diff --git a/.gitmodules b/.gitmodules index 815b4321..722ef3de 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "notebooks/utils"] path = notebooks/utils - url = git@code.ama-inc.com:teams3/data_cube_utilities.git + url = https://github.com/ceos-seo/data_cube_utilities.git diff --git a/build/reqs/full_requirements.txt b/build/reqs/full_requirements.txt index 5b57f760..13a98236 100644 --- a/build/reqs/full_requirements.txt +++ b/build/reqs/full_requirements.txt @@ -154,7 +154,7 @@ pyasn1-modules==0.2.8 pycparser==2.20 pyct==0.4.8 pydantic==1.8.2 -Pygments==2.6.1 +Pygments==2.7.4 pyparsing==2.4.7 pyproj @ file:///wheels/pyproj-2.6.1.post1-cp36-cp36m-linux_x86_64.whl pyrsistent==0.16.0 diff --git a/build/reqs/requirements.txt b/build/reqs/requirements.txt index 68b449b1..954b20fd 100644 --- a/build/reqs/requirements.txt +++ b/build/reqs/requirements.txt @@ -126,7 +126,7 @@ pyasn1==0.4.8 pyasn1-modules==0.2.8 pycparser==2.20 pyct==0.4.6 -Pygments==2.7.1 +Pygments==2.7.4 pyparsing==2.4.7 pyproj @ file:///wheels/pyproj-2.6.1.post1-cp36-cp36m-linux_x86_64.whl pyrsistent==0.17.3 diff --git a/notebooks/animation/3D/GA_Water_3D_Reservoir/ga_utils.py b/notebooks/animation/3D/GA_Water_3D_Reservoir/ga_utils.py index 1aa9170d..97c0f5b1 100644 --- a/notebooks/animation/3D/GA_Water_3D_Reservoir/ga_utils.py +++ b/notebooks/animation/3D/GA_Water_3D_Reservoir/ga_utils.py @@ -1,7 +1,7 @@ import pandas as pd import numpy as np import xarray as xr -import gdal +from osgeo import gdal import affine import fiona import collections diff --git a/notebooks/experimental/voxel_visualizer/Voxel_Visualizer_Test.ipynb b/notebooks/experimental/voxel_visualizer/Voxel_Visualizer_Test.ipynb index 8afc2c1a..b68ab958 100644 --- a/notebooks/experimental/voxel_visualizer/Voxel_Visualizer_Test.ipynb +++ b/notebooks/experimental/voxel_visualizer/Voxel_Visualizer_Test.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -33,28 +33,164 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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namedescriptionlatinstrumentregion_codelonproduct_familyplatformformatcreation_timetimelabeldataset_maturitycrsresolutiontile_sizespatial_dimensions
id
2ls8_l2_c1_t1_googleLandsat 8 Collection 1 Level 2 Surface Reflect...NoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneEPSG:4326(-0.00027777777778, 0.00027777777778)None(latitude, longitude)
1ls8_l2_c1_t2_googleLandsat 8 Collection 1 Level 2 Surface Reflect...NoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneEPSG:4326(-0.00027777777778, 0.00027777777778)None(latitude, longitude)
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"outputs": [], "source": [ "ds = dc.load(product='ls8_l2_c1_t1_google',\n", + " # Lake Mead\n", + "# lat = (36.384826, 36.445486),\n", + "# lon = (-114.400928, -114.326445),\n", + "# time= ('2020-06-01', '2021-06-30'),\n", " # Elizabeth River, VA (sml tst)\n", - "# lat=(36.89, 36.895),\n", - "# lon=(-76.40,-76.395),\n", - "# time=('2014-01-01', '2014-01-31'),\n", - " # Elizabeth River, VA\n", - " lat=(36.894872, 36.969353),\n", - " lon=(-76.394949,-76.260025),\n", + " lat=(36.89, 36.895),\n", + " lon=(-76.40,-76.395),\n", " time=('2014-01-01', '2014-06-30'),\n", + " # Elizabeth River, VA\n", + "# lat=(36.894872, 36.969353),\n", + "# lon=(-76.394949,-76.260025),\n", + "# time=('2014-01-01', '2014-06-30'),\n", " # Prospect Lake, CO\n", "# lat = (38.822297, 38.827771),\n", "# lon = (-104.804378, -104.793997),\n", @@ -68,7 +204,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -80,7 +216,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -90,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -108,20 +244,78 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "# clean_da.mean('time').plot()" + "clean_da.mean('time').plot()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 101, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + "
\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import importlib\n", "from utils.data_cube_utilities.voxel_visualizer import voxel_visualizer\n", @@ -130,14 +324,21 @@ "\n", "voxel_visualize(clean_da, \n", " # Voxel distances\n", - " x_scale=1, y_scale=1, z_scale=1, distance_scale=1, \n", + "# x_scale=1, y_scale=1, z_scale=1, distance_scale=1, \n", " # Voxel size\n", "# voxel_size=4,\n", "# voxel_opacity=0.75,\n", "# show_stats=True,\n", "# show_controls=False\n", - " )" + ")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/notebooks/utils b/notebooks/utils index e254251c..c2a8dd8c 160000 --- a/notebooks/utils +++ b/notebooks/utils @@ -1 +1 @@ -Subproject commit e254251c3aea06b65c4722600fb13d73712778bd +Subproject commit c2a8dd8ced487f3026c185e6213039c573554dab