset\"),Kt=qe.get(\"text-rotation-alignment\")===\"map\",xr=qe.get(\"text-pitch-alignment\")===\"map\",Ir=qe.get(\"icon-text-fit\")!==\"none\",ve=new On(null,0,ot&&(Tt||!w.hasIconData()||qe.get(\"icon-optional\")),Tt&&(ot||!w.hasTextData()||qe.get(\"text-optional\")),!0);!w.collisionArrays&&ee&&(w.hasIconCollisionBoxData()||w.hasTextCollisionBoxData())&&w.deserializeCollisionBoxes(ee);let be=(Be,et,We)=>{for(let it=0;it<et/4;it++)Be.opacityVertexArray.emplaceBack(We);Be.hasVisibleVertices=Be.hasVisibleVertices||We!==fn},De=this.collisionBoxArrays.get(w.bucketInstanceId);for(let Be=0;Be<w.symbolInstances.length;Be++){let et=w.symbolInstances.get(Be),{numHorizontalGlyphVertices:We,numVerticalGlyphVertices:it,crossTileID:Ft}=et,Ht=this.opacities[Ft];Q[Ft]?Ht=Xe:Ht||(Ht=ve,this.opacities[Ft]=Ht),Q[Ft]=!0;let tr=et.numIconVertices>0,dr=this.placedOrientations[et.crossTileID],Sr=dr===a.ah.vertical,Or=dr===a.ah.horizontal||dr===a.ah.horizontalOnly;if(We>0||it>0){let ni=tn(Ht.text);be(w.text,We,Sr?fn:ni),be(w.text,it,Or?fn:ni);let Pi=Ht.text.isHidden();[et.rightJustifiedTextSymbolIndex,et.centerJustifiedTextSymbolIndex,et.leftJustifiedTextSymbolIndex].forEach(Cn=>{Cn>=0&&(w.text.placedSymbolArray.get(Cn).hidden=Pi||Sr?1:0)}),et.verticalPlacedTextSymbolIndex>=0&&(w.text.placedSymbolArray.get(et.verticalPlacedTextSymbolIndex).hidden=Pi||Or?1:0);let cn=this.variableOffsets[et.crossTileID];cn&&this.markUsedJustification(w,cn.anchor,et,dr);let ln=this.placedOrientations[et.crossTileID];ln&&(this.markUsedJustification(w,\"left\",et,ln),this.markUsedOrientation(w,ln,et))}if(tr){let ni=tn(Ht.icon),Pi=!(Ir&&et.verticalPlacedIconSymbolIndex&&Sr);et.placedIconSymbolIndex>=0&&(be(w.icon,et.numIconVertices,Pi?ni:fn),w.icon.placedSymbolArray.get(et.placedIconSymbolIndex).hidden=Ht.icon.isHidden()),et.verticalPlacedIconSymbolIndex>=0&&(be(w.icon,et.numVerticalIconVertices,Pi?fn:ni),w.icon.placedSymbolArray.get(et.verticalPlacedIconSymbolIndex).hidden=Ht.icon.isHidden())}let Wr=De&&De.has(Be)?De.get(Be):{text:null,icon:null};if(w.hasIconCollisionBoxData()||w.hasTextCollisionBoxData()){let ni=w.collisionArrays[Be];if(ni){let Pi=new a.P(0,0);if(ni.textBox||ni.verticalTextBox){let cn=!0;if(Yt){let ln=this.variableOffsets[Ft];ln?(Pi=Ut(ln.anchor,ln.width,ln.height,ln.textOffset,ln.textBoxScale),Kt&&Pi._rotate(xr?this.transform.angle:-this.transform.angle)):cn=!1}if(ni.textBox||ni.verticalTextBox){let ln;ni.textBox&&(ln=Sr),ni.verticalTextBox&&(ln=Or),rr(w.textCollisionBox.collisionVertexArray,Ht.text.placed,!cn||ln,Wr.text,Pi.x,Pi.y)}}if(ni.iconBox||ni.verticalIconBox){let cn=!!(!Or&&ni.verticalIconBox),ln;ni.iconBox&&(ln=cn),ni.verticalIconBox&&(ln=!cn),rr(w.iconCollisionBox.collisionVertexArray,Ht.icon.placed,ln,Wr.icon,Ir?Pi.x:0,Ir?Pi.y:0)}}}}if(w.sortFeatures(this.transform.angle),this.retainedQueryData[w.bucketInstanceId]&&(this.retainedQueryData[w.bucketInstanceId].featureSortOrder=w.featureSortOrder),w.hasTextData()&&w.text.opacityVertexBuffer&&w.text.opacityVertexBuffer.updateData(w.text.opacityVertexArray),w.hasIconData()&&w.icon.opacityVertexBuffer&&w.icon.opacityVertexBuffer.updateData(w.icon.opacityVertexArray),w.hasIconCollisionBoxData()&&w.iconCollisionBox.collisionVertexBuffer&&w.iconCollisionBox.collisionVertexBuffer.updateData(w.iconCollisionBox.collisionVertexArray),w.hasTextCollisionBoxData()&&w.textCollisionBox.collisionVertexBuffer&&w.textCollisionBox.collisionVertexBuffer.updateData(w.textCollisionBox.collisionVertexArray),w.text.opacityVertexArray.length!==w.text.layoutVertexArray.length/4)throw new Error(`bucket.text.opacityVertexArray.length (= ${w.text.opacityVertexArray.length}) !== bucket.text.layoutVertexArray.length (= ${w.text.layoutVertexArray.length}) / 4`);if(w.icon.opacityVertexArray.length!==w.icon.layoutVertexArray.length/4)throw new Error(`bucket.icon.opacityVertexArray.length (= ${w.icon.opacityVertexArray.length}) !== bucket.icon.layoutVertexArray.length (= ${w.icon.layoutVertexArray.length}) / 4`);if(w.bucketInstanceId in this.collisionCircleArrays){let Be=this.collisionCircleArrays[w.bucketInstanceId];w.placementInvProjMatrix=Be.invProjMatrix,w.placementViewportMatrix=Be.viewportMatrix,w.collisionCircleArray=Be.circles,delete this.collisionCircleArrays[w.bucketInstanceId]}}symbolFadeChange(w){return this.fadeDuration===0?1:(w-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment}zoomAdjustment(w){return Math.max(0,(this.transform.zoom-w)/1.5)}hasTransitions(w){return this.stale||w-this.lastPlacementChangeTime<this.fadeDuration}stillRecent(w,B){let Q=this.zoomAtLastRecencyCheck===B?1-this.zoomAdjustment(B):1;return this.zoomAtLastRecencyCheck=B,this.commitTime+this.fadeDuration*Q>w}setStale(){this.stale=!0}}function rr(ue,w,B,Q,ee,le){Q&&Q.length!==0||(Q=[0,0,0,0]);let qe=Q[0]-di,Xe=Q[1]-di,ot=Q[2]-di,Tt=Q[3]-di;ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,qe,Xe),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,ot,Xe),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,ot,Tt),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,qe,Tt)}let nr=Math.pow(2,25),Er=Math.pow(2,24),Xr=Math.pow(2,17),ri=Math.pow(2,16),Qr=Math.pow(2,9),Oi=Math.pow(2,8),$i=Math.pow(2,1);function tn(ue){if(ue.opacity===0&&!ue.placed)return 0;if(ue.opacity===1&&ue.placed)return 4294967295;let w=ue.placed?1:0,B=Math.floor(127*ue.opacity);return B*nr+w*Er+B*Xr+w*ri+B*Qr+w*Oi+B*$i+w}let fn=0;function yn(){return{isOccluded:(ue,w,B)=>!1,getPitchedTextCorrection:(ue,w,B)=>1,get useSpecialProjectionForSymbols(){return!1},projectTileCoordinates(ue,w,B,Q){throw new Error(\"Not implemented.\")},translatePosition:(ue,w,B,Q)=>function(ee,le,qe,Xe,ot=!1){if(!qe[0]&&!qe[1])return[0,0];let Tt=ot?Xe===\"map\"?ee.angle:0:Xe===\"viewport\"?-ee.angle:0;if(Tt){let Yt=Math.sin(Tt),Kt=Math.cos(Tt);qe=[qe[0]*Kt-qe[1]*Yt,qe[0]*Yt+qe[1]*Kt]}return[ot?qe[0]:In(le,qe[0],ee.zoom),ot?qe[1]:In(le,qe[1],ee.zoom)]}(ue,w,B,Q),getCircleRadiusCorrection:ue=>1}}class Sn{constructor(w){this._sortAcrossTiles=w.layout.get(\"symbol-z-order\")!==\"viewport-y\"&&!w.layout.get(\"symbol-sort-key\").isConstant(),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]}continuePlacement(w,B,Q,ee,le){let qe=this._bucketParts;for(;this._currentTileIndex<w.length;)if(B.getBucketParts(qe,ee,w[this._currentTileIndex],this._sortAcrossTiles),this._currentTileIndex++,le())return!0;for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,qe.sort((Xe,ot)=>Xe.sortKey-ot.sortKey));this._currentPartIndex<qe.length;)if(B.placeLayerBucketPart(qe[this._currentPartIndex],this._seenCrossTileIDs,Q),this._currentPartIndex++,le())return!0;return!1}}class Ba{constructor(w,B,Q,ee,le,qe,Xe,ot){this.placement=new wt(w,yn(),B,qe,Xe,ot),this._currentPlacementIndex=Q.length-1,this._forceFullPlacement=ee,this._showCollisionBoxes=le,this._done=!1}isDone(){return this._done}continuePlacement(w,B,Q){let ee=u.now(),le=()=>!this._forceFullPlacement&&u.now()-ee>2;for(;this._currentPlacementIndex>=0;){let qe=B[w[this._currentPlacementIndex]],Xe=this.placement.collisionIndex.transform.zoom;if(qe.type===\"symbol\"&&(!qe.minzoom||qe.minzoom<=Xe)&&(!qe.maxzoom||qe.maxzoom>Xe)){if(this._inProgressLayer||(this._inProgressLayer=new Sn(qe)),this._inProgressLayer.continuePlacement(Q[qe.source],this.placement,this._showCollisionBoxes,qe,le))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0}commit(w){return this.placement.commit(w),this.placement}}let ua=512/a.X/2;class ma{constructor(w,B,Q){this.tileID=w,this.bucketInstanceId=Q,this._symbolsByKey={};let ee=new Map;for(let le=0;le<B.length;le++){let qe=B.get(le),Xe=qe.key,ot=ee.get(Xe);ot?ot.push(qe):ee.set(Xe,[qe])}for(let[le,qe]of ee){let Xe={positions:qe.map(ot=>({x:Math.floor(ot.anchorX*ua),y:Math.floor(ot.anchorY*ua)})),crossTileIDs:qe.map(ot=>ot.crossTileID)};if(Xe.positions.length>128){let ot=new a.av(Xe.positions.length,16,Uint16Array);for(let{x:Tt,y:Yt}of Xe.positions)ot.add(Tt,Yt);ot.finish(),delete Xe.positions,Xe.index=ot}this._symbolsByKey[le]=Xe}}getScaledCoordinates(w,B){let{x:Q,y:ee,z:le}=this.tileID.canonical,{x:qe,y:Xe,z:ot}=B.canonical,Tt=ua/Math.pow(2,ot-le),Yt=(Xe*a.X+w.anchorY)*Tt,Kt=ee*a.X*ua;return{x:Math.floor((qe*a.X+w.anchorX)*Tt-Q*a.X*ua),y:Math.floor(Yt-Kt)}}findMatches(w,B,Q){let ee=this.tileID.canonical.z<B.canonical.z?1:Math.pow(2,this.tileID.canonical.z-B.canonical.z);for(let le=0;le<w.length;le++){let qe=w.get(le);if(qe.crossTileID)continue;let Xe=this._symbolsByKey[qe.key];if(!Xe)continue;let ot=this.getScaledCoordinates(qe,B);if(Xe.index){let Tt=Xe.index.range(ot.x-ee,ot.y-ee,ot.x+ee,ot.y+ee).sort();for(let Yt of Tt){let Kt=Xe.crossTileIDs[Yt];if(!Q[Kt]){Q[Kt]=!0,qe.crossTileID=Kt;break}}}else if(Xe.positions)for(let Tt=0;Tt<Xe.positions.length;Tt++){let Yt=Xe.positions[Tt],Kt=Xe.crossTileIDs[Tt];if(Math.abs(Yt.x-ot.x)<=ee&&Math.abs(Yt.y-ot.y)<=ee&&!Q[Kt]){Q[Kt]=!0,qe.crossTileID=Kt;break}}}}getCrossTileIDsLists(){return Object.values(this._symbolsByKey).map(({crossTileIDs:w})=>w)}}class Wa{constructor(){this.maxCrossTileID=0}generate(){return++this.maxCrossTileID}}class Fa{constructor(){this.indexes={},this.usedCrossTileIDs={},this.lng=0}handleWrapJump(w){let B=Math.round((w-this.lng)/360);if(B!==0)for(let Q in this.indexes){let ee=this.indexes[Q],le={};for(let qe in ee){let Xe=ee[qe];Xe.tileID=Xe.tileID.unwrapTo(Xe.tileID.wrap+B),le[Xe.tileID.key]=Xe}this.indexes[Q]=le}this.lng=w}addBucket(w,B,Q){if(this.indexes[w.overscaledZ]&&this.indexes[w.overscaledZ][w.key]){if(this.indexes[w.overscaledZ][w.key].bucketInstanceId===B.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(w.overscaledZ,this.indexes[w.overscaledZ][w.key])}for(let le=0;le<B.symbolInstances.length;le++)B.symbolInstances.get(le).crossTileID=0;this.usedCrossTileIDs[w.overscaledZ]||(this.usedCrossTileIDs[w.overscaledZ]={});let ee=this.usedCrossTileIDs[w.overscaledZ];for(let le in this.indexes){let qe=this.indexes[le];if(Number(le)>w.overscaledZ)for(let Xe in qe){let ot=qe[Xe];ot.tileID.isChildOf(w)&&ot.findMatches(B.symbolInstances,w,ee)}else{let Xe=qe[w.scaledTo(Number(le)).key];Xe&&Xe.findMatches(B.symbolInstances,w,ee)}}for(let le=0;le<B.symbolInstances.length;le++){let qe=B.symbolInstances.get(le);qe.crossTileID||(qe.crossTileID=Q.generate(),ee[qe.crossTileID]=!0)}return this.indexes[w.overscaledZ]===void 0&&(this.indexes[w.overscaledZ]={}),this.indexes[w.overscaledZ][w.key]=new ma(w,B.symbolInstances,B.bucketInstanceId),!0}removeBucketCrossTileIDs(w,B){for(let Q of B.getCrossTileIDsLists())for(let ee of Q)delete this.usedCrossTileIDs[w][ee]}removeStaleBuckets(w){let B=!1;for(let Q in this.indexes){let ee=this.indexes[Q];for(let le in ee)w[ee[le].bucketInstanceId]||(this.removeBucketCrossTileIDs(Q,ee[le]),delete ee[le],B=!0)}return B}}class Wo{constructor(){this.layerIndexes={},this.crossTileIDs=new Wa,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}}addLayer(w,B,Q){let ee=this.layerIndexes[w.id];ee===void 0&&(ee=this.layerIndexes[w.id]=new Fa);let le=!1,qe={};ee.handleWrapJump(Q);for(let Xe of B){let ot=Xe.getBucket(w);ot&&w.id===ot.layerIds[0]&&(ot.bucketInstanceId||(ot.bucketInstanceId=++this.maxBucketInstanceId),ee.addBucket(Xe.tileID,ot,this.crossTileIDs)&&(le=!0),qe[ot.bucketInstanceId]=!0)}return ee.removeStaleBuckets(qe)&&(le=!0),le}pruneUnusedLayers(w){let B={};w.forEach(Q=>{B[Q]=!0});for(let Q in this.layerIndexes)B[Q]||delete this.layerIndexes[Q]}}let da=(ue,w)=>a.t(ue,w&&w.filter(B=>B.identifier!==\"source.canvas\")),Wn=a.aw();class Ga extends a.E{constructor(w,B={}){super(),this._rtlPluginLoaded=()=>{for(let Q in this.sourceCaches){let ee=this.sourceCaches[Q].getSource().type;ee!==\"vector\"&&ee!==\"geojson\"||this.sourceCaches[Q].reload()}},this.map=w,this.dispatcher=new Le(Se(),w._getMapId()),this.dispatcher.registerMessageHandler(\"GG\",(Q,ee)=>this.getGlyphs(Q,ee)),this.dispatcher.registerMessageHandler(\"GI\",(Q,ee)=>this.getImages(Q,ee)),this.imageManager=new T,this.imageManager.setEventedParent(this),this.glyphManager=new G(w._requestManager,B.localIdeographFontFamily),this.lineAtlas=new oe(256,512),this.crossTileSymbolIndex=new Wo,this._spritesImagesIds={},this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new a.ax,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"SR\",a.ay()),Qt().on(cr,this._rtlPluginLoaded),this.on(\"data\",Q=>{if(Q.dataType!==\"source\"||Q.sourceDataType!==\"metadata\")return;let ee=this.sourceCaches[Q.sourceId];if(!ee)return;let le=ee.getSource();if(le&&le.vectorLayerIds)for(let qe in this._layers){let Xe=this._layers[qe];Xe.source===le.id&&this._validateLayer(Xe)}})}loadURL(w,B={},Q){this.fire(new a.k(\"dataloading\",{dataType:\"style\"})),B.validate=typeof B.validate!=\"boolean\"||B.validate;let ee=this.map._requestManager.transformRequest(w,\"Style\");this._loadStyleRequest=new AbortController;let le=this._loadStyleRequest;a.h(ee,this._loadStyleRequest).then(qe=>{this._loadStyleRequest=null,this._load(qe.data,B,Q)}).catch(qe=>{this._loadStyleRequest=null,qe&&!le.signal.aborted&&this.fire(new a.j(qe))})}loadJSON(w,B={},Q){this.fire(new a.k(\"dataloading\",{dataType:\"style\"})),this._frameRequest=new AbortController,u.frameAsync(this._frameRequest).then(()=>{this._frameRequest=null,B.validate=B.validate!==!1,this._load(w,B,Q)}).catch(()=>{})}loadEmpty(){this.fire(new a.k(\"dataloading\",{dataType:\"style\"})),this._load(Wn,{validate:!1})}_load(w,B,Q){var ee;let le=B.transformStyle?B.transformStyle(Q,w):w;if(!B.validate||!da(this,a.u(le))){this._loaded=!0,this.stylesheet=le;for(let qe in le.sources)this.addSource(qe,le.sources[qe],{validate:!1});le.sprite?this._loadSprite(le.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(le.glyphs),this._createLayers(),this.light=new N(this.stylesheet.light),this.sky=new re(this.stylesheet.sky),this.map.setTerrain((ee=this.stylesheet.terrain)!==null&&ee!==void 0?ee:null),this.fire(new a.k(\"data\",{dataType:\"style\"})),this.fire(new a.k(\"style.load\"))}}_createLayers(){let w=a.az(this.stylesheet.layers);this.dispatcher.broadcast(\"SL\",w),this._order=w.map(B=>B.id),this._layers={},this._serializedLayers=null;for(let B of w){let Q=a.aA(B);Q.setEventedParent(this,{layer:{id:B.id}}),this._layers[B.id]=Q}}_loadSprite(w,B=!1,Q=void 0){let ee;this.imageManager.setLoaded(!1),this._spriteRequest=new AbortController,function(le,qe,Xe,ot){return a._(this,void 0,void 0,function*(){let Tt=C(le),Yt=Xe>1?\"@2x\":\"\",Kt={},xr={};for(let{id:Ir,url:ve}of Tt){let be=qe.transformRequest(M(ve,Yt,\".json\"),\"SpriteJSON\");Kt[Ir]=a.h(be,ot);let De=qe.transformRequest(M(ve,Yt,\".png\"),\"SpriteImage\");xr[Ir]=p.getImage(De,ot)}return yield Promise.all([...Object.values(Kt),...Object.values(xr)]),function(Ir,ve){return a._(this,void 0,void 0,function*(){let be={};for(let De in Ir){be[De]={};let Be=u.getImageCanvasContext((yield ve[De]).data),et=(yield Ir[De]).data;for(let We in et){let{width:it,height:Ft,x:Ht,y:tr,sdf:dr,pixelRatio:Sr,stretchX:Or,stretchY:Wr,content:ni,textFitWidth:Pi,textFitHeight:cn}=et[We];be[De][We]={data:null,pixelRatio:Sr,sdf:dr,stretchX:Or,stretchY:Wr,content:ni,textFitWidth:Pi,textFitHeight:cn,spriteData:{width:it,height:Ft,x:Ht,y:tr,context:Be}}}}return be})}(Kt,xr)})}(w,this.map._requestManager,this.map.getPixelRatio(),this._spriteRequest).then(le=>{if(this._spriteRequest=null,le)for(let qe in le){this._spritesImagesIds[qe]=[];let Xe=this._spritesImagesIds[qe]?this._spritesImagesIds[qe].filter(ot=>!(ot in le)):[];for(let ot of Xe)this.imageManager.removeImage(ot),this._changedImages[ot]=!0;for(let ot in le[qe]){let Tt=qe===\"default\"?ot:`${qe}:${ot}`;this._spritesImagesIds[qe].push(Tt),Tt in this.imageManager.images?this.imageManager.updateImage(Tt,le[qe][ot],!1):this.imageManager.addImage(Tt,le[qe][ot]),B&&(this._changedImages[Tt]=!0)}}}).catch(le=>{this._spriteRequest=null,ee=le,this.fire(new a.j(ee))}).finally(()=>{this.imageManager.setLoaded(!0),this._availableImages=this.imageManager.listImages(),B&&(this._changed=!0),this.dispatcher.broadcast(\"SI\",this._availableImages),this.fire(new a.k(\"data\",{dataType:\"style\"})),Q&&Q(ee)})}_unloadSprite(){for(let w of Object.values(this._spritesImagesIds).flat())this.imageManager.removeImage(w),this._changedImages[w]=!0;this._spritesImagesIds={},this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast(\"SI\",this._availableImages),this.fire(new a.k(\"data\",{dataType:\"style\"}))}_validateLayer(w){let B=this.sourceCaches[w.source];if(!B)return;let Q=w.sourceLayer;if(!Q)return;let ee=B.getSource();(ee.type===\"geojson\"||ee.vectorLayerIds&&ee.vectorLayerIds.indexOf(Q)===-1)&&this.fire(new a.j(new Error(`Source layer \"${Q}\" does not exist on source \"${ee.id}\" as specified by style layer \"${w.id}\".`)))}loaded(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(let w in this.sourceCaches)if(!this.sourceCaches[w].loaded())return!1;return!!this.imageManager.isLoaded()}_serializeByIds(w,B=!1){let Q=this._serializedAllLayers();if(!w||w.length===0)return Object.values(B?a.aB(Q):Q);let ee=[];for(let le of w)if(Q[le]){let qe=B?a.aB(Q[le]):Q[le];ee.push(qe)}return ee}_serializedAllLayers(){let w=this._serializedLayers;if(w)return w;w=this._serializedLayers={};let B=Object.keys(this._layers);for(let Q of B){let ee=this._layers[Q];ee.type!==\"custom\"&&(w[Q]=ee.serialize())}return w}hasTransitions(){if(this.light&&this.light.hasTransition()||this.sky&&this.sky.hasTransition())return!0;for(let w in this.sourceCaches)if(this.sourceCaches[w].hasTransition())return!0;for(let w in this._layers)if(this._layers[w].hasTransition())return!0;return!1}_checkLoaded(){if(!this._loaded)throw new Error(\"Style is not done loading.\")}update(w){if(!this._loaded)return;let B=this._changed;if(B){let ee=Object.keys(this._updatedLayers),le=Object.keys(this._removedLayers);(ee.length||le.length)&&this._updateWorkerLayers(ee,le);for(let qe in this._updatedSources){let Xe=this._updatedSources[qe];if(Xe===\"reload\")this._reloadSource(qe);else{if(Xe!==\"clear\")throw new Error(`Invalid action ${Xe}`);this._clearSource(qe)}}this._updateTilesForChangedImages(),this._updateTilesForChangedGlyphs();for(let qe in this._updatedPaintProps)this._layers[qe].updateTransitions(w);this.light.updateTransitions(w),this.sky.updateTransitions(w),this._resetUpdates()}let Q={};for(let ee in this.sourceCaches){let le=this.sourceCaches[ee];Q[ee]=le.used,le.used=!1}for(let ee of this._order){let le=this._layers[ee];le.recalculate(w,this._availableImages),!le.isHidden(w.zoom)&&le.source&&(this.sourceCaches[le.source].used=!0)}for(let ee in Q){let le=this.sourceCaches[ee];!!Q[ee]!=!!le.used&&le.fire(new a.k(\"data\",{sourceDataType:\"visibility\",dataType:\"source\",sourceId:ee}))}this.light.recalculate(w),this.sky.recalculate(w),this.z=w.zoom,B&&this.fire(new a.k(\"data\",{dataType:\"style\"}))}_updateTilesForChangedImages(){let w=Object.keys(this._changedImages);if(w.length){for(let B in this.sourceCaches)this.sourceCaches[B].reloadTilesForDependencies([\"icons\",\"patterns\"],w);this._changedImages={}}}_updateTilesForChangedGlyphs(){if(this._glyphsDidChange){for(let w in this.sourceCaches)this.sourceCaches[w].reloadTilesForDependencies([\"glyphs\"],[\"\"]);this._glyphsDidChange=!1}}_updateWorkerLayers(w,B){this.dispatcher.broadcast(\"UL\",{layers:this._serializeByIds(w,!1),removedIds:B})}_resetUpdates(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={},this._glyphsDidChange=!1}setState(w,B={}){var Q;this._checkLoaded();let ee=this.serialize();if(w=B.transformStyle?B.transformStyle(ee,w):w,((Q=B.validate)===null||Q===void 0||Q)&&da(this,a.u(w)))return!1;(w=a.aB(w)).layers=a.az(w.layers);let le=a.aC(ee,w),qe=this._getOperationsToPerform(le);if(qe.unimplemented.length>0)throw new Error(`Unimplemented: ${qe.unimplemented.join(\", \")}.`);if(qe.operations.length===0)return!1;for(let Xe of qe.operations)Xe();return this.stylesheet=w,this._serializedLayers=null,!0}_getOperationsToPerform(w){let B=[],Q=[];for(let ee of w)switch(ee.command){case\"setCenter\":case\"setZoom\":case\"setBearing\":case\"setPitch\":continue;case\"addLayer\":B.push(()=>this.addLayer.apply(this,ee.args));break;case\"removeLayer\":B.push(()=>this.removeLayer.apply(this,ee.args));break;case\"setPaintProperty\":B.push(()=>this.setPaintProperty.apply(this,ee.args));break;case\"setLayoutProperty\":B.push(()=>this.setLayoutProperty.apply(this,ee.args));break;case\"setFilter\":B.push(()=>this.setFilter.apply(this,ee.args));break;case\"addSource\":B.push(()=>this.addSource.apply(this,ee.args));break;case\"removeSource\":B.push(()=>this.removeSource.apply(this,ee.args));break;case\"setLayerZoomRange\":B.push(()=>this.setLayerZoomRange.apply(this,ee.args));break;case\"setLight\":B.push(()=>this.setLight.apply(this,ee.args));break;case\"setGeoJSONSourceData\":B.push(()=>this.setGeoJSONSourceData.apply(this,ee.args));break;case\"setGlyphs\":B.push(()=>this.setGlyphs.apply(this,ee.args));break;case\"setSprite\":B.push(()=>this.setSprite.apply(this,ee.args));break;case\"setSky\":B.push(()=>this.setSky.apply(this,ee.args));break;case\"setTerrain\":B.push(()=>this.map.setTerrain.apply(this,ee.args));break;case\"setTransition\":B.push(()=>{});break;default:Q.push(ee.command)}return{operations:B,unimplemented:Q}}addImage(w,B){if(this.getImage(w))return this.fire(new a.j(new Error(`An image named \"${w}\" already exists.`)));this.imageManager.addImage(w,B),this._afterImageUpdated(w)}updateImage(w,B){this.imageManager.updateImage(w,B)}getImage(w){return this.imageManager.getImage(w)}removeImage(w){if(!this.getImage(w))return this.fire(new a.j(new Error(`An image named \"${w}\" does not exist.`)));this.imageManager.removeImage(w),this._afterImageUpdated(w)}_afterImageUpdated(w){this._availableImages=this.imageManager.listImages(),this._changedImages[w]=!0,this._changed=!0,this.dispatcher.broadcast(\"SI\",this._availableImages),this.fire(new a.k(\"data\",{dataType:\"style\"}))}listImages(){return this._checkLoaded(),this.imageManager.listImages()}addSource(w,B,Q={}){if(this._checkLoaded(),this.sourceCaches[w]!==void 0)throw new Error(`Source \"${w}\" already exists.`);if(!B.type)throw new Error(`The type property must be defined, but only the following properties were given: ${Object.keys(B).join(\", \")}.`);if([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(B.type)>=0&&this._validate(a.u.source,`sources.${w}`,B,null,Q))return;this.map&&this.map._collectResourceTiming&&(B.collectResourceTiming=!0);let ee=this.sourceCaches[w]=new mt(w,B,this.dispatcher);ee.style=this,ee.setEventedParent(this,()=>({isSourceLoaded:ee.loaded(),source:ee.serialize(),sourceId:w})),ee.onAdd(this.map),this._changed=!0}removeSource(w){if(this._checkLoaded(),this.sourceCaches[w]===void 0)throw new Error(\"There is no source with this ID\");for(let Q in this._layers)if(this._layers[Q].source===w)return this.fire(new a.j(new Error(`Source \"${w}\" cannot be removed while layer \"${Q}\" is using it.`)));let B=this.sourceCaches[w];delete this.sourceCaches[w],delete this._updatedSources[w],B.fire(new a.k(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:w})),B.setEventedParent(null),B.onRemove(this.map),this._changed=!0}setGeoJSONSourceData(w,B){if(this._checkLoaded(),this.sourceCaches[w]===void 0)throw new Error(`There is no source with this ID=${w}`);let Q=this.sourceCaches[w].getSource();if(Q.type!==\"geojson\")throw new Error(`geojsonSource.type is ${Q.type}, which is !== 'geojson`);Q.setData(B),this._changed=!0}getSource(w){return this.sourceCaches[w]&&this.sourceCaches[w].getSource()}addLayer(w,B,Q={}){this._checkLoaded();let ee=w.id;if(this.getLayer(ee))return void this.fire(new a.j(new Error(`Layer \"${ee}\" already exists on this map.`)));let le;if(w.type===\"custom\"){if(da(this,a.aD(w)))return;le=a.aA(w)}else{if(\"source\"in w&&typeof w.source==\"object\"&&(this.addSource(ee,w.source),w=a.aB(w),w=a.e(w,{source:ee})),this._validate(a.u.layer,`layers.${ee}`,w,{arrayIndex:-1},Q))return;le=a.aA(w),this._validateLayer(le),le.setEventedParent(this,{layer:{id:ee}})}let qe=B?this._order.indexOf(B):this._order.length;if(B&&qe===-1)this.fire(new a.j(new Error(`Cannot add layer \"${ee}\" before non-existing layer \"${B}\".`)));else{if(this._order.splice(qe,0,ee),this._layerOrderChanged=!0,this._layers[ee]=le,this._removedLayers[ee]&&le.source&&le.type!==\"custom\"){let Xe=this._removedLayers[ee];delete this._removedLayers[ee],Xe.type!==le.type?this._updatedSources[le.source]=\"clear\":(this._updatedSources[le.source]=\"reload\",this.sourceCaches[le.source].pause())}this._updateLayer(le),le.onAdd&&le.onAdd(this.map)}}moveLayer(w,B){if(this._checkLoaded(),this._changed=!0,!this._layers[w])return void this.fire(new a.j(new Error(`The layer '${w}' does not exist in the map's style and cannot be moved.`)));if(w===B)return;let Q=this._order.indexOf(w);this._order.splice(Q,1);let ee=B?this._order.indexOf(B):this._order.length;B&&ee===-1?this.fire(new a.j(new Error(`Cannot move layer \"${w}\" before non-existing layer \"${B}\".`))):(this._order.splice(ee,0,w),this._layerOrderChanged=!0)}removeLayer(w){this._checkLoaded();let B=this._layers[w];if(!B)return void this.fire(new a.j(new Error(`Cannot remove non-existing layer \"${w}\".`)));B.setEventedParent(null);let Q=this._order.indexOf(w);this._order.splice(Q,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[w]=B,delete this._layers[w],this._serializedLayers&&delete this._serializedLayers[w],delete this._updatedLayers[w],delete this._updatedPaintProps[w],B.onRemove&&B.onRemove(this.map)}getLayer(w){return this._layers[w]}getLayersOrder(){return[...this._order]}hasLayer(w){return w in this._layers}setLayerZoomRange(w,B,Q){this._checkLoaded();let ee=this.getLayer(w);ee?ee.minzoom===B&&ee.maxzoom===Q||(B!=null&&(ee.minzoom=B),Q!=null&&(ee.maxzoom=Q),this._updateLayer(ee)):this.fire(new a.j(new Error(`Cannot set the zoom range of non-existing layer \"${w}\".`)))}setFilter(w,B,Q={}){this._checkLoaded();let ee=this.getLayer(w);if(ee){if(!a.aE(ee.filter,B))return B==null?(ee.filter=void 0,void this._updateLayer(ee)):void(this._validate(a.u.filter,`layers.${ee.id}.filter`,B,null,Q)||(ee.filter=a.aB(B),this._updateLayer(ee)))}else this.fire(new a.j(new Error(`Cannot filter non-existing layer \"${w}\".`)))}getFilter(w){return a.aB(this.getLayer(w).filter)}setLayoutProperty(w,B,Q,ee={}){this._checkLoaded();let le=this.getLayer(w);le?a.aE(le.getLayoutProperty(B),Q)||(le.setLayoutProperty(B,Q,ee),this._updateLayer(le)):this.fire(new a.j(new Error(`Cannot style non-existing layer \"${w}\".`)))}getLayoutProperty(w,B){let Q=this.getLayer(w);if(Q)return Q.getLayoutProperty(B);this.fire(new a.j(new Error(`Cannot get style of non-existing layer \"${w}\".`)))}setPaintProperty(w,B,Q,ee={}){this._checkLoaded();let le=this.getLayer(w);le?a.aE(le.getPaintProperty(B),Q)||(le.setPaintProperty(B,Q,ee)&&this._updateLayer(le),this._changed=!0,this._updatedPaintProps[w]=!0,this._serializedLayers=null):this.fire(new a.j(new Error(`Cannot style non-existing layer \"${w}\".`)))}getPaintProperty(w,B){return this.getLayer(w).getPaintProperty(B)}setFeatureState(w,B){this._checkLoaded();let Q=w.source,ee=w.sourceLayer,le=this.sourceCaches[Q];if(le===void 0)return void this.fire(new a.j(new Error(`The source '${Q}' does not exist in the map's style.`)));let qe=le.getSource().type;qe===\"geojson\"&&ee?this.fire(new a.j(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):qe!==\"vector\"||ee?(w.id===void 0&&this.fire(new a.j(new Error(\"The feature id parameter must be provided.\"))),le.setFeatureState(ee,w.id,B)):this.fire(new a.j(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}removeFeatureState(w,B){this._checkLoaded();let Q=w.source,ee=this.sourceCaches[Q];if(ee===void 0)return void this.fire(new a.j(new Error(`The source '${Q}' does not exist in the map's style.`)));let le=ee.getSource().type,qe=le===\"vector\"?w.sourceLayer:void 0;le!==\"vector\"||qe?B&&typeof w.id!=\"string\"&&typeof w.id!=\"number\"?this.fire(new a.j(new Error(\"A feature id is required to remove its specific state property.\"))):ee.removeFeatureState(qe,w.id,B):this.fire(new a.j(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}getFeatureState(w){this._checkLoaded();let B=w.source,Q=w.sourceLayer,ee=this.sourceCaches[B];if(ee!==void 0)return ee.getSource().type!==\"vector\"||Q?(w.id===void 0&&this.fire(new a.j(new Error(\"The feature id parameter must be provided.\"))),ee.getFeatureState(Q,w.id)):void this.fire(new a.j(new Error(\"The sourceLayer parameter must be provided for vector source types.\")));this.fire(new a.j(new Error(`The source '${B}' does not exist in the map's style.`)))}getTransition(){return a.e({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)}serialize(){if(!this._loaded)return;let w=a.aF(this.sourceCaches,le=>le.serialize()),B=this._serializeByIds(this._order,!0),Q=this.map.getTerrain()||void 0,ee=this.stylesheet;return a.aG({version:ee.version,name:ee.name,metadata:ee.metadata,light:ee.light,sky:ee.sky,center:ee.center,zoom:ee.zoom,bearing:ee.bearing,pitch:ee.pitch,sprite:ee.sprite,glyphs:ee.glyphs,transition:ee.transition,sources:w,layers:B,terrain:Q},le=>le!==void 0)}_updateLayer(w){this._updatedLayers[w.id]=!0,w.source&&!this._updatedSources[w.source]&&this.sourceCaches[w.source].getSource().type!==\"raster\"&&(this._updatedSources[w.source]=\"reload\",this.sourceCaches[w.source].pause()),this._serializedLayers=null,this._changed=!0}_flattenAndSortRenderedFeatures(w){let B=qe=>this._layers[qe].type===\"fill-extrusion\",Q={},ee=[];for(let qe=this._order.length-1;qe>=0;qe--){let Xe=this._order[qe];if(B(Xe)){Q[Xe]=qe;for(let ot of w){let Tt=ot[Xe];if(Tt)for(let Yt of Tt)ee.push(Yt)}}}ee.sort((qe,Xe)=>Xe.intersectionZ-qe.intersectionZ);let le=[];for(let qe=this._order.length-1;qe>=0;qe--){let Xe=this._order[qe];if(B(Xe))for(let ot=ee.length-1;ot>=0;ot--){let Tt=ee[ot].feature;if(Q[Tt.layer.id]<qe)break;le.push(Tt),ee.pop()}else for(let ot of w){let Tt=ot[Xe];if(Tt)for(let Yt of Tt)le.push(Yt.feature)}}return le}queryRenderedFeatures(w,B,Q){B&&B.filter&&this._validate(a.u.filter,\"queryRenderedFeatures.filter\",B.filter,null,B);let ee={};if(B&&B.layers){if(!Array.isArray(B.layers))return this.fire(new a.j(new Error(\"parameters.layers must be an Array.\"))),[];for(let Xe of B.layers){let ot=this._layers[Xe];if(!ot)return this.fire(new a.j(new Error(`The layer '${Xe}' does not exist in the map's style and cannot be queried for features.`))),[];ee[ot.source]=!0}}let le=[];B.availableImages=this._availableImages;let qe=this._serializedAllLayers();for(let Xe in this.sourceCaches)B.layers&&!ee[Xe]||le.push(Pe(this.sourceCaches[Xe],this._layers,qe,w,B,Q));return this.placement&&le.push(function(Xe,ot,Tt,Yt,Kt,xr,Ir){let ve={},be=xr.queryRenderedSymbols(Yt),De=[];for(let Be of Object.keys(be).map(Number))De.push(Ir[Be]);De.sort(ge);for(let Be of De){let et=Be.featureIndex.lookupSymbolFeatures(be[Be.bucketInstanceId],ot,Be.bucketIndex,Be.sourceLayerIndex,Kt.filter,Kt.layers,Kt.availableImages,Xe);for(let We in et){let it=ve[We]=ve[We]||[],Ft=et[We];Ft.sort((Ht,tr)=>{let dr=Be.featureSortOrder;if(dr){let Sr=dr.indexOf(Ht.featureIndex);return dr.indexOf(tr.featureIndex)-Sr}return tr.featureIndex-Ht.featureIndex});for(let Ht of Ft)it.push(Ht)}}for(let Be in ve)ve[Be].forEach(et=>{let We=et.feature,it=Tt[Xe[Be].source].getFeatureState(We.layer[\"source-layer\"],We.id);We.source=We.layer.source,We.layer[\"source-layer\"]&&(We.sourceLayer=We.layer[\"source-layer\"]),We.state=it});return ve}(this._layers,qe,this.sourceCaches,w,B,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(le)}querySourceFeatures(w,B){B&&B.filter&&this._validate(a.u.filter,\"querySourceFeatures.filter\",B.filter,null,B);let Q=this.sourceCaches[w];return Q?function(ee,le){let qe=ee.getRenderableIds().map(Tt=>ee.getTileByID(Tt)),Xe=[],ot={};for(let Tt=0;Tt<qe.length;Tt++){let Yt=qe[Tt],Kt=Yt.tileID.canonical.key;ot[Kt]||(ot[Kt]=!0,Yt.querySourceFeatures(Xe,le))}return Xe}(Q,B):[]}getLight(){return this.light.getLight()}setLight(w,B={}){this._checkLoaded();let Q=this.light.getLight(),ee=!1;for(let qe in w)if(!a.aE(w[qe],Q[qe])){ee=!0;break}if(!ee)return;let le={now:u.now(),transition:a.e({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(w,B),this.light.updateTransitions(le)}getSky(){var w;return(w=this.stylesheet)===null||w===void 0?void 0:w.sky}setSky(w,B={}){let Q=this.getSky(),ee=!1;if(!w&&!Q)return;if(w&&!Q)ee=!0;else if(!w&&Q)ee=!0;else for(let qe in w)if(!a.aE(w[qe],Q[qe])){ee=!0;break}if(!ee)return;let le={now:u.now(),transition:a.e({duration:300,delay:0},this.stylesheet.transition)};this.stylesheet.sky=w,this.sky.setSky(w,B),this.sky.updateTransitions(le)}_validate(w,B,Q,ee,le={}){return(!le||le.validate!==!1)&&da(this,w.call(a.u,a.e({key:B,style:this.serialize(),value:Q,styleSpec:a.v},ee)))}_remove(w=!0){this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._loadStyleRequest&&(this._loadStyleRequest.abort(),this._loadStyleRequest=null),this._spriteRequest&&(this._spriteRequest.abort(),this._spriteRequest=null),Qt().off(cr,this._rtlPluginLoaded);for(let B in this._layers)this._layers[B].setEventedParent(null);for(let B in this.sourceCaches){let Q=this.sourceCaches[B];Q.setEventedParent(null),Q.onRemove(this.map)}this.imageManager.setEventedParent(null),this.setEventedParent(null),w&&this.dispatcher.broadcast(\"RM\",void 0),this.dispatcher.remove(w)}_clearSource(w){this.sourceCaches[w].clearTiles()}_reloadSource(w){this.sourceCaches[w].resume(),this.sourceCaches[w].reload()}_updateSources(w){for(let B in this.sourceCaches)this.sourceCaches[B].update(w,this.map.terrain)}_generateCollisionBoxes(){for(let w in this.sourceCaches)this._reloadSource(w)}_updatePlacement(w,B,Q,ee,le=!1){let qe=!1,Xe=!1,ot={};for(let Tt of this._order){let Yt=this._layers[Tt];if(Yt.type!==\"symbol\")continue;if(!ot[Yt.source]){let xr=this.sourceCaches[Yt.source];ot[Yt.source]=xr.getRenderableIds(!0).map(Ir=>xr.getTileByID(Ir)).sort((Ir,ve)=>ve.tileID.overscaledZ-Ir.tileID.overscaledZ||(Ir.tileID.isLessThan(ve.tileID)?-1:1))}let Kt=this.crossTileSymbolIndex.addLayer(Yt,ot[Yt.source],w.center.lng);qe=qe||Kt}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((le=le||this._layerOrderChanged||Q===0)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(u.now(),w.zoom))&&(this.pauseablePlacement=new Ba(w,this.map.terrain,this._order,le,B,Q,ee,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,ot),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(u.now()),Xe=!0),qe&&this.pauseablePlacement.placement.setStale()),Xe||qe)for(let Tt of this._order){let Yt=this._layers[Tt];Yt.type===\"symbol\"&&this.placement.updateLayerOpacities(Yt,ot[Yt.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(u.now())}_releaseSymbolFadeTiles(){for(let w in this.sourceCaches)this.sourceCaches[w].releaseSymbolFadeTiles()}getImages(w,B){return a._(this,void 0,void 0,function*(){let Q=yield this.imageManager.getImages(B.icons);this._updateTilesForChangedImages();let ee=this.sourceCaches[B.source];return ee&&ee.setDependencies(B.tileID.key,B.type,B.icons),Q})}getGlyphs(w,B){return a._(this,void 0,void 0,function*(){let Q=yield this.glyphManager.getGlyphs(B.stacks),ee=this.sourceCaches[B.source];return ee&&ee.setDependencies(B.tileID.key,B.type,[\"\"]),Q})}getGlyphsUrl(){return this.stylesheet.glyphs||null}setGlyphs(w,B={}){this._checkLoaded(),w&&this._validate(a.u.glyphs,\"glyphs\",w,null,B)||(this._glyphsDidChange=!0,this.stylesheet.glyphs=w,this.glyphManager.entries={},this.glyphManager.setURL(w))}addSprite(w,B,Q={},ee){this._checkLoaded();let le=[{id:w,url:B}],qe=[...C(this.stylesheet.sprite),...le];this._validate(a.u.sprite,\"sprite\",qe,null,Q)||(this.stylesheet.sprite=qe,this._loadSprite(le,!0,ee))}removeSprite(w){this._checkLoaded();let B=C(this.stylesheet.sprite);if(B.find(Q=>Q.id===w)){if(this._spritesImagesIds[w])for(let Q of this._spritesImagesIds[w])this.imageManager.removeImage(Q),this._changedImages[Q]=!0;B.splice(B.findIndex(Q=>Q.id===w),1),this.stylesheet.sprite=B.length>0?B:void 0,delete this._spritesImagesIds[w],this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast(\"SI\",this._availableImages),this.fire(new a.k(\"data\",{dataType:\"style\"}))}else this.fire(new a.j(new Error(`Sprite \"${w}\" doesn't exists on this map.`)))}getSprite(){return C(this.stylesheet.sprite)}setSprite(w,B={},Q){this._checkLoaded(),w&&this._validate(a.u.sprite,\"sprite\",w,null,B)||(this.stylesheet.sprite=w,w?this._loadSprite(w,!0,Q):(this._unloadSprite(),Q&&Q(null)))}}var vo=a.Y([{name:\"a_pos\",type:\"Int16\",components:2}]);let jn={prelude:Mt(`#ifdef GL_ES\n",
+       "precision mediump float;\n",
+       "#else\n",
+       "#if !defined(lowp)\n",
+       "#define lowp\n",
+       "#endif\n",
+       "#if !defined(mediump)\n",
+       "#define mediump\n",
+       "#endif\n",
+       "#if !defined(highp)\n",
+       "#define highp\n",
+       "#endif\n",
+       "#endif\n",
+       "`,`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#else\n",
+       "#if !defined(lowp)\n",
+       "#define lowp\n",
+       "#endif\n",
+       "#if !defined(mediump)\n",
+       "#define mediump\n",
+       "#endif\n",
+       "#if !defined(highp)\n",
+       "#define highp\n",
+       "#endif\n",
+       "#endif\n",
+       "vec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\n",
+       ");}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\n",
+       "#ifdef TERRAIN3D\n",
+       "uniform sampler2D u_terrain;uniform float u_terrain_dim;uniform mat4 u_terrain_matrix;uniform vec4 u_terrain_unpack;uniform float u_terrain_exaggeration;uniform highp sampler2D u_depth;\n",
+       "#endif\n",
+       "const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitShifts=vec4(1.)/bitSh;highp float unpack(highp vec4 color) {return dot(color,bitShifts);}highp float depthOpacity(vec3 frag) {\n",
+       "#ifdef TERRAIN3D\n",
+       "highp float d=unpack(texture2D(u_depth,frag.xy*0.5+0.5))+0.0001-frag.z;return 1.0-max(0.0,min(1.0,-d*500.0));\n",
+       "#else\n",
+       "return 1.0;\n",
+       "#endif\n",
+       "}float calculate_visibility(vec4 pos) {\n",
+       "#ifdef TERRAIN3D\n",
+       "vec3 frag=pos.xyz/pos.w;highp float d=depthOpacity(frag);if (d > 0.95) return 1.0;return (d+depthOpacity(frag+vec3(0.0,0.01,0.0)))/2.0;\n",
+       "#else\n",
+       "return 1.0;\n",
+       "#endif\n",
+       "}float ele(vec2 pos) {\n",
+       "#ifdef TERRAIN3D\n",
+       "vec4 rgb=(texture2D(u_terrain,pos)*255.0)*u_terrain_unpack;return rgb.r+rgb.g+rgb.b-u_terrain_unpack.a;\n",
+       "#else\n",
+       "return 0.0;\n",
+       "#endif\n",
+       "}float get_elevation(vec2 pos) {\n",
+       "#ifdef TERRAIN3D\n",
+       "vec2 coord=(u_terrain_matrix*vec4(pos,0.0,1.0)).xy*u_terrain_dim+1.0;vec2 f=fract(coord);vec2 c=(floor(coord)+0.5)/(u_terrain_dim+2.0);float d=1.0/(u_terrain_dim+2.0);float tl=ele(c);float tr=ele(c+vec2(d,0.0));float bl=ele(c+vec2(0.0,d));float br=ele(c+vec2(d,d));float elevation=mix(mix(tl,tr,f.x),mix(bl,br,f.x),f.y);return elevation*u_terrain_exaggeration;\n",
+       "#else\n",
+       "return 0.0;\n",
+       "#endif\n",
+       "}`),background:Mt(`uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),backgroundPattern:Mt(`uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),circle:Mt(`varying vec3 v_data;varying float v_visibility;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define highp vec4 stroke_color\n",
+       "#pragma mapbox: define mediump float stroke_width\n",
+       "#pragma mapbox: define lowp float stroke_opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize highp vec4 stroke_color\n",
+       "#pragma mapbox: initialize mediump float stroke_width\n",
+       "#pragma mapbox: initialize lowp float stroke_opacity\n",
+       "vec2 extrude=v_data.xy;float extrude_length=length(extrude);float antialiased_blur=v_data.z;float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=v_visibility*opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;varying float v_visibility;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define highp vec4 stroke_color\n",
+       "#pragma mapbox: define mediump float stroke_width\n",
+       "#pragma mapbox: define lowp float stroke_opacity\n",
+       "void main(void) {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize highp vec4 stroke_color\n",
+       "#pragma mapbox: initialize mediump float stroke_width\n",
+       "#pragma mapbox: initialize lowp float stroke_opacity\n",
+       "vec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);float ele=get_elevation(circle_center);v_visibility=calculate_visibility(u_matrix*vec4(circle_center,ele,1.0));if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,ele,1);} else {gl_Position=u_matrix*vec4(circle_center,ele,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}float antialiasblur=-max(1.0/u_device_pixel_ratio/(radius+stroke_width),blur);v_data=vec3(extrude.x,extrude.y,antialiasblur);}`),clippingMask:Mt(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),heatmap:Mt(`uniform highp float u_intensity;varying vec2 v_extrude;\n",
+       "#pragma mapbox: define highp float weight\n",
+       "#define GAUSS_COEF 0.3989422804014327\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp float weight\n",
+       "float d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\n",
+       "#pragma mapbox: define highp float weight\n",
+       "#pragma mapbox: define mediump float radius\n",
+       "const highp float ZERO=1.0/255.0/16.0;\n",
+       "#define GAUSS_COEF 0.3989422804014327\n",
+       "void main(void) {\n",
+       "#pragma mapbox: initialize highp float weight\n",
+       "#pragma mapbox: initialize mediump float radius\n",
+       "vec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,get_elevation(floor(a_pos*0.5)),1);gl_Position=u_matrix*pos;}`),heatmapTexture:Mt(`uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(0.0);\n",
+       "#endif\n",
+       "}`,\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),collisionBox:Mt(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_anchor_pos;attribute vec2 a_placed;attribute vec2 a_box_real;uniform mat4 u_matrix;uniform vec2 u_pixel_extrude_scale;varying float v_placed;varying float v_notUsed;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}void main() {gl_Position=projectTileWithElevation(a_anchor_pos,get_elevation(a_anchor_pos));gl_Position.xy=((a_box_real+0.5)*u_pixel_extrude_scale*2.0-1.0)*vec2(1.0,-1.0)*gl_Position.w;if (gl_Position.z/gl_Position.w < 1.1) {gl_Position.z=0.5;}v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),collisionCircle:Mt(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),debug:Mt(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,get_elevation(a_pos),1);}\"),fill:Mt(`#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_FragColor=color*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`attribute vec2 a_pos;uniform mat4 u_matrix;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_Position=u_matrix*vec4(a_pos,0,1);}`),fillOutline:Mt(`varying vec2 v_pos;\n",
+       "#pragma mapbox: define highp vec4 outline_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 outline_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n",
+       "#pragma mapbox: define highp vec4 outline_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 outline_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillOutlinePattern:Mt(`uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillPattern:Mt(`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#endif\n",
+       "uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}`),fillExtrusion:Mt(`varying vec4 v_color;void main() {gl_FragColor=v_color;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;\n",
+       "#ifdef TERRAIN3D\n",
+       "attribute vec2 a_centroid;\n",
+       "#endif\n",
+       "varying vec4 v_color;\n",
+       "#pragma mapbox: define highp float base\n",
+       "#pragma mapbox: define highp float height\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp float base\n",
+       "#pragma mapbox: initialize highp float height\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "vec3 normal=a_normal_ed.xyz;\n",
+       "#ifdef TERRAIN3D\n",
+       "float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0);\n",
+       "#else\n",
+       "float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0;\n",
+       "#endif\n",
+       "base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`),fillExtrusionPattern:Mt(`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n",
+       "#pragma mapbox: define lowp float base\n",
+       "#pragma mapbox: define lowp float height\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float base\n",
+       "#pragma mapbox: initialize lowp float height\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;\n",
+       "#ifdef TERRAIN3D\n",
+       "attribute vec2 a_centroid;\n",
+       "#endif\n",
+       "varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n",
+       "#pragma mapbox: define lowp float base\n",
+       "#pragma mapbox: define lowp float height\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float base\n",
+       "#pragma mapbox: initialize lowp float height\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;\n",
+       "#ifdef TERRAIN3D\n",
+       "float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0);\n",
+       "#else\n",
+       "float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0;\n",
+       "#endif\n",
+       "base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n",
+       "? a_pos\n",
+       ": vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`),hillshadePrepare:Mt(`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#endif\n",
+       "uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hillshade:Mt(`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n",
+       "#define PI 3.141592653589793\n",
+       "void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),line:Mt(`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`\n",
+       "#define scale 0.015873016\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n",
+       "#ifdef TERRAIN3D\n",
+       "v_gamma_scale=1.0;\n",
+       "#else\n",
+       "float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n",
+       "#endif\n",
+       "v_width2=vec2(outset,inset);}`),lineGradient:Mt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`\n",
+       "#define scale 0.015873016\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n",
+       "#ifdef TERRAIN3D\n",
+       "v_gamma_scale=1.0;\n",
+       "#else\n",
+       "float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n",
+       "#endif\n",
+       "v_width2=vec2(outset,inset);}`),linePattern:Mt(`#ifdef GL_ES\n",
+       "precision highp float;\n",
+       "#endif\n",
+       "uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`\n",
+       "#define scale 0.015873016\n",
+       "#define LINE_DISTANCE_SCALE 2.0\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "#pragma mapbox: define lowp vec4 pattern_from\n",
+       "#pragma mapbox: define lowp vec4 pattern_to\n",
+       "#pragma mapbox: define lowp float pixel_ratio_from\n",
+       "#pragma mapbox: define lowp float pixel_ratio_to\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_from\n",
+       "#pragma mapbox: initialize mediump vec4 pattern_to\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_from\n",
+       "#pragma mapbox: initialize lowp float pixel_ratio_to\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n",
+       "#ifdef TERRAIN3D\n",
+       "v_gamma_scale=1.0;\n",
+       "#else\n",
+       "float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n",
+       "#endif\n",
+       "v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`),lineSDF:Mt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`\n",
+       "#define scale 0.015873016\n",
+       "#define LINE_DISTANCE_SCALE 2.0\n",
+       "attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n",
+       "#pragma mapbox: define highp vec4 color\n",
+       "#pragma mapbox: define lowp float blur\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define mediump float gapwidth\n",
+       "#pragma mapbox: define lowp float offset\n",
+       "#pragma mapbox: define mediump float width\n",
+       "#pragma mapbox: define lowp float floorwidth\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 color\n",
+       "#pragma mapbox: initialize lowp float blur\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize mediump float gapwidth\n",
+       "#pragma mapbox: initialize lowp float offset\n",
+       "#pragma mapbox: initialize mediump float width\n",
+       "#pragma mapbox: initialize lowp float floorwidth\n",
+       "float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n",
+       "#ifdef TERRAIN3D\n",
+       "v_gamma_scale=1.0;\n",
+       "#else\n",
+       "float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n",
+       "#endif\n",
+       "v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`),raster:Mt(`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),symbolIcon:Mt(`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_tex;varying float v_fade_opacity;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}gl_Position=finalPos;v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float visibility=calculate_visibility(projectedPoint);v_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));}`),symbolSDF:Mt(`#define SDF_PX 8.0\n",
+       "uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float inner_edge=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);inner_edge=inner_edge+gamma*gamma_scale;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(inner_edge-gamma_scaled,inner_edge+gamma_scaled,dist);if (u_is_halo) {lowp float halo_edge=(6.0-halo_width/fontScale)/SDF_PX;alpha=min(smoothstep(halo_edge-gamma_scaled,halo_edge+gamma_scaled,dist),1.0-alpha);}gl_FragColor=color*(alpha*opacity*fade_opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_data0;varying vec3 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`),symbolTextAndIcon:Mt(`#define SDF_PX 8.0\n",
+       "#define SDF 1.0\n",
+       "#define ICON 0.0\n",
+       "uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n",
+       "#ifdef OVERDRAW_INSPECTOR\n",
+       "gl_FragColor=vec4(1.0);\n",
+       "#endif\n",
+       "}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec4 v_data0;varying vec4 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n",
+       "#pragma mapbox: define highp vec4 fill_color\n",
+       "#pragma mapbox: define highp vec4 halo_color\n",
+       "#pragma mapbox: define lowp float opacity\n",
+       "#pragma mapbox: define lowp float halo_width\n",
+       "#pragma mapbox: define lowp float halo_blur\n",
+       "void main() {\n",
+       "#pragma mapbox: initialize highp vec4 fill_color\n",
+       "#pragma mapbox: initialize highp vec4 halo_color\n",
+       "#pragma mapbox: initialize lowp float opacity\n",
+       "#pragma mapbox: initialize lowp float halo_width\n",
+       "#pragma mapbox: initialize lowp float halo_blur\n",
+       "vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\n",
+       "camera_to_anchor_distance/u_camera_to_center_distance :\n",
+       "u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`),terrain:Mt(\"uniform sampler2D u_texture;uniform vec4 u_fog_color;uniform vec4 u_horizon_color;uniform float u_fog_ground_blend;uniform float u_fog_ground_blend_opacity;uniform float u_horizon_fog_blend;varying vec2 v_texture_pos;varying float v_fog_depth;const float gamma=2.2;vec4 gammaToLinear(vec4 color) {return pow(color,vec4(gamma));}vec4 linearToGamma(vec4 color) {return pow(color,vec4(1.0/gamma));}void main() {vec4 surface_color=texture2D(u_texture,v_texture_pos);if (v_fog_depth > u_fog_ground_blend) {vec4 surface_color_linear=gammaToLinear(surface_color);float blend_color=smoothstep(0.0,1.0,max((v_fog_depth-u_horizon_fog_blend)/(1.0-u_horizon_fog_blend),0.0));vec4 fog_horizon_color_linear=mix(gammaToLinear(u_fog_color),gammaToLinear(u_horizon_color),blend_color);float factor_fog=max(v_fog_depth-u_fog_ground_blend,0.0)/(1.0-u_fog_ground_blend);gl_FragColor=linearToGamma(mix(surface_color_linear,fog_horizon_color_linear,pow(factor_fog,2.0)*u_fog_ground_blend_opacity));} else {gl_FragColor=surface_color;}}\",\"attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform mat4 u_fog_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;varying float v_fog_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);vec4 pos=u_fog_matrix*vec4(a_pos3d.xy,ele,1.0);v_fog_depth=pos.z/pos.w*0.5+0.5;}\"),terrainDepth:Mt(\"varying float v_depth;const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitMsk=vec4(0.,vec3(1./256.0));highp vec4 pack(highp float value) {highp vec4 comp=fract(value*bitSh);comp-=comp.xxyz*bitMsk;return comp;}void main() {gl_FragColor=pack(v_depth);}\",\"attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying float v_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);v_depth=gl_Position.z/gl_Position.w;}\"),terrainCoords:Mt(\"precision mediump float;uniform sampler2D u_texture;uniform float u_terrain_coords_id;varying vec2 v_texture_pos;void main() {vec4 rgba=texture2D(u_texture,v_texture_pos);gl_FragColor=vec4(rgba.r,rgba.g,rgba.b,u_terrain_coords_id);}\",\"attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);}\"),sky:Mt(\"uniform vec4 u_sky_color;uniform vec4 u_horizon_color;uniform float u_horizon;uniform float u_sky_horizon_blend;void main() {float y=gl_FragCoord.y;if (y > u_horizon) {float blend=y-u_horizon;if (blend < u_sky_horizon_blend) {gl_FragColor=mix(u_sky_color,u_horizon_color,pow(1.0-blend/u_sky_horizon_blend,2.0));} else {gl_FragColor=u_sky_color;}}}\",\"attribute vec2 a_pos;void main() {gl_Position=vec4(a_pos,1.0,1.0);}\")};function Mt(ue,w){let B=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,Q=w.match(/attribute ([\\w]+) ([\\w]+)/g),ee=ue.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),le=w.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),qe=le?le.concat(ee):ee,Xe={};return{fragmentSource:ue=ue.replace(B,(ot,Tt,Yt,Kt,xr)=>(Xe[xr]=!0,Tt===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "varying ${Yt} ${Kt} ${xr};\n",
+       "#else\n",
+       "uniform ${Yt} ${Kt} u_${xr};\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifdef HAS_UNIFORM_u_${xr}\n",
+       "    ${Yt} ${Kt} ${xr} = u_${xr};\n",
+       "#endif\n",
+       "`)),vertexSource:w=w.replace(B,(ot,Tt,Yt,Kt,xr)=>{let Ir=Kt===\"float\"?\"vec2\":\"vec4\",ve=xr.match(/color/)?\"color\":Ir;return Xe[xr]?Tt===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "uniform lowp float u_${xr}_t;\n",
+       "attribute ${Yt} ${Ir} a_${xr};\n",
+       "varying ${Yt} ${Kt} ${xr};\n",
+       "#else\n",
+       "uniform ${Yt} ${Kt} u_${xr};\n",
+       "#endif\n",
+       "`:ve===\"vec4\"?`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "    ${xr} = a_${xr};\n",
+       "#else\n",
+       "    ${Yt} ${Kt} ${xr} = u_${xr};\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "    ${xr} = unpack_mix_${ve}(a_${xr}, u_${xr}_t);\n",
+       "#else\n",
+       "    ${Yt} ${Kt} ${xr} = u_${xr};\n",
+       "#endif\n",
+       "`:Tt===\"define\"?`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "uniform lowp float u_${xr}_t;\n",
+       "attribute ${Yt} ${Ir} a_${xr};\n",
+       "#else\n",
+       "uniform ${Yt} ${Kt} u_${xr};\n",
+       "#endif\n",
+       "`:ve===\"vec4\"?`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "    ${Yt} ${Kt} ${xr} = a_${xr};\n",
+       "#else\n",
+       "    ${Yt} ${Kt} ${xr} = u_${xr};\n",
+       "#endif\n",
+       "`:`\n",
+       "#ifndef HAS_UNIFORM_u_${xr}\n",
+       "    ${Yt} ${Kt} ${xr} = unpack_mix_${ve}(a_${xr}, u_${xr}_t);\n",
+       "#else\n",
+       "    ${Yt} ${Kt} ${xr} = u_${xr};\n",
+       "#endif\n",
+       "`}),staticAttributes:Q,staticUniforms:qe}}class kr{constructor(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null}bind(w,B,Q,ee,le,qe,Xe,ot,Tt){this.context=w;let Yt=this.boundPaintVertexBuffers.length!==ee.length;for(let Kt=0;!Yt&&Kt<ee.length;Kt++)this.boundPaintVertexBuffers[Kt]!==ee[Kt]&&(Yt=!0);!this.vao||this.boundProgram!==B||this.boundLayoutVertexBuffer!==Q||Yt||this.boundIndexBuffer!==le||this.boundVertexOffset!==qe||this.boundDynamicVertexBuffer!==Xe||this.boundDynamicVertexBuffer2!==ot||this.boundDynamicVertexBuffer3!==Tt?this.freshBind(B,Q,ee,le,qe,Xe,ot,Tt):(w.bindVertexArray.set(this.vao),Xe&&Xe.bind(),le&&le.dynamicDraw&&le.bind(),ot&&ot.bind(),Tt&&Tt.bind())}freshBind(w,B,Q,ee,le,qe,Xe,ot){let Tt=w.numAttributes,Yt=this.context,Kt=Yt.gl;this.vao&&this.destroy(),this.vao=Yt.createVertexArray(),Yt.bindVertexArray.set(this.vao),this.boundProgram=w,this.boundLayoutVertexBuffer=B,this.boundPaintVertexBuffers=Q,this.boundIndexBuffer=ee,this.boundVertexOffset=le,this.boundDynamicVertexBuffer=qe,this.boundDynamicVertexBuffer2=Xe,this.boundDynamicVertexBuffer3=ot,B.enableAttributes(Kt,w);for(let xr of Q)xr.enableAttributes(Kt,w);qe&&qe.enableAttributes(Kt,w),Xe&&Xe.enableAttributes(Kt,w),ot&&ot.enableAttributes(Kt,w),B.bind(),B.setVertexAttribPointers(Kt,w,le);for(let xr of Q)xr.bind(),xr.setVertexAttribPointers(Kt,w,le);qe&&(qe.bind(),qe.setVertexAttribPointers(Kt,w,le)),ee&&ee.bind(),Xe&&(Xe.bind(),Xe.setVertexAttribPointers(Kt,w,le)),ot&&(ot.bind(),ot.setVertexAttribPointers(Kt,w,le)),Yt.currentNumAttributes=Tt}destroy(){this.vao&&(this.context.deleteVertexArray(this.vao),this.vao=null)}}let Jr=(ue,w,B,Q,ee)=>({u_matrix:ue,u_texture:0,u_ele_delta:w,u_fog_matrix:B,u_fog_color:Q?Q.properties.get(\"fog-color\"):a.aM.white,u_fog_ground_blend:Q?Q.properties.get(\"fog-ground-blend\"):1,u_fog_ground_blend_opacity:Q?Q.calculateFogBlendOpacity(ee):0,u_horizon_color:Q?Q.properties.get(\"horizon-color\"):a.aM.white,u_horizon_fog_blend:Q?Q.properties.get(\"horizon-fog-blend\"):1});function vi(ue){let w=[];for(let B=0;B<ue.length;B++){if(ue[B]===null)continue;let Q=ue[B].split(\" \");w.push(Q.pop())}return w}class hn{constructor(w,B,Q,ee,le,qe){let Xe=w.gl;this.program=Xe.createProgram();let ot=vi(B.staticAttributes),Tt=Q?Q.getBinderAttributes():[],Yt=ot.concat(Tt),Kt=jn.prelude.staticUniforms?vi(jn.prelude.staticUniforms):[],xr=B.staticUniforms?vi(B.staticUniforms):[],Ir=Q?Q.getBinderUniforms():[],ve=Kt.concat(xr).concat(Ir),be=[];for(let Ht of ve)be.indexOf(Ht)<0&&be.push(Ht);let De=Q?Q.defines():[];le&&De.push(\"#define OVERDRAW_INSPECTOR;\"),qe&&De.push(\"#define TERRAIN3D;\");let Be=De.concat(jn.prelude.fragmentSource,B.fragmentSource).join(`\n",
+       "`),et=De.concat(jn.prelude.vertexSource,B.vertexSource).join(`\n",
+       "`),We=Xe.createShader(Xe.FRAGMENT_SHADER);if(Xe.isContextLost())return void(this.failedToCreate=!0);if(Xe.shaderSource(We,Be),Xe.compileShader(We),!Xe.getShaderParameter(We,Xe.COMPILE_STATUS))throw new Error(`Could not compile fragment shader: ${Xe.getShaderInfoLog(We)}`);Xe.attachShader(this.program,We);let it=Xe.createShader(Xe.VERTEX_SHADER);if(Xe.isContextLost())return void(this.failedToCreate=!0);if(Xe.shaderSource(it,et),Xe.compileShader(it),!Xe.getShaderParameter(it,Xe.COMPILE_STATUS))throw new Error(`Could not compile vertex shader: ${Xe.getShaderInfoLog(it)}`);Xe.attachShader(this.program,it),this.attributes={};let Ft={};this.numAttributes=Yt.length;for(let Ht=0;Ht<this.numAttributes;Ht++)Yt[Ht]&&(Xe.bindAttribLocation(this.program,Ht,Yt[Ht]),this.attributes[Yt[Ht]]=Ht);if(Xe.linkProgram(this.program),!Xe.getProgramParameter(this.program,Xe.LINK_STATUS))throw new Error(`Program failed to link: ${Xe.getProgramInfoLog(this.program)}`);Xe.deleteShader(it),Xe.deleteShader(We);for(let Ht=0;Ht<be.length;Ht++){let tr=be[Ht];if(tr&&!Ft[tr]){let dr=Xe.getUniformLocation(this.program,tr);dr&&(Ft[tr]=dr)}}this.fixedUniforms=ee(w,Ft),this.terrainUniforms=((Ht,tr)=>({u_depth:new a.aH(Ht,tr.u_depth),u_terrain:new a.aH(Ht,tr.u_terrain),u_terrain_dim:new a.aI(Ht,tr.u_terrain_dim),u_terrain_matrix:new a.aJ(Ht,tr.u_terrain_matrix),u_terrain_unpack:new a.aK(Ht,tr.u_terrain_unpack),u_terrain_exaggeration:new a.aI(Ht,tr.u_terrain_exaggeration)}))(w,Ft),this.binderUniforms=Q?Q.getUniforms(w,Ft):[]}draw(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve,be,De,Be,et){let We=w.gl;if(this.failedToCreate)return;if(w.program.set(this.program),w.setDepthMode(Q),w.setStencilMode(ee),w.setColorMode(le),w.setCullFace(qe),ot){w.activeTexture.set(We.TEXTURE2),We.bindTexture(We.TEXTURE_2D,ot.depthTexture),w.activeTexture.set(We.TEXTURE3),We.bindTexture(We.TEXTURE_2D,ot.texture);for(let Ft in this.terrainUniforms)this.terrainUniforms[Ft].set(ot[Ft])}for(let Ft in this.fixedUniforms)this.fixedUniforms[Ft].set(Xe[Ft]);be&&be.setUniforms(w,this.binderUniforms,Ir,{zoom:ve});let it=0;switch(B){case We.LINES:it=2;break;case We.TRIANGLES:it=3;break;case We.LINE_STRIP:it=1}for(let Ft of xr.get()){let Ht=Ft.vaos||(Ft.vaos={});(Ht[Tt]||(Ht[Tt]=new kr)).bind(w,this,Yt,be?be.getPaintVertexBuffers():[],Kt,Ft.vertexOffset,De,Be,et),We.drawElements(B,Ft.primitiveLength*it,We.UNSIGNED_SHORT,Ft.primitiveOffset*it*2)}}}function An(ue,w,B){let Q=1/In(B,1,w.transform.tileZoom),ee=Math.pow(2,B.tileID.overscaledZ),le=B.tileSize*Math.pow(2,w.transform.tileZoom)/ee,qe=le*(B.tileID.canonical.x+B.tileID.wrap*ee),Xe=le*B.tileID.canonical.y;return{u_image:0,u_texsize:B.imageAtlasTexture.size,u_scale:[Q,ue.fromScale,ue.toScale],u_fade:ue.t,u_pixel_coord_upper:[qe>>16,Xe>>16],u_pixel_coord_lower:[65535&qe,65535&Xe]}}let Mn=(ue,w,B,Q)=>{let ee=w.style.light,le=ee.properties.get(\"position\"),qe=[le.x,le.y,le.z],Xe=function(){var Tt=new a.A(9);return a.A!=Float32Array&&(Tt[1]=0,Tt[2]=0,Tt[3]=0,Tt[5]=0,Tt[6]=0,Tt[7]=0),Tt[0]=1,Tt[4]=1,Tt[8]=1,Tt}();ee.properties.get(\"anchor\")===\"viewport\"&&function(Tt,Yt){var Kt=Math.sin(Yt),xr=Math.cos(Yt);Tt[0]=xr,Tt[1]=Kt,Tt[2]=0,Tt[3]=-Kt,Tt[4]=xr,Tt[5]=0,Tt[6]=0,Tt[7]=0,Tt[8]=1}(Xe,-w.transform.angle),function(Tt,Yt,Kt){var xr=Yt[0],Ir=Yt[1],ve=Yt[2];Tt[0]=xr*Kt[0]+Ir*Kt[3]+ve*Kt[6],Tt[1]=xr*Kt[1]+Ir*Kt[4]+ve*Kt[7],Tt[2]=xr*Kt[2]+Ir*Kt[5]+ve*Kt[8]}(qe,qe,Xe);let ot=ee.properties.get(\"color\");return{u_matrix:ue,u_lightpos:qe,u_lightintensity:ee.properties.get(\"intensity\"),u_lightcolor:[ot.r,ot.g,ot.b],u_vertical_gradient:+B,u_opacity:Q}},Li=(ue,w,B,Q,ee,le,qe)=>a.e(Mn(ue,w,B,Q),An(le,w,qe),{u_height_factor:-Math.pow(2,ee.overscaledZ)/qe.tileSize/8}),_n=ue=>({u_matrix:ue}),ya=(ue,w,B,Q)=>a.e(_n(ue),An(B,w,Q)),Jn=(ue,w)=>({u_matrix:ue,u_world:w}),Ma=(ue,w,B,Q,ee)=>a.e(ya(ue,w,B,Q),{u_world:ee}),_o=(ue,w,B,Q)=>{let ee=ue.transform,le,qe;if(Q.paint.get(\"circle-pitch-alignment\")===\"map\"){let Xe=In(B,1,ee.zoom);le=!0,qe=[Xe,Xe]}else le=!1,qe=ee.pixelsToGLUnits;return{u_camera_to_center_distance:ee.cameraToCenterDistance,u_scale_with_map:+(Q.paint.get(\"circle-pitch-scale\")===\"map\"),u_matrix:ue.translatePosMatrix(w.posMatrix,B,Q.paint.get(\"circle-translate\"),Q.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+le,u_device_pixel_ratio:ue.pixelRatio,u_extrude_scale:qe}},No=(ue,w,B)=>({u_matrix:ue,u_inv_matrix:w,u_camera_to_center_distance:B.cameraToCenterDistance,u_viewport_size:[B.width,B.height]}),po=(ue,w,B=1)=>({u_matrix:ue,u_color:w,u_overlay:0,u_overlay_scale:B}),Lo=ue=>({u_matrix:ue}),ko=(ue,w,B,Q)=>({u_matrix:ue,u_extrude_scale:In(w,1,B),u_intensity:Q}),Ds=(ue,w,B,Q)=>{let ee=a.H();a.aP(ee,0,ue.width,ue.height,0,0,1);let le=ue.context.gl;return{u_matrix:ee,u_world:[le.drawingBufferWidth,le.drawingBufferHeight],u_image:B,u_color_ramp:Q,u_opacity:w.paint.get(\"heatmap-opacity\")}};function Fs(ue,w){let B=Math.pow(2,w.canonical.z),Q=w.canonical.y;return[new a.Z(0,Q/B).toLngLat().lat,new a.Z(0,(Q+1)/B).toLngLat().lat]}let ll=(ue,w,B,Q)=>{let ee=ue.transform;return{u_matrix:As(ue,w,B,Q),u_ratio:1/In(w,1,ee.zoom),u_device_pixel_ratio:ue.pixelRatio,u_units_to_pixels:[1/ee.pixelsToGLUnits[0],1/ee.pixelsToGLUnits[1]]}},ul=(ue,w,B,Q,ee)=>a.e(ll(ue,w,B,ee),{u_image:0,u_image_height:Q}),zl=(ue,w,B,Q,ee)=>{let le=ue.transform,qe=il(w,le);return{u_matrix:As(ue,w,B,ee),u_texsize:w.imageAtlasTexture.size,u_ratio:1/In(w,1,le.zoom),u_device_pixel_ratio:ue.pixelRatio,u_image:0,u_scale:[qe,Q.fromScale,Q.toScale],u_fade:Q.t,u_units_to_pixels:[1/le.pixelsToGLUnits[0],1/le.pixelsToGLUnits[1]]}},us=(ue,w,B,Q,ee,le)=>{let qe=ue.lineAtlas,Xe=il(w,ue.transform),ot=B.layout.get(\"line-cap\")===\"round\",Tt=qe.getDash(Q.from,ot),Yt=qe.getDash(Q.to,ot),Kt=Tt.width*ee.fromScale,xr=Yt.width*ee.toScale;return a.e(ll(ue,w,B,le),{u_patternscale_a:[Xe/Kt,-Tt.height/2],u_patternscale_b:[Xe/xr,-Yt.height/2],u_sdfgamma:qe.width/(256*Math.min(Kt,xr)*ue.pixelRatio)/2,u_image:0,u_tex_y_a:Tt.y,u_tex_y_b:Yt.y,u_mix:ee.t})};function il(ue,w){return 1/In(ue,1,w.tileZoom)}function As(ue,w,B,Q){return ue.translatePosMatrix(Q?Q.posMatrix:w.tileID.posMatrix,w,B.paint.get(\"line-translate\"),B.paint.get(\"line-translate-anchor\"))}let cl=(ue,w,B,Q,ee)=>{return{u_matrix:ue,u_tl_parent:w,u_scale_parent:B,u_buffer_scale:1,u_fade_t:Q.mix,u_opacity:Q.opacity*ee.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:ee.paint.get(\"raster-brightness-min\"),u_brightness_high:ee.paint.get(\"raster-brightness-max\"),u_saturation_factor:(qe=ee.paint.get(\"raster-saturation\"),qe>0?1-1/(1.001-qe):-qe),u_contrast_factor:(le=ee.paint.get(\"raster-contrast\"),le>0?1/(1-le):1+le),u_spin_weights:Ks(ee.paint.get(\"raster-hue-rotate\"))};var le,qe};function Ks(ue){ue*=Math.PI/180;let w=Math.sin(ue),B=Math.cos(ue);return[(2*B+1)/3,(-Math.sqrt(3)*w-B+1)/3,(Math.sqrt(3)*w-B+1)/3]}let zs=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir)=>{let ve=qe.transform;return{u_is_size_zoom_constant:+(ue===\"constant\"||ue===\"source\"),u_is_size_feature_constant:+(ue===\"constant\"||ue===\"camera\"),u_size_t:w?w.uSizeT:0,u_size:w?w.uSize:0,u_camera_to_center_distance:ve.cameraToCenterDistance,u_pitch:ve.pitch/360*2*Math.PI,u_rotate_symbol:+B,u_aspect_ratio:ve.width/ve.height,u_fade_change:qe.options.fadeDuration?qe.symbolFadeChange:1,u_matrix:Xe,u_label_plane_matrix:ot,u_coord_matrix:Tt,u_is_text:+Kt,u_pitch_with_map:+Q,u_is_along_line:ee,u_is_variable_anchor:le,u_texsize:xr,u_texture:0,u_translation:Yt,u_pitched_scale:Ir}},Io=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve)=>{let be=qe.transform;return a.e(zs(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,ve),{u_gamma_scale:Q?Math.cos(be._pitch)*be.cameraToCenterDistance:1,u_device_pixel_ratio:qe.pixelRatio,u_is_halo:+Ir})},ls=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir)=>a.e(Io(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,!0,Kt,!0,Ir),{u_texsize_icon:xr,u_texture_icon:1}),Zl=(ue,w,B)=>({u_matrix:ue,u_opacity:w,u_color:B}),Su=(ue,w,B,Q,ee,le)=>a.e(function(qe,Xe,ot,Tt){let Yt=ot.imageManager.getPattern(qe.from.toString()),Kt=ot.imageManager.getPattern(qe.to.toString()),{width:xr,height:Ir}=ot.imageManager.getPixelSize(),ve=Math.pow(2,Tt.tileID.overscaledZ),be=Tt.tileSize*Math.pow(2,ot.transform.tileZoom)/ve,De=be*(Tt.tileID.canonical.x+Tt.tileID.wrap*ve),Be=be*Tt.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:Yt.tl,u_pattern_br_a:Yt.br,u_pattern_tl_b:Kt.tl,u_pattern_br_b:Kt.br,u_texsize:[xr,Ir],u_mix:Xe.t,u_pattern_size_a:Yt.displaySize,u_pattern_size_b:Kt.displaySize,u_scale_a:Xe.fromScale,u_scale_b:Xe.toScale,u_tile_units_to_pixels:1/In(Tt,1,ot.transform.tileZoom),u_pixel_coord_upper:[De>>16,Be>>16],u_pixel_coord_lower:[65535&De,65535&Be]}}(Q,le,B,ee),{u_matrix:ue,u_opacity:w}),nc={fillExtrusion:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_lightpos:new a.aN(ue,w.u_lightpos),u_lightintensity:new a.aI(ue,w.u_lightintensity),u_lightcolor:new a.aN(ue,w.u_lightcolor),u_vertical_gradient:new a.aI(ue,w.u_vertical_gradient),u_opacity:new 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a.aO(ue,w.u_world)}),fillOutlinePattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_world:new a.aO(ue,w.u_world),u_image:new a.aH(ue,w.u_image),u_texsize:new a.aO(ue,w.u_texsize),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_scale:new a.aN(ue,w.u_scale),u_fade:new a.aI(ue,w.u_fade)}),circle:(ue,w)=>({u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_scale_with_map:new a.aH(ue,w.u_scale_with_map),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_extrude_scale:new a.aO(ue,w.u_extrude_scale),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_matrix:new a.aJ(ue,w.u_matrix)}),collisionBox:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_pixel_extrude_scale:new a.aO(ue,w.u_pixel_extrude_scale)}),collisionCircle:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_inv_matrix:new a.aJ(ue,w.u_inv_matrix),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_viewport_size:new a.aO(ue,w.u_viewport_size)}),debug:(ue,w)=>({u_color:new a.aL(ue,w.u_color),u_matrix:new a.aJ(ue,w.u_matrix),u_overlay:new a.aH(ue,w.u_overlay),u_overlay_scale:new a.aI(ue,w.u_overlay_scale)}),clippingMask:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix)}),heatmap:(ue,w)=>({u_extrude_scale:new a.aI(ue,w.u_extrude_scale),u_intensity:new a.aI(ue,w.u_intensity),u_matrix:new a.aJ(ue,w.u_matrix)}),heatmapTexture:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_world:new a.aO(ue,w.u_world),u_image:new a.aH(ue,w.u_image),u_color_ramp:new a.aH(ue,w.u_color_ramp),u_opacity:new a.aI(ue,w.u_opacity)}),hillshade:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_image:new a.aH(ue,w.u_image),u_latrange:new a.aO(ue,w.u_latrange),u_light:new a.aO(ue,w.u_light),u_shadow:new a.aL(ue,w.u_shadow),u_highlight:new a.aL(ue,w.u_highlight),u_accent:new a.aL(ue,w.u_accent)}),hillshadePrepare:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_image:new a.aH(ue,w.u_image),u_dimension:new a.aO(ue,w.u_dimension),u_zoom:new 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a.aO(ue,w.u_units_to_pixels),u_patternscale_a:new a.aO(ue,w.u_patternscale_a),u_patternscale_b:new a.aO(ue,w.u_patternscale_b),u_sdfgamma:new a.aI(ue,w.u_sdfgamma),u_image:new a.aH(ue,w.u_image),u_tex_y_a:new a.aI(ue,w.u_tex_y_a),u_tex_y_b:new a.aI(ue,w.u_tex_y_b),u_mix:new a.aI(ue,w.u_mix)}),raster:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_tl_parent:new a.aO(ue,w.u_tl_parent),u_scale_parent:new a.aI(ue,w.u_scale_parent),u_buffer_scale:new a.aI(ue,w.u_buffer_scale),u_fade_t:new a.aI(ue,w.u_fade_t),u_opacity:new a.aI(ue,w.u_opacity),u_image0:new a.aH(ue,w.u_image0),u_image1:new a.aH(ue,w.u_image1),u_brightness_low:new a.aI(ue,w.u_brightness_low),u_brightness_high:new a.aI(ue,w.u_brightness_high),u_saturation_factor:new a.aI(ue,w.u_saturation_factor),u_contrast_factor:new a.aI(ue,w.u_contrast_factor),u_spin_weights:new a.aN(ue,w.u_spin_weights)}),symbolIcon:(ue,w)=>({u_is_size_zoom_constant:new a.aH(ue,w.u_is_size_zoom_constant),u_is_size_feature_constant:new a.aH(ue,w.u_is_size_feature_constant),u_size_t:new a.aI(ue,w.u_size_t),u_size:new a.aI(ue,w.u_size),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_pitch:new a.aI(ue,w.u_pitch),u_rotate_symbol:new a.aH(ue,w.u_rotate_symbol),u_aspect_ratio:new a.aI(ue,w.u_aspect_ratio),u_fade_change:new a.aI(ue,w.u_fade_change),u_matrix:new a.aJ(ue,w.u_matrix),u_label_plane_matrix:new a.aJ(ue,w.u_label_plane_matrix),u_coord_matrix:new a.aJ(ue,w.u_coord_matrix),u_is_text:new a.aH(ue,w.u_is_text),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_is_along_line:new a.aH(ue,w.u_is_along_line),u_is_variable_anchor:new a.aH(ue,w.u_is_variable_anchor),u_texsize:new a.aO(ue,w.u_texsize),u_texture:new a.aH(ue,w.u_texture),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),symbolSDF:(ue,w)=>({u_is_size_zoom_constant:new a.aH(ue,w.u_is_size_zoom_constant),u_is_size_feature_constant:new a.aH(ue,w.u_is_size_feature_constant),u_size_t:new a.aI(ue,w.u_size_t),u_size:new a.aI(ue,w.u_size),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_pitch:new a.aI(ue,w.u_pitch),u_rotate_symbol:new a.aH(ue,w.u_rotate_symbol),u_aspect_ratio:new a.aI(ue,w.u_aspect_ratio),u_fade_change:new a.aI(ue,w.u_fade_change),u_matrix:new a.aJ(ue,w.u_matrix),u_label_plane_matrix:new a.aJ(ue,w.u_label_plane_matrix),u_coord_matrix:new a.aJ(ue,w.u_coord_matrix),u_is_text:new a.aH(ue,w.u_is_text),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_is_along_line:new a.aH(ue,w.u_is_along_line),u_is_variable_anchor:new a.aH(ue,w.u_is_variable_anchor),u_texsize:new a.aO(ue,w.u_texsize),u_texture:new a.aH(ue,w.u_texture),u_gamma_scale:new a.aI(ue,w.u_gamma_scale),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_is_halo:new a.aH(ue,w.u_is_halo),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),symbolTextAndIcon:(ue,w)=>({u_is_size_zoom_constant:new 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a.aH(ue,w.u_is_halo),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),background:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_opacity:new a.aI(ue,w.u_opacity),u_color:new a.aL(ue,w.u_color)}),backgroundPattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_opacity:new a.aI(ue,w.u_opacity),u_image:new a.aH(ue,w.u_image),u_pattern_tl_a:new a.aO(ue,w.u_pattern_tl_a),u_pattern_br_a:new a.aO(ue,w.u_pattern_br_a),u_pattern_tl_b:new a.aO(ue,w.u_pattern_tl_b),u_pattern_br_b:new a.aO(ue,w.u_pattern_br_b),u_texsize:new a.aO(ue,w.u_texsize),u_mix:new a.aI(ue,w.u_mix),u_pattern_size_a:new a.aO(ue,w.u_pattern_size_a),u_pattern_size_b:new a.aO(ue,w.u_pattern_size_b),u_scale_a:new a.aI(ue,w.u_scale_a),u_scale_b:new a.aI(ue,w.u_scale_b),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_tile_units_to_pixels:new a.aI(ue,w.u_tile_units_to_pixels)}),terrain:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_texture:new a.aH(ue,w.u_texture),u_ele_delta:new a.aI(ue,w.u_ele_delta),u_fog_matrix:new a.aJ(ue,w.u_fog_matrix),u_fog_color:new a.aL(ue,w.u_fog_color),u_fog_ground_blend:new a.aI(ue,w.u_fog_ground_blend),u_fog_ground_blend_opacity:new a.aI(ue,w.u_fog_ground_blend_opacity),u_horizon_color:new a.aL(ue,w.u_horizon_color),u_horizon_fog_blend:new a.aI(ue,w.u_horizon_fog_blend)}),terrainDepth:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_ele_delta:new a.aI(ue,w.u_ele_delta)}),terrainCoords:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_texture:new a.aH(ue,w.u_texture),u_terrain_coords_id:new a.aI(ue,w.u_terrain_coords_id),u_ele_delta:new a.aI(ue,w.u_ele_delta)}),sky:(ue,w)=>({u_sky_color:new a.aL(ue,w.u_sky_color),u_horizon_color:new a.aL(ue,w.u_horizon_color),u_horizon:new a.aI(ue,w.u_horizon),u_sky_horizon_blend:new a.aI(ue,w.u_sky_horizon_blend)})};class bs{constructor(w,B,Q){this.context=w;let ee=w.gl;this.buffer=ee.createBuffer(),this.dynamicDraw=!!Q,this.context.unbindVAO(),w.bindElementBuffer.set(this.buffer),ee.bufferData(ee.ELEMENT_ARRAY_BUFFER,B.arrayBuffer,this.dynamicDraw?ee.DYNAMIC_DRAW:ee.STATIC_DRAW),this.dynamicDraw||delete B.arrayBuffer}bind(){this.context.bindElementBuffer.set(this.buffer)}updateData(w){let B=this.context.gl;if(!this.dynamicDraw)throw new Error(\"Attempted to update data while not in dynamic mode.\");this.context.unbindVAO(),this.bind(),B.bufferSubData(B.ELEMENT_ARRAY_BUFFER,0,w.arrayBuffer)}destroy(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)}}let Rn={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"};class _a{constructor(w,B,Q,ee){this.length=B.length,this.attributes=Q,this.itemSize=B.bytesPerElement,this.dynamicDraw=ee,this.context=w;let le=w.gl;this.buffer=le.createBuffer(),w.bindVertexBuffer.set(this.buffer),le.bufferData(le.ARRAY_BUFFER,B.arrayBuffer,this.dynamicDraw?le.DYNAMIC_DRAW:le.STATIC_DRAW),this.dynamicDraw||delete B.arrayBuffer}bind(){this.context.bindVertexBuffer.set(this.buffer)}updateData(w){if(w.length!==this.length)throw new Error(`Length of new data is ${w.length}, which doesn't match current length of ${this.length}`);let B=this.context.gl;this.bind(),B.bufferSubData(B.ARRAY_BUFFER,0,w.arrayBuffer)}enableAttributes(w,B){for(let Q=0;Q<this.attributes.length;Q++){let ee=B.attributes[this.attributes[Q].name];ee!==void 0&&w.enableVertexAttribArray(ee)}}setVertexAttribPointers(w,B,Q){for(let ee=0;ee<this.attributes.length;ee++){let le=this.attributes[ee],qe=B.attributes[le.name];qe!==void 0&&w.vertexAttribPointer(qe,le.components,w[Rn[le.type]],!1,this.itemSize,le.offset+this.itemSize*(Q||0))}}destroy(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)}}let Vu=new WeakMap;function Ol(ue){var w;if(Vu.has(ue))return Vu.get(ue);{let B=(w=ue.getParameter(ue.VERSION))===null||w===void 0?void 0:w.startsWith(\"WebGL 2.0\");return Vu.set(ue,B),B}}class xo{constructor(w){this.gl=w.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1}get(){return this.current}set(w){}getDefault(){return this.default}setDefault(){this.set(this.default)}}class Yl extends xo{getDefault(){return a.aM.transparent}set(w){let B=this.current;(w.r!==B.r||w.g!==B.g||w.b!==B.b||w.a!==B.a||this.dirty)&&(this.gl.clearColor(w.r,w.g,w.b,w.a),this.current=w,this.dirty=!1)}}class Ns extends xo{getDefault(){return 1}set(w){(w!==this.current||this.dirty)&&(this.gl.clearDepth(w),this.current=w,this.dirty=!1)}}class Hl extends xo{getDefault(){return 0}set(w){(w!==this.current||this.dirty)&&(this.gl.clearStencil(w),this.current=w,this.dirty=!1)}}class ac extends xo{getDefault(){return[!0,!0,!0,!0]}set(w){let B=this.current;(w[0]!==B[0]||w[1]!==B[1]||w[2]!==B[2]||w[3]!==B[3]||this.dirty)&&(this.gl.colorMask(w[0],w[1],w[2],w[3]),this.current=w,this.dirty=!1)}}class aa extends xo{getDefault(){return!0}set(w){(w!==this.current||this.dirty)&&(this.gl.depthMask(w),this.current=w,this.dirty=!1)}}class Oo extends xo{getDefault(){return 255}set(w){(w!==this.current||this.dirty)&&(this.gl.stencilMask(w),this.current=w,this.dirty=!1)}}class qo extends xo{getDefault(){return{func:this.gl.ALWAYS,ref:0,mask:255}}set(w){let B=this.current;(w.func!==B.func||w.ref!==B.ref||w.mask!==B.mask||this.dirty)&&(this.gl.stencilFunc(w.func,w.ref,w.mask),this.current=w,this.dirty=!1)}}class ql extends xo{getDefault(){let w=this.gl;return[w.KEEP,w.KEEP,w.KEEP]}set(w){let B=this.current;(w[0]!==B[0]||w[1]!==B[1]||w[2]!==B[2]||this.dirty)&&(this.gl.stencilOp(w[0],w[1],w[2]),this.current=w,this.dirty=!1)}}class Pc extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;w?B.enable(B.STENCIL_TEST):B.disable(B.STENCIL_TEST),this.current=w,this.dirty=!1}}class Do extends xo{getDefault(){return[0,1]}set(w){let B=this.current;(w[0]!==B[0]||w[1]!==B[1]||this.dirty)&&(this.gl.depthRange(w[0],w[1]),this.current=w,this.dirty=!1)}}class rf extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;w?B.enable(B.DEPTH_TEST):B.disable(B.DEPTH_TEST),this.current=w,this.dirty=!1}}class Uf extends xo{getDefault(){return this.gl.LESS}set(w){(w!==this.current||this.dirty)&&(this.gl.depthFunc(w),this.current=w,this.dirty=!1)}}class pl extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;w?B.enable(B.BLEND):B.disable(B.BLEND),this.current=w,this.dirty=!1}}class Zc extends xo{getDefault(){let w=this.gl;return[w.ONE,w.ZERO]}set(w){let B=this.current;(w[0]!==B[0]||w[1]!==B[1]||this.dirty)&&(this.gl.blendFunc(w[0],w[1]),this.current=w,this.dirty=!1)}}class Kl extends xo{getDefault(){return a.aM.transparent}set(w){let B=this.current;(w.r!==B.r||w.g!==B.g||w.b!==B.b||w.a!==B.a||this.dirty)&&(this.gl.blendColor(w.r,w.g,w.b,w.a),this.current=w,this.dirty=!1)}}class Os extends xo{getDefault(){return this.gl.FUNC_ADD}set(w){(w!==this.current||this.dirty)&&(this.gl.blendEquation(w),this.current=w,this.dirty=!1)}}class yu extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;w?B.enable(B.CULL_FACE):B.disable(B.CULL_FACE),this.current=w,this.dirty=!1}}class oc extends xo{getDefault(){return this.gl.BACK}set(w){(w!==this.current||this.dirty)&&(this.gl.cullFace(w),this.current=w,this.dirty=!1)}}class Cf extends xo{getDefault(){return this.gl.CCW}set(w){(w!==this.current||this.dirty)&&(this.gl.frontFace(w),this.current=w,this.dirty=!1)}}class sc extends xo{getDefault(){return null}set(w){(w!==this.current||this.dirty)&&(this.gl.useProgram(w),this.current=w,this.dirty=!1)}}class Vh extends xo{getDefault(){return this.gl.TEXTURE0}set(w){(w!==this.current||this.dirty)&&(this.gl.activeTexture(w),this.current=w,this.dirty=!1)}}class Lf extends xo{getDefault(){let w=this.gl;return[0,0,w.drawingBufferWidth,w.drawingBufferHeight]}set(w){let B=this.current;(w[0]!==B[0]||w[1]!==B[1]||w[2]!==B[2]||w[3]!==B[3]||this.dirty)&&(this.gl.viewport(w[0],w[1],w[2],w[3]),this.current=w,this.dirty=!1)}}class cs extends xo{getDefault(){return null}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.bindFramebuffer(B.FRAMEBUFFER,w),this.current=w,this.dirty=!1}}class nf extends xo{getDefault(){return null}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.bindRenderbuffer(B.RENDERBUFFER,w),this.current=w,this.dirty=!1}}class Vf extends xo{getDefault(){return null}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.bindTexture(B.TEXTURE_2D,w),this.current=w,this.dirty=!1}}class Jl extends xo{getDefault(){return null}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.bindBuffer(B.ARRAY_BUFFER,w),this.current=w,this.dirty=!1}}class fl extends xo{getDefault(){return null}set(w){let B=this.gl;B.bindBuffer(B.ELEMENT_ARRAY_BUFFER,w),this.current=w,this.dirty=!1}}class lc extends xo{getDefault(){return null}set(w){var B;if(w===this.current&&!this.dirty)return;let Q=this.gl;Ol(Q)?Q.bindVertexArray(w):(B=Q.getExtension(\"OES_vertex_array_object\"))===null||B===void 0||B.bindVertexArrayOES(w),this.current=w,this.dirty=!1}}class Fu extends xo{getDefault(){return 4}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.pixelStorei(B.UNPACK_ALIGNMENT,w),this.current=w,this.dirty=!1}}class Es extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.pixelStorei(B.UNPACK_PREMULTIPLY_ALPHA_WEBGL,w),this.current=w,this.dirty=!1}}class Hs extends xo{getDefault(){return!1}set(w){if(w===this.current&&!this.dirty)return;let B=this.gl;B.pixelStorei(B.UNPACK_FLIP_Y_WEBGL,w),this.current=w,this.dirty=!1}}class Go extends xo{constructor(w,B){super(w),this.context=w,this.parent=B}getDefault(){return null}}class ps extends Go{setDirty(){this.dirty=!0}set(w){if(w===this.current&&!this.dirty)return;this.context.bindFramebuffer.set(this.parent);let B=this.gl;B.framebufferTexture2D(B.FRAMEBUFFER,B.COLOR_ATTACHMENT0,B.TEXTURE_2D,w,0),this.current=w,this.dirty=!1}}class uc extends Go{set(w){if(w===this.current&&!this.dirty)return;this.context.bindFramebuffer.set(this.parent);let B=this.gl;B.framebufferRenderbuffer(B.FRAMEBUFFER,B.DEPTH_ATTACHMENT,B.RENDERBUFFER,w),this.current=w,this.dirty=!1}}class xl extends Go{set(w){if(w===this.current&&!this.dirty)return;this.context.bindFramebuffer.set(this.parent);let B=this.gl;B.framebufferRenderbuffer(B.FRAMEBUFFER,B.DEPTH_STENCIL_ATTACHMENT,B.RENDERBUFFER,w),this.current=w,this.dirty=!1}}class Gu{constructor(w,B,Q,ee,le){this.context=w,this.width=B,this.height=Q;let qe=w.gl,Xe=this.framebuffer=qe.createFramebuffer();if(this.colorAttachment=new ps(w,Xe),ee)this.depthAttachment=le?new xl(w,Xe):new uc(w,Xe);else if(le)throw new Error(\"Stencil cannot be set without depth\");if(qe.checkFramebufferStatus(qe.FRAMEBUFFER)!==qe.FRAMEBUFFER_COMPLETE)throw new Error(\"Framebuffer is not complete\")}destroy(){let w=this.context.gl,B=this.colorAttachment.get();if(B&&w.deleteTexture(B),this.depthAttachment){let Q=this.depthAttachment.get();Q&&w.deleteRenderbuffer(Q)}w.deleteFramebuffer(this.framebuffer)}}class qs{constructor(w,B,Q){this.blendFunction=w,this.blendColor=B,this.mask=Q}}qs.Replace=[1,0],qs.disabled=new qs(qs.Replace,a.aM.transparent,[!1,!1,!1,!1]),qs.unblended=new qs(qs.Replace,a.aM.transparent,[!0,!0,!0,!0]),qs.alphaBlended=new qs([1,771],a.aM.transparent,[!0,!0,!0,!0]);class ad{constructor(w){var B,Q;if(this.gl=w,this.clearColor=new Yl(this),this.clearDepth=new Ns(this),this.clearStencil=new Hl(this),this.colorMask=new ac(this),this.depthMask=new aa(this),this.stencilMask=new Oo(this),this.stencilFunc=new qo(this),this.stencilOp=new ql(this),this.stencilTest=new Pc(this),this.depthRange=new Do(this),this.depthTest=new rf(this),this.depthFunc=new Uf(this),this.blend=new pl(this),this.blendFunc=new Zc(this),this.blendColor=new Kl(this),this.blendEquation=new Os(this),this.cullFace=new yu(this),this.cullFaceSide=new oc(this),this.frontFace=new Cf(this),this.program=new sc(this),this.activeTexture=new Vh(this),this.viewport=new Lf(this),this.bindFramebuffer=new cs(this),this.bindRenderbuffer=new nf(this),this.bindTexture=new Vf(this),this.bindVertexBuffer=new Jl(this),this.bindElementBuffer=new fl(this),this.bindVertexArray=new lc(this),this.pixelStoreUnpack=new Fu(this),this.pixelStoreUnpackPremultiplyAlpha=new Es(this),this.pixelStoreUnpackFlipY=new Hs(this),this.extTextureFilterAnisotropic=w.getExtension(\"EXT_texture_filter_anisotropic\")||w.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||w.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=w.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.maxTextureSize=w.getParameter(w.MAX_TEXTURE_SIZE),Ol(w)){this.HALF_FLOAT=w.HALF_FLOAT;let ee=w.getExtension(\"EXT_color_buffer_half_float\");this.RGBA16F=(B=w.RGBA16F)!==null&&B!==void 0?B:ee==null?void 0:ee.RGBA16F_EXT,this.RGB16F=(Q=w.RGB16F)!==null&&Q!==void 0?Q:ee==null?void 0:ee.RGB16F_EXT,w.getExtension(\"EXT_color_buffer_float\")}else{w.getExtension(\"EXT_color_buffer_half_float\"),w.getExtension(\"OES_texture_half_float_linear\");let ee=w.getExtension(\"OES_texture_half_float\");this.HALF_FLOAT=ee==null?void 0:ee.HALF_FLOAT_OES}}setDefault(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()}setDirty(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.bindVertexArray.dirty=!0,this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0}createIndexBuffer(w,B){return new bs(this,w,B)}createVertexBuffer(w,B,Q){return new _a(this,w,B,Q)}createRenderbuffer(w,B,Q){let ee=this.gl,le=ee.createRenderbuffer();return this.bindRenderbuffer.set(le),ee.renderbufferStorage(ee.RENDERBUFFER,w,B,Q),this.bindRenderbuffer.set(null),le}createFramebuffer(w,B,Q,ee){return new Gu(this,w,B,Q,ee)}clear({color:w,depth:B,stencil:Q}){let ee=this.gl,le=0;w&&(le|=ee.COLOR_BUFFER_BIT,this.clearColor.set(w),this.colorMask.set([!0,!0,!0,!0])),B!==void 0&&(le|=ee.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(B),this.depthMask.set(!0)),Q!==void 0&&(le|=ee.STENCIL_BUFFER_BIT,this.clearStencil.set(Q),this.stencilMask.set(255)),ee.clear(le)}setCullFace(w){w.enable===!1?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(w.mode),this.frontFace.set(w.frontFace))}setDepthMode(w){w.func!==this.gl.ALWAYS||w.mask?(this.depthTest.set(!0),this.depthFunc.set(w.func),this.depthMask.set(w.mask),this.depthRange.set(w.range)):this.depthTest.set(!1)}setStencilMode(w){w.test.func!==this.gl.ALWAYS||w.mask?(this.stencilTest.set(!0),this.stencilMask.set(w.mask),this.stencilOp.set([w.fail,w.depthFail,w.pass]),this.stencilFunc.set({func:w.test.func,ref:w.ref,mask:w.test.mask})):this.stencilTest.set(!1)}setColorMode(w){a.aE(w.blendFunction,qs.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(w.blendFunction),this.blendColor.set(w.blendColor)),this.colorMask.set(w.mask)}createVertexArray(){var w;return Ol(this.gl)?this.gl.createVertexArray():(w=this.gl.getExtension(\"OES_vertex_array_object\"))===null||w===void 0?void 0:w.createVertexArrayOES()}deleteVertexArray(w){var B;return Ol(this.gl)?this.gl.deleteVertexArray(w):(B=this.gl.getExtension(\"OES_vertex_array_object\"))===null||B===void 0?void 0:B.deleteVertexArrayOES(w)}unbindVAO(){this.bindVertexArray.set(null)}}class Po{constructor(w,B,Q){this.func=w,this.mask=B,this.range=Q}}Po.ReadOnly=!1,Po.ReadWrite=!0,Po.disabled=new Po(519,Po.ReadOnly,[0,1]);let od=7680;class Yo{constructor(w,B,Q,ee,le,qe){this.test=w,this.ref=B,this.mask=Q,this.fail=ee,this.depthFail=le,this.pass=qe}}Yo.disabled=new Yo({func:519,mask:0},0,0,od,od,od);class Pa{constructor(w,B,Q){this.enable=w,this.mode=B,this.frontFace=Q}}let af;function Hu(ue,w,B,Q,ee){let le=ue.context,qe=le.gl,Xe=ue.useProgram(\"collisionBox\"),ot=[],Tt=0,Yt=0;for(let Be=0;Be<Q.length;Be++){let et=Q[Be],We=w.getTile(et).getBucket(B);if(!We)continue;let it=ee?We.textCollisionBox:We.iconCollisionBox,Ft=We.collisionCircleArray;if(Ft.length>0){let Ht=a.H();a.aQ(Ht,We.placementInvProjMatrix,ue.transform.glCoordMatrix),a.aQ(Ht,Ht,We.placementViewportMatrix),ot.push({circleArray:Ft,circleOffset:Yt,transform:et.posMatrix,invTransform:Ht,coord:et}),Tt+=Ft.length/4,Yt=Tt}it&&Xe.draw(le,qe.LINES,Po.disabled,Yo.disabled,ue.colorModeForRenderPass(),Pa.disabled,{u_matrix:et.posMatrix,u_pixel_extrude_scale:[1/(Kt=ue.transform).width,1/Kt.height]},ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(et),B.id,it.layoutVertexBuffer,it.indexBuffer,it.segments,null,ue.transform.zoom,null,null,it.collisionVertexBuffer)}var Kt;if(!ee||!ot.length)return;let xr=ue.useProgram(\"collisionCircle\"),Ir=new a.aR;Ir.resize(4*Tt),Ir._trim();let ve=0;for(let Be of ot)for(let et=0;et<Be.circleArray.length/4;et++){let We=4*et,it=Be.circleArray[We+0],Ft=Be.circleArray[We+1],Ht=Be.circleArray[We+2],tr=Be.circleArray[We+3];Ir.emplace(ve++,it,Ft,Ht,tr,0),Ir.emplace(ve++,it,Ft,Ht,tr,1),Ir.emplace(ve++,it,Ft,Ht,tr,2),Ir.emplace(ve++,it,Ft,Ht,tr,3)}(!af||af.length<2*Tt)&&(af=function(Be){let et=2*Be,We=new a.aT;We.resize(et),We._trim();for(let it=0;it<et;it++){let Ft=6*it;We.uint16[Ft+0]=4*it+0,We.uint16[Ft+1]=4*it+1,We.uint16[Ft+2]=4*it+2,We.uint16[Ft+3]=4*it+2,We.uint16[Ft+4]=4*it+3,We.uint16[Ft+5]=4*it+0}return We}(Tt));let be=le.createIndexBuffer(af,!0),De=le.createVertexBuffer(Ir,a.aS.members,!0);for(let Be of ot){let et=No(Be.transform,Be.invTransform,ue.transform);xr.draw(le,qe.TRIANGLES,Po.disabled,Yo.disabled,ue.colorModeForRenderPass(),Pa.disabled,et,ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(Be.coord),B.id,De,be,a.a0.simpleSegment(0,2*Be.circleOffset,Be.circleArray.length,Be.circleArray.length/2),null,ue.transform.zoom,null,null,null)}De.destroy(),be.destroy()}Pa.disabled=new Pa(!1,1029,2305),Pa.backCCW=new Pa(!0,1029,2305);let bl=a.an(new Float32Array(16));function Gf(ue,w,B,Q,ee,le){let{horizontalAlign:qe,verticalAlign:Xe}=a.au(ue);return new a.P((-(qe-.5)*w/ee+Q[0])*le,(-(Xe-.5)*B/ee+Q[1])*le)}function Ic(ue,w,B,Q,ee,le){let qe=w.tileAnchorPoint.add(new a.P(w.translation[0],w.translation[1]));if(w.pitchWithMap){let Xe=Q.mult(le);B||(Xe=Xe.rotate(-ee));let ot=qe.add(Xe);return dt(ot.x,ot.y,w.labelPlaneMatrix,w.getElevation).point}if(B){let Xe=vt(w.tileAnchorPoint.x+1,w.tileAnchorPoint.y,w).point.sub(ue),ot=Math.atan(Xe.y/Xe.x)+(Xe.x<0?Math.PI:0);return ue.add(Q.rotate(ot))}return ue.add(Q)}function yf(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir){let ve=ue.text.placedSymbolArray,be=ue.text.dynamicLayoutVertexArray,De=ue.icon.dynamicLayoutVertexArray,Be={};be.clear();for(let et=0;et<ve.length;et++){let We=ve.get(et),it=We.hidden||!We.crossTileID||ue.allowVerticalPlacement&&!We.placedOrientation?null:Q[We.crossTileID];if(it){let Ft=new a.P(We.anchorX,We.anchorY),Ht={getElevation:Ir,width:ee.width,height:ee.height,labelPlaneMatrix:le,lineVertexArray:null,pitchWithMap:B,projection:Yt,projectionCache:null,tileAnchorPoint:Ft,translation:Kt,unwrappedTileID:xr},tr=B?dt(Ft.x,Ft.y,qe,Ir):vt(Ft.x,Ft.y,Ht),dr=Ge(ee.cameraToCenterDistance,tr.signedDistanceFromCamera),Sr=a.ai(ue.textSizeData,ot,We)*dr/a.ap;B&&(Sr*=ue.tilePixelRatio/Xe);let{width:Or,height:Wr,anchor:ni,textOffset:Pi,textBoxScale:cn}=it,ln=Gf(ni,Or,Wr,Pi,cn,Sr),Cn=Yt.getPitchedTextCorrection(ee,Ft.add(new a.P(Kt[0],Kt[1])),xr),Kn=Ic(tr.point,Ht,w,ln,ee.angle,Cn),Ta=ue.allowVerticalPlacement&&We.placedOrientation===a.ah.vertical?Math.PI/2:0;for(let fa=0;fa<We.numGlyphs;fa++)a.aj(be,Kn,Ta);Tt&&We.associatedIconIndex>=0&&(Be[We.associatedIconIndex]={shiftedAnchor:Kn,angle:Ta})}else pi(We.numGlyphs,be)}if(Tt){De.clear();let et=ue.icon.placedSymbolArray;for(let We=0;We<et.length;We++){let it=et.get(We);if(it.hidden)pi(it.numGlyphs,De);else{let Ft=Be[We];if(Ft)for(let Ht=0;Ht<it.numGlyphs;Ht++)a.aj(De,Ft.shiftedAnchor,Ft.angle);else pi(it.numGlyphs,De)}}ue.icon.dynamicLayoutVertexBuffer.updateData(De)}ue.text.dynamicLayoutVertexBuffer.updateData(be)}function Bl(ue,w,B){return B.iconsInText&&w?\"symbolTextAndIcon\":ue?\"symbolSDF\":\"symbolIcon\"}function wh(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt){let xr=ue.context,Ir=xr.gl,ve=ue.transform,be=yn(),De=Xe===\"map\",Be=ot===\"map\",et=Xe!==\"viewport\"&&B.layout.get(\"symbol-placement\")!==\"point\",We=De&&!Be&&!et,it=!Be&&et,Ft=!B.layout.get(\"symbol-sort-key\").isConstant(),Ht=!1,tr=ue.depthModeForSublayer(0,Po.ReadOnly),dr=B._unevaluatedLayout.hasValue(\"text-variable-anchor\")||B._unevaluatedLayout.hasValue(\"text-variable-anchor-offset\"),Sr=[],Or=be.getCircleRadiusCorrection(ve);for(let Wr of Q){let ni=w.getTile(Wr),Pi=ni.getBucket(B);if(!Pi)continue;let cn=ee?Pi.text:Pi.icon;if(!cn||!cn.segments.get().length||!cn.hasVisibleVertices)continue;let ln=cn.programConfigurations.get(B.id),Cn=ee||Pi.sdfIcons,Kn=ee?Pi.textSizeData:Pi.iconSizeData,Ta=Be||ve.pitch!==0,fa=ue.useProgram(Bl(Cn,ee,Pi),ln),$a=a.ag(Kn,ve.zoom),Co=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(Wr),Qa,mo,Bo,Ps,Ts=[0,0],wo=null;if(ee)mo=ni.glyphAtlasTexture,Bo=Ir.LINEAR,Qa=ni.glyphAtlasTexture.size,Pi.iconsInText&&(Ts=ni.imageAtlasTexture.size,wo=ni.imageAtlasTexture,Ps=Ta||ue.options.rotating||ue.options.zooming||Kn.kind===\"composite\"||Kn.kind===\"camera\"?Ir.LINEAR:Ir.NEAREST);else{let Ye=B.layout.get(\"icon-size\").constantOr(0)!==1||Pi.iconsNeedLinear;mo=ni.imageAtlasTexture,Bo=Cn||ue.options.rotating||ue.options.zooming||Ye||Ta?Ir.LINEAR:Ir.NEAREST,Qa=ni.imageAtlasTexture.size}let To=In(ni,1,ue.transform.zoom),hl=it?Wr.posMatrix:bl,Ul=Br(hl,Be,De,ue.transform,To),Lu=Vr(hl,Be,De,ue.transform,To),au=Vr(Wr.posMatrix,Be,De,ue.transform,To),Js=be.translatePosition(ue.transform,ni,le,qe),Ql=dr&&Pi.hasTextData(),dc=B.layout.get(\"icon-text-fit\")!==\"none\"&&Ql&&Pi.hasIconData();if(et){let Ye=ue.style.map.terrain?(nt,jt)=>ue.style.map.terrain.getElevation(Wr,nt,jt):null,kt=B.layout.get(\"text-rotation-alignment\")===\"map\";je(Pi,Wr.posMatrix,ue,ee,Ul,au,Be,Tt,kt,be,Wr.toUnwrapped(),ve.width,ve.height,Js,Ye)}let Tl=Wr.posMatrix,Al=ee&&dr||dc,X=et||Al?bl:Ul,se=Lu,Te=Cn&&B.paint.get(ee?\"text-halo-width\":\"icon-halo-width\").constantOr(1)!==0,Ne;Ne=Cn?Pi.iconsInText?ls(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,Qa,Ts,Or):Io(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,ee,Qa,!0,Or):zs(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,ee,Qa,Or);let He={program:fa,buffers:cn,uniformValues:Ne,atlasTexture:mo,atlasTextureIcon:wo,atlasInterpolation:Bo,atlasInterpolationIcon:Ps,isSDF:Cn,hasHalo:Te};if(Ft&&Pi.canOverlap){Ht=!0;let Ye=cn.segments.get();for(let kt of Ye)Sr.push({segments:new a.a0([kt]),sortKey:kt.sortKey,state:He,terrainData:Co})}else Sr.push({segments:cn.segments,sortKey:0,state:He,terrainData:Co})}Ht&&Sr.sort((Wr,ni)=>Wr.sortKey-ni.sortKey);for(let Wr of Sr){let ni=Wr.state;if(xr.activeTexture.set(Ir.TEXTURE0),ni.atlasTexture.bind(ni.atlasInterpolation,Ir.CLAMP_TO_EDGE),ni.atlasTextureIcon&&(xr.activeTexture.set(Ir.TEXTURE1),ni.atlasTextureIcon&&ni.atlasTextureIcon.bind(ni.atlasInterpolationIcon,Ir.CLAMP_TO_EDGE)),ni.isSDF){let Pi=ni.uniformValues;ni.hasHalo&&(Pi.u_is_halo=1,Qf(ni.buffers,Wr.segments,B,ue,ni.program,tr,Yt,Kt,Pi,Wr.terrainData)),Pi.u_is_halo=0}Qf(ni.buffers,Wr.segments,B,ue,ni.program,tr,Yt,Kt,ni.uniformValues,Wr.terrainData)}}function Qf(ue,w,B,Q,ee,le,qe,Xe,ot,Tt){let Yt=Q.context;ee.draw(Yt,Yt.gl.TRIANGLES,le,qe,Xe,Pa.disabled,ot,Tt,B.id,ue.layoutVertexBuffer,ue.indexBuffer,w,B.paint,Q.transform.zoom,ue.programConfigurations.get(B.id),ue.dynamicLayoutVertexBuffer,ue.opacityVertexBuffer)}function _f(ue,w,B,Q){let ee=ue.context,le=ee.gl,qe=Yo.disabled,Xe=new qs([le.ONE,le.ONE],a.aM.transparent,[!0,!0,!0,!0]),ot=w.getBucket(B);if(!ot)return;let Tt=Q.key,Yt=B.heatmapFbos.get(Tt);Yt||(Yt=eh(ee,w.tileSize,w.tileSize),B.heatmapFbos.set(Tt,Yt)),ee.bindFramebuffer.set(Yt.framebuffer),ee.viewport.set([0,0,w.tileSize,w.tileSize]),ee.clear({color:a.aM.transparent});let Kt=ot.programConfigurations.get(B.id),xr=ue.useProgram(\"heatmap\",Kt),Ir=ue.style.map.terrain.getTerrainData(Q);xr.draw(ee,le.TRIANGLES,Po.disabled,qe,Xe,Pa.disabled,ko(Q.posMatrix,w,ue.transform.zoom,B.paint.get(\"heatmap-intensity\")),Ir,B.id,ot.layoutVertexBuffer,ot.indexBuffer,ot.segments,B.paint,ue.transform.zoom,Kt)}function Yc(ue,w,B){let Q=ue.context,ee=Q.gl;Q.setColorMode(ue.colorModeForRenderPass());let le=th(Q,w),qe=B.key,Xe=w.heatmapFbos.get(qe);Xe&&(Q.activeTexture.set(ee.TEXTURE0),ee.bindTexture(ee.TEXTURE_2D,Xe.colorAttachment.get()),Q.activeTexture.set(ee.TEXTURE1),le.bind(ee.LINEAR,ee.CLAMP_TO_EDGE),ue.useProgram(\"heatmapTexture\").draw(Q,ee.TRIANGLES,Po.disabled,Yo.disabled,ue.colorModeForRenderPass(),Pa.disabled,Ds(ue,w,0,1),null,w.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments,w.paint,ue.transform.zoom),Xe.destroy(),w.heatmapFbos.delete(qe))}function eh(ue,w,B){var Q,ee;let le=ue.gl,qe=le.createTexture();le.bindTexture(le.TEXTURE_2D,qe),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_S,le.CLAMP_TO_EDGE),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_T,le.CLAMP_TO_EDGE),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MIN_FILTER,le.LINEAR),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MAG_FILTER,le.LINEAR);let Xe=(Q=ue.HALF_FLOAT)!==null&&Q!==void 0?Q:le.UNSIGNED_BYTE,ot=(ee=ue.RGBA16F)!==null&&ee!==void 0?ee:le.RGBA;le.texImage2D(le.TEXTURE_2D,0,ot,w,B,0,le.RGBA,Xe,null);let Tt=ue.createFramebuffer(w,B,!1,!1);return Tt.colorAttachment.set(qe),Tt}function th(ue,w){return w.colorRampTexture||(w.colorRampTexture=new g(ue,w.colorRamp,ue.gl.RGBA)),w.colorRampTexture}function ju(ue,w,B,Q,ee){if(!B||!Q||!Q.imageAtlas)return;let le=Q.imageAtlas.patternPositions,qe=le[B.to.toString()],Xe=le[B.from.toString()];if(!qe&&Xe&&(qe=Xe),!Xe&&qe&&(Xe=qe),!qe||!Xe){let ot=ee.getPaintProperty(w);qe=le[ot],Xe=le[ot]}qe&&Xe&&ue.setConstantPatternPositions(qe,Xe)}function Hf(ue,w,B,Q,ee,le,qe){let Xe=ue.context.gl,ot=\"fill-pattern\",Tt=B.paint.get(ot),Yt=Tt&&Tt.constantOr(1),Kt=B.getCrossfadeParameters(),xr,Ir,ve,be,De;qe?(Ir=Yt&&!B.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",xr=Xe.LINES):(Ir=Yt?\"fillPattern\":\"fill\",xr=Xe.TRIANGLES);let Be=Tt.constantOr(null);for(let et of Q){let We=w.getTile(et);if(Yt&&!We.patternsLoaded())continue;let it=We.getBucket(B);if(!it)continue;let Ft=it.programConfigurations.get(B.id),Ht=ue.useProgram(Ir,Ft),tr=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(et);Yt&&(ue.context.activeTexture.set(Xe.TEXTURE0),We.imageAtlasTexture.bind(Xe.LINEAR,Xe.CLAMP_TO_EDGE),Ft.updatePaintBuffers(Kt)),ju(Ft,ot,Be,We,B);let dr=tr?et:null,Sr=ue.translatePosMatrix(dr?dr.posMatrix:et.posMatrix,We,B.paint.get(\"fill-translate\"),B.paint.get(\"fill-translate-anchor\"));if(qe){be=it.indexBuffer2,De=it.segments2;let Or=[Xe.drawingBufferWidth,Xe.drawingBufferHeight];ve=Ir===\"fillOutlinePattern\"&&Yt?Ma(Sr,ue,Kt,We,Or):Jn(Sr,Or)}else be=it.indexBuffer,De=it.segments,ve=Yt?ya(Sr,ue,Kt,We):_n(Sr);Ht.draw(ue.context,xr,ee,ue.stencilModeForClipping(et),le,Pa.disabled,ve,tr,B.id,it.layoutVertexBuffer,be,De,B.paint,ue.transform.zoom,Ft)}}function cc(ue,w,B,Q,ee,le,qe){let Xe=ue.context,ot=Xe.gl,Tt=\"fill-extrusion-pattern\",Yt=B.paint.get(Tt),Kt=Yt.constantOr(1),xr=B.getCrossfadeParameters(),Ir=B.paint.get(\"fill-extrusion-opacity\"),ve=Yt.constantOr(null);for(let be of Q){let De=w.getTile(be),Be=De.getBucket(B);if(!Be)continue;let et=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(be),We=Be.programConfigurations.get(B.id),it=ue.useProgram(Kt?\"fillExtrusionPattern\":\"fillExtrusion\",We);Kt&&(ue.context.activeTexture.set(ot.TEXTURE0),De.imageAtlasTexture.bind(ot.LINEAR,ot.CLAMP_TO_EDGE),We.updatePaintBuffers(xr)),ju(We,Tt,ve,De,B);let Ft=ue.translatePosMatrix(be.posMatrix,De,B.paint.get(\"fill-extrusion-translate\"),B.paint.get(\"fill-extrusion-translate-anchor\")),Ht=B.paint.get(\"fill-extrusion-vertical-gradient\"),tr=Kt?Li(Ft,ue,Ht,Ir,be,xr,De):Mn(Ft,ue,Ht,Ir);it.draw(Xe,Xe.gl.TRIANGLES,ee,le,qe,Pa.backCCW,tr,et,B.id,Be.layoutVertexBuffer,Be.indexBuffer,Be.segments,B.paint,ue.transform.zoom,We,ue.style.map.terrain&&Be.centroidVertexBuffer)}}function of(ue,w,B,Q,ee,le,qe){let Xe=ue.context,ot=Xe.gl,Tt=B.fbo;if(!Tt)return;let Yt=ue.useProgram(\"hillshade\"),Kt=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(w);Xe.activeTexture.set(ot.TEXTURE0),ot.bindTexture(ot.TEXTURE_2D,Tt.colorAttachment.get()),Yt.draw(Xe,ot.TRIANGLES,ee,le,qe,Pa.disabled,((xr,Ir,ve,be)=>{let De=ve.paint.get(\"hillshade-shadow-color\"),Be=ve.paint.get(\"hillshade-highlight-color\"),et=ve.paint.get(\"hillshade-accent-color\"),We=ve.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);ve.paint.get(\"hillshade-illumination-anchor\")===\"viewport\"&&(We-=xr.transform.angle);let it=!xr.options.moving;return{u_matrix:be?be.posMatrix:xr.transform.calculatePosMatrix(Ir.tileID.toUnwrapped(),it),u_image:0,u_latrange:Fs(0,Ir.tileID),u_light:[ve.paint.get(\"hillshade-exaggeration\"),We],u_shadow:De,u_highlight:Be,u_accent:et}})(ue,B,Q,Kt?w:null),Kt,Q.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments)}function Nl(ue,w,B,Q,ee,le){let qe=ue.context,Xe=qe.gl,ot=w.dem;if(ot&&ot.data){let Tt=ot.dim,Yt=ot.stride,Kt=ot.getPixels();if(qe.activeTexture.set(Xe.TEXTURE1),qe.pixelStoreUnpackPremultiplyAlpha.set(!1),w.demTexture=w.demTexture||ue.getTileTexture(Yt),w.demTexture){let Ir=w.demTexture;Ir.update(Kt,{premultiply:!1}),Ir.bind(Xe.NEAREST,Xe.CLAMP_TO_EDGE)}else w.demTexture=new g(qe,Kt,Xe.RGBA,{premultiply:!1}),w.demTexture.bind(Xe.NEAREST,Xe.CLAMP_TO_EDGE);qe.activeTexture.set(Xe.TEXTURE0);let xr=w.fbo;if(!xr){let Ir=new g(qe,{width:Tt,height:Tt,data:null},Xe.RGBA);Ir.bind(Xe.LINEAR,Xe.CLAMP_TO_EDGE),xr=w.fbo=qe.createFramebuffer(Tt,Tt,!0,!1),xr.colorAttachment.set(Ir.texture)}qe.bindFramebuffer.set(xr.framebuffer),qe.viewport.set([0,0,Tt,Tt]),ue.useProgram(\"hillshadePrepare\").draw(qe,Xe.TRIANGLES,Q,ee,le,Pa.disabled,((Ir,ve)=>{let be=ve.stride,De=a.H();return a.aP(De,0,a.X,-a.X,0,0,1),a.J(De,De,[0,-a.X,0]),{u_matrix:De,u_image:1,u_dimension:[be,be],u_zoom:Ir.overscaledZ,u_unpack:ve.getUnpackVector()}})(w.tileID,ot),null,B.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments),w.needsHillshadePrepare=!1}}function Kc(ue,w,B,Q,ee,le){let qe=Q.paint.get(\"raster-fade-duration\");if(!le&&qe>0){let Xe=u.now(),ot=(Xe-ue.timeAdded)/qe,Tt=w?(Xe-w.timeAdded)/qe:-1,Yt=B.getSource(),Kt=ee.coveringZoomLevel({tileSize:Yt.tileSize,roundZoom:Yt.roundZoom}),xr=!w||Math.abs(w.tileID.overscaledZ-Kt)>Math.abs(ue.tileID.overscaledZ-Kt),Ir=xr&&ue.refreshedUponExpiration?1:a.ac(xr?ot:1-Tt,0,1);return ue.refreshedUponExpiration&&ot>=1&&(ue.refreshedUponExpiration=!1),w?{opacity:1,mix:1-Ir}:{opacity:Ir,mix:0}}return{opacity:1,mix:0}}let Rc=new a.aM(1,0,0,1),gs=new a.aM(0,1,0,1),jf=new a.aM(0,0,1,1),Gh=new a.aM(1,0,1,1),rh=new a.aM(0,1,1,1);function sf(ue,w,B,Q){Mu(ue,0,w+B/2,ue.transform.width,B,Q)}function Th(ue,w,B,Q){Mu(ue,w-B/2,0,B,ue.transform.height,Q)}function Mu(ue,w,B,Q,ee,le){let qe=ue.context,Xe=qe.gl;Xe.enable(Xe.SCISSOR_TEST),Xe.scissor(w*ue.pixelRatio,B*ue.pixelRatio,Q*ue.pixelRatio,ee*ue.pixelRatio),qe.clear({color:le}),Xe.disable(Xe.SCISSOR_TEST)}function ih(ue,w,B){let Q=ue.context,ee=Q.gl,le=B.posMatrix,qe=ue.useProgram(\"debug\"),Xe=Po.disabled,ot=Yo.disabled,Tt=ue.colorModeForRenderPass(),Yt=\"$debug\",Kt=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(B);Q.activeTexture.set(ee.TEXTURE0);let xr=w.getTileByID(B.key).latestRawTileData,Ir=Math.floor((xr&&xr.byteLength||0)/1024),ve=w.getTile(B).tileSize,be=512/Math.min(ve,512)*(B.overscaledZ/ue.transform.zoom)*.5,De=B.canonical.toString();B.overscaledZ!==B.canonical.z&&(De+=` => ${B.overscaledZ}`),function(Be,et){Be.initDebugOverlayCanvas();let We=Be.debugOverlayCanvas,it=Be.context.gl,Ft=Be.debugOverlayCanvas.getContext(\"2d\");Ft.clearRect(0,0,We.width,We.height),Ft.shadowColor=\"white\",Ft.shadowBlur=2,Ft.lineWidth=1.5,Ft.strokeStyle=\"white\",Ft.textBaseline=\"top\",Ft.font=\"bold 36px Open Sans, sans-serif\",Ft.fillText(et,5,5),Ft.strokeText(et,5,5),Be.debugOverlayTexture.update(We),Be.debugOverlayTexture.bind(it.LINEAR,it.CLAMP_TO_EDGE)}(ue,`${De} ${Ir}kB`),qe.draw(Q,ee.TRIANGLES,Xe,ot,qs.alphaBlended,Pa.disabled,po(le,a.aM.transparent,be),null,Yt,ue.debugBuffer,ue.quadTriangleIndexBuffer,ue.debugSegments),qe.draw(Q,ee.LINE_STRIP,Xe,ot,Tt,Pa.disabled,po(le,a.aM.red),Kt,Yt,ue.debugBuffer,ue.tileBorderIndexBuffer,ue.debugSegments)}function js(ue,w,B){let Q=ue.context,ee=Q.gl,le=ue.colorModeForRenderPass(),qe=new Po(ee.LEQUAL,Po.ReadWrite,ue.depthRangeFor3D),Xe=ue.useProgram(\"terrain\"),ot=w.getTerrainMesh();Q.bindFramebuffer.set(null),Q.viewport.set([0,0,ue.width,ue.height]);for(let Tt of B){let Yt=ue.renderToTexture.getTexture(Tt),Kt=w.getTerrainData(Tt.tileID);Q.activeTexture.set(ee.TEXTURE0),ee.bindTexture(ee.TEXTURE_2D,Yt.texture);let xr=ue.transform.calculatePosMatrix(Tt.tileID.toUnwrapped()),Ir=w.getMeshFrameDelta(ue.transform.zoom),ve=ue.transform.calculateFogMatrix(Tt.tileID.toUnwrapped()),be=Jr(xr,Ir,ve,ue.style.sky,ue.transform.pitch);Xe.draw(Q,ee.TRIANGLES,qe,Yo.disabled,le,Pa.backCCW,be,Kt,\"terrain\",ot.vertexBuffer,ot.indexBuffer,ot.segments)}}class Eu{constructor(w,B,Q){this.vertexBuffer=w,this.indexBuffer=B,this.segments=Q}destroy(){this.vertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.vertexBuffer=null,this.indexBuffer=null,this.segments=null}}class Dc{constructor(w,B){this.context=new ad(w),this.transform=B,this._tileTextures={},this.terrainFacilitator={dirty:!0,matrix:a.an(new Float64Array(16)),renderTime:0},this.setup(),this.numSublayers=mt.maxUnderzooming+mt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Wo}resize(w,B,Q){if(this.width=Math.floor(w*Q),this.height=Math.floor(B*Q),this.pixelRatio=Q,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(let ee of this.style._order)this.style._layers[ee].resize()}setup(){let w=this.context,B=new a.aX;B.emplaceBack(0,0),B.emplaceBack(a.X,0),B.emplaceBack(0,a.X),B.emplaceBack(a.X,a.X),this.tileExtentBuffer=w.createVertexBuffer(B,vo.members),this.tileExtentSegments=a.a0.simpleSegment(0,0,4,2);let Q=new a.aX;Q.emplaceBack(0,0),Q.emplaceBack(a.X,0),Q.emplaceBack(0,a.X),Q.emplaceBack(a.X,a.X),this.debugBuffer=w.createVertexBuffer(Q,vo.members),this.debugSegments=a.a0.simpleSegment(0,0,4,5);let ee=new a.$;ee.emplaceBack(0,0,0,0),ee.emplaceBack(a.X,0,a.X,0),ee.emplaceBack(0,a.X,0,a.X),ee.emplaceBack(a.X,a.X,a.X,a.X),this.rasterBoundsBuffer=w.createVertexBuffer(ee,lt.members),this.rasterBoundsSegments=a.a0.simpleSegment(0,0,4,2);let le=new a.aX;le.emplaceBack(0,0),le.emplaceBack(1,0),le.emplaceBack(0,1),le.emplaceBack(1,1),this.viewportBuffer=w.createVertexBuffer(le,vo.members),this.viewportSegments=a.a0.simpleSegment(0,0,4,2);let qe=new a.aZ;qe.emplaceBack(0),qe.emplaceBack(1),qe.emplaceBack(3),qe.emplaceBack(2),qe.emplaceBack(0),this.tileBorderIndexBuffer=w.createIndexBuffer(qe);let Xe=new a.aY;Xe.emplaceBack(0,1,2),Xe.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=w.createIndexBuffer(Xe);let ot=this.context.gl;this.stencilClearMode=new Yo({func:ot.ALWAYS,mask:0},0,255,ot.ZERO,ot.ZERO,ot.ZERO)}clearStencil(){let w=this.context,B=w.gl;this.nextStencilID=1,this.currentStencilSource=void 0;let Q=a.H();a.aP(Q,0,this.width,this.height,0,0,1),a.K(Q,Q,[B.drawingBufferWidth,B.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(w,B.TRIANGLES,Po.disabled,this.stencilClearMode,qs.disabled,Pa.disabled,Lo(Q),null,\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)}_renderTileClippingMasks(w,B){if(this.currentStencilSource===w.source||!w.isTileClipped()||!B||!B.length)return;this.currentStencilSource=w.source;let Q=this.context,ee=Q.gl;this.nextStencilID+B.length>256&&this.clearStencil(),Q.setColorMode(qs.disabled),Q.setDepthMode(Po.disabled);let le=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(let qe of B){let Xe=this._tileClippingMaskIDs[qe.key]=this.nextStencilID++,ot=this.style.map.terrain&&this.style.map.terrain.getTerrainData(qe);le.draw(Q,ee.TRIANGLES,Po.disabled,new Yo({func:ee.ALWAYS,mask:0},Xe,255,ee.KEEP,ee.KEEP,ee.REPLACE),qs.disabled,Pa.disabled,Lo(qe.posMatrix),ot,\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}stencilModeFor3D(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();let w=this.nextStencilID++,B=this.context.gl;return new Yo({func:B.NOTEQUAL,mask:255},w,255,B.KEEP,B.KEEP,B.REPLACE)}stencilModeForClipping(w){let B=this.context.gl;return new Yo({func:B.EQUAL,mask:255},this._tileClippingMaskIDs[w.key],0,B.KEEP,B.KEEP,B.REPLACE)}stencilConfigForOverlap(w){let B=this.context.gl,Q=w.sort((qe,Xe)=>Xe.overscaledZ-qe.overscaledZ),ee=Q[Q.length-1].overscaledZ,le=Q[0].overscaledZ-ee+1;if(le>1){this.currentStencilSource=void 0,this.nextStencilID+le>256&&this.clearStencil();let qe={};for(let Xe=0;Xe<le;Xe++)qe[Xe+ee]=new Yo({func:B.GEQUAL,mask:255},Xe+this.nextStencilID,255,B.KEEP,B.KEEP,B.REPLACE);return this.nextStencilID+=le,[qe,Q]}return[{[ee]:Yo.disabled},Q]}colorModeForRenderPass(){let w=this.context.gl;return this._showOverdrawInspector?new qs([w.CONSTANT_COLOR,w.ONE],new a.aM(.125,.125,.125,0),[!0,!0,!0,!0]):this.renderPass===\"opaque\"?qs.unblended:qs.alphaBlended}depthModeForSublayer(w,B,Q){if(!this.opaquePassEnabledForLayer())return Po.disabled;let ee=1-((1+this.currentLayer)*this.numSublayers+w)*this.depthEpsilon;return new Po(Q||this.context.gl.LEQUAL,B,[ee,ee])}opaquePassEnabledForLayer(){return this.currentLayer<this.opaquePassCutoff}render(w,B){this.style=w,this.options=B,this.lineAtlas=w.lineAtlas,this.imageManager=w.imageManager,this.glyphManager=w.glyphManager,this.symbolFadeChange=w.placement.symbolFadeChange(u.now()),this.imageManager.beginFrame();let Q=this.style._order,ee=this.style.sourceCaches,le={},qe={},Xe={};for(let ot in ee){let Tt=ee[ot];Tt.used&&Tt.prepare(this.context),le[ot]=Tt.getVisibleCoordinates(),qe[ot]=le[ot].slice().reverse(),Xe[ot]=Tt.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(let ot=0;ot<Q.length;ot++)if(this.style._layers[Q[ot]].is3D()){this.opaquePassCutoff=ot;break}this.maybeDrawDepthAndCoords(!1),this.renderToTexture&&(this.renderToTexture.prepareForRender(this.style,this.transform.zoom),this.opaquePassCutoff=0),this.renderPass=\"offscreen\";for(let ot of Q){let Tt=this.style._layers[ot];if(!Tt.hasOffscreenPass()||Tt.isHidden(this.transform.zoom))continue;let Yt=qe[Tt.source];(Tt.type===\"custom\"||Yt.length)&&this.renderLayer(this,ee[Tt.source],Tt,Yt)}if(this.context.bindFramebuffer.set(null),this.context.clear({color:B.showOverdrawInspector?a.aM.black:a.aM.transparent,depth:1}),this.clearStencil(),this.style.sky&&function(ot,Tt){let Yt=ot.context,Kt=Yt.gl,xr=((Be,et,We)=>({u_sky_color:Be.properties.get(\"sky-color\"),u_horizon_color:Be.properties.get(\"horizon-color\"),u_horizon:(et.height/2+et.getHorizon())*We,u_sky_horizon_blend:Be.properties.get(\"sky-horizon-blend\")*et.height/2*We}))(Tt,ot.style.map.transform,ot.pixelRatio),Ir=new Po(Kt.LEQUAL,Po.ReadWrite,[0,1]),ve=Yo.disabled,be=ot.colorModeForRenderPass(),De=ot.useProgram(\"sky\");if(!Tt.mesh){let Be=new a.aX;Be.emplaceBack(-1,-1),Be.emplaceBack(1,-1),Be.emplaceBack(1,1),Be.emplaceBack(-1,1);let et=new a.aY;et.emplaceBack(0,1,2),et.emplaceBack(0,2,3),Tt.mesh=new Eu(Yt.createVertexBuffer(Be,vo.members),Yt.createIndexBuffer(et),a.a0.simpleSegment(0,0,Be.length,et.length))}De.draw(Yt,Kt.TRIANGLES,Ir,ve,be,Pa.disabled,xr,void 0,\"sky\",Tt.mesh.vertexBuffer,Tt.mesh.indexBuffer,Tt.mesh.segments)}(this,this.style.sky),this._showOverdrawInspector=B.showOverdrawInspector,this.depthRangeFor3D=[0,1-(w._order.length+2)*this.numSublayers*this.depthEpsilon],!this.renderToTexture)for(this.renderPass=\"opaque\",this.currentLayer=Q.length-1;this.currentLayer>=0;this.currentLayer--){let ot=this.style._layers[Q[this.currentLayer]],Tt=ee[ot.source],Yt=le[ot.source];this._renderTileClippingMasks(ot,Yt),this.renderLayer(this,Tt,ot,Yt)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<Q.length;this.currentLayer++){let ot=this.style._layers[Q[this.currentLayer]],Tt=ee[ot.source];if(this.renderToTexture&&this.renderToTexture.renderLayer(ot))continue;let Yt=(ot.type===\"symbol\"?Xe:qe)[ot.source];this._renderTileClippingMasks(ot,le[ot.source]),this.renderLayer(this,Tt,ot,Yt)}if(this.options.showTileBoundaries){let ot=function(Tt,Yt){let Kt=null,xr=Object.values(Tt._layers).flatMap(De=>De.source&&!De.isHidden(Yt)?[Tt.sourceCaches[De.source]]:[]),Ir=xr.filter(De=>De.getSource().type===\"vector\"),ve=xr.filter(De=>De.getSource().type!==\"vector\"),be=De=>{(!Kt||Kt.getSource().maxzoom<De.getSource().maxzoom)&&(Kt=De)};return Ir.forEach(De=>be(De)),Kt||ve.forEach(De=>be(De)),Kt}(this.style,this.transform.zoom);ot&&function(Tt,Yt,Kt){for(let xr=0;xr<Kt.length;xr++)ih(Tt,Yt,Kt[xr])}(this,ot,ot.getVisibleCoordinates())}this.options.showPadding&&function(ot){let Tt=ot.transform.padding;sf(ot,ot.transform.height-(Tt.top||0),3,Rc),sf(ot,Tt.bottom||0,3,gs),Th(ot,Tt.left||0,3,jf),Th(ot,ot.transform.width-(Tt.right||0),3,Gh);let Yt=ot.transform.centerPoint;(function(Kt,xr,Ir,ve){Mu(Kt,xr-1,Ir-10,2,20,ve),Mu(Kt,xr-10,Ir-1,20,2,ve)})(ot,Yt.x,ot.transform.height-Yt.y,rh)}(this),this.context.setDefault()}maybeDrawDepthAndCoords(w){if(!this.style||!this.style.map||!this.style.map.terrain)return;let B=this.terrainFacilitator.matrix,Q=this.transform.modelViewProjectionMatrix,ee=this.terrainFacilitator.dirty;ee||(ee=w?!a.a_(B,Q):!a.a$(B,Q)),ee||(ee=this.style.map.terrain.sourceCache.tilesAfterTime(this.terrainFacilitator.renderTime).length>0),ee&&(a.b0(B,Q),this.terrainFacilitator.renderTime=Date.now(),this.terrainFacilitator.dirty=!1,function(le,qe){let Xe=le.context,ot=Xe.gl,Tt=qs.unblended,Yt=new Po(ot.LEQUAL,Po.ReadWrite,[0,1]),Kt=qe.getTerrainMesh(),xr=qe.sourceCache.getRenderableTiles(),Ir=le.useProgram(\"terrainDepth\");Xe.bindFramebuffer.set(qe.getFramebuffer(\"depth\").framebuffer),Xe.viewport.set([0,0,le.width/devicePixelRatio,le.height/devicePixelRatio]),Xe.clear({color:a.aM.transparent,depth:1});for(let ve of xr){let be=qe.getTerrainData(ve.tileID),De={u_matrix:le.transform.calculatePosMatrix(ve.tileID.toUnwrapped()),u_ele_delta:qe.getMeshFrameDelta(le.transform.zoom)};Ir.draw(Xe,ot.TRIANGLES,Yt,Yo.disabled,Tt,Pa.backCCW,De,be,\"terrain\",Kt.vertexBuffer,Kt.indexBuffer,Kt.segments)}Xe.bindFramebuffer.set(null),Xe.viewport.set([0,0,le.width,le.height])}(this,this.style.map.terrain),function(le,qe){let Xe=le.context,ot=Xe.gl,Tt=qs.unblended,Yt=new Po(ot.LEQUAL,Po.ReadWrite,[0,1]),Kt=qe.getTerrainMesh(),xr=qe.getCoordsTexture(),Ir=qe.sourceCache.getRenderableTiles(),ve=le.useProgram(\"terrainCoords\");Xe.bindFramebuffer.set(qe.getFramebuffer(\"coords\").framebuffer),Xe.viewport.set([0,0,le.width/devicePixelRatio,le.height/devicePixelRatio]),Xe.clear({color:a.aM.transparent,depth:1}),qe.coordsIndex=[];for(let be of Ir){let De=qe.getTerrainData(be.tileID);Xe.activeTexture.set(ot.TEXTURE0),ot.bindTexture(ot.TEXTURE_2D,xr.texture);let Be={u_matrix:le.transform.calculatePosMatrix(be.tileID.toUnwrapped()),u_terrain_coords_id:(255-qe.coordsIndex.length)/255,u_texture:0,u_ele_delta:qe.getMeshFrameDelta(le.transform.zoom)};ve.draw(Xe,ot.TRIANGLES,Yt,Yo.disabled,Tt,Pa.backCCW,Be,De,\"terrain\",Kt.vertexBuffer,Kt.indexBuffer,Kt.segments),qe.coordsIndex.push(be.tileID.key)}Xe.bindFramebuffer.set(null),Xe.viewport.set([0,0,le.width,le.height])}(this,this.style.map.terrain))}renderLayer(w,B,Q,ee){if(!Q.isHidden(this.transform.zoom)&&(Q.type===\"background\"||Q.type===\"custom\"||(ee||[]).length))switch(this.id=Q.id,Q.type){case\"symbol\":(function(le,qe,Xe,ot,Tt){if(le.renderPass!==\"translucent\")return;let Yt=Yo.disabled,Kt=le.colorModeForRenderPass();(Xe._unevaluatedLayout.hasValue(\"text-variable-anchor\")||Xe._unevaluatedLayout.hasValue(\"text-variable-anchor-offset\"))&&function(xr,Ir,ve,be,De,Be,et,We,it){let Ft=Ir.transform,Ht=yn(),tr=De===\"map\",dr=Be===\"map\";for(let Sr of xr){let Or=be.getTile(Sr),Wr=Or.getBucket(ve);if(!Wr||!Wr.text||!Wr.text.segments.get().length)continue;let ni=a.ag(Wr.textSizeData,Ft.zoom),Pi=In(Or,1,Ir.transform.zoom),cn=Br(Sr.posMatrix,dr,tr,Ir.transform,Pi),ln=ve.layout.get(\"icon-text-fit\")!==\"none\"&&Wr.hasIconData();if(ni){let Cn=Math.pow(2,Ft.zoom-Or.tileID.overscaledZ),Kn=Ir.style.map.terrain?(fa,$a)=>Ir.style.map.terrain.getElevation(Sr,fa,$a):null,Ta=Ht.translatePosition(Ft,Or,et,We);yf(Wr,tr,dr,it,Ft,cn,Sr.posMatrix,Cn,ni,ln,Ht,Ta,Sr.toUnwrapped(),Kn)}}}(ot,le,Xe,qe,Xe.layout.get(\"text-rotation-alignment\"),Xe.layout.get(\"text-pitch-alignment\"),Xe.paint.get(\"text-translate\"),Xe.paint.get(\"text-translate-anchor\"),Tt),Xe.paint.get(\"icon-opacity\").constantOr(1)!==0&&wh(le,qe,Xe,ot,!1,Xe.paint.get(\"icon-translate\"),Xe.paint.get(\"icon-translate-anchor\"),Xe.layout.get(\"icon-rotation-alignment\"),Xe.layout.get(\"icon-pitch-alignment\"),Xe.layout.get(\"icon-keep-upright\"),Yt,Kt),Xe.paint.get(\"text-opacity\").constantOr(1)!==0&&wh(le,qe,Xe,ot,!0,Xe.paint.get(\"text-translate\"),Xe.paint.get(\"text-translate-anchor\"),Xe.layout.get(\"text-rotation-alignment\"),Xe.layout.get(\"text-pitch-alignment\"),Xe.layout.get(\"text-keep-upright\"),Yt,Kt),qe.map.showCollisionBoxes&&(Hu(le,qe,Xe,ot,!0),Hu(le,qe,Xe,ot,!1))})(w,B,Q,ee,this.style.placement.variableOffsets);break;case\"circle\":(function(le,qe,Xe,ot){if(le.renderPass!==\"translucent\")return;let Tt=Xe.paint.get(\"circle-opacity\"),Yt=Xe.paint.get(\"circle-stroke-width\"),Kt=Xe.paint.get(\"circle-stroke-opacity\"),xr=!Xe.layout.get(\"circle-sort-key\").isConstant();if(Tt.constantOr(1)===0&&(Yt.constantOr(1)===0||Kt.constantOr(1)===0))return;let Ir=le.context,ve=Ir.gl,be=le.depthModeForSublayer(0,Po.ReadOnly),De=Yo.disabled,Be=le.colorModeForRenderPass(),et=[];for(let We=0;We<ot.length;We++){let it=ot[We],Ft=qe.getTile(it),Ht=Ft.getBucket(Xe);if(!Ht)continue;let tr=Ht.programConfigurations.get(Xe.id),dr=le.useProgram(\"circle\",tr),Sr=Ht.layoutVertexBuffer,Or=Ht.indexBuffer,Wr=le.style.map.terrain&&le.style.map.terrain.getTerrainData(it),ni={programConfiguration:tr,program:dr,layoutVertexBuffer:Sr,indexBuffer:Or,uniformValues:_o(le,it,Ft,Xe),terrainData:Wr};if(xr){let Pi=Ht.segments.get();for(let cn of Pi)et.push({segments:new a.a0([cn]),sortKey:cn.sortKey,state:ni})}else et.push({segments:Ht.segments,sortKey:0,state:ni})}xr&&et.sort((We,it)=>We.sortKey-it.sortKey);for(let We of et){let{programConfiguration:it,program:Ft,layoutVertexBuffer:Ht,indexBuffer:tr,uniformValues:dr,terrainData:Sr}=We.state;Ft.draw(Ir,ve.TRIANGLES,be,De,Be,Pa.disabled,dr,Sr,Xe.id,Ht,tr,We.segments,Xe.paint,le.transform.zoom,it)}})(w,B,Q,ee);break;case\"heatmap\":(function(le,qe,Xe,ot){if(Xe.paint.get(\"heatmap-opacity\")===0)return;let Tt=le.context;if(le.style.map.terrain){for(let Yt of ot){let Kt=qe.getTile(Yt);qe.hasRenderableParent(Yt)||(le.renderPass===\"offscreen\"?_f(le,Kt,Xe,Yt):le.renderPass===\"translucent\"&&Yc(le,Xe,Yt))}Tt.viewport.set([0,0,le.width,le.height])}else le.renderPass===\"offscreen\"?function(Yt,Kt,xr,Ir){let ve=Yt.context,be=ve.gl,De=Yo.disabled,Be=new qs([be.ONE,be.ONE],a.aM.transparent,[!0,!0,!0,!0]);(function(et,We,it){let Ft=et.gl;et.activeTexture.set(Ft.TEXTURE1),et.viewport.set([0,0,We.width/4,We.height/4]);let Ht=it.heatmapFbos.get(a.aU);Ht?(Ft.bindTexture(Ft.TEXTURE_2D,Ht.colorAttachment.get()),et.bindFramebuffer.set(Ht.framebuffer)):(Ht=eh(et,We.width/4,We.height/4),it.heatmapFbos.set(a.aU,Ht))})(ve,Yt,xr),ve.clear({color:a.aM.transparent});for(let et=0;et<Ir.length;et++){let We=Ir[et];if(Kt.hasRenderableParent(We))continue;let it=Kt.getTile(We),Ft=it.getBucket(xr);if(!Ft)continue;let Ht=Ft.programConfigurations.get(xr.id),tr=Yt.useProgram(\"heatmap\",Ht),{zoom:dr}=Yt.transform;tr.draw(ve,be.TRIANGLES,Po.disabled,De,Be,Pa.disabled,ko(We.posMatrix,it,dr,xr.paint.get(\"heatmap-intensity\")),null,xr.id,Ft.layoutVertexBuffer,Ft.indexBuffer,Ft.segments,xr.paint,Yt.transform.zoom,Ht)}ve.viewport.set([0,0,Yt.width,Yt.height])}(le,qe,Xe,ot):le.renderPass===\"translucent\"&&function(Yt,Kt){let xr=Yt.context,Ir=xr.gl;xr.setColorMode(Yt.colorModeForRenderPass());let ve=Kt.heatmapFbos.get(a.aU);ve&&(xr.activeTexture.set(Ir.TEXTURE0),Ir.bindTexture(Ir.TEXTURE_2D,ve.colorAttachment.get()),xr.activeTexture.set(Ir.TEXTURE1),th(xr,Kt).bind(Ir.LINEAR,Ir.CLAMP_TO_EDGE),Yt.useProgram(\"heatmapTexture\").draw(xr,Ir.TRIANGLES,Po.disabled,Yo.disabled,Yt.colorModeForRenderPass(),Pa.disabled,Ds(Yt,Kt,0,1),null,Kt.id,Yt.viewportBuffer,Yt.quadTriangleIndexBuffer,Yt.viewportSegments,Kt.paint,Yt.transform.zoom))}(le,Xe)})(w,B,Q,ee);break;case\"line\":(function(le,qe,Xe,ot){if(le.renderPass!==\"translucent\")return;let Tt=Xe.paint.get(\"line-opacity\"),Yt=Xe.paint.get(\"line-width\");if(Tt.constantOr(1)===0||Yt.constantOr(1)===0)return;let Kt=le.depthModeForSublayer(0,Po.ReadOnly),xr=le.colorModeForRenderPass(),Ir=Xe.paint.get(\"line-dasharray\"),ve=Xe.paint.get(\"line-pattern\"),be=ve.constantOr(1),De=Xe.paint.get(\"line-gradient\"),Be=Xe.getCrossfadeParameters(),et=be?\"linePattern\":Ir?\"lineSDF\":De?\"lineGradient\":\"line\",We=le.context,it=We.gl,Ft=!0;for(let Ht of ot){let tr=qe.getTile(Ht);if(be&&!tr.patternsLoaded())continue;let dr=tr.getBucket(Xe);if(!dr)continue;let Sr=dr.programConfigurations.get(Xe.id),Or=le.context.program.get(),Wr=le.useProgram(et,Sr),ni=Ft||Wr.program!==Or,Pi=le.style.map.terrain&&le.style.map.terrain.getTerrainData(Ht),cn=ve.constantOr(null);if(cn&&tr.imageAtlas){let Kn=tr.imageAtlas,Ta=Kn.patternPositions[cn.to.toString()],fa=Kn.patternPositions[cn.from.toString()];Ta&&fa&&Sr.setConstantPatternPositions(Ta,fa)}let ln=Pi?Ht:null,Cn=be?zl(le,tr,Xe,Be,ln):Ir?us(le,tr,Xe,Ir,Be,ln):De?ul(le,tr,Xe,dr.lineClipsArray.length,ln):ll(le,tr,Xe,ln);if(be)We.activeTexture.set(it.TEXTURE0),tr.imageAtlasTexture.bind(it.LINEAR,it.CLAMP_TO_EDGE),Sr.updatePaintBuffers(Be);else if(Ir&&(ni||le.lineAtlas.dirty))We.activeTexture.set(it.TEXTURE0),le.lineAtlas.bind(We);else if(De){let Kn=dr.gradients[Xe.id],Ta=Kn.texture;if(Xe.gradientVersion!==Kn.version){let fa=256;if(Xe.stepInterpolant){let $a=qe.getSource().maxzoom,Co=Ht.canonical.z===$a?Math.ceil(1<<le.transform.maxZoom-Ht.canonical.z):1;fa=a.ac(a.aV(dr.maxLineLength/a.X*1024*Co),256,We.maxTextureSize)}Kn.gradient=a.aW({expression:Xe.gradientExpression(),evaluationKey:\"lineProgress\",resolution:fa,image:Kn.gradient||void 0,clips:dr.lineClipsArray}),Kn.texture?Kn.texture.update(Kn.gradient):Kn.texture=new g(We,Kn.gradient,it.RGBA),Kn.version=Xe.gradientVersion,Ta=Kn.texture}We.activeTexture.set(it.TEXTURE0),Ta.bind(Xe.stepInterpolant?it.NEAREST:it.LINEAR,it.CLAMP_TO_EDGE)}Wr.draw(We,it.TRIANGLES,Kt,le.stencilModeForClipping(Ht),xr,Pa.disabled,Cn,Pi,Xe.id,dr.layoutVertexBuffer,dr.indexBuffer,dr.segments,Xe.paint,le.transform.zoom,Sr,dr.layoutVertexBuffer2),Ft=!1}})(w,B,Q,ee);break;case\"fill\":(function(le,qe,Xe,ot){let Tt=Xe.paint.get(\"fill-color\"),Yt=Xe.paint.get(\"fill-opacity\");if(Yt.constantOr(1)===0)return;let Kt=le.colorModeForRenderPass(),xr=Xe.paint.get(\"fill-pattern\"),Ir=le.opaquePassEnabledForLayer()&&!xr.constantOr(1)&&Tt.constantOr(a.aM.transparent).a===1&&Yt.constantOr(0)===1?\"opaque\":\"translucent\";if(le.renderPass===Ir){let ve=le.depthModeForSublayer(1,le.renderPass===\"opaque\"?Po.ReadWrite:Po.ReadOnly);Hf(le,qe,Xe,ot,ve,Kt,!1)}if(le.renderPass===\"translucent\"&&Xe.paint.get(\"fill-antialias\")){let ve=le.depthModeForSublayer(Xe.getPaintProperty(\"fill-outline-color\")?2:0,Po.ReadOnly);Hf(le,qe,Xe,ot,ve,Kt,!0)}})(w,B,Q,ee);break;case\"fill-extrusion\":(function(le,qe,Xe,ot){let Tt=Xe.paint.get(\"fill-extrusion-opacity\");if(Tt!==0&&le.renderPass===\"translucent\"){let Yt=new Po(le.context.gl.LEQUAL,Po.ReadWrite,le.depthRangeFor3D);if(Tt!==1||Xe.paint.get(\"fill-extrusion-pattern\").constantOr(1))cc(le,qe,Xe,ot,Yt,Yo.disabled,qs.disabled),cc(le,qe,Xe,ot,Yt,le.stencilModeFor3D(),le.colorModeForRenderPass());else{let Kt=le.colorModeForRenderPass();cc(le,qe,Xe,ot,Yt,Yo.disabled,Kt)}}})(w,B,Q,ee);break;case\"hillshade\":(function(le,qe,Xe,ot){if(le.renderPass!==\"offscreen\"&&le.renderPass!==\"translucent\")return;let Tt=le.context,Yt=le.depthModeForSublayer(0,Po.ReadOnly),Kt=le.colorModeForRenderPass(),[xr,Ir]=le.renderPass===\"translucent\"?le.stencilConfigForOverlap(ot):[{},ot];for(let ve of Ir){let be=qe.getTile(ve);be.needsHillshadePrepare!==void 0&&be.needsHillshadePrepare&&le.renderPass===\"offscreen\"?Nl(le,be,Xe,Yt,Yo.disabled,Kt):le.renderPass===\"translucent\"&&of(le,ve,be,Xe,Yt,xr[ve.overscaledZ],Kt)}Tt.viewport.set([0,0,le.width,le.height])})(w,B,Q,ee);break;case\"raster\":(function(le,qe,Xe,ot){if(le.renderPass!==\"translucent\"||Xe.paint.get(\"raster-opacity\")===0||!ot.length)return;let Tt=le.context,Yt=Tt.gl,Kt=qe.getSource(),xr=le.useProgram(\"raster\"),Ir=le.colorModeForRenderPass(),[ve,be]=Kt instanceof Gt?[{},ot]:le.stencilConfigForOverlap(ot),De=be[be.length-1].overscaledZ,Be=!le.options.moving;for(let et of be){let We=le.depthModeForSublayer(et.overscaledZ-De,Xe.paint.get(\"raster-opacity\")===1?Po.ReadWrite:Po.ReadOnly,Yt.LESS),it=qe.getTile(et);it.registerFadeDuration(Xe.paint.get(\"raster-fade-duration\"));let Ft=qe.findLoadedParent(et,0),Ht=qe.findLoadedSibling(et),tr=Kc(it,Ft||Ht||null,qe,Xe,le.transform,le.style.map.terrain),dr,Sr,Or=Xe.paint.get(\"raster-resampling\")===\"nearest\"?Yt.NEAREST:Yt.LINEAR;Tt.activeTexture.set(Yt.TEXTURE0),it.texture.bind(Or,Yt.CLAMP_TO_EDGE,Yt.LINEAR_MIPMAP_NEAREST),Tt.activeTexture.set(Yt.TEXTURE1),Ft?(Ft.texture.bind(Or,Yt.CLAMP_TO_EDGE,Yt.LINEAR_MIPMAP_NEAREST),dr=Math.pow(2,Ft.tileID.overscaledZ-it.tileID.overscaledZ),Sr=[it.tileID.canonical.x*dr%1,it.tileID.canonical.y*dr%1]):it.texture.bind(Or,Yt.CLAMP_TO_EDGE,Yt.LINEAR_MIPMAP_NEAREST),it.texture.useMipmap&&Tt.extTextureFilterAnisotropic&&le.transform.pitch>20&&Yt.texParameterf(Yt.TEXTURE_2D,Tt.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,Tt.extTextureFilterAnisotropicMax);let Wr=le.style.map.terrain&&le.style.map.terrain.getTerrainData(et),ni=Wr?et:null,Pi=ni?ni.posMatrix:le.transform.calculatePosMatrix(et.toUnwrapped(),Be),cn=cl(Pi,Sr||[0,0],dr||1,tr,Xe);Kt instanceof Gt?xr.draw(Tt,Yt.TRIANGLES,We,Yo.disabled,Ir,Pa.disabled,cn,Wr,Xe.id,Kt.boundsBuffer,le.quadTriangleIndexBuffer,Kt.boundsSegments):xr.draw(Tt,Yt.TRIANGLES,We,ve[et.overscaledZ],Ir,Pa.disabled,cn,Wr,Xe.id,le.rasterBoundsBuffer,le.quadTriangleIndexBuffer,le.rasterBoundsSegments)}})(w,B,Q,ee);break;case\"background\":(function(le,qe,Xe,ot){let Tt=Xe.paint.get(\"background-color\"),Yt=Xe.paint.get(\"background-opacity\");if(Yt===0)return;let Kt=le.context,xr=Kt.gl,Ir=le.transform,ve=Ir.tileSize,be=Xe.paint.get(\"background-pattern\");if(le.isPatternMissing(be))return;let De=!be&&Tt.a===1&&Yt===1&&le.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(le.renderPass!==De)return;let Be=Yo.disabled,et=le.depthModeForSublayer(0,De===\"opaque\"?Po.ReadWrite:Po.ReadOnly),We=le.colorModeForRenderPass(),it=le.useProgram(be?\"backgroundPattern\":\"background\"),Ft=ot||Ir.coveringTiles({tileSize:ve,terrain:le.style.map.terrain});be&&(Kt.activeTexture.set(xr.TEXTURE0),le.imageManager.bind(le.context));let Ht=Xe.getCrossfadeParameters();for(let tr of Ft){let dr=ot?tr.posMatrix:le.transform.calculatePosMatrix(tr.toUnwrapped()),Sr=be?Su(dr,Yt,le,be,{tileID:tr,tileSize:ve},Ht):Zl(dr,Yt,Tt),Or=le.style.map.terrain&&le.style.map.terrain.getTerrainData(tr);it.draw(Kt,xr.TRIANGLES,et,Be,We,Pa.disabled,Sr,Or,Xe.id,le.tileExtentBuffer,le.quadTriangleIndexBuffer,le.tileExtentSegments)}})(w,0,Q,ee);break;case\"custom\":(function(le,qe,Xe){let ot=le.context,Tt=Xe.implementation;if(le.renderPass===\"offscreen\"){let Yt=Tt.prerender;Yt&&(le.setCustomLayerDefaults(),ot.setColorMode(le.colorModeForRenderPass()),Yt.call(Tt,ot.gl,le.transform.customLayerMatrix()),ot.setDirty(),le.setBaseState())}else if(le.renderPass===\"translucent\"){le.setCustomLayerDefaults(),ot.setColorMode(le.colorModeForRenderPass()),ot.setStencilMode(Yo.disabled);let Yt=Tt.renderingMode===\"3d\"?new Po(le.context.gl.LEQUAL,Po.ReadWrite,le.depthRangeFor3D):le.depthModeForSublayer(0,Po.ReadOnly);ot.setDepthMode(Yt),Tt.render(ot.gl,le.transform.customLayerMatrix(),{farZ:le.transform.farZ,nearZ:le.transform.nearZ,fov:le.transform._fov,modelViewProjectionMatrix:le.transform.modelViewProjectionMatrix,projectionMatrix:le.transform.projectionMatrix}),ot.setDirty(),le.setBaseState(),ot.bindFramebuffer.set(null)}})(w,0,Q)}}translatePosMatrix(w,B,Q,ee,le){if(!Q[0]&&!Q[1])return w;let qe=le?ee===\"map\"?this.transform.angle:0:ee===\"viewport\"?-this.transform.angle:0;if(qe){let Tt=Math.sin(qe),Yt=Math.cos(qe);Q=[Q[0]*Yt-Q[1]*Tt,Q[0]*Tt+Q[1]*Yt]}let Xe=[le?Q[0]:In(B,Q[0],this.transform.zoom),le?Q[1]:In(B,Q[1],this.transform.zoom),0],ot=new Float32Array(16);return a.J(ot,w,Xe),ot}saveTileTexture(w){let B=this._tileTextures[w.size[0]];B?B.push(w):this._tileTextures[w.size[0]]=[w]}getTileTexture(w){let B=this._tileTextures[w];return B&&B.length>0?B.pop():null}isPatternMissing(w){if(!w)return!1;if(!w.from||!w.to)return!0;let B=this.imageManager.getPattern(w.from.toString()),Q=this.imageManager.getPattern(w.to.toString());return!B||!Q}useProgram(w,B){this.cache=this.cache||{};let Q=w+(B?B.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\")+(this.style.map.terrain?\"/terrain\":\"\");return this.cache[Q]||(this.cache[Q]=new hn(this.context,jn[w],B,nc[w],this._showOverdrawInspector,this.style.map.terrain)),this.cache[Q]}setCustomLayerDefaults(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()}setBaseState(){let w=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(w.FUNC_ADD)}initDebugOverlayCanvas(){this.debugOverlayCanvas==null&&(this.debugOverlayCanvas=document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new g(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))}destroy(){this.debugOverlayTexture&&this.debugOverlayTexture.destroy()}overLimit(){let{drawingBufferWidth:w,drawingBufferHeight:B}=this.context.gl;return this.width!==w||this.height!==B}}class ks{constructor(w,B){this.points=w,this.planes=B}static fromInvProjectionMatrix(w,B,Q){let ee=Math.pow(2,Q),le=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map(Xe=>{let ot=1/(Xe=a.af([],Xe,w))[3]/B*ee;return a.b1(Xe,Xe,[ot,ot,1/Xe[3],ot])}),qe=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map(Xe=>{let ot=function(xr,Ir){var ve=Ir[0],be=Ir[1],De=Ir[2],Be=ve*ve+be*be+De*De;return Be>0&&(Be=1/Math.sqrt(Be)),xr[0]=Ir[0]*Be,xr[1]=Ir[1]*Be,xr[2]=Ir[2]*Be,xr}([],function(xr,Ir,ve){var be=Ir[0],De=Ir[1],Be=Ir[2],et=ve[0],We=ve[1],it=ve[2];return xr[0]=De*it-Be*We,xr[1]=Be*et-be*it,xr[2]=be*We-De*et,xr}([],L([],le[Xe[0]],le[Xe[1]]),L([],le[Xe[2]],le[Xe[1]]))),Tt=-((Yt=ot)[0]*(Kt=le[Xe[1]])[0]+Yt[1]*Kt[1]+Yt[2]*Kt[2]);var Yt,Kt;return ot.concat(Tt)});return new ks(le,qe)}}class bc{constructor(w,B){this.min=w,this.max=B,this.center=function(Q,ee,le){return Q[0]=.5*ee[0],Q[1]=.5*ee[1],Q[2]=.5*ee[2],Q}([],function(Q,ee,le){return Q[0]=ee[0]+le[0],Q[1]=ee[1]+le[1],Q[2]=ee[2]+le[2],Q}([],this.min,this.max))}quadrant(w){let B=[w%2==0,w<2],Q=E(this.min),ee=E(this.max);for(let le=0;le<B.length;le++)Q[le]=B[le]?this.min[le]:this.center[le],ee[le]=B[le]?this.center[le]:this.max[le];return ee[2]=this.max[2],new bc(Q,ee)}distanceX(w){return Math.max(Math.min(this.max[0],w[0]),this.min[0])-w[0]}distanceY(w){return Math.max(Math.min(this.max[1],w[1]),this.min[1])-w[1]}intersects(w){let B=[[this.min[0],this.min[1],this.min[2],1],[this.max[0],this.min[1],this.min[2],1],[this.max[0],this.max[1],this.min[2],1],[this.min[0],this.max[1],this.min[2],1],[this.min[0],this.min[1],this.max[2],1],[this.max[0],this.min[1],this.max[2],1],[this.max[0],this.max[1],this.max[2],1],[this.min[0],this.max[1],this.max[2],1]],Q=!0;for(let ee=0;ee<w.planes.length;ee++){let le=w.planes[ee],qe=0;for(let Xe=0;Xe<B.length;Xe++)a.b2(le,B[Xe])>=0&&qe++;if(qe===0)return 0;qe!==B.length&&(Q=!1)}if(Q)return 2;for(let ee=0;ee<3;ee++){let le=Number.MAX_VALUE,qe=-Number.MAX_VALUE;for(let Xe=0;Xe<w.points.length;Xe++){let ot=w.points[Xe][ee]-this.min[ee];le=Math.min(le,ot),qe=Math.max(qe,ot)}if(qe<0||le>this.max[ee]-this.min[ee])return 0}return 1}}class hu{constructor(w=0,B=0,Q=0,ee=0){if(isNaN(w)||w<0||isNaN(B)||B<0||isNaN(Q)||Q<0||isNaN(ee)||ee<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=w,this.bottom=B,this.left=Q,this.right=ee}interpolate(w,B,Q){return B.top!=null&&w.top!=null&&(this.top=a.y.number(w.top,B.top,Q)),B.bottom!=null&&w.bottom!=null&&(this.bottom=a.y.number(w.bottom,B.bottom,Q)),B.left!=null&&w.left!=null&&(this.left=a.y.number(w.left,B.left,Q)),B.right!=null&&w.right!=null&&(this.right=a.y.number(w.right,B.right,Q)),this}getCenter(w,B){let Q=a.ac((this.left+w-this.right)/2,0,w),ee=a.ac((this.top+B-this.bottom)/2,0,B);return new a.P(Q,ee)}equals(w){return this.top===w.top&&this.bottom===w.bottom&&this.left===w.left&&this.right===w.right}clone(){return new hu(this.top,this.bottom,this.left,this.right)}toJSON(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}}}let _u=85.051129;class nl{constructor(w,B,Q,ee,le){this.tileSize=512,this._renderWorldCopies=le===void 0||!!le,this._minZoom=w||0,this._maxZoom=B||22,this._minPitch=Q==null?0:Q,this._maxPitch=ee==null?60:ee,this.setMaxBounds(),this.width=0,this.height=0,this._center=new a.N(0,0),this._elevation=0,this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new hu,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={},this.minElevationForCurrentTile=0}clone(){let w=new nl(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return w.apply(this),w}apply(w){this.tileSize=w.tileSize,this.latRange=w.latRange,this.lngRange=w.lngRange,this.width=w.width,this.height=w.height,this._center=w._center,this._elevation=w._elevation,this.minElevationForCurrentTile=w.minElevationForCurrentTile,this.zoom=w.zoom,this.angle=w.angle,this._fov=w._fov,this._pitch=w._pitch,this._unmodified=w._unmodified,this._edgeInsets=w._edgeInsets.clone(),this._calcMatrices()}get minZoom(){return this._minZoom}set minZoom(w){this._minZoom!==w&&(this._minZoom=w,this.zoom=Math.max(this.zoom,w))}get maxZoom(){return this._maxZoom}set maxZoom(w){this._maxZoom!==w&&(this._maxZoom=w,this.zoom=Math.min(this.zoom,w))}get minPitch(){return this._minPitch}set minPitch(w){this._minPitch!==w&&(this._minPitch=w,this.pitch=Math.max(this.pitch,w))}get maxPitch(){return this._maxPitch}set maxPitch(w){this._maxPitch!==w&&(this._maxPitch=w,this.pitch=Math.min(this.pitch,w))}get renderWorldCopies(){return this._renderWorldCopies}set renderWorldCopies(w){w===void 0?w=!0:w===null&&(w=!1),this._renderWorldCopies=w}get worldSize(){return this.tileSize*this.scale}get centerOffset(){return this.centerPoint._sub(this.size._div(2))}get size(){return new a.P(this.width,this.height)}get bearing(){return-this.angle/Math.PI*180}set bearing(w){let B=-a.b3(w,-180,180)*Math.PI/180;this.angle!==B&&(this._unmodified=!1,this.angle=B,this._calcMatrices(),this.rotationMatrix=function(){var Q=new a.A(4);return a.A!=Float32Array&&(Q[1]=0,Q[2]=0),Q[0]=1,Q[3]=1,Q}(),function(Q,ee,le){var qe=ee[0],Xe=ee[1],ot=ee[2],Tt=ee[3],Yt=Math.sin(le),Kt=Math.cos(le);Q[0]=qe*Kt+ot*Yt,Q[1]=Xe*Kt+Tt*Yt,Q[2]=qe*-Yt+ot*Kt,Q[3]=Xe*-Yt+Tt*Kt}(this.rotationMatrix,this.rotationMatrix,this.angle))}get pitch(){return this._pitch/Math.PI*180}set pitch(w){let B=a.ac(w,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==B&&(this._unmodified=!1,this._pitch=B,this._calcMatrices())}get fov(){return this._fov/Math.PI*180}set fov(w){w=Math.max(.01,Math.min(60,w)),this._fov!==w&&(this._unmodified=!1,this._fov=w/180*Math.PI,this._calcMatrices())}get zoom(){return this._zoom}set zoom(w){let B=Math.min(Math.max(w,this.minZoom),this.maxZoom);this._zoom!==B&&(this._unmodified=!1,this._zoom=B,this.tileZoom=Math.max(0,Math.floor(B)),this.scale=this.zoomScale(B),this._constrain(),this._calcMatrices())}get center(){return this._center}set center(w){w.lat===this._center.lat&&w.lng===this._center.lng||(this._unmodified=!1,this._center=w,this._constrain(),this._calcMatrices())}get elevation(){return this._elevation}set elevation(w){w!==this._elevation&&(this._elevation=w,this._constrain(),this._calcMatrices())}get padding(){return this._edgeInsets.toJSON()}set padding(w){this._edgeInsets.equals(w)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,w,1),this._calcMatrices())}get centerPoint(){return this._edgeInsets.getCenter(this.width,this.height)}isPaddingEqual(w){return this._edgeInsets.equals(w)}interpolatePadding(w,B,Q){this._unmodified=!1,this._edgeInsets.interpolate(w,B,Q),this._constrain(),this._calcMatrices()}coveringZoomLevel(w){let B=(w.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/w.tileSize));return Math.max(0,B)}getVisibleUnwrappedCoordinates(w){let B=[new a.b4(0,w)];if(this._renderWorldCopies){let Q=this.pointCoordinate(new a.P(0,0)),ee=this.pointCoordinate(new a.P(this.width,0)),le=this.pointCoordinate(new a.P(this.width,this.height)),qe=this.pointCoordinate(new a.P(0,this.height)),Xe=Math.floor(Math.min(Q.x,ee.x,le.x,qe.x)),ot=Math.floor(Math.max(Q.x,ee.x,le.x,qe.x)),Tt=1;for(let Yt=Xe-Tt;Yt<=ot+Tt;Yt++)Yt!==0&&B.push(new a.b4(Yt,w))}return B}coveringTiles(w){var B,Q;let ee=this.coveringZoomLevel(w),le=ee;if(w.minzoom!==void 0&&ee<w.minzoom)return[];w.maxzoom!==void 0&&ee>w.maxzoom&&(ee=w.maxzoom);let qe=this.pointCoordinate(this.getCameraPoint()),Xe=a.Z.fromLngLat(this.center),ot=Math.pow(2,ee),Tt=[ot*qe.x,ot*qe.y,0],Yt=[ot*Xe.x,ot*Xe.y,0],Kt=ks.fromInvProjectionMatrix(this.invModelViewProjectionMatrix,this.worldSize,ee),xr=w.minzoom||0;!w.terrain&&this.pitch<=60&&this._edgeInsets.top<.1&&(xr=ee);let Ir=w.terrain?2/Math.min(this.tileSize,w.tileSize)*this.tileSize:3,ve=We=>({aabb:new bc([We*ot,0,0],[(We+1)*ot,ot,0]),zoom:0,x:0,y:0,wrap:We,fullyVisible:!1}),be=[],De=[],Be=ee,et=w.reparseOverscaled?le:ee;if(this._renderWorldCopies)for(let We=1;We<=3;We++)be.push(ve(-We)),be.push(ve(We));for(be.push(ve(0));be.length>0;){let We=be.pop(),it=We.x,Ft=We.y,Ht=We.fullyVisible;if(!Ht){let Wr=We.aabb.intersects(Kt);if(Wr===0)continue;Ht=Wr===2}let tr=w.terrain?Tt:Yt,dr=We.aabb.distanceX(tr),Sr=We.aabb.distanceY(tr),Or=Math.max(Math.abs(dr),Math.abs(Sr));if(We.zoom===Be||Or>Ir+(1<<Be-We.zoom)-2&&We.zoom>=xr){let Wr=Be-We.zoom,ni=Tt[0]-.5-(it<<Wr),Pi=Tt[1]-.5-(Ft<<Wr);De.push({tileID:new a.S(We.zoom===Be?et:We.zoom,We.wrap,We.zoom,it,Ft),distanceSq:x([Yt[0]-.5-it,Yt[1]-.5-Ft]),tileDistanceToCamera:Math.sqrt(ni*ni+Pi*Pi)})}else for(let Wr=0;Wr<4;Wr++){let ni=(it<<1)+Wr%2,Pi=(Ft<<1)+(Wr>>1),cn=We.zoom+1,ln=We.aabb.quadrant(Wr);if(w.terrain){let Cn=new a.S(cn,We.wrap,cn,ni,Pi),Kn=w.terrain.getMinMaxElevation(Cn),Ta=(B=Kn.minElevation)!==null&&B!==void 0?B:this.elevation,fa=(Q=Kn.maxElevation)!==null&&Q!==void 0?Q:this.elevation;ln=new bc([ln.min[0],ln.min[1],Ta],[ln.max[0],ln.max[1],fa])}be.push({aabb:ln,zoom:cn,x:ni,y:Pi,wrap:We.wrap,fullyVisible:Ht})}}return De.sort((We,it)=>We.distanceSq-it.distanceSq).map(We=>We.tileID)}resize(w,B){this.width=w,this.height=B,this.pixelsToGLUnits=[2/w,-2/B],this._constrain(),this._calcMatrices()}get unmodified(){return this._unmodified}zoomScale(w){return Math.pow(2,w)}scaleZoom(w){return Math.log(w)/Math.LN2}project(w){let B=a.ac(w.lat,-85.051129,_u);return new a.P(a.O(w.lng)*this.worldSize,a.Q(B)*this.worldSize)}unproject(w){return new a.Z(w.x/this.worldSize,w.y/this.worldSize).toLngLat()}get point(){return this.project(this.center)}getCameraPosition(){return{lngLat:this.pointLocation(this.getCameraPoint()),altitude:Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter+this.elevation}}recalculateZoom(w){let B=this.elevation,Q=Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter,ee=this.pointLocation(this.centerPoint,w),le=w.getElevationForLngLatZoom(ee,this.tileZoom);if(!(this.elevation-le))return;let qe=Q+B-le,Xe=Math.cos(this._pitch)*this.cameraToCenterDistance/qe/a.b5(1,ee.lat),ot=this.scaleZoom(Xe/this.tileSize);this._elevation=le,this._center=ee,this.zoom=ot}setLocationAtPoint(w,B){let Q=this.pointCoordinate(B),ee=this.pointCoordinate(this.centerPoint),le=this.locationCoordinate(w),qe=new a.Z(le.x-(Q.x-ee.x),le.y-(Q.y-ee.y));this.center=this.coordinateLocation(qe),this._renderWorldCopies&&(this.center=this.center.wrap())}locationPoint(w,B){return B?this.coordinatePoint(this.locationCoordinate(w),B.getElevationForLngLatZoom(w,this.tileZoom),this.pixelMatrix3D):this.coordinatePoint(this.locationCoordinate(w))}pointLocation(w,B){return this.coordinateLocation(this.pointCoordinate(w,B))}locationCoordinate(w){return a.Z.fromLngLat(w)}coordinateLocation(w){return w&&w.toLngLat()}pointCoordinate(w,B){if(B){let xr=B.pointCoordinate(w);if(xr!=null)return xr}let Q=[w.x,w.y,0,1],ee=[w.x,w.y,1,1];a.af(Q,Q,this.pixelMatrixInverse),a.af(ee,ee,this.pixelMatrixInverse);let le=Q[3],qe=ee[3],Xe=Q[1]/le,ot=ee[1]/qe,Tt=Q[2]/le,Yt=ee[2]/qe,Kt=Tt===Yt?0:(0-Tt)/(Yt-Tt);return new a.Z(a.y.number(Q[0]/le,ee[0]/qe,Kt)/this.worldSize,a.y.number(Xe,ot,Kt)/this.worldSize)}coordinatePoint(w,B=0,Q=this.pixelMatrix){let ee=[w.x*this.worldSize,w.y*this.worldSize,B,1];return a.af(ee,ee,Q),new a.P(ee[0]/ee[3],ee[1]/ee[3])}getBounds(){let w=Math.max(0,this.height/2-this.getHorizon());return new ce().extend(this.pointLocation(new a.P(0,w))).extend(this.pointLocation(new a.P(this.width,w))).extend(this.pointLocation(new a.P(this.width,this.height))).extend(this.pointLocation(new a.P(0,this.height)))}getMaxBounds(){return this.latRange&&this.latRange.length===2&&this.lngRange&&this.lngRange.length===2?new ce([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null}getHorizon(){return Math.tan(Math.PI/2-this._pitch)*this.cameraToCenterDistance*.85}setMaxBounds(w){w?(this.lngRange=[w.getWest(),w.getEast()],this.latRange=[w.getSouth(),w.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-85.051129,_u])}calculateTileMatrix(w){let B=w.canonical,Q=this.worldSize/this.zoomScale(B.z),ee=B.x+Math.pow(2,B.z)*w.wrap,le=a.an(new Float64Array(16));return a.J(le,le,[ee*Q,B.y*Q,0]),a.K(le,le,[Q/a.X,Q/a.X,1]),le}calculatePosMatrix(w,B=!1){let Q=w.key,ee=B?this._alignedPosMatrixCache:this._posMatrixCache;if(ee[Q])return ee[Q];let le=this.calculateTileMatrix(w);return a.L(le,B?this.alignedModelViewProjectionMatrix:this.modelViewProjectionMatrix,le),ee[Q]=new Float32Array(le),ee[Q]}calculateFogMatrix(w){let B=w.key,Q=this._fogMatrixCache;if(Q[B])return Q[B];let ee=this.calculateTileMatrix(w);return a.L(ee,this.fogMatrix,ee),Q[B]=new Float32Array(ee),Q[B]}customLayerMatrix(){return this.mercatorMatrix.slice()}getConstrained(w,B){B=a.ac(+B,this.minZoom,this.maxZoom);let Q={center:new a.N(w.lng,w.lat),zoom:B},ee=this.lngRange;if(!this._renderWorldCopies&&ee===null){let We=179.9999999999;ee=[-We,We]}let le=this.tileSize*this.zoomScale(Q.zoom),qe=0,Xe=le,ot=0,Tt=le,Yt=0,Kt=0,{x:xr,y:Ir}=this.size;if(this.latRange){let We=this.latRange;qe=a.Q(We[1])*le,Xe=a.Q(We[0])*le,Xe-qe<Ir&&(Yt=Ir/(Xe-qe))}ee&&(ot=a.b3(a.O(ee[0])*le,0,le),Tt=a.b3(a.O(ee[1])*le,0,le),Tt<ot&&(Tt+=le),Tt-ot<xr&&(Kt=xr/(Tt-ot)));let{x:ve,y:be}=this.project.call({worldSize:le},w),De,Be,et=Math.max(Kt||0,Yt||0);if(et){let We=new a.P(Kt?(Tt+ot)/2:ve,Yt?(Xe+qe)/2:be);return Q.center=this.unproject.call({worldSize:le},We).wrap(),Q.zoom+=this.scaleZoom(et),Q}if(this.latRange){let We=Ir/2;be-We<qe&&(Be=qe+We),be+We>Xe&&(Be=Xe-We)}if(ee){let We=(ot+Tt)/2,it=ve;this._renderWorldCopies&&(it=a.b3(ve,We-le/2,We+le/2));let Ft=xr/2;it-Ft<ot&&(De=ot+Ft),it+Ft>Tt&&(De=Tt-Ft)}if(De!==void 0||Be!==void 0){let We=new a.P(De!=null?De:ve,Be!=null?Be:be);Q.center=this.unproject.call({worldSize:le},We).wrap()}return Q}_constrain(){if(!this.center||!this.width||!this.height||this._constraining)return;this._constraining=!0;let w=this._unmodified,{center:B,zoom:Q}=this.getConstrained(this.center,this.zoom);this.center=B,this.zoom=Q,this._unmodified=w,this._constraining=!1}_calcMatrices(){if(!this.height)return;let w=this.centerOffset,B=this.point.x,Q=this.point.y;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height,this._pixelPerMeter=a.b5(1,this.center.lat)*this.worldSize;let ee=a.an(new Float64Array(16));a.K(ee,ee,[this.width/2,-this.height/2,1]),a.J(ee,ee,[1,-1,0]),this.labelPlaneMatrix=ee,ee=a.an(new Float64Array(16)),a.K(ee,ee,[1,-1,1]),a.J(ee,ee,[-1,-1,0]),a.K(ee,ee,[2/this.width,2/this.height,1]),this.glCoordMatrix=ee;let le=this.cameraToCenterDistance+this._elevation*this._pixelPerMeter/Math.cos(this._pitch),qe=Math.min(this.elevation,this.minElevationForCurrentTile),Xe=le-qe*this._pixelPerMeter/Math.cos(this._pitch),ot=qe<0?Xe:le,Tt=Math.PI/2+this._pitch,Yt=this._fov*(.5+w.y/this.height),Kt=Math.sin(Yt)*ot/Math.sin(a.ac(Math.PI-Tt-Yt,.01,Math.PI-.01)),xr=this.getHorizon(),Ir=2*Math.atan(xr/this.cameraToCenterDistance)*(.5+w.y/(2*xr)),ve=Math.sin(Ir)*ot/Math.sin(a.ac(Math.PI-Tt-Ir,.01,Math.PI-.01)),be=Math.min(Kt,ve);this.farZ=1.01*(Math.cos(Math.PI/2-this._pitch)*be+ot),this.nearZ=this.height/50,ee=new Float64Array(16),a.b6(ee,this._fov,this.width/this.height,this.nearZ,this.farZ),ee[8]=2*-w.x/this.width,ee[9]=2*w.y/this.height,this.projectionMatrix=a.ae(ee),a.K(ee,ee,[1,-1,1]),a.J(ee,ee,[0,0,-this.cameraToCenterDistance]),a.b7(ee,ee,this._pitch),a.ad(ee,ee,this.angle),a.J(ee,ee,[-B,-Q,0]),this.mercatorMatrix=a.K([],ee,[this.worldSize,this.worldSize,this.worldSize]),a.K(ee,ee,[1,1,this._pixelPerMeter]),this.pixelMatrix=a.L(new Float64Array(16),this.labelPlaneMatrix,ee),a.J(ee,ee,[0,0,-this.elevation]),this.modelViewProjectionMatrix=ee,this.invModelViewProjectionMatrix=a.as([],ee),this.fogMatrix=new Float64Array(16),a.b6(this.fogMatrix,this._fov,this.width/this.height,le,this.farZ),this.fogMatrix[8]=2*-w.x/this.width,this.fogMatrix[9]=2*w.y/this.height,a.K(this.fogMatrix,this.fogMatrix,[1,-1,1]),a.J(this.fogMatrix,this.fogMatrix,[0,0,-this.cameraToCenterDistance]),a.b7(this.fogMatrix,this.fogMatrix,this._pitch),a.ad(this.fogMatrix,this.fogMatrix,this.angle),a.J(this.fogMatrix,this.fogMatrix,[-B,-Q,0]),a.K(this.fogMatrix,this.fogMatrix,[1,1,this._pixelPerMeter]),a.J(this.fogMatrix,this.fogMatrix,[0,0,-this.elevation]),this.pixelMatrix3D=a.L(new Float64Array(16),this.labelPlaneMatrix,ee);let De=this.width%2/2,Be=this.height%2/2,et=Math.cos(this.angle),We=Math.sin(this.angle),it=B-Math.round(B)+et*De+We*Be,Ft=Q-Math.round(Q)+et*Be+We*De,Ht=new Float64Array(ee);if(a.J(Ht,Ht,[it>.5?it-1:it,Ft>.5?Ft-1:Ft,0]),this.alignedModelViewProjectionMatrix=Ht,ee=a.as(new Float64Array(16),this.pixelMatrix),!ee)throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=ee,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={}}maxPitchScaleFactor(){if(!this.pixelMatrixInverse)return 1;let w=this.pointCoordinate(new a.P(0,0)),B=[w.x*this.worldSize,w.y*this.worldSize,0,1];return a.af(B,B,this.pixelMatrix)[3]/this.cameraToCenterDistance}getCameraPoint(){let w=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new a.P(0,w))}getCameraQueryGeometry(w){let B=this.getCameraPoint();if(w.length===1)return[w[0],B];{let Q=B.x,ee=B.y,le=B.x,qe=B.y;for(let Xe of w)Q=Math.min(Q,Xe.x),ee=Math.min(ee,Xe.y),le=Math.max(le,Xe.x),qe=Math.max(qe,Xe.y);return[new a.P(Q,ee),new a.P(le,ee),new a.P(le,qe),new a.P(Q,qe),new a.P(Q,ee)]}}lngLatToCameraDepth(w,B){let Q=this.locationCoordinate(w),ee=[Q.x*this.worldSize,Q.y*this.worldSize,B,1];return a.af(ee,ee,this.modelViewProjectionMatrix),ee[2]/ee[3]}}function nh(ue,w){let B,Q=!1,ee=null,le=null,qe=()=>{ee=null,Q&&(ue.apply(le,B),ee=setTimeout(qe,w),Q=!1)};return(...Xe)=>(Q=!0,le=this,B=Xe,ee||qe(),ee)}class Ah{constructor(w){this._getCurrentHash=()=>{let B=window.location.hash.replace(\"#\",\"\");if(this._hashName){let Q;return B.split(\"&\").map(ee=>ee.split(\"=\")).forEach(ee=>{ee[0]===this._hashName&&(Q=ee)}),(Q&&Q[1]||\"\").split(\"/\")}return B.split(\"/\")},this._onHashChange=()=>{let B=this._getCurrentHash();if(B.length>=3&&!B.some(Q=>isNaN(Q))){let Q=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(B[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+B[2],+B[1]],zoom:+B[0],bearing:Q,pitch:+(B[4]||0)}),!0}return!1},this._updateHashUnthrottled=()=>{let B=window.location.href.replace(/(#.*)?$/,this.getHashString());window.history.replaceState(window.history.state,null,B)},this._removeHash=()=>{let B=this._getCurrentHash();if(B.length===0)return;let Q=B.join(\"/\"),ee=Q;ee.split(\"&\").length>0&&(ee=ee.split(\"&\")[0]),this._hashName&&(ee=`${this._hashName}=${Q}`);let le=window.location.hash.replace(ee,\"\");le.startsWith(\"#&\")?le=le.slice(0,1)+le.slice(2):le===\"#\"&&(le=\"\");let qe=window.location.href.replace(/(#.+)?$/,le);qe=qe.replace(\"&&\",\"&\"),window.history.replaceState(window.history.state,null,qe)},this._updateHash=nh(this._updateHashUnthrottled,300),this._hashName=w&&encodeURIComponent(w)}addTo(w){return this._map=w,addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this}remove(){return removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),this._removeHash(),delete this._map,this}getHashString(w){let B=this._map.getCenter(),Q=Math.round(100*this._map.getZoom())/100,ee=Math.ceil((Q*Math.LN2+Math.log(512/360/.5))/Math.LN10),le=Math.pow(10,ee),qe=Math.round(B.lng*le)/le,Xe=Math.round(B.lat*le)/le,ot=this._map.getBearing(),Tt=this._map.getPitch(),Yt=\"\";if(Yt+=w?`/${qe}/${Xe}/${Q}`:`${Q}/${Xe}/${qe}`,(ot||Tt)&&(Yt+=\"/\"+Math.round(10*ot)/10),Tt&&(Yt+=`/${Math.round(Tt)}`),this._hashName){let Kt=this._hashName,xr=!1,Ir=window.location.hash.slice(1).split(\"&\").map(ve=>{let be=ve.split(\"=\")[0];return be===Kt?(xr=!0,`${be}=${Yt}`):ve}).filter(ve=>ve);return xr||Ir.push(`${Kt}=${Yt}`),`#${Ir.join(\"&\")}`}return`#${Yt}`}}let zu={linearity:.3,easing:a.b8(0,0,.3,1)},Fc=a.e({deceleration:2500,maxSpeed:1400},zu),wc=a.e({deceleration:20,maxSpeed:1400},zu),bd=a.e({deceleration:1e3,maxSpeed:360},zu),xf=a.e({deceleration:1e3,maxSpeed:90},zu);class Pf{constructor(w){this._map=w,this.clear()}clear(){this._inertiaBuffer=[]}record(w){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:u.now(),settings:w})}_drainInertiaBuffer(){let w=this._inertiaBuffer,B=u.now();for(;w.length>0&&B-w[0].time>160;)w.shift()}_onMoveEnd(w){if(this._drainInertiaBuffer(),this._inertiaBuffer.length<2)return;let B={zoom:0,bearing:0,pitch:0,pan:new a.P(0,0),pinchAround:void 0,around:void 0};for(let{settings:le}of this._inertiaBuffer)B.zoom+=le.zoomDelta||0,B.bearing+=le.bearingDelta||0,B.pitch+=le.pitchDelta||0,le.panDelta&&B.pan._add(le.panDelta),le.around&&(B.around=le.around),le.pinchAround&&(B.pinchAround=le.pinchAround);let Q=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,ee={};if(B.pan.mag()){let le=bf(B.pan.mag(),Q,a.e({},Fc,w||{}));ee.offset=B.pan.mult(le.amount/B.pan.mag()),ee.center=this._map.transform.center,Ou(ee,le)}if(B.zoom){let le=bf(B.zoom,Q,wc);ee.zoom=this._map.transform.zoom+le.amount,Ou(ee,le)}if(B.bearing){let le=bf(B.bearing,Q,bd);ee.bearing=this._map.transform.bearing+a.ac(le.amount,-179,179),Ou(ee,le)}if(B.pitch){let le=bf(B.pitch,Q,xf);ee.pitch=this._map.transform.pitch+le.amount,Ou(ee,le)}if(ee.zoom||ee.bearing){let le=B.pinchAround===void 0?B.around:B.pinchAround;ee.around=le?this._map.unproject(le):this._map.getCenter()}return this.clear(),a.e(ee,{noMoveStart:!0})}}function Ou(ue,w){(!ue.duration||ue.duration<w.duration)&&(ue.duration=w.duration,ue.easing=w.easing)}function bf(ue,w,B){let{maxSpeed:Q,linearity:ee,deceleration:le}=B,qe=a.ac(ue*ee/(w/1e3),-Q,Q),Xe=Math.abs(qe)/(le*ee);return{easing:B.easing,duration:1e3*Xe,amount:qe*(Xe/2)}}class jl extends a.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(w,B,Q,ee={}){let le=c.mousePos(B.getCanvas(),Q),qe=B.unproject(le);super(w,a.e({point:le,lngLat:qe,originalEvent:Q},ee)),this._defaultPrevented=!1,this.target=B}}class lf extends a.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(w,B,Q){let ee=w===\"touchend\"?Q.changedTouches:Q.touches,le=c.touchPos(B.getCanvasContainer(),ee),qe=le.map(ot=>B.unproject(ot)),Xe=le.reduce((ot,Tt,Yt,Kt)=>ot.add(Tt.div(Kt.length)),new a.P(0,0));super(w,{points:le,point:Xe,lngLats:qe,lngLat:B.unproject(Xe),originalEvent:Q}),this._defaultPrevented=!1}}class Hh extends a.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(w,B,Q){super(w,{originalEvent:Q}),this._defaultPrevented=!1}}class If{constructor(w,B){this._map=w,this._clickTolerance=B.clickTolerance}reset(){delete this._mousedownPos}wheel(w){return this._firePreventable(new Hh(w.type,this._map,w))}mousedown(w,B){return this._mousedownPos=B,this._firePreventable(new jl(w.type,this._map,w))}mouseup(w){this._map.fire(new jl(w.type,this._map,w))}click(w,B){this._mousedownPos&&this._mousedownPos.dist(B)>=this._clickTolerance||this._map.fire(new jl(w.type,this._map,w))}dblclick(w){return this._firePreventable(new jl(w.type,this._map,w))}mouseover(w){this._map.fire(new jl(w.type,this._map,w))}mouseout(w){this._map.fire(new jl(w.type,this._map,w))}touchstart(w){return this._firePreventable(new lf(w.type,this._map,w))}touchmove(w){this._map.fire(new lf(w.type,this._map,w))}touchend(w){this._map.fire(new lf(w.type,this._map,w))}touchcancel(w){this._map.fire(new lf(w.type,this._map,w))}_firePreventable(w){if(this._map.fire(w),w.defaultPrevented)return{}}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class Cs{constructor(w){this._map=w}reset(){this._delayContextMenu=!1,this._ignoreContextMenu=!0,delete this._contextMenuEvent}mousemove(w){this._map.fire(new jl(w.type,this._map,w))}mousedown(){this._delayContextMenu=!0,this._ignoreContextMenu=!1}mouseup(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new jl(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)}contextmenu(w){this._delayContextMenu?this._contextMenuEvent=w:this._ignoreContextMenu||this._map.fire(new jl(w.type,this._map,w)),this._map.listens(\"contextmenu\")&&w.preventDefault()}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class du{constructor(w){this._map=w}get transform(){return this._map._requestedCameraState||this._map.transform}get center(){return{lng:this.transform.center.lng,lat:this.transform.center.lat}}get zoom(){return this.transform.zoom}get pitch(){return this.transform.pitch}get bearing(){return this.transform.bearing}unproject(w){return this.transform.pointLocation(a.P.convert(w),this._map.terrain)}}class ku{constructor(w,B){this._map=w,this._tr=new du(w),this._el=w.getCanvasContainer(),this._container=w.getContainer(),this._clickTolerance=B.clickTolerance||1}isEnabled(){return!!this._enabled}isActive(){return!!this._active}enable(){this.isEnabled()||(this._enabled=!0)}disable(){this.isEnabled()&&(this._enabled=!1)}mousedown(w,B){this.isEnabled()&&w.shiftKey&&w.button===0&&(c.disableDrag(),this._startPos=this._lastPos=B,this._active=!0)}mousemoveWindow(w,B){if(!this._active)return;let Q=B;if(this._lastPos.equals(Q)||!this._box&&Q.dist(this._startPos)<this._clickTolerance)return;let ee=this._startPos;this._lastPos=Q,this._box||(this._box=c.create(\"div\",\"maplibregl-boxzoom\",this._container),this._container.classList.add(\"maplibregl-crosshair\"),this._fireEvent(\"boxzoomstart\",w));let le=Math.min(ee.x,Q.x),qe=Math.max(ee.x,Q.x),Xe=Math.min(ee.y,Q.y),ot=Math.max(ee.y,Q.y);c.setTransform(this._box,`translate(${le}px,${Xe}px)`),this._box.style.width=qe-le+\"px\",this._box.style.height=ot-Xe+\"px\"}mouseupWindow(w,B){if(!this._active||w.button!==0)return;let Q=this._startPos,ee=B;if(this.reset(),c.suppressClick(),Q.x!==ee.x||Q.y!==ee.y)return this._map.fire(new a.k(\"boxzoomend\",{originalEvent:w})),{cameraAnimation:le=>le.fitScreenCoordinates(Q,ee,this._tr.bearing,{linear:!0})};this._fireEvent(\"boxzoomcancel\",w)}keydown(w){this._active&&w.keyCode===27&&(this.reset(),this._fireEvent(\"boxzoomcancel\",w))}reset(){this._active=!1,this._container.classList.remove(\"maplibregl-crosshair\"),this._box&&(c.remove(this._box),this._box=null),c.enableDrag(),delete this._startPos,delete this._lastPos}_fireEvent(w,B){return this._map.fire(new a.k(w,{originalEvent:B}))}}function Wf(ue,w){if(ue.length!==w.length)throw new Error(`The number of touches and points are not equal - touches ${ue.length}, points ${w.length}`);let B={};for(let Q=0;Q<ue.length;Q++)B[ue[Q].identifier]=w[Q];return B}class Us{constructor(w){this.reset(),this.numTouches=w.numTouches}reset(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1}touchstart(w,B,Q){(this.centroid||Q.length>this.numTouches)&&(this.aborted=!0),this.aborted||(this.startTime===void 0&&(this.startTime=w.timeStamp),Q.length===this.numTouches&&(this.centroid=function(ee){let le=new a.P(0,0);for(let qe of ee)le._add(qe);return le.div(ee.length)}(B),this.touches=Wf(Q,B)))}touchmove(w,B,Q){if(this.aborted||!this.centroid)return;let ee=Wf(Q,B);for(let le in this.touches){let qe=ee[le];(!qe||qe.dist(this.touches[le])>30)&&(this.aborted=!0)}}touchend(w,B,Q){if((!this.centroid||w.timeStamp-this.startTime>500)&&(this.aborted=!0),Q.length===0){let ee=!this.aborted&&this.centroid;if(this.reset(),ee)return ee}}}class wf{constructor(w){this.singleTap=new Us(w),this.numTaps=w.numTaps,this.reset()}reset(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()}touchstart(w,B,Q){this.singleTap.touchstart(w,B,Q)}touchmove(w,B,Q){this.singleTap.touchmove(w,B,Q)}touchend(w,B,Q){let ee=this.singleTap.touchend(w,B,Q);if(ee){let le=w.timeStamp-this.lastTime<500,qe=!this.lastTap||this.lastTap.dist(ee)<30;if(le&&qe||this.reset(),this.count++,this.lastTime=w.timeStamp,this.lastTap=ee,this.count===this.numTaps)return this.reset(),ee}}}class zc{constructor(w){this._tr=new du(w),this._zoomIn=new wf({numTouches:1,numTaps:2}),this._zoomOut=new wf({numTouches:2,numTaps:1}),this.reset()}reset(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()}touchstart(w,B,Q){this._zoomIn.touchstart(w,B,Q),this._zoomOut.touchstart(w,B,Q)}touchmove(w,B,Q){this._zoomIn.touchmove(w,B,Q),this._zoomOut.touchmove(w,B,Q)}touchend(w,B,Q){let ee=this._zoomIn.touchend(w,B,Q),le=this._zoomOut.touchend(w,B,Q),qe=this._tr;return ee?(this._active=!0,w.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:Xe=>Xe.easeTo({duration:300,zoom:qe.zoom+1,around:qe.unproject(ee)},{originalEvent:w})}):le?(this._active=!0,w.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:Xe=>Xe.easeTo({duration:300,zoom:qe.zoom-1,around:qe.unproject(le)},{originalEvent:w})}):void 0}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Wu{constructor(w){this._enabled=!!w.enable,this._moveStateManager=w.moveStateManager,this._clickTolerance=w.clickTolerance||1,this._moveFunction=w.move,this._activateOnStart=!!w.activateOnStart,w.assignEvents(this),this.reset()}reset(w){this._active=!1,this._moved=!1,delete this._lastPoint,this._moveStateManager.endMove(w)}_move(...w){let B=this._moveFunction(...w);if(B.bearingDelta||B.pitchDelta||B.around||B.panDelta)return this._active=!0,B}dragStart(w,B){this.isEnabled()&&!this._lastPoint&&this._moveStateManager.isValidStartEvent(w)&&(this._moveStateManager.startMove(w),this._lastPoint=B.length?B[0]:B,this._activateOnStart&&this._lastPoint&&(this._active=!0))}dragMove(w,B){if(!this.isEnabled())return;let Q=this._lastPoint;if(!Q)return;if(w.preventDefault(),!this._moveStateManager.isValidMoveEvent(w))return void this.reset(w);let ee=B.length?B[0]:B;return!this._moved&&ee.dist(Q)<this._clickTolerance?void 0:(this._moved=!0,this._lastPoint=ee,this._move(Q,ee))}dragEnd(w){this.isEnabled()&&this._lastPoint&&this._moveStateManager.isValidEndEvent(w)&&(this._moved&&c.suppressClick(),this.reset(w))}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}getClickTolerance(){return this._clickTolerance}}let Rf={0:1,2:2};class Xu{constructor(w){this._correctEvent=w.checkCorrectEvent}startMove(w){let B=c.mouseButton(w);this._eventButton=B}endMove(w){delete this._eventButton}isValidStartEvent(w){return this._correctEvent(w)}isValidMoveEvent(w){return!function(B,Q){let ee=Rf[Q];return B.buttons===void 0||(B.buttons&ee)!==ee}(w,this._eventButton)}isValidEndEvent(w){return c.mouseButton(w)===this._eventButton}}class uf{constructor(){this._firstTouch=void 0}_isOneFingerTouch(w){return w.targetTouches.length===1}_isSameTouchEvent(w){return w.targetTouches[0].identifier===this._firstTouch}startMove(w){this._firstTouch=w.targetTouches[0].identifier}endMove(w){delete this._firstTouch}isValidStartEvent(w){return this._isOneFingerTouch(w)}isValidMoveEvent(w){return this._isOneFingerTouch(w)&&this._isSameTouchEvent(w)}isValidEndEvent(w){return this._isOneFingerTouch(w)&&this._isSameTouchEvent(w)}}let Xf=ue=>{ue.mousedown=ue.dragStart,ue.mousemoveWindow=ue.dragMove,ue.mouseup=ue.dragEnd,ue.contextmenu=w=>{w.preventDefault()}},Wl=({enable:ue,clickTolerance:w,bearingDegreesPerPixelMoved:B=.8})=>{let Q=new Xu({checkCorrectEvent:ee=>c.mouseButton(ee)===0&&ee.ctrlKey||c.mouseButton(ee)===2});return new Wu({clickTolerance:w,move:(ee,le)=>({bearingDelta:(le.x-ee.x)*B}),moveStateManager:Q,enable:ue,assignEvents:Xf})},ah=({enable:ue,clickTolerance:w,pitchDegreesPerPixelMoved:B=-.5})=>{let Q=new Xu({checkCorrectEvent:ee=>c.mouseButton(ee)===0&&ee.ctrlKey||c.mouseButton(ee)===2});return new Wu({clickTolerance:w,move:(ee,le)=>({pitchDelta:(le.y-ee.y)*B}),moveStateManager:Q,enable:ue,assignEvents:Xf})};class Zu{constructor(w,B){this._clickTolerance=w.clickTolerance||1,this._map=B,this.reset()}reset(){this._active=!1,this._touches={},this._sum=new a.P(0,0)}_shouldBePrevented(w){return w<(this._map.cooperativeGestures.isEnabled()?2:1)}touchstart(w,B,Q){return this._calculateTransform(w,B,Q)}touchmove(w,B,Q){if(this._active){if(!this._shouldBePrevented(Q.length))return w.preventDefault(),this._calculateTransform(w,B,Q);this._map.cooperativeGestures.notifyGestureBlocked(\"touch_pan\",w)}}touchend(w,B,Q){this._calculateTransform(w,B,Q),this._active&&this._shouldBePrevented(Q.length)&&this.reset()}touchcancel(){this.reset()}_calculateTransform(w,B,Q){Q.length>0&&(this._active=!0);let ee=Wf(Q,B),le=new a.P(0,0),qe=new a.P(0,0),Xe=0;for(let Tt in ee){let Yt=ee[Tt],Kt=this._touches[Tt];Kt&&(le._add(Yt),qe._add(Yt.sub(Kt)),Xe++,ee[Tt]=Yt)}if(this._touches=ee,this._shouldBePrevented(Xe)||!qe.mag())return;let ot=qe.div(Xe);return this._sum._add(ot),this._sum.mag()<this._clickTolerance?void 0:{around:le.div(Xe),panDelta:ot}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Oc{constructor(){this.reset()}reset(){this._active=!1,delete this._firstTwoTouches}touchstart(w,B,Q){this._firstTwoTouches||Q.length<2||(this._firstTwoTouches=[Q[0].identifier,Q[1].identifier],this._start([B[0],B[1]]))}touchmove(w,B,Q){if(!this._firstTwoTouches)return;w.preventDefault();let[ee,le]=this._firstTwoTouches,qe=Tc(Q,B,ee),Xe=Tc(Q,B,le);if(!qe||!Xe)return;let ot=this._aroundCenter?null:qe.add(Xe).div(2);return this._move([qe,Xe],ot,w)}touchend(w,B,Q){if(!this._firstTwoTouches)return;let[ee,le]=this._firstTwoTouches,qe=Tc(Q,B,ee),Xe=Tc(Q,B,le);qe&&Xe||(this._active&&c.suppressClick(),this.reset())}touchcancel(){this.reset()}enable(w){this._enabled=!0,this._aroundCenter=!!w&&w.around===\"center\"}disable(){this._enabled=!1,this.reset()}isEnabled(){return!!this._enabled}isActive(){return!!this._active}}function Tc(ue,w,B){for(let Q=0;Q<ue.length;Q++)if(ue[Q].identifier===B)return w[Q]}function wl(ue,w){return Math.log(ue/w)/Math.LN2}class vu extends Oc{reset(){super.reset(),delete this._distance,delete this._startDistance}_start(w){this._startDistance=this._distance=w[0].dist(w[1])}_move(w,B){let Q=this._distance;if(this._distance=w[0].dist(w[1]),this._active||!(Math.abs(wl(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:wl(this._distance,Q),pinchAround:B}}}function qc(ue,w){return 180*ue.angleWith(w)/Math.PI}class cf extends Oc{reset(){super.reset(),delete this._minDiameter,delete this._startVector,delete this._vector}_start(w){this._startVector=this._vector=w[0].sub(w[1]),this._minDiameter=w[0].dist(w[1])}_move(w,B,Q){let ee=this._vector;if(this._vector=w[0].sub(w[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:qc(this._vector,ee),pinchAround:B}}_isBelowThreshold(w){this._minDiameter=Math.min(this._minDiameter,w.mag());let B=25/(Math.PI*this._minDiameter)*360,Q=qc(w,this._startVector);return Math.abs(Q)<B}}function fc(ue){return Math.abs(ue.y)>Math.abs(ue.x)}class Bc extends Oc{constructor(w){super(),this._currentTouchCount=0,this._map=w}reset(){super.reset(),this._valid=void 0,delete this._firstMove,delete this._lastPoints}touchstart(w,B,Q){super.touchstart(w,B,Q),this._currentTouchCount=Q.length}_start(w){this._lastPoints=w,fc(w[0].sub(w[1]))&&(this._valid=!1)}_move(w,B,Q){if(this._map.cooperativeGestures.isEnabled()&&this._currentTouchCount<3)return;let ee=w[0].sub(this._lastPoints[0]),le=w[1].sub(this._lastPoints[1]);return this._valid=this.gestureBeginsVertically(ee,le,Q.timeStamp),this._valid?(this._lastPoints=w,this._active=!0,{pitchDelta:(ee.y+le.y)/2*-.5}):void 0}gestureBeginsVertically(w,B,Q){if(this._valid!==void 0)return this._valid;let ee=w.mag()>=2,le=B.mag()>=2;if(!ee&&!le)return;if(!ee||!le)return this._firstMove===void 0&&(this._firstMove=Q),Q-this._firstMove<100&&void 0;let qe=w.y>0==B.y>0;return fc(w)&&fc(B)&&qe}}let At={panStep:100,bearingStep:15,pitchStep:10};class Wt{constructor(w){this._tr=new du(w);let B=At;this._panStep=B.panStep,this._bearingStep=B.bearingStep,this._pitchStep=B.pitchStep,this._rotationDisabled=!1}reset(){this._active=!1}keydown(w){if(w.altKey||w.ctrlKey||w.metaKey)return;let B=0,Q=0,ee=0,le=0,qe=0;switch(w.keyCode){case 61:case 107:case 171:case 187:B=1;break;case 189:case 109:case 173:B=-1;break;case 37:w.shiftKey?Q=-1:(w.preventDefault(),le=-1);break;case 39:w.shiftKey?Q=1:(w.preventDefault(),le=1);break;case 38:w.shiftKey?ee=1:(w.preventDefault(),qe=-1);break;case 40:w.shiftKey?ee=-1:(w.preventDefault(),qe=1);break;default:return}return this._rotationDisabled&&(Q=0,ee=0),{cameraAnimation:Xe=>{let ot=this._tr;Xe.easeTo({duration:300,easeId:\"keyboardHandler\",easing:Cr,zoom:B?Math.round(ot.zoom)+B*(w.shiftKey?2:1):ot.zoom,bearing:ot.bearing+Q*this._bearingStep,pitch:ot.pitch+ee*this._pitchStep,offset:[-le*this._panStep,-qe*this._panStep],center:ot.center},{originalEvent:w})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}disableRotation(){this._rotationDisabled=!0}enableRotation(){this._rotationDisabled=!1}}function Cr(ue){return ue*(2-ue)}let Ar=4.000244140625;class Kr{constructor(w,B){this._onTimeout=Q=>{this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(Q)},this._map=w,this._tr=new du(w),this._triggerRenderFrame=B,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222}setZoomRate(w){this._defaultZoomRate=w}setWheelZoomRate(w){this._wheelZoomRate=w}isEnabled(){return!!this._enabled}isActive(){return!!this._active||this._finishTimeout!==void 0}isZooming(){return!!this._zooming}enable(w){this.isEnabled()||(this._enabled=!0,this._aroundCenter=!!w&&w.around===\"center\")}disable(){this.isEnabled()&&(this._enabled=!1)}_shouldBePrevented(w){return!!this._map.cooperativeGestures.isEnabled()&&!(w.ctrlKey||this._map.cooperativeGestures.isBypassed(w))}wheel(w){if(!this.isEnabled())return;if(this._shouldBePrevented(w))return void this._map.cooperativeGestures.notifyGestureBlocked(\"wheel_zoom\",w);let B=w.deltaMode===WheelEvent.DOM_DELTA_LINE?40*w.deltaY:w.deltaY,Q=u.now(),ee=Q-(this._lastWheelEventTime||0);this._lastWheelEventTime=Q,B!==0&&B%Ar==0?this._type=\"wheel\":B!==0&&Math.abs(B)<4?this._type=\"trackpad\":ee>400?(this._type=null,this._lastValue=B,this._timeout=setTimeout(this._onTimeout,40,w)):this._type||(this._type=Math.abs(ee*B)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,B+=this._lastValue)),w.shiftKey&&B&&(B/=4),this._type&&(this._lastWheelEvent=w,this._delta-=B,this._active||this._start(w)),w.preventDefault()}_start(w){if(!this._delta)return;this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);let B=c.mousePos(this._map.getCanvas(),w),Q=this._tr;this._around=B.y>Q.transform.height/2-Q.transform.getHorizon()?a.N.convert(this._aroundCenter?Q.center:Q.unproject(B)):a.N.convert(Q.center),this._aroundPoint=Q.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._triggerRenderFrame())}renderFrame(){if(!this._frameId||(this._frameId=null,!this.isActive()))return;let w=this._tr.transform;if(this._delta!==0){let ot=this._type===\"wheel\"&&Math.abs(this._delta)>Ar?this._wheelZoomRate:this._defaultZoomRate,Tt=2/(1+Math.exp(-Math.abs(this._delta*ot)));this._delta<0&&Tt!==0&&(Tt=1/Tt);let Yt=typeof this._targetZoom==\"number\"?w.zoomScale(this._targetZoom):w.scale;this._targetZoom=Math.min(w.maxZoom,Math.max(w.minZoom,w.scaleZoom(Yt*Tt))),this._type===\"wheel\"&&(this._startZoom=w.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}let B=typeof this._targetZoom==\"number\"?this._targetZoom:w.zoom,Q=this._startZoom,ee=this._easing,le,qe=!1,Xe=u.now()-this._lastWheelEventTime;if(this._type===\"wheel\"&&Q&&ee&&Xe){let ot=Math.min(Xe/200,1),Tt=ee(ot);le=a.y.number(Q,B,Tt),ot<1?this._frameId||(this._frameId=!0):qe=!0}else le=B,qe=!0;return this._active=!0,qe&&(this._active=!1,this._finishTimeout=setTimeout(()=>{this._zooming=!1,this._triggerRenderFrame(),delete this._targetZoom,delete this._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!qe,zoomDelta:le-w.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}_smoothOutEasing(w){let B=a.b9;if(this._prevEase){let Q=this._prevEase,ee=(u.now()-Q.start)/Q.duration,le=Q.easing(ee+.01)-Q.easing(ee),qe=.27/Math.sqrt(le*le+1e-4)*.01,Xe=Math.sqrt(.0729-qe*qe);B=a.b8(qe,Xe,.25,1)}return this._prevEase={start:u.now(),duration:w,easing:B},B}reset(){this._active=!1,this._zooming=!1,delete this._targetZoom,this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout)}}class ki{constructor(w,B){this._clickZoom=w,this._tapZoom=B}enable(){this._clickZoom.enable(),this._tapZoom.enable()}disable(){this._clickZoom.disable(),this._tapZoom.disable()}isEnabled(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()}isActive(){return this._clickZoom.isActive()||this._tapZoom.isActive()}}class Xi{constructor(w){this._tr=new du(w),this.reset()}reset(){this._active=!1}dblclick(w,B){return w.preventDefault(),{cameraAnimation:Q=>{Q.easeTo({duration:300,zoom:this._tr.zoom+(w.shiftKey?-1:1),around:this._tr.unproject(B)},{originalEvent:w})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class dn{constructor(){this._tap=new wf({numTouches:1,numTaps:1}),this.reset()}reset(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,delete this._tapPoint,this._tap.reset()}touchstart(w,B,Q){if(!this._swipePoint)if(this._tapTime){let ee=B[0],le=w.timeStamp-this._tapTime<500,qe=this._tapPoint.dist(ee)<30;le&&qe?Q.length>0&&(this._swipePoint=ee,this._swipeTouch=Q[0].identifier):this.reset()}else this._tap.touchstart(w,B,Q)}touchmove(w,B,Q){if(this._tapTime){if(this._swipePoint){if(Q[0].identifier!==this._swipeTouch)return;let ee=B[0],le=ee.y-this._swipePoint.y;return this._swipePoint=ee,w.preventDefault(),this._active=!0,{zoomDelta:le/128}}}else this._tap.touchmove(w,B,Q)}touchend(w,B,Q){if(this._tapTime)this._swipePoint&&Q.length===0&&this.reset();else{let ee=this._tap.touchend(w,B,Q);ee&&(this._tapTime=w.timeStamp,this._tapPoint=ee)}}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class wn{constructor(w,B,Q){this._el=w,this._mousePan=B,this._touchPan=Q}enable(w){this._inertiaOptions=w||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"maplibregl-touch-drag-pan\")}disable(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"maplibregl-touch-drag-pan\")}isEnabled(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()}isActive(){return this._mousePan.isActive()||this._touchPan.isActive()}}class Nn{constructor(w,B,Q){this._pitchWithRotate=w.pitchWithRotate,this._mouseRotate=B,this._mousePitch=Q}enable(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()}disable(){this._mouseRotate.disable(),this._mousePitch.disable()}isEnabled(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())}isActive(){return this._mouseRotate.isActive()||this._mousePitch.isActive()}}class Yi{constructor(w,B,Q,ee){this._el=w,this._touchZoom=B,this._touchRotate=Q,this._tapDragZoom=ee,this._rotationDisabled=!1,this._enabled=!0}enable(w){this._touchZoom.enable(w),this._rotationDisabled||this._touchRotate.enable(w),this._tapDragZoom.enable(),this._el.classList.add(\"maplibregl-touch-zoom-rotate\")}disable(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"maplibregl-touch-zoom-rotate\")}isEnabled(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()}isActive(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()}disableRotation(){this._rotationDisabled=!0,this._touchRotate.disable()}enableRotation(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()}}class Qi{constructor(w,B){this._bypassKey=navigator.userAgent.indexOf(\"Mac\")!==-1?\"metaKey\":\"ctrlKey\",this._map=w,this._options=B,this._enabled=!1}isActive(){return!1}reset(){}_setupUI(){if(this._container)return;let w=this._map.getCanvasContainer();w.classList.add(\"maplibregl-cooperative-gestures\"),this._container=c.create(\"div\",\"maplibregl-cooperative-gesture-screen\",w);let B=this._map._getUIString(\"CooperativeGesturesHandler.WindowsHelpText\");this._bypassKey===\"metaKey\"&&(B=this._map._getUIString(\"CooperativeGesturesHandler.MacHelpText\"));let Q=this._map._getUIString(\"CooperativeGesturesHandler.MobileHelpText\"),ee=document.createElement(\"div\");ee.className=\"maplibregl-desktop-message\",ee.textContent=B,this._container.appendChild(ee);let le=document.createElement(\"div\");le.className=\"maplibregl-mobile-message\",le.textContent=Q,this._container.appendChild(le),this._container.setAttribute(\"aria-hidden\",\"true\")}_destroyUI(){this._container&&(c.remove(this._container),this._map.getCanvasContainer().classList.remove(\"maplibregl-cooperative-gestures\")),delete this._container}enable(){this._setupUI(),this._enabled=!0}disable(){this._enabled=!1,this._destroyUI()}isEnabled(){return this._enabled}isBypassed(w){return w[this._bypassKey]}notifyGestureBlocked(w,B){this._enabled&&(this._map.fire(new a.k(\"cooperativegestureprevented\",{gestureType:w,originalEvent:B})),this._container.classList.add(\"maplibregl-show\"),setTimeout(()=>{this._container.classList.remove(\"maplibregl-show\")},100))}}let on=ue=>ue.zoom||ue.drag||ue.pitch||ue.rotate;class Fi extends a.k{}function $n(ue){return ue.panDelta&&ue.panDelta.mag()||ue.zoomDelta||ue.bearingDelta||ue.pitchDelta}class Ca{constructor(w,B){this.handleWindowEvent=ee=>{this.handleEvent(ee,`${ee.type}Window`)},this.handleEvent=(ee,le)=>{if(ee.type===\"blur\")return void this.stop(!0);this._updatingCamera=!0;let qe=ee.type===\"renderFrame\"?void 0:ee,Xe={needsRenderFrame:!1},ot={},Tt={},Yt=ee.touches,Kt=Yt?this._getMapTouches(Yt):void 0,xr=Kt?c.touchPos(this._map.getCanvas(),Kt):c.mousePos(this._map.getCanvas(),ee);for(let{handlerName:be,handler:De,allowed:Be}of this._handlers){if(!De.isEnabled())continue;let et;this._blockedByActive(Tt,Be,be)?De.reset():De[le||ee.type]&&(et=De[le||ee.type](ee,xr,Kt),this.mergeHandlerResult(Xe,ot,et,be,qe),et&&et.needsRenderFrame&&this._triggerRenderFrame()),(et||De.isActive())&&(Tt[be]=De)}let Ir={};for(let be in this._previousActiveHandlers)Tt[be]||(Ir[be]=qe);this._previousActiveHandlers=Tt,(Object.keys(Ir).length||$n(Xe))&&(this._changes.push([Xe,ot,Ir]),this._triggerRenderFrame()),(Object.keys(Tt).length||$n(Xe))&&this._map._stop(!0),this._updatingCamera=!1;let{cameraAnimation:ve}=Xe;ve&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],ve(this._map))},this._map=w,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Pf(w),this._bearingSnap=B.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(B);let Q=this._el;this._listeners=[[Q,\"touchstart\",{passive:!0}],[Q,\"touchmove\",{passive:!1}],[Q,\"touchend\",void 0],[Q,\"touchcancel\",void 0],[Q,\"mousedown\",void 0],[Q,\"mousemove\",void 0],[Q,\"mouseup\",void 0],[document,\"mousemove\",{capture:!0}],[document,\"mouseup\",void 0],[Q,\"mouseover\",void 0],[Q,\"mouseout\",void 0],[Q,\"dblclick\",void 0],[Q,\"click\",void 0],[Q,\"keydown\",{capture:!1}],[Q,\"keyup\",void 0],[Q,\"wheel\",{passive:!1}],[Q,\"contextmenu\",void 0],[window,\"blur\",void 0]];for(let[ee,le,qe]of this._listeners)c.addEventListener(ee,le,ee===document?this.handleWindowEvent:this.handleEvent,qe)}destroy(){for(let[w,B,Q]of this._listeners)c.removeEventListener(w,B,w===document?this.handleWindowEvent:this.handleEvent,Q)}_addDefaultHandlers(w){let B=this._map,Q=B.getCanvasContainer();this._add(\"mapEvent\",new If(B,w));let ee=B.boxZoom=new ku(B,w);this._add(\"boxZoom\",ee),w.interactive&&w.boxZoom&&ee.enable();let le=B.cooperativeGestures=new Qi(B,w.cooperativeGestures);this._add(\"cooperativeGestures\",le),w.cooperativeGestures&&le.enable();let qe=new zc(B),Xe=new Xi(B);B.doubleClickZoom=new ki(Xe,qe),this._add(\"tapZoom\",qe),this._add(\"clickZoom\",Xe),w.interactive&&w.doubleClickZoom&&B.doubleClickZoom.enable();let ot=new dn;this._add(\"tapDragZoom\",ot);let Tt=B.touchPitch=new Bc(B);this._add(\"touchPitch\",Tt),w.interactive&&w.touchPitch&&B.touchPitch.enable(w.touchPitch);let Yt=Wl(w),Kt=ah(w);B.dragRotate=new Nn(w,Yt,Kt),this._add(\"mouseRotate\",Yt,[\"mousePitch\"]),this._add(\"mousePitch\",Kt,[\"mouseRotate\"]),w.interactive&&w.dragRotate&&B.dragRotate.enable();let xr=(({enable:et,clickTolerance:We})=>{let it=new Xu({checkCorrectEvent:Ft=>c.mouseButton(Ft)===0&&!Ft.ctrlKey});return new Wu({clickTolerance:We,move:(Ft,Ht)=>({around:Ht,panDelta:Ht.sub(Ft)}),activateOnStart:!0,moveStateManager:it,enable:et,assignEvents:Xf})})(w),Ir=new Zu(w,B);B.dragPan=new wn(Q,xr,Ir),this._add(\"mousePan\",xr),this._add(\"touchPan\",Ir,[\"touchZoom\",\"touchRotate\"]),w.interactive&&w.dragPan&&B.dragPan.enable(w.dragPan);let ve=new cf,be=new vu;B.touchZoomRotate=new Yi(Q,be,ve,ot),this._add(\"touchRotate\",ve,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",be,[\"touchPan\",\"touchRotate\"]),w.interactive&&w.touchZoomRotate&&B.touchZoomRotate.enable(w.touchZoomRotate);let De=B.scrollZoom=new Kr(B,()=>this._triggerRenderFrame());this._add(\"scrollZoom\",De,[\"mousePan\"]),w.interactive&&w.scrollZoom&&B.scrollZoom.enable(w.scrollZoom);let Be=B.keyboard=new Wt(B);this._add(\"keyboard\",Be),w.interactive&&w.keyboard&&B.keyboard.enable(),this._add(\"blockableMapEvent\",new Cs(B))}_add(w,B,Q){this._handlers.push({handlerName:w,handler:B,allowed:Q}),this._handlersById[w]=B}stop(w){if(!this._updatingCamera){for(let{handler:B}of this._handlers)B.reset();this._inertia.clear(),this._fireEvents({},{},w),this._changes=[]}}isActive(){for(let{handler:w}of this._handlers)if(w.isActive())return!0;return!1}isZooming(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()}isRotating(){return!!this._eventsInProgress.rotate}isMoving(){return!!on(this._eventsInProgress)||this.isZooming()}_blockedByActive(w,B,Q){for(let ee in w)if(ee!==Q&&(!B||B.indexOf(ee)<0))return!0;return!1}_getMapTouches(w){let B=[];for(let Q of w)this._el.contains(Q.target)&&B.push(Q);return B}mergeHandlerResult(w,B,Q,ee,le){if(!Q)return;a.e(w,Q);let qe={handlerName:ee,originalEvent:Q.originalEvent||le};Q.zoomDelta!==void 0&&(B.zoom=qe),Q.panDelta!==void 0&&(B.drag=qe),Q.pitchDelta!==void 0&&(B.pitch=qe),Q.bearingDelta!==void 0&&(B.rotate=qe)}_applyChanges(){let w={},B={},Q={};for(let[ee,le,qe]of this._changes)ee.panDelta&&(w.panDelta=(w.panDelta||new a.P(0,0))._add(ee.panDelta)),ee.zoomDelta&&(w.zoomDelta=(w.zoomDelta||0)+ee.zoomDelta),ee.bearingDelta&&(w.bearingDelta=(w.bearingDelta||0)+ee.bearingDelta),ee.pitchDelta&&(w.pitchDelta=(w.pitchDelta||0)+ee.pitchDelta),ee.around!==void 0&&(w.around=ee.around),ee.pinchAround!==void 0&&(w.pinchAround=ee.pinchAround),ee.noInertia&&(w.noInertia=ee.noInertia),a.e(B,le),a.e(Q,qe);this._updateMapTransform(w,B,Q),this._changes=[]}_updateMapTransform(w,B,Q){let ee=this._map,le=ee._getTransformForUpdate(),qe=ee.terrain;if(!($n(w)||qe&&this._terrainMovement))return this._fireEvents(B,Q,!0);let{panDelta:Xe,zoomDelta:ot,bearingDelta:Tt,pitchDelta:Yt,around:Kt,pinchAround:xr}=w;xr!==void 0&&(Kt=xr),ee._stop(!0),Kt=Kt||ee.transform.centerPoint;let Ir=le.pointLocation(Xe?Kt.sub(Xe):Kt);Tt&&(le.bearing+=Tt),Yt&&(le.pitch+=Yt),ot&&(le.zoom+=ot),qe?this._terrainMovement||!B.drag&&!B.zoom?B.drag&&this._terrainMovement?le.center=le.pointLocation(le.centerPoint.sub(Xe)):le.setLocationAtPoint(Ir,Kt):(this._terrainMovement=!0,this._map._elevationFreeze=!0,le.setLocationAtPoint(Ir,Kt)):le.setLocationAtPoint(Ir,Kt),ee._applyUpdatedTransform(le),this._map._update(),w.noInertia||this._inertia.record(w),this._fireEvents(B,Q,!0)}_fireEvents(w,B,Q){let ee=on(this._eventsInProgress),le=on(w),qe={};for(let Kt in w){let{originalEvent:xr}=w[Kt];this._eventsInProgress[Kt]||(qe[`${Kt}start`]=xr),this._eventsInProgress[Kt]=w[Kt]}!ee&&le&&this._fireEvent(\"movestart\",le.originalEvent);for(let Kt in qe)this._fireEvent(Kt,qe[Kt]);le&&this._fireEvent(\"move\",le.originalEvent);for(let Kt in w){let{originalEvent:xr}=w[Kt];this._fireEvent(Kt,xr)}let Xe={},ot;for(let Kt in this._eventsInProgress){let{handlerName:xr,originalEvent:Ir}=this._eventsInProgress[Kt];this._handlersById[xr].isActive()||(delete this._eventsInProgress[Kt],ot=B[xr]||Ir,Xe[`${Kt}end`]=ot)}for(let Kt in Xe)this._fireEvent(Kt,Xe[Kt]);let Tt=on(this._eventsInProgress),Yt=(ee||le)&&!Tt;if(Yt&&this._terrainMovement){this._map._elevationFreeze=!1,this._terrainMovement=!1;let Kt=this._map._getTransformForUpdate();Kt.recalculateZoom(this._map.terrain),this._map._applyUpdatedTransform(Kt)}if(Q&&Yt){this._updatingCamera=!0;let Kt=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),xr=Ir=>Ir!==0&&-this._bearingSnap<Ir&&Ir<this._bearingSnap;!Kt||!Kt.essential&&u.prefersReducedMotion?(this._map.fire(new a.k(\"moveend\",{originalEvent:ot})),xr(this._map.getBearing())&&this._map.resetNorth()):(xr(Kt.bearing||this._map.getBearing())&&(Kt.bearing=0),Kt.freezeElevation=!0,this._map.easeTo(Kt,{originalEvent:ot})),this._updatingCamera=!1}}_fireEvent(w,B){this._map.fire(new a.k(w,B?{originalEvent:B}:{}))}_requestFrame(){return this._map.triggerRepaint(),this._map._renderTaskQueue.add(w=>{delete this._frameId,this.handleEvent(new Fi(\"renderFrame\",{timeStamp:w})),this._applyChanges()})}_triggerRenderFrame(){this._frameId===void 0&&(this._frameId=this._requestFrame())}}class Ra extends a.E{constructor(w,B){super(),this._renderFrameCallback=()=>{let Q=Math.min((u.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(Q)),Q<1&&this._easeFrameId?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},this._moving=!1,this._zooming=!1,this.transform=w,this._bearingSnap=B.bearingSnap,this.on(\"moveend\",()=>{delete this._requestedCameraState})}getCenter(){return new a.N(this.transform.center.lng,this.transform.center.lat)}setCenter(w,B){return this.jumpTo({center:w},B)}panBy(w,B,Q){return w=a.P.convert(w).mult(-1),this.panTo(this.transform.center,a.e({offset:w},B),Q)}panTo(w,B,Q){return this.easeTo(a.e({center:w},B),Q)}getZoom(){return this.transform.zoom}setZoom(w,B){return this.jumpTo({zoom:w},B),this}zoomTo(w,B,Q){return this.easeTo(a.e({zoom:w},B),Q)}zoomIn(w,B){return this.zoomTo(this.getZoom()+1,w,B),this}zoomOut(w,B){return this.zoomTo(this.getZoom()-1,w,B),this}getBearing(){return this.transform.bearing}setBearing(w,B){return this.jumpTo({bearing:w},B),this}getPadding(){return this.transform.padding}setPadding(w,B){return this.jumpTo({padding:w},B),this}rotateTo(w,B,Q){return this.easeTo(a.e({bearing:w},B),Q)}resetNorth(w,B){return this.rotateTo(0,a.e({duration:1e3},w),B),this}resetNorthPitch(w,B){return this.easeTo(a.e({bearing:0,pitch:0,duration:1e3},w),B),this}snapToNorth(w,B){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(w,B):this}getPitch(){return this.transform.pitch}setPitch(w,B){return this.jumpTo({pitch:w},B),this}cameraForBounds(w,B){w=ce.convert(w).adjustAntiMeridian();let Q=B&&B.bearing||0;return this._cameraForBoxAndBearing(w.getNorthWest(),w.getSouthEast(),Q,B)}_cameraForBoxAndBearing(w,B,Q,ee){let le={top:0,bottom:0,right:0,left:0};if(typeof(ee=a.e({padding:le,offset:[0,0],maxZoom:this.transform.maxZoom},ee)).padding==\"number\"){let Wr=ee.padding;ee.padding={top:Wr,bottom:Wr,right:Wr,left:Wr}}ee.padding=a.e(le,ee.padding);let qe=this.transform,Xe=qe.padding,ot=new ce(w,B),Tt=qe.project(ot.getNorthWest()),Yt=qe.project(ot.getNorthEast()),Kt=qe.project(ot.getSouthEast()),xr=qe.project(ot.getSouthWest()),Ir=a.ba(-Q),ve=Tt.rotate(Ir),be=Yt.rotate(Ir),De=Kt.rotate(Ir),Be=xr.rotate(Ir),et=new a.P(Math.max(ve.x,be.x,Be.x,De.x),Math.max(ve.y,be.y,Be.y,De.y)),We=new a.P(Math.min(ve.x,be.x,Be.x,De.x),Math.min(ve.y,be.y,Be.y,De.y)),it=et.sub(We),Ft=(qe.width-(Xe.left+Xe.right+ee.padding.left+ee.padding.right))/it.x,Ht=(qe.height-(Xe.top+Xe.bottom+ee.padding.top+ee.padding.bottom))/it.y;if(Ht<0||Ft<0)return void a.w(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\");let tr=Math.min(qe.scaleZoom(qe.scale*Math.min(Ft,Ht)),ee.maxZoom),dr=a.P.convert(ee.offset),Sr=new a.P((ee.padding.left-ee.padding.right)/2,(ee.padding.top-ee.padding.bottom)/2).rotate(a.ba(Q)),Or=dr.add(Sr).mult(qe.scale/qe.zoomScale(tr));return{center:qe.unproject(Tt.add(Kt).div(2).sub(Or)),zoom:tr,bearing:Q}}fitBounds(w,B,Q){return this._fitInternal(this.cameraForBounds(w,B),B,Q)}fitScreenCoordinates(w,B,Q,ee,le){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(a.P.convert(w)),this.transform.pointLocation(a.P.convert(B)),Q,ee),ee,le)}_fitInternal(w,B,Q){return w?(delete(B=a.e(w,B)).padding,B.linear?this.easeTo(B,Q):this.flyTo(B,Q)):this}jumpTo(w,B){this.stop();let Q=this._getTransformForUpdate(),ee=!1,le=!1,qe=!1;return\"zoom\"in w&&Q.zoom!==+w.zoom&&(ee=!0,Q.zoom=+w.zoom),w.center!==void 0&&(Q.center=a.N.convert(w.center)),\"bearing\"in w&&Q.bearing!==+w.bearing&&(le=!0,Q.bearing=+w.bearing),\"pitch\"in w&&Q.pitch!==+w.pitch&&(qe=!0,Q.pitch=+w.pitch),w.padding==null||Q.isPaddingEqual(w.padding)||(Q.padding=w.padding),this._applyUpdatedTransform(Q),this.fire(new a.k(\"movestart\",B)).fire(new a.k(\"move\",B)),ee&&this.fire(new a.k(\"zoomstart\",B)).fire(new a.k(\"zoom\",B)).fire(new a.k(\"zoomend\",B)),le&&this.fire(new a.k(\"rotatestart\",B)).fire(new a.k(\"rotate\",B)).fire(new a.k(\"rotateend\",B)),qe&&this.fire(new a.k(\"pitchstart\",B)).fire(new a.k(\"pitch\",B)).fire(new a.k(\"pitchend\",B)),this.fire(new a.k(\"moveend\",B))}calculateCameraOptionsFromTo(w,B,Q,ee=0){let le=a.Z.fromLngLat(w,B),qe=a.Z.fromLngLat(Q,ee),Xe=qe.x-le.x,ot=qe.y-le.y,Tt=qe.z-le.z,Yt=Math.hypot(Xe,ot,Tt);if(Yt===0)throw new Error(\"Can't calculate camera options with same From and To\");let Kt=Math.hypot(Xe,ot),xr=this.transform.scaleZoom(this.transform.cameraToCenterDistance/Yt/this.transform.tileSize),Ir=180*Math.atan2(Xe,-ot)/Math.PI,ve=180*Math.acos(Kt/Yt)/Math.PI;return ve=Tt<0?90-ve:90+ve,{center:qe.toLngLat(),zoom:xr,pitch:ve,bearing:Ir}}easeTo(w,B){var Q;this._stop(!1,w.easeId),((w=a.e({offset:[0,0],duration:500,easing:a.b9},w)).animate===!1||!w.essential&&u.prefersReducedMotion)&&(w.duration=0);let ee=this._getTransformForUpdate(),le=ee.zoom,qe=ee.bearing,Xe=ee.pitch,ot=ee.padding,Tt=\"bearing\"in w?this._normalizeBearing(w.bearing,qe):qe,Yt=\"pitch\"in w?+w.pitch:Xe,Kt=\"padding\"in w?w.padding:ee.padding,xr=a.P.convert(w.offset),Ir=ee.centerPoint.add(xr),ve=ee.pointLocation(Ir),{center:be,zoom:De}=ee.getConstrained(a.N.convert(w.center||ve),(Q=w.zoom)!==null&&Q!==void 0?Q:le);this._normalizeCenter(be,ee);let Be=ee.project(ve),et=ee.project(be).sub(Be),We=ee.zoomScale(De-le),it,Ft;w.around&&(it=a.N.convert(w.around),Ft=ee.locationPoint(it));let Ht={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||De!==le,this._rotating=this._rotating||qe!==Tt,this._pitching=this._pitching||Yt!==Xe,this._padding=!ee.isPaddingEqual(Kt),this._easeId=w.easeId,this._prepareEase(B,w.noMoveStart,Ht),this.terrain&&this._prepareElevation(be),this._ease(tr=>{if(this._zooming&&(ee.zoom=a.y.number(le,De,tr)),this._rotating&&(ee.bearing=a.y.number(qe,Tt,tr)),this._pitching&&(ee.pitch=a.y.number(Xe,Yt,tr)),this._padding&&(ee.interpolatePadding(ot,Kt,tr),Ir=ee.centerPoint.add(xr)),this.terrain&&!w.freezeElevation&&this._updateElevation(tr),it)ee.setLocationAtPoint(it,Ft);else{let dr=ee.zoomScale(ee.zoom-le),Sr=De>le?Math.min(2,We):Math.max(.5,We),Or=Math.pow(Sr,1-tr),Wr=ee.unproject(Be.add(et.mult(tr*Or)).mult(dr));ee.setLocationAtPoint(ee.renderWorldCopies?Wr.wrap():Wr,Ir)}this._applyUpdatedTransform(ee),this._fireMoveEvents(B)},tr=>{this.terrain&&w.freezeElevation&&this._finalizeElevation(),this._afterEase(B,tr)},w),this}_prepareEase(w,B,Q={}){this._moving=!0,B||Q.moving||this.fire(new a.k(\"movestart\",w)),this._zooming&&!Q.zooming&&this.fire(new a.k(\"zoomstart\",w)),this._rotating&&!Q.rotating&&this.fire(new a.k(\"rotatestart\",w)),this._pitching&&!Q.pitching&&this.fire(new a.k(\"pitchstart\",w))}_prepareElevation(w){this._elevationCenter=w,this._elevationStart=this.transform.elevation,this._elevationTarget=this.terrain.getElevationForLngLatZoom(w,this.transform.tileZoom),this._elevationFreeze=!0}_updateElevation(w){this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);let B=this.terrain.getElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);if(w<1&&B!==this._elevationTarget){let Q=this._elevationTarget-this._elevationStart;this._elevationStart+=w*(Q-(B-(Q*w+this._elevationStart))/(1-w)),this._elevationTarget=B}this.transform.elevation=a.y.number(this._elevationStart,this._elevationTarget,w)}_finalizeElevation(){this._elevationFreeze=!1,this.transform.recalculateZoom(this.terrain)}_getTransformForUpdate(){return this.transformCameraUpdate||this.terrain?(this._requestedCameraState||(this._requestedCameraState=this.transform.clone()),this._requestedCameraState):this.transform}_elevateCameraIfInsideTerrain(w){let B=w.getCameraPosition(),Q=this.terrain.getElevationForLngLatZoom(B.lngLat,w.zoom);if(B.altitude<Q){let ee=this.calculateCameraOptionsFromTo(B.lngLat,Q,w.center,w.elevation);return{pitch:ee.pitch,zoom:ee.zoom}}return{}}_applyUpdatedTransform(w){let B=[];if(this.terrain&&B.push(ee=>this._elevateCameraIfInsideTerrain(ee)),this.transformCameraUpdate&&B.push(ee=>this.transformCameraUpdate(ee)),!B.length)return;let Q=w.clone();for(let ee of B){let le=Q.clone(),{center:qe,zoom:Xe,pitch:ot,bearing:Tt,elevation:Yt}=ee(le);qe&&(le.center=qe),Xe!==void 0&&(le.zoom=Xe),ot!==void 0&&(le.pitch=ot),Tt!==void 0&&(le.bearing=Tt),Yt!==void 0&&(le.elevation=Yt),Q.apply(le)}this.transform.apply(Q)}_fireMoveEvents(w){this.fire(new a.k(\"move\",w)),this._zooming&&this.fire(new a.k(\"zoom\",w)),this._rotating&&this.fire(new a.k(\"rotate\",w)),this._pitching&&this.fire(new a.k(\"pitch\",w))}_afterEase(w,B){if(this._easeId&&B&&this._easeId===B)return;delete this._easeId;let Q=this._zooming,ee=this._rotating,le=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,Q&&this.fire(new a.k(\"zoomend\",w)),ee&&this.fire(new a.k(\"rotateend\",w)),le&&this.fire(new a.k(\"pitchend\",w)),this.fire(new a.k(\"moveend\",w))}flyTo(w,B){var Q;if(!w.essential&&u.prefersReducedMotion){let Cn=a.M(w,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(Cn,B)}this.stop(),w=a.e({offset:[0,0],speed:1.2,curve:1.42,easing:a.b9},w);let ee=this._getTransformForUpdate(),le=ee.zoom,qe=ee.bearing,Xe=ee.pitch,ot=ee.padding,Tt=\"bearing\"in w?this._normalizeBearing(w.bearing,qe):qe,Yt=\"pitch\"in w?+w.pitch:Xe,Kt=\"padding\"in w?w.padding:ee.padding,xr=a.P.convert(w.offset),Ir=ee.centerPoint.add(xr),ve=ee.pointLocation(Ir),{center:be,zoom:De}=ee.getConstrained(a.N.convert(w.center||ve),(Q=w.zoom)!==null&&Q!==void 0?Q:le);this._normalizeCenter(be,ee);let Be=ee.zoomScale(De-le),et=ee.project(ve),We=ee.project(be).sub(et),it=w.curve,Ft=Math.max(ee.width,ee.height),Ht=Ft/Be,tr=We.mag();if(\"minZoom\"in w){let Cn=a.ac(Math.min(w.minZoom,le,De),ee.minZoom,ee.maxZoom),Kn=Ft/ee.zoomScale(Cn-le);it=Math.sqrt(Kn/tr*2)}let dr=it*it;function Sr(Cn){let Kn=(Ht*Ht-Ft*Ft+(Cn?-1:1)*dr*dr*tr*tr)/(2*(Cn?Ht:Ft)*dr*tr);return Math.log(Math.sqrt(Kn*Kn+1)-Kn)}function Or(Cn){return(Math.exp(Cn)-Math.exp(-Cn))/2}function Wr(Cn){return(Math.exp(Cn)+Math.exp(-Cn))/2}let ni=Sr(!1),Pi=function(Cn){return Wr(ni)/Wr(ni+it*Cn)},cn=function(Cn){return Ft*((Wr(ni)*(Or(Kn=ni+it*Cn)/Wr(Kn))-Or(ni))/dr)/tr;var Kn},ln=(Sr(!0)-ni)/it;if(Math.abs(tr)<1e-6||!isFinite(ln)){if(Math.abs(Ft-Ht)<1e-6)return this.easeTo(w,B);let Cn=Ht<Ft?-1:1;ln=Math.abs(Math.log(Ht/Ft))/it,cn=()=>0,Pi=Kn=>Math.exp(Cn*it*Kn)}return w.duration=\"duration\"in w?+w.duration:1e3*ln/(\"screenSpeed\"in w?+w.screenSpeed/it:+w.speed),w.maxDuration&&w.duration>w.maxDuration&&(w.duration=0),this._zooming=!0,this._rotating=qe!==Tt,this._pitching=Yt!==Xe,this._padding=!ee.isPaddingEqual(Kt),this._prepareEase(B,!1),this.terrain&&this._prepareElevation(be),this._ease(Cn=>{let Kn=Cn*ln,Ta=1/Pi(Kn);ee.zoom=Cn===1?De:le+ee.scaleZoom(Ta),this._rotating&&(ee.bearing=a.y.number(qe,Tt,Cn)),this._pitching&&(ee.pitch=a.y.number(Xe,Yt,Cn)),this._padding&&(ee.interpolatePadding(ot,Kt,Cn),Ir=ee.centerPoint.add(xr)),this.terrain&&!w.freezeElevation&&this._updateElevation(Cn);let fa=Cn===1?be:ee.unproject(et.add(We.mult(cn(Kn))).mult(Ta));ee.setLocationAtPoint(ee.renderWorldCopies?fa.wrap():fa,Ir),this._applyUpdatedTransform(ee),this._fireMoveEvents(B)},()=>{this.terrain&&w.freezeElevation&&this._finalizeElevation(),this._afterEase(B)},w),this}isEasing(){return!!this._easeFrameId}stop(){return this._stop()}_stop(w,B){var Q;if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){let ee=this._onEaseEnd;delete this._onEaseEnd,ee.call(this,B)}return w||(Q=this.handlers)===null||Q===void 0||Q.stop(!1),this}_ease(w,B,Q){Q.animate===!1||Q.duration===0?(w(1),B()):(this._easeStart=u.now(),this._easeOptions=Q,this._onEaseFrame=w,this._onEaseEnd=B,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))}_normalizeBearing(w,B){w=a.b3(w,-180,180);let Q=Math.abs(w-B);return Math.abs(w-360-B)<Q&&(w-=360),Math.abs(w+360-B)<Q&&(w+=360),w}_normalizeCenter(w,B){if(!B.renderWorldCopies||B.lngRange)return;let Q=w.lng-B.center.lng;w.lng+=Q>180?-360:Q<-180?360:0}queryTerrainElevation(w){return this.terrain?this.terrain.getElevationForLngLatZoom(a.N.convert(w),this.transform.tileZoom)-this.transform.elevation:null}}let La={compact:!0,customAttribution:'<a href=\"https://maplibre.org/\" target=\"_blank\">MapLibre</a>'};class Na{constructor(w=La){this._toggleAttribution=()=>{this._container.classList.contains(\"maplibregl-compact\")&&(this._container.classList.contains(\"maplibregl-compact-show\")?(this._container.setAttribute(\"open\",\"\"),this._container.classList.remove(\"maplibregl-compact-show\")):(this._container.classList.add(\"maplibregl-compact-show\"),this._container.removeAttribute(\"open\")))},this._updateData=B=>{!B||B.sourceDataType!==\"metadata\"&&B.sourceDataType!==\"visibility\"&&B.dataType!==\"style\"&&B.type!==\"terrain\"||this._updateAttributions()},this._updateCompact=()=>{this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact===!1?this._container.setAttribute(\"open\",\"\"):this._container.classList.contains(\"maplibregl-compact\")||this._container.classList.contains(\"maplibregl-attrib-empty\")||(this._container.setAttribute(\"open\",\"\"),this._container.classList.add(\"maplibregl-compact\",\"maplibregl-compact-show\")):(this._container.setAttribute(\"open\",\"\"),this._container.classList.contains(\"maplibregl-compact\")&&this._container.classList.remove(\"maplibregl-compact\",\"maplibregl-compact-show\"))},this._updateCompactMinimize=()=>{this._container.classList.contains(\"maplibregl-compact\")&&this._container.classList.contains(\"maplibregl-compact-show\")&&this._container.classList.remove(\"maplibregl-compact-show\")},this.options=w}getDefaultPosition(){return\"bottom-right\"}onAdd(w){return this._map=w,this._compact=this.options.compact,this._container=c.create(\"details\",\"maplibregl-ctrl maplibregl-ctrl-attrib\"),this._compactButton=c.create(\"summary\",\"maplibregl-ctrl-attrib-button\",this._container),this._compactButton.addEventListener(\"click\",this._toggleAttribution),this._setElementTitle(this._compactButton,\"ToggleAttribution\"),this._innerContainer=c.create(\"div\",\"maplibregl-ctrl-attrib-inner\",this._container),this._updateAttributions(),this._updateCompact(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"terrain\",this._updateData),this._map.on(\"resize\",this._updateCompact),this._map.on(\"drag\",this._updateCompactMinimize),this._container}onRemove(){c.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"terrain\",this._updateData),this._map.off(\"resize\",this._updateCompact),this._map.off(\"drag\",this._updateCompactMinimize),this._map=void 0,this._compact=void 0,this._attribHTML=void 0}_setElementTitle(w,B){let Q=this._map._getUIString(`AttributionControl.${B}`);w.title=Q,w.setAttribute(\"aria-label\",Q)}_updateAttributions(){if(!this._map.style)return;let w=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?w=w.concat(this.options.customAttribution.map(ee=>typeof ee!=\"string\"?\"\":ee)):typeof this.options.customAttribution==\"string\"&&w.push(this.options.customAttribution)),this._map.style.stylesheet){let ee=this._map.style.stylesheet;this.styleOwner=ee.owner,this.styleId=ee.id}let B=this._map.style.sourceCaches;for(let ee in B){let le=B[ee];if(le.used||le.usedForTerrain){let qe=le.getSource();qe.attribution&&w.indexOf(qe.attribution)<0&&w.push(qe.attribution)}}w=w.filter(ee=>String(ee).trim()),w.sort((ee,le)=>ee.length-le.length),w=w.filter((ee,le)=>{for(let qe=le+1;qe<w.length;qe++)if(w[qe].indexOf(ee)>=0)return!1;return!0});let Q=w.join(\" | \");Q!==this._attribHTML&&(this._attribHTML=Q,w.length?(this._innerContainer.innerHTML=Q,this._container.classList.remove(\"maplibregl-attrib-empty\")):this._container.classList.add(\"maplibregl-attrib-empty\"),this._updateCompact(),this._editLink=null)}}class Yn{constructor(w={}){this._updateCompact=()=>{let B=this._container.children;if(B.length){let Q=B[0];this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact!==!1&&Q.classList.add(\"maplibregl-compact\"):Q.classList.remove(\"maplibregl-compact\")}},this.options=w}getDefaultPosition(){return\"bottom-left\"}onAdd(w){this._map=w,this._compact=this.options&&this.options.compact,this._container=c.create(\"div\",\"maplibregl-ctrl\");let B=c.create(\"a\",\"maplibregl-ctrl-logo\");return B.target=\"_blank\",B.rel=\"noopener nofollow\",B.href=\"https://maplibre.org/\",B.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),B.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(B),this._container.style.display=\"block\",this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container}onRemove(){c.remove(this._container),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._compact=void 0}}class Dn{constructor(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1}add(w){let B=++this._id;return this._queue.push({callback:w,id:B,cancelled:!1}),B}remove(w){let B=this._currentlyRunning,Q=B?this._queue.concat(B):this._queue;for(let ee of Q)if(ee.id===w)return void(ee.cancelled=!0)}run(w=0){if(this._currentlyRunning)throw new Error(\"Attempting to run(), but is already running.\");let B=this._currentlyRunning=this._queue;this._queue=[];for(let Q of B)if(!Q.cancelled&&(Q.callback(w),this._cleared))break;this._cleared=!1,this._currentlyRunning=!1}clear(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]}}var Ka=a.Y([{name:\"a_pos3d\",type:\"Int16\",components:3}]);class bo extends a.E{constructor(w){super(),this.sourceCache=w,this._tiles={},this._renderableTilesKeys=[],this._sourceTileCache={},this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.deltaZoom=1,w.usedForTerrain=!0,w.tileSize=this.tileSize*2**this.deltaZoom}destruct(){this.sourceCache.usedForTerrain=!1,this.sourceCache.tileSize=null}update(w,B){this.sourceCache.update(w,B),this._renderableTilesKeys=[];let Q={};for(let ee of w.coveringTiles({tileSize:this.tileSize,minzoom:this.minzoom,maxzoom:this.maxzoom,reparseOverscaled:!1,terrain:B}))Q[ee.key]=!0,this._renderableTilesKeys.push(ee.key),this._tiles[ee.key]||(ee.posMatrix=new Float64Array(16),a.aP(ee.posMatrix,0,a.X,0,a.X,0,1),this._tiles[ee.key]=new Vt(ee,this.tileSize));for(let ee in this._tiles)Q[ee]||delete this._tiles[ee]}freeRtt(w){for(let B in this._tiles){let Q=this._tiles[B];(!w||Q.tileID.equals(w)||Q.tileID.isChildOf(w)||w.isChildOf(Q.tileID))&&(Q.rtt=[])}}getRenderableTiles(){return this._renderableTilesKeys.map(w=>this.getTileByID(w))}getTileByID(w){return this._tiles[w]}getTerrainCoords(w){let B={};for(let Q of this._renderableTilesKeys){let ee=this._tiles[Q].tileID;if(ee.canonical.equals(w.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16),a.aP(le.posMatrix,0,a.X,0,a.X,0,1),B[Q]=le}else if(ee.canonical.isChildOf(w.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16);let qe=ee.canonical.z-w.canonical.z,Xe=ee.canonical.x-(ee.canonical.x>>qe<<qe),ot=ee.canonical.y-(ee.canonical.y>>qe<<qe),Tt=a.X>>qe;a.aP(le.posMatrix,0,Tt,0,Tt,0,1),a.J(le.posMatrix,le.posMatrix,[-Xe*Tt,-ot*Tt,0]),B[Q]=le}else if(w.canonical.isChildOf(ee.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16);let qe=w.canonical.z-ee.canonical.z,Xe=w.canonical.x-(w.canonical.x>>qe<<qe),ot=w.canonical.y-(w.canonical.y>>qe<<qe),Tt=a.X>>qe;a.aP(le.posMatrix,0,a.X,0,a.X,0,1),a.J(le.posMatrix,le.posMatrix,[Xe*Tt,ot*Tt,0]),a.K(le.posMatrix,le.posMatrix,[1/2**qe,1/2**qe,0]),B[Q]=le}}return B}getSourceTile(w,B){let Q=this.sourceCache._source,ee=w.overscaledZ-this.deltaZoom;if(ee>Q.maxzoom&&(ee=Q.maxzoom),ee<Q.minzoom)return null;this._sourceTileCache[w.key]||(this._sourceTileCache[w.key]=w.scaledTo(ee).key);let le=this.sourceCache.getTileByID(this._sourceTileCache[w.key]);if((!le||!le.dem)&&B)for(;ee>=Q.minzoom&&(!le||!le.dem);)le=this.sourceCache.getTileByID(w.scaledTo(ee--).key);return le}tilesAfterTime(w=Date.now()){return Object.values(this._tiles).filter(B=>B.timeAdded>=w)}}class Xo{constructor(w,B,Q){this.painter=w,this.sourceCache=new bo(B),this.options=Q,this.exaggeration=typeof Q.exaggeration==\"number\"?Q.exaggeration:1,this.qualityFactor=2,this.meshSize=128,this._demMatrixCache={},this.coordsIndex=[],this._coordsTextureSize=1024}getDEMElevation(w,B,Q,ee=a.X){var le;if(!(B>=0&&B<ee&&Q>=0&&Q<ee))return 0;let qe=this.getTerrainData(w),Xe=(le=qe.tile)===null||le===void 0?void 0:le.dem;if(!Xe)return 0;let ot=function(ve,be,De){var Be=be[0],et=be[1];return ve[0]=De[0]*Be+De[4]*et+De[12],ve[1]=De[1]*Be+De[5]*et+De[13],ve}([],[B/ee*a.X,Q/ee*a.X],qe.u_terrain_matrix),Tt=[ot[0]*Xe.dim,ot[1]*Xe.dim],Yt=Math.floor(Tt[0]),Kt=Math.floor(Tt[1]),xr=Tt[0]-Yt,Ir=Tt[1]-Kt;return Xe.get(Yt,Kt)*(1-xr)*(1-Ir)+Xe.get(Yt+1,Kt)*xr*(1-Ir)+Xe.get(Yt,Kt+1)*(1-xr)*Ir+Xe.get(Yt+1,Kt+1)*xr*Ir}getElevationForLngLatZoom(w,B){if(!a.bb(B,w.wrap()))return 0;let{tileID:Q,mercatorX:ee,mercatorY:le}=this._getOverscaledTileIDFromLngLatZoom(w,B);return this.getElevation(Q,ee%a.X,le%a.X,a.X)}getElevation(w,B,Q,ee=a.X){return this.getDEMElevation(w,B,Q,ee)*this.exaggeration}getTerrainData(w){if(!this._emptyDemTexture){let ee=this.painter.context,le=new a.R({width:1,height:1},new Uint8Array(4));this._emptyDepthTexture=new g(ee,le,ee.gl.RGBA,{premultiply:!1}),this._emptyDemUnpack=[0,0,0,0],this._emptyDemTexture=new g(ee,new a.R({width:1,height:1}),ee.gl.RGBA,{premultiply:!1}),this._emptyDemTexture.bind(ee.gl.NEAREST,ee.gl.CLAMP_TO_EDGE),this._emptyDemMatrix=a.an([])}let B=this.sourceCache.getSourceTile(w,!0);if(B&&B.dem&&(!B.demTexture||B.needsTerrainPrepare)){let ee=this.painter.context;B.demTexture=this.painter.getTileTexture(B.dem.stride),B.demTexture?B.demTexture.update(B.dem.getPixels(),{premultiply:!1}):B.demTexture=new g(ee,B.dem.getPixels(),ee.gl.RGBA,{premultiply:!1}),B.demTexture.bind(ee.gl.NEAREST,ee.gl.CLAMP_TO_EDGE),B.needsTerrainPrepare=!1}let Q=B&&B+B.tileID.key+w.key;if(Q&&!this._demMatrixCache[Q]){let ee=this.sourceCache.sourceCache._source.maxzoom,le=w.canonical.z-B.tileID.canonical.z;w.overscaledZ>w.canonical.z&&(w.canonical.z>=ee?le=w.canonical.z-ee:a.w(\"cannot calculate elevation if elevation maxzoom > source.maxzoom\"));let qe=w.canonical.x-(w.canonical.x>>le<<le),Xe=w.canonical.y-(w.canonical.y>>le<<le),ot=a.bc(new Float64Array(16),[1/(a.X<<le),1/(a.X<<le),0]);a.J(ot,ot,[qe*a.X,Xe*a.X,0]),this._demMatrixCache[w.key]={matrix:ot,coord:w}}return{u_depth:2,u_terrain:3,u_terrain_dim:B&&B.dem&&B.dem.dim||1,u_terrain_matrix:Q?this._demMatrixCache[w.key].matrix:this._emptyDemMatrix,u_terrain_unpack:B&&B.dem&&B.dem.getUnpackVector()||this._emptyDemUnpack,u_terrain_exaggeration:this.exaggeration,texture:(B&&B.demTexture||this._emptyDemTexture).texture,depthTexture:(this._fboDepthTexture||this._emptyDepthTexture).texture,tile:B}}getFramebuffer(w){let B=this.painter,Q=B.width/devicePixelRatio,ee=B.height/devicePixelRatio;return!this._fbo||this._fbo.width===Q&&this._fbo.height===ee||(this._fbo.destroy(),this._fboCoordsTexture.destroy(),this._fboDepthTexture.destroy(),delete this._fbo,delete this._fboDepthTexture,delete this._fboCoordsTexture),this._fboCoordsTexture||(this._fboCoordsTexture=new g(B.context,{width:Q,height:ee,data:null},B.context.gl.RGBA,{premultiply:!1}),this._fboCoordsTexture.bind(B.context.gl.NEAREST,B.context.gl.CLAMP_TO_EDGE)),this._fboDepthTexture||(this._fboDepthTexture=new g(B.context,{width:Q,height:ee,data:null},B.context.gl.RGBA,{premultiply:!1}),this._fboDepthTexture.bind(B.context.gl.NEAREST,B.context.gl.CLAMP_TO_EDGE)),this._fbo||(this._fbo=B.context.createFramebuffer(Q,ee,!0,!1),this._fbo.depthAttachment.set(B.context.createRenderbuffer(B.context.gl.DEPTH_COMPONENT16,Q,ee))),this._fbo.colorAttachment.set(w===\"coords\"?this._fboCoordsTexture.texture:this._fboDepthTexture.texture),this._fbo}getCoordsTexture(){let w=this.painter.context;if(this._coordsTexture)return this._coordsTexture;let B=new Uint8Array(this._coordsTextureSize*this._coordsTextureSize*4);for(let le=0,qe=0;le<this._coordsTextureSize;le++)for(let Xe=0;Xe<this._coordsTextureSize;Xe++,qe+=4)B[qe+0]=255&Xe,B[qe+1]=255&le,B[qe+2]=Xe>>8<<4|le>>8,B[qe+3]=0;let Q=new a.R({width:this._coordsTextureSize,height:this._coordsTextureSize},new Uint8Array(B.buffer)),ee=new g(w,Q,w.gl.RGBA,{premultiply:!1});return ee.bind(w.gl.NEAREST,w.gl.CLAMP_TO_EDGE),this._coordsTexture=ee,ee}pointCoordinate(w){this.painter.maybeDrawDepthAndCoords(!0);let B=new Uint8Array(4),Q=this.painter.context,ee=Q.gl,le=Math.round(w.x*this.painter.pixelRatio/devicePixelRatio),qe=Math.round(w.y*this.painter.pixelRatio/devicePixelRatio),Xe=Math.round(this.painter.height/devicePixelRatio);Q.bindFramebuffer.set(this.getFramebuffer(\"coords\").framebuffer),ee.readPixels(le,Xe-qe-1,1,1,ee.RGBA,ee.UNSIGNED_BYTE,B),Q.bindFramebuffer.set(null);let ot=B[0]+(B[2]>>4<<8),Tt=B[1]+((15&B[2])<<8),Yt=this.coordsIndex[255-B[3]],Kt=Yt&&this.sourceCache.getTileByID(Yt);if(!Kt)return null;let xr=this._coordsTextureSize,Ir=(1<<Kt.tileID.canonical.z)*xr;return new a.Z((Kt.tileID.canonical.x*xr+ot)/Ir+Kt.tileID.wrap,(Kt.tileID.canonical.y*xr+Tt)/Ir,this.getElevation(Kt.tileID,ot,Tt,xr))}depthAtPoint(w){let B=new Uint8Array(4),Q=this.painter.context,ee=Q.gl;return Q.bindFramebuffer.set(this.getFramebuffer(\"depth\").framebuffer),ee.readPixels(w.x,this.painter.height/devicePixelRatio-w.y-1,1,1,ee.RGBA,ee.UNSIGNED_BYTE,B),Q.bindFramebuffer.set(null),(B[0]/16777216+B[1]/65536+B[2]/256+B[3])/256}getTerrainMesh(){if(this._mesh)return this._mesh;let w=this.painter.context,B=new a.bd,Q=new a.aY,ee=this.meshSize,le=a.X/ee,qe=ee*ee;for(let Kt=0;Kt<=ee;Kt++)for(let xr=0;xr<=ee;xr++)B.emplaceBack(xr*le,Kt*le,0);for(let Kt=0;Kt<qe;Kt+=ee+1)for(let xr=0;xr<ee;xr++)Q.emplaceBack(xr+Kt,ee+xr+Kt+1,ee+xr+Kt+2),Q.emplaceBack(xr+Kt,ee+xr+Kt+2,xr+Kt+1);let Xe=B.length,ot=Xe+2*(ee+1);for(let Kt of[0,1])for(let xr=0;xr<=ee;xr++)for(let Ir of[0,1])B.emplaceBack(xr*le,Kt*a.X,Ir);for(let Kt=0;Kt<2*ee;Kt+=2)Q.emplaceBack(ot+Kt,ot+Kt+1,ot+Kt+3),Q.emplaceBack(ot+Kt,ot+Kt+3,ot+Kt+2),Q.emplaceBack(Xe+Kt,Xe+Kt+3,Xe+Kt+1),Q.emplaceBack(Xe+Kt,Xe+Kt+2,Xe+Kt+3);let Tt=B.length,Yt=Tt+2*(ee+1);for(let Kt of[0,1])for(let xr=0;xr<=ee;xr++)for(let Ir of[0,1])B.emplaceBack(Kt*a.X,xr*le,Ir);for(let Kt=0;Kt<2*ee;Kt+=2)Q.emplaceBack(Tt+Kt,Tt+Kt+1,Tt+Kt+3),Q.emplaceBack(Tt+Kt,Tt+Kt+3,Tt+Kt+2),Q.emplaceBack(Yt+Kt,Yt+Kt+3,Yt+Kt+1),Q.emplaceBack(Yt+Kt,Yt+Kt+2,Yt+Kt+3);return this._mesh=new Eu(w.createVertexBuffer(B,Ka.members),w.createIndexBuffer(Q),a.a0.simpleSegment(0,0,B.length,Q.length)),this._mesh}getMeshFrameDelta(w){return 2*Math.PI*a.be/Math.pow(2,w)/5}getMinTileElevationForLngLatZoom(w,B){var Q;let{tileID:ee}=this._getOverscaledTileIDFromLngLatZoom(w,B);return(Q=this.getMinMaxElevation(ee).minElevation)!==null&&Q!==void 0?Q:0}getMinMaxElevation(w){let B=this.getTerrainData(w).tile,Q={minElevation:null,maxElevation:null};return B&&B.dem&&(Q.minElevation=B.dem.min*this.exaggeration,Q.maxElevation=B.dem.max*this.exaggeration),Q}_getOverscaledTileIDFromLngLatZoom(w,B){let Q=a.Z.fromLngLat(w.wrap()),ee=(1<<B)*a.X,le=Q.x*ee,qe=Q.y*ee,Xe=Math.floor(le/a.X),ot=Math.floor(qe/a.X);return{tileID:new a.S(B,0,B,Xe,ot),mercatorX:le,mercatorY:qe}}}class Ss{constructor(w,B,Q){this._context=w,this._size=B,this._tileSize=Q,this._objects=[],this._recentlyUsed=[],this._stamp=0}destruct(){for(let w of this._objects)w.texture.destroy(),w.fbo.destroy()}_createObject(w){let B=this._context.createFramebuffer(this._tileSize,this._tileSize,!0,!0),Q=new g(this._context,{width:this._tileSize,height:this._tileSize,data:null},this._context.gl.RGBA);return Q.bind(this._context.gl.LINEAR,this._context.gl.CLAMP_TO_EDGE),B.depthAttachment.set(this._context.createRenderbuffer(this._context.gl.DEPTH_STENCIL,this._tileSize,this._tileSize)),B.colorAttachment.set(Q.texture),{id:w,fbo:B,texture:Q,stamp:-1,inUse:!1}}getObjectForId(w){return this._objects[w]}useObject(w){w.inUse=!0,this._recentlyUsed=this._recentlyUsed.filter(B=>w.id!==B),this._recentlyUsed.push(w.id)}stampObject(w){w.stamp=++this._stamp}getOrCreateFreeObject(){for(let B of this._recentlyUsed)if(!this._objects[B].inUse)return this._objects[B];if(this._objects.length>=this._size)throw new Error(\"No free RenderPool available, call freeAllObjects() required!\");let w=this._createObject(this._objects.length);return this._objects.push(w),w}freeObject(w){w.inUse=!1}freeAllObjects(){for(let w of this._objects)this.freeObject(w)}isFull(){return!(this._objects.length<this._size)&&this._objects.some(w=>!w.inUse)===!1}}let as={background:!0,fill:!0,line:!0,raster:!0,hillshade:!0};class ws{constructor(w,B){this.painter=w,this.terrain=B,this.pool=new Ss(w.context,30,B.sourceCache.tileSize*B.qualityFactor)}destruct(){this.pool.destruct()}getTexture(w){return this.pool.getObjectForId(w.rtt[this._stacks.length-1].id).texture}prepareForRender(w,B){this._stacks=[],this._prevType=null,this._rttTiles=[],this._renderableTiles=this.terrain.sourceCache.getRenderableTiles(),this._renderableLayerIds=w._order.filter(Q=>!w._layers[Q].isHidden(B)),this._coordsDescendingInv={};for(let Q in w.sourceCaches){this._coordsDescendingInv[Q]={};let ee=w.sourceCaches[Q].getVisibleCoordinates();for(let le of ee){let qe=this.terrain.sourceCache.getTerrainCoords(le);for(let Xe in qe)this._coordsDescendingInv[Q][Xe]||(this._coordsDescendingInv[Q][Xe]=[]),this._coordsDescendingInv[Q][Xe].push(qe[Xe])}}this._coordsDescendingInvStr={};for(let Q of w._order){let ee=w._layers[Q],le=ee.source;if(as[ee.type]&&!this._coordsDescendingInvStr[le]){this._coordsDescendingInvStr[le]={};for(let qe in this._coordsDescendingInv[le])this._coordsDescendingInvStr[le][qe]=this._coordsDescendingInv[le][qe].map(Xe=>Xe.key).sort().join()}}for(let Q of this._renderableTiles)for(let ee in this._coordsDescendingInvStr){let le=this._coordsDescendingInvStr[ee][Q.tileID.key];le&&le!==Q.rttCoords[ee]&&(Q.rtt=[])}}renderLayer(w){if(w.isHidden(this.painter.transform.zoom))return!1;let B=w.type,Q=this.painter,ee=this._renderableLayerIds[this._renderableLayerIds.length-1]===w.id;if(as[B]&&(this._prevType&&as[this._prevType]||this._stacks.push([]),this._prevType=B,this._stacks[this._stacks.length-1].push(w.id),!ee))return!0;if(as[this._prevType]||as[B]&&ee){this._prevType=B;let le=this._stacks.length-1,qe=this._stacks[le]||[];for(let Xe of this._renderableTiles){if(this.pool.isFull()&&(js(this.painter,this.terrain,this._rttTiles),this._rttTiles=[],this.pool.freeAllObjects()),this._rttTiles.push(Xe),Xe.rtt[le]){let Tt=this.pool.getObjectForId(Xe.rtt[le].id);if(Tt.stamp===Xe.rtt[le].stamp){this.pool.useObject(Tt);continue}}let ot=this.pool.getOrCreateFreeObject();this.pool.useObject(ot),this.pool.stampObject(ot),Xe.rtt[le]={id:ot.id,stamp:ot.stamp},Q.context.bindFramebuffer.set(ot.fbo.framebuffer),Q.context.clear({color:a.aM.transparent,stencil:0}),Q.currentStencilSource=void 0;for(let Tt=0;Tt<qe.length;Tt++){let Yt=Q.style._layers[qe[Tt]],Kt=Yt.source?this._coordsDescendingInv[Yt.source][Xe.tileID.key]:[Xe.tileID];Q.context.viewport.set([0,0,ot.fbo.width,ot.fbo.height]),Q._renderTileClippingMasks(Yt,Kt),Q.renderLayer(Q,Q.style.sourceCaches[Yt.source],Yt,Kt),Yt.source&&(Xe.rttCoords[Yt.source]=this._coordsDescendingInvStr[Yt.source][Xe.tileID.key])}}return js(this.painter,this.terrain,this._rttTiles),this._rttTiles=[],this.pool.freeAllObjects(),as[B]}return!1}}let Ho={\"AttributionControl.ToggleAttribution\":\"Toggle attribution\",\"AttributionControl.MapFeedback\":\"Map feedback\",\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"MapLibre logo\",\"Map.Title\":\"Map\",\"Marker.Title\":\"Map marker\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"Popup.Close\":\"Close popup\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\",\"TerrainControl.Enable\":\"Enable terrain\",\"TerrainControl.Disable\":\"Disable terrain\",\"CooperativeGesturesHandler.WindowsHelpText\":\"Use Ctrl + scroll to zoom the map\",\"CooperativeGesturesHandler.MacHelpText\":\"Use \\u2318 + scroll to zoom the map\",\"CooperativeGesturesHandler.MobileHelpText\":\"Use two fingers to move the map\"},ml=o,Ws={hash:!1,interactive:!0,bearingSnap:7,attributionControl:La,maplibreLogo:!1,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,refreshExpiredTiles:!0,scrollZoom:!0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,cooperativeGestures:!1,trackResize:!0,center:[0,0],zoom:0,bearing:0,pitch:0,renderWorldCopies:!0,maxTileCacheSize:null,maxTileCacheZoomLevels:a.a.MAX_TILE_CACHE_ZOOM_LEVELS,transformRequest:null,transformCameraUpdate:null,fadeDuration:300,crossSourceCollisions:!0,clickTolerance:3,localIdeographFontFamily:\"sans-serif\",pitchWithRotate:!0,validateStyle:!0,maxCanvasSize:[4096,4096],cancelPendingTileRequestsWhileZooming:!0},Ls=ue=>{ue.touchstart=ue.dragStart,ue.touchmoveWindow=ue.dragMove,ue.touchend=ue.dragEnd},va={showCompass:!0,showZoom:!0,visualizePitch:!1};class no{constructor(w,B,Q=!1){this.mousedown=qe=>{this.startMouse(a.e({},qe,{ctrlKey:!0,preventDefault:()=>qe.preventDefault()}),c.mousePos(this.element,qe)),c.addEventListener(window,\"mousemove\",this.mousemove),c.addEventListener(window,\"mouseup\",this.mouseup)},this.mousemove=qe=>{this.moveMouse(qe,c.mousePos(this.element,qe))},this.mouseup=qe=>{this.mouseRotate.dragEnd(qe),this.mousePitch&&this.mousePitch.dragEnd(qe),this.offTemp()},this.touchstart=qe=>{qe.targetTouches.length!==1?this.reset():(this._startPos=this._lastPos=c.touchPos(this.element,qe.targetTouches)[0],this.startTouch(qe,this._startPos),c.addEventListener(window,\"touchmove\",this.touchmove,{passive:!1}),c.addEventListener(window,\"touchend\",this.touchend))},this.touchmove=qe=>{qe.targetTouches.length!==1?this.reset():(this._lastPos=c.touchPos(this.element,qe.targetTouches)[0],this.moveTouch(qe,this._lastPos))},this.touchend=qe=>{qe.targetTouches.length===0&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),delete this._startPos,delete this._lastPos,this.offTemp()},this.reset=()=>{this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),this.touchRotate.reset(),this.touchPitch&&this.touchPitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()},this._clickTolerance=10;let ee=w.dragRotate._mouseRotate.getClickTolerance(),le=w.dragRotate._mousePitch.getClickTolerance();this.element=B,this.mouseRotate=Wl({clickTolerance:ee,enable:!0}),this.touchRotate=(({enable:qe,clickTolerance:Xe,bearingDegreesPerPixelMoved:ot=.8})=>{let Tt=new uf;return new Wu({clickTolerance:Xe,move:(Yt,Kt)=>({bearingDelta:(Kt.x-Yt.x)*ot}),moveStateManager:Tt,enable:qe,assignEvents:Ls})})({clickTolerance:ee,enable:!0}),this.map=w,Q&&(this.mousePitch=ah({clickTolerance:le,enable:!0}),this.touchPitch=(({enable:qe,clickTolerance:Xe,pitchDegreesPerPixelMoved:ot=-.5})=>{let Tt=new uf;return new Wu({clickTolerance:Xe,move:(Yt,Kt)=>({pitchDelta:(Kt.y-Yt.y)*ot}),moveStateManager:Tt,enable:qe,assignEvents:Ls})})({clickTolerance:le,enable:!0})),c.addEventListener(B,\"mousedown\",this.mousedown),c.addEventListener(B,\"touchstart\",this.touchstart,{passive:!1}),c.addEventListener(B,\"touchcancel\",this.reset)}startMouse(w,B){this.mouseRotate.dragStart(w,B),this.mousePitch&&this.mousePitch.dragStart(w,B),c.disableDrag()}startTouch(w,B){this.touchRotate.dragStart(w,B),this.touchPitch&&this.touchPitch.dragStart(w,B),c.disableDrag()}moveMouse(w,B){let Q=this.map,{bearingDelta:ee}=this.mouseRotate.dragMove(w,B)||{};if(ee&&Q.setBearing(Q.getBearing()+ee),this.mousePitch){let{pitchDelta:le}=this.mousePitch.dragMove(w,B)||{};le&&Q.setPitch(Q.getPitch()+le)}}moveTouch(w,B){let Q=this.map,{bearingDelta:ee}=this.touchRotate.dragMove(w,B)||{};if(ee&&Q.setBearing(Q.getBearing()+ee),this.touchPitch){let{pitchDelta:le}=this.touchPitch.dragMove(w,B)||{};le&&Q.setPitch(Q.getPitch()+le)}}off(){let w=this.element;c.removeEventListener(w,\"mousedown\",this.mousedown),c.removeEventListener(w,\"touchstart\",this.touchstart,{passive:!1}),c.removeEventListener(window,\"touchmove\",this.touchmove,{passive:!1}),c.removeEventListener(window,\"touchend\",this.touchend),c.removeEventListener(w,\"touchcancel\",this.reset),this.offTemp()}offTemp(){c.enableDrag(),c.removeEventListener(window,\"mousemove\",this.mousemove),c.removeEventListener(window,\"mouseup\",this.mouseup),c.removeEventListener(window,\"touchmove\",this.touchmove,{passive:!1}),c.removeEventListener(window,\"touchend\",this.touchend)}}let ys;function rs(ue,w,B){let Q=new a.N(ue.lng,ue.lat);if(ue=new a.N(ue.lng,ue.lat),w){let ee=new a.N(ue.lng-360,ue.lat),le=new a.N(ue.lng+360,ue.lat),qe=B.locationPoint(ue).distSqr(w);B.locationPoint(ee).distSqr(w)<qe?ue=ee:B.locationPoint(le).distSqr(w)<qe&&(ue=le)}for(;Math.abs(ue.lng-B.center.lng)>180;){let ee=B.locationPoint(ue);if(ee.x>=0&&ee.y>=0&&ee.x<=B.width&&ee.y<=B.height)break;ue.lng>B.center.lng?ue.lng-=360:ue.lng+=360}return ue.lng!==Q.lng&&B.locationPoint(ue).y>B.height/2-B.getHorizon()?ue:Q}let $l={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Cu(ue,w,B){let Q=ue.classList;for(let ee in $l)Q.remove(`maplibregl-${B}-anchor-${ee}`);Q.add(`maplibregl-${B}-anchor-${w}`)}class Yu extends a.E{constructor(w){if(super(),this._onKeyPress=B=>{let Q=B.code,ee=B.charCode||B.keyCode;Q!==\"Space\"&&Q!==\"Enter\"&&ee!==32&&ee!==13||this.togglePopup()},this._onMapClick=B=>{let Q=B.originalEvent.target,ee=this._element;this._popup&&(Q===ee||ee.contains(Q))&&this.togglePopup()},this._update=B=>{var Q;if(!this._map)return;let ee=this._map.loaded()&&!this._map.isMoving();((B==null?void 0:B.type)===\"terrain\"||(B==null?void 0:B.type)===\"render\"&&!ee)&&this._map.once(\"render\",this._update),this._lngLat=this._map.transform.renderWorldCopies?rs(this._lngLat,this._flatPos,this._map.transform):(Q=this._lngLat)===null||Q===void 0?void 0:Q.wrap(),this._flatPos=this._pos=this._map.project(this._lngLat)._add(this._offset),this._map.terrain&&(this._flatPos=this._map.transform.locationPoint(this._lngLat)._add(this._offset));let le=\"\";this._rotationAlignment===\"viewport\"||this._rotationAlignment===\"auto\"?le=`rotateZ(${this._rotation}deg)`:this._rotationAlignment===\"map\"&&(le=`rotateZ(${this._rotation-this._map.getBearing()}deg)`);let qe=\"\";this._pitchAlignment===\"viewport\"||this._pitchAlignment===\"auto\"?qe=\"rotateX(0deg)\":this._pitchAlignment===\"map\"&&(qe=`rotateX(${this._map.getPitch()}deg)`),this._subpixelPositioning||B&&B.type!==\"moveend\"||(this._pos=this._pos.round()),c.setTransform(this._element,`${$l[this._anchor]} translate(${this._pos.x}px, ${this._pos.y}px) ${qe} ${le}`),u.frameAsync(new AbortController).then(()=>{this._updateOpacity(B&&B.type===\"moveend\")}).catch(()=>{})},this._onMove=B=>{if(!this._isDragging){let Q=this._clickTolerance||this._map._clickTolerance;this._isDragging=B.point.dist(this._pointerdownPos)>=Q}this._isDragging&&(this._pos=B.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",this._state===\"pending\"&&(this._state=\"active\",this.fire(new a.k(\"dragstart\"))),this.fire(new a.k(\"drag\")))},this._onUp=()=>{this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),this._state===\"active\"&&this.fire(new a.k(\"dragend\")),this._state=\"inactive\"},this._addDragHandler=B=>{this._element.contains(B.originalEvent.target)&&(B.preventDefault(),this._positionDelta=B.point.sub(this._pos).add(this._offset),this._pointerdownPos=B.point,this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},this._anchor=w&&w.anchor||\"center\",this._color=w&&w.color||\"#3FB1CE\",this._scale=w&&w.scale||1,this._draggable=w&&w.draggable||!1,this._clickTolerance=w&&w.clickTolerance||0,this._subpixelPositioning=w&&w.subpixelPositioning||!1,this._isDragging=!1,this._state=\"inactive\",this._rotation=w&&w.rotation||0,this._rotationAlignment=w&&w.rotationAlignment||\"auto\",this._pitchAlignment=w&&w.pitchAlignment&&w.pitchAlignment!==\"auto\"?w.pitchAlignment:this._rotationAlignment,this.setOpacity(),this.setOpacity(w==null?void 0:w.opacity,w==null?void 0:w.opacityWhenCovered),w&&w.element)this._element=w.element,this._offset=a.P.convert(w&&w.offset||[0,0]);else{this._defaultMarker=!0,this._element=c.create(\"div\");let B=c.createNS(\"http://www.w3.org/2000/svg\",\"svg\"),Q=41,ee=27;B.setAttributeNS(null,\"display\",\"block\"),B.setAttributeNS(null,\"height\",`${Q}px`),B.setAttributeNS(null,\"width\",`${ee}px`),B.setAttributeNS(null,\"viewBox\",`0 0 ${ee} ${Q}`);let le=c.createNS(\"http://www.w3.org/2000/svg\",\"g\");le.setAttributeNS(null,\"stroke\",\"none\"),le.setAttributeNS(null,\"stroke-width\",\"1\"),le.setAttributeNS(null,\"fill\",\"none\"),le.setAttributeNS(null,\"fill-rule\",\"evenodd\");let qe=c.createNS(\"http://www.w3.org/2000/svg\",\"g\");qe.setAttributeNS(null,\"fill-rule\",\"nonzero\");let Xe=c.createNS(\"http://www.w3.org/2000/svg\",\"g\");Xe.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),Xe.setAttributeNS(null,\"fill\",\"#000000\");let ot=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];for(let Be of ot){let et=c.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");et.setAttributeNS(null,\"opacity\",\"0.04\"),et.setAttributeNS(null,\"cx\",\"10.5\"),et.setAttributeNS(null,\"cy\",\"5.80029008\"),et.setAttributeNS(null,\"rx\",Be.rx),et.setAttributeNS(null,\"ry\",Be.ry),Xe.appendChild(et)}let Tt=c.createNS(\"http://www.w3.org/2000/svg\",\"g\");Tt.setAttributeNS(null,\"fill\",this._color);let Yt=c.createNS(\"http://www.w3.org/2000/svg\",\"path\");Yt.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),Tt.appendChild(Yt);let 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De=c.createNS(\"http://www.w3.org/2000/svg\",\"circle\");De.setAttributeNS(null,\"fill\",\"#FFFFFF\"),De.setAttributeNS(null,\"cx\",\"5.5\"),De.setAttributeNS(null,\"cy\",\"5.5\"),De.setAttributeNS(null,\"r\",\"5.4999962\"),ve.appendChild(be),ve.appendChild(De),qe.appendChild(Xe),qe.appendChild(Tt),qe.appendChild(Kt),qe.appendChild(Ir),qe.appendChild(ve),B.appendChild(qe),B.setAttributeNS(null,\"height\",Q*this._scale+\"px\"),B.setAttributeNS(null,\"width\",ee*this._scale+\"px\"),this._element.appendChild(B),this._offset=a.P.convert(w&&w.offset||[0,-14])}if(this._element.classList.add(\"maplibregl-marker\"),this._element.addEventListener(\"dragstart\",B=>{B.preventDefault()}),this._element.addEventListener(\"mousedown\",B=>{B.preventDefault()}),Cu(this._element,this._anchor,\"marker\"),w&&w.className)for(let B of w.className.split(\" \"))this._element.classList.add(B);this._popup=null}addTo(w){return 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this._lngLat}setLngLat(w){return this._lngLat=a.N.convert(w),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this}getElement(){return this._element}setPopup(w){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),w){if(!(\"offset\"in w.options)){let ee=Math.abs(13.5)/Math.SQRT2;w.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[ee,-1*(38.1-13.5+ee)],\"bottom-right\":[-ee,-1*(38.1-13.5+ee)],left:[13.5,-1*(38.1-13.5)],right:[-13.5,-1*(38.1-13.5)]}:this._offset}this._popup=w,this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this}setSubpixelPositioning(w){return this._subpixelPositioning=w,this}getPopup(){return this._popup}togglePopup(){let w=this._popup;return this._element.style.opacity===this._opacityWhenCovered?this:w?(w.isOpen()?w.remove():(w.setLngLat(this._lngLat),w.addTo(this._map)),this):this}_updateOpacity(w=!1){var B,Q;if(!(!((B=this._map)===null||B===void 0)&&B.terrain))return void(this._element.style.opacity!==this._opacity&&(this._element.style.opacity=this._opacity));if(w)this._opacityTimeout=null;else{if(this._opacityTimeout)return;this._opacityTimeout=setTimeout(()=>{this._opacityTimeout=null},100)}let ee=this._map,le=ee.terrain.depthAtPoint(this._pos),qe=ee.terrain.getElevationForLngLatZoom(this._lngLat,ee.transform.tileZoom);if(ee.transform.lngLatToCameraDepth(this._lngLat,qe)-le<.006)return void(this._element.style.opacity=this._opacity);let Xe=-this._offset.y/ee.transform._pixelPerMeter,ot=Math.sin(ee.getPitch()*Math.PI/180)*Xe,Tt=ee.terrain.depthAtPoint(new a.P(this._pos.x,this._pos.y-this._offset.y)),Yt=ee.transform.lngLatToCameraDepth(this._lngLat,qe+ot)-Tt>.006;!((Q=this._popup)===null||Q===void 0)&&Q.isOpen()&&Yt&&this._popup.remove(),this._element.style.opacity=Yt?this._opacityWhenCovered:this._opacity}getOffset(){return this._offset}setOffset(w){return this._offset=a.P.convert(w),this._update(),this}addClassName(w){this._element.classList.add(w)}removeClassName(w){this._element.classList.remove(w)}toggleClassName(w){return this._element.classList.toggle(w)}setDraggable(w){return this._draggable=!!w,this._map&&(w?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this}isDraggable(){return this._draggable}setRotation(w){return this._rotation=w||0,this._update(),this}getRotation(){return this._rotation}setRotationAlignment(w){return this._rotationAlignment=w||\"auto\",this._update(),this}getRotationAlignment(){return this._rotationAlignment}setPitchAlignment(w){return this._pitchAlignment=w&&w!==\"auto\"?w:this._rotationAlignment,this._update(),this}getPitchAlignment(){return this._pitchAlignment}setOpacity(w,B){return w===void 0&&B===void 0&&(this._opacity=\"1\",this._opacityWhenCovered=\"0.2\"),w!==void 0&&(this._opacity=w),B!==void 0&&(this._opacityWhenCovered=B),this._map&&this._updateOpacity(!0),this}}let Nc={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},pu=0,Uc=!1,xu={maxWidth:100,unit:\"metric\"};function Ac(ue,w,B){let Q=B&&B.maxWidth||100,ee=ue._container.clientHeight/2,le=ue.unproject([0,ee]),qe=ue.unproject([Q,ee]),Xe=le.distanceTo(qe);if(B&&B.unit===\"imperial\"){let ot=3.2808*Xe;ot>5280?Ua(w,Q,ot/5280,ue._getUIString(\"ScaleControl.Miles\")):Ua(w,Q,ot,ue._getUIString(\"ScaleControl.Feet\"))}else B&&B.unit===\"nautical\"?Ua(w,Q,Xe/1852,ue._getUIString(\"ScaleControl.NauticalMiles\")):Xe>=1e3?Ua(w,Q,Xe/1e3,ue._getUIString(\"ScaleControl.Kilometers\")):Ua(w,Q,Xe,ue._getUIString(\"ScaleControl.Meters\"))}function Ua(ue,w,B,Q){let ee=function(le){let qe=Math.pow(10,`${Math.floor(le)}`.length-1),Xe=le/qe;return Xe=Xe>=10?10:Xe>=5?5:Xe>=3?3:Xe>=2?2:Xe>=1?1:function(ot){let Tt=Math.pow(10,Math.ceil(-Math.log(ot)/Math.LN10));return Math.round(ot*Tt)/Tt}(Xe),qe*Xe}(B);ue.style.width=w*(ee/B)+\"px\",ue.innerHTML=`${ee}&nbsp;${Q}`}let oo={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:\"\",maxWidth:\"240px\",subpixelPositioning:!1},Vc=[\"a[href]\",\"[tabindex]:not([tabindex='-1'])\",\"[contenteditable]:not([contenteditable='false'])\",\"button:not([disabled])\",\"input:not([disabled])\",\"select:not([disabled])\",\"textarea:not([disabled])\"].join(\", \");function hc(ue){if(ue){if(typeof ue==\"number\"){let w=Math.round(Math.abs(ue)/Math.SQRT2);return{center:new a.P(0,0),top:new a.P(0,ue),\"top-left\":new a.P(w,w),\"top-right\":new a.P(-w,w),bottom:new a.P(0,-ue),\"bottom-left\":new a.P(w,-w),\"bottom-right\":new a.P(-w,-w),left:new a.P(ue,0),right:new a.P(-ue,0)}}if(ue instanceof a.P||Array.isArray(ue)){let w=a.P.convert(ue);return{center:w,top:w,\"top-left\":w,\"top-right\":w,bottom:w,\"bottom-left\":w,\"bottom-right\":w,left:w,right:w}}return{center:a.P.convert(ue.center||[0,0]),top:a.P.convert(ue.top||[0,0]),\"top-left\":a.P.convert(ue[\"top-left\"]||[0,0]),\"top-right\":a.P.convert(ue[\"top-right\"]||[0,0]),bottom:a.P.convert(ue.bottom||[0,0]),\"bottom-left\":a.P.convert(ue[\"bottom-left\"]||[0,0]),\"bottom-right\":a.P.convert(ue[\"bottom-right\"]||[0,0]),left:a.P.convert(ue.left||[0,0]),right:a.P.convert(ue.right||[0,0])}}return hc(new a.P(0,0))}let Ku=o;i.AJAXError=a.bh,i.Evented=a.E,i.LngLat=a.N,i.MercatorCoordinate=a.Z,i.Point=a.P,i.addProtocol=a.bi,i.config=a.a,i.removeProtocol=a.bj,i.AttributionControl=Na,i.BoxZoomHandler=ku,i.CanvasSource=Jt,i.CooperativeGesturesHandler=Qi,i.DoubleClickZoomHandler=ki,i.DragPanHandler=wn,i.DragRotateHandler=Nn,i.EdgeInsets=hu,i.FullscreenControl=class extends a.E{constructor(ue={}){super(),this._onFullscreenChange=()=>{var w;let B=window.document.fullscreenElement||window.document.mozFullScreenElement||window.document.webkitFullscreenElement||window.document.msFullscreenElement;for(;!((w=B==null?void 0:B.shadowRoot)===null||w===void 0)&&w.fullscreenElement;)B=B.shadowRoot.fullscreenElement;B===this._container!==this._fullscreen&&this._handleFullscreenChange()},this._onClickFullscreen=()=>{this._isFullscreen()?this._exitFullscreen():this._requestFullscreen()},this._fullscreen=!1,ue&&ue.container&&(ue.container instanceof HTMLElement?this._container=ue.container:a.w(\"Full screen control 'container' must be a DOM element.\")),\"onfullscreenchange\"in document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in document&&(this._fullscreenchange=\"MSFullscreenChange\")}onAdd(ue){return this._map=ue,this._container||(this._container=this._map.getContainer()),this._controlContainer=c.create(\"div\",\"maplibregl-ctrl maplibregl-ctrl-group\"),this._setupUI(),this._controlContainer}onRemove(){c.remove(this._controlContainer),this._map=null,window.document.removeEventListener(this._fullscreenchange,this._onFullscreenChange)}_setupUI(){let ue=this._fullscreenButton=c.create(\"button\",\"maplibregl-ctrl-fullscreen\",this._controlContainer);c.create(\"span\",\"maplibregl-ctrl-icon\",ue).setAttribute(\"aria-hidden\",\"true\"),ue.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),window.document.addEventListener(this._fullscreenchange,this._onFullscreenChange)}_updateTitle(){let ue=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",ue),this._fullscreenButton.title=ue}_getTitle(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")}_isFullscreen(){return this._fullscreen}_handleFullscreenChange(){this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"maplibregl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"maplibregl-ctrl-fullscreen\"),this._updateTitle(),this._fullscreen?(this.fire(new a.k(\"fullscreenstart\")),this._prevCooperativeGesturesEnabled=this._map.cooperativeGestures.isEnabled(),this._map.cooperativeGestures.disable()):(this.fire(new a.k(\"fullscreenend\")),this._prevCooperativeGesturesEnabled&&this._map.cooperativeGestures.enable())}_exitFullscreen(){window.document.exitFullscreen?window.document.exitFullscreen():window.document.mozCancelFullScreen?window.document.mozCancelFullScreen():window.document.msExitFullscreen?window.document.msExitFullscreen():window.document.webkitCancelFullScreen?window.document.webkitCancelFullScreen():this._togglePseudoFullScreen()}_requestFullscreen(){this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen?this._container.webkitRequestFullscreen():this._togglePseudoFullScreen()}_togglePseudoFullScreen(){this._container.classList.toggle(\"maplibregl-pseudo-fullscreen\"),this._handleFullscreenChange(),this._map.resize()}},i.GeoJSONSource=st,i.GeolocateControl=class extends a.E{constructor(ue){super(),this._onSuccess=w=>{if(this._map){if(this._isOutOfMapMaxBounds(w))return this._setErrorState(),this.fire(new a.k(\"outofmaxbounds\",w)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=w,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-background\");break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}this.options.showUserLocation&&this._watchState!==\"OFF\"&&this._updateMarker(w),this.options.trackUserLocation&&this._watchState!==\"ACTIVE_LOCK\"||this._updateCamera(w),this.options.showUserLocation&&this._dotElement.classList.remove(\"maplibregl-user-location-dot-stale\"),this.fire(new a.k(\"geolocate\",w)),this._finish()}},this._updateCamera=w=>{let B=new a.N(w.coords.longitude,w.coords.latitude),Q=w.coords.accuracy,ee=this._map.getBearing(),le=a.e({bearing:ee},this.options.fitBoundsOptions),qe=ce.fromLngLat(B,Q);this._map.fitBounds(qe,le,{geolocateSource:!0})},this._updateMarker=w=>{if(w){let B=new a.N(w.coords.longitude,w.coords.latitude);this._accuracyCircleMarker.setLngLat(B).addTo(this._map),this._userLocationDotMarker.setLngLat(B).addTo(this._map),this._accuracy=w.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},this._onZoom=()=>{this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},this._onError=w=>{if(this._map){if(this.options.trackUserLocation)if(w.code===1){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;let B=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=B,this._geolocateButton.setAttribute(\"aria-label\",B),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(w.code===3&&Uc)return;this._setErrorState()}this._watchState!==\"OFF\"&&this.options.showUserLocation&&this._dotElement.classList.add(\"maplibregl-user-location-dot-stale\"),this.fire(new a.k(\"error\",w)),this._finish()}},this._finish=()=>{this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},this._setupUI=()=>{this._map&&(this._container.addEventListener(\"contextmenu\",w=>w.preventDefault()),this._geolocateButton=c.create(\"button\",\"maplibregl-ctrl-geolocate\",this._container),c.create(\"span\",\"maplibregl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",\"true\"),this._geolocateButton.type=\"button\",this._geolocateButton.disabled=!0)},this._finishSetupUI=w=>{if(this._map){if(w===!1){a.w(\"Geolocation support is not available so the GeolocateControl will be disabled.\");let B=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=B,this._geolocateButton.setAttribute(\"aria-label\",B)}else{let B=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.disabled=!1,this._geolocateButton.title=B,this._geolocateButton.setAttribute(\"aria-label\",B)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=c.create(\"div\",\"maplibregl-user-location-dot\"),this._userLocationDotMarker=new Yu({element:this._dotElement}),this._circleElement=c.create(\"div\",\"maplibregl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Yu({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",()=>this.trigger()),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",B=>{B.geolocateSource||this._watchState!==\"ACTIVE_LOCK\"||B.originalEvent&&B.originalEvent.type===\"resize\"||(this._watchState=\"BACKGROUND\",this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active\"),this.fire(new a.k(\"trackuserlocationend\")),this.fire(new a.k(\"userlocationlostfocus\")))})}},this.options=a.e({},Nc,ue)}onAdd(ue){return this._map=ue,this._container=c.create(\"div\",\"maplibregl-ctrl maplibregl-ctrl-group\"),this._setupUI(),function(){return a._(this,arguments,void 0,function*(w=!1){if(ys!==void 0&&!w)return ys;if(window.navigator.permissions===void 0)return ys=!!window.navigator.geolocation,ys;try{ys=(yield window.navigator.permissions.query({name:\"geolocation\"})).state!==\"denied\"}catch(B){ys=!!window.navigator.geolocation}return ys})}().then(w=>this._finishSetupUI(w)),this._container}onRemove(){this._geolocationWatchID!==void 0&&(window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),c.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,pu=0,Uc=!1}_isOutOfMapMaxBounds(ue){let w=this._map.getMaxBounds(),B=ue.coords;return w&&(B.longitude<w.getWest()||B.longitude>w.getEast()||B.latitude<w.getSouth()||B.latitude>w.getNorth())}_setErrorState(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-waiting\");break;case\"ACTIVE_ERROR\":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}}_updateCircleRadius(){let ue=this._map.getBounds(),w=ue.getSouthEast(),B=ue.getNorthEast(),Q=w.distanceTo(B),ee=Math.ceil(this._accuracy/(Q/this._map._container.clientHeight)*2);this._circleElement.style.width=`${ee}px`,this._circleElement.style.height=`${ee}px`}trigger(){if(!this._setup)return a.w(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new a.k(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":pu--,Uc=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background-error\"),this.fire(new a.k(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new a.k(\"trackuserlocationstart\")),this.fire(new a.k(\"userlocationfocus\"));break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-active\");break;case\"OFF\":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}if(this._watchState===\"OFF\"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){let ue;this._geolocateButton.classList.add(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),pu++,pu>1?(ue={maximumAge:6e5,timeout:0},Uc=!0):(ue=this.options.positionOptions,Uc=!1),this._geolocationWatchID=window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,ue)}}else window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0}_clearWatch(){window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"maplibregl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)}},i.Hash=Ah,i.ImageSource=Gt,i.KeyboardHandler=Wt,i.LngLatBounds=ce,i.LogoControl=Yn,i.Map=class extends Ra{constructor(ue){a.bf.mark(a.bg.create);let w=Object.assign(Object.assign({},Ws),ue);if(w.minZoom!=null&&w.maxZoom!=null&&w.minZoom>w.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(w.minPitch!=null&&w.maxPitch!=null&&w.minPitch>w.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(w.minPitch!=null&&w.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(w.maxPitch!=null&&w.maxPitch>85)throw new Error(\"maxPitch must be less than or equal to 85\");if(super(new nl(w.minZoom,w.maxZoom,w.minPitch,w.maxPitch,w.renderWorldCopies),{bearingSnap:w.bearingSnap}),this._idleTriggered=!1,this._crossFadingFactor=1,this._renderTaskQueue=new Dn,this._controls=[],this._mapId=a.a4(),this._contextLost=B=>{B.preventDefault(),this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this.fire(new a.k(\"webglcontextlost\",{originalEvent:B}))},this._contextRestored=B=>{this._setupPainter(),this.resize(),this._update(),this.fire(new a.k(\"webglcontextrestored\",{originalEvent:B}))},this._onMapScroll=B=>{if(B.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},this._onWindowOnline=()=>{this._update()},this._interactive=w.interactive,this._maxTileCacheSize=w.maxTileCacheSize,this._maxTileCacheZoomLevels=w.maxTileCacheZoomLevels,this._failIfMajorPerformanceCaveat=w.failIfMajorPerformanceCaveat===!0,this._preserveDrawingBuffer=w.preserveDrawingBuffer===!0,this._antialias=w.antialias===!0,this._trackResize=w.trackResize===!0,this._bearingSnap=w.bearingSnap,this._refreshExpiredTiles=w.refreshExpiredTiles===!0,this._fadeDuration=w.fadeDuration,this._crossSourceCollisions=w.crossSourceCollisions===!0,this._collectResourceTiming=w.collectResourceTiming===!0,this._locale=Object.assign(Object.assign({},Ho),w.locale),this._clickTolerance=w.clickTolerance,this._overridePixelRatio=w.pixelRatio,this._maxCanvasSize=w.maxCanvasSize,this.transformCameraUpdate=w.transformCameraUpdate,this.cancelPendingTileRequestsWhileZooming=w.cancelPendingTileRequestsWhileZooming===!0,this._imageQueueHandle=p.addThrottleControl(()=>this.isMoving()),this._requestManager=new k(w.transformRequest),typeof w.container==\"string\"){if(this._container=document.getElementById(w.container),!this._container)throw new Error(`Container '${w.container}' not found.`)}else{if(!(w.container instanceof HTMLElement))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=w.container}if(w.maxBounds&&this.setMaxBounds(w.maxBounds),this._setupContainer(),this._setupPainter(),this.on(\"move\",()=>this._update(!1)).on(\"moveend\",()=>this._update(!1)).on(\"zoom\",()=>this._update(!0)).on(\"terrain\",()=>{this.painter.terrainFacilitator.dirty=!0,this._update(!0)}).once(\"idle\",()=>{this._idleTriggered=!0}),typeof window!=\"undefined\"){addEventListener(\"online\",this._onWindowOnline,!1);let B=!1,Q=nh(ee=>{this._trackResize&&!this._removed&&(this.resize(ee),this.redraw())},50);this._resizeObserver=new ResizeObserver(ee=>{B?Q(ee):B=!0}),this._resizeObserver.observe(this._container)}this.handlers=new Ca(this,w),this._hash=w.hash&&new Ah(typeof w.hash==\"string\"&&w.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:w.center,zoom:w.zoom,bearing:w.bearing,pitch:w.pitch}),w.bounds&&(this.resize(),this.fitBounds(w.bounds,a.e({},w.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=w.localIdeographFontFamily,this._validateStyle=w.validateStyle,w.style&&this.setStyle(w.style,{localIdeographFontFamily:w.localIdeographFontFamily}),w.attributionControl&&this.addControl(new Na(typeof w.attributionControl==\"boolean\"?void 0:w.attributionControl)),w.maplibreLogo&&this.addControl(new Yn,w.logoPosition),this.on(\"style.load\",()=>{this.transform.unmodified&&this.jumpTo(this.style.stylesheet)}),this.on(\"data\",B=>{this._update(B.dataType===\"style\"),this.fire(new a.k(`${B.dataType}data`,B))}),this.on(\"dataloading\",B=>{this.fire(new a.k(`${B.dataType}dataloading`,B))}),this.on(\"dataabort\",B=>{this.fire(new a.k(\"sourcedataabort\",B))})}_getMapId(){return this._mapId}addControl(ue,w){if(w===void 0&&(w=ue.getDefaultPosition?ue.getDefaultPosition():\"top-right\"),!ue||!ue.onAdd)return this.fire(new a.j(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));let B=ue.onAdd(this);this._controls.push(ue);let Q=this._controlPositions[w];return w.indexOf(\"bottom\")!==-1?Q.insertBefore(B,Q.firstChild):Q.appendChild(B),this}removeControl(ue){if(!ue||!ue.onRemove)return this.fire(new a.j(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));let w=this._controls.indexOf(ue);return w>-1&&this._controls.splice(w,1),ue.onRemove(this),this}hasControl(ue){return this._controls.indexOf(ue)>-1}calculateCameraOptionsFromTo(ue,w,B,Q){return Q==null&&this.terrain&&(Q=this.terrain.getElevationForLngLatZoom(B,this.transform.tileZoom)),super.calculateCameraOptionsFromTo(ue,w,B,Q)}resize(ue){var w;let B=this._containerDimensions(),Q=B[0],ee=B[1],le=this._getClampedPixelRatio(Q,ee);if(this._resizeCanvas(Q,ee,le),this.painter.resize(Q,ee,le),this.painter.overLimit()){let Xe=this.painter.context.gl;this._maxCanvasSize=[Xe.drawingBufferWidth,Xe.drawingBufferHeight];let ot=this._getClampedPixelRatio(Q,ee);this._resizeCanvas(Q,ee,ot),this.painter.resize(Q,ee,ot)}this.transform.resize(Q,ee),(w=this._requestedCameraState)===null||w===void 0||w.resize(Q,ee);let qe=!this._moving;return qe&&(this.stop(),this.fire(new a.k(\"movestart\",ue)).fire(new a.k(\"move\",ue))),this.fire(new a.k(\"resize\",ue)),qe&&this.fire(new a.k(\"moveend\",ue)),this}_getClampedPixelRatio(ue,w){let{0:B,1:Q}=this._maxCanvasSize,ee=this.getPixelRatio(),le=ue*ee,qe=w*ee;return Math.min(le>B?B/le:1,qe>Q?Q/qe:1)*ee}getPixelRatio(){var ue;return(ue=this._overridePixelRatio)!==null&&ue!==void 0?ue:devicePixelRatio}setPixelRatio(ue){this._overridePixelRatio=ue,this.resize()}getBounds(){return this.transform.getBounds()}getMaxBounds(){return this.transform.getMaxBounds()}setMaxBounds(ue){return this.transform.setMaxBounds(ce.convert(ue)),this._update()}setMinZoom(ue){if((ue=ue==null?-2:ue)>=-2&&ue<=this.transform.maxZoom)return this.transform.minZoom=ue,this._update(),this.getZoom()<ue&&this.setZoom(ue),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")}getMinZoom(){return this.transform.minZoom}setMaxZoom(ue){if((ue=ue==null?22:ue)>=this.transform.minZoom)return this.transform.maxZoom=ue,this._update(),this.getZoom()>ue&&this.setZoom(ue),this;throw new Error(\"maxZoom must be greater than the current minZoom\")}getMaxZoom(){return this.transform.maxZoom}setMinPitch(ue){if((ue=ue==null?0:ue)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(ue>=0&&ue<=this.transform.maxPitch)return this.transform.minPitch=ue,this._update(),this.getPitch()<ue&&this.setPitch(ue),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")}getMinPitch(){return this.transform.minPitch}setMaxPitch(ue){if((ue=ue==null?60:ue)>85)throw new Error(\"maxPitch must be less than or equal to 85\");if(ue>=this.transform.minPitch)return this.transform.maxPitch=ue,this._update(),this.getPitch()>ue&&this.setPitch(ue),this;throw new Error(\"maxPitch must be greater than the current minPitch\")}getMaxPitch(){return this.transform.maxPitch}getRenderWorldCopies(){return this.transform.renderWorldCopies}setRenderWorldCopies(ue){return this.transform.renderWorldCopies=ue,this._update()}project(ue){return this.transform.locationPoint(a.N.convert(ue),this.style&&this.terrain)}unproject(ue){return this.transform.pointLocation(a.P.convert(ue),this.terrain)}isMoving(){var ue;return this._moving||((ue=this.handlers)===null||ue===void 0?void 0:ue.isMoving())}isZooming(){var ue;return this._zooming||((ue=this.handlers)===null||ue===void 0?void 0:ue.isZooming())}isRotating(){var ue;return this._rotating||((ue=this.handlers)===null||ue===void 0?void 0:ue.isRotating())}_createDelegatedListener(ue,w,B){if(ue===\"mouseenter\"||ue===\"mouseover\"){let Q=!1;return{layers:w,listener:B,delegates:{mousemove:le=>{let qe=w.filter(ot=>this.getLayer(ot)),Xe=qe.length!==0?this.queryRenderedFeatures(le.point,{layers:qe}):[];Xe.length?Q||(Q=!0,B.call(this,new jl(ue,this,le.originalEvent,{features:Xe}))):Q=!1},mouseout:()=>{Q=!1}}}}if(ue===\"mouseleave\"||ue===\"mouseout\"){let Q=!1;return{layers:w,listener:B,delegates:{mousemove:qe=>{let Xe=w.filter(ot=>this.getLayer(ot));(Xe.length!==0?this.queryRenderedFeatures(qe.point,{layers:Xe}):[]).length?Q=!0:Q&&(Q=!1,B.call(this,new jl(ue,this,qe.originalEvent)))},mouseout:qe=>{Q&&(Q=!1,B.call(this,new jl(ue,this,qe.originalEvent)))}}}}{let Q=ee=>{let le=w.filter(Xe=>this.getLayer(Xe)),qe=le.length!==0?this.queryRenderedFeatures(ee.point,{layers:le}):[];qe.length&&(ee.features=qe,B.call(this,ee),delete ee.features)};return{layers:w,listener:B,delegates:{[ue]:Q}}}}_saveDelegatedListener(ue,w){this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[ue]=this._delegatedListeners[ue]||[],this._delegatedListeners[ue].push(w)}_removeDelegatedListener(ue,w,B){if(!this._delegatedListeners||!this._delegatedListeners[ue])return;let Q=this._delegatedListeners[ue];for(let ee=0;ee<Q.length;ee++){let le=Q[ee];if(le.listener===B&&le.layers.length===w.length&&le.layers.every(qe=>w.includes(qe))){for(let qe in le.delegates)this.off(qe,le.delegates[qe]);return void Q.splice(ee,1)}}}on(ue,w,B){if(B===void 0)return super.on(ue,w);let Q=this._createDelegatedListener(ue,typeof w==\"string\"?[w]:w,B);this._saveDelegatedListener(ue,Q);for(let ee in Q.delegates)this.on(ee,Q.delegates[ee]);return this}once(ue,w,B){if(B===void 0)return super.once(ue,w);let Q=typeof w==\"string\"?[w]:w,ee=this._createDelegatedListener(ue,Q,B);for(let le in ee.delegates){let qe=ee.delegates[le];ee.delegates[le]=(...Xe)=>{this._removeDelegatedListener(ue,Q,B),qe(...Xe)}}this._saveDelegatedListener(ue,ee);for(let le in ee.delegates)this.once(le,ee.delegates[le]);return this}off(ue,w,B){return B===void 0?super.off(ue,w):(this._removeDelegatedListener(ue,typeof w==\"string\"?[w]:w,B),this)}queryRenderedFeatures(ue,w){if(!this.style)return[];let B,Q=ue instanceof a.P||Array.isArray(ue),ee=Q?ue:[[0,0],[this.transform.width,this.transform.height]];if(w=w||(Q?{}:ue)||{},ee instanceof a.P||typeof ee[0]==\"number\")B=[a.P.convert(ee)];else{let le=a.P.convert(ee[0]),qe=a.P.convert(ee[1]);B=[le,new a.P(qe.x,le.y),qe,new a.P(le.x,qe.y),le]}return this.style.queryRenderedFeatures(B,w,this.transform)}querySourceFeatures(ue,w){return this.style.querySourceFeatures(ue,w)}setStyle(ue,w){return(w=a.e({},{localIdeographFontFamily:this._localIdeographFontFamily,validate:this._validateStyle},w)).diff!==!1&&w.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&ue?(this._diffStyle(ue,w),this):(this._localIdeographFontFamily=w.localIdeographFontFamily,this._updateStyle(ue,w))}setTransformRequest(ue){return this._requestManager.setTransformRequest(ue),this}_getUIString(ue){let w=this._locale[ue];if(w==null)throw new Error(`Missing UI string '${ue}'`);return w}_updateStyle(ue,w){if(w.transformStyle&&this.style&&!this.style._loaded)return void this.style.once(\"style.load\",()=>this._updateStyle(ue,w));let B=this.style&&w.transformStyle?this.style.serialize():void 0;return this.style&&(this.style.setEventedParent(null),this.style._remove(!ue)),ue?(this.style=new Ga(this,w||{}),this.style.setEventedParent(this,{style:this.style}),typeof ue==\"string\"?this.style.loadURL(ue,w,B):this.style.loadJSON(ue,w,B),this):(delete this.style,this)}_lazyInitEmptyStyle(){this.style||(this.style=new Ga(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())}_diffStyle(ue,w){if(typeof ue==\"string\"){let B=this._requestManager.transformRequest(ue,\"Style\");a.h(B,new AbortController).then(Q=>{this._updateDiff(Q.data,w)}).catch(Q=>{Q&&this.fire(new a.j(Q))})}else typeof ue==\"object\"&&this._updateDiff(ue,w)}_updateDiff(ue,w){try{this.style.setState(ue,w)&&this._update(!0)}catch(B){a.w(`Unable to perform style diff: ${B.message||B.error||B}.  Rebuilding the style from scratch.`),this._updateStyle(ue,w)}}getStyle(){if(this.style)return this.style.serialize()}isStyleLoaded(){return this.style?this.style.loaded():a.w(\"There is no style added to the map.\")}addSource(ue,w){return this._lazyInitEmptyStyle(),this.style.addSource(ue,w),this._update(!0)}isSourceLoaded(ue){let w=this.style&&this.style.sourceCaches[ue];if(w!==void 0)return w.loaded();this.fire(new a.j(new Error(`There is no source with ID '${ue}'`)))}setTerrain(ue){if(this.style._checkLoaded(),this._terrainDataCallback&&this.style.off(\"data\",this._terrainDataCallback),ue){let w=this.style.sourceCaches[ue.source];if(!w)throw new Error(`cannot load terrain, because there exists no source with ID: ${ue.source}`);this.terrain===null&&w.reload();for(let B in this.style._layers){let Q=this.style._layers[B];Q.type===\"hillshade\"&&Q.source===ue.source&&a.w(\"You are using the same source for a hillshade layer and for 3D terrain. Please consider using two separate sources to improve rendering quality.\")}this.terrain=new Xo(this.painter,w,ue),this.painter.renderToTexture=new ws(this.painter,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._terrainDataCallback=B=>{B.dataType===\"style\"?this.terrain.sourceCache.freeRtt():B.dataType===\"source\"&&B.tile&&(B.sourceId!==ue.source||this._elevationFreeze||(this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom)),this.terrain.sourceCache.freeRtt(B.tile.tileID))},this.style.on(\"data\",this._terrainDataCallback)}else this.terrain&&this.terrain.sourceCache.destruct(),this.terrain=null,this.painter.renderToTexture&&this.painter.renderToTexture.destruct(),this.painter.renderToTexture=null,this.transform.minElevationForCurrentTile=0,this.transform.elevation=0;return this.fire(new a.k(\"terrain\",{terrain:ue})),this}getTerrain(){var ue,w;return(w=(ue=this.terrain)===null||ue===void 0?void 0:ue.options)!==null&&w!==void 0?w:null}areTilesLoaded(){let ue=this.style&&this.style.sourceCaches;for(let w in ue){let B=ue[w]._tiles;for(let Q in B){let ee=B[Q];if(ee.state!==\"loaded\"&&ee.state!==\"errored\")return!1}}return!0}removeSource(ue){return this.style.removeSource(ue),this._update(!0)}getSource(ue){return this.style.getSource(ue)}addImage(ue,w,B={}){let{pixelRatio:Q=1,sdf:ee=!1,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt}=B;if(this._lazyInitEmptyStyle(),!(w instanceof HTMLImageElement||a.b(w))){if(w.width===void 0||w.height===void 0)return this.fire(new a.j(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));{let{width:Yt,height:Kt,data:xr}=w,Ir=w;return this.style.addImage(ue,{data:new a.R({width:Yt,height:Kt},new Uint8Array(xr)),pixelRatio:Q,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt,sdf:ee,version:0,userImage:Ir}),Ir.onAdd&&Ir.onAdd(this,ue),this}}{let{width:Yt,height:Kt,data:xr}=u.getImageData(w);this.style.addImage(ue,{data:new a.R({width:Yt,height:Kt},xr),pixelRatio:Q,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt,sdf:ee,version:0})}}updateImage(ue,w){let B=this.style.getImage(ue);if(!B)return this.fire(new a.j(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));let Q=w instanceof HTMLImageElement||a.b(w)?u.getImageData(w):w,{width:ee,height:le,data:qe}=Q;if(ee===void 0||le===void 0)return this.fire(new a.j(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(ee!==B.data.width||le!==B.data.height)return this.fire(new a.j(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));let Xe=!(w instanceof HTMLImageElement||a.b(w));return B.data.replace(qe,Xe),this.style.updateImage(ue,B),this}getImage(ue){return this.style.getImage(ue)}hasImage(ue){return ue?!!this.style.getImage(ue):(this.fire(new a.j(new Error(\"Missing required image id\"))),!1)}removeImage(ue){this.style.removeImage(ue)}loadImage(ue){return p.getImage(this._requestManager.transformRequest(ue,\"Image\"),new AbortController)}listImages(){return this.style.listImages()}addLayer(ue,w){return this._lazyInitEmptyStyle(),this.style.addLayer(ue,w),this._update(!0)}moveLayer(ue,w){return this.style.moveLayer(ue,w),this._update(!0)}removeLayer(ue){return this.style.removeLayer(ue),this._update(!0)}getLayer(ue){return this.style.getLayer(ue)}getLayersOrder(){return this.style.getLayersOrder()}setLayerZoomRange(ue,w,B){return this.style.setLayerZoomRange(ue,w,B),this._update(!0)}setFilter(ue,w,B={}){return this.style.setFilter(ue,w,B),this._update(!0)}getFilter(ue){return this.style.getFilter(ue)}setPaintProperty(ue,w,B,Q={}){return this.style.setPaintProperty(ue,w,B,Q),this._update(!0)}getPaintProperty(ue,w){return this.style.getPaintProperty(ue,w)}setLayoutProperty(ue,w,B,Q={}){return this.style.setLayoutProperty(ue,w,B,Q),this._update(!0)}getLayoutProperty(ue,w){return this.style.getLayoutProperty(ue,w)}setGlyphs(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setGlyphs(ue,w),this._update(!0)}getGlyphs(){return this.style.getGlyphsUrl()}addSprite(ue,w,B={}){return this._lazyInitEmptyStyle(),this.style.addSprite(ue,w,B,Q=>{Q||this._update(!0)}),this}removeSprite(ue){return this._lazyInitEmptyStyle(),this.style.removeSprite(ue),this._update(!0)}getSprite(){return this.style.getSprite()}setSprite(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setSprite(ue,w,B=>{B||this._update(!0)}),this}setLight(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setLight(ue,w),this._update(!0)}getLight(){return this.style.getLight()}setSky(ue){return this._lazyInitEmptyStyle(),this.style.setSky(ue),this._update(!0)}getSky(){return this.style.getSky()}setFeatureState(ue,w){return this.style.setFeatureState(ue,w),this._update()}removeFeatureState(ue,w){return this.style.removeFeatureState(ue,w),this._update()}getFeatureState(ue){return this.style.getFeatureState(ue)}getContainer(){return this._container}getCanvasContainer(){return this._canvasContainer}getCanvas(){return this._canvas}_containerDimensions(){let ue=0,w=0;return this._container&&(ue=this._container.clientWidth||400,w=this._container.clientHeight||300),[ue,w]}_setupContainer(){let ue=this._container;ue.classList.add(\"maplibregl-map\");let w=this._canvasContainer=c.create(\"div\",\"maplibregl-canvas-container\",ue);this._interactive&&w.classList.add(\"maplibregl-interactive\"),this._canvas=c.create(\"canvas\",\"maplibregl-canvas\",w),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",this._interactive?\"0\":\"-1\"),this._canvas.setAttribute(\"aria-label\",this._getUIString(\"Map.Title\")),this._canvas.setAttribute(\"role\",\"region\");let B=this._containerDimensions(),Q=this._getClampedPixelRatio(B[0],B[1]);this._resizeCanvas(B[0],B[1],Q);let ee=this._controlContainer=c.create(\"div\",\"maplibregl-control-container\",ue),le=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(qe=>{le[qe]=c.create(\"div\",`maplibregl-ctrl-${qe} `,ee)}),this._container.addEventListener(\"scroll\",this._onMapScroll,!1)}_resizeCanvas(ue,w,B){this._canvas.width=Math.floor(B*ue),this._canvas.height=Math.floor(B*w),this._canvas.style.width=`${ue}px`,this._canvas.style.height=`${w}px`}_setupPainter(){let ue={alpha:!0,stencil:!0,depth:!0,failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1},w=null;this._canvas.addEventListener(\"webglcontextcreationerror\",Q=>{w={requestedAttributes:ue},Q&&(w.statusMessage=Q.statusMessage,w.type=Q.type)},{once:!0});let B=this._canvas.getContext(\"webgl2\",ue)||this._canvas.getContext(\"webgl\",ue);if(!B){let Q=\"Failed to initialize WebGL\";throw w?(w.message=Q,new Error(JSON.stringify(w))):new Error(Q)}this.painter=new Dc(B,this.transform),f.testSupport(B)}loaded(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()}_update(ue){return this.style&&this.style._loaded?(this._styleDirty=this._styleDirty||ue,this._sourcesDirty=!0,this.triggerRepaint(),this):this}_requestRenderFrame(ue){return this._update(),this._renderTaskQueue.add(ue)}_cancelRenderFrame(ue){this._renderTaskQueue.remove(ue)}_render(ue){let w=this._idleTriggered?this._fadeDuration:0;if(this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(ue),this._removed)return;let B=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;let ee=this.transform.zoom,le=u.now();this.style.zoomHistory.update(ee,le);let qe=new a.z(ee,{now:le,fadeDuration:w,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),Xe=qe.crossFadingFactor();Xe===1&&Xe===this._crossFadingFactor||(B=!0,this._crossFadingFactor=Xe),this.style.update(qe)}this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.terrain?(this.terrain.sourceCache.update(this.transform,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._elevationFreeze||(this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom))):(this.transform.minElevationForCurrentTile=0,this.transform.elevation=0),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,w,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:w,showPadding:this.showPadding}),this.fire(new a.k(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,a.bf.mark(a.bg.load),this.fire(new a.k(\"load\"))),this.style&&(this.style.hasTransitions()||B)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles();let Q=this._sourcesDirty||this._styleDirty||this._placementDirty;return Q||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new a.k(\"idle\")),!this._loaded||this._fullyLoaded||Q||(this._fullyLoaded=!0,a.bf.mark(a.bg.fullLoad)),this}redraw(){return this.style&&(this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._render(0)),this}remove(){var ue;this._hash&&this._hash.remove();for(let B of this._controls)B.onRemove(this);this._controls=[],this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),typeof window!=\"undefined\"&&removeEventListener(\"online\",this._onWindowOnline,!1),p.removeThrottleControl(this._imageQueueHandle),(ue=this._resizeObserver)===null||ue===void 0||ue.disconnect();let w=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");w!=null&&w.loseContext&&w.loseContext(),this._canvas.removeEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.removeEventListener(\"webglcontextlost\",this._contextLost,!1),c.remove(this._canvasContainer),c.remove(this._controlContainer),this._container.classList.remove(\"maplibregl-map\"),a.bf.clearMetrics(),this._removed=!0,this.fire(new a.k(\"remove\"))}triggerRepaint(){this.style&&!this._frameRequest&&(this._frameRequest=new AbortController,u.frameAsync(this._frameRequest).then(ue=>{a.bf.frame(ue),this._frameRequest=null,this._render(ue)}).catch(()=>{}))}get showTileBoundaries(){return!!this._showTileBoundaries}set showTileBoundaries(ue){this._showTileBoundaries!==ue&&(this._showTileBoundaries=ue,this._update())}get showPadding(){return!!this._showPadding}set showPadding(ue){this._showPadding!==ue&&(this._showPadding=ue,this._update())}get showCollisionBoxes(){return!!this._showCollisionBoxes}set showCollisionBoxes(ue){this._showCollisionBoxes!==ue&&(this._showCollisionBoxes=ue,ue?this.style._generateCollisionBoxes():this._update())}get showOverdrawInspector(){return!!this._showOverdrawInspector}set showOverdrawInspector(ue){this._showOverdrawInspector!==ue&&(this._showOverdrawInspector=ue,this._update())}get repaint(){return!!this._repaint}set repaint(ue){this._repaint!==ue&&(this._repaint=ue,this.triggerRepaint())}get vertices(){return!!this._vertices}set vertices(ue){this._vertices=ue,this._update()}get version(){return ml}getCameraTargetElevation(){return this.transform.elevation}},i.MapMouseEvent=jl,i.MapTouchEvent=lf,i.MapWheelEvent=Hh,i.Marker=Yu,i.NavigationControl=class{constructor(ue){this._updateZoomButtons=()=>{let w=this._map.getZoom(),B=w===this._map.getMaxZoom(),Q=w===this._map.getMinZoom();this._zoomInButton.disabled=B,this._zoomOutButton.disabled=Q,this._zoomInButton.setAttribute(\"aria-disabled\",B.toString()),this._zoomOutButton.setAttribute(\"aria-disabled\",Q.toString())},this._rotateCompassArrow=()=>{let w=this.options.visualizePitch?`scale(${1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)}) rotateX(${this._map.transform.pitch}deg) rotateZ(${this._map.transform.angle*(180/Math.PI)}deg)`:`rotate(${this._map.transform.angle*(180/Math.PI)}deg)`;this._compassIcon.style.transform=w},this._setButtonTitle=(w,B)=>{let Q=this._map._getUIString(`NavigationControl.${B}`);w.title=Q,w.setAttribute(\"aria-label\",Q)},this.options=a.e({},va,ue),this._container=c.create(\"div\",\"maplibregl-ctrl maplibregl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",w=>w.preventDefault()),this.options.showZoom&&(this._zoomInButton=this._createButton(\"maplibregl-ctrl-zoom-in\",w=>this._map.zoomIn({},{originalEvent:w})),c.create(\"span\",\"maplibregl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",\"true\"),this._zoomOutButton=this._createButton(\"maplibregl-ctrl-zoom-out\",w=>this._map.zoomOut({},{originalEvent:w})),c.create(\"span\",\"maplibregl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",\"true\")),this.options.showCompass&&(this._compass=this._createButton(\"maplibregl-ctrl-compass\",w=>{this.options.visualizePitch?this._map.resetNorthPitch({},{originalEvent:w}):this._map.resetNorth({},{originalEvent:w})}),this._compassIcon=c.create(\"span\",\"maplibregl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",\"true\"))}onAdd(ue){return this._map=ue,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new no(this._map,this._compass,this.options.visualizePitch)),this._container}onRemove(){c.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map}_createButton(ue,w){let B=c.create(\"button\",ue,this._container);return B.type=\"button\",B.addEventListener(\"click\",w),B}},i.Popup=class extends a.E{constructor(ue){super(),this.remove=()=>(this._content&&c.remove(this._content),this._container&&(c.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),this._map._canvasContainer.classList.remove(\"maplibregl-track-pointer\"),delete this._map,this.fire(new a.k(\"close\"))),this),this._onMouseUp=w=>{this._update(w.point)},this._onMouseMove=w=>{this._update(w.point)},this._onDrag=w=>{this._update(w.point)},this._update=w=>{var B;if(!this._map||!this._lngLat&&!this._trackPointer||!this._content)return;if(!this._container){if(this._container=c.create(\"div\",\"maplibregl-popup\",this._map.getContainer()),this._tip=c.create(\"div\",\"maplibregl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className)for(let Xe of this.options.className.split(\" \"))this._container.classList.add(Xe);this._closeButton&&this._closeButton.setAttribute(\"aria-label\",this._map._getUIString(\"Popup.Close\")),this._trackPointer&&this._container.classList.add(\"maplibregl-popup-track-pointer\")}if(this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._lngLat=this._map.transform.renderWorldCopies&&!this._trackPointer?rs(this._lngLat,this._flatPos,this._map.transform):(B=this._lngLat)===null||B===void 0?void 0:B.wrap(),this._trackPointer&&!w)return;let Q=this._flatPos=this._pos=this._trackPointer&&w?w:this._map.project(this._lngLat);this._map.terrain&&(this._flatPos=this._trackPointer&&w?w:this._map.transform.locationPoint(this._lngLat));let ee=this.options.anchor,le=hc(this.options.offset);if(!ee){let Xe=this._container.offsetWidth,ot=this._container.offsetHeight,Tt;Tt=Q.y+le.bottom.y<ot?[\"top\"]:Q.y>this._map.transform.height-ot?[\"bottom\"]:[],Q.x<Xe/2?Tt.push(\"left\"):Q.x>this._map.transform.width-Xe/2&&Tt.push(\"right\"),ee=Tt.length===0?\"bottom\":Tt.join(\"-\")}let qe=Q.add(le[ee]);this.options.subpixelPositioning||(qe=qe.round()),c.setTransform(this._container,`${$l[ee]} translate(${qe.x}px,${qe.y}px)`),Cu(this._container,ee,\"popup\")},this._onClose=()=>{this.remove()},this.options=a.e(Object.create(oo),ue)}addTo(ue){return this._map&&this.remove(),this._map=ue,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"maplibregl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"maplibregl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new a.k(\"open\")),this}isOpen(){return!!this._map}getLngLat(){return this._lngLat}setLngLat(ue){return this._lngLat=a.N.convert(ue),this._pos=null,this._flatPos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"maplibregl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"maplibregl-track-pointer\")),this}trackPointer(){return this._trackPointer=!0,this._pos=null,this._flatPos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"maplibregl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"maplibregl-track-pointer\")),this}getElement(){return this._container}setText(ue){return this.setDOMContent(document.createTextNode(ue))}setHTML(ue){let w=document.createDocumentFragment(),B=document.createElement(\"body\"),Q;for(B.innerHTML=ue;Q=B.firstChild,Q;)w.appendChild(Q);return this.setDOMContent(w)}getMaxWidth(){var ue;return(ue=this._container)===null||ue===void 0?void 0:ue.style.maxWidth}setMaxWidth(ue){return this.options.maxWidth=ue,this._update(),this}setDOMContent(ue){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=c.create(\"div\",\"maplibregl-popup-content\",this._container);return this._content.appendChild(ue),this._createCloseButton(),this._update(),this._focusFirstElement(),this}addClassName(ue){return this._container&&this._container.classList.add(ue),this}removeClassName(ue){return this._container&&this._container.classList.remove(ue),this}setOffset(ue){return this.options.offset=ue,this._update(),this}toggleClassName(ue){if(this._container)return this._container.classList.toggle(ue)}setSubpixelPositioning(ue){this.options.subpixelPositioning=ue}_createCloseButton(){this.options.closeButton&&(this._closeButton=c.create(\"button\",\"maplibregl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))}_focusFirstElement(){if(!this.options.focusAfterOpen||!this._container)return;let ue=this._container.querySelector(Vc);ue&&ue.focus()}},i.RasterDEMTileSource=Zt,i.RasterTileSource=pt,i.ScaleControl=class{constructor(ue){this._onMove=()=>{Ac(this._map,this._container,this.options)},this.setUnit=w=>{this.options.unit=w,Ac(this._map,this._container,this.options)},this.options=Object.assign(Object.assign({},xu),ue)}getDefaultPosition(){return\"bottom-left\"}onAdd(ue){return this._map=ue,this._container=c.create(\"div\",\"maplibregl-ctrl maplibregl-ctrl-scale\",ue.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container}onRemove(){c.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0}},i.ScrollZoomHandler=Kr,i.Style=Ga,i.TerrainControl=class{constructor(ue){this._toggleTerrain=()=>{this._map.getTerrain()?this._map.setTerrain(null):this._map.setTerrain(this.options),this._updateTerrainIcon()},this._updateTerrainIcon=()=>{this._terrainButton.classList.remove(\"maplibregl-ctrl-terrain\"),this._terrainButton.classList.remove(\"maplibregl-ctrl-terrain-enabled\"),this._map.terrain?(this._terrainButton.classList.add(\"maplibregl-ctrl-terrain-enabled\"),this._terrainButton.title=this._map._getUIString(\"TerrainControl.Disable\")):(this._terrainButton.classList.add(\"maplibregl-ctrl-terrain\"),this._terrainButton.title=this._map._getUIString(\"TerrainControl.Enable\"))},this.options=ue}onAdd(ue){return this._map=ue,this._container=c.create(\"div\",\"maplibregl-ctrl maplibregl-ctrl-group\"),this._terrainButton=c.create(\"button\",\"maplibregl-ctrl-terrain\",this._container),c.create(\"span\",\"maplibregl-ctrl-icon\",this._terrainButton).setAttribute(\"aria-hidden\",\"true\"),this._terrainButton.type=\"button\",this._terrainButton.addEventListener(\"click\",this._toggleTerrain),this._updateTerrainIcon(),this._map.on(\"terrain\",this._updateTerrainIcon),this._container}onRemove(){c.remove(this._container),this._map.off(\"terrain\",this._updateTerrainIcon),this._map=void 0}},i.TwoFingersTouchPitchHandler=Bc,i.TwoFingersTouchRotateHandler=cf,i.TwoFingersTouchZoomHandler=vu,i.TwoFingersTouchZoomRotateHandler=Yi,i.VectorTileSource=ut,i.VideoSource=Nt,i.addSourceType=(ue,w)=>a._(void 0,void 0,void 0,function*(){if(wr(ue))throw new Error(`A source type called \"${ue}\" already exists.`);((B,Q)=>{sr[B]=Q})(ue,w)}),i.clearPrewarmedResources=function(){let ue=me;ue&&(ue.isPreloaded()&&ue.numActive()===1?(ue.release(_e),me=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},i.getMaxParallelImageRequests=function(){return a.a.MAX_PARALLEL_IMAGE_REQUESTS},i.getRTLTextPluginStatus=function(){return Qt().getRTLTextPluginStatus()},i.getVersion=function(){return Ku},i.getWorkerCount=function(){return Ee.workerCount},i.getWorkerUrl=function(){return a.a.WORKER_URL},i.importScriptInWorkers=function(ue){return Ae().broadcast(\"IS\",ue)},i.prewarm=function(){Se().acquire(_e)},i.setMaxParallelImageRequests=function(ue){a.a.MAX_PARALLEL_IMAGE_REQUESTS=ue},i.setRTLTextPlugin=function(ue,w){return Qt().setRTLTextPlugin(ue,w)},i.setWorkerCount=function(ue){Ee.workerCount=ue},i.setWorkerUrl=function(ue){a.a.WORKER_URL=ue}});var n=e;return n})});var cje=ye((Ebr,uje)=>{\"use strict\";var nw=Dr(),AXt=ru().sanitizeHTML,SXt=AJ(),oje=wx();function sje(e,t){this.subplot=e,this.uid=e.uid+\"-\"+t,this.index=t,this.idSource=\"source-\"+this.uid,this.idLayer=oje.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var ag=sje.prototype;ag.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=u7(t)};ag.needsNewImage=function(e){var t=this.subplot.map;return t.getSource(this.idSource)&&this.sourceType===\"image\"&&e.sourcetype===\"image\"&&(this.source!==e.source||JSON.stringify(this.coordinates)!==JSON.stringify(e.coordinates))};ag.needsNewSource=function(e){return this.sourceType!==e.sourcetype||JSON.stringify(this.source)!==JSON.stringify(e.source)||this.layerType!==e.type};ag.needsNewLayer=function(e){return this.layerType!==e.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]};ag.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]};ag.updateImage=function(e){var t=this.subplot.map;t.getSource(this.idSource).updateImage({url:e.source,coordinates:e.coordinates});var r=this.findFollowingMapLayerId(this.lookupBelow());r!==null&&this.subplot.map.moveLayer(this.idLayer,r)};ag.updateSource=function(e){var t=this.subplot.map;if(t.getSource(this.idSource)&&t.removeSource(this.idSource),this.sourceType=e.sourcetype,this.source=e.source,!!u7(e)){var r=MXt(e);t.addSource(this.idSource,r)}};ag.findFollowingMapLayerId=function(e){if(e===\"traces\")for(var t=this.subplot.getMapLayers(),r=0;r<t.length;r++){var n=t[r].id;if(typeof n==\"string\"&&n.indexOf(oje.traceLayerPrefix)===0){e=n;break}}return e};ag.updateLayer=function(e){var t=this.subplot,r=lje(e),n=this.lookupBelow(),i=this.findFollowingMapLayerId(n);this.removeLayer(),u7(e)&&t.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":e.sourcelayer||\"\",type:e.type,minzoom:e.minzoom,maxzoom:e.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=e.type,this.below=n};ag.updateStyle=function(e){if(u7(e)){var t=lje(e);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",t.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",t.paint)}};ag.removeLayer=function(){var e=this.subplot.map;e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer)};ag.dispose=function(){var e=this.subplot.map;e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer),e.getSource(this.idSource)&&e.removeSource(this.idSource)};function u7(e){if(!e.visible)return!1;var t=e.source;if(Array.isArray(t)&&t.length>0){for(var r=0;r<t.length;r++)if(typeof t[r]!=\"string\"||t[r].length===0)return!1;return!0}return nw.isPlainObject(t)||typeof t==\"string\"&&t.length>0}function lje(e){var t={},r={};switch(e.type){case\"circle\":nw.extendFlat(r,{\"circle-radius\":e.circle.radius,\"circle-color\":e.color,\"circle-opacity\":e.opacity});break;case\"line\":nw.extendFlat(r,{\"line-width\":e.line.width,\"line-color\":e.color,\"line-opacity\":e.opacity,\"line-dasharray\":e.line.dash});break;case\"fill\":nw.extendFlat(r,{\"fill-color\":e.color,\"fill-outline-color\":e.fill.outlinecolor,\"fill-opacity\":e.opacity});break;case\"symbol\":var n=e.symbol,i=SXt(n.textposition,n.iconsize);nw.extendFlat(t,{\"icon-image\":n.icon+\"-15\",\"icon-size\":n.iconsize/10,\"text-field\":n.text,\"text-size\":n.textfont.size,\"text-anchor\":i.anchor,\"text-offset\":i.offset,\"symbol-placement\":n.placement}),nw.extendFlat(r,{\"icon-color\":e.color,\"text-color\":n.textfont.color,\"text-opacity\":e.opacity});break;case\"raster\":nw.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":e.opacity});break}return{layout:t,paint:r}}function MXt(e){var t=e.sourcetype,r=e.source,n={type:t},i;return t===\"geojson\"?i=\"data\":t===\"vector\"?i=typeof r==\"string\"?\"url\":\"tiles\":t===\"raster\"?(i=\"tiles\",n.tileSize=256):t===\"image\"&&(i=\"url\",n.coordinates=e.coordinates),n[i]=r,e.sourceattribution&&(n.attribution=AXt(e.sourceattribution)),n}uje.exports=function(t,r,n){var i=new sje(t,r);return i.update(n),i}});var yje=ye((kbr,mje)=>{\"use strict\";var LJ=aje(),PJ=Dr(),dje=ix(),fje=qa(),EXt=ho(),kXt=yv(),c7=vf(),vje=Mg(),CXt=vje.drawMode,LXt=vje.selectMode,PXt=Of().prepSelect,IXt=Of().clearOutline,RXt=Of().clearSelectionsCache,DXt=Of().selectOnClick,aw=wx(),FXt=cje();function pje(e,t){this.id=t,this.gd=e;var r=e._fullLayout,n=e._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var Uh=pje.prototype;Uh.plot=function(e,t,r){var n=this,i;n.map?i=new Promise(function(a,o){n.updateMap(e,t,a,o)}):i=new Promise(function(a,o){n.createMap(e,t,a,o)}),r.push(i)};Uh.createMap=function(e,t,r,n){var i=this,a=t[i.id],o=i.styleObj=gje(a.style),s=a.bounds,l=s?[[s.west,s.south],[s.east,s.north]]:null,u=i.map=new LJ.Map({container:i.div,style:o.style,center:IJ(a.center),zoom:a.zoom,bearing:a.bearing,pitch:a.pitch,maxBounds:l,interactive:!i.isStatic,preserveDrawingBuffer:i.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new LJ.AttributionControl({compact:!0})),c={};u.on(\"styleimagemissing\",function(h){var d=h.id;if(!c[d]&&d.includes(\"-15\")){c[d]=!0;var v=new Image(15,15);v.onload=function(){u.addImage(d,v)},v.crossOrigin=\"Anonymous\",v.src=\"https://unpkg.com/maki@2.1.0/icons/\"+d+\".svg\"}}),u.setTransformRequest(function(h){return h=h.replace(\"https://fonts.openmaptiles.org/Open Sans Extrabold\",\"https://fonts.openmaptiles.org/Open Sans Extra Bold\"),h=h.replace(\"https://tiles.basemaps.cartocdn.com/fonts/Open Sans Extrabold\",\"https://fonts.openmaptiles.org/Open Sans Extra Bold\"),h=h.replace(\"https://fonts.openmaptiles.org/Open Sans Regular,Arial Unicode MS Regular\",\"https://fonts.openmaptiles.org/Klokantech Noto Sans Regular\"),{url:h}}),u._canvas.style.left=\"0px\",u._canvas.style.top=\"0px\",i.rejectOnError(n),i.isStatic||i.initFx(e,t);var f=[];f.push(new Promise(function(h){u.once(\"load\",h)})),f=f.concat(dje.fetchTraceGeoData(e)),Promise.all(f).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Uh.updateMap=function(e,t,r,n){var i=this,a=i.map,o=t[this.id];i.rejectOnError(n);var s=[],l=gje(o.style);JSON.stringify(i.styleObj)!==JSON.stringify(l)&&(i.styleObj=l,a.setStyle(l.style),i.traceHash={},s.push(new Promise(function(u){a.once(\"styledata\",u)}))),s=s.concat(dje.fetchTraceGeoData(e)),Promise.all(s).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Uh.fillBelowLookup=function(e,t){var r=t[this.id],n=r.layers,i,a,o=this.belowLookup={},s=!1;for(i=0;i<e.length;i++){var l=e[i][0].trace,u=l._module;typeof l.below==\"string\"?a=l.below:u.getBelow&&(a=u.getBelow(l,this)),a===\"\"&&(s=!0),o[\"trace-\"+l.uid]=a||\"\"}for(i=0;i<n.length;i++){var c=n[i];typeof c.below==\"string\"?a=c.below:s?a=\"traces\":a=\"\",o[\"layout-\"+i]=a}var f={},h,d;for(h in o)a=o[h],f[a]?f[a].push(h):f[a]=[h];for(a in f){var v=f[a];if(v.length>1)for(i=0;i<v.length;i++)h=v[i],h.indexOf(\"trace-\")===0?(d=h.split(\"trace-\")[1],this.traceHash[d]&&(this.traceHash[d].below=null)):h.indexOf(\"layout-\")===0&&(d=h.split(\"layout-\")[1],this.layerList[d]&&(this.layerList[d].below=null))}};var hje={choroplethmap:0,densitymap:1,scattermap:2};Uh.updateData=function(e){var t=this.traceHash,r,n,i,a,o=e.slice().sort(function(f,h){return hje[f[0].trace.type]-hje[h[0].trace.type]});for(i=0;i<o.length;i++){var s=o[i];n=s[0].trace,r=t[n.uid];var l=!1;r&&(r.type===n.type?(r.update(s),l=!0):r.dispose()),!l&&n._module&&(t[n.uid]=n._module.plot(this,s))}var u=Object.keys(t);e:for(i=0;i<u.length;i++){var c=u[i];for(a=0;a<e.length;a++)if(n=e[a][0].trace,c===n.uid)continue e;r=t[c],r.dispose(),delete t[c]}};Uh.updateLayout=function(e){var t=this.map,r=e[this.id];!this.dragging&&!this.wheeling&&(t.setCenter(IJ(r.center)),t.setZoom(r.zoom),t.setBearing(r.bearing),t.setPitch(r.pitch)),this.updateLayers(e),this.updateFramework(e),this.updateFx(e),this.map.resize(),this.gd._context._scrollZoom.map?t.scrollZoom.enable():t.scrollZoom.disable()};Uh.resolveOnRender=function(e){var t=this.map;t.on(\"render\",function r(){t.loaded()&&(t.off(\"render\",r),setTimeout(e,10))})};Uh.rejectOnError=function(e){var t=this.map;function r(){e(new Error(aw.mapOnErrorMsg))}t.once(\"error\",r),t.once(\"style.error\",r),t.once(\"source.error\",r),t.once(\"tile.error\",r),t.once(\"layer.error\",r)};Uh.createFramework=function(e){var t=this,r=t.div=document.createElement(\"div\");r.id=t.uid,r.style.position=\"absolute\",t.container.appendChild(r),t.xaxis={_id:\"x\",c2p:function(n){return t.project(n).x}},t.yaxis={_id:\"y\",c2p:function(n){return t.project(n).y}},t.updateFramework(e),t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},EXt.setConvert(t.mockAxis,e)};Uh.initFx=function(e,t){var r=this,n=r.gd,i=r.map;i.on(\"moveend\",function(s){if(r.map){var l=n._fullLayout;if(s.originalEvent||r.wheeling){var u=l[r.id];fje.call(\"_storeDirectGUIEdit\",n.layout,l._preGUI,r.getViewEdits(u));var c=r.getView();u._input.center=u.center=c.center,u._input.zoom=u.zoom=c.zoom,u._input.bearing=u.bearing=c.bearing,u._input.pitch=u.pitch=c.pitch,n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(c))}s.originalEvent&&s.originalEvent.type===\"mouseup\"?r.dragging=!1:r.wheeling&&(r.wheeling=!1),l&&l._rehover&&l._rehover()}}),i.on(\"wheel\",function(){r.wheeling=!0}),i.on(\"mousemove\",function(s){var l=r.div.getBoundingClientRect(),u=[s.originalEvent.offsetX,s.originalEvent.offsetY];s.target.getBoundingClientRect=function(){return l},r.xaxis.p2c=function(){return i.unproject(u).lng},r.yaxis.p2c=function(){return i.unproject(u).lat},n._fullLayout._rehover=function(){n._fullLayout._hoversubplot===r.id&&n._fullLayout[r.id]&&c7.hover(n,s,r.id)},c7.hover(n,s,r.id),n._fullLayout._hoversubplot=r.id});function a(){c7.loneUnhover(t._hoverlayer)}i.on(\"dragstart\",function(){r.dragging=!0,a()}),i.on(\"zoomstart\",a),i.on(\"mouseout\",function(){n._fullLayout._hoversubplot=null});function o(){var s=r.getView();n.emit(\"plotly_relayouting\",r.getViewEditsWithDerived(s))}i.on(\"drag\",o),i.on(\"zoom\",o),i.on(\"dblclick\",function(){var s=n._fullLayout[r.id];fje.call(\"_storeDirectGUIEdit\",n.layout,n._fullLayout._preGUI,r.getViewEdits(s));var l=r.viewInitial;i.setCenter(IJ(l.center)),i.setZoom(l.zoom),i.setBearing(l.bearing),i.setPitch(l.pitch);var u=r.getView();s._input.center=s.center=u.center,s._input.zoom=s.zoom=u.zoom,s._input.bearing=s.bearing=u.bearing,s._input.pitch=s.pitch=u.pitch,n.emit(\"plotly_doubleclick\",null),n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(u))}),r.clearOutline=function(){RXt(r.dragOptions),IXt(r.dragOptions.gd)},r.onClickInPanFn=function(s){return function(l){var u=n._fullLayout.clickmode;u.indexOf(\"select\")>-1&&DXt(l.originalEvent,n,[r.xaxis],[r.yaxis],r.id,s),u.indexOf(\"event\")>-1&&c7.click(n,l.originalEvent)}}};Uh.updateFx=function(e){var t=this,r=t.map,n=t.gd;if(t.isStatic)return;function i(l){var u=t.map.unproject(l);return[u.lng,u.lat]}var a=e.dragmode,o;o=function(l,u){if(u.isRect){var c=l.range={};c[t.id]=[i([u.xmin,u.ymin]),i([u.xmax,u.ymax])]}else{var f=l.lassoPoints={};f[t.id]=u.map(i)}};var s=t.dragOptions;t.dragOptions=PJ.extendDeep(s||{},{dragmode:e.dragmode,element:t.div,gd:n,plotinfo:{id:t.id,domain:e[t.id].domain,xaxis:t.xaxis,yaxis:t.yaxis,fillRangeItems:o},xaxes:[t.xaxis],yaxes:[t.yaxis],subplot:t.id}),r.off(\"click\",t.onClickInPanHandler),LXt(a)||CXt(a)?(r.dragPan.disable(),r.on(\"zoomstart\",t.clearOutline),t.dragOptions.prepFn=function(l,u,c){PXt(l,u,c,t.dragOptions,a)},kXt.init(t.dragOptions)):(r.dragPan.enable(),r.off(\"zoomstart\",t.clearOutline),t.div.onmousedown=null,t.div.ontouchstart=null,t.div.removeEventListener(\"touchstart\",t.div._ontouchstart),t.onClickInPanHandler=t.onClickInPanFn(t.dragOptions),r.on(\"click\",t.onClickInPanHandler))};Uh.updateFramework=function(e){var t=e[this.id].domain,r=e._size,n=this.div.style;n.width=r.w*(t.x[1]-t.x[0])+\"px\",n.height=r.h*(t.y[1]-t.y[0])+\"px\",n.left=r.l+t.x[0]*r.w+\"px\",n.top=r.t+(1-t.y[1])*r.h+\"px\",this.xaxis._offset=r.l+t.x[0]*r.w,this.xaxis._length=r.w*(t.x[1]-t.x[0]),this.yaxis._offset=r.t+(1-t.y[1])*r.h,this.yaxis._length=r.h*(t.y[1]-t.y[0])};Uh.updateLayers=function(e){var t=e[this.id],r=t.layers,n=this.layerList,i;if(r.length!==n.length){for(i=0;i<n.length;i++)n[i].dispose();for(n=this.layerList=[],i=0;i<r.length;i++)n.push(FXt(this,i,r[i]))}else for(i=0;i<r.length;i++)n[i].update(r[i])};Uh.destroy=function(){this.map&&(this.map.remove(),this.map=null,this.container.removeChild(this.div))};Uh.toImage=function(){return this.map.stop(),this.map.getCanvas().toDataURL()};Uh.setOptions=function(e,t,r){for(var n in r)this.map[t](e,n,r[n])};Uh.getMapLayers=function(){return this.map.getStyle().layers};Uh.addLayer=function(e,t){var r=this.map;if(typeof t==\"string\"){if(t===\"\"){r.addLayer(e,t);return}for(var n=this.getMapLayers(),i=0;i<n.length;i++)if(t===n[i].id){r.addLayer(e,t);return}PJ.warn([\"Trying to add layer with *below* value\",t,\"referencing a layer that does not exist\",\"or that does not yet exist.\"].join(\" \"))}r.addLayer(e)};Uh.project=function(e){return this.map.project(new LJ.LngLat(e[0],e[1]))};Uh.getView=function(){var e=this.map,t=e.getCenter(),r=t.lng,n=t.lat,i={lon:r,lat:n},a=e.getCanvas(),o=parseInt(a.style.width),s=parseInt(a.style.height);return{center:i,zoom:e.getZoom(),bearing:e.getBearing(),pitch:e.getPitch(),_derived:{coordinates:[e.unproject([0,0]).toArray(),e.unproject([o,0]).toArray(),e.unproject([o,s]).toArray(),e.unproject([0,s]).toArray()]}}};Uh.getViewEdits=function(e){for(var t=this.id,r=[\"center\",\"zoom\",\"bearing\",\"pitch\"],n={},i=0;i<r.length;i++){var a=r[i];n[t+\".\"+a]=e[a]}return n};Uh.getViewEditsWithDerived=function(e){var t=this.id,r=this.getViewEdits(e);return r[t+\"._derived\"]=e._derived,r};function gje(e){var t={};return PJ.isPlainObject(e)?(t.id=e.id,t.style=e):typeof e==\"string\"?(t.id=e,aw.stylesMap[e]?t.style=aw.stylesMap[e]:t.style=e):(t.id=aw.styleValueDflt,t.style=zXt(aw.styleValueDflt)),t.transition={duration:0,delay:0},t}function zXt(e){return aw.styleUrlPrefix+e+\"-\"+aw.styleUrlSuffix}function IJ(e){return[e.lon,e.lat]}mje.exports=pje});var bje=ye((Cbr,xje)=>{\"use strict\";var RJ=Dr(),OXt=k_(),qXt=Yd(),_je=jk();xje.exports=function(t,r,n){OXt(t,r,n,{type:\"map\",attributes:_je,handleDefaults:BXt,partition:\"y\"})};function BXt(e,t,r){r(\"style\"),r(\"center.lon\"),r(\"center.lat\"),r(\"zoom\"),r(\"bearing\"),r(\"pitch\");var n=r(\"bounds.west\"),i=r(\"bounds.east\"),a=r(\"bounds.south\"),o=r(\"bounds.north\");(n===void 0||i===void 0||a===void 0||o===void 0)&&delete t.bounds,qXt(e,t,{name:\"layers\",handleItemDefaults:NXt}),t._input=e}function NXt(e,t){function r(l,u){return RJ.coerce(e,t,_je.layers,l,u)}var n=r(\"visible\");if(n){var i=r(\"sourcetype\"),a=i===\"raster\"||i===\"image\";r(\"source\"),r(\"sourceattribution\"),i===\"vector\"&&r(\"sourcelayer\"),i===\"image\"&&r(\"coordinates\");var o;a&&(o=\"raster\");var s=r(\"type\",o);a&&s!==\"raster\"&&(s=t.type=\"raster\",RJ.log(\"Source types *raster* and *image* must drawn *raster* layer type.\")),r(\"below\"),r(\"color\"),r(\"opacity\"),r(\"minzoom\"),r(\"maxzoom\"),s===\"circle\"&&r(\"circle.radius\"),s===\"line\"&&(r(\"line.width\"),r(\"line.dash\")),s===\"fill\"&&r(\"fill.outlinecolor\"),s===\"symbol\"&&(r(\"symbol.icon\"),r(\"symbol.iconsize\"),r(\"symbol.text\"),RJ.coerceFont(r,\"symbol.textfont\",void 0,{noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0}),r(\"symbol.textposition\"),r(\"symbol.placement\"))}}});var h7=ye(l0=>{\"use strict\";var f7=Dr(),wje=f7.strTranslate,UXt=f7.strScale,VXt=Id().getSubplotCalcData,GXt=Wp(),HXt=Oa(),Tje=So(),jXt=ru(),WXt=yje(),Tx=\"map\";l0.name=Tx;l0.attr=\"subplot\";l0.idRoot=Tx;l0.idRegex=l0.attrRegex=f7.counterRegex(Tx);l0.attributes={subplot:{valType:\"subplotid\",dflt:\"map\",editType:\"calc\"}};l0.layoutAttributes=jk();l0.supplyLayoutDefaults=bje();l0.plot=function(t){for(var r=t._fullLayout,n=t.calcdata,i=r._subplots[Tx],a=0;a<i.length;a++){var o=i[a],s=VXt(n,Tx,o),l=r[o],u=l._subplot;u||(u=new WXt(t,o),r[o]._subplot=u),u.viewInitial||(u.viewInitial={center:f7.extendFlat({},l.center),zoom:l.zoom,bearing:l.bearing,pitch:l.pitch}),u.plot(s,r,t._promises)}};l0.clean=function(e,t,r,n){for(var i=n._subplots[Tx]||[],a=0;a<i.length;a++){var o=i[a];!t[o]&&n[o]._subplot&&n[o]._subplot.destroy()}};l0.toSVG=function(e){for(var t=e._fullLayout,r=t._subplots[Tx],n=t._size,i=0;i<r.length;i++){var a=t[r[i]],o=a.domain,s=a._subplot,l=s.toImage(\"png\"),u=t._glimages.append(\"svg:image\");u.attr({xmlns:GXt.svg,\"xlink:href\":l,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"});var c=HXt.select(a._subplot.div),f=c.select(\".maplibregl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),h=t._glimages.append(\"g\"),d=h.append(\"text\");d.text(f).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":f});var v=Tje.bBox(d.node()),_=n.w*(o.x[1]-o.x[0]);if(v.width>_/2){var b=f.split(\"|\").join(\"<br>\");d.text(b).attr(\"data-unformatted\",b).call(jXt.convertToTspans,e),v=Tje.bBox(d.node())}d.attr(\"transform\",wje(-3,-v.height+8)),h.insert(\"rect\",\".static-attribution\").attr({x:-v.width-6,y:-v.height-3,width:v.width+6,height:v.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var p=1;v.width+6>_&&(p=_/(v.width+6));var k=[n.l+n.w*o.x[1],n.t+n.h*(1-o.y[0])];h.attr(\"transform\",wje(k[0],k[1])+UXt(p))}};l0.updateFx=function(e){for(var t=e._fullLayout,r=t._subplots[Tx],n=0;n<r.length;n++){var i=t[r[n]]._subplot;i.updateFx(t)}}});var Sje=ye((Pbr,Aje)=>{\"use strict\";Aje.exports={attributes:i7(),supplyDefaults:OHe(),colorbar:$d(),formatLabels:TJ(),calc:vF(),plot:JHe(),hoverPoints:l7().hoverPoints,eventData:tje(),selectPoints:ije(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.update(t)}},moduleType:\"trace\",name:\"scattermap\",basePlotModule:h7(),categories:[\"map\",\"gl\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}});var Eje=ye((Ibr,Mje)=>{\"use strict\";Mje.exports=Sje()});var DJ=ye((Rbr,kje)=>{\"use strict\";var d1=e5(),XXt=Tu(),{hovertemplateAttrs:ZXt,templatefallbackAttrs:YXt}=Ll(),KXt=Gl(),Ax=Ao().extendFlat;kje.exports=Ax({locations:{valType:\"data_array\",editType:\"calc\"},z:{valType:\"data_array\",editType:\"calc\"},geojson:{valType:\"any\",editType:\"calc\"},featureidkey:Ax({},d1.featureidkey,{}),below:{valType:\"string\",editType:\"plot\"},text:d1.text,hovertext:d1.hovertext,marker:{line:{color:Ax({},d1.marker.line.color,{editType:\"plot\"}),width:Ax({},d1.marker.line.width,{editType:\"plot\"}),editType:\"calc\"},opacity:Ax({},d1.marker.opacity,{editType:\"plot\"}),editType:\"calc\"},selected:{marker:{opacity:Ax({},d1.selected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},unselected:{marker:{opacity:Ax({},d1.unselected.marker.opacity,{editType:\"plot\"}),editType:\"plot\"},editType:\"plot\"},hoverinfo:d1.hoverinfo,hovertemplate:ZXt({},{keys:[\"properties\"]}),hovertemplatefallback:YXt(),showlegend:Ax({},KXt.showlegend,{dflt:!1})},XXt(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))});var Lje=ye((Dbr,Cje)=>{\"use strict\";var Yk=Dr(),JXt=Qh(),$Xt=DJ();Cje.exports=function(t,r,n,i){function a(c,f){return Yk.coerce(t,r,$Xt,c,f)}var o=a(\"locations\"),s=a(\"z\"),l=a(\"geojson\");if(!Yk.isArrayOrTypedArray(o)||!o.length||!Yk.isArrayOrTypedArray(s)||!s.length||!(typeof l==\"string\"&&l!==\"\"||Yk.isPlainObject(l))){r.visible=!1;return}a(\"featureidkey\"),r._length=Math.min(o.length,s.length),a(\"below\"),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\");var u=a(\"marker.line.width\");u&&a(\"marker.line.color\"),a(\"marker.opacity\"),JXt(t,r,i,a,{prefix:\"\",cLetter:\"z\"}),Yk.coerceSelectionMarkerOpacity(r,a)}});var FJ=ye((Fbr,Rje)=>{\"use strict\";var QXt=Eo(),v1=Dr(),eZt=tc(),tZt=So(),rZt=tx().makeBlank,Pje=ix();function iZt(e){var t=e[0].trace,r=t.visible===!0&&t._length!==0,n={layout:{visibility:\"none\"},paint:{}},i={layout:{visibility:\"none\"},paint:{}},a=t._opts={fill:n,line:i,geojson:rZt()};if(!r)return a;var o=Pje.extractTraceFeature(e);if(!o)return a;var s=eZt.makeColorScaleFuncFromTrace(t),l=t.marker,u=l.line||{},c;v1.isArrayOrTypedArray(l.opacity)&&(c=function(k){var E=k.mo;return QXt(E)?+v1.constrain(E,0,1):0});var f;v1.isArrayOrTypedArray(u.color)&&(f=function(k){return k.mlc});var h;v1.isArrayOrTypedArray(u.width)&&(h=function(k){return k.mlw});for(var d=0;d<e.length;d++){var v=e[d],_=v.fOut;if(_){var b=_.properties;b.fc=s(v.z),c&&(b.mo=c(v)),f&&(b.mlc=f(v)),h&&(b.mlw=h(v)),v.ct=b.ct,v._polygons=Pje.feature2polygons(_)}}var p=c?{type:\"identity\",property:\"mo\"}:l.opacity;return v1.extendFlat(n.paint,{\"fill-color\":{type:\"identity\",property:\"fc\"},\"fill-opacity\":p}),v1.extendFlat(i.paint,{\"line-color\":f?{type:\"identity\",property:\"mlc\"}:u.color,\"line-width\":h?{type:\"identity\",property:\"mlw\"}:u.width,\"line-opacity\":p}),n.layout.visibility=\"visible\",i.layout.visibility=\"visible\",a.geojson={type:\"FeatureCollection\",features:o},Ije(e),a}function Ije(e){var t=e[0].trace,r=t._opts,n;if(t.selectedpoints){for(var i=tZt.makeSelectedPointStyleFns(t),a=0;a<e.length;a++){var o=e[a];o.fOut&&(o.fOut.properties.mo2=i.selectedOpacityFn(o))}n={type:\"identity\",property:\"mo2\"}}else n=v1.isArrayOrTypedArray(t.marker.opacity)?{type:\"identity\",property:\"mo\"}:t.marker.opacity;return v1.extendFlat(r.fill.paint,{\"fill-opacity\":n}),v1.extendFlat(r.line.paint,{\"line-opacity\":n}),r}Rje.exports={convert:iZt,convertOnSelect:Ije}});var qje=ye((zbr,Oje)=>{\"use strict\";var Fje=FJ().convert,nZt=FJ().convertOnSelect,Dje=wx().traceLayerPrefix;function zje(e,t){this.type=\"choroplethmap\",this.subplot=e,this.uid=t,this.sourceId=\"source-\"+t,this.layerList=[[\"fill\",Dje+t+\"-fill\"],[\"line\",Dje+t+\"-line\"]],this.below=null}var C5=zje.prototype;C5.update=function(e){this._update(Fje(e)),e[0].trace._glTrace=this};C5.updateOnSelect=function(e){this._update(nZt(e))};C5._update=function(e){var t=this.subplot,r=this.layerList,n=t.belowLookup[\"trace-\"+this.uid];t.map.getSource(this.sourceId).setData(e.geojson),n!==this.below&&(this._removeLayers(),this._addLayers(e,n),this.below=n);for(var i=0;i<r.length;i++){var a=r[i],o=a[0],s=a[1],l=e[o];t.setOptions(s,\"setLayoutProperty\",l.layout),l.layout.visibility===\"visible\"&&t.setOptions(s,\"setPaintProperty\",l.paint)}};C5._addLayers=function(e,t){for(var r=this.subplot,n=this.layerList,i=this.sourceId,a=0;a<n.length;a++){var o=n[a],s=o[0],l=e[s];r.addLayer({type:s,id:o[1],source:i,layout:l.layout,paint:l.paint},t)}};C5._removeLayers=function(){for(var e=this.subplot.map,t=this.layerList,r=t.length-1;r>=0;r--)e.removeLayer(t[r][1])};C5.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};Oje.exports=function(t,r){var n=r[0].trace,i=new zje(t,n.uid),a=i.sourceId,o=Fje(r),s=i.below=t.belowLookup[\"trace-\"+n.uid];return t.map.addSource(a,{type:\"geojson\",data:o.geojson}),i._addLayers(o,s),r[0].trace._glTrace=i,i}});var Nje=ye((Obr,Bje)=>{\"use strict\";Bje.exports={attributes:DJ(),supplyDefaults:Lje(),colorbar:S_(),calc:FF(),plot:qje(),hoverPoints:OF(),eventData:qF(),selectPoints:BF(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.updateOnSelect(t)}},getBelow:function(e,t){for(var r=t.getMapLayers(),n=r.length-2;n>=0;n--){var i=r[n].id;if(typeof i==\"string\"&&i.indexOf(\"water\")===0){for(var a=n+1;a<r.length;a++)if(i=r[a].id,typeof i==\"string\"&&i.indexOf(\"plotly-\")===-1)return i}}},moduleType:\"trace\",name:\"choroplethmap\",basePlotModule:h7(),categories:[\"map\",\"gl\",\"noOpacity\",\"showLegend\"],meta:{hr_name:\"choropleth_map\"}}});var Vje=ye((qbr,Uje)=>{\"use strict\";Uje.exports=Nje()});var OJ=ye((Bbr,Hje)=>{\"use strict\";var aZt=Tu(),{hovertemplateAttrs:oZt,templatefallbackAttrs:sZt}=Ll(),Gje=Gl(),d7=i7(),zJ=Ao().extendFlat;Hje.exports=zJ({lon:d7.lon,lat:d7.lat,z:{valType:\"data_array\",editType:\"calc\"},radius:{valType:\"number\",editType:\"plot\",arrayOk:!0,min:1,dflt:30},below:{valType:\"string\",editType:\"plot\"},text:d7.text,hovertext:d7.hovertext,hoverinfo:zJ({},Gje.hoverinfo,{flags:[\"lon\",\"lat\",\"z\",\"text\",\"name\"]}),hovertemplate:oZt(),hovertemplatefallback:sZt(),showlegend:zJ({},Gje.showlegend,{dflt:!1})},aZt(\"\",{cLetter:\"z\",editTypeOverride:\"calc\"}))});var Wje=ye((Nbr,jje)=>{\"use strict\";var lZt=Dr(),uZt=Qh(),cZt=OJ();jje.exports=function(t,r,n,i){function a(u,c){return lZt.coerce(t,r,cZt,u,c)}var o=a(\"lon\")||[],s=a(\"lat\")||[],l=Math.min(o.length,s.length);if(!l){r.visible=!1;return}r._length=l,a(\"z\"),a(\"radius\"),a(\"below\"),a(\"text\"),a(\"hovertext\"),a(\"hovertemplate\"),a(\"hovertemplatefallback\"),uZt(t,r,i,a,{prefix:\"\",cLetter:\"z\"})}});var Yje=ye((Ubr,Zje)=>{\"use strict\";var qJ=Eo(),fZt=Dr().isArrayOrTypedArray,BJ=fs().BADNUM,hZt=gv(),Xje=Dr()._;Zje.exports=function(t,r){for(var n=r._length,i=new Array(n),a=r.z,o=fZt(a)&&a.length,s=0;s<n;s++){var l=i[s]={},u=r.lon[s],c=r.lat[s];if(l.lonlat=qJ(u)&&qJ(c)?[+u,+c]:[BJ,BJ],o){var f=a[s];l.z=qJ(f)?f:BJ}}return hZt(t,r,{vals:o?a:[0,1],containerStr:\"\",cLetter:\"z\"}),n&&(i[0].t={labels:{lat:Xje(t,\"lat:\")+\" \",lon:Xje(t,\"lon:\")+\" \"}}),i}});var eWe=ye((Vbr,Qje)=>{\"use strict\";var dZt=Eo(),NJ=Dr(),Kje=ka(),Jje=tc(),$je=fs().BADNUM,vZt=tx().makeBlank;Qje.exports=function(t){var r=t[0].trace,n=r.visible===!0&&r._length!==0,i={layout:{visibility:\"none\"},paint:{}},a=r._opts={heatmap:i,geojson:vZt()};if(!n)return a;var o=[],s,l=r.z,u=r.radius,c=NJ.isArrayOrTypedArray(l)&&l.length,f=NJ.isArrayOrTypedArray(u);for(s=0;s<t.length;s++){var h=t[s],d=h.lonlat;if(d[0]!==$je){var v={};if(c){var 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v7=rWe.prototype;v7.update=function(e){var t=this.subplot,r=this.layerList,n=tWe(e),i=t.belowLookup[\"trace-\"+this.uid];t.map.getSource(this.sourceId).setData(n.geojson),i!==this.below&&(this._removeLayers(),this._addLayers(n,i),this.below=i);for(var a=0;a<r.length;a++){var o=r[a],s=o[0],l=o[1],u=n[s];t.setOptions(l,\"setLayoutProperty\",u.layout),u.layout.visibility===\"visible\"&&t.setOptions(l,\"setPaintProperty\",u.paint)}};v7._addLayers=function(e,t){for(var r=this.subplot,n=this.layerList,i=this.sourceId,a=0;a<n.length;a++){var o=n[a],s=o[0],l=e[s];r.addLayer({type:s,id:o[1],source:i,layout:l.layout,paint:l.paint},t)}};v7._removeLayers=function(){for(var e=this.subplot.map,t=this.layerList,r=t.length-1;r>=0;r--)e.removeLayer(t[r][1])};v7.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};iWe.exports=function(t,r){var n=r[0].trace,i=new rWe(t,n.uid),a=i.sourceId,o=tWe(r),s=i.below=t.belowLookup[\"trace-\"+n.uid];return t.map.addSource(a,{type:\"geojson\",data:o.geojson}),i._addLayers(o,s),i}});var oWe=ye((Hbr,aWe)=>{\"use strict\";var gZt=ho(),mZt=l7().hoverPoints,yZt=l7().getExtraText;aWe.exports=function(t,r,n){var i=mZt(t,r,n);if(i){var a=i[0],o=a.cd,s=o[0].trace,l=o[a.index];if(delete a.color,\"z\"in l){var u=a.subplot.mockAxis;a.z=l.z,a.zLabel=gZt.tickText(u,u.c2l(l.z),\"hover\").text}return a.extraText=yZt(s,l,o[0].t.labels),[a]}}});var lWe=ye((jbr,sWe)=>{\"use strict\";sWe.exports=function(t,r){return t.lon=r.lon,t.lat=r.lat,t.z=r.z,t}});var cWe=ye((Wbr,uWe)=>{\"use strict\";uWe.exports={attributes:OJ(),supplyDefaults:Wje(),colorbar:S_(),formatLabels:TJ(),calc:Yje(),plot:nWe(),hoverPoints:oWe(),eventData:lWe(),getBelow:function(e,t){for(var r=t.getMapLayers(),n=0;n<r.length;n++){var i=r[n],a=i.id;if(i.type===\"symbol\"&&typeof a==\"string\"&&a.indexOf(\"plotly-\")===-1)return a}},moduleType:\"trace\",name:\"densitymap\",basePlotModule:h7(),categories:[\"map\",\"gl\",\"showLegend\"],meta:{hr_name:\"density_map\"}}});var hWe=ye((Xbr,fWe)=>{\"use strict\";fWe.exports=cWe()});var VJ=ye((Ybr,mWe)=>{\"use strict\";var _Zt=ec(),xZt=Gl(),dWe=Lh(),UJ=n3(),bZt=Cc().attributes,{hovertemplateAttrs:vWe,templatefallbackAttrs:pWe}=Ll(),wZt=Tu(),TZt=vl().templatedArray,AZt=df().descriptionOnlyNumbers,gWe=Ao().extendFlat,SZt=mc().overrideAll,Zbr=mWe.exports=SZt({hoverinfo:gWe({},xZt.hoverinfo,{flags:[],arrayOk:!1}),hoverlabel:UJ.hoverlabel,domain:bZt({name:\"sankey\",trace:!0}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\"},valueformat:{valType:\"string\",dflt:\".3s\",description:AZt(\"value\")},valuesuffix:{valType:\"string\",dflt:\"\"},arrangement:{valType:\"enumerated\",values:[\"snap\",\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"snap\"},textfont:_Zt({autoShadowDflt:!0}),customdata:void 0,node:{label:{valType:\"data_array\",dflt:[]},groups:{valType:\"info_array\",impliedEdits:{x:[],y:[]},dimensions:2,freeLength:!0,dflt:[],items:{valType:\"number\",editType:\"calc\"}},x:{valType:\"data_array\",dflt:[]},y:{valType:\"data_array\",dflt:[]},color:{valType:\"color\",arrayOk:!0},customdata:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:dWe.defaultLine,arrayOk:!0},width:{valType:\"number\",min:0,dflt:.5,arrayOk:!0}},pad:{valType:\"number\",arrayOk:!1,min:0,dflt:20},thickness:{valType:\"number\",arrayOk:!1,min:1,dflt:20},hoverinfo:{valType:\"enumerated\",values:[\"all\",\"none\",\"skip\"],dflt:\"all\"},hoverlabel:UJ.hoverlabel,hovertemplate:vWe({},{keys:[\"value\",\"label\"]}),hovertemplatefallback:pWe(),align:{valType:\"enumerated\",values:[\"justify\",\"left\",\"right\",\"center\"],dflt:\"justify\"}},link:{arrowlen:{valType:\"number\",min:0,dflt:0},label:{valType:\"data_array\",dflt:[]},color:{valType:\"color\",arrayOk:!0},hovercolor:{valType:\"color\",arrayOk:!0},customdata:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:dWe.defaultLine,arrayOk:!0},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0}},source:{valType:\"data_array\",dflt:[]},target:{valType:\"data_array\",dflt:[]},value:{valType:\"data_array\",dflt:[]},hoverinfo:{valType:\"enumerated\",values:[\"all\",\"none\",\"skip\"],dflt:\"all\"},hoverlabel:UJ.hoverlabel,hovertemplate:vWe({},{keys:[\"value\",\"label\"]}),hovertemplatefallback:pWe(),colorscales:TZt(\"concentrationscales\",{editType:\"calc\",label:{valType:\"string\",editType:\"calc\",dflt:\"\"},cmax:{valType:\"number\",editType:\"calc\",dflt:1},cmin:{valType:\"number\",editType:\"calc\",dflt:0},colorscale:gWe(wZt().colorscale,{dflt:[[0,\"white\"],[1,\"black\"]]})})}},\"calc\",\"nested\")});var 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3:this._point=4;default:lr(this,Mt,kr);break}this._x0=this._x1,this._x1=Mt,this._y0=this._y1,this._y1=kr}};function dt(Mt){return new Vr(Mt)}function Ge(Mt,kr){this._basis=new Tr(Mt),this._beta=kr}Ge.prototype={lineStart:function(){this._x=[],this._y=[],this._basis.lineStart()},lineEnd:function(){var Mt=this._x,kr=this._y,Jr=Mt.length-1;if(Jr>0)for(var vi=Mt[0],hn=kr[0],An=Mt[Jr]-vi,Mn=kr[Jr]-hn,Li=-1,_n;++Li<=Jr;)_n=Li/Jr,this._basis.point(this._beta*Mt[Li]+(1-this._beta)*(vi+_n*An),this._beta*kr[Li]+(1-this._beta)*(hn+_n*Mn));this._x=this._y=null,this._basis.lineEnd()},point:function(Mt,kr){this._x.push(+Mt),this._y.push(+kr)}};var Je=function Mt(kr){function Jr(vi){return kr===1?new Tr(vi):new Ge(vi,kr)}return Jr.beta=function(vi){return Mt(+vi)},Jr}(.85);function je(Mt,kr,Jr){Mt._context.bezierCurveTo(Mt._x1+Mt._k*(Mt._x2-Mt._x0),Mt._y1+Mt._k*(Mt._y2-Mt._y0),Mt._x2+Mt._k*(Mt._x1-kr),Mt._y2+Mt._k*(Mt._y1-Jr),Mt._x2,Mt._y2)}function tt(Mt,kr){this._context=Mt,this._k=(1-kr)/6}tt.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:je(this,this._x1,this._y1);break}(this._line||this._line!==0&&this._point===1)&&this._context.closePath(),this._line=1-this._line},point:function(Mt,kr){switch(Mt=+Mt,kr=+kr,this._point){case 0:this._point=1,this._line?this._context.lineTo(Mt,kr):this._context.moveTo(Mt,kr);break;case 1:this._point=2,this._x1=Mt,this._y1=kr;break;case 2:this._point=3;default:je(this,Mt,kr);break}this._x0=this._x1,this._x1=this._x2,this._x2=Mt,this._y0=this._y1,this._y1=this._y2,this._y2=kr}};var xt=function Mt(kr){function Jr(vi){return new tt(vi,kr)}return Jr.tension=function(vi){return Mt(+vi)},Jr}(0);function 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Mt(+vi)},Jr}(0);function ke(Mt,kr){this._context=Mt,this._k=(1-kr)/6}ke.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._point=0},lineEnd:function(){(this._line||this._line!==0&&this._point===3)&&this._context.closePath(),this._line=1-this._line},point:function(Mt,kr){switch(Mt=+Mt,kr=+kr,this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3,this._line?this._context.lineTo(this._x2,this._y2):this._context.moveTo(this._x2,this._y2);break;case 3:this._point=4;default:je(this,Mt,kr);break}this._x0=this._x1,this._x1=this._x2,this._x2=Mt,this._y0=this._y1,this._y1=this._y2,this._y2=kr}};var vt=function Mt(kr){function Jr(vi){return new ke(vi,kr)}return Jr.tension=function(vi){return Mt(+vi)},Jr}(0);function ir(Mt,kr,Jr){var vi=Mt._x1,hn=Mt._y1,An=Mt._x2,Mn=Mt._y2;if(Mt._l01_a>c){var Li=2*Mt._l01_2a+3*Mt._l01_a*Mt._l12_a+Mt._l12_2a,_n=3*Mt._l01_a*(Mt._l01_a+Mt._l12_a);vi=(vi*Li-Mt._x0*Mt._l12_2a+Mt._x2*Mt._l01_2a)/_n,hn=(hn*Li-Mt._y0*Mt._l12_2a+Mt._y2*Mt._l01_2a)/_n}if(Mt._l23_a>c){var ya=2*Mt._l23_2a+3*Mt._l23_a*Mt._l12_a+Mt._l12_2a,Jn=3*Mt._l23_a*(Mt._l23_a+Mt._l12_a);An=(An*ya+Mt._x1*Mt._l23_2a-kr*Mt._l12_2a)/Jn,Mn=(Mn*ya+Mt._y1*Mt._l23_2a-Jr*Mt._l12_2a)/Jn}Mt._context.bezierCurveTo(vi,hn,An,Mn,Mt._x2,Mt._y2)}function ar(Mt,kr){this._context=Mt,this._alpha=kr}ar.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x2,this._y2);break;case 3:this.point(this._x2,this._y2);break}(this._line||this._line!==0&&this._point===1)&&this._context.closePath(),this._line=1-this._line},point:function(Mt,kr){if(Mt=+Mt,kr=+kr,this._point){var Jr=this._x2-Mt,vi=this._y2-kr;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(Jr*Jr+vi*vi,this._alpha))}switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(Mt,kr):this._context.moveTo(Mt,kr);break;case 1:this._point=2;break;case 2:this._point=3;default:ir(this,Mt,kr);break}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=Mt,this._y0=this._y1,this._y1=this._y2,this._y2=kr}};var vr=function Mt(kr){function Jr(vi){return kr?new ar(vi,kr):new tt(vi,0)}return Jr.alpha=function(vi){return Mt(+vi)},Jr}(.5);function ii(Mt,kr){this._context=Mt,this._alpha=kr}ii.prototype={areaStart:er,areaEnd:er,lineStart:function(){this._x0=this._x1=this._x2=this._x3=this._x4=this._x5=this._y0=this._y1=this._y2=this._y3=this._y4=this._y5=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){switch(this._point){case 1:{this._context.moveTo(this._x3,this._y3),this._context.closePath();break}case 2:{this._context.lineTo(this._x3,this._y3),this._context.closePath();break}case 3:{this.point(this._x3,this._y3),this.point(this._x4,this._y4),this.point(this._x5,this._y5);break}}},point:function(Mt,kr){if(Mt=+Mt,kr=+kr,this._point){var Jr=this._x2-Mt,vi=this._y2-kr;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(Jr*Jr+vi*vi,this._alpha))}switch(this._point){case 0:this._point=1,this._x3=Mt,this._y3=kr;break;case 1:this._point=2,this._context.moveTo(this._x4=Mt,this._y4=kr);break;case 2:this._point=3,this._x5=Mt,this._y5=kr;break;default:ir(this,Mt,kr);break}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=Mt,this._y0=this._y1,this._y1=this._y2,this._y2=kr}};var pi=function Mt(kr){function Jr(vi){return kr?new ii(vi,kr):new Ie(vi,0)}return Jr.alpha=function(vi){return Mt(+vi)},Jr}(.5);function $r(Mt,kr){this._context=Mt,this._alpha=kr}$r.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._x2=this._y0=this._y1=this._y2=NaN,this._l01_a=this._l12_a=this._l23_a=this._l01_2a=this._l12_2a=this._l23_2a=this._point=0},lineEnd:function(){(this._line||this._line!==0&&this._point===3)&&this._context.closePath(),this._line=1-this._line},point:function(Mt,kr){if(Mt=+Mt,kr=+kr,this._point){var Jr=this._x2-Mt,vi=this._y2-kr;this._l23_a=Math.sqrt(this._l23_2a=Math.pow(Jr*Jr+vi*vi,this._alpha))}switch(this._point){case 0:this._point=1;break;case 1:this._point=2;break;case 2:this._point=3,this._line?this._context.lineTo(this._x2,this._y2):this._context.moveTo(this._x2,this._y2);break;case 3:this._point=4;default:ir(this,Mt,kr);break}this._l01_a=this._l12_a,this._l12_a=this._l23_a,this._l01_2a=this._l12_2a,this._l12_2a=this._l23_2a,this._x0=this._x1,this._x1=this._x2,this._x2=Mt,this._y0=this._y1,this._y1=this._y2,this._y2=kr}};var di=function Mt(kr){function Jr(vi){return kr?new $r(vi,kr):new ke(vi,0)}return Jr.alpha=function(vi){return Mt(+vi)},Jr}(.5);function ji(Mt){this._context=Mt}ji.prototype={areaStart:er,areaEnd:er,lineStart:function(){this._point=0},lineEnd:function(){this._point&&this._context.closePath()},point:function(Mt,kr){Mt=+Mt,kr=+kr,this._point?this._context.lineTo(Mt,kr):(this._point=1,this._context.moveTo(Mt,kr))}};function In(Mt){return new ji(Mt)}function wi(Mt){return Mt<0?-1:1}function On(Mt,kr,Jr){var vi=Mt._x1-Mt._x0,hn=kr-Mt._x1,An=(Mt._y1-Mt._y0)/(vi||hn<0&&-0),Mn=(Jr-Mt._y1)/(hn||vi<0&&-0),Li=(An*hn+Mn*vi)/(vi+hn);return(wi(An)+wi(Mn))*Math.min(Math.abs(An),Math.abs(Mn),.5*Math.abs(Li))||0}function qn(Mt,kr){var Jr=Mt._x1-Mt._x0;return Jr?(3*(Mt._y1-Mt._y0)/Jr-kr)/2:kr}function Fn(Mt,kr,Jr){var vi=Mt._x0,hn=Mt._y0,An=Mt._x1,Mn=Mt._y1,Li=(An-vi)/3;Mt._context.bezierCurveTo(vi+Li,hn+Li*kr,An-Li,Mn-Li*Jr,An,Mn)}function ra(Mt){this._context=Mt}ra.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x0=this._x1=this._y0=this._y1=this._t0=NaN,this._point=0},lineEnd:function(){switch(this._point){case 2:this._context.lineTo(this._x1,this._y1);break;case 3:Fn(this,this._t0,qn(this,this._t0));break}(this._line||this._line!==0&&this._point===1)&&this._context.closePath(),this._line=1-this._line},point:function(Mt,kr){var Jr=NaN;if(Mt=+Mt,kr=+kr,!(Mt===this._x1&&kr===this._y1)){switch(this._point){case 0:this._point=1,this._line?this._context.lineTo(Mt,kr):this._context.moveTo(Mt,kr);break;case 1:this._point=2;break;case 2:this._point=3,Fn(this,qn(this,Jr=On(this,Mt,kr)),Jr);break;default:Fn(this,this._t0,Jr=On(this,Mt,kr));break}this._x0=this._x1,this._x1=Mt,this._y0=this._y1,this._y1=kr,this._t0=Jr}}};function la(Mt){this._context=new Ut(Mt)}(la.prototype=Object.create(ra.prototype)).point=function(Mt,kr){ra.prototype.point.call(this,kr,Mt)};function Ut(Mt){this._context=Mt}Ut.prototype={moveTo:function(Mt,kr){this._context.moveTo(kr,Mt)},closePath:function(){this._context.closePath()},lineTo:function(Mt,kr){this._context.lineTo(kr,Mt)},bezierCurveTo:function(Mt,kr,Jr,vi,hn,An){this._context.bezierCurveTo(kr,Mt,vi,Jr,An,hn)}};function wt(Mt){return new ra(Mt)}function rr(Mt){return new la(Mt)}function nr(Mt){this._context=Mt}nr.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=[],this._y=[]},lineEnd:function(){var Mt=this._x,kr=this._y,Jr=Mt.length;if(Jr)if(this._line?this._context.lineTo(Mt[0],kr[0]):this._context.moveTo(Mt[0],kr[0]),Jr===2)this._context.lineTo(Mt[1],kr[1]);else for(var vi=Er(Mt),hn=Er(kr),An=0,Mn=1;Mn<Jr;++An,++Mn)this._context.bezierCurveTo(vi[0][An],hn[0][An],vi[1][An],hn[1][An],Mt[Mn],kr[Mn]);(this._line||this._line!==0&&Jr===1)&&this._context.closePath(),this._line=1-this._line,this._x=this._y=null},point:function(Mt,kr){this._x.push(+Mt),this._y.push(+kr)}};function Er(Mt){var kr,Jr=Mt.length-1,vi,hn=new Array(Jr),An=new Array(Jr),Mn=new Array(Jr);for(hn[0]=0,An[0]=2,Mn[0]=Mt[0]+2*Mt[1],kr=1;kr<Jr-1;++kr)hn[kr]=1,An[kr]=4,Mn[kr]=4*Mt[kr]+2*Mt[kr+1];for(hn[Jr-1]=2,An[Jr-1]=7,Mn[Jr-1]=8*Mt[Jr-1]+Mt[Jr],kr=1;kr<Jr;++kr)vi=hn[kr]/An[kr-1],An[kr]-=vi,Mn[kr]-=vi*Mn[kr-1];for(hn[Jr-1]=Mn[Jr-1]/An[Jr-1],kr=Jr-2;kr>=0;--kr)hn[kr]=(Mn[kr]-hn[kr+1])/An[kr];for(An[Jr-1]=(Mt[Jr]+hn[Jr-1])/2,kr=0;kr<Jr-1;++kr)An[kr]=2*Mt[kr+1]-hn[kr+1];return[hn,An]}function Xr(Mt){return new nr(Mt)}function ri(Mt,kr){this._context=Mt,this._t=kr}ri.prototype={areaStart:function(){this._line=0},areaEnd:function(){this._line=NaN},lineStart:function(){this._x=this._y=NaN,this._point=0},lineEnd:function(){0<this._t&&this._t<1&&this._point===2&&this._context.lineTo(this._x,this._y),(this._line||this._line!==0&&this._point===1)&&this._context.closePath(),this._line>=0&&(this._t=1-this._t,this._line=1-this._line)},point:function(Mt,kr){switch(Mt=+Mt,kr=+kr,this._point){case 0:this._point=1,this._line?this._context.lineTo(Mt,kr):this._context.moveTo(Mt,kr);break;case 1:this._point=2;default:{if(this._t<=0)this._context.lineTo(this._x,kr),this._context.lineTo(Mt,kr);else{var Jr=this._x*(1-this._t)+Mt*this._t;this._context.lineTo(Jr,this._y),this._context.lineTo(Jr,kr)}break}}this._x=Mt,this._y=kr}};function Qr(Mt){return new ri(Mt,.5)}function Oi(Mt){return new ri(Mt,0)}function $i(Mt){return new ri(Mt,1)}function tn(Mt,kr){if((Mn=Mt.length)>1)for(var Jr=1,vi,hn,An=Mt[kr[0]],Mn,Li=An.length;Jr<Mn;++Jr)for(hn=An,An=Mt[kr[Jr]],vi=0;vi<Li;++vi)An[vi][1]+=An[vi][0]=isNaN(hn[vi][1])?hn[vi][0]:hn[vi][1]}function fn(Mt){for(var kr=Mt.length,Jr=new Array(kr);--kr>=0;)Jr[kr]=kr;return Jr}function yn(Mt,kr){return Mt[kr]}function Sn(){var Mt=r([]),kr=fn,Jr=tn,vi=yn;function hn(An){var Mn=Mt.apply(this,arguments),Li,_n=An.length,ya=Mn.length,Jn=new Array(ya),Ma;for(Li=0;Li<ya;++Li){for(var _o=Mn[Li],No=Jn[Li]=new Array(_n),po=0,Lo;po<_n;++po)No[po]=Lo=[0,+vi(An[po],_o,po,An)],Lo.data=An[po];No.key=_o}for(Li=0,Ma=kr(Jn);Li<ya;++Li)Jn[Ma[Li]].index=Li;return Jr(Jn,Ma),Jn}return hn.keys=function(An){return arguments.length?(Mt=typeof An==\"function\"?An:r(Ce.call(An)),hn):Mt},hn.value=function(An){return arguments.length?(vi=typeof An==\"function\"?An:r(+An),hn):vi},hn.order=function(An){return arguments.length?(kr=An==null?fn:typeof An==\"function\"?An:r(Ce.call(An)),hn):kr},hn.offset=function(An){return arguments.length?(Jr=An==null?tn:An,hn):Jr},hn}function Ba(Mt,kr){if((vi=Mt.length)>0){for(var Jr,vi,hn=0,An=Mt[0].length,Mn;hn<An;++hn){for(Mn=Jr=0;Jr<vi;++Jr)Mn+=Mt[Jr][hn][1]||0;if(Mn)for(Jr=0;Jr<vi;++Jr)Mt[Jr][hn][1]/=Mn}tn(Mt,kr)}}function ua(Mt,kr){if((_n=Mt.length)>0)for(var Jr,vi=0,hn,An,Mn,Li,_n,ya=Mt[kr[0]].length;vi<ya;++vi)for(Mn=Li=0,Jr=0;Jr<_n;++Jr)(An=(hn=Mt[kr[Jr]][vi])[1]-hn[0])>0?(hn[0]=Mn,hn[1]=Mn+=An):An<0?(hn[1]=Li,hn[0]=Li+=An):(hn[0]=0,hn[1]=An)}function 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st.targetLinks.forEach(function(Jt){Nt=Jt.circular&&!pt(Jt,lt)?Nt+1:Nt}),Gt+Nt}function H(st){var lt=st.source.sourceLinks,Gt=0;lt.forEach(function(sr){Gt=sr.circular?Gt+1:Gt});var Nt=st.target.targetLinks,Jt=0;return Nt.forEach(function(sr){Jt=sr.circular?Jt+1:Jt}),!(Gt>1||Jt>1)}function N(st,lt,Gt){return st.sort(oe),st.forEach(function(Nt,Jt){var sr=0;if(pt(Nt,Gt)&&H(Nt))Nt.circularPathData.verticalBuffer=sr+Nt.width/2;else{var wr=0;for(wr;wr<Jt;wr++)if(G(st[Jt],st[wr])){var cr=st[wr].circularPathData.verticalBuffer+st[wr].width/2+lt;sr=cr>sr?cr:sr}Nt.circularPathData.verticalBuffer=sr+Nt.width/2}}),st}function j(st,lt,Gt,Nt){var Jt=5,sr=t.min(st.links,function($e){return $e.source.y0});st.links.forEach(function($e){$e.circular&&($e.circularPathData={})});var wr=st.links.filter(function($e){return $e.circularLinkType==\"top\"});N(wr,lt,Nt);var cr=st.links.filter(function($e){return $e.circularLinkType==\"bottom\"});N(cr,lt,Nt),st.links.forEach(function($e){if($e.circular){if($e.circularPathData.arcRadius=$e.width+g,$e.circularPathData.leftNodeBuffer=Jt,$e.circularPathData.rightNodeBuffer=Jt,$e.circularPathData.sourceWidth=$e.source.x1-$e.source.x0,$e.circularPathData.sourceX=$e.source.x0+$e.circularPathData.sourceWidth,$e.circularPathData.targetX=$e.target.x0,$e.circularPathData.sourceY=$e.y0,$e.circularPathData.targetY=$e.y1,pt($e,Nt)&&H($e))$e.circularPathData.leftSmallArcRadius=g+$e.width/2,$e.circularPathData.leftLargeArcRadius=g+$e.width/2,$e.circularPathData.rightSmallArcRadius=g+$e.width/2,$e.circularPathData.rightLargeArcRadius=g+$e.width/2,$e.circularLinkType==\"bottom\"?($e.circularPathData.verticalFullExtent=$e.source.y1+M+$e.circularPathData.verticalBuffer,$e.circularPathData.verticalLeftInnerExtent=$e.circularPathData.verticalFullExtent-$e.circularPathData.leftLargeArcRadius,$e.circularPathData.verticalRightInnerExtent=$e.circularPathData.verticalFullExtent-$e.circularPathData.rightLargeArcRadius):($e.circularPathData.verticalFullExtent=$e.source.y0-M-$e.circularPathData.verticalBuffer,$e.circularPathData.verticalLeftInnerExtent=$e.circularPathData.verticalFullExtent+$e.circularPathData.leftLargeArcRadius,$e.circularPathData.verticalRightInnerExtent=$e.circularPathData.verticalFullExtent+$e.circularPathData.rightLargeArcRadius);else{var St=$e.source.column,Qt=$e.circularLinkType,Vt=st.links.filter(function(mt){return mt.source.column==St&&mt.circularLinkType==Qt});$e.circularLinkType==\"bottom\"?Vt.sort(Ee):Vt.sort(_e);var _t=0;Vt.forEach(function(mt,er){mt.circularLinkID==$e.circularLinkID&&($e.circularPathData.leftSmallArcRadius=g+$e.width/2+_t,$e.circularPathData.leftLargeArcRadius=g+$e.width/2+er*lt+_t),_t=_t+mt.width}),St=$e.target.column,Vt=st.links.filter(function(mt){return mt.target.column==St&&mt.circularLinkType==Qt}),$e.circularLinkType==\"bottom\"?Vt.sort(me):Vt.sort(Ce),_t=0,Vt.forEach(function(mt,er){mt.circularLinkID==$e.circularLinkID&&($e.circularPathData.rightSmallArcRadius=g+$e.width/2+_t,$e.circularPathData.rightLargeArcRadius=g+$e.width/2+er*lt+_t),_t=_t+mt.width}),$e.circularLinkType==\"bottom\"?($e.circularPathData.verticalFullExtent=Math.max(Gt,$e.source.y1,$e.target.y1)+M+$e.circularPathData.verticalBuffer,$e.circularPathData.verticalLeftInnerExtent=$e.circularPathData.verticalFullExtent-$e.circularPathData.leftLargeArcRadius,$e.circularPathData.verticalRightInnerExtent=$e.circularPathData.verticalFullExtent-$e.circularPathData.rightLargeArcRadius):($e.circularPathData.verticalFullExtent=sr-M-$e.circularPathData.verticalBuffer,$e.circularPathData.verticalLeftInnerExtent=$e.circularPathData.verticalFullExtent+$e.circularPathData.leftLargeArcRadius,$e.circularPathData.verticalRightInnerExtent=$e.circularPathData.verticalFullExtent+$e.circularPathData.rightLargeArcRadius)}$e.circularPathData.leftInnerExtent=$e.circularPathData.sourceX+$e.circularPathData.leftNodeBuffer,$e.circularPathData.rightInnerExtent=$e.circularPathData.targetX-$e.circularPathData.rightNodeBuffer,$e.circularPathData.leftFullExtent=$e.circularPathData.sourceX+$e.circularPathData.leftLargeArcRadius+$e.circularPathData.leftNodeBuffer,$e.circularPathData.rightFullExtent=$e.circularPathData.targetX-$e.circularPathData.rightLargeArcRadius-$e.circularPathData.rightNodeBuffer}if($e.circular)$e.path=re($e);else{var It=n.linkHorizontal().source(function(mt){var er=mt.source.x0+(mt.source.x1-mt.source.x0),lr=mt.y0;return[er,lr]}).target(function(mt){var er=mt.target.x0,lr=mt.y1;return[er,lr]});$e.path=It($e)}})}function re(st){var lt=\"\";return st.circularLinkType==\"top\"?lt=\"M\"+st.circularPathData.sourceX+\" \"+st.circularPathData.sourceY+\" L\"+st.circularPathData.leftInnerExtent+\" \"+st.circularPathData.sourceY+\" A\"+st.circularPathData.leftLargeArcRadius+\" \"+st.circularPathData.leftSmallArcRadius+\" 0 0 0 \"+st.circularPathData.leftFullExtent+\" \"+(st.circularPathData.sourceY-st.circularPathData.leftSmallArcRadius)+\" L\"+st.circularPathData.leftFullExtent+\" \"+st.circularPathData.verticalLeftInnerExtent+\" A\"+st.circularPathData.leftLargeArcRadius+\" \"+st.circularPathData.leftLargeArcRadius+\" 0 0 0 \"+st.circularPathData.leftInnerExtent+\" \"+st.circularPathData.verticalFullExtent+\" L\"+st.circularPathData.rightInnerExtent+\" \"+st.circularPathData.verticalFullExtent+\" A\"+st.circularPathData.rightLargeArcRadius+\" \"+st.circularPathData.rightLargeArcRadius+\" 0 0 0 \"+st.circularPathData.rightFullExtent+\" \"+st.circularPathData.verticalRightInnerExtent+\" L\"+st.circularPathData.rightFullExtent+\" \"+(st.circularPathData.targetY-st.circularPathData.rightSmallArcRadius)+\" A\"+st.circularPathData.rightLargeArcRadius+\" \"+st.circularPathData.rightSmallArcRadius+\" 0 0 0 \"+st.circularPathData.rightInnerExtent+\" \"+st.circularPathData.targetY+\" L\"+st.circularPathData.targetX+\" \"+st.circularPathData.targetY:lt=\"M\"+st.circularPathData.sourceX+\" \"+st.circularPathData.sourceY+\" L\"+st.circularPathData.leftInnerExtent+\" \"+st.circularPathData.sourceY+\" A\"+st.circularPathData.leftLargeArcRadius+\" \"+st.circularPathData.leftSmallArcRadius+\" 0 0 1 \"+st.circularPathData.leftFullExtent+\" \"+(st.circularPathData.sourceY+st.circularPathData.leftSmallArcRadius)+\" L\"+st.circularPathData.leftFullExtent+\" \"+st.circularPathData.verticalLeftInnerExtent+\" A\"+st.circularPathData.leftLargeArcRadius+\" \"+st.circularPathData.leftLargeArcRadius+\" 0 0 1 \"+st.circularPathData.leftInnerExtent+\" \"+st.circularPathData.verticalFullExtent+\" L\"+st.circularPathData.rightInnerExtent+\" \"+st.circularPathData.verticalFullExtent+\" A\"+st.circularPathData.rightLargeArcRadius+\" \"+st.circularPathData.rightLargeArcRadius+\" 0 0 1 \"+st.circularPathData.rightFullExtent+\" \"+st.circularPathData.verticalRightInnerExtent+\" L\"+st.circularPathData.rightFullExtent+\" \"+(st.circularPathData.targetY+st.circularPathData.rightSmallArcRadius)+\" A\"+st.circularPathData.rightLargeArcRadius+\" \"+st.circularPathData.rightSmallArcRadius+\" 0 0 1 \"+st.circularPathData.rightInnerExtent+\" \"+st.circularPathData.targetY+\" L\"+st.circularPathData.targetX+\" \"+st.circularPathData.targetY,lt}function oe(st,lt){return ie(st)==ie(lt)?st.circularLinkType==\"bottom\"?Ee(st,lt):_e(st,lt):ie(lt)-ie(st)}function _e(st,lt){return st.y0-lt.y0}function Ee(st,lt){return lt.y0-st.y0}function Ce(st,lt){return st.y1-lt.y1}function me(st,lt){return lt.y1-st.y1}function ie(st){return st.target.column-st.source.column}function Se(st){return st.target.x0-st.source.x1}function Le(st,lt){var Gt=V(st),Nt=Se(lt)/Math.tan(Gt),Jt=ut(st)==\"up\"?st.y1+Nt:st.y1-Nt;return Jt}function Ae(st,lt){var Gt=V(st),Nt=Se(lt)/Math.tan(Gt),Jt=ut(st)==\"up\"?st.y1-Nt:st.y1+Nt;return Jt}function Fe(st,lt,Gt,Nt){st.links.forEach(function(Jt){if(!Jt.circular&&Jt.target.column-Jt.source.column>1){var sr=Jt.source.column+1,wr=Jt.target.column-1,cr=1,$e=wr-sr+1;for(cr=1;sr<=wr;sr++,cr++)st.nodes.forEach(function(St){if(St.column==sr){var Qt=cr/($e+1),Vt=Math.pow(1-Qt,3),_t=3*Qt*Math.pow(1-Qt,2),It=3*Math.pow(Qt,2)*(1-Qt),mt=Math.pow(Qt,3),er=Vt*Jt.y0+_t*Jt.y0+It*Jt.y1+mt*Jt.y1,lr=er-Jt.width/2,Tr=er+Jt.width/2,Lr;lr>St.y0&&lr<St.y1?(Lr=St.y1-lr+10,Lr=St.circularLinkType==\"bottom\"?Lr:-Lr,St=ge(St,Lr,lt,Gt),st.nodes.forEach(function(ti){C(ti,Nt)==C(St,Nt)||ti.column!=St.column||Pe(St,ti)&&ge(ti,Lr,lt,Gt)})):Tr>St.y0&&Tr<St.y1?(Lr=Tr-St.y0+10,St=ge(St,Lr,lt,Gt),st.nodes.forEach(function(ti){C(ti,Nt)==C(St,Nt)||ti.column!=St.column||ti.y0<St.y1&&ti.y1>St.y1&&ge(ti,Lr,lt,Gt)})):lr<St.y0&&Tr>St.y1&&(Lr=Tr-St.y0+10,St=ge(St,Lr,lt,Gt),st.nodes.forEach(function(ti){C(ti,Nt)==C(St,Nt)||ti.column!=St.column||ti.y0<St.y1&&ti.y1>St.y1&&ge(ti,Lr,lt,Gt)}))}})}})}function Pe(st,lt){return st.y0>lt.y0&&st.y0<lt.y1||st.y1>lt.y0&&st.y1<lt.y1?!0:st.y0<lt.y0&&st.y1>lt.y1}function ge(st,lt,Gt,Nt){return st.y0+lt>=Gt&&st.y1+lt<=Nt&&(st.y0=st.y0+lt,st.y1=st.y1+lt,st.targetLinks.forEach(function(Jt){Jt.y1=Jt.y1+lt}),st.sourceLinks.forEach(function(Jt){Jt.y0=Jt.y0+lt})),st}function Re(st,lt,Gt,Nt){st.nodes.forEach(function(Jt){Nt&&Jt.y+(Jt.y1-Jt.y0)>lt&&(Jt.y=Jt.y-(Jt.y+(Jt.y1-Jt.y0)-lt));var sr=st.links.filter(function($e){return C($e.source,Gt)==C(Jt,Gt)}),wr=sr.length;wr>1&&sr.sort(function($e,St){if(!$e.circular&&!St.circular){if($e.target.column==St.target.column)return $e.y1-St.y1;if(Ze($e,St)){if($e.target.column>St.target.column){var Qt=Ae(St,$e);return $e.y1-Qt}if(St.target.column>$e.target.column){var Vt=Ae($e,St);return Vt-St.y1}}else return $e.y1-St.y1}if($e.circular&&!St.circular)return $e.circularLinkType==\"top\"?-1:1;if(St.circular&&!$e.circular)return St.circularLinkType==\"top\"?1:-1;if($e.circular&&St.circular)return $e.circularLinkType===St.circularLinkType&&$e.circularLinkType==\"top\"?$e.target.column===St.target.column?$e.target.y1-St.target.y1:St.target.column-$e.target.column:$e.circularLinkType===St.circularLinkType&&$e.circularLinkType==\"bottom\"?$e.target.column===St.target.column?St.target.y1-$e.target.y1:$e.target.column-St.target.column:$e.circularLinkType==\"top\"?-1:1});var cr=Jt.y0;sr.forEach(function($e){$e.y0=cr+$e.width/2,cr=cr+$e.width}),sr.forEach(function($e,St){if($e.circularLinkType==\"bottom\"){var Qt=St+1,Vt=0;for(Qt;Qt<wr;Qt++)Vt=Vt+sr[Qt].width;$e.y0=Jt.y1-Vt-$e.width/2}})})}function ce(st,lt,Gt){st.nodes.forEach(function(Nt){var Jt=st.links.filter(function(cr){return C(cr.target,Gt)==C(Nt,Gt)}),sr=Jt.length;sr>1&&Jt.sort(function(cr,$e){if(!cr.circular&&!$e.circular){if(cr.source.column==$e.source.column)return cr.y0-$e.y0;if(Ze(cr,$e)){if($e.source.column<cr.source.column){var St=Le($e,cr);return cr.y0-St}if(cr.source.column<$e.source.column){var Qt=Le(cr,$e);return Qt-$e.y0}}else return cr.y0-$e.y0}if(cr.circular&&!$e.circular)return cr.circularLinkType==\"top\"?-1:1;if($e.circular&&!cr.circular)return $e.circularLinkType==\"top\"?1:-1;if(cr.circular&&$e.circular)return cr.circularLinkType===$e.circularLinkType&&cr.circularLinkType==\"top\"?cr.source.column===$e.source.column?cr.source.y1-$e.source.y1:cr.source.column-$e.source.column:cr.circularLinkType===$e.circularLinkType&&cr.circularLinkType==\"bottom\"?cr.source.column===$e.source.column?cr.source.y1-$e.source.y1:$e.source.column-cr.source.column:cr.circularLinkType==\"top\"?-1:1});var wr=Nt.y0;Jt.forEach(function(cr){cr.y1=wr+cr.width/2,wr=wr+cr.width}),Jt.forEach(function(cr,$e){if(cr.circularLinkType==\"bottom\"){var St=$e+1,Qt=0;for(St;St<sr;St++)Qt=Qt+Jt[St].width;cr.y1=Nt.y1-Qt-cr.width/2}})})}function Ze(st,lt){return ut(st)==ut(lt)}function ut(st){return st.y0-st.y1>0?\"up\":\"down\"}function pt(st,lt){return C(st.source,lt)==C(st.target,lt)}function Zt(st,lt,Gt){var Nt=st.nodes,Jt=st.links,sr=!1,wr=!1;if(Jt.forEach(function(_t){_t.circularLinkType==\"top\"?sr=!0:_t.circularLinkType==\"bottom\"&&(wr=!0)}),sr==!1||wr==!1){var cr=t.min(Nt,function(_t){return _t.y0}),$e=t.max(Nt,function(_t){return _t.y1}),St=$e-cr,Qt=Gt-lt,Vt=Qt/St;Nt.forEach(function(_t){var It=(_t.y1-_t.y0)*Vt;_t.y0=(_t.y0-cr)*Vt,_t.y1=_t.y0+It}),Jt.forEach(function(_t){_t.y0=(_t.y0-cr)*Vt,_t.y1=(_t.y1-cr)*Vt,_t.width=_t.width*Vt})}}e.sankeyCircular=T,e.sankeyCenter=u,e.sankeyLeft=o,e.sankeyRight=s,e.sankeyJustify=l,Object.defineProperty(e,\"__esModule\",{value:!0})})});var jJ=ye((e2r,WWe)=>{\"use strict\";WWe.exports={nodeTextOffsetHorizontal:4,nodeTextOffsetVertical:3,nodePadAcross:10,sankeyIterations:50,forceIterations:5,forceTicksPerFrame:10,duration:500,ease:\"linear\",cn:{sankey:\"sankey\",sankeyLinks:\"sankey-links\",sankeyLink:\"sankey-link\",sankeyNodeSet:\"sankey-node-set\",sankeyNode:\"sankey-node\",nodeRect:\"node-rect\",nodeLabel:\"node-label\"}}});var aXe=ye((t2r,nXe)=>{\"use strict\";var XWe=zWe(),zZt=(D2(),ob(R2)).interpolateNumber,I5=Oa(),Jk=UWe(),OZt=jWe(),Nu=jJ(),R5=cd(),ow=ka(),qZt=So(),p1=Dr(),ZJ=p1.strTranslate,BZt=p1.strRotate,YJ=Jm(),$k=YJ.keyFun,M7=YJ.repeat,QWe=YJ.unwrap,ZWe=ru(),NZt=qa(),eXe=$h(),UZt=eXe.CAP_SHIFT,VZt=eXe.LINE_SPACING,GZt=3;function HZt(e,t,r){var n=QWe(t),i=n.trace,a=i.domain,o=i.orientation===\"h\",s=i.node.pad,l=i.node.thickness,u={justify:Jk.sankeyJustify,left:Jk.sankeyLeft,right:Jk.sankeyRight,center:Jk.sankeyCenter}[i.node.align],c=e.width*(a.x[1]-a.x[0]),f=e.height*(a.y[1]-a.y[0]),h=n._nodes,d=n._links,v=n.circular,_;v?_=OZt.sankeyCircular().circularLinkGap(0):_=Jk.sankey(),_.iterations(Nu.sankeyIterations).size(o?[c,f]:[f,c]).nodeWidth(l).nodePadding(s).nodeId(function(V){return V.pointNumber}).nodeAlign(u).nodes(h).links(d);var b=_();_.nodePadding()<s&&p1.warn(\"node.pad was reduced to \",_.nodePadding(),\" to fit within the figure.\");var p,k,E;for(var S in n._groupLookup){var L=parseInt(n._groupLookup[S]),x;for(p=0;p<b.nodes.length;p++)if(b.nodes[p].pointNumber===L){x=b.nodes[p];break}if(x){var C={pointNumber:parseInt(S),x0:x.x0,x1:x.x1,y0:x.y0,y1:x.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};b.nodes.unshift(C),x.childrenNodes.unshift(C)}}function M(){for(p=0;p<b.nodes.length;p++){var V=b.nodes[p],G={},Z,H;for(k=0;k<V.targetLinks.length;k++)H=V.targetLinks[k],Z=H.source.pointNumber+\":\"+H.target.pointNumber,G.hasOwnProperty(Z)||(G[Z]=[]),G[Z].push(H);var N=Object.keys(G);for(k=0;k<N.length;k++){Z=N[k];var j=G[Z],re=0,oe={};for(E=0;E<j.length;E++)H=j[E],oe[H.label]||(oe[H.label]=0),oe[H.label]+=H.value,re+=H.value;for(E=0;E<j.length;E++)H=j[E],H.flow={value:re,labelConcentration:oe[H.label]/re,concentration:H.value/re,links:j},H.concentrationscale&&(H.color=R5(H.concentrationscale(H.flow.labelConcentration)))}var _e=0;for(k=0;k<V.sourceLinks.length;k++)_e+=V.sourceLinks[k].value;for(k=0;k<V.sourceLinks.length;k++)H=V.sourceLinks[k],H.concentrationOut=H.value/_e;var Ee=0;for(k=0;k<V.targetLinks.length;k++)Ee+=V.targetLinks[k].value;for(k=0;k<V.targetLinks.length;k++)H=V.targetLinks[k],H.concenrationIn=H.value/Ee}}M();function g(V){V.forEach(function(G){var Z,H,N=0,j=G.length,re;for(G.sort(function(oe,_e){return oe.y0-_e.y0}),re=0;re<j;++re)Z=G[re],Z.y0>=N||(H=N-Z.y0,H>1e-6&&(Z.y0+=H,Z.y1+=H)),N=Z.y1+s})}function P(V){var G=V.map(function(_e,Ee){return{x0:_e.x0,index:Ee}}).sort(function(_e,Ee){return _e.x0-Ee.x0}),Z=[],H=-1,N,j=-1/0,re;for(p=0;p<G.length;p++){var oe=V[G[p].index];oe.x0>j+l&&(H+=1,N=oe.x0),j=oe.x0,Z[H]||(Z[H]=[]),Z[H].push(oe),re=N-oe.x0,oe.x0+=re,oe.x1+=re}return Z}if(i.node.x.length&&i.node.y.length){for(p=0;p<Math.min(i.node.x.length,i.node.y.length,b.nodes.length);p++)if(i.node.x[p]&&i.node.y[p]){var T=[i.node.x[p]*c,i.node.y[p]*f];b.nodes[p].x0=T[0]-l/2,b.nodes[p].x1=T[0]+l/2;var z=b.nodes[p].y1-b.nodes[p].y0;b.nodes[p].y0=T[1]-z/2,b.nodes[p].y1=T[1]+z/2}if(i.arrangement===\"snap\"){h=b.nodes;var O=P(h);g(O)}_.update(b)}return{circular:v,key:r,trace:i,guid:p1.randstr(),horizontal:o,width:c,height:f,nodePad:i.node.pad,nodeLineColor:i.node.line.color,nodeLineWidth:i.node.line.width,linkLineColor:i.link.line.color,linkLineWidth:i.link.line.width,linkArrowLength:i.link.arrowlen,valueFormat:i.valueformat,valueSuffix:i.valuesuffix,textFont:i.textfont,translateX:a.x[0]*e.width+e.margin.l,translateY:e.height-a.y[1]*e.height+e.margin.t,dragParallel:o?f:c,dragPerpendicular:o?c:f,arrangement:i.arrangement,sankey:_,graph:b,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function jZt(e,t,r){var n=R5(t.color),i=R5(t.hovercolor),a=t.source.label+\"|\"+t.target.label,o=a+\"__\"+r;return t.trace=e.trace,t.curveNumber=e.trace.index,{circular:e.circular,key:o,traceId:e.key,pointNumber:t.pointNumber,link:t,tinyColorHue:ow.tinyRGB(n),tinyColorAlpha:n.getAlpha(),tinyColorHoverHue:ow.tinyRGB(i),tinyColorHoverAlpha:i.getAlpha(),linkPath:KJ,linkLineColor:e.linkLineColor,linkLineWidth:e.linkLineWidth,linkArrowLength:e.linkArrowLength,valueFormat:e.valueFormat,valueSuffix:e.valueSuffix,sankey:e.sankey,parent:e,interactionState:e.interactionState,flow:t.flow}}function WZt(e,t){var r=\"\",n=e.width/2,i=e.circularPathData,a=i.sourceX+i.verticalBuffer<i.targetX,o=i.rightFullExtent-i.rightLargeArcRadius-t<=i.leftFullExtent-n,s=Math.abs(i.rightFullExtent-i.leftFullExtent-n)<n;return e.circularLinkType===\"top\"?(r=\"M \"+(i.targetX-t)+\" \"+(i.targetY+n)+\" L \"+(i.rightInnerExtent-t)+\" \"+(i.targetY+n)+\"A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightSmallArcRadius+n)+\" 0 0 1 \"+(i.rightFullExtent-n-t)+\" \"+(i.targetY-i.rightSmallArcRadius)+\"L \"+(i.rightFullExtent-n-t)+\" 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\"+(i.leftSmallArcRadius+n)+\" 0 0 0 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent:a?r+=\" A \"+(i.leftLargeArcRadius+n)+\" \"+(i.leftSmallArcRadius+n)+\" 0 0 1 \"+(i.leftFullExtent+n)+\" \"+(i.verticalFullExtent-n)+\" L \"+(i.rightFullExtent-n-t)+\" \"+(i.verticalFullExtent-n)+\" A \"+(i.leftLargeArcRadius+n)+\" \"+(i.leftSmallArcRadius+n)+\" 0 0 1 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent:r+=\" A \"+(i.leftLargeArcRadius-n)+\" \"+(i.leftLargeArcRadius-n)+\" 0 0 0 \"+i.leftInnerExtent+\" \"+(i.verticalFullExtent+n)+\" L \"+(i.rightInnerExtent-t)+\" \"+(i.verticalFullExtent+n)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightLargeArcRadius-n)+\" 0 0 0 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent,r+=\" L \"+(i.rightFullExtent+n-t)+\" \"+(i.targetY-i.rightSmallArcRadius)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 0 \"+(i.rightInnerExtent-t)+\" \"+(i.targetY-n)+\" L \"+(i.targetX-t)+\" \"+(i.targetY-n)+(t>0?\" L \"+i.targetX+\" \"+i.targetY:\"\")+\"Z\"):(r=\"M \"+(i.targetX-t)+\" \"+(i.targetY-n)+\"  L \"+(i.rightInnerExtent-t)+\" \"+(i.targetY-n)+\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightSmallArcRadius+n)+\" 0 0 0 \"+(i.rightFullExtent-n-t)+\" \"+(i.targetY+i.rightSmallArcRadius)+\" L \"+(i.rightFullExtent-n-t)+\" \"+i.verticalRightInnerExtent,a&&o?r+=\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightLargeArcRadius+n)+\" 0 0 0 \"+(i.rightInnerExtent-n-t)+\" \"+(i.verticalFullExtent+n)+\" L \"+(i.rightFullExtent+n-t-(i.rightLargeArcRadius-n))+\" \"+(i.verticalFullExtent+n)+\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightLargeArcRadius+n)+\" 0 0 0 \"+(i.leftFullExtent+n)+\" \"+i.verticalLeftInnerExtent:a?r+=\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 1 \"+(i.rightFullExtent-t-n-(i.rightLargeArcRadius-n))+\" \"+(i.verticalFullExtent-n)+\" L \"+(i.leftFullExtent+n+(i.rightLargeArcRadius-n))+\" \"+(i.verticalFullExtent-n)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 1 \"+(i.leftFullExtent+n)+\" \"+i.verticalLeftInnerExtent:r+=\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightLargeArcRadius+n)+\" 0 0 0 \"+(i.rightInnerExtent-t)+\" \"+(i.verticalFullExtent+n)+\" L \"+i.leftInnerExtent+\" \"+(i.verticalFullExtent+n)+\" A \"+(i.leftLargeArcRadius+n)+\" \"+(i.leftLargeArcRadius+n)+\" 0 0 0 \"+(i.leftFullExtent+n)+\" \"+i.verticalLeftInnerExtent,r+=\" L \"+(i.leftFullExtent+n)+\" \"+(i.sourceY+i.leftSmallArcRadius)+\" A \"+(i.leftLargeArcRadius+n)+\" \"+(i.leftSmallArcRadius+n)+\" 0 0 0 \"+i.leftInnerExtent+\" \"+(i.sourceY-n)+\" L \"+i.sourceX+\" \"+(i.sourceY-n)+\" L \"+i.sourceX+\" \"+(i.sourceY+n)+\" L \"+i.leftInnerExtent+\" \"+(i.sourceY+n)+\" A \"+(i.leftLargeArcRadius-n)+\" \"+(i.leftSmallArcRadius-n)+\" 0 0 1 \"+(i.leftFullExtent-n)+\" \"+(i.sourceY+i.leftSmallArcRadius)+\" L \"+(i.leftFullExtent-n)+\" \"+i.verticalLeftInnerExtent,a&&o?r+=\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 1 \"+(i.leftFullExtent-n-(i.rightLargeArcRadius-n))+\" \"+(i.verticalFullExtent-n)+\" L \"+(i.rightFullExtent+n-t+(i.rightLargeArcRadius-n))+\" \"+(i.verticalFullExtent-n)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 1 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent:a?r+=\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightLargeArcRadius+n)+\" 0 0 0 \"+(i.leftFullExtent+n)+\" \"+(i.verticalFullExtent+n)+\" L \"+(i.rightFullExtent-t-n)+\" \"+(i.verticalFullExtent+n)+\" A \"+(i.rightLargeArcRadius+n)+\" \"+(i.rightLargeArcRadius+n)+\" 0 0 0 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent:r+=\" A \"+(i.leftLargeArcRadius-n)+\" \"+(i.leftLargeArcRadius-n)+\" 0 0 1 \"+i.leftInnerExtent+\" \"+(i.verticalFullExtent-n)+\" L \"+(i.rightInnerExtent-t)+\" \"+(i.verticalFullExtent-n)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightLargeArcRadius-n)+\" 0 0 1 \"+(i.rightFullExtent+n-t)+\" \"+i.verticalRightInnerExtent,r+=\" L \"+(i.rightFullExtent+n-t)+\" \"+(i.targetY+i.rightSmallArcRadius)+\" A \"+(i.rightLargeArcRadius-n)+\" \"+(i.rightSmallArcRadius-n)+\" 0 0 1 \"+(i.rightInnerExtent-t)+\" \"+(i.targetY+n)+\" L \"+(i.targetX-t)+\" \"+(i.targetY+n)+(t>0?\" L \"+i.targetX+\" \"+i.targetY:\"\")+\"Z\"),r}function KJ(){var e=.5;function t(r){var n=r.linkArrowLength;if(r.link.circular)return WZt(r.link,n);var i=Math.abs((r.link.target.x0-r.link.source.x1)/2);n>i&&(n=i);var a=r.link.source.x1,o=r.link.target.x0-n,s=zZt(a,o),l=s(e),u=s(1-e),c=r.link.y0-r.link.width/2,f=r.link.y0+r.link.width/2,h=r.link.y1-r.link.width/2,d=r.link.y1+r.link.width/2,v=\"M\"+a+\",\"+c,_=\"C\"+l+\",\"+c+\" \"+u+\",\"+h+\" \"+o+\",\"+h,b=\"C\"+u+\",\"+d+\" \"+l+\",\"+f+\" \"+a+\",\"+f,p=n>0?\"L\"+(o+n)+\",\"+(h+r.link.width/2):\"\";return p+=\"L\"+o+\",\"+d,v+_+p+b+\"Z\"}return t}function XZt(e,t){var r=R5(t.color),n=Nu.nodePadAcross,i=e.nodePad/2;t.dx=t.x1-t.x0,t.dy=t.y1-t.y0;var a=t.dx,o=Math.max(.5,t.dy),s=\"node_\"+t.pointNumber;return t.group&&(s=p1.randstr()),t.trace=e.trace,t.curveNumber=e.trace.index,{index:t.pointNumber,key:s,partOfGroup:t.partOfGroup||!1,group:t.group,traceId:e.key,trace:e.trace,node:t,nodePad:e.nodePad,nodeLineColor:e.nodeLineColor,nodeLineWidth:e.nodeLineWidth,textFont:e.textFont,size:e.horizontal?e.height:e.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:e.horizontal?t.dy/2+1:t.dx/2+1,left:t.originalLayer===1,sizeAcross:e.width,forceLayouts:e.forceLayouts,horizontal:e.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:ow.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:e.valueFormat,valueSuffix:e.valueSuffix,sankey:e.sankey,graph:e.graph,arrangement:e.arrangement,uniqueNodeLabelPathId:[e.guid,e.key,s].join(\"_\"),interactionState:e.interactionState,figure:e}}function XJ(e){e.attr(\"transform\",function(t){return ZJ(t.node.x0.toFixed(3),t.node.y0.toFixed(3))})}function ZZt(e){e.call(XJ)}function tXe(e,t){e.call(ZZt),t.attr(\"d\",KJ())}function YWe(e){e.attr(\"width\",function(t){return t.node.x1-t.node.x0}).attr(\"height\",function(t){return t.visibleHeight})}function WJ(e){return e.link.width>1||e.linkLineWidth>0}function KWe(e){var t=ZJ(e.translateX,e.translateY);return t+(e.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function JWe(e,t,r){e.on(\".basic\",null).on(\"mouseover.basic\",function(n){!n.interactionState.dragInProgress&&!n.partOfGroup&&(r.hover(this,n,t),n.interactionState.hovered=[this,n])}).on(\"mousemove.basic\",function(n){!n.interactionState.dragInProgress&&!n.partOfGroup&&(r.follow(this,n),n.interactionState.hovered=[this,n])}).on(\"mouseout.basic\",function(n){!n.interactionState.dragInProgress&&!n.partOfGroup&&(r.unhover(this,n,t),n.interactionState.hovered=!1)}).on(\"click.basic\",function(n){n.interactionState.hovered&&(r.unhover(this,n,t),n.interactionState.hovered=!1),!n.interactionState.dragInProgress&&!n.partOfGroup&&r.select(this,n,t)})}function YZt(e,t,r,n){var i=I5.behavior.drag().origin(function(a){return{x:a.node.x0+a.visibleWidth/2,y:a.node.y0+a.visibleHeight/2}}).on(\"dragstart\",function(a){if(a.arrangement!==\"fixed\"&&(p1.ensureSingle(n._fullLayout._infolayer,\"g\",\"dragcover\",function(s){n._fullLayout._dragCover=s}),p1.raiseToTop(this),a.interactionState.dragInProgress=a.node,$We(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),a.arrangement===\"snap\")){var o=a.traceId+\"|\"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):KZt(e,o,a,n),JZt(e,t,a,o,n)}}).on(\"drag\",function(a){if(a.arrangement!==\"fixed\"){var o=I5.event.x,s=I5.event.y;a.arrangement===\"snap\"?(a.node.x0=o-a.visibleWidth/2,a.node.x1=o+a.visibleWidth/2,a.node.y0=s-a.visibleHeight/2,a.node.y1=s+a.visibleHeight/2):(a.arrangement===\"freeform\"&&(a.node.x0=o-a.visibleWidth/2,a.node.x1=o+a.visibleWidth/2),s=Math.max(0,Math.min(a.size-a.visibleHeight/2,s)),a.node.y0=s-a.visibleHeight/2,a.node.y1=s+a.visibleHeight/2),$We(a.node),a.arrangement!==\"snap\"&&(a.sankey.update(a.graph),tXe(e.filter(iXe(a)),t))}}).on(\"dragend\",function(a){if(a.arrangement!==\"fixed\"){a.interactionState.dragInProgress=!1;for(var o=0;o<a.node.childrenNodes.length;o++)a.node.childrenNodes[o].x=a.node.x,a.node.childrenNodes[o].y=a.node.y;a.arrangement!==\"snap\"&&rXe(a,n)}});e.on(\".drag\",null).call(i)}function KZt(e,t,r,n){eYt(r.graph.nodes);var i=r.graph.nodes.filter(function(a){return a.originalX===r.node.originalX}).filter(function(a){return!a.partOfGroup});r.forceLayouts[t]=XWe.forceSimulation(i).alphaDecay(0).force(\"collide\",XWe.forceCollide().radius(function(a){return a.dy/2+r.nodePad/2}).strength(1).iterations(Nu.forceIterations)).force(\"constrain\",$Zt(e,t,i,r,n)).stop()}function JZt(e,t,r,n,i){window.requestAnimationFrame(function a(){var o;for(o=0;o<Nu.forceTicksPerFrame;o++)r.forceLayouts[n].tick();var s=r.graph.nodes;if(tYt(s),r.sankey.update(r.graph),tXe(e.filter(iXe(r)),t),r.forceLayouts[n].alpha()>0)window.requestAnimationFrame(a);else{var l=r.node.originalX;r.node.x0=l-r.visibleWidth/2,r.node.x1=l+r.visibleWidth/2,rXe(r,i)}})}function $Zt(e,t,r,n){return function(){for(var a=0,o=0;o<r.length;o++){var s=r[o];s===n.interactionState.dragInProgress?(s.x=s.lastDraggedX,s.y=s.lastDraggedY):(s.vx=(s.originalX-s.x)/Nu.forceTicksPerFrame,s.y=Math.min(n.size-s.dy/2,Math.max(s.dy/2,s.y))),a=Math.max(a,Math.abs(s.vx),Math.abs(s.vy))}!n.interactionState.dragInProgress&&a<.1&&n.forceLayouts[t].alpha()>0&&n.forceLayouts[t].alpha(0)}}function rXe(e,t){for(var r=[],n=[],i=0;i<e.graph.nodes.length;i++){var a=(e.graph.nodes[i].x0+e.graph.nodes[i].x1)/2,o=(e.graph.nodes[i].y0+e.graph.nodes[i].y1)/2;r.push(a/e.figure.width),n.push(o/e.figure.height)}NZt.call(\"_guiRestyle\",t,{\"node.x\":[r],\"node.y\":[n]},e.trace.index).then(function(){t._fullLayout._dragCover&&t._fullLayout._dragCover.remove()})}function QZt(e){var t=[],r;for(r=0;r<e.length;r++)e[r].originalX=(e[r].x0+e[r].x1)/2,e[r].originalY=(e[r].y0+e[r].y1)/2,t.indexOf(e[r].originalX)===-1&&t.push(e[r].originalX);for(t.sort(function(n,i){return n-i}),r=0;r<e.length;r++)e[r].originalLayerIndex=t.indexOf(e[r].originalX),e[r].originalLayer=e[r].originalLayerIndex/(t.length-1)}function $We(e){e.lastDraggedX=e.x0+e.dx/2,e.lastDraggedY=e.y0+e.dy/2}function iXe(e){return function(t){return t.node.originalX===e.node.originalX}}function eYt(e){for(var t=0;t<e.length;t++)e[t].y=(e[t].y0+e[t].y1)/2,e[t].x=(e[t].x0+e[t].x1)/2}function tYt(e){for(var t=0;t<e.length;t++)e[t].y0=e[t].y-e[t].dy/2,e[t].y1=e[t].y0+e[t].dy,e[t].x0=e[t].x-e[t].dx/2,e[t].x1=e[t].x0+e[t].dx}nXe.exports=function(e,t,r,n,i){var a=e._context.staticPlot,o=!1;p1.ensureSingle(e._fullLayout._infolayer,\"g\",\"first-render\",function(){o=!0});var s=e._fullLayout._dragCover,l=r.filter(function(b){return QWe(b).trace.visible}).map(HZt.bind(null,n)),u=t.selectAll(\".\"+Nu.cn.sankey).data(l,$k);u.exit().remove(),u.enter().append(\"g\").classed(Nu.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",a?\"none\":\"auto\").attr(\"transform\",KWe),u.each(function(b,p){e._fullData[p]._sankey=b;var k=\"bgsankey-\"+b.trace.uid+\"-\"+p;p1.ensureSingle(e._fullLayout._draggers,\"rect\",k),e._fullData[p]._bgRect=I5.select(\".\"+k),e._fullData[p]._bgRect.style(\"pointer-events\",a?\"none\":\"all\").attr(\"width\",b.width).attr(\"height\",b.height).attr(\"x\",b.translateX).attr(\"y\",b.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})}),u.transition().ease(Nu.ease).duration(Nu.duration).attr(\"transform\",KWe);var c=u.selectAll(\".\"+Nu.cn.sankeyLinks).data(M7,$k);c.enter().append(\"g\").classed(Nu.cn.sankeyLinks,!0).style(\"fill\",\"none\");var f=c.selectAll(\".\"+Nu.cn.sankeyLink).data(function(b){var p=b.graph.links;return p.filter(function(k){return k.value}).map(jZt.bind(null,b))},$k);f.enter().append(\"path\").classed(Nu.cn.sankeyLink,!0).call(JWe,u,i.linkEvents),f.style(\"stroke\",function(b){return WJ(b)?ow.tinyRGB(R5(b.linkLineColor)):b.tinyColorHue}).style(\"stroke-opacity\",function(b){return WJ(b)?ow.opacity(b.linkLineColor):b.tinyColorAlpha}).style(\"fill\",function(b){return b.tinyColorHue}).style(\"fill-opacity\",function(b){return b.tinyColorAlpha}).style(\"stroke-width\",function(b){return WJ(b)?b.linkLineWidth:1}).attr(\"d\",KJ()),f.style(\"opacity\",function(){return e._context.staticPlot||o||s?1:0}).transition().ease(Nu.ease).duration(Nu.duration).style(\"opacity\",1),f.exit().transition().ease(Nu.ease).duration(Nu.duration).style(\"opacity\",0).remove();var h=u.selectAll(\".\"+Nu.cn.sankeyNodeSet).data(M7,$k);h.enter().append(\"g\").classed(Nu.cn.sankeyNodeSet,!0),h.style(\"cursor\",function(b){switch(b.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}});var d=h.selectAll(\".\"+Nu.cn.sankeyNode).data(function(b){var p=b.graph.nodes;return QZt(p),p.map(XZt.bind(null,b))},$k);d.enter().append(\"g\").classed(Nu.cn.sankeyNode,!0).call(XJ).style(\"opacity\",function(b){return(e._context.staticPlot||o)&&!b.partOfGroup?1:0}),d.call(JWe,u,i.nodeEvents).call(YZt,f,i,e),d.transition().ease(Nu.ease).duration(Nu.duration).call(XJ).style(\"opacity\",function(b){return b.partOfGroup?0:1}),d.exit().transition().ease(Nu.ease).duration(Nu.duration).style(\"opacity\",0).remove();var v=d.selectAll(\".\"+Nu.cn.nodeRect).data(M7);v.enter().append(\"rect\").classed(Nu.cn.nodeRect,!0).call(YWe),v.style(\"stroke-width\",function(b){return b.nodeLineWidth}).style(\"stroke\",function(b){return 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pXe=ye(sw=>{\"use strict\";var nYt=mc().overrideAll,aYt=Id().getModuleCalcData,oYt=QJ(),sYt=B1(),lYt=Ag(),uYt=yv(),cYt=Of().prepSelect,e$=Dr(),fYt=qa(),k7=\"sankey\";sw.name=k7;sw.baseLayoutAttrOverrides=nYt({hoverlabel:sYt.hoverlabel},\"plot\",\"nested\");sw.plot=function(e){var t=aYt(e.calcdata,k7)[0];oYt(e,t),sw.updateFx(e)};sw.clean=function(e,t,r,n){var i=n._has&&n._has(k7),a=t._has&&t._has(k7);i&&!a&&(n._paperdiv.selectAll(\".sankey\").remove(),n._paperdiv.selectAll(\".bgsankey\").remove())};sw.updateFx=function(e){for(var t=0;t<e._fullData.length;t++)hYt(e,t)};function hYt(e,t){var r=e._fullData[t],n=e._fullLayout,i=n.dragmode,a=n.dragmode===\"pan\"?\"move\":\"crosshair\",o=r._bgRect;if(o&&!(i===\"pan\"||i===\"zoom\")){lYt(o,a);var 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i$=ye((u2r,LXe)=>{\"use strict\";LXe.exports={defaultNumberFontSize:80,bulletNumberDomainSize:.25,bulletPadding:.025,innerRadius:.75,valueThickness:.5,titlePadding:5,horizontalPadding:10}});var RXe=ye((c2r,IXe)=>{\"use strict\";var ty=Dr(),P7=r$(),mYt=Cc().defaults,PXe=vl(),yYt=Yd(),L7=i$(),_Yt=bb(),xYt=S3(),bYt=e_(),wYt=t_();function TYt(e,t,r,n){function i(x,C){return ty.coerce(e,t,P7,x,C)}mYt(t,n,i),i(\"mode\"),t._hasNumber=t.mode.indexOf(\"number\")!==-1,t._hasDelta=t.mode.indexOf(\"delta\")!==-1,t._hasGauge=t.mode.indexOf(\"gauge\")!==-1;var a=i(\"value\");t._range=[0,typeof a==\"number\"?1.5*a:1];var o=new Array(2),s;if(t._hasNumber){i(\"number.valueformat\");var l=ty.extendFlat({},n.font);l.size=void 0,ty.coerceFont(i,\"number.font\",l),t.number.font.size===void 0&&(t.number.font.size=L7.defaultNumberFontSize,o[0]=!0),i(\"number.prefix\"),i(\"number.suffix\"),s=t.number.font.size}var u;if(t._hasDelta){var c=ty.extendFlat({},n.font);c.size=void 0,ty.coerceFont(i,\"delta.font\",c),t.delta.font.size===void 0&&(t.delta.font.size=(t._hasNumber?.5:1)*(s||L7.defaultNumberFontSize),o[1]=!0),i(\"delta.reference\",t.value),i(\"delta.relative\"),i(\"delta.valueformat\",t.delta.relative?\"2%\":\"\"),i(\"delta.increasing.symbol\"),i(\"delta.increasing.color\"),i(\"delta.decreasing.symbol\"),i(\"delta.decreasing.color\"),i(\"delta.position\"),i(\"delta.prefix\"),i(\"delta.suffix\"),u=t.delta.font.size}t._scaleNumbers=(!t._hasNumber||o[0])&&(!t._hasDelta||o[1])||!1;var f=ty.extendFlat({},n.font);f.size=.25*(s||u||L7.defaultNumberFontSize),ty.coerceFont(i,\"title.font\",f),i(\"title.text\");var h,d,v,_;function b(x,C){return ty.coerce(h,d,P7.gauge,x,C)}function p(x,C){return ty.coerce(v,_,P7.gauge.axis,x,C)}if(t._hasGauge){h=e.gauge,h||(h={}),d=PXe.newContainer(t,\"gauge\"),b(\"shape\");var k=t._isBullet=t.gauge.shape===\"bullet\";k||i(\"title.align\",\"center\");var E=t._isAngular=t.gauge.shape===\"angular\";E||i(\"align\",\"center\"),b(\"bgcolor\",n.paper_bgcolor),b(\"borderwidth\"),b(\"bordercolor\"),b(\"bar.color\"),b(\"bar.line.color\"),b(\"bar.line.width\");var S=L7.valueThickness*(t.gauge.shape===\"bullet\"?.5:1);b(\"bar.thickness\",S),yYt(h,d,{name:\"steps\",handleItemDefaults:AYt}),b(\"threshold.value\"),b(\"threshold.thickness\"),b(\"threshold.line.width\"),b(\"threshold.line.color\"),v={},h&&(v=h.axis||{}),_=PXe.newContainer(d,\"axis\"),p(\"visible\"),t._range=p(\"range\",t._range);var L={font:n.font,noAutotickangles:!0,outerTicks:!0,noTicklabelshift:!0,noTicklabelstandoff:!0};_Yt(v,_,p,\"linear\"),wYt(v,_,p,\"linear\",L),bYt(v,_,p,\"linear\",L),xYt(v,_,p,L)}else i(\"title.align\",\"center\"),i(\"align\",\"center\"),t._isAngular=t._isBullet=!1;t._length=null}function AYt(e,t){function r(n,i){return ty.coerce(e,t,P7.gauge.steps,n,i)}r(\"color\"),r(\"line.color\"),r(\"line.width\"),r(\"range\"),r(\"thickness\")}IXe.exports={supplyDefaults:TYt}});var FXe=ye((f2r,DXe)=>{\"use strict\";function SYt(e,t){var r=[],n=t.value;typeof t._lastValue!=\"number\"&&(t._lastValue=t.value);var i=t._lastValue,a=i;return t._hasDelta&&typeof t.delta.reference==\"number\"&&(a=t.delta.reference),r[0]={y:n,lastY:i,delta:n-a,relativeDelta:(n-a)/a},r}DXe.exports={calc:SYt}});var UXe=ye((h2r,NXe)=>{\"use strict\";var hw=Oa(),MYt=(D2(),ob(R2)).interpolate,zXe=(D2(),ob(R2)).interpolateNumber,Ex=Dr(),EYt=Ex.strScale,rC=Ex.strTranslate,kYt=Ex.rad2deg,CYt=$h().MID_SHIFT,fw=So(),lw=i$(),R7=ru(),sv=ho(),LYt=r4(),PYt=lI(),IYt=Rd(),O5=ka(),n$={left:\"start\",center:\"middle\",right:\"end\"},uw={left:0,center:.5,right:1},OXe=/[yzafpnµmkMGTPEZY]/;function iC(e){return e&&e.duration>0}NXe.exports=function(t,r,n,i){var a=t._fullLayout,o;iC(n)&&i&&(o=i()),Ex.makeTraceGroups(a._indicatorlayer,r,\"trace\").each(function(s){var l=s[0],u=l.trace,c=hw.select(this),f=u._hasGauge,h=u._isAngular,d=u._isBullet,v=u.domain,_={w:a._size.w*(v.x[1]-v.x[0]),h:a._size.h*(v.y[1]-v.y[0]),l:a._size.l+a._size.w*v.x[0],r:a._size.r+a._size.w*(1-v.x[1]),t:a._size.t+a._size.h*(1-v.y[1]),b:a._size.b+a._size.h*v.y[0]},b=_.l+_.w/2,p=_.t+_.h/2,k=Math.min(_.w/2,_.h),E=lw.innerRadius*k,S,L,x,C=u.align||\"center\";if(L=p,!f)S=_.l+uw[C]*_.w,x=function(H){return qXe(H,_.w,_.h)};else if(h&&(S=b,L=p+k/2,x=function(H){return OYt(H,.9*E)}),d){var M=lw.bulletPadding,g=1-lw.bulletNumberDomainSize+M;S=_.l+(g+(1-g)*uw[C])*_.w,x=function(H){return qXe(H,(lw.bulletNumberDomainSize-M)*_.w,_.h)}}FYt(t,c,s,{numbersX:S,numbersY:L,numbersScaler:x,transitionOpts:n,onComplete:o});var P,T;f&&(P={range:u.gauge.axis.range,color:u.gauge.bgcolor,line:{color:u.gauge.bordercolor,width:0},thickness:1},T={range:u.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:u.gauge.bordercolor,width:u.gauge.borderwidth},thickness:1});var z=c.selectAll(\"g.angular\").data(h?s:[]);z.exit().remove();var O=c.selectAll(\"g.angularaxis\").data(h?s:[]);O.exit().remove(),h&&DYt(t,c,s,{radius:k,innerRadius:E,gauge:z,layer:O,size:_,gaugeBg:P,gaugeOutline:T,transitionOpts:n,onComplete:o});var V=c.selectAll(\"g.bullet\").data(d?s:[]);V.exit().remove();var G=c.selectAll(\"g.bulletaxis\").data(d?s:[]);G.exit().remove(),d&&RYt(t,c,s,{gauge:V,layer:G,size:_,gaugeBg:P,gaugeOutline:T,transitionOpts:n,onComplete:o});var Z=c.selectAll(\"text.title\").data(s);Z.exit().remove(),Z.enter().append(\"text\").classed(\"title\",!0),Z.attr(\"text-anchor\",function(){return d?n$.right:n$[u.title.align]}).text(u.title.text).call(fw.font,u.title.font).call(R7.convertToTspans,t),Z.attr(\"transform\",function(){var H=_.l+_.w*uw[u.title.align],N,j=lw.titlePadding,re=fw.bBox(Z.node());if(f){if(h)if(u.gauge.axis.visible){var oe=fw.bBox(O.node());N=oe.top-j-re.bottom}else N=_.t+_.h/2-k/2-re.bottom-j;d&&(N=L-(re.top+re.bottom)/2,H=_.l-lw.bulletPadding*_.w)}else N=u._numbersTop-j-re.bottom;return rC(H,N)})})};function RYt(e,t,r,n){var i=r[0].trace,a=n.gauge,o=n.layer,s=n.gaugeBg,l=n.gaugeOutline,u=n.size,c=i.domain,f=n.transitionOpts,h=n.onComplete,d,v,_,b,p;a.enter().append(\"g\").classed(\"bullet\",!0),a.attr(\"transform\",rC(u.l,u.t)),o.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),o.selectAll(\"g.xbulletaxistick,path,text\").remove();var k=u.h,E=i.gauge.bar.thickness*k,S=c.x[0],L=c.x[0]+(c.x[1]-c.x[0])*(i._hasNumber||i._hasDelta?1-lw.bulletNumberDomainSize:1);d=tC(e,i.gauge.axis),d._id=\"xbulletaxis\",d.domain=[S,L],d.setScale(),v=sv.calcTicks(d),_=sv.makeTransTickFn(d),b=sv.getTickSigns(d)[2],p=u.t+u.h,d.visible&&(sv.drawTicks(e,d,{vals:d.ticks===\"inside\"?sv.clipEnds(d,v):v,layer:o,path:sv.makeTickPath(d,p,b),transFn:_}),sv.drawLabels(e,d,{vals:v,layer:o,transFn:_,labelFns:sv.makeLabelFns(d,p)}));function x(O){O.attr(\"width\",function(V){return Math.max(0,d.c2p(V.range[1])-d.c2p(V.range[0]))}).attr(\"x\",function(V){return d.c2p(V.range[0])}).attr(\"y\",function(V){return .5*(1-V.thickness)*k}).attr(\"height\",function(V){return V.thickness*k})}var C=[s].concat(i.gauge.steps),M=a.selectAll(\"g.bg-bullet\").data(C);M.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),M.select(\"rect\").call(x).call(cw),M.exit().remove();var g=a.selectAll(\"g.value-bullet\").data([i.gauge.bar]);g.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),g.select(\"rect\").attr(\"height\",E).attr(\"y\",(k-E)/2).call(cw),iC(f)?g.select(\"rect\").transition().duration(f.duration).ease(f.easing).each(\"end\",function(){h&&h()}).each(\"interrupt\",function(){h&&h()}).attr(\"width\",Math.max(0,d.c2p(Math.min(i.gauge.axis.range[1],r[0].y)))):g.select(\"rect\").attr(\"width\",typeof r[0].y==\"number\"?Math.max(0,d.c2p(Math.min(i.gauge.axis.range[1],r[0].y))):0),g.exit().remove();var P=r.filter(function(){return i.gauge.threshold.value||i.gauge.threshold.value===0}),T=a.selectAll(\"g.threshold-bullet\").data(P);T.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),T.select(\"line\").attr(\"x1\",d.c2p(i.gauge.threshold.value)).attr(\"x2\",d.c2p(i.gauge.threshold.value)).attr(\"y1\",(1-i.gauge.threshold.thickness)/2*k).attr(\"y2\",(1-(1-i.gauge.threshold.thickness)/2)*k).call(O5.stroke,i.gauge.threshold.line.color).style(\"stroke-width\",i.gauge.threshold.line.width),T.exit().remove();var z=a.selectAll(\"g.gauge-outline\").data([l]);z.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),z.select(\"rect\").call(x).call(cw),z.exit().remove()}function DYt(e,t,r,n){var i=r[0].trace,a=n.size,o=n.radius,s=n.innerRadius,l=n.gaugeBg,u=n.gaugeOutline,c=[a.l+a.w/2,a.t+a.h/2+o/2],f=n.gauge,h=n.layer,d=n.transitionOpts,v=n.onComplete,_=Math.PI/2;function b(_e){var Ee=i.gauge.axis.range[0],Ce=i.gauge.axis.range[1],me=(_e-Ee)/(Ce-Ee)*Math.PI-_;return me<-_?-_:me>_?_:me}function p(_e){return hw.svg.arc().innerRadius((s+o)/2-_e/2*(o-s)).outerRadius((s+o)/2+_e/2*(o-s)).startAngle(-_)}function k(_e){_e.attr(\"d\",function(Ee){return p(Ee.thickness).startAngle(b(Ee.range[0])).endAngle(b(Ee.range[1]))()})}var E,S,L,x;f.enter().append(\"g\").classed(\"angular\",!0),f.attr(\"transform\",rC(c[0],c[1])),h.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),h.selectAll(\"g.xangularaxistick,path,text\").remove(),E=tC(e,i.gauge.axis),E.type=\"linear\",E.range=i.gauge.axis.range,E._id=\"xangularaxis\",E.ticklabeloverflow=\"allow\",E.setScale();var C=function(_e){return(E.range[0]-_e.x)/(E.range[1]-E.range[0])*Math.PI+Math.PI},M={},g=sv.makeLabelFns(E,0),P=g.labelStandoff;M.xFn=function(_e){var Ee=C(_e);return Math.cos(Ee)*P},M.yFn=function(_e){var Ee=C(_e),Ce=Math.sin(Ee)>0?.2:1;return-Math.sin(Ee)*(P+_e.fontSize*Ce)+Math.abs(Math.cos(Ee))*(_e.fontSize*CYt)},M.anchorFn=function(_e){var Ee=C(_e),Ce=Math.cos(Ee);return Math.abs(Ce)<.1?\"middle\":Ce>0?\"start\":\"end\"},M.heightFn=function(_e,Ee,Ce){var me=C(_e);return-.5*(1+Math.sin(me))*Ce};var T=function(_e){return rC(c[0]+o*Math.cos(_e),c[1]-o*Math.sin(_e))};L=function(_e){return T(C(_e))};var z=function(_e){var Ee=C(_e);return T(Ee)+\"rotate(\"+-kYt(Ee)+\")\"};if(S=sv.calcTicks(E),x=sv.getTickSigns(E)[2],E.visible){x=E.ticks===\"inside\"?-1:1;var O=(E.linewidth||1)/2;sv.drawTicks(e,E,{vals:S,layer:h,path:\"M\"+x*O+\",0h\"+x*E.ticklen,transFn:z}),sv.drawLabels(e,E,{vals:S,layer:h,transFn:L,labelFns:M})}var V=[l].concat(i.gauge.steps),G=f.selectAll(\"g.bg-arc\").data(V);G.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),G.select(\"path\").call(k).call(cw),G.exit().remove();var Z=p(i.gauge.bar.thickness),H=f.selectAll(\"g.value-arc\").data([i.gauge.bar]);H.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var N=H.select(\"path\");iC(d)?(N.transition().duration(d.duration).ease(d.easing).each(\"end\",function(){v&&v()}).each(\"interrupt\",function(){v&&v()}).attrTween(\"d\",zYt(Z,b(r[0].lastY),b(r[0].y))),i._lastValue=r[0].y):N.attr(\"d\",typeof r[0].y==\"number\"?Z.endAngle(b(r[0].y)):\"M0,0Z\"),N.call(cw),H.exit().remove(),V=[];var j=i.gauge.threshold.value;(j||j===0)&&V.push({range:[j,j],color:i.gauge.threshold.color,line:{color:i.gauge.threshold.line.color,width:i.gauge.threshold.line.width},thickness:i.gauge.threshold.thickness});var re=f.selectAll(\"g.threshold-arc\").data(V);re.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),re.select(\"path\").call(k).call(cw),re.exit().remove();var oe=f.selectAll(\"g.gauge-outline\").data([u]);oe.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),oe.select(\"path\").call(k).call(cw),oe.exit().remove()}function FYt(e,t,r,n){var i=r[0].trace,a=n.numbersX,o=n.numbersY,s=i.align||\"center\",l=n$[s],u=n.transitionOpts,c=n.onComplete,f=Ex.ensureSingle(t,\"g\",\"numbers\"),h,d,v,_=[];i._hasNumber&&_.push(\"number\"),i._hasDelta&&(_.push(\"delta\"),i.delta.position===\"left\"&&_.reverse());var b=f.selectAll(\"text\").data(_);b.enter().append(\"text\"),b.attr(\"text-anchor\",function(){return l}).attr(\"class\",function(T){return T}).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),b.exit().remove();function p(T,z,O,V){if(T.match(\"s\")&&O>=0!=V>=0&&!z(O).slice(-1).match(OXe)&&!z(V).slice(-1).match(OXe)){var G=T.slice().replace(\"s\",\"f\").replace(/\\d+/,function(H){return parseInt(H)-1}),Z=tC(e,{tickformat:G});return function(H){return Math.abs(H)<1?sv.tickText(Z,H).text:z(H)}}else return z}function k(){var T=tC(e,{tickformat:i.number.valueformat},i._range);T.setScale(),sv.prepTicks(T);var z=function(H){return sv.tickText(T,H).text},O=i.number.suffix,V=i.number.prefix,G=f.select(\"text.number\");function Z(){var H=typeof r[0].y==\"number\"?V+z(r[0].y)+O:\"-\";G.text(H).call(fw.font,i.number.font).call(R7.convertToTspans,e)}return iC(u)?G.transition().duration(u.duration).ease(u.easing).each(\"end\",function(){Z(),c&&c()}).each(\"interrupt\",function(){Z(),c&&c()}).attrTween(\"text\",function(){var H=hw.select(this),N=zXe(r[0].lastY,r[0].y);i._lastValue=r[0].y;var j=p(i.number.valueformat,z,r[0].lastY,r[0].y);return function(re){H.text(V+j(N(re))+O)}}):Z(),h=BXe(V+z(r[0].y)+O,i.number.font,l,e),G}function E(){var T=tC(e,{tickformat:i.delta.valueformat},i._range);T.setScale(),sv.prepTicks(T);var z=function(re){return sv.tickText(T,re).text},O=i.delta.suffix,V=i.delta.prefix,G=function(re){var oe=i.delta.relative?re.relativeDelta:re.delta;return oe},Z=function(re,oe){return re===0||typeof re!=\"number\"||isNaN(re)?\"-\":(re>0?i.delta.increasing.symbol:i.delta.decreasing.symbol)+V+oe(re)+O},H=function(re){return re.delta>=0?i.delta.increasing.color:i.delta.decreasing.color};i._deltaLastValue===void 0&&(i._deltaLastValue=G(r[0]));var N=f.select(\"text.delta\");N.call(fw.font,i.delta.font).call(O5.fill,H({delta:i._deltaLastValue}));function j(){N.text(Z(G(r[0]),z)).call(O5.fill,H(r[0])).call(R7.convertToTspans,e)}return iC(u)?N.transition().duration(u.duration).ease(u.easing).tween(\"text\",function(){var re=hw.select(this),oe=G(r[0]),_e=i._deltaLastValue,Ee=p(i.delta.valueformat,z,_e,oe),Ce=zXe(_e,oe);return i._deltaLastValue=oe,function(me){re.text(Z(Ce(me),Ee)),re.call(O5.fill,H({delta:Ce(me)}))}}).each(\"end\",function(){j(),c&&c()}).each(\"interrupt\",function(){j(),c&&c()}):j(),d=BXe(Z(G(r[0]),z),i.delta.font,l,e),N}var S=i.mode+i.align,L;if(i._hasDelta&&(L=E(),S+=i.delta.position+i.delta.font.size+i.delta.font.family+i.delta.valueformat,S+=i.delta.increasing.symbol+i.delta.decreasing.symbol,v=d),i._hasNumber&&(k(),S+=i.number.font.size+i.number.font.family+i.number.valueformat+i.number.suffix+i.number.prefix,v=h),i._hasDelta&&i._hasNumber){var x=[(h.left+h.right)/2,(h.top+h.bottom)/2],C=[(d.left+d.right)/2,(d.top+d.bottom)/2],M,g,P=.75*i.delta.font.size;i.delta.position===\"left\"&&(M=I7(i,\"deltaPos\",0,-1*(h.width*uw[i.align]+d.width*(1-uw[i.align])+P),S,Math.min),g=x[1]-C[1],v={width:h.width+d.width+P,height:Math.max(h.height,d.height),left:d.left+M,right:h.right,top:Math.min(h.top,d.top+g),bottom:Math.max(h.bottom,d.bottom+g)}),i.delta.position===\"right\"&&(M=I7(i,\"deltaPos\",0,h.width*(1-uw[i.align])+d.width*uw[i.align]+P,S,Math.max),g=x[1]-C[1],v={width:h.width+d.width+P,height:Math.max(h.height,d.height),left:h.left,right:d.right+M,top:Math.min(h.top,d.top+g),bottom:Math.max(h.bottom,d.bottom+g)}),i.delta.position===\"bottom\"&&(M=null,g=d.height,v={width:Math.max(h.width,d.width),height:h.height+d.height,left:Math.min(h.left,d.left),right:Math.max(h.right,d.right),top:h.bottom-h.height,bottom:h.bottom+d.height}),i.delta.position===\"top\"&&(M=null,g=h.top,v={width:Math.max(h.width,d.width),height:h.height+d.height,left:Math.min(h.left,d.left),right:Math.max(h.right,d.right),top:h.bottom-h.height-d.height,bottom:h.bottom}),L.attr({dx:M,dy:g})}(i._hasNumber||i._hasDelta)&&f.attr(\"transform\",function(){var T=n.numbersScaler(v);S+=T[2];var z=I7(i,\"numbersScale\",1,T[0],S,Math.min),O;i._scaleNumbers||(z=1),i._isAngular?O=o-z*v.bottom:O=o-z*(v.top+v.bottom)/2,i._numbersTop=z*v.top+O;var V=v[s];s===\"center\"&&(V=(v.left+v.right)/2);var G=a-z*V;return G=I7(i,\"numbersTranslate\",0,G,S,Math.max),rC(G,O)+EYt(z)})}function cw(e){e.each(function(t){O5.stroke(hw.select(this),t.line.color)}).each(function(t){O5.fill(hw.select(this),t.color)}).style(\"stroke-width\",function(t){return t.line.width})}function zYt(e,t,r){return function(){var n=MYt(t,r);return function(i){return e.endAngle(n(i))()}}}function tC(e,t,r){var n=e._fullLayout,i=Ex.extendFlat({type:\"linear\",ticks:\"outside\",range:r,showline:!0},t),a={type:\"linear\",_id:\"x\"+t._id},o={letter:\"x\",font:n.font,noAutotickangles:!0,noHover:!0,noTickson:!0};function s(l,u){return Ex.coerce(i,a,IYt,l,u)}return LYt(i,a,s,o,n),PYt(i,a,s,o),a}function qXe(e,t,r){var n=Math.min(t/e.width,r/e.height);return[n,e,t+\"x\"+r]}function OYt(e,t){var 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P=h(g),T=Math.cos(P),z=Math.sin(P);return\"M\"+[s+o*T,l-o*z]+\"L\"+[s+a*T,l-a*z]},p=vp.makeLabelFns(c,0),k=p.labelStandoff,E={};E.xFn=function(g){var P=h(g);return Math.cos(P)*k},E.yFn=function(g){var P=h(g),T=Math.sin(P)>0?.2:1;return-Math.sin(P)*(k+g.fontSize*T)+Math.abs(Math.cos(P))*(g.fontSize*j$t)},E.anchorFn=function(g){var P=h(g),T=Math.cos(P);return Math.abs(T)<.1?\"middle\":T>0?\"start\":\"end\"},E.heightFn=function(g,P,T){var z=h(g);return-.5*(1+Math.sin(z))*T};var S=VJe(u);r.angularTickLayout!==S&&(i[\"angular-axis\"].selectAll(\".\"+c._id+\"tick\").remove(),r.angularTickLayout=S);var L=f?[1/0].concat(c.tickvals||[]).map(function(g){return vp.tickText(c,g,!0,!1)}):vp.calcTicks(c);f&&(L[0].text=\"\\u221E\",L[0].fontSize*=1.75);var x;if(t.gridshape===\"linear\"?(x=L.map(h),Xc.angleDelta(x[0],x[1])<0&&(x=x.slice().reverse())):x=null,r.vangles=x,c.type===\"category\"&&(L=L.filter(function(g){return Xc.isAngleInsideSector(h(g),r.sectorInRad)})),c.visible){var 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t=this,r=t.isSmith,n=t.gd,i=t.layers,a=e._zoomlayer,o=Lx.MINZOOM,s=Lx.OFFEDGE,l=t.radius,u=t.innerRadius,c=t.cx,f=t.cy,h=t.cxx,d=t.cyy,v=t.sectorInRad,_=t.vangles,b=t.radialAxis,p=_1.clampTiny,k=_1.findXYatLength,E=_1.findEnclosingVertexAngles,S=Lx.cornerHalfWidth,L=Lx.cornerLen/2,x,C,M=y1.makeDragger(i,\"path\",\"maindrag\",e.dragmode===!1?\"none\":\"crosshair\");pw.select(M).attr(\"d\",t.pathSubplot()).attr(\"transform\",xd(c,f)),M.onmousemove=function(ce){zJe.hover(n,ce,t.id),n._fullLayout._lasthover=M,n._fullLayout._hoversubplot=t.id},M.onmouseout=function(ce){n._dragging||d9.unhover(n,ce)};var g={element:M,gd:n,subplot:t.id,plotinfo:{id:t.id,xaxis:t.xaxis,yaxis:t.yaxis},xaxes:[t.xaxis],yaxes:[t.yaxis]},P,T,z,O,V,G,Z,H,N;function j(ce,Ze){return Math.sqrt(ce*ce+Ze*Ze)}function re(ce,Ze){return j(ce-h,Ze-d)}function oe(ce,Ze){return Math.atan2(d-Ze,ce-h)}function _e(ce,Ze){return[ce*Math.cos(Ze),ce*Math.sin(-Ze)]}function Ee(ce,Ze){if(ce===0)return t.pathSector(2*S);var 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n=this,i=n.gd,a=n.layers,o=n.radius,s=n.innerRadius,l=n.cx,u=n.cy,c=n.radialAxis,f=Lx.radialDragBoxSize,h=f/2;if(!c.visible)return;var d=Px(n.radialAxisAngle),v=c._rl,_=v[0],b=v[1],p=v[r],k=.75*(v[1]-v[0])/(1-n.getHole(t))/o,E,S,L;r?(E=l+(o+h)*Math.cos(d),S=u-(o+h)*Math.sin(d),L=\"radialdrag\"):(E=l+(s-h)*Math.cos(d),S=u-(s-h)*Math.sin(d),L=\"radialdrag-inner\");var x=y1.makeRectDragger(a,L,\"crosshair\",-h,-h,f,f),C={element:x,gd:i};e.dragmode===!1&&(C.dragmode=!1),fC(pw.select(x),c.visible&&s<o,{transform:xd(E,S)});var M,g,P;function T(Z,H){if(M)M(Z,H);else{var N=[Z,-H],j=[Math.cos(d),Math.sin(d)],re=Math.abs(Xc.dot(N,j)/Math.sqrt(Xc.dot(N,N)));isNaN(re)||(M=re<.5?V:G)}var oe={};z(oe),i.emit(\"plotly_relayouting\",oe)}function z(Z){g!==null?Z[n.id+\".radialaxis.angle\"]=g:P!==null&&(Z[n.id+\".radialaxis.range[\"+r+\"]\"]=P)}function 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i=r.layers.frontplot.select(\"g.scatterlayer\"),a=r.xaxis,o=r.yaxis,s={xaxis:a,yaxis:o,plot:r.framework,layerClipId:r._hasClipOnAxisFalse?r.clipIds.forTraces:null},l=0;l<n.length;l++)for(var u=n[l],c=0;c<u.length;c++){c===0&&(u[0].trace._xA=a,u[0].trace._yA=o);var f=u[c],h=f.real;if(h===DQe)f.x=f.y=DQe;else{var d=Atr([h,f.imag]);f.x=d[0],f.y=d[1]}}wtr(t,s,n,i)}});var BQe=ye((w3r,qQe)=>{\"use strict\";var Str=cT();function Mtr(e,t,r,n){var i=Str(e,t,r,n);if(!(!i||i[0].index===!1)){var a=i[0];if(a.index===void 0)return i;var o=e.subplot,s=a.cd[a.index],l=a.trace;if(o.isPtInside(s))return a.xLabelVal=void 0,a.yLabelVal=void 0,OQe(s,l,o,a),a.hovertemplate=l.hovertemplate,i}}function OQe(e,t,r,n){var i=r.radialAxis,a=r.angularAxis;i._hovertitle=\"real\",a._hovertitle=\"imag\";var o={};o[t.subplot]={_subplot:r};var s=t._module.formatLabels(e,t,o);n.realLabel=s.realLabel,n.imagLabel=s.imagLabel;var l=e.hi||t.hoverinfo,u=[];function c(h,d){u.push(h._hovertitle+\": \"+d)}if(!t.hovertemplate){var f=l.split(\"+\");f.indexOf(\"all\")!==-1&&(f=[\"real\",\"imag\",\"text\"]),f.indexOf(\"real\")!==-1&&c(i,n.realLabel),f.indexOf(\"imag\")!==-1&&c(a,n.imagLabel),f.indexOf(\"text\")!==-1&&n.text&&(u.push(n.text),delete n.text),n.extraText=u.join(\"<br>\")}}qQe.exports={hoverPoints:Mtr,makeHoverPointText:OQe}});var UQe=ye((T3r,NQe)=>{\"use strict\";NQe.exports={moduleType:\"trace\",name:\"scattersmith\",basePlotModule:wQe(),categories:[\"smith\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:oQ(),supplyDefaults:EQe(),colorbar:$d(),formatLabels:LQe(),calc:RQe(),plot:zQe(),style:op().style,styleOnSelect:op().styleOnSelect,hoverPoints:BQe().hoverPoints,selectPoints:fT(),meta:{}}});var GQe=ye((A3r,VQe)=>{\"use strict\";VQe.exports=UQe()});var kv=ye((S3r,jQe)=>{var C9=Oh();function HQe(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}C9(HQe.prototype,{instance:function(e,t){e=(e||\"gregorian\").toLowerCase(),t=t||\"\";var r=this._localCals[e+\"-\"+t];if(!r&&this.calendars[e]&&(r=new this.calendars[e](t),this._localCals[e+\"-\"+t]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,e);return r},newDate:function(e,t,r,n,i){return n=(e!=null&&e.year?e.calendar():typeof n==\"string\"?this.instance(n,i):n)||this.instance(),n.newDate(e,t,r)},substituteDigits:function(e){return function(t){return(t+\"\").replace(/[0-9]/g,function(r){return e[r]})}},substituteChineseDigits:function(e,t){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(a===0?\"\":e[a]+t[i])+n,i++,r=Math.floor(r/10)}return n.indexOf(e[1]+t[1])===0&&(n=n.substr(1)),n||e[0]}}});function sQ(e,t,r,n){if(this._calendar=e,this._year=t,this._month=r,this._day=n,this._calendar._validateLevel===0&&!this._calendar.isValid(this._year,this._month,this._day))throw(Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function k9(e,t){return e=\"\"+e,\"000000\".substring(0,t-e.length)+e}C9(sQ.prototype,{newDate:function(e,t,r){return this._calendar.newDate(e==null?this:e,t,r)},year:function(e){return arguments.length===0?this._year:this.set(e,\"y\")},month:function(e){return arguments.length===0?this._month:this.set(e,\"m\")},day:function(e){return arguments.length===0?this._day:this.set(e,\"d\")},date:function(e,t,r){if(!this._calendar.isValid(e,t,r))throw(Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=e,this._month=t,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(e,t){return this._calendar.add(this,e,t)},set:function(e,t){return this._calendar.set(this,e,t)},compareTo:function(e){if(this._calendar.name!==e._calendar.name)throw(Gs.local.differentCalendars||Gs.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,e._calendar.local.name);var t=this._year!==e._year?this._year-e._year:this._month!==e._month?this.monthOfYear()-e.monthOfYear():this._day-e._day;return t===0?0:t<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(e){return this._calendar.fromJD(e)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(e){return this._calendar.fromJSDate(e)},toString:function(){return(this.year()<0?\"-\":\"\")+k9(Math.abs(this.year()),4)+\"-\"+k9(this.month(),2)+\"-\"+k9(this.day(),2)}});function lQ(){this.shortYearCutoff=\"+10\"}C9(lQ.prototype,{_validateLevel:0,newDate:function(e,t,r){return e==null?this.today():(e.year&&(this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate),r=e.day(),t=e.month(),e=e.year()),new sQ(this,e,t,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(e){var t=this._validate(e,this.minMonth,this.minDay,Gs.local.invalidYear||Gs.regionalOptions[\"\"].invalidYear);return t.year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,Gs.local.invalidYear||Gs.regionalOptions[\"\"].invalidYear);return(t.year()<0?\"-\":\"\")+k9(Math.abs(t.year()),4)},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,Gs.local.invalidYear||Gs.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(e,t){var r=this._validate(e,t,this.minDay,Gs.local.invalidMonth||Gs.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(e,t){var r=(t+this.firstMonth-2*this.minMonth)%this.monthsInYear(e)+this.minMonth;return this._validate(e,r,this.minDay,Gs.local.invalidMonth||Gs.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,Gs.local.invalidYear||Gs.regionalOptions[\"\"].invalidYear);return this.leapYear(t)?366:365},dayOfYear:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(e,t,r){return this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate),{}},add:function(e,t,r){return this._validate(e,this.minMonth,this.minDay,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate),this._correctAdd(e,this._add(e,t,r),t,r)},_add:function(e,t,r){if(this._validateLevel++,r===\"d\"||r===\"w\"){var n=e.toJD()+t*(r===\"w\"?this.daysInWeek():1),i=e.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=e.year()+(r===\"y\"?t:0),o=e.monthOfYear()+(r===\"m\"?t:0),i=e.day(),s=function(c){for(;o<c.minMonth;)a--,o+=c.monthsInYear(a);for(var f=c.monthsInYear(a);o>f-1+c.minMonth;)a++,o-=f,f=c.monthsInYear(a)};r===\"y\"?(e.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,e.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):r===\"m\"&&(s(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var l=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,l}catch(u){throw this._validateLevel--,u}},_correctAdd:function(e,t,r,n){if(!this.hasYearZero&&(n===\"y\"||n===\"m\")&&(t[0]===0||e.year()>0!=t[0]>0)){var i={y:[1,1,\"y\"],m:[1,this.monthsInYear(-1),\"m\"],w:[this.daysInWeek(),this.daysInYear(-1),\"d\"],d:[1,this.daysInYear(-1),\"d\"]}[n],a=r<0?-1:1;t=this._add(e,r*i[0]+a*i[1],i[2])}return e.date(t[0],t[1],t[2])},set:function(e,t,r){this._validate(e,this.minMonth,this.minDay,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate);var n=r===\"y\"?t:e.year(),i=r===\"m\"?t:e.month(),a=r===\"d\"?t:e.day();return(r===\"y\"||r===\"m\")&&(a=Math.min(a,this.daysInMonth(n,i))),e.date(n,i,a)},isValid:function(e,t,r){this._validateLevel++;var n=this.hasYearZero||e!==0;if(n){var i=this.newDate(e,t,this.minDay);n=t>=this.minMonth&&t-this.minMonth<this.monthsInYear(i)&&r>=this.minDay&&r-this.minDay<this.daysInMonth(i)}return this._validateLevel--,n},toJSDate:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate);return Gs.instance().fromJD(this.toJD(n)).toJSDate()},fromJSDate:function(e){return this.fromJD(Gs.instance().fromJSDate(e).toJD())},_validate:function(e,t,r,n){if(e.year){if(this._validateLevel===0&&this.name!==e.calendar().name)throw(Gs.local.differentCalendars||Gs.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this.local.name).replace(/\\{1\\}/,e.calendar().local.name);return e}try{if(this._validateLevel++,this._validateLevel===1&&!this.isValid(e,t,r))throw n.replace(/\\{0\\}/,this.local.name);var i=this.newDate(e,t,r);return this._validateLevel--,i}catch(a){throw this._validateLevel--,a}}});function uQ(e){this.local=this.regionalOptions[e]||this.regionalOptions[\"\"]}uQ.prototype=new lQ;C9(uQ.prototype,{name:\"Gregorian\",jdEpoch:17214255e-1,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Gregorian\",epochs:[\"BCE\",\"CE\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,Gs.local.invalidYear||Gs.regionalOptions[\"\"].invalidYear),r=t.year()+(t.year()<0?1:0);return r%4===0&&(r%100!==0||r%400===0)},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Gs.local.invalidMonth||Gs.regionalOptions[\"\"].invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate);e=n.year(),t=n.month(),r=n.day(),e<0&&e++,t<3&&(t+=12,e--);var i=Math.floor(e/100),a=2-i+Math.floor(i/4);return Math.floor(365.25*(e+4716))+Math.floor(30.6001*(t+1))+r+a-1524.5},fromJD:function(e){var t=Math.floor(e+.5),r=Math.floor((t-186721625e-2)/36524.25);r=t+1+r-Math.floor(r/4);var n=r+1524,i=Math.floor((n-122.1)/365.25),a=Math.floor(365.25*i),o=Math.floor((n-a)/30.6001),s=n-a-Math.floor(o*30.6001),l=o-(o>13.5?13:1),u=i-(l>2.5?4716:4715);return u<=0&&u--,this.newDate(u,l,s)},toJSDate:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[\"\"].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(e){return this.newDate(e.getFullYear(),e.getMonth()+1,e.getDate())}});var Gs=jQe.exports=new HQe;Gs.cdate=sQ;Gs.baseCalendar=lQ;Gs.calendars.gregorian=uQ});var WQe=ye(()=>{var cQ=Oh(),Ud=kv();cQ(Ud.regionalOptions[\"\"],{invalidArguments:\"Invalid arguments\",invalidFormat:\"Cannot format a date from another calendar\",missingNumberAt:\"Missing number at position {0}\",unknownNameAt:\"Unknown name at position {0}\",unexpectedLiteralAt:\"Unexpected literal at position {0}\",unexpectedText:\"Additional text found at end\"});Ud.local=Ud.regionalOptions[\"\"];cQ(Ud.cdate.prototype,{formatDate:function(e,t){return typeof e!=\"string\"&&(t=e,e=\"\"),this._calendar.formatDate(e||\"\",this,t)}});cQ(Ud.baseCalendar.prototype,{UNIX_EPOCH:Ud.instance().newDate(1970,1,1).toJD(),SECS_PER_DAY:24*60*60,TICKS_EPOCH:Ud.instance().jdEpoch,TICKS_PER_DAY:24*60*60*1e7,ATOM:\"yyyy-mm-dd\",COOKIE:\"D, dd M yyyy\",FULL:\"DD, MM d, yyyy\",ISO_8601:\"yyyy-mm-dd\",JULIAN:\"J\",RFC_822:\"D, d M yy\",RFC_850:\"DD, dd-M-yy\",RFC_1036:\"D, d M yy\",RFC_1123:\"D, d M yyyy\",RFC_2822:\"D, d M yyyy\",RSS:\"D, d M yy\",TICKS:\"!\",TIMESTAMP:\"@\",W3C:\"yyyy-mm-dd\",formatDate:function(e,t,r){if(typeof e!=\"string\"&&(r=t,t=e,e=\"\"),!t)return\"\";if(t.calendar()!==this)throw Ud.local.invalidFormat||Ud.regionalOptions[\"\"].invalidFormat;e=e||this.local.dateFormat,r=r||{};for(var n=r.dayNamesShort||this.local.dayNamesShort,i=r.dayNames||this.local.dayNames,a=r.monthNumbers||this.local.monthNumbers,o=r.monthNamesShort||this.local.monthNamesShort,s=r.monthNames||this.local.monthNames,l=r.calculateWeek||this.local.calculateWeek,u=function(S,L){for(var x=1;E+x<e.length&&e.charAt(E+x)===S;)x++;return E+=x-1,Math.floor(x/(L||1))>1},c=function(S,L,x,C){var M=\"\"+L;if(u(S,C))for(;M.length<x;)M=\"0\"+M;return M},f=function(S,L,x,C){return u(S)?C[L]:x[L]},h=this,d=function(S){return typeof a==\"function\"?a.call(h,S,u(\"m\")):b(c(\"m\",S.month(),2))},v=function(S,L){return L?typeof s==\"function\"?s.call(h,S):s[S.month()-h.minMonth]:typeof o==\"function\"?o.call(h,S):o[S.month()-h.minMonth]},_=this.local.digits,b=function(S){return r.localNumbers&&_?_(S):S},p=\"\",k=!1,E=0;E<e.length;E++)if(k)e.charAt(E)===\"'\"&&!u(\"'\")?k=!1:p+=e.charAt(E);else switch(e.charAt(E)){case\"d\":p+=b(c(\"d\",t.day(),2));break;case\"D\":p+=f(\"D\",t.dayOfWeek(),n,i);break;case\"o\":p+=c(\"o\",t.dayOfYear(),3);break;case\"w\":p+=c(\"w\",t.weekOfYear(),2);break;case\"m\":p+=d(t);break;case\"M\":p+=v(t,u(\"M\"));break;case\"y\":p+=u(\"y\",2)?t.year():(t.year()%100<10?\"0\":\"\")+t.year()%100;break;case\"Y\":u(\"Y\",2),p+=t.formatYear();break;case\"J\":p+=t.toJD();break;case\"@\":p+=(t.toJD()-this.UNIX_EPOCH)*this.SECS_PER_DAY;break;case\"!\":p+=(t.toJD()-this.TICKS_EPOCH)*this.TICKS_PER_DAY;break;case\"'\":u(\"'\")?p+=\"'\":k=!0;break;default:p+=e.charAt(E)}return p},parseDate:function(e,t,r){if(t==null)throw Ud.local.invalidArguments||Ud.regionalOptions[\"\"].invalidArguments;if(t=typeof t==\"object\"?t.toString():t+\"\",t===\"\")return null;e=e||this.local.dateFormat,r=r||{};var n=r.shortYearCutoff||this.shortYearCutoff;n=typeof n!=\"string\"?n:this.today().year()%100+parseInt(n,10);for(var i=r.dayNamesShort||this.local.dayNamesShort,a=r.dayNames||this.local.dayNames,o=r.parseMonth||this.local.parseMonth,s=r.monthNumbers||this.local.monthNumbers,l=r.monthNamesShort||this.local.monthNamesShort,u=r.monthNames||this.local.monthNames,c=-1,f=-1,h=-1,d=-1,v=-1,_=!1,b=!1,p=function(z,O){for(var V=1;g+V<e.length&&e.charAt(g+V)===z;)V++;return g+=V-1,Math.floor(V/(O||1))>1},k=function(z,O){var V=p(z,O),G=[2,3,V?4:2,V?4:2,10,11,20][\"oyYJ@!\".indexOf(z)+1],Z=new RegExp(\"^-?\\\\d{1,\"+G+\"}\"),H=t.substring(M).match(Z);if(!H)throw(Ud.local.missingNumberAt||Ud.regionalOptions[\"\"].missingNumberAt).replace(/\\{0\\}/,M);return M+=H[0].length,parseInt(H[0],10)},E=this,S=function(){if(typeof s==\"function\"){p(\"m\");var z=s.call(E,t.substring(M));return M+=z.length,z}return k(\"m\")},L=function(z,O,V,G){for(var Z=p(z,G)?V:O,H=0;H<Z.length;H++)if(t.substr(M,Z[H].length).toLowerCase()===Z[H].toLowerCase())return M+=Z[H].length,H+E.minMonth;throw(Ud.local.unknownNameAt||Ud.regionalOptions[\"\"].unknownNameAt).replace(/\\{0\\}/,M)},x=function(){if(typeof u==\"function\"){var z=p(\"M\")?u.call(E,t.substring(M)):l.call(E,t.substring(M));return M+=z.length,z}return L(\"M\",l,u)},C=function(){if(t.charAt(M)!==e.charAt(g))throw(Ud.local.unexpectedLiteralAt||Ud.regionalOptions[\"\"].unexpectedLiteralAt).replace(/\\{0\\}/,M);M++},M=0,g=0;g<e.length;g++)if(b)e.charAt(g)===\"'\"&&!p(\"'\")?b=!1:C();else switch(e.charAt(g)){case\"d\":d=k(\"d\");break;case\"D\":L(\"D\",i,a);break;case\"o\":v=k(\"o\");break;case\"w\":k(\"w\");break;case\"m\":h=S();break;case\"M\":h=x();break;case\"y\":var P=g;_=!p(\"y\",2),g=P,f=k(\"y\",2);break;case\"Y\":f=k(\"Y\",2);break;case\"J\":c=k(\"J\")+.5,t.charAt(M)===\".\"&&(M++,k(\"J\"));break;case\"@\":c=k(\"@\")/this.SECS_PER_DAY+this.UNIX_EPOCH;break;case\"!\":c=k(\"!\")/this.TICKS_PER_DAY+this.TICKS_EPOCH;break;case\"*\":M=t.length;break;case\"'\":p(\"'\")?C():b=!0;break;default:C()}if(M<t.length)throw Ud.local.unexpectedText||Ud.regionalOptions[\"\"].unexpectedText;if(f===-1?f=this.today().year():f<100&&_&&(f+=n===-1?1900:this.today().year()-this.today().year()%100-(f<=n?0:100)),typeof h==\"string\"&&(h=o.call(this,f,h)),v>-1){h=1,d=v;for(var T=this.daysInMonth(f,h);d>T;T=this.daysInMonth(f,h))h++,d-=T}return c>-1?this.fromJD(c):this.newDate(f,h,d)},determineDate:function(e,t,r,n,i){r&&typeof r!=\"object\"&&(i=n,n=r,r=null),typeof n!=\"string\"&&(i=n,n=\"\");var a=this,o=function(s){try{return a.parseDate(n,s,i)}catch(f){}s=s.toLowerCase();for(var l=(s.match(/^c/)&&r?r.newDate():null)||a.today(),u=/([+-]?[0-9]+)\\s*(d|w|m|y)?/g,c=u.exec(s);c;)l.add(parseInt(c[1],10),c[2]||\"d\"),c=u.exec(s);return l};return t=t?t.newDate():null,e=e==null?t:typeof e==\"string\"?o(e):typeof e==\"number\"?isNaN(e)||e===1/0||e===-1/0?t:a.today().add(e,\"d\"):a.newDate(e),e}})});var XQe=ye(()=>{var Fx=kv(),Etr=Oh(),fQ=Fx.instance();function L9(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}L9.prototype=new Fx.baseCalendar;Etr(L9.prototype,{name:\"Chinese\",jdEpoch:17214255e-1,hasYearZero:!1,minMonth:0,firstMonth:0,minDay:1,regionalOptions:{\"\":{name:\"Chinese\",epochs:[\"BEC\",\"EC\"],monthNumbers:function(e,t){if(typeof e==\"string\"){var r=e.match(Ctr);return r?r[0]:\"\"}var n=this._validateYear(e),i=e.month(),a=\"\"+this.toChineseMonth(n,i);return t&&a.length<2&&(a=\"0\"+a),this.isIntercalaryMonth(n,i)&&(a+=\"i\"),a},monthNames:function(e){if(typeof e==\"string\"){var t=e.match(Ltr);return t?t[0]:\"\"}var r=this._validateYear(e),n=e.month(),i=this.toChineseMonth(r,n),a=[\"\\u4E00\\u6708\",\"\\u4E8C\\u6708\",\"\\u4E09\\u6708\",\"\\u56DB\\u6708\",\"\\u4E94\\u6708\",\"\\u516D\\u6708\",\"\\u4E03\\u6708\",\"\\u516B\\u6708\",\"\\u4E5D\\u6708\",\"\\u5341\\u6708\",\"\\u5341\\u4E00\\u6708\",\"\\u5341\\u4E8C\\u6708\"][i-1];return this.isIntercalaryMonth(r,n)&&(a=\"\\u95F0\"+a),a},monthNamesShort:function(e){if(typeof e==\"string\"){var t=e.match(Ptr);return t?t[0]:\"\"}var r=this._validateYear(e),n=e.month(),i=this.toChineseMonth(r,n),a=[\"\\u4E00\",\"\\u4E8C\",\"\\u4E09\",\"\\u56DB\",\"\\u4E94\",\"\\u516D\",\"\\u4E03\",\"\\u516B\",\"\\u4E5D\",\"\\u5341\",\"\\u5341\\u4E00\",\"\\u5341\\u4E8C\"][i-1];return this.isIntercalaryMonth(r,n)&&(a=\"\\u95F0\"+a),a},parseMonth:function(e,t){e=this._validateYear(e);var r=parseInt(t),n;if(isNaN(r))t[0]===\"\\u95F0\"&&(n=!0,t=t.substring(1)),t[t.length-1]===\"\\u6708\"&&(t=t.substring(0,t.length-1)),r=1+[\"\\u4E00\",\"\\u4E8C\",\"\\u4E09\",\"\\u56DB\",\"\\u4E94\",\"\\u516D\",\"\\u4E03\",\"\\u516B\",\"\\u4E5D\",\"\\u5341\",\"\\u5341\\u4E00\",\"\\u5341\\u4E8C\"].indexOf(t);else{var i=t[t.length-1];n=i===\"i\"||i===\"I\"}var a=this.toMonthIndex(e,r,n);return a},dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},_validateYear:function(e,t){if(e.year&&(e=e.year()),typeof e!=\"number\"||e<1888||e>2111)throw t.replace(/\\{0\\}/,this.local.name);return e},toMonthIndex:function(e,t,r){var n=this.intercalaryMonth(e),i=r&&t!==n;if(i||t<1||t>12)throw Fx.local.invalidMonth.replace(/\\{0\\}/,this.local.name);var a;return n?!r&&t<=n?a=t-1:a=t:a=t-1,a},toChineseMonth:function(e,t){e.year&&(e=e.year(),t=e.month());var r=this.intercalaryMonth(e),n=r?12:11;if(t<0||t>n)throw Fx.local.invalidMonth.replace(/\\{0\\}/,this.local.name);var i;return r?t<r?i=t+1:i=t:i=t+1,i},intercalaryMonth:function(e){e=this._validateYear(e);var t=zx[e-zx[0]],r=t>>13;return r},isIntercalaryMonth:function(e,t){e.year&&(e=e.year(),t=e.month());var r=this.intercalaryMonth(e);return!!r&&r===t},leapYear:function(e){return this.intercalaryMonth(e)!==0},weekOfYear:function(e,t,r){var n=this._validateYear(e,Fx.local.invalidyear),i=Ox[n-Ox[0]],a=i>>9&4095,o=i>>5&15,s=i&31,l;l=fQ.newDate(a,o,s),l.add(4-(l.dayOfWeek()||7),\"d\");var u=this.toJD(e,t,r)-l.toJD();return 1+Math.floor(u/7)},monthsInYear:function(e){return this.leapYear(e)?13:12},daysInMonth:function(e,t){e.year&&(t=e.month(),e=e.year()),e=this._validateYear(e);var r=zx[e-zx[0]],n=r>>13,i=n?12:11;if(t>i)throw Fx.local.invalidMonth.replace(/\\{0\\}/,this.local.name);var a=r&1<<12-t?30:29;return a},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,a,r,Fx.local.invalidDate);e=this._validateYear(n.year()),t=n.month(),r=n.day();var i=this.isIntercalaryMonth(e,t),a=this.toChineseMonth(e,t),o=Rtr(e,a,r,i);return fQ.toJD(o.year,o.month,o.day)},fromJD:function(e){var t=fQ.fromJD(e),r=Itr(t.year(),t.month(),t.day()),n=this.toMonthIndex(r.year,r.month,r.isIntercalary);return this.newDate(r.year,n,r.day)},fromString:function(e){var t=e.match(ktr),r=this._validateYear(+t[1]),n=+t[2],i=!!t[3],a=this.toMonthIndex(r,n,i),o=+t[4];return this.newDate(r,a,o)},add:function(e,t,r){var n=e.year(),i=e.month(),a=this.isIntercalaryMonth(n,i),o=this.toChineseMonth(n,i),s=Object.getPrototypeOf(L9.prototype).add.call(this,e,t,r);if(r===\"y\"){var l=s.year(),u=s.month(),c=this.isIntercalaryMonth(l,o),f=a&&c?this.toMonthIndex(l,o,!0):this.toMonthIndex(l,o,!1);f!==u&&s.month(f)}return s}});var ktr=/^\\s*(-?\\d\\d\\d\\d|\\d\\d)[-/](\\d?\\d)([iI]?)[-/](\\d?\\d)/m,Ctr=/^\\d?\\d[iI]?/m,Ltr=/^闰?十?[一二三四五六七八九]?月/m,Ptr=/^闰?十?[一二三四五六七八九]?/m;Fx.calendars.chinese=L9;var 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Itr(e,t,r,n){var i,a;if(typeof e==\"object\")i=e,a=t||{};else{var o=typeof e==\"number\"&&e>=1888&&e<=2111;if(!o)throw new Error(\"Solar year outside range 1888-2111\");var s=typeof t==\"number\"&&t>=1&&t<=12;if(!s)throw new Error(\"Solar month outside range 1 - 12\");var l=typeof r==\"number\"&&r>=1&&r<=31;if(!l)throw new Error(\"Solar day outside range 1 - 31\");i={year:e,month:t,day:r},a=n||{}}var u=Ox[i.year-Ox[0]],c=i.year<<9|i.month<<5|i.day;a.year=c>=u?i.year:i.year-1,u=Ox[a.year-Ox[0]];var f=u>>9&4095,h=u>>5&15,d=u&31,v,_=new Date(f,h-1,d),b=new Date(i.year,i.month-1,i.day);v=Math.round((b-_)/(24*3600*1e3));var p=zx[a.year-zx[0]],k;for(k=0;k<13;k++){var E=p&1<<12-k?30:29;if(v<E)break;v-=E}var S=p>>13;return!S||k<S?(a.isIntercalary=!1,a.month=1+k):k===S?(a.isIntercalary=!0,a.month=k):(a.isIntercalary=!1,a.month=k),a.day=1+v,a}function Rtr(e,t,r,n,i){var a,o;if(typeof e==\"object\")o=e,a=t||{};else{var s=typeof e==\"number\"&&e>=1888&&e<=2111;if(!s)throw new Error(\"Lunar year 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xw.baseCalendar;Dtr(hQ.prototype,{name:\"Coptic\",jdEpoch:18250295e-1,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Coptic\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Thout\",\"Paopi\",\"Hathor\",\"Koiak\",\"Tobi\",\"Meshir\",\"Paremhat\",\"Paremoude\",\"Pashons\",\"Paoni\",\"Epip\",\"Mesori\",\"Pi Kogi Enavot\"],monthNamesShort:[\"Tho\",\"Pao\",\"Hath\",\"Koi\",\"Tob\",\"Mesh\",\"Pat\",\"Pad\",\"Pash\",\"Pao\",\"Epi\",\"Meso\",\"PiK\"],dayNames:[\"Tkyriaka\",\"Pesnau\",\"Pshoment\",\"Peftoou\",\"Ptiou\",\"Psoou\",\"Psabbaton\"],dayNamesShort:[\"Tky\",\"Pes\",\"Psh\",\"Pef\",\"Pti\",\"Pso\",\"Psa\"],dayNamesMin:[\"Tk\",\"Pes\",\"Psh\",\"Pef\",\"Pt\",\"Pso\",\"Psa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,xw.local.invalidYear),r=t.year()+(t.year()<0?1:0);return r%4===3||r%4===-1},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,xw.local.invalidYear||xw.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,xw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===13&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,xw.local.invalidDate);return e=n.year(),e<0&&e++,n.day()+(n.month()-1)*30+(e-1)*365+Math.floor(e/4)+this.jdEpoch-1},fromJD:function(e){var t=Math.floor(e)+.5-this.jdEpoch,r=Math.floor((t-Math.floor((t+366)/1461))/365)+1;r<=0&&r--,t=Math.floor(e)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(t/30)+1,i=t-(n-1)*30+1;return this.newDate(r,n,i)}});xw.calendars.coptic=hQ});var YQe=ye(()=>{var x1=kv(),Ftr=Oh();function dQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}dQ.prototype=new x1.baseCalendar;Ftr(dQ.prototype,{name:\"Discworld\",jdEpoch:17214255e-1,daysPerMonth:[16,32,32,32,32,32,32,32,32,32,32,32,32],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Discworld\",epochs:[\"BUC\",\"UC\"],monthNames:[\"Ick\",\"Offle\",\"February\",\"March\",\"April\",\"May\",\"June\",\"Grune\",\"August\",\"Spune\",\"Sektober\",\"Ember\",\"December\"],monthNamesShort:[\"Ick\",\"Off\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Gru\",\"Aug\",\"Spu\",\"Sek\",\"Emb\",\"Dec\"],dayNames:[\"Sunday\",\"Octeday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Oct\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Oc\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:2,isRTL:!1}},leapYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),!1},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),13},daysInYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),400},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,x1.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return(n.day()+1)%8},weekDay:function(e,t,r){var n=this.dayOfWeek(e,t,r);return n>=2&&n<=6},extraInfo:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return{century:ztr[Math.floor((n.year()-1)/100)+1]||\"\"}},toJD:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return e=n.year()+(n.year()<0?1:0),t=n.month(),r=n.day(),r+(t>1?16:0)+(t>2?(t-2)*32:0)+(e-1)*400+this.jdEpoch-1},fromJD:function(e){e=Math.floor(e+.5)-Math.floor(this.jdEpoch)-1;var t=Math.floor(e/400)+1;e-=(t-1)*400,e+=e>15?16:0;var r=Math.floor(e/32)+1,n=e-(r-1)*32+1;return this.newDate(t<=0?t-1:t,r,n)}});var ztr={20:\"Fruitbat\",21:\"Anchovy\"};x1.calendars.discworld=dQ});var KQe=ye(()=>{var bw=kv(),Otr=Oh();function vQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}vQ.prototype=new bw.baseCalendar;Otr(vQ.prototype,{name:\"Ethiopian\",jdEpoch:17242205e-1,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Ethiopian\",epochs:[\"BEE\",\"EE\"],monthNames:[\"Meskerem\",\"Tikemet\",\"Hidar\",\"Tahesas\",\"Tir\",\"Yekatit\",\"Megabit\",\"Miazia\",\"Genbot\",\"Sene\",\"Hamle\",\"Nehase\",\"Pagume\"],monthNamesShort:[\"Mes\",\"Tik\",\"Hid\",\"Tah\",\"Tir\",\"Yek\",\"Meg\",\"Mia\",\"Gen\",\"Sen\",\"Ham\",\"Neh\",\"Pag\"],dayNames:[\"Ehud\",\"Segno\",\"Maksegno\",\"Irob\",\"Hamus\",\"Arb\",\"Kidame\"],dayNamesShort:[\"Ehu\",\"Seg\",\"Mak\",\"Iro\",\"Ham\",\"Arb\",\"Kid\"],dayNamesMin:[\"Eh\",\"Se\",\"Ma\",\"Ir\",\"Ha\",\"Ar\",\"Ki\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,bw.local.invalidYear),r=t.year()+(t.year()<0?1:0);return r%4===3||r%4===-1},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,bw.local.invalidYear||bw.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,bw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===13&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,bw.local.invalidDate);return e=n.year(),e<0&&e++,n.day()+(n.month()-1)*30+(e-1)*365+Math.floor(e/4)+this.jdEpoch-1},fromJD:function(e){var t=Math.floor(e)+.5-this.jdEpoch,r=Math.floor((t-Math.floor((t+366)/1461))/365)+1;r<=0&&r--,t=Math.floor(e)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(t/30)+1,i=t-(n-1)*30+1;return this.newDate(r,n,i)}});bw.calendars.ethiopian=vQ});var JQe=ye(()=>{var qx=kv(),qtr=Oh();function pQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}pQ.prototype=new qx.baseCalendar;qtr(pQ.prototype,{name:\"Hebrew\",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{\"\":{name:\"Hebrew\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Nisan\",\"Iyar\",\"Sivan\",\"Tammuz\",\"Av\",\"Elul\",\"Tishrei\",\"Cheshvan\",\"Kislev\",\"Tevet\",\"Shevat\",\"Adar\",\"Adar II\"],monthNamesShort:[\"Nis\",\"Iya\",\"Siv\",\"Tam\",\"Av\",\"Elu\",\"Tis\",\"Che\",\"Kis\",\"Tev\",\"She\",\"Ada\",\"Ad2\"],dayNames:[\"Yom Rishon\",\"Yom Sheni\",\"Yom Shlishi\",\"Yom Revi'i\",\"Yom Chamishi\",\"Yom Shishi\",\"Yom Shabbat\"],dayNamesShort:[\"Ris\",\"She\",\"Shl\",\"Rev\",\"Cha\",\"Shi\",\"Sha\"],dayNamesMin:[\"Ri\",\"She\",\"Shl\",\"Re\",\"Ch\",\"Shi\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear);return this._leapYear(t.year())},_leapYear:function(e){return e=e<0?e+1:e,P9(e*7+1,19)<7},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear),this._leapYear(e.year?e.year():e)?13:12},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear);return e=t.year(),this.toJD(e===-1?1:e+1,7,1)-this.toJD(e,7,1)},daysInMonth:function(e,t){return e.year&&(t=e.month(),e=e.year()),this._validate(e,t,this.minDay,qx.local.invalidMonth),t===12&&this.leapYear(e)||t===8&&P9(this.daysInYear(e),10)===5?30:t===9&&P9(this.daysInYear(e),10)===3?29:this.daysPerMonth[t-1]},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==6},extraInfo:function(e,t,r){var n=this._validate(e,t,r,qx.local.invalidDate);return{yearType:(this.leapYear(n)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(n)%10-3]}},toJD:function(e,t,r){var n=this._validate(e,t,r,qx.local.invalidDate);e=n.year(),t=n.month(),r=n.day();var i=e<=0?e+1:e,a=this.jdEpoch+this._delay1(i)+this._delay2(i)+r+1;if(t<7){for(var o=7;o<=this.monthsInYear(e);o++)a+=this.daysInMonth(e,o);for(var o=1;o<t;o++)a+=this.daysInMonth(e,o)}else for(var o=7;o<t;o++)a+=this.daysInMonth(e,o);return a},_delay1:function(e){var t=Math.floor((235*e-234)/19),r=12084+13753*t,n=t*29+Math.floor(r/25920);return P9(3*(n+1),7)<3&&n++,n},_delay2:function(e){var t=this._delay1(e-1),r=this._delay1(e),n=this._delay1(e+1);return n-r===356?2:r-t===382?1:0},fromJD:function(e){e=Math.floor(e)+.5;for(var t=Math.floor((e-this.jdEpoch)*98496/35975351)-1;e>=this.toJD(t===-1?1:t+1,7,1);)t++;for(var r=e<this.toJD(t,1,1)?7:1;e>this.toJD(t,r,this.daysInMonth(t,r));)r++;var n=e-this.toJD(t,r,1)+1;return this.newDate(t,r,n)}});function P9(e,t){return e-t*Math.floor(e/t)}qx.calendars.hebrew=pQ});var $Qe=ye(()=>{var dC=kv(),Btr=Oh();function gQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}gQ.prototype=new dC.baseCalendar;Btr(gQ.prototype,{name:\"Islamic\",jdEpoch:19484395e-1,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012Bs\",\"Yawm al-jum'a\",\"Yawm 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t=Math.floor((30*(e-this.jdEpoch)+10646)/10631);t=t<=0?t-1:t;var r=Math.min(12,Math.ceil((e-29-this.toJD(t,1,1))/29.5)+1),n=e-this.toJD(t,r,1)+1;return this.newDate(t,r,n)}});dC.calendars.islamic=gQ});var QQe=ye(()=>{var vC=kv(),Ntr=Oh();function mQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}mQ.prototype=new vC.baseCalendar;Ntr(mQ.prototype,{name:\"Julian\",jdEpoch:17214235e-1,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,vC.local.invalidYear),r=t.year()<0?t.year()+1:t.year();return r%4===0},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,vC.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,vC.local.invalidDate);return e=n.year(),t=n.month(),r=n.day(),e<0&&e++,t<=2&&(e--,t+=12),Math.floor(365.25*(e+4716))+Math.floor(30.6001*(t+1))+r-1524.5},fromJD:function(e){var t=Math.floor(e+.5),r=t+1524,n=Math.floor((r-122.1)/365.25),i=Math.floor(365.25*n),a=Math.floor((r-i)/30.6001),o=a-Math.floor(a<14?1:13),s=n-Math.floor(o>2?4716:4715),l=r-i-Math.floor(30.6001*a);return s<=0&&s--,this.newDate(s,o,l)}});vC.calendars.julian=mQ});var tet=ye(()=>{var ug=kv(),Utr=Oh();function _Q(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}_Q.prototype=new ug.baseCalendar;Utr(_Q.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),!1},formatYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear);e=t.year();var r=Math.floor(e/400);e=e%400,e+=e<0?400:0;var n=Math.floor(e/20);return r+\".\"+n+\".\"+e%20},forYear:function(e){if(e=e.split(\".\"),e.length<3)throw\"Invalid Mayan year\";for(var t=0,r=0;r<e.length;r++){var n=parseInt(e[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";t=t*20+n}return t},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),18},weekOfYear:function(e,t,r){return this._validate(e,t,r,ug.local.invalidDate),0},daysInYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),360},daysInMonth:function(e,t){return this._validate(e,t,this.minDay,ug.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate);return n.day()},weekDay:function(e,t,r){return this._validate(e,t,r,ug.local.invalidDate),!0},extraInfo:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate),i=n.toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(e){e-=this.jdEpoch;var t=yQ(e+8+17*20,365);return[Math.floor(t/20)+1,yQ(t,20)]},_toTzolkin:function(e){return e-=this.jdEpoch,[eet(e+20,20),eet(e+4,13)]},toJD:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate);return n.day()+n.month()*20+n.year()*360+this.jdEpoch},fromJD:function(e){e=Math.floor(e)+.5-this.jdEpoch;var t=Math.floor(e/360);e=e%360,e+=e<0?360:0;var r=Math.floor(e/20),n=e%20;return this.newDate(t,r,n)}});function yQ(e,t){return e-t*Math.floor(e/t)}function eet(e,t){return yQ(e-1,t)+1}ug.calendars.mayan=_Q});var iet=ye(()=>{var ww=kv(),Vtr=Oh();function xQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}xQ.prototype=new ww.baseCalendar;var ret=ww.instance(\"gregorian\");Vtr(xQ.prototype,{name:\"Nanakshahi\",jdEpoch:22576735e-1,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,ww.local.invalidYear||ww.regionalOptions[\"\"].invalidYear);return ret.leapYear(t.year()+(t.year()<1?1:0)+1469)},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,ww.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===12&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,ww.local.invalidMonth),i=n.year();i<0&&i++;for(var a=n.day(),o=1;o<n.month();o++)a+=this.daysPerMonth[o-1];return a+ret.toJD(i+1468,3,13)},fromJD:function(e){e=Math.floor(e+.5);for(var t=Math.floor((e-(this.jdEpoch-1))/366);e>=this.toJD(t+1,1,1);)t++;for(var r=e-Math.floor(this.toJD(t,1,1)+.5)+1,n=1;r>this.daysInMonth(t,n);)r-=this.daysInMonth(t,n),n++;return this.newDate(t,n,r)}});ww.calendars.nanakshahi=xQ});var net=ye(()=>{var Tw=kv(),Gtr=Oh();function bQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}bQ.prototype=new Tw.baseCalendar;Gtr(bQ.prototype,{name:\"Nepali\",jdEpoch:17007095e-1,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(e){return 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l=e-(o>9||o===9&&r>=this.NEPALI_CALENDAR_DATA[s][0]?56:57);for(t!==9&&(a=r,o--);o!==9;)o<=0&&(o=12,s--),a+=this.NEPALI_CALENDAR_DATA[s][o],o--;return t===9?(a+=r-this.NEPALI_CALENDAR_DATA[s][0],a<0&&(a+=i.daysInYear(l))):a+=this.NEPALI_CALENDAR_DATA[s][9]-this.NEPALI_CALENDAR_DATA[s][0],i.newDate(l,1,1).add(a,\"d\").toJD()},fromJD:function(e){var t=Tw.instance(),r=t.fromJD(e),n=r.year(),i=r.dayOfYear(),a=n+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)o++,o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,u)},_createMissingCalendarData:function(e){var t=this.daysPerMonth.slice(0);t.unshift(17);for(var r=e-1;r<e+2;r++)typeof this.NEPALI_CALENDAR_DATA[r]==\"undefined\"&&(this.NEPALI_CALENDAR_DATA[r]=t)},NEPALI_CALENDAR_DATA:{1970:[18,31,31,32,31,31,31,30,29,30,29,30,30],1971:[18,31,31,32,31,32,30,30,29,30,29,30,30],1972:[17,31,32,31,32,31,30,30,30,29,29,30,30],1973:[19,30,32,31,32,31,30,30,30,29,30,29,31],1974:[19,31,31,32,30,31,31,30,29,30,29,30,30],1975:[18,31,31,32,32,30,31,30,29,30,29,30,30],1976:[17,31,32,31,32,31,30,30,30,29,29,30,31],1977:[18,31,32,31,32,31,31,29,30,29,30,29,31],1978:[18,31,31,32,31,31,31,30,29,30,29,30,30],1979:[18,31,31,32,32,31,30,30,29,30,29,30,30],1980:[17,31,32,31,32,31,30,30,30,29,29,30,31],1981:[18,31,31,31,32,31,31,29,30,30,29,30,30],1982:[18,31,31,32,31,31,31,30,29,30,29,30,30],1983:[18,31,31,32,32,31,30,30,29,30,29,30,30],1984:[17,31,32,31,32,31,30,30,30,29,29,30,31],1985:[18,31,31,31,32,31,31,29,30,30,29,30,30],1986:[18,31,31,32,31,31,31,30,29,30,29,30,30],1987:[18,31,32,31,32,31,30,30,29,30,29,30,30],1988:[17,31,32,31,32,31,30,30,30,29,29,30,31],1989:[18,31,31,31,32,31,31,30,29,30,29,30,30],1990:[18,31,31,32,31,31,31,30,29,30,29,30,30],1991:[18,31,32,31,32,31,30,30,29,30,29,30,30],1992:[17,31,32,31,32,31,30,30,30,29,30,29,31],1993:[18,31,31,31,32,31,31,30,29,30,29,30,30],1994:[18,31,31,32,31,31,31,30,29,30,29,30,30],1995:[17,31,32,31,32,31,30,30,30,29,29,30,30],1996:[17,31,32,31,32,31,30,30,30,29,30,29,31],1997:[18,31,31,32,31,31,31,30,29,30,29,30,30],1998:[18,31,31,32,31,31,31,30,29,30,29,30,30],1999:[17,31,32,31,32,31,30,30,30,29,29,30,31],2e3:[17,30,32,31,32,31,30,30,30,29,30,29,31],2001:[18,31,31,32,31,31,31,30,29,30,29,30,30],2002:[18,31,31,32,32,31,30,30,29,30,29,30,30],2003:[17,31,32,31,32,31,30,30,30,29,29,30,31],2004:[17,30,32,31,32,31,30,30,30,29,30,29,31],2005:[18,31,31,32,31,31,31,30,29,30,29,30,30],2006:[18,31,31,32,32,31,30,30,29,30,29,30,30],2007:[17,31,32,31,32,31,30,30,30,29,29,30,31],2008:[17,31,31,31,32,31,31,29,30,30,29,29,31],2009:[18,31,31,32,31,31,31,30,29,30,29,30,30],2010:[18,31,31,32,32,31,30,30,29,30,29,30,30],2011:[17,31,32,31,32,31,30,30,30,29,29,30,31],2012:[17,31,31,31,32,31,31,29,30,30,29,30,30],2013:[18,31,31,32,31,31,31,30,29,30,29,30,30],2014:[18,31,31,32,32,31,30,30,29,30,29,30,30],2015:[17,31,32,31,32,31,30,30,30,29,29,30,31],2016:[17,31,31,31,32,31,31,29,30,30,29,30,30],2017:[18,31,31,32,31,31,31,30,29,30,29,30,30],2018:[18,31,32,31,32,31,30,30,29,30,29,30,30],2019:[17,31,32,31,32,31,30,30,30,29,30,29,31],2020:[17,31,31,31,32,31,31,30,29,30,29,30,30],2021:[18,31,31,32,31,31,31,30,29,30,29,30,30],2022:[17,31,32,31,32,31,30,30,30,29,29,30,30],2023:[17,31,32,31,32,31,30,30,30,29,30,29,31],2024:[17,31,31,31,32,31,31,30,29,30,29,30,30],2025:[18,31,31,32,31,31,31,30,29,30,29,30,30],2026:[17,31,32,31,32,31,30,30,30,29,29,30,31],2027:[17,30,32,31,32,31,30,30,30,29,30,29,31],2028:[17,31,31,32,31,31,31,30,29,30,29,30,30],2029:[18,31,31,32,31,32,30,30,29,30,29,30,30],2030:[17,31,32,31,32,31,30,30,30,30,30,30,31],2031:[17,31,32,31,32,31,31,31,31,31,31,31,31],2032:[17,32,32,32,32,32,32,32,32,32,32,32,32],2033:[18,31,31,32,32,31,30,30,29,30,29,30,30],2034:[17,31,32,31,32,31,30,30,30,29,29,30,31],2035:[17,30,32,31,32,31,31,29,30,30,29,29,31],2036:[17,31,31,32,31,31,31,30,29,30,29,30,30],2037:[18,31,31,32,32,31,30,30,29,30,29,30,30],2038:[17,31,32,31,32,31,30,30,30,29,29,30,31],2039:[17,31,31,31,32,31,31,29,30,30,29,30,30],2040:[17,31,31,32,31,31,31,30,29,30,29,30,30],2041:[18,31,31,32,32,31,30,30,29,30,29,30,30],2042:[17,31,32,31,32,31,30,30,30,29,29,30,31],2043:[17,31,31,31,32,31,31,29,30,30,29,30,30],2044:[17,31,31,32,31,31,31,30,29,30,29,30,30],2045:[18,31,32,31,32,31,30,30,29,30,29,30,30],2046:[17,31,32,31,32,31,30,30,30,29,29,30,31],2047:[17,31,31,31,32,31,31,30,29,30,29,30,30],2048:[17,31,31,32,31,31,31,30,29,30,29,30,30],2049:[17,31,32,31,32,31,30,30,30,29,29,30,30],2050:[17,31,32,31,32,31,30,30,30,29,30,29,31],2051:[17,31,31,31,32,31,31,30,29,30,29,30,30],2052:[17,31,31,32,31,31,31,30,29,30,29,30,30],2053:[17,31,32,31,32,31,30,30,30,29,29,30,30],2054:[17,31,32,31,32,31,30,30,30,29,30,29,31],2055:[17,31,31,32,31,31,31,30,29,30,30,29,30],2056:[17,31,31,32,31,32,30,30,29,30,29,30,30],2057:[17,31,32,31,32,31,30,30,30,29,29,30,31],2058:[17,30,32,31,32,31,30,30,30,29,30,29,31],2059:[17,31,31,32,31,31,31,30,29,30,29,30,30],2060:[17,31,31,32,32,31,30,30,29,30,29,30,30],2061:[17,31,32,31,32,31,30,30,30,29,29,30,31],2062:[17,30,32,31,32,31,31,29,30,29,30,29,31],2063:[17,31,31,32,31,31,31,30,29,30,29,30,30],2064:[17,31,31,32,32,31,30,30,29,30,29,30,30],2065:[17,31,32,31,32,31,30,30,30,29,29,30,31],2066:[17,31,31,31,32,31,31,29,30,30,29,29,31],2067:[17,31,31,32,31,31,31,30,29,30,29,30,30],2068:[17,31,31,32,32,31,30,30,29,30,29,30,30],2069:[17,31,32,31,32,31,30,30,30,29,29,30,31],2070:[17,31,31,31,32,31,31,29,30,30,29,30,30],2071:[17,31,31,32,31,31,31,30,29,30,29,30,30],2072:[17,31,32,31,32,31,30,30,29,30,29,30,30],2073:[17,31,32,31,32,31,30,30,30,29,29,30,31],2074:[17,31,31,31,32,31,31,30,29,30,29,30,30],2075:[17,31,31,32,31,31,31,30,29,30,29,30,30],2076:[16,31,32,31,32,31,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aet=ye(()=>{var tS=kv(),Htr=Oh();function R9(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}function I9(e){var t=e-475;e<0&&t++;var r=.242197,n=r*t,i=r*(t+1),a=n-Math.floor(n),o=i-Math.floor(i);return a>o}R9.prototype=new tS.baseCalendar;Htr(R9.prototype,{name:\"Persian\",jdEpoch:19483205e-1,daysPerMonth:[31,31,31,31,31,31,30,30,30,30,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Persian\",epochs:[\"BP\",\"AP\"],monthNames:[\"Farvardin\",\"Ordibehesht\",\"Khordad\",\"Tir\",\"Mordad\",\"Shahrivar\",\"Mehr\",\"Aban\",\"Azar\",\"Dey\",\"Bahman\",\"Esfand\"],monthNamesShort:[\"Far\",\"Ord\",\"Kho\",\"Tir\",\"Mor\",\"Sha\",\"Meh\",\"Aba\",\"Aza\",\"Dey\",\"Bah\",\"Esf\"],dayNames:[\"Yekshanbeh\",\"Doshanbeh\",\"Seshanbeh\",\"Chah\\u0101rshanbeh\",\"Panjshanbeh\",\"Jom'eh\",\"Shanbeh\"],dayNamesShort:[\"Yek\",\"Do\",\"Se\",\"Cha\",\"Panj\",\"Jom\",\"Sha\"],dayNamesMin:[\"Ye\",\"Do\",\"Se\",\"Ch\",\"Pa\",\"Jo\",\"Sh\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,tS.local.invalidYear);return I9(t.year())},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-((n.dayOfWeek()+1)%7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,tS.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===12&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==5},toJD:function(e,t,r){var n=this._validate(e,t,r,tS.local.invalidDate);e=n.year(),t=n.month(),r=n.day();var i=0;if(e>0)for(var a=1;a<e;a++)I9(a)&&i++;else if(e<0)for(var a=e;a<0;a++)I9(a)&&i--;return r+(t<=7?(t-1)*31:(t-1)*30+6)+(e>0?e-1:e)*365+i+this.jdEpoch-1},fromJD:function(e){e=Math.floor(e)+.5;var t=475+(e-this.toJD(475,1,1))/365.242197,r=Math.floor(t);r<=0&&r--,e>this.toJD(r,12,I9(r)?30:29)&&(r++,r===0&&r++);var n=e-this.toJD(r,1,1)+1,i=n<=186?Math.ceil(n/31):Math.ceil((n-6)/30),a=e-this.toJD(r,i,1)+1;return this.newDate(r,i,a)}});tS.calendars.persian=R9;tS.calendars.jalali=R9});var oet=ye(()=>{var Aw=kv(),jtr=Oh(),D9=Aw.instance();function wQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}wQ.prototype=new Aw.baseCalendar;jtr(wQ.prototype,{name:\"Taiwan\",jdEpoch:24194025e-1,yearsOffset:1911,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Taiwan\",epochs:[\"BROC\",\"ROC\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,Aw.local.invalidYear),r=this._t2gYear(t.year());return D9.leapYear(r)},weekOfYear:function(i,t,r){var n=this._validate(i,this.minMonth,this.minDay,Aw.local.invalidYear),i=this._t2gYear(n.year());return D9.weekOfYear(i,n.month(),n.day())},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Aw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,Aw.local.invalidDate),i=this._t2gYear(n.year());return D9.toJD(i,n.month(),n.day())},fromJD:function(e){var t=D9.fromJD(e),r=this._g2tYear(t.year());return this.newDate(r,t.month(),t.day())},_t2gYear:function(e){return e+this.yearsOffset+(e>=-this.yearsOffset&&e<=-1?1:0)},_g2tYear:function(e){return e-this.yearsOffset-(e>=1&&e<=this.yearsOffset?1:0)}});Aw.calendars.taiwan=wQ});var set=ye(()=>{var Sw=kv(),Wtr=Oh(),F9=Sw.instance();function TQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}TQ.prototype=new Sw.baseCalendar;Wtr(TQ.prototype,{name:\"Thai\",jdEpoch:15230985e-1,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Thai\",epochs:[\"BBE\",\"BE\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,Sw.local.invalidYear),r=this._t2gYear(t.year());return F9.leapYear(r)},weekOfYear:function(i,t,r){var n=this._validate(i,this.minMonth,this.minDay,Sw.local.invalidYear),i=this._t2gYear(n.year());return F9.weekOfYear(i,n.month(),n.day())},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Sw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,Sw.local.invalidDate),i=this._t2gYear(n.year());return F9.toJD(i,n.month(),n.day())},fromJD:function(e){var t=F9.fromJD(e),r=this._g2tYear(t.year());return this.newDate(r,t.month(),t.day())},_t2gYear:function(e){return e-this.yearsOffset-(e>=1&&e<=this.yearsOffset?1:0)},_g2tYear:function(e){return e+this.yearsOffset+(e>=-this.yearsOffset&&e<=-1?1:0)}});Sw.calendars.thai=TQ});var uet=ye(()=>{var Mw=kv(),Xtr=Oh();function AQ(e){this.local=this.regionalOptions[e||\"\"]||this.regionalOptions[\"\"]}AQ.prototype=new Mw.baseCalendar;Xtr(AQ.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012Bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,Mw.local.invalidYear);return this.daysInYear(t.year())===355},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(e){for(var t=0,r=1;r<=12;r++)t+=this.daysInMonth(e,r);return t},daysInMonth:function(e,t){for(var r=this._validate(e,t,this.minDay,Mw.local.invalidMonth),n=r.toJD()-24e5+.5,i=0,a=0;a<Bx.length;a++){if(Bx[a]>n)return Bx[i]-Bx[i-1];i++}return 30},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==5},toJD:function(e,t,r){var n=this._validate(e,t,r,Mw.local.invalidDate),i=12*(n.year()-1)+n.month()-15292,a=n.day()+Bx[i-1]-1;return a+24e5-.5},fromJD:function(e){for(var t=e-24e5+.5,r=0,n=0;n<Bx.length&&!(Bx[n]>t);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),o=a+1,s=i-12*a,l=t-Bx[r-1]+1;return this.newDate(o,s,l)},isValid:function(e,t,r){var n=Mw.baseCalendar.prototype.isValid.apply(this,arguments);return n&&(e=e.year!=null?e.year:e,n=e>=1276&&e<=1500),n},_validate:function(e,t,r,n){var i=Mw.baseCalendar.prototype._validate.apply(this,arguments);if(i.year<1276||i.year>1500)throw n.replace(/\\{0\\}/,this.local.name);return i}});Mw.calendars.ummalqura=AQ;var 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i=0;i<r.length;i++)pet(e,t,r[i]+\"calendar\",n.calendar)},Jtr={chinese:\"2000-01-01\",coptic:\"2000-01-01\",discworld:\"2000-01-01\",ethiopian:\"2000-01-01\",hebrew:\"5000-01-01\",islamic:\"1000-01-01\",julian:\"2000-01-01\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-01\",nepali:\"2000-01-01\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-01\",thai:\"2000-01-01\",ummalqura:\"1400-01-01\"},$tr={chinese:\"2000-01-02\",coptic:\"2000-01-03\",discworld:\"2000-01-03\",ethiopian:\"2000-01-05\",hebrew:\"5000-01-01\",islamic:\"1000-01-02\",julian:\"2000-01-03\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-05\",nepali:\"2000-01-05\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-04\",thai:\"2000-01-04\",ummalqura:\"1400-01-06\"},Qtr={chinese:[\"2000-01-01\",\"2001-01-01\"],coptic:[\"1700-01-01\",\"1701-01-01\"],discworld:[\"1800-01-01\",\"1801-01-01\"],ethiopian:[\"2000-01-01\",\"2001-01-01\"],hebrew:[\"5700-01-01\",\"5701-01-01\"],islamic:[\"1400-01-01\",\"1401-01-01\"],julian:[\"2000-01-01\",\"2001-01-01\"],mayan:[\"5200-01-01\",\"5201-01-01\"],nanakshahi:[\"0500-01-01\",\"0501-01-01\"],nepali:[\"2000-01-01\",\"2001-01-01\"],persian:[\"1400-01-01\",\"1401-01-01\"],jalali:[\"1400-01-01\",\"1401-01-01\"],taiwan:[\"0100-01-01\",\"0101-01-01\"],thai:[\"2500-01-01\",\"2501-01-01\"],ummalqura:[\"1400-01-01\",\"1401-01-01\"]},z9=\"##\",err={d:{0:\"dd\",\"-\":\"d\"},e:{0:\"d\",\"-\":\"d\"},a:{0:\"D\",\"-\":\"D\"},A:{0:\"DD\",\"-\":\"DD\"},j:{0:\"oo\",\"-\":\"o\"},W:{0:\"ww\",\"-\":\"w\"},m:{0:\"mm\",\"-\":\"m\"},b:{0:\"M\",\"-\":\"M\"},B:{0:\"MM\",\"-\":\"MM\"},y:{0:\"yy\",\"-\":\"yy\"},Y:{0:\"yyyy\",\"-\":\"yyyy\"},U:z9,w:z9,c:{0:\"D 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This does not set the calendar for\",\"interpreting data on this axis, that's specified in the trace\",\"or via the global `layout.calendar`\"].join(\" \"));met.exports={moduleType:\"component\",name:\"calendars\",schema:{traces:{scatter:ny,bar:ny,box:ny,heatmap:ny,contour:ny,histogram:ny,histogram2d:ny,histogram2dcontour:ny,scatter3d:SQ,surface:SQ,mesh3d:SQ,scattergl:ny,ohlc:MQ,candlestick:MQ},layout:{calendar:gC([\"Sets the default calendar system to use for interpreting and\",\"displaying dates throughout the plot.\"].join(\" \"))},subplots:{xaxis:{calendar:rS},yaxis:{calendar:rS},scene:{xaxis:{calendar:rS},yaxis:{calendar:rS},zaxis:{calendar:rS}},polar:{radialaxis:{calendar:rS}}}},layoutAttributes:EQ,handleDefaults:pet,handleTraceDefaults:Ktr,CANONICAL_SUNDAY:$tr,CANONICAL_TICK:Jtr,DFLTRANGE:Qtr,getCal:get,worldCalFmt:trr}});var xet=ye((nTr,_et)=>{\"use strict\";_et.exports=yet()});var rrr=ye((aTr,wet)=>{var bet=rye();bet.register([a1e(),W1e(),oxe(),Exe(),Uxe(),Obe(),Kbe(),O2e(),hwe(),Zwe(),F3e(),XEe(),zke(),E6e(),pLe(),WLe(),gPe(),UIe(),o8e(),A8e(),z8e(),K8e(),fRe(),ERe(),tFe(),bFe(),qBe(),qNe(),ZUe(),xVe(),LGe(),jGe(),pHe(),Eje(),Vje(),hWe(),bXe(),jXe(),MZe(),ZYe(),yKe(),BKe(),fJe(),SJe(),A$e(),G$e(),lQe(),GQe(),xet()]);wet.exports=bet});return rrr();})();\n",
+       "/*!\n",
+       " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT license.\n",
+       " */\n",
+       "/*!\n",
+       " * repeat-string <https://github.com/jonschlinkert/repeat-string>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT License.\n",
+       " */\n",
+       "/*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh <https://feross.org/opensource> */\n",
+       "/*!\n",
+       " * The buffer module from node.js, for the browser.\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
+       "/*!\n",
+       " * Determine if an object is a Buffer\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
+       "/*! Bundled license information:\n",
+       "\n",
+       "native-promise-only/lib/npo.src.js:\n",
+       "  (*! Native Promise Only\n",
+       "      v0.8.1 (c) Kyle Simpson\n",
+       "      MIT License: http://getify.mit-license.org\n",
+       "  *)\n",
+       "\n",
+       "polybooljs/index.js:\n",
+       "  (*\n",
+       "   * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
+       "   * @license MIT\n",
+       "   * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
+       "   *)\n",
+       "\n",
+       "ieee754/index.js:\n",
+       "  (*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh <https://feross.org/opensource> *)\n",
+       "\n",
+       "buffer/index.js:\n",
+       "  (*!\n",
+       "   * The buffer module from node.js, for the browser.\n",
+       "   *\n",
+       "   * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       "   * @license  MIT\n",
+       "   *)\n",
+       "\n",
+       "safe-buffer/index.js:\n",
+       "  (*! safe-buffer. MIT License. Feross Aboukhadijeh <https://feross.org/opensource> *)\n",
+       "\n",
+       "assert/build/internal/util/comparisons.js:\n",
+       "  (*!\n",
+       "   * The buffer module from node.js, for the browser.\n",
+       "   *\n",
+       "   * @author   Feross Aboukhadijeh <feross@feross.org> <http://feross.org>\n",
+       "   * @license  MIT\n",
+       "   *)\n",
+       "\n",
+       "object-assign/index.js:\n",
+       "  (*\n",
+       "  object-assign\n",
+       "  (c) Sindre Sorhus\n",
+       "  @license MIT\n",
+       "  *)\n",
+       "\n",
+       "maplibre-gl/dist/maplibre-gl.js:\n",
+       "  (**\n",
+       "   * MapLibre GL JS\n",
+       "   * @license 3-Clause BSD. Full text of license: https://github.com/maplibre/maplibre-gl-js/blob/v4.7.1/LICENSE.txt\n",
+       "   *)\n",
+       "*/\n",
+       "\n",
+       "window.Plotly = Plotly;\n",
+       "return Plotly;\n",
+       "}));</script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+       "                            \n",
+       "var gd = document.getElementById('31539a9a-31d7-403c-af42-b3c21ffe5779');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
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+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from abaco.plots import plotPCoA\n",
+    "import plotly.io as pio\n",
+    "pio.renderers.default = \"notebook\"\n",
+    "\n",
+    "plotPCoA(\n",
+    "    data=df_all, \n",
+    "    sample_label=id_col, \n",
+    "    batch_label=batch_col,  \n",
+    "    experiment_label=bio_col,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ddbd9118",
+   "metadata": {},
+   "source": [
+    "- Batch effect (colours): \n",
+    "    - Analysis of the samples were completed on 2 different dates which could result in a technical source of variation captured by the slight clustering of batches along PCo1\n",
+    "- Biological effect (shapes): \n",
+    "    - The samples were collected from 3 different wwtps which we use as the biological source of variation for abaco to retain during batch correction. \n",
+    "    - There isn't a clear clustering of shapes in the PCoA plot, but we can take a look at other metrics such as alpha diversity indices between wwtp locations that should be retained after abaco reconstruction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cfdd9a92",
+   "metadata": {},
+   "source": [
+    "## Alpha diversity of original samples\n",
+    "\n",
+    "For each sample we will calculate the below richess, evenness and diversity indices and store them as additional sample (obs) metadata in the anndata set.\n",
+    "\n",
+    "Richness\n",
+    "- number of unique species per sample\n",
+    "- Chao1 estimate - correction to above which is likely an underestimation\n",
+    "\n",
+    "Diversity\n",
+    "- Shannon diversity index - if a sample is more diverse then there is more entropy (predicting the next taxa is more difficult) and thus the Shannon diversity index is higher. \n",
+    "- Simpson index (and inverse) - probability of 2 microbes being the same taxa (Simpson index closer to 0 is more diverse, while a higher inverse Simpson index means a sample is more diverse)\n",
+    "\n",
+    "Evenness\n",
+    "- Pielou's evenness index - when abundances are more homogenous in a sample then more even so higher Pielou\n",
+    "\n",
+    "The formulas are included with the below code. The metrics name will be prefixed with 'X_' so that we can later compare them to 'abaco_' metrics. \n",
+    "\n",
+    "### Preprocessing the count tables\n",
+    "\n",
+    "The raw counts require preprocessing because samples will have different total read counts due to technical differences during sequencing. We can normalize the samples to get relative abundances of the taxa summing to 1 (composition data)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "506a301e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1.])"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# normalize original data and store as additional anndata layer\n",
+    "adata.layers['normalized_X'] = adata.layers['nona']/adata.layers['nona'].sum(axis=1).reshape(-1,1)\n",
+    "# sanity check \n",
+    "adata.layers['normalized_X'].sum(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2238f8d2",
+   "metadata": {},
+   "source": [
+    "Our normalized, compositional data (CoDa) is bound to a simplex. To move forward with any statistical tests or ML we can choose to map the coda to unconstrained vectors by log-ratio transforming (e.g., centred log-ratio via `skbio.stats.composition.clr()`) the data. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "54ab5719",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from skbio.stats.composition import clr \n",
+    "\n",
+    "# CLR transform normalized data, replacing zeros with smallll val to avoid log(0)\n",
+    "adata.layers['clr_X'] = clr(np.where(adata.layers['normalized_X'] > 0, adata.layers['normalized_X'], 1e-10))\n",
+    "\n",
+    "# save anndata with new layers\n",
+    "adata.write_h5ad(\"data/mgnify_tomato.h5ad\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b63709a3",
+   "metadata": {},
+   "source": [
+    "### Alpha diversity as sample metadata"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "cf343afd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/14881299.py:8: RuntimeWarning:\n",
+      "\n",
+      "divide by zero encountered in divide\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Diversity: Number of unique taxa per sample as new metadata\n",
+    "adata.obs['X_numtaxa'] = (adata.X > 0).sum(axis=1) \n",
+    "\n",
+    "# Diversity with correction: Chao1 estimator\n",
+    "# Chao1 = num observed taxa + (num singletons / (2 x num doubletons))\n",
+    "num_singletons = (adata.X == 1).sum(axis=1)\n",
+    "num_doubletons = (adata.X == 2).sum(axis=1)\n",
+    "adata.obs['X_chao1'] = (adata.X > 0).sum(axis=1) + (num_singletons / (2 * num_doubletons))\n",
+    "\n",
+    "# Diversity: Shannon index H = -sum(p_i * log(p_i)), entropy\n",
+    "from scipy.stats import entropy\n",
+    "adata.obs['X_shannon'] = entropy(adata.layers['normalized_X'], nan_policy='omit', axis=1)\n",
+    "\n",
+    "# Evenness: Pielou evenness index P = H/H_max, H_max = ln(num species)\n",
+    "adata.obs['X_pielou'] = adata.obs['X_shannon'] / np.log(adata.obs['X_numtaxa'])\n",
+    "\n",
+    "# Diversity: simpson index lambda = sum(p_i ^2)\n",
+    "adata.obs['X_simpson'] = (adata.layers['normalized_X'] ** 2).sum(axis=1)\n",
+    "\n",
+    "# Diversity: inverse simpson index D = 1/lambda\n",
+    "adata.obs['X_inv_simpson'] = 1 / adata.obs['X_simpson']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d93a9846",
+   "metadata": {},
+   "source": [
+    "We can quickly visualize the distribution and relationships between the metrics by batch and biological groups using [`seaborn.pairplot()`](https://seaborn.pydata.org/generated/seaborn.pairplot.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5b7f3d3e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[None]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1181.25x1080 with 27 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1239.38x1080 with 27 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# preparing the df for vis\n",
+    "df_alphas = adata.obs[[\n",
+    "    'X_numtaxa', 'X_chao1', 'X_shannon', \n",
+    "    'X_pielou', 'X_simpson', 'X_inv_simpson',\n",
+    "    batch_col, bio_col\n",
+    "]].copy()\n",
+    "\n",
+    "# plotting by bio groups\n",
+    "g1 = sns.pairplot(df_alphas, hue=bio_col, corner=True, height=1.8)\n",
+    "g1.figure.suptitle('Alpha Diversity by Biological Groups', fontsize=22)\n",
+    "plt.setp(g1._legend.get_texts(), fontsize=18)\n",
+    "plt.setp(g1._legend.get_title(), fontsize=20)\n",
+    "\n",
+    "g2 = sns.pairplot(df_alphas, hue=batch_col, corner=True, height=1.8)\n",
+    "g2.figure.suptitle('Alpha Diversity by Batch Groups', fontsize=22)\n",
+    "plt.setp(g2._legend.get_texts(), fontsize=18)\n",
+    "plt.setp(g2._legend.get_title(), fontsize=20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2fac173b",
+   "metadata": {},
+   "source": [
+    "The pairplots suggest that the batch effect could be influencing the alpha diversity of the samples. \n",
+    "\n",
+    "-----"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bbae141c",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "## The goal \n",
+    "\n",
+    "Here the aim of **ABaCo** is to: \n",
+    "1) correct the batch effect (e.g., the points should no longer cluster by colour in the PCoA and pairplot) while\n",
+    "2) maintaining biological variance (e.g., the pairplot coloured by bio group should be not change).\n",
+    "\n",
+    "Ideally, after using AbaCo to transform the data, the resulting PCoA and pairplot coloured by batches will look like a colourful mixture of points and the pairplot coloured by wwtp location should not change.\n",
+    "\n",
+    "-----\n",
+    "\n",
+    "## Using `ABaCo`\n",
+    "\n",
+    "### Setting up ABaCo\n",
+    "\n",
+    "We instantiate the `abaco.metaABaCo()` class and pass the required parameters shown in the cell below. Thus, running abaco with the default optional parameters.\n",
+    "\n",
+    "Usually, setup of the parameters is required, which are explained in brief in the documentation e.g. `help(metaABaCo)`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ac1c6cc7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from abaco.ABaCo import metaABaCo\n",
+    "import torch\n",
+    "\n",
+    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+    "\n",
+    "# Instaantiate the ABaCo model\n",
+    "model = metaABaCo(\n",
+    "    data=df_all, # Pre-processed dataframe\n",
+    "    n_bios=df_all[bio_col].nunique(), # Number of biological groups in the data\n",
+    "    bio_label=bio_col, # Column where biological groups are labeled in the dataframe\n",
+    "    n_batches=df_all[batch_col].nunique(), # Number of batch groups in the data\n",
+    "    batch_label=batch_col, # Column where batch groups are labeled in the dataframe\n",
+    "    n_features=df_taxa.shape[1], # Number of features (taxonomic groups)\n",
+    "    prior=\"MoG\", # Prior distribution \n",
+    "    device=device, # Device\n",
+    "    epochs = [1000, 2000, 2000]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2f20940c",
+   "metadata": {
+    "tags": [
+     "hide-output"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on class metaABaCo in module abaco.ABaCo:\n",
+      "\n",
+      "class metaABaCo(torch.nn.modules.module.Module)\n",
+      " |  metaABaCo(data, n_bios, bio_label, n_batches, batch_label, n_features, device, prior='MoG', pdist='ZINB', d_z=16, epochs=[1000, 2000, 2000], encoder_net=[512, 256, 128], decoder_net=[128, 256, 512], vae_act_fun=ReLU(), disc_net=[128, 64], disc_act_fun=ReLU())\n",
+      " |  \n",
+      " |  Method resolution order:\n",
+      " |      metaABaCo\n",
+      " |      torch.nn.modules.module.Module\n",
+      " |      builtins.object\n",
+      " |  \n",
+      " |  Methods defined here:\n",
+      " |  \n",
+      " |  __init__(self, data, n_bios, bio_label, n_batches, batch_label, n_features, device, prior='MoG', pdist='ZINB', d_z=16, epochs=[1000, 2000, 2000], encoder_net=[512, 256, 128], decoder_net=[128, 256, 512], vae_act_fun=ReLU(), disc_net=[128, 64], disc_act_fun=ReLU())\n",
+      " |      Function to create the metaABaCo model.\n",
+      " |      \n",
+      " |      Parameters\n",
+      " |      ----------\n",
+      " |      data: pd.DataFrame\n",
+      " |          Pre-processed DataFrame to correct. Only feature columns to correct should be of numerical data type.\n",
+      " |      n_bios: int\n",
+      " |          Number of labels or (potential) clusters based on biological variance. For example, if 2 experimental\n",
+      " |          conditions (e.g., control and treatment) then n_bios = 2.\n",
+      " |      bio_label: char\n",
+      " |          Column label where biological labels are contained in data.\n",
+      " |      n_batches: int\n",
+      " |          Number of batches in the dataset. For example, if samples were sequenced in\n",
+      " |          5 batches (e.g., 5 different dates) then batches = 5.\n",
+      " |      batch_label: char\n",
+      " |          Column label where batch labels are contained in data.\n",
+      " |      n_features: int\n",
+      " |          Number of features in the input data, columns. For example, if the input is a gene expression matrix with 1000 genes,\n",
+      " |          then input_size = 1000.\n",
+      " |      device: torch.device\n",
+      " |          Device to run the model on, e.g., \"cuda\" or \"cpu\".\n",
+      " |      prior: str\n",
+      " |          Prior distribution used. Baseline is \"VMM\" (VampPrior Mixture Model). Options are \"VMM\" and\n",
+      " |          \"MoG\" (Mixture of Gaussians).\n",
+      " |      pdist: str\n",
+      " |          Output distribution used. Baseline is \"ZINB\" (Zero-inflated Negative Binomial).\n",
+      " |      d_z: int\n",
+      " |          Dimensionality of the latent space. For example, if d_z = 16, then the latent space will have 16 dimensions.\n",
+      " |      epochs: list\n",
+      " |          Number of epochs for first, second and third phase of ABaCo. Default is [1000, 2000, 2000]\n",
+      " |      encoder_net: list\n",
+      " |          List of integers defining the architecture of the encoder. Each integer is a layer size.\n",
+      " |          For example, [1024, 512, 256] means the encoder will have three layers with 1024, 512, and 256 neurons respectively.\n",
+      " |      decoder_net: list\n",
+      " |          List of integers defining the architecture of the decoder. Each integer is a layer size.\n",
+      " |          For example, [256, 512, 1024] means the decoder will have three layers with 256, 512, and 1024 neurons respectively.\n",
+      " |      vae_act_func: nn.Module\n",
+      " |          Activation function for the VAE encoder and decoder. Default is nn.ReLU().\n",
+      " |      disc_net: list\n",
+      " |          List of integers defining the architecture of the discriminator. Each integer is a layer size.\n",
+      " |          For example, [256, 128, 64] means the discriminator will have three layers with 256, 128, and 64 neurons respectively.\n",
+      " |      disc_act_fun: nn.Module\n",
+      " |          Activation function for the discriminator. Default is nn.ReLU().\n",
+      " |  \n",
+      " |  batch_correct(self, train_loader, vae_optimizer, disc_optimizer, adv_optimizer, w_disc=1.0, w_adv=1.0, w_elbo_nll=1.0, w_elbo_kl=1.0, w_bio_penalty=1.0, w_cluster_penalty=1.0)\n",
+      " |      Train the conditional VAE model for batch correction. This is trained after VAE prior parameters are defined,\n",
+      " |  \n",
+      " |  batch_mask(self, train_loader, decoder_optimizer, smooth_annealing=True, cycle_reg=None, w_elbo_nll=1.0, w_cycle=0.001)\n",
+      " |      Pre-trained VAE will now have frozen encoder and batch labels masked at the encoder.\n",
+      " |  \n",
+      " |  correct(self, seed=None, mask=True)\n",
+      " |  \n",
+      " |  fit(self, smooth_annealing=True, cycle_reg=None, seed=None, w_elbo_nll=1.0, w_elbo_kl=1.0, w_bio_penalty=1.0, w_cluster_penalty=1.0, w_cycle=0.001, w_disc=1.0, w_adv=1.0, phase_1_vae_lr=0.001, phase_2_vae_lr=0.001, phase_3_vae_lr=1e-06, disc_lr=0.001, adv_lr=0.001)\n",
+      " |  \n",
+      " |  plot_pca_posterior(self, figsize=(14, 6), palette='tab10')\n",
+      " |      Get the plot of the first 2 principal components of the posterior distribution.\n",
+      " |  \n",
+      " |  train_vae(self, train_loader, optimizer, w_elbo_nll=1.0, w_elbo_kl=1.0, w_bio_penalty=1.0, w_cluster_penalty=1.0)\n",
+      " |      Train the conditional VAE model. If clustering prior is used, penalization term is applied to increase sparsity of the clusters.\n",
+      " |      \n",
+      " |      Parameters:\n",
+      " |          vae: [VAE]\n",
+      " |              Variational Autoencoder model\n",
+      " |          train_loader: [torch.utils.data.DataLoader]\n",
+      " |              DataLoader for the training data\n",
+      " |          optimizer: [torch.optim.Optimizer]\n",
+      " |              Optimizer for training\n",
+      " |          epochs: [int]\n",
+      " |              Number of training epochs\n",
+      " |          device: [str]\n",
+      " |              Device to use for computations\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes defined here:\n",
+      " |  \n",
+      " |  __annotations__ = {}\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Methods inherited from torch.nn.modules.module.Module:\n",
+      " |  \n",
+      " |  __call__ = _wrapped_call_impl(self, *args, **kwargs)\n",
+      " |  \n",
+      " |  __delattr__(self, name) -> None\n",
+      " |      Implement delattr(self, name).\n",
+      " |  \n",
+      " |  __dir__(self)\n",
+      " |      Default dir() implementation.\n",
+      " |  \n",
+      " |  __getattr__(self, name: str) -> Union[torch.Tensor, ForwardRef('Module')]\n",
+      " |      # It is crucial that the return type is not annotated as `Any`, otherwise type checking\n",
+      " |      # on `torch.nn.Module` and all its subclasses is largely disabled as a result. See:\n",
+      " |      # https://github.com/pytorch/pytorch/pull/115074\n",
+      " |  \n",
+      " |  __getstate__(self)\n",
+      " |      Helper for pickle.\n",
+      " |  \n",
+      " |  __repr__(self) -> str\n",
+      " |      Return repr(self).\n",
+      " |  \n",
+      " |  __setattr__(self, name: str, value: Union[torch.Tensor, ForwardRef('Module')]) -> None\n",
+      " |      Implement setattr(self, name, value).\n",
+      " |  \n",
+      " |  __setstate__(self, state)\n",
+      " |  \n",
+      " |  add_module(self, name: str, module: Optional[ForwardRef('Module')]) -> None\n",
+      " |      Add a child module to the current module.\n",
+      " |      \n",
+      " |      The module can be accessed as an attribute using the given name.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          name (str): name of the child module. The child module can be\n",
+      " |              accessed from this module using the given name\n",
+      " |          module (Module): child module to be added to the module.\n",
+      " |  \n",
+      " |  apply(self, fn: Callable[[ForwardRef('Module')], NoneType]) -> Self\n",
+      " |      Apply ``fn`` recursively to every submodule (as returned by ``.children()``) as well as self.\n",
+      " |      \n",
+      " |      Typical use includes initializing the parameters of a model\n",
+      " |      (see also :ref:`nn-init-doc`).\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          fn (:class:`Module` -> None): function to be applied to each submodule\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> @torch.no_grad()\n",
+      " |          >>> def init_weights(m):\n",
+      " |          >>>     print(m)\n",
+      " |          >>>     if type(m) == nn.Linear:\n",
+      " |          >>>         m.weight.fill_(1.0)\n",
+      " |          >>>         print(m.weight)\n",
+      " |          >>> net = nn.Sequential(nn.Linear(2, 2), nn.Linear(2, 2))\n",
+      " |          >>> net.apply(init_weights)\n",
+      " |          Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[1., 1.],\n",
+      " |                  [1., 1.]], requires_grad=True)\n",
+      " |          Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[1., 1.],\n",
+      " |                  [1., 1.]], requires_grad=True)\n",
+      " |          Sequential(\n",
+      " |            (0): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |            (1): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          )\n",
+      " |  \n",
+      " |  bfloat16(self) -> Self\n",
+      " |      Casts all floating point parameters and buffers to ``bfloat16`` datatype.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  buffers(self, recurse: bool = True) -> collections.abc.Iterator[torch.Tensor]\n",
+      " |      Return an iterator over module buffers.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          recurse (bool): if True, then yields buffers of this module\n",
+      " |              and all submodules. Otherwise, yields only buffers that\n",
+      " |              are direct members of this module.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          torch.Tensor: module buffer\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> for buf in model.buffers():\n",
+      " |          >>>     print(type(buf), buf.size())\n",
+      " |          <class 'torch.Tensor'> (20L,)\n",
+      " |          <class 'torch.Tensor'> (20L, 1L, 5L, 5L)\n",
+      " |  \n",
+      " |  children(self) -> collections.abc.Iterator['Module']\n",
+      " |      Return an iterator over immediate children modules.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          Module: a child module\n",
+      " |  \n",
+      " |  compile(self, *args, **kwargs)\n",
+      " |      Compile this Module's forward using :func:`torch.compile`.\n",
+      " |      \n",
+      " |      This Module's `__call__` method is compiled and all arguments are passed as-is\n",
+      " |      to :func:`torch.compile`.\n",
+      " |      \n",
+      " |      See :func:`torch.compile` for details on the arguments for this function.\n",
+      " |  \n",
+      " |  cpu(self) -> Self\n",
+      " |      Move all model parameters and buffers to the CPU.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  cuda(self, device: Union[torch.device, int, NoneType] = None) -> Self\n",
+      " |      Move all model parameters and buffers to the GPU.\n",
+      " |      \n",
+      " |      This also makes associated parameters and buffers different objects. So\n",
+      " |      it should be called before constructing the optimizer if the module will\n",
+      " |      live on GPU while being optimized.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          device (int, optional): if specified, all parameters will be\n",
+      " |              copied to that device\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  double(self) -> Self\n",
+      " |      Casts all floating point parameters and buffers to ``double`` datatype.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  eval(self) -> Self\n",
+      " |      Set the module in evaluation mode.\n",
+      " |      \n",
+      " |      This has an effect only on certain modules. See the documentation of\n",
+      " |      particular modules for details of their behaviors in training/evaluation\n",
+      " |      mode, i.e. whether they are affected, e.g. :class:`Dropout`, :class:`BatchNorm`,\n",
+      " |      etc.\n",
+      " |      \n",
+      " |      This is equivalent with :meth:`self.train(False) <torch.nn.Module.train>`.\n",
+      " |      \n",
+      " |      See :ref:`locally-disable-grad-doc` for a comparison between\n",
+      " |      `.eval()` and several similar mechanisms that may be confused with it.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  extra_repr(self) -> str\n",
+      " |      Return the extra representation of the module.\n",
+      " |      \n",
+      " |      To print customized extra information, you should re-implement\n",
+      " |      this method in your own modules. Both single-line and multi-line\n",
+      " |      strings are acceptable.\n",
+      " |  \n",
+      " |  float(self) -> Self\n",
+      " |      Casts all floating point parameters and buffers to ``float`` datatype.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  forward = _forward_unimplemented(self, *input: Any) -> None\n",
+      " |      Define the computation performed at every call.\n",
+      " |      \n",
+      " |      Should be overridden by all subclasses.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          Although the recipe for forward pass needs to be defined within\n",
+      " |          this function, one should call the :class:`Module` instance afterwards\n",
+      " |          instead of this since the former takes care of running the\n",
+      " |          registered hooks while the latter silently ignores them.\n",
+      " |  \n",
+      " |  get_buffer(self, target: str) -> 'Tensor'\n",
+      " |      Return the buffer given by ``target`` if it exists, otherwise throw an error.\n",
+      " |      \n",
+      " |      See the docstring for ``get_submodule`` for a more detailed\n",
+      " |      explanation of this method's functionality as well as how to\n",
+      " |      correctly specify ``target``.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          target: The fully-qualified string name of the buffer\n",
+      " |              to look for. (See ``get_submodule`` for how to specify a\n",
+      " |              fully-qualified string.)\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          torch.Tensor: The buffer referenced by ``target``\n",
+      " |      \n",
+      " |      Raises:\n",
+      " |          AttributeError: If the target string references an invalid\n",
+      " |              path or resolves to something that is not a\n",
+      " |              buffer\n",
+      " |  \n",
+      " |  get_extra_state(self) -> Any\n",
+      " |      Return any extra state to include in the module's state_dict.\n",
+      " |      \n",
+      " |      Implement this and a corresponding :func:`set_extra_state` for your module\n",
+      " |      if you need to store extra state. This function is called when building the\n",
+      " |      module's `state_dict()`.\n",
+      " |      \n",
+      " |      Note that extra state should be picklable to ensure working serialization\n",
+      " |      of the state_dict. We only provide backwards compatibility guarantees\n",
+      " |      for serializing Tensors; other objects may break backwards compatibility if\n",
+      " |      their serialized pickled form changes.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          object: Any extra state to store in the module's state_dict\n",
+      " |  \n",
+      " |  get_parameter(self, target: str) -> 'Parameter'\n",
+      " |      Return the parameter given by ``target`` if it exists, otherwise throw an error.\n",
+      " |      \n",
+      " |      See the docstring for ``get_submodule`` for a more detailed\n",
+      " |      explanation of this method's functionality as well as how to\n",
+      " |      correctly specify ``target``.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          target: The fully-qualified string name of the Parameter\n",
+      " |              to look for. (See ``get_submodule`` for how to specify a\n",
+      " |              fully-qualified string.)\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          torch.nn.Parameter: The Parameter referenced by ``target``\n",
+      " |      \n",
+      " |      Raises:\n",
+      " |          AttributeError: If the target string references an invalid\n",
+      " |              path or resolves to something that is not an\n",
+      " |              ``nn.Parameter``\n",
+      " |  \n",
+      " |  get_submodule(self, target: str) -> 'Module'\n",
+      " |      Return the submodule given by ``target`` if it exists, otherwise throw an error.\n",
+      " |      \n",
+      " |      For example, let's say you have an ``nn.Module`` ``A`` that\n",
+      " |      looks like this:\n",
+      " |      \n",
+      " |      .. code-block:: text\n",
+      " |      \n",
+      " |          A(\n",
+      " |              (net_b): Module(\n",
+      " |                  (net_c): Module(\n",
+      " |                      (conv): Conv2d(16, 33, kernel_size=(3, 3), stride=(2, 2))\n",
+      " |                  )\n",
+      " |                  (linear): Linear(in_features=100, out_features=200, bias=True)\n",
+      " |              )\n",
+      " |          )\n",
+      " |      \n",
+      " |      (The diagram shows an ``nn.Module`` ``A``. ``A`` which has a nested\n",
+      " |      submodule ``net_b``, which itself has two submodules ``net_c``\n",
+      " |      and ``linear``. ``net_c`` then has a submodule ``conv``.)\n",
+      " |      \n",
+      " |      To check whether or not we have the ``linear`` submodule, we\n",
+      " |      would call ``get_submodule(\"net_b.linear\")``. To check whether\n",
+      " |      we have the ``conv`` submodule, we would call\n",
+      " |      ``get_submodule(\"net_b.net_c.conv\")``.\n",
+      " |      \n",
+      " |      The runtime of ``get_submodule`` is bounded by the degree\n",
+      " |      of module nesting in ``target``. A query against\n",
+      " |      ``named_modules`` achieves the same result, but it is O(N) in\n",
+      " |      the number of transitive modules. So, for a simple check to see\n",
+      " |      if some submodule exists, ``get_submodule`` should always be\n",
+      " |      used.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          target: The fully-qualified string name of the submodule\n",
+      " |              to look for. (See above example for how to specify a\n",
+      " |              fully-qualified string.)\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          torch.nn.Module: The submodule referenced by ``target``\n",
+      " |      \n",
+      " |      Raises:\n",
+      " |          AttributeError: If at any point along the path resulting from\n",
+      " |              the target string the (sub)path resolves to a non-existent\n",
+      " |              attribute name or an object that is not an instance of ``nn.Module``.\n",
+      " |  \n",
+      " |  half(self) -> Self\n",
+      " |      Casts all floating point parameters and buffers to ``half`` datatype.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  ipu(self, device: Union[torch.device, int, NoneType] = None) -> Self\n",
+      " |      Move all model parameters and buffers to the IPU.\n",
+      " |      \n",
+      " |      This also makes associated parameters and buffers different objects. So\n",
+      " |      it should be called before constructing the optimizer if the module will\n",
+      " |      live on IPU while being optimized.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Arguments:\n",
+      " |          device (int, optional): if specified, all parameters will be\n",
+      " |              copied to that device\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  load_state_dict(self, state_dict: collections.abc.Mapping[str, typing.Any], strict: bool = True, assign: bool = False)\n",
+      " |      Copy parameters and buffers from :attr:`state_dict` into this module and its descendants.\n",
+      " |      \n",
+      " |      If :attr:`strict` is ``True``, then\n",
+      " |      the keys of :attr:`state_dict` must exactly match the keys returned\n",
+      " |      by this module's :meth:`~torch.nn.Module.state_dict` function.\n",
+      " |      \n",
+      " |      .. warning::\n",
+      " |          If :attr:`assign` is ``True`` the optimizer must be created after\n",
+      " |          the call to :attr:`load_state_dict` unless\n",
+      " |          :func:`~torch.__future__.get_swap_module_params_on_conversion` is ``True``.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          state_dict (dict): a dict containing parameters and\n",
+      " |              persistent buffers.\n",
+      " |          strict (bool, optional): whether to strictly enforce that the keys\n",
+      " |              in :attr:`state_dict` match the keys returned by this module's\n",
+      " |              :meth:`~torch.nn.Module.state_dict` function. Default: ``True``\n",
+      " |          assign (bool, optional): When set to ``False``, the properties of the tensors\n",
+      " |              in the current module are preserved whereas setting it to ``True`` preserves\n",
+      " |              properties of the Tensors in the state dict. The only\n",
+      " |              exception is the ``requires_grad`` field of :class:`~torch.nn.Parameter`\n",
+      " |              for which the value from the module is preserved. Default: ``False``\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          ``NamedTuple`` with ``missing_keys`` and ``unexpected_keys`` fields:\n",
+      " |              * ``missing_keys`` is a list of str containing any keys that are expected\n",
+      " |                  by this module but missing from the provided ``state_dict``.\n",
+      " |              * ``unexpected_keys`` is a list of str containing the keys that are not\n",
+      " |                  expected by this module but present in the provided ``state_dict``.\n",
+      " |      \n",
+      " |      Note:\n",
+      " |          If a parameter or buffer is registered as ``None`` and its corresponding key\n",
+      " |          exists in :attr:`state_dict`, :meth:`load_state_dict` will raise a\n",
+      " |          ``RuntimeError``.\n",
+      " |  \n",
+      " |  modules(self) -> collections.abc.Iterator['Module']\n",
+      " |      Return an iterator over all modules in the network.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          Module: a module in the network\n",
+      " |      \n",
+      " |      Note:\n",
+      " |          Duplicate modules are returned only once. In the following\n",
+      " |          example, ``l`` will be returned only once.\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> l = nn.Linear(2, 2)\n",
+      " |          >>> net = nn.Sequential(l, l)\n",
+      " |          >>> for idx, m in enumerate(net.modules()):\n",
+      " |          ...     print(idx, '->', m)\n",
+      " |      \n",
+      " |          0 -> Sequential(\n",
+      " |            (0): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |            (1): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          )\n",
+      " |          1 -> Linear(in_features=2, out_features=2, bias=True)\n",
+      " |  \n",
+      " |  mtia(self, device: Union[torch.device, int, NoneType] = None) -> Self\n",
+      " |      Move all model parameters and buffers to the MTIA.\n",
+      " |      \n",
+      " |      This also makes associated parameters and buffers different objects. So\n",
+      " |      it should be called before constructing the optimizer if the module will\n",
+      " |      live on MTIA while being optimized.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Arguments:\n",
+      " |          device (int, optional): if specified, all parameters will be\n",
+      " |              copied to that device\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  named_buffers(self, prefix: str = '', recurse: bool = True, remove_duplicate: bool = True) -> collections.abc.Iterator[tuple[str, torch.Tensor]]\n",
+      " |      Return an iterator over module buffers, yielding both the name of the buffer as well as the buffer itself.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          prefix (str): prefix to prepend to all buffer names.\n",
+      " |          recurse (bool, optional): if True, then yields buffers of this module\n",
+      " |              and all submodules. Otherwise, yields only buffers that\n",
+      " |              are direct members of this module. Defaults to True.\n",
+      " |          remove_duplicate (bool, optional): whether to remove the duplicated buffers in the result. Defaults to True.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          (str, torch.Tensor): Tuple containing the name and buffer\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> for name, buf in self.named_buffers():\n",
+      " |          >>>     if name in ['running_var']:\n",
+      " |          >>>         print(buf.size())\n",
+      " |  \n",
+      " |  named_children(self) -> collections.abc.Iterator[tuple[str, 'Module']]\n",
+      " |      Return an iterator over immediate children modules, yielding both the name of the module as well as the module itself.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          (str, Module): Tuple containing a name and child module\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> for name, module in model.named_children():\n",
+      " |          >>>     if name in ['conv4', 'conv5']:\n",
+      " |          >>>         print(module)\n",
+      " |  \n",
+      " |  named_modules(self, memo: Optional[set['Module']] = None, prefix: str = '', remove_duplicate: bool = True)\n",
+      " |      Return an iterator over all modules in the network, yielding both the name of the module as well as the module itself.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          memo: a memo to store the set of modules already added to the result\n",
+      " |          prefix: a prefix that will be added to the name of the module\n",
+      " |          remove_duplicate: whether to remove the duplicated module instances in the result\n",
+      " |              or not\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          (str, Module): Tuple of name and module\n",
+      " |      \n",
+      " |      Note:\n",
+      " |          Duplicate modules are returned only once. In the following\n",
+      " |          example, ``l`` will be returned only once.\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> l = nn.Linear(2, 2)\n",
+      " |          >>> net = nn.Sequential(l, l)\n",
+      " |          >>> for idx, m in enumerate(net.named_modules()):\n",
+      " |          ...     print(idx, '->', m)\n",
+      " |      \n",
+      " |          0 -> ('', Sequential(\n",
+      " |            (0): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |            (1): Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          ))\n",
+      " |          1 -> ('0', Linear(in_features=2, out_features=2, bias=True))\n",
+      " |  \n",
+      " |  named_parameters(self, prefix: str = '', recurse: bool = True, remove_duplicate: bool = True) -> collections.abc.Iterator[tuple[str, torch.nn.parameter.Parameter]]\n",
+      " |      Return an iterator over module parameters, yielding both the name of the parameter as well as the parameter itself.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          prefix (str): prefix to prepend to all parameter names.\n",
+      " |          recurse (bool): if True, then yields parameters of this module\n",
+      " |              and all submodules. Otherwise, yields only parameters that\n",
+      " |              are direct members of this module.\n",
+      " |          remove_duplicate (bool, optional): whether to remove the duplicated\n",
+      " |              parameters in the result. Defaults to True.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          (str, Parameter): Tuple containing the name and parameter\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> for name, param in self.named_parameters():\n",
+      " |          >>>     if name in ['bias']:\n",
+      " |          >>>         print(param.size())\n",
+      " |  \n",
+      " |  parameters(self, recurse: bool = True) -> collections.abc.Iterator[torch.nn.parameter.Parameter]\n",
+      " |      Return an iterator over module parameters.\n",
+      " |      \n",
+      " |      This is typically passed to an optimizer.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          recurse (bool): if True, then yields parameters of this module\n",
+      " |              and all submodules. Otherwise, yields only parameters that\n",
+      " |              are direct members of this module.\n",
+      " |      \n",
+      " |      Yields:\n",
+      " |          Parameter: module parameter\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> for param in model.parameters():\n",
+      " |          >>>     print(type(param), param.size())\n",
+      " |          <class 'torch.Tensor'> (20L,)\n",
+      " |          <class 'torch.Tensor'> (20L, 1L, 5L, 5L)\n",
+      " |  \n",
+      " |  register_backward_hook(self, hook: Callable[[ForwardRef('Module'), Union[tuple[torch.Tensor, ...], torch.Tensor], Union[tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, tuple[torch.Tensor, ...], torch.Tensor]]) -> torch.utils.hooks.RemovableHandle\n",
+      " |      Register a backward hook on the module.\n",
+      " |      \n",
+      " |      This function is deprecated in favor of :meth:`~torch.nn.Module.register_full_backward_hook` and\n",
+      " |      the behavior of this function will change in future versions.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_buffer(self, name: str, tensor: Optional[torch.Tensor], persistent: bool = True) -> None\n",
+      " |      Add a buffer to the module.\n",
+      " |      \n",
+      " |      This is typically used to register a buffer that should not be\n",
+      " |      considered a model parameter. For example, BatchNorm's ``running_mean``\n",
+      " |      is not a parameter, but is part of the module's state. Buffers, by\n",
+      " |      default, are persistent and will be saved alongside parameters. This\n",
+      " |      behavior can be changed by setting :attr:`persistent` to ``False``. The\n",
+      " |      only difference between a persistent buffer and a non-persistent buffer\n",
+      " |      is that the latter will not be a part of this module's\n",
+      " |      :attr:`state_dict`.\n",
+      " |      \n",
+      " |      Buffers can be accessed as attributes using given names.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          name (str): name of the buffer. The buffer can be accessed\n",
+      " |              from this module using the given name\n",
+      " |          tensor (Tensor or None): buffer to be registered. If ``None``, then operations\n",
+      " |              that run on buffers, such as :attr:`cuda`, are ignored. If ``None``,\n",
+      " |              the buffer is **not** included in the module's :attr:`state_dict`.\n",
+      " |          persistent (bool): whether the buffer is part of this module's\n",
+      " |              :attr:`state_dict`.\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> self.register_buffer('running_mean', torch.zeros(num_features))\n",
+      " |  \n",
+      " |  register_forward_hook(self, hook: Union[Callable[[~T, tuple[Any, ...], Any], Optional[Any]], Callable[[~T, tuple[Any, ...], dict[str, Any], Any], Optional[Any]]], *, prepend: bool = False, with_kwargs: bool = False, always_call: bool = False) -> torch.utils.hooks.RemovableHandle\n",
+      " |      Register a forward hook on the module.\n",
+      " |      \n",
+      " |      The hook will be called every time after :func:`forward` has computed an output.\n",
+      " |      \n",
+      " |      If ``with_kwargs`` is ``False`` or not specified, the input contains only\n",
+      " |      the positional arguments given to the module. Keyword arguments won't be\n",
+      " |      passed to the hooks and only to the ``forward``. The hook can modify the\n",
+      " |      output. It can modify the input inplace but it will not have effect on\n",
+      " |      forward since this is called after :func:`forward` is called. The hook\n",
+      " |      should have the following signature::\n",
+      " |      \n",
+      " |          hook(module, args, output) -> None or modified output\n",
+      " |      \n",
+      " |      If ``with_kwargs`` is ``True``, the forward hook will be passed the\n",
+      " |      ``kwargs`` given to the forward function and be expected to return the\n",
+      " |      output possibly modified. The hook should have the following signature::\n",
+      " |      \n",
+      " |          hook(module, args, kwargs, output) -> None or modified output\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          hook (Callable): The user defined hook to be registered.\n",
+      " |          prepend (bool): If ``True``, the provided ``hook`` will be fired\n",
+      " |              before all existing ``forward`` hooks on this\n",
+      " |              :class:`torch.nn.Module`. Otherwise, the provided\n",
+      " |              ``hook`` will be fired after all existing ``forward`` hooks on\n",
+      " |              this :class:`torch.nn.Module`. Note that global\n",
+      " |              ``forward`` hooks registered with\n",
+      " |              :func:`register_module_forward_hook` will fire before all hooks\n",
+      " |              registered by this method.\n",
+      " |              Default: ``False``\n",
+      " |          with_kwargs (bool): If ``True``, the ``hook`` will be passed the\n",
+      " |              kwargs given to the forward function.\n",
+      " |              Default: ``False``\n",
+      " |          always_call (bool): If ``True`` the ``hook`` will be run regardless of\n",
+      " |              whether an exception is raised while calling the Module.\n",
+      " |              Default: ``False``\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_forward_pre_hook(self, hook: Union[Callable[[~T, tuple[Any, ...]], Optional[Any]], Callable[[~T, tuple[Any, ...], dict[str, Any]], Optional[tuple[Any, dict[str, Any]]]]], *, prepend: bool = False, with_kwargs: bool = False) -> torch.utils.hooks.RemovableHandle\n",
+      " |      Register a forward pre-hook on the module.\n",
+      " |      \n",
+      " |      The hook will be called every time before :func:`forward` is invoked.\n",
+      " |      \n",
+      " |      \n",
+      " |      If ``with_kwargs`` is false or not specified, the input contains only\n",
+      " |      the positional arguments given to the module. Keyword arguments won't be\n",
+      " |      passed to the hooks and only to the ``forward``. The hook can modify the\n",
+      " |      input. User can either return a tuple or a single modified value in the\n",
+      " |      hook. We will wrap the value into a tuple if a single value is returned\n",
+      " |      (unless that value is already a tuple). The hook should have the\n",
+      " |      following signature::\n",
+      " |      \n",
+      " |          hook(module, args) -> None or modified input\n",
+      " |      \n",
+      " |      If ``with_kwargs`` is true, the forward pre-hook will be passed the\n",
+      " |      kwargs given to the forward function. And if the hook modifies the\n",
+      " |      input, both the args and kwargs should be returned. The hook should have\n",
+      " |      the following signature::\n",
+      " |      \n",
+      " |          hook(module, args, kwargs) -> None or a tuple of modified input and kwargs\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          hook (Callable): The user defined hook to be registered.\n",
+      " |          prepend (bool): If true, the provided ``hook`` will be fired before\n",
+      " |              all existing ``forward_pre`` hooks on this\n",
+      " |              :class:`torch.nn.Module`. Otherwise, the provided\n",
+      " |              ``hook`` will be fired after all existing ``forward_pre`` hooks\n",
+      " |              on this :class:`torch.nn.Module`. Note that global\n",
+      " |              ``forward_pre`` hooks registered with\n",
+      " |              :func:`register_module_forward_pre_hook` will fire before all\n",
+      " |              hooks registered by this method.\n",
+      " |              Default: ``False``\n",
+      " |          with_kwargs (bool): If true, the ``hook`` will be passed the kwargs\n",
+      " |              given to the forward function.\n",
+      " |              Default: ``False``\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_full_backward_hook(self, hook: Callable[[ForwardRef('Module'), Union[tuple[torch.Tensor, ...], torch.Tensor], Union[tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, tuple[torch.Tensor, ...], torch.Tensor]], prepend: bool = False) -> torch.utils.hooks.RemovableHandle\n",
+      " |      Register a backward hook on the module.\n",
+      " |      \n",
+      " |      The hook will be called every time the gradients with respect to a module are computed, and its firing rules are as follows:\n",
+      " |      \n",
+      " |          1. Ordinarily, the hook fires when the gradients are computed with respect to the module inputs.\n",
+      " |          2. If none of the module inputs require gradients, the hook will fire when the gradients are computed\n",
+      " |             with respect to module outputs.\n",
+      " |          3. If none of the module outputs require gradients, then the hooks will not fire.\n",
+      " |      \n",
+      " |      The hook should have the following signature::\n",
+      " |      \n",
+      " |          hook(module, grad_input, grad_output) -> tuple(Tensor) or None\n",
+      " |      \n",
+      " |      The :attr:`grad_input` and :attr:`grad_output` are tuples that contain the gradients\n",
+      " |      with respect to the inputs and outputs respectively. The hook should\n",
+      " |      not modify its arguments, but it can optionally return a new gradient with\n",
+      " |      respect to the input that will be used in place of :attr:`grad_input` in\n",
+      " |      subsequent computations. :attr:`grad_input` will only correspond to the inputs given\n",
+      " |      as positional arguments and all kwarg arguments are ignored. Entries\n",
+      " |      in :attr:`grad_input` and :attr:`grad_output` will be ``None`` for all non-Tensor\n",
+      " |      arguments.\n",
+      " |      \n",
+      " |      For technical reasons, when this hook is applied to a Module, its forward function will\n",
+      " |      receive a view of each Tensor passed to the Module. Similarly the caller will receive a view\n",
+      " |      of each Tensor returned by the Module's forward function.\n",
+      " |      \n",
+      " |      .. warning ::\n",
+      " |          Modifying inputs or outputs inplace is not allowed when using backward hooks and\n",
+      " |          will raise an error.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          hook (Callable): The user-defined hook to be registered.\n",
+      " |          prepend (bool): If true, the provided ``hook`` will be fired before\n",
+      " |              all existing ``backward`` hooks on this\n",
+      " |              :class:`torch.nn.Module`. Otherwise, the provided\n",
+      " |              ``hook`` will be fired after all existing ``backward`` hooks on\n",
+      " |              this :class:`torch.nn.Module`. Note that global\n",
+      " |              ``backward`` hooks registered with\n",
+      " |              :func:`register_module_full_backward_hook` will fire before\n",
+      " |              all hooks registered by this method.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_full_backward_pre_hook(self, hook: Callable[[ForwardRef('Module'), Union[tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, tuple[torch.Tensor, ...], torch.Tensor]], prepend: bool = False) -> torch.utils.hooks.RemovableHandle\n",
+      " |      Register a backward pre-hook on the module.\n",
+      " |      \n",
+      " |      The hook will be called every time the gradients for the module are computed.\n",
+      " |      The hook should have the following signature::\n",
+      " |      \n",
+      " |          hook(module, grad_output) -> tuple[Tensor] or None\n",
+      " |      \n",
+      " |      The :attr:`grad_output` is a tuple. The hook should\n",
+      " |      not modify its arguments, but it can optionally return a new gradient with\n",
+      " |      respect to the output that will be used in place of :attr:`grad_output` in\n",
+      " |      subsequent computations. Entries in :attr:`grad_output` will be ``None`` for\n",
+      " |      all non-Tensor arguments.\n",
+      " |      \n",
+      " |      For technical reasons, when this hook is applied to a Module, its forward function will\n",
+      " |      receive a view of each Tensor passed to the Module. Similarly the caller will receive a view\n",
+      " |      of each Tensor returned by the Module's forward function.\n",
+      " |      \n",
+      " |      .. warning ::\n",
+      " |          Modifying inputs inplace is not allowed when using backward hooks and\n",
+      " |          will raise an error.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          hook (Callable): The user-defined hook to be registered.\n",
+      " |          prepend (bool): If true, the provided ``hook`` will be fired before\n",
+      " |              all existing ``backward_pre`` hooks on this\n",
+      " |              :class:`torch.nn.Module`. Otherwise, the provided\n",
+      " |              ``hook`` will be fired after all existing ``backward_pre`` hooks\n",
+      " |              on this :class:`torch.nn.Module`. Note that global\n",
+      " |              ``backward_pre`` hooks registered with\n",
+      " |              :func:`register_module_full_backward_pre_hook` will fire before\n",
+      " |              all hooks registered by this method.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_load_state_dict_post_hook(self, hook)\n",
+      " |      Register a post-hook to be run after module's :meth:`~nn.Module.load_state_dict` is called.\n",
+      " |      \n",
+      " |      It should have the following signature::\n",
+      " |          hook(module, incompatible_keys) -> None\n",
+      " |      \n",
+      " |      The ``module`` argument is the current module that this hook is registered\n",
+      " |      on, and the ``incompatible_keys`` argument is a ``NamedTuple`` consisting\n",
+      " |      of attributes ``missing_keys`` and ``unexpected_keys``. ``missing_keys``\n",
+      " |      is a ``list`` of ``str`` containing the missing keys and\n",
+      " |      ``unexpected_keys`` is a ``list`` of ``str`` containing the unexpected keys.\n",
+      " |      \n",
+      " |      The given incompatible_keys can be modified inplace if needed.\n",
+      " |      \n",
+      " |      Note that the checks performed when calling :func:`load_state_dict` with\n",
+      " |      ``strict=True`` are affected by modifications the hook makes to\n",
+      " |      ``missing_keys`` or ``unexpected_keys``, as expected. Additions to either\n",
+      " |      set of keys will result in an error being thrown when ``strict=True``, and\n",
+      " |      clearing out both missing and unexpected keys will avoid an error.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          :class:`torch.utils.hooks.RemovableHandle`:\n",
+      " |              a handle that can be used to remove the added hook by calling\n",
+      " |              ``handle.remove()``\n",
+      " |  \n",
+      " |  register_load_state_dict_pre_hook(self, hook)\n",
+      " |      Register a pre-hook to be run before module's :meth:`~nn.Module.load_state_dict` is called.\n",
+      " |      \n",
+      " |      It should have the following signature::\n",
+      " |          hook(module, state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) -> None  # noqa: B950\n",
+      " |      \n",
+      " |      Arguments:\n",
+      " |          hook (Callable): Callable hook that will be invoked before\n",
+      " |              loading the state dict.\n",
+      " |  \n",
+      " |  register_module(self, name: str, module: Optional[ForwardRef('Module')]) -> None\n",
+      " |      Alias for :func:`add_module`.\n",
+      " |  \n",
+      " |  register_parameter(self, name: str, param: Optional[torch.nn.parameter.Parameter]) -> None\n",
+      " |      Add a parameter to the module.\n",
+      " |      \n",
+      " |      The parameter can be accessed as an attribute using given name.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          name (str): name of the parameter. The parameter can be accessed\n",
+      " |              from this module using the given name\n",
+      " |          param (Parameter or None): parameter to be added to the module. If\n",
+      " |              ``None``, then operations that run on parameters, such as :attr:`cuda`,\n",
+      " |              are ignored. If ``None``, the parameter is **not** included in the\n",
+      " |              module's :attr:`state_dict`.\n",
+      " |  \n",
+      " |  register_state_dict_post_hook(self, hook)\n",
+      " |      Register a post-hook for the :meth:`~torch.nn.Module.state_dict` method.\n",
+      " |      \n",
+      " |      It should have the following signature::\n",
+      " |          hook(module, state_dict, prefix, local_metadata) -> None\n",
+      " |      \n",
+      " |      The registered hooks can modify the ``state_dict`` inplace.\n",
+      " |  \n",
+      " |  register_state_dict_pre_hook(self, hook)\n",
+      " |      Register a pre-hook for the :meth:`~torch.nn.Module.state_dict` method.\n",
+      " |      \n",
+      " |      It should have the following signature::\n",
+      " |          hook(module, prefix, keep_vars) -> None\n",
+      " |      \n",
+      " |      The registered hooks can be used to perform pre-processing before the ``state_dict``\n",
+      " |      call is made.\n",
+      " |  \n",
+      " |  requires_grad_(self, requires_grad: bool = True) -> Self\n",
+      " |      Change if autograd should record operations on parameters in this module.\n",
+      " |      \n",
+      " |      This method sets the parameters' :attr:`requires_grad` attributes\n",
+      " |      in-place.\n",
+      " |      \n",
+      " |      This method is helpful for freezing part of the module for finetuning\n",
+      " |      or training parts of a model individually (e.g., GAN training).\n",
+      " |      \n",
+      " |      See :ref:`locally-disable-grad-doc` for a comparison between\n",
+      " |      `.requires_grad_()` and several similar mechanisms that may be confused with it.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          requires_grad (bool): whether autograd should record operations on\n",
+      " |                                parameters in this module. Default: ``True``.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  set_extra_state(self, state: Any) -> None\n",
+      " |      Set extra state contained in the loaded `state_dict`.\n",
+      " |      \n",
+      " |      This function is called from :func:`load_state_dict` to handle any extra state\n",
+      " |      found within the `state_dict`. Implement this function and a corresponding\n",
+      " |      :func:`get_extra_state` for your module if you need to store extra state within its\n",
+      " |      `state_dict`.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          state (dict): Extra state from the `state_dict`\n",
+      " |  \n",
+      " |  set_submodule(self, target: str, module: 'Module', strict: bool = False) -> None\n",
+      " |      Set the submodule given by ``target`` if it exists, otherwise throw an error.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          If ``strict`` is set to ``False`` (default), the method will replace an existing submodule\n",
+      " |          or create a new submodule if the parent module exists. If ``strict`` is set to ``True``,\n",
+      " |          the method will only attempt to replace an existing submodule and throw an error if\n",
+      " |          the submodule does not exist.\n",
+      " |      \n",
+      " |      For example, let's say you have an ``nn.Module`` ``A`` that\n",
+      " |      looks like this:\n",
+      " |      \n",
+      " |      .. code-block:: text\n",
+      " |      \n",
+      " |          A(\n",
+      " |              (net_b): Module(\n",
+      " |                  (net_c): Module(\n",
+      " |                      (conv): Conv2d(3, 3, 3)\n",
+      " |                  )\n",
+      " |                  (linear): Linear(3, 3)\n",
+      " |              )\n",
+      " |          )\n",
+      " |      \n",
+      " |      (The diagram shows an ``nn.Module`` ``A``. ``A`` has a nested\n",
+      " |      submodule ``net_b``, which itself has two submodules ``net_c``\n",
+      " |      and ``linear``. ``net_c`` then has a submodule ``conv``.)\n",
+      " |      \n",
+      " |      To override the ``Conv2d`` with a new submodule ``Linear``, you\n",
+      " |      could call ``set_submodule(\"net_b.net_c.conv\", nn.Linear(1, 1))``\n",
+      " |      where ``strict`` could be ``True`` or ``False``\n",
+      " |      \n",
+      " |      To add a new submodule ``Conv2d`` to the existing ``net_b`` module,\n",
+      " |      you would call ``set_submodule(\"net_b.conv\", nn.Conv2d(1, 1, 1))``.\n",
+      " |      \n",
+      " |      In the above if you set ``strict=True`` and call\n",
+      " |      ``set_submodule(\"net_b.conv\", nn.Conv2d(1, 1, 1), strict=True)``, an AttributeError\n",
+      " |      will be raised because ``net_b`` does not have a submodule named ``conv``.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          target: The fully-qualified string name of the submodule\n",
+      " |              to look for. (See above example for how to specify a\n",
+      " |              fully-qualified string.)\n",
+      " |          module: The module to set the submodule to.\n",
+      " |          strict: If ``False``, the method will replace an existing submodule\n",
+      " |              or create a new submodule if the parent module exists. If ``True``,\n",
+      " |              the method will only attempt to replace an existing submodule and throw an error\n",
+      " |              if the submodule doesn't already exist.\n",
+      " |      \n",
+      " |      Raises:\n",
+      " |          ValueError: If the ``target`` string is empty or if ``module`` is not an instance of ``nn.Module``.\n",
+      " |          AttributeError: If at any point along the path resulting from\n",
+      " |              the ``target`` string the (sub)path resolves to a non-existent\n",
+      " |              attribute name or an object that is not an instance of ``nn.Module``.\n",
+      " |  \n",
+      " |  share_memory(self) -> Self\n",
+      " |      See :meth:`torch.Tensor.share_memory_`.\n",
+      " |  \n",
+      " |  state_dict(self, *args, destination=None, prefix='', keep_vars=False)\n",
+      " |      Return a dictionary containing references to the whole state of the module.\n",
+      " |      \n",
+      " |      Both parameters and persistent buffers (e.g. running averages) are\n",
+      " |      included. Keys are corresponding parameter and buffer names.\n",
+      " |      Parameters and buffers set to ``None`` are not included.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          The returned object is a shallow copy. It contains references\n",
+      " |          to the module's parameters and buffers.\n",
+      " |      \n",
+      " |      .. warning::\n",
+      " |          Currently ``state_dict()`` also accepts positional arguments for\n",
+      " |          ``destination``, ``prefix`` and ``keep_vars`` in order. However,\n",
+      " |          this is being deprecated and keyword arguments will be enforced in\n",
+      " |          future releases.\n",
+      " |      \n",
+      " |      .. warning::\n",
+      " |          Please avoid the use of argument ``destination`` as it is not\n",
+      " |          designed for end-users.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          destination (dict, optional): If provided, the state of module will\n",
+      " |              be updated into the dict and the same object is returned.\n",
+      " |              Otherwise, an ``OrderedDict`` will be created and returned.\n",
+      " |              Default: ``None``.\n",
+      " |          prefix (str, optional): a prefix added to parameter and buffer\n",
+      " |              names to compose the keys in state_dict. Default: ``''``.\n",
+      " |          keep_vars (bool, optional): by default the :class:`~torch.Tensor` s\n",
+      " |              returned in the state dict are detached from autograd. If it's\n",
+      " |              set to ``True``, detaching will not be performed.\n",
+      " |              Default: ``False``.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          dict:\n",
+      " |              a dictionary containing a whole state of the module\n",
+      " |      \n",
+      " |      Example::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +SKIP(\"undefined vars\")\n",
+      " |          >>> module.state_dict().keys()\n",
+      " |          ['bias', 'weight']\n",
+      " |  \n",
+      " |  to(self, *args, **kwargs)\n",
+      " |      Move and/or cast the parameters and buffers.\n",
+      " |      \n",
+      " |      This can be called as\n",
+      " |      \n",
+      " |      .. function:: to(device=None, dtype=None, non_blocking=False)\n",
+      " |         :noindex:\n",
+      " |      \n",
+      " |      .. function:: to(dtype, non_blocking=False)\n",
+      " |         :noindex:\n",
+      " |      \n",
+      " |      .. function:: to(tensor, non_blocking=False)\n",
+      " |         :noindex:\n",
+      " |      \n",
+      " |      .. function:: to(memory_format=torch.channels_last)\n",
+      " |         :noindex:\n",
+      " |      \n",
+      " |      Its signature is similar to :meth:`torch.Tensor.to`, but only accepts\n",
+      " |      floating point or complex :attr:`dtype`\\ s. In addition, this method will\n",
+      " |      only cast the floating point or complex parameters and buffers to :attr:`dtype`\n",
+      " |      (if given). The integral parameters and buffers will be moved\n",
+      " |      :attr:`device`, if that is given, but with dtypes unchanged. When\n",
+      " |      :attr:`non_blocking` is set, it tries to convert/move asynchronously\n",
+      " |      with respect to the host if possible, e.g., moving CPU Tensors with\n",
+      " |      pinned memory to CUDA devices.\n",
+      " |      \n",
+      " |      See below for examples.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          device (:class:`torch.device`): the desired device of the parameters\n",
+      " |              and buffers in this module\n",
+      " |          dtype (:class:`torch.dtype`): the desired floating point or complex dtype of\n",
+      " |              the parameters and buffers in this module\n",
+      " |          tensor (torch.Tensor): Tensor whose dtype and device are the desired\n",
+      " |              dtype and device for all parameters and buffers in this module\n",
+      " |          memory_format (:class:`torch.memory_format`): the desired memory\n",
+      " |              format for 4D parameters and buffers in this module (keyword\n",
+      " |              only argument)\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |      \n",
+      " |      Examples::\n",
+      " |      \n",
+      " |          >>> # xdoctest: +IGNORE_WANT(\"non-deterministic\")\n",
+      " |          >>> linear = nn.Linear(2, 2)\n",
+      " |          >>> linear.weight\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[ 0.1913, -0.3420],\n",
+      " |                  [-0.5113, -0.2325]])\n",
+      " |          >>> linear.to(torch.double)\n",
+      " |          Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          >>> linear.weight\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[ 0.1913, -0.3420],\n",
+      " |                  [-0.5113, -0.2325]], dtype=torch.float64)\n",
+      " |          >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA1)\n",
+      " |          >>> gpu1 = torch.device(\"cuda:1\")\n",
+      " |          >>> linear.to(gpu1, dtype=torch.half, non_blocking=True)\n",
+      " |          Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          >>> linear.weight\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[ 0.1914, -0.3420],\n",
+      " |                  [-0.5112, -0.2324]], dtype=torch.float16, device='cuda:1')\n",
+      " |          >>> cpu = torch.device(\"cpu\")\n",
+      " |          >>> linear.to(cpu)\n",
+      " |          Linear(in_features=2, out_features=2, bias=True)\n",
+      " |          >>> linear.weight\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[ 0.1914, -0.3420],\n",
+      " |                  [-0.5112, -0.2324]], dtype=torch.float16)\n",
+      " |      \n",
+      " |          >>> linear = nn.Linear(2, 2, bias=None).to(torch.cdouble)\n",
+      " |          >>> linear.weight\n",
+      " |          Parameter containing:\n",
+      " |          tensor([[ 0.3741+0.j,  0.2382+0.j],\n",
+      " |                  [ 0.5593+0.j, -0.4443+0.j]], dtype=torch.complex128)\n",
+      " |          >>> linear(torch.ones(3, 2, dtype=torch.cdouble))\n",
+      " |          tensor([[0.6122+0.j, 0.1150+0.j],\n",
+      " |                  [0.6122+0.j, 0.1150+0.j],\n",
+      " |                  [0.6122+0.j, 0.1150+0.j]], dtype=torch.complex128)\n",
+      " |  \n",
+      " |  to_empty(self, *, device: Union[int, str, torch.device, NoneType], recurse: bool = True) -> Self\n",
+      " |      Move the parameters and buffers to the specified device without copying storage.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          device (:class:`torch.device`): The desired device of the parameters\n",
+      " |              and buffers in this module.\n",
+      " |          recurse (bool): Whether parameters and buffers of submodules should\n",
+      " |              be recursively moved to the specified device.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  train(self, mode: bool = True) -> Self\n",
+      " |      Set the module in training mode.\n",
+      " |      \n",
+      " |      This has an effect only on certain modules. See the documentation of\n",
+      " |      particular modules for details of their behaviors in training/evaluation\n",
+      " |      mode, i.e., whether they are affected, e.g. :class:`Dropout`, :class:`BatchNorm`,\n",
+      " |      etc.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          mode (bool): whether to set training mode (``True``) or evaluation\n",
+      " |                       mode (``False``). Default: ``True``.\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  type(self, dst_type: Union[torch.dtype, str]) -> Self\n",
+      " |      Casts all parameters and buffers to :attr:`dst_type`.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          dst_type (type or string): the desired type\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  xpu(self, device: Union[torch.device, int, NoneType] = None) -> Self\n",
+      " |      Move all model parameters and buffers to the XPU.\n",
+      " |      \n",
+      " |      This also makes associated parameters and buffers different objects. So\n",
+      " |      it should be called before constructing optimizer if the module will\n",
+      " |      live on XPU while being optimized.\n",
+      " |      \n",
+      " |      .. note::\n",
+      " |          This method modifies the module in-place.\n",
+      " |      \n",
+      " |      Arguments:\n",
+      " |          device (int, optional): if specified, all parameters will be\n",
+      " |              copied to that device\n",
+      " |      \n",
+      " |      Returns:\n",
+      " |          Module: self\n",
+      " |  \n",
+      " |  zero_grad(self, set_to_none: bool = True) -> None\n",
+      " |      Reset gradients of all model parameters.\n",
+      " |      \n",
+      " |      See similar function under :class:`torch.optim.Optimizer` for more context.\n",
+      " |      \n",
+      " |      Args:\n",
+      " |          set_to_none (bool): instead of setting to zero, set the grads to None.\n",
+      " |              See :meth:`torch.optim.Optimizer.zero_grad` for details.\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data descriptors inherited from torch.nn.modules.module.Module:\n",
+      " |  \n",
+      " |  __dict__\n",
+      " |      dictionary for instance variables (if defined)\n",
+      " |  \n",
+      " |  __weakref__\n",
+      " |      list of weak references to the object (if defined)\n",
+      " |  \n",
+      " |  ----------------------------------------------------------------------\n",
+      " |  Data and other attributes inherited from torch.nn.modules.module.Module:\n",
+      " |  \n",
+      " |  T_destination = ~T_destination\n",
+      " |  \n",
+      " |  call_super_init = False\n",
+      " |  \n",
+      " |  dump_patches = False\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(metaABaCo)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a6f00887",
+   "metadata": {},
+   "source": [
+    "### Training the ABaCo model\n",
+    "\n",
+    "To train ABaCo on the prepared dataset, we then use method `abaco.metaABaCo.correct()`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e5c0aec5",
+   "metadata": {
+    "tags": [
+     "hide-output"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Training: VAE for learning meaningful embeddings: 100%|██████████| 1000/1000 [00:13<00:00, 75.99it/s, bio_penalty=0.0000, clustering_loss=100000000.0000, elbo=45.3159, epoch=999/1001, vae_loss=100000048.0000]\n",
+      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:33<00:00, 58.92it/s, adv_loss=-0.5996, bio_penalty=0.0000, clustering_loss=100000000.0000, disc_loss=0.5996, elbo=44.3152, epoch=1999/2001, vae_loss=100000048.0000]\n",
+      "Training: VAE decoder with masked batch labels: 100%|██████████| 2000/2000 [00:19<00:00, 102.63it/s, cycle_loss=0.0000, epoch=2000/2000, vae_loss=81.0403] \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Train the model\n",
+    "model.fit(seed=42)#, w_bio_penalty=0, w_cluster_penalty=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "58848ce7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model.plot_pca_posterior()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18852212",
+   "metadata": {},
+   "source": [
+    "### Reconstructing the dataset with ABaCO\n",
+    "\n",
+    "To reconstruct the dataset we use method `abaco.metaABaCo.reconstruct()` and save it as a new layer `abaco` in the annotated dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "2c9dbf2a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Reconstruct the dataset using the trained ABaCo model\n",
+    "corrected_dataset = model.correct(seed=42)\n",
+    "# save back to adata\n",
+    "adata.layers['abaco'] = corrected_dataset.set_index(id_col).drop(columns=[batch_col, bio_col]).values\n",
+    "adata.write_h5ad(\"data/mgnify_tomato.h5ad\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0d6c9c1",
+   "metadata": {},
+   "source": [
+    "## Viewing the ABaCo reconstructed dataset\n",
+    "\n",
+    "Here we again create PCoA and look at sample alpha diversities via pairplots but on the batch corrected data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "0399387d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>index</th>\n",
+       "      <th>source</th>\n",
+       "      <th>bio</th>\n",
+       "      <th>5</th>\n",
+       "      <th>10</th>\n",
+       "      <th>11</th>\n",
+       "      <th>12</th>\n",
+       "      <th>20</th>\n",
+       "      <th>21</th>\n",
+       "      <th>23</th>\n",
+       "      <th>...</th>\n",
+       "      <th>489</th>\n",
+       "      <th>497</th>\n",
+       "      <th>502</th>\n",
+       "      <th>504</th>\n",
+       "      <th>514</th>\n",
+       "      <th>515</th>\n",
+       "      <th>516</th>\n",
+       "      <th>518</th>\n",
+       "      <th>519</th>\n",
+       "      <th>527</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ERZ12633510</td>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ERZ12633501</td>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ERZ12633502</td>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ERZ12633503</td>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>ERZ12633504</td>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 223 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         index        source     bio    5   10   11   12   20   21   23  ...  \\\n",
+       "0  ERZ12633510  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
+       "1  ERZ12633501  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
+       "2  ERZ12633502  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
+       "3  ERZ12633503  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
+       "4  ERZ12633504  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
+       "\n",
+       "   489  497  502  504  514  515  516  518  519  527  \n",
+       "0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "2  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "3  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "4  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "\n",
+       "[5 rows x 223 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corrected_dataset.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a23a2c21",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/anglup/GitHub/abaco/.venv/lib/python3.11/site-packages/skbio/stats/ordination/_principal_coordinate_analysis.py:157: RuntimeWarning:\n",
+      "\n",
+      "EIGH: since no value for dimensions is specified, PCoA for all dimensions will be computed, which may result in long computation time if the original distance matrix is large.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot the PCoA of the reconstructed dataset\n",
+    "plotPCoA(\n",
+    "    data = corrected_dataset, \n",
+    "    sample_label=id_col, \n",
+    "    batch_label=batch_col, \n",
+    "    experiment_label=bio_col\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e761983",
+   "metadata": {},
+   "source": [
+    "In the PCoA we see that there is more overlap of the batches based on the blue and red points being more mixed. \n",
+    "\n",
+    "We can also take a look at the alpha diversity metrics:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "be1b2c3c",
+   "metadata": {
+    "tags": [
+     "hide-input"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2384117532.py:14: RuntimeWarning:\n",
+      "\n",
+      "divide by zero encountered in divide\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[None]"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1181.25x1080 with 27 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1239.38x1080 with 27 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "## PREPROCESSING THE ABaCo DATA\n",
+    "# normalize abaco corrected data\n",
+    "adata.layers['normalized_abaco'] = (adata.layers['abaco']/adata.layers['abaco'].sum(axis=1).reshape(-1,1))\n",
+    "# CLR transform normalized ABaCo data\n",
+    "adata.layers['clr_abaco'] = clr(np.where(adata.layers['normalized_abaco'] > 0, adata.layers['normalized_abaco'], 1e-10))\n",
+    "\n",
+    "## Alpha diversity metrics on ABaCo corrected data\n",
+    "# Diversity: Number of unique taxa per sample as new metadata\n",
+    "adata.obs['abaco_numtaxa'] = (adata.layers['abaco'] > 0).sum(axis=1) \n",
+    "# Diversity with correction: Chao1 estimator\n",
+    "# Chao1 = num observed taxa + (num singletons / (2 x num doubletons))\n",
+    "num_singletons = (adata.layers['abaco'] == 1).sum(axis=1)\n",
+    "num_doubletons = (adata.layers['abaco'] == 2).sum(axis=1)\n",
+    "adata.obs['abaco_chao1'] = (adata.layers['abaco'] > 0).sum(axis=1) + (num_singletons / (2 * num_doubletons))\n",
+    "# Diversity: Shannon index H = -sum(p_i * log(p_i)), entropy\n",
+    "adata.obs['abaco_shannon'] = entropy(adata.layers['normalized_abaco'], nan_policy='omit', axis=1)\n",
+    "# Evenness: Pielou evenness index P = H/H_max, H_max = ln(num species)\n",
+    "adata.obs['abaco_pielou'] = adata.obs['abaco_shannon'] / np.log(adata.obs['abaco_numtaxa'])\n",
+    "# Diversity: simpson index lambda = sum(p_i ^2)\n",
+    "adata.obs['abaco_simpson'] = (adata.layers['normalized_abaco'] ** 2).sum(axis=1)\n",
+    "# Diversity: inverse simpson index D = 1/lambda\n",
+    "adata.obs['abaco_inv_simpson'] = 1 / adata.obs['abaco_simpson']\n",
+    "\n",
+    "## PAIRPLOTS OF ALPHA DIVERSITY METRICS\n",
+    "# prep df for vis\n",
+    "df_abaco_alphas = adata.obs[[\n",
+    "    'abaco_numtaxa', 'abaco_chao1', 'abaco_shannon', \n",
+    "    'abaco_pielou', 'abaco_simpson', 'abaco_inv_simpson',\n",
+    "    batch_col, bio_col\n",
+    "]].copy()\n",
+    "# plotting by bio groups\n",
+    "g1 = sns.pairplot(df_abaco_alphas, hue=bio_col, corner=True, height=1.8)\n",
+    "g1.figure.suptitle('ABaCo: Alpha Diversity by Biological Groups', fontsize=22)\n",
+    "plt.setp(g1._legend.get_texts(), fontsize=18)\n",
+    "plt.setp(g1._legend.get_title(), fontsize=20)\n",
+    "g2 = sns.pairplot(df_abaco_alphas, hue=batch_col, corner=True, height=1.8)\n",
+    "g2.figure.suptitle('ABaCo: Alpha Diversity by Batch Groups', fontsize=22)\n",
+    "plt.setp(g2._legend.get_texts(), fontsize=18)\n",
+    "plt.setp(g2._legend.get_title(), fontsize=20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b433f7df",
+   "metadata": {},
+   "source": [
+    "### Conclusion\n",
+    "\n",
+    "The goal was to: \n",
+    "\n",
+    "&#x2705; correct the batch effect (reduce clustering of points by colour in the PCoA and pairplot coloured by batches)\n",
+    "\n",
+    "&#x2705; maintain biological variance (maintain pattern of shapes in PCoA and maintain pairplot coloured by wwtp location)\n",
+    "\n",
+    "A brief visual inspection of the PCoA and alpha diversity of the reconstructed data suggests that ABaCo reduced the batch effect associated with analyzing the samples on different dates, while still retaining any variance due to the condition of wwtp location.\n",
+    "\n",
+    "\n",
+    "---"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 9fa301f6ee4c3208f1a82c9336a095a9d11177d5 Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Fri, 19 Dec 2025 17:36:47 +0100
Subject: [PATCH 2/9] :construction: tried add miseq but maybe incomplete
 analysis?

---
 docs/tutorial/demo-mgnify-ww-biomes.ipynb | 1767 +++++++++------------
 1 file changed, 760 insertions(+), 1007 deletions(-)

diff --git a/docs/tutorial/demo-mgnify-ww-biomes.ipynb b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
index 5f8cd61..80b66ab 100644
--- a/docs/tutorial/demo-mgnify-ww-biomes.ipynb
+++ b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
@@ -5,7 +5,7 @@
    "id": "ad5a71b5",
    "metadata": {},
    "source": [
-    "# `ABaCo` demo: No biological labels e.g., Mgnify tomoatos"
+    "# `ABaCo` demo: No biological labels w/ Mgnify tomoatos"
    ]
   },
   {
@@ -13,30 +13,42 @@
    "id": "bcc12d4b",
    "metadata": {},
    "source": [
-    "In this demo we will implement ABaCo for batch correction on Mgnify study [MGYS00001135](https://www.ebi.ac.uk/metagenomics/studies/MGYS00001135#overview) and ENA Bioproject [PRJEB13832](https://www.ebi.ac.uk/ena/browser/view/PRJEB13832), a proof-of-concept study for surveilling infections diseases and AMR via metagenomics analysis of local sewage samples in Copenhagen.\n",
+    "In this tutorial we demonstrate how ABaCo can be used: \n",
+    "- without known biological group labels (e.g., only correct batch effect)\n",
+    "- and for integrating samples from multiple studies.\n",
     "\n",
-    "-----\n",
-    "**Data Description:**\n",
-    "- The metagenomics dataset collected by the Technical University of Denmark (DTU) and analysed via Mgnify [pipeline version 2.0](https://www.ebi.ac.uk/metagenomics/pipelines/2.0) is a dataset composed of 54 samples with 749 identified taxa at the genus level. \n",
-    "- The samples were collected from 3 different wastewater treatment plant (WWTP) locations, accounting for the biological source of variation. \n",
-    "- Samples were analyzed on 2 different dates accounting for the technical source of variation (i.e., batch effect).\n",
-    "- The sample data and metadata were retrieved from the [Mgnify API](https://docs.mgnify.org/src/docs/api.html) using the following [mgnifyapi repo](https://github.com/Multiomics-Analytics-Group/Retrieve_info_MGnifyAPI/tree/angel-learning) and stored as an Annotated Dataset [AnnData](https://anndata.readthedocs.io/en/latest/index.html). \n",
+    "Specifically, we integrate tomato rhizosphere metagenomics analyses available on MGniFy. \n",
+    "- MGYS00006231, Illumina HiSeq 4000\n",
+    "- MGYS00006204, Illumina HiSeq 2500\n",
+    "- MGYS00006205, Illumina HiSeq 2500\n",
+    "- MGYS00006018, Illumina MiSeq\n",
     "\n",
+    "-----\n",
     "**Goal:**\n",
     "\n",
-    "With ABaCo the aim is to remove the technical variation (batch effect) while maintaining any biological variation (wastewater treatment plant location). \n",
+    "With ABaCo the aim is to remove the technical variation between sequencing platforms. \n",
     "\n",
     "-----\n",
     "\n",
-    "To start we read in the annotated dataset. "
+    "To start we retrieve the data from MGniFy. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 651,
    "id": "f94eae83",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(189, 12)\n",
+      "(446, 114)\n",
+      "(188, 12)\n",
+      "(2588, 210)\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -58,73 +70,83 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>ERZ12633490</th>\n",
+       "      <th>ERZ12633491</th>\n",
+       "      <th>ERZ12633492</th>\n",
+       "      <th>ERZ12633493</th>\n",
+       "      <th>ERZ12633494</th>\n",
+       "      <th>ERZ12633495</th>\n",
+       "      <th>ERZ12633496</th>\n",
+       "      <th>ERZ12633497</th>\n",
+       "      <th>ERZ12633488</th>\n",
+       "      <th>ERZ12633498</th>\n",
+       "      <th>ERZ12633489</th>\n",
+       "      <th>ERZ12633499</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>taxa</th>\n",
-       "      <th>ERZ12633510</th>\n",
-       "      <th>ERZ12633501</th>\n",
-       "      <th>ERZ12633502</th>\n",
-       "      <th>ERZ12633503</th>\n",
-       "      <th>ERZ12633504</th>\n",
-       "      <th>ERZ12633505</th>\n",
-       "      <th>ERZ12633506</th>\n",
-       "      <th>ERZ12633507</th>\n",
-       "      <th>ERZ12633517</th>\n",
-       "      <th>ERZ12633508</th>\n",
-       "      <th>ERZ12633518</th>\n",
-       "      <th>ERZ12633509</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>sk__Archaea</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>3</td>\n",
+       "      <th>sk__Archaea</th>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>2</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>3</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>sk__Archaea;k__;p__Euryarchaeota;c__Methanococ...</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Archaea;k__;p__Euryarchaeota;c__Halobacteria;o__Halobacteriales</th>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>sk__Archaea;k__;p__Euryarchaeota;c__Methanomic...</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Archaea;k__;p__Euryarchaeota;c__Methanomicrobia;o__Methanosarcinales;f__Methanosarcinaceae;g__Methanosarcina</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>sk__Archaea;k__;p__Euryarchaeota;c__Thermoplas...</td>\n",
+       "      <th>sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
@@ -136,19 +158,18 @@
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>sk__Archaea;k__;p__Thaumarchaeota;c__Nitrososp...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Archaea;k__;p__Thaumarchaeota</th>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -159,36 +180,56 @@
        "</div>"
       ],
       "text/plain": [
-       "                                                taxa  ERZ12633510  \\\n",
-       "0                                        sk__Archaea            3   \n",
-       "1  sk__Archaea;k__;p__Euryarchaeota;c__Methanococ...            0   \n",
-       "2  sk__Archaea;k__;p__Euryarchaeota;c__Methanomic...            0   \n",
-       "3  sk__Archaea;k__;p__Euryarchaeota;c__Thermoplas...            0   \n",
-       "4  sk__Archaea;k__;p__Thaumarchaeota;c__Nitrososp...            1   \n",
-       "\n",
-       "   ERZ12633501  ERZ12633502  ERZ12633503  ERZ12633504  ERZ12633505  \\\n",
-       "0            0            2            3            0            1   \n",
-       "1            0            1            0            0            0   \n",
-       "2            0            0            0            0            0   \n",
-       "3            0            1            0            0            0   \n",
-       "4            0            0            0            0            0   \n",
-       "\n",
-       "   ERZ12633506  ERZ12633507  ERZ12633517  ERZ12633508  ERZ12633518  \\\n",
-       "0            2            0            0            3            0   \n",
-       "1            0            0            0            0            0   \n",
-       "2            1            0            0            0            0   \n",
-       "3            0            0            0            0            0   \n",
-       "4            0            0            0            0            0   \n",
-       "\n",
-       "   ERZ12633509  \n",
-       "0            1  \n",
-       "1            0  \n",
-       "2            0  \n",
-       "3            1  \n",
-       "4            0  "
+       "                                                    ERZ12633490  ERZ12633491  \\\n",
+       "taxa                                                                           \n",
+       "sk__Archaea                                                   0            1   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            1            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            1   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            1   \n",
+       "\n",
+       "                                                    ERZ12633492  ERZ12633493  \\\n",
+       "taxa                                                                           \n",
+       "sk__Archaea                                                   0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            1            0   \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "\n",
+       "                                                    ERZ12633494  ERZ12633495  \\\n",
+       "taxa                                                                           \n",
+       "sk__Archaea                                                   0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "\n",
+       "                                                    ERZ12633496  ERZ12633497  \\\n",
+       "taxa                                                                           \n",
+       "sk__Archaea                                                   0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            0            1   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            1   \n",
+       "\n",
+       "                                                    ERZ12633488  ERZ12633498  \\\n",
+       "taxa                                                                           \n",
+       "sk__Archaea                                                   1            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            1   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0   \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "\n",
+       "                                                    ERZ12633489  ERZ12633499  \n",
+       "taxa                                                                          \n",
+       "sk__Archaea                                                   0            0  \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0  \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0  \n",
+       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0  \n",
+       "sk__Archaea;k__;p__Thaumarchaeota                             0            0  "
       ]
      },
-     "execution_count": 1,
+     "execution_count": 651,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -202,7 +243,8 @@
     "datasets = {\n",
     "    \"MGYS00006205\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006205/pipelines/5.0/file/ERP140107_taxonomy_abundances_SSU_v5.0.tsv\",\n",
     "    \"MGYS00006231\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006231/pipelines/5.0/file/ERP139927_taxonomy_abundances_SSU_v5.0.tsv\",\n",
-    "    \"MGYS00006204\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006204/pipelines/5.0/file/ERP140102_taxonomy_abundances_SSU_v5.0.tsv\"\n",
+    "    \"MGYS00006204\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006204/pipelines/5.0/file/ERP140102_taxonomy_abundances_SSU_v5.0.tsv\",\n",
+    "    \"MGYS00006018\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006018/pipelines/5.0/file/SRP109260_taxonomy_abundances_SSU_v5.0.tsv\"\n",
     "}\n",
     "\n",
     "dfs = {}\n",
@@ -217,38 +259,169 @@
     "    #dfs[url]['source'] = url\n",
     "    # rename sampleid col to taxa\n",
     "    dfs[key] = dfs[key].rename(columns={\"#SampleID\": \"taxa\"})\n",
+    "    dfs[key] = dfs[key].set_index('taxa')\n",
+    "    # drop rows with all zeros\n",
+    "    dfs[key] = dfs[key][dfs[key].sum(axis=1)>0]\n",
+    "    print(dfs[key].shape)\n",
     "# sanity check\n",
-    "dfs[\"MGYS00006205\"].head()"
+    "dfs[\"MGYS00006204\"].head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "61f54861",
+   "execution_count": 656,
+   "id": "f428c58f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(103676)"
+      ]
+     },
+     "execution_count": 656,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dfs['MGYS00006018'].sum()['SRR5685058']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 616,
+   "id": "cc9c3646",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "Index: 531 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
-      "Columns: 138 entries, ERZ12633510 to ERZ12633499\n",
-      "dtypes: float64(138)\n",
-      "memory usage: 576.6+ KB\n"
+      "(218, 28)\n",
+      "(69, 2)\n",
+      "(69, 11)\n",
+      "(2588, 67)\n",
+      "(2588, 23)\n",
+      "(1958, 23)\n",
+      "(1958, 23)\n"
      ]
     }
    ],
    "source": [
-    "# join datasets on taxa col\n",
-    "inter_joined = dfs[\"MGYS00006205\"].merge(\n",
-    "    dfs[\"MGYS00006231\"], on='taxa', how='outer',\n",
+    "# tidy up MGYS00006018\n",
+    "\n",
+    "# read in mg metadata\n",
+    "mg_meta = pd.read_csv(\n",
+    "    \"data/analysisjob.csv\"\n",
+    ")\n",
+    "print(mg_meta.shape)\n",
+    "\n",
+    "# getting ids from urls\n",
+    "mg_meta['run_id'] = mg_meta['run'].str.extract(r'\\/runs\\/(S[A-Z0-9]*)\\?format=csv')\n",
+    "mg_meta['sample_id'] = mg_meta['sample'].str.extract(r'\\/samples\\/(S[A-Z0-9]*)\\?format=csv')\n",
+    "\n",
+    "# for each sample keep run with highest reads\n",
+    "keep_ids = mg_meta.groupby('sample_id')[\n",
+    "    'analysis_summary.4.value'\n",
+    "    ].idxmax().to_list()\n",
+    "\n",
+    "mg_meta = mg_meta.loc[\n",
+    "    mg_meta.index.isin(keep_ids), \n",
+    "    ['run_id', 'sample_id', ]\n",
+    "].copy()\n",
+    "print(mg_meta.shape)\n",
+    "\n",
+    "# read in metadata\n",
+    "ena_meta = pd.read_csv(\n",
+    "    \"data/filereport_read_run_SRP109260.tsv\",\n",
+    "    sep=\"\\t\",\n",
     ")\n",
-    "joined = inter_joined.merge(\n",
-    "    dfs[\"MGYS00006204\"], on='taxa', how='outer',\n",
+    "# only rhizosphere samples\n",
+    "rhiz = ena_meta.query(\n",
+    "    \"sample_alias.str.lower().str.contains('rhizosphere')\"\n",
     ")\n",
-    "# put taxa in index\n",
-    "joined = joined.set_index('taxa')\n",
+    "print(rhiz.shape)\n",
+    "\n",
+    "# filtering columns (samples) to rhizosphere samples only\n",
+    "rhizo = dfs[\"MGYS00006018\"].loc[\n",
+    "    :, \n",
+    "    dfs[\"MGYS00006018\"].columns.isin(\n",
+    "        rhiz['run_accession'].to_list() #+ ['taxa']\n",
+    "    )\n",
+    "]\n",
+    "print(rhizo.shape)\n",
+    "\n",
+    "# also only keeping run with highest reads per sample\n",
+    "rhizo = rhizo.loc[:, rhizo.columns.isin(\n",
+    "    mg_meta['run_id'].to_list()\n",
+    ")].copy()\n",
+    "print(rhizo.shape)\n",
+    "\n",
+    "# drop rows with all zeros\n",
+    "rhizo = rhizo[rhizo.sum(axis=1)>0]\n",
+    "print(rhizo.shape)\n",
+    "# replace in dfs \n",
+    "dfs[\"MGYS00006018\"] = rhizo\n",
+    "print(dfs[\"MGYS00006018\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 617,
+   "id": "c6d2108b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 446 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
+      "Columns: 161 entries, ERZ12633510 to SRR5685149\n",
+      "dtypes: float64(161)\n",
+      "memory usage: 564.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "def df_joiner(\n",
+    "    df_dict: dict[pd.DataFrame],\n",
+    "    on: str = \"taxa\",\n",
+    "    how: str = \"outer\",\n",
+    ")->pd.DataFrame:\n",
+    "    \n",
+    "    \"\"\"\n",
+    "    Join multiple dataframes on a common column.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    df_dict : dict of pandas.DataFrame\n",
+    "        Dictionary of dataframes to join.\n",
+    "    on : str, optional\n",
+    "        Column to join on. Defaults to \"taxa\".\n",
+    "    how : str, optional\n",
+    "        Type of join. Defaults to \"outer\".\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    pandas.DataFrame\n",
+    "        Joined dataframe.\n",
+    "    \"\"\"\n",
+    "    # dfs into a list\n",
+    "    df_list = list(df_dict.values())\n",
+    "    # init the merged df with the first one\n",
+    "    df_merged = df_list[0]\n",
+    "    # for all others, merge iteratively\n",
+    "    for df in df_list[1:]:\n",
+    "        df_merged = pd.merge(df_merged, df, on=on, how=how)\n",
+    "    return df_merged\n",
+    "\n",
+    "joined = df_joiner(dfs)#.set_index('taxa')\n",
+    "\n",
+    "# filtering if taxa is missing in more than 30% of samples\n",
+    "joined = joined[(joined.isna().sum(axis=1) / joined.shape[1] <= 0.3)].copy()\n",
+    "#joined = joined.dropna(axis=0)\n",
     "\n",
     "joined.info()"
    ]
@@ -263,10 +436,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 618,
    "id": "b6303749",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(161, 2)\n",
+      "(446, 8)\n"
+     ]
+    }
+   ],
    "source": [
     "# preparing obs metadata\n",
     "dfs_T = {}\n",
@@ -274,39 +456,70 @@
     "    # transpose\n",
     "    dfs_T[key] = dfs[key].T\n",
     "    # drop taxa row\n",
-    "    dfs_T[key] = dfs_T[key].drop('taxa')\n",
+    "    #dfs_T[key] = dfs_T[key].drop('taxa')\n",
     "    # add source column\n",
     "    dfs_T[key]['source'] = key\n",
     "    # dummy bio column\n",
-    "    dfs_T[key]['bio'] = np.random.choice([\"Group1\"], size = len(dfs_T[key]))\n",
+    "    dfs_T[key]['bio'] = np.random.choice([\"Group1\",\"Group2\"], size = len(dfs_T[key]))\n",
     "    # drop allother cols\n",
     "    dfs_T[key] = dfs_T[key][['source', 'bio']]\n",
     "\n",
     "obsm = pd.concat(dfs_T.values())\n",
+    "print(obsm.shape)\n",
     "\n",
     "varm = joined.reset_index()[['taxa']]\n",
     "varm = varm['taxa'].str.split(';', expand=True)\n",
     "varm.columns = [\n",
     "    \"superkingdom\", \"kingdom\",\"phylum\", \"class\", \n",
     "    \"order\", \"family\", \"genus\", \"species\"\n",
-    "]"
+    "]\n",
+    "print(varm.shape)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 623,
    "id": "d98ecaf7",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AnnData object with n_obs × n_vars = 161 × 446\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "View of AnnData object with n_obs × n_vars = 161 × 176\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n"
+     ]
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning: Transforming to str index.\n",
-      "  return dispatch(args[0].__class__)(*args, **kw)\n",
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2118209775.py:15: ImplicitModificationWarning: Setting element `.layers['nona']` of view, initializing view as actual.\n",
-      "  adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n"
+      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning:\n",
+      "\n",
+      "Transforming to str index.\n",
+      "\n",
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2436230638.py:20: ImplicitModificationWarning:\n",
+      "\n",
+      "Setting element `.layers['nona']` of view, initializing view as actual.\n",
+      "\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 161 × 176\n",
+       "    obs: 'source', 'bio'\n",
+       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+       "    layers: 'nona'"
+      ]
+     },
+     "execution_count": 623,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -320,819 +533,67 @@
     "    obs=obsm,\n",
     "    var=varm,    \n",
     ")\n",
+    "print(full)\n",
     "# must have genus level\n",
     "adata = full[:, ~full.var['genus'].isna()]\n",
+    "print(adata)\n",
+    "\n",
+    "# drop all na \n",
+    "#adata = adata[adata.to_df().dropna().index, adata.to_df().dropna().columns]\n",
     "\n",
     "# layer with no na\n",
-    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)"
+    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n",
+    "adata"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 624,
    "id": "80fcd19b",
    "metadata": {},
    "outputs": [
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('1220bd4b-fe23-43e7-b630-2cf391ee5f6e');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };            </script>        </div>"
+      ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "TtestResult(statistic=np.float64(1.6943713373358462), pvalue=np.float64(0.0910842898454701), df=np.float64(350.0))"
+      ]
+     },
+     "execution_count": 624,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -1153,7 +614,7 @@
     "fig = go.Figure()\n",
     "# add traces\n",
     "fig.add_trace(go.Histogram(x=bio_mean['Group1'], name='Group1'))\n",
-    "#fig.add_trace(go.Histogram(x=bio_mean['Group2'], name='Group2'))\n",
+    "fig.add_trace(go.Histogram(x=bio_mean['Group2'], name='Group2'))\n",
     "\n",
     "# Overlay both histograms\n",
     "fig.update_layout(barmode='overlay')\n",
@@ -1162,7 +623,7 @@
     "fig.show()\n",
     "\n",
     "# no diff in stats \n",
-    "#stats.ttest_ind(bio_mean['Group1'], bio_mean['Group2'])"
+    "stats.ttest_ind(bio_mean['Group1'], bio_mean['Group2'])"
    ]
   },
   {
@@ -1185,7 +646,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 625,
    "id": "1d77b8ab",
    "metadata": {},
    "outputs": [
@@ -1194,10 +655,10 @@
      "output_type": "stream",
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 138 entries, 0 to 137\n",
-      "Columns: 223 entries, index to bio\n",
-      "dtypes: category(1), float64(220), object(2)\n",
-      "memory usage: 239.7+ KB\n"
+      "RangeIndex: 161 entries, 0 to 160\n",
+      "Columns: 179 entries, index to bio\n",
+      "dtypes: category(1), float64(176), object(2)\n",
+      "memory usage: 224.3+ KB\n"
      ]
     }
    ],
@@ -1245,17 +706,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 626,
    "id": "128ba953",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      ">> clustergrammer2 backend version 0.18.0\n"
-     ]
-    },
     {
      "name": "stderr",
      "output_type": "stream",
@@ -5164,9 +4618,9 @@
     {
      "data": {
       "text/html": [
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        "                            \n",
-       "var gd = document.getElementById('31539a9a-31d7-403c-af42-b3c21ffe5779');\n",
+       "var gd = document.getElementById('bc0beaae-dcf6-4d0d-8caf-d88f76a1c632');\n",
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@@ -5249,7 +4703,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 627,
    "id": "506a301e",
    "metadata": {},
    "outputs": [
@@ -5264,10 +4718,11 @@
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1.])"
+       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
+       "       1., 1., 1., 1., 1., 1., 1., 1.])"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 627,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5289,7 +4744,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 628,
    "id": "54ab5719",
    "metadata": {},
    "outputs": [],
@@ -5313,7 +4768,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 629,
    "id": "cf343afd",
    "metadata": {},
    "outputs": [
@@ -5362,7 +4817,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 630,
    "id": "5b7f3d3e",
    "metadata": {},
    "outputs": [
@@ -5372,13 +4827,13 @@
        "[None]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 630,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1181.25x1080 with 27 Axes>"
       ]
@@ -5388,9 +4843,9 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1239.38x1080 with 27 Axes>"
+       "<Figure size 1239.5x1080 with 27 Axes>"
       ]
      },
      "metadata": {},
@@ -5458,7 +4913,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 631,
    "id": "ac1c6cc7",
    "metadata": {},
    "outputs": [],
@@ -5478,13 +4933,14 @@
     "    n_features=df_taxa.shape[1], # Number of features (taxonomic groups)\n",
     "    prior=\"MoG\", # Prior distribution \n",
     "    device=device, # Device\n",
+    "    d_z=16,\n",
     "    epochs = [1000, 2000, 2000]\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 632,
    "id": "2f20940c",
    "metadata": {
     "tags": [
@@ -6675,12 +6131,12 @@
    "source": [
     "### Training the ABaCo model\n",
     "\n",
-    "To train ABaCo on the prepared dataset, we then use method `abaco.metaABaCo.correct()`. "
+    "To train ABaCo on the prepared dataset, we then use method `abaco.metaABaCo.fit()`. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 633,
    "id": "e5c0aec5",
    "metadata": {
     "tags": [
@@ -6692,26 +6148,26 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Training: VAE for learning meaningful embeddings: 100%|██████████| 1000/1000 [00:13<00:00, 75.99it/s, bio_penalty=0.0000, clustering_loss=100000000.0000, elbo=45.3159, epoch=999/1001, vae_loss=100000048.0000]\n",
-      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:33<00:00, 58.92it/s, adv_loss=-0.5996, bio_penalty=0.0000, clustering_loss=100000000.0000, disc_loss=0.5996, elbo=44.3152, epoch=1999/2001, vae_loss=100000048.0000]\n",
-      "Training: VAE decoder with masked batch labels: 100%|██████████| 2000/2000 [00:19<00:00, 102.63it/s, cycle_loss=0.0000, epoch=2000/2000, vae_loss=81.0403] \n"
+      "Training: VAE for learning meaningful embeddings: 100%|██████████| 1000/1000 [00:13<00:00, 73.98it/s, bio_penalty=0.0000, clustering_loss=0.0000, elbo=828.6095, epoch=999/1001, vae_loss=828.6095] \n",
+      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:34<00:00, 57.86it/s, adv_loss=-0.8679, bio_penalty=0.0000, clustering_loss=0.0000, disc_loss=0.8679, elbo=1199.6460, epoch=1999/2001, vae_loss=1199.6460]  \n",
+      "Training: VAE decoder with masked batch labels: 100%|██████████| 2000/2000 [00:18<00:00, 107.64it/s, cycle_loss=0.0000, epoch=2000/2000, vae_loss=3908.0784]\n"
      ]
     }
    ],
    "source": [
-    "# Train the model\n",
-    "model.fit(seed=42)#, w_bio_penalty=0, w_cluster_penalty=0)"
+    "# Train the model,\n",
+    "model.fit(seed=42, w_bio_penalty=0, w_cluster_penalty=0, w_elbo_nll=10)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 634,
    "id": "58848ce7",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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DS+k7Cez++eefyjlL47l2w0SQlljPgRufyzS3v42/t7Xn0e3R+HmWQLkE5zknJm/BoC2RE8nV0Yb1MO1pqTaOjEvdIqkrJPWD5Kqw1FR97rnnlG3yQeKIBPvEP/7xDyWz1p7GH3aOajJ1RHvuUxowSZ1YRwFImWBs3ry51fdnzfaUOqv2yJXixoErb9b4mFqfa6nXKhOWxuTCgSdIVoLUXZXmY9LgQAKrcmW9ceCxvSRLWbKEJatcaoz17dtXqdssGeRSL8t6XJzFURa6s5t2deR96OhvihwrIiIKTJyTqjgndT7OSf2bBHalObLMsZ9//nllBakkFkjmqSQUOXuu3Zb3bUdqzHJeTL6KQVsiN+nSpYvyIScZktYrptai87LMXcYbkiLtcpMi+JK5ePnll+Ozzz5TirA7+sCyBiElW1WWxTlz34UUZ28Y6JTl1JmZmU59LEfOPvtsvP3228oV39GjRzf7vbJPEjSUJd+SudyQPAdSBF+O6UMPPeTwPuQKdktBYjkuGzduVO6zYVBy+/btdeP2SBkIKfsgx7Mx+Vm5L5kgNceaiSxdXZs7/tZ9sGbmNmTv8VvK4m742tu5c6fyb8OutNLgSn4/CZpLtoBcnZfj3VqN91MeUx7b2mhv06ZNyuNKIwIJEDcsF9GYo/eJHDu5GCKB39Zk27aHHHdZxtb4mDXM+m7NfbTm9SWZv0L+jjTkKOtA7k8uWlizax09l0RE5J84J+0YzkltBeqc1NHvKKWmZHVgw2zbls4NrGOOzg0a/mxH5pitmQNL0lB1dbWSeNFwxVlrG53Z+71k7innZw2zWts6J27tebTMixvPieWcVUrG2SP3efLJJ9d9LSXI5HvPPPPMVu8fkSuxpi2Rm1j/8Evn0YbkCqawdtCUZdeNs/ik86iQD1AhAT/R+ANJJktSTuGtt96y+8Eky/LbQyZgcoX15Zdfttm39957T1ki01z3T2e57777lIxKCVrLB7S9q8IvvfSSTZat/IzUn2p4k7qrEshtWHfVHimN8Pfff9vtRmo9BvKcSj1XKcVgJR1YX3nlFSUjunHAuGH25qRJk7Bw4UKbpTfye0kwWWpZWcsbOCKZ1PI90lXVXu1j63Mty3vk9SNBzoalAyTIaa2N1RpHjhyxORZSc/fDDz9U7rthpq9k+EoNVqkbLJ1pJdu2ucltY3KfDctgSNa5vJalw23DzNeGr0P5f+tz35C8Xuy9T+S5lZ+REiSuyqCV50eyf2XCa1VVVYV33nmn1ffR2teXTFTluCxbtszm519//XWH9/3qq6/a/M7ytVzskcwKIiLyb5yTdgznpLYCdU7q6L0lGZ0N51lCMlQlwNrSz65atUpJUGnYu0GSViQYbe1F0ZE5ZmvmwPbm2vJ8zZo1C+1hXf3ZeF4q81ln/82yBqYbz4nlGDrKtJWxhq/bN954Q5lvN/dcEbkTM22J3ESaWkkzKPlgkCCSBFzkg1kmLlKz1nqFT76WDzVp+iQfOjJZkA9hmQxZP7BkyYh8cEswR7Ll5Eqp1DiSm9Qwk6CfTEykIL1kxkowUCYAhw4dUgKRbSVXqR944AHlA16uWkvhe7kSLPt5/PHHt7qgf0fIsZCA5tSpU5UrrJJlKb+vXDmVrFpZki/L44UEZGXi5ihbVfZfit9LPdfhw4fb/Z57771XmZxdfPHFSnmKESNGKFelZYL05ptvKs+nFK6XALk87tq1a5UJlfyM1IGSSUVzjdOefPJJZZIqz5WUD5CJpdyXBOb/85//tHg85PUgkwrJGJDfQRrfyfMk9V6lGL+UhbBOGJ9++mllMiOPJb+L/B4yUZKauXI1uTXkdXbttddi9erVSr3m999/X3ld2ZvAyXMjAX65Iv/ss8+iLeS1LPspTbnk/uU4SkkPa3MFWaolrwUpASITVjkOUg/ZXo1Zec6ENIOQCaNMQuU4yXtNjpvso1xdl9e0XL1fvny5MtawSVd7STM9Of5ysnDHHXcoJyryupRGEa1d3tXa15fUFZPXqTyncr9yfKSRodSvtkf2QZpCyN8jyTyRphjymvnXv/6lvIaIiMi/cU7aMZyT2grUOak90ttB5pIPPvigkpgh7zVpPiyJGtLQuWHPjsbuv/9+fPrpp0qwUOau8vhyXigZqjLXta666sgcszVzYEkskWQd+V3kseR5kXNRSQ5ylK3aHJmPS7BYjp80ipaVpNJM15od3Zo5cWv/ZglJ8JFGZvKYUlJNzn0lu9hRGT45l5SkBUnssZ7fyvPesNEbkUdZiKjDZs2aJZciLatXr272+2pray2PP/64pVu3bha9Xm/p1KmT5YEHHrBUVVXVfc+6dessl112maVz586W4OBgS1JSkuXss8+2rFmzxua+VqxYYRkxYoTFYDAoj/3oo4/Wje3Zs8dy1VVXWVJSUpTHSU9PV+5j/vz5rdpn61hmZqbN9ldffdXSt29f5T6Tk5MtN998s6WwsNDme0466STLgAEDWn3sZL/lsXJzc1v1/Tt37rRcf/31lq5duyq/e2RkpGXs2LGWV155RTmOa9euVe7v4Ycfdngf+/btU77nrrvuavax8vPzLbfeeqty/OSxMjIyLNOnT7fk5eXVfc/Ro0ctV199tSUhIUH5nkGDBinHr7HGz5H1uT799NMtERERlrCwMMvJJ5+sPK9teW399ttvyn1ER0dbQkJCLD169LDMmDGjyevliy++sPTr1095TfXv39+yYMEC5Xfp0qWLpSXyPWeddZZl0aJFlsGDByv3Ia+DefPmOfwZeQ1oNBrLoUOHWrx/6+8hv+enn36qvCfkdR8aGqo87v79+22+d+vWrZaJEycqx02Ou7we/v77b+XnGx57o9Foue222yyJiYmWoKAgZbzh2H//+1/l95DnTb5n8uTJyuvHSr5/5syZdo+HHLuW7N27V9l/+T3k/u+55x7leZD7XblyZaveM619fcn758ILL1ReR7GxsZYbb7zRsnnz5ibHRPY7PDxc+RsxadIk5fvlvSyvTZPJ1OLvRERE3o1z0nqck3JO6uo5qb25dGlpqXKOkZaWppwz9erVS5lzms3mFueTMj+76KKLLDExMcq8fuTIkZZvv/223XNMe/vXmjnw119/rcz5ZR/knOvZZ5+1vP/++03OD+U9JreWlJeXK3PquLg4Zf4+ZcoUy44dO5T7e+aZZ1p1Xtia82gh89l//vOfytxZ5rlynrR79+4mx9v6t3Lp0qWWG264QZk/y75dfvnlyjkgkbcIkv94NmxMRET+ZtiwYUqGwC+//OLpXfEqkmVw1113KVnv0sHY3SRrV7J1W5vNQkREROTLAmVO6uk5Zltt2LBBeW7mzJmj9G5xNymZIVnUkrHdUiNxIk9iTVsiInKqNWvWKBOxho3CAlFlZaXN11JvTModSBMGX5hMExEREfkyf52T+tocs/H+WoPMUvJh/PjxHtknIl/BmrZEROQUmzdvVmqvPvfcc0p9Lak/HMguuOACpeuu1FeWBg6SSSAdgFtqgkdERERE7efvc1Jfm2NKvw55PqT2rPTxkH4KcpP+DY56kBCRikFbIiJyCll2/+9//xt9+vRRGilYGyIEKml+9u677yoTaOlYK80DP/vsM787cSAiIiLyJv4+J/W1OeaYMWOUBsxPPPGEUqJLAs6PPfaY0rCNiJrHmrZEREREREREREREXoQ1bYmIiIiIiIiIiIi8CIO2RERERERERERERF7Eq2vams1mHDlyBJGRkQgKCvL07hARERGRh1ksFpSWliItLU3pPO0LOKclIiIiorbOZ706aCsBW3YTJCIiIqLGDh48iIyMDJ84MJzTEhEREVFb57NeHbSVDFvrLxEVFeXp3SEiIiIiDyspKVEu6lvnib6Ac1oiIiIiaut81quDttaSCBKwZdCWiIiIiBrPE30B57RERERE1Nb5rG8UAiMiIiIiIiIiIiIKEAzaEhEREREREREREXkRBm2JiIiIiIiIiIiIvIhX17QlIiIiIltmsxk1NTV+e1j0ej20Wq2nd4OIiIiIXMhkMqG2ttYvj7HeSfNZBm2JiIiIfIQEazMzM5XArT+LiYlBSkqKTzUbIyIiIqKWWSwWZGdno6ioyK8PV4wT5rMM2hIRERH5yAQ3KytLuWrfqVMnaDQav/wdKyoqkJOTo3ydmprq6V0iIiIiIieyBmyTkpIQFhbmdxfpLU6czzJoS0REROQDjEajMgFMS0tTJrj+KjQ0VPlXJroymWepBCIiIiL/KYlgDdjGx8fDX4U6aT7rfykaRERERH46yRUGgwH+zhqU9tc6Z0RERESByDq38+cEBGfOZxm0JSIiIvIh/raELFB/RyIiIqJAFQhzvSAn/I4M2hIRERERERERERF5EQZtiYiIiIiIiIiIiLwIg7ZERERE5HKvvfYaunbtipCQEJxwwglYtWoVjzoRERER+ZTX3DinZdCWiIiIKIAUV9RgT04Z1h8oxJ7cMuVrV5s7dy7uvvtuPProo1i3bh2GDBmC008/XemoS0RERETUVsUBMKfVueReiYiIiMjrHCmqxD+/2Ijlu/Lqto3vlYBnLhyMtJhQlz3u888/j+uvvx5XX3218vWbb76J7777Du+//z7uv/9+lz0uEREREfmfIwEyp2WmLREREVEAkOyDxpNbsWxXHu7/YqPLshNqamqwdu1aTJw4sW6bRqNRvv7zzz9d8phERERE5J+KA2hOy6AtERERUQDIK6tpMrltOMmVcZc8bl4eTCYTkpOTbbbL19nZ2S55TCIiIiLyT3kBNKdl0JaoAywWC48fERH5hJKq2mbHS1sYJyL/xPksERH5kpIAmtOypi1RG5mKi1Fz+DCKv1gAU1ERos46EyEDBkDf6GoLERGRN4kK0Tc7HtnCeHslJCRAq9Xi6NGjNtvl65SUFJc8JhG17HBhBf7cW4AlO3LQNT4MU4ZlIC0mBGEGniISEZH3igqgOS0zbYnaGLDNnz0b+y64EIUff4yS777DoVtm4uD116OWSzyJiMiLJUQYlAYN9sh2GXcFg8GAESNG4JdffqnbZjabla9Hjx7tksckouZl5pVhymsr8I95f+PbjVl49bc9OO2Fpfh5Ww6qak08fERE5LUSAmhOy6AtURvUHjmC/DfebLK9eucuFH7yCSy1/pOGT0RE/iU6zKB01G08yZWvn71wsDLuKnfffTfeeecdfPDBB9i2bRtuvvlmlJeX13XeJSL3KamsxSMLtyC3rNpmu1T9uufzDcgptd1ORETkTaIDaE7LtS9EbVD89dcOxwrnfo7Yyy9nmQQiIvJaaTGheOWyYUqDBqn3JcvHJBvBlZNbMXXqVOTm5uKRRx5RGjUMHToUP/74Y5NGDkTkegXljhu41Jos2HSoCJ3jwvhUEBGR10oLkDktg7ZEbWAqLnE4ZqmoUFMUiIiIvJhMZl09obXn1ltvVW5E5FlGc/Pz1fJqlkcgIiLvFx0Ac1qWRyBqg6gzJzscizjpJGgiI3k8iYiIiMhrRYXqlMZjjgztHOPW/SEiIiL7GLQlaoPg3r0RMnBgk+1BISFIvPMOaMPDeTyJiIiIyGslRYbgySkDERTUdOyCYelIigz2xG4RERFRIwzaErWBPikJGa+9ioTbb4c2IQFBYWGIPP10dPtiPgxdu/JYEhEREZHXG94lFl/eMhajuschRK9Ratg+fcEg/OusfojxwFJTIiIiaoo1bYnaSJ+cjIQbb0DMhRcCFjM0UVHQhrFZAxERERH5hjCDDkM7xeCtK0agotYEbVAQkqJCPL1bRERE1ACDtkTtEKTVQp+cxGNHRERERL7dxMXTO0FERER2sTwCERERERERERERkRdh0JaIiIiIiIiIiIjIizBoS0RERERERERERORFGLQlIiIiIiIiIiIi8iJsREZEZIexoAA1Bw6g+IsFMNfUIGbKeTD07Al9YiKPFxERERF5PbPZgsNFlfh1ew5W7ytAv9QonDUoFWkxITDotJ7ePSIiagEzbYmIGjHm5yPnP//B/ksvQ9G8eShZuBAHrr4GR+67D7U5OTxeRERttGzZMpxzzjlIS0tDUFAQvvrqKx5DIiIX25ZVgjNfWo5Hv96Cbzdm4b+LdmDSC8uwZn8hjCYzjz8RkZfPZxm0JSJqpGrHDhR/tbDJcan4cyXKly3n8SIi31ZZCOTtBA6tAfJ2qV+7WHl5OYYMGYLXXnvN5Y9FRERAbmk1bv9sPUqrjTaHo8Zkxs1z1iGntJqHiYh8W6V757SemM+yPAIRUQPmqmoUzvnY4TEp+OgjRJxyMnRxcTxuROR7ig8DC28F9v5av63HqcC5rwDR6S572MmTJys3IiJyj4LyGuzJLbc7VlxZi+ySKqTFhPLpICLfVOz+Oa0n5rPMtCUiasBiNsFcXubwmJgrKmDhcjIi8kWSfdB4civ2/AJ8fZtbMm6JiMg9jObmyx9U15r4VBCRb6oMnDktg7ZERA1ow8IQddZZDo9J5GkToY2J5jEjIt9Tntt0cttwkivjRETkF2LCDIgKtb+wVqcJQjqzbInIV5UHzpyWQVsiokYiTjwR+oyMJsdFGxOD2Msug0av5zEjIt9TVdKxcSIi8hnJkcF45OwBdsduObkn4iOC3b5PREROURU4c1oGbYmIGtGnpqLzhx8g7uqrlUCtJjwcMRddiK6fz7UbzCUi8gkhUR0bJyIin6HTajCpfzLmXDcSgzOiEazToGdSBF6bNgwzxnRBeDDb2xCRjwoJnDkt/1ITEdlhSEtD4t13IW7GdMBigTYmFpoQZiQQkQ8LT1QbNMiyscZku4wTEZHfiArVY1zPRPS/OlqpYavXaZDADFsi8nXhgTOnZdCWiMgBKYOgSU7m8SEi/xAaq3bUlQYNDSe51k67Mu4iZWVl2L17d93XmZmZ2LBhA+Li4tC5c2eXPS4REQFx4QYeBiLyH6GemdN6Yj7LoC0RERFRoIhOBy56T23QIPW+ZPmYZCO4MGAr1qxZg5NPPrnu67vvvlv5d/r06Zg9e7ZLH5uIiIiI/Ey0++e0npjPMmhLFEgsFqC2AtDoAB2X+hMRBSSZzLo4SNvYhAkTYJHPICIiZzDWAKYawBAOBAXxmBIRBaJQ985pPTGfZdCWKFAUHQR2/ABs/xYIjQNG3QQk9AbC4jy9Z0RERERELassBPL3AH+9CZQdBXpNAvqdC8R24dEjIiK/w6AtUSAoyARmnQGUZtdv2/olMPZOYNydbs+4IiIiIiJqE1n+uvo94Ncn6rdlLgN+fwG45icgoScPKBER+RWNp3eAiFysphz47f9sA7ZWf7wIlGTxKSAiIiIi7yaZtQ0DtlYV+cBPDwJVpZ7YKyIiIpdh0JYoEJaRbVngeFzKJRARERERebO9vzke27UIqCxw594QERG5HIO2RP5OCmVbTI7HjVXu3BsiIiIiovY1H2t2vmvmUSUiIr/CoC2RvwuJBnqc6ni879nu3BsiIiIiorbrPsHxWKdR6pyXiIh8gtns/xfazE74HdmIjMjfhUQBk54EDvyp1rdtSLrtxnT21J4REREREbVOVBow9HJgw8e223XBwJn/BcLieCSJiLycwWCARqPBkSNHkJiYqHwdFBQEf2KxWFBTU4Pc3Fzld5Xfsb0YtCUKBAm9gRuXASteBXb/DITGAKNvUzMWwhM8vXdERERERM2ToOzEx4BepwG/v6g2IOs6Hhh3JxDbjUePiMgHSBCzW7duyMrKUgK3/iwsLAydO3dWfuf2YtCWKBBotEB8T+CMZ4CqYkCjA8LjPb1XREREREStF5EEDDgf6HYSYKoFgqMAQyiPIBGRD5HMUwlmGo1GmEzN9N/xYVqtFjqdrsNZxAzaEgUSfYh6IyIiIiLyVSyFQETk0ySYqdfrlRs5xkZkREREROQyTz/9NI4//nhERkYiKSkJU6ZMwY4dO3jEiYiIiIiawaAtERERUQApri5GZnEmNuZuVP6Vr11p6dKlmDlzJlauXInFixejtrYWkyZNQnl5o+aYRERERERUh+URiIiIiAJEdnk2Hl3xKFYcWVG3bWzaWDw25jGkhKe45DF//PFHm69nz56tZNyuXbsW48ePd8ljEhERERH5OmbaEhEREQUAyahtHLAVfxz5A4+teMzlGbd1+1GsPk5cXJxbHo+IiIiIyBcxaEtEREQUAAqqCpoEbBsGbmXc1cxmM+68806MHTsWAwcOdPnjERERERH5KpZHICIiIgoApTWlHRp3Bqltu3nzZvz+++8ufywiIiIiIl/GoC0RERFRAIg0RHZovKNuvfVWfPvtt1i2bBkyMjJc+lhERERERL6O5RGIiIh8jdns6T0gHxQXEqc0HbNHtsu4K1gsFiVg++WXX+LXX39Ft27dXPI4RERE5GM4pyVqFjNtiYiIfIHFAhQdAHb/DOxdAiT0BoZMBaI7AfpQT+8d+YDo4Gg8NuYxpemY1LBtGLCV7TLuqpIIn3zyCRYuXIjIyEhkZ2er+xMdjdBQvnaJiIgCSkU+UJAJrPsAqC4DhlwKpAwGolI9vWdEXodBWyIiIl+Qux2YNRmoLKzf9vvzwNQ5QM/TAJ3Bk3tHPiIlPAXPjn9WaTomNWylJIJk2LoqYCveeOMN5d8JEybYbJ81axZmzJjhssclIiIiLwzY/vY0sPqd+m1bFgCpQ4HLPgWi0jy5d0Reh0FbIiIib1eeD3x1i23AVljMwBfXAjNXATGdPbV35GMkQOvKIK298ghEREREyN9jG7C1ytoAbPwcGHM7oGEVTyIrBm2JyL8VHQIOrwUOrQIS+wLdTgSiMgAt//yRD6ksAI6ssz9WWwnk7WLQloiIyE8VVdQgu7gKP27JRnWtGZMGJKNzXBjiI4I9vWtEbatfu/p9x+Or31VLJUSm8KgSHcOoBRH5r7ydwKwzgfLc+m36MOCqhUD6CECj9eTeUTOMubmwmEwI0uuhi4/nsTLXNn8Masp5jIiIiPxQYXkN3lq2B28u3Vu37Y2lezCpfzKeOn8gEiNDPLp/1ML8rLJI/f+weEAf6M+VGagpdTxcW66uIiOiOsw7JyL/VJ4HfHG9bcBW1FYAn14KlKqNcMi7GAsKUPTlV9h32TTsPvkU7J8+A6W//gZTcTECWkiM4xpfQUFA8gB37xERERG5wd68cpuArdVPW49i2c48PgfeSMoC5e0Gvr4NeHko8OpxwI/3A4X7EdA0OjWT1pE+ZwGhse7cIyKvx6AtEflvkXupjeRorOSwu/eIWmAqL0f++7OQ9cADqD10SJnw1uzejUO33IKSH36EpbaFbFN/FpkKnPWc/bGRNwFhCe7eIyIiInKxGqMZs1dkOhx/Z/le5JdV83nwNoX7gHdPATZ/AZhq1KSRtbPUhrLFhxDQZLVjUv+m24OjgHF3AfpQT+wVkddi0JaI/JOxhQlsdYm79oRayZSfj4JZs+yO5fzvf6jNbZQ1HUgkm7bricA1PwFdxgKGCCChN3DBO8D4fwCh7msqRURERO5hMltQUF7jcLy4shZGM5s9et05yKq3gSo7q8QkaWTHj2ombqCSlWOXzwdOuh+ISAZCooEh04AbfgNiu3l674gCK2j79NNP4/jjj0dkZCSSkpIwZcoU7Nixw5UPSUSkkqU1csXWUQCMkwKvU5uVBZhMdsfMZWUwFR2rCRaogiOBzicAl34M3LoKmPEdMPgSIJxZtkSuxPksEXlKqEGLMwY4bso0oXciokP1bt0naoHUsN35o+PxrV8CNWWBfRij04Hx9wE3LAVu+RM4+zkgviegYU4hUWMufVcsXboUM2fOxMqVK7F48WLU1tZi0qRJKC9nwxQicjHpOjrxMftjI64BwhP5FHgZTWjzy6GkKRkduyARlQ5EJPFwELkB57NE5Emn9E1GSlTTBlZhBi1uOKk7QvRsrOtVtDr1QrsjwdGAhnNaaLVAVKo6p5VG0URklw4u9OOPtleYZs+erWTcrl27FuPHj3flQxNRoNPqgQHnq7U+f3kMKNirLsE58R51e4iDLFzyGF1SErSxsTAVFjYZM/TsCV1cnEf2i4gCG+ezRORJ6bGh+Pym0Xjp5534+u8jSjmEk3sn4v4z+6FTLINdXicsHhh1C/DljfbHR90E6JsG4YmI3B60baz4WPfvOJ54E5E7hMUBA84DOo8CTNXqVW0J3HLpjdcGbTNefQUHrrkWlur6msSaqCikP/c/6OLjPbp/RESC81kicrfOcWF48vyBuGdSH6UcalSoDpEhzNb0Wt1PBnqfDuxcZLt9xAz7TbiIiDwdtDWbzbjzzjsxduxYDBw40O73VFdXKzerkhI2CiIiJ4hM5mH0AUEaDUKHDEH3b79B2dKlqNq+A2HDhyFs5AnQp6d5eveIiFo1nxWc0xKRs4XqdQiNcWvOFXXk3OPcV9WVfpvmA1qD2ocguhMQziQEImo9t/3Vl9q2mzdvxu+//95so4fHH3/cXbtEROS7qqWBQRAQHA5/EqTTwdCpE+KuuMLTu0JETvLGG28ot3379ilfDxgwAI888ggmT57sc8e4NfNZwTktEVHLak0mVNaYEWrQQC81Tv2J9B6Qm6z4IyJqpyCLRRZYuNatt96KhQsXYtmyZejWrVubshI6deqkLEOLimL9SSIilGQBB1YAa2erQdvjrgY6jVIL+RORX6uqqkJmZqYylwoJaX89PGNxMUz5+TCXlkITGQVtfBx00dFwlW+++QZarRa9evWCTDs/+OAD/Pe//8X69euVAG5bf1eZH0ZHR7t9ftja+azgnJaIyLHKWhMOFlTggxX7sD27FP1TInHVmK5KGYhgNlYjogBQ0sr5rEszbWViftttt+HLL7/EkiVLWpzgBgcHKzciInIQsJ17OXB4bf22zKVAxkjgkg8ZuCWiFtVmZePIQw+h4o8/6raFjRuHtCeegD41xSVH8JxzzrH5+qmnnlIyb1euXOkwaOtN2jqfFZzTEhHZZzJbsHJPPq79YDXMx9LH1u4vxCerD2LWjOMxtmcCtJogHj4iIunv4uolZHPmzMEnn3yCyMhIZGdnK7fKykoefCKittrzq23A1urQKiBzGY8nEbWYYds4YCsqfv8dRx5+WBl3NZPJhM8++wzl5eUYPXo0fAHns0REzpNTUoW7Pt9QF7BtGMy9a+4GZZyIiNwQtJUsCkn1nTBhAlJTU+tuc+fOdeXDEhH5n8pCYM17jsfXvAtUFrlzj4jIx0hJhMYB24aBWxl3lU2bNiEiIkLJQL3pppuUrNX+/X2jgzbns0REzpNXVoOiilq7Y/nlNcgrry+XSEQU6FxeHoGIiJzyBxUwmxyPyxj/5hJRM6SGbfPj0uDQNfr06YMNGzYoF/Pnz5+P6dOnY+nSpT4RuOV8lojIecwtzFc5nSUiclPQloiInCQ0Fhg6DcjaYH982BVAWKxvH+7aKqD0CLBzEVCwD+g+HkgdCkSne3rPiPyCJjKyhfEIlz22wWBAz549lf8fMWIEVq9ejZdeeglvvfWWyx6TiIi8T0KEARHBOpRVG5uMRYXoEB/h+z1uckqrsDenHIu3HVV+pzMHpSI5OgRRIXpP7xoR+RgGbYmIfEFQEND3bGDVW0D+HtuxhN5Ar9Ph04w1wL7lwKeXAuZjk/hVbwLRnYDp3wBxLTf+IaLmaePjlaZjUgqhMdku4+5iNptRXc0lsEREgSYxKhhPTBmo1K9t7MkpA5Ec6dtB2+ziKsz8ZJ3SXM3qhZ934cEz+2Hq8Z0QFcrALRF5SU1bIiJyIsk4veprYNKTQGJfIKkfcPr/AVd+5fvZqKVZwNwr6gO2VsUHgR/uA6pKPLVnRH5DFx2NtCeeUAK0DcnXaU8+oYy7wgMPPIBly5Zh3759Sm1b+XrJkiW4/PLLXfJ4RETkvQxaLSb2S8JXt4zFKX2T0CU+DKf1T8LCmWNxSr9k6LS+G6IwmcyYt+agTcDW6qnvt+FIERuyE1HbMNOWiMiXRGcAo2YCgy9Vs2/D4tV/fd3RzYDRQbfg3YuBinwgJMrde0Xkd/SpKUh/7n9K0zGpYSslESTD1lUBW5GTk4OrrroKWVlZiI6OxuDBg7Fo0SKcdtppLntMIiLyXpEhegztHIOXLxuKyhoTwgw6hAf7fmgit7wGH/y5z+H4gvWH8a9UzmeJqPV8/y8jEVGg0WiAiET4lcqmGQk2HSlMNe7cGyK/JgFaVwZpG3vvvffc9lhEROQ7IoL1ys1fWMwWlFY1rdVrlVfKskBE1Da+u/aAiIj8R9owx2NS15ZZtkRERETkxSJCdBjbw3F9+MmDUt26P0Tk+5hpS0REnheZAvQ9F9j+ddOxyc8CkW2Y5FYWA6VHgK1fA1XFQL+zgfieQESSU3eZiIiIiKhh2Yd7z+iL33fno8ZktjkwPRIjMCi9jaURig8BR9YD+/5Qm/L2Og2ISgd0vt2sjYhaj0FbIiLyPKnNe9b/gPThwJ+vqDVskwcCpz8FpA1v/f1UFgFr3gN++Xf9tpWvAV3GAhe9rwaHiYiIiIhcoEdiOL6aOQb/9/12/L47D6F6LaYen4EbxvdASnRo6++oYC8w+2yg5HD9tp/0wLTPgS7jAJ2Bzx9RAGDQloiIvENkMjD2dmDIVMBsAvQhQHgba/cWHbAN2Frt/wPY+Dkw+la1JjARERERkZMZdFr0T4vGa5cPR1m1UalHGR9hULa3KQnh27ttA7bCVAt8djkwcyUQ04XPHVEA4JkrERF5D40WiEoDYjq1PWAr1n/keOyvN4GynA7tHpE3sEhzPj8XCL8jERH5r+hQPdJjQpEaE9q2gK2oKAD2/mZ/rLYCyNnhlH0kIu/HoC0REfkHs7n5oKzUt4XJnXtE5FRarXrSV1NT4/dHtqKiQvlXr/efruJEREStYmrhc76qiAeSKECwPAIREfkHKXsw4AJg61f2x3ucDARHu3uviJxGp9MhLCwMubm5SjBT44elPiTDVgK2OTk5iImJqQtUExERBYyQKLUPQ2m2/fGUwe7eIyLyEAZtiYjIf2QcB8T3APL32G6XLrsnPwgER3hqz4g6LCgoCKmpqcjMzMT+/fv9+ohKwDYlhY0DiYgoAEWmAmc8A8yb0XRs4IVARJIn9oqIPIBBWyIi8h/R6cCVC4HfXwT+/hgwVgHdJgCTngTienp674g6zGAwoFevXn5dIkGyiJlhS0REASsoCOhxCnDFAuCnh4CcrUB4AjDmDrVhb1icp/eQiNyEQVsiIvIv0sTsjKeAE++WxdaAIRIIZVkE8h9SFiEkJMTTu0FERESuEhIN9DxVLYUgSQjSrDciRS0HRkQBg0FbIiLyP7oQNeuWiIiIiMhXRSR6eg+IyIN4mYaIiIiIiIiIiIjIizBoS0RERERERERERORFGLQlIiIiIiIiIiIi8iIM2hIRERERERERERF5ETYiI/JWpUeBwkzgyHoguhOQOgSITAW0fNsSERERkferqDEit7Qaa/YXoqzKiOO7xSElKgRx4QZP7xoREZHXY/SHyBsVHQQ+vRQ4url+myECuPJLIH0EoNF6cu+IiIiIiJpVXm3Eoi3ZuHf+RpjMlrrtkwem4N/nDURiZDCPIBERUTNYHoHI21SXAT89bBuwFTVlwJwLgZIjntozIiIiIqJWOVJciXvm/W0TsBU/bM7GD5uzYLHYbiciIiJbDNoSeZPaKqDkMLD9a/vj1SVA3k537xURERERUetVFODLNQfgKC779rK9StkEIiIicoxBWyJvYTYBB/4Ecrap/+9I2VF37hURERERUeuVZAEr38DBoiqH3yIBWxMzbYmIiJrFoC2RtyjNAr64BjBWAuEJjr8veaA794qIRFUJkL8HOLASOLqFF0+IiIgc2bsE2PoVJnZ2fKo5oksswgxsr0LkVmYzUHwYOLIBOPgXULgPqKngk0DkxfhJSeQtynKVpWRY9xEw5g5g8cNNv6friUBUmif2jihwlWardaY3z0PdOs+E3sClnwAJvTy9d0RERN5D5rKr3lbKeR0fV4GUqBBkl9hm3GqCgPsn90V0qN5ju0kUcIy1wOE1wLyrgLIcdZvWAEx4ABgxAwiL8/QeEpEdzLQl8hZmo/rv/j+AqmLg9P8DIlPVbboQ4LhrgQvebj4Ll4icy1gF/PEysOnz+oCtkNrSH01hY0AiIqKGLGbApNaqTVt0A+ZenITT+sQrgVrRKykCn153gvIvEblRySF17moN2ApTDfDL4+r5JxF5JWbaEnmLiGRAHwrUVgLL/wdkHA+c/C8gOAoIClK/ZpYtkXuVHgXWvm9/rPiQuqyM70siIiJVaBww6GK1lFDxIXSZfyZeGHI1CkZOhtEShKjIKCR0YQICkdtt+0ZNRrDnt6eATqOAiER37xURtYCZtkTeFLSd9FT914dWA1/fBsybrgZyw/khSuR2UmNa3n+OFGS6c2+IiIi8m0YDDLwIiO6kfl1dgohVL6HzvDPQ/debkRAT5ek9JApMR9Y7HivYC5hr3Lk3RNRKDNoSeQt9MDDwQmD6N0DnMUBEklrD9ppFQJ8zAS3rfhG5/30ZBhjCHY/H93Dn3hAREXm/mE7A1T8AJ94LRGcAMZ2BCf9S57jyNRG5X6eRjscS+gDaYHfuDRG1EssjEHmT0Big23ggZbCa3SflEmQbEXlGRApwws1qyZLG4roDsV09sVdERETeH7idcD8w8jr167BEQKv19F4RBa4+k4FfnwBqypuOnfoI+6YQeSlm2hJ5IwnURqUyYEvkaToDcMKNwMgbAU2D65zpw4ErFgCRKZ7cOyIiIu+l1amfk3JjwJbIs6RkyfTvbBMODBHAWc8DGcd5cs+IqBnMtCUiImqOlCqZ+Cgw6magslAtlxCWAITH87gRERERkffTaIH0YWrpvfI8wFyrzmeViyosw0fkrRi0JSIiaokEauO6AZAbEREREZEPsma/E5FPYHkEIiIiIiIiIiIiIi/CoC0RERERERERERGRF2F5BCIiTzDWABX56v+HJ7CWFBERERH5nMLyGlQZTQjRaREbbvD07hAR+RUGbYmcpbocqMwHLBYgOBIIi+OxJfsKDwB/vQFsmgcEaYDBlwIjrwdiOvGIERERkWeVZgO1lYDWAEQkA1qeMlJTRRU1+PtgEZ5bvBP78svRIyEC/zi9DwamRyE6lMFbIiJn4CcwkTMU7gN+fhzY9jVgNgKdRgGTnwWS+gM6TlqogaIDwPuTgNKs+m0rXgK2fglc/QMQncHDRURERO5XWQjs+VWd0xbtB0JigFE3AyNmsHER2aiuNeHL9Yfx+Ddb67atP1iEy9/9C89cMAgXjEiHQavlUSMi6iDWtCXqqKKDwKzJwJYFasBWHFwJvHcaULCHx5fqmU3Axs9tA7Z1r6MDwPZv1UxtIiIiIncymYCtXwPzr1EDtqKqCFjyNPDj/UBFIZ8PqpNTWo1nfthu94g8+d025JZU82gRETkBg7ZEHZW5FCg50nS7qQZY8gxQXcZjTPUZLBLcd0QCunKCREREROROZVnAz4/aH9vyJVCew+eD6uSWVaPaaLb/Uqo2Ir+8hkeLiMgJGLQl6mgzKcmObC6gW13CY+wJkrFaVQLUVnjP8Q/SAroQx+P6MEDDqjVERETkZlXF6sVlR3J3uHNvqKHaKvX5kRVbXkKvaT6MoNMEuW1fiIj8GaMDRB0hAbaIFMfj0oyMQTj3k1ID275RawyHxAKjb1HrC4cnwKPCYoETbgIWXG9/XOrGSRM7IiIiInfSBTc/Hhrrrj0hKylJkb8T+PN1tbRWz4nA4EuAmC5AkGeDogkRBuWWV9Y0ozYtOgTx4S28noiIqFWYaUvUEXKV+birHY+Pvg2ISOIxdqeCfcC7E4FF/wIOrAR2/gB8cI5ak62iwPPPRbfxQPeTm27vPRlIP84Te0RERESBLixBnaPYIw3J4rq6e48Cm6wWW/Me8N4kYOtXwMG/gN+eAt46Ccjb6em9Q3JUCF6dNhwGrW04IVinwSvThiE5upmVZURE1GrMtCXqqNiuwGlPAosfst3e5yygz5k8vu4kpRCWPgOUHW06tvpdYPh0NfvZkyJTgPPfAnK2AmtnAxqt2pU5sS8D/EREROQZoTHAOS8DH56rrlhqWLpp2udAZBqfGXcqywF+faLpdul98P19wCUfqM+Zh2g0QRjeJQaL7hqPrzccxuYjJRiaEYOzB6ciPTbUY/tFRORvGLQl6qiQaGDEdKDPGcCuxUBNOdDrNCA6w/PL8QONZNJunu94XBpppA6Gx0UmqzcloyVIzdgmIiIi8qS4bsA1i4CjW4FDq4H4HkCnE4CodPUiM7nPvuWOxzKXqPWHPRi0FQatFt0SwnHHxN6oNZmhb5R1S0REHcegLZEzhESpt4RePJ6eZrHfyVZhqoVX4QkQEREReZOoNPXWa6Kn9ySwmY0tfIMF3oQBWyIi1+DlMCLyH1JzrbmSFAPOd+feEBERERG1XdcTHY9lHK/OeYmIyO8xaEtE/iM4Ajj1UbVkRWP9zwNiOntir4iIiIiIWk/KaI28oel2XQhw1nOe79FARERuwfIIRORf4noANywFVr0D7PoRCI4GxtwGdB0LRCR6eu+IiIiIiJoXGguc9E+gx6nA788D5blA1/HAmFuB2G48ekREAYJBWyLyL9LUSxppTHwMGHcnoNExG4GIiIiIfIs0NJZGx51HAaYaIDgK0Id4eq+IiMiNGLQlIv+kMwARSZ7eCyIiIiKi9gtl/VoiokDFmrZEREREREREREREXoRBWyIiIiIiIiIiIiIvwvIIREQBrrCiBpU1Jmg1QUiMCIZGE+TpXSIiIiIiaj1TrdqwzWIGDJFAaDSPHhH5PAZtiYgCVHm1EduySvDU99uw4WAREsKDcd2J3XD+sHQkRbHRBRERERH5gJIjwF9vA2vfB6pLgW4TgEn/BhL6qH0uiIh8FMsjEBEFqLX7C3HRm39i/YEiWCxAblk1nv5hOx78ahMKyqs9vXtERERERM0rzQI+mQr88QJQVaxm2u79FXjnZCBvJ48eEfk0Bm2JiLyFqQYoOgDsWgxs+gLI3QlUFLrkoXJKq/DIws12xxZvzUF2CYO2RERERNQO5XlA9iZg4zxg71Kg+BBgNrvmUB7dBmRvtF8uYfEjQGWxax6XiMgNWB6BiMgb1FYBmcuAeVcBtZX124dMA057HIhIcurDlVUZsS+/wuH4uv2F6J8a5dTHJCIiIiI/V5IFfHkjkLm0fltoLHDFAiB1KKBxct7Y9m8cj+39DagpZX1bIvJZzLQlIvKWWlyfXWYbsBV/fwJs+QpK/QIn0mk1aK7fWFSoHm5hMgLFB9Xla0UHAWONex6XiIiIiJyfhLD0P7YBW1FZCHw0BSg57PwjHhbveCw4EghyU8ijogAo2Avk71YzjYmInIBBWyIibyBZAmaj/TGp0VV21KkPFxdmwMR+yXbH9NogDO0UA5crywVWvAy8MRZ49Xjg9ROAX58ESp37uxIRERGRG5TnAH9/bH9M6s3mbHH+Yw680PHYcdcC4YlwKSn7cHQL8OmlwMvDgFdGAB+dDxxaq5Y+IyLqAAZticjzjNXqFWnp9hqo5Kp8cw0WHAV02ykiRIcHz+qH9JhQm+2SffvypcOQFBkMl5KM4j9fBX55XJ3Ei5pyYMVLwE8P128jIiIi8hVSP1XmtLKSKFDn9HJzRGrbOltUGjDpqabbUwYDI68HtC5ePVa0H3j/dODgX/XbpMburDOAgn2ufWwi8nusaUtEniMT2sJ9wKq3gH3LgfAkYNxdQOoQICwusJ6ZbicB6z60P5YyBNDZBledoUt8OObfNBobDhVh2c48dIoNxRkDU5AaHYIQvRYuJZnDK1+3P7b5c2DCP4GQaNfuAxEREZEzlOWoQTu5IC1JCH3OAoZdAcR2Cazjqw9TM1vLc+2PSyDV2WS+OPxKoOepwKb5apmC/ucASf2AyFS4lMkE/P2Z/cQTybKVFWVn/hfQO38eT0SBgUFbIvIcWSIlV6br6rhuU2tgjbsHGHcnEBJAjbA6jQIiku2XQZj0BBDeTL2uDkiNCVVukwe6eFLbWGWR4yVjUr9Xsovje7h3n4iIiIjaU+7p+3uBrV/Vb5Pl8mveBa79ObDmMxIkPflB4Ns7m44lDwRiXBTElsCt3E59GG5VWwZkLnE8vv8PNaDLoC0RtRPLIxCRZ5TnA9/c2bTxlvj9OafXcPV6MRnAjO+BLuNsl3tN/QhIHQa/09LkNTiAAvZERETku2TVWMOArZVkfEpTrtoKBAyNBuh/rppdGhqrbpNGYP3OAS77DIi030/BZ2mDgcg0x+OSkKE1uHOPiMjPMNOWiDyjqgg4ss7xeN4uNbAn2QsiIhGISAG0fvxnK6EncOkcdZIvWaiSMSAZC0FB8DthCUD6CODw2qZjsV2BiCRP7BURERFR22ye73hs548oLn8aeTVmlFTVIipEj4QIA6LD/DiQFxYPjLgW6DMZqC4DdCFAeAIQHAm/ow8BRs8EtiywPz7ubiDUDc19ichv+XH0g4i8WzOByAEXqBm4b44DKgvVbXK1/txXgB6nAIZw+C35Pa2ZCf5Myj1c+J7aXbcws367BGsvmwtEpnhy74iIiIg6tnhVH4as8+fj/gW7sHRnXt3mE3sl4D8XDlbKU/ktrRaI7oSAEN8LOO1J4OeH1RJfVqNvUxMUiIg6IMhiafiXxbuUlJQgOjoaxcXFiIriUlkivyLZpJ9cAhxa3bSBwcWzgE8vtZ34CMk4vXE5kDLIrbtKLlSSBRTsBXK3A3HdgYTeQHQ6DzkR+dX80Bf3mYha6dAa4N1Tm2wuGvcI7tg/Bkt3FTQZk8DtK5cNQ4w/Z9wGEskoltJu0ozObAI6S6+KJDbVJaIOzw2ZaUtEnhEWB5z9IvD+JKCmvH671MHaOK9pwFbItj9eUjNuWdDfP0SlqreuYz29J0RERERtJ2WdBl8KbPzMZnN+5zOw9Od9dn9k+a485JfXMGjrL4Ij1FsgNZ0jIrdg0JaIPCepH3DT78DaD4DMZeoV6dG3Al/d7PhncrYBNRUM2hIRERGR50m91klPAAMvBFa+BlSVKEkIpcHSdMt+0FaUVNa6dTeJiMj3MGhLRJ6j0apL4k956FijAoPaYTapP5C9yXGg1xDm7j0lIiIiIrJPEg96TwK6jAZMRiAkClH5lc0eLWlKRkRE1I6q6UREbqTVA2GxaoMxKXsw5ja1fm1jsm3sHcyytSrLAY5uBQ6uBvL3qJkdREREROQZwZHqnFajRXy4ASf1TrT7bVLTNj6C9WwV0ny4cL9aGzhrA1ByxH6ZNCKiAMRMWyLyPpJ9e8kc4OtbgcpCdVtIDHDeq+oYqUHauVcAOVvVoyEZykOmAac+AkTKcjwiIiIi8pToMAOevmAQHliwCUt35toEbP9z4WDWs7U2Jt7wMfDrk4CxSj1AkanAJR8AaSMALcMVRBTYgiwW772MxU67RAFMlpaVZQPluerVdll2FpHCyZuQDIT3zwCK9jc9bpKlfMrDgC7Y/c8ZEZEb+OL80Bf3mYico6iiBvllNSipqlVKIkiGbUwYs2wV278DPpvW9KDJyrub/wTiuvFlSER+qbVzQ166IiLvJFfWozPUG9mSJWT2ArZi9bvAyBuAmM48akREREQeJgFaBmntkMSM355yXDJh+7dqMgIRUQBj0JaIyNcU7HE8JpPc2gp4k+KqYhRWF8JoNiLSEImksCQE2atZTERERESBwVgD5O92PH54HbyJ0WTG0dJqlFXVIlinVTKmI9lMjohcjEFbIiJfE9/T8Zg+TL15iX3F+/DIH49gfe565evE0EQ8cMIDGJU6SgngEhEREVEAklJeCb2B7E32xzOOh7coKK/GV+uP4MVfdqKk0ghNEHBa/2Q8cs4ApMeEenr3iMiPaTy9A0RE1EaxXYBYBzW+TrgRiPCORmRZZVmY8eOMuoCtyK3Mxd1L7sa2/G0e3TciIiIi8qDwBLUPgz2SgNBnMryByWzB95uy8e9vtyoBW2G2AIu2HMV1H6xGbumxBmpERC7ATFsiIl8jXXWvXADMmwEUZAJDpgLpxwNh8UDaUK9pQrb26FrkV+XbHXtu7XN4c+KbiA2Jdft+EREREZEX6DQSOONZ4JfHYUnqj9xBN8AUkYrQpG6IiU6FN8gpqcLzi3faHduWVYqDhZVIjAxx+34RUWBg0JaIyBfFdQeu+AIozQaWPAOsux0IjgCOuxYYMQOISvP0HuKvrL8cjm0v2I5qU7Vb94eIiIiIvEhoLHDc1cjtfSkWbc/Hm0v3I6ekHEM7H8T9Z0Sgb0okwoI9G7IorzGhoLzG4fi2IyUY3plJCETkGgzaErlCbRVQdhTI3a42hUoeCEQkASHRPN7kPOV5wLsTAeOxZVny79JngZ0/AtPmqhm5HtQt2kEJB0BpRqYN0rp1f4iIiKiNynKB0iNA3m4gMgWI7apeGGZDUXKSwuogPPVTJr7acKRu26rMQlz45gp8cPVIjO+d6NFjHazTKLdqo9nueHosa9oSkeswaEvkbDXlwO5fgAXXAcZq21qj4+8Fwp0w8TAZgbJsNcvSbFSDcxIU1nvBpKH0KFBVDGh0QFisegWdnK+6FPjl3/UB24ay/gaObvV40PbULqfilfWvwGhR6381dP2g65EQmuCR/SIiIqJWKD6slmI6tKp+m8w3r/gKSO7vnMBtZaF6Ebo8V01uCE8CIjwbpFN2q9aIvNIaVBtNCDPokBwZDK2W7WBcIae02iZga2WxAA8v3Ix5N41GkgfLDyRGBuOiERn4+K8DTcaiQ/XolczGukTkOgzaEjlb8SFg3nTA0uhq7F9vqV1QB13c8SzefcuBL64DqorUbVLD9LR/A4MvBUJj4BE1FcCh1cB3dwH5e9RtXccBZ7+gdoYl56oqAXb/7Hh88wKg56kePeop4Sl45ZRXcPfSu1FprKzbfkHPC3Bq51MRxCwdn1NlrIIFFoTqvOACERERuU51GbD4YduArSjLAeZMAa5fAkSnd+wxSrKAb+4Adi2q35Y8AJj6MRDneLWOq2UXV+KFxTvx5fojqDGZEROmx50Te+HcIWmIC/eOvgH+5O+Dx85n7NifX6E0/0ryYFw0RK/Fbaf0wr78cvyxu75XQ2yYHh9ecwJSo1jP1teYTGZUGc1KBrWOF2MokIO2y5Ytw3//+1+sXbsWWVlZ+PLLLzFlyhRXPiSR5234tGnA1mrZf4FuEzqWQVB0APh0KmA21W+TjN4f/gkk9gW6T4BH5O4APjpPvSxute934P0zgBuWADGdPbNf/koCnoZwoNJBjS0vyHAO1gbjhNQT8NV5XyGzOBNltWXoFdsLCSEJiAqO8vTuUcMTcLnootWpGU46Q5Njk1uRiy35WzB3x1yYLWZc2OtCDE0aqpS5IAoEnNNSwJHM161fOf7cKNrfsaCtNSjcMGArjm4BPrkEmP4tEJkMdysoq8Gdczdg5d6Cum1FFbV47OutMJosmDGmK4M8ThYerG12uqvXOiGju4NSokPwymXDcLSkGntyy5AQHozO8WFIiQqBRuP5/aNjiU3yd8tiAgwRQHjTFX01RhMOFVbis9UHselQMXqnROCKE7ogIy4MoXqWbaMADNqWl5djyJAhuOaaa3DBBRe48qGIvIMEUvN3OR4vOQKYazp2/+s+tA3YNiQNqVKHuD9gJ+UQfnncNmBrVZGvlos47mr37pO/kzIbI64Gfn/e/viQqfAGeq0eaRFpyo28TFWpmkH14/1A3k71IoC8pkbfCkSl2gRsH/z9QfyZ9WfdthVHVmBgwkC8OOFFJIe7/6SayN04p6WAU1vpeL5pndN2hARXtiywPyafSaVZHgnaHi2tsgnYNvTyL7sweVAK0mPC3L5f/mxQRowSmK01NT2POLFnAmLDml5M9gTJspZbv1QmHnjlStel/wU2fqomM8n58BnPqv8a1PerxWLB+oNFuPLdVUoGvfhzbz4++nM/3rnqOJzUO5EXZMgrubQwz+TJk/Hkk0/i/PPPd+XDEHkPjRbofrLj8dShgD68/fdvqgZytjoeL9irXmX0RB3fw2sdj8syfqm9S86j1QPHX6c2uWvspPuB6Awe7Y7UZS45rNbZ82cHVgBzLlBPjq3v4z9fBebPULOojtmYt9EmYGu1OW8zlh9a7s49JvIYzmkp4ARHAs2tiulo6auasuaDwtK3wQN255Q5HCupMqKsivNZZ0uKDMaLU4c1KZEs2x8/byCiQvVOf8xAUFZVi6ziSqXch5QD8FtSZmXOhcC62fX9ZKS/x+wz1cz9YyRL+o5PN9QFbK3MFuCuzzcotZWJvJFX1bStrq5WblYlJSUe3R+iduk9CfgttmnAR2YiEx/rWM1ZbQiQPgLY84v9cSmPcOxqoltJ0zHJhqh28J6VTsPyPeRcsizx8vlA9kZg8xdAaBww9HIgppPnahv7MglUbv8O+ONF9WRR3msTH1ebrUgWqr8FpiXD1p4DK4Gig0qzmYraCny67VOHd/PZjs+UhnOxIZ4vx0HkTTinJZ8XmQKMuxv45bGmY51GdbzZqQSF5QK0qdb+eEfr5bZTYoTjmrWyCl7qm5JzyTE9uW8ifr7rJHz99xHszy/HSX0SMbJrPNJjWUO/rYwmMzLzyvH84p1YsiNXKT9xxaguuPT4TkiJ9sPjKQlNudubbpdyhYseAKZ9DoTFoaCiBtkl9pObpG6yBG3TYvzw+JDP86oWmE8//TSio6Prbp06dfL0LhG1XXQn4OofgfTjbLdd9rkaVO0IjQYYcqnaeKwhXQgw6CLgjKfVCbC7SSdhmdjbI8HqYVe4e498Xn5ZNXYeLVWaM8jktbzaQWaHLGPvfTpwwdvAZCmPMYgB2/aoKAB+ehj49k6gcB9grAL2/wG8fxpw8C/4nZpSNTPfEQncKtkHZhgtjrOKZEyWmxGRLc5pyefJfHL4lcCpj9Vn3MqKsgEXAhe937H+DNa547Crmm6XufLpT6kXoj3w+dIlPgxx4faX40/qn4L4CO9Yqu8r1BqiFdh4qAhbs4odBs3CDDr0SIrAXaf1xouXDsP5wzIYsG0nCdie8+rv+GFzNiprTcgrq8GLP+/CdR+sQY6D4+/Tdi12PCZNsmUlmSxYlZTaZpjMfpyNTD7Nq1LfHnjgAdx99902mbYM3JLPkSBlUl/g8nlqPVcpCxASY1MjskOkoddV3wBfXKPW75GA3fE3qJmWX94IxPUAxt4BxPcCQtzYarXnRHXyvf7D+m2SXTvlDTYha6MD+eWY+cl6bDpcrHyt1QRh2vGdcPvEXkiMZIdal2XZbvys6XY5YfzuHvVCjAdq67mMxtB8hpOcTMs/hgic1/M8rD1qv/zJOd3PQXRwtCv3lMgncU5LfkEa+Yy5VU0MqC4F9KHq54MzVp/ow4CT/ql+Dv39MaANBs5+AagqATbPAzZ9AQy5DOh7pltLPknDqQ+vGYkr3vtLaUBm1T8tCo+c0x8RwVyq31pFFTVK5uwzP2xHRY1aCiMjNhSvThuOgWlRrB/qAmXVtfjfTztRVds0ALn5SAm2ZZcgKSrE/1YFOCIXnORiE4D4cANiwvQ272urEL0Gyf52XMhveFXQNjg4WLkR+YWwOPXmbBJo6XwCcN3PQFUZUHwA+OTi+rpg2ZvUbr8SLB1wAaB30weQTOIn/Vud3B9ao07o04YCEcnqJJ9a5WhJFa56fxX25VfUbZMrwx/9dQCRoXrcObEXDDouzXO6w2scj0lGqjTb86egbUQCMPAi4G87pQ+0BqDT8XVfjk4dje7R3bG32DYzNy08DWd2OxPaY5NhIqrHOS35DZl3StklV5DPVVkldOJdgMkIfHM7cKBBDfUj64BVbwJXfe22wG1QUBAGpEXh+9tPxJ7cMhwuqkTflEikx4TywnkbrT9QhEcW1tcUFYcKKzHtnZX48Y4T0Tnez0pPeYHSKiOW7KjvS9DY1xuO4KTe6oV5v9H3bLWMi73M/JE3qM2bj9VIfmrKIMz8ZF2Tb3v47P7NlkYh8iSvKo9ARG0gtcSCw4Gvb7XfyOG7u4Fyxx/aLhEaCyT2AYZdDgyYotayZcC2TQ4WVNgEbBuavWIfi+S7itTWa47Wq65xOifD6ZSHgMR+ttslO37qxza1ClPCU/DWaW/hnhH3oGtUV3SK7ISZQ2Zi9hmzkRrhpBUEREQUmOQif1x3IG+HbcDWKn8PsGle803LXBC4ldqWJ/ZKxKXHd8bQTrEM2LZRQVk1/vfTDrtjknW7eJubz1EChPRyCzM4vpgeHeaHmeJRKcCUt9TVro1rb0vT5mOlA3VajVIr+auZY3FKn0TlQszYHvGYe+MonD04FcGsV01eyqVnoWVlZdi9e3fd15mZmdiwYQPi4uLQuXNnVz40UeDU4Sw5Yn+stlJtJiTlFMhn7MtX6y45muRal5eRk6UOcVwuoNsEtbaev5Gspau+BPJ2A/t+V5u+dD1RDdg2qpstgdurBlyFc3qcAwssiA2OZYYtBRTOaYlcqKYCWDPL8fj6OWqj1WOle8j7VRvN2J1T5nB8/QFp2NzNrfsUCOIjgjHthC547bf6GExDFw53X6kRtzFEqNm2t65Tm3WX5wM9JqgXgxr9zYgI1mFopxi8fNlwVNQYlSZ4UaF+GMgmv+LSoO2aNWtw8skn131trVc7ffp0zJ4925UPTUTkk7rEOV4qJvWWmrt6TvaV15SjpKZEST+ICY5BqM5OuY6IFOCCd4D5V9sur5LJ3tnP+W9zNwnQyq3biS1+qyZIg/jQeLfsFpG34ZyWyJPY8NLXGHQadI0Px46jpXbHB2ewHn5bSePXnNJqGE0W5fgmRjZdzq/XanDFqM74ZdtRbM+2Pfa3ndJTyS71S7L6NLg7EN+9Vd8eEaJTbkS+wKWv1AkTJrCrNJErSc3cqDT72bZSlsBVNcjIZTrFhSlNGqTmV2NXjOqCJDYiazWzxYz9Jfvx4toXseTQEiXoKDVYbx5yMzIiG2UaSO3nXqcDM1cBG+cB+buBXpOAruP4PiIizmmJXMkQBhx3tZolZ8+wK4EwXjT0tYzPeyb1xg0fNW1kGqzT4PQBzTSPoibyy6qxaEs2Xv5lN7JLqtA1Pgz3nd4XY3rGIybMYPO9qdGhmH3NSGw5XIxv/j6CmFA9Lj6uE9JjQ5t8LxF5vyCLXLLxUiUlJYiOjkZxcTGioqI8vTtE3kfevnuXAh9f0LTW13mvAwMvdF8jMnKazLwy3PDhWuw6tqxMSjSdPywd90/uy6BtGxwoOYBLvr0E5bW2JScSQxMx58w5SItI46vWF5UeBcpzgZpytbO5ZEO3VJOY/Iovzg99cZ+J3Ko0G/h8OnBwpe12WeI8/Ru3NSIj5yksr8Hnaw7i+cU7lXIJQrJD37h8uLJEXWqMUsvKqmrx4s+78O7vmU3GHju3Py4/oTP0Wq7E8zWVNUbkltUgt7QKwTotEiKCkRwVrNTUpsBQ0sq5IXPCiXyZ/FHvPAq46Q9gxatA1gYgvgcw9g4gvjcDtj6qW0IEPrl+FArKq1FebUJcuAHxEQZEhrDmUmtVm6oxZ9ucJgFbkVuZi98O/oZpfadxYuRrcrYDc6epjWlEkEbNwDrlQSAi2dN7R0RE7RWZAlw8G8hcBqx+BzAbgSGXAX3PYsDWR8WGGzB9TFecOSgVuWXVMGg1ynw2JSqE8682yCuvwft/NA3Yiv8t2onT+iUjPTbMWU8buYGc481esR9vLNmNWpOaQykB27euPA6D0qOh1TBwS/UYtCXydZJJm9QPOOs5NfNMyiLIMjPyLWVHgeoyQKNTsgcTI8Pt1qqi1imtKcXyw8sdjv+8/2ec1+M8REjzAvINxYeBD89V3ytWFjOw7gP1ZH/8vXUdgomIyAdFpQJDpgK9T1f/vofGNu0IT95NGiHLahhp7GoIR0hkilL6S27UPllFlTA7WBtdVm1EYUUt0mN5dH3Jkh25ePmXXTbbjpZUY9o7K/HjnePRme8XaoBrEoj8KXgbHs+Ara+RQO2e34DZZwGvDFdv39wFFB3w9J75NG2QFlF6x8tMpCGZXsMAn0/J22EbsG1o5evq0loiIvJ90vxT+jYwYOt7F1d/+Cfwygh1Pvv+GcD274GqYk/vmU8LMzSfZydNych35JRWKeUu7KmoMWH5zly37xN5N77DiYhaQcp/ZxVXYvPhYqzdX4ADBeWoqDF2/NhJSYuPpgB5xz68ZTngprnAR+cDJVl8btopNiQW0wdMdzh+eb/LEaxjJrNPsb5H7KkuBYxV7twbIiIin1RaVYt9eeVYs68A27JKlCBSx+/0KPDZNHX1i6lG3VaYCXx2GbD/j47ffwBLigxGQoT9BmJ9kiMRH87mYr7EaLLgQEGFw/EtR0rcuj/k/VgegYioBUaTGZsOF+PGj9Yip7Ra2abXBuG2U3riilFdEBfezuBfeR6w6F/2x/J3Azlb1KWC/sRYA2i06s3FRqaOxKmdT8UvB2y7UUst2x4xPVz++ORkiX0dj4XEALpQHnIiIqJm5JZW478/bse8dYeUfsaie0I43r7qOPRM6kDJKAnQSiKCPYseBNKGq6WM/IXZDJhrATckACRHheDtK4/D5e/+hcra+sbTsWF6vDJtGOIjmITgS+QcUt5ze/Oa9t0QQzpFu32fyLsxaEtE1IIjxVWY9o7tREmKxj+/eJfSNOycIWntO4a1FUDW347H9ywBek70nyVz+38HNi9Qa9Qdf53aEVqWP7pIQmgCHhn1CK4deC1+2v+TUg5hUtdJSAlPUcojkI9J6KU2oyk+1HRMmi/608kgERGRk9UYTfhgRSY+X2v7OSrBo8vfXYmvZo5FanQ7L4AeWOl4rGCvOuf1B1WlQNE+YO1stZRZr0lqDeaYzi57SI0mCIMzorHorvFYsTsP27NLMaxzDEZ0iUUGG5D5nMTIEPzj9D645eN1TcYig3UY0yPBI/tF3otBWyKiFizZkWMTsG3o+cU7Map7nPIB3GZBWiAk2nGtr+h0my9rc3JRe/AgqnfthD4jA8E9ekCXkuL9HXiLDgIfnKNmYVj9/Skw5nZg3F1tD9xKk4u6pnvhzX5rXGicchuUOKidO09eIyoNuGohMG8GkL1J3SaNx0beBAy7EtBySkNERNRclu2sP/bZHZMmSHtzy9sftJXPaEd0IUCDPgIV1UbkllVj/YEiVBlNOK5LLBIighET5uXL/GvKgC1fAN/cUb9t10/AkqeBa34EEnq3/T4rC4813Wu+hrNOq1GaU3Ue6brgMLnP6O7xeOisfvjfTztQVWtWtnWJD8Prlw9HegxXjpEtnuEQEbVg8yHHDRT255crtYnaJSIJGHkjsOw/TceCNOrV+2NqDh/GwetvQM3evXXbtLGx6DxrFoL79PbewK2xGljxsm3A1kq2D7649UFbCdYWZAJ/vARk/w3E9VCDvjJJDnHcdIz8SHxP4IovgYp8NWtHTnIikwA9u1ITERE1p7LWjPIa+0kIIjOvHGN7tjPLr9NIQGuor2fb0NDLgfDEunq63/ydhYe+2gRzg+nzFSd0xl2n9fbupf5lOcC3dzXdLnOS7+8DLp6tNtFrDelbsedXYM27gMkIDLkU6H+euqKI/F5suAFXje6CMwamoKC8BgatBnERBiS1JwmI/B4bkRERtWBo51iHY90TI5Sr3+0iWYLHXwt0Hd/oL7MOuOTDuqwFU3Exsh55xCZgq2wvLMTBG26A8ehR730OZSK74WPH4xvnt+5+pPDa/j+Bt8YBGz8DcrYB278F3j0V2PY1UMsmVAEjIhFI6gukDwfiujJgS0RE1AqhBo2y/NqRnokdqGkbmQZMm9u0xmvaCODEewC9Gow6WFCJf31pG7AVc/46gJV78+HVDq5Ss2Lt2fubmjXbGqVZwOdXAQtvAQ6vA7I3qj0uZp9tvwQU+SWDTquUtxicEYO+qVEM2JJDzLQlImrBib0SEBGsQ1m1scnYvaf3QWJkB7ICpA7nxe+rJQSku254AtBplLpdlv9LsmpBISr+WGH3x405OTBmZ0Of4qX1PCXYKtm2jtTaL8Jvd4Irk1uznQyR7/8BdD0RiO3S/v0kIiIi8mOSxXfD+O54bvHOJmMZsaHomtCBVSs6A9BlHDBzNXBoFVCaDXQ6AYjtqq4sk2QDkxkf/mm/PIN4fckejO6RgLhwLy2T0FKCgMVxFnOT4K8co8ZkVdrGz9U6/W5o2EtEvoFBWyLybdXlgKkaCI4GtK6Z4Ehtoc9uGKUUjD9QoDZSCNVrlYDtCd2c0EhLlozJTTIH7bBUNT9JNBYVwWtJ2YLeZ6hZsfYMuKB191NRoAZuHZVNkMwEBm2JiIjIF5lMQHUxoA0Ggpuv199eeq0Gl53QGUWVtUrwVJrqigFpUXht2nCktLeebcPArczFHMzHas1mHCmqdPjjOaXVqDU5yGT1Bp1PcDyW1F/tU9ES6ckgTcwckdVpw66oC3QTETFoS0S+qTxPXU604hV1OVLPScCwaUBMl2YL+be3a+vA9GjMv2m0UneoxmRWsgCSIoOVpS2upomKRFBYGCwV9jvvGjI6wWsFRwKnPqIuG5OJakOSHZvQ0zmP4601fYmIiIiaW5FUuF8N1u1erNZqH3MbkDIYCI93+nGThl/3TOqN6aO7KMHbEL0W8eEGt9SSDdZpMb53IpbtyrM7Lg3JZGWb15JVcMOuAtZ/aLtdsmLPfqGubm/zZL7azJyV81kiasSL/yoSETlQUQgsfRZY9Xb9tiPrgVVvAdctbl/31lZIigpRbu6mS0pCwo03IPeFF5uMRZxyCrQJzp/UO5U0DLthGbD8eWD3IiA4CjjhZqD/uUBEcuvuQ5qVRaUDJYebjkkTKjZuICIiIl+Ttwt47zSgqsGqqT2/ACfcBJx0PxDmuK9Ce4UZdOgcr0NnuJc0zT1jQApe/W03iipqbcZ0miDcMbEXwr05aBsaC5z6MNDtROD3F4Cyo2pJs5P/pTZKbQ1DGHDcNepzbM/QK4GwdjaDIyK/FGSxyOU971RSUoLo6GgUFxcjKoqdwYnomKNbgDfG2D8cvScDF7ytLsv3I8aCApR88w3y3ngTpqIiBIWEIObiixB//fXQJ/nIEqraCqCyGAjSqMu+2pJNIB9V+5YDH50PmBvVFpbnu/+Ups0v3EF+n4pcoDxXDUaHJQKRPvJ8EPkoX5wf+uI+E5GLVZUAX1wL7PrJ/vjNfwLJ/f3qaZDQw57cMjz81Wb8ubdA2dYnORJPnT8Qg9KjEaz3kVquMu8zGYHgCHVVWVtIvd/516i9LBqSwO9VXwPR6XA7s1ktQ1aeAxhr1KxiyRyWIDMReXRu6MWXsojIaUqPAqYaQGsAIluZ2ejNdi5yPLZrkZqt4GdBW11cHGKvuAKRkybBXFmJoOBg6BISoAn2QKCyvSQjVm7tIQHejJHAzSuAlW+omdXxPdRmDZLJ64mArUy6f/wXsOWL+m2JfYCpnziv7AMREREpyquNKK5UMzRjwvRKxqhPk/mqlERwRIK5fha0lWzbnkmReOOKEUq2rdliQVSoXinb4FNaVQrBAQmIXvQesP9PddWguRYYegXQa5JnArZyjnhwNTDvKrX8nJBzxgn/AkZMV1e7EZHH+PgnHRE1Sz54dy0GlvwfUHQAiOkMTHgQ6HWaS+pkuU9zCwQszQ/7sCCtFvrUVAQsfYgaFJ38rFofVx+q3jzVQXj5C7YBW5G7A5hzAXDNj0BUmmf2jYiIyM+yM/fll+N/i3bixy3ZyjZZZv+P03ujW0IE/Jb3LojtsJgwg3ILWJGpwMALgJ4TAYsZCI3x3L5IM9855wPGattA7i+PqfPuvmd6bt+ICBoeAyI/VVMBrH4P+OomNWAr5N+vbgTWvA/UOu7e6q3ZFQcKKrAnpwxGaTrmiEx+PDnxIdeTrFq56u+pgK2QOmbrZtkfK9pf/54jIiKiDjlUWIkLXl+B7zZlwWS2KDf5f9l2sMB+k1avVpIF5O1Ug7I9TnX8fb2bme+Sf5CVgZ4+b9nypW3AtqHfnqrPviUij2CmLZG/klpLy/9nf2z5f4HBlwCxXeALDhdW4OkftuOHzdnKRP3/zkjHJcOmQ7f+A9tvlJqik57yu9IIDRmLi2EqKIAxNw/aqEho4+OhT+zAEi1qf31eRxNcUbgP6DyKR5eIiKgDTCYz5q89hMJGjauUj9qKWixYdwi3ntwTWq3GN2rYZi4DfrwfKD4IhMUDl3wIHPwLqC61/V5pViXZmH7KaDIjp7RaudUYTUiJDkVChMH3S174Gqllm/W34/GCvc3Pd4nI5fhXkbyHsQqoyK/vztne2pfUoEB+jYNjXa2O+0DQ9mhJFWbMXo1dR8vqtj246DCCz7wGZ11yJkJWvQJUFgI9TwNGXK2WgPBTtTk5OPrEkyhdXF//zNCtGzLeeB3BXbt6dN8CjiFc/RslwVt7pM4uEREFprJjczCtXm28Se1WXGXE4q1HHY7/tPUorhrdFbHhPrDU/tBqYO7l9V/LeY8EcC/9RK1fu+dX9Rxo7J1A2jC/rSUqQdo1+wpxyyfrlLq2Qq8Nwt2n9calIzsjNpDLJribRqP2jNi60P64lEeQ8mRE5DEM2pJ3KNwP/PEisPFzwGIC+p8PnHQvENutbR3mqV5LjZk80bipHTLzym0CtkJWk93z3WF80jkGH1z+ESJ0ZiAkWj058lPSfCzvtddtAraiJjMTB6+9Dl0++Rj6ZD9oMucrIpKBkTcCf7zQdCyhFxDTyRN7RUREnlRRCBxcCfzybyBvhzqPPflfQPcJalYltZkE86JCHZ+yShMrvS9k2Uog/6cHm27P3gR8NAW4+ic1WCsNoPx4xZg4UlSF6bNWodZUX7NX/v/ZH3coTcpO68/5rFv1PVvtfyL9Iho75RH+7SLyMB/4hCO/V3QQmHWGWme1pkyttfr3J8C7p7IuZEeEJQAxDjJpY7t2rOupG63bX+hwbO2BIuQZg4HwBL8O2ApjXj6KFyywO1Z7+DBqjxxx+z4FNLnoMfpm4PgbAE2Dk8mM44DL56udgYmIKHCYaoHN84FPLwVytgJmE5C/G5h/DbDqHbXXALVZZIge15/Y3eG4jEWE+EAekrESyNlmf0xeK9u+Vuezfh6wFV9tOGwTsG3oxZ93oqCMy/HdKjoDmP6t7XljcCRw9ktA+nD37gsRNeEDn3Dk1yRlcvu3QImdgFNFAbB2tpqh4OcBOZeISgWmzgFmnwVUl9jWfb3kI58JKmXEOm42FarXQi/LegKAubICltqm9dysag8fAYYNc+s+BTzJtp34GDD6FqCyCDCEqRdLwplNRUQUcEqzgJ8fsz8mPQaGXAoYWMqoPYZ0isGFw9PxxbrDNtsvGp6BwRnR8AlBOiAkBqgqsj/uAyXLnMFkNmNbVoPzkkb251eg2mR26z4FPK1ODc5es0gt2WGuVeezkclq5jcReRSDtuRZEkyUjpWOSEB31C1AhG9khXqd5IHATb8D+/8AsjYCqUOALmOAaN9Zuj2scyyCdRpUG5tO4Kad0BmJkYExmdCEhyMoJASWqiq744Yu/lvL16sFhwPB3Ty9F0RE5GmSbCArxhxl4UpQV1Y6UZslRATjwbP6Y8aYrvh+UzYQBJw5KBXpMaGI84VatkJqG4+6GVjydNMxSU7pcQoCgVajwfDOsVi0xX6d4l7JEUpSBnko4UduRORVGLQlz5JlxbL8whFDBKDhB3f7j69GvXIvt6HT4ItSokLwwTUjcfWs1aisNdVtH909TlkSZ9AFxutDl5iIuCuuQP677zYZC+7VC7oU38icJiIi8kstrQrTsZlPR0hwVm6DMmLgs9mMI2YAh9cBuxbZvi4u/RiISkOgmDwwFS/9sgsVNfXzeqt7T++DGDYiIyKqw6Ateb4Du1x13v2z/fHRM/22cyq1jl6nwXFdYrH47vHYnl2KvNJqDEyPRmp0COIjfKOZmjNoDAbEzZgOc1UVCufOBY6VSgg97jikPfMM9InMRiciIvIYWU4c1x0o2Nt0TPoISKYlBTYpTTbldTXr+vB69RwnZRAQmQrofCRj2AnSYkLw6fWjcNun63GgQK31HBWiwyPnDMDANB8pd0FE5CZBFosUFfVOJSUliI6ORnFxMaKi/L8oe8BSuqk+BGz8zHZ779OBc15R6+kQkcJcWQljXh5MJSXQhIVBGxsLXYyPZp0QEQXI/NAX95naIevvY70ESm0zKa9aCGSMVFdAEZEip6QKBRU1MJosiA03IDkyGDot3yNEFBhKWjk3ZKYteZ7Uqz39KWDk9cDfnwFmIzB4KhDfg1kJRI1oQkNh6OQ7NYmJiIgCRvIg4KY/gN2/AAdXAamDgT6T1V4CDNgS2UiKClFuRETkGIO25B3CpeN6ApBxnFPurqiiBvllNSitqkVUqB7xEQZEhwbOsiMiIiIi8lAvgeOvUW8dZDSZcbS0Gvll1dJ7SykLlRwVAq1GviIiIiJ/x6At+Z0jRZW4b/5G/L47r27bKX0S8dQFg5AaHerRfSMiIiIiakl5tRFLd+bi/gUbUVJpVLbFhOnx3MVDMKZHPEINPI0jIiLydywa0wJzba1SP9JYWOieZ4Q6pLC8BnfN3WATsBW/7sjFIws3o6RSbd5EREREFFAqi4DSo0BNpaf3hFphb145Zn6yri5gK4oqanH9h2uw/1jzJiIiIvJvDNo6IP3Zag4eRO7zL2Df5Vfg4LXXoWjh16jNzXXvM0Rtkl9ejb8yC+yOLd6ag7yyah5RIiIiChzl+cDOn4BPpwKzzgC+uwfI3QGYajy9Z+RARbURb/y2G/baRZstwKzfM1FjNPP4ERER+Tmuq3Gg9sABZF4yFebiYvVraQj7z38ifPx4pP3fU9AlJLjzeaJWkgyE5pRW1WcrEDVhNqn/arQ8OERE5Psqi4EVLwF/vFS/rWAvsHkecPUPTuslQM5VUWvCjqNlDse3Z5eiosYIg479GsgBUy2g1fPwEBH5OAZt7TBXViL3tdfrArYNlS9bhpr9+xm09VJS66s5kSF8yZMdslz06GZg3YdqwHbEDCCxLxCRxMNFRES+q/yobcDWSrJsv70TuPIrtREseZUwvRa9kyOwJ9d+4LZPSiTCWNOWGjPWAMUHgY1zgexNQPpxwMDzgejOgJbnQEREvoh/ve0wFRejdNEihwet+OuvETZihCufF2qn+PBgnNAtzm6JhIn9kpAQEcxjS7ZKs4EFNwCZS+u3bf4C6HMmcPaLQGQyjxgREfmmg6sdj0lQR+rcMmjrdcKCdbhlQg/8sDm7yZgmCLhmXDcYdKxyR41Wix1cCcy5sL70yY7vgWX/AaZ/A3QaycNFROSD+GnvQJDO8fLoIB2Xmnir2HADXpg6VOmq29DJfRLxxJSBiArlc0eN7F1iG7C1konukbU8XN6cTVJ0EMjbDRQfqi9tQURE9VrKrgsK4tHyUt0TI/DqtGGIarBKTFaUvX3lcegSF+bRfSMvTUKYN6NprWpjFTD/GqAky1N7Ri0oKK9GZl45DuSXo7iCtcaJyBYzbe3QxsYi6txzUfTpZ/aGEX3euXa3k3dIiwnF65cPR35ZDUqrapVAbVy4ATFhrPtFjVQUAH+95fiwrHwT6DoeCI7gofO2E5OVbwCr3wFqyoGwOGD8vcCgS5gxRkTUUPrxQJAGsNhpWpUxEgiN5fHyUuHBOpwxIAXDOsciv6waQQhCQoQBiZHB0GmZd0ONlOUAFfn2D4uUTKjIA6JSedi8SI3JhK1HSvHQV5uw+XCJsk0Sjx4/bwB6JkYgiBfViIiZtvZpgoMRf9110KWkNBmLvuAC6DMy+OLxchKg7ZEUgaGdY5VMBQZsyS45iTVWOj44MmZm8zqvIkt5Fz0I/PGiGrC1Bt9/fABY/S5QW+3pPSQi8h5Sm33Sk023B0cC57yoXvQiryXB2fSYUAzOiMGgjGikxoQyYEv2mZtvxsz5rPfZn1eBS978sy5gK1bsycdFb/yJQ4XNnJ8QUUBhpq0DhvR0dP3kE5T+9htKfvgB2ogIxE6/CiF9+kAXxwmutzMWFsJSWQVoNUrTuCCt43IXFMBCYoEBFwA5T9kfl8zNkGjnPFZtJVB2FKgqAQzhQHgiEBKFQFVjNCurcvVtzRYqzwU2z7c/JoHcoZcBMV2cso9ERD5PVooMvRzoPAr483Wg5DDQ7SRgyKX8W+kDaowmZeWY5ElHBGsRHcpVY+RARDKgCwaMdi5eB0cBYc5rOJhXWo2CihqYzBalZEdyZAg0Umw5AJnNFtSazEqN6bZkxlbUGPH6kt2oMTVdBVFcWYvvNmbhhvHdA/a4ElE9Bm2boU9LRey0y5RyCEE6HTQhIc19O3kBU3k5qrZsRc6zzyj/amNiEDdjOqIvvBD6xERP7x55Gwnmy4nrmvfUJfcNSeCvz2Tn1PuTJWsrXgFWvaVOpuU+e50OnPUcEB1YmftHS6qw8VAx5q4+AINWg8tHdUHv5EhluWeryBK/5gLjlcVAjNN2l4jI94XGAOkjgCmvq/XADWGAhhezvV1WcSXe/z0Tn/x1AOU1JozqHoeHzuqP3skRMDTTe4MCOKv+1EeBRf9qOnbG00Bk0xWkbSVB2m1ZJbhz7gbszilTtiVGBCt9Q8b1SkBEcOCEFqpqTThcVIm5qw9iZ3YphneJwXlD05XM+NaULymrMmJVZqHD8aW7cnHl6C5KmRQiCmz8K9ACuWImWbbkGyrXrcPB62+o+9pUVITcF19Cxbr1SHvmaWZJU1MxnYFrfgL+ehPYNE+t/SdZScdd45yAqgRpJbtpxcv12ywWYOePQHkecNlnQEQ7LiiYzWrGVP4uNeCc1B+ISm/ffblJdnEVbv54LdYfKKrb9v3mbJw+IBlPThmIxMhWXBgLaSEiqw91wp4SEfkhycKTG/nEBc5rZq/GtqzSum0r9xZgymt/YOHMsRiQ7qRVQOQ/ZP4zdBqQ0Bv47f+Agr1AYh/glAeB1KGAtuPNmCVIOfWtP5WLCFa5ZdW4ac5aLLh5DIZ3aV+N7KKKGuSWVmPT4WJEhujQNyUKyVHBXntxwmgy48+9+bjugzVKIFss2ZmL15fswWfXj1LK87VEVppJjWo5pvakRIW0fTUaEfklBm3Jb9Tm5iL7SfvL3MuXLYPx6FEGbZ1MJlhl1bXQaTRKszefvRoc2wWY+Dgw5nb16/AEp0xuFRJQXfWm/bHDa9TxtgZaJWCbtQH46Hygqj4AiowTgEtmA1Fp8EY/bztqE7C1WrTlKKaN7IyT+rQiaCuZIhKcloB1Y51GAWHxTtpbIiIiz9ieXWITsLUymi14+ofteO3y4YgOddI8hVBZY0R+eY2yzD3MoENylI+urpTGgr1OUzPrjVWALsSpdau/23jEJmDb0HM/7cDrV4xo8+syr6wa//fdNixYXz+vC9Zp8Mplw3Bi70SE6r0vcHu0tBp3fLq+LmBrVVVrxh1zN2DejaOR1MJrKDbcgJsn9MBNc9bZHZ8xpqtScoGIiH8JyG+Yy8pQu3+/w/GK9evduj9+o7oUKMlSmz0dU15txPJducrV9pP/txQT/rcE983fiIMFFfBZOoPaVVduzgrYipoyddm+I4WZbb9PCVh+NMU2YCsO/QX8+hRQ633Pg3S+/vDPfQ7HZ/+5D5W1rWj6JgHpaZ83PQmJ7Qqc/yab6hARkc9bvOWow7E/9uQp8zBqI1nlJL0FZE7boO5rVlElHvt6C07531JlTnvB6yvww6YsFFfW+O4hljmSzJecGLCVXgSr9zlezr81q0QJfreFxWJRjnXDgK2oNpqV7F15brxRdnElSqrs/6778yuUer+tcXzXOFwxyrYPg1RQe/CsfuiaEOaUfSUi3+ejaXHk9SoL1SCf2ag2cnJCHaWWBOn0gEajZiHaoY1mocs2qalQl94veQY4sk6d/I2/D+g0EnIuceV7q+q+Va40f7cpS1nW9PmNo5ASzSXqdfTHagea7WcmKEHitsrdDlQV2x/bNBc46T41e9iLmC0WZcLviGQnOHjrNpU8ALhxOZCzDcjfA6QMBOJ6tO9YEhEROWIyAWVZ6gVYXajaRFRqArtYfITjMhaRwTqnlNsPKBKo3fIlsOZdoLYK6HcOMOpm5OtTcONHa7DxcEndt8py9Zs/Xoc3Lh+OyYM4r7DSa4PQKykCv27PsXuIM2LD2lzOQFbsvbFkj90xSWL9flMWbj2lF7xNrck2w7axxhm4zb3P/zGpN6aP7oJVmQXQ6zRKIFf6PARSfWAiah7/GpDz5e0Cvr0T2Pe7+nVcd+Cs55VgHwzhLjvi2rhYRE6ciNKffmo6qNcjdMhglz22Xzq4EphzIWA5FkmTZfyfXgrzif/AJpxn90cOFFRgy5ESBm0bkhO8/ucDm+c3PWDS7CyqHXVzS444HjPV2u8c7GGxYQacNTgNr/222+74RcMzWl9eQ85Wpd6w3GQZIBERkbNJ3fnNXwBLnlaTEWQVzqBLgFMecnkZorMHp+KlX3bZHbtyVBckNBPUpUZKs4DPLgeOrK3fJn0MNs5F+NW/YHu22lCrsae+36bUaPXZUgku6PNy8XEZeGf5XiWg2tgdE3sppdLaQoKbOaWO56yZeeXwRmkxoUoQ217wNjZMj7iw1h+HmDCDcuuVHOnkvSQif8HyCORcRQeAWWfUB2yFFMKfc76aHehC2vBwJN13L/QZjYJgGg3SX3geukTvbdDklRPcb+6oD9g2oPn9eZzSKchhlsfyXXmu3z9fEhwBTHoC6HaS7fbYbsAV89uXHZo80PGY1ON14cWR9pJOutNGdlKyBxrrkRiBMT1Zi5aIiLyEyag2J/3hPjVgq2yrBTZ8DMy7BijPdenDp0SH4LFzBzTZPig9CleO7soGRW1x5G/bgK1VZSG0K1/FuQPtzz8OFVaiwkH91kCVHhuGt688DuGG+oxarSYId03sheGtaL7VWIhei0EZjpvqndjLO8/dEiMMuO/0vnbHnpgysMV6tkREbcFMW3KuPUvUzAR7daR+fgy4ZA4Q6rqOt4aMDHSZ8xGqtm5F+Yo/oU9PQ8TJp0CfkgxNMLMSWq2ySA3A22MxI7xoBxIiYpRlTY2lxXCi0oRk5Fw8CyjLUY9reBIQlQJEtnPZXUwnIG0YcMROneaTH2z//bpAbXY2qvfuRc3uPYju2QO/XdUPH+6qwAcr9ysnnVOP64QLR2QglSU1iIjImy5eS3koew7+qS63l5U0LhIZoseFw9Mxrmc8vt+UjcKKGkzsl6wsT2dAqA2kTJsE2h3Qb1+IMyZMx/y/m45JMyzJpqR60hRsfJ8E/HTXeBwsrFRqz3aND1Myv9vTjFiacf1rcj9c/NafTcbkIv/x3ZxXk7ejSitrkVNWrZQxEBP6JOKE7nF4dOEWZaVh35RI3D2pD/okRyiBbCIiZ2HQlpxHClLu+dnx+OG1QG25S4O2Qp+SotwiTznFpY/j14Kar0kVFhYGo8lOFm4QcFp/19cv9klh8eotqV/H7ysiCZj6MbD4EWDrl2q9XGk2cfJDQP8pam1nL1CdmYkDM66G8Wh9QxVdUhKumT0LFx8/TlleJxN9Tm6JiMirSA3bxs0+G5LVY6muLbslgVu53X4ql023nwbQNZNMoAt2WE//gmHpLENhh0GrVTJu5eYM/dOi8P6M4/HIws1KdrMY2zMeT04ZiPQY7+iRUVheg1l/ZOLlX21LfM2c0BNvXDFcTpwQZtAiKtSJjYyJiI5h0JacRwJFsuTbEWlGpnHvS85cXQ1TYaFSzV4TEQ5tVJRbH99nSQAwZRCQvanpmC4YIan9MSj9KJY1KIWg0wTh1WnDlCV95AbR6cA5L6u19Uw1akkEybCVpmeNST1iqTW9azEQkQj0nqy+H6V0Q0Pl+UBFHmCsAkJi1O/RtS9D3ZiXj8O332ETsFW25+Tg8G23o8sHs6FLSGjXfRMREbmUBPqaayLqhga7TZTlqp/PMpeWi7f2Pu+p6bnJcVcDmz63e2Qsw6cjI6MzgnVZStao1ZCMaNw+sZeyfJ9cSzJ0T+mbhAFpY1BaVQudRqNk4EbbCYBW1ppwtLgKv+3IQVZRJcb1SkTvlEikNC5HIKVMJFteSpvIPDY0Xp3/ttOO7NImAVvx2pLdSoB5TE/OZ4nIdRi0JecaOg1Y8ZJaDqGxcfeok0w3qT1yBHnvvoviBV/CUlWFsDFjkPzP+2Do3h0aPa+ENkvqok55A3j/DDXbxEoK2Z77GnRRKXhhaiqyiquwel+B0mRKmjUkRQZzgutOweFAcDMXSkTxYeCzy4CsBmv/Fj8MnPc60O/c+sBt/h5gwXXA4XXq1/owYPw/gOHT1ddDGxkL8lG9y34TlZo9e2AsKGDQloiIvJOUPuh3HrBlgf0L29Jk112qioFDa4GfHgRytqqrdsbeCQyZCkQku28/fFVCL2DwpcDGzxpt74OgYVeiZ3g0fr77JGw6VITs0moM6xSDjNhQJEYyCcGdpOFbc03fqmpNWLIjBzM/XlfXCO3t5ZlKX4QPrx1Zn5VbUaA0mcOvT9afw0giyoXvAYl92rxfFdVGvLlsj8NxGRvSKRrhwTy3JCLXYNCWnEu6uV/4PvDlDepVTqthVzmvy7t8GMsEVgKIkg0YGmO3juaBa65Fzb599T+2YgX2XXwJun7xBUJ69XTOvvizpAHATb+rJyzSWC6uh5qtENMF0IcgXg/ERwRjYLpry134CovZDIvRCI2hbZ1zXcpYA6x83TZgK+SiysJbgIyRQHBPNbD7wTlAyeH676mtAH75NxAaCwyf0eaSC5bKqhbG1SVwREREXttEtHAfcOTYxUxrwPbKr4Co9I4/hsyTy7LVz2rJ7FVWpGmbfl7v+Q2YN71+W0W+evE1awNw5v/UfaLmA/CTngSGXwmsehuoKQeGXAZ0GaP0HJBZW6e4MOVGx8hrUuZ9bl4h2Zyc0mrc9sn6uoCt1Z7cMryweCeemDIAoXodsPc34Mf7bb9JVg7OPhO4fonaF6INJAPbXg8PKxmT7wln6xQichHv+UtM/kGWaPeZDNy6FsjeCFSXAenD1cZLYW3vKtqkk69kGHx3N3Botbqt+8nA5GeBhN5qEPeYyr//tgnYWllqapD38stIfeZpaMPDO7Y//k4ma3HdgHF3AyfcDGiDAS2XiTVmrqhQsroL581H7b59CBs5EpGnT4I+LQ1Bnq4tK92t186yPyYngjt+ABJuU2vzNQzYNiSNWHqfoTZTawNtbCyg0wFGo51BrTpORETkzYkI0+YCxYfU+acEahN6AlEZNnPOdpHGpKvfUy+sVpeoK1pOvBcYdJHt6hZZ4t04AGW1+Qtg/H0M2raGLI2Xm1ystpgAvXfUSvU6JUeAQ2uAvz8B9OHA8depmcrtWHHlbH/tzYexccT2mIUbDuPOib2QocsHfnnC/h1Io2zpr9LGoG1EiBZjeyZgy5ESu+NjesQjoh1N2IiIWot/Ycj5ZCIU20W9OVNhJvDeaWo9Lyu5mvreJODGZXWPJxmPJT/86PBuyv74A+bSUgZtW0tOTAzMPnBUM7ls2TIcvuvuupIgZUuXIu+NN9Dl4zkI6dP2ZVhOJScmklHiSNmxerNygaW572n4nmslXUI8Yi+7DIUffdRkLGbqVGjj49t8n0RERG4lZb3kJgkIzlJVAvz8GLDhY9uA0o//VJufjbuzvnmWrCyTwK0j8vmd1Nd5++bvdF60GsrbyKqrTy4Bjm6u37Z5PjDsSmDiYx4P3BaU1zgcqzVZYDRZgKBq9XzREQlID5jSpsfVa7WYNrIz5qzcj4oa2xrXoXotrhzVFQYdk1qIyHW8o8U4UUtqK4E/XrYfPJIJrmQbHGsWIdmNumYCQkozMk9nQJJfMObm4ch9/2xSw9lcVoasB/6l1G31KEMEkH6c4/Hek9R/43s5/h4pQaJt+0mOJiwMCTfegMQ77oAmUu18Lf8m3HE7Em+5mRdNiIgoMMkqGMlktOf3F4DSBg08ZZVTc+Qzmqij5Bzq709tA7ZW6z8C8ps24XK3kd0clwHpmRShZrtq9M3XeU7q167HltIZX9w8BiO61K8SG94lRtkm9Y+JiFyJmbbkGyQrYd9yx+O7F6tLeEKilC9jLroQhR83yGBoIO7KK9gAiZyiJnOvUnLDnqqtW2EqKoIuzoO15qTO3eRn1Gx0S31XZEXKYLWsiEgdop74yQWQxkbPBCLa1yVbl5CA+OuvQ/SU82CuqoImOAS6pEQESdkEIiKiQCTliOw17BWSnCAd762r1eRzXEqBycqyxqRhKLNsyVkXEta873hcSnlIaQkPJr10ig3DyK5xWLWvaULEY+cMQEJkMGBOBk78B/DDvfZL+HUd167H1mqC0C81Cu9edRxKqmqVt29MmB4xYczcJiLXY7oh+c5ypuaW5UhQqUE2oD49HYl339Xk20KPPw5R55zj+Vqj5Bcs1dXNj5tsl1F5RPJA4Jqf6jNuZdI6aiYw7TO16Ym1bt/0b4DIVNuyGEMvB0ZMB7TtD7JKgFafmorgbt2gT0tlwJaIiAJbsJpg4FDDeqvSbPfs55s2PtPqgUs/bvdFVSIbEoVsrhSWNKdtfPHfzSQo+8q0YZh5cg9EHqshOyAtCnNvGIVhnY9lnMv53cDzgZE3yNJL22Z0Vy1U57sdEBtuQJf4cHRNCGfAlojcJshicXSp1/NKSkoQHR2N4uJiRMmSdgps278DPptmf+zaxUCnkTabTCWlqD2ajdKffoKptAxRp02EoUsXZtmS01Tv34+9Z0y2mzGjS01F17mfQZ+U5B1HvKIAqCkDgrTq5LVxXTf5HaRuXmk2UF2qTmzlQklItKf2mIjIb+aHvrjP5CIlWcB7E9UGZ42lDQcunw+ENyrzJd97ZAOw73e1SWyv09RAro4t68kJaqvUhneOmtde+gnQ9yyvONS1JjPySqthslgQZtAiLtzOe6CqFKjIBYoOqqXCJElBEhOYtENEPjg35BpV8h2dTgCOu6bp8p1THlY7mzaijYpUbiG9mqnXSdQBUjs57rrrUPDOO7YDQUFIfewx7wnYWpdYys0RyayNSlNvRERE5BpRqcBlc4EPz1EvqFrJxdIL320asLWOya3f2XxWyPn0IcDY24GtX6nlORqSElpyMcFL6LUapMa0UEc2JFK9xXV3124REbkMM23Jt1QUAmXZQOYytdh8txPVgvPHatlSADObgZJDwKHVQM42dZKZOgyI6dhSqJZIs7HKtWuR+/obMGZlIWTgQCTecTuCe/RQmnEREZFz+WLWqi/uM7mQrG6R2rbZm4H8XWopo8Q+vHBKisLyGhwprsRv23OgCQrCqf2SkRIdguhQvWtfk4X7gBWvAtsWqjWTJVlm8CV8XRIReXBuyKAtEfk+mWhmbwQ+OAeoKq7fLsv7Z3yvngi5mARvLbW1SqBWGxnp8scjIgpUvhgA9cV9JiL3yyurxjPfb8f8dbblM64/sRtuntATceEubn4ltW0lA9xaToslBYiIPDo3ZDcmIvJ9Uov108tsA7aiPA+YNx0oy3H5Luji4qBPTmbAloiIiIjaZe3+wiYBW/HO8kzszC51/VHVhaiZtZHJDNgSEXkB1rT1d2W5QEUeYKxW61lKKQE2LQjc8gFlR9Xur4YwIDTW03vkPOW56jJDe6RUQkU+EOFF9WWJvO1vg7mWnw1E5LWqjSbklFSjqKIGIXppPmRAfASbcAWsyuJjzVU1QHgSoNXCHxRX1OCtpXscjr/3RyaGdI5GqJ6n8ER2GWvUvwtavkfIf/DV7M9ytgPzZ6hBKyG1iSY8AAy7HAiz0+SA/FdpNvD3XGDlq2oAs9NoYNK/gaT+gL6FYv6+oKa85aVeRNTofVMBFB8E1n0I5O0AOo8FBpwPxHQCNP5xAkxEvi+/rBpzVu7H60v2oNpoVrYNSIvCK5cNQ/fECE/vHrmTJKHk7gAWPwLsWw6ERAMjbwRGXAVEpvr8c1FrtqCootbheH5ZDWqNFriytC2RTyrJAg6vBTbMAXShwPHXAgl9gIhET+8ZUYcxaOuvig4Cs89UA3RWtRXA4ofVbNshUz25d+ROUiLgq5nAnp/rt+3/HXh3IjDjO6DLGN9/PiJT1KuqkkXcmASlQ+M8sVdE3p2JsPc3YO4V9e+bXYuB5f8Drv5ebeRHRORhZrMF32/Kwgs/77LZvuVICS57ZyW+umVsy53kyX9IIsq7pwJmo/q1nOcs+T9gz6/A1A/VcxwfFhWiw/jeidibZz8ZYWK/JIQH8/SdyEbJEbVMXtaG+m1bFgCDLgZOf5qBW/J5rGnrr+RKU8OAbUO/PalmXpJ3fMhs/w748QFg+Qtq9kC1k+tVSSZdw4CtlQRqvr9XLS3g62Rp3PE32B878R9ARIq794jIu5VlAwuub3qhQ5abLrjBLXWgiYhacrS0Ci//stv+WEk1dhx1Q41PapnMXWWF35JngUUPATt+VOe4zlRRqM6XrQHbhg6uBPIdlxXwFQadFjPGdEW4oelql9gwPc4ZkgatJsgj+0bktSW+Nn9hG7C12jQPyD224pjIhzFo668Or3M8VnRAXV5Ens+GXvkGoNUDcd2B0BigMBPYvwKoLnPe42Quczx2dLPzg8SeEBwBjP8HcMYzaqdbIU0Uzn0VGHE1oA/QunfyPi/cr2amyL8sE0FWhfsclxXJ3e74oh8RkRtJOYTcMsdz1i2HS/h8eJrMWXf8ABxeDST2BqLTAJOs5lgKFDvoN9AeclHxwArH4zsXwR90igvDlzPHYkLvRAQFARKjPX1AChbcMkYZC1iSZJK3E8jdqfZsIRIVucCa9x0fi1XvqKvLiHwY11c0ZKpVM1AliCVLqiX4I8EgX5TUz/GYLB3SGty5N9SYlKo4uArKbOyTqfXZbhLAPeURIKG38157ITGOxzQ6IMhPaldKzSKpa9b/PPVkQRt8rGxCgGYklB4F/nwFWP0uUFupdgOWAPa4O9XjQoFN3iPNMZvctSdE5AIF5TVK065akxnRoXokR4UgyAc/Dw1ajbL/xZX263z2SvbRebq/BdOkV8Z3d6sXBK2SBwDxPdVGyM7onyCvX5nLOLoALckPfkAyaXsnR+Lly4ahpEp93ceE6RERHKCFbE1GIHsjsHAmkLNV3ZbYFzjvVbWUE89pA5vF0nwymrHSfvk8Ih/CTNuGdT9XvAy8Pgp4YzTwynDgq5uA4kPwSVKnNDjS/tj4exm08bSKIrVb+x8v2X6QyIUDqTvszCVlXU9U673aIwHOsAT4DY1GzbCN7QpEpQZuwFayXn77P2DFK2rAVshJzl9vAD8/DlQxMyngxfVw3GxMgvpykk1EPsdisWDX0VLMmLUKpzy3FKe/uBznvfYHFm89irJqO8vKvVxyZDBuHN/d7pgEcwekR7t9n6iR0izgx3/aBmzF0S3AL485rwxXeAIw9ArH433O9KunJipUj4zYMOUWsAFbUbQPmDW5PmBrXRE060x1FRkFttBY9XzWkaGXA/oQd+4RkdMxaGsNlK3/GPjl3+rSGyGBtG3fqE1afLG2X3QGMP0b206qcoI+6hag/5TADWZ5CwnYSsd2R9bOdt5Sjshk4LzXm26P6QKc+igQHA6XkYm6LM2Xch0Fshy7wnWP5U/lDPYsUZf5FextX6mM8hxgvYPX18ZP/aOOMXWMrCQZf5/9sbOe94su3ESB6HBRJS5+609sPFRsU/v1ho/WYnuW712w02o1uOS4Tpg2srOyTNwqLToEn90wSvmXvCDTLc+2UVydfb87r+SXZNmeeBeQ0Kvp2OT/AJFpcJnaarW8nMxnJRjN3iAtyi+rxrasEvy0JRsbDhbiaImDDOnmyLmQsry9yv6KISkzx5J/gU0XDJxwo5rt31jSAKDTCZ7YKyKnYnkEIR+80jHbniPr1azHiCT4FAnQpg4Frv9VDTpL7ULJQPTlkg/+RILmzWXTFkvd4SpA54QyFoZwoN85QPpwYPMCtTFZn8lA2nAgOh0uk78bmDcDyN5UX4ph5A3AuLvZxdMeeY/u/hn48sb67FjJkJbAmjIZaUPmY2Wh46VAcnJVWQCgR5ufUvIj8jkw8nr1c2LpM+rJaMpg4JSH1GWHvLBH5JOW7shFUYX9UgLP/rgd71x1HGLCfKtEVkJkMB44sy9uGN9daUwWbtAhMSIYyQzYegdZftyR8bYmpVz1tTq33Pq1WvJt8MVAVDoQ4mCFYUdVFAAbPgZ+e6p+fhbbDbjkAyB5kLrKi2xkFVXitk/XY83+wrptGbGh+ODqkeiRFNHGOsYrHY9LAzopayiBOwpcssJSYh4SxN/ypfp6kJJwg6eq8Q8iH8egrfUDobqZ7ANZgpE2FD5HTrrlDxX/WLlVRW0F8qvysb9kPwwaAzIiM5AQmgBDw5pLUpJAgqjSeMyezqMBfbhzAzSJfYCTH4BbSED6w/Nsy4tIt9+Vr6sXDsbcDmjVPz+yXFOWc0aGBPDSL2tjunnT1aCqlQReJaCWNgzoc0br76ul144zX1vkuyQrQV5XnUaqF4nkAk8IlxoT+Sqz2YLfd+c5HN98uASVtSb4YuVPmSPIrWsCP7/cnthSkgWUHQViOqlBUilT0FBUhuOfl14NoU4ut2M9t+l9Otwicznw00O222T+Pvts4Kbfgdgu9Vmh0rNC6vcGcBCxrMqIf3+71SZgKw4VVmLG7FWYf+OY1l9wkeMogfqsDfbHJbtaMrCJJHB72hPA2DvVpBf5O+WoDBiRj2HQVsiHq2QBSlDJHrl6S9QKxVXF+Hzn53h9w+swWtTXU6guFE+NfQrjMsYp/68whAEn3gNsXdj0dacPA4ZfJWsCffeYyzI5R/WgpY7v4EtwNCgBa/YVYs7K/TBZLLhkRAbG9kpAarQTmlX4Gmn6JCUxGgZsG1r2rBpYa222rUxUJIPS3iRXGoM0PuGiwMb6tUR+QaMJQq+kCPzgYDwtJgR6ZgVSW1ZMfXyxWqrJqvMY4MJ3bVdqSRmuPmcBO75reh8jrlEDvb5KgtW//tv+mCT8ZC4DIi5R667KMv6s9UBCH7UcXVxXwBB4qxvzyqqxaEu23bGDBZXILqlqfdBWLiZLosf2b+2Pj7uLK0ipnqxQlZ4mRH6G6zmEZP4NutjxWJz9BgjkZ6QmkgQapZFCO2t+bs7fjJfXv1wXsBWVxkrcs/QeHC493LQR0FULbV9fSf2Bq78HojvDp0l2uiNVRTBWleP2T9dj5ifr8OfefKzKLMA/5m/E1bNWI6vYicvofKmudv7O5rNw21KzS4KyF89u+rdLWc73ke+VeyEiolY5b1i60n3enltP6aWUGqDAqCd6sKBCqXFcYzS3L8O2ccBWHFgB/HCfbUNTaQR01nPA8OlqZq01IWbsHcD4e9REBZ+en+12PH54DZC/C3hjDLD6HeDQGrWUwlvjgF0/q3VXA0xFjQlmBzkIIqe0DfNZISsFT/8/26xJyaQ89TH1vImIyM8x09Z6Fe/UR9Ran1Iw30quDF+xwLV1P8k7yHL+P14G1n2gLm2SbMQzZFn68FZfwS2uLsYbf79hd8wCi5KB+8/j/wmtddIhnSy7jgOu/lGtQSrlLCTjTS4U+LqE3o7HgqNQatLjr0ypq2pre3YpFm05iumjuyAokGpqyvKvLmOB3b/YH08dov6daou4buoFAAn4FmSqy/fkxgZTRER+Kz0mFG9dMQK3froOVbVqsE4+TqeP7orxvbjKwt9V1Bix6VAxHv9mK7ZmlSBEr8HU4zrhppN6IDUmtG1B28YBWyvJqJXkhpCo+m2S3Sbz5hPvVmv0S4ZpZIrvlwnQ6NUL3o7KmUkteCmd0HjVnKyc+vpWIP1PtaxEAIkM0SFYp0G1g4sFnWLbuKIuNEa9INDnTCBro3JWhdTBQHgSs2yJKCAwaGsltZEu/gAozQLy96gB25jODNgGgtKjwGdXAEfW1m+TzrAfnKM2O+h+UqvuptpUjazyLIfj+4r3ocZUg1BNo8mKLCuTmz+RoK1M1u1017WMugUfbHacTfvpXwdwzuBUxEd48US/skg9YZFGGJJBkthP/Zshgfj2kDPqARcCy59Xa2w3Hjv5QduTo9aSAK3cpLQCkb+QCxH7VwCZS9Uu4v3OVcsYtff954alotIYSi7exYYamOlILhWi12J87wT8fNdJ2JtXrmS99UmOUD5To0IDvHZ8ANh0uBiXvrOyrtqSBO4/+HO/Ul901ozjkRTVyr+T5TmOx+TOJcGhMZkPGbrCr8j8/OR/AQuubzomF9Ml+eK7u+3/rDTIkvNKLw7aSk+J7OIq7M+vUJr89UiMQEp0CBI6MAdPigrG1WO74s2lTYP+I7vFISmyHZ/VkkAjN0lIIPIXFYVq0uDGuerfiwEXAEl91XNoL1RVa0JuabVycTBMGoJGBitzDnI9Bm0bLymWW8ogNxx68hqFe20Dtg39+E/gqm+AiJazX8N0Yegb2xc5FfYnusOShiHY1zMOWkuy0yXg/dm0+mVlspRp+HSYRlyNVZ/tc/ijUt+2mVVVnleWCyx9Vl0GZyXP6wXvAj1PbXtGrJVM6iUz9ssbgZxt9ReTznoBSGwmc9mXScmHksPA7p+Bgn1AtxPVrBWubqDm6mXPmmxbwubXJ4FLPwV6TAAaNnz0sFqjGVuySnDvvL+xK0e9GCMnxP+9aDAGZkTB4Mt1y8mrGXRaZMSFKTcKHAXl1fj3N1vtlsffcqQEe3PLWx+0bba5mAEIjkTA6HEqMOEBYPn/1HIJQi6IT/1YSfpsljSU9eKAraxwu/K9v5BXVl/GYUSXWLx62bC2ZWY3EKzT4rpxanB11h/7lIxbqdhyxoAUPHx2f8RFeM/ntNOTgAr2ADt+AEJigH5nq6+T9iRdUGAEbFe8BPz+Qv02WfHb6QQ1kdDLavPmlFThrWV7MGflAeU9Ldn0l43sjFsm9Gj95wq1G4O2RPv+sH8MpEaXNBLI3Qb8/Yk6gc047lin0qbZKhGGCNwy9BYsP7xcyaiyuStdKM7qfhY0ErgMFFKDasb3anBFMjLCEpTgty44ElOPN2HF3ny7P3bR8AzEhXnxhG7Pr7YBW2vwcd504JaV6u/dHlI2Q8ogSLC7skBtTiavQZnw+WOpCKnztm858Oml9SdBK19TVzhM/wZKF1iihioKgIW3Nq05LstS510FzFylvn68xKHCCkx960+bJaJ7cstw6dsr8cMdJ6JHUuA1qCEi1ymvNinBWXsmD0xBsF6DuasPoKTSiFHd45AWG4r4cAfJBFL7Xso27bczRz7+Ot9uLtZW4fFqM6whlwJlOcD/t3cf4E2Wax/A/9lp0zTdu5Sy95CNgICgOHAjOEFxj3Mc57jn+Y7ruBXcCwducIOggIgMGaLsDYXuvZvZ73ryWtq0SelM3iT/33Xlgr5Pmz590yZP7vd+7lutl5J8xPpMlFcT/68saPp1oq6vuPguUyLDtnHAVth8pBhPLNmNJy4YCIOubaGCGKMet0/thctGpaHCLLLyVIgO0yJMF6DZ/mXZwBdXARnr6o+JBnaiFu/QywG9yZezIzkSJVcaBmzrHN0AbPsMGHOr6C4KOagwW/HMsj34bFN9k3Gxtn1v7WGUVVvx6Ln9YdQH6N+2TMjjN4HIl9zVkBULrQveBNa/KpVJWP4Q8OXVwCujgGMbAHuj2lV/SzelY96p8xAXWt/oKT08He+c/g6SwpKkLWVia7250Rb4QCW2lSUMkLbnR3c7npkxqlsUBiQ1vfLcJSoU5wxJcnbAliWxWP/1ac/ZFH9+0v7vId4oxfaR6iqLxX4gBmzrFrifXl4fsK1TktG0yQmRIC5mHF3v/lxYq4H8Zpr5eZnFZseCdVKGUZMxuwPvrDnUtuZAREQeqJUKhLjZqnrO4CSM6BqFC19di7u/3IbHftiF6fN+w52f/enMnnJLBCLFOrjfudJOKec30AGjbwbG3eZcJ9dYbSipssBqtwf+YyJKP4iLyWI9K+qp1q3PROD2nPnu12pnPC3VXZUpURKhccC2zvfbslFY2cqGYW4yblOjQtE3MRxp0YbADdiKJAuR3NMwYFvnx/ukJtdEDYl4wOb3PJ+T399ovkSNl4nniS82u/89Xrw1E4Uenkeo4zDTlih9gpTlKF506wyaBfzxAZC3s2lgQHTTvXk9EJHW5NyFakIxPnk8Fp650NmYTKlUIkIXgZiQGKkO465vgR1fAppQYNSNQMqw4MpW+FuCKQRvzR6Bn3blYuGGDNgcDlx4UgqmD05CUhu3Y7WXo9bhLG1RWF0Ii8OC2JBYRIdEO7Ok6z/JJgUbPRGlIBwO2VwZlTVRN1r8PbmzbxlQVcgtZeSqcYC/MUu5bM5YpcWOjYeLPY6L+pLlNVZ51+4mIr8iMhlnjUx1bkmvo1IqcN7QZMxdsLFJ2YRVe/Kx+I9MXDu+m/uL5aJU0bnzgVMfAayVzkay4sJyqU2FgxnFeGP1QWSWVDsDwpeP7oLUyFCoVUG2/hHrPfE+4rrVUl+C3G1AdHdg/L+kC/A+qrUuXl9EoCW/vAZheg1iwrRNasmKGrae2B21qLbwwmKLEzo2vO55fOvHwOn/bfFjR0FAJPqIJuSeiOQuGZVWEX0ZHB5KwYjXlaIqC7qijeUBqUUYtCUSxb4veg/4Yk594FbUJhXb3d0RW/1zdrgN2goKhQLxhnjnzSV7UNRhbHi19dBqoM904OznpOzKICMaHVw+Og1nDkxwPuFHhmp9lmFrc9iwvWA7blt5GwprpLINaqUa1w+6HjN7z0SkPlL6RBFsTxoCHF7j/o66T2LAtqWaW6yIXwhRPoGoIbG9UGQ1icYu7sT1l835ErW+UiJCPG5VTo4MYfMGIurwWsbXTeiGTYeLsC1Teu4Z0TUSv+0vcFvnVnhrzSGcNyQZ8SYPwUWxQ6pB/doqsw2L/ziGR77ZcfzYX8dK8eH6I/js+jEYnBoRfI+qyMIV2bfnzQcsldJaUTTN8hGRPf3k0t3OgHzd494txoA3rxzuUpZH1Fj3JFyvRpiOdddbxgHUlHgersht8WNHQUIkiw24ENj1jfvxHlNlVVLDoG3+ucCgZUixswXZ5VAiuC+F0HMKcMsm4KzngAl3AaZU18zbxlqzZcFmAda/5n57zO5v6xt1Bakog86ZbebLkgjZldm4Ztk1xwO2dYHc+VvnY0P2hvpPDIkApjzifhtcaBTQY4qXZhwARPDbk/BkKaOHqCERsD3jf+7PydArZXXxS3TVvf6U7h7Hbzile5trBRIReZJoCsHbs0fgs+tH49bJPXD9hG4orfZ8EbSo0gKHp4iuG/kVZvzfd412of1d3/DuL/9CYUX7ttT7NdGIVrwO+TBgK0rzvL3mEBZtqQ/YCgcLKnHpW+uRXVLtkjwhmo65c8vkHmwu1FJao5Rt7YkoMULUWMpIIKZn0/MiLvpMvKvtja07aRfHoBT3QeT+SeHOcepcDNoS1T1BRnUDRswFJt8vLbpEgMCTxGYCTo1VFQB/NVPrVNS0acWCmTreqqOrYLa7f6PxytZXnCUTjovtC1zymWvDI/HCO2eJrJog+UWGe++z3Y+d8aTsuqaSDIiLJd0mAbO/A5KGSnUWTSnAWc8Dpz4kXVSRkR5xBjw8vZ9ze3Id8f/7z+yLXvFsQkZEnUN08h6ZHo07T+uNSX3icWofz2W4hqdFIOQEWVQN7c4ud26ddzuWU47iqhOUsaFOlVduxvvrjrgdyy0z43Bh5fGPY8J0mHfJUGfN47rXKZFhe9+ZfZwlyzTBVuqirfThwKmPAio3NXujewDJJ/liViR3piTgiq+AsbdKWbXi96fP2cB1q4DIbpBbgpV4ruge6xpI7hodivmXnuR8LqHOxTQPaj3RhEvUDlTppC1BgUgEbKf+H7DomqZjaWOlTMDWaK4ujaiBKoK2gdpwyg/sKtrlcSyjPANWR4M3ISKDotdpQMIyoKYUUKqlLFtxo5YLjZZKg4jF7LqXpXIJcX2B0x4HUobzTJJ7epHRMh647EvAViNtMRN1wWX4/BkeosXM4amY3CfOGcxALdAn0ehc3DLLlkgmxHZ2US9b7O4I0Hr0Q1IjkBIZgmPFrnXkRZzu3jP7ISK05VlSrcnKJe+rsTpQbfW8U/BwQRXGNNgEkhgRgicuGIh/nd7LWcM2TK9CvFEffLWJ20tkTF7zs9R4TJRQU+uBIZdLTftE0zoid0TiweSHgNE3SbEAEbz1YaZ+c7pEG/DxtaOddcyPFlUhJSoUyREhiA/3Td3uYOOVoO38+fPx9NNPIycnB4MHD8bLL7+MkSNHeuNbU0cSwcWSI8AfHwEHV0hvlMXVIVFoP9ACViIA0HMqMGMBsPxBqSatKKMgtuCKF+Cw2NYFpwbOkDpBujP4YqnxknjBF11mRVCCvGpw7GB8e+Bbt2PdTN2gVbl5QyMyQZkN2j7GeODk24Ahl0hN3sTfmKEVf1sUvAzR8AehOjXSxC1aPtvcqO24ng0glflA9l/AuvmAuVTKcBI1BgNwx4wIzIk32/9buhs/bM9xZsr2STDi0XP6o3crs/77JYU7g73ukm17xIWh0mx11tQVQWLRdJa8K0SjRJhOjQqzze14w5q2dcRFRF5IbCe1FkgcDMz8UGoiJd5HGmKk4C3RiX53/CSwL3ZxiNvQLu7LqlDnUdTWdu4l008//RRXXnklXnvtNYwaNQovvPACPv/8c+zZswdxcc3XnysrK4PJZEJpaSnCw1nf0OfydgFvnwaYGzVWOeVuYMzNsiqY3aHKc6RMDBG4E2UT1G3YAlB8BHh7atNi9OmnAH2nAz/8S3qBF91mxdW2QAuCy1xmeSYu/PZCVIruyI28PPllTEyd6JN5ERGRPNaH7VnP+mrO5EFlIfDzo8CWBa7HxUXDucukclkBqNJsc9awFUFbo17t7CfQlvt4f91hPLV0j8txrUqJFy8ZgqeW7MbhwiokmfT4YO4ot0FC6jxWuwOvrDqA55fvbTLWJSoUn98whplxREQy0dK1YacHbcXCdsSIEZg3b57zY4fDgdTUVNx666245557mv1aLnBlRGxd/vRyacuHO6KJl7ti2lRPZOv++SmwY5FUVmLARVJH3u/vAGwN6qle+rm0/Z68xlHrwJ6iPbjzlztxtPyo81ioOhS3D7sdZ6SfAZMuQC9IEBH5IV+sD9uznhW4ppWR7K3A66e4Hxs4E5j+QuCW/+oAJVUWZ8mXV1btR3ZJjbNBjaiL+vrqg1h7oL4HAIOEvpFfbsbrvxzAgnWHYbVLb/MHp5jw0iVDueuDiEhGWro27NTyCBaLBZs3b8a99957/JhSqcSUKVOwbt26Jp9vNpudt4Y/BMlEdYnngK1w6FcGbU9EbLkbdwdw0mzg0Gpg9VNAQdMr4Vj9PyB1BBDCrQfeolQo0Te6LxZMW4BiczGsdisi9ZGIDYmFxl1jASIiChqtXc8KXNPK2I6vPI/tXARMeYhB22aIGriju0VjQHI48svMeP6nfbjug80w21z7N2QUVSGvzMzMTi+LNepwx2m9cOWYNJRUWxGiUTm7u4tmQkRE5H86NWhbUFAAu92O+HjXrqXi4927dzf5/CeeeAKPPvpoZ06JOkut56L31IBKJb0R+GOB+4CtUJ7tmnlLXhMbGuu8kQyIxjAVeYDdItW6NSb4ekZEFKRau54VuKaVeY+GtjSOJRdhOg2OWKvwzZ9ZHs9McZWFZ80HQrVqdIlWI/AqNPupqiKpvKBCCYREAzrWuSeilpNVa0iRwSBSg+tuR49K25RJBkS92pRmmselT/DmbPybJhRIG+d5PGmYVDaBKFiJOtK//A94ZTTw0hCplvaOxUBVsa9nRkTUIlzTylj/cz2P9TmHO51awajXQKf2/HYyKYKNmCiIiSSczD+AhRcDLw4GXhoKfPsPoPiwr2dGRH6kU4O2MTExUKlUyM11bb4kPk5IaJo1pdPpnLUcGt5IJkRjrLOfkzLeGhONs8Jcs0+oGUolMOhiQOumOYNSBUy8G9DyCiwFcTbC9/+SyoTUNT0sOQJ8PgfY8wPgYFY/EXlXa9ezAte0MhaRBgy4sOlxfQQw+QGuwVohzqjD7LFd3Y5N7h2HmDY0OyMKGIX7gXemAsc2Sh87bMD2L4D3zgJKj/l6dkTkJzo1aKvVajFs2DD8/PPPx4+Jxg3i4zFjxnTmt6bOENsXuGENMPI6ILY30HU8cNmXwPh/ASERPOetrW971RIgYVD9MdGt+IqvArZrMVGLVOQCu791P7b8QSkLl4jIi7ieDTCGGGDak8DMD4HUkdKa9uTbgOtWAdHdfT07v6LXqHDt+G64ZVIPZ+1UQaNSYObwFDxx4UBn/VuioGQuB1Y+JpX7akwEbJvrFUNE5K2atsIdd9yB2bNnY/jw4Rg5ciReeOEFVFZW4qqrrursb00dTaUGonsApz0mZcCptICe2dBtIjJqEwcBVywGqoul7EHReMzIjGUKcrk7PY9VFQI1pYAp2ZszIiLiejbQhMUBfadLCQgOq5Rly8ajbW589Y9Te2DWiFRUWuwI0aoQE6Z11lUlClo1ZVKjbk92fQsMnCG9JyQiakanv5rOnDkT+fn5eOihh5CTk4MhQ4Zg6dKlTZo5kB9RawF1jK9nETjZHuJGRJLQaM9nQqEA1NxqSUTex/VsgOJOsQ6hVauQEhXaMXdGFAiUamlNW1fqq7HwJAZsiahFFLW1tbWQqbKyMphMJmdTMta3JVkR2bGWKunFVtTzFcEkImq/kqPAaydLGbWNdT8VuOhdIMTEM00UxPxxfeiPc6YgYLcDlXlArUNqgssddEQdQ4RYNr0NfH+n+3FRcjBhIM82URAra+HasFNr2hIFHEslcGwz8OnlUlf7t04Ffn8DKHdtTkJEbWRMBC79rGnTw8iuUjNEBmyJiIjarywbWPMs8Pp44OWTgEXXSSWKbBaeXaL2Egk9faYDvc5oOjbtCcDUheeYiFqEmbZErXFoNfD+OdLV04b6nQuc9TxgaGZrNxG1jN0GlGUCGeuBokNA6gggrq+0lYyIgp4/Zq3645wpgImmnp9cBmRucj0uShBduxKI7++rmREFlsoCoPQosO8nKZu9x6lAWAKgN/p6ZkTkJ2tDVognak1Xe7HFxV1FkZ1fAxPuYtCWqKOaHkamSTciIiLqWPl7mgZsBZsZWP4QcNE7gJ6liIg6rH9J0lCeTCJqE5ZHIGopczlQsNfzeMY6nksiIiIikjfRud6TAyukNS8RERH5HIO2RC2lUDXfcIzNG4iIiIhI7prLotWEAgq+RSQiIpIDviITtVRoNNBzmoe/JBWQMpLnkoiIiIjkbcCFnseGzQFCY7w5GyIiIvKAQVuilhKZtNMeb9oMSWTfnvc6YEzguSQi/1KRD5RmSv8SEVFwCE8GTn2k6fHYvsDomwC11hezIiJqG2u11MRY3MT/iQIIG5ERtUZUN2Ducqmr/d4fgciuwMCLAFMyoAmR/7msyAPKsoCSDGnBLubNYDNR8KkqAo6sBVb8H1C4H4juAUx+EEgbC4RG+Xp2RETUmUJMwPCrgJ5TgT8/ljrc9z8fSBzUNDlBjkRQRqxp83cDtQ4p2BwWC2gNvp4ZEXlb8WHg1+eB7Z9LHw+YAYy7DYhK52NBAUFRW1tbC5kqKyuDyWRCaWkpwsPDfTOJmlLpza3DCujCGeAi/1VyBPj4EiB3R/2x6O7AZV9IwWgiCg7WGmDjm8CyB5qOnfZfYMS1gEbvi5kR+c/60N/m7HAA5dmApQJQ6wGDCHCFen8eRO1VUwbs+Ar44Q7Abq0vUyYyh4deAYRG8hwTBQuRiPTWqdJFnIbC4oBrfgYiuvhqZkQdtjZkeYTmFB0EvpwLvDwUmDcCePcMYP8KacFL5E/EhYdFN7gGbIXCA8AnlzV9oSOiwFWRC6z4r/uxlY9J40QUWGuArR8Bb04E5o8E5g0DfviXVBqFyB/fn317a33AVnDYgeUPAnmN1rlEFLjE3/1fn7l/HyuObftC+hwiP8egrSelx4B3zwT2LQfqkpHFIuGjC5oGvojkTmx7y1jrfixvJ1DJepZEQaOqALDVeN5yKp4viCgwiAzb3d8B39xS/8ZWBLtEEPez2bxoS/63U2Tty57Hf31WysQlosBXUwLs+sbz+M6vpM8h8nMM2noiapaKbWSNiQDusgelrAUif3Gi7HBRBoSIgoPyBA1mVBpvzYSIOptYy/78H/djmRulJAUifyEuOJYcbn6rtKeLkkQUWJSa5utYa8OkzyHycwzaerL/Z89nLXMzuxKSfwmJlOp9eSJq2xFRcDBES40I3TGl8PmAKNAu2ja3myZnuzdnQ9Q+IkCTOtrzePJwQGvkWSYKBvpwYPTNnsfH3Cx9DpGfY9DWk+a6DYbFNx8AI5IbUYx9yBXux/qewyCNv7FbgKJDwMa3gR8fAHb/wNqE1HKiM/jF7wOaRk2IxMczFgDhiTybRIFCrQOUas/jxgRvzoaofcROkOFXSc30GhO/56JjvDaEZ9mfiLItYofr8oeB1c8AebtZ4oJaLnWk9F62sX7nAikjeCYpIDSzigty/c8HVj0B1Dqajp38TylwS+RPmQmT7gM0IcDmdwCbWVr4DroEmHwfEBLh6xlSS9msQMY64KOLpOCtsO5lKUNy9nfNX3CSCVthIWptNihDQ6EyMiPGJxKHADetA/b+KO0eSR4G9DodCE/xzXyIqHMY4oCBM4A/P246pgsH4vryzJN/MaUBc74HvroRKNgrHYtMB86dJ/1L/qM8B1h0HXDol/pjK/4PmPKoFJzXmyBnNVY7SqosUCoUiA7TQaVU+HpKwZmYdPZzwJhb6l/nBs8CorszKYkChqK2tq7LlvyUlZXBZDKhtLQU4eFeTm23VAH7lgGLrnHtTtr/AuCMJxm0Jf8kmgyJK9qWckATJr3QaRtl25G8iXptr4wGLJVNx7pNAma8J9sgvK2oCJUbNqDw1VdhzcmFfkB/xP3zNuh6dIfS0ExNKiIiuawP/XHOpZnAp5cDWVvqj+mMwOWLpAs23D1G/kisZ509RmqBkCjAyIQav2uSuP4VYNn97sdvWAMkDIQcORy1yCiqwqur9mPZzlzoNSpcNqoLLhyWgkQTM72JqGPXhgzanqhDaUUOkPUHUFMOpAyXtpGFRrXwYSAi6mD7fwI+vNDz+K1bpKvLMmMvL0fBK6+g6N33XAcUCqS8+iqME0/x1dSIyM8waNvGAFfpUSBnG2BMBOL6SaVSGLAlIl9l2b41RXpecmfkdcCZT0OODhdU4px5a1BWY3M53i/RiHfmjESCyU35DiKiNq5nWR6hORo9ENlVupF3OezSi7mtGlDppGA5O5r7J+fFj1zp8VSppSz1MPF48umnTapLmh+vK5kgw5IIRe8taDpQW4ucRx+Fvt8n0MTF+WJqRESBT+ysETeRWUteVVZtRUm11ZmdFx6iQZRBy0fAX4mLH5UFQE2JtPXaECM1+6XWEyUIxXn0eK5zpWxcpVJ2JRFEhm3jgK2wM7sc246VIMHEWuFE1HEYNSH5EYuh7YuAX54EqgqlLXwjr5euuHLrk/8FGP/6DFj+IGCrkY6Jxe2F7wBpY6ULI3VEd2sR4BVZP2z251n8AM9j4rzJtP6Xee9eZ4DWHVt2NuylpQzaEhFRwBAV6A7kV+LRb3fg130FzmODUkz473kD0CfBCK2aTY39imgA+9kVUrZ6nd5nAmc959LA02yzo6jCAtEVJUynhilE45v5yp14f5d+CrD7O8/9ZWQWsBVEDVtREsGTL7ZkYlLfOKhlOHci8k98NiF5sZqBTe8CS/4tBWwFcznw6zPAsgdPnGVI8pL9p/RY1gVshepiYOGM+u1QNaXA/p+BBdOBFwYAr40D1r4MlHteEAU1kSklFrLunP64tO1VhpQhzdf4Uqj45pUAW34+rDk5sBZIAQ4iIn91rLgaF7669njAVvjrWClmvLYOGUXVPp0btZJYk3480zVgK+z5AfjpkeN9BjKLq/B/3+7ExGdW4eQnV+Dmj7ZgZ1YZLDY7T7m7oO3k+wGVm8xz0VAuZaQsz5loOiZq2HoSplNBCTYkC3ZVZhuyS6qdN5GdTdQeDNqSvFTmAGuedT+27VMpG5P8gwjOrnzc/ZjDBmz5ALDbgQMrgA8vAPJ2SWMiWP/Tw8DSu/9uMNEGIhAsGq+UZ0ulNgKJqKk97Sng1Ifr62vH9gYu/RzoMcVZI1aOtOndoNDp3I6JhmSqSG4vDGaiSV3J11/j8KWXYf/ESci4cjbKli+HrbTU11MjImo1UQrhh23ZKK1u0Mz4b2abw7m9utradHs1yZRYT+bvcT+2/XNn2QQRnLnsrQ34cEOG8zEW1uwvwHnzf8Ohgqo2/x7lltUgu7QapdXyLH/VLlE9gGtXAOkTpI/VOmDYVcDsbwBTMuQoOkznbDrmyaWj0qBUynMtTt7ZYXGooAL3Lt6GU55e5byA89DX252N64jaiuURSF5EJq21meyD0mNATE9vzojaSpQ6KD7oeTx3O1CRDSy9x/34jsXAKfe0rvGfzQwU7AF+ehQ49AugjwBG3QAMucxl65rfE2VCTv4nMHiWFABX66UMXBlTx8Ui6en/IfO226UaZX9Thocj8fHHoWbQNmg5qqpQ9MEHKHz1tePHLAcPIvPWfyD+/vsRMWsmlBpuLyUi/1FltWHVHs+JBhsOFaG8xoYQDd+K+U3Q1hORHGC34I/MEhwubBqYsdgdeG75Xjx78SCE6Vr+WpZXVoOvtmbirV8PoajSghFdI3HvmX3RM96IkGYyPf2KWgskDAQu/kDaWalQAqHRruXTZEalVODCYSnOizKihm1Dl45MRXpMqM/mRr53tLga581f63LB7rNNx5yvB4tvOhnJkc3vPCRyhysFkhfNCV7oZFqvkzw8lrF9pKYN7ohmKOYKqUGZJzl/AXF9Wn56RbbuW6dKgUxBZGav+D9g/3JpQSjzwGariNq/ovO3n1BqtTCMH49u336DkkWLYDl0GKGjR8E4eTI0yfLMpiDvNakrfPMtt2N5zz+PsMmToU32n991IiKtSoWEcM+Bp2iDFhrWvPQf4Smex1QaOEIi8cO2Yx4/5dd9+c4gfUuDtoUVZtz15V8ugf91B4ucWbufXT8Gw7u2IqHBH4RESDc/kWgKwTtzRjqbjokatqIkgsiwFQHbKIP7XWUU+Kx2BxZuOOJ2h0VeuRlLtmfj6pPTmYlNrcagLcmLuLqaOgo4uqHpmAhQGdmN02+EmIBJ9wOHVrse73ceMHCGVHtVdI495W7g9zekcgpN7qMVW+arioEf76sP2DaUsR4oPBBYQVs/pAoJgap7d8T/+99w2GxQqvkSRIAtLw+wud8mXFtVBXtJMcCgLRH5Ea1aiTknd8XirZlux2+c2B2RBje1PEmexPuPxCFA9tb6Y+HJwOgbnceV5dm4e0wYyqsi8cv+putZ0YxM1YryVZkl1W4ztR21wENf78AHc0c6t+mT7ySY9EgwJTibjokatiyJQKVVVizf6SFZCcAP23Jw8fBUhLM5IbUSa9qSvIit8Oe/DkSkNQ3eiZqdfpRZSADi+gEXvCWVKRCmPQlEpAKLrgHemgy8OkYK6l74dtOAqjNTt3fLT6OlAjjym+fxvUv5kMgIA7ZUR6FvfhukgqURiMgPdY0x4N4z+jQpNS+2UAdcpmSgC4sFZn4IdB0vfSzWp9NfBP78GFhwNvD6BKR+OgUv9NmJO8fHN/nyOWO7IqYVQdZ1B/5uxuzGzuwyVJhZD1ku1EolA7Yk/S6oFDDqPSekhOvV0KgYfqPWY5oTyU9UOnD1UqBgH5CzHYjuDsQPkG1BemqGPhzofz6QNgawVAF7lwBrX3b9nIx1wA//khprfX2zdEylAWYtBMJaUYdW1MEStV1tNR7mwtIaRHKkjoqAKiYG9oL6Dut1tF27Qh1u8Mm8iIjaQ2RXXjqqC07rF4/1h4qcW2dHd4tGnFGHiFBm2fodkXRw8ftAVYG0U+ydaa67xGpKEfnTnZg1/X0sijHhUEGl8/DoblE4b2hyqwJ74nenuZqqSpk2nSUKZuJ5/Zqxqbjl0xK343PHJCNEGyD1qMmrGLQleRIZteLW7RRfz0S2rLl5MO/dg/IVK6COiUH4tGlQJyRAZZBZgEOlBkwpUhO5Nc+7/5yig9LWs3F3SA3DekyVtp2pW9F8yBANDLkc2OS+Nib6nN22+VNwqSwAykSX6F3S72RUN8CYBLD2YKdRhziQ8sQDyLj1HtTW1F90URqNSP7Pv6FWujb6ICLyF0a9xnlLjw3z9VTky1IJlGUBO78GSjOBXqcDiYPkubtO7AgUt60L3Zf1Ekm4G57A/HM/wuK9ZpzWLwFdY0IRa2xdYy0R3BcxXlEOobGzBiYgOoxBfzoBm0VqoJe/W+ohIhq+iYzx1pSeo9ZxODDKVILTekdg2R7XwO3Fg6PQz/IXUB0mlRAkagUGbYn8kDU7GxnXXQ/Lvn3HjxW8PA8Jjz6K8LPPkl/gVrBWe1zgOhUdAqY83Pb7F1m2428Hig4A1iqg5Eh9k7MznpJq6BI1R7xpXHQtcHhN/THx5uzyxUDCIP8I3IrfedGQb9tngMYADL1MKjcjfg6ZUtSUIGT30+j2ztOo+GM3zAePIaRXOkIHdIVmw4NAxEOta0hIRET+E7Dd/QOw+Fqg9u8I5eZ3pAumV34NRHSBLIleCZ7k7UK/OD369eze5ruPNerw7IzBeH/dEVgdDuzKLofdUYuUyBDcdXofhGr5Fp5O8J7r4C/A57NddyAOvULa2SiCt3JnrQHKMoEdi6XAc/opUjKXXJ8TBFsNYn97FI/3Ogc3DD8JX+81Q61U4NyeWqQU/Iqon18G0lcwaEutxmd8Ij/jsFhQ+NbbLgHbOjkPP4zQkSOgSk+H7IigqqhTKwKq7ogFejvYHDbkKuz4c+zVOFx6GANN6eilj0O8PhIISwD0xnbdP/mRqiKgJAPY+ZXzqjf6nysFLg0xzS9wVz7hGrCtu68PzgNuWCNljMuZyBD+fA5wtMGbyY1vAqNuBE75t9ToUY60YVBkb4H2mwsRlTgY6J8AlPwCfLtTGucFFyKiwFSRCyy+rj5g23AH1orHgLOfB7ShkGXPBk/EekPZvrfYWksxpsflY/qAdbAqdKicPhH5iERERDQSI0Ladd/kP2pra51N6X4/VIQ/j5ZgQLIJY7pFIykipPlyGyIJ4dNLAYfd9fgfHwDJJwHDr4as2azAkTXAwpn1Daa3fS4lIMxZIt8L+WodEN8fMcv/gRi9CSeljJCe277ZIPVe6ToO0PDvl1qPQVsiP2MvLETJl196HK9YuQo6OQZtRaOxEXOb1rQVRDCpNU3HxHmoqIC9pMQZlFOEGbDPlok5y69Bta36+OckGhLx9tQ3kCpq61LwlDf46RFpYVpn7YvAwBnA6Y83bXhXpyIP+OsT92MiQzx/j7yDtiI4LbIRGgZs62x4FRhwgXyDtuIxGTgT+HMhkP2ndKsT318qU0FERIHn0K9SfVh3dnwJTL4f0Mows06UcPjpIcBmbjp2yl2AsWkzsuYCc7llZtRY7dCqlYhUVkH9wx1Q7/7m+Jt1EeaJnPwIlPFX/f0RBQORYT3rjXUoq6lvPGfQqvDJdWMwMKWZLfZiPdg4YFtHlKrrfVarfke9riIb+OzK+oBtw0SKr24ELvtCKosnN0oVcNIVwPr5zhrX2P+T6/jE+4CQv5tzE7WCH+z1JKKGah0Ol7qPjdmLmylB0JZ6SGLrWuMMiLZefRxzC9DvfNfjonbt7G9bFRCzHDmCrLvuxoHTTnfejl13A4yHCnBS5ECXz8uuzMZD6x5FqXjh7AhiASRq8x7dCBxYJWWC1LDepqxk/eEasK0jrtAf2+j568T2MbvF87h43OWsMh/4/Q3P4xvf9ryA9zWtAZjyEND3XNfjIhtk1seeA+1EROTfmiubZbc2Ddq0Q5XFBovNQ4C4tcJTgCu+cq0PKhriinWuCOi2UHGlBV9sPoZz56/BxGdW4bTnV+PlNdko7j9HasrbgGrFI7AXHkSHqS6Rmj4fWAFkbpGyM0k28spqcMOHm10CtkKlxY7rP9iE3FLP7wVRsN/zmHicO/DvqlOIknni/ac7WVuA6kLIlijfcNmXrrv7xDp3+stAwgBfzoz8GDNtifyMqFcbMnQIqv/Y6nbccMqEjlnIiYDkhteB8iypMVg/scW8C9CejrUiY276C1LmROlRQJQuEFd6W9FswpKVhcOXXe7Sab5m+3bgmttwzwfzMbN4O6ps9SUYNuVuQnF1Pkz6dhZ9t9uAzE3AJ5dIV3rrFuhi6/m42/2jPlSgE40W1s3zPC6yvNPGua8lJRZUIhO1ysNCUGR8ypnIVBJbrzypEVnpdikLQI5ECYRzXpaCt1XFgM4oLXibK2lBRET+LX2857H4AdJrQTtlFldj5Z48/LAtG5GhWswZ2xXd48IQZWhHMy/RKDd1lFQ6SQTBLFVAZBfAEAfoWtZ0zmZ34Os/M/HINzvrEwzNNryy+ggO9Y3EE2MfQMSvrr0elJveAUQZIZWq/fXvf3wA2P65axLFpZ9J6532rPWpQxRWWpBR5L6kXFZpDQoqzYg3eWhw130i8NfH7scSh8h/i76ngG3DCzpyJZKU0icA162WEipEgFwkH4hSfWo2EKS2YaYtkZ9RRUQg/t773C7Y9EMGQ5uW1r5vYC4H/vgQeHOStF380Gpg+YPAG6cAhU3r6Laa2BYS0xPoPhlIHtrq7sCVq391CdgeZ7Wi9u1PcWHKWU2GzPZmrka3VNkx4P1z6wO2dYEysQVmzw/tv39qP5EpW1PmeVxkXDusnoOGYttSYyLIOeQKILqHvB8hfQTQa5rn8UEz5b9YFMF0cZ5TR0j1yhiwJSIKbKYuQPrEpsdF0PCM/wGG9l0QP1pUhYteW4sHvtqOtQcK8f22bMx4fR3mr9yPkqpmdte0hFgfiF1iqSOlIJnozdDCgK0gSiI8t2yv27Elu4qRn3yqlBzQ8FtW5gK1tvbvotvwmmvAVhBNn96fLv1LPneirHBzc+NpJ7v/2xGBeXGBXMbNaZ1ienm+cCACoCLpR85E42JTMpA0BEgZLiU9yX0NTrLGoC1Reztbiuw+L9P16omun36C0JEjnS9qyvBwRN94A1JefBGa2HZmfJbnAssfcL+F7Ye7gepSKRNX1PgU27FFNm7e7ua3uHUQh9mMipUrPY5bN/+BIYZeLsfCteEI13RAE7L9P7t2YG1o9f+krAVqlr2sDJZjx2A5etT5/w4nsqn7NA3aH9f7TOlzPL356n8+MO2p49sdqwbPxKG5S/Ba1/54dOuLWHV0FXLFGyY50oYA425zn5UkAqFdRvliVkRE5AccjlpUmK0dVz6gpcQupQteByY9UB9IEhmsVy+XAh7tUG2x4eUV+5DtZhv522sOIaukpr780b7lwJoXgL0/eq0cUnmNtcnW94YOldia1KI39zhDyuRrb/O33990PyYSE3LrM3/J899Ldmk1DhdWOv+1OzqgjFwjIhNcp3YfqtGoFIgJa+b3ICIVuGqJFLwVQqOQc9E3WHHaUty/1oYXftqL/XnlzsxuWRLPCyOudT92xtPsdUBBh+URiNra7Chvl9TgR2Sm9r8A6DnVa42KlHo9QgYMQPLLL6G2qsp5RU8dHQ2FugP+pI/85rmG7aGVUnB2ywJgzXOuY2NuBsbd2amF4cXPp4r3XN9SFRWFUrtrEP3WgdcjNqx12bxu5e7wPCYW+HKvD+XjOsyWQ4eQ8/gTqPrtN+ex0LFjEH/vvdB16wZFe7f5NQy8DrpY+rsUf6MNiUCsaA7QqEacC/G7KxaJfc9Cld2C5YV/4cGfrkUtpL+HL/Z+gbTwNLwx9Q0kdcTvVEeLTAeuXQmsehLY8z2g1gNDrwRGXSdlVxARETUKPh0rqcY3WzOxZn8BEk0huPrkrkiLNiA8pJnXy44kSmeNuwMYepm0g0kT2iGZgCVVVny91XOd1l/25KGfJgdYcLYUyKwjMhRnf9fpHeo9BeTqRISoAWuD7fHGBCh6nNr+bywSEJorp1R0oP3fI4AVVpjxzZ9ZmLdiv7OEgQiu3jSxO84bmtx8ILWV4ow6/PPUnvjfj3uajN04sQdiw06QuSl2Nc78EKguQlZtDK5Y8CcO5G87PvzCT/vw5IUDMX1QEgw6mYWERIKFaOgnSjn8+oxUUi9hIDD1P0DCYCmTlSiIyOwvlMgPiJqXK/4LbH63/pgoISC2Psz5XvrXS9QmEyBuHcnuphNundAYoPhg04CtsG4+0H0K0GMyOosI7kXOmoXSzxpt6fqbYfYl+K7oR+f/Ew2J+OeAazEuZRzUzQXqWkpkKm562/M2HhW3vXhizczE4VmXwFFe37Stau06HJk1C+mLF0PbpQP/ZsTf39zlwIrHgZ2LRcgY6HsOMPkBIKIFpUNEANmUivyyI3hw7cPHA7Z1jpQdwStbX8EDox+AXgRF5UQErcUi/ZyXgOr/SFvLxJvPjvj9JyKigLM/r8JZPqBhxufiPzLxyDn9MWNYiveCOeK1t5Xlsk5EvHpb7Z4zh8cn1wKfXeEasBVEHcpPLwXm/NCpGX1RYVqM7R7tLNvQWGSoBik6EVytdL62W3tNR+2pD0Eb3c4SaEJdULxhua/GtYTJY/b2W2sO4dVV9YHtokoL/vv9LmdG951TeyG0g/5mdBoVZo3sgqSIEDy7fA+OFlUjOSIEd0zthUl94hCibcH3CY1CjcaE+d/uxIH8poH6e77chpFdo9AttuVlPbxGrF/FhZweU6TEGFGHV+5lHYg6CYO2RK1VfMQ1YFunJANY+xJw2mPt37rkS13HeR4TTbfWv+p5/LcXgJQRgL4DyhF4oE1JRfx99yL3iSddMoLDzzoLURMm4intKFgdNujUOsSFxndcsf0uYz0vcqc8yg73HtTabChZtMglYFvHUVmF4k8+Qeztt0Op6cDAoqgrd86LwNRH6rNsRaOxVliftb5JwLbOD4d+wE1DbpJntq0gftZW/rxERBRcRE3X+77a5naL/n++3YFJvWPll4HXCka9GlP6xmPZTvdljXoaaoD83e6/uPCAtGOnE4O2phAtnrxwEC5/a4NLw6kwnRrvXjUCYUYHqm7cAoVSCZsuEsbwiI75xuJnmnAXsPSepmORXeVfw9+H8ivMeOvXg27HFqw9jNlj0tClA/9mRBavyOAVwX2rvdZZFiEuvHUJAyKo/MUWzyU/RJM+WQZt64iG1URBzn9fiYl85a9PPY9t/Vja4tXB2QJeJRoyDZsDbH7P9bjIJO1zJrDrG89fW1Xwd6Zu5wVtVeFGmC68EGETJqBi/XrU1tTAMHoM1PFxUEdGIsFmluryitq7Nrt0pVYf3v5vLOpDiayLL+fWl0oQ23emPAJ0GdP++w9Q9ooKVK5e7XG8cs1viL7mGiijomQVuCyxlHgcszqssNfa23zfREREvibKB2w67L4fgSjR+UdGibNMgr8y6jW4a1of/La/AJUW19fsyX3ioHY0s7NMsFZ37gRFPkBUKD67fgwO5lfgz2Ml6BpjwMBkk7NMhUqpACprpR1+VSLoVgmEJbZ/a7jYlTNwBmAuA9Y8X/9zpo4Gzn8NCE/skJ8tEBVXWp3BU3dsjloUVFrQpRP+ZlobqG1I1NttrmmZeB4gInlj0JaotURQ0BPRmd5TPVh/IbISRUOI7pOlxZzYJiYK2Y+/U9peLo5nb3X/taIDsK4DAqQnoDIYnLeorl1dByrypRIGv70o1QET28N7ngac+awUdG2vuL7AlV9LC2ixyBU/q9gi76nDKUGh1UIVHeP5sYyKcn6O3IxOHI15f8xzO9Y3qi/CNDLOSiAiIjoBxwnWq82VFvAX6TEGfP+P8c7syJV78p3Zt9eMS8eEXrFQ2XKk8kF2q/vApsHz2qUjJZj0ztvYHg2+n3hsREOwxdcBOX/XIQ2Lk5owdT+1/TvaxM829jZg0CzU1pTCrtShShOJKpURsY5aKWBMTeg1zQfMQzQd1KOhA4ls+SGpJmw9Wup2/JRe7WxgTUSdjkFbotYSV6fdlUcQ+p4LhHTQ9iVfd+3sdy7QdTxgt0jBSW2oNHbSlcDGt6Qr9A2JrMaR1wBqHwXgxKL7jw+AVU+4LnpFJ+CyHODyL5qWMBCBV1HLTJQ8EMFXsYht/Dnu6vpWlwArnwD2L5O+hygpccb/gJjegIpPqw2pQkMRfdUcj9m20XOvhipMfgHQlLAUjEgYgY05G12OKxVK3DPyHkTqI302NyIiovYyhWjQJ8GI3TlNyxcJJ3Xx/9c5EXwU2asPTu+Hf5xqdX4cXdcsyhInlf0Spc0aG36NtFPLV0TjpXfPAGoa7PqpyAM+nw1ctQRIG9vkS/LLzSiqNKPG6nBuq4816qBvLoio0aFQm4Cle6WmVPnl+xERqsGNp3THhcNSOrSpVqCIMujQPTbMbX3YrtGhiDbILwlB/C48PL0/LnptnTPrtqERaZFIi/77/R0RyRZb7xG1lmj0I65yN6aPACbeHVi1JEUNV1H7qi5gK4hs27nLpIBunbRxUvOnljR66izlOVJmsDs5fwKljeo5iVpl4vPnjQDenAS8OgZ47ywgb1fz30fULn57KrDvx/qs6sNrgLemACVHOuiHCSy6Pn0QddVVTY5HXn4Z9P37Q46iQ6Lx5PgncfOQmxGhi4ACCgyLH4YPz/zQmWlLRETkz0Tw8vHzBzrrZDY2d1w6YozyC0C1lU6tcm4xPx6wFcTaduw/pF4UdQ2OxG4z0adgwr8AnQ8vKO9b7hqwbeinR5r0V9ibW45Zb6zH6S/8inPn/4Ypz/3ibJYlgriemK12fLQ+A/cv3u4M+NZtlX9iyW688NNelNdw23xjIhD+2uUnISZM2yQw+voVw9tVxqAz9U0Mx+KbxmJUepRzc6C4YHPbqT0x77KTEGuU55yJqJ6itla+e7nLyspgMplQWlqK8PDO33JN1KoA4f6fpKZclgqg9xnAyOuloGV7a035C5FtWv13LTSRXSwWur6Utxt4ZZTn8fNfBwbPkv4vnvZEtvR3tzf9vNBo4LrVQERK0zGHXSq98POj7r+HyMyY9rh/N6LrJPbSUtjy81GxZo2zpbNh3MlQx8ZBHWGCnNkddhTUFMBR60CoOhQmnbznSxQM/HF96I9zpsBnsdlxuLAK81fux+YjxYgN0+HmST0wNC0C0YYgWcuItZ1Y19tqpF1XYQmAyofb3B0O4IurgJ1fuR/XhAK3bAJMyc4PM0uqMP3l35wNpxp7/PwBuGRkFyjclPE6WlTlDO66q3cqqiOsuHOiM0uZmsoqqcbO7DLszi5D7wQj+ieZkBTRQY2PO7n5YJXFDqVCgdgwLVSqIHnPSuTna0Pu4yVqC5F9OvRyoNc0abEngpbBFqhzBmplVApCo/dcm0wwNQjClmcDvzzl/vNEvdrsP9wHbUWAfu9Sz3M4tBKoKT1xiYUgpDKZnDddD//qSqxSqhAfys61REQUeLRqFXrFG/HEBQNRUWODVq1ERGjgZNi2iKhf+3cAVBZE8kdsH8/jokeDWO/+bduxMrcBW0GUPZjcJ95ZM9ddAM9Tgyqxiz63rIZBWw9EgFbcpvT1r/Wh+NuOYDUEIr/DyytE7SFqoBrjgy9gK0eGOGDgTPdjYfFAZLprMzmRVeFJXdOHxlTa5muchUS5LKSJiIiI5C5Uq3Zu7Q66gK2c+2eIYLI7E/7tkhywI8t9gykhr9wMi4eGcroTNM0SDayIiMj3GLQlosAgapNNvh/oNtn1eHgScOVXrlkUIsjeXPA13kOdVU0IMOZmz1938m2+LxNBRERERP5L7A6b9QmgbVBXV5Q4GHsr0G2Sy6eKZnKeiHIXWjc1iwXRNKtfovvtuEkmvbN+KxER+R4voRFR4BAB2gvfAipygeLDUia0WPiK4w2JemXj/wUsvbvpfYiga9JJnr+H2LI27k5gzbOux4deCXRppqYuEREREVFLSn51mwjctE5az1qqpEbIIuFA7xpoHZwagfAQNcqqbU3u5ubJPRDnodGUaMr28iVDMevN9ccbkQnivt6aPRzxMm2qRUQUbNiIjIiCU0U+8NsLwIZXpbrEgmgkN2uhlGnrpmnDcaWZUhO2AytE5S+gx1TAmFjffZiIiDqNPzb18sc5E5H8iZ7iu3PKce37m3CsuNp5TK1U4OqTu+L6U7o7g7MeWaqQVWbB7txK7MiuQM+EcAxMjkBShN5t8zIiIuo4bERGRNScsFhg4r3AiGuAynyp9IHIYBBN5jwxVwBHfgOW3AWUHgMSBgJdx0nb1+QesBVBZjF/USNN/Jwtrb1rrQEUSkDNOndEREREciKCq30Tw/HljWNRWGlBjcWO6DCtszRCaHN1acU69qf/IGnHl0gyxGJy4hAg+QpAfzKgCIFc2e0O5FdYYK+tRYhGhShDC9endjtgNwNqvdTsjYjIT7A8AhEFL12YdItq0KSsOVlbgIUXN/j4D+m28xvg6iVAuIy6DzcMuubvAn58ADiyBtAZgeFzgVHXNy0b0VBZFpCxHvhzobTAHXEtENfXpfkF+ZnaWqAiD6i1S78H4kZERER+T5QzaHFJg/JcYOEsIPfvxrvl2dJt7xLgoneBARdAjvLKavDJxgy889thlFRZMTjFhAfP7ueszesxQG2pBEqOAJveBQr3A13GSI3eTKmAiqEQv2UuB8xlgEItvTdhZjgFMD5TEVHgK8+RbiKjVgRWw+IBQ3Tr7qOyAPjxfvdjYjGY/Zc8g7Z5u4C3T60vASEWOaIsxMFVwKWfus8sFuUfPpoB5O2oP7brW6D/hcAZT0lZyuRfxO//zq+BdfOlrOv08cCkB4DoHsyiJiIi8gNVFhsKys04UlQFjUqJlMgQxIWLZmOq1t1R8aH6gG1jyx+SApvhiR0y545SWGHGnZ/9iV/3Fxw/9uexUsx4fR0+nDsKJ/eIafpFNjOwbznwxRzpwrUgSpuJdfCc74GkoV78CahDiMdUBN9X/Bc4vEba6TjmFqDvOYAxnieZAhKDtkQU2AoPAAtnSP/WSTsZuOBNwNSKIKu1Gsj5y/P4wV+A3mdAVkRw7sf76gO2DWVvBfL3NA3ais/d9plrwLbOji+B4XMYtPXH+s1f3wLsX15/bPf3wL5lwDU/A4mDfTk7IiIiOoGSKgs+/j0Dzy7bC5tDCkCGalV4fuYQTOgZgxBtK97WH9vkeaz0KGCtkt3jkVVS7RKwrSNisQ99vQOfXDcascZG9XtFY+KvbqgP2DbMvl18PTD7O+4g8ze5O4B3TgPsVuljkW37w7+A/T8B586TSsARBRgWdCGiwM4u/Ogi14CtIOrSLr1HyjptKVELtrm6tRFdIDvmSiBjrefxvUvdZxRvfs/z12x8q36hRP5BZII3DNjWEY/jkruBqmJfzIqIiIhaSGSVPrV0z/GArVBlsePGDzfj6N8NyFrMlOJ5TJTEamnfAy/acKjI49iB/ApUmG1NBwoPSkkX7ojEhSrP90kyJB4v0VfE3fsQ8Z5G1GkmCkAM2hJRYAdtiw66H9v9nVQuoaUM8cDomz0HdHudDtkRjRa0Bs/jbq9GO6StR57YaoBaR4dMj7xEbA30JGOdlKVAREREss2yffGnfW7HRAxXZOCKBl0tJsoCiAa87gy5HDDIr39BZDMNx9RKhfPWhMPS/J2KGv/kP8R69dhGz+P7fvLmbIi8hkFbIpIla14+zIcOwZKRAXt5KzJiG2+L8kQEHsX2qJYS9cKGXgH0mtbouBaY+ZE869mGxgDDrvI83ufspsdCooD+53v+GnEO1I22n5G8iWZ7nohsGgWXAkRERJ2h2mrD0aIq7M+rQHZpNRwNMmVbymxz4Fix55IF4r7NrQnaijXrZV8CmlDX411GAxPuBDQtbGjmRcPTIqFyF5gFcObARES7C+qKuv0iscId0Yw3JLKDZ0mdSqxXlc2UAWGDXQpQrGlLRLLiqKpC1R9bkfOf/8B65IizG6hh/Dgk3H8/tGlpHbf9SwRbW/viLgrcn/cKUJYl1QMTiz2RrSDqwsoxkKnWAmNukurtNm44cfbz7ptMiJ9j1PVSXVtRKqEhUfs0eTi8prpEypY+vFqs1ID0U6QmciEm780hEIgs8GUPuB8bcFHrm/IRERHRCYkg7fPL92LxH5mw2msRE6bFv07vjdP7JTSbOdqYqF3bNzEceeXud4gNS4uEXt2KZmQqNZA6Crh5PZCzQ0pyEGs8U6ps+xbEhevx0qyhuPXjLc7s4jpp0aG4a1pvhOrchDVExvAp9wIr/+t6XKEAzn4BMHqx2ZrYui/qsebvBuL6A3F9W9dbg4CQaKDf+cD2z92fjR5TeJYoIClqaxtX5paPsrIymEwmlJaWIjw83NfTISIvqNq6FUcuubRJ0wB1XBy6fvoJNImtWGCJoOMnlwNH1zUdG3UjMOVhz9vDAokIfObtAvb8IC1g+50jZRg0F7QuPgL8/gawY7EUyB1+NTDgQunrvEE8dqufATa86np8wr+B0Tc1X1+YXNWUAVveB5bd37QOs2jCEdnKiyFEPuaP60N/nDMRtV1BuRnXf7gZm480rRv/5AUDcfHwVCg9ZI668+fREpz3ym9NemrpNUr8eNsEpEU3Uw4rQFRbbMgpq8GyHbnOxmQTesWif1I4EkwhzddBzdwM/PKkFDhNGARMug+I6dV8CbGOJNbgC852TYYQAePZ3wIxPb0zh0BRfBh476ym9WunPQUMvYzZtuRXWro2ZNCWiGTDVlqKYzfdjOrNm92OJz39NEzT3Wzpb05pJvDDv4G9P0iBYJFhKwKQ4++QsjbbqNxcjqKaIpRYSmBQGxAVEoUofYAFEm0WoLpIykgIjZVq5HqzDqtoIufOVUuAtLHem0sgqC4FSjOk4G15NtD3HOkcNpeNTiRT/hgA9cc5E1HbbTtWgunzfnM7Jrbyf3frOCRGtDxxoNJsw9oDhbhv8Tbkl0u9B7rFGPDczCEYkBQOtaptazRRriG3vAYFFRbYHQ7EhOkQZ9RB25rMXX8ggreiZ4MI1OrDvZs48c40oPhQ07H4/sCVX3voMUEeiYCtaCq961sp+H3SlVIigp478ci/tHRtyPIIRCQbtdXVqP7rL4/jFb/+2vqgrdh6dP5rUtMxUcNWFy4Fa7Vtz7DNr8rHUxufwrLDy1ALKeWhX3Q/PHvKs0gxBlAQTJRXEKUfvK2mFFjzvOfxtS8DiUMAbaNabOSZKCkRMhA482nxDs27AXgiIqIgszPbc5PPwkoLKi22Vt2fQafGlL5xGJB8MkqqrFAqFIg0aBBnbHv9WYvNji0ZJbhl4RZn0FYI0ajwwNl9MX1QIsJDWl7CQfZ8tUNLvP9wF7AVRLkEkX3LoG3riISDQTOlEl+eahYTBRAGbYkaZhWKmk5VBYBKB4RGSzVMyXuUSqhjYmDLznY7rOmS2rb7FVfUO+iqerWtGvO2zsOPh390Ob6zcCduWXEL3jrtLcSExHTI9wrqv0Xxd+iJ+Du1iywTBm3bhAFbIqKAVlRpRmGFBdVWOyJCtYgN0yJEy7d93hQf7jmYqlYqoFW3/uKpQqFAoinEeesImcXVuOLtDc56u3XE78z9i7cjPcaAsd25nm23EzU9tla3/3sEKwZsKUjw1ZuobsvMts+Bnx+tf3GN7g7MeA+IG8Agh7eekGJjEX3NNcj9v/9rOqhQwHTmmT7/fS2oLsA3+79xO3ag5AByK3MZtG0vEWAXTcfy97gf7z4F0HJ7MRERUWOHCypx68d/YFtmqfNjrUqJOSd3xXUTujm3vpN39IwLQ7hejbKaphm1Zw9ORIzBt4+FKIvw5ZZjLgHbhp5bvhf9EsOdQX9qh7A4QKEEah1Nx0TJNvZoIKIT4P5I6lyihmhpFnBsI7BvGVCwF6huWpDf5zLWAUvucr0aWngAeO9soKxRoXPqNCKDIPz002A86yzXAY0GSc89C3Wkwee/P1XWKthqPW9py63K9ep8ApJofDbqBkDjJpNWlLcYeimg4nYoIiLynvIaqzMgumpPHjYeLnI2QrI3bGMvAzml1bj87Q3HA7aCxe7AG6sP4rONR2GzuwkcUacQzbEWXD0SRp1rjtSg5HDcNbUnQq1/11j1EfF7sT3TcwmHQ/mVqLHy96XdRE+IYVe5HxONdQ3c1UlEzWOmLXVuwDZnG7BwhlSEvU6/84AznvJNrUx3KvKlDFtPtTUPrpIKnJNXiPIICQ8+gJjrr0f1n1uhCguDvm9vqLNXQPnhA0BIJDD2H0CX0dLVay8zaAxQK9WwOdwHbhMMMvm99ncRacDcZVITOXFRRRDZt+K5w9TF17MjIqIgUlBhxks/78MH6484l7eCKUSDN68chqGpkdC0Yat7ZzhcWIVjxe63W7+2+gDOG5qMpFY0v6K2UykVGJQSgaW3jcee3HJkl9Sgf2IYkjXliP3uMqD0KNBtMjD6RmnNo/Lu23KdWomBKSas2pvvdrx7nAF6jTx+r/2a3ghMvAcIT5J6MtSUSNm14/4FDL64XT02iCg4MGhLnac0E3j/nKaZkTu/AiK7ApPulxod+ZrdImUAe3L0dwZtvUwdEeG86Xv1BAr2A29OAMzl9Z/w2RXAoFnA6Y8Dhmivzi06JBrndT8PX+z7oslYz4ieiAv1fiA5IIk3LwkDgVkfSwtchQLQRwAhEb6eGRERBZHa2lr8uD0H76874nK8tNqKK97+Hctvn4Au0QbIwb68BmulRsqqbai22L06n2AnArfJkaHOG6pLgBX/BTa+6bqrb+tHwDU/AfH9vb677YKTUvD6LwedWbeN3TG1N0sjdBSRZHLybcDgWVJ2tVovJS+xJisRtQAvn1HnydvheSu7WLCIZkJyoFQDkemexxMHe3M21FBNGfDjPa4B2zp/fQKUHfX6+QpRh+CmITdherfpUIoaVX8bHDMYL09+OTDr2YqM88KDQO5OoPQYYPfim77QSCAqXbrQw4AtERF5WX65GS+v2O92zGxzeMxU9IX0ZoLHBq0KOmZO+k5ZpmvAto61ClhytxTU9bLkSD0+mDsScUady+/JUxcOdNazDTgOh5RUlLcTKNzv3XMukhFMKVLPFFMyA7ZE1GLMtKXOU3TQ85ioHevs/i4Dxnhg4r3AomubjmlCgB5TfTErqgsW7v/J87nY/QOQOMTr5yo2NBb3jboPNwy+AaWWUhjUBkTqI523gFN8BPj+DuDAz1LJE1GeYvKDQP/z2TyBiIgCns1Ri5yyGo/j+3I9Z7d6W/fYMMQadc5Ac2Ozx3Z1Cc6Rl4l1lCeHf5V2FXn54rRWpcLI9Ch8c8s4FFaanTWaow1axIbrnGMBRQRo9/0I/Hg/UPn3hZa0ccA5L0mBVCIimWKmLXUesbXZE0MMoJZRDZ/uk4EJd0lZtw23slz5jXRVlHynQTZrE0oNfCVMG4Yu4V0wMGYgukV0C8yAbVk28OH5UuC8roifyJ4XQdy9P9YfIyIiClBalRI94sI8jg/vGgW5SIwIwcJrRiEtur6Rp6gudOFJybjq5K7QqgMsEOdPFM2ce/EgQdy8T5RJSDDp0T/J5KzBK0o5BFzAVji6Hlh0XX3AVjiyBlhwtrSLjIhIpphpS50nqrtUdqD4UNOxU+4GjInyOfsiiDzuNmDoZUB5tlRryBAnzVHJaxs+I7I6e58N7Pra/XifM709o+Aito6JemvurPgP0O0UqbECERFRgIox6nDPtD645v1NTcaiDFoMT5PXRdue8UZ8fv0YFFRaUFFjRaxRj5gwLYx6313oJpEgcqrn0yB29Yk1L3WOijxg2YPux8qygKytTNIhItliNIo6T3gicMViaetJHa0BOPVhoP+F8guGirmJupldxgBJQ/+uNySzOQYbXRgw5WEg1E2zMdFt18iAYafK2uJ5TCxyre47VBMREQWS4V0j8eQFAxEeUp/v0j8pHJ9dP1pqMiUzceF6Z03SkenRSI8xMGArB6Lx1Lg7mh4XwdrTHwP0AVhDVi5sNc03nT7ymzdnQ0TUKsy0pc4lGgjN/BCoKpBeMPUmICwBUGt55qllRJ2pa1cBOxYBe34AQqKAMTcDcf2kJlUyZ7PbUGQucnafjtBFQKf2o3py4iKGJ9owQMW/YyIiCnwRoVrMGJaC8b1iUVplhVatcGbZRhn86DWdfEvUqx17K9BzKrB2nvTeqOdpwMAZQEQXv3h0SqosqLHaoVUr/et3X5S/E7sqKwvcj0f39PaMiIhajEFb6nwisOYHwTWSscguwNh/AMOvAlQaQCO/rBZ3siuy8emeT/HV/q9gr7VjWtdpmN1/NlKMflInWWSci+CspaLp2PC5QFi8L2ZFRETkdSqVEskRIc4bUZuERgFpY6X1ld0irbGU8q8fW15txY7sMvzvx93Yl1OB1KhQ3D61J4anRSHS4AcX8MV6dew/geVuSiSIBITuk3wxKyKiFuHebyLyD6JUhcjU9pOAbU5lDuYum4u3t7+NwppClJhL8MmeT3DZD5chszwTfiE8Gbjy66Z11npNA8bcxIx5IiIiotbShEhrWj8I2NrtDvy0Ow+z3liPLUdKUG62YWd2Ga59fzMWbshAlcUG2RPnefBMYNBM1+M6I3D5IqkkHhGRTDHTloj8hsNsRq3ZDGVICBQaeTfUWJu1FkfLjzY5XlRThM/3fo5bhtwCtUot/0WuyAa5/leg+DBQVQjE9pJKnIhsESIiIiJqtfIaK5QKBQw6ea8Fc8vNeOSbHW7HXvh5L6YPSUKXKHn/DMezbc94Chj/LyBvJ6CPkEqwiabTcl+PE1FQ4zMUEcmevaIClowMFC14H9aMIwgZPAQRs2ZCm5wsy+BtpbUS3x38zuP48iPLcXm/yxETEgPZE4HbiFTpRkRERERtllVSjdX78rFoSya0KiVmj+2KIakmxBr1sjyrxVUWlFZb3Y5Z7bXOn6dLlH/sgnPuHBM3kYBAROQnGLQlok5TbbVBpVA6Gxa0laOmBhU//4ysu++pv98/tqJ44UJ0WbAAoUOHQG5UChVCVJ5r3unVeufnEBEREZG82ewOZ4BSr1FCoVC0+X5EgPPytzbgYEHl8WNr9hdgUp84/O/CgbIM3KqVzf+8unas8YmI6MT4LEtEHS67pBpf/XEMN3ywBf/89A+sP1CIwgpzm+7LVlCA7AcfanK81mJB1j33wJqfD7kRQdlL+17qcfzSPpciUs/mfERERERyVWG2YVd2GR76egeufX8TXl11ABlFVXA4attUG/aLzcdcArZ1Vu7Ow67scsiRaDTWNdp9Jm14iBrx4fILNBMRBRJm2hJRh3KXRbBkWw5mDEvBPWf2QbRB16r7E2URRIDWHeuRI7CXlEATGwu56RPVB9O6TsPSw0tdjg+LG4bxKeN9Ni+/VZ4LWCsBpQYIiwXUfJNAREREnaPaasfS7Tn41+d/umTFvrLqAD6/YQz6Joa36v4KKy34bFPTXgd1PtxwBKO7Rbdrd1pniDPq8dIlQ52NyKos9uPHNSoF5l96EuKMrVvXBz1rNVCZDzhsgNYorWmJiJrBoC0RdRir3YGP1me4zSL4fPMxzBrZpdVBWzgczY/Xtj7bwRuiQ6Jxz8h7MKvPLHyx9wtY7Vac3/N89IrshdhQLtBarKYMyFgP/HgPUHhACtYOuRwYfwe7/RIREVGnyC83495Ff7nNvv33F3/i/atHIqoVa1qxWm0uQ9fehuxdb+mfZMLS2yZg6fZsbD5SjD4J4ThvSBKSI0OgVskryCxrJUeBVU8C2z4D7BYgtg9w5tNA8kmANszXsyMimWLQlog6TGGFBZ9uyvA4/snvGTipS0Sr6oFp09IA0WzM2rQJgjopCSpTBORKBG7FbWjcUOdqXankwrbVMtYBCy+u/9hWA2x6C8jaAlz6idQNuK2ZuyLLQaMHQqPbdh9EREQUkHZnlznr2LqzPbMMJVXWVgVtowxanDskGa/+csDt+KwRXWSXZVtHpVQ4m41dN6E7bA4H1FzPtl5ZNvDhBUDB3vpj+buB988B5vwApI1t24NjrgRqSgDx3soQC6jk16CZiNpHnq8MROSnamGxe86MrbHaW50Yq46JQfy//tV0QKVC4n//D5r4OMidUqFkwLatgdWl9Q3oXIigbfHh1t9nRT6wdSHw7jTgpcHAhxcBh1ZLGb1EREREf+8ea05rM2M1KiUuG90FCW5qwA5Li8SgFJNfnHcGbNsob6drwLaOeGO09F6gsqD1OxEL9gHf3grMGwa8Mgb4+T9A6bG2zpCIZIqZtkTUYSJCtTijfwI+3eR+wXDRsBQoT9CFtjFlSAhM550LXb++KHztdVgzM6Hv3x/R118HbZcuHTRzkiVLBVB00PO4KJuQOqrl9ycCs78+A2x4zTX4u2A6cNG7QL/zRDp0++ZMREREfq9fksmZvOgu2SAtOhSmkNZnNKZEhuLLG8dg0ZZMfP1nFnRqJa4Yk4ZJvePY0CvQHVjheSx7K2Ctat39FR8C3pwMmMvqa+WufQnY8z1w5bcsIUYUQBi0JaIOo9eocOOkHli6Ixel1a7lDIanRaJPK5s21FGZTDCMGAF9376oramB0mBwBnMpwIktXmodYDO7Hw9LaN39icYPv7/ufmzJXVIA2JTc+nkSERFRQIkJ0+L6Cd3w2i8Hm5QKeOL8gYhzkzHbEsmRobhpYndcMqoLRB5Da0oskB8LT/I8pgsHFKqW35cI0P72Un3AtiHR/yFjLTBwRtvmSUSyw5QiIupQaVGh+PaWk3HVyV2RaNKje6wBj57T39lhNr6NC9w6qrAwZ7kEBmyDhKjNNfhS92MqLdBldOvuT2xL81SfQwR0RU0wIiIiCnpGvQbXTeiGt64cjsEpJsSH63B6/wR8e8s4nJQW2a7zo1IpEROmY8A2mPQ6A1B4CL2MvBYIa0W5t+oSYO8Pnse3fe454YGI/A4zbYmoQ4kmY12iDbj3jD644ZTuUCkUiA7Ttqr5GNHxwOzYfwC9pwF2K3BwlVSP1mEFZn0MGFuZaas1ND+uZPMGIiIikogs2Cn94p01Z0XPBoNWhTA91wrUBvpw4NqVQMkRKei66W0g+0+gyxhgxLWtayAmgr/aMFEo1/24zgQoW5G5S0TBGbR97LHH8P3332Pr1q3QarUoKWEGE/k/seU/r6wGGw4VOYORo7pFIdaoc16NJ1datQrx4VwwUBtVFQG7vwN+flRqziAWn33OBuYulxa+YfFS6YTWiEwHdEbAXN50LGkoEBrVtrk67ECtgx17iQIU17QUiLJKqrE3txwH8yvRK8GI7jEGJEaw9JQ7kQat1x8fCiCiP8N3dwIH/65ra0oBpjwKxPWVdpW1JstWEJ8/8npg6d3ux0dcAyjbFuax2BxQKxWt7kFCRH4YtLVYLJgxYwbGjBmDt99+u7O+DZHXFFWaMW/FAbzz2yGX43dO7eVsIiCacCHYg2wiuGYpB/QR0oJCBMiIWkuUMNi7FPjmVtfA6M6vgcKDwOVftj5gW1cDd8YCYOHFgMNWfzwkEjjvVcAQ0/rfebEQF9kS1cXAgIukjAnWxSUKKFzTUqDZm1OOS95cj8JKy/FjSSY9Prp2FNJjRAZf8LLaHc4EDXFuRP3aaIPOWRqBO8aoTUqPAe+dBZRluR77ci4w+1sgvn/r71PsXux3LrDzKyBjnevYyOuA6B6tvstjxVVYuTsPq/bmIyUiBJeM7IKUyBBmlhMFctD20Ucfdf773nvvdda3IPKqP4+WNgnYCs8u34uxPaIxLK2NWXqBoOQosPh64Mhv9dt2Bl4MTH209VvYicqzpQxbd3K3ASWHAWN868+TWgOknQzc/LsUAM7bCaRPALpNBEyprbsvEaRd8xyw9uX6Y3uWANHdgSu/kbIoiCggcE1LgSS3rAZz39/oErAVskprcMvCP/D+1SMRHRaczbHKa6z4eVcuHvp6B8pqpIu7ImD70iVDMTQ1wrmLjKhVjm1yDdg2tOxBKRGhtUkDQngiMOM9IH8P8NenUgmwIZcCEWmt3jl2IL8CM15bh6IGzwkL1h3B/y4ahLMHJSJUy4qaRL4kq79As9nsvNUpK3PTEZHIG0RXzrJMYNd3QNEhOLpPQrKmj7OxVnZpTZNPf3P1IfSfFQ69RlZ/Ut5RkQd8ejmQvbX+mNgq/tcnUjbktCdOXEuUqCFLJVCe4/mcZG0FUke17Zxp9FJgdfwd7b9Q0TBg27Br77pXgCmPAOogz74nCmJc05JsiNfTvF3Arm+dO0si+56P6b3C8Mr66iafuiOrDEVVlqAN2u7JKcdtn/7pciy3zIwr3vodP94+PuizkKkNDv7ieUy8d7I1fV/ZYiIxRty6ndLmuyittuDBr7a7BGzr3LtoG0Z3i0aXqCB8f0skIx5aGPrGE088AZPJdPyWmtrKzCeijmCtAfb/DMwbAfz0MLDlPSg/n41e312Ajy+KR7i+6QtXXrkZFpuHrvSBriLXNWDb0NaPpKAuUWuIYH9z5Q/kkMUqLkp48sf7QFUBgjIwkLsTyNkmXfRyOHw9IyKf4ZqWZEFk+C2cCXxwnlTK59dnoH3jZFwf9gtuHhPr9ktqLHYEo7JqK55fvtftmGhC9vmmY7A7gnStT20X1c3zmCgl5+OGYcWVVqw9UOh2TPy+/5FRjKBMHik6BGT/JSVj1DCRkPwoaHvPPfc46/k0d9u9e3ebJ3PvvfeitLT0+O3o0aNtvi+idgUhv7hKyhZtqCwTKesfxZzh0U2+ZELPGGdH2aDkacuPIOqGumv6RNQcQxww+DL3Y6JOcsJA358/c6XnMZE1IeryBgubFTj6O/DONODVMcBr44A3JgL7fpQWvkQyxDUtBTy7Ddj0rtsL66Y1/8WsXgpoVa5vBcXHpiDt0VBttWNfXoXH8b+OlcJsC86ANrVDn7M8NwU7+TbA0IZyXx3IfoL1anWwXcQRCQg/PgDMGw68Ph6YNwxYfANQmunrmVEQa1Wu+5133ok5c+Y0+zndujVzNekEdDqd80bkU9l/AvamW0QE9cHlOGPGA3hpTf0xo06NC4YlQ9Vo4Rs0mqtZK64esxkZtaWEwSn/Bgr21NdJFnThwOWLgPBk35/TgRc6s/Dd6nUmoDchaJQeARacDdjqyxs5M+w/uQS4diWQNNSXsyNyi2taCniVecCmtzwORx/8CiPTz8Ga/fU7Q+aOT0ecMTjfi+k1KqTHGJy759zpm2iEjjVtqbXCk4BZC4HPrnQthdD/QqmBrdK37x9Neg16xIVhv4cLFsPSIhE0RKLBqieBze/WHxNB7T3fAzWlwMz3gdCmyVtEsgraxsbGOm9EAa2mxPNYbS1CVfVXJEd3i8Kj5wxASkQogpYxEYjrJzV1amzADMDA5wyq56h1QCka1bVkkXvxAqAsG8jdDoTFAzG9pOM+3krmFNMbSBsLHFnrelzUb578AKALku7bdjvwx0euAduGC91f/gdc8AYv3pDscE1LAU88Bzez20lnKUZUqMb5/4hQDW6e2AMXnJTsDF4GI1OIBrdP7YVZb6xvMqZWKjBrZBeolAqfzI1kSJSAaknAVSQidJskNcEV75XE+8zEIdK6tpUNwzpDjFGHx88fgEve3NCk/MfMEamIDaaLOCLh4I8P3I8dWSONM2hLPtBpVaUzMjJQVFTk/Ndut2PrVmlrTo8ePRAWFiRvZsk/JQ/zPBaZjuTYKPzy757HF7mmkODcRuZSj+mSj4HP5wBZf7huBxLNmIIleEUeme1mZFdk4/uD32N/yX6MSBiBU1JPQZIhyVlWxyMR8Be3xEHyO7vGeODCd4Adi4Hf3wDMZUDP04HxdwJR6Qgatmrg2EbP46K+rchcYMY9+TGuackv6Yyo7TYJin3L3A7X9jsP9yf0w+2n9XJmkMYbdcG7a6xBNu3j5w/E/32301kuQYgM1eClS4YiJSLE19Mj2dTv3w5sXQhoQoGTrgSiugOGZjIwRWPayDTpJkODUiLwzS0nO2s6bz5S7AzU3jSxB8b1jEFEMJVLEWt5UdrPk/JsIK6vN2dE5KSore2cwnuijMKCBQuaHF+5ciUmTpzYovsoKytzNiQT9W3Dw8M7YZZEHmrafvtPYM+SpmPnvQKkjZPti+4JrwhX5AB2q9TkqbmyBm1RkS81XxIveCFRUrAtJKJjvwf5HZvdhg05G3DLz7fAVlu/EDJqjHjvjPfQK7IX/Jp4CRVbUMXfV4hJWsAHE/F8suRuqcGNO+L5ctZHfC6gDuXt9SHXtOSvrFnboXl7UpOyX47Y/th32ntITeuGUK3aL5uGldVYIS77RoZqEarruJ/BbLUjv8LsLJMgMmxjwnSID9czy5akoN2ns4FjG1zPxtArgSkPA4YYvz5LFTU2VJit0KiUiA4LogzbOqLpmKhh6yk8dv2v8kwkoYBfz3Za0LYjMGhLPlFyFMhYBxTsBba8LwVkRE3Gsf8A9i4FEgYBY272rwdHbOfY9jmw5jmgsgCISANOfQjoPlkWW3MocGVVZOGCby5ApbVpQyoRsH1z6puIEkF+8l9iu9+rY90vcmd/A6Sf4otZUQDzx/WhP86Z/N+Pf2VgoC4PcRuegPrQCkAbhoqBVyCjxxW44vOj+OaW8UiO9J8MUpvdgQP5lfjv9zudtXhVCgXOGpSIO6b2Qlq0wdfTo0Am1ji/vy5dqHbnqiVS2SzyXzVlwOLrgT0/NB2L7SOtaUVZCyIvrw3979IqUWerdQCLrpVeeCfdJzUUEgHcZQ8ApceAiK7+9RiIwukrnwA2v1N/rOQI8OVcYNpTwIi5gEqqaUbU0TIrMt0GbIW9xXtRbC5m0NbfiefEGQuAr26USiEIKi0w5VHpIhcREfnE3nwz7v6tCFcPuw9jhzwCs60WH26vwrL3DznrVzrkm7vj1tGiKpw3/7fjpQtstbX4emsW1h4oxFc3nexXAWjyM5X5wO9veh7f8AaQPFwqhUD+SR8OnPk0UF0CZDToWRHbG7jkEwZsyWcYtCVqTNReTBkpNRhq3GRI6DnVv86ZyKzd0qALZkMrH5Nqz0akentWFCRqGnbKdcPWXO0o8g/aUKD3GcBN66ULW+IxFdn8okSKGCMiIp8Y3ysGzy7fi+d+zcFzjcaGdolAWAeWFehsNVY7XvvlwPGAbUP55Wb8vDsXV4xOa75WPlFbOeyAtcrzuKVcSvwh/2ZKAWZ+KO20LcuS1rKipKDo4ULkI8FdbZ7IHVEu4IynAKWbhWy3iVIwwp+IrFpPmRSi/mx1sbdnREEkLTwNBo3BeWssSh8Fk87kk3lRBxOZtRFdpB0K6ROkut8M2BIR+VRKZChO6RXb5Lio1frw2f0QadD6VR3bNfsLPY4v3Z7jNqBL1GHvD3ufDYREut+hOGgmoNHzZAcC0VRONBzrcapUw5YBW/Ix/7m8SuRN8f2B61YBP/8HOLxGeoEefSMwcAYQ1nTxK2taY/Pjai4wqHM4LBbElSnwdZfHUFlVBktSFD7K/R5fHZOa/N078l7EhfLKNRERUWcQTbSevmgQvv0rC2//egjFVVaM7haFf5/eG91jw/zqpKtVCphCNMgsqXY7Hh2mhVrJfCTqJOZyYOhlQMIAKYAryiX88j+pOVl0DyDtZJ56IuoUDNoSuf3L0AEJA4EL35ZepJUqwBAH+ONiMDxJ6mYqyiQ0JhqsiauJRB3MUVWFitWrkXXvfait/vsNllqNuTfNxcgx9yEpsRd6RfWCUuGHf1MkayVVFhRUWLAnp8z5Bj89xuDs/K1W8XeNiIJPXLgeV41Nx/RBSbDX1jpLIhj1/tfLIMqgw7UT0nH7p3+6HZ8zNh1aNZ/nqROI0k9fzAWOrq8/JgK1570GZP0BDJoBmJJ56qlDibrjuWU1OFJYicJKC3rFGRFj1CHKj3ZIUMdg0JboRAXJxc2fGROl4unvn1vfJEgQWz0ueAMIZdCWOp7l2DFk3n6Ha2kOmw3VL72OiYPehDFhGE87dThR11B0FReNaeqIAMWbVw7HsK4R0KpUPOtEFHSUSoUzeOvvxvWIwRkDErBke47L8Zsmdkf32KZlmIjaraYM+OHfrgFboXA/8MOdwOzvgfAEnmjqUDa7A9sySzHn3Y0orbYePz6lbxweO3+gMxmBggeDtkSBTmQHJw4FblwnNVbL3w2kDJeybEWxdaIOVmuzofjjTzzWUi587XWEDhwIlYn1bKljMxIWbTnmErAVKsw2zHn3dyy/fQK6RPNNPRGRv4o16vHf8wbgxond8dPOXGdm7Wn9EhBv0sEUwuwz6gSiDMJeqaxXEyJwW5nLoC11uJyyGlz+1gZUWlzrdP+0Kw894g7hjqm9oFUzESFYMGhLFAxUaqkxkLgReaGWreXQIY/j1mPH4DCbobBaYS8thUKphDoqio8LtUt+eQ1eX33Q7ZjZ5sCa/QW4lEFbIiK/Fh2mc94GpUT4eioUDMQuRU8NneuCuqKCQpUFFrsDBp0aoVqGWKh9/jpa0iRgW+eDdUdwxeiuSI4M4WkOEnxGISKiDqXU6RAydCiq1jfaSvY3fb++qLVakf/c8yj/6ScoQ0MRNftKhI0bB3UcG5NR29gctSiqtHgcP1jQoDwMERER0YmIMnkqDWCv36LekD0sCat352Heyv3O+qPD0iJx86Qe6BodykxIarMjRVUex0Qw12p38OwGEVZrJyKiDqVQqRBx3rlQ6N3UW1IoEHPDDciYcxWK3n0X1qNHYd6zB9n33Y+se+6FLV/KWCBqLb1a1WxNw5Fdmc1NRERErSB6gAy72u1Qbdo4bCvV4qr3NmLzkWIcK652lmg666VfsS2zjKeZ2mxwMzsJEk166DUsjRBMGLQlIqIOp0lORtr7C6Dt2vX4MXVcLFJemY+qP/90Bmsbq1y7FuaDnssqEDVHdNS998y+Hhe4A5JZQ5mIiIhaQRMKjL8TGHkDoPq7brJCCfQ9B5ZzX8OlH+1v8iVWey3uXfQXCirMPNXUJt1jw5zZ2u7cdXpvxIfreGaDCMsjEBFRh1Oo1QgZNAhpH34Ae3Exah0OqEwRgFqFzDv/5fHrSr/6CoZRI/mIUJuM6BqJ52cOxmPf70JBhVQqYUy3KDxxwSAkRbD2FxEREbWSMR6Y8ggw5kbAXA5oDEBYLH7cVYYqD3VH9+ZWoLTKipgwBteo9eJNenwwdxQe+no7Vu3Nd5ZVjgjVOAO2E3vHQaFQ8LQGEQZtiYio815kYmKctzrWnFxn+QRPLR0UWg0fDWoz0T383MHJGJ0ejbIaq7OeXGSoBhGh7CpOREREbaQNAbT1u8cEhaK82S9hXI3aIzUqFC/OGurs12C22WHUaxBv1EGl4mb5YMOgLREReY0qKhKm889H8fvvux2PuOACPhrULkqlAokRIUgEM2uJiIiocwxKMUGlVMDuaJqKMLRLBCJ5wZjaKTxE47xRcGOYnoiIvPeio9UiavZsaJKTmoyZLjgfmtRUPhqdpaoIyNkGrH5Guon/i2NERERE1CqxYTo8Mr1fk+NhOjUeP38gIg3c5dMpRK2AkqPAjq+Anx6V/i3JkI4TBSBm2hIRkVdpk5OQ9uGHqFj9K8q+/w7KMCOirrgcul69oI6K4qPRGSoLgJWPAZveqT+24v+A4VcDk+4DDLE870REREQtFKpT47whyRiSGoF3fjuMzJJqnNw9GueflIIU1tHvPLk7gAVnA9XF9cdCIoHZ3wEJAzrxGxP5hqK2Vr6XJMrKymAymVBaWorw8HBfT4fI+8qygNKj0r9R6YAxCQiL4yPRmWwWwGGVusWyGFWns1dWQqFSQ6lno4ZOtf8n4MML3Y9d/iXQY0rnfn+iIF8f+uOciTqMaN5UkQ/k7QRUGiC2j7Se1bCMTaeyVAJKDaBmxmdns9gczrqjoVq1s2QCdZLyXODdaUDRwaZjUd2Aq5YAxgSefgqotSEzbYnkqmCvFGQR2z3qJA4BZn4IRHALeYcTV2vFAmDDG0BFDtBrGtDnLCCiS8d/LzpOZTDwbHQ2cwXw20uex8VY6ihAZ+RjQUREHauqENjwOrD6aaDWIR1TaYFz5wG9zwJ0YTzjHU1sHd+3DNj1LRAaDYy6DojuCYRyN1Nn0aqVzht1sqoC9wFbQRwXO8sYtKUAw2cWIjkqzwE+utg1YCtkbwW+ux2oLvXVzAJTTRmw6T3gzcnAX58AB1cBS+8B3pwEFOz39eyI2sdudt1C1pgYs1t4lomIqOMd2wz88lR9wNb5umQBFl0HFB/mGe9oRYeAt6cC398BHFwJbP8CePs0YO3Lza8FiPyBtab5cdsJxon8EIO2RHIN2hYfcj924CfpKiN1nIpc4OdHmh4XV2uXPSAFdYn8lc4E9DzN87gYE59DRETUkUSQcPX/PI9vfBuw23jOO4qlClj5BFCe3XRszXNAmZvjRP5EZI6LEivuiOOhMd6eEVGnY9CWSI4q8z2PiTLUokYVdRyRWevJvh+ZmUD+TaUGTroC0Ec0HRPHxJj4HCIioo5kMwNlmZ7Hiw5Iu0GoY1QXATsXeR7f/R3PNPk3UQt77D/cj4nj7P1CAYhBWyI5MjVTs1atA/TMiuvwNxWeiO18Dbf0EbVTpaUSR8uP4lDpIeRW5XrnfEakAdcsB3qdASiU0k38/5qfpDEiIqKOpg0DkoZ6Hu86DlCzGVmHEYkdjmYyl63VHfe9iMTvm2iWnb8XKDos9VDobNpQYPRNwNkv1NeuFf+e9bx0XIwTBRim1hDJUVgs0H0ycJkZiNgAACeTSURBVGBF07GR1wFh8b6YVeDqdornsZSRDJJTh8msyMTTG5/GyqMr4ah1ID40HneNuAtjksbAqO3ERmAKBRDTC7jwzfrMcX0koGfzMSIi6iSiydjEe4A9S5peANcagIEzACVziDqMPhzofiqw/yf3433P7rjvRcFN9Fc5uAL48T4pcCuSAfqcDZz+WOc3cTbEAMPmSE2jRaa+SicFbsValygA8VWSSK71es6dDwyaBSj/vraiCQHG3SFt/dDofT3DwBKeLJ1rd1nNZz3DbrvUIfKq8nDdsuvwc8bPzoCtIDJt7/zlTmzJ3eKds6wzSotpcWPAloiIOltUD+DyRa67OuIHAFct6fzgTrARO/FO+y+gcZNt2Ptsnm/qOBm/AZ/PkQK2gljX7voG+OB879ROFgHa8EQgsqv0LwO2FMCYaUskV+FJwFnPAZPulRoLiC1mxngpkEgdKzRKWuT2nAr89iJQVQh0HQ+MvwOI7Oads20ulx5nEZwXmRIUcA6UHEBGeYbbsWc3PYv+Mf0RE8IGCkREFEDEduXuk4C5y6SdHgoVEBoJGGJ9PbPAFN0TuP5X4LeXpObFIRHAmFulHXzeOOcOx98Nk2sBsaZRqTr/e5J3lecCP97vfqxwP1CwRwqkElGHYNCWSM50BulG3ilJMfAioNskwGEFdOHeqYsk6j/l7wF+eRLI2wVEdZO2Esb3Z1mGALM5d7PHsUNlh1Bjq/HqfIiIiLxGbF+uq0FJnUc0Fo3pAZz5FFBTKu3YE9vJvaE0E9j+BbDlfSnzctBMYOhlzffqIP9jrQKKDnoez1gPdJvozRkRBTQGbYmIGjJEe+982G1S3bHPZ9cfKz0KHPoFOPt5YPBlgIaZ1YEiKSzJ41iYJgwqJbNRiIiIqAOInVvi5i1lmcCH50uJCHVWPQFs/QiY8wMQwcBtwFBppB2gFg+NxxikJ+pQrGlLROQrFTnAd7e5HxOF/StzvT0j6kQjE0ZCo9S4HbukzyWI1XOrKBEREfmhAytdA7Z1SjKk7FuH3Rezos4gGmKPuMb9mCjj1/VknneiDsSgLZEciXpQ5TlAaRZQU+br2VBnqSyQ6ru5Y632TiF/8pq40DjMP3U+9CrXRoJjk8Y6g7ZqsaVR5modDtgKC2ErKkJtba2vp0NERDJXXmNFdmk18spq+LoRqMR7FZFR68mfnwDVRd6cEXV2pu3oG6WScg2JzO5LP5P6sviBCrMV+eU1qDTbfD0VombJ/x0iUbARwdptnwPrXwVqSoC0ccCUh6XGAmqtr2dHHelE2+G5XT6gaFVaDI8fjq/O+wp7ivaguKYY/aP7I84Qhyh9FOTOmp2NsiVLUbp4sbNLr+miCxF+2mnQJLBGIRERuTJb7TiQX4Gnf9yD9QeLEBmqwTUTuuHsQYmIM7pevCQ/p1ACHnYSHQ/yMVcssIj61Be+BZRlAVlbpbrJCQOAsMS/H295X0jan1eBeSv242BBJXrFh+HmST3QPTYMBh3DYyQ/iloZp8qUlZXBZDKhtLQU4eHsph5UWaZiW7jYRqPWe694vhxU5AOLrgEOrnI9Ll785v4EJA3x1cyoM4iFzlunSv82po8AblzDulAkm4BtxlVXw3L4sMtxbc+e6PLmGwzcklf54/rQH+dMHRMcKK+xietciDZooVUHT+3yrRnFuOi1dbA5XN9qTuodi2dmDEZ0GGv2B5Rd3wKfXu5+7OwXgOFXeXtGRE1Y7HZ8/1c2bv/0T5fj4jn6lUtPwtR+8VCruBmd5LU25G8kyUtFLrDhNeD1CcDz/YH3z5VqJAVLiYDiQ00DtoLdCiy9F6jysJWefEJc87JkZqL488+Reee/UPDa67AcPgKH2dyyOzAmAhe8Bai0TTMWzn9dulpNJIPf87Lly5sEbAXLvn2oXPObT+ZFRCRXVpsDe3LKcOvCPzDuqRWY/MwvePyH3cgqqUYwKKq04MGvdzQJ2Aor9+QjM0jOg1+pLAQytwDf3QksvlF6/yV2/7VUyoim2+WFpJOAXtM6dKpEbZVfZsYDi7c3OS7SGO9ZtA155S18D0fkRcz/JvmoKgKWPQj89Wn9sdztwAfnARe/D/Q9R7oMFsj2LfM8lrEWMJcBoZHenBE1w7x/P45cfgUcpaXHj+XPm4fU116FYdQoKDQn2B4kfp/FIvfGdcCWBUDWH0BsX2DEXCAyDfCDGqcU+OwlJShd/JXH8ZIvv4DxtKlQMXuQiMjpcGElzpn3G8w2h/Pjaqsd7609jNV78/HRtaOQaAoJ6DMlakVuy6xfGzX2674CDEqJ8Oqc6AQB21WPAxvfqj/250KgyxjgoneB8MSWbZcXCQfZW4Hf3xBF8IGTZgOpo1r29URekF9uRqXFfVO80morCivMSIoI7Odn8j+MCJB8VOa7BmwbWnqPFNzyk8LmbaZrZsukyMZUMjleLkQjpqy77nYJ2EoDNmT+85/o9u230CS14PdV1CmO6QGc+ghgq5a6rsq8FhQFH4VS0Xzt5UC/oEZE1EKiqc1zy/ceD9g2JOon/nm0JOCDtkqFAmqlwm2mrWDU8y2orBTucw3Y1slYB+z6Bhh5Xcte543xgPF0IH28lLqoNXTKdInaSnGC3+MTjRP5AiNAJB852zyPiZqfNZ6v2AeM5rYPDZoJhARRfV+ZsxcXw7xrl9sxR2UVLEePte4OVSpAF8aALcmOOjISEbNmeRyPvPRSqIxGr86JiEiuymqszkxST779MwsOD8HMQBEVqsWZA903qRQxkfE9uJ6VDbtNyoz15PfXpcSa1tCEMmBLshRr1CE8xP1Fo9gwnbP2OJHcMGhL/pFlKjSu+xmIRI3T059oejyyK3DKXYA2sDMz/EmtzdbsuKO6ymtzIepsYRMmQN+/f5Pj+qFDETp8OB8AIqIGWaZhzXQgjzLooGxu90IACNWp8e/T+yDZzTbj/5zTH3FGvU/mRW7U2gFzuedTY66QmkMTBYA4ow7PXzwEjZ+CVUoFnr14MOLD+dxE8sO9KSQfcX2kK7NWN8Gu9AlAaDQCnt4IDL1M+nm3LgTKs4B+5wIpIwFTsq9nRw2oTCaooqJgLypqel4UCmjT03m+KGBo4uOR8sp8VG3ciJLPPnM2y4u4ZBZCTzoJmrg4X0+PiEg2RLbWnLFd8eTS3W7HZ41IRTBIjQrF5zeMweYjxfhxRw4STXpcNCzFWS/SwPII8iHKcg28yHNfjd5nsp8GBQy1Somx3aOx5J8TsGDtIezOqUD/pHBcOSYNXaJCA/6CGvknRa1oCy1TZWVlMJlMKC0tRTgbnAQ+mwU4vBpYOBNw2FyzT+d8D0R3R9ARf56srSNLtQ4HypYuRdYddzYZi5o9GzG33Mwt4xSQ7BUVzucllYG16sg3/HF96I9zprbLLa3BLQu3YOORYpfjd0ztidlj02EKCa7a9eLtJmtFylhpJvD+dKDwQNNdkNetCs73YBTwLDYHaqx26DVKaNUqX0+HglBZC9eGDNqSvFhrpPq1e5cARQeBruOBlOGAKcXXMyNqwl5ejpqdO5H3zLMw794NTXIyom+8AWHjx0MdFcUzRkTUCfwxAOqPc6b2yS+vwYH8SizdnuNsvHX2oEQkmPQwhQRBuS/yP6XHgA1vAH+8D9jMQJ/pwMS7gMhubIRMRNQJGLQlooBQVF2EUkspFFDApDMhUh/Zoq+zl5XBVlQEe2EhlEYj1NHRzltnsBUXo9ZshkKthjqGzTWIiDqTPwZA/XHORNSxWX155TWottgRqlU5GyK1JLvP7qhFblkN8svNsDkcznrA4mv1mk7IDLRb/246VgvoI9hMjIhIBmtD1rQlIlmy2q3YXbQbj6x7BHuL9zqP9Yvqh0fGPoKekT2hVnp++rLm5SH3v/9F+bLlx4/pevVCyryXoe3SpcPnqo5sWSA5ILGEBxEREZFHIlj7xuqD+HD9EdRYHTBoVZg7Lh1XjumKGKPO49dZbHZsPFzsLLVRXGV1HtOplbj7jD64YGgyIkI7OGtbpQHCk4L3keSalohkSOnrCRCRH9Qatnu/a+yximOYvXT28YCtsLNop/NYVkWWx69zVFUh/6WXXAK2gnnvXhy9/npnQJc6qP7Z9kXAF1cBS+8DcncANWU8tURERCQ/Doe07d/LymuseOKH3Xjr10POgK1QabHjpRX7MW/lPlSZG/TxaORYcTXmvPv78YCtYLY58J9vd+KvY6VemX/AE2tXsYYVa1mxphVrW7HGJSKSCWbaEpF7YsFy5DdgxyIgJBIYPheI6gaEdn6tVrPNjAU7FsDqqF+k1qm2VePLfV/i1iG3Qq1q+hRmKyxE6Vdfu71fy6HDsOXmstt9e5VkAAumA8WH64+tnw+c8T9gyKWAztjub0FERETUbjXlQMkRYNO7QNlRoMdpQK/TgIiO33nlTmGFBV9tdR8E/HB9Bq46OR1pOrXb5m2LthyD1e6+Z/jzy/diYLIJkQbWSG4zcznw16fAD/+qP7ZjMRCRBsz+FohMa/t9ExF1EAZtiaipkqN/B+UO1R/buhA4+TbpFtq55QAqrBXYkrfF4/jGnI2otFXCpDK5zbSFzXPWgjU7GyEDB3bYXIOOtQpY+bhrwLbOkruA7pMZtCUiIiLfs1QAO74Evv1n/bG9PwK/xABXLQVienb6FAoqzM5d9+7YHLUorW6aoCCIYO3O7HKP93u4sBJmm/d3wgWU8hzXgG0dEeQXa93pzwOaUF/MjIjoOJZHkCtLtRQUydwC5O4EKrilm7xEbB1b+6JrwLbOby8AZcc6fQo6lQ5xIXEex+MN8c7PcUdpMECh0Xj8Wk1ycofMMWhVFgLbv/A8vs+1LAUREQW58lxp+7FY0xYfAazVvp4RBQvx/um725serywAfrgLqOn8EgMGN1m0DYV4aCimUSkwOKVpckKdnvFhndOMLJjs/8nzmAj2izUvEZGPMWgrR6Jr5+qngXkjgDcnAa+OARacDeTt9vXMKBhUFQB/fOR5fFszAbsOEqYNwzWDrvE4Pqf/HOjVerdj6phYRMyc6XZMNCPTxMd32DyDUq1D6i7siZl1bYmI6O+mPiJY+96ZwKtjpTXt/BHAby9KQTOiznZ0g7RucefQSqCqqNOnEBOmRffYMLdjIigbHea+vIFCocC5Q5KdjcfcuXNq745vRBaM5RE8EWvdWmYyE5HvMWgrxyL52xcDa54F7Jb64/l7pMCt2LZO1NlvsuzNNGqwVHrl/PeJ7IMbB98IBRTHjykVSvx7+L+RHp7u8euUeh1irr8OETMuAlT1GQghw4cj5dVXoI6J6fS5BzRRrzZlhOfxHlO8ORsiIpKr0mPAe2cBhftdd/OsegLYs0RabxB1JkuV5zHx++eFoFysUY83rhyGJJNrskFadCheumQoogzud44JKZEhWHjtaJevDder8cyMweiXGN6p8w4KoqSXJ2Ktq+M5JiLfY01buanIAVb/z3MGbu52ICLV27OiYKI3AT2nAXu+dz8+4AKvTCNCH4Er+l2Bs7qdhe0F250B2/7R/RGtj4ZBa2j2a9WxsYi75x5EX3st7KWlzpIJ6qgoqCIivDL3gCYa0YmGY29PBRyNagd3P1Vq3kBERJS5Cagudn8eVj0uXeQLT+R5os6TNtbzWHx/ac3rBSLTdtFNY3GksApHiqrQLcaA1KhQxIe73zVWR61SYlhaJBbffDIKKy2w2x2ICtMh3qhzjlE7iTVr9ynAgUZlEpRq4IynvNJ8mYjoRBi0lRtbjRSc9SRnO9D7DG/OiIIxk/LUh4CDK6WmUw11HQ9E9/DaVIxao/OWFt76QKDKYHDeqBOINzrX/QKs+D/g0GppUTv6ZimgHxbLU05EREDWVs9noSzLdUcZUWcIiweGXA5s/dD1uFIFnPU8YPDemiXBFOK8jeoW3eqvFcHdEwV4qQ3EmvW8+cD2RcD6+VK5jK7jgFMf9ur7HSKi5jBoKzeiuVJoNFDlofB5XD9vz4iCkVioXL8a+PVZYP9yaXvQqBuAfucCYZ4bhHW0WrsdUCqddb1IRtQ6IGEAcMGbUj0w8ebHEOd8rIiIiJwSBno+EcYEQMV6nNTJxEXlKY8A6eOlZrqiMVnqaGDSfd4NyjlLMTik9RLJi3guGn2jlHjgsEvJK3qWRSAi+WDQVo4vHOPuBJbd537hkTjIF7OiYKNSAzE9gbOekzrrKpRSsNZLwVNrdjYqN25ExbLlUMXGIvLiGdAkp0AVbvTK96cWEotaLmyJiMid1JHS9nOxjmhswl3SmpfIG9mUg2dJJZwcVikoJ27eUFMGlBwBNi8AyrOBvtOlTE5Tine+P7WMeH/D5yMikikGbeVGXIEdfDFQdgz4/XXpip8QmQ7MWsgXefIubah08yLLsWM4cuVs2LKyjh8r+fhjxN19FyJmzIAqzH0HXiIiIpIRUyow5zvgk8uAkoz6WpFjbgH6neO1C8FETt4u31RTDvzxIfDjvfXHdn8nvZeb8z0Q2ZUPDBERnRCDtnIk6itNegAYeZ1U31YTIh3jFUAKcI7qauS/+KJLwLZO3lP/Q9gpExm0JSIi8gciKJswCLh6GVBZANiqpV07Yk17goaiRH6vIts1YFun9Biw4jFg+oteT4wgIiL/w6CtXOkMgC4diEr39UyIvMZeXIyyJUs9jles/gW6bvybICIi8hvhidKNKJjs+8nz2I5FUtNfBm2JiOgEGLQlInkoz0GtuQqw2Tx+iqOy0qtTIiIiIiJqMXMlYC51X8u5jsMmNSYjIiI6Abb6JiLfsluAjPXAO6dDufcLhAwd4vFTw8aP9+rUiIiIiIhapDwH+PE+4JUxQHw/z5+XOsp7zdCIiMivMWhLRL5VnAEsmA4UH4Z62zuI/8fVgEbT5NMMEyZAk5zskykSEREREXlkqQRW/BfY8h5QUwIUHwG6T276eSoNcMZTQGgUTyYREZ0QyyMQke/YbcDm96RsW6EiF7pdLyH93RdR8M5nqNy4GaqICETNmY3w006DOjqajxYRERERyUtFHvDnwvqPV/wHOHc+0GUMsHUhUF0EdB0HTLofiO7py5kSEZEfYdCWiHzHWgVkbnI5pMxYDX3uViSefgkcs++GostIqBJSoBBdqImIiIiI5EbUsHXY6z+2W4FF1wHJw4CR1wLppwCRaSyLQERErcLyCETkO2q9+2wDcxlUf7wOzZ73oY40MWBLRERERPKlC3N/PHOzVOdWJB+wji0REbUSg7ZE5DtqLTD6Bmkh686EuwB9uLdnRURERETUcqGxQM/T3I/F9wcMsTybRETUagzaEpFvia1iF70LaA31x1Ra4IynpUUuEREREZGchZiAs5+Xatg2FNcPmPkREBbnq5kREZEfY01bIvItbRjQ+yzgpmFA6THAYQMi0qTFrSaEjw4RERERyZ8pBZj5IVCZD5RlAYY4ICweMDJgS0REbcOgLRHJo0xCRBfpRkRERETkjwwx0i2ur69nQkREAYDlEYiIiIiIiIiIiIhkhEFbIiIiIiIiIiIiIhlh0JaIiIiIiIiIiIhIRhi0JSIiIiIiIiIiIpIRBm2JiIiIiIiIiIiIZIRBWyIiIiIiIiIiIiIZYdCWiIiIiIiIiIiISEYYtCUiIiIiIiIiIiKSEQZtiYiIiIiIiIiIiGSEQVsiIiIiIiIiIiIiGWHQloiIiIiIiIiIiEhGGLQlIiIiIiIiIiIikhEGbYmIiIiIiIiIiIhkhEFbIiIiIiIiIiIiIhlh0JaIiIiIiIiIiIhIRhi0JSIiIiIiIiIiIpIRBm2JiIiIiIiIiIiIZIRBWyIiIiIiIiIiIiIZYdCWiIiIiIiIiIiIKBiCtocPH8bcuXORnp6OkJAQdO/eHQ8//DAsFktnfUsiIiIiog7D9SwRERER+Yq6s+549+7dcDgceP3119GjRw9s374d1157LSorK/HMM8901rclIiIiIuoQXM8SERERka8oamtra731zZ5++mm8+uqrOHjwYIs+v6ysDCaTCaWlpQgPD+/0+RERERGRvPl6fdja9awc5kxERERE8tHStaFXa9qKyURFRXnzWxIRERERdRiuZ4mIiIjIr8sjNLZ//368/PLLzZZGMJvNzlvDyDMRERERkRy0ZD0rcE1LRERERO3V6kzbe+65BwqFotmbqP/VUGZmJqZNm4YZM2Y469p68sQTTzjTg+tuqampbfupiIiIiIh8sJ4VuKYlIiIiIq/XtM3Pz0dhYWGzn9OtWzdotVrn/7OysjBx4kSMHj0a7733HpRKZauyEkTglvW/iIiIiKij6sN25npW4JqWiIiIiNq7nm11eYTY2FjnrSVERsKkSZMwbNgwvPvuuydc4Op0OueNiIiIiKizdOZ6VuCaloiIiIhkW9NWLHBFRkJaWpqz7pfIaKiTkJDQWd+WiIiIiKhDcD1LRERERAEXtF2+fLmzWYO4paSkuIy1siIDEREREclJZT5QVQzU2oGQCMCYiEDE9SwRERFRgLKagYpcwFIBaEIAQxygM8Cva9r6W80yIiIiIuogDjuQuwP46kYgd7t0LCINmP4ikDoK0IZ2+qn2x/WhP86ZiIiIKGBV5AEbXgPWvwJYqwGlGhhwETDlYSA8STZrwxMX5SIiIiIiEkoygHen1QdsnceOAB9eABTt5zkiIiIiInmzVgNrXwZ+fVb6v+CwAX99Anx9M1DVfLNab2LQloiIiIhOzOEAtn0OWCqbjtU6gFVPAeYKnkkiIiIikneW7e+vux87sAKoqO/J5WsM2hIRERHRidmqgSO/eR7P2gKYy3kmiYiIiEi+akoBm9nzeOlRBHwjMqJOq6VXegw4slaqqZd8EpAyAohI5QknIiLqTCotEJkOYJX78fBkQK3jY0DUEpUF0pvCXd8BShXQd7r0NxQaxfNHRETUmbQn6MFgiJHN+WfQlvyH6JmX/SewYLrU3a+OWNzO+QGI6+vL2REREQU2lQYYcQ2w+V334xPuYsCJqKXbMpfeC2z/ov7YL08BI68HTrkbMETzPBIREXWW0Fig51Rg3/KmYyJBwZgIuWB5BPIf5dnAJ5e4BmyFqiLg8znSApiIiIg6T2RX4II3pKzbOgolMOFuIGU4zzxRS4gdYw0DtnVEfb28nTyHREREnSnEBJz1PJA4xPW4KRW47HPAmCCb889MW/IfIihbnuN+LH+3tM0sLM7bsyIiIgoeujCg77lA6mggfw9gtwDx/QBDLKAz+np2RPInkg3WvuR5fN18IGUYoDnB1k0iIiJqu4i/A7TlWUDRISA8SQrain9lhEFb8h/WqubH7c0UkiYiIqKOodEDkWnSjYhax2EDako8j1cXAXYroOGJJSIi6lQi6U/cGmfcygjLI5D/EHVFRKMGd0Q2QijrfxERERGRjOlNQM/TPI/3ORvQMmudiIiIGLQlfyK2Xo660f3YxPuAsHhvz4iIiIiIqOXUOqnhmC7c/Vq3/3mAknk1RERExKAt+VsdvXG3SQWj67r5RaQBF7wFDL1MWgQTEREREcmZWL9e8xPQ+0ypkZ9SDQyYAcxdDkR08fXsiIiISCZY05b8i8hAGH4V0PsMwGEFVDrAyAxbIiIiIvITIpM2tjdwwRtA9d/1bUOiAJ3B1zMjIiIiGWHQlvyPQgGE/51pS0RERETkj3RG6UZERETkBgsmEREREREREREREckIg7ZEREREREREREREMsKgLREREREREREREZGMMGhLREREREREREREJCMM2hIRERERERERERHJCIO2RERERERERERERDLCoC0RERERERERERGRjDBoS0RERERERERERCQjDNoSERERERERERERyQiDtkREREREREREREQywqAtERERERERERERkYwwaEtEREREREREREQkIwzaEhEREREREREREckIg7ZEREREREREREREMsKgLREREREREREREZGMMGhLREREREREREREJCMM2hIRERERERERERHJCIO2RERERERERERERDLCoC0RERERERERERGRjDBoS0RERERERERERCQjDNoSERERERERERERyQiDtkREREREREREREQywqAtERERERERERERkYyofT0BIpKR2lqgPBuoyAOsVYAxETDEArowX8+MiIiIiKhFymusKKywILe8BgatGrFhOsSb9Dx7RETkVxi0JSKJww7k/AV8fIkUuBWUKmDkDcD426XgLRERERGRjBVUmPH88r34+PcMOGqlY8kRIXhr9nD0STBCoVD4eopEREQtwvIIRCQpPQYsmF4fsK0L5K6fD+z8WsrCJSIiIiKSKbvdgc83HcVHG+oDtkJmSTUueXM9skqqfTk9IiKiVmHQlogkGesBc7n7s7H6aaA8h2eKiIiIiGQrr9yM11cfdDtWUmXFjqwyr8+JiIiorRi0JSJJ7g7PZ0IEbO0WnikiIiIiki2z3eEMznqyL7fCq/MhIiJqDwZtiUiSfJLnMxHRBVDreKaIiIiISLZ0aqWz6Zgn/ZLDvTofIiKi9mDQlogkycOA0Cj3Z2PSA4AxgWeKiIiIiGQr3qjHP07t4XYszqhDn3ij1+dERETUVgzaEpEkIhWYswSI7VN/RjShwJT/AD2m8CwRERERkawplQqcOTAR/zy1pzPrtk6/xHB8fN1oJEaE+HR+REREraFu1WcTUWCL6wPM/haoKgRsNVLmrSEB0LA0AhERERHJX3SYDjdO7I6LhqWguMoCvUaFaIPWeZyIiMifMGhLRK7C4qQbEREREZEfEoHa1KhQ542IiMhfsTwCERERERERERERkYwwaEtEREREREREREQkIwzaEhEREREREREREckIg7ZEREREREREREREMsKgLREREREREREREZGMMGhLREREREREREREJCMM2hIRERERERERERHJCIO2RERERERERERERDLCoC0RERERERERERGRjDBoS0RERERERERERCQjDNoSERERERERERERyQiDtkREREREREREREQywqAtERERERERERERkYwwaEtEREREREREREQkIwzaEhEREREREREREckIg7ZEREREREREREREMsKgLREREREREREREZGMqCFjtbW1zn/Lysp8PRUiIiIikoG6dWHdOtEfcE1LRERERK1dz8o6aFteXu78NzU11ddTISIiIiKZrRNNJhP8Ade0RERERNTa9ayiVsZpCg6HA1lZWTAajVAoFL6ejt9E60WQ++jRowgPD/f1dOgE+Hj5Fz5e/oePmX/h4+VffPV4iaWrWOAmJSVBqfSPSl9c07YOnwv8Dx8z/8LHy7/w8fIvfLz8S5nM17OyzrQVE09JSfH1NPyS+GVj0NZ/8PHyL3y8/A8fM//Cx8u/+OLx8pcM2zpc07YNnwv8Dx8z/8LHy7/w8fIvfLz8S7hM17P+kZ5AREREREREREREFCQYtCUiIiIiIiIiIiKSEQZtA4xOp8PDDz/s/Jfkj4+Xf+Hj5X/4mPkXPl7+hY8X8XeL+Hzgn/j87V/4ePkXPl7+RSfzGJqsG5ERERERERERERERBRtm2hIRERERERERERHJCIO2RERERERERERERDLCoC0RERERERERERGRjDBoS0RERERERERERCQjDNoGqMOHD2Pu3LlIT09HSEgIunfv7uyIZ7FYfD018uCxxx7D2LFjERoaioiICJ4nGZo/fz66du0KvV6PUaNG4ffff/f1lMiD1atXY/r06UhKSoJCocBXX33FcyVTTzzxBEaMGAGj0Yi4uDicd9552LNnj6+nRc149dVXMWjQIISHhztvY8aMwZIlS3jOqFNwTet/uKaVN65n/QfXs/6Fa1r/8qqfrGcZtA1Qu3fvhsPhwOuvv44dO3bg+eefx2uvvYb77rvP11MjD0RAfcaMGbjxxht5jmTo008/xR133OG8+LFlyxYMHjwYp59+OvLy8nw9NXKjsrLS+RiJNyYkb7/88gtuvvlmrF+/HsuXL4fVasVpp53mfAxJnlJSUvDkk09i8+bN2LRpEyZPnoxzzz3Xud4g6mhc0/ofrmnli+tZ/8L1rH/hmta/pPjJelZRW1tb6+tJkHc8/fTTzqsJBw8e5CmXsffeew+33XYbSkpKfD0VakBk1opswHnz5jk/FhdFUlNTceutt+Kee+7huZIxkWm7ePFiZwYnyV9+fr4z41YsfCdMmODr6VALRUVFOdcZYpcPUWfjmtY/cE0rP1zP+i+uZ/0P17T+J0qG61lm2gaR0tJS5y8hEbU+Y0RcgZsyZcrxY0ql0vnxunXreDqJOvi1SuDrlX+w2+345JNPnNlAYlsZkTdwTUvUelzPEnkX17T+wy7j9aza1xMg79i/fz9efvllPPPMMzzlRK1UUFDgfCKPj493OS4+Fts2iahjiAx2sdPg5JNPxoABA3haZWzbtm3ORW1NTQ3CwsKc2ez9+vXz9bQoCHBNS9Q2XM8SeQ/XtP5hmx+sZ5lp62fENmyxNaK5W+MgUmZmJqZNm+asl3rttdf6bO7BqC2PFxFRsBK1bbdv3+680k3y1rt3b2zduhUbNmxw1mKfPXs2du7c6etpkR/hmta/cE1LRNRyXNP6h95+sJ5lpq2fufPOOzFnzpxmP6dbt27H/5+VlYVJkyZh7NixeOONN7wwQ2rP40XyFBMTA5VKhdzcXJfj4uOEhASfzYsokNxyyy347rvvnJ2SRWMAkjetVosePXo4/z9s2DBs3LgRL774orMBKlFLcE3rX7im9X9czxJ5B9e0/kPrB+tZBm39TGxsrPPWEiLDVgRsxS/fu+++66zBSfJ9vEjeT+bi7+jnn38+3sxKbHkRH4sXZSJqO9EPVTT0E9uRVq1ahfT0dJ5OPySeE81ms6+nQX6Ea1r/wjWt/+N6lqhzcU3r/xwyXM8yaBugRMB24sSJSEtLc9axFZ0L6zAzUJ4yMjJQVFTk/FfUTxVp+oK48iPqq5Bv3XHHHc7tEsOHD8fIkSPxwgsvOAuVX3XVVXxoZKiiosJZ97DOoUOHnH9TorlVly5dfDo3arp9bOHChfj6669hNBqRk5PjPG4ymRASEsLTJUP33nsvzjjjDOffUnl5ufPxEwH3H3/80ddTowDENa3/4ZpWvrie9S9cz/oXrmn9y71+sp5V1IrLARRw3nvvPY/BJD7k8iTKKCxYsKDJ8ZUrVzoD8OR78+bNw9NPP+0MKg0ZMgQvvfQSRo0a5etpkRviBVfsNGhMBN7F8yPJh6jt7Y7YIXKi8jLkG3PnznXuNMjOznYG1wcNGoS7774bU6dO5UNCHY5rWv/DNa28cT3rP7ie9S9c0/qXuX6ynmXQloiIiIiIiIiIiEhGWOSUiIiIiIiIiIiISEYYtCUiIiIiIiIiIiKSEQZtiYiIiIiIiIiIiGSEQVsiIiIiIiIiIiIiGWHQloiIiIiIiIiIiEhGGLQlIiIiIiIiIiIikhEGbYmIiIiIiIiIiIhkhEFbIiIiIiIiIiIiIhlh0JaIiIiIiIiIiIhIRhi0JSIiIiIiIiIiIpIRBm2JiIiIiIiIiIiIZIRBWyIiIiIiIiIiIiLIx/8DNCNyaqhxGEkAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 1400x600 with 2 Axes>"
       ]
@@ -6736,7 +6192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 635,
    "id": "2c9dbf2a",
    "metadata": {},
    "outputs": [],
@@ -6760,7 +6216,308 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 646,
+   "id": "321b7c6b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>166</th>\n",
+       "      <th>167</th>\n",
+       "      <th>168</th>\n",
+       "      <th>169</th>\n",
+       "      <th>170</th>\n",
+       "      <th>171</th>\n",
+       "      <th>172</th>\n",
+       "      <th>173</th>\n",
+       "      <th>174</th>\n",
+       "      <th>175</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "      <td>161.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-0.360248</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>10.968944</td>\n",
+       "      <td>-0.322981</td>\n",
+       "      <td>-11.714286</td>\n",
+       "      <td>-0.111801</td>\n",
+       "      <td>-0.074534</td>\n",
+       "      <td>0.012422</td>\n",
+       "      <td>0.031056</td>\n",
+       "      <td>-12.273292</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.161491</td>\n",
+       "      <td>0.012422</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>0.018634</td>\n",
+       "      <td>0.012422</td>\n",
+       "      <td>0.006211</td>\n",
+       "      <td>-0.018634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>6.171054</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>107.047444</td>\n",
+       "      <td>11.464403</td>\n",
+       "      <td>75.836290</td>\n",
+       "      <td>8.127110</td>\n",
+       "      <td>1.876009</td>\n",
+       "      <td>0.111107</td>\n",
+       "      <td>0.343190</td>\n",
+       "      <td>70.089406</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.369131</td>\n",
+       "      <td>0.111107</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>0.135649</td>\n",
+       "      <td>0.111107</td>\n",
+       "      <td>0.078811</td>\n",
+       "      <td>4.618539</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-16.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-118.000000</td>\n",
+       "      <td>-22.000000</td>\n",
+       "      <td>-329.000000</td>\n",
+       "      <td>-14.000000</td>\n",
+       "      <td>-5.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-158.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-15.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-2.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-30.000000</td>\n",
+       "      <td>-3.000000</td>\n",
+       "      <td>-39.000000</td>\n",
+       "      <td>-2.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-47.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-13.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-19.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-24.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-2.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-4.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>32.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>571.000000</td>\n",
+       "      <td>86.000000</td>\n",
+       "      <td>379.000000</td>\n",
+       "      <td>78.000000</td>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>276.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>24.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8 rows × 176 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              0           1           2           3           4           5    \\\n",
+       "count  161.000000  161.000000  161.000000  161.000000  161.000000  161.000000   \n",
+       "mean    -0.360248    0.006211   10.968944   -0.322981  -11.714286   -0.111801   \n",
+       "std      6.171054    0.078811  107.047444   11.464403   75.836290    8.127110   \n",
+       "min    -16.000000    0.000000 -118.000000  -22.000000 -329.000000  -14.000000   \n",
+       "25%     -2.000000    0.000000  -30.000000   -3.000000  -39.000000   -2.000000   \n",
+       "50%     -1.000000    0.000000  -13.000000    0.000000  -19.000000    0.000000   \n",
+       "75%      0.000000    0.000000   -2.000000    0.000000    0.000000    0.000000   \n",
+       "max     32.000000    1.000000  571.000000   86.000000  379.000000   78.000000   \n",
+       "\n",
+       "              6           7           8           9    ...         166  \\\n",
+       "count  161.000000  161.000000  161.000000  161.000000  ...  161.000000   \n",
+       "mean    -0.074534    0.012422    0.031056  -12.273292  ...    0.161491   \n",
+       "std      1.876009    0.111107    0.343190   70.089406  ...    0.369131   \n",
+       "min     -5.000000    0.000000   -1.000000 -158.000000  ...    0.000000   \n",
+       "25%     -1.000000    0.000000    0.000000  -47.000000  ...    0.000000   \n",
+       "50%      0.000000    0.000000    0.000000  -24.000000  ...    0.000000   \n",
+       "75%      0.000000    0.000000    0.000000   -4.000000  ...    0.000000   \n",
+       "max     14.000000    1.000000    1.000000  276.000000  ...    1.000000   \n",
+       "\n",
+       "              167         168         169         170         171         172  \\\n",
+       "count  161.000000  161.000000  161.000000  161.000000  161.000000  161.000000   \n",
+       "mean     0.012422    0.006211    0.006211    0.006211    0.006211    0.018634   \n",
+       "std      0.111107    0.078811    0.078811    0.078811    0.078811    0.135649   \n",
+       "min      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "max      1.000000    1.000000    1.000000    1.000000    1.000000    1.000000   \n",
+       "\n",
+       "              173         174         175  \n",
+       "count  161.000000  161.000000  161.000000  \n",
+       "mean     0.012422    0.006211   -0.018634  \n",
+       "std      0.111107    0.078811    4.618539  \n",
+       "min      0.000000    0.000000  -15.000000  \n",
+       "25%      0.000000    0.000000   -1.000000  \n",
+       "50%      0.000000    0.000000    0.000000  \n",
+       "75%      0.000000    0.000000    0.000000  \n",
+       "max      1.000000    1.000000   24.000000  \n",
+       "\n",
+       "[8 rows x 176 columns]"
+      ]
+     },
+     "execution_count": 646,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DataFrame(adata.layers['nona'] - adata.layers['abaco']).describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 636,
    "id": "0399387d",
    "metadata": {},
    "outputs": [
@@ -6789,23 +6546,23 @@
        "      <th>source</th>\n",
        "      <th>bio</th>\n",
        "      <th>5</th>\n",
-       "      <th>10</th>\n",
-       "      <th>11</th>\n",
-       "      <th>12</th>\n",
-       "      <th>20</th>\n",
-       "      <th>21</th>\n",
-       "      <th>23</th>\n",
+       "      <th>6</th>\n",
+       "      <th>14</th>\n",
+       "      <th>15</th>\n",
+       "      <th>16</th>\n",
+       "      <th>19</th>\n",
+       "      <th>24</th>\n",
        "      <th>...</th>\n",
-       "      <th>489</th>\n",
-       "      <th>497</th>\n",
-       "      <th>502</th>\n",
-       "      <th>504</th>\n",
-       "      <th>514</th>\n",
-       "      <th>515</th>\n",
-       "      <th>516</th>\n",
-       "      <th>518</th>\n",
-       "      <th>519</th>\n",
-       "      <th>527</th>\n",
+       "      <th>401</th>\n",
+       "      <th>403</th>\n",
+       "      <th>405</th>\n",
+       "      <th>410</th>\n",
+       "      <th>411</th>\n",
+       "      <th>412</th>\n",
+       "      <th>422</th>\n",
+       "      <th>423</th>\n",
+       "      <th>429</th>\n",
+       "      <th>443</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -6816,7 +6573,7 @@
        "      <td>Group1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>89.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -6837,12 +6594,12 @@
        "      <th>1</th>\n",
        "      <td>ERZ12633501</td>\n",
        "      <td>MGYS00006205</td>\n",
-       "      <td>Group1</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>Group2</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>...</td>\n",
@@ -6864,10 +6621,10 @@
        "      <td>Group1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>10.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
@@ -6886,12 +6643,12 @@
        "      <td>ERZ12633503</td>\n",
        "      <td>MGYS00006205</td>\n",
        "      <td>Group1</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>27.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
@@ -6903,18 +6660,18 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>ERZ12633504</td>\n",
        "      <td>MGYS00006205</td>\n",
        "      <td>Group1</td>\n",
+       "      <td>8.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>23.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>64.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>...</td>\n",
@@ -6927,32 +6684,32 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 223 columns</p>\n",
+       "<p>5 rows × 179 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "         index        source     bio    5   10   11   12   20   21   23  ...  \\\n",
-       "0  ERZ12633510  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
-       "1  ERZ12633501  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
-       "2  ERZ12633502  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
-       "3  ERZ12633503  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
-       "4  ERZ12633504  MGYS00006205  Group1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...   \n",
-       "\n",
-       "   489  497  502  504  514  515  516  518  519  527  \n",
-       "0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "2  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "3  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "4  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "\n",
-       "[5 rows x 223 columns]"
+       "         index        source     bio    5    6    14    15    16    19   24  \\\n",
+       "0  ERZ12633510  MGYS00006205  Group1  0.0  0.0  89.0   0.0   0.0   0.0  0.0   \n",
+       "1  ERZ12633501  MGYS00006205  Group2  0.0  0.0   1.0   0.0   3.0   0.0  0.0   \n",
+       "2  ERZ12633502  MGYS00006205  Group1  0.0  0.0  22.0  14.0  27.0  10.0  0.0   \n",
+       "3  ERZ12633503  MGYS00006205  Group1  1.0  0.0  27.0   0.0   0.0   1.0  0.0   \n",
+       "4  ERZ12633504  MGYS00006205  Group1  8.0  0.0  23.0   0.0  64.0   0.0  0.0   \n",
+       "\n",
+       "   ...  401  403  405  410  411  412  422  423  429  443  \n",
+       "0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "1  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "2  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "3  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  \n",
+       "4  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  \n",
+       "\n",
+       "[5 rows x 179 columns]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 636,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6963,7 +6720,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 637,
    "id": "a23a2c21",
    "metadata": {},
    "outputs": [
@@ -6980,9 +6737,9 @@
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@@ -7033,7 +6790,7 @@
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@@ -7041,29 +6798,19 @@
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    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2384117532.py:14: RuntimeWarning:\n",
-      "\n",
-      "divide by zero encountered in divide\n",
-      "\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
        "[None]"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 575,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
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",
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",
       "text/plain": [
        "<Figure size 1181.25x1080 with 27 Axes>"
       ]
@@ -7073,9 +6820,9 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1239.38x1080 with 27 Axes>"
+       "<Figure size 1239.5x1080 with 27 Axes>"
       ]
      },
      "metadata": {},
@@ -7142,6 +6889,12 @@
     "\n",
     "---"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ebec2c5",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {

From c1357d983167abee35020d0e23bfa2f668dd36ae Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 13:02:34 +0100
Subject: [PATCH 3/9] :sparkles:Feat: mv df_joiner() function to abaco.utils

helper function for joining N dataframes on common col
---
 docs/tutorial/demo-mgnify-ww-biomes.ipynb | 1412 ++++++++++++---------
 src/abaco/utils.py                        |   50 +
 2 files changed, 885 insertions(+), 577 deletions(-)

diff --git a/docs/tutorial/demo-mgnify-ww-biomes.ipynb b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
index 80b66ab..3482c3f 100644
--- a/docs/tutorial/demo-mgnify-ww-biomes.ipynb
+++ b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
@@ -5,7 +5,7 @@
    "id": "ad5a71b5",
    "metadata": {},
    "source": [
-    "# `ABaCo` demo: No biological labels w/ Mgnify tomoatos"
+    "# `ABaCo` demo: No biological labels w/ Mgnify tomatoes"
    ]
   },
   {
@@ -21,7 +21,6 @@
     "- MGYS00006231, Illumina HiSeq 4000\n",
     "- MGYS00006204, Illumina HiSeq 2500\n",
     "- MGYS00006205, Illumina HiSeq 2500\n",
-    "- MGYS00006018, Illumina MiSeq\n",
     "\n",
     "-----\n",
     "**Goal:**\n",
@@ -35,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 651,
+   "execution_count": 1,
    "id": "f94eae83",
    "metadata": {},
    "outputs": [
@@ -43,10 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(189, 12)\n",
-      "(446, 114)\n",
-      "(188, 12)\n",
-      "(2588, 210)\n"
+      "(189, 12)\n"
      ]
     },
     {
@@ -70,18 +66,18 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>ERZ12633490</th>\n",
-       "      <th>ERZ12633491</th>\n",
-       "      <th>ERZ12633492</th>\n",
-       "      <th>ERZ12633493</th>\n",
-       "      <th>ERZ12633494</th>\n",
-       "      <th>ERZ12633495</th>\n",
-       "      <th>ERZ12633496</th>\n",
-       "      <th>ERZ12633497</th>\n",
-       "      <th>ERZ12633488</th>\n",
-       "      <th>ERZ12633498</th>\n",
-       "      <th>ERZ12633489</th>\n",
-       "      <th>ERZ12633499</th>\n",
+       "      <th>ERZ12633510</th>\n",
+       "      <th>ERZ12633501</th>\n",
+       "      <th>ERZ12633502</th>\n",
+       "      <th>ERZ12633503</th>\n",
+       "      <th>ERZ12633504</th>\n",
+       "      <th>ERZ12633505</th>\n",
+       "      <th>ERZ12633506</th>\n",
+       "      <th>ERZ12633507</th>\n",
+       "      <th>ERZ12633517</th>\n",
+       "      <th>ERZ12633508</th>\n",
+       "      <th>ERZ12633518</th>\n",
+       "      <th>ERZ12633509</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>taxa</th>\n",
@@ -101,52 +97,497 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>sk__Archaea</th>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Betaproteobacteria;o__Burkholderiales;f__Oxalobacteraceae</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__candidate_division_NC10</th>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Archaea;k__;p__Euryarchaeota;c__Halobacteria;o__Halobacteriales</th>\n",
+       "      <th>sk__Eukaryota;k__Metazoa</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Alphaproteobacteria;o__Rhizobiales;f__Xanthobacteraceae</th>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
+       "      <td>2</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Archaea;k__;p__Euryarchaeota;c__Methanomicrobia;o__Methanosarcinales;f__Methanosarcinaceae;g__Methanosarcina</th>\n",
+       "      <th>sk__Bacteria;k__;p__Actinobacteria;c__Actinobacteria;o__Propionibacteriales;f__Propionibacteriaceae;g__Microlunatus</th>\n",
+       "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
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+       "taxa                                                                           \n",
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+       "taxa                                                                           \n",
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+       "taxa                                                                           \n",
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+       "taxa                                                                           \n",
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+       "taxa                                                                           \n",
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+       "taxa                                                                          \n",
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+       "                                                    ERZ12343720  ERZ12343730  \\\n",
+       "taxa                                                                           \n",
+       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
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+       "\n",
+       "                                                    ERZ12343740  ERZ12343750  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ERZ12343760  ERZ12343770  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ERZ12343780  ERZ12343721  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ERZ12343731  ERZ12343741  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ...  ERZ12590947  \\\n",
+       "taxa                                                ...                \n",
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+       "\n",
+       "                                                    ERZ12593067  ERZ12590878  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ERZ12590908  ERZ12590968  \\\n",
+       "taxa                                                                           \n",
+       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
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+       "\n",
+       "                                                    ERZ12590988  ERZ12590849  \\\n",
+       "taxa                                                                           \n",
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+       "\n",
+       "                                                    ERZ12590879  ERZ12590889  \\\n",
+       "taxa                                                                           \n",
+       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            1   \n",
+       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
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+       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "\n",
+       "                                                    ERZ12590909  \n",
+       "taxa                                                             \n",
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+       "\n",
+       "[5 rows x 114 columns]"
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__Acidobacteria;c__Acidobacteriia;o__Bryobacterales;f__Bryobacteraceae;g__Bryobacter</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -175,6 +642,21 @@
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Bacillales;f__Bacillaceae;g__Bacillus</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
@@ -182,56 +664,55 @@
       "text/plain": [
        "                                                    ERZ12633490  ERZ12633491  \\\n",
        "taxa                                                                           \n",
-       "sk__Archaea                                                   0            1   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            1            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            1   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            1   \n",
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            2   \n",
        "\n",
        "                                                    ERZ12633492  ERZ12633493  \\\n",
        "taxa                                                                           \n",
-       "sk__Archaea                                                   0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            1            0   \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            1   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            4            2   \n",
        "\n",
        "                                                    ERZ12633494  ERZ12633495  \\\n",
        "taxa                                                                           \n",
-       "sk__Archaea                                                   0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            0            2   \n",
        "\n",
        "                                                    ERZ12633496  ERZ12633497  \\\n",
        "taxa                                                                           \n",
-       "sk__Archaea                                                   0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            0            1   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            1   \n",
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            1            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            1   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            3            3   \n",
        "\n",
        "                                                    ERZ12633488  ERZ12633498  \\\n",
        "taxa                                                                           \n",
-       "sk__Archaea                                                   1            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            1   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0   \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0   \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            0   \n",
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            1            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            0   \n",
        "\n",
        "                                                    ERZ12633489  ERZ12633499  \n",
        "taxa                                                                          \n",
-       "sk__Archaea                                                   0            0  \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Halobacteri...            0            0  \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Methanomicr...            1            0  \n",
-       "sk__Archaea;k__;p__Euryarchaeota;c__Thermoplasmata            0            0  \n",
-       "sk__Archaea;k__;p__Thaumarchaeota                             0            0  "
+       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0  \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            1            0  \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            1  \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0  \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            1  "
       ]
      },
-     "execution_count": 651,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -240,13 +721,13 @@
     "import pandas as pd\n",
     "import numpy as np\n",
     "\n",
+    "# urls manually retrieved from mgnify website\n",
     "datasets = {\n",
     "    \"MGYS00006205\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006205/pipelines/5.0/file/ERP140107_taxonomy_abundances_SSU_v5.0.tsv\",\n",
     "    \"MGYS00006231\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006231/pipelines/5.0/file/ERP139927_taxonomy_abundances_SSU_v5.0.tsv\",\n",
     "    \"MGYS00006204\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006204/pipelines/5.0/file/ERP140102_taxonomy_abundances_SSU_v5.0.tsv\",\n",
-    "    \"MGYS00006018\": \"https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006018/pipelines/5.0/file/SRP109260_taxonomy_abundances_SSU_v5.0.tsv\"\n",
     "}\n",
-    "\n",
+    "# init for dfs\n",
     "dfs = {}\n",
     "for key, url in datasets.items():\n",
     "    # download\n",
@@ -255,120 +736,33 @@
     "    file_like = StringIO(response.content.decode('utf-8'))\n",
     "    # read into pd df\n",
     "    dfs[key] = pd.read_csv(file_like, sep='\\t')\n",
-    "    # add a column with the dataset url (batches)\n",
-    "    #dfs[url]['source'] = url\n",
     "    # rename sampleid col to taxa\n",
     "    dfs[key] = dfs[key].rename(columns={\"#SampleID\": \"taxa\"})\n",
+    "    # set index to taxa\n",
     "    dfs[key] = dfs[key].set_index('taxa')\n",
     "    # drop rows with all zeros\n",
     "    dfs[key] = dfs[key][dfs[key].sum(axis=1)>0]\n",
+    "    # sanity check\n",
     "    print(dfs[key].shape)\n",
-    "# sanity check\n",
-    "dfs[\"MGYS00006204\"].head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 656,
-   "id": "f428c58f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "np.int64(103676)"
-      ]
-     },
-     "execution_count": 656,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dfs['MGYS00006018'].sum()['SRR5685058']"
+    "    display(dfs[key].sample(5))"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 616,
-   "id": "cc9c3646",
+   "cell_type": "markdown",
+   "id": "6a035933",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(218, 28)\n",
-      "(69, 2)\n",
-      "(69, 11)\n",
-      "(2588, 67)\n",
-      "(2588, 23)\n",
-      "(1958, 23)\n",
-      "(1958, 23)\n"
-     ]
-    }
-   ],
    "source": [
-    "# tidy up MGYS00006018\n",
-    "\n",
-    "# read in mg metadata\n",
-    "mg_meta = pd.read_csv(\n",
-    "    \"data/analysisjob.csv\"\n",
-    ")\n",
-    "print(mg_meta.shape)\n",
-    "\n",
-    "# getting ids from urls\n",
-    "mg_meta['run_id'] = mg_meta['run'].str.extract(r'\\/runs\\/(S[A-Z0-9]*)\\?format=csv')\n",
-    "mg_meta['sample_id'] = mg_meta['sample'].str.extract(r'\\/samples\\/(S[A-Z0-9]*)\\?format=csv')\n",
+    "Based on the sampled outputs printed above, w can see that the data: \n",
+    "- has taxa as rows\n",
+    "- the samples as columns \n",
+    "- and the values are the number of taxanomic assignments for the given taxa x sample\n",
     "\n",
-    "# for each sample keep run with highest reads\n",
-    "keep_ids = mg_meta.groupby('sample_id')[\n",
-    "    'analysis_summary.4.value'\n",
-    "    ].idxmax().to_list()\n",
-    "\n",
-    "mg_meta = mg_meta.loc[\n",
-    "    mg_meta.index.isin(keep_ids), \n",
-    "    ['run_id', 'sample_id', ]\n",
-    "].copy()\n",
-    "print(mg_meta.shape)\n",
-    "\n",
-    "# read in metadata\n",
-    "ena_meta = pd.read_csv(\n",
-    "    \"data/filereport_read_run_SRP109260.tsv\",\n",
-    "    sep=\"\\t\",\n",
-    ")\n",
-    "# only rhizosphere samples\n",
-    "rhiz = ena_meta.query(\n",
-    "    \"sample_alias.str.lower().str.contains('rhizosphere')\"\n",
-    ")\n",
-    "print(rhiz.shape)\n",
-    "\n",
-    "# filtering columns (samples) to rhizosphere samples only\n",
-    "rhizo = dfs[\"MGYS00006018\"].loc[\n",
-    "    :, \n",
-    "    dfs[\"MGYS00006018\"].columns.isin(\n",
-    "        rhiz['run_accession'].to_list() #+ ['taxa']\n",
-    "    )\n",
-    "]\n",
-    "print(rhizo.shape)\n",
-    "\n",
-    "# also only keeping run with highest reads per sample\n",
-    "rhizo = rhizo.loc[:, rhizo.columns.isin(\n",
-    "    mg_meta['run_id'].to_list()\n",
-    ")].copy()\n",
-    "print(rhizo.shape)\n",
-    "\n",
-    "# drop rows with all zeros\n",
-    "rhizo = rhizo[rhizo.sum(axis=1)>0]\n",
-    "print(rhizo.shape)\n",
-    "# replace in dfs \n",
-    "dfs[\"MGYS00006018\"] = rhizo\n",
-    "print(dfs[\"MGYS00006018\"].shape)"
+    "To join them we will use a helper function `abaco.utils.df_joiner()`. Additionally we filter out some taxa if they are missing in more than 30% of the samples. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 617,
+   "execution_count": 2,
    "id": "c6d2108b",
    "metadata": {},
    "outputs": [
@@ -378,46 +772,20 @@
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
       "Index: 446 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
-      "Columns: 161 entries, ERZ12633510 to SRR5685149\n",
-      "dtypes: float64(161)\n",
-      "memory usage: 564.5+ KB\n"
+      "Columns: 138 entries, ERZ12633510 to ERZ12633499\n",
+      "dtypes: float64(138)\n",
+      "memory usage: 484.3+ KB\n"
      ]
     }
    ],
    "source": [
-    "def df_joiner(\n",
-    "    df_dict: dict[pd.DataFrame],\n",
-    "    on: str = \"taxa\",\n",
-    "    how: str = \"outer\",\n",
-    ")->pd.DataFrame:\n",
-    "    \n",
-    "    \"\"\"\n",
-    "    Join multiple dataframes on a common column.\n",
-    "\n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    df_dict : dict of pandas.DataFrame\n",
-    "        Dictionary of dataframes to join.\n",
-    "    on : str, optional\n",
-    "        Column to join on. Defaults to \"taxa\".\n",
-    "    how : str, optional\n",
-    "        Type of join. Defaults to \"outer\".\n",
+    "from abaco.utils import df_joiner\n",
     "\n",
-    "    Returns\n",
-    "    -------\n",
-    "    pandas.DataFrame\n",
-    "        Joined dataframe.\n",
-    "    \"\"\"\n",
-    "    # dfs into a list\n",
-    "    df_list = list(df_dict.values())\n",
-    "    # init the merged df with the first one\n",
-    "    df_merged = df_list[0]\n",
-    "    # for all others, merge iteratively\n",
-    "    for df in df_list[1:]:\n",
-    "        df_merged = pd.merge(df_merged, df, on=on, how=how)\n",
-    "    return df_merged\n",
-    "\n",
-    "joined = df_joiner(dfs)#.set_index('taxa')\n",
+    "joined = df_joiner(\n",
+    "    df_dict=dfs, \n",
+    "    on=\"taxa\",\n",
+    "    how=\"outer\",\n",
+    ")\n",
     "\n",
     "# filtering if taxa is missing in more than 30% of samples\n",
     "joined = joined[(joined.isna().sum(axis=1) / joined.shape[1] <= 0.3)].copy()\n",
@@ -431,12 +799,14 @@
    "id": "319d691e",
    "metadata": {},
    "source": [
-    "Using anndata to annotated the samples and taxa"
+    "Based on the printed df info, there are 138 samples and 446 taxa. \n",
+    "\n",
+    "For this example we will use anndata to store multiple layers of the data (e.g., raw counts, normalized, etc.) and annotate the samples and taxa with metadata. Below we prepare the annotations.  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 618,
+   "execution_count": null,
    "id": "b6303749",
    "metadata": {},
    "outputs": [
@@ -444,7 +814,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(161, 2)\n",
+      "(138, 2)\n",
       "(446, 8)\n"
      ]
     }
@@ -452,23 +822,25 @@
    "source": [
     "# preparing obs metadata\n",
     "dfs_T = {}\n",
+    "# for each study\n",
     "for key in dfs:\n",
     "    # transpose\n",
     "    dfs_T[key] = dfs[key].T\n",
-    "    # drop taxa row\n",
-    "    #dfs_T[key] = dfs_T[key].drop('taxa')\n",
-    "    # add source column\n",
+    "    # add study source column to be batch effect\n",
     "    dfs_T[key]['source'] = key\n",
-    "    # dummy bio column\n",
+    "    # dummy bio column, rando group assign, for checking and demo \n",
     "    dfs_T[key]['bio'] = np.random.choice([\"Group1\",\"Group2\"], size = len(dfs_T[key]))\n",
     "    # drop allother cols\n",
     "    dfs_T[key] = dfs_T[key][['source', 'bio']]\n",
-    "\n",
+    "# now concat all study metadata \n",
     "obsm = pd.concat(dfs_T.values())\n",
     "print(obsm.shape)\n",
     "\n",
+    "# preparing var metadata (taxa levels)\n",
+    "# get taxa index as df and split on ';'\n",
     "varm = joined.reset_index()[['taxa']]\n",
     "varm = varm['taxa'].str.split(';', expand=True)\n",
+    "# rename cols \n",
     "varm.columns = [\n",
     "    \"superkingdom\", \"kingdom\",\"phylum\", \"class\", \n",
     "    \"order\", \"family\", \"genus\", \"species\"\n",
@@ -478,7 +850,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 623,
+   "execution_count": 660,
    "id": "d98ecaf7",
    "metadata": {},
    "outputs": [
@@ -486,10 +858,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "AnnData object with n_obs × n_vars = 161 × 446\n",
+      "AnnData object with n_obs × n_vars = 138 × 446\n",
       "    obs: 'source', 'bio'\n",
       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
-      "View of AnnData object with n_obs × n_vars = 161 × 176\n",
+      "View of AnnData object with n_obs × n_vars = 138 × 176\n",
       "    obs: 'source', 'bio'\n",
       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n"
      ]
@@ -511,13 +883,13 @@
     {
      "data": {
       "text/plain": [
-       "AnnData object with n_obs × n_vars = 161 × 176\n",
+       "AnnData object with n_obs × n_vars = 138 × 176\n",
        "    obs: 'source', 'bio'\n",
        "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
        "    layers: 'nona'"
       ]
      },
-     "execution_count": 623,
+     "execution_count": 660,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -548,16 +920,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 624,
+   "execution_count": 661,
    "id": "80fcd19b",
    "metadata": {},
    "outputs": [
     {
      "data": {
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        "                            \n",
-       "var gd = document.getElementById('1220bd4b-fe23-43e7-b630-2cf391ee5f6e');\n",
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@@ -588,10 +960,10 @@
     {
      "data": {
       "text/plain": [
-       "TtestResult(statistic=np.float64(1.6943713373358462), pvalue=np.float64(0.0910842898454701), df=np.float64(350.0))"
+       "TtestResult(statistic=np.float64(-0.24147215889460413), pvalue=np.float64(0.8093305979731169), df=np.float64(350.0))"
       ]
      },
-     "execution_count": 624,
+     "execution_count": 661,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -646,7 +1018,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 625,
+   "execution_count": 662,
    "id": "1d77b8ab",
    "metadata": {},
    "outputs": [
@@ -655,10 +1027,10 @@
      "output_type": "stream",
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 161 entries, 0 to 160\n",
+      "RangeIndex: 138 entries, 0 to 137\n",
       "Columns: 179 entries, index to bio\n",
       "dtypes: category(1), float64(176), object(2)\n",
-      "memory usage: 224.3+ KB\n"
+      "memory usage: 192.3+ KB\n"
      ]
     }
    ],
@@ -706,7 +1078,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 626,
+   "execution_count": 663,
    "id": "128ba953",
    "metadata": {},
    "outputs": [
@@ -4618,9 +4990,9 @@
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                       {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('bc0beaae-dcf6-4d0d-8caf-d88f76a1c632');\n",
+       "var gd = document.getElementById('7a610700-a91c-413e-be9f-8a7312bd49fe');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -4703,7 +5075,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 627,
+   "execution_count": 664,
    "id": "506a301e",
    "metadata": {},
    "outputs": [
@@ -4718,11 +5090,10 @@
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
        "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1.])"
+       "       1., 1.])"
       ]
      },
-     "execution_count": 627,
+     "execution_count": 664,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4744,7 +5115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 628,
+   "execution_count": 665,
    "id": "54ab5719",
    "metadata": {},
    "outputs": [],
@@ -4768,7 +5139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 629,
+   "execution_count": 666,
    "id": "cf343afd",
    "metadata": {},
    "outputs": [
@@ -4817,7 +5188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 630,
+   "execution_count": 667,
    "id": "5b7f3d3e",
    "metadata": {},
    "outputs": [
@@ -4827,13 +5198,13 @@
        "[None]"
       ]
      },
-     "execution_count": 630,
+     "execution_count": 667,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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",
       "text/plain": [
        "<Figure size 1181.25x1080 with 27 Axes>"
       ]
@@ -4843,9 +5214,9 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1239.5x1080 with 27 Axes>"
+       "<Figure size 1239.38x1080 with 27 Axes>"
       ]
      },
      "metadata": {},
@@ -4913,7 +5284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 631,
+   "execution_count": 701,
    "id": "ac1c6cc7",
    "metadata": {},
    "outputs": [],
@@ -4934,13 +5305,13 @@
     "    prior=\"MoG\", # Prior distribution \n",
     "    device=device, # Device\n",
     "    d_z=16,\n",
-    "    epochs = [1000, 2000, 2000]\n",
+    "    epochs = [3000, 2000, 3000]\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 632,
+   "execution_count": 702,
    "id": "2f20940c",
    "metadata": {
     "tags": [
@@ -6136,7 +6507,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 633,
+   "execution_count": 703,
    "id": "e5c0aec5",
    "metadata": {
     "tags": [
@@ -6148,9 +6519,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Training: VAE for learning meaningful embeddings: 100%|██████████| 1000/1000 [00:13<00:00, 73.98it/s, bio_penalty=0.0000, clustering_loss=0.0000, elbo=828.6095, epoch=999/1001, vae_loss=828.6095] \n",
-      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:34<00:00, 57.86it/s, adv_loss=-0.8679, bio_penalty=0.0000, clustering_loss=0.0000, disc_loss=0.8679, elbo=1199.6460, epoch=1999/2001, vae_loss=1199.6460]  \n",
-      "Training: VAE decoder with masked batch labels: 100%|██████████| 2000/2000 [00:18<00:00, 107.64it/s, cycle_loss=0.0000, epoch=2000/2000, vae_loss=3908.0784]\n"
+      "Training: VAE for learning meaningful embeddings: 100%|██████████| 3000/3000 [00:43<00:00, 68.54it/s, bio_penalty=0.0000, clustering_loss=0.0000, elbo=255.0634, epoch=2999/3001, vae_loss=255.0634]\n",
+      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:36<00:00, 55.16it/s, adv_loss=-0.5765, bio_penalty=0.0000, clustering_loss=0.0000, disc_loss=0.5765, elbo=268.6828, epoch=1999/2001, vae_loss=268.6828]\n",
+      "Training: VAE decoder with masked batch labels: 100%|██████████| 3000/3000 [00:29<00:00, 101.87it/s, cycle_loss=0.0000, epoch=3000/3000, vae_loss=387.4835]\n"
      ]
     }
    ],
@@ -6161,13 +6532,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 634,
+   "execution_count": 704,
    "id": "58848ce7",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1400x600 with 2 Axes>"
       ]
@@ -6192,7 +6563,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 635,
+   "execution_count": 705,
    "id": "2c9dbf2a",
    "metadata": {},
    "outputs": [],
@@ -6216,7 +6587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 646,
+   "execution_count": 706,
    "id": "321b7c6b",
    "metadata": {},
    "outputs": [
@@ -6267,91 +6638,102 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
        "      <td>...</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
-       "      <td>161.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.000000</td>\n",
+       "      <td>138.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>-0.360248</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>10.968944</td>\n",
-       "      <td>-0.322981</td>\n",
-       "      <td>-11.714286</td>\n",
-       "      <td>-0.111801</td>\n",
-       "      <td>-0.074534</td>\n",
-       "      <td>0.012422</td>\n",
-       "      <td>0.031056</td>\n",
-       "      <td>-12.273292</td>\n",
+       "      <td>-0.007246</td>\n",
+       "      <td>-0.007246</td>\n",
+       "      <td>0.014493</td>\n",
+       "      <td>-0.014493</td>\n",
+       "      <td>0.014493</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.007246</td>\n",
+       "      <td>0.007246</td>\n",
+       "      <td>-0.021739</td>\n",
+       "      <td>-0.239130</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.161491</td>\n",
-       "      <td>0.012422</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>0.018634</td>\n",
-       "      <td>0.012422</td>\n",
-       "      <td>0.006211</td>\n",
-       "      <td>-0.018634</td>\n",
+       "      <td>0.028986</td>\n",
+       "      <td>0.014493</td>\n",
+       "      <td>-0.007246</td>\n",
+       "      <td>-0.007246</td>\n",
+       "      <td>0.007246</td>\n",
+       "      <td>-0.014493</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.007246</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
-       "      <td>6.171054</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>107.047444</td>\n",
-       "      <td>11.464403</td>\n",
-       "      <td>75.836290</td>\n",
-       "      <td>8.127110</td>\n",
-       "      <td>1.876009</td>\n",
-       "      <td>0.111107</td>\n",
-       "      <td>0.343190</td>\n",
-       "      <td>70.089406</td>\n",
+       "      <td>0.330811</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.170251</td>\n",
+       "      <td>0.170251</td>\n",
+       "      <td>0.119946</td>\n",
+       "      <td>0.209274</td>\n",
+       "      <td>0.190902</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.351584</td>\n",
+       "      <td>0.850542</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.369131</td>\n",
-       "      <td>0.111107</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>0.135649</td>\n",
-       "      <td>0.111107</td>\n",
-       "      <td>0.078811</td>\n",
-       "      <td>4.618539</td>\n",
+       "      <td>0.417536</td>\n",
+       "      <td>0.119946</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.119946</td>\n",
+       "      <td>0.120824</td>\n",
+       "      <td>0.085126</td>\n",
+       "      <td>0.120824</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>-16.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-118.000000</td>\n",
-       "      <td>-22.000000</td>\n",
-       "      <td>-329.000000</td>\n",
-       "      <td>-14.000000</td>\n",
-       "      <td>-5.000000</td>\n",
+       "      <td>-2.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-2.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>-1.000000</td>\n",
-       "      <td>-158.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-2.000000</td>\n",
+       "      <td>-4.000000</td>\n",
        "      <td>...</td>\n",
+       "      <td>-2.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-1.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
@@ -6359,20 +6741,9 @@
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-15.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>-2.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-30.000000</td>\n",
-       "      <td>-3.000000</td>\n",
-       "      <td>-39.000000</td>\n",
-       "      <td>-2.000000</td>\n",
-       "      <td>-1.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-47.000000</td>\n",
        "      <td>...</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
@@ -6383,47 +6754,46 @@
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-1.000000</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>-1.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-13.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-19.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-24.000000</td>\n",
-       "      <td>...</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-2.000000</td>\n",
        "      <td>0.000000</td>\n",
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        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>-4.000000</td>\n",
-       "      <td>...</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
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        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
@@ -6432,30 +6802,31 @@
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
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        "    <tr>\n",
        "      <th>max</th>\n",
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        "      <td>1.000000</td>\n",
-       "      <td>571.000000</td>\n",
-       "      <td>86.000000</td>\n",
-       "      <td>379.000000</td>\n",
-       "      <td>78.000000</td>\n",
-       "      <td>14.000000</td>\n",
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        "      <td>1.000000</td>\n",
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        "      <td>1.000000</td>\n",
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-       "      <td>...</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
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+       "      <td>1.000000</td>\n",
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        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>24.000000</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -6464,49 +6835,49 @@
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        "              0           1           2           3           4           5    \\\n",
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-       "mean    -0.360248    0.006211   10.968944   -0.322981  -11.714286   -0.111801   \n",
-       "std      6.171054    0.078811  107.047444   11.464403   75.836290    8.127110   \n",
-       "min    -16.000000    0.000000 -118.000000  -22.000000 -329.000000  -14.000000   \n",
-       "25%     -2.000000    0.000000  -30.000000   -3.000000  -39.000000   -2.000000   \n",
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-       "max     32.000000    1.000000  571.000000   86.000000  379.000000   78.000000   \n",
+       "count  138.000000  138.000000  138.000000  138.000000  138.000000  138.000000   \n",
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+       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
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+       "max      1.000000    0.000000    1.000000    0.000000    1.000000    1.000000   \n",
        "\n",
        "              6           7           8           9    ...         166  \\\n",
-       "count  161.000000  161.000000  161.000000  161.000000  ...  161.000000   \n",
-       "mean    -0.074534    0.012422    0.031056  -12.273292  ...    0.161491   \n",
-       "std      1.876009    0.111107    0.343190   70.089406  ...    0.369131   \n",
-       "min     -5.000000    0.000000   -1.000000 -158.000000  ...    0.000000   \n",
-       "25%     -1.000000    0.000000    0.000000  -47.000000  ...    0.000000   \n",
-       "50%      0.000000    0.000000    0.000000  -24.000000  ...    0.000000   \n",
-       "75%      0.000000    0.000000    0.000000   -4.000000  ...    0.000000   \n",
-       "max     14.000000    1.000000    1.000000  276.000000  ...    1.000000   \n",
+       "count  138.000000  138.000000  138.000000  138.000000  ...  138.000000   \n",
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+       "std      0.190902    0.085126    0.351584    0.850542  ...    0.417536   \n",
+       "min     -1.000000    0.000000   -2.000000   -4.000000  ...   -2.000000   \n",
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+       "max      1.000000    1.000000    1.000000    1.000000  ...    1.000000   \n",
        "\n",
        "              167         168         169         170         171         172  \\\n",
-       "count  161.000000  161.000000  161.000000  161.000000  161.000000  161.000000   \n",
-       "mean     0.012422    0.006211    0.006211    0.006211    0.006211    0.018634   \n",
-       "std      0.111107    0.078811    0.078811    0.078811    0.078811    0.135649   \n",
-       "min      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
+       "count  138.000000  138.000000  138.000000  138.000000  138.000000  138.000000   \n",
+       "mean     0.014493   -0.007246   -0.007246    0.007246   -0.014493    0.000000   \n",
+       "std      0.119946    0.085126    0.085126    0.085126    0.119946    0.120824   \n",
+       "min      0.000000   -1.000000   -1.000000    0.000000   -1.000000   -1.000000   \n",
        "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
        "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
        "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "max      1.000000    1.000000    1.000000    1.000000    1.000000    1.000000   \n",
-       "\n",
-       "              173         174         175  \n",
-       "count  161.000000  161.000000  161.000000  \n",
-       "mean     0.012422    0.006211   -0.018634  \n",
-       "std      0.111107    0.078811    4.618539  \n",
-       "min      0.000000    0.000000  -15.000000  \n",
-       "25%      0.000000    0.000000   -1.000000  \n",
-       "50%      0.000000    0.000000    0.000000  \n",
-       "75%      0.000000    0.000000    0.000000  \n",
-       "max      1.000000    1.000000   24.000000  \n",
+       "max      1.000000    0.000000    0.000000    1.000000    0.000000    1.000000   \n",
+       "\n",
+       "              173         174    175  \n",
+       "count  138.000000  138.000000  138.0  \n",
+       "mean     0.007246    0.000000    0.0  \n",
+       "std      0.085126    0.120824    0.0  \n",
+       "min      0.000000   -1.000000    0.0  \n",
+       "25%      0.000000    0.000000    0.0  \n",
+       "50%      0.000000    0.000000    0.0  \n",
+       "75%      0.000000    0.000000    0.0  \n",
+       "max      1.000000    1.000000    0.0  \n",
        "\n",
        "[8 rows x 176 columns]"
       ]
      },
-     "execution_count": 646,
+     "execution_count": 706,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6517,210 +6888,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 636,
-   "id": "0399387d",
-   "metadata": {},
-   "outputs": [
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-       "      <th></th>\n",
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-       "      <th>source</th>\n",
-       "      <th>bio</th>\n",
-       "      <th>5</th>\n",
-       "      <th>6</th>\n",
-       "      <th>14</th>\n",
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-       "      <th>411</th>\n",
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-       "    <tr>\n",
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-       "      <td>ERZ12633501</td>\n",
-       "      <td>MGYS00006205</td>\n",
-       "      <td>Group2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>0.0</td>\n",
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-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>ERZ12633502</td>\n",
-       "      <td>MGYS00006205</td>\n",
-       "      <td>Group1</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>14.0</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>ERZ12633503</td>\n",
-       "      <td>MGYS00006205</td>\n",
-       "      <td>Group1</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>ERZ12633504</td>\n",
-       "      <td>MGYS00006205</td>\n",
-       "      <td>Group1</td>\n",
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-       "      <td>23.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>0.0</td>\n",
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-       "  </tbody>\n",
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-       "<p>5 rows × 179 columns</p>\n",
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-       "         index        source     bio    5    6    14    15    16    19   24  \\\n",
-       "0  ERZ12633510  MGYS00006205  Group1  0.0  0.0  89.0   0.0   0.0   0.0  0.0   \n",
-       "1  ERZ12633501  MGYS00006205  Group2  0.0  0.0   1.0   0.0   3.0   0.0  0.0   \n",
-       "2  ERZ12633502  MGYS00006205  Group1  0.0  0.0  22.0  14.0  27.0  10.0  0.0   \n",
-       "3  ERZ12633503  MGYS00006205  Group1  1.0  0.0  27.0   0.0   0.0   1.0  0.0   \n",
-       "4  ERZ12633504  MGYS00006205  Group1  8.0  0.0  23.0   0.0  64.0   0.0  0.0   \n",
-       "\n",
-       "   ...  401  403  405  410  411  412  422  423  429  443  \n",
-       "0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "1  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "2  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
-       "3  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  \n",
-       "4  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  \n",
-       "\n",
-       "[5 rows x 179 columns]"
-      ]
-     },
-     "execution_count": 636,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "corrected_dataset.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 637,
+   "execution_count": 708,
    "id": "a23a2c21",
    "metadata": {},
    "outputs": [
@@ -6737,9 +6905,9 @@
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      "data": {
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                       {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('73da6326-ffb7-4cc7-b7d8-a1e7b70a7e2c');\n",
+       "var gd = document.getElementById('c8c00df4-bb7d-4d30-9579-7b829a7e77ed');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -6790,7 +6958,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 575,
+   "execution_count": 709,
    "id": "be1b2c3c",
    "metadata": {
     "tags": [
@@ -6798,19 +6966,29 @@
     ]
    },
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2384117532.py:14: RuntimeWarning:\n",
+      "\n",
+      "divide by zero encountered in divide\n",
+      "\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "[None]"
       ]
      },
-     "execution_count": 575,
+     "execution_count": 709,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1181.25x1080 with 27 Axes>"
       ]
@@ -6820,9 +6998,9 @@
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 1239.5x1080 with 27 Axes>"
+       "<Figure size 1239.38x1080 with 27 Axes>"
       ]
      },
      "metadata": {},
@@ -6871,6 +7049,86 @@
     "plt.setp(g2._legend.get_title(), fontsize=20)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 732,
+   "id": "01521c69",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3415170421.py:1: FutureWarning:\n",
+      "\n",
+      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "ERZ12633510    16.250000\n",
+       "ERZ12633502    26.875000\n",
+       "ERZ12633503    14.500000\n",
+       "ERZ12633504    16.333333\n",
+       "ERZ12633506    17.666667\n",
+       "                 ...    \n",
+       "ERZ12633497     7.500000\n",
+       "ERZ12633488    17.000000\n",
+       "ERZ12633498    15.333333\n",
+       "ERZ12633489    24.300000\n",
+       "ERZ12633499    17.800000\n",
+       "Name: abaco_chao1, Length: 61, dtype: float64"
+      ]
+     },
+     "execution_count": 732,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "adata.obs.groupby('bio').get_group('Group1')['abaco_chao1']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 736,
+   "id": "a7f66563",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3042419068.py:2: FutureWarning:\n",
+      "\n",
+      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "\n",
+      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3042419068.py:3: FutureWarning:\n",
+      "\n",
+      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "TtestResult(statistic=np.float64(1.2158839045417509), pvalue=np.float64(0.226135424601057), df=np.float64(136.0))"
+      ]
+     },
+     "execution_count": 736,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stats.ttest_ind(\n",
+    "    adata.obs.groupby('bio').get_group('Group1')['abaco_pielou'], \n",
+    "    adata.obs.groupby('bio').get_group('Group2')['abaco_pielou']\n",
+    "    )"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b433f7df",
diff --git a/src/abaco/utils.py b/src/abaco/utils.py
index 3c132f0..9f74429 100644
--- a/src/abaco/utils.py
+++ b/src/abaco/utils.py
@@ -5,6 +5,7 @@
 import sys
 from datetime import datetime
 from urllib.parse import urlparse, urlunsplit
+import pandas as pd 
 
 # import yaml
 
@@ -456,3 +457,52 @@ def get_logger():
 #     assert isinstance(contents, dict), "content not returned as a dict"
 
 #     return contents
+
+
+def df_joiner(
+    df_dict: dict[pd.DataFrame],
+    on: str,
+    how: str = "outer",
+) -> pd.DataFrame:
+    
+    """
+    Join multiple dataframes on a common column.
+
+    Parameters
+    ----------
+    df_dict : dict of pandas.DataFrame
+        Dictionary of dataframes to join.
+    on : str, optional
+        Column to join on. Defaults to "taxa".
+    how : str, optional
+        Type of join. Defaults to "outer".
+
+    Returns
+    -------
+    pandas.DataFrame
+        Joined dataframe.
+    """
+
+    ## PRECONDITION CHECKS
+    if not isinstance(df_dict, dict):
+        raise TypeError(f"df_dict must be a dict: {type(df_dict)}")
+    if not isinstance(on, str):
+        raise TypeError(f"on must be a str: {type(on)}")
+    for key, df in df_dict.items():
+        if not isinstance(df, pd.DataFrame):
+            raise TypeError(f"df_dict values must be pd.DataFrame: {type(df)}")
+        if (on not in df.columns) and (on not in df.index.names):
+            raise ValueError(f"Column '{on}' not found in dataframe with key '{key}'")
+    if how not in ["left", "right", "outer", "inner"]:
+        raise ValueError(f"how must be one of 'left', 'right', 'outer', 'inner': {how}")
+
+
+    ## MAIN FUNCTION 
+    # dfs into a list
+    df_list = list(df_dict.values())
+    # init the merged df with the first one
+    df_merged = df_list[0]
+    # for all others, merge iteratively
+    for df in df_list[1:]:
+        df_merged = pd.merge(df_merged, df, on=on, how=how)
+    return df_merged
\ No newline at end of file

From ec24e6e8c3e318ddd216f5a75e41aba0226e7512 Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 14:10:18 +0100
Subject: [PATCH 4/9] :construction::memo:Docs: Updating demo, removing alpha
 diversity metrics

---
 docs/tutorial/demo-mgnify-ww-biomes.ipynb | 2156 ++++++++++++++++-----
 1 file changed, 1697 insertions(+), 459 deletions(-)

diff --git a/docs/tutorial/demo-mgnify-ww-biomes.ipynb b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
index 3482c3f..66c55c4 100644
--- a/docs/tutorial/demo-mgnify-ww-biomes.ipynb
+++ b/docs/tutorial/demo-mgnify-ww-biomes.ipynb
@@ -22,6 +22,10 @@
     "- MGYS00006204, Illumina HiSeq 2500\n",
     "- MGYS00006205, Illumina HiSeq 2500\n",
     "\n",
+    "**Additionally** we provide an intro to [working with anndata](https://anndata.readthedocs.io/en/stable/tutorials/notebooks/getting-started.html)  \n",
+    "\n",
+    "**Note** in this tutorial we include a dummy bio column for demo purposes, but it is not necessary to have a bio column to use abaco. \n",
+    "\n",
     "-----\n",
     "**Goal:**\n",
     "\n",
@@ -32,6 +36,14 @@
     "To start we retrieve the data from MGniFy. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0ac42400",
+   "metadata": {},
+   "source": [
+    "## Downloading the data"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -799,14 +811,24 @@
    "id": "319d691e",
    "metadata": {},
    "source": [
-    "Based on the printed df info, there are 138 samples and 446 taxa. \n",
+    "Based on the printed df info, there are 138 samples and 446 taxa. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9511c611",
+   "metadata": {},
+   "source": [
+    "## A brief intro to `anndata`\n",
     "\n",
-    "For this example we will use anndata to store multiple layers of the data (e.g., raw counts, normalized, etc.) and annotate the samples and taxa with metadata. Below we prepare the annotations.  "
+    "![img](https://raw.githubusercontent.com/scverse/anndata/main/docs/_static/img/anndata_schema.svg)\n",
+    "\n",
+    "For this example we will use anndata to store multiple layers of the data (e.g., raw counts, normalized, etc.) and annotate the samples and taxa with metadata. Below we prepare the annotations (i.e., obs, var).  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "b6303749",
    "metadata": {},
    "outputs": [
@@ -814,12 +836,205 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(138, 2)\n",
+      "(138, 2)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>taxa</th>\n",
+       "      <th>source</th>\n",
+       "      <th>bio</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ERZ12343723</th>\n",
+       "      <td>MGYS00006231</td>\n",
+       "      <td>Group2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12590849</th>\n",
+       "      <td>MGYS00006231</td>\n",
+       "      <td>Group1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12590855</th>\n",
+       "      <td>MGYS00006231</td>\n",
+       "      <td>Group2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12343782</th>\n",
+       "      <td>MGYS00006231</td>\n",
+       "      <td>Group1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633517</th>\n",
+       "      <td>MGYS00006205</td>\n",
+       "      <td>Group1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "taxa               source     bio\n",
+       "ERZ12343723  MGYS00006231  Group2\n",
+       "ERZ12590849  MGYS00006231  Group1\n",
+       "ERZ12590855  MGYS00006231  Group2\n",
+       "ERZ12343782  MGYS00006231  Group1\n",
+       "ERZ12633517  MGYS00006205  Group1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "(446, 8)\n"
      ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>superkingdom</th>\n",
+       "      <th>kingdom</th>\n",
+       "      <th>phylum</th>\n",
+       "      <th>class</th>\n",
+       "      <th>order</th>\n",
+       "      <th>family</th>\n",
+       "      <th>genus</th>\n",
+       "      <th>species</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>236</th>\n",
+       "      <td>sk__Bacteria</td>\n",
+       "      <td>k__</td>\n",
+       "      <td>p__Planctomycetes</td>\n",
+       "      <td>c__Phycisphaerae</td>\n",
+       "      <td>o__Tepidisphaerales</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>393</th>\n",
+       "      <td>sk__Eukaryota</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>sk__Bacteria</td>\n",
+       "      <td>k__</td>\n",
+       "      <td>p__</td>\n",
+       "      <td>c__Candidatus_Babeliae</td>\n",
+       "      <td>o__Candidatus_Babeliales</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>286</th>\n",
+       "      <td>sk__Bacteria</td>\n",
+       "      <td>k__</td>\n",
+       "      <td>p__Proteobacteria</td>\n",
+       "      <td>c__Alphaproteobacteria</td>\n",
+       "      <td>o__Sphingomonadales</td>\n",
+       "      <td>f__Sphingomonadaceae</td>\n",
+       "      <td>g__Novosphingobium</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>sk__Bacteria</td>\n",
+       "      <td>k__</td>\n",
+       "      <td>p__Proteobacteria</td>\n",
+       "      <td>c__Alphaproteobacteria</td>\n",
+       "      <td>o__Rhizobiales</td>\n",
+       "      <td>f__Xanthobacteraceae</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      superkingdom kingdom             phylum                   class  \\\n",
+       "236   sk__Bacteria     k__  p__Planctomycetes        c__Phycisphaerae   \n",
+       "393  sk__Eukaryota    None               None                    None   \n",
+       "8     sk__Bacteria     k__                p__  c__Candidatus_Babeliae   \n",
+       "286   sk__Bacteria     k__  p__Proteobacteria  c__Alphaproteobacteria   \n",
+       "267   sk__Bacteria     k__  p__Proteobacteria  c__Alphaproteobacteria   \n",
+       "\n",
+       "                        order                family               genus  \\\n",
+       "236       o__Tepidisphaerales                  None                None   \n",
+       "393                      None                  None                None   \n",
+       "8    o__Candidatus_Babeliales                  None                None   \n",
+       "286       o__Sphingomonadales  f__Sphingomonadaceae  g__Novosphingobium   \n",
+       "267            o__Rhizobiales  f__Xanthobacteraceae                None   \n",
+       "\n",
+       "    species  \n",
+       "236    None  \n",
+       "393    None  \n",
+       "8      None  \n",
+       "286    None  \n",
+       "267    None  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
+    "import anndata as ad\n",
+    "import scanpy as sc\n",
+    "\n",
     "# preparing obs metadata\n",
     "dfs_T = {}\n",
     "# for each study\n",
@@ -833,126 +1048,1510 @@
     "    # drop allother cols\n",
     "    dfs_T[key] = dfs_T[key][['source', 'bio']]\n",
     "# now concat all study metadata \n",
-    "obsm = pd.concat(dfs_T.values())\n",
-    "print(obsm.shape)\n",
+    "obs = pd.concat(dfs_T.values())\n",
+    "print(obs.shape)\n",
+    "display(obs.sample(5))\n",
     "\n",
     "# preparing var metadata (taxa levels)\n",
     "# get taxa index as df and split on ';'\n",
-    "varm = joined.reset_index()[['taxa']]\n",
-    "varm = varm['taxa'].str.split(';', expand=True)\n",
+    "var = joined.reset_index()[['taxa']]\n",
+    "var = var['taxa'].str.split(';', expand=True)\n",
     "# rename cols \n",
-    "varm.columns = [\n",
+    "var.columns = [\n",
     "    \"superkingdom\", \"kingdom\",\"phylum\", \"class\", \n",
     "    \"order\", \"family\", \"genus\", \"species\"\n",
     "]\n",
-    "print(varm.shape)"
+    "print(var.shape)\n",
+    "display(var.sample(5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "62e44f01",
+   "metadata": {},
+   "source": [
+    "We can initiate the AnnData objct with the values (taxanomic assignment counts) and the metadata we prepped above. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 660,
+   "execution_count": 16,
    "id": "d98ecaf7",
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning: Transforming to str index.\n",
+      "  return dispatch(args[0].__class__)(*args, **kw)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 138 × 446\n",
+       "    obs: 'source', 'bio'\n",
+       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# init anndata object\n",
+    "full = ad.AnnData(\n",
+    "    X=joined.T.values,\n",
+    "    obs=obs,\n",
+    "    var=var,    \n",
+    ")\n",
+    "# check it out\n",
+    "full"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed4b1b01",
+   "metadata": {},
+   "source": [
+    "With anndata we can also filter the data using the annotations/metadata. Below we will keep the variables (taxa) with genus assignment."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "4d2802f7",
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "AnnData object with n_obs × n_vars = 138 × 446\n",
-      "    obs: 'source', 'bio'\n",
-      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
       "View of AnnData object with n_obs × n_vars = 138 × 176\n",
       "    obs: 'source', 'bio'\n",
       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n"
      ]
+    }
+   ],
+   "source": [
+    "# must have genus level\n",
+    "adata = full[:, ~full.var['genus'].isna()]\n",
+    "print(adata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d17b0bd",
+   "metadata": {},
+   "source": [
+    "We are down to 176 taxa. With anndata we can also store additional layers seamlessly with the same annoations. Below we will create a layer with the NaNs filled with 0s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d272c7b1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AnnData object with n_obs × n_vars = 138 × 176\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "    layers: 'nona'\n",
+      "original:\n"
+     ]
     },
     {
-     "name": "stderr",
+     "data": {
+      "text/html": [
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+       "      <th>26</th>\n",
+       "      <th>30</th>\n",
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+       "      <th>411</th>\n",
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+       "      <th>422</th>\n",
+       "      <th>423</th>\n",
+       "      <th>429</th>\n",
+       "      <th>443</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633510</th>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633501</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633502</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633503</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633504</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 176 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              5   6  14  15   16   19  24  25   26   30  ...  401  403  405  \\\n",
+       "ERZ12633510 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633501 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633502 NaN NaN NaN NaN  1.0  1.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633503 NaN NaN NaN NaN  0.0  0.0 NaN NaN  1.0  1.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633504 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
+       "\n",
+       "             410  411  412  422  423  429  443  \n",
+       "ERZ12633510  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
+       "ERZ12633501  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
+       "ERZ12633502  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
+       "ERZ12633503  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
+       "ERZ12633504  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
+       "\n",
+       "[5 rows x 176 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning:\n",
-      "\n",
-      "Transforming to str index.\n",
-      "\n",
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2436230638.py:20: ImplicitModificationWarning:\n",
-      "\n",
-      "Setting element `.layers['nona']` of view, initializing view as actual.\n",
-      "\n"
+      "no na:\n"
      ]
     },
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      "data": {
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633501</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633502</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633503</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ERZ12633504</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 176 columns</p>\n",
+       "</div>"
+      ],
       "text/plain": [
-       "AnnData object with n_obs × n_vars = 138 × 176\n",
-       "    obs: 'source', 'bio'\n",
-       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
-       "    layers: 'nona'"
+       "               5    6   14   15   16   19   24   25   26   30  ...  401  403  \\\n",
+       "ERZ12633510  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
+       "ERZ12633501  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
+       "ERZ12633502  0.0  0.0  0.0  0.0  1.0  1.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
+       "ERZ12633503  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  1.0  ...  0.0  0.0   \n",
+       "ERZ12633504  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
+       "\n",
+       "             405  410  411  412  422  423  429  443  \n",
+       "ERZ12633510  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "ERZ12633501  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "ERZ12633502  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "ERZ12633503  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "ERZ12633504  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "\n",
+       "[5 rows x 176 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# layer with no na\n",
+    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n",
+    "print(adata)\n",
+    "\n",
+    "# checking it out, also demoing to_df method\n",
+    "print(\"original:\")\n",
+    "display(adata.to_df().head(5))\n",
+    "print(\"no na:\")\n",
+    "display(adata.to_df(layer='nona').head(5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ba030e0",
+   "metadata": {},
+   "source": [
+    "However, it can be trickier to aggregate with anndata -- but we can use the [scanpy toolkit](https://scanpy.readthedocs.io/en/stable/index.html) to help.  \n",
+    "\n",
+    "Specifically we will use [scanpy.get.aggregate()](https://scanpy.readthedocs.io/en/stable/generated/scanpy.get.aggregate.html) to help us check that the dummy biological groups we created are not different. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "f47a2606",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AnnData object with n_obs × n_vars = 2 × 176\n",
+      "    obs: 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "    layers: 'mean'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>14</th>\n",
+       "      <th>15</th>\n",
+       "      <th>16</th>\n",
+       "      <th>19</th>\n",
+       "      <th>24</th>\n",
+       "      <th>25</th>\n",
+       "      <th>26</th>\n",
+       "      <th>30</th>\n",
+       "      <th>...</th>\n",
+       "      <th>401</th>\n",
+       "      <th>403</th>\n",
+       "      <th>405</th>\n",
+       "      <th>410</th>\n",
+       "      <th>411</th>\n",
+       "      <th>412</th>\n",
+       "      <th>422</th>\n",
+       "      <th>423</th>\n",
+       "      <th>429</th>\n",
+       "      <th>443</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Group1</th>\n",
+       "      <td>0.120000</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.106667</td>\n",
+       "      <td>0.226667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.160000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.026667</td>\n",
+       "      <td>0.026667</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Group2</th>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.031746</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.031746</td>\n",
+       "      <td>0.079365</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.047619</td>\n",
+       "      <td>0.174603</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.031746</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.015873</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.015873</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2 rows × 176 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               5         6        14        15        16        19        24  \\\n",
+       "Group1  0.120000  0.013333  0.040000  0.013333  0.013333  0.040000  0.093333   \n",
+       "Group2  0.111111  0.000000  0.031746  0.000000  0.015873  0.031746  0.079365   \n",
+       "\n",
+       "              25        26        30  ...       401       403       405  \\\n",
+       "Group1  0.013333  0.106667  0.226667  ...  0.160000  0.000000  0.013333   \n",
+       "Group2  0.015873  0.047619  0.174603  ...  0.222222  0.031746  0.000000   \n",
+       "\n",
+       "             410       411       412       422       423       429       443  \n",
+       "Group1  0.000000  0.000000  0.013333  0.026667  0.026667  0.013333  0.000000  \n",
+       "Group2  0.015873  0.015873  0.000000  0.015873  0.000000  0.000000  0.015873  \n",
+       "\n",
+       "[2 rows x 176 columns]"
       ]
      },
-     "execution_count": 660,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "import anndata as ad\n",
-    "import numpy as np\n",
-    "import scanpy as sc\n",
-    "\n",
-    "# init anndata object\n",
-    "full = ad.AnnData(\n",
-    "    X=joined.T.values,\n",
-    "    obs=obsm,\n",
-    "    var=varm,    \n",
+    "# agg by fake bio group \n",
+    "agg_mean = sc.get.aggregate(\n",
+    "    # the anndata object\n",
+    "    adata=adata,\n",
+    "    # what layer to use\n",
+    "    layer='nona',\n",
+    "    # group by col\n",
+    "    by=\"bio\",\n",
+    "    # axis that the group lives\n",
+    "    axis=\"obs\",\n",
+    "    # how to agg\n",
+    "    func='mean',\n",
     ")\n",
-    "print(full)\n",
-    "# must have genus level\n",
-    "adata = full[:, ~full.var['genus'].isna()]\n",
-    "print(adata)\n",
-    "\n",
-    "# drop all na \n",
-    "#adata = adata[adata.to_df().dropna().index, adata.to_df().dropna().columns]\n",
-    "\n",
-    "# layer with no na\n",
-    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n",
-    "adata"
+    "# check out the returned AnnData objct\n",
+    "print(agg_mean)\n",
+    "# we can see taht the default layer name if not provided is the func name \n",
+    "display(agg_mean.to_df('mean').head(5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e1f33e18",
+   "metadata": {},
+   "source": [
+    "Now lets quickly check that group 1 and 2 are not different visually and quick stats."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 661,
+   "execution_count": 28,
    "id": "80fcd19b",
    "metadata": {},
    "outputs": [
     {
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+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
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+            "gridwidth": 2,
+            "linecolor": "white",
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+            "ticks": "",
+            "zerolinecolor": "white"
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+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
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+          },
+          "shapedefaults": {
+           "line": {
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+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        }
+       }
+      }
      },
      "metadata": {},
      "output_type": "display_data"
@@ -960,27 +2559,20 @@
     {
      "data": {
       "text/plain": [
-       "TtestResult(statistic=np.float64(-0.24147215889460413), pvalue=np.float64(0.8093305979731169), df=np.float64(350.0))"
+       "WilcoxonResult(statistic=np.float64(7703.0), pvalue=np.float64(0.899994181048203))"
       ]
      },
-     "execution_count": 661,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# hist\n",
     "import plotly.graph_objects as go\n",
     "from scipy import stats\n",
     "\n",
-    "# agg by fake bio group \n",
-    "bio_mean = sc.get.aggregate(\n",
-    "    adata,\n",
-    "    by=\"bio\",\n",
-    "    axis=\"obs\",\n",
-    "    func='mean',\n",
-    "    layer='nona'\n",
-    ").to_df('mean').T\n",
+    "# transpose for easier plotting\n",
+    "bio_mean = agg_mean.to_df('mean').T\n",
     "\n",
     "# init fig\n",
     "fig = go.Figure()\n",
@@ -988,14 +2580,13 @@
     "fig.add_trace(go.Histogram(x=bio_mean['Group1'], name='Group1'))\n",
     "fig.add_trace(go.Histogram(x=bio_mean['Group2'], name='Group2'))\n",
     "\n",
-    "# Overlay both histograms\n",
+    "# formatting\n",
     "fig.update_layout(barmode='overlay')\n",
-    "# Reduce opacity to see both histograms\n",
     "fig.update_traces(opacity=0.75)\n",
     "fig.show()\n",
     "\n",
-    "# no diff in stats \n",
-    "stats.ttest_ind(bio_mean['Group1'], bio_mean['Group2'])"
+    "# check no diff in stats \n",
+    "stats.wilcoxon(bio_mean['Group1'], bio_mean['Group2'])"
    ]
   },
   {
@@ -1003,17 +2594,9 @@
    "id": "66663906",
    "metadata": {},
    "source": [
-    "The columns (variables, vars) are the different taxa annotated with taxonomic ranks (sk = super kingdom, k = kingdom, p = phylum, c = class, o = order, f = family, g = genus).\n",
-    "\n",
-    "The rows (observations, obs) are the metadata for the different samples in the study MGYS00001135. \n",
-    "\n",
-    "The ones of interest for this demo are: \n",
-    "- The `analysis_completed_date` which accounts for batch effect for our purposes, and\n",
-    "- `ww_plant` which are the different sampling locations and we will use as our biological variance that we wish to retain after batch correction.\n",
+    "## Prepare data for ABaCo\n",
     "\n",
-    "-----\n",
-    "\n",
-    "We can easily extract a df from anndata so that we meet the data format required for abaco."
+    "Great. Now lets proceed with adata where we can easily extract a df to meet the data format required for abaco."
    ]
   },
   {
@@ -1068,12 +2651,12 @@
     "\n",
     "- The data has categorical columns: \n",
     "    1. unique ids to identify the observations/samples e.g. sample id col\n",
-    "    2. ids for the batch/factor groupings to be corrected by abaco. e.g. dates of sample analysis batch_col\n",
-    "    3. biological/experimental factor variation for abaco to retain when correcting batch effect e.g., sampling location bio_col\n",
+    "    2. ids for the batch/factor groupings to be corrected by abaco. e.g. our phony bio data \n",
+    "    3. biological/experimental factor variation for abaco to retain when correcting batch effect e.g., study id \n",
     "\n",
     "- And taxa counts to be trained on. \n",
     "\n",
-    "We can use `abaco.BatchEffectPlots.plotPCoA()` to visualize any batch and biological effects based on the given categories. "
+    "We can use `abaco.plots.plotPCoA()` to visualize any batch and biological effects based on the given categories. "
    ]
   },
   {
@@ -5040,219 +6623,10 @@
    "metadata": {},
    "source": [
     "- Batch effect (colours): \n",
-    "    - Analysis of the samples were completed on 2 different dates which could result in a technical source of variation captured by the slight clustering of batches along PCo1\n",
-    "- Biological effect (shapes): \n",
-    "    - The samples were collected from 3 different wwtps which we use as the biological source of variation for abaco to retain during batch correction. \n",
-    "    - There isn't a clear clustering of shapes in the PCoA plot, but we can take a look at other metrics such as alpha diversity indices between wwtp locations that should be retained after abaco reconstruction."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cfdd9a92",
-   "metadata": {},
-   "source": [
-    "## Alpha diversity of original samples\n",
-    "\n",
-    "For each sample we will calculate the below richess, evenness and diversity indices and store them as additional sample (obs) metadata in the anndata set.\n",
-    "\n",
-    "Richness\n",
-    "- number of unique species per sample\n",
-    "- Chao1 estimate - correction to above which is likely an underestimation\n",
-    "\n",
-    "Diversity\n",
-    "- Shannon diversity index - if a sample is more diverse then there is more entropy (predicting the next taxa is more difficult) and thus the Shannon diversity index is higher. \n",
-    "- Simpson index (and inverse) - probability of 2 microbes being the same taxa (Simpson index closer to 0 is more diverse, while a higher inverse Simpson index means a sample is more diverse)\n",
-    "\n",
-    "Evenness\n",
-    "- Pielou's evenness index - when abundances are more homogenous in a sample then more even so higher Pielou\n",
-    "\n",
-    "The formulas are included with the below code. The metrics name will be prefixed with 'X_' so that we can later compare them to 'abaco_' metrics. \n",
-    "\n",
-    "### Preprocessing the count tables\n",
-    "\n",
-    "The raw counts require preprocessing because samples will have different total read counts due to technical differences during sequencing. We can normalize the samples to get relative abundances of the taxa summing to 1 (composition data)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 664,
-   "id": "506a301e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
-       "       1., 1.])"
-      ]
-     },
-     "execution_count": 664,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# normalize original data and store as additional anndata layer\n",
-    "adata.layers['normalized_X'] = adata.layers['nona']/adata.layers['nona'].sum(axis=1).reshape(-1,1)\n",
-    "# sanity check \n",
-    "adata.layers['normalized_X'].sum(axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2238f8d2",
-   "metadata": {},
-   "source": [
-    "Our normalized, compositional data (CoDa) is bound to a simplex. To move forward with any statistical tests or ML we can choose to map the coda to unconstrained vectors by log-ratio transforming (e.g., centred log-ratio via `skbio.stats.composition.clr()`) the data. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 665,
-   "id": "54ab5719",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from skbio.stats.composition import clr \n",
-    "\n",
-    "# CLR transform normalized data, replacing zeros with smallll val to avoid log(0)\n",
-    "adata.layers['clr_X'] = clr(np.where(adata.layers['normalized_X'] > 0, adata.layers['normalized_X'], 1e-10))\n",
-    "\n",
-    "# save anndata with new layers\n",
-    "adata.write_h5ad(\"data/mgnify_tomato.h5ad\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b63709a3",
-   "metadata": {},
-   "source": [
-    "### Alpha diversity as sample metadata"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 666,
-   "id": "cf343afd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/14881299.py:8: RuntimeWarning:\n",
-      "\n",
-      "divide by zero encountered in divide\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Diversity: Number of unique taxa per sample as new metadata\n",
-    "adata.obs['X_numtaxa'] = (adata.X > 0).sum(axis=1) \n",
-    "\n",
-    "# Diversity with correction: Chao1 estimator\n",
-    "# Chao1 = num observed taxa + (num singletons / (2 x num doubletons))\n",
-    "num_singletons = (adata.X == 1).sum(axis=1)\n",
-    "num_doubletons = (adata.X == 2).sum(axis=1)\n",
-    "adata.obs['X_chao1'] = (adata.X > 0).sum(axis=1) + (num_singletons / (2 * num_doubletons))\n",
-    "\n",
-    "# Diversity: Shannon index H = -sum(p_i * log(p_i)), entropy\n",
-    "from scipy.stats import entropy\n",
-    "adata.obs['X_shannon'] = entropy(adata.layers['normalized_X'], nan_policy='omit', axis=1)\n",
-    "\n",
-    "# Evenness: Pielou evenness index P = H/H_max, H_max = ln(num species)\n",
-    "adata.obs['X_pielou'] = adata.obs['X_shannon'] / np.log(adata.obs['X_numtaxa'])\n",
-    "\n",
-    "# Diversity: simpson index lambda = sum(p_i ^2)\n",
-    "adata.obs['X_simpson'] = (adata.layers['normalized_X'] ** 2).sum(axis=1)\n",
-    "\n",
-    "# Diversity: inverse simpson index D = 1/lambda\n",
-    "adata.obs['X_inv_simpson'] = 1 / adata.obs['X_simpson']"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d93a9846",
-   "metadata": {},
-   "source": [
-    "We can quickly visualize the distribution and relationships between the metrics by batch and biological groups using [`seaborn.pairplot()`](https://seaborn.pydata.org/generated/seaborn.pairplot.html)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 667,
-   "id": "5b7f3d3e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[None]"
-      ]
-     },
-     "execution_count": 667,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1181.25x1080 with 27 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1239.38x1080 with 27 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "# preparing the df for vis\n",
-    "df_alphas = adata.obs[[\n",
-    "    'X_numtaxa', 'X_chao1', 'X_shannon', \n",
-    "    'X_pielou', 'X_simpson', 'X_inv_simpson',\n",
-    "    batch_col, bio_col\n",
-    "]].copy()\n",
-    "\n",
-    "# plotting by bio groups\n",
-    "g1 = sns.pairplot(df_alphas, hue=bio_col, corner=True, height=1.8)\n",
-    "g1.figure.suptitle('Alpha Diversity by Biological Groups', fontsize=22)\n",
-    "plt.setp(g1._legend.get_texts(), fontsize=18)\n",
-    "plt.setp(g1._legend.get_title(), fontsize=20)\n",
-    "\n",
-    "g2 = sns.pairplot(df_alphas, hue=batch_col, corner=True, height=1.8)\n",
-    "g2.figure.suptitle('Alpha Diversity by Batch Groups', fontsize=22)\n",
-    "plt.setp(g2._legend.get_texts(), fontsize=18)\n",
-    "plt.setp(g2._legend.get_title(), fontsize=20)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2fac173b",
-   "metadata": {},
-   "source": [
-    "The pairplots suggest that the batch effect could be influencing the alpha diversity of the samples. \n",
+    "    - Different sequencing platforms which could result in a technical source of variation captured by the clustering of studies 6204 & 6205 (Illumina HiSeq 2500) vs. study 6231 (Illumina HiSeq 4000) along PCo1\n",
     "\n",
+    "- Biological effect (shapes): \n",
+    "    - The groups were randomly assigned so we expect no clustering by shape as supported by the pcoa above. This behaviour should not change with abaco reconstruction.\n",
     "-----"
    ]
   },
@@ -5261,8 +6635,6 @@
    "id": "bbae141c",
    "metadata": {},
    "source": [
-    "\n",
-    "\n",
     "## The goal \n",
     "\n",
     "Here the aim of **ABaCo** is to: \n",
@@ -5277,14 +6649,15 @@
     "\n",
     "### Setting up ABaCo\n",
     "\n",
-    "We instantiate the `abaco.metaABaCo()` class and pass the required parameters shown in the cell below. Thus, running abaco with the default optional parameters.\n",
+    "We instantiate the `abaco.metaABaCo()` class and pass the required parameters shown in the cell below. \n",
     "\n",
-    "Usually, setup of the parameters is required, which are explained in brief in the documentation e.g. `help(metaABaCo)`"
+    "Usually, setup of the parameters is required, which are explained in brief in the documentation e.g. `help(metaABaCo)`\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 701,
+   "execution_count": null,
    "id": "ac1c6cc7",
    "metadata": {},
    "outputs": [],
@@ -5304,8 +6677,8 @@
     "    n_features=df_taxa.shape[1], # Number of features (taxonomic groups)\n",
     "    prior=\"MoG\", # Prior distribution \n",
     "    device=device, # Device\n",
-    "    d_z=16,\n",
-    "    epochs = [3000, 2000, 3000]\n",
+    "    d_z=16, # dimensionality of the latent space\n",
+    "    epochs = [3000, 2000, 3000] # num epochs for each training phase\n",
     ")"
    ]
   },
@@ -6956,141 +8329,6 @@
     "We can also take a look at the alpha diversity metrics:"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 709,
-   "id": "be1b2c3c",
-   "metadata": {
-    "tags": [
-     "hide-input"
-    ]
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/2384117532.py:14: RuntimeWarning:\n",
-      "\n",
-      "divide by zero encountered in divide\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[None]"
-      ]
-     },
-     "execution_count": 709,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1181.25x1080 with 27 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1239.38x1080 with 27 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "## PREPROCESSING THE ABaCo DATA\n",
-    "# normalize abaco corrected data\n",
-    "adata.layers['normalized_abaco'] = (adata.layers['abaco']/adata.layers['abaco'].sum(axis=1).reshape(-1,1))\n",
-    "# CLR transform normalized ABaCo data\n",
-    "adata.layers['clr_abaco'] = clr(np.where(adata.layers['normalized_abaco'] > 0, adata.layers['normalized_abaco'], 1e-10))\n",
-    "\n",
-    "## Alpha diversity metrics on ABaCo corrected data\n",
-    "# Diversity: Number of unique taxa per sample as new metadata\n",
-    "adata.obs['abaco_numtaxa'] = (adata.layers['abaco'] > 0).sum(axis=1) \n",
-    "# Diversity with correction: Chao1 estimator\n",
-    "# Chao1 = num observed taxa + (num singletons / (2 x num doubletons))\n",
-    "num_singletons = (adata.layers['abaco'] == 1).sum(axis=1)\n",
-    "num_doubletons = (adata.layers['abaco'] == 2).sum(axis=1)\n",
-    "adata.obs['abaco_chao1'] = (adata.layers['abaco'] > 0).sum(axis=1) + (num_singletons / (2 * num_doubletons))\n",
-    "# Diversity: Shannon index H = -sum(p_i * log(p_i)), entropy\n",
-    "adata.obs['abaco_shannon'] = entropy(adata.layers['normalized_abaco'], nan_policy='omit', axis=1)\n",
-    "# Evenness: Pielou evenness index P = H/H_max, H_max = ln(num species)\n",
-    "adata.obs['abaco_pielou'] = adata.obs['abaco_shannon'] / np.log(adata.obs['abaco_numtaxa'])\n",
-    "# Diversity: simpson index lambda = sum(p_i ^2)\n",
-    "adata.obs['abaco_simpson'] = (adata.layers['normalized_abaco'] ** 2).sum(axis=1)\n",
-    "# Diversity: inverse simpson index D = 1/lambda\n",
-    "adata.obs['abaco_inv_simpson'] = 1 / adata.obs['abaco_simpson']\n",
-    "\n",
-    "## PAIRPLOTS OF ALPHA DIVERSITY METRICS\n",
-    "# prep df for vis\n",
-    "df_abaco_alphas = adata.obs[[\n",
-    "    'abaco_numtaxa', 'abaco_chao1', 'abaco_shannon', \n",
-    "    'abaco_pielou', 'abaco_simpson', 'abaco_inv_simpson',\n",
-    "    batch_col, bio_col\n",
-    "]].copy()\n",
-    "# plotting by bio groups\n",
-    "g1 = sns.pairplot(df_abaco_alphas, hue=bio_col, corner=True, height=1.8)\n",
-    "g1.figure.suptitle('ABaCo: Alpha Diversity by Biological Groups', fontsize=22)\n",
-    "plt.setp(g1._legend.get_texts(), fontsize=18)\n",
-    "plt.setp(g1._legend.get_title(), fontsize=20)\n",
-    "g2 = sns.pairplot(df_abaco_alphas, hue=batch_col, corner=True, height=1.8)\n",
-    "g2.figure.suptitle('ABaCo: Alpha Diversity by Batch Groups', fontsize=22)\n",
-    "plt.setp(g2._legend.get_texts(), fontsize=18)\n",
-    "plt.setp(g2._legend.get_title(), fontsize=20)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 732,
-   "id": "01521c69",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3415170421.py:1: FutureWarning:\n",
-      "\n",
-      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "ERZ12633510    16.250000\n",
-       "ERZ12633502    26.875000\n",
-       "ERZ12633503    14.500000\n",
-       "ERZ12633504    16.333333\n",
-       "ERZ12633506    17.666667\n",
-       "                 ...    \n",
-       "ERZ12633497     7.500000\n",
-       "ERZ12633488    17.000000\n",
-       "ERZ12633498    15.333333\n",
-       "ERZ12633489    24.300000\n",
-       "ERZ12633499    17.800000\n",
-       "Name: abaco_chao1, Length: 61, dtype: float64"
-      ]
-     },
-     "execution_count": 732,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "adata.obs.groupby('bio').get_group('Group1')['abaco_chao1']"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 736,

From 7e3d1cfce30c8d2c20b5150f8c6745489995a5d9 Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 18:42:18 +0100
Subject: [PATCH 5/9] :bug:Fix: error for min_kl

if no kl > 0 then set min to 0 to prevent empty array error
---
 src/abaco/ABaCo.py | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/src/abaco/ABaCo.py b/src/abaco/ABaCo.py
index dd93495..9379b6f 100644
--- a/src/abaco/ABaCo.py
+++ b/src/abaco/ABaCo.py
@@ -3567,7 +3567,12 @@ def cluster_loss(self):
                     kl_matrix[i, j] = kl
 
         # Take the minimum KL divergence between any two components
-        min_kl = kl_matrix[kl_matrix > 0].min()
+        positive_kl = kl_matrix[kl_matrix > 0]
+        if positive_kl.numel() == 0:
+            # Handle the case where there are no positive KL values
+            min_kl = 0.0  # or float('inf'), or another default
+        else:
+            min_kl = positive_kl.min()
         # Loss is inverse of min KL (maximize separation)
         return 1.0 / (min_kl + 1e-8)
 
@@ -3702,7 +3707,12 @@ def cluster_loss(self):
                     kl_matrix[i, j] = kl
 
         # Take the minimum KL divergence between any two components
-        min_kl = kl_matrix[kl_matrix > 0].min()
+        positive_kl = kl_matrix[kl_matrix > 0]
+        if positive_kl.numel() == 0:
+            # Handle the case where there are no positive KL values
+            min_kl = 0.0  # or float('inf'), or another default
+        else:
+            min_kl = positive_kl.min()
         # Loss is inverse of min KL (maximize separation)
         return 1.0 / (min_kl + 1e-8)
 

From ece68b5a21e6599e38c3b648e128e7c45a3e25d1 Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 18:42:33 +0100
Subject: [PATCH 6/9] add scanpy

---
 requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements.txt b/requirements.txt
index 2d86214..63bdb1e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -55,6 +55,7 @@ python-dateutil
 pytz
 PyYAML
 requests
+scanpy
 scikit-bio
 scikit-learn
 scipy

From ec91bddec61d1910872f5e2649b97f2dae03223f Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 18:46:45 +0100
Subject: [PATCH 7/9] :truck: renaming tutorial

---
 ...iomes.ipynb => demo-mgnify-tomatoes.ipynb} | 2331 +++++------------
 1 file changed, 678 insertions(+), 1653 deletions(-)
 rename docs/tutorial/{demo-mgnify-ww-biomes.ipynb => demo-mgnify-tomatoes.ipynb} (88%)

diff --git a/docs/tutorial/demo-mgnify-ww-biomes.ipynb b/docs/tutorial/demo-mgnify-tomatoes.ipynb
similarity index 88%
rename from docs/tutorial/demo-mgnify-ww-biomes.ipynb
rename to docs/tutorial/demo-mgnify-tomatoes.ipynb
index 66c55c4..6949cd6 100644
--- a/docs/tutorial/demo-mgnify-ww-biomes.ipynb
+++ b/docs/tutorial/demo-mgnify-tomatoes.ipynb
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 126,
    "id": "f94eae83",
    "metadata": {},
    "outputs": [
@@ -109,26 +109,26 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Betaproteobacteria;o__Burkholderiales;f__Oxalobacteraceae</th>\n",
+       "      <th>sk__Bacteria;k__;p__Planctomycetes;c__Planctomycetia;o__Pirellulales</th>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__candidate_division_NC10</th>\n",
+       "      <th>sk__Bacteria;k__;p__Actinobacteria;c__Acidimicrobiia;o__Acidimicrobiales;f__Ilumatobacteraceae;g__Ilumatobacter</th>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -139,49 +139,49 @@
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Eukaryota;k__Metazoa</th>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Deltaproteobacteria;o__Myxococcales;f__Kofleriaceae</th>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Alphaproteobacteria;o__Rhizobiales;f__Xanthobacteraceae</th>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Betaproteobacteria;o__Burkholderiales;f__Comamonadaceae</th>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Actinobacteria;c__Actinobacteria;o__Propionibacteriales;f__Propionibacteriaceae;g__Microlunatus</th>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -190,51 +190,51 @@
       "text/plain": [
        "                                                    ERZ12633510  ERZ12633501  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            1   \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            0   \n",
-       "sk__Eukaryota;k__Metazoa                                      0            1   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            1   \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            1            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            0            0   \n",
        "\n",
        "                                                    ERZ12633502  ERZ12633503  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            1   \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            1   \n",
-       "sk__Eukaryota;k__Metazoa                                      0            1   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            2   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            1            0   \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            0            1   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            1            0   \n",
        "\n",
        "                                                    ERZ12633504  ERZ12633505  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            1            1   \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            0   \n",
-       "sk__Eukaryota;k__Metazoa                                      0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            1            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            1            0   \n",
        "\n",
        "                                                    ERZ12633506  ERZ12633507  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            1   \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            0   \n",
-       "sk__Eukaryota;k__Metazoa                                      1            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            1            1   \n",
        "\n",
        "                                                    ERZ12633517  ERZ12633508  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            0   \n",
-       "sk__Eukaryota;k__Metazoa                                      0            1   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            1            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            1   \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            1            0   \n",
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            0            0   \n",
        "\n",
        "                                                    ERZ12633518  ERZ12633509  \n",
        "taxa                                                                          \n",
+       "sk__Bacteria;k__;p__Planctomycetes;c__Planctomy...            0            0  \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Acidimicr...            0            0  \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            1            0  \n",
        "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0  \n",
-       "sk__Bacteria;k__;p__candidate_division_NC10                   0            0  \n",
-       "sk__Eukaryota;k__Metazoa                                      0            0  \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0  \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            1  "
+       "sk__Bacteria;k__;p__Firmicutes;c__Clostridia;o_...            0            0  "
       ]
      },
      "metadata": {},
@@ -317,14 +317,14 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Planctomycetes</th>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae;o__Opitutales;f__Opitutaceae;g__Opitutus</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
@@ -334,20 +334,20 @@
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Betaproteobacteria;o__Burkholderiales;f__Oxalobacteraceae;g__Janthinobacterium</th>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Bacteria;k__;p__Candidatus_Saccharibacteria;c__;o__;f__;g__Candidatus_Saccharimonas</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -362,12 +362,12 @@
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumatomonadida</th>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Entomophthoromycetes</th>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -389,31 +389,31 @@
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Actinobacteria;c__Actinobacteria;o__Streptomycetales;f__Streptomycetaceae;g__Streptomyces</th>\n",
-       "      <td>1</td>\n",
-       "      <td>5</td>\n",
-       "      <td>5</td>\n",
-       "      <td>1</td>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Gammaproteobacteria;o__Xanthomonadales;f__Xanthomonadaceae;g__Pseudoxanthomonas</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>4</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>1</td>\n",
        "      <td>...</td>\n",
-       "      <td>5</td>\n",
-       "      <td>3</td>\n",
        "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>4</td>\n",
-       "      <td>1</td>\n",
-       "      <td>3</td>\n",
        "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Euamoebida;f__Hartmannellidae;g__Saccamoeba</th>\n",
+       "      <th>sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia;o__Herpetosiphonales;f__Herpetosiphonaceae</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -444,91 +444,91 @@
       "text/plain": [
        "                                                    ERZ12343720  ERZ12343730  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            1            5   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            1   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12343740  ERZ12343750  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            5            1   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12343760  ERZ12343770  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            1   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            1   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12343780  ERZ12343721  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            4            3   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            1            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12343731  ERZ12343741  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            1   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            3            1   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            1   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ...  ERZ12590947  \\\n",
        "taxa                                                ...                \n",
-       "sk__Bacteria;k__;p__Planctomycetes                  ...            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...  ...            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...  ...            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...  ...            5   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...  ...            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...  ...            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...  ...            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...  ...            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...  ...            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...  ...            0   \n",
        "\n",
        "                                                    ERZ12593067  ERZ12590878  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            3            0   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            1            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12590908  ERZ12590968  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            2            4   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12590988  ERZ12590849  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            0   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            1            3   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            1            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            0   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12590879  ERZ12590889  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0            1   \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0            0   \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            1            1   \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0            0   \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            0            0   \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            0            1   \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0            0   \n",
        "\n",
        "                                                    ERZ12590909  \n",
        "taxa                                                             \n",
-       "sk__Bacteria;k__;p__Planctomycetes                            0  \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Betaprote...            0  \n",
-       "sk__Eukaryota;k__;p__Imbricatea;c__;o__Thaumato...            0  \n",
-       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            3  \n",
-       "sk__Eukaryota;k__;p__Tubulinea;c__Elardia;o__Eu...            0  \n",
+       "sk__Bacteria;k__;p__Verrucomicrobia;c__Opitutae...            1  \n",
+       "sk__Bacteria;k__;p__Candidatus_Saccharibacteria...            1  \n",
+       "sk__Eukaryota;k__Fungi;p__Zoopagomycota;c__Ento...            0  \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Gammaprot...            0  \n",
+       "sk__Bacteria;k__;p__Chloroflexi;c__Chloroflexia...            0  \n",
        "\n",
        "[5 rows x 114 columns]"
       ]
@@ -595,26 +595,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o__Nitrospirales;f__Nitrospiraceae;g__Nitrospira;s__Nitrospira_japonica</th>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromadorea;o__Rhabditida;f__Cephalobidae</th>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
+       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Alphaproteobacteria;o__Sphingomonadales;f__Sphingomonadaceae;g__Sphingomonas</th>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Bacteria;k__;p__Acidobacteria;c__Blastocatellia;o__Blastocatellales;f__Pyrinomonadaceae</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "      <td>1</td>\n",
-       "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacteriia;o__Flavobacteriales;f__Flavobacteriaceae</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -623,28 +636,26 @@
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromadorea;o__Rhabditida;f__Cephalobidae;g__Acrobeloides</th>\n",
+       "      <th>sk__Bacteria;k__;p__Proteobacteria;c__Deltaproteobacteria;o__Myxococcales;f__Archangiaceae</th>\n",
+       "      <td>2</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Acidobacteria;c__Acidobacteriia;o__Bryobacterales;f__Bryobacteraceae;g__Bryobacter</th>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <th>sk__Bacteria;k__;p__Actinobacteria;c__Actinobacteria;o__Propionibacteriales;f__Propionibacteriaceae;g__Microlunatus</th>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
@@ -653,18 +664,7 @@
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Bacillales;f__Bacillaceae;g__Bacillus</th>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>4</td>\n",
-       "      <td>2</td>\n",
        "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
@@ -676,51 +676,51 @@
       "text/plain": [
        "                                                    ERZ12633490  ERZ12633491  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
-       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            2   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            1   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            1            1   \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            1            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            2            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
        "\n",
        "                                                    ERZ12633492  ERZ12633493  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            1   \n",
-       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            1   \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            4            2   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            1            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            1            1   \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            1   \n",
        "\n",
        "                                                    ERZ12633494  ERZ12633495  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
-       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            0            2   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            1            1   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            1            1   \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
        "\n",
        "                                                    ERZ12633496  ERZ12633497  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            1            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
-       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0   \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            1   \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            3            3   \n",
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            1            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            2            2   \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            0            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
        "\n",
        "                                                    ERZ12633488  ERZ12633498  \\\n",
        "taxa                                                                           \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0   \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            0            0   \n",
        "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            1            0   \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0   \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            0   \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            2            1   \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            1            0   \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            0            0   \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            0            0   \n",
        "\n",
        "                                                    ERZ12633489  ERZ12633499  \n",
        "taxa                                                                          \n",
-       "sk__Bacteria;k__;p__Nitrospirae;c__Nitrospira;o...            0            0  \n",
-       "sk__Bacteria;k__;p__Proteobacteria;c__Alphaprot...            1            0  \n",
-       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            1  \n",
-       "sk__Bacteria;k__;p__Acidobacteria;c__Acidobacte...            0            0  \n",
-       "sk__Bacteria;k__;p__Firmicutes;c__Bacilli;o__Ba...            1            1  "
+       "sk__Eukaryota;k__Metazoa;p__Nematoda;c__Chromad...            0            0  \n",
+       "sk__Bacteria;k__;p__Acidobacteria;c__Blastocate...            1            1  \n",
+       "sk__Bacteria;k__;p__Bacteroidetes;c__Flavobacte...            0            0  \n",
+       "sk__Bacteria;k__;p__Proteobacteria;c__Deltaprot...            1            0  \n",
+       "sk__Bacteria;k__;p__Actinobacteria;c__Actinobac...            1            1  "
       ]
      },
      "metadata": {},
@@ -769,12 +769,12 @@
     "- the samples as columns \n",
     "- and the values are the number of taxanomic assignments for the given taxa x sample\n",
     "\n",
-    "To join them we will use a helper function `abaco.utils.df_joiner()`. Additionally we filter out some taxa if they are missing in more than 30% of the samples. "
+    "To join them we will use a helper function `abaco.utils.df_joiner()`. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 153,
    "id": "c6d2108b",
    "metadata": {},
    "outputs": [
@@ -783,10 +783,10 @@
      "output_type": "stream",
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
-      "Index: 446 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
+      "Index: 531 entries, sk__Archaea to sk__Eukaryota;k__Viridiplantae;p__Streptophyta;c__Magnoliopsida;o__Solanales;f__Solanaceae\n",
       "Columns: 138 entries, ERZ12633510 to ERZ12633499\n",
       "dtypes: float64(138)\n",
-      "memory usage: 484.3+ KB\n"
+      "memory usage: 576.6+ KB\n"
      ]
     }
    ],
@@ -799,21 +799,9 @@
     "    how=\"outer\",\n",
     ")\n",
     "\n",
-    "# filtering if taxa is missing in more than 30% of samples\n",
-    "joined = joined[(joined.isna().sum(axis=1) / joined.shape[1] <= 0.3)].copy()\n",
-    "#joined = joined.dropna(axis=0)\n",
-    "\n",
     "joined.info()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "319d691e",
-   "metadata": {},
-   "source": [
-    "Based on the printed df info, there are 138 samples and 446 taxa. "
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "9511c611",
@@ -828,7 +816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 154,
    "id": "b6303749",
    "metadata": {},
    "outputs": [
@@ -866,29 +854,29 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>ERZ12343723</th>\n",
+       "      <th>ERZ12343766</th>\n",
        "      <td>MGYS00006231</td>\n",
-       "      <td>Group2</td>\n",
+       "      <td>Group1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ERZ12590849</th>\n",
+       "      <th>ERZ12590853</th>\n",
        "      <td>MGYS00006231</td>\n",
-       "      <td>Group1</td>\n",
+       "      <td>Group2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ERZ12590855</th>\n",
+       "      <th>ERZ12343727</th>\n",
        "      <td>MGYS00006231</td>\n",
        "      <td>Group2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ERZ12343782</th>\n",
+       "      <th>ERZ12343729</th>\n",
        "      <td>MGYS00006231</td>\n",
        "      <td>Group1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ERZ12633517</th>\n",
-       "      <td>MGYS00006205</td>\n",
-       "      <td>Group1</td>\n",
+       "      <th>ERZ12590922</th>\n",
+       "      <td>MGYS00006231</td>\n",
+       "      <td>Group2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -896,11 +884,11 @@
       ],
       "text/plain": [
        "taxa               source     bio\n",
-       "ERZ12343723  MGYS00006231  Group2\n",
-       "ERZ12590849  MGYS00006231  Group1\n",
-       "ERZ12590855  MGYS00006231  Group2\n",
-       "ERZ12343782  MGYS00006231  Group1\n",
-       "ERZ12633517  MGYS00006205  Group1"
+       "ERZ12343766  MGYS00006231  Group1\n",
+       "ERZ12590853  MGYS00006231  Group2\n",
+       "ERZ12343727  MGYS00006231  Group2\n",
+       "ERZ12343729  MGYS00006231  Group1\n",
+       "ERZ12590922  MGYS00006231  Group2"
       ]
      },
      "metadata": {},
@@ -910,7 +898,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(446, 8)\n"
+      "(531, 8)\n"
      ]
     },
     {
@@ -946,58 +934,58 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>236</th>\n",
+       "      <th>175</th>\n",
        "      <td>sk__Bacteria</td>\n",
        "      <td>k__</td>\n",
-       "      <td>p__Planctomycetes</td>\n",
-       "      <td>c__Phycisphaerae</td>\n",
-       "      <td>o__Tepidisphaerales</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
+       "      <td>p__Candidatus_Omnitrophica</td>\n",
+       "      <td>c__</td>\n",
+       "      <td>o__</td>\n",
+       "      <td>f__</td>\n",
+       "      <td>g__</td>\n",
+       "      <td>s__Omnitrophica_WOR_2_bacterium_RBG_13_44_8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>393</th>\n",
+       "      <th>478</th>\n",
        "      <td>sk__Eukaryota</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
+       "      <td>k__</td>\n",
+       "      <td>p__Haptista</td>\n",
+       "      <td>c__Centroplasthelida</td>\n",
+       "      <td>o__Pterocystida</td>\n",
+       "      <td>f__</td>\n",
+       "      <td>g__Choanocystis</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>219</th>\n",
        "      <td>sk__Bacteria</td>\n",
        "      <td>k__</td>\n",
-       "      <td>p__</td>\n",
-       "      <td>c__Candidatus_Babeliae</td>\n",
-       "      <td>o__Candidatus_Babeliales</td>\n",
+       "      <td>p__Fibrobacteres</td>\n",
+       "      <td>c__Chitinivibrionia</td>\n",
+       "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>286</th>\n",
+       "      <th>165</th>\n",
        "      <td>sk__Bacteria</td>\n",
        "      <td>k__</td>\n",
-       "      <td>p__Proteobacteria</td>\n",
-       "      <td>c__Alphaproteobacteria</td>\n",
-       "      <td>o__Sphingomonadales</td>\n",
-       "      <td>f__Sphingomonadaceae</td>\n",
-       "      <td>g__Novosphingobium</td>\n",
+       "      <td>p__Candidatus_Doudnabacteria</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>267</th>\n",
+       "      <th>369</th>\n",
        "      <td>sk__Bacteria</td>\n",
        "      <td>k__</td>\n",
        "      <td>p__Proteobacteria</td>\n",
-       "      <td>c__Alphaproteobacteria</td>\n",
-       "      <td>o__Rhizobiales</td>\n",
-       "      <td>f__Xanthobacteraceae</td>\n",
-       "      <td>None</td>\n",
+       "      <td>c__Deltaproteobacteria</td>\n",
+       "      <td>o__Myxococcales</td>\n",
+       "      <td>f__Kofleriaceae</td>\n",
+       "      <td>g__Haliangium</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -1005,26 +993,26 @@
        "</div>"
       ],
       "text/plain": [
-       "      superkingdom kingdom             phylum                   class  \\\n",
-       "236   sk__Bacteria     k__  p__Planctomycetes        c__Phycisphaerae   \n",
-       "393  sk__Eukaryota    None               None                    None   \n",
-       "8     sk__Bacteria     k__                p__  c__Candidatus_Babeliae   \n",
-       "286   sk__Bacteria     k__  p__Proteobacteria  c__Alphaproteobacteria   \n",
-       "267   sk__Bacteria     k__  p__Proteobacteria  c__Alphaproteobacteria   \n",
-       "\n",
-       "                        order                family               genus  \\\n",
-       "236       o__Tepidisphaerales                  None                None   \n",
-       "393                      None                  None                None   \n",
-       "8    o__Candidatus_Babeliales                  None                None   \n",
-       "286       o__Sphingomonadales  f__Sphingomonadaceae  g__Novosphingobium   \n",
-       "267            o__Rhizobiales  f__Xanthobacteraceae                None   \n",
-       "\n",
-       "    species  \n",
-       "236    None  \n",
-       "393    None  \n",
-       "8      None  \n",
-       "286    None  \n",
-       "267    None  "
+       "      superkingdom kingdom                        phylum  \\\n",
+       "175   sk__Bacteria     k__    p__Candidatus_Omnitrophica   \n",
+       "478  sk__Eukaryota     k__                   p__Haptista   \n",
+       "219   sk__Bacteria     k__              p__Fibrobacteres   \n",
+       "165   sk__Bacteria     k__  p__Candidatus_Doudnabacteria   \n",
+       "369   sk__Bacteria     k__             p__Proteobacteria   \n",
+       "\n",
+       "                      class            order           family  \\\n",
+       "175                     c__              o__              f__   \n",
+       "478    c__Centroplasthelida  o__Pterocystida              f__   \n",
+       "219     c__Chitinivibrionia             None             None   \n",
+       "165                    None             None             None   \n",
+       "369  c__Deltaproteobacteria  o__Myxococcales  f__Kofleriaceae   \n",
+       "\n",
+       "               genus                                      species  \n",
+       "175              g__  s__Omnitrophica_WOR_2_bacterium_RBG_13_44_8  \n",
+       "478  g__Choanocystis                                         None  \n",
+       "219             None                                         None  \n",
+       "165             None                                         None  \n",
+       "369    g__Haliangium                                         None  "
       ]
      },
      "metadata": {},
@@ -1044,7 +1032,7 @@
     "    # add study source column to be batch effect\n",
     "    dfs_T[key]['source'] = key\n",
     "    # dummy bio column, rando group assign, for checking and demo \n",
-    "    dfs_T[key]['bio'] = np.random.choice([\"Group1\",\"Group2\"], size = len(dfs_T[key]))\n",
+    "    dfs_T[key]['bio'] = np.random.choice([\"Group1\", \"Group2\"], size = len(dfs_T[key]))\n",
     "    # drop allother cols\n",
     "    dfs_T[key] = dfs_T[key][['source', 'bio']]\n",
     "# now concat all study metadata \n",
@@ -1075,7 +1063,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 155,
    "id": "d98ecaf7",
    "metadata": {},
    "outputs": [
@@ -1083,19 +1071,21 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning: Transforming to str index.\n",
-      "  return dispatch(args[0].__class__)(*args, **kw)\n"
+      "/Users/anglup/.pyenv/versions/3.11.0/lib/python3.11/functools.py:909: ImplicitModificationWarning:\n",
+      "\n",
+      "Transforming to str index.\n",
+      "\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "AnnData object with n_obs × n_vars = 138 × 446\n",
+       "AnnData object with n_obs × n_vars = 138 × 531\n",
        "    obs: 'source', 'bio'\n",
        "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 155,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1111,47 +1101,17 @@
     "full"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "ed4b1b01",
-   "metadata": {},
-   "source": [
-    "With anndata we can also filter the data using the annotations/metadata. Below we will keep the variables (taxa) with genus assignment."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "4d2802f7",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "View of AnnData object with n_obs × n_vars = 138 × 176\n",
-      "    obs: 'source', 'bio'\n",
-      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n"
-     ]
-    }
-   ],
-   "source": [
-    "# must have genus level\n",
-    "adata = full[:, ~full.var['genus'].isna()]\n",
-    "print(adata)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "7d17b0bd",
    "metadata": {},
    "source": [
-    "We are down to 176 taxa. With anndata we can also store additional layers seamlessly with the same annoations. Below we will create a layer with the NaNs filled with 0s"
+    "With anndata we can also store additional layers seamlessly with the same annoations. Below we will create a layer with the NaNs filled with 0s"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 156,
    "id": "d272c7b1",
    "metadata": {},
    "outputs": [
@@ -1159,7 +1119,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "AnnData object with n_obs × n_vars = 138 × 176\n",
+      "AnnData object with n_obs × n_vars = 138 × 531\n",
       "    obs: 'source', 'bio'\n",
       "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
       "    layers: 'nona'\n",
@@ -1187,171 +1147,171 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
        "      <th>5</th>\n",
        "      <th>6</th>\n",
-       "      <th>14</th>\n",
-       "      <th>15</th>\n",
-       "      <th>16</th>\n",
-       "      <th>19</th>\n",
-       "      <th>24</th>\n",
-       "      <th>25</th>\n",
-       "      <th>26</th>\n",
-       "      <th>30</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
        "      <th>...</th>\n",
-       "      <th>401</th>\n",
-       "      <th>403</th>\n",
-       "      <th>405</th>\n",
-       "      <th>410</th>\n",
-       "      <th>411</th>\n",
-       "      <th>412</th>\n",
-       "      <th>422</th>\n",
-       "      <th>423</th>\n",
-       "      <th>429</th>\n",
-       "      <th>443</th>\n",
+       "      <th>521</th>\n",
+       "      <th>522</th>\n",
+       "      <th>523</th>\n",
+       "      <th>524</th>\n",
+       "      <th>525</th>\n",
+       "      <th>526</th>\n",
+       "      <th>527</th>\n",
+       "      <th>528</th>\n",
+       "      <th>529</th>\n",
+       "      <th>530</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>ERZ12633510</th>\n",
+       "      <td>3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633501</th>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633502</th>\n",
-       "      <td>NaN</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633503</th>\n",
-       "      <td>NaN</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633504</th>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 176 columns</p>\n",
+       "<p>5 rows × 531 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "              5   6  14  15   16   19  24  25   26   30  ...  401  403  405  \\\n",
-       "ERZ12633510 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
-       "ERZ12633501 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
-       "ERZ12633502 NaN NaN NaN NaN  1.0  1.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
-       "ERZ12633503 NaN NaN NaN NaN  0.0  0.0 NaN NaN  1.0  1.0  ...  NaN  NaN  NaN   \n",
-       "ERZ12633504 NaN NaN NaN NaN  0.0  0.0 NaN NaN  0.0  0.0  ...  NaN  NaN  NaN   \n",
-       "\n",
-       "             410  411  412  422  423  429  443  \n",
-       "ERZ12633510  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
-       "ERZ12633501  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
-       "ERZ12633502  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
-       "ERZ12633503  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
-       "ERZ12633504  NaN  NaN  NaN  NaN  NaN  NaN  NaN  \n",
-       "\n",
-       "[5 rows x 176 columns]"
+       "               0   1   2   3    4    5    6   7    8    9  ...  521  522  523  \\\n",
+       "ERZ12633510  3.0 NaN NaN NaN  0.0  0.0  0.0 NaN  1.0  2.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633501  0.0 NaN NaN NaN  0.0  0.0  0.0 NaN  0.0  2.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633502  2.0 NaN NaN NaN  1.0  0.0  1.0 NaN  0.0  4.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633503  3.0 NaN NaN NaN  0.0  0.0  0.0 NaN  0.0  1.0  ...  NaN  NaN  NaN   \n",
+       "ERZ12633504  0.0 NaN NaN NaN  0.0  0.0  0.0 NaN  0.0  2.0  ...  NaN  NaN  NaN   \n",
+       "\n",
+       "             524  525  526  527  528  529  530  \n",
+       "ERZ12633510  NaN  1.0  NaN  NaN  0.0  NaN  NaN  \n",
+       "ERZ12633501  NaN  0.0  NaN  NaN  0.0  NaN  NaN  \n",
+       "ERZ12633502  NaN  0.0  NaN  NaN  0.0  NaN  NaN  \n",
+       "ERZ12633503  NaN  0.0  NaN  NaN  0.0  NaN  NaN  \n",
+       "ERZ12633504  NaN  0.0  NaN  NaN  0.0  NaN  NaN  \n",
+       "\n",
+       "[5 rows x 531 columns]"
       ]
      },
      "metadata": {},
@@ -1385,32 +1345,33 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
        "      <th>5</th>\n",
        "      <th>6</th>\n",
-       "      <th>14</th>\n",
-       "      <th>15</th>\n",
-       "      <th>16</th>\n",
-       "      <th>19</th>\n",
-       "      <th>24</th>\n",
-       "      <th>25</th>\n",
-       "      <th>26</th>\n",
-       "      <th>30</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
        "      <th>...</th>\n",
-       "      <th>401</th>\n",
-       "      <th>403</th>\n",
-       "      <th>405</th>\n",
-       "      <th>410</th>\n",
-       "      <th>411</th>\n",
-       "      <th>412</th>\n",
-       "      <th>422</th>\n",
-       "      <th>423</th>\n",
-       "      <th>429</th>\n",
-       "      <th>443</th>\n",
+       "      <th>521</th>\n",
+       "      <th>522</th>\n",
+       "      <th>523</th>\n",
+       "      <th>524</th>\n",
+       "      <th>525</th>\n",
+       "      <th>526</th>\n",
+       "      <th>527</th>\n",
+       "      <th>528</th>\n",
+       "      <th>529</th>\n",
+       "      <th>530</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>ERZ12633510</th>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1418,15 +1379,14 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1444,7 +1404,7 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1459,16 +1419,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633502</th>\n",
+       "      <td>2.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1483,6 +1443,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ERZ12633503</th>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1492,7 +1453,6 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1516,7 +1476,7 @@
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
@@ -1531,25 +1491,25 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 176 columns</p>\n",
+       "<p>5 rows × 531 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "               5    6   14   15   16   19   24   25   26   30  ...  401  403  \\\n",
-       "ERZ12633510  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
-       "ERZ12633501  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
-       "ERZ12633502  0.0  0.0  0.0  0.0  1.0  1.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
-       "ERZ12633503  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  1.0  ...  0.0  0.0   \n",
-       "ERZ12633504  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0   \n",
-       "\n",
-       "             405  410  411  412  422  423  429  443  \n",
-       "ERZ12633510  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
+       "               0    1    2    3    4    5    6    7    8    9  ...  521  522  \\\n",
+       "ERZ12633510  3.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  2.0  ...  0.0  0.0   \n",
+       "ERZ12633501  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  2.0  ...  0.0  0.0   \n",
+       "ERZ12633502  2.0  0.0  0.0  0.0  1.0  0.0  1.0  0.0  0.0  4.0  ...  0.0  0.0   \n",
+       "ERZ12633503  3.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  ...  0.0  0.0   \n",
+       "ERZ12633504  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  2.0  ...  0.0  0.0   \n",
+       "\n",
+       "             523  524  525  526  527  528  529  530  \n",
+       "ERZ12633510  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  \n",
        "ERZ12633501  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
        "ERZ12633502  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
        "ERZ12633503  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
        "ERZ12633504  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
        "\n",
-       "[5 rows x 176 columns]"
+       "[5 rows x 531 columns]"
       ]
      },
      "metadata": {},
@@ -1558,14 +1518,89 @@
    ],
    "source": [
     "# layer with no na\n",
-    "adata.layers['nona'] = np.nan_to_num(adata.X, nan=0)\n",
-    "print(adata)\n",
+    "full.layers['nona'] = np.nan_to_num(full.X, nan=0)\n",
+    "print(full)\n",
     "\n",
     "# checking it out, also demoing to_df method\n",
     "print(\"original:\")\n",
-    "display(adata.to_df().head(5))\n",
+    "display(full.to_df().head(5))\n",
     "print(\"no na:\")\n",
-    "display(adata.to_df(layer='nona').head(5))"
+    "display(full.to_df(layer='nona').head(5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f31ba7c",
+   "metadata": {},
+   "source": [
+    "we can also add normalized and clr layers. For more details on the reasoning of these layers visit our other tutorials."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "id": "2300de51",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AnnData object with n_obs × n_vars = 138 × 531\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "    layers: 'nona', 'norm', 'clr'\n"
+     ]
+    }
+   ],
+   "source": [
+    "from skbio.stats.composition import clr \n",
+    "\n",
+    "full.layers['norm'] = full.layers['nona']/full.layers['nona'].sum(axis=1).reshape(-1,1)\n",
+    "\n",
+    "# CLR transform normalized data, replacing zeros with smallll val to avoid log(0)\n",
+    "full.layers['clr'] = clr(np.where(full.layers['norm'] > 0, full.layers['norm'], 1e-10))\n",
+    "\n",
+    "print(full)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "205062a7",
+   "metadata": {},
+   "source": [
+    "With anndata we can also filter the data using the annotations/metadata. Below we will keep the variables (taxa) with genus assignment. Additionally we filter out some taxa if they are missing in more than 30% of the samples. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "id": "a6d0c0f7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "View of AnnData object with n_obs × n_vars = 138 × 220\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "    layers: 'nona', 'norm', 'clr'\n",
+      "View of AnnData object with n_obs × n_vars = 138 × 176\n",
+      "    obs: 'source', 'bio'\n",
+      "    var: 'superkingdom', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'\n",
+      "    layers: 'nona', 'norm', 'clr'\n"
+     ]
+    }
+   ],
+   "source": [
+    "# must have genus level\n",
+    "adata = full[:, ~full.var['genus'].isna()]\n",
+    "print(adata)\n",
+    "\n",
+    "# filtering if taxa is missing (NaN) in more than 30% of samples\n",
+    "adata = adata[:, np.isnan(adata.X).sum(axis=0)/adata.X.shape[0] <= 0.3]\n",
+    "print(adata)"
    ]
   },
   {
@@ -1573,6 +1608,8 @@
    "id": "4ba030e0",
    "metadata": {},
    "source": [
+    "We are down to 176 taxa. \n",
+    "\n",
     "However, it can be trickier to aggregate with anndata -- but we can use the [scanpy toolkit](https://scanpy.readthedocs.io/en/stable/index.html) to help.  \n",
     "\n",
     "Specifically we will use [scanpy.get.aggregate()](https://scanpy.readthedocs.io/en/stable/generated/scanpy.get.aggregate.html) to help us check that the dummy biological groups we created are not different. "
@@ -1580,7 +1617,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 161,
    "id": "f47a2606",
    "metadata": {},
    "outputs": [
@@ -1615,77 +1652,77 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>5</th>\n",
-       "      <th>6</th>\n",
-       "      <th>14</th>\n",
-       "      <th>15</th>\n",
-       "      <th>16</th>\n",
-       "      <th>19</th>\n",
-       "      <th>24</th>\n",
-       "      <th>25</th>\n",
+       "      <th>11</th>\n",
+       "      <th>12</th>\n",
+       "      <th>20</th>\n",
+       "      <th>21</th>\n",
+       "      <th>23</th>\n",
        "      <th>26</th>\n",
-       "      <th>30</th>\n",
+       "      <th>31</th>\n",
+       "      <th>32</th>\n",
+       "      <th>33</th>\n",
+       "      <th>37</th>\n",
        "      <th>...</th>\n",
-       "      <th>401</th>\n",
-       "      <th>403</th>\n",
-       "      <th>405</th>\n",
-       "      <th>410</th>\n",
-       "      <th>411</th>\n",
-       "      <th>412</th>\n",
-       "      <th>422</th>\n",
-       "      <th>423</th>\n",
-       "      <th>429</th>\n",
-       "      <th>443</th>\n",
+       "      <th>466</th>\n",
+       "      <th>468</th>\n",
+       "      <th>470</th>\n",
+       "      <th>476</th>\n",
+       "      <th>477</th>\n",
+       "      <th>478</th>\n",
+       "      <th>488</th>\n",
+       "      <th>489</th>\n",
+       "      <th>497</th>\n",
+       "      <th>527</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Group1</th>\n",
-       "      <td>0.120000</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.040000</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.040000</td>\n",
-       "      <td>0.093333</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.106667</td>\n",
-       "      <td>0.226667</td>\n",
+       "      <td>-0.656399</td>\n",
+       "      <td>-2.371363</td>\n",
+       "      <td>-2.117223</td>\n",
+       "      <td>-2.125450</td>\n",
+       "      <td>-2.122299</td>\n",
+       "      <td>-1.382745</td>\n",
+       "      <td>-0.883526</td>\n",
+       "      <td>-2.371363</td>\n",
+       "      <td>-1.382469</td>\n",
+       "      <td>1.598991</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.160000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.026667</td>\n",
-       "      <td>0.026667</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <td>1.300304</td>\n",
+       "      <td>-1.892162</td>\n",
+       "      <td>-2.371363</td>\n",
+       "      <td>-2.124440</td>\n",
+       "      <td>-2.371363</td>\n",
+       "      <td>-2.371363</td>\n",
+       "      <td>-2.122834</td>\n",
+       "      <td>-2.126390</td>\n",
+       "      <td>-2.122834</td>\n",
+       "      <td>-2.371363</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Group2</th>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.031746</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.015873</td>\n",
-       "      <td>0.031746</td>\n",
-       "      <td>0.079365</td>\n",
-       "      <td>0.015873</td>\n",
-       "      <td>0.047619</td>\n",
-       "      <td>0.174603</td>\n",
+       "      <td>0.064966</td>\n",
+       "      <td>-2.202220</td>\n",
+       "      <td>-1.344149</td>\n",
+       "      <td>-2.475478</td>\n",
+       "      <td>-2.190108</td>\n",
+       "      <td>-2.189974</td>\n",
+       "      <td>-0.786739</td>\n",
+       "      <td>-1.912433</td>\n",
+       "      <td>-0.481874</td>\n",
+       "      <td>0.379781</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.031746</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.015873</td>\n",
-       "      <td>0.015873</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.015873</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.015873</td>\n",
+       "      <td>0.599701</td>\n",
+       "      <td>-2.475478</td>\n",
+       "      <td>-2.197352</td>\n",
+       "      <td>-2.475478</td>\n",
+       "      <td>-2.194094</td>\n",
+       "      <td>-2.202220</td>\n",
+       "      <td>-1.905638</td>\n",
+       "      <td>-2.189702</td>\n",
+       "      <td>-2.475478</td>\n",
+       "      <td>-2.189974</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1693,17 +1730,17 @@
        "</div>"
       ],
       "text/plain": [
-       "               5         6        14        15        16        19        24  \\\n",
-       "Group1  0.120000  0.013333  0.040000  0.013333  0.013333  0.040000  0.093333   \n",
-       "Group2  0.111111  0.000000  0.031746  0.000000  0.015873  0.031746  0.079365   \n",
+       "              11        12        20        21        23        26        31  \\\n",
+       "Group1 -0.656399 -2.371363 -2.117223 -2.125450 -2.122299 -1.382745 -0.883526   \n",
+       "Group2  0.064966 -2.202220 -1.344149 -2.475478 -2.190108 -2.189974 -0.786739   \n",
        "\n",
-       "              25        26        30  ...       401       403       405  \\\n",
-       "Group1  0.013333  0.106667  0.226667  ...  0.160000  0.000000  0.013333   \n",
-       "Group2  0.015873  0.047619  0.174603  ...  0.222222  0.031746  0.000000   \n",
+       "              32        33        37  ...       466       468       470  \\\n",
+       "Group1 -2.371363 -1.382469  1.598991  ...  1.300304 -1.892162 -2.371363   \n",
+       "Group2 -1.912433 -0.481874  0.379781  ...  0.599701 -2.475478 -2.197352   \n",
        "\n",
-       "             410       411       412       422       423       429       443  \n",
-       "Group1  0.000000  0.000000  0.013333  0.026667  0.026667  0.013333  0.000000  \n",
-       "Group2  0.015873  0.015873  0.000000  0.015873  0.000000  0.000000  0.015873  \n",
+       "             476       477       478       488       489       497       527  \n",
+       "Group1 -2.124440 -2.371363 -2.371363 -2.122834 -2.126390 -2.122834 -2.371363  \n",
+       "Group2 -2.475478 -2.194094 -2.202220 -1.905638 -2.189702 -2.475478 -2.189974  \n",
        "\n",
        "[2 rows x 176 columns]"
       ]
@@ -1718,7 +1755,7 @@
     "    # the anndata object\n",
     "    adata=adata,\n",
     "    # what layer to use\n",
-    "    layer='nona',\n",
+    "    layer='clr',\n",
     "    # group by col\n",
     "    by=\"bio\",\n",
     "    # axis that the group lives\n",
@@ -1742,816 +1779,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 162,
    "id": "80fcd19b",
    "metadata": {},
    "outputs": [
     {
      "data": {
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                       {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('bd3b704e-297d-45a5-b078-49e61d3107f4');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };            </script>        </div>"
+      ]
      },
      "metadata": {},
      "output_type": "display_data"
@@ -2559,10 +1819,10 @@
     {
      "data": {
       "text/plain": [
-       "WilcoxonResult(statistic=np.float64(7703.0), pvalue=np.float64(0.899994181048203))"
+       "WilcoxonResult(statistic=np.float64(7108.0), pvalue=np.float64(0.3150957187537212))"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 162,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2572,13 +1832,13 @@
     "from scipy import stats\n",
     "\n",
     "# transpose for easier plotting\n",
-    "bio_mean = agg_mean.to_df('mean').T\n",
+    "bio_sum = agg_mean.to_df('mean').T\n",
     "\n",
     "# init fig\n",
     "fig = go.Figure()\n",
     "# add traces\n",
-    "fig.add_trace(go.Histogram(x=bio_mean['Group1'], name='Group1'))\n",
-    "fig.add_trace(go.Histogram(x=bio_mean['Group2'], name='Group2'))\n",
+    "fig.add_trace(go.Histogram(x=bio_sum['Group1'], name='Group1'))\n",
+    "fig.add_trace(go.Histogram(x=bio_sum['Group2'], name='Group2'))\n",
     "\n",
     "# formatting\n",
     "fig.update_layout(barmode='overlay')\n",
@@ -2586,7 +1846,7 @@
     "fig.show()\n",
     "\n",
     "# check no diff in stats \n",
-    "stats.wilcoxon(bio_mean['Group1'], bio_mean['Group2'])"
+    "stats.wilcoxon(bio_sum['Group1'], bio_sum['Group2'])"
    ]
   },
   {
@@ -2601,7 +1861,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 662,
+   "execution_count": 163,
    "id": "1d77b8ab",
    "metadata": {},
    "outputs": [
@@ -2612,8 +1872,8 @@
       "<class 'pandas.core.frame.DataFrame'>\n",
       "RangeIndex: 138 entries, 0 to 137\n",
       "Columns: 179 entries, index to bio\n",
-      "dtypes: category(1), float64(176), object(2)\n",
-      "memory usage: 192.3+ KB\n"
+      "dtypes: category(2), float64(176), object(1)\n",
+      "memory usage: 191.5+ KB\n"
      ]
     }
    ],
@@ -2623,13 +1883,13 @@
     "id_col = 'index'\n",
     "\n",
     "# the raw counts as df\n",
-    "df_taxa = adata.to_df()\n",
+    "df_taxa = adata.to_df(\"nona\")\n",
     "\n",
     "# appending on the categorical data of interest\n",
     "df_all = pd.concat([df_taxa, adata.obs[[batch_col, bio_col]]], axis=1).reset_index()\n",
-    "df_all = df_all.fillna(0)\n",
     "\n",
     "df_all['bio'] = df_all['bio'].astype('category')\n",
+    "df_all['source'] = df_all['source'].astype('category')\n",
     "\n",
     "df_all.info()"
    ]
@@ -2661,7 +1921,7 @@
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   {
    "cell_type": "code",
-   "execution_count": 663,
+   "execution_count": 164,
    "id": "128ba953",
    "metadata": {},
    "outputs": [
@@ -6573,9 +5833,9 @@
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     "## The goal \n",
     "\n",
     "Here the aim of **ABaCo** is to: \n",
-    "1) correct the batch effect (e.g., the points should no longer cluster by colour in the PCoA and pairplot) while\n",
-    "2) maintaining biological variance (e.g., the pairplot coloured by bio group should be not change).\n",
+    "1) correct the batch effect (e.g., the points should no longer cluster by colour in the PCoA) while\n",
+    "2) maintaining biological variance (or lack thereof).\n",
     "\n",
-    "Ideally, after using AbaCo to transform the data, the resulting PCoA and pairplot coloured by batches will look like a colourful mixture of points and the pairplot coloured by wwtp location should not change.\n",
+    "Ideally, after using AbaCo to transform the data, the resulting PCoA coloured by batches will look like a colourful mixture of points.\n",
     "\n",
     "-----\n",
     "\n",
@@ -6657,7 +5917,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 264,
    "id": "ac1c6cc7",
    "metadata": {},
    "outputs": [],
@@ -6677,14 +5937,16 @@
     "    n_features=df_taxa.shape[1], # Number of features (taxonomic groups)\n",
     "    prior=\"MoG\", # Prior distribution \n",
     "    device=device, # Device\n",
-    "    d_z=16, # dimensionality of the latent space\n",
-    "    epochs = [3000, 2000, 3000] # num epochs for each training phase\n",
+    "    d_z=16, # default dim of latent space\n",
+    "    epochs = [3000, 1000, 3000], # num epochs for each training phase\n",
+    "    disc_net=[256, 128, 64], # stronger discriminator\n",
+    "    disc_act_fun=torch.nn.LeakyReLU(0.1),\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 702,
+   "execution_count": 265,
    "id": "2f20940c",
    "metadata": {
     "tags": [
@@ -7880,9 +7142,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 703,
+   "execution_count": 266,
    "id": "e5c0aec5",
    "metadata": {
+    "lines_to_next_cell": 2,
     "tags": [
      "hide-output"
     ]
@@ -7892,26 +7155,40 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Training: VAE for learning meaningful embeddings: 100%|██████████| 3000/3000 [00:43<00:00, 68.54it/s, bio_penalty=0.0000, clustering_loss=0.0000, elbo=255.0634, epoch=2999/3001, vae_loss=255.0634]\n",
-      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 2000/2000 [00:36<00:00, 55.16it/s, adv_loss=-0.5765, bio_penalty=0.0000, clustering_loss=0.0000, disc_loss=0.5765, elbo=268.6828, epoch=1999/2001, vae_loss=268.6828]\n",
-      "Training: VAE decoder with masked batch labels: 100%|██████████| 3000/3000 [00:29<00:00, 101.87it/s, cycle_loss=0.0000, epoch=3000/3000, vae_loss=387.4835]\n"
+      "Training: VAE for learning meaningful embeddings: 100%|██████████| 3000/3000 [00:40<00:00, 74.64it/s, bio_penalty=0.0000, clustering_loss=0.0000, elbo=257.3351, epoch=2999/3001, vae_loss=257.3351]\n",
+      "Training: Embeddings batch effect correction using adversrial training: 100%|██████████| 1000/1000 [00:17<00:00, 56.72it/s, adv_loss=-0.5191, bio_penalty=0.0000, clustering_loss=0.0000, disc_loss=0.5191, elbo=281.0243, epoch=999/1001, vae_loss=281.0243]\n",
+      "Training: VAE decoder with masked batch labels: 100%|██████████| 3000/3000 [00:27<00:00, 108.09it/s, cycle_loss=0.0000, epoch=3000/3000, vae_loss=326.0634]\n"
      ]
     }
    ],
    "source": [
     "# Train the model,\n",
-    "model.fit(seed=42, w_bio_penalty=0, w_cluster_penalty=0, w_elbo_nll=10)"
+    "model.fit(\n",
+    "  seed=42,\n",
+    "  w_elbo_nll=10, # more emphasis on reconstruction\n",
+    "  w_bio_penalty=0.0, # disable bio supervision\n",
+    "  w_cluster_penalty=0.0, # light regularization or can be 0\n",
+    "  w_disc=1.0, # default, discriminator training strength\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f02f6b0d",
+   "metadata": {},
+   "source": [
+    "`abaco.metaABaCo` provides a method that visualizes the latent vectors via PCA for dimensionality reduction: `.plot_pca_posterior()`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 704,
+   "execution_count": 268,
    "id": "58848ce7",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1400x600 with 2 Axes>"
       ]
@@ -7929,14 +7206,14 @@
    "id": "18852212",
    "metadata": {},
    "source": [
-    "### Reconstructing the dataset with ABaCO\n",
+    "### Reconstructing the dataset with ABaCo\n",
     "\n",
-    "To reconstruct the dataset we use method `abaco.metaABaCo.reconstruct()` and save it as a new layer `abaco` in the annotated dataset. "
+    "To reconstruct the dataset we use method `abaco.metaABaCo.correct()` and save it as a new layer `abaco` in the annotated dataset. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 705,
+   "execution_count": 269,
    "id": "2c9dbf2a",
    "metadata": {},
    "outputs": [],
@@ -7955,313 +7232,103 @@
    "source": [
     "## Viewing the ABaCo reconstructed dataset\n",
     "\n",
-    "Here we again create PCoA and look at sample alpha diversities via pairplots but on the batch corrected data."
+    "Here we again take a look at the PCoA but first lets check out the mean differences between the original and batch corrected counts."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 706,
-   "id": "321b7c6b",
+   "execution_count": 327,
+   "id": "b31f4a15",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(24288,) (24288,)\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
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+       "                            \n",
+       "var gd = document.getElementById('31fb6ad4-26fb-4d2a-bfb4-f83ef524fc39');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
        "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
        "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>1</th>\n",
-       "      <th>2</th>\n",
-       "      <th>3</th>\n",
-       "      <th>4</th>\n",
-       "      <th>5</th>\n",
-       "      <th>6</th>\n",
-       "      <th>7</th>\n",
-       "      <th>8</th>\n",
-       "      <th>9</th>\n",
-       "      <th>...</th>\n",
-       "      <th>166</th>\n",
-       "      <th>167</th>\n",
-       "      <th>168</th>\n",
-       "      <th>169</th>\n",
-       "      <th>170</th>\n",
-       "      <th>171</th>\n",
-       "      <th>172</th>\n",
-       "      <th>173</th>\n",
-       "      <th>174</th>\n",
-       "      <th>175</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.000000</td>\n",
-       "      <td>138.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>-0.007246</td>\n",
-       "      <td>-0.007246</td>\n",
-       "      <td>0.014493</td>\n",
-       "      <td>-0.014493</td>\n",
-       "      <td>0.014493</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.007246</td>\n",
-       "      <td>0.007246</td>\n",
-       "      <td>-0.021739</td>\n",
-       "      <td>-0.239130</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.028986</td>\n",
-       "      <td>0.014493</td>\n",
-       "      <td>-0.007246</td>\n",
-       "      <td>-0.007246</td>\n",
-       "      <td>0.007246</td>\n",
-       "      <td>-0.014493</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.007246</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>0.330811</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.170251</td>\n",
-       "      <td>0.170251</td>\n",
-       "      <td>0.119946</td>\n",
-       "      <td>0.209274</td>\n",
-       "      <td>0.190902</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.351584</td>\n",
-       "      <td>0.850542</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.417536</td>\n",
-       "      <td>0.119946</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.119946</td>\n",
-       "      <td>0.120824</td>\n",
-       "      <td>0.085126</td>\n",
-       "      <td>0.120824</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>-2.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>-2.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-2.000000</td>\n",
-       "      <td>-4.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>-2.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>8 rows × 176 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "              0           1           2           3           4           5    \\\n",
-       "count  138.000000  138.000000  138.000000  138.000000  138.000000  138.000000   \n",
-       "mean    -0.007246   -0.007246    0.014493   -0.014493    0.014493    0.000000   \n",
-       "std      0.330811    0.085126    0.170251    0.170251    0.119946    0.209274   \n",
-       "min     -2.000000   -1.000000   -1.000000   -2.000000    0.000000   -1.000000   \n",
-       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "max      1.000000    0.000000    1.000000    0.000000    1.000000    1.000000   \n",
-       "\n",
-       "              6           7           8           9    ...         166  \\\n",
-       "count  138.000000  138.000000  138.000000  138.000000  ...  138.000000   \n",
-       "mean     0.007246    0.007246   -0.021739   -0.239130  ...    0.028986   \n",
-       "std      0.190902    0.085126    0.351584    0.850542  ...    0.417536   \n",
-       "min     -1.000000    0.000000   -2.000000   -4.000000  ...   -2.000000   \n",
-       "25%      0.000000    0.000000    0.000000    0.000000  ...    0.000000   \n",
-       "50%      0.000000    0.000000    0.000000    0.000000  ...    0.000000   \n",
-       "75%      0.000000    0.000000    0.000000    0.000000  ...    0.000000   \n",
-       "max      1.000000    1.000000    1.000000    1.000000  ...    1.000000   \n",
-       "\n",
-       "              167         168         169         170         171         172  \\\n",
-       "count  138.000000  138.000000  138.000000  138.000000  138.000000  138.000000   \n",
-       "mean     0.014493   -0.007246   -0.007246    0.007246   -0.014493    0.000000   \n",
-       "std      0.119946    0.085126    0.085126    0.085126    0.119946    0.120824   \n",
-       "min      0.000000   -1.000000   -1.000000    0.000000   -1.000000   -1.000000   \n",
-       "25%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "50%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "75%      0.000000    0.000000    0.000000    0.000000    0.000000    0.000000   \n",
-       "max      1.000000    0.000000    0.000000    1.000000    0.000000    1.000000   \n",
-       "\n",
-       "              173         174    175  \n",
-       "count  138.000000  138.000000  138.0  \n",
-       "mean     0.007246    0.000000    0.0  \n",
-       "std      0.085126    0.120824    0.0  \n",
-       "min      0.000000   -1.000000    0.0  \n",
-       "25%      0.000000    0.000000    0.0  \n",
-       "50%      0.000000    0.000000    0.0  \n",
-       "75%      0.000000    0.000000    0.0  \n",
-       "max      1.000000    1.000000    0.0  \n",
-       "\n",
-       "[8 rows x 176 columns]"
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };            </script>        </div>"
       ]
      },
-     "execution_count": 706,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "pd.DataFrame(adata.layers['nona'] - adata.layers['abaco']).describe()"
+    "# flatten \n",
+    "nona = adata.layers['nona'].flatten()\n",
+    "abaco = adata.layers['abaco'].flatten()\n",
+    "# calculate means and diffs\n",
+    "means = (nona + abaco) / 2\n",
+    "diffs = nona - abaco\n",
+    "print(means.shape, diffs.shape)\n",
+    "# mean and limits of agreement\n",
+    "mean_diff = np.mean(diffs)\n",
+    "std_diff = np.std(diffs)\n",
+    "loa_upper = mean_diff + 1.96 * std_diff\n",
+    "loa_lower = mean_diff - 1.96 * std_diff\n",
+    "\n",
+    "# creating plot\n",
+    "fig = go.Figure()\n",
+    "fig.add_trace(\n",
+    "    go.Scatter(\n",
+    "        x=means, y=diffs, \n",
+    "        mode='markers', \n",
+    "        marker=dict(color='blue', opacity=0.1)\n",
+    "    )\n",
+    ")\n",
+    "fig.add_hline(y=mean_diff,line_color=\"black\", annotation_text=\"Mean Diff\")\n",
+    "fig.add_hline(y=loa_upper, line_dash=\"dot\", line_color=\"black\")\n",
+    "fig.add_hline(y=loa_lower, line_dash=\"dot\", line_color=\"black\")\n",
+    "# titles\n",
+    "fig.update_layout(\n",
+    "    template=\"plotly_white\",\n",
+    "    title=\"Bland-Altman Plot: Original vs. ABaCo Corrected\",\n",
+    "    xaxis_title=\"Mean of Original and ABaCo Corrected\",\n",
+    "    yaxis_title=\"Difference (original - abaco)\",\n",
+    ")\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f39389fb",
+   "metadata": {},
+   "source": [
+    "No clear tendency for abaco correction to be lower or higher than original counts."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 708,
+   "execution_count": 329,
    "id": "a23a2c21",
    "metadata": {},
    "outputs": [
@@ -8278,9 +7345,9 @@
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@@ -8324,47 +7391,7 @@
    "id": "1e761983",
    "metadata": {},
    "source": [
-    "In the PCoA we see that there is more overlap of the batches based on the blue and red points being more mixed. \n",
-    "\n",
-    "We can also take a look at the alpha diversity metrics:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 736,
-   "id": "a7f66563",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3042419068.py:2: FutureWarning:\n",
-      "\n",
-      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
-      "\n",
-      "/var/folders/3d/vpv9_sk51c584kypm0w04hmh0000gp/T/ipykernel_49665/3042419068.py:3: FutureWarning:\n",
-      "\n",
-      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "TtestResult(statistic=np.float64(1.2158839045417509), pvalue=np.float64(0.226135424601057), df=np.float64(136.0))"
-      ]
-     },
-     "execution_count": 736,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "stats.ttest_ind(\n",
-    "    adata.obs.groupby('bio').get_group('Group1')['abaco_pielou'], \n",
-    "    adata.obs.groupby('bio').get_group('Group2')['abaco_pielou']\n",
-    "    )"
+    "In the PCoA we see that there is more overlap of the batches based on the colours mixing. "
    ]
   },
   {
@@ -8372,15 +7399,13 @@
    "id": "b433f7df",
    "metadata": {},
    "source": [
-    "### Conclusion\n",
+    "## Conclusion\n",
     "\n",
     "The goal was to: \n",
     "\n",
     "&#x2705; correct the batch effect (reduce clustering of points by colour in the PCoA and pairplot coloured by batches)\n",
     "\n",
-    "&#x2705; maintain biological variance (maintain pattern of shapes in PCoA and maintain pairplot coloured by wwtp location)\n",
-    "\n",
-    "A brief visual inspection of the PCoA and alpha diversity of the reconstructed data suggests that ABaCo reduced the batch effect associated with analyzing the samples on different dates, while still retaining any variance due to the condition of wwtp location.\n",
+    "A brief visual inspection of the PCoA suggests that ABaCo reduced the batch effect associated with analyzing the samples from different instruments, while still maintaining the original biological variance.\n",
     "\n",
     "\n",
     "---"

From 322918512cb4bc51b4bb2868351878aaa0ce9eff Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 18:47:15 +0100
Subject: [PATCH 8/9] :memo:Docs: adding tutorials

---
 docs/index.md                                 |   1 +
 docs/tutorial/demo-mgnify-mgys-1135.py        |   2 +-
 docs/tutorial/demo-mgnify-tomatoes.py         | 445 ++++++++++++++++++
 docs/tutorial/tutorial-anaerobic-digestion.py |   2 +-
 4 files changed, 448 insertions(+), 2 deletions(-)
 create mode 100644 docs/tutorial/demo-mgnify-tomatoes.py

diff --git a/docs/index.md b/docs/index.md
index bd87695..7bf5397 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -13,6 +13,7 @@
 
 tutorial/tutorial-anaerobic-digestion
 tutorial/demo-mgnify-mgys-1135
+tutorial/demo-mgnify-tomatoes
 ```
 
 ```{toctree}
diff --git a/docs/tutorial/demo-mgnify-mgys-1135.py b/docs/tutorial/demo-mgnify-mgys-1135.py
index f65909c..ac7a0c6 100644
--- a/docs/tutorial/demo-mgnify-mgys-1135.py
+++ b/docs/tutorial/demo-mgnify-mgys-1135.py
@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.17.2
+#       jupytext_version: 1.18.1
 #   kernelspec:
 #     display_name: .venv
 #     language: python
diff --git a/docs/tutorial/demo-mgnify-tomatoes.py b/docs/tutorial/demo-mgnify-tomatoes.py
new file mode 100644
index 0000000..7186fb6
--- /dev/null
+++ b/docs/tutorial/demo-mgnify-tomatoes.py
@@ -0,0 +1,445 @@
+# ---
+# jupyter:
+#   jupytext:
+#     text_representation:
+#       extension: .py
+#       format_name: percent
+#       format_version: '1.3'
+#       jupytext_version: 1.18.1
+#   kernelspec:
+#     display_name: .venv
+#     language: python
+#     name: python3
+# ---
+
+# %% [markdown]
+# # `ABaCo` demo: No biological labels w/ Mgnify tomatoes
+
+# %% [markdown]
+# In this tutorial we demonstrate how ABaCo can be used: 
+# - without known biological group labels (e.g., only correct batch effect)
+# - and for integrating samples from multiple studies.
+#
+# Specifically, we integrate tomato rhizosphere metagenomics analyses available on MGniFy. 
+# - MGYS00006231, Illumina HiSeq 4000
+# - MGYS00006204, Illumina HiSeq 2500
+# - MGYS00006205, Illumina HiSeq 2500
+#
+# **Additionally** we provide an intro to [working with anndata](https://anndata.readthedocs.io/en/stable/tutorials/notebooks/getting-started.html)  
+#
+# **Note** in this tutorial we include a dummy bio column for demo purposes, but it is not necessary to have a bio column to use abaco. 
+#
+# -----
+# **Goal:**
+#
+# With ABaCo the aim is to remove the technical variation between sequencing platforms. 
+#
+# -----
+#
+# To start we retrieve the data from MGniFy. 
+
+# %% [markdown]
+# ## Downloading the data
+
+# %%
+import requests 
+from io import StringIO
+import pandas as pd
+import numpy as np
+
+# urls manually retrieved from mgnify website
+datasets = {
+    "MGYS00006205": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006205/pipelines/5.0/file/ERP140107_taxonomy_abundances_SSU_v5.0.tsv",
+    "MGYS00006231": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006231/pipelines/5.0/file/ERP139927_taxonomy_abundances_SSU_v5.0.tsv",
+    "MGYS00006204": "https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00006204/pipelines/5.0/file/ERP140102_taxonomy_abundances_SSU_v5.0.tsv",
+}
+# init for dfs
+dfs = {}
+for key, url in datasets.items():
+    # download
+    response = requests.get(url)
+    # treat as file
+    file_like = StringIO(response.content.decode('utf-8'))
+    # read into pd df
+    dfs[key] = pd.read_csv(file_like, sep='\t')
+    # rename sampleid col to taxa
+    dfs[key] = dfs[key].rename(columns={"#SampleID": "taxa"})
+    # set index to taxa
+    dfs[key] = dfs[key].set_index('taxa')
+    # drop rows with all zeros
+    dfs[key] = dfs[key][dfs[key].sum(axis=1)>0]
+    # sanity check
+    print(dfs[key].shape)
+    display(dfs[key].sample(5))
+
+# %% [markdown]
+# Based on the sampled outputs printed above, w can see that the data: 
+# - has taxa as rows
+# - the samples as columns 
+# - and the values are the number of taxanomic assignments for the given taxa x sample
+#
+# To join them we will use a helper function `abaco.utils.df_joiner()`. 
+
+# %%
+from abaco.utils import df_joiner
+
+joined = df_joiner(
+    df_dict=dfs, 
+    on="taxa",
+    how="outer",
+)
+
+joined.info()
+
+# %% [markdown]
+# ## A brief intro to `anndata`
+#
+# ![img](https://raw.githubusercontent.com/scverse/anndata/main/docs/_static/img/anndata_schema.svg)
+#
+# For this example we will use anndata to store multiple layers of the data (e.g., raw counts, normalized, etc.) and annotate the samples and taxa with metadata. Below we prepare the annotations (i.e., obs, var).  
+
+# %%
+import anndata as ad
+import scanpy as sc
+
+# preparing obs metadata
+dfs_T = {}
+# for each study
+for key in dfs:
+    # transpose
+    dfs_T[key] = dfs[key].T
+    # add study source column to be batch effect
+    dfs_T[key]['source'] = key
+    # dummy bio column, rando group assign, for checking and demo 
+    dfs_T[key]['bio'] = np.random.choice(["Group1", "Group2"], size = len(dfs_T[key]))
+    # drop allother cols
+    dfs_T[key] = dfs_T[key][['source', 'bio']]
+# now concat all study metadata 
+obs = pd.concat(dfs_T.values())
+print(obs.shape)
+display(obs.sample(5))
+
+# preparing var metadata (taxa levels)
+# get taxa index as df and split on ';'
+var = joined.reset_index()[['taxa']]
+var = var['taxa'].str.split(';', expand=True)
+# rename cols 
+var.columns = [
+    "superkingdom", "kingdom","phylum", "class", 
+    "order", "family", "genus", "species"
+]
+print(var.shape)
+display(var.sample(5))
+
+# %% [markdown]
+# We can initiate the AnnData objct with the values (taxanomic assignment counts) and the metadata we prepped above. 
+
+# %%
+# init anndata object
+full = ad.AnnData(
+    X=joined.T.values,
+    obs=obs,
+    var=var,    
+)
+# check it out
+full
+
+# %% [markdown]
+# With anndata we can also store additional layers seamlessly with the same annoations. Below we will create a layer with the NaNs filled with 0s
+
+# %%
+# layer with no na
+full.layers['nona'] = np.nan_to_num(full.X, nan=0)
+print(full)
+
+# checking it out, also demoing to_df method
+print("original:")
+display(full.to_df().head(5))
+print("no na:")
+display(full.to_df(layer='nona').head(5))
+
+# %% [markdown]
+# we can also add normalized and clr layers. For more details on the reasoning of these layers visit our other tutorials.
+
+# %%
+from skbio.stats.composition import clr 
+
+full.layers['norm'] = full.layers['nona']/full.layers['nona'].sum(axis=1).reshape(-1,1)
+
+# CLR transform normalized data, replacing zeros with smallll val to avoid log(0)
+full.layers['clr'] = clr(np.where(full.layers['norm'] > 0, full.layers['norm'], 1e-10))
+
+print(full)
+
+# %% [markdown]
+# With anndata we can also filter the data using the annotations/metadata. Below we will keep the variables (taxa) with genus assignment. Additionally we filter out some taxa if they are missing in more than 30% of the samples. 
+
+# %%
+# must have genus level
+adata = full[:, ~full.var['genus'].isna()]
+print(adata)
+
+# filtering if taxa is missing (NaN) in more than 30% of samples
+adata = adata[:, np.isnan(adata.X).sum(axis=0)/adata.X.shape[0] <= 0.3]
+print(adata)
+
+# %% [markdown]
+# We are down to 176 taxa. 
+#
+# However, it can be trickier to aggregate with anndata -- but we can use the [scanpy toolkit](https://scanpy.readthedocs.io/en/stable/index.html) to help.  
+#
+# Specifically we will use [scanpy.get.aggregate()](https://scanpy.readthedocs.io/en/stable/generated/scanpy.get.aggregate.html) to help us check that the dummy biological groups we created are not different. 
+
+# %%
+# agg by fake bio group 
+agg_mean = sc.get.aggregate(
+    # the anndata object
+    adata=adata,
+    # what layer to use
+    layer='clr',
+    # group by col
+    by="bio",
+    # axis that the group lives
+    axis="obs",
+    # how to agg
+    func='mean',
+)
+# check out the returned AnnData objct
+print(agg_mean)
+# we can see taht the default layer name if not provided is the func name 
+display(agg_mean.to_df('mean').head(5))
+
+# %% [markdown]
+# Now lets quickly check that group 1 and 2 are not different visually and quick stats.
+
+# %%
+import plotly.graph_objects as go
+from scipy import stats
+
+# transpose for easier plotting
+bio_sum = agg_mean.to_df('mean').T
+
+# init fig
+fig = go.Figure()
+# add traces
+fig.add_trace(go.Histogram(x=bio_sum['Group1'], name='Group1'))
+fig.add_trace(go.Histogram(x=bio_sum['Group2'], name='Group2'))
+
+# formatting
+fig.update_layout(barmode='overlay')
+fig.update_traces(opacity=0.75)
+fig.show()
+
+# check no diff in stats 
+stats.wilcoxon(bio_sum['Group1'], bio_sum['Group2'])
+
+# %% [markdown]
+# ## Prepare data for ABaCo
+#
+# Great. Now lets proceed with adata where we can easily extract a df to meet the data format required for abaco.
+
+# %%
+batch_col = 'source'
+bio_col = 'bio'
+id_col = 'index'
+
+# the raw counts as df
+df_taxa = adata.to_df("nona")
+
+# appending on the categorical data of interest
+df_all = pd.concat([df_taxa, adata.obs[[batch_col, bio_col]]], axis=1).reset_index()
+
+df_all['bio'] = df_all['bio'].astype('category')
+df_all['source'] = df_all['source'].astype('category')
+
+df_all.info()
+
+# %% [markdown]
+# **`pd.DataFrame` Requirements for ABaCo:**
+#
+# The dataset contains the following making it compatible with the ABaCo framework:
+#
+# | id_col | batch_col  | bio_col  | count1 | count2 | ... |
+# |--------|------------|----------|--------|--------|-----|
+# | A      | 24/07/2025 | RA       | #      | #      | ... |
+# | B      | 15/06/2024 | RD       | #      | #      | ... |
+# | C      | 24/07/2025 | RL       | #      | #      | ... |
+#
+# - The data has categorical columns: 
+#     1. unique ids to identify the observations/samples e.g. sample id col
+#     2. ids for the batch/factor groupings to be corrected by abaco. e.g. our phony bio data 
+#     3. biological/experimental factor variation for abaco to retain when correcting batch effect e.g., study id 
+#
+# - And taxa counts to be trained on. 
+#
+# We can use `abaco.plots.plotPCoA()` to visualize any batch and biological effects based on the given categories. 
+
+# %%
+from abaco.plots import plotPCoA
+import plotly.io as pio
+pio.renderers.default = "notebook"
+
+plotPCoA(
+    data=df_all, 
+    sample_label=id_col, 
+    batch_label=batch_col,  
+    experiment_label=bio_col,
+)
+
+# %% [markdown]
+# - Batch effect (colours): 
+#     - Different sequencing platforms which could result in a technical source of variation captured by the clustering of studies 6204 & 6205 (Illumina HiSeq 2500) vs. study 6231 (Illumina HiSeq 4000) along PCo1
+#
+# - Biological effect (shapes): 
+#     - The groups were randomly assigned so we expect no clustering by shape as supported by the pcoa above. This behaviour should not change with abaco reconstruction.
+# -----
+
+# %% [markdown]
+# ## The goal 
+#
+# Here the aim of **ABaCo** is to: 
+# 1) correct the batch effect (e.g., the points should no longer cluster by colour in the PCoA) while
+# 2) maintaining biological variance (or lack thereof).
+#
+# Ideally, after using AbaCo to transform the data, the resulting PCoA coloured by batches will look like a colourful mixture of points.
+#
+# -----
+#
+# ## Using `ABaCo`
+#
+# ### Setting up ABaCo
+#
+# We instantiate the `abaco.metaABaCo()` class and pass the required parameters shown in the cell below. 
+#
+# Usually, setup of the parameters is required, which are explained in brief in the documentation e.g. `help(metaABaCo)`
+#
+#
+
+# %%
+from abaco.ABaCo import metaABaCo
+import torch
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Instaantiate the ABaCo model
+model = metaABaCo(
+    data=df_all, # Pre-processed dataframe
+    n_bios=df_all[bio_col].nunique(), # Number of biological groups in the data
+    bio_label=bio_col, # Column where biological groups are labeled in the dataframe
+    n_batches=df_all[batch_col].nunique(), # Number of batch groups in the data
+    batch_label=batch_col, # Column where batch groups are labeled in the dataframe
+    n_features=df_taxa.shape[1], # Number of features (taxonomic groups)
+    prior="MoG", # Prior distribution 
+    device=device, # Device
+    d_z=16, # default dim of latent space
+    epochs = [3000, 1000, 3000], # num epochs for each training phase
+    disc_net=[256, 128, 64], # stronger discriminator
+    disc_act_fun=torch.nn.LeakyReLU(0.1),
+)
+
+# %% tags=["hide-output"]
+help(metaABaCo)
+
+# %% [markdown]
+# ### Training the ABaCo model
+#
+# To train ABaCo on the prepared dataset, we then use method `abaco.metaABaCo.fit()`. 
+
+# %% tags=["hide-output"]
+# Train the model,
+model.fit(
+  seed=42,
+  w_elbo_nll=10, # more emphasis on reconstruction
+  w_bio_penalty=0.0, # disable bio supervision
+  w_cluster_penalty=0.0, # light regularization or can be 0
+  w_disc=1.0, # default, discriminator training strength
+)
+
+
+# %% [markdown]
+# `abaco.metaABaCo` provides a method that visualizes the latent vectors via PCA for dimensionality reduction: `.plot_pca_posterior()`
+
+# %%
+model.plot_pca_posterior()
+
+# %% [markdown]
+# ### Reconstructing the dataset with ABaCo
+#
+# To reconstruct the dataset we use method `abaco.metaABaCo.correct()` and save it as a new layer `abaco` in the annotated dataset. 
+
+# %%
+# Reconstruct the dataset using the trained ABaCo model
+corrected_dataset = model.correct(seed=42)
+# save back to adata
+adata.layers['abaco'] = corrected_dataset.set_index(id_col).drop(columns=[batch_col, bio_col]).values
+adata.write_h5ad("data/mgnify_tomato.h5ad")
+
+# %% [markdown]
+# ## Viewing the ABaCo reconstructed dataset
+#
+# Here we again take a look at the PCoA but first lets check out the mean differences between the original and batch corrected counts.
+
+# %%
+# flatten 
+nona = adata.layers['nona'].flatten()
+abaco = adata.layers['abaco'].flatten()
+# calculate means and diffs
+means = (nona + abaco) / 2
+diffs = nona - abaco
+print(means.shape, diffs.shape)
+# mean and limits of agreement
+mean_diff = np.mean(diffs)
+std_diff = np.std(diffs)
+loa_upper = mean_diff + 1.96 * std_diff
+loa_lower = mean_diff - 1.96 * std_diff
+
+# creating plot
+fig = go.Figure()
+fig.add_trace(
+    go.Scatter(
+        x=means, y=diffs, 
+        mode='markers', 
+        marker=dict(color='blue', opacity=0.1)
+    )
+)
+fig.add_hline(y=mean_diff,line_color="black", annotation_text="Mean Diff")
+fig.add_hline(y=loa_upper, line_dash="dot", line_color="black")
+fig.add_hline(y=loa_lower, line_dash="dot", line_color="black")
+# titles
+fig.update_layout(
+    template="plotly_white",
+    title="Bland-Altman Plot: Original vs. ABaCo Corrected",
+    xaxis_title="Mean of Original and ABaCo Corrected",
+    yaxis_title="Difference (original - abaco)",
+)
+fig.show()
+
+# %% [markdown]
+# No clear tendency for abaco correction to be lower or higher than original counts.
+
+# %%
+# Plot the PCoA of the reconstructed dataset
+plotPCoA(
+    data = corrected_dataset, 
+    sample_label=id_col, 
+    batch_label=batch_col, 
+    experiment_label=bio_col
+)
+
+# %% [markdown]
+# In the PCoA we see that there is more overlap of the batches based on the colours mixing. 
+
+# %% [markdown]
+# ## Conclusion
+#
+# The goal was to: 
+#
+# &#x2705; correct the batch effect (reduce clustering of points by colour in the PCoA and pairplot coloured by batches)
+#
+# A brief visual inspection of the PCoA suggests that ABaCo reduced the batch effect associated with analyzing the samples from different instruments, while still maintaining the original biological variance.
+#
+#
+# ---
+
+# %% [markdown]
+#
diff --git a/docs/tutorial/tutorial-anaerobic-digestion.py b/docs/tutorial/tutorial-anaerobic-digestion.py
index e9b2130..270407b 100644
--- a/docs/tutorial/tutorial-anaerobic-digestion.py
+++ b/docs/tutorial/tutorial-anaerobic-digestion.py
@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.17.2
+#       jupytext_version: 1.18.1
 #   kernelspec:
 #     display_name: .venv
 #     language: python

From 33cd79bf5d49289549f186c8ab40ffdd217eb9a1 Mon Sep 17 00:00:00 2001
From: "Angel L. P" <59593766+angelphanth@users.noreply.github.com>
Date: Mon, 22 Dec 2025 18:59:27 +0100
Subject: [PATCH 9/9] :art: lint and style

---
 src/abaco/utils.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/src/abaco/utils.py b/src/abaco/utils.py
index 9f74429..b5c2b54 100644
--- a/src/abaco/utils.py
+++ b/src/abaco/utils.py
@@ -5,7 +5,7 @@
 import sys
 from datetime import datetime
 from urllib.parse import urlparse, urlunsplit
-import pandas as pd 
+import pandas as pd
 
 # import yaml
 
@@ -464,7 +464,6 @@ def df_joiner(
     on: str,
     how: str = "outer",
 ) -> pd.DataFrame:
-    
     """
     Join multiple dataframes on a common column.
 
@@ -496,8 +495,7 @@ def df_joiner(
     if how not in ["left", "right", "outer", "inner"]:
         raise ValueError(f"how must be one of 'left', 'right', 'outer', 'inner': {how}")
 
-
-    ## MAIN FUNCTION 
+    ## MAIN FUNCTION
     # dfs into a list
     df_list = list(df_dict.values())
     # init the merged df with the first one
@@ -505,4 +503,4 @@ def df_joiner(
     # for all others, merge iteratively
     for df in df_list[1:]:
         df_merged = pd.merge(df_merged, df, on=on, how=how)
-    return df_merged
\ No newline at end of file
+    return df_merged