diff --git a/.github/workflows/docs-deploy.yml b/.github/workflows/docs-deploy.yml
index 7d98e6d..5da08aa 100644
--- a/.github/workflows/docs-deploy.yml
+++ b/.github/workflows/docs-deploy.yml
@@ -6,7 +6,6 @@ on:
       - main
     paths:
       - "docs/**"
-      - "mkdocs.yml"
       - "pyproject.toml"
       - "sst.config.ts"
       - "package.json"
@@ -66,7 +65,7 @@ jobs:
         run: |
           set -euo pipefail
           python -m pip install --upgrade pip
-          python -m pip install mkdocs mkdocs-material mkdocs-jupyter
+          python -m pip install sphinx pydata-sphinx-theme myst-parser myst-nb sphinx-copybutton sphinx-design linkify-it-py
 
       - name: Install deploy dependencies
         run: |
diff --git a/.github/workflows/docs-doctest.yml b/.github/workflows/docs-doctest.yml
index cb5ec0c..c53b9c4 100644
--- a/.github/workflows/docs-doctest.yml
+++ b/.github/workflows/docs-doctest.yml
@@ -30,7 +30,7 @@ jobs:
         run: |
           set -euo pipefail
           python -m pip install --upgrade pip
-          python -m pip install mkdocs mkdocs-material mkdocs-jupyter pytest
+          python -m pip install sphinx pydata-sphinx-theme myst-parser myst-nb sphinx-copybutton sphinx-design linkify-it-py pytest
 
       - name: Run docs build doctest
         run: |
diff --git a/.gitignore b/.gitignore
index 7ff9750..efd4560 100644
--- a/.gitignore
+++ b/.gitignore
@@ -28,6 +28,8 @@ MANIFEST
 
 # built docs
 site/
+jupyter_execute/
+.jupyter_cache/
 
 # Installer logs
 pip-log.txt
diff --git a/README.md b/README.md
index 4d864f4..b8eca3c 100644
--- a/README.md
+++ b/README.md
@@ -100,7 +100,7 @@ dipole antennas, horn antennas, and planar microwave circuits.
 ## Building the docs
 
 The documentation site is built with
-[MkDocs Material](https://squidfunk.github.io/mkdocs-material/).
+[PyData Sphinx Theme](https://pydata-sphinx-theme.readthedocs.io/en/stable/index.html).
 A [justfile](https://github.com/casey/just) automates the full pipeline.
 
 ```bash
@@ -118,8 +118,8 @@ just doctest
 
 # Or run each step individually:
 just nbrun      # execute docs example notebooks with papermill
-just nbdocs     # no-op (MkDocs renders .ipynb directly)
-just docs       # build the MkDocs static site
+just nbdocs     # no-op (Sphinx renders .ipynb directly)
+just docs       # build the Sphinx static site (strict mode)
 
 # Serve locally for development
 just serve      # starts a dev server on http://localhost:8080
@@ -136,7 +136,7 @@ Router managed by the private website infrastructure.
 
 ```bash
 npm install
-python -m pip install mkdocs mkdocs-material mkdocs-jupyter
+python -m pip install sphinx pydata-sphinx-theme myst-parser myst-nb sphinx-copybutton sphinx-design linkify-it-py
 ```
 
 2. Set environment variables:
diff --git a/docs/PalaceToolkit.png b/docs/PalaceToolkit.png
index 85f3fc3..facc6a2 100644
Binary files a/docs/PalaceToolkit.png and b/docs/PalaceToolkit.png differ
diff --git a/docs/conf.py b/docs/conf.py
new file mode 100644
index 0000000..b61beed
--- /dev/null
+++ b/docs/conf.py
@@ -0,0 +1,79 @@
+"""Sphinx configuration for PalaceToolkit documentation."""
+
+from __future__ import annotations
+
+project = "PalaceToolkit"
+author = "EpsilonForge"
+
+extensions = [
+    "myst_nb",
+    "sphinx.ext.mathjax",
+    "sphinx_copybutton",
+    "sphinx_design",
+]
+
+source_suffix = {
+    ".md": "myst-nb",
+    ".ipynb": "myst-nb",
+}
+
+root_doc = "index"
+exclude_patterns = [
+    "_build",
+    "Thumbs.db",
+    ".DS_Store",
+    "**/.ipynb_checkpoints",
+]
+
+# MyST and notebook behavior
+myst_enable_extensions = [
+    "colon_fence",
+    "deflist",
+    "dollarmath",
+    "html_admonition",
+    "html_image",
+    "linkify",
+    "replacements",
+    "substitution",
+    "tasklist",
+]
+
+nb_execution_mode = "off"
+nb_render_markdown_format = "myst"
+suppress_warnings = ["myst.header"]
+
+html_theme = "pydata_sphinx_theme"
+html_title = "PalaceToolkit"
+html_logo = "PalaceToolkit.png"
+html_favicon = "PalaceToolkit.png"
+
+html_theme_options = {
+    "show_nav_level": 2,
+    "navigation_with_keys": True,
+    "logo": {
+        "text": "PalaceToolkit",
+    },
+}
+
+html_static_path = [
+    "stylesheets",
+    "javascripts",
+]
+
+html_css_files = ["interactive.css"]
+html_js_files = [
+    "https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.6/require.min.js",
+    "mathjax.js",
+]
+
+mathjax3_config = {
+    "tex": {
+        "inlineMath": [["$", "$"], ["\\(", "\\)"]],
+        "displayMath": [["$$", "$$"], ["\\[", "\\]"]],
+        "processEscapes": True,
+        "processEnvironments": True,
+    },
+    "options": {
+        "ignoreHtmlClass": "tex2jax_ignore|mathjax_ignore",
+    },
+}
diff --git a/docs/examples/differential_microstrip_modes.ipynb b/docs/examples/differential_microstrip_modes.ipynb
index d50659f..56a449a 100644
--- a/docs/examples/differential_microstrip_modes.ipynb
+++ b/docs/examples/differential_microstrip_modes.ipynb
@@ -14,7 +14,7 @@
     "tags": []
    },
    "source": [
-    "# Differential Microstrip Modes (2D Cross-Section)\n",
+    "# Differential Microstrip Modes\n",
     "\n",
     "This notebook builds a boxed differential microstrip cross-section (substrate + air + ground plane + two PEC strips), solves eigenmodes, and plots the first fields."
    ]
@@ -491,4 +491,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}
diff --git a/docs/examples/img/dipole_mesh.htm b/docs/examples/img/dipole_mesh.htm
deleted file mode 100644
index 2780b12..0000000
--- a/docs/examples/img/dipole_mesh.htm
+++ /dev/null
@@ -1,26 +0,0 @@
-<!doctype html>
-<html lang="en">
-  <head>
-    <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1" />
-    <title>VTK.js | Example - OfflineLocalView</title>
-    <style>
-      html, body { margin: 0; padding: 0; height: 100%; }
-      body { font-family: sans-serif; }
-    </style>
-  </head>
-  <body>
-    <div id="vtk-root" style="height:100%; width:100%;"></div>
-    <script>
-      window.global = window.global || {};
-    </script>
-    <script>var OfflineLocalView=function(e){"use strict";const t=document.querySelector("head");t&&[16,32,96,160,196].forEach((e=>{const n=document.createElement("link");n.setAttribute("rel","icon"),n.setAttribute("href",`https://kitware.github.io/vtk-js/icon/favicon-${e}x${e}.png`),n.setAttribute("sizes",`${e}x${e}`),n.setAttribute("type","image/png"),t.appendChild(n)}));var n=1e-6,r="undefined"!=typeof Float32Array?Float32Array:Array,o=Math.PI/180;function a(e){return e*o}function i(){var e=new r(9);return r!=Float32Array&&(e[1]=0,e[2]=0,e[3]=0,e[5]=0,e[6]=0,e[7]=0),e[0]=1,e[4]=1,e[8]=1,e}function s(e,t){return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[4],e[4]=t[5],e[5]=t[6],e[6]=t[8],e[7]=t[9],e[8]=t[10],e}function l(e,t,n,r,o,a,i,s,l,c){return e[0]=t,e[1]=n,e[2]=r,e[3]=o,e[4]=a,e[5]=i,e[6]=s,e[7]=l,e[8]=c,e}function c(e){return e[0]=1,e[1]=0,e[2]=0,e[3]=0,e[4]=1,e[5]=0,e[6]=0,e[7]=0,e[8]=1,e}function u(e,t){if(e===t){var 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M?(M=1/M,e[0]=(s*R-l*O+c*I)*M,e[1]=(o*O-r*R-a*I)*M,e[2]=(m*C-h*A+v*b)*M,e[3]=(p*A-d*C-f*b)*M,e[4]=(l*w-i*R-c*P)*M,e[5]=(n*R-o*w+a*P)*M,e[6]=(h*y-g*C-v*x)*M,e[7]=(u*C-p*y+f*x)*M,e[8]=(i*O-s*w+c*S)*M,e[9]=(r*w-n*O-a*S)*M,e[10]=(g*A-m*y+v*T)*M,e[11]=(d*y-u*A-f*T)*M,e[12]=(s*P-i*I-l*S)*M,e[13]=(n*I-r*P+o*S)*M,e[14]=(m*x-g*b-h*T)*M,e[15]=(u*b-d*x+p*T)*M,e):null}function A(e,t,n){var r=t[0],o=t[1],a=t[2],i=t[3],s=t[4],l=t[5],c=t[6],u=t[7],d=t[8],p=t[9],f=t[10],g=t[11],m=t[12],h=t[13],v=t[14],T=t[15],x=n[0],y=n[1],b=n[2],A=n[3];return e[0]=x*r+y*s+b*d+A*m,e[1]=x*o+y*l+b*p+A*h,e[2]=x*a+y*c+b*f+A*v,e[3]=x*i+y*u+b*g+A*T,x=n[4],y=n[5],b=n[6],A=n[7],e[4]=x*r+y*s+b*d+A*m,e[5]=x*o+y*l+b*p+A*h,e[6]=x*a+y*c+b*f+A*v,e[7]=x*i+y*u+b*g+A*T,x=n[8],y=n[9],b=n[10],A=n[11],e[8]=x*r+y*s+b*d+A*m,e[9]=x*o+y*l+b*p+A*h,e[10]=x*a+y*c+b*f+A*v,e[11]=x*i+y*u+b*g+A*T,x=n[12],y=n[13],b=n[14],A=n[15],e[12]=x*r+y*s+b*d+A*m,e[13]=x*o+y*l+b*p+A*h,e[14]=x*a+y*c+b*f+A*v,e[15]=x*i+y*u+b*g+A*T,e}function C(e,t,n){var r,o,a,i,s,l,c,u,d,p,f,g,m=n[0],h=n[1],v=n[2];return t===e?(e[12]=t[0]*m+t[4]*h+t[8]*v+t[12],e[13]=t[1]*m+t[5]*h+t[9]*v+t[13],e[14]=t[2]*m+t[6]*h+t[10]*v+t[14],e[15]=t[3]*m+t[7]*h+t[11]*v+t[15]):(r=t[0],o=t[1],a=t[2],i=t[3],s=t[4],l=t[5],c=t[6],u=t[7],d=t[8],p=t[9],f=t[10],g=t[11],e[0]=r,e[1]=o,e[2]=a,e[3]=i,e[4]=s,e[5]=l,e[6]=c,e[7]=u,e[8]=d,e[9]=p,e[10]=f,e[11]=g,e[12]=r*m+s*h+d*v+t[12],e[13]=o*m+l*h+p*v+t[13],e[14]=a*m+c*h+f*v+t[14],e[15]=i*m+u*h+g*v+t[15]),e}function S(e,t,n){var r=n[0],o=n[1],a=n[2];return e[0]=t[0]*r,e[1]=t[1]*r,e[2]=t[2]*r,e[3]=t[3]*r,e[4]=t[4]*o,e[5]=t[5]*o,e[6]=t[6]*o,e[7]=t[7]*o,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}function P(e,t,r,o){var a,i,s,l,c,u,d,p,f,g,m,h,v,T,x,y,b,A,C,S,P,w,I,O,R=o[0],M=o[1],D=o[2],E=Math.hypot(R,M,D);return E<n?null:(R*=E=1/E,M*=E,D*=E,a=Math.sin(r),s=1-(i=Math.cos(r)),l=t[0],c=t[1],u=t[2],d=t[3],p=t[4],f=t[5],g=t[6],m=t[7],h=t[8],v=t[9],T=t[10],x=t[11],y=R*R*s+i,b=M*R*s+D*a,A=D*R*s-M*a,C=R*M*s-D*a,S=M*M*s+i,P=D*M*s+R*a,w=R*D*s+M*a,I=M*D*s-R*a,O=D*D*s+i,e[0]=l*y+p*b+h*A,e[1]=c*y+f*b+v*A,e[2]=u*y+g*b+T*A,e[3]=d*y+m*b+x*A,e[4]=l*C+p*S+h*P,e[5]=c*C+f*S+v*P,e[6]=u*C+g*S+T*P,e[7]=d*C+m*S+x*P,e[8]=l*w+p*I+h*O,e[9]=c*w+f*I+v*O,e[10]=u*w+g*I+T*O,e[11]=d*w+m*I+x*O,t!==e&&(e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15]),e)}function w(e,t,n){var r=Math.sin(n),o=Math.cos(n),a=t[4],i=t[5],s=t[6],l=t[7],c=t[8],u=t[9],d=t[10],p=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*o+c*r,e[5]=i*o+u*r,e[6]=s*o+d*r,e[7]=l*o+p*r,e[8]=c*o-a*r,e[9]=u*o-i*r,e[10]=d*o-s*r,e[11]=p*o-l*r,e}function I(e,t,n){var r=Math.sin(n),o=Math.cos(n),a=t[0],i=t[1],s=t[2],l=t[3],c=t[8],u=t[9],d=t[10],p=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*o-c*r,e[1]=i*o-u*r,e[2]=s*o-d*r,e[3]=l*o-p*r,e[8]=a*r+c*o,e[9]=i*r+u*o,e[10]=s*r+d*o,e[11]=l*r+p*o,e}function O(e,t,n){var r=Math.sin(n),o=Math.cos(n),a=t[0],i=t[1],s=t[2],l=t[3],c=t[4],u=t[5],d=t[6],p=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*o+c*r,e[1]=i*o+u*r,e[2]=s*o+d*r,e[3]=l*o+p*r,e[4]=c*o-a*r,e[5]=u*o-i*r,e[6]=d*o-s*r,e[7]=p*o-l*r,e}function R(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}function M(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}function D(e,t,r){var o,a,i,s=r[0],l=r[1],c=r[2],u=Math.hypot(s,l,c);return u<n?null:(s*=u=1/u,l*=u,c*=u,o=Math.sin(t),i=1-(a=Math.cos(t)),e[0]=s*s*i+a,e[1]=l*s*i+c*o,e[2]=c*s*i-l*o,e[3]=0,e[4]=s*l*i-c*o,e[5]=l*l*i+a,e[6]=c*l*i+s*o,e[7]=0,e[8]=s*c*i+l*o,e[9]=l*c*i-s*o,e[10]=c*c*i+a,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e)}function E(e,t,n){var r=t[0],o=t[1],a=t[2],i=t[3],s=r+r,l=o+o,c=a+a,u=r*s,d=r*l,p=r*c,f=o*l,g=o*c,m=a*c,h=i*s,v=i*l,T=i*c;return e[0]=1-(f+m),e[1]=d+T,e[2]=p-v,e[3]=0,e[4]=d-T,e[5]=1-(u+m),e[6]=g+h,e[7]=0,e[8]=p+v,e[9]=g-h,e[10]=1-(u+f),e[11]=0,e[12]=n[0],e[13]=n[1],e[14]=n[2],e[15]=1,e}function V(e,t){var n=t[0],r=t[1],o=t[2],a=t[4],i=t[5],s=t[6],l=t[8],c=t[9],u=t[10];return e[0]=Math.hypot(n,r,o),e[1]=Math.hypot(a,i,s),e[2]=Math.hypot(l,c,u),e}function L(e,t){var n=new r(3);V(n,t);var o=1/n[0],a=1/n[1],i=1/n[2],s=t[0]*o,l=t[1]*a,c=t[2]*i,u=t[4]*o,d=t[5]*a,p=t[6]*i,f=t[8]*o,g=t[9]*a,m=t[10]*i,h=s+d+m,v=0;return h>0?(v=2*Math.sqrt(h+1),e[3]=.25*v,e[0]=(p-g)/v,e[1]=(f-c)/v,e[2]=(l-u)/v):s>d&&s>m?(v=2*Math.sqrt(1+s-d-m),e[3]=(p-g)/v,e[0]=.25*v,e[1]=(l+u)/v,e[2]=(f+c)/v):d>m?(v=2*Math.sqrt(1+d-s-m),e[3]=(f-c)/v,e[0]=(l+u)/v,e[1]=.25*v,e[2]=(p+g)/v):(v=2*Math.sqrt(1+m-s-d),e[3]=(l-u)/v,e[0]=(f+c)/v,e[1]=(p+g)/v,e[2]=.25*v),e}function B(e,t,n,r){var o=t[0],a=t[1],i=t[2],s=t[3],l=o+o,c=a+a,u=i+i,d=o*l,p=o*c,f=o*u,g=a*c,m=a*u,h=i*u,v=s*l,T=s*c,x=s*u,y=r[0],b=r[1],A=r[2];return e[0]=(1-(g+h))*y,e[1]=(p+x)*y,e[2]=(f-T)*y,e[3]=0,e[4]=(p-x)*b,e[5]=(1-(d+h))*b,e[6]=(m+v)*b,e[7]=0,e[8]=(f+T)*A,e[9]=(m-v)*A,e[10]=(1-(d+g))*A,e[11]=0,e[12]=n[0],e[13]=n[1],e[14]=n[2],e[15]=1,e}function F(e,t){var n=t[0],r=t[1],o=t[2],a=t[3],i=n+n,s=r+r,l=o+o,c=n*i,u=r*i,d=r*s,p=o*i,f=o*s,g=o*l,m=a*i,h=a*s,v=a*l;return e[0]=1-d-g,e[1]=u+v,e[2]=p-h,e[3]=0,e[4]=u-v,e[5]=1-c-g,e[6]=f+m,e[7]=0,e[8]=p+h,e[9]=f-m,e[10]=1-c-d,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,e}function N(e,t,n,r,o){var a,i=1/Math.tan(t/2);return e[0]=i/n,e[1]=0,e[2]=0,e[3]=0,e[4]=0,e[5]=i,e[6]=0,e[7]=0,e[8]=0,e[9]=0,e[11]=-1,e[12]=0,e[13]=0,e[15]=0,null!=o&&o!==1/0?(a=1/(r-o),e[10]=(o+r)*a,e[14]=2*o*r*a):(e[10]=-1,e[14]=-2*r),e}var k=N;function G(e,t,n,r,o,a,i){var s=1/(t-n),l=1/(r-o),c=1/(a-i);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*c,e[11]=0,e[12]=(t+n)*s,e[13]=(o+r)*l,e[14]=(i+a)*c,e[15]=1,e}var U=G;function _(e,t,r,o){var a,i,s,l,c,u,d,p,f,g,m=t[0],h=t[1],v=t[2],T=o[0],y=o[1],b=o[2],A=r[0],C=r[1],S=r[2];return Math.abs(m-A)<n&&Math.abs(h-C)<n&&Math.abs(v-S)<n?x(e):(d=m-A,p=h-C,f=v-S,a=y*(f*=g=1/Math.hypot(d,p,f))-b*(p*=g),i=b*(d*=g)-T*f,s=T*p-y*d,(g=Math.hypot(a,i,s))?(a*=g=1/g,i*=g,s*=g):(a=0,i=0,s=0),l=p*s-f*i,c=f*a-d*s,u=d*i-p*a,(g=Math.hypot(l,c,u))?(l*=g=1/g,c*=g,u*=g):(l=0,c=0,u=0),e[0]=a,e[1]=l,e[2]=d,e[3]=0,e[4]=i,e[5]=c,e[6]=p,e[7]=0,e[8]=s,e[9]=u,e[10]=f,e[11]=0,e[12]=-(a*m+i*h+s*v),e[13]=-(l*m+c*h+u*v),e[14]=-(d*m+p*h+f*v),e[15]=1,e)}function K(e,t,n){return 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n=e.getBoundsByReference();return t.center=Hi.isValid(n)?Hi.getCenter(n):null,t.center?.slice()},e.getLength=()=>{const t=e.getBoundsByReference();return Hi.getDiagonalLength(t)}}(e,t)}};const{vtkErrorMacro:Bs,vtkWarningMacro:Fs}=sn;const Ns={arrays:[],copyFieldFlags:[],doCopyAllOn:!0,doCopyAllOff:!1};function ks(e,t,n={}){Object.assign(t,Ns,n),sn.obj(e,t),function(e,t){t.classHierarchy.push("vtkFieldData");const n=e.getState;t.arrays&&(t.arrays=t.arrays.map((e=>({data:it(e.data)})))),e.initialize=()=>{e.initializeFields(),e.copyAllOn(),e.clearFieldFlags()},e.initializeFields=()=>{t.arrays=[],t.copyFieldFlags={},e.modified()},e.copyStructure=n=>{e.initializeFields(),t.copyFieldFlags=n.getCopyFieldFlags().map((e=>e)),t.arrays=n.getArrays().map((e=>({data:e})))},e.getNumberOfArrays=()=>t.arrays.length,e.getNumberOfActiveArrays=()=>t.arrays.length,e.addArray=n=>{const r=n.getName(),{array:o,index:a}=e.getArrayWithIndex(r);return 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u=a>-1?a:r;c<=u*l&&(c=(u+1)*l),t=Is.newInstance({name:s.getName(),dataType:s.getDataType(),numberOfComponents:l,values:sn.newTypedArray(s.getDataType(),c),size:0}),t.interpolateTuple(u,s,r,s,o,i),e.addArray(t),n.getAttributes(s).forEach((n=>{e.setAttribute(t,n)}))}}}))},e.copyFieldOn=e=>{t.copyFieldFlags[e]=!0},e.copyFieldOff=e=>{t.copyFieldFlags[e]=!1},e.copyAllOn=()=>{t.doCopyAllOn&&!t.doCopyAllOff||(t.doCopyAllOn=!0,t.doCopyAllOff=!1,e.modified())},e.copyAllOff=()=>{!t.doCopyAllOn&&t.doCopyAllOff||(t.doCopyAllOn=!1,t.doCopyAllOff=!0,e.modified())},e.clearFieldFlags=()=>{t.copyFieldFlags={}},e.deepCopy=e=>{t.arrays=e.getArrays().map((e=>{const t=e.newClone();return t.deepCopy(e),{data:t}}))},e.copyFlags=e=>e.getCopyFieldFlags().map((e=>e)),e.reset=()=>t.arrays.forEach((e=>e.data.reset())),e.getMTime=()=>t.arrays.reduce(((e,t)=>t.data.getMTime()>e?t.data.getMTime():e),t.mtime),e.getNumberOfComponents=()=>t.arrays.reduce(((e,t)=>e+t.data.getNumberOfComponents()),0),e.getNumberOfTuples=()=>t.arrays.length>0?t.arrays[0].getNumberOfTuples():0,e.getState=e=>{const r=n(e);return r&&(r.arrays=t.arrays.map((t=>({data:t.data.getState(e)})))),r}}(e,t)}var Gs={newInstance:sn.newInstance(ks,"vtkFieldData"),extend:ks};const Us={DEFAULT:0,SINGLE:1,DOUBLE:2};var 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Incorrect number of components.`),-1}return t[`active${a}`]=n,e.modified(),n}return-1===n&&(t[`active${a}`]=n,e.modified()),-1},e.getActiveAttribute=t=>{const n=r(t);return e[`get${n}`]()},e.removeAllArrays=()=>{n.forEach((e=>{t[`active${e}`]=-1})),o.removeAllArrays()},e.removeArrayByIndex=e=>(-1!==e&&n.forEach((n=>{e===t[`active${n}`]?t[`active${n}`]=-1:e<t[`active${n}`]&&(t[`active${n}`]-=1)})),o.removeArrayByIndex(e)),n.forEach((n=>{const r=`active${n}`;e[`get${n}`]=()=>e.getArrayByIndex(t[r]),e[`set${n}`]=t=>e.setAttribute(t,n),e[`setActive${n}`]=t=>e.setActiveAttributeByIndex(e.getArrayWithIndex(t).index,n),e[`copy${n}Off`]=()=>{const e=n.toUpperCase();t.copyAttributeFlags[zs.PASSDATA][Ks[e]]=!1},e[`copy${n}On`]=()=>{const e=n.toUpperCase();t.copyAttributeFlags[zs.PASSDATA][Ks[e]]=!0}})),e.initializeAttributeCopyFlags=()=>{t.copyAttributeFlags=[],Object.keys(zs).filter((e=>"ALLCOPY"!==e)).forEach((e=>{t.copyAttributeFlags[zs[e]]=Object.keys(Ks).filter((e=>"NUM_ATTRIBUTES"!==e)).reduce(((e,t)=>(e[Ks[t]]=!0,e)),[])})),t.copyAttributeFlags[zs.COPYTUPLE][Ks.GLOBALIDS]=!1,t.copyAttributeFlags[zs.INTERPOLATE][Ks.GLOBALIDS]=!1,t.copyAttributeFlags[zs.COPYTUPLE][Ks.PEDIGREEIDS]=!1},e.initialize=sn.chain(e.initialize,e.initializeAttributeCopyFlags),t.dataArrays&&Object.keys(t.dataArrays).length&&Object.keys(t.dataArrays).forEach((n=>{t.dataArrays[n].ref||"vtkDataArray"!==t.dataArrays[n].type||e.addArray(Is.newInstance(t.dataArrays[n]))}));const a=e.shallowCopy;e.shallowCopy=(e,n)=>{a(e,n),t.arrays=e.getArrays().map((e=>{const t=e.newClone();return t.shallowCopy(e,n),{data:t}}))},e.initializeAttributeCopyFlags()}(e,t)}var Xs={newInstance:sn.newInstance(js,"vtkDataSetAttributes"),extend:js,..._s};var qs={FieldDataTypes:{UNIFORM:0,DATA_OBJECT_FIELD:0,COORDINATE:1,POINT_DATA:1,POINT:2,POINT_FIELD_DATA:2,CELL:3,CELL_FIELD_DATA:3,VERTEX:4,VERTEX_FIELD_DATA:4,EDGE:5,EDGE_FIELD_DATA:5,ROW:6,ROW_DATA:6},FieldAssociations:{FIELD_ASSOCIATION_POINTS:0,FIELD_ASSOCIATION_CELLS:1,FIELD_ASSOCIATION_NONE:2,FIELD_ASSOCIATION_POINTS_THEN_CELLS:3,FIELD_ASSOCIATION_VERTICES:4,FIELD_ASSOCIATION_EDGES:5,FIELD_ASSOCIATION_ROWS:6,NUMBER_OF_ASSOCIATIONS:7}};const Ys=["pointData","cellData","fieldData"];const Js={};function Zs(e,t,n={}){Object.assign(t,Js,n),sn.obj(e,t),sn.setGet(e,t,Ys),sn.getArray(e,t,["bounds"],6),function(e,t){t.classHierarchy.push("vtkDataSet"),Ys.forEach((e=>{t[e]?t[e]=it(t[e]):t[e]=Xs.newInstance()})),e.computeBounds=()=>{if(t.modifiedTime&&t.computeTime&&t.modifiedTime>t.computeTime||!t.computeTime){const n=e.getPoints();n?.getNumberOfPoints()?Hi.setBounds(t.bounds,n.getBoundsByReference()):t.bounds=za.createUninitializedBounds(),t.computeTime=sn.getCurrentGlobalMTime()}},e.getLength2=()=>{const t=e.getBoundsByReference();return t&&6===t.length?Hi.getDiagonalLength2(t):0},e.getLength=()=>Math.sqrt(e.getLength2()),e.getCenter=()=>{const t=e.getBoundsByReference();return t&&6===t.length?Hi.getCenter(t):[0,0,0]},e.getCellBounds=t=>{const n=e.getCell(t);return n?n.getBounds():za.createUninitializedBounds()},e.getBounds=sn.chain((()=>e.computeBounds),e.getBounds),e.getBoundsByReference=sn.chain((()=>e.computeBounds),e.getBoundsByReference);const n=e.shallowCopy;e.shallowCopy=(e,r=!1)=>{n(e,r),Ys.forEach((n=>{t[n]=Xs.newInstance(),t[n].shallowCopy(e.getReferenceByName(n))}))};const r=e.getMTime;e.getMTime=()=>Ys.reduce(((e,n)=>Math.max(e,t[n]?.getMTime()??e)),r()),e.initialize=()=>(Ys.forEach((e=>t[e]?.initialize())),e)}(e,t)}var Qs={newInstance:sn.newInstance(Zs,"vtkDataSet"),extend:Zs,...qs};const $s={UNCHANGED:0,SINGLE_POINT:1,X_LINE:2,Y_LINE:3,Z_LINE:4,XY_PLANE:5,YZ_PLANE:6,XZ_PLANE:7,XYZ_GRID:8,EMPTY:9};var el={StructuredType:$s};const{StructuredType:tl}=el;var nl={getDataDescriptionFromExtent:function(e){let t=0;for(let n=0;n<3;++n)e[2*n]<e[2*n+1]&&t++;return e[0]>e[1]||e[2]>e[3]||e[4]>e[5]?tl.EMPTY:3===t?tl.XYZ_GRID:2===t?e[0]===e[1]?tl.YZ_PLANE:e[2]===e[3]?tl.XZ_PLANE:tl.XY_PLANE:1===t?e[0]<e[1]?tl.X_LINE:e[2]<e[3]?tl.Y_LINE:tl.Z_LINE:tl.SINGLE_POINT},...el};const{vtkErrorMacro:rl}=sn;const ol={direction:null,indexToWorld:null,worldToIndex:null,spacing:[1,1,1],origin:[0,0,0],extent:[0,-1,0,-1,0,-1],dataDescription:$s.EMPTY};function al(e,t,n={}){Object.assign(t,ol,n),Qs.extend(e,t,n),t.direction?Array.isArray(t.direction)&&(t.direction=new Float64Array(t.direction.slice(0,9))):t.direction=c(new Float64Array(9)),t.indexToWorld=new Float64Array(16),t.worldToIndex=new Float64Array(16),sn.get(e,t,["indexToWorld","worldToIndex"]),sn.setGetArray(e,t,["origin","spacing"],3),sn.setGetArray(e,t,["direction"],9),sn.getArray(e,t,["extent"],6),function(e,t){t.classHierarchy.push("vtkImageData"),e.setExtent=(...n)=>{if(t.deleted)return rl("instance deleted - 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Current Scalar numberOfComponents: ${r}`),NaN;const o=e.getOffsetIndexFromWorld(t);return Number.isNaN(o)?o:e.getPointData().getScalars().getComponent(o,n)};const n=e.initialize;e.initialize=()=>(e.set({direction:c(t.direction),spacing:[1,1,1],origin:[0,0,0],extent:[0,-1,0,-1,0,-1],dataDescription:$s.EMPTY}),n())}(e,t)}var il={newInstance:sn.newInstance(al,"vtkImageData"),extend:al};const sl={LUMINANCE:1,LUMINANCE_ALPHA:2,RGB:3,RGBA:4};var ll={VectorMode:{MAGNITUDE:0,COMPONENT:1,RGBCOLORS:2},ScalarMappingTarget:sl,Scale:{LINEAR:0,LOG10:1}};var cl={ColorMode:{DEFAULT:0,MAP_SCALARS:1,DIRECT_SCALARS:2},GetArray:{BY_ID:0,BY_NAME:1},ScalarMode:{DEFAULT:0,USE_POINT_DATA:1,USE_CELL_DATA:2,USE_POINT_FIELD_DATA:3,USE_CELL_FIELD_DATA:4,USE_FIELD_DATA:5}};const{ScalarMappingTarget:ul,Scale:dl,VectorMode:pl}=ll,{VtkDataTypes:fl}=Is,{ColorMode:gl}=cl,{vtkErrorMacro:ml}=sn;function hl(e){return e}function vl(e){return Math.floor(255*e+.5)}const Tl={alpha:1,vectorComponent:0,vectorSize:-1,vectorMode:pl.COMPONENT,mappingRange:null,annotationArray:null,annotatedValueMap:null,indexedLookup:!1,scale:dl.LINEAR};function xl(e,t,n={}){Object.assign(t,Tl,n),sn.obj(e,t),t.mappingRange=[0,255],t.annotationArray=[],t.annotatedValueMap=[],sn.setGet(e,t,["vectorSize","vectorComponent","vectorMode","alpha","indexedLookup"]),sn.setArray(e,t,["mappingRange"],2),sn.getArray(e,t,["mappingRange"]),function(e,t){t.classHierarchy.push("vtkScalarsToColors"),e.setVectorModeToMagnitude=()=>e.setVectorMode(pl.MAGNITUDE),e.setVectorModeToComponent=()=>e.setVectorMode(pl.COMPONENT),e.setVectorModeToRGBColors=()=>e.setVectorMode(pl.RGBCOLORS),e.build=()=>{},e.isOpaque=()=>!0,e.setAnnotations=(n,r)=>{if(!(n&&!r||!n&&r))if(n&&r&&n.length!==r.length)ml("Values and annotations do not have the same number of tuples so ignoring");else{if(t.annotationArray=[],r&&n){const e=r.length;for(let o=0;o<e;o++)t.annotationArray.push({value:n[o],annotation:String(r[o])})}e.updateAnnotatedValueMap(),e.modified()}},e.setAnnotation=(n,r)=>{let o=e.checkForAnnotatedValue(n),a=!1;return o>=0?t.annotationArray[o].annotation!==r&&(t.annotationArray[o].annotation=r,a=!0):(t.annotationArray.push({value:n,annotation:r}),o=t.annotationArray.length-1,a=!0),a&&(e.updateAnnotatedValueMap(),e.modified()),o},e.getNumberOfAnnotatedValues=()=>t.annotationArray.length,e.getAnnotatedValue=e=>e<0||e>=t.annotationArray.length?null:t.annotationArray[e].value,e.getAnnotation=e=>void 0===t.annotationArray[e]?null:t.annotationArray[e].annotation,e.getAnnotatedValueIndex=n=>t.annotationArray.length?e.checkForAnnotatedValue(n):-1,e.removeAnnotation=n=>{const r=e.checkForAnnotatedValue(n),o=r>=0;return o&&(t.annotationArray.splice(r,1),e.updateAnnotatedValueMap(),e.modified()),o},e.resetAnnotations=()=>{t.annotationArray=[],t.annotatedValueMap=[],e.modified()},e.getAnnotationColor=(n,r)=>{if(t.indexedLookup){const t=e.getAnnotatedValueIndex(n);e.getIndexedColor(t,r)}else e.getColor(parseFloat(n),r),r[3]=1},e.checkForAnnotatedValue=t=>e.getAnnotatedValueIndexInternal(t),e.getAnnotatedValueIndexInternal=e=>{if(void 0!==t.annotatedValueMap[e]){const n=t.annotationArray.length;return t.annotatedValueMap[e]%n}return-1},e.getIndexedColor=(e,t)=>{t[0]=0,t[1]=0,t[2]=0,t[3]=0},e.updateAnnotatedValueMap=()=>{t.annotatedValueMap=[];const e=t.annotationArray.length;for(let n=0;n<e;n++)t.annotatedValueMap[t.annotationArray[n].value]=n},e.mapScalars=(t,n,r)=>{const o=t.getNumberOfComponents();let a=null;if(n===gl.DEFAULT&&(t.getDataType()===fl.UNSIGNED_CHAR||t.getDataType()===fl.UNSIGNED_CHAR_CLAMPED)||n===gl.DIRECT_SCALARS&&t)a=e.convertToRGBA(t,o,t.getNumberOfTuples());else{const n={type:"vtkDataArray",name:"temp",numberOfComponents:4,dataType:fl.UNSIGNED_CHAR},i=sn.newTypedArray(n.dataType,4*t.getNumberOfTuples());n.values=i,n.size=i.length,a=Is.newInstance(n);let s=r;s<0&&o>1?e.mapVectorsThroughTable(t,a,ul.RGBA,-1,-1):(s<0&&(s=0),s>=o&&(s=o-1),e.mapScalarsThroughTable(t,a,ul.RGBA,s))}return a},e.mapVectorsToMagnitude=(e,t,n)=>{const r=e.getNumberOfTuples(),o=e.getNumberOfComponents(),a=t.getData(),i=e.getData();for(let e=0;e<r;e++){let t=0;for(let r=0;r<n;r++)t+=i[e*o+r]*i[e*o+r];a[e]=Math.sqrt(t)}},e.mapVectorsThroughTable=(t,n,r,o,a)=>{let i=e.getVectorMode(),s=a,l=o;const c=t.getNumberOfComponents();i===pl.COMPONENT?(-1===l&&(l=e.getVectorComponent()),l<0&&(l=0),l>=c&&(l=c-1)):(-1===s&&(s=e.getVectorSize()),s<=0?(l=0,s=c):(l<0&&(l=0),l>=c&&(l=c-1),l+s>c&&(s=c-l)),i!==pl.MAGNITUDE||1!==c&&1!==s||(i=pl.COMPONENT));let u=0;switch(l>0&&(u=l),i){case pl.COMPONENT:e.mapScalarsThroughTable(t,n,r,u);break;case pl.RGBCOLORS:break;case pl.MAGNITUDE:default:{const o=Is.newInstance({numberOfComponents:1,values:new Float32Array(t.getNumberOfTuples())});e.mapVectorsToMagnitude(t,o,s),e.mapScalarsThroughTable(o,n,r,0);break}}},e.luminanceToRGBA=(e,t,n,r)=>{const o=r(n),a=t.getData(),i=e.getData(),s=a.length;let l=0;for(let e=0;e<s;e+=1){const t=r(a[e]);i[4*l]=t,i[4*l+1]=t,i[4*l+2]=t,i[4*l+3]=o,l++}},e.luminanceAlphaToRGBA=(e,t,n,r)=>{const o=t.getData(),a=e.getData(),i=o.length;let s=0;for(let e=0;e<i;e+=2){const t=r(o[e]);a[s]=t,a[s+1]=t,a[s+2]=t,a[s+3]=r(o[e+1])*n,s+=4}},e.rGBToRGBA=(e,t,n,r)=>{const o=vl(n),a=t.getData(),i=e.getData(),s=a.length;let l=0;for(let e=0;e<s;e+=3)i[4*l]=r(a[e]),i[4*l+1]=r(a[e+1]),i[4*l+2]=r(a[e+2]),i[4*l+3]=o,l++},e.rGBAToRGBA=(e,t,n,r)=>{const o=t.getData(),a=e.getData(),i=o.length;let s=0;for(let e=0;e<i;e+=4)a[4*s]=r(o[e]),a[4*s+1]=r(o[e+1]),a[4*s+2]=r(o[e+2]),a[4*s+3]=r(o[e+3])*n,s++},e.convertToRGBA=(n,r,o)=>{let{alpha:a}=t;if(4===r&&a>=1&&n.getDataType()===fl.UNSIGNED_CHAR)return n;const i=Is.newInstance({numberOfComponents:4,empty:!0,size:4*o,dataType:fl.UNSIGNED_CHAR});if(o<=0)return i;a=a>0?a:0,a=a<1?a:1;let s=hl;switch(n.getDataType()!==fl.FLOAT&&n.getDataType()!==fl.DOUBLE||(s=vl),r){case 1:e.luminanceToRGBA(i,n,a,s);break;case 2:e.luminanceAlphaToRGBA(i,n,s);break;case 3:e.rGBToRGBA(i,n,a,s);break;case 4:e.rGBAToRGBA(i,n,a,s);break;default:return ml("Cannot convert colors"),null}return i},e.usingLogScale=()=>!1,e.getNumberOfAvailableColors=()=>16777216,e.setRange=(t,n)=>e.setMappingRange(t,n),e.getRange=()=>e.getMappingRange(),e.areScalarsOpaque=(n,r,o)=>{if(!n)return e.isOpaque();const a=n.getNumberOfComponents();return(r!==gl.DEFAULT||n.getDataType()!==fl.UNSIGNED_CHAR)&&r!==gl.DIRECT_SCALARS||(3===a||1===a?t.alpha>=1:255===n.getRange(a-1)[0])}}(e,t)}var yl={newInstance:sn.newInstance(xl,"vtkScalarsToColors"),extend:xl,...ll};const{vtkErrorMacro:bl}=sn;const Al={numberOfColors:256,hueRange:[0,.66667],saturationRange:[1,1],valueRange:[1,1],alphaRange:[1,1],nanColor:[.5,0,0,1],belowRangeColor:[0,0,0,1],aboveRangeColor:[1,1,1,1],useAboveRangeColor:!1,useBelowRangeColor:!1,alpha:1};function Cl(e,t,n={}){Object.assign(t,Al,n),yl.extend(e,t,n),t.table||(t.table=[]),t.buildTime={},sn.obj(t.buildTime),t.opaqueFlagBuildTime={},sn.obj(t.opaqueFlagBuildTime,{mtime:0}),t.insertTime={},sn.obj(t.insertTime,{mtime:0}),sn.get(e,t,["buildTime"]),sn.setGet(e,t,["numberOfColors","useAboveRangeColor","useBelowRangeColor"]),sn.setArray(e,t,["alphaRange","hueRange","saturationRange","valueRange"],2),sn.setArray(e,t,["nanColor","belowRangeColor","aboveRangeColor"],4),sn.getArray(e,t,["hueRange","saturationRange","valueRange","alphaRange","nanColor","belowRangeColor","aboveRangeColor"]),function(e,t){t.classHierarchy.push("vtkLookupTable"),e.isOpaque=()=>{if(t.opaqueFlagBuildTime.getMTime()<e.getMTime()){let e=!0;t.nanColor[3]<1&&(e=0),t.useBelowRangeColor&&t.belowRangeColor[3]<1&&(e=0),t.useAboveRangeColor&&t.aboveRangeColor[3]<1&&(e=0);for(let n=3;n<t.table.length&&e;n+=4)t.table[n]<255&&(e=!1);t.opaqueFlag=e,t.opaqueFlagBuildTime.modified()}return t.opaqueFlag},e.usingLogScale=()=>!1,e.getNumberOfAvailableColors=()=>t.table.length/4-3,e.linearIndexLookup=(e,t)=>{let n=0;const r=Number(e);return r<t.range[0]?n=t.maxIndex+0+1.5:r>t.range[1]?n=t.maxIndex+1+1.5:(n=(r+t.shift)*t.scale,n=n<t.maxIndex?n:t.maxIndex),Math.floor(n)},e.linearLookup=(t,n,r)=>{let o=0;o=ka(t)?Math.floor(r.maxIndex+1.5+2):e.linearIndexLookup(t,r);const a=4*o;return n.slice(a,a+4)},e.indexedLookupFunction=(n,r,o)=>{let a=e.getAnnotatedValueIndexInternal(n);-1===a&&(a=t.numberOfColors+2);const i=4*a;return[r[i],r[i+1],r[i+2],r[i+3]]},e.lookupShiftAndScale=(e,t)=>{t.shift=-e[0],t.scale=Number.MAX_VALUE,e[1]>e[0]&&(t.scale=(t.maxIndex+1)/(e[1]-e[0]))},e.mapScalarsThroughTable=(n,r,o,a)=>{let i=e.linearLookup;t.indexedLookup&&(i=e.indexedLookupFunction);const s=e.getMappingRange(),l={maxIndex:e.getNumberOfColors()-1,range:s,shift:0,scale:0};e.lookupShiftAndScale(s,l);const c=e.getAlpha(),u=n.getNumberOfTuples(),d=n.getNumberOfComponents(),p=r.getData(),f=n.getData();if(c>=1){if(o===sl.RGBA)for(let e=0;e<u;e++){const n=i(f[e*d+a],t.table,l);p[4*e]=n[0],p[4*e+1]=n[1],p[4*e+2]=n[2],p[4*e+3]=n[3]}}else if(o===sl.RGBA)for(let e=0;e<u;e++){const n=i(f[e*d+a],t.table,l);p[4*e]=n[0],p[4*e+1]=n[1],p[4*e+2]=n[2],p[4*e+3]=Math.floor(n[3]*c+.5)}},e.forceBuild=()=>{let n=0,r=0,o=0,a=0;const i=t.numberOfColors-1;i&&(n=(t.hueRange[1]-t.hueRange[0])/i,r=(t.saturationRange[1]-t.saturationRange[0])/i,o=(t.valueRange[1]-t.valueRange[0])/i,a=(t.alphaRange[1]-t.alphaRange[0])/i),t.table.length=4*i+16;const s=[],l=[];for(let e=0;e<=i;e++)s[0]=t.hueRange[0]+e*n,s[1]=t.saturationRange[0]+e*r,s[2]=t.valueRange[0]+e*o,ya(s,l),l[3]=t.alphaRange[0]+e*a,t.table[4*e]=255*l[0]+.5,t.table[4*e+1]=255*l[1]+.5,t.table[4*e+2]=255*l[2]+.5,t.table[4*e+3]=255*l[3]+.5;e.buildSpecialColors(),t.buildTime.modified()},e.setTable=n=>{if(Array.isArray(n)){const r=n[0].length;t.numberOfColors=n.length;const o=4-r;let a=0;for(let e=0;e<t.numberOfColors;e++)t.table[4*e]=255,t.table[4*e+1]=255,t.table[4*e+2]=255,t.table[4*e+3]=255;for(let e=0;e<n.length;e++){const i=n[e];for(let e=0;e<r;e++)t.table[a++]=i[e];a+=o}return e.buildSpecialColors(),t.insertTime.modified(),e.modified(),!0}if(4!==n.getNumberOfComponents())return bl("Expected 4 components for RGBA colors"),!1;if(n.getDataType()!==ms.UNSIGNED_CHAR)return bl("Expected unsigned char values for RGBA colors"),!1;t.numberOfColors=n.getNumberOfTuples();const r=n.getData();t.table.length=r.length;for(let e=0;e<r.length;e++)t.table[e]=r[e];return e.buildSpecialColors(),t.insertTime.modified(),e.modified(),!0},e.buildSpecialColors=()=>{const{numberOfColors:e}=t,n=t.table;let r=4*(e+0);t.useBelowRangeColor||0===e?(n[r]=255*t.belowRangeColor[0]+.5,n[r+1]=255*t.belowRangeColor[1]+.5,n[r+2]=255*t.belowRangeColor[2]+.5,n[r+3]=255*t.belowRangeColor[3]+.5):(n[r]=n[0],n[r+1]=n[1],n[r+2]=n[2],n[r+3]=n[3]),r=4*(e+1),t.useAboveRangeColor||0===e?(n[r]=255*t.aboveRangeColor[0]+.5,n[r+1]=255*t.aboveRangeColor[1]+.5,n[r+2]=255*t.aboveRangeColor[2]+.5,n[r+3]=255*t.aboveRangeColor[3]+.5):(n[r]=n[4*(e-1)+0],n[r+1]=n[4*(e-1)+1],n[r+2]=n[4*(e-1)+2],n[r+3]=n[4*(e-1)+3]),r=4*(e+2),n[r]=255*t.nanColor[0]+.5,n[r+1]=255*t.nanColor[1]+.5,n[r+2]=255*t.nanColor[2]+.5,n[r+3]=255*t.nanColor[3]+.5},e.build=()=>{(t.table.length<1||e.getMTime()>t.buildTime.getMTime()&&t.insertTime.getMTime()<=t.buildTime.getMTime())&&e.forceBuild()},t.table.length>0&&(e.buildSpecialColors(),t.insertTime.modified())}(e,t)}var Sl={newInstance:sn.newInstance(Cl,"vtkLookupTable"),extend:Cl};const Pl={Off:0,PolygonOffset:1};let wl=Pl.PolygonOffset,Il=Pl.Off;const Ol=["VTK_RESOLVE_OFF","VTK_RESOLVE_POLYGON_OFFSET"];function Rl(e=0){const t=Il===e;return Il=e,t}var Ml={Resolve:Pl,getResolveCoincidentTopologyAsString:function(){return Ol[Il]},getResolveCoincidentTopologyPolygonOffsetFaces:function(){return wl},getResolveCoincidentTopology:function(){return Il},setResolveCoincidentTopology:Rl,setResolveCoincidentTopologyPolygonOffsetFaces:function(e){const t=wl===e;return wl=e,t},setResolveCoincidentTopologyToDefault:function(){return Rl(Pl.Off)},setResolveCoincidentTopologyToOff:function(){return Rl(Pl.Off)},setResolveCoincidentTopologyToPolygonOffset:function(){return Rl(Pl.PolygonOffset)}};function Dl(e,t,n){n.forEach((n=>{e[`get${n.method}`]=()=>t[n.key],e[`set${n.method}`]=sn.objectSetterMap.object(e,t,{name:n.key,params:["factor","offset"]})}))}const El=["Polygon","Line","Point"],Vl={modified:()=>{}};Dl(Vl,{Polygon:{factor:2,offset:0},Line:{factor:1,offset:-1},Point:{factor:0,offset:-2}},El.map((e=>({key:e,method:`ResolveCoincidentTopology${e}OffsetParameters`}))));var Ll={implementCoincidentTopologyMethods:function(e,t){void 0===t.resolveCoincidentTopology&&(t.resolveCoincidentTopology=!1),sn.setGet(e,t,["resolveCoincidentTopology"]),t.topologyOffset={Polygon:{factor:0,offset:0},Line:{factor:0,offset:0},Point:{factor:0,offset:0}},Object.keys(Ml).forEach((t=>{e[t]=Ml[t]})),Object.keys(Vl).filter((e=>"modified"!==e)).forEach((t=>{e[t]=Vl[t]})),Dl(e,t.topologyOffset,El.map((e=>({key:e,method:`RelativeCoincidentTopology${e}OffsetParameters`})))),e.getCoincidentTopologyPolygonOffsetParameters=()=>{const t=Vl.getResolveCoincidentTopologyPolygonOffsetParameters(),n=e.getRelativeCoincidentTopologyPolygonOffsetParameters();return{factor:t.factor+n.factor,offset:t.offset+n.offset}},e.getCoincidentTopologyLineOffsetParameters=()=>{const t=Vl.getResolveCoincidentTopologyLineOffsetParameters(),n=e.getRelativeCoincidentTopologyLineOffsetParameters();return{factor:t.factor+n.factor,offset:t.offset+n.offset}},e.getCoincidentTopologyPointOffsetParameter=()=>{const t=Vl.getResolveCoincidentTopologyPointOffsetParameters(),n=e.getRelativeCoincidentTopologyPointOffsetParameters();return{factor:t.factor+n.factor,offset:t.offset+n.offset}}},staticOffsetAPI:Vl,otherStaticMethods:Ml,CATEGORIES:El,Resolve:Pl};const Bl={MIN_KNOWN_PASS:0,ACTOR_PASS:0,COMPOSITE_INDEX_PASS:1,ID_LOW24:2,ID_HIGH24:3,MAX_KNOWN_PASS:3};var Fl={PassTypes:Bl};const{FieldAssociations:Nl}=Qs,{staticOffsetAPI:kl,otherStaticMethods:Gl}=Ll,{ColorMode:Ul,ScalarMode:_l,GetArray:Kl}=cl,{VectorMode:zl}=ll,{VtkDataTypes:Wl}=Is;function Hl(e){return()=>sn.vtkErrorMacro(`vtkMapper::${e} - NOT IMPLEMENTED`)}function jl(e,t){const n=e[1]%2==0?1:-1;if(e[0]+=n,e[0]>=t[0]||e[0]<0){const r=e[2]%2==0?1:-1;e[0]-=n,e[1]+=r,(e[1]>=t[1]||e[1]<0)&&(e[1]-=r,e[2]++)}}function Xl(e,t,n){const r=Math.floor(t),o=r%(2*n[0]);let a,i;o<n[0]?(e[0]=o,a=1,i=e[0]===n[0]-1):(e[0]=2*n[0]-1-o,a=-1,i=0===e[0]);const s=Math.floor(r/n[0]),l=s%(2*n[1]);let c,u;l<n[1]?(e[1]=l,c=1,u=e[1]===n[1]-1):(e[1]=2*n[1]-1-l,c=-1,u=0===e[1]),e[2]=Math.floor(s/n[1]);const d=t-r;i?u?e[2]+=d:e[1]+=c*d:e[0]+=a*d,e[0]=(e[0]+.5)/n[0],e[1]=(e[1]+.5)/n[1],e[2]=(e[2]+.5)/n[2]}const ql=new WeakMap;function Yl(e,t){t.classHierarchy.push("vtkMapper"),e.computeBounds=()=>{const n=e.getInputData();n?(t.static||e.update(),Hi.setBounds(t.bounds,n.getBounds())):Hi.reset(t.bounds)},e.setForceCompileOnly=e=>{t.forceCompileOnly=e},e.setSelectionWebGLIdsToVTKIds=e=>{t.selectionWebGLIdsToVTKIds=e},e.createDefaultLookupTable=()=>{t.lookupTable=Sl.newInstance()},e.getColorModeAsString=()=>sn.enumToString(Ul,t.colorMode),e.setColorModeToDefault=()=>e.setColorMode(0),e.setColorModeToMapScalars=()=>e.setColorMode(1),e.setColorModeToDirectScalars=()=>e.setColorMode(2),e.getScalarModeAsString=()=>sn.enumToString(_l,t.scalarMode),e.setScalarModeToDefault=()=>e.setScalarMode(0),e.setScalarModeToUsePointData=()=>e.setScalarMode(1),e.setScalarModeToUseCellData=()=>e.setScalarMode(2),e.setScalarModeToUsePointFieldData=()=>e.setScalarMode(3),e.setScalarModeToUseCellFieldData=()=>e.setScalarMode(4),e.setScalarModeToUseFieldData=()=>e.setScalarMode(5),e.getAbstractScalars=(e,n,r,o,a)=>{if(!e||!t.scalarVisibility)return{scalars:null,cellFlag:!1};let i=null,s=!1;if(n===_l.DEFAULT)i=e.getPointData().getScalars(),i||(i=e.getCellData().getScalars(),s=!0);else if(n===_l.USE_POINT_DATA)i=e.getPointData().getScalars();else if(n===_l.USE_CELL_DATA)i=e.getCellData().getScalars(),s=!0;else if(n===_l.USE_POINT_FIELD_DATA){const t=e.getPointData();i=r===Kl.BY_ID?t.getArrayByIndex(o):t.getArrayByName(a)}else if(n===_l.USE_CELL_FIELD_DATA){const t=e.getCellData();s=!0,i=r===Kl.BY_ID?t.getArrayByIndex(o):t.getArrayByName(a)}else if(n===_l.USE_FIELD_DATA){const t=e.getFieldData();i=r===Kl.BY_ID?t.getArrayByIndex(o):t.getArrayByName(a)}return{scalars:i,cellFlag:s}},e.mapScalars=(n,r)=>{const{scalars:o,cellFlag:a}=e.getAbstractScalars(n,t.scalarMode,t.arrayAccessMode,t.arrayId,t.colorByArrayName);if(t.areScalarsMappedFromCells=a,!o)return t.colorCoordinates=null,t.colorTextureMap=null,void(t.colorMapColors=null);const i=`${e.getMTime()}${o.getMTime()}${r}`;if(t.colorBuildString!==i){if(t.useLookupTableScalarRange||e.getLookupTable().setRange(t.scalarRange[0],t.scalarRange[1]),e.canUseTextureMapForColoring(o,a))t.mapScalarsToTexture(o,a,r);else{t.colorCoordinates=null,t.colorTextureMap=null;const n=e.getLookupTable();n&&(n.build(),t.colorMapColors=n.mapScalars(o,t.colorMode,t.fieldDataTupleId))}t.colorBuildString=`${e.getMTime()}${o.getMTime()}${r}`}},t.mapScalarsToTexture=(n,r,o)=>{const a=t.lookupTable.getRange(),i=t.lookupTable.usingLogScale(),s=t.lookupTable.getAlpha(),l=i?[Math.log10(a[0]),Math.log10(a[1])]:a;if(t.colorMapColors=null,null==t.colorTextureMap||e.getMTime()>t.colorTextureMap.getMTime()||t.lookupTable.getMTime()>t.colorTextureMap.getMTime()||t.lookupTable.getAlpha()!==o){t.lookupTable.setAlpha(o),t.colorTextureMap=null,t.lookupTable.build();const e=t.lookupTable.getNumberOfAvailableColors(),n=2048,a=2,d=r?n**3-3:4096-2;t.numberOfColorsInRange=Math.min(Math.max(e,a),d);const 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Zl(e,t,n={}){Object.assign(t,Jl,n),Ls.extend(e,t,n),sn.get(e,t,["areScalarsMappedFromCells","colorCoordinates","colorMapColors","colorTextureMap","numberOfColorsInRange","selectionWebGLIdsToVTKIds"]),sn.setGet(e,t,["colorByArrayName","arrayAccessMode","colorMode","fieldDataTupleId","interpolateScalarsBeforeMapping","lookupTable","populateSelectionSettings","renderTime","scalarMode","scalarVisibility","static","useLookupTableScalarRange","customShaderAttributes"]),sn.setGetArray(e,t,["scalarRange"],2),Ll.implementCoincidentTopologyMethods(e,t),Yl(e,t)}var Ql={newInstance:sn.newInstance(Zl,"vtkMapper"),extend:Zl,...kl,...Gl,...cl};const{isVtkObject:$l}=sn;function ec(e){const t=[];for(let n=0;n<e.length;n+=e[n]+1)t.push(e[n]);return t}function tc(e){let t=0;for(let n=0;n<e.length;)n+=e[n]+1,t++;return t}const nc={extractCellSizes:ec,getNumberOfCells:tc};function rc(e,t,n={}){Is.extend(e,t,function(e){return{empty:!0,numberOfComponents:1,dataType:ms.UNSIGNED_INT,...e}}(n)),function(e,t){t.classHierarchy.push("vtkCellArray");const n={...e};e.getNumberOfCells=n=>void 0===t.numberOfCells||n?(t.cellSizes?t.numberOfCells=t.cellSizes.length:t.numberOfCells=tc(e.getData()),t.numberOfCells):t.numberOfCells,e.getCellSizes=n=>void 0===t.cellSizes||n?(t.cellSizes=ec(e.getData()),t.cellSizes):t.cellSizes,e.resize=r=>{const o=e.getNumberOfTuples();n.resize(r);const a=e.getNumberOfTuples();a<o&&(0===a?(t.numberOfCells=0,t.cellSizes=[]):(t.numberOfCells=void 0,t.cellSizes=void 0))},e.setData=e=>{n.setData(e,1),t.numberOfCells=void 0,t.cellSizes=void 0},e.getCell=e=>{let n=e;const r=t.values[n++];return t.values.subarray(n,n+r)},e.insertNextCell=n=>{let r;r=$l(n)?n.getPointsIds():n;const o=e.getNumberOfCells();return e.insertNextTuples([r.length,...r]),++t.numberOfCells,null!=t.cellSizes&&t.cellSizes.push(r.length),o},e.getMaxCellSize=()=>e.getCellSizes().reduce(((e,t)=>Math.max(e,t)),0)}(e,t)}var oc={newInstance:sn.newInstance(rc,"vtkCellArray"),extend:rc,...nc};const{vtkErrorMacro:ac}=sn;const ic={empty:!0,numberOfComponents:3,dataType:ms.FLOAT,bounds:[1,-1,1,-1,1,-1]};function sc(e,t,n={}){Object.assign(t,ic,n),Is.extend(e,t,n),sn.getArray(e,t,["bounds"],6),function(e,t){let n=0;t.classHierarchy.push("vtkPoints"),e.getNumberOfPoints=e.getNumberOfTuples,e.setNumberOfPoints=(n,r=3)=>{e.getNumberOfPoints()!==n&&(t.size=n*r,t.values=sn.newTypedArray(t.dataType,t.size),e.setNumberOfComponents(r),e.modified())},e.setPoint=(t,...n)=>{e.setTuple(t,n)},e.getPoint=e.getTuple,e.findPoint=e.findTuple,e.insertNextPoint=(t,n,r)=>e.insertNextTuple([t,n,r]),e.insertPoint=(t,n)=>e.insertTuple(t,n);const r=e.getBounds;e.getBounds=()=>(n<t.mtime&&e.computeBounds(),r());const o=e.getBoundsByReference;e.getBoundsByReference=()=>(n<t.mtime&&e.computeBounds(),o()),e.computeBounds=()=>{if(3===e.getNumberOfComponents()){const n=e.getRange(0);t.bounds[0]=n[0],t.bounds[1]=n[1];const r=e.getRange(1);t.bounds[2]=r[0],t.bounds[3]=r[1];const o=e.getRange(2);t.bounds[4]=o[0],t.bounds[5]=o[1]}else if(2===e.getNumberOfComponents()){const n=e.getRange(0);t.bounds[0]=n[0],t.bounds[1]=n[1];const r=e.getRange(1);t.bounds[2]=r[0],t.bounds[3]=r[1],t.bounds[4]=0,t.bounds[5]=0}else ac(`getBounds called on an array with components of ${e.getNumberOfComponents()}`),Ia(t.bounds);n=sn.getCurrentGlobalMTime()},e.setNumberOfComponents(t.numberOfComponents<2?3:t.numberOfComponents)}(e,t)}var lc={newInstance:sn.newInstance(sc,"vtkPoints"),extend:sc};const cc={bounds:[-1,-1,-1,-1,-1,-1],pointsIds:[]};function uc(e,t,n={}){Object.assign(t,cc,n),sn.obj(e,t),t.points||(t.points=lc.newInstance()),sn.get(e,t,["points","pointsIds"]),function(e,t){t.classHierarchy.push("vtkCell"),e.initialize=(e,n=null)=>{if(n){t.pointsIds=n;let r=t.points.getData();r.length!==3*t.pointsIds.length&&(r=sn.newTypedArray(e.getDataType(),3*t.pointsIds.length));const o=e.getData();t.pointsIds.forEach(((e,t)=>{let n=3*e,a=3*t;r[a]=o[n],r[++a]=o[++n],r[++a]=o[++n]})),t.points.setData(r)}else{t.points=e,t.pointsIds=new Array(e.getNumberOfPoints());for(let n=e.getNumberOfPoints()-1;n>=0;--n)t.pointsIds[n]=n}},e.getBounds=()=>t.points.getBounds(),e.getLength2=()=>{const t=Hi.getLengths(e.getBounds());return t[0]*t[0]+t[1]*t[1]+t[2]*t[2]},e.getParametricDistance=e=>{let t,n=0;for(let r=0;r<3;r++)t=e[r]<0?-e[r]:e[r]>1?e[r]-1:0,t>n&&(n=t);return n},e.getNumberOfPoints=()=>t.points.getNumberOfPoints(),e.deepCopy=e=>{e.initialize(t.points,t.pointsIds)},e.getCellDimension=()=>{},e.intersectWithLine=(e,t,n,r,o,a,i)=>{},e.evaluatePosition=(e,t,n,r,o,a)=>{sn.vtkErrorMacro("vtkCell.evaluatePosition is not implemented.")}}(e,t)}var dc={newInstance:sn.newInstance(uc,"vtkCell"),extend:uc};const pc={array:null,maxId:0,extend:0};function fc(e,t,n={}){Object.assign(t,pc,n),sn.obj(e,t),function(e,t){t.classHierarchy.push("vtkCellLinks"),e.buildLinks=n=>{const r=n.getPoints().getNumberOfPoints(),o=n.getNumberOfCells(),a=new Uint32Array(r);if(n.isA("vtkPolyData")){for(let t=0;t<o;++t){const{cellPointIds:r}=n.getCellPoints(t);r.forEach((t=>{e.incrementLinkCount(t)}))}e.allocateLinks(r),t.maxId=r-1;for(let t=0;t<o;++t){const{cellPointIds:r}=n.getCellPoints(t);r.forEach((n=>{e.insertCellReference(n,a[n]++,t)}))}}else{for(let t=0;t<o;t++)dc.newInstance().getPointsIds().forEach((t=>{e.incrementLinkCount(t)}));e.allocateLinks(r),t.maxId=r-1;for(let t=0;t<o;++t)dc.newInstance().getPointsIds().forEach((n=>{e.insertCellReference(n,a[n]++,t)}))}},e.allocate=(e,n=1e3)=>{t.array=Array(e).fill().map((()=>({ncells:0,cells:null}))),t.extend=n,t.maxId=-1},e.initialize=()=>{t.array=null},e.getLink=e=>t.array[e],e.getNcells=e=>t.array[e].ncells,e.getCells=e=>t.array[e].cells,e.insertNextPoint=e=>{t.array.push({ncells:e,cells:Array(e)}),++t.maxId},e.insertNextCellReference=(e,n)=>{t.array[e].cells[t.array[e].ncells++]=n},e.deletePoint=e=>{t.array[e].ncells=0,t.array[e].cells=null},e.removeCellReference=(e,n)=>{t.array[n].cells=t.array[n].cells.filter((t=>t!==e)),t.array[n].ncells=t.array[n].cells.length},e.addCellReference=(e,n)=>{t.array[n].cells[t.array[n].ncells++]=e},e.resizeCellList=(e,n)=>{t.array[e].cells.length=n},e.squeeze=()=>{!function(e,t){let n=t;for(t>=e.array.length&&(n+=e.array.length);n>e.array.length;)e.array.push({ncells:0,cells:null});e.array.length=n}(t,t.maxId+1)},e.reset=()=>{t.maxId=-1},e.deepCopy=e=>{t.array=[...e.array],t.extend=e.extend,t.maxId=e.maxId},e.incrementLinkCount=e=>{++t.array[e].ncells},e.allocateLinks=e=>{for(let n=0;n<e;++n)t.array[n].cells=new Array(t.array[n].ncells)},e.insertCellReference=(e,n,r)=>{t.array[e].cells[n]=r}}(e,t)}var gc={newInstance:sn.newInstance(fc,"vtkCellLinks"),extend:fc};const mc=0,hc=1,vc=2,Tc=3,xc=4,yc=5,bc=6,Ac=7,Cc=9,Sc=21,Pc=41,wc=42,Ic=["vtkEmptyCell","vtkVertex","vtkPolyVertex","vtkLine","vtkPolyLine","vtkTriangle","vtkTriangleStrip","vtkPolygon","vtkPixel","vtkQuad","vtkTetra","vtkVoxel","vtkHexahedron","vtkWedge","vtkPyramid","vtkPentagonalPrism","vtkHexagonalPrism","UnknownClass","UnknownClass","UnknownClass","UnknownClass","vtkQuadraticEdge","vtkQuadraticTriangle","vtkQuadraticQuad","vtkQuadraticTetra","vtkQuadraticHexahedron","vtkQuadraticWedge","vtkQuadraticPyramid","vtkBiQuadraticQuad","vtkTriQuadraticHexahedron","vtkQuadraticLinearQuad","vtkQuadraticLinearWedge","vtkBiQuadraticQuadraticWedge","vtkBiQuadraticQuadraticHexahedron","vtkBiQuadraticTriangle","vtkCubicLine","vtkQuadraticPolygon","UnknownClass","UnknownClass","UnknownClass","UnknownClass","vtkConvexPointSet","UnknownClass","UnknownClass","UnknownClass","UnknownClass","UnknownClass","UnknownClass","UnknownClass","UnknownClass","UnknownClass","vtkParametricCurve","vtkParametricSurface","vtkParametricTriSurface","vtkParametricQuadSurface","vtkParametricTetraRegion","vtkParametricHexRegion","UnknownClass","UnknownClass","UnknownClass","vtkHigherOrderEdge","vtkHigherOrderTriangle","vtkHigherOrderQuad","vtkHigherOrderPolygon","vtkHigherOrderTetrahedron","vtkHigherOrderWedge","vtkHigherOrderPyramid","vtkHigherOrderHexahedron"];const Oc={getClassNameFromTypeId:function(e){return e<Ic.length?Ic[e]:"UnknownClass"},getTypeIdFromClassName:function(e){return Ic.findIndex(e)},isLinear:function(e){return e<Sc||e===Pc||e===wc},hasSubCells:function(e){return e===bc||e===xc||e===vc}};const Rc={size:0,maxId:-1,extend:1e3};function Mc(e,t,n={}){Object.assign(t,Rc,n),sn.obj(e,t),sn.get(e,t,["size","maxId","extend"]),sn.getArray(e,t,["typeArray","locationArray"]),function(e,t){t.classHierarchy.push("vtkCellTypes"),e.allocate=(e=512,n=1e3)=>{t.size=e>0?e:1,t.extend=n>0?n:1,t.maxId=-1,t.typeArray=new Uint8Array(e),t.locationArray=new Uint32Array(e)},e.insertCell=(e,n,r)=>{t.typeArray[e]=n,t.locationArray[e]=r,e>t.maxId&&(t.maxId=e)},e.insertNextCell=(n,r)=>(e.insertCell(++t.maxId,n,r),t.maxId),e.setCellTypes=(e,n,r)=>{t.size=e,t.typeArray=n,t.locationArray=r,t.maxId=e-1},e.getCellLocation=e=>t.locationArray[e],e.deleteCell=e=>{t.typeArray[e]=mc},e.getNumberOfTypes=()=>t.maxId+1,e.isType=t=>{const n=e.getNumberOfTypes();for(let r=0;r<n;++r)if(t===e.getCellType(r))return!0;return!1},e.insertNextType=t=>e.insertNextCell(t,-1),e.getCellType=e=>t.typeArray[e],e.reset=()=>{t.maxId=-1},e.deepCopy=n=>{e.allocate(n.getSize(),n.getExtend()),t.typeArray.set(n.getTypeArray()),t.locationArray.set(n.getLocationArray()),t.maxId=n.getMaxId()}}(e,t)}var Dc={newInstance:sn.newInstance(Mc,"vtkCellTypes"),extend:Mc,...Oc};const Ec={NO_INTERSECTION:0,YES_INTERSECTION:1,ON_LINE:2};var Vc={IntersectionState:Ec};const{IntersectionState:Lc}=Vc;function Bc(e,t,n,r=null){const o={t:Number.MIN_VALUE,distance:0},a=[];let i;a[0]=n[0]-t[0],a[1]=n[1]-t[1],a[2]=n[2]-t[2];const s=a[0]*(e[0]-t[0])+a[1]*(e[1]-t[1])+a[2]*(e[2]-t[2]),l=zo(a,a);let c=1e-5*s;return 0!==l&&(o.t=s/l),c<0&&(c=-c),-c<l&&l<c||l<=0||o.t<0?i=t:o.t>1?i=n:(i=a,a[0]=t[0]+o.t*a[0],a[1]=t[1]+o.t*a[1],a[2]=t[2]+o.t*a[2]),r&&(r[0]=i[0],r[1]=i[1],r[2]=i[2]),o.distance=Yo(i,e),o}function Fc(e,t,n,r,o,a){const i=[],s=[],l=[];o[0]=0,a[0]=0,Go(t,e,i),Go(r,n,s),Go(n,e,l);const c=[zo(i,i),-zo(i,s),-zo(i,s),zo(s,s)],u=[];if(u[0]=zo(i,l),u[1]=-zo(s,l),0===ha(c,u,2)){let i=Number.MAX_VALUE;const s=[e,t,n,r],l=[n,n,e,e],c=[r,r,t,t];let u;a[0],a[0],o[0],o[0],o[0],o[0],a[0],a[0];for(let e=0;e<4;e++)u=Bc(s[e],l[e],c[e]),u.distance<i&&(i=u.distance,u.t);return Lc.ON_LINE}return o[0]=u[0],a[0]=u[1],o[0]>=0&&o[0]<=1&&a[0]>=0&&a[0]<=1?Lc.YES_INTERSECTION:Lc.NO_INTERSECTION}const Nc={distanceToLine:Bc,intersection:Fc};const kc={orientations:null};function Gc(e,t,n={}){Object.assign(t,kc,n),dc.extend(e,t,n),sn.setGet(e,t,["orientations"]),function(e,t){t.classHierarchy.push("vtkLine"),e.getCellDimension=()=>1,e.intersectWithLine=(e,n,r,o,a)=>{const i={intersect:0,t:Number.MAX_VALUE,subId:0,betweenPoints:null};a[1]=0,a[2]=0;const s=[],l=[],c=[];t.points.getPoint(0,l),t.points.getPoint(1,c);const u=[],d=[],p=Fc(e,n,l,c,u,d);var f;if(i.t=u[0],i.betweenPoints=(f=i.t)>=0&&f<=1,a[0]=d[0],p===Lc.YES_INTERSECTION){for(let 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s,l;Math.abs(r[0])>Math.abs(r[1])?Math.abs(r[0])>Math.abs(r[2])?(s=1,l=2):(s=0,l=1):Math.abs(r[1])>Math.abs(r[2])?(s=0,l=2):(s=0,l=1);let c=0;for(let n=0;n<t.length;)a[0]=t[n++],a[1]=t[n++],a[2]=t[n++],n<t.length?(i[0]=t[n],i[1]=t[n+1],i[2]=t[n+2]):(i[0]=t[0],i[1]=t[1],i[2]=t[2]),a[l]<=e[l]?i[l]>e[l]&&$c(s,l,a,i,e)>0&&++c:i[l]<=e[l]&&$c(s,l,a,i,e)<0&&--c;return 0===c?Qc.OUTSIDE:Qc.INSIDE},getBounds:function(e,t,n){const r=e.length,o=[];t.getPoint(e[0],o),n[0]=o[0],n[1]=o[0],n[2]=o[1],n[3]=o[1],n[4]=o[2],n[5]=o[2];for(let a=1;a<r;a++)t.getPoint(e[a],o),Hi.addPoint(n,...o);const a=Hi.getLengths(n);return zo(a,a)},getNormal:function(e,t,n){n.length=3,n[0]=0,n[1]=0,n[2]=0;const r=[];let o=[],a=[];const i=[],s=[];t.getPoint(e[0],r),t.getPoint(e[1],o);for(let l=2;l<e.length;l++){t.getPoint(e[l],a),Go(a,o,i),Go(r,o,s);const c=[0,0,0];Wo(i,s,c),ko(n,c,n),[o,a]=[a,o]}return jo(n)},computeCentroid:function(e,t,n=[0,0,0]){n[0]=0,n[1]=0,n[2]=0;const r=e.length,o=[];for(let 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l=[];t.points.getPoint(e+2,l);const c=t.triangle.getPoints();c.setPoint(0,...i),c.setPoint(1,...s),c.setPoint(2,...l),t.triangle.derivatives(0,n,r,o,a)},e.getParametricCenter=e=>(e[0]=.333333,e[1]=.333333,e[2]=0,Math.floor((t.pointsIds.length-2)/2)),e.contour=(e,t,n,r,o,a,i,s,l,c,u)=>{return(d="contour",()=>Tu(`vtkTriangleStrip.${d} - NOT IMPLEMENTED`))();var d},e.clip=(e,n,r,o,a,i,s,l,c,u)=>{const d=t.points.getNumberOfPoints()-2,p=new Float32Array(3),f=n.newClone();f.setNumberOfComponents(n.getNumberOfComponents()),f.setData(p,n.getNumberOfComponents());const g=t.triangle.getPoints();g.setNumberOfPoints(3);const m=t.triangle.getPointsIds(),h=[0,0,0];for(let v=0;v<d;v++){let 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r=e.getCellPoints(t),o=n||wu[r.cellType].newInstance();return o.initialize(e.getPoints(),r.cellPointIds),o},e.getMaxCellSize=()=>Su.reduce(((e,n)=>Math.max(e,t[n]?.getMaxCellSize?.()??0)),0)}(e,t)}var Ru={newInstance:sn.newInstance(Ou,"vtkPolyData"),extend:Ou};const Mu={image:null,canvas:null,jsImageData:null,imageBitmap:null,imageLoaded:!1,repeat:!1,interpolate:!1,edgeClamp:!1,mipLevel:0,resizable:!1};function Du(e,t,n={}){Object.assign(t,Mu,n),sn.obj(e,t),sn.algo(e,t,6,0),sn.get(e,t,["canvas","image","jsImageData","imageBitmap","imageLoaded","resizable"]),sn.setGet(e,t,["repeat","edgeClamp","interpolate","mipLevel"]),function(e,t){t.classHierarchy.push("vtkTexture"),e.imageLoaded=()=>{t.image.removeEventListener("load",e.imageLoaded),t.imageLoaded=!0,e.modified()},e.setJsImageData=n=>{t.jsImageData!==n&&(null!==n&&(e.setInputData(null),e.setInputConnection(null),t.image=null,t.canvas=null,t.imageBitmap=null),t.jsImageData=n,t.imageLoaded=!0,e.modified())},e.setImageBitmap=n=>{t.imageBitmap!==n&&(null!==n&&(e.setInputData(null),e.setInputConnection(null),t.image=null,t.canvas=null,t.jsImageData=null),t.imageBitmap=n,t.imageLoaded=!0,e.modified())},e.setCanvas=n=>{t.canvas!==n&&(null!==n&&(e.setInputData(null),e.setInputConnection(null),t.image=null,t.imageBitmap=null,t.jsImageData=null),t.canvas=n,e.modified())},e.setImage=n=>{t.image!==n&&(null!==n&&(e.setInputData(null),e.setInputConnection(null),t.canvas=null,t.jsImageData=null,t.imageBitmap=null),t.image=n,t.imageLoaded=!1,n.complete?e.imageLoaded():n.addEventListener("load",e.imageLoaded),e.modified())},e.getDimensionality=()=>{let n=0,r=0,o=1;if(e.getInputData()){const t=e.getInputData();n=t.getDimensions()[0],r=t.getDimensions()[1],o=t.getDimensions()[2]}return t.jsImageData&&(n=t.jsImageData.width,r=t.jsImageData.height),t.canvas&&(n=t.canvas.width,r=t.canvas.height),t.image&&(n=t.image.width,r=t.image.height),t.imageBitmap&&(n=t.imageBitmap.width,r=t.imageBitmap.height),(n>1)+(r>1)+(o>1)},e.getInputAsJsImageData=()=>{if(!t.imageLoaded||e.getInputData())return null;if(t.jsImageData)return t.jsImageData;if(t.imageBitmap)return t.imageBitmap;if(t.canvas)return t.canvas.getContext("2d").getImageData(0,0,t.canvas.width,t.canvas.height);if(t.image){const e=t.image.width,n=t.image.height,r=new OffscreenCanvas(e,n).getContext("2d");return r.translate(0,n),r.scale(1,-1),r.drawImage(t.image,0,0,e,n),r.getImageData(0,0,e,n)}return null}}(e,t)}var Eu={newInstance:sn.newInstance(Du,"vtkTexture"),extend:Du,...{generateMipmaps:(e,t,n)=>{const r=e.createShaderModule({code:"\n    @group(0) @binding(0) var inputTexture: texture_2d<f32>;\n    @group(0) @binding(1) var outputTexture: texture_storage_2d<rgba8unorm, write>;\n\n    @compute @workgroup_size(8, 8)\n    fn main(@builtin(global_invocation_id) global_id: vec3<u32>) {\n      let texelCoord = vec2<i32>(global_id.xy);\n      let outputSize = textureDimensions(outputTexture);\n\n      if (texelCoord.x >= i32(outputSize.x) || texelCoord.y >= i32(outputSize.y)) {\n        return;\n      }\n\n      let inputSize = textureDimensions(inputTexture);\n      let scale = vec2<f32>(inputSize) / vec2<f32>(outputSize);\n\n      // Compute the floating-point source coordinate\n      let srcCoord = (vec2<f32>(texelCoord) + 0.5) * scale - 0.5;\n\n      // Get integer coordinates for the four surrounding texels\n      let x0 = i32(floor(srcCoord.x));\n      let x1 = min(x0 + 1, i32(inputSize.x) - 1);\n      let y0 = i32(floor(srcCoord.y));\n      let y1 = min(y0 + 1, i32(inputSize.y) - 1);\n\n      // Compute the weights\n      let wx = srcCoord.x - f32(x0);\n      let wy = srcCoord.y - f32(y0);\n\n      // Fetch the four texels\n      let c00 = textureLoad(inputTexture, vec2<i32>(x0, y0), 0);\n      let c10 = textureLoad(inputTexture, vec2<i32>(x1, y0), 0);\n      let c01 = textureLoad(inputTexture, vec2<i32>(x0, y1), 0);\n      let c11 = textureLoad(inputTexture, vec2<i32>(x1, y1), 0);\n\n      // Bilinear interpolation\n      let color = mix(\n        mix(c00, c10, wx),\n        mix(c01, c11, wx),\n        wy\n      );\n\n      textureStore(outputTexture, texelCoord, color);\n    }\n  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u=Math.max(1,t.width>>r),d=Math.max(1,t.height>>r),p=Math.ceil(u/8),f=Math.ceil(d/8);c.dispatchWorkgroups(p,f),c.end(),e.queue.submit([l.finish()])}}}};const Vu=[[-1,0,0],[1,0,0],[0,-1,0],[0,1,0],[0,0,-1],[0,0,1]],Lu=[[8,7,11,3],[9,1,10,5],[4,9,0,8],[2,11,6,10],[0,3,2,1],[4,5,6,7]],Bu=[[0,1],[1,3],[2,3],[0,2],[4,5],[5,7],[6,7],[4,6],[0,4],[1,5],[3,7],[2,6]],Fu=[0,1,0,1,0,1,0,1,2,2,2,2],Nu=[[1,2],[1,2],[0,2],[0,2],[0,1],[0,1]],ku=new Float64Array(3),Gu=new Float64Array(3),Uu=new Float64Array(3),_u=new Float64Array(3),Ku=new Float64Array(3),zu=new Float64Array(3),Wu=new Float64Array(16);function Hu(e,t){e.strokeStyle=t.strokeColor,e.lineWidth=t.strokeSize,e.fillStyle=t.fontColor,e.font=`${t.fontStyle} ${t.fontSize}px ${t.fontFamily}`}function ju(e){const t=[],n=[];for(let r=0;r<3;r++){const o=$r().domain([e[2*r],e[2*r+1]]);t[r]=o.ticks(5);const a=o.tickFormat(5);n[r]=t[r].map(a)}return{ticks:t,tickStrings:n}}const Xu=sn.newInstance(((e,t,n={renderable:null})=>{Object.assign(t,{},n),sn.obj(e,t),t.tmPolyData=Ru.newInstance(),t.tmMapper=Ql.newInstance(),t.tmMapper.setInputData(t.tmPolyData),t.tmActor=fs.newInstance({parentProp:e}),t.tmActor.setMapper(t.tmMapper),sn.setGet(e,t,["renderable"]),sn.get(e,t,["lastSize","lastAspectRatio","axisTextStyle","tickTextStyle","tmActor","ticks"]),t.forceUpdate=!1,t.lastRedrawTime={},sn.obj(t.lastRedrawTime,{mtime:0}),t.lastRebuildTime={},sn.obj(t.lastRebuildTime,{mtime:0}),t.lastSize=[-1,-1],t.lastTickBounds=[],function(e,t){t.classHierarchy.push("vtkCubeAxesActorHelper"),e.setRenderable=n=>{t.renderable!==n&&(t.renderable=n,t.tmActor.addTexture(t.renderable.getTmTexture()),t.tmActor.setProperty(n.getProperty()),t.tmActor.setParentProp(n),e.modified())},e.createPolyDataForOneLabel=(e,n,r,o,a,i,s)=>{const l=t.renderable.get_tmAtlas().get(e);if(!l)return;const c=t.renderable.getTextPolyData().getPoints().getData(),u=t.lastSize;ku[0]=c[3*n],ku[1]=c[3*n+1],ku[2]=c[3*n+2],oe(Uu,ku,r),Uu[0]+=.1,oe(Gu,Uu,o),Z(Ku,Gu,ku),Uu[0]-=.1,Uu[1]+=.1,oe(Gu,Uu,o),Z(zu,Gu,ku);for(let e=0;e<3;e++)Ku[e]/=.05*u[0],zu[e]/=.05*u[1];let d=s.ptIdx,p=s.cellIdx;ku[0]=c[3*n],ku[1]=c[3*n+1],ku[2]=c[3*n+2],a[0]<-.5?$(Uu,Ku,a[0]*i-l.width):a[0]>.5?$(Uu,Ku,a[0]*i):$(Uu,Ku,a[0]*i-l.width/2),J(ku,ku,Uu),$(Uu,zu,a[1]*i-l.height/2),J(ku,ku,Uu),s.points[3*d]=ku[0],s.points[3*d+1]=ku[1],s.points[3*d+2]=ku[2],s.tcoords[2*d]=l.tcoords[0],s.tcoords[2*d+1]=l.tcoords[1],d++,$(Uu,Ku,l.width),J(ku,ku,Uu),s.points[3*d]=ku[0],s.points[3*d+1]=ku[1],s.points[3*d+2]=ku[2],s.tcoords[2*d]=l.tcoords[2],s.tcoords[2*d+1]=l.tcoords[3],d++,$(Uu,zu,l.height),J(ku,ku,Uu),s.points[3*d]=ku[0],s.points[3*d+1]=ku[1],s.points[3*d+2]=ku[2],s.tcoords[2*d]=l.tcoords[4],s.tcoords[2*d+1]=l.tcoords[5],d++,$(Uu,Ku,l.width),Z(ku,ku,Uu),s.points[3*d]=ku[0],s.points[3*d+1]=ku[1],s.points[3*d+2]=ku[2],s.tcoords[2*d]=l.tcoords[6],s.tcoords[2*d+1]=l.tcoords[7],d++,s.polys[4*p]=3,s.polys[4*p+1]=d-4,s.polys[4*p+2]=d-3,s.polys[4*p+3]=d-2,p++,s.polys[4*p]=3,s.polys[4*p+1]=d-4,s.polys[4*p+2]=d-2,s.polys[4*p+3]=d-1,s.ptIdx+=4,s.cellIdx+=2},e.updateTexturePolyData=()=>{const n=t.camera.getCompositeProjectionMatrix(t.lastAspectRatio,-1,1);y(n,n);const r=t.renderable.getTextValues().length,o=4*r,a=2*r,i=new Float64Array(3*o),s=new Uint16Array(4*a),l=new Float32Array(2*o);b(Wu,n);const c={ptIdx:0,cellIdx:0,polys:s,points:i,tcoords:l};let u=0,d=0,p=0;const f=t.renderable.getTextPolyData().getPoints().getData(),g=t.renderable.getTextValues();for(;u<f.length/3;){ku[0]=f[3*u],ku[1]=f[3*u+1],ku[2]=f[3*u+2],oe(Uu,ku,n),ku[0]=f[3*u+3],ku[1]=f[3*u+4],ku[2]=f[3*u+5],oe(_u,ku,n),Z(Uu,Uu,_u);const r=[Uu[0],Uu[1]];Zo(r),e.createPolyDataForOneLabel(g[d],u,n,Wu,r,t.renderable.getAxisTitlePixelOffset(),c),u+=2,d++;for(let o=0;o<t.renderable.getTickCounts()[p];o++)e.createPolyDataForOneLabel(g[d],u,n,Wu,r,t.renderable.getTickLabelPixelOffset(),c),u++,d++;p++}const m=Is.newInstance({numberOfComponents:2,values:l,name:"TextureCoordinates"});t.tmPolyData.getPointData().setTCoords(m),t.tmPolyData.getPoints().setData(i,3),t.tmPolyData.getPoints().modified(),t.tmPolyData.getPolys().setData(s,1),t.tmPolyData.getPolys().modified(),t.tmPolyData.modified()},e.updateAPISpecificData=(n,r,o)=>{t.lastSize[0]===n[0]&&t.lastSize[1]===n[1]||(t.lastSize[0]=n[0],t.lastSize[1]=n[1],t.lastAspectRatio=n[0]/n[1],t.forceUpdate=!0),t.camera=r,e.updateTexturePolyData()}}(e,t)}),"vtkCubeAxesActorHelper");function qu(e,t,n={}){fs.extend(e,t,function(e,t,n){return{boundsScaleFactor:1.3,camera:null,dataBounds:[...Hi.INIT_BOUNDS],faceVisibilityAngle:8,gridLines:!0,axisLabels:null,axisTitlePixelOffset:35,tickLabelPixelOffset:12,generateTicks:ju,...n,axisTextStyle:{fontColor:"white",fontStyle:"normal",fontSize:18,fontFamily:"serif",...n?.axisTextStyle},tickTextStyle:{fontColor:"white",fontStyle:"normal",fontSize:14,fontFamily:"serif",...n?.tickTextStyle}}}(0,0,n)),t.lastFacesToDraw=[!1,!1,!1,!1,!1,!1],t.axisLabels=["X-Axis","Y-Axis","Z-Axis"],t.tickCounts=[],t.textValues=[],t.lastTickBounds=[],t.tmCanvas=document.createElement("canvas"),t.tmContext=t.tmCanvas.getContext("2d"),t._tmAtlas=new Map,t.tmTexture=Eu.newInstance({resizable:!0}),t.tmTexture.setInterpolate(!1),e.getProperty().setDiffuse(0),e.getProperty().setAmbient(1),t.gridMapper=Ql.newInstance(),t.polyData=Ru.newInstance(),t.gridMapper.setInputData(t.polyData),t.gridActor=fs.newInstance(),t.gridActor.setMapper(t.gridMapper),t.gridActor.setProperty(e.getProperty()),t.gridActor.setParentProp(e),t.textPolyData=Ru.newInstance(),sn.setGet(e,t,["axisTitlePixelOffset","boundsScaleFactor","faceVisibilityAngle","gridLines","tickLabelPixelOffset","generateTicks"]),sn.setGetArray(e,t,["dataBounds"],6),sn.setGetArray(e,t,["axisLabels"],3),sn.get(e,t,["axisTextStyle","tickTextStyle","camera","tmTexture","textValues","textPolyData","tickCounts","gridActor"]),function(e,t){t.classHierarchy.push("vtkCubeAxesActor"),e.setCamera=n=>{t.camera!==n&&(t.cameraModifiedSub&&(t.cameraModifiedSub.unsubscribe(),t.cameraModifiedSub=null),t.camera=n,n&&(t.cameraModifiedSub=n.onModified(e.update)),e.update(),e.modified())},e.computeFacesToDraw=()=>{const e=t.camera.getViewMatrix();y(e,e);let n=!1;const r=Hi.getDiagonalLength(t.dataBounds),o=Math.sin(t.faceVisibilityAngle*Math.PI/180);for(let a=0;a<6;a++){let i=!1;const s=Math.floor(a/2),l=(s+1)%3,c=(s+2)%3;t.dataBounds[2*l]!==t.dataBounds[2*l+1]&&t.dataBounds[2*c]!==t.dataBounds[2*c+1]&&(ku[s]=t.dataBounds[a]-.1*r*Vu[a][s],ku[l]=.5*(t.dataBounds[2*l]+t.dataBounds[2*l+1]),ku[c]=.5*(t.dataBounds[2*c]+t.dataBounds[2*c+1]),oe(Uu,ku,e),ku[s]=t.dataBounds[a],oe(_u,ku,e),Z(Uu,_u,Uu),te(Uu,Uu),i=Uu[2]>o,t.camera.getParallelProjection()||(te(_u,_u),i=ne(_u,Uu)>o)),i!==t.lastFacesToDraw[a]&&(t.lastFacesToDraw[a]=i,n=!0)}return n},e.updatePolyData=(e,n,r)=>{let o=0,a=0;o+=8;let i=0;for(let e=0;e<12;e++)n[e]>0&&i++;if(a+=i,t.gridLines)for(let t=0;t<6;t++)e[t]&&(o+=2*r[Nu[t][0]].length+2*r[Nu[t][1]].length,a+=r[Nu[t][0]].length+r[Nu[t][1]].length);const s=new Float64Array(3*o),l=new Uint32Array(3*a);let c=0,u=0;for(let e=0;e<2;e++)for(let n=0;n<2;n++)for(let r=0;r<2;r++)s[3*c]=t.dataBounds[r],s[3*c+1]=t.dataBounds[2+n],s[3*c+2]=t.dataBounds[4+e],c++;for(let e=0;e<12;e++)n[e]>0&&(l[3*u]=2,l[3*u+1]=Bu[e][0],l[3*u+2]=Bu[e][1],u++);if(t.gridLines)for(let n=0;n<6;n++)if(e[n]){const e=Math.floor(n/2);let o=r[Nu[n][0]];for(let r=0;r<o.length;r++)s[3*c+e]=t.dataBounds[n],s[3*c+Nu[n][0]]=o[r],s[3*c+Nu[n][1]]=t.dataBounds[2*Nu[n][1]],c++,s[3*c+e]=t.dataBounds[n],s[3*c+Nu[n][0]]=o[r],s[3*c+Nu[n][1]]=t.dataBounds[2*Nu[n][1]+1],c++,l[3*u]=2,l[3*u+1]=c-2,l[3*u+2]=c-1,u++;o=r[Nu[n][1]];for(let r=0;r<o.length;r++)s[3*c+e]=t.dataBounds[n],s[3*c+Nu[n][1]]=o[r],s[3*c+Nu[n][0]]=t.dataBounds[2*Nu[n][0]],c++,s[3*c+e]=t.dataBounds[n],s[3*c+Nu[n][1]]=o[r],s[3*c+Nu[n][0]]=t.dataBounds[2*Nu[n][0]+1],c++,l[3*u]=2,l[3*u+1]=c-2,l[3*u+2]=c-1,u++}t.polyData.getPoints().setData(s,3),t.polyData.getPoints().modified(),t.polyData.getLines().setData(l,1),t.polyData.getLines().modified(),t.polyData.modified()},e.updateTextData=(e,n,r,o)=>{let a=0;for(let e=0;e<12;e++)1===n[e]&&(a+=2,a+=r[Fu[e]].length);const i=t.polyData.getPoints().getData(),s=new Float64Array(3*a);let l=0,c=0,u=0;for(let a=0;a<6;a++)if(e[a])for(let e=0;e<4;e++){const d=Lu[a][e];if(1===n[d]){const e=Fu[d],n=3*Bu[d][0],p=3*Bu[d][1];s[3*l]=.5*(i[n]+i[p]),s[3*l+1]=.5*(i[n+1]+i[p+1]),s[3*l+2]=.5*(i[n+2]+i[p+2]),l++,s[3*l+Math.floor(a/2)]=t.dataBounds[a],s[3*l+Nu[a][0]]=.5*(t.dataBounds[2*Nu[a][0]]+t.dataBounds[2*Nu[a][0]+1]),s[3*l+Nu[a][1]]=.5*(t.dataBounds[2*Nu[a][1]]+t.dataBounds[2*Nu[a][1]+1]),l++,t.textValues[c]=t.axisLabels[e],c++;const f=(e+1)%3,g=(e+2)%3,m=r[e],h=o[e];t.tickCounts[u]=m.length;for(let r=0;r<m.length;r++)s[3*l+e]=m[r],s[3*l+f]=i[n+f],s[3*l+g]=i[n+g],l++,t.textValues[c]=h[r],c++;u++}}t.textPolyData.getPoints().setData(s,3),t.textPolyData.modified()},e.update=()=>{if(!t.camera)return;const n=e.computeFacesToDraw(),r=t.lastFacesToDraw;let o=!1;for(let e=0;e<6;e++)t.dataBounds[e]!==t.lastTickBounds[e]&&(o=!0,t.lastTickBounds[e]=t.dataBounds[e]);if(n||o||t.forceUpdate){const n=new Array(12).fill(0);for(let e=0;e<6;e++)if(r[e])for(let t=0;t<4;t++)n[Lu[e][t]]++;const a=t.generateTicks(t.dataBounds);e.updatePolyData(r,n,a.ticks),e.updateTextData(r,n,a.ticks,a.tickStrings),(o||t.forceUpdate)&&e.updateTextureAtlas(a.tickStrings)}t.forceUpdate=!1},e.updateTextureAtlas=e=>{t.tmContext.textBaseline="bottom",t.tmContext.textAlign="left",t._tmAtlas.clear();let n=0,r=1;for(let o=0;o<3;o++){if(!t._tmAtlas.has(t.axisLabels[o])){Hu(t.tmContext,t.axisTextStyle);const e=t.tmContext.measureText(t.axisLabels[o]),a={height:e.actualBoundingBoxAscent+2,startingHeight:r,width:e.width+2,textStyle:t.axisTextStyle};t._tmAtlas.set(t.axisLabels[o],a),r+=a.height,n<a.width&&(n=a.width)}Hu(t.tmContext,t.tickTextStyle);for(let a=0;a<e[o].length;a++)if(!t._tmAtlas.has(e[o][a])){const i=t.tmContext.measureText(e[o][a]),s={height:i.actualBoundingBoxAscent+2,startingHeight:r,width:i.width+2,textStyle:t.tickTextStyle};t._tmAtlas.set(e[o][a],s),r+=s.height,n<s.width&&(n=s.width)}}n=Bo(n),r=Bo(r),t._tmAtlas.forEach((e=>{e.tcoords=[0,(r-e.startingHeight-e.height)/r,e.width/n,(r-e.startingHeight-e.height)/r,e.width/n,(r-e.startingHeight)/r,0,(r-e.startingHeight)/r]})),t.tmCanvas.width=n,t.tmCanvas.height=r,t.tmContext.textBaseline="bottom",t.tmContext.textAlign="left",t.tmContext.clearRect(0,0,n,r),t._tmAtlas.forEach(((e,n)=>{Hu(t.tmContext,e.textStyle),t.tmContext.fillText(n,1,e.startingHeight+e.height-1)})),t.tmTexture.setCanvas(t.tmCanvas),t.tmTexture.modified()},e.onModified((()=>{t.forceUpdate=!0,e.update()})),e.setTickTextStyle=n=>{t.tickTextStyle={...t.tickTextStyle,...n},e.modified()},e.setAxisTextStyle=n=>{t.axisTextStyle={...t.axisTextStyle,...n},e.modified()},e.get_tmAtlas=()=>t._tmAtlas,e.computeBounds=()=>{e.update(),Hi.setBounds(t.bounds,t.gridActor.getBounds()),Hi.scaleAboutCenter(t.bounds,t.boundsScaleFactor,t.boundsScaleFactor,t.boundsScaleFactor)};const n=e.setProperty;e.setProperty=e=>{const r=n(e);return t.gridActor.setProperty(e),r}}(e,t)}var Yu={newInstance:sn.newInstance(qu,"vtkCubeAxesActor"),extend:qu,newCubeAxesActorHelper:Xu,defaultGenerateTicks:ju};const Ju={};vn("vtkCubeAxesActor",Xt((function(e,t,n={}){Object.assign(t,Ju,n),pn.extend(e,t,n),t.CubeAxesActorHelper=Yu.newCubeAxesActorHelper(),function(e,t){t.classHierarchy.push("vtkOpenGLCubeAxesActor"),e.buildPass=n=>{n&&(t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getParent(),t.CubeAxesActorHelper.getRenderable()||t.CubeAxesActorHelper.setRenderable(t.renderable),e.prepareNodes(),e.addMissingNode(t.CubeAxesActorHelper.getTmActor()),e.addMissingNode(t.renderable.getGridActor()),e.removeUnusedNodes())},e.opaquePass=(e,n)=>{if(e){const e=t._openGLRenderer?t._openGLRenderer.getRenderable().getActiveCamera():null,n=t._openGLRenderer.getTiledSizeAndOrigin();t.CubeAxesActorHelper.updateAPISpecificData([n.usize,n.vsize],e,t._openGLRenderWindow.getRenderable())}}}(e,t)}),"vtkOpenGLCubeAxesActor"));const Zu={ARRAY_BUFFER:0,ELEMENT_ARRAY_BUFFER:1,TEXTURE_BUFFER:2};var Qu={ObjectType:Zu};const{ObjectType:$u}=Qu;const ed={objectType:$u.ARRAY_BUFFER,context:null,allocatedGPUMemoryInBytes:0};function td(e,t,n={}){Object.assign(t,ed,n),sn.obj(e,t),sn.get(e,t,["_openGLRenderWindow","allocatedGPUMemoryInBytes"]),sn.moveToProtected(e,t,["openGLRenderWindow"]),function(e,t){function n(e){switch(e){case $u.ELEMENT_ARRAY_BUFFER:return t.context.ELEMENT_ARRAY_BUFFER;case $u.TEXTURE_BUFFER:if("TEXTURE_BUFFER"in t.context)return t.context.TEXTURE_BUFFER;case $u.ARRAY_BUFFER:default:return t.context.ARRAY_BUFFER}}t.classHierarchy.push("vtkOpenGLBufferObject");let 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program.",!1):(t.context.detachShader(t.handle,e.getHandle()),t.vertexShaderHandle=0,t.linked=!1,!0);case"Fragment":return t.fragmentShaderHandle!==e.getHandle()?(t.error="The supplied shader was not attached to this program.",!1):(t.context.detachShader(t.handle,e.getHandle()),t.fragmentShaderHandle=0,t.linked=!1,!0);default:return!1}},e.setContext=e=>{t.context=e,t.vertexShader.setContext(e),t.fragmentShader.setContext(e),t.geometryShader.setContext(e)},e.setLastCameraMTime=e=>{t.lastCameraMTime=e}}(e,t)}var vd={newInstance:sn.newInstance(hd,"vtkShaderProgram"),extend:hd,substitute:function(e,t,n,r){const o="string"==typeof n?n:n.join("\n"),a=!1===r?t:new RegExp(t,"g"),i=e.replace(a,o);return{replace:i!==o,result:i}}};const Td={forceEmulation:!1,handleVAO:0,handleProgram:0,supported:!0,buffers:null,context:null};function xd(e,t,n={}){Object.assign(t,Td,n),t.buffers=[],sn.obj(e,t),sn.get(e,t,["supported"]),sn.setGet(e,t,["forceEmulation"]),function(e,t){t.classHierarchy.push("vtkOpenGLVertexArrayObject"),e.exposedMethod=()=>{},e.initialize=()=>{t.instancingExtension=null,t._openGLRenderWindow.getWebgl2()||(t.instancingExtension=t.context.getExtension("ANGLE_instanced_arrays")),!t.forceEmulation&&t._openGLRenderWindow&&t._openGLRenderWindow.getWebgl2()?(t.extension=null,t.supported=!0,t.handleVAO=t.context.createVertexArray()):(t.extension=t.context.getExtension("OES_vertex_array_object"),!t.forceEmulation&&t.extension?(t.supported=!0,t.handleVAO=t.extension.createVertexArrayOES()):t.supported=!1)},e.isReady=()=>0!==t.handleVAO||!1===t.supported,e.bind=()=>{if(e.isReady()||e.initialize(),e.isReady()&&t.supported)t.extension?t.extension.bindVertexArrayOES(t.handleVAO):t.context.bindVertexArray(t.handleVAO);else if(e.isReady()){const e=t.context;for(let n=0;n<t.buffers.length;++n){const r=t.buffers[n];t.context.bindBuffer(e.ARRAY_BUFFER,r.buffer);for(let n=0;n<r.attributes.length;++n){const o=r.attributes[n],a=o.isMatrix?o.size:1;for(let n=0;n<a;++n)e.enableVertexAttribArray(o.index+n),e.vertexAttribPointer(o.index+n,o.size,o.type,o.normalize,o.stride,o.offset+o.stride*n/o.size),o.divisor>0&&(t.instancingExtension?t.instancingExtension.vertexAttribDivisorANGLE(o.index+n,1):e.vertexAttribDivisor(o.index+n,1))}}}},e.release=()=>{if(e.isReady()&&t.supported)t.extension?t.extension.bindVertexArrayOES(null):t.context.bindVertexArray(null);else if(e.isReady()){const e=t.context;for(let n=0;n<t.buffers.length;++n){const r=t.buffers[n];t.context.bindBuffer(e.ARRAY_BUFFER,r.buffer);for(let n=0;n<r.attributes.length;++n){const o=r.attributes[n],a=o.isMatrix?o.size:1;for(let n=0;n<a;++n)e.enableVertexAttribArray(o.index+n),e.vertexAttribPointer(o.index+n,o.size,o.type,o.normalize,o.stride,o.offset+o.stride*n/o.size),o.divisor>0&&(t.instancingExtension?t.instancingExtension.vertexAttribDivisorANGLE(o.index+n,0):e.vertexAttribDivisor(o.index+n,0)),e.disableVertexAttribArray(o.index+n)}}}},e.shaderProgramChanged=()=>{e.release(),t.handleVAO&&(t.extension?t.extension.deleteVertexArrayOES(t.handleVAO):t.context.deleteVertexArray(t.handleVAO)),t.handleVAO=0,t.handleProgram=0},e.releaseGraphicsResources=()=>{e.shaderProgramChanged(),t.handleVAO&&(t.extension?t.extension.deleteVertexArrayOES(t.handleVAO):t.context.deleteVertexArray(t.handleVAO)),t.handleVAO=0,t.supported=!0,t.handleProgram=0},e.addAttributeArray=(t,n,r,o,a,i,s,l)=>e.addAttributeArrayWithDivisor(t,n,r,o,a,i,s,l,0,!1),e.addAttributeArrayWithDivisor=(n,r,o,a,i,s,l,c,u,d)=>{if(!n)return!1;if(!n.isBound()||0===r.getHandle()||r.getType()!==Zu.ARRAY_BUFFER)return!1;if(0===t.handleProgram&&(t.handleProgram=n.getHandle()),e.isReady()||e.initialize(),!e.isReady()||t.handleProgram!==n.getHandle())return!1;const p=t.context,f={};if(f.name=o,f.index=p.getAttribLocation(t.handleProgram,o),f.offset=a,f.stride=i,f.type=s,f.size=l,f.normalize=c,f.isMatrix=d,f.divisor=u,-1===f.Index)return!1;if(r.bind(),p.enableVertexAttribArray(f.index),p.vertexAttribPointer(f.index,f.size,f.type,f.normalize,f.stride,f.offset),u>0&&(t.instancingExtension?t.instancingExtension.vertexAttribDivisorANGLE(f.index,1):p.vertexAttribDivisor(f.index,1)),f.buffer=r.getHandle(),!t.supported){let e=!1;for(let n=0;n<t.buffers.length;++n){const r=t.buffers[n];if(r.buffer===f.buffer){e=!0;let t=!1;for(let e=0;e<r.attributes.length;++e)r.attributes[e].name===o&&(t=!0,r.attributes[e]=f);t||r.attributes.push(f)}}e||t.buffers.push({buffer:f.buffer,attributes:[f]})}return!0},e.addAttributeMatrixWithDivisor=(n,r,o,a,i,s,l,c,u)=>{const d=e.addAttributeArrayWithDivisor(n,r,o,a,i,s,l,c,u,!0);if(!d)return d;const p=t.context,f=p.getAttribLocation(t.handleProgram,o);for(let e=1;e<l;e++)p.enableVertexAttribArray(f+e),p.vertexAttribPointer(f+e,l,s,c,i,a+i*e/l),u>0&&(t.instancingExtension?t.instancingExtension.vertexAttribDivisorANGLE(f+e,1):p.vertexAttribDivisor(f+e,1));return!0},e.removeAttributeArray=n=>{if(!e.isReady()||0===t.handleProgram)return!1;if(!t.supported)for(let e=0;e<t.buffers.length;++e){const r=t.buffers[e];for(let o=0;o<r.attributes.length;++o)if(r.attributes[o].name===n)return r.attributes.splice(o,1),r.attributes.length||t.buffers.splice(e,1),!0}return!0},e.setOpenGLRenderWindow=n=>{t._openGLRenderWindow!==n&&(e.releaseGraphicsResources(),t._openGLRenderWindow=n,t.context=null,n&&(t.context=t._openGLRenderWindow.getContext()))}}(e,t)}var yd={newInstance:sn.newInstance(xd,"vtkOpenGLVertexArrayObject"),extend:xd};const bd={Start:0,Points:0,Lines:1,Tris:2,TriStrips:3,TrisEdges:4,TriStripsEdges:5,End:6};const Ad={context:null,program:null,shaderSourceTime:null,VAO:null,attributeUpdateTime:null,CABO:null,primitiveType:0,pointPicking:!1};function Cd(e,t,n={}){Object.assign(t,Ad,n),sn.obj(e,t),t.shaderSourceTime={},sn.obj(t.shaderSourceTime),t.attributeUpdateTime={},sn.obj(t.attributeUpdateTime),sn.setGet(e,t,["program","shaderSourceTime","VAO","attributeUpdateTime","CABO","primitiveType","pointPicking"]),t.program=vd.newInstance(),t.VAO=yd.newInstance(),t.CABO=cd.newInstance(),function(e,t){t.classHierarchy.push("vtkOpenGLHelper"),e.setOpenGLRenderWindow=e=>{t.context=e.getContext(),t.program.setContext(t.context),t.VAO.setOpenGLRenderWindow(e),t.CABO.setOpenGLRenderWindow(e)},e.releaseGraphicsResources=e=>{t.VAO.releaseGraphicsResources(),t.CABO.releaseGraphicsResources(),t.CABO.setElementCount(0)},e.drawArrays=(n,r,o,a)=>{if(t.CABO.getElementCount()){const i=e.getOpenGLMode(o),s=e.haveWideLines(n,r),l=t.context,c=l.getParameter(l.DEPTH_WRITEMASK);t.pointPicking&&l.depthMask(!1),i===l.LINES&&s?(e.updateShaders(n,r,a),l.drawArraysInstanced(i,0,t.CABO.getElementCount(),2*Math.ceil(r.getProperty().getLineWidth()))):(l.lineWidth(r.getProperty().getLineWidth()),e.updateShaders(n,r,a),l.drawArrays(i,0,t.CABO.getElementCount()),l.lineWidth(1));const u=(i===l.POINTS?1:0)||(i===l.LINES?2:3);return t.pointPicking&&l.depthMask(c),t.CABO.getElementCount()/u}return 0},e.getOpenGLMode=e=>{if(t.pointPicking)return t.context.POINTS;const n=t.primitiveType;return e===rs.POINTS||n===bd.Points?t.context.POINTS:e===rs.WIREFRAME||n===bd.Lines||n===bd.TrisEdges||n===bd.TriStripsEdges?t.context.LINES:t.context.TRIANGLES},e.haveWideLines=(e,n)=>n.getProperty().getLineWidth()>1&&!(t.CABO.getOpenGLRenderWindow()&&t.CABO.getOpenGLRenderWindow().getHardwareMaximumLineWidth()>=n.getProperty().getLineWidth()),e.getNeedToRebuildShaders=(t,n,r)=>!!(r.getNeedToRebuildShaders(e,t,n)||0===e.getProgram()||e.getShaderSourceTime().getMTime()<r.getMTime()||e.getShaderSourceTime().getMTime()<n.getMTime()),e.updateShaders=(n,r,o)=>{if(e.getNeedToRebuildShaders(n,r,o)){const a={Vertex:null,Fragment:null,Geometry:null};o.buildShaders(a,n,r);const i=t.CABO.getOpenGLRenderWindow().getShaderCache().readyShaderProgramArray(a.Vertex,a.Fragment,a.Geometry);i!==e.getProgram()&&(e.setProgram(i),e.getVAO().releaseGraphicsResources()),e.getShaderSourceTime().modified()}else t.CABO.getOpenGLRenderWindow().getShaderCache().readyShaderProgram(e.getProgram());e.getVAO().bind(),o.setMapperShaderParameters(e,n,r),o.setPropertyShaderParameters(e,n,r),o.setCameraShaderParameters(e,n,r),o.setLightingShaderParameters(e,n,r),o.invokeShaderCallbacks(e,n,r)},e.setMapperShaderParameters=(n,r,o)=>{if(e.haveWideLines(n,r)){e.getProgram().setUniform2f("viewportSize",o.usize,o.vsize);const t=parseFloat(r.getProperty().getLineWidth()),n=t/2;e.getProgram().setUniformf("lineWidthStepSize",t/Math.ceil(t)),e.getProgram().setUniformf("halfLineWidth",n)}t.primitiveType===bd.Points||r.getProperty().getRepresentation()===rs.POINTS?e.getProgram().setUniformf("pointSize",r.getProperty().getPointSize()):t.pointPicking&&e.getProgram().setUniformf("pointSize",e.getPointPickingPrimitiveSize())},e.replaceShaderPositionVC=(n,r,o)=>{let a=n.Vertex;a=vd.substitute(a,"//VTK::PositionVC::Dec",["//VTK::PositionVC::Dec","uniform float pointSize;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Impl",["//VTK::PositionVC::Impl","  gl_PointSize = pointSize;"],!1).result,e.getOpenGLMode(o.getProperty().getRepresentation())===t.context.LINES&&e.haveWideLines(r,o)&&(a=vd.substitute(a,"//VTK::PositionVC::Dec",["//VTK::PositionVC::Dec","uniform vec2 viewportSize;","uniform float lineWidthStepSize;","uniform float halfLineWidth;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Impl",["//VTK::PositionVC::Impl"," if (halfLineWidth > 0.0)","   {","   float offset = float(gl_InstanceID / 2) * lineWidthStepSize - halfLineWidth;","   vec4 tmpPos = gl_Position;","   vec3 tmpPos2 = tmpPos.xyz / tmpPos.w;","   tmpPos2.x = tmpPos2.x + 2.0 * mod(float(gl_InstanceID), 2.0) * offset / viewportSize[0];","   tmpPos2.y = tmpPos2.y + 2.0 * mod(float(gl_InstanceID + 1), 2.0) * offset / viewportSize[1];","   gl_Position = vec4(tmpPos2.xyz * tmpPos.w, tmpPos.w);","   }"]).result),n.Vertex=a},e.getPointPickingPrimitiveSize=()=>t.primitiveType===bd.Points?2:t.primitiveType===bd.Lines?4:6,e.getAllocatedGPUMemoryInBytes=()=>e.getCABO().getAllocatedGPUMemoryInBytes()}(e,t)}var Sd={newInstance:sn.newInstance(Cd),extend:Cd,primTypes:bd};const Pd={CLAMP_TO_EDGE:0,REPEAT:1,MIRRORED_REPEAT:2},wd={NEAREST:0,LINEAR:1,NEAREST_MIPMAP_NEAREST:2,NEAREST_MIPMAP_LINEAR:3,LINEAR_MIPMAP_NEAREST:4,LINEAR_MIPMAP_LINEAR:5};var Id={Wrap:Pd,Filter:wd};const Od=new Float32Array(1),Rd=new Int32Array(Od.buffer);var Md={fromHalf:function(e){const t=(32768&e)>>15,n=(31744&e)>>10,r=1023&e;return 0===n?(t?-1:1)*2**-14*(r/1024):31===n?r?NaN:1/0*(t?-1:1):(t?-1:1)*2**(n-15)*(1+r/1024)},toHalf:function(e){Od[0]=e;const t=Rd[0];let n=t>>16&32768,r=t>>12&2047;const o=t>>23&255;return o<103?n:o>142?(n|=31744,n|=(255===o?0:1)&&8388607&t,n):o<113?(r|=2048,n|=(r>>114-o)+(r>>113-o&1),n):(n|=o-112<<10|r>>1,n+=1&r,n)}};let Dd;function Ed(){return void 0===Dd&&(Dd=function(){try{const e=4,t=2,n=1,r=new Int16Array([0,32767]),o=[1,1],a=document.createElement("canvas");a.width=e,a.height=e;const i=a.getContext("webgl2");if(!i)return!1;const s=i.getExtension("EXT_texture_norm16");if(!s)return!1;const l=`#version 300 es\n    void main() {\n      gl_PointSize = ${e.toFixed(1)};\n      gl_Position = vec4(0, 0, 0, 1);\n    }\n  `,c="#version 300 es\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n\n    uniform sampler2D u_image;\n\n    out vec4 color;\n\n    void main() {\n        vec4 intColor = texture(u_image, gl_PointCoord.xy);\n        color = vec4(vec3(intColor.rrr), 1);\n    }\n    ",u=i.createShader(i.VERTEX_SHADER);if(i.shaderSource(u,l),i.compileShader(u),!i.getShaderParameter(u,i.COMPILE_STATUS))return!1;const d=i.createShader(i.FRAGMENT_SHADER);if(i.shaderSource(d,c),i.compileShader(d),!i.getShaderParameter(d,i.COMPILE_STATUS))return!1;const p=i.createProgram();if(i.attachShader(p,u),i.attachShader(p,d),i.linkProgram(p),!i.getProgramParameter(p,i.LINK_STATUS))return!1;const f=i.createTexture();i.bindTexture(i.TEXTURE_2D,f),i.texImage2D(i.TEXTURE_2D,0,s.R16_SNORM_EXT,t,n,0,i.RED,i.SHORT,r),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MAG_FILTER,i.LINEAR),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MIN_FILTER,i.LINEAR),i.useProgram(p),i.drawArrays(i.POINTS,0,1);const g=new Uint8Array(4);i.readPixels(o[0],o[1],1,1,i.RGBA,i.UNSIGNED_BYTE,g);const[m,h,v]=g,T=i.getExtension("WEBGL_lose_context");return T&&T.loseContext(),m===h&&h===v&&0!==m}catch(e){return!1}}()),Dd}const{Wrap:Vd,Filter:Ld}=Id,{VtkDataTypes:Bd}=Is,{vtkDebugMacro:Fd,vtkErrorMacro:Nd,vtkWarningMacro:kd,requiredParam:Gd}=ln,{toHalf:Ud}=Md;function _d(e,t){function n(){return{internalFormat:t.internalFormat,format:t.format,openGLDataType:t.openGLDataType,width:t.width,height:t.height}}t.classHierarchy.push("vtkOpenGLTexture"),e.render=(n=null)=>{if(n?t._openGLRenderWindow=n:(t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow")),t.context=t._openGLRenderWindow.getContext(),t.renderable.getInterpolate()?(t.generateMipmap?e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR):e.setMinificationFilter(Ld.LINEAR),e.setMagnificationFilter(Ld.LINEAR)):(e.setMinificationFilter(Ld.NEAREST),e.setMagnificationFilter(Ld.NEAREST)),t.renderable.getRepeat()&&(e.setWrapR(Vd.REPEAT),e.setWrapS(Vd.REPEAT),e.setWrapT(Vd.REPEAT)),t.renderable.getInputData()&&t.renderable.setImage(null),!t.handle||t.renderable.getMTime()>t.textureBuildTime.getMTime()){if(null!==t.renderable.getImageBitmap()&&(t.renderable.getInterpolate()&&(t.generateMipmap=!0,e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR)),t.renderable.getImageBitmap()&&t.renderable.getImageLoaded()&&(e.create2DFromImageBitmap(t.renderable.getImageBitmap()),e.activate(),e.sendParameters(),t.textureBuildTime.modified())),null!==t.renderable.getImage()&&(t.renderable.getInterpolate()&&(t.generateMipmap=!0,e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR)),t.renderable.getImage()&&t.renderable.getImageLoaded()&&(e.create2DFromImage(t.renderable.getImage()),e.activate(),e.sendParameters(),t.textureBuildTime.modified())),null!==t.renderable.getCanvas()){t.renderable.getInterpolate()&&(t.generateMipmap=!0,e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR));const n=t.renderable.getCanvas();e.create2DFromRaw({width:n.width,height:n.height,numComps:4,dataType:Bd.UNSIGNED_CHAR,data:n,flip:!0}),e.activate(),e.sendParameters(),t.textureBuildTime.modified()}if(null!==t.renderable.getJsImageData()){const n=t.renderable.getJsImageData();t.renderable.getInterpolate()&&(t.generateMipmap=!0,e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR)),e.create2DFromRaw({width:n.width,height:n.height,numComps:4,dataType:Bd.UNSIGNED_CHAR,data:n.data,flip:!0}),e.activate(),e.sendParameters(),t.textureBuildTime.modified()}const n=t.renderable.getInputData(0);if(n&&n.getPointData().getScalars()){const r=n.getExtent(),o=n.getPointData().getScalars(),a=[];for(let e=0;e<t.renderable.getNumberOfInputPorts();++e){const n=t.renderable.getInputData(e),r=n?n.getPointData().getScalars().getData():null;r&&a.push(r)}t.renderable.getInterpolate()&&4===o.getNumberOfComponents()&&(t.generateMipmap=!0,e.setMinificationFilter(Ld.LINEAR_MIPMAP_LINEAR)),a.length%6==0?e.createCubeFromRaw({width:r[1]-r[0]+1,height:r[3]-r[2]+1,numComps:o.getNumberOfComponents(),dataType:o.getDataType(),data:a}):e.create2DFromRaw({width:r[1]-r[0]+1,height:r[3]-r[2]+1,numComps:o.getNumberOfComponents(),dataType:o.getDataType(),data:o.getData()}),e.activate(),e.sendParameters(),t.textureBuildTime.modified()}}t.handle&&e.activate()};const r=()=>{if(t.minificationFilter!==Ld.LINEAR&&t.magnificationFilter!==Ld.LINEAR||Ed())return t.oglNorm16Ext};function o(e){const[t,n,r,o,a,i]=e;return[n-t+1,o-r+1,i-a+1]}function a(e){const[t,n,r]=o(e);return t*n*r}function i(e,n,r=null){const o=new(r||e.constructor)(n.reduce(((e,t)=>e+a(t)),0)),i=[t.width,t.height,t.depth];let s=0;return n.forEach((t=>{!function(e,t,n,r,o){const[a,i,s,l,c,u]=n,[d,p]=t,f=d*p;let g=o;for(let t=c;t<=u;t++){const n=t*f;for(let t=s;t<=l;t++){const o=n+t*d;for(let t=o+a,n=o+i;t<=n;t++,g++)r[g]=e[t]}}}(e,i,t,o,s),s+=a(t)})),o}function s(e){if(t._openGLRenderWindow.getWebgl2())return e;const n=[],r=t.width,o=t.height,a=t.components;if(e&&(!Fo(r)||!Fo(o))){const i=t.context.getExtension("OES_texture_half_float"),s=Bo(r),l=Bo(o),c=s*l*t.components;for(let u=0;u<e.length;u++)if(null!==e[u]){let d=null;const p=o/l,f=r/s;let g=!1;t.openGLDataType===t.context.FLOAT?d=new Float32Array(c):i&&t.openGLDataType===i.HALF_FLOAT_OES?(d=new Uint16Array(c),g=!0):d=new Uint8Array(c);for(let t=0;t<l;t++){const n=t*s*a,i=t*p;let l=Math.floor(i),c=Math.ceil(i);c>=o&&(c=o-1);const m=i-l,h=1-m;l=l*r*a,c=c*r*a;for(let t=0;t<s;t++){const o=t*a,i=t*f;let s=Math.floor(i),p=Math.ceil(i);p>=r&&(p=r-1);const v=i-s;s*=a,p*=a;for(let t=0;t<a;t++)d[n+o+t]=g?Md.toHalf(Md.fromHalf(e[u][l+s+t])*h*(1-v)+Md.fromHalf(e[u][l+p+t])*h*v+Md.fromHalf(e[u][c+s+t])*m*(1-v)+Md.fromHalf(e[u][c+p+t])*m*v):e[u][l+s+t]*h*(1-v)+e[u][l+p+t]*h*v+e[u][c+s+t]*m*(1-v)+e[u][c+p+t]*m*v}}n.push(d),t.width=s,t.height=l}else n.push(null)}if(0===n.length)for(let t=0;t<e.length;t++)n.push(e[t]);return n}function l(e){if(t._openGLRenderWindow){if(t.resizable||t.renderable?.getResizable())return!1;if(t._openGLRenderWindow.getWebgl2()){return!(t._openGLRenderWindow.getGLInformations().RENDERER.value.match(/WebKit/gi)&&navigator.platform.match(/Mac/gi)&&r())||e!==Bd.UNSIGNED_SHORT&&e!==Bd.SHORT}return!1}return!1}function c(n,r){const o=n.getNumberOfComponents(),a=n.getDataType(),i=n.getData(),s=new Array(o),l=new Array(o);for(let e=0;e<o;++e){const[t,r]=n.getRange(e);s[e]=t,l[e]=r}const c=function(e,t,n){const r=new Array(n),o=new Array(n);for(let a=0;a<n;++a)r[a]=e[a],o[a]=t[a]-e[a]||1;return{scale:o,offset:r}}(s,l,o);return function(n,r,o,a){e.getOpenGLDataType(n);const i=function(e,t){for(let n=0;n<e.length;n++){const r=e[n],o=t[n]+r;if(r<-2048||r>2048||o<-2048||o>2048)return!1}return!0}(r,o)||a;let s=!1;if(t._openGLRenderWindow.getWebgl2())s=t.openGLDataType===t.context.FLOAT&&null===t.context.getExtension("OES_texture_float_linear")&&i||t.openGLDataType===t.context.HALF_FLOAT;else{const e=t.context.getExtension("OES_texture_half_float");s=e&&t.openGLDataType===e.HALF_FLOAT_OES}t.canUseHalfFloat=s&&i}(a,c.offset,c.scale,r),e.useHalfFloat()||e.getOpenGLDataType(a,!0),{numComps:o,dataType:a,data:i,scaleOffsets:c}}e.destroyTexture=()=>{e.deactivate(),t.context&&t.handle&&t.context.deleteTexture(t.handle),t._prevTexParams=null,t.handle=0,t.numberOfDimensions=0,t.target=0,t.components=0,t.width=0,t.height=0,t.depth=0,e.resetFormatAndType()},e.createTexture=()=>{t.handle||(t.handle=t.context.createTexture(),t.target&&(t.context.bindTexture(t.target,t.handle),t.context.texParameteri(t.target,t.context.TEXTURE_MIN_FILTER,e.getOpenGLFilterMode(t.minificationFilter)),t.context.texParameteri(t.target,t.context.TEXTURE_MAG_FILTER,e.getOpenGLFilterMode(t.magnificationFilter)),t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_S,e.getOpenGLWrapMode(t.wrapS)),t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_T,e.getOpenGLWrapMode(t.wrapT)),t._openGLRenderWindow.getWebgl2()&&t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_R,e.getOpenGLWrapMode(t.wrapR)),t.context.bindTexture(t.target,null)))},e.getTextureUnit=()=>t._openGLRenderWindow?t._openGLRenderWindow.getTextureUnitForTexture(e):-1,e.activate=()=>{t._openGLRenderWindow.activateTexture(e),e.bind()},e.deactivate=()=>{t._openGLRenderWindow&&t._openGLRenderWindow.deactivateTexture(e)},e.releaseGraphicsResources=n=>{n&&t.handle&&(n.activateTexture(e),n.deactivateTexture(e),t.context.deleteTexture(t.handle),t._prevTexParams=null,t.handle=0,t.numberOfDimensions=0,t.target=0,t.internalFormat=0,t.format=0,t.openGLDataType=0,t.components=0,t.width=0,t.height=0,t.depth=0,t.allocatedGPUMemoryInBytes=0),t.shaderProgram&&(t.shaderProgram.releaseGraphicsResources(n),t.shaderProgram=null)},e.bind=()=>{t.context.bindTexture(t.target,t.handle),t.autoParameters&&e.getMTime()>t.sendParametersTime.getMTime()&&e.sendParameters()},e.isBound=()=>{let e=!1;if(t.context&&t.handle){let n=0;if(t.target===t.context.TEXTURE_2D)n=t.context.TEXTURE_BINDING_2D;else kd("impossible case");e=t.context.getIntegerv(n)===t.handle}return e},e.sendParameters=()=>{t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_S,e.getOpenGLWrapMode(t.wrapS)),t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_T,e.getOpenGLWrapMode(t.wrapT)),t._openGLRenderWindow.getWebgl2()&&t.context.texParameteri(t.target,t.context.TEXTURE_WRAP_R,e.getOpenGLWrapMode(t.wrapR)),t.context.texParameteri(t.target,t.context.TEXTURE_MIN_FILTER,e.getOpenGLFilterMode(t.minificationFilter)),t.context.texParameteri(t.target,t.context.TEXTURE_MAG_FILTER,e.getOpenGLFilterMode(t.magnificationFilter)),t._openGLRenderWindow.getWebgl2()&&(t.context.texParameteri(t.target,t.context.TEXTURE_BASE_LEVEL,t.baseLevel),t.context.texParameteri(t.target,t.context.TEXTURE_MAX_LEVEL,t.maxLevel)),t.sendParametersTime.modified()},e.getInternalFormat=(n,r)=>(t._forceInternalFormat||(t.internalFormat=e.getDefaultInternalFormat(n,r)),t.internalFormat||Fd(`Unable to find suitable internal format for T=${n} NC= 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Texture filtering is not available for *32F internal formats."),t.internalFormat),e.getDefaultInternalFormat=(n,o)=>{let a=0;return a=t._openGLRenderWindow.getDefaultTextureInternalFormat(n,o,r(),e.useHalfFloat()),a||(a||(Fd("Unsupported internal texture type!"),Fd(`Unable to find suitable internal format for T=${n} NC= ${o}`)),a)},e.useHalfFloat=()=>t.enableUseHalfFloat&&t.canUseHalfFloat,e.setInternalFormat=n=>{t._forceInternalFormat=!0,n!==t.internalFormat&&(t.internalFormat=n,e.modified())},e.getFormat=(n,r)=>(t.format=e.getDefaultFormat(n,r),t.format),e.getDefaultFormat=(e,n)=>{if(t._openGLRenderWindow.getWebgl2())switch(n){case 1:return t.context.RED;case 2:return t.context.RG;case 3:default:return t.context.RGB;case 4:return t.context.RGBA}else switch(n){case 1:return t.context.LUMINANCE;case 2:return t.context.LUMINANCE_ALPHA;case 3:default:return t.context.RGB;case 4:return t.context.RGBA}},e.resetFormatAndType=()=>{t._prevTexParams=null,t.format=0,t.internalFormat=0,t._forceInternalFormat=!1,t.openGLDataType=0},e.getDefaultDataType=n=>{const o=e.useHalfFloat();if(t._openGLRenderWindow.getWebgl2())switch(n){case Bd.UNSIGNED_CHAR:return t.context.UNSIGNED_BYTE;case r()&&!o&&Bd.SHORT:return t.context.SHORT;case r()&&!o&&Bd.UNSIGNED_SHORT:return t.context.UNSIGNED_SHORT;case o&&Bd.SHORT:case o&&Bd.UNSIGNED_SHORT:return t.context.HALF_FLOAT;case Bd.FLOAT:case Bd.VOID:default:return t.context.FLOAT}switch(n){case Bd.UNSIGNED_CHAR:return t.context.UNSIGNED_BYTE;case Bd.FLOAT:case Bd.VOID:default:if(t.context.getExtension("OES_texture_float")&&t.context.getExtension("OES_texture_float_linear"))return t.context.FLOAT;{const e=t.context.getExtension("OES_texture_half_float");if(e&&t.context.getExtension("OES_texture_half_float_linear"))return e.HALF_FLOAT_OES}return t.context.UNSIGNED_BYTE}},e.getOpenGLDataType=(n,r=!1)=>(t.openGLDataType&&!r||(t.openGLDataType=e.getDefaultDataType(n)),t.openGLDataType),e.getShiftAndScale=()=>{let e=0,n=1;switch(t.openGLDataType){case t.context.BYTE:n=127.5,e=n-128;break;case t.context.UNSIGNED_BYTE:n=255,e=0;break;case t.context.SHORT:n=32767.5,e=n-32768;break;case t.context.UNSIGNED_SHORT:n=65536,e=0;break;case t.context.INT:n=2147483647.5,e=n-2147483648;break;case t.context.UNSIGNED_INT:n=4294967295,e=0;case t.context.FLOAT:}return{shift:e,scale:n}},e.getOpenGLFilterMode=e=>{switch(e){case Ld.NEAREST:return t.context.NEAREST;case Ld.LINEAR:return t.context.LINEAR;case Ld.NEAREST_MIPMAP_NEAREST:return t.context.NEAREST_MIPMAP_NEAREST;case Ld.NEAREST_MIPMAP_LINEAR:return t.context.NEAREST_MIPMAP_LINEAR;case Ld.LINEAR_MIPMAP_NEAREST:return t.context.LINEAR_MIPMAP_NEAREST;case Ld.LINEAR_MIPMAP_LINEAR:return t.context.LINEAR_MIPMAP_LINEAR;default:return t.context.NEAREST}},e.getOpenGLWrapMode=e=>{switch(e){case Vd.CLAMP_TO_EDGE:return t.context.CLAMP_TO_EDGE;case Vd.REPEAT:return t.context.REPEAT;case Vd.MIRRORED_REPEAT:return t.context.MIRRORED_REPEAT;default:return t.context.CLAMP_TO_EDGE}},e.updateArrayDataTypeForGL=(e,n,r=!1,o=[])=>{const a=[];let s=t.width*t.height*t.components;r&&(s*=t.depth);const l=!!o.length;if(e!==Bd.FLOAT&&t.openGLDataType===t.context.FLOAT)for(let e=0;e<n.length;e++)if(n[e])if(l)a.push(i(n[e],o,Float32Array));else{const t=n[e].length>s?n[e].subarray(0,s):n[e];a.push(new Float32Array(t))}else a.push(null);if(e!==Bd.UNSIGNED_CHAR&&t.openGLDataType===t.context.UNSIGNED_BYTE)for(let e=0;e<n.length;e++)if(n[e])if(l)a.push(i(n[e],o,Uint8Array));else{const t=n[e].length>s?n[e].subarray(0,s):n[e];a.push(new Uint8Array(t))}else a.push(null);let c=!1;if(t._openGLRenderWindow.getWebgl2())c=t.openGLDataType===t.context.HALF_FLOAT;else{const e=t.context.getExtension("OES_texture_half_float");c=e&&t.openGLDataType===e.HALF_FLOAT_OES}if(c)for(let e=0;e<n.length;e++)if(n[e]){const t=l?i(n[e],o):n[e],r=new Uint16Array(l?t.length:s),c=r.length;for(let e=0;e<c;e++)r[e]=Ud(t[e]);a.push(r)}else a.push(null);if(0===a.length)for(let e=0;e<n.length;e++)a.push(l&&n[e]?i(n[e],o):n[e]);return a},e.create2DFromRaw=({width:n=Gd("width"),height:o=Gd("height"),numComps:a=Gd("numComps"),dataType:i=Gd("dataType"),data:c=Gd("data"),flip:u=!1}={})=>{if(e.getOpenGLDataType(i,!0),e.getInternalFormat(i,a),e.getFormat(i,a),!t.internalFormat||!t.format||!t.openGLDataType)return Nd("Failed to determine texture parameters."),!1;t.target=t.context.TEXTURE_2D,t.components=a,t.width=n,t.height=o,t.depth=1,t.numberOfDimensions=2,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind();const d=[c],p=s(e.updateArrayDataTypeForGL(i,d));return t.context.pixelStorei(t.context.UNPACK_FLIP_Y_WEBGL,u),t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),l(i)?(t.context.texStorage2D(t.target,1,t.internalFormat,t.width,t.height),null!=p[0]&&t.context.texSubImage2D(t.target,0,0,0,t.width,t.height,t.format,t.openGLDataType,p[0])):t.context.texImage2D(t.target,0,t.internalFormat,t.width,t.height,0,t.format,t.openGLDataType,p[0]),t.generateMipmap&&t.context.generateMipmap(t.target),u&&t.context.pixelStorei(t.context.UNPACK_FLIP_Y_WEBGL,!1),t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*a*t._openGLRenderWindow.getDefaultTextureByteSize(i,r(),e.useHalfFloat()),e.deactivate(),!0},e.createCubeFromRaw=({width:n=Gd("width"),height:o=Gd("height"),numComps:a=Gd("numComps"),dataType:i=Gd("dataType"),data:c=Gd("data")}={})=>{if(e.getOpenGLDataType(i),e.getInternalFormat(i,a),e.getFormat(i,a),!t.internalFormat||!t.format||!t.openGLDataType)return Nd("Failed to determine texture parameters."),!1;t.target=t.context.TEXTURE_CUBE_MAP,t.components=a,t.width=n,t.height=o,t.depth=1,t.numberOfDimensions=2,t._openGLRenderWindow.activateTexture(e),t.maxLevel=c.length/6-1,e.createTexture(),e.bind();const u=s(e.updateArrayDataTypeForGL(i,c)),d=[];let p=t.width,f=t.height;for(let e=0;e<u.length;e++){e%6==0&&0!==e&&(p/=2,f/=2),d[e]=Ct(i,f*p*t.components);for(let n=0;n<f;++n){const r=n*p*t.components,o=(f-n-1)*p*t.components;d[e].set(u[e].slice(o,o+p*t.components),r)}}t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),l(i)&&t.context.texStorage2D(t.target,6,t.internalFormat,t.width,t.height);for(let e=0;e<6;e++){let n=0,r=t.width,o=t.height;for(;r>=1&&o>=1;){let a=null;n<=t.maxLevel&&(a=d[6*n+e]),l(i)?null!=a&&t.context.texSubImage2D(t.context.TEXTURE_CUBE_MAP_POSITIVE_X+e,n,0,0,r,o,t.format,t.openGLDataType,a):t.context.texImage2D(t.context.TEXTURE_CUBE_MAP_POSITIVE_X+e,n,t.internalFormat,r,o,0,t.format,t.openGLDataType,a),n++,r/=2,o/=2}}return t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*a*t._openGLRenderWindow.getDefaultTextureByteSize(i,r(),e.useHalfFloat()),e.deactivate(),!0},e.createDepthFromRaw=({width:n=Gd("width"),height:o=Gd("height"),dataType:a=Gd("dataType"),data:i=Gd("data")}={})=>(e.getOpenGLDataType(a),t.format=t.context.DEPTH_COMPONENT,t._openGLRenderWindow.getWebgl2()?a===Bd.FLOAT?t.internalFormat=t.context.DEPTH_COMPONENT32F:t.internalFormat=t.context.DEPTH_COMPONENT16:t.internalFormat=t.context.DEPTH_COMPONENT,t.internalFormat&&t.format&&t.openGLDataType?(t.target=t.context.TEXTURE_2D,t.components=1,t.width=n,t.height=o,t.depth=1,t.numberOfDimensions=2,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind(),t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),l(a)?(t.context.texStorage2D(t.target,1,t.internalFormat,t.width,t.height),null!=i&&t.context.texSubImage2D(t.target,0,0,0,t.width,t.height,t.format,t.openGLDataType,i)):t.context.texImage2D(t.target,0,t.internalFormat,t.width,t.height,0,t.format,t.openGLDataType,i),t.generateMipmap&&t.context.generateMipmap(t.target),t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*t.components*t._openGLRenderWindow.getDefaultTextureByteSize(a,r(),e.useHalfFloat()),e.deactivate(),!0):(Nd("Failed to determine texture parameters."),!1)),e.create2DFromImage=n=>{if(e.getOpenGLDataType(Bd.UNSIGNED_CHAR),e.getInternalFormat(Bd.UNSIGNED_CHAR,4),e.getFormat(Bd.UNSIGNED_CHAR,4),!t.internalFormat||!t.format||!t.openGLDataType)return Nd("Failed to determine texture parameters."),!1;t.target=t.context.TEXTURE_2D,t.components=4,t.depth=1,t.numberOfDimensions=2,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind();const o=!(t._openGLRenderWindow.getWebgl2()||Fo(n.width)&&Fo(n.height));let a=n,i=n.width,s=n.height,c=!0;const u=window.chrome;if(o||u){const e=new OffscreenCanvas(Bo(n.width),Bo(n.height));i=e.width,s=e.height;const t=e.getContext("2d");t.translate(0,e.height),t.scale(1,-1),t.drawImage(n,0,0,n.width,n.height,0,0,e.width,e.height),a=e,c=!1}return t.width=i,t.height=s,t.context.pixelStorei(t.context.UNPACK_FLIP_Y_WEBGL,c),t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),l(Bd.UNSIGNED_CHAR)?(t.context.texStorage2D(t.target,1,t.internalFormat,t.width,t.height),t.context.texSubImage2D(t.target,0,0,0,t.width,t.height,t.format,t.openGLDataType,a)):t.context.texImage2D(t.target,0,t.internalFormat,t.width,t.height,0,t.format,t.openGLDataType,a),t.generateMipmap&&t.context.generateMipmap(t.target),t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*t.components*t._openGLRenderWindow.getDefaultTextureByteSize(Bd.UNSIGNED_CHAR,r(),e.useHalfFloat()),e.deactivate(),!0},e.create2DFromImageBitmap=n=>(e.getOpenGLDataType(Bd.UNSIGNED_CHAR),e.getInternalFormat(Bd.UNSIGNED_CHAR,4),e.getFormat(Bd.UNSIGNED_CHAR,4),t.internalFormat&&t.format&&t.openGLDataType?(t.target=t.context.TEXTURE_2D,t.components=4,t.depth=1,t.numberOfDimensions=2,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind(),t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),t.width=n.width,t.height=n.height,l(Bd.UNSIGNED_CHAR)?(t.context.texStorage2D(t.target,1,t.internalFormat,t.width,t.height),t.context.texSubImage2D(t.target,0,0,0,t.width,t.height,t.format,t.openGLDataType,n)):t.context.texImage2D(t.target,0,t.internalFormat,t.width,t.height,0,t.format,t.openGLDataType,n),t.generateMipmap&&t.context.generateMipmap(t.target),t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*t.components*t._openGLRenderWindow.getDefaultTextureByteSize(Bd.UNSIGNED_CHAR,r(),e.useHalfFloat()),e.deactivate(),!0):(Nd("Failed to determine texture parameters."),!1)),e.create2DFilterableFromRaw=({width:t=Gd("width"),height:n=Gd("height"),numComps:r=Gd("numComps"),dataType:o=Gd("dataType"),data:a=Gd("data"),preferSizeOverAccuracy:i=!1,ranges:s}={})=>e.create2DFilterableFromDataArray({width:t,height:n,dataArray:Is.newInstance({numberOfComponents:r,dataType:o,values:a,ranges:s}),preferSizeOverAccuracy:i}),e.create2DFilterableFromDataArray=({width:t=Gd("width"),height:n=Gd("height"),dataArray:r=Gd("dataArray"),preferSizeOverAccuracy:o=!1}={})=>{const{numComps:a,dataType:i,data:s}=c(r,o);e.create2DFromRaw({width:t,height:n,numComps:a,dataType:i,data:s})},e.updateVolumeInfoForGL=(n,o)=>{let a=!1;const i=e.useHalfFloat();t.volumeInfo?.scale&&t.volumeInfo?.offset||(t.volumeInfo={scale:new Array(o),offset:new Array(o)});for(let e=0;e<o;++e)t.volumeInfo.scale[e]=1,t.volumeInfo.offset[e]=0;if(r()&&!i&&n===Bd.SHORT){for(let e=0;e<o;++e)t.volumeInfo.scale[e]=32767;a=!0}if(r()&&!i&&n===Bd.UNSIGNED_SHORT){for(let e=0;e<o;++e)t.volumeInfo.scale[e]=65535;a=!0}if(n===Bd.UNSIGNED_CHAR){for(let e=0;e<o;++e)t.volumeInfo.scale[e]=255;a=!0}return(n===Bd.FLOAT||i&&(n===Bd.SHORT||n===Bd.UNSIGNED_SHORT))&&(a=!0),a},e.create3DFromRaw=({width:i=Gd("width"),height:c=Gd("height"),depth:u=Gd("depth"),numComps:d=Gd("numComps"),dataType:p=Gd("dataType"),data:f=Gd("data"),updatedExtents:g=[]}={})=>{let m=p,h=f;if(!e.updateVolumeInfoForGL(m,d)&&h){const e=i*c*u,n=structuredClone(t.volumeInfo),r=new Float32Array(e*d);t.volumeInfo.offset=n.offset,t.volumeInfo.scale=n.scale;let o=0;const a=n.scale.map((e=>1/e));for(let t=0;t<e;t++)for(let e=0;e<d;e++)r[o]=(h[o]-n.offset[e])*a[e],o++;m=Bd.FLOAT,h=r}if(e.getOpenGLDataType(m),e.getInternalFormat(m,d),e.getFormat(m,d),!t.internalFormat||!t.format||!t.openGLDataType)return Nd("Failed to determine texture parameters."),!1;t.target=t.context.TEXTURE_3D,t.components=d,t.width=i,t.height=c,t.depth=u,t.numberOfDimensions=3,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind();const v=g.length>0,T=!v||!xe(t._prevTexParams,n()),x=[h],y=s(e.updateArrayDataTypeForGL(m,x,!0,T?[]:g));if(t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),T)l(m)?(t.context.texStorage3D(t.target,1,t.internalFormat,t.width,t.height,t.depth),null!=y[0]&&t.context.texSubImage3D(t.target,0,0,0,0,t.width,t.height,t.depth,t.format,t.openGLDataType,y[0])):t.context.texImage3D(t.target,0,t.internalFormat,t.width,t.height,t.depth,0,t.format,t.openGLDataType,y[0]),t._prevTexParams=n();else if(v){const e=y[0];let n=0;for(let r=0;r<g.length;r++){const i=g[r],s=o(i),l=a(i),c=new e.constructor(e.buffer,n,l);n+=c.byteLength,t.context.texSubImage3D(t.target,0,i[0],i[2],i[4],s[0],s[1],s[2],t.format,t.openGLDataType,c)}}return t.generateMipmap&&t.context.generateMipmap(t.target),t.allocatedGPUMemoryInBytes=t.width*t.height*t.depth*t.components*t._openGLRenderWindow.getDefaultTextureByteSize(m,r(),e.useHalfFloat()),e.deactivate(),!0},e.create3DFilterableFromRaw=({width:t=Gd("width"),height:n=Gd("height"),depth:r=Gd("depth"),numComps:o=Gd("numComps"),dataType:a=Gd("dataType"),data:i=Gd("data"),preferSizeOverAccuracy:s=!1,ranges:l,updatedExtents:c=[]}={})=>e.create3DFilterableFromDataArray({width:t,height:n,depth:r,dataArray:Is.newInstance({numberOfComponents:o,dataType:a,values:i,ranges:l}),preferSizeOverAccuracy:s,updatedExtents:c}),e.create3DFilterableFromDataArray=({width:n=Gd("width"),height:r=Gd("height"),depth:o=Gd("depth"),dataArray:a=Gd("dataArray"),preferSizeOverAccuracy:i=!1,updatedExtents:s=[]}={})=>{const{numComps:u,dataType:d,data:p,scaleOffsets:f}=c(a,i),g=[],m=[];for(let e=0;e<u;++e)g[e]=0,m[e]=1;if(t.volumeInfo={scale:m,offset:g,dataComputedScale:f.scale,dataComputedOffset:f.offset,width:n,height:r,depth:o},t._openGLRenderWindow.getWebgl2())return e.create3DFromRaw({width:n,height:r,depth:o,numComps:u,dataType:d,data:p,updatedExtents:s});const h=n*r*o,v=structuredClone(f);let T=(e,t,n,r,o)=>{e[t]=n},x=Bd.UNSIGNED_CHAR;if(d===Bd.UNSIGNED_CHAR)for(let e=0;e<u;++e)v.offset[e]=0,v.scale[e]=255;else t.context.getExtension("OES_texture_float")&&t.context.getExtension("OES_texture_float_linear")?(x=Bd.FLOAT,T=(e,t,n,r,o)=>{e[t]=(n-r)/o}):(x=Bd.UNSIGNED_CHAR,T=(e,t,n,r,o)=>{e[t]=255*(n-r)/o});if(e.getOpenGLDataType(x),e.getInternalFormat(x,u),e.getFormat(x,u),!t.internalFormat||!t.format||!t.openGLDataType)return Nd("Failed to determine texture parameters."),!1;t.target=t.context.TEXTURE_2D,t.components=u,t.depth=1,t.numberOfDimensions=2;let y=t.context.getParameter(t.context.MAX_TEXTURE_SIZE);y>4096&&(x===Bd.FLOAT||u>=3)&&(y=4096);let b=1,A=1;h>y*y&&(b=Math.ceil(Math.sqrt(h/(y*y))),A=b);let C=Math.sqrt(h)/b;C=Bo(C);const S=Math.floor(C*b/n),P=Math.ceil(o/S),w=Bo(r*P/A);let I;t.width=C,t.height=w,t._openGLRenderWindow.activateTexture(e),e.createTexture(),e.bind(),t.volumeInfo.xreps=S,t.volumeInfo.yreps=P,t.volumeInfo.xstride=b,t.volumeInfo.ystride=A,t.volumeInfo.offset=v.offset,t.volumeInfo.scale=v.scale;const O=C*w*u;I=x===Bd.FLOAT?new Float32Array(O):new Uint8Array(O);let R=0;const M=Math.floor(n/b),D=Math.floor(r/A);for(let e=0;e<P;e++){const a=Math.min(S,o-e*S),i=u*(t.width-a*Math.floor(n/b));for(let t=0;t<D;t++){for(let o=0;o<a;o++){const a=u*((e*S+o)*n*r+A*t*n);for(let e=0;e<M;e++)for(let t=0;t<u;t++)T(I,R,p[a+b*e*u+t],v.offset[t],v.scale[t]),R++}R+=i}}return t.context.pixelStorei(t.context.UNPACK_ALIGNMENT,1),l(x)?(t.context.texStorage2D(t.target,1,t.internalFormat,t.width,t.height),null!=I&&t.context.texSubImage2D(t.target,0,0,0,t.width,t.height,t.format,t.openGLDataType,I)):t.context.texImage2D(t.target,0,t.internalFormat,t.width,t.height,0,t.format,t.openGLDataType,I),e.deactivate(),!0},e.setOpenGLRenderWindow=n=>{t._openGLRenderWindow!==n&&(e.releaseGraphicsResources(),t._openGLRenderWindow=n,t.context=null,n&&(t.context=t._openGLRenderWindow.getContext()))},e.getMaximumTextureSize=e=>e&&e.isCurrent()?e.getIntegerv(e.MAX_TEXTURE_SIZE):-1,e.enableUseHalfFloat=e=>{t.enableUseHalfFloat=e}}const Kd={_openGLRenderWindow:null,_forceInternalFormat:!1,_prevTexParams:null,context:null,handle:0,sendParametersTime:null,textureBuildTime:null,numberOfDimensions:0,target:0,format:0,openGLDataType:0,components:0,width:0,height:0,depth:0,autoParameters:!0,wrapS:Vd.CLAMP_TO_EDGE,wrapT:Vd.CLAMP_TO_EDGE,wrapR:Vd.CLAMP_TO_EDGE,minificationFilter:Ld.NEAREST,magnificationFilter:Ld.NEAREST,minLOD:-1e3,maxLOD:1e3,baseLevel:0,maxLevel:1e3,generateMipmap:!1,oglNorm16Ext:null,allocatedGPUMemoryInBytes:0,enableUseHalfFloat:!0,canUseHalfFloat:!1};function zd(e,t,n={}){Object.assign(t,Kd,n),pn.extend(e,t,n),t.sendParametersTime={},Vt(t.sendParametersTime,{mtime:0}),t.textureBuildTime={},Vt(t.textureBuildTime,{mtime:0}),kt(e,t,["format","openGLDataType"]),Gt(e,t,["keyMatrixTime","minificationFilter","magnificationFilter","wrapS","wrapT","wrapR","generateMipmap","oglNorm16Ext"]),Bt(e,t,["width","height","volumeInfo","components","handle","target","allocatedGPUMemoryInBytes"]),zt(0,t,["openGLRenderWindow"]),_d(e,t)}const Wd=Xt(zd,"vtkOpenGLTexture");var Hd={newInstance:Wd,extend:zd,...Id};vn("vtkTexture",Wd);var jd="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkPolyDataVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\nattribute vec4 vertexMC;\n\n// frag position in VC\n//VTK::PositionVC::Dec\n\n// optional normal declaration\n//VTK::Normal::Dec\n\n// extra lighting parameters\n//VTK::Light::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// material property values\n//VTK::Color::Dec\n\n// clipping plane vars\n//VTK::Clip::Dec\n\n// camera and actor matrix values\n//VTK::Camera::Dec\n\n// Apple Bug\n//VTK::PrimID::Dec\n\n// picking support\n//VTK::Picking::Dec\n\nvoid main()\n{\n  //VTK::Color::Impl\n\n  //VTK::Normal::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Clip::Impl\n\n  //VTK::PrimID::Impl\n\n  //VTK::PositionVC::Impl\n\n  //VTK::Light::Impl\n\n  //VTK::Picking::Impl\n}\n",Xd="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkPolyDataFS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n// Template for the polydata mappers fragment shader\n\nuniform int PrimitiveIDOffset;\n\n// VC position of this fragment\n//VTK::PositionVC::Dec\n\n// optional color passed in from the vertex shader, vertexColor\n//VTK::Color::Dec\n\n// optional surface normal declaration\n//VTK::Normal::Dec\n\n// extra lighting parameters\n//VTK::Light::Dec\n\n// define vtkImageLabelOutlineOn\n//VTK::ImageLabelOutlineOn\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// picking support\n//VTK::Picking::Dec\n\n// Depth Peeling Support\n//VTK::DepthPeeling::Dec\n\n// clipping plane vars\n//VTK::Clip::Dec\n\n// label outline \n//VTK::LabelOutline::Dec\n\n// the output of this shader\n//VTK::Output::Dec\n\n// Apple Bug\n//VTK::PrimID::Dec\n\n// handle coincident offsets\n//VTK::Coincident::Dec\n\n//VTK::ZBuffer::Dec\n\n//VTK::LabelOutlineHelperFunction\n\nvoid main()\n{\n  // VC position of this fragment. This should not branch/return/discard.\n  //VTK::PositionVC::Impl\n\n  // Place any calls that require uniform flow (e.g. dFdx) here.\n  //VTK::UniformFlow::Impl\n\n  // Set gl_FragDepth here (gl_FragCoord.z by default)\n  //VTK::Depth::Impl\n\n  // Early depth peeling abort:\n  //VTK::DepthPeeling::PreColor\n\n  // Apple Bug\n  //VTK::PrimID::Impl\n\n  //VTK::Clip::Impl\n\n  //VTK::Color::Impl\n\n  // Generate the normal if we are not passed in one\n  //VTK::Normal::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Light::Impl\n\n  if (gl_FragData[0].a <= 0.0)\n    {\n    discard;\n    }\n\n  //VTK::DepthPeeling::Impl\n\n  //VTK::Picking::Impl\n\n  // handle coincident offsets\n  //VTK::Coincident::Impl\n\n  //VTK::ZBuffer::Impl\n\n  //VTK::RenderPassFragmentShader::Impl\n}\n";var qd={implementReplaceShaderCoincidentOffset:function(e,t,n={}){e.replaceShaderCoincidentOffset=(n,r,o)=>{const a=e.getCoincidentParameters(r,o);if(a&&(0!==a.factor||0!==a.offset)){let e=n.Fragment;e=vd.substitute(e,"//VTK::Coincident::Dec",["uniform float cfactor;","uniform float coffset;"]).result,t.context.getExtension("EXT_frag_depth")&&(0!==a.factor?(e=vd.substitute(e,"//VTK::UniformFlow::Impl",["float cscale = length(vec2(dFdx(gl_FragCoord.z),dFdy(gl_FragCoord.z)));","//VTK::UniformFlow::Impl"],!1).result,e=vd.substitute(e,"//VTK::Depth::Impl","gl_FragDepthEXT = gl_FragCoord.z + cfactor*cscale + 0.000016*coffset;").result):e=vd.substitute(e,"//VTK::Depth::Impl","gl_FragDepthEXT = gl_FragCoord.z + 0.000016*coffset;").result),t._openGLRenderWindow.getWebgl2()&&(0!==a.factor?(e=vd.substitute(e,"//VTK::UniformFlow::Impl",["float cscale = length(vec2(dFdx(gl_FragCoord.z),dFdy(gl_FragCoord.z)));","//VTK::UniformFlow::Impl"],!1).result,e=vd.substitute(e,"//VTK::Depth::Impl","gl_FragDepth = gl_FragCoord.z + cfactor*cscale + 0.000016*coffset;").result):e=vd.substitute(e,"//VTK::Depth::Impl","gl_FragDepth = gl_FragCoord.z + 0.000016*coffset;").result),n.Fragment=e}}},implementBuildShadersWithReplacements:function(e,t,n={}){e.applyShaderReplacements=(e,t,n)=>{let r=null;if(t&&(r=t.ShaderReplacements),r)for(let t=0;t<r.length;t++){const o=r[t];if(n&&o.replaceFirst||!n&&!o.replaceFirst){const t=o.shaderType,n=e[t],r=vd.substitute(n,o.originalValue,o.replacementValue,o.replaceAll);e[t]=r.result}}},e.buildShaders=(n,r,o)=>{e.getReplacedShaderTemplate(n,r,o),t.lastRenderPassShaderReplacement=t.currentRenderPass?t.currentRenderPass.getShaderReplacement():null,t.lastRenderPassShaderReplacement&&t.lastRenderPassShaderReplacement(n);const a=t.renderable.getViewSpecificProperties().OpenGL;e.applyShaderReplacements(n,a,!0),e.replaceShaderValues(n,r,o),e.applyShaderReplacements(n,a)},e.getReplacedShaderTemplate=(n,r,o)=>{const a=t.renderable.getViewSpecificProperties().OpenGL;e.getShaderTemplate(n,r,o);let i=n.Vertex;if(a){const e=a.VertexShaderCode;void 0!==e&&""!==e&&(i=e)}n.Vertex=i;let s=n.Fragment;if(a){const e=a.FragmentShaderCode;void 0!==e&&""!==e&&(s=e)}n.Fragment=s;let l=n.Geometry;if(a){const e=a.GeometryShaderCode;void 0!==e&&(l=e)}n.Geometry=l}}};const{FieldAssociations:Yd}=Qs,{primTypes:Jd}=Sd,{Representation:Zd,Shading:Qd}=us,{ScalarMode:$d}=Ql,{Filter:ep,Wrap:tp}=Hd,{vtkErrorMacro:np}=ln,rp={type:"StartEvent"},op={type:"EndEvent"},{CoordinateSystem:ap}=Zi;function ip(e,t){function n(e,t,n){return t.identity(n),e.reduce(((e,n,r)=>0===r?n?t.copy(e,n):t.identity(e):n?t.multiply(e,e,n):e),n)}t.classHierarchy.push("vtkOpenGLPolyDataMapper"),e.buildPass=n=>{n&&(t.currentRenderPass=null,t.openGLActor=e.getFirstAncestorOfType("vtkOpenGLActor"),t._openGLRenderer=t.openGLActor.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow"),t.openGLCamera=t._openGLRenderer.getViewNodeFor(t._openGLRenderer.getRenderable().getActiveCamera(),t.openGLCamera))},e.translucentPass=(n,r)=>{n&&(t.currentRenderPass=r,e.render())},e.zBufferPass=n=>{n&&(t.haveSeenDepthRequest=!0,t.renderDepth=!0,e.render(),t.renderDepth=!1)},e.opaqueZBufferPass=t=>e.zBufferPass(t),e.opaquePass=t=>{t&&e.render()},e.render=()=>{const n=t._openGLRenderWindow.getContext();if(t.context!==n){t.context=n;for(let e=Jd.Start;e<Jd.End;e++)t.primitives[e].setOpenGLRenderWindow(t._openGLRenderWindow)}const r=t.openGLActor.getRenderable(),o=t._openGLRenderer.getRenderable();e.renderPiece(o,r)},e.getShaderTemplate=(e,t,n)=>{e.Vertex=jd,e.Fragment=Xd,e.Geometry=""},e.replaceShaderColor=(e,n,r)=>{let o=e.Vertex,a=e.Geometry,i=e.Fragment;const s=t.lastBoundBO.getReferenceByName("lastLightComplexity");let l=["uniform float ambient;","uniform float diffuse;","uniform float specular;","uniform float opacityUniform; // the fragment opacity","uniform vec3 ambientColorUniform;","uniform vec3 diffuseColorUniform;"];s&&(l=l.concat(["uniform vec3 specularColorUniform;","uniform float specularPowerUniform;"]));let c=["vec3 ambientColor;","  vec3 diffuseColor;","  float opacity;"];s&&(c=c.concat(["  vec3 specularColor;","  float specularPower;"])),c=c.concat(["  ambientColor = ambientColorUniform;","  diffuseColor = diffuseColorUniform;","  opacity = opacityUniform;"]),s&&(c=c.concat(["  specularColor = specularColorUniform;","  specularPower = specularPowerUniform;"])),0===t.lastBoundBO.getCABO().getColorComponents()||t.drawingEdges||(l=l.concat(["varying vec4 vertexColorVSOutput;"]),o=vd.substitute(o,"//VTK::Color::Dec",["attribute vec4 scalarColor;","varying vec4 vertexColorVSOutput;"]).result,o=vd.substitute(o,"//VTK::Color::Impl",["vertexColorVSOutput =  scalarColor;"]).result,a=vd.substitute(a,"//VTK::Color::Dec",["in vec4 vertexColorVSOutput[];","out vec4 vertexColorGSOutput;"]).result,a=vd.substitute(a,"//VTK::Color::Impl",["vertexColorGSOutput = vertexColorVSOutput[i];"]).result),0===t.lastBoundBO.getCABO().getColorComponents()||t.drawingEdges?(t.renderable.getAreScalarsMappedFromCells()||t.renderable.getInterpolateScalarsBeforeMapping())&&t.renderable.getColorCoordinates()&&!t.drawingEdges?i=vd.substitute(i,"//VTK::Color::Impl",c.concat(["  vec4 texColor = texture2D(texture1, tcoordVCVSOutput.st);","  diffuseColor = texColor.rgb;","  ambientColor = texColor.rgb;","  opacity = opacity*texColor.a;"])).result:(r.getBackfaceProperty()&&!t.drawingEdges&&(l=l.concat(["uniform float opacityUniformBF; // the fragment opacity","uniform float ambientIntensityBF; // the material ambient","uniform float diffuseIntensityBF; // the material diffuse","uniform vec3 ambientColorUniformBF; // ambient material color","uniform vec3 diffuseColorUniformBF; // diffuse material color"]),s?(l=l.concat(["uniform float specularIntensityBF; // the material specular intensity","uniform vec3 specularColorUniformBF; // intensity weighted color","uniform float specularPowerUniformBF;"]),c=c.concat(["if (gl_FrontFacing == false) {","  ambientColor = ambientIntensityBF * ambientColorUniformBF;","  diffuseColor = diffuseIntensityBF * diffuseColorUniformBF;","  specularColor = specularIntensityBF * specularColorUniformBF;","  specularPower = specularPowerUniformBF;","  opacity = opacityUniformBF; }"])):c=c.concat(["if (gl_FrontFacing == false) {","  ambientColor = ambientIntensityBF * ambientColorUniformBF;","  diffuseColor = diffuseIntensityBF * diffuseColorUniformBF;","  opacity = opacityUniformBF; }"])),t.haveCellScalars&&!t.drawingEdges&&(l=l.concat(["uniform samplerBuffer texture1;"])),i=vd.substitute(i,"//VTK::Color::Impl",c).result):i=vd.substitute(i,"//VTK::Color::Impl",c.concat(["  diffuseColor = vertexColorVSOutput.rgb;","  ambientColor = vertexColorVSOutput.rgb;","  opacity = opacity*vertexColorVSOutput.a;"])).result,i=vd.substitute(i,"//VTK::Color::Dec",l).result,e.Vertex=o,e.Geometry=a,e.Fragment=i},e.replaceShaderLight=(e,n,r)=>{let o=e.Fragment;const a=t.lastBoundBO.getReferenceByName("lastLightComplexity"),i=t.lastBoundBO.getReferenceByName("lastLightCount");let s=[];switch(a){case 0:o=vd.substitute(o,"//VTK::Light::Impl",["  gl_FragData[0] = vec4(ambientColor * ambient + diffuseColor * diffuse, opacity);","  //VTK::Light::Impl"],!1).result;break;case 1:o=vd.substitute(o,"//VTK::Light::Impl",["  float df = max(0.0, normalVCVSOutput.z);","  float sf = pow(df, specularPower);","  vec3 diffuseL = df * diffuseColor;","  vec3 specularL = sf * specularColor;","  gl_FragData[0] = vec4(ambientColor * ambient + diffuseL * diffuse + specularL * specular, opacity);","  //VTK::Light::Impl"],!1).result;break;case 2:for(let e=0;e<i;++e)s=s.concat([`uniform vec3 lightColor${e};`,`uniform vec3 lightDirectionVC${e}; // normalized`,`uniform vec3 lightHalfAngleVC${e}; // normalized`]);o=vd.substitute(o,"//VTK::Light::Dec",s).result,s=["vec3 diffuseL = vec3(0,0,0);","  vec3 specularL = vec3(0,0,0);","  float df;"];for(let e=0;e<i;++e)s=s.concat([`  df = max(0.0, dot(normalVCVSOutput, -lightDirectionVC${e}));`,`  diffuseL += ((df) * lightColor${e});`,`  if (dot(normalVCVSOutput, lightDirectionVC${e}) < 0.0)`,"    {",`    float sf = sign(df)*pow(max(1e-5,\n                                              dot(reflect(lightDirectionVC${e},normalVCVSOutput),\n                                                  normalize(-vertexVC.xyz))),\n                                         specularPower);`,`    specularL += (sf * lightColor${e});`,"    }"]);s=s.concat(["  diffuseL = diffuseL * diffuseColor;","  specularL = specularL * specularColor;","  gl_FragData[0] = vec4(ambientColor * ambient + diffuseL * diffuse + specularL * specular, opacity);","  //VTK::Light::Impl"]),o=vd.substitute(o,"//VTK::Light::Impl",s,!1).result;break;case 3:for(let e=0;e<i;++e)s=s.concat([`uniform vec3 lightColor${e};`,`uniform vec3 lightDirectionVC${e}; // normalized`,`uniform vec3 lightHalfAngleVC${e}; // normalized`,`uniform vec3 lightPositionVC${e};`,`uniform vec3 lightAttenuation${e};`,`uniform float lightConeAngle${e};`,`uniform float lightExponent${e};`,`uniform int lightPositional${e};`]);o=vd.substitute(o,"//VTK::Light::Dec",s).result,s=["vec3 diffuseL = vec3(0,0,0);","  vec3 specularL = vec3(0,0,0);","  vec3 vertLightDirectionVC;","  float attenuation;","  float df;"];for(let e=0;e<i;++e)s=s.concat(["  attenuation = 1.0;",`  if (lightPositional${e} == 0)`,"    {",`      vertLightDirectionVC = lightDirectionVC${e};`,"    }","  else","    {",`    vertLightDirectionVC = vertexVC.xyz - lightPositionVC${e};`,"    float distanceVC = length(vertLightDirectionVC);","    vertLightDirectionVC = normalize(vertLightDirectionVC);","    attenuation = 1.0 /",`      (lightAttenuation${e}.x`,`       + lightAttenuation${e}.y * distanceVC`,`       + lightAttenuation${e}.z * distanceVC * distanceVC);`,"    // per OpenGL standard cone angle is 90 or less for a spot light",`    if (lightConeAngle${e} <= 90.0)`,"      {",`      float coneDot = dot(vertLightDirectionVC, lightDirectionVC${e});`,"      // if inside the cone",`      if (coneDot >= cos(radians(lightConeAngle${e})))`,"        {",`        attenuation = attenuation * pow(coneDot, lightExponent${e});`,"        }","      else","        {","        attenuation = 0.0;","        }","      }","    }","    df = max(0.0, attenuation*dot(normalVCVSOutput, -vertLightDirectionVC));",`    diffuseL += ((df) * lightColor${e});`,"    if (dot(normalVCVSOutput, vertLightDirectionVC) < 0.0)","      {",`      float sf = sign(df)*attenuation*pow(max(1e-5,\n                                                           dot(reflect(lightDirectionVC${e},\n                                                                       normalVCVSOutput),\n                                                               normalize(-vertexVC.xyz))),\n                                                       specularPower);`,`    specularL += ((sf) * lightColor${e});`,"    }"]);s=s.concat(["  diffuseL = diffuseL * diffuseColor;","  specularL = specularL * specularColor;","  gl_FragData[0] = vec4(ambientColor * ambient + diffuseL * diffuse + specularL * specular, opacity);","  //VTK::Light::Impl"]),o=vd.substitute(o,"//VTK::Light::Impl",s,!1).result;break;default:np("bad light complexity")}e.Fragment=o},e.replaceShaderNormal=(e,n,r)=>{if(t.lastBoundBO.getReferenceByName("lastLightComplexity")>0){let n=e.Vertex,o=e.Geometry,a=e.Fragment;t.lastBoundBO.getCABO().getNormalOffset()?(n=vd.substitute(n,"//VTK::Normal::Dec",["attribute vec3 normalMC;","uniform mat3 normalMatrix;","varying vec3 normalVCVSOutput;"]).result,n=vd.substitute(n,"//VTK::Normal::Impl",["normalVCVSOutput = normalMatrix * normalMC;"]).result,o=vd.substitute(o,"//VTK::Normal::Dec",["in vec3 normalVCVSOutput[];","out vec3 normalVCGSOutput;"]).result,o=vd.substitute(o,"//VTK::Normal::Impl",["normalVCGSOutput = normalVCVSOutput[i];"]).result,a=vd.substitute(a,"//VTK::Normal::Dec",["varying vec3 normalVCVSOutput;"]).result,a=vd.substitute(a,"//VTK::Normal::Impl",["vec3 normalVCVSOutput = normalize(normalVCVSOutput);","  if (gl_FrontFacing == false) { normalVCVSOutput = -normalVCVSOutput; }"]).result):t.haveCellNormals?(a=vd.substitute(a,"//VTK::Normal::Dec",["uniform mat3 normalMatrix;","uniform samplerBuffer textureN;"]).result,a=vd.substitute(a,"//VTK::Normal::Impl",["vec3 normalVCVSOutput = normalize(normalMatrix *","    texelFetchBuffer(textureN, gl_PrimitiveID + PrimitiveIDOffset).xyz);","  if (gl_FrontFacing == false) { normalVCVSOutput = -normalVCVSOutput; }"]).result):t.lastBoundBO.getOpenGLMode(r.getProperty().getRepresentation())===t.context.LINES?(a=vd.substitute(a,"//VTK::UniformFlow::Impl",["  vec3 fdx = dFdx(vertexVC.xyz);","  vec3 fdy = dFdy(vertexVC.xyz);","  //VTK::UniformFlow::Impl"]).result,a=vd.substitute(a,"//VTK::Normal::Impl",["vec3 normalVCVSOutput;","  if (abs(fdx.x) > 0.0)","    { fdx = normalize(fdx); normalVCVSOutput = normalize(cross(vec3(fdx.y, -fdx.x, 0.0), fdx)); }","  else { fdy = normalize(fdy); normalVCVSOutput = normalize(cross(vec3(fdy.y, -fdy.x, 0.0), fdy));}"]).result):(a=vd.substitute(a,"//VTK::Normal::Dec",["uniform int cameraParallel;"]).result,a=vd.substitute(a,"//VTK::UniformFlow::Impl",["  vec3 fdx = dFdx(vertexVC.xyz);","  vec3 fdy = dFdy(vertexVC.xyz);","  //VTK::UniformFlow::Impl"]).result,a=vd.substitute(a,"//VTK::Normal::Impl",["  fdx = normalize(fdx);","  fdy = normalize(fdy);","  vec3 normalVCVSOutput = normalize(cross(fdx,fdy));","  if (cameraParallel == 1 && normalVCVSOutput.z < 0.0) { normalVCVSOutput = -1.0*normalVCVSOutput; }","  if (cameraParallel == 0 && dot(normalVCVSOutput,vertexVC.xyz) > 0.0) { normalVCVSOutput = -1.0*normalVCVSOutput; }"]).result),e.Vertex=n,e.Geometry=o,e.Fragment=a}},e.replaceShaderPositionVC=(e,n,r)=>{t.lastBoundBO.replaceShaderPositionVC(e,n,r);let o=e.Vertex,a=e.Geometry,i=e.Fragment;t.lastBoundBO.getReferenceByName("lastLightComplexity")>0?(o=vd.substitute(o,"//VTK::PositionVC::Dec",["varying vec4 vertexVCVSOutput;"]).result,o=vd.substitute(o,"//VTK::PositionVC::Impl",["vertexVCVSOutput = MCVCMatrix * vertexMC;","  gl_Position = MCPCMatrix * vertexMC;"]).result,o=vd.substitute(o,"//VTK::Camera::Dec",["uniform mat4 MCPCMatrix;","uniform mat4 MCVCMatrix;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Dec",["in vec4 vertexVCVSOutput[];","out vec4 vertexVCGSOutput;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Impl",["vertexVCGSOutput = vertexVCVSOutput[i];"]).result,i=vd.substitute(i,"//VTK::PositionVC::Dec",["varying vec4 vertexVCVSOutput;"]).result,i=vd.substitute(i,"//VTK::PositionVC::Impl",["vec4 vertexVC = vertexVCVSOutput;"]).result):(o=vd.substitute(o,"//VTK::Camera::Dec",["uniform mat4 MCPCMatrix;"]).result,o=vd.substitute(o,"//VTK::PositionVC::Impl",["  gl_Position = MCPCMatrix * vertexMC;"]).result),e.Vertex=o,e.Geometry=a,e.Fragment=i},e.replaceShaderTCoord=(e,n,r)=>{if(t.lastBoundBO.getCABO().getTCoordOffset()){let n=e.Vertex,r=e.Geometry,o=e.Fragment;if(t.drawingEdges)return;n=vd.substitute(n,"//VTK::TCoord::Impl","tcoordVCVSOutput = tcoordMC;").result;const a=t.openGLActor.getActiveTextures();let i=2,s=2;if(a&&a.length>0&&(i=a[0].getComponents(),a[0].getTarget()===t.context.TEXTURE_CUBE_MAP&&(s=3)),t.renderable.getColorTextureMap()&&(i=t.renderable.getColorTextureMap().getPointData().getScalars().getNumberOfComponents(),s=2),2===s){if(n=vd.substitute(n,"//VTK::TCoord::Dec","attribute vec2 tcoordMC; varying vec2 tcoordVCVSOutput;").result,r=vd.substitute(r,"//VTK::TCoord::Dec",["in vec2 tcoordVCVSOutput[];","out vec2 tcoordVCGSOutput;"]).result,r=vd.substitute(r,"//VTK::TCoord::Impl","tcoordVCGSOutput = tcoordVCVSOutput[i];").result,o=vd.substitute(o,"//VTK::TCoord::Dec",["varying vec2 tcoordVCVSOutput;","uniform sampler2D texture1;"]).result,a&&a.length>=1)switch(i){case 1:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = texture2D(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.r;","  diffuseColor = diffuseColor*tcolor.r;"]).result;break;case 2:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = texture2D(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.r;","  diffuseColor = diffuseColor*tcolor.r;","  opacity = opacity * tcolor.g;"]).result;break;default:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = texture2D(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.rgb;","  diffuseColor = diffuseColor*tcolor.rgb;","  opacity = opacity * tcolor.a;"]).result}}else switch(n=vd.substitute(n,"//VTK::TCoord::Dec","attribute vec3 tcoordMC; varying vec3 tcoordVCVSOutput;").result,r=vd.substitute(r,"//VTK::TCoord::Dec",["in vec3 tcoordVCVSOutput[];","out vec3 tcoordVCGSOutput;"]).result,r=vd.substitute(r,"//VTK::TCoord::Impl","tcoordVCGSOutput = tcoordVCVSOutput[i];").result,o=vd.substitute(o,"//VTK::TCoord::Dec",["varying vec3 tcoordVCVSOutput;","uniform samplerCube texture1;"]).result,i){case 1:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = textureCube(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.r;","  diffuseColor = diffuseColor*tcolor.r;"]).result;break;case 2:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = textureCube(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.r;","  diffuseColor = diffuseColor*tcolor.r;","  opacity = opacity * tcolor.g;"]).result;break;default:o=vd.substitute(o,"//VTK::TCoord::Impl",["  vec4 tcolor = textureCube(texture1, tcoordVCVSOutput);","  ambientColor = ambientColor*tcolor.rgb;","  diffuseColor = diffuseColor*tcolor.rgb;","  opacity = opacity * tcolor.a;"]).result}e.Vertex=n,e.Geometry=r,e.Fragment=o}},e.replaceShaderClip=(e,n,r)=>{let o=e.Vertex,a=e.Fragment;if(t.renderable.getNumberOfClippingPlanes()){const e=t.renderable.getNumberOfClippingPlanes();o=vd.substitute(o,"//VTK::Clip::Dec",["uniform int numClipPlanes;",`uniform vec4 clipPlanes[${e}];`,`varying float clipDistancesVSOutput[${e}];`]).result,o=vd.substitute(o,"//VTK::Clip::Impl",[`for (int planeNum = 0; planeNum < ${e}; planeNum++)`,"    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    clipDistancesVSOutput[planeNum] = dot(clipPlanes[planeNum], vertexMC);","    }"]).result,a=vd.substitute(a,"//VTK::Clip::Dec",["uniform int numClipPlanes;",`varying float clipDistancesVSOutput[${e}];`]).result,a=vd.substitute(a,"//VTK::Clip::Impl",[`for (int planeNum = 0; planeNum < ${e}; planeNum++)`,"    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    if (clipDistancesVSOutput[planeNum] < 0.0) discard;","    }"]).result}e.Vertex=o,e.Fragment=a},e.getCoincidentParameters=(e,n)=>{let r={factor:0,offset:0};const o=n.getProperty();if(t.renderable.getResolveCoincidentTopology()==Pl.PolygonOffset||o.getEdgeVisibility()&&o.getRepresentation()===Zd.SURFACE){const e=t.lastBoundBO.getPrimitiveType();e===Jd.Points||o.getRepresentation()===Zd.POINTS?r=t.renderable.getCoincidentTopologyPointOffsetParameter():e===Jd.Lines||o.getRepresentation()===Zd.WIREFRAME?r=t.renderable.getCoincidentTopologyLineOffsetParameters():e!==Jd.Tris&&e!==Jd.TriStrips||(r=t.renderable.getCoincidentTopologyPolygonOffsetParameters()),e!==Jd.TrisEdges&&e!==Jd.TriStripsEdges||(r=t.renderable.getCoincidentTopologyPolygonOffsetParameters(),r.factor/=2,r.offset/=2)}const a=t._openGLRenderer.getSelector();return a&&a.getFieldAssociation()===Yd.FIELD_ASSOCIATION_POINTS&&(r.offset-=2),r},e.replaceShaderPicking=(e,n,r)=>{let o=e.Fragment,a=e.Vertex;if(o=vd.substitute(o,"//VTK::Picking::Dec",["uniform int picking;","//VTK::Picking::Dec"]).result,t._openGLRenderer.getSelector()){switch(t.lastSelectionState!==Bl.ID_LOW24&&t.lastSelectionState!==Bl.ID_HIGH24||(a=vd.substitute(a,"//VTK::Picking::Dec",["flat out int vertexIDVSOutput;\n","uniform int VertexIDOffset;\n"]).result,a=vd.substitute(a,"//VTK::Picking::Impl","  vertexIDVSOutput = gl_VertexID + VertexIDOffset;\n").result,o=vd.substitute(o,"//VTK::Picking::Dec","flat in int vertexIDVSOutput;\n").result,o=vd.substitute(o,"//VTK::Picking::Impl",["  int idx = vertexIDVSOutput;","//VTK::Picking::Impl"]).result),t.lastSelectionState){case Bl.ID_LOW24:o=vd.substitute(o,"//VTK::Picking::Impl","  gl_FragData[0] = vec4(float(idx%256)/255.0, float((idx/256)%256)/255.0, float((idx/65536)%256)/255.0, 1.0);").result;break;case Bl.ID_HIGH24:o=vd.substitute(o,"//VTK::Picking::Impl","  gl_FragData[0] = vec4(float((idx/16777216)%256)/255.0, 0.0, 0.0, 1.0);").result;break;default:o=vd.substitute(o,"//VTK::Picking::Dec","uniform vec3 mapperIndex;").result,o=vd.substitute(o,"//VTK::Picking::Impl","  gl_FragData[0] = picking != 0 ? vec4(mapperIndex,1.0) : gl_FragData[0];").result}e.Fragment=o,e.Vertex=a}},e.replaceShaderValues=(n,r,o)=>{if(e.replaceShaderColor(n,r,o),e.replaceShaderNormal(n,r,o),e.replaceShaderLight(n,r,o),e.replaceShaderTCoord(n,r,o),e.replaceShaderPicking(n,r,o),e.replaceShaderClip(n,r,o),e.replaceShaderCoincidentOffset(n,r,o),e.replaceShaderPositionVC(n,r,o),t.haveSeenDepthRequest){let e=n.Fragment;e=vd.substitute(e,"//VTK::ZBuffer::Dec","uniform int depthRequest;").result,e=vd.substitute(e,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float iz = floor(gl_FragCoord.z*65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); }"]).result,n.Fragment=e}},e.getNeedToRebuildShaders=(e,n,r)=>{let o=0,a=0;const i=e.getPrimitiveType(),s=t.currentInput;let l=!1;const c=s.getPointData().getNormals(),u=s.getCellData().getNormals(),d=r.getProperty().getInterpolation()===Qd.FLAT,p=r.getProperty().getRepresentation(),f=e.getOpenGLMode(p,i);if(f===t.context.TRIANGLES||u&&!c||!d&&c?l=!0:d||f!==t.context.LINES||(l=!0),r.getProperty().getLighting()&&l){o=0;const e=n.getLightsByReference();for(let t=0;t<e.length;++t){const n=e[t];n.getSwitch()>0&&(a++,0===o&&(o=1)),1===o&&(a>1||1!==n.getIntensity()||!n.lightTypeIsHeadLight())&&(o=2),o<3&&n.getPositional()&&(o=3)}}let g=!1;const m=t.lastBoundBO.getReferenceByName("lastLightComplexity"),h=t.lastBoundBO.getReferenceByName("lastLightCount");return m===o&&h===a||(t.lastBoundBO.set({lastLightComplexity:o},!0),t.lastBoundBO.set({lastLightCount:a},!0),g=!0),(!t.currentRenderPass&&t.lastRenderPassShaderReplacement||t.currentRenderPass&&t.currentRenderPass.getShaderReplacement()!==t.lastRenderPassShaderReplacement)&&(g=!0),!!(t.lastHaveSeenDepthRequest!==t.haveSeenDepthRequest||e.getShaderSourceTime().getMTime()<t.renderable.getMTime()||e.getShaderSourceTime().getMTime()<t.currentInput.getMTime()||e.getShaderSourceTime().getMTime()<t.selectionStateChanged.getMTime()||g)&&(t.lastHaveSeenDepthRequest=t.haveSeenDepthRequest,!0)},e.invokeShaderCallbacks=(e,n,r)=>{const o=t.renderable.getViewSpecificProperties().ShadersCallbacks;o&&o.forEach((t=>{t.callback(t.userData,e,n,r)}))},e.setMapperShaderParameters=(n,r,o)=>{if(n.getProgram().isUniformUsed("PrimitiveIDOffset")&&n.getProgram().setUniformi("PrimitiveIDOffset",t.primitiveIDOffset),n.getProgram().isUniformUsed("VertexIDOffset")&&n.getProgram().setUniformi("VertexIDOffset",t.vertexIDOffset),n.getCABO().getElementCount()&&(t.VBOBuildTime.getMTime()>n.getAttributeUpdateTime().getMTime()||n.getShaderSourceTime().getMTime()>n.getAttributeUpdateTime().getMTime())){const e=t.lastBoundBO.getReferenceByName("lastLightComplexity");n.getProgram().isAttributeUsed("vertexMC")&&(n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),"vertexMC",n.getCABO().getVertexOffset(),n.getCABO().getStride(),t.context.FLOAT,3,!1)||np("Error setting vertexMC in shader VAO.")),n.getProgram().isAttributeUsed("normalMC")&&n.getCABO().getNormalOffset()&&e>0?n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),"normalMC",n.getCABO().getNormalOffset(),n.getCABO().getStride(),t.context.FLOAT,3,!1)||np("Error setting normalMC in shader VAO."):n.getVAO().removeAttributeArray("normalMC"),t.renderable.getCustomShaderAttributes().forEach(((e,r)=>{n.getProgram().isAttributeUsed(`${e}MC`)&&(n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),`${e}MC`,n.getCABO().getCustomData()[r].offset,n.getCABO().getStride(),t.context.FLOAT,n.getCABO().getCustomData()[r].components,!1)||np(`Error setting ${e}MC in shader VAO.`))})),n.getProgram().isAttributeUsed("tcoordMC")&&n.getCABO().getTCoordOffset()?n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),"tcoordMC",n.getCABO().getTCoordOffset(),n.getCABO().getStride(),t.context.FLOAT,n.getCABO().getTCoordComponents(),!1)||np("Error setting tcoordMC in shader VAO."):n.getVAO().removeAttributeArray("tcoordMC"),n.getProgram().isAttributeUsed("scalarColor")&&n.getCABO().getColorComponents()?n.getVAO().addAttributeArray(n.getProgram(),n.getCABO().getColorBO(),"scalarColor",n.getCABO().getColorOffset(),n.getCABO().getColorBOStride(),t.context.UNSIGNED_BYTE,4,!0)||np("Error setting scalarColor in shader VAO."):n.getVAO().removeAttributeArray("scalarColor"),n.getAttributeUpdateTime().modified()}if(t.renderable.getNumberOfClippingPlanes()){const e=t.renderable.getNumberOfClippingPlanes(),r=[],a=n.getCABO().getCoordShiftAndScaleEnabled()?n.getCABO().getInverseShiftAndScaleMatrix():null,i=a?T(t.tmpMat4,o.getMatrix()):o.getMatrix();a&&(y(i,i),A(i,i,a),y(i,i));for(let n=0;n<e;n++){const e=[];t.renderable.getClippingPlaneInDataCoords(i,n,e);for(let t=0;t<4;t++)r.push(e[t])}n.getProgram().setUniformi("numClipPlanes",e),n.getProgram().setUniform4fv("clipPlanes",r)}t.internalColorTexture&&n.getProgram().isUniformUsed("texture1")&&n.getProgram().setUniformi("texture1",t.internalColorTexture.getTextureUnit());const a=t.openGLActor.getActiveTextures();if(a)for(let e=0;e<a.length;++e){const t=a[e].getTextureUnit(),r=`texture${t+1}`;n.getProgram().isUniformUsed(r)&&n.getProgram().setUniformi(r,t)}if(t.haveSeenDepthRequest&&n.getProgram().setUniformi("depthRequest",t.renderDepth?1:0),n.getProgram().isUniformUsed("coffset")){const t=e.getCoincidentParameters(r,o);n.getProgram().setUniformf("coffset",t.offset),n.getProgram().isUniformUsed("cfactor")&&n.getProgram().setUniformf("cfactor",t.factor)}n.setMapperShaderParameters(r,o,t._openGLRenderer.getTiledSizeAndOrigin());const i=t._openGLRenderer.getSelector();n.getProgram().setUniform3fArray("mapperIndex",i?i.getPropColorValue():[0,0,0]),n.getProgram().setUniformi("picking",i?i.getCurrentPass()+1:0)},e.setLightingShaderParameters=(e,n,r)=>{const o=t.lastBoundBO.getReferenceByName("lastLightComplexity");if(o<2)return;const a=e.getProgram();let i=0;const s=n.getLightsByReference();for(let e=0;e<s.length;++e){const r=s[e];if(r.getSwitch()>0){const e=r.getColorByReference(),o=r.getIntensity();t.lightColor[0]=e[0]*o,t.lightColor[1]=e[1]*o,t.lightColor[2]=e[2]*o;const s=r.getDirection(),l=n.getActiveCamera().getViewMatrix(),c=[...s];r.lightTypeIsSceneLight()&&(c[0]=l[0]*s[0]+l[1]*s[1]+l[2]*s[2],c[1]=l[4]*s[0]+l[5]*s[1]+l[6]*s[2],c[2]=l[8]*s[0]+l[9]*s[1]+l[10]*s[2],jo(c)),t.lightDirection[0]=c[0],t.lightDirection[1]=c[1],t.lightDirection[2]=c[2],jo(t.lightDirection),a.setUniform3fArray(`lightColor${i}`,t.lightColor),a.setUniform3fArray(`lightDirectionVC${i}`,t.lightDirection),i++}}if(o<3)return;const l=n.getActiveCamera().getViewMatrix();y(l,l),i=0;for(let e=0;e<s.length;++e){const t=s[e];if(t.getSwitch()>0){const e=t.getTransformedPosition(),n=new Float64Array(3);oe(n,e,l),a.setUniform3fArray(`lightAttenuation${i}`,t.getAttenuationValuesByReference()),a.setUniformi(`lightPositional${i}`,t.getPositional()),a.setUniformf(`lightExponent${i}`,t.getExponent()),a.setUniformf(`lightConeAngle${i}`,t.getConeAngle()),a.setUniform3fArray(`lightPositionVC${i}`,[n[0],n[1],n[2]]),i++}}},e.setCameraShaderParameters=(e,r,o)=>{const a=e.getProgram(),i=t.openGLCamera.getKeyMatrices(r),s=r.getActiveCamera(),l=t.openGLCamera.getKeyMatrixTime().getMTime(),c=a.getLastCameraMTime(),u=e.getCABO().getCoordShiftAndScaleEnabled()?e.getCABO().getInverseShiftAndScaleMatrix():null,d=o.getIsIdentity(),p=d?{mcwc:null,normalMatrix:null}:t.openGLActor.getKeyMatrices();if(o.getCoordinateSystem()===ap.DISPLAY){const e=t._openGLRenderer.getTiledSizeAndOrigin();x(t.tmpMat4),t.tmpMat4[0]=2/e.usize,t.tmpMat4[12]=-1,t.tmpMat4[5]=2/e.vsize,t.tmpMat4[13]=-1,A(t.tmpMat4,t.tmpMat4,u),a.setUniformMatrix("MCPCMatrix",t.tmpMat4)}else a.setUniformMatrix("MCPCMatrix",n([i.wcpc,p.mcwc,u],H,t.tmpMat4));a.isUniformUsed("MCVCMatrix")&&a.setUniformMatrix("MCVCMatrix",n([i.wcvc,p.mcwc,u],H,t.tmpMat4)),a.isUniformUsed("normalMatrix")&&a.setUniformMatrix3x3("normalMatrix",n([i.normalMatrix,p.normalMatrix],h,t.tmpMat3)),c!==l&&(a.isUniformUsed("cameraParallel")&&a.setUniformi("cameraParallel",s.getParallelProjection()),a.setLastCameraMTime(l)),d||a.setLastCameraMTime(0)},e.setPropertyShaderParameters=(e,n,r)=>{const o=e.getProgram();let a=r.getProperty();let i=t.drawingEdges||a.getRepresentation()===Zd.WIREFRAME?a.getEdgeOpacity():a.getOpacity(),s=t.drawingEdges?a.getEdgeColorByReference():a.getAmbientColorByReference(),l=t.drawingEdges?a.getEdgeColorByReference():a.getDiffuseColorByReference(),c=t.drawingEdges?1:a.getAmbient(),u=t.drawingEdges?0:a.getDiffuse(),d=t.drawingEdges?0:a.getSpecular();const p=a.getSpecularPower();o.setUniformf("opacityUniform",i),o.setUniform3fArray("ambientColorUniform",s),o.setUniform3fArray("diffuseColorUniform",l),o.setUniformf("ambient",c),o.setUniformf("diffuse",u);const f=t.lastBoundBO.getReferenceByName("lastLightComplexity");if(f<1)return;let g=a.getSpecularColorByReference();if(o.setUniform3fArray("specularColorUniform",g),o.setUniformf("specularPowerUniform",p),o.setUniformf("specular",d),o.isUniformUsed("ambientIntensityBF")){if(a=r.getBackfaceProperty(),i=a.getOpacity(),s=a.getAmbientColor(),c=a.getAmbient(),l=a.getDiffuseColor(),u=a.getDiffuse(),g=a.getSpecularColor(),d=a.getSpecular(),o.setUniformf("ambientIntensityBF",c),o.setUniformf("diffuseIntensityBF",u),o.setUniformf("opacityUniformBF",i),o.setUniform3fArray("ambientColorUniformBF",s),o.setUniform3fArray("diffuseColorUniformBF",l),f<1)return;o.setUniformf("specularIntensityBF",d),o.setUniform3fArray("specularColorUniformBF",g),o.setUniformf("specularPowerUniformBF",p)}},e.updateMaximumPointCellIds=(e,n)=>{const r=t._openGLRenderer.getSelector();if(!r)return;if(t.selectionWebGLIdsToVTKIds?.points?.length){const e=t.selectionWebGLIdsToVTKIds.points.length;r.setMaximumPointId(e-1)}if(t.selectionWebGLIdsToVTKIds?.cells?.length){const e=t.selectionWebGLIdsToVTKIds.cells.length;r.setMaximumCellId(e-1)}r.getFieldAssociation()===Yd.FIELD_ASSOCIATION_POINTS&&(t.pointPicking=!0)},e.renderPieceStart=(n,r)=>{t.primitiveIDOffset=0,t.vertexIDOffset=0;const o=function(e){const t=e.getSelector();return t?t.getCurrentPass():Bl.MIN_KNOWN_PASS-1}(t._openGLRenderer);t.lastSelectionState!==o&&(t.selectionStateChanged.modified(),t.lastSelectionState=o),t._openGLRenderer.getSelector()&&t._openGLRenderer.getSelector().renderProp(r),e.updateBufferObjects(n,r),t.renderable.getColorTextureMap()&&t.internalColorTexture.activate(),t.lastBoundBO=null},e.renderPieceDraw=(n,r)=>{const o=r.getProperty().getRepresentation(),a=r.getProperty().getEdgeVisibility()&&o===Zd.SURFACE,i=t._openGLRenderer.getSelector(),s=i&&i.getFieldAssociation()===Yd.FIELD_ASSOCIATION_POINTS&&(t.lastSelectionState===Bl.ID_LOW24||t.lastSelectionState===Bl.ID_HIGH24);for(let i=Jd.Start;i<Jd.End;i++){t.primitives[i].setPointPicking(s);t.primitives[i].getCABO().getElementCount()&&(t.drawingEdges=a&&(i===Jd.TrisEdges||i===Jd.TriStripsEdges),t.drawingEdges&&(t.renderDepth||t.lastSelectionState>=0)||(t.lastBoundBO=t.primitives[i],t.primitiveIDOffset+=t.primitives[i].drawArrays(n,r,o,e),t.vertexIDOffset+=t.primitives[i].getCABO().getElementCount()))}},e.renderPieceFinish=(e,n)=>{t.LastBoundBO&&t.LastBoundBO.getVAO().release(),t.renderable.getColorTextureMap()&&t.internalColorTexture.deactivate()},e.renderPiece=(n,r)=>{if(e.invokeEvent(rp),t.renderable.getStatic()||t.renderable.update(),t.currentInput=t.renderable.getInputData(),e.invokeEvent(op),!t.currentInput)return void np("No input!");if(!t.currentInput.getPoints||!t.currentInput.getPoints().getNumberOfValues())return;const o=t.context,a=r.getProperty().getBackfaceCulling(),i=r.getProperty().getFrontfaceCulling();a||i?i?(t._openGLRenderWindow.enableCullFace(),o.cullFace(o.FRONT)):(t._openGLRenderWindow.enableCullFace(),o.cullFace(o.BACK)):t._openGLRenderWindow.disableCullFace(),e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r)},e.updateBufferObjects=(t,n)=>{e.getNeedToRebuildBufferObjects(t,n)&&e.buildBufferObjects(t,n),e.updateMaximumPointCellIds()},e.getNeedToRebuildBufferObjects=(n,r)=>{const o=t.VBOBuildTime.getMTime();return o<e.getMTime()||o<t.renderable.getMTime()||o<r.getMTime()||o<t.currentInput.getMTime()},e.buildBufferObjects=(e,n)=>{const r=t.currentInput;if(null===r)return;t.renderable.mapScalars(r,1);const o=t.renderable.getColorMapColors();t.haveCellScalars=!1;const a=t.renderable.getScalarMode();t.renderable.getScalarVisibility()&&(a!==$d.USE_CELL_DATA&&a!==$d.USE_CELL_FIELD_DATA&&a!==$d.USE_FIELD_DATA&&r.getPointData().getScalars()||a===$d.USE_POINT_FIELD_DATA||!o||(t.haveCellScalars=!0));let i=n.getProperty().getInterpolation()!==Qd.FLAT?r.getPointData().getNormals():null;null===i&&r.getCellData().getNormals()&&(t.haveCellNormals=!0,i=r.getCellData().getNormals());const s=n.getProperty().getRepresentation();let l=r.getPointData().getTCoords();t.openGLActor.getActiveTextures()||(l=null);let c=!1;if(t.renderable.getColorCoordinates()){l=t.renderable.getColorCoordinates(),c=t.renderable.getAreScalarsMappedFromCells(),t.internalColorTexture||(t.internalColorTexture=Hd.newInstance({resizable:!0}));const e=t.internalColorTexture;e.setMinificationFilter(ep.NEAREST),e.setMagnificationFilter(ep.NEAREST),e.setWrapS(tp.CLAMP_TO_EDGE),e.setWrapT(tp.CLAMP_TO_EDGE),e.setOpenGLRenderWindow(t._openGLRenderWindow);const n=t.renderable.getColorTextureMap(),r=n.getExtent(),o=n.getPointData().getScalars();e.create2DFromRaw({width:r[1]-r[0]+1,height:r[3]-r[2]+1,numComps:o.getNumberOfComponents(),dataType:o.getDataType(),data:o.getData()}),e.activate(),e.sendParameters(),e.deactivate()}const u=t.renderable.getCustomShaderAttributes().map((e=>r.getPointData().getArrayByName(e))),d=`${r.getMTime()}A${s}B${r.getMTime()}C${i?i.getMTime():1}D${o?o.getMTime():1}E${n.getProperty().getEdgeVisibility()}F${l?l.getMTime():1}G${u.map((e=>e.getMTime())).join(",")}`;if(t.VBOBuildString!==d){const e={points:r.getPoints(),normals:i,tcoords:l,colors:o,cellOffset:0,vertexOffset:0,useTCoordsPerCell:c,haveCellScalars:t.haveCellScalars,haveCellNormals:t.haveCellNormals,customAttributes:u};t.renderable.getPopulateSelectionSettings()&&(t.selectionWebGLIdsToVTKIds={points:null,cells:null});const a=[{inRep:"verts",cells:r.getVerts()},{inRep:"lines",cells:r.getLines()},{inRep:"polys",cells:r.getPolys()},{inRep:"strips",cells:r.getStrips()},{inRep:"polys",cells:r.getPolys()},{inRep:"strips",cells:r.getStrips()}],p=n.getProperty().getEdgeVisibility()&&s===Zd.SURFACE;for(let n=Jd.Start;n<Jd.End;n++)n!==Jd.TrisEdges&&n!==Jd.TriStripsEdges?(e.cellOffset+=t.primitives[n].getCABO().createVBO(a[n].cells,a[n].inRep,s,e,t.selectionWebGLIdsToVTKIds),e.vertexOffset+=t.primitives[n].getCABO().getElementCount()):p?t.primitives[n].getCABO().createVBO(a[n].cells,a[n].inRep,Zd.WIREFRAME,{...e,tcoords:null,colors:null,haveCellScalars:!1,haveCellNormals:!1}):t.primitives[n].releaseGraphicsResources();t.renderable.getPopulateSelectionSettings()&&t.renderable.setSelectionWebGLIdsToVTKIds(t.selectionWebGLIdsToVTKIds),t.VBOBuildString=d}t.VBOBuildTime.modified()},e.getAllocatedGPUMemoryInBytes=()=>{let e=0;return t.primitives.forEach((t=>{e+=t.getAllocatedGPUMemoryInBytes()})),e}}const sp={context:null,VBOBuildTime:0,VBOBuildString:null,primitives:null,primTypes:null,shaderRebuildString:null,tmpMat4:null,ambientColor:[],diffuseColor:[],specularColor:[],lightColor:[],lightDirection:[],lastHaveSeenDepthRequest:!1,haveSeenDepthRequest:!1,lastSelectionState:Bl.MIN_KNOWN_PASS-1,selectionStateChanged:null,selectionWebGLIdsToVTKIds:null,pointPicking:!1};function lp(e,t,n={}){Object.assign(t,sp,n),pn.extend(e,t,n),qd.implementReplaceShaderCoincidentOffset(e,t,n),qd.implementBuildShadersWithReplacements(e,t,n),t.primitives=[],t.primTypes=Jd,t.tmpMat3=c(new Float64Array(9)),t.tmpMat4=x(new Float64Array(16));for(let e=Jd.Start;e<Jd.End;e++)t.primitives[e]=Sd.newInstance(),t.primitives[e].setPrimitiveType(e),t.primitives[e].set({lastLightComplexity:0,lastLightCount:0,lastSelectionPass:!1},!0);Gt(e,t,["context"]),t.VBOBuildTime={},Vt(t.VBOBuildTime,{mtime:0}),t.selectionStateChanged={},Vt(t.selectionStateChanged,{mtime:0}),ip(e,t)}const cp=Xt(lp,"vtkOpenGLPolyDataMapper");var up={newInstance:cp,extend:lp};vn("vtkMapper",cp);const dp=1,{primTypes:pp}=Sd,{Filter:fp,Wrap:gp}=Hd,{vtkErrorMacro:mp}=ln,hp={type:"StartEvent"},vp={type:"EndEvent"};const Tp={context:null,VBOBuildTime:0,VBOBuildString:null,primitives:null,primTypes:null,shaderRebuildString:null};const xp=Xt((function(e,t,n={}){Object.assign(t,Tp,n),pn.extend(e,t,n),qd.implementReplaceShaderCoincidentOffset(e,t,n),qd.implementBuildShadersWithReplacements(e,t,n),t.primitives=[],t.primTypes=pp,t.tmpMat4=x(new Float64Array(16));for(let e=pp.Start;e<pp.End;e++)t.primitives[e]=Sd.newInstance(),t.primitives[e].setPrimitiveType(e),t.primitives[e].set({lastLightComplexity:0,lastLightCount:0,lastSelectionPass:!1},!0);Gt(e,t,["context"]),t.VBOBuildTime={},Vt(t.VBOBuildTime,{mtime:0}),function(e,t){t.classHierarchy.push("vtkOpenGLPolyDataMapper2D"),e.buildPass=n=>{n&&(t.openGLActor2D=e.getFirstAncestorOfType("vtkOpenGLActor2D"),t._openGLRenderer=t.openGLActor2D.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow"),t.openGLCamera=t._openGLRenderer.getViewNodeFor(t._openGLRenderer.getRenderable().getActiveCamera(),t.openGLCamera))},e.overlayPass=t=>{t&&e.render()},e.getShaderTemplate=(e,t,n)=>{e.Vertex="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkPolyData2DVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\n// all variables that represent positions or directions have a suffix\n// indicating the coordinate system they are in. The possible values are\n// MC - Model Coordinates\n// WC - WC world coordinates\n// VC - View Coordinates\n// DC - Display Coordinates\n\nin vec4 vertexWC;\n\n// frag position in VC\n//VTK::PositionVC::Dec\n\n// material property values\n//VTK::Color::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// Apple Bug\n//VTK::PrimID::Dec\n\nuniform mat4 WCVCMatrix;  // World to view matrix\n\nvoid main()\n{\n  // Apple Bug\n  //VTK::PrimID::Impl\n\n  gl_Position = WCVCMatrix*vertexWC;\n\n  //VTK::TCoord::Impl\n\n  //VTK::Color::Impl\n\n  //VTK::PositionVC::Impl\n}\n",e.Fragment="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkPolyData2DFS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\nuniform int PrimitiveIDOffset;\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// Scalar coloring\n//VTK::Color::Dec\n\n// Depth Peeling\n//VTK::DepthPeeling::Dec\n\n// picking support\n//VTK::Picking::Dec\n\n// the output of this shader\n//VTK::Output::Dec\n\n// Apple Bug\n//VTK::PrimID::Dec\n\nvoid main()\n{\n  // Apple Bug\n  //VTK::PrimID::Impl\n\n  //VTK::Color::Impl\n  //VTK::TCoord::Impl\n\n  //VTK::DepthPeeling::Impl\n  //VTK::Picking::Impl\n\n  if (gl_FragData[0].a <= 0.0)\n    {\n    discard;\n    }\n}\n",e.Geometry=""},e.render=()=>{const n=t._openGLRenderWindow.getContext();if(t.context!==n){t.context=n;for(let e=pp.Start;e<pp.End;e++)t.primitives[e].setOpenGLRenderWindow(t._openGLRenderWindow)}const r=t.openGLActor2D.getRenderable(),o=t._openGLRenderer.getRenderable();e.renderPiece(o,r)},e.renderPiece=(n,r)=>{if(e.invokeEvent(hp),t.renderable.getStatic()||t.renderable.update(),t.currentInput=t.renderable.getInputData(),e.invokeEvent(vp),!t.currentInput)return void mp("No input!");if(!t.currentInput.getPoints||!t.currentInput.getPoints().getNumberOfValues())return;const o=t.context;t._openGLRenderWindow.enableCullFace(),o.cullFace(o.BACK),e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r)},e.renderPieceStart=(n,r)=>{t.primitiveIDOffset=0,t._openGLRenderer.getSelector()&&(t._openGLRenderer.getSelector().getCurrentPass(),t._openGLRenderer.getSelector().renderProp(r)),t.renderable.getColorTextureMap()&&t.internalColorTexture.activate(),e.updateBufferObjects(n,r),t.lastBoundBO=null},e.getNeedToRebuildShaders=(e,n,r)=>e.getShaderSourceTime().getMTime()<t.renderable.getMTime()||e.getShaderSourceTime().getMTime()<t.currentInput.getMTime(),e.updateBufferObjects=(t,n)=>{e.getNeedToRebuildBufferObjects(t,n)&&e.buildBufferObjects(t,n)},e.getNeedToRebuildBufferObjects=(n,r)=>{const o=t.VBOBuildTime.getMTime();return!!(o<e.getMTime()||o<t._openGLRenderWindow.getMTime()||o<t.renderable.getMTime()||o<r.getMTime()||o<t.currentInput.getMTime()||t.renderable.getTransformCoordinate()&&o<n.getMTime())},e.buildBufferObjects=(e,n)=>{const r=t.currentInput;if(null===r)return;t.renderable.mapScalars(r,n.getProperty().getOpacity());const o=t.renderable.getColorMapColors(),a=n.getProperty().getRepresentation();let i=r.getPointData().getTCoords();t.openGLActor2D.getActiveTextures()||(i=null);let s=!1;if(t.renderable.getColorCoordinates()){i=t.renderable.getColorCoordinates(),s=t.renderable.getAreScalarsMappedFromCells(),t.internalColorTexture||(t.internalColorTexture=Hd.newInstance({resizable:!0}));const e=t.internalColorTexture;e.setMinificationFilter(fp.NEAREST),e.setMagnificationFilter(fp.NEAREST),e.setWrapS(gp.CLAMP_TO_EDGE),e.setWrapT(gp.CLAMP_TO_EDGE),e.setOpenGLRenderWindow(t._openGLRenderWindow);const n=t.renderable.getColorTextureMap(),r=n.getExtent(),o=n.getPointData().getScalars();e.create2DFromRaw({width:r[1]-r[0]+1,height:r[3]-r[2]+1,numComps:o.getNumberOfComponents(),dataType:o.getDataType(),data:o.getData()}),e.activate(),e.sendParameters(),e.deactivate()}const l=t.renderable.getTransformCoordinate(),c=e.getRenderWindow().getViews()[0].getViewportSize(e),u=`${r.getMTime()}A${a}B${r.getMTime()}C${o?o.getMTime():1}D${i?i.getMTime():1}E${l?e.getMTime():1}F${c}`;if(t.VBOBuildString!==u){let n=r.getPoints();if(l){const t=lc.newInstance(),r=n.getNumberOfPoints();t.setNumberOfPoints(r);const o=[];for(let a=0;a<r;++a){n.getPoint(a,o),l.setValue(o);const r=l.getComputedDoubleViewportValue(e);t.setPoint(a,r[0],r[1],0)}n=t}const c={points:n,tcoords:i,colors:o,cellOffset:0,useTCoordsPerCell:s,haveCellScalars:t.renderable.getAreScalarsMappedFromCells(),customAttributes:t.renderable.getCustomShaderAttributes().map((e=>r.getPointData().getArrayByName(e)))};c.cellOffset+=t.primitives[pp.Points].getCABO().createVBO(r.getVerts(),"verts",a,c),c.cellOffset+=t.primitives[pp.Lines].getCABO().createVBO(r.getLines(),"lines",a,c),c.cellOffset+=t.primitives[pp.Tris].getCABO().createVBO(r.getPolys(),"polys",a,c),c.cellOffset+=t.primitives[pp.TriStrips].getCABO().createVBO(r.getStrips(),"strips",a,c),t.VBOBuildTime.modified(),t.VBOBuildString=u}},e.renderPieceDraw=(n,r)=>{const o=r.getProperty().getRepresentation();t.context.depthMask(!0);for(let a=pp.Start;a<pp.End;a++)t.primitives[a].getCABO().getElementCount()&&(t.lastBoundBO=t.primitives[a],t.primitiveIDOffset+=t.primitives[a].drawArrays(n,r,o,e))},e.renderPieceFinish=(e,n)=>{t.lastBoundBO&&t.lastBoundBO.getVAO().release(),t.renderable.getColorTextureMap()&&t.internalColorTexture.deactivate()},e.replaceShaderValues=(t,n,r)=>{e.replaceShaderColor(t,n,r),e.replaceShaderTCoord(t,n,r),e.replaceShaderPicking(t,n,r),e.replaceShaderPositionVC(t,n,r)},e.replaceShaderColor=(e,n,r)=>{let o=e.Vertex,a=e.Geometry,i=e.Fragment,s=["uniform vec3 diffuseColorUniform;","uniform float opacityUniform;"],l=["vec3 diffuseColor = diffuseColorUniform;","float opacity = opacityUniform;"];0!==t.lastBoundBO.getCABO().getColorComponents()?(s=s.concat(["varying vec4 vertexColorVSOutput;"]),o=vd.substitute(o,"//VTK::Color::Dec",["attribute vec4 scalarColor;","varying vec4 vertexColorVSOutput;"]).result,o=vd.substitute(o,"//VTK::Color::Impl",["vertexColorVSOutput =  scalarColor;"]).result,a=vd.substitute(a,"//VTK::Color::Dec",["in vec4 vertexColorVSOutput[];","out vec4 vertexColorGSOutput;"]).result,a=vd.substitute(a,"//VTK::Color::Impl",["vertexColorGSOutput = vertexColorVSOutput[i];"]).result,i=vd.substitute(i,"//VTK::Color::Impl",l.concat(["  diffuseColor = vertexColorVSOutput.rgb;","  opacity = opacity*vertexColorVSOutput.a;"])).result):t.renderable.getAreScalarsMappedFromCells()&&(l=l.concat(["  vec4 texColor = texture2D(texture1, tcoordVCVSOutput.st);","  diffuseColor = texColor.rgb;","  opacity = opacity*texColor.a;"])),l=l.concat(["gl_FragData[0] = vec4(diffuseColor, opacity);"]),i=vd.substitute(i,"//VTK::Color::Dec",s).result,i=vd.substitute(i,"//VTK::Color::Impl",l).result,e.Vertex=o,e.Geometry=a,e.Fragment=i},e.replaceShaderTCoord=(e,n,r)=>{if(t.lastBoundBO.getCABO().getTCoordOffset()){let n=e.Vertex,r=e.Geometry,o=e.Fragment;const a=t.lastBoundBO.getCABO().getTCoordComponents();1===a?(n=vd.substitute(n,"//VTK::TCoord::Dec",["in float tcoordMC;","out float tcoordVCVSOutput;"]).result,n=vd.substitute(n,"//VTK::TCoord::Impl",["tcoordVCVSOutput = tcoordMC;"]).result,r=vd.substitute(r,"//VTK::TCoord::Dec",["in float tcoordVCVSOutput[];\n","out float tcoordVCGSOutput;"]).result,r=vd.substitute(r,["//VTK::TCoord::Impl","tcoordVCGSOutput = tcoordVCVSOutput[i];"]).result,o=vd.substitute(o,"//VTK::TCoord::Dec",["in float tcoordVCVSOutput;","uniform sampler2D texture1;"]).result,o=vd.substitute(o,"//VTK::TCoord::Impl",["gl_FragData[0] = gl_FragData[0]*texture2D(texture1, vec2(tcoordVCVSOutput,0));"]).result):2===a&&(n=vd.substitute(n,"//VTK::TCoord::Dec",["in vec2 tcoordMC;","out vec2 tcoordVCVSOutput;"]).result,n=vd.substitute(n,"//VTK::TCoord::Impl",["tcoordVCVSOutput = tcoordMC;"]).result,r=vd.substitute(r,"//VTK::TCoord::Dec",["in vec2 tcoordVCVSOutput[];\n","out vec2 tcoordVCGSOutput;"]).result,r=vd.substitute(r,"//VTK::TCoord::Impl",["tcoordVCGSOutput = tcoordVCVSOutput[i];"]).result,o=vd.substitute(o,"//VTK::TCoord::Dec",["in vec2 tcoordVCVSOutput;","uniform sampler2D texture1;"]).result,o=vd.substitute(o,"//VTK::TCoord::Impl",["gl_FragData[0] = gl_FragData[0]*texture2D(texture1, tcoordVCVSOutput.st);"]).result),t.renderable.getAreScalarsMappedFromCells()&&(r=vd.substitute(r,"//VTK::PrimID::Impl",["gl_PrimitiveID = gl_PrimitiveIDIn;"]).result),e.Vertex=n,e.Geometry=r,e.Fragment=o}},e.replaceShaderPicking=(e,t,n)=>{let r=e.Fragment;r=vd.substitute(r,"//VTK::Picking::Dec",["uniform vec3 mapperIndex;","uniform int picking;"]).result,r=vd.substitute(r,"//VTK::Picking::Impl","  gl_FragData[0] = picking != 0 ? vec4(mapperIndex,1.0) : gl_FragData[0];").result,e.Fragment=r},e.replaceShaderPositionVC=(e,n,r)=>{t.lastBoundBO.replaceShaderPositionVC(e,n,r)},e.invokeShaderCallbacks=(e,n,r)=>{const o=t.renderable.getViewSpecificProperties().ShadersCallbacks;o&&o.forEach((t=>{t.callback(t.userData,e,n,r)}))},e.setMapperShaderParameters=(e,n,r)=>{if(e.getProgram().isUniformUsed("PrimitiveIDOffset")&&e.getProgram().setUniformi("PrimitiveIDOffset",t.primitiveIDOffset),e.getProgram().isAttributeUsed("vertexWC")&&(e.getVAO().addAttributeArray(e.getProgram(),e.getCABO(),"vertexWC",e.getCABO().getVertexOffset(),e.getCABO().getStride(),t.context.FLOAT,3,!1)||mp("Error setting vertexWC in shader VAO.")),e.getCABO().getElementCount()&&(t.VBOBuildTime.getMTime()>e.getAttributeUpdateTime().getMTime()||e.getShaderSourceTime().getMTime()>e.getAttributeUpdateTime().getMTime())){t.renderable.getCustomShaderAttributes().forEach(((n,r)=>{e.getProgram().isAttributeUsed(`${n}MC`)&&(e.getVAO().addAttributeArray(e.getProgram(),e.getCABO(),`${n}MC`,e.getCABO().getCustomData()[r].offset,e.getCABO().getStride(),t.context.FLOAT,e.getCABO().getCustomData()[r].components,!1)||mp(`Error setting ${n}MC in shader VAO.`))})),e.getProgram().isAttributeUsed("tcoordMC")&&e.getCABO().getTCoordOffset()?e.getVAO().addAttributeArray(e.getProgram(),e.getCABO(),"tcoordMC",e.getCABO().getTCoordOffset(),e.getCABO().getStride(),t.context.FLOAT,e.getCABO().getTCoordComponents(),!1)||mp("Error setting tcoordMC in shader VAO."):e.getVAO().removeAttributeArray("tcoordMC"),e.getProgram().isAttributeUsed("scalarColor")&&e.getCABO().getColorComponents()?e.getVAO().addAttributeArray(e.getProgram(),e.getCABO().getColorBO(),"scalarColor",e.getCABO().getColorOffset(),e.getCABO().getColorBOStride(),t.context.UNSIGNED_BYTE,4,!0)||mp("Error setting scalarColor in shader VAO."):e.getVAO().removeAttributeArray("scalarColor"),t.internalColorTexture&&e.getProgram().isUniformUsed("texture1")&&t.internalColorTexture.getTextureUnit()>-1&&e.getProgram().setUniformi("texture1",t.internalColorTexture.getTextureUnit());const o=t.openGLActor2D.getActiveTextures();if(o)for(let t=0;t<o.length;++t){const n=o[t].getTextureUnit(),r=`texture${n+1}`;e.getProgram().isUniformUsed(r)&&e.getProgram().setUniformi(r,n)}e.setMapperShaderParameters(n,r,t._openGLRenderer.getTiledSizeAndOrigin());const a=t._openGLRenderer.getSelector();e.getProgram().setUniform3fArray("mapperIndex",a?a.getPropColorValue():[0,0,0]),e.getProgram().setUniformi("picking",a?a.getCurrentPass()+1:0)}},e.setPropertyShaderParameters=(e,n,r)=>{const o=t.renderable.getColorMapColors();if(!o||0===o.getNumberOfComponents()){const t=e.getProgram(),n=r.getProperty(),o=n.getOpacity();t.setUniformf("opacityUniform",o);const a=n.getColor();t.setUniform3fArray("diffuseColorUniform",a)}},e.setLightingShaderParameters=(e,t,n)=>{},e.setCameraShaderParameters=(e,n,r)=>{const o=e.getProgram(),a=e.getCABO().getCoordShiftAndScaleEnabled()?e.getCABO().getInverseShiftAndScaleMatrix():null,i=n.getRenderWindow().getViews()[0].getViewportSize(n),s=n.getViewport(),l=r.getActualPositionCoordinate().getComputedDoubleViewportValue(n),c=[0,0,1,1],u=[0,0,1,1];if(u[0]=s[0]>=c[0]?s[0]:c[0],u[1]=s[1]>=c[1]?s[1]:c[1],u[2]=s[2]<=c[2]?s[2]:c[2],u[3]=s[3]<=c[3]?s[3]:c[3],u[0]>=u[2])return;if(u[1]>=u[3])return;i[0]=Oo(i[0]*(u[2]-u[0])/(s[2]-s[0])),i[1]=Oo(i[1]*(u[3]-u[1])/(s[3]-s[1]));const d=t._openGLRenderer.getParent().getSize(),p=Oo(l[0]-(u[0]-s[0])*d[0]),f=Oo(l[1]-(u[1]-s[1])*d[1]),g=-p;let m=-p+i[0];const h=-f;let v=-f+i[1];g===m&&(m=g+1),h===v&&(v=h+1);const T=x(new Float64Array(16));var b,A,C;T[0]=2/(m-g),T[5]=2/(v-h),T[3]=-1*(m+g)/(m-g),T[7]=-1*(v+h)/(v-h),T[10]=0,T[11]=r.getProperty().getDisplayLocation()===dp?-1:1,T[15]=1,y(T,T),o.setUniformMatrix("WCVCMatrix",(b=[T,a],A=H,C=t.tmpMat4,A.identity(C),b.reduce(((e,t,n)=>0===n?t?A.copy(e,t):A.identity(e):t?A.multiply(e,e,t):e),C)))},e.getAllocatedGPUMemoryInBytes=()=>{let e=0;return t.primitives.forEach((t=>{e+=t.getAllocatedGPUMemoryInBytes()})),e}}(e,t)}),"vtkOpenGLPolyDataMapper2D");vn("vtkMapper2D",xp);var yp={Orientation:{HORIZONTAL:"horizontal",VERTICAL:"vertical",AUTO:"auto"}};const{VectorMode:bp}=yl,{Orientation:Ap}=yp;function Cp(e,t,n){e.strokeStyle=t.strokeColor,e.lineWidth=t.strokeSize,e.fillStyle=t.fontColor;const r=t.fontSize??n;e.font=`${t.fontStyle} ${r}px ${t.fontFamily}`}function Sp(e,t){return e=>{const n=e.getLastSize(),r=(n[0]/700)**.8,o=(n[1]/700)**.8,a=Math.min(r,o),i=e.getAxisTextStyle(),s=e.getTickTextStyle();Object.assign(i,t.axisTextStyle),Object.assign(s,t.tickTextStyle),void 0===i.fontSize&&(i.fontSize=Math.max(24*a,12)),void 0===s.fontSize&&(e.getLastAspectRatio()>1?s.fontSize=Math.max(20*a,10):s.fontSize=Math.max(16*a,10));const l=e.updateTextureAtlas();e.setTopTitle(!1);const c=e.getBoxSizeByReference();let u=!1;if(u=t.orientation===Ap.VERTICAL||t.orientation!==Ap.HORIZONTAL&&e.getLastAspectRatio()>1,u)e.setTickLabelPixelOffset(.3*s.fontSize),l.titleWidth<=l.tickWidth+e.getTickLabelPixelOffset()+.8*s.fontSize?(e.setTopTitle(!0),e.setAxisTitlePixelOffset(.2*s.fontSize),c[0]=2*(l.tickWidth+e.getTickLabelPixelOffset()+.8*s.fontSize)/n[0],e.setBoxPosition([.98-c[0],-.92])):(e.setAxisTitlePixelOffset(.2*s.fontSize),c[0]=2*(l.titleHeight+e.getAxisTitlePixelOffset()+l.tickWidth+e.getTickLabelPixelOffset()+.8*s.fontSize)/n[0],e.setBoxPosition([.99-c[0],-.92])),c[1]=Math.max(1.2,Math.min(1.84/o,1.84));else{e.setAxisTitlePixelOffset(1.2*s.fontSize),e.setTickLabelPixelOffset(.1*s.fontSize);const t=2*(.8*s.fontSize+l.titleHeight+e.getAxisTitlePixelOffset())/n[1],r=2*l.tickWidth/n[0];c[0]=Math.min(1.9,Math.max(1.4,1.4*r*(e.getTicks().length+3))),c[1]=t,e.setBoxPosition([-.5*c[0],-.97])}e.recomputeBarSegments(l)}}function Pp(e,t){return e=>{const t=e.getLastTickBounds(),n=$r().domain([t[0],t[1]]),r=n.ticks(5),o=n.tickFormat(5);e.setTicks(r),e.setTickStrings(r.map(o))}}const wp=sn.newInstance(((e,t,n={renderable:null})=>{Object.assign(t,{},n),sn.obj(e,t),sn.setGet(e,t,["axisTitlePixelOffset","tickLabelPixelOffset","renderable","topTitle","ticks","tickStrings","tickPositions"]),sn.get(e,t,["lastSize","lastAspectRatio","lastTickBounds","axisTextStyle","tickTextStyle","barActor","tmActor"]),sn.getArray(e,t,["boxPosition","boxSize"]),sn.setArray(e,t,["boxPosition","boxSize"],2),t.forceUpdate=!1,t.lastRebuildTime={},sn.obj(t.lastRebuildTime,{mtime:0}),t.lastSize=[-1,-1],t.tmCanvas=document.createElement("canvas"),t.tmContext=t.tmCanvas.getContext("2d"),t._tmAtlas=new Map,t.barMapper=Ql.newInstance(),t.barMapper.setInterpolateScalarsBeforeMapping(!0),t.barMapper.setUseLookupTableScalarRange(!0),t.polyData=Ru.newInstance(),t.barMapper.setInputData(t.polyData),t.barActor=fs.newInstance(),t.barActor.setMapper(t.barMapper),t.tmPolyData=Ru.newInstance(),t.tmMapper=Ql.newInstance(),t.tmMapper.setInputData(t.tmPolyData),t.tmTexture=Eu.newInstance({resizable:!0}),t.tmTexture.setInterpolate(!1),t.tmActor=fs.newInstance({parentProp:e}),t.tmActor.setMapper(t.tmMapper),t.tmActor.addTexture(t.tmTexture),t.barPosition=[0,0],t.barSize=[0,0],t.boxPosition=[.88,-.92],t.boxSize=[.1,1.1],t.lastTickBounds=[],function(e,t){t.classHierarchy.push("vtkScalarBarActorHelper"),e.setRenderable=n=>{t.renderable!==n&&(t.renderable=n,t.barActor.setProperty(n.getProperty()),t.barActor.setParentProp(n),t.barActor.setCoordinateSystemToDisplay(),t.tmActor.setProperty(n.getProperty()),t.tmActor.setParentProp(n),t.tmActor.setCoordinateSystemToDisplay(),t.generateTicks=n.generateTicks,t.axisTextStyle={...n.getAxisTextStyle()},t.tickTextStyle={...n.getTickTextStyle()},e.modified())},e.updateAPISpecificData=(n,r,o)=>{t.lastSize[0]===n[0]&&t.lastSize[1]===n[1]||(t.lastSize[0]=n[0],t.lastSize[1]=n[1],t.lastAspectRatio=n[0]/n[1],t.forceUpdate=!0);const a=t.renderable.getScalarsToColors();if(a&&t.renderable.getVisibility()&&(t.barMapper.setLookupTable(a),t.camera=r,t.renderWindow=o,t.forceUpdate||Math.max(a.getMTime(),e.getMTime(),t.renderable.getMTime())>t.lastRebuildTime.getMTime())){const n=a.getMappingRange();if(t.lastTickBounds=[...n],t.renderable.getGenerateTicks()(e),t.renderable.getAutomated())t.renderable.getAutoLayout()(e);else{t.axisTextStyle={...t.renderable.getAxisTextStyle()},t.tickTextStyle={...t.renderable.getTickTextStyle()},t.barPosition=[...t.renderable.getBarPosition()],t.barSize=[...t.renderable.getBarSize()],t.boxPosition=[...t.renderable.getBoxPosition()],t.boxSize=[...t.renderable.getBoxSize()],t.axisTitlePixelOffset=t.renderable.getAxisTitlePixelOffset(),t.tickLabelPixelOffset=t.renderable.getTickLabelPixelOffset();const n=e.updateTextureAtlas();e.recomputeBarSegments(n)}e.updatePolyDataForLabels(),e.updatePolyDataForBarSegments(),t.lastRebuildTime.modified(),t.forceUpdate=!1}},e.updateTextureAtlas=()=>{t.tmContext.textBaseline="bottom",t.tmContext.textAlign="left";const n={},r=new Map;let o=0,a=1;Cp(t.tmContext,t.axisTextStyle,18);let i=t.tmContext.measureText(t.renderable.getAxisLabel()),s={height:i.actualBoundingBoxAscent+2,startingHeight:a,width:i.width+2,textStyle:t.axisTextStyle};r.set(t.renderable.getAxisLabel(),s),a+=s.height,o=s.width,n.titleWidth=s.width,n.titleHeight=s.height,n.tickWidth=0,n.tickHeight=0,Cp(t.tmContext,t.tickTextStyle,14);const l=[...e.getTickStrings(),"NaN","Below","Above"];for(let e=0;e<l.length;e++)r.has(l[e])||(i=t.tmContext.measureText(l[e]),s={height:i.actualBoundingBoxAscent+2,startingHeight:a,width:i.width+2,textStyle:t.tickTextStyle},r.set(l[e],s),a+=s.height,o<s.width&&(o=s.width),n.tickWidth<s.width&&(n.tickWidth=s.width),n.tickHeight<s.height&&(n.tickHeight=s.height));return o=Bo(o),a=Bo(a),r.forEach((e=>{e.tcoords=[0,(a-e.startingHeight-e.height)/a,e.width/o,(a-e.startingHeight-e.height)/a,e.width/o,(a-e.startingHeight)/a,0,(a-e.startingHeight)/a]})),t.tmCanvas.width=o,t.tmCanvas.height=a,t.tmContext.textBaseline="bottom",t.tmContext.textAlign="left",t.tmContext.clearRect(0,0,o,a),r.forEach(((e,n)=>{const r=e.textStyle===t.axisTextStyle?18:14;Cp(t.tmContext,e.textStyle,r),t.tmContext.fillText(n,1,e.startingHeight+e.height-1)})),t.tmTexture.setCanvas(t.tmCanvas),t.tmTexture.modified(),t._tmAtlas=r,n},e.computeBarSize=e=>{t.vertical=t.boxSize[1]>t.boxSize[0];const n=2*e.tickHeight/t.lastSize[1],r=[1,1];if(t.vertical){const o=2*(e.tickWidth+t.tickLabelPixelOffset)/t.lastSize[0];if(t.topTitle){const n=2*(e.titleHeight+t.axisTitlePixelOffset)/t.lastSize[1];t.barSize[0]=t.boxSize[0]-o,t.barSize[1]=t.boxSize[1]-n}else{const n=2*(e.titleHeight+t.axisTitlePixelOffset)/t.lastSize[0];t.barSize[0]=t.boxSize[0]-n-o,t.barSize[1]=t.boxSize[1]}t.barPosition[0]=t.boxPosition[0]+o,t.barPosition[1]=t.boxPosition[1],r[1]=n}else{const n=(2*e.tickWidth-8)/t.lastSize[0],o=2*(e.titleHeight+t.axisTitlePixelOffset)/t.lastSize[1];t.barSize[0]=t.boxSize[0],t.barPosition[0]=t.boxPosition[0],t.barSize[1]=t.boxSize[1]-o,t.barPosition[1]=t.boxPosition[1],r[0]=n}return r},e.recomputeBarSegments=n=>{const r=e.computeBarSize(n);t.barSegments=[];const o=[0,0],a=t.vertical?1:0,i=t.vertical?.01:.02;function s(e,n){t.barSegments.push({corners:[[...o],[o[0]+r[0],o[1]],[o[0]+r[0],o[1]+r[1]],[o[0],o[1]+r[1]]],scalars:n,title:e}),o[a]+=r[a]+i}t.renderable.getDrawNanAnnotation()&&t.renderable.getScalarsToColors().getNanColor()&&s("NaN",[NaN,NaN,NaN,NaN]),t.renderable.getDrawBelowRangeSwatch()&&t.renderable.getScalarsToColors().getUseBelowRangeColor?.()&&s("Below",[-.1,-.1,-.1,-.1]);const l=t.renderable.getScalarsToColors().getUseAboveRangeColor?.();o[a]+=i;const c=r[a];r[a]=l?1-2*i-r[a]-o[a]:1-i-o[a],s("ticks",t.vertical?[0,0,.995,.995]:[0,.995,.995,0]),t.renderable.getDrawAboveRangeSwatch()&&l&&(r[a]=c,o[a]+=i,s("Above",[1.1,1.1,1.1,1.1]))};const n=new Float64Array(3);e.createPolyDataForOneLabel=(e,r,o,a,i,s)=>{const l=t._tmAtlas.get(e);if(!l)return;let c=s.ptIdx,u=s.cellIdx;n[0]=(.5*r[0]+.5)*t.lastSize[0],n[1]=(.5*r[1]+.5)*t.lastSize[1],n[2]=r[2],n[0]+=i[0],n[1]+=i[1];const d=[],p="vertical"===a?[1,0]:[0,1];"vertical"===a?(d[0]=l.width,d[1]=-l.height,"middle"===o[0]?n[1]-=l.width/2:"right"===o[0]&&(n[1]-=l.width),"middle"===o[1]?n[0]+=l.height/2:"top"===o[1]&&(n[0]+=l.height)):(d[0]=l.width,d[1]=l.height,"middle"===o[0]?n[0]-=l.width/2:"right"===o[0]&&(n[0]-=l.width),"middle"===o[1]?n[1]-=l.height/2:"top"===o[1]&&(n[1]-=l.height)),s.points[3*c]=n[0],s.points[3*c+1]=n[1],s.points[3*c+2]=n[2],s.tcoords[2*c]=l.tcoords[0],s.tcoords[2*c+1]=l.tcoords[1],c++,n[p[0]]+=d[0],s.points[3*c]=n[0],s.points[3*c+1]=n[1],s.points[3*c+2]=n[2],s.tcoords[2*c]=l.tcoords[2],s.tcoords[2*c+1]=l.tcoords[3],c++,n[p[1]]+=d[1],s.points[3*c]=n[0],s.points[3*c+1]=n[1],s.points[3*c+2]=n[2],s.tcoords[2*c]=l.tcoords[4],s.tcoords[2*c+1]=l.tcoords[5],c++,n[p[0]]-=d[0],s.points[3*c]=n[0],s.points[3*c+1]=n[1],s.points[3*c+2]=n[2],s.tcoords[2*c]=l.tcoords[6],s.tcoords[2*c+1]=l.tcoords[7],c++,s.polys[4*u]=3,s.polys[4*u+1]=c-4,s.polys[4*u+2]=c-3,s.polys[4*u+3]=c-2,u++,s.polys[4*u]=3,s.polys[4*u+1]=c-4,s.polys[4*u+2]=c-2,s.polys[4*u+3]=c-1,s.ptIdx+=4,s.cellIdx+=2};const r=new Float64Array(3);e.updatePolyDataForLabels=()=>{const n=e.getTickStrings().length+t.barSegments.length,o=4*n,a=2*n,i=new Float64Array(3*o),s=new Uint16Array(4*a),l=new Float32Array(2*o),c={ptIdx:0,cellIdx:0,polys:s,points:i,tcoords:l},u=t.vertical?0:1,d=t.vertical?1:0;r[2]=-.99;const p=t.vertical?["right","middle"]:["middle","bottom"];let f=[0,1];const g=[0,0];t.vertical?(g[0]=-t.tickLabelPixelOffset,t.topTitle?(r[0]=t.boxPosition[0]+.5*t.boxSize[0],r[1]=t.barPosition[1]+t.barSize[1],e.createPolyDataForOneLabel(t.renderable.getAxisLabel(),r,["middle","bottom"],"horizontal",[0,t.axisTitlePixelOffset],c)):(r[0]=t.barPosition[0]+t.barSize[0],r[1]=t.barPosition[1]+.5*t.barSize[1],e.createPolyDataForOneLabel(t.renderable.getAxisLabel(),r,["middle","top"],"vertical",[t.axisTitlePixelOffset,0],c)),f=[-1,0]):(g[1]=t.tickLabelPixelOffset,r[0]=t.barPosition[0]+.5*t.barSize[0],r[1]=t.barPosition[1]+t.barSize[1],e.createPolyDataForOneLabel(t.renderable.getAxisLabel(),r,["middle","bottom"],"horizontal",[0,t.axisTitlePixelOffset],c)),r[u]=t.barPosition[u]+(.5*f[u]+.5)*t.barSize[u],r[d]=t.barPosition[d]+.5*t.barSize[d];let m=null;for(let n=0;n<t.barSegments.length;n++){const o=t.barSegments[n];"ticks"===o.title?m=o:(r[d]=t.barPosition[d]+.5*t.barSize[d]*(o.corners[2][d]+o.corners[0][d]),e.createPolyDataForOneLabel(o.title,r,p,"horizontal",g,c))}const h=t.barPosition[d]+t.barSize[d]*m.corners[0][d],v=t.barSize[d]*(m.corners[2][d]-m.corners[0][d]),T=e.getTicks(),x=e.getTickStrings(),y=e.getTickPositions();for(let n=0;n<T.length;n++){const o=y?y[n]:(T[n]-t.lastTickBounds[0])/(t.lastTickBounds[1]-t.lastTickBounds[0]);r[d]=h+v*o,e.createPolyDataForOneLabel(x[n],r,p,"horizontal",g,c)}const b=Is.newInstance({numberOfComponents:2,values:l,name:"TextureCoordinates"});t.tmPolyData.getPointData().setTCoords(b),t.tmPolyData.getPoints().setData(i,3),t.tmPolyData.getPoints().modified(),t.tmPolyData.getPolys().setData(s,1),t.tmPolyData.getPolys().modified(),t.tmPolyData.modified()},e.updatePolyDataForBarSegments=()=>{const e=t.renderable.getScalarsToColors();let n=0;t.renderable.getDrawNanAnnotation()&&e.getNanColor()&&(n+=1),t.renderable.getDrawBelowRangeSwatch()&&e.getUseBelowRangeColor?.()&&(n+=1),t.renderable.getDrawAboveRangeSwatch()&&e.getUseAboveRangeColor?.()&&(n+=1);const o=4*(1+n),a=o;let i=1;e.getVectorMode()===bp.COMPONENT&&(i=e.getVectorComponent()+1);const s=new Float64Array(3*o),l=new Uint16Array(5*a),c=new Float32Array(o*i);let u=0,d=0;for(let e=0;e<t.barSegments.length;e++){const n=t.barSegments[e];for(let e=0;e<4;e++){r[0]=t.barPosition[0]+n.corners[e][0]*t.barSize[0],r[1]=t.barPosition[1]+n.corners[e][1]*t.barSize[1],s[3*u]=(.5*r[0]+.5)*t.lastSize[0],s[3*u+1]=(.5*r[1]+.5)*t.lastSize[1],s[3*u+2]=r[2];for(let r=0;r<i;r++)c[u*i+r]=t.lastTickBounds[0]+n.scalars[e]*(t.lastTickBounds[1]-t.lastTickBounds[0]);u++}l[5*d]=4,l[5*d+1]=u-4,l[5*d+2]=u-3,l[5*d+3]=u-2,l[5*d+4]=u-1,d++}const p=Is.newInstance({numberOfComponents:i,values:c,name:"Scalars"});t.polyData.getPointData().setScalars(p),t.polyData.getPoints().setData(s,3),t.polyData.getPoints().modified(),t.polyData.getPolys().setData(l,1),t.polyData.getPolys().modified(),t.polyData.modified()}}(e,t)}),"vtkScalarBarActorHelper");function Ip(e,t,n={}){Object.assign(t,function(e){return{automated:!0,autoLayout:null,axisLabel:"Scalar Value",barPosition:[0,0],barSize:[0,0],boxPosition:[.88,-.92],boxSize:[.1,1.1],scalarToColors:null,axisTitlePixelOffset:36,axisTextStyle:{fontColor:"white",fontStyle:"normal",fontSize:void 0,fontFamily:"serif"},tickLabelPixelOffset:14,tickTextStyle:{fontColor:"white",fontStyle:"normal",fontSize:void 0,fontFamily:"serif"},generateTicks:null,drawNanAnnotation:!0,drawBelowRangeSwatch:!0,drawAboveRangeSwatch:!0,orientation:null,...e}}(n)),t.autoLayout||(t.autoLayout=Sp(0,t)),t.generateTicks||(t.generateTicks=Pp()),fs.extend(e,t,n),e.getProperty().setDiffuse(0),e.getProperty().setAmbient(1),sn.setGet(e,t,["automated","autoLayout","axisTitlePixelOffset","axisLabel","scalarsToColors","tickLabelPixelOffset","generateTicks","drawNanAnnotation","drawBelowRangeSwatch","drawAboveRangeSwatch","orientation"]),sn.get(e,t,["axisTextStyle","tickTextStyle"]),sn.getArray(e,t,["barPosition","barSize","boxPosition","boxSize"]),sn.setArray(e,t,["barPosition","barSize","boxPosition","boxSize"],2),function(e,t){t.classHierarchy.push("vtkScalarBarActor"),e.setTickTextStyle=n=>{t.tickTextStyle={...t.tickTextStyle,...n},e.modified()},e.setAxisTextStyle=n=>{t.axisTextStyle={...t.axisTextStyle,...n},e.modified()},e.setOrientationToHorizontal=()=>e.setOrientation(Ap.HORIZONTAL),e.setOrientationToVertical=()=>e.setOrientation(Ap.VERTICAL),e.resetAutoLayoutToDefault=()=>{e.setAutoLayout(Sp(0,t))},e.resetGenerateTicksToDefault=()=>{e.setGenerateTicks(Pp())}}(e,t)}var Op={newInstance:sn.newInstance(Ip,"vtkScalarBarActor"),extend:Ip,newScalarBarActorHelper:wp,...yp};const Rp={};vn("vtkScalarBarActor",Xt((function(e,t,n={}){Object.assign(t,Rp,n),pn.extend(e,t,n),t.scalarBarActorHelper=Op.newScalarBarActorHelper(),function(e,t){t.classHierarchy.push("vtkOpenGLScalarBarActor"),e.buildPass=n=>{n&&(t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getParent(),t.scalarBarActorHelper.getRenderable()||t.scalarBarActorHelper.setRenderable(t.renderable),e.prepareNodes(),e.addMissingNode(t.scalarBarActorHelper.getBarActor()),e.addMissingNode(t.scalarBarActorHelper.getTmActor()),e.removeUnusedNodes())},e.opaquePass=(e,n)=>{if(e){const e=t._openGLRenderer?t._openGLRenderer.getRenderable().getActiveCamera():null,n=t._openGLRenderer.getTiledSizeAndOrigin();t.scalarBarActorHelper.updateAPISpecificData([n.usize,n.vsize],e,t._openGLRenderWindow.getRenderable())}}}(e,t)}),"vtkOpenGLScalarBarActor"));const{vtkErrorMacro:Mp}=ln;const Dp={context:null};const Ep=Xt((function(e,t,n={}){Object.assign(t,Dp,n),pn.extend(e,t,n),t.openGLTexture=Hd.newInstance(),t.tris=Sd.newInstance(),t.keyMatrixTime={},Vt(t.keyMatrixTime,{mtime:0}),t.keyMatrices={normalMatrix:c(new Float64Array(9)),mcwc:x(new Float64Array(16))},Gt(e,t,["context"]),Bt(e,t,["activeTextures"]),function(e,t){t.classHierarchy.push("vtkOpenGLSkybox"),e.buildPass=n=>{if(n){t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getParent(),t.context=t._openGLRenderWindow.getContext(),t.tris.setOpenGLRenderWindow(t._openGLRenderWindow),t.openGLTexture.setOpenGLRenderWindow(t._openGLRenderWindow);const n=t._openGLRenderer.getRenderable();t.openGLCamera=t._openGLRenderer.getViewNodeFor(n.getActiveCamera(),t.openGLCamera)}},e.queryPass=(e,n)=>{if(e){if(!t.renderable||!t.renderable.getVisibility())return;n.incrementOpaqueActorCount()}},e.opaquePass=(n,r)=>{if(n&&!t._openGLRenderer.getSelector()){e.updateBufferObjects(),t.context.depthMask(!0),t._openGLRenderWindow.getShaderCache().readyShaderProgram(t.tris.getProgram()),t.openGLTexture.render(t._openGLRenderWindow);const n=t.openGLTexture.getTextureUnit();t.tris.getProgram().setUniformi("sbtexture",n);const r=t._openGLRenderer.getRenderable(),o=t.openGLCamera.getKeyMatrices(r),a=new Float64Array(16);if(b(a,o.wcpc),t.tris.getProgram().setUniformMatrix("IMCPCMatrix",a),"box"===t.lastFormat){const e=r.getActiveCamera().getPosition();t.tris.getProgram().setUniform3f("camPos",e[0],e[1],e[2])}t.tris.getVAO().bind(),t.context.drawArrays(t.context.TRIANGLES,0,t.tris.getCABO().getElementCount()),t.tris.getVAO().release(),t.openGLTexture.deactivate()}},e.updateBufferObjects=()=>{if(!t.tris.getCABO().getElementCount()){const e=new Float32Array(12);for(let t=0;t<4;t++)e[3*t]=t%2*2-1,e[3*t+1]=t>1?1:-1,e[3*t+2]=1;const n=Is.newInstance({numberOfComponents:3,values:e});n.setName("points");const r=new Uint16Array(8);r[0]=3,r[1]=0,r[2]=1,r[3]=3,r[4]=3,r[5]=0,r[6]=3,r[7]=2;const o=Is.newInstance({numberOfComponents:1,values:r});t.tris.getCABO().createVBO(o,"polys",rs.SURFACE,{points:n,cellOffset:0})}t.renderable.getFormat()!==t.lastFormat&&(t.lastFormat=t.renderable.getFormat(),"box"===t.lastFormat&&t.tris.setProgram(t._openGLRenderWindow.getShaderCache().readyShaderProgramArray("//VTK::System::Dec\n             attribute vec3 vertexMC;\n             uniform mat4 IMCPCMatrix;\n             varying vec3 TexCoords;\n             void main () {\n              gl_Position = vec4(vertexMC.xyz, 1.0);\n              vec4 wpos = IMCPCMatrix * gl_Position;\n              TexCoords = wpos.xyz/wpos.w;\n             }","//VTK::System::Dec\n             //VTK::Output::Dec\n             varying vec3 TexCoords;\n             uniform samplerCube sbtexture;\n             uniform vec3 camPos;\n             void main () {\n               // skybox looks from inside out\n               // which means we have to adjust\n               // our tcoords. Otherwise text would\n               // be flipped\n               vec3 tc = normalize(TexCoords - camPos);\n               if (abs(tc.z) < max(abs(tc.x),abs(tc.y)))\n               {\n                 tc = vec3(1.0, 1.0, -1.0) * tc;\n               }\n               else\n               {\n                 tc = vec3(-1.0, 1.0, 1.0) * tc;\n               }\n               gl_FragData[0] = textureCube(sbtexture, tc);\n             }","")),"background"===t.lastFormat&&t.tris.setProgram(t._openGLRenderWindow.getShaderCache().readyShaderProgramArray("//VTK::System::Dec\n             attribute vec3 vertexMC;\n             uniform mat4 IMCPCMatrix;\n             varying vec2 TexCoords;\n             void main () {\n              gl_Position = vec4(vertexMC.xyz, 1.0);\n              vec4 wpos = IMCPCMatrix * gl_Position;\n              TexCoords = vec2(vertexMC.x, vertexMC.y)*0.5 + 0.5;\n             }","//VTK::System::Dec\n             //VTK::Output::Dec\n             varying vec2 TexCoords;\n             uniform sampler2D sbtexture;\n             void main () {\n               gl_FragData[0] = texture2D(sbtexture, TexCoords);\n             }","")),t.tris.getShaderSourceTime().modified(),t.tris.getVAO().bind(),t.tris.getVAO().addAttributeArray(t.tris.getProgram(),t.tris.getCABO(),"vertexMC",t.tris.getCABO().getVertexOffset(),t.tris.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||Mp("Error setting vertexMC in shader VAO."));const e=t.renderable.getTextures();e.length||Mp("vtkSkybox requires a texture map"),t.openGLTexture.getRenderable()!==e[0]&&(t.openGLTexture.releaseGraphicsResources(t._openGLRenderWindow),t.openGLTexture.setRenderable(e[0]))}}(e,t)}));vn("vtkSkybox",Ep);const{FieldAssociations:Vp}=Qs;const Lp={fieldAssociation:Vp.FIELD_ASSOCIATION_CELLS,captureZValues:!1};function Bp(e,t,n={}){Object.assign(t,Lp,n),sn.obj(e,t),sn.setGet(e,t,["fieldAssociation","captureZValues"]),function(e,t){t.classHierarchy.push("vtkHardwareSelector"),e.getSourceDataAsync=async(e,t,n,r,o)=>{},e.selectAsync=async(t,n,r,o,a)=>{const i=await e.getSourceDataAsync(t,n,r,o,a);return i?i.generateSelection(n,r,o,a):[]}}(e,t)}var Fp={newInstance:sn.newInstance(Bp,"vtkHardwareSelector"),extend:Bp};const Np={glFramebuffer:null,colorBuffers:null,depthTexture:null,previousDrawBinding:0,previousReadBinding:0,previousDrawBuffer:0,previousReadBuffer:0,previousActiveFramebuffer:null};function kp(e,t,n={}){Object.assign(t,Np,n),Vt(e,t),t.colorBuffers&&Tt("you cannot initialize colorBuffers through the constructor. You should call setColorBuffer() instead."),t.colorBuffers=[],Ut(e,t,["colorBuffers"]),function(e,t){t.classHierarchy.push("vtkFramebuffer"),e.getBothMode=()=>t.context.FRAMEBUFFER,e.saveCurrentBindingsAndBuffers=t=>{const n=void 0!==t?t:e.getBothMode();e.saveCurrentBindings(n),e.saveCurrentBuffers(n)},e.saveCurrentBindings=e=>{if(!t.context)return void Tt("you must set the OpenGLRenderWindow before calling saveCurrentBindings");const n=t.context;t.previousDrawBinding=n.getParameter(t.context.FRAMEBUFFER_BINDING),t.previousActiveFramebuffer=t._openGLRenderWindow.getActiveFramebuffer()},e.saveCurrentBuffers=e=>{},e.restorePreviousBindingsAndBuffers=t=>{const n=void 0!==t?t:e.getBothMode();e.restorePreviousBindings(n),e.restorePreviousBuffers(n)},e.restorePreviousBindings=e=>{if(!t.context)return void Tt("you must set the OpenGLRenderWindow before calling restorePreviousBindings");const n=t.context;n.bindFramebuffer(n.FRAMEBUFFER,t.previousDrawBinding),t._openGLRenderWindow.setActiveFramebuffer(t.previousActiveFramebuffer)},e.restorePreviousBuffers=e=>{},e.bind=(n=null)=>{let r=n;null===r&&(r=t.context.FRAMEBUFFER),t.context.bindFramebuffer(r,t.glFramebuffer);for(let e=0;e<t.colorBuffers.length;e++)t.colorBuffers[e].bind();t._openGLRenderWindow.setActiveFramebuffer(e)},e.create=(e,n)=>{t.context?(t.glFramebuffer=t.context.createFramebuffer(),t.glFramebuffer.width=e,t.glFramebuffer.height=n):Tt("you must set the OpenGLRenderWindow before calling create")},e.setColorBuffer=(e,n=0)=>{const r=t.context;if(!r)return void Tt("you must set the OpenGLRenderWindow before calling setColorBuffer");let o=r.COLOR_ATTACHMENT0;if(n>0){if(!t._openGLRenderWindow.getWebgl2())return void Tt("Using multiple framebuffer attachments requires WebGL 2");o+=n}t.colorBuffers[n]=e,r.framebufferTexture2D(r.FRAMEBUFFER,o,r.TEXTURE_2D,e.getHandle(),0)},e.removeColorBuffer=(e=0)=>{const n=t.context;if(!n)return void Tt("you must set the OpenGLRenderWindow before calling removeColorBuffer");let r=n.COLOR_ATTACHMENT0;if(e>0){if(!t._openGLRenderWindow.getWebgl2())return void Tt("Using multiple framebuffer attachments requires WebGL 2");r+=e}n.framebufferTexture2D(n.FRAMEBUFFER,r,n.TEXTURE_2D,null,0),t.colorBuffers=t.colorBuffers.splice(e,1)},e.setDepthBuffer=e=>{if(t.context)if(t._openGLRenderWindow.getWebgl2()){const n=t.context;n.framebufferTexture2D(n.FRAMEBUFFER,n.DEPTH_ATTACHMENT,n.TEXTURE_2D,e.getHandle(),0)}else Tt("Attaching depth buffer textures to fbo requires WebGL 2");else Tt("you must set the OpenGLRenderWindow before calling setDepthBuffer")},e.removeDepthBuffer=()=>{if(t.context)if(t._openGLRenderWindow.getWebgl2()){const e=t.context;e.framebufferTexture2D(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.TEXTURE_2D,null,0)}else Tt("Attaching depth buffer textures to framebuffers requires WebGL 2");else Tt("you must set the OpenGLRenderWindow before calling removeDepthBuffer")},e.getGLFramebuffer=()=>t.glFramebuffer,e.setOpenGLRenderWindow=n=>{t._openGLRenderWindow!==n&&(e.releaseGraphicsResources(),t._openGLRenderWindow=n,t.context=null,n&&(t.context=t._openGLRenderWindow.getContext()))},e.releaseGraphicsResources=()=>{t.glFramebuffer&&t.context.deleteFramebuffer(t.glFramebuffer)},e.getSize=()=>null==t.glFramebuffer?null:[t.glFramebuffer.width,t.glFramebuffer.height],e.populateFramebuffer=()=>{if(!t.context)return void Tt("you must set the OpenGLRenderWindow before calling populateFrameBuffer");e.bind();const n=t.context,r=Hd.newInstance();r.setOpenGLRenderWindow(t._openGLRenderWindow),r.setMinificationFilter(wd.LINEAR),r.setMagnificationFilter(wd.LINEAR),r.create2DFromRaw({width:t.glFramebuffer.width,height:t.glFramebuffer.height,numComps:4,dataType:ms.UNSIGNED_CHAR,data:null}),e.setColorBuffer(r),t.depthTexture=n.createRenderbuffer(),n.bindRenderbuffer(n.RENDERBUFFER,t.depthTexture),n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t.glFramebuffer.width,t.glFramebuffer.height),n.framebufferRenderbuffer(n.FRAMEBUFFER,n.DEPTH_ATTACHMENT,n.RENDERBUFFER,t.depthTexture)},e.getColorTexture=()=>t.colorBuffers[0]}(e,t)}var Gp={newInstance:Xt(kp,"vtkFramebuffer"),extend:kp};var Up={SelectionContent:{GLOBALIDS:0,PEDIGREEIDS:1,VALUES:2,INDICES:3,FRUSTUM:4,LOCATIONS:5,THRESHOLDS:6,BLOCKS:7,QUERY:8},SelectionField:{CELL:0,POINT:1,FIELD:2,VERTEX:3,EDGE:4,ROW:5}};const _p={contentType:-1,fieldType:-1,properties:null,selectionList:[]};function Kp(e,t,n={}){Object.assign(t,_p,n),sn.obj(e,t),t.properties={},sn.setGet(e,t,["contentType","fieldType","properties","selectionList"]),function(e,t){t.classHierarchy.push("vtkSelectionNode"),e.getBounds=()=>t.points.getBounds()}(e,t)}var zp={newInstance:sn.newInstance(Kp,"vtkSelectionNode"),extend:Kp,...Up};const{PassTypes:Wp}=Fl,{SelectionContent:Hp,SelectionField:jp}=zp,{FieldAssociations:Xp}=Qs,{vtkErrorMacro:qp,vtkDebugMacro:Yp}=sn;function Jp(e){return`${e.propID} ${e.compositeID}`}function Zp(e,t,n,r){if(!n)return 0;return n[4*(t*(r[2]-r[0]+1)+e)+3]}function Qp(e,t,n,r,o=null){if(!n)return 0;const a=4*(t*(r[2]-r[0]+1)+e),i=n[a],s=n[a+1];return 256*(256*n[a+2]+s)+i}function $p(e,t){let n=t;return n<<=24,n|=e,n}function ef(e,t,n,r){const o=n<0?0:n;if(0===o){if(r[0]=t[0],r[1]=t[1],t[0]<e.area[0]||t[0]>e.area[2]||t[1]<e.area[1]||t[1]>e.area[3])return null;const n=[t[0]-e.area[0],t[1]-e.area[1]],o=Qp(n[0],n[1],e.pixBuffer[Wp.ACTOR_PASS],e.area,"getPixelInformationWithData1");if(o<=0||o-1>=e.props.length)return null;const a={valid:!0};a.propID=o-1,a.prop=e.props[a.propID];let i=Qp(n[0],n[1],e.pixBuffer[Wp.COMPOSITE_INDEX_PASS],e.area,"getPixelInformationWithData2");if((i<0||i>16777215)&&(i=0),a.compositeID=i-1,e.captureZValues){const r=4*(n[1]*(e.area[2]-e.area[0]+1)+n[0]);a.zValue=(256*e.zBuffer[r]+e.zBuffer[r+1])/65535,a.displayPosition=t}if(e.pixBuffer[Wp.ID_LOW24]&&0===Zp(n[0],n[1],e.pixBuffer[Wp.ID_LOW24],e.area))return a;const s=Qp(n[0],n[1],e.pixBuffer[Wp.ID_LOW24],e.area,"getPixelInformationWithData3"),l=Qp(n[0],n[1],e.pixBuffer[Wp.ID_HIGH24],e.area,"getPixelInformationWithData4");return a.attributeID=$p(s,l),a}const a=[t[0],t[1]],i=[0,0];let s=ef(e,t,0,r);if(s&&s.valid)return s;for(let t=1;t<o;++t){for(let n=a[1]>t?a[1]-t:0;n<=a[1]+t;++n){if(i[1]=n,a[0]>=t&&(i[0]=a[0]-t,s=ef(e,i,0,r),s&&s.valid))return s;if(i[0]=a[0]+t,s=ef(e,i,0,r),s&&s.valid)return s}for(let n=a[0]>=t?a[0]-(t-1):0;n<=a[0]+(t-1);++n){if(i[0]=n,a[1]>=t&&(i[1]=a[1]-t,s=ef(e,i,0,r),s&&s.valid))return s;if(i[1]=a[1]+t,s=ef(e,i,0,r),s&&s.valid)return s}}return r[0]=t[0],r[1]=t[1],null}function tf(e,t,n,r,o){const a=[];let i=0;return t.forEach(((t,s)=>{const l=zp.newInstance();switch(l.setContentType(Hp.INDICES),e){case Xp.FIELD_ASSOCIATION_CELLS:l.setFieldType(jp.CELL);break;case Xp.FIELD_ASSOCIATION_POINTS:l.setFieldType(jp.POINT);break;default:qp("Unknown field association")}l.getProperties().propID=t.info.propID,l.getProperties().prop=t.info.prop,l.getProperties().compositeID=t.info.compositeID,l.getProperties().attributeID=t.info.attributeID,l.getProperties().pixelCount=t.pixelCount,n&&(l.getProperties().displayPosition=[t.info.displayPosition[0],t.info.displayPosition[1],t.info.zValue],l.getProperties().worldPosition=o.displayToWorld(t.info.displayPosition[0],t.info.displayPosition[1],t.info.zValue,r)),l.setSelectionList(t.attributeIDs),a[i]=l,i++})),a}function nf(e,t){t.classHierarchy.push("vtkOpenGLHardwareSelector"),e.releasePixBuffers=()=>{t.rawPixBuffer=[],t.pixBuffer=[],t.zBuffer=null},e.beginSelection=()=>{t._openGLRenderer=t._openGLRenderWindow.getViewNodeFor(t._renderer,t._openGLRenderer),t.maxAttributeId=0;const n=t._openGLRenderWindow.getSize();if(t.framebuffer){t.framebuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.framebuffer.saveCurrentBindingsAndBuffers();const e=t.framebuffer.getSize();e&&e[0]===n[0]&&e[1]===n[1]?t.framebuffer.bind():(t.framebuffer.create(n[0],n[1]),t.framebuffer.populateFramebuffer())}else t.framebuffer=Gp.newInstance(),t.framebuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.framebuffer.saveCurrentBindingsAndBuffers(),t.framebuffer.create(n[0],n[1]),t.framebuffer.populateFramebuffer();if(t._openGLRenderer.clear(),t._openGLRenderer.setSelector(e),t.hitProps={},t.propPixels={},t.props=[],e.releasePixBuffers(),t.fieldAssociation===Xp.FIELD_ASSOCIATION_POINTS){const e=t._openGLRenderWindow.getContext(),n=e.isEnabled(e.BLEND);e.disable(e.BLEND),t._openGLRenderWindow.traverseAllPasses(),n&&e.enable(e.BLEND)}},e.endSelection=()=>{t.hitProps={},t._openGLRenderer.setSelector(null),t.framebuffer.restorePreviousBindingsAndBuffers()},e.preCapturePass=()=>{const e=t._openGLRenderWindow.getContext();t.originalBlending=e.isEnabled(e.BLEND),e.disable(e.BLEND)},e.postCapturePass=()=>{const e=t._openGLRenderWindow.getContext();t.originalBlending&&e.enable(e.BLEND)},e.select=()=>{let n=null;return e.captureBuffers()&&(n=e.generateSelection(t.area[0],t.area[1],t.area[2],t.area[3]),e.releasePixBuffers()),n},e.getSourceDataAsync=async(n,r,o,a,i)=>{if(t._renderer=n,void 0===r){const n=t._openGLRenderWindow.getSize();e.setArea(0,0,n[0]-1,n[1]-1)}else e.setArea(r,o,a,i);if(!e.captureBuffers())return!1;const s={area:[...t.area],pixBuffer:[...t.pixBuffer],captureZValues:t.captureZValues,zBuffer:t.zBuffer,props:[...t.props],fieldAssociation:t.fieldAssociation,renderer:n,openGLRenderWindow:t._openGLRenderWindow};return s.generateSelection=(...e)=>function(e,t,n,r,o){const a=Math.floor(t),i=Math.floor(n),s=Math.floor(r),l=Math.floor(o),c=new Map,u=[0,0];for(let t=i;t<=l;t++)for(let n=a;n<=s;n++){const r=ef(e,[n,t],0,u);if(r&&r.valid){const t=Jp(r);if(c.has(t)){const n=c.get(t);n.pixelCount++,e.captureZValues&&r.zValue<n.info.zValue&&(n.info=r),-1===n.attributeIDs.indexOf(r.attributeID)&&n.attributeIDs.push(r.attributeID)}else c.set(t,{info:r,pixelCount:1,attributeIDs:[r.attributeID]})}}return tf(e.fieldAssociation,c,e.captureZValues,e.renderer,e.openGLRenderWindow)}(s,...e),s},e.captureBuffers=()=>{if(!t._renderer||!t._openGLRenderWindow)return qp("Renderer and view must be set before calling Select."),!1;t._openGLRenderer=t._openGLRenderWindow.getViewNodeFor(t._renderer,t._openGLRenderer),t._openGLRenderWindow.getRenderable().preRender(),e.invokeEvent({type:"StartEvent"}),t.originalBackground=t._renderer.getBackgroundByReference(),t._renderer.setBackground(0,0,0,0);const n=t._openGLRenderWindow.getRenderPasses();e.beginSelection();const r=[];for(t.currentPass=Wp.MIN_KNOWN_PASS;t.currentPass<=Wp.MAX_KNOWN_PASS;t.currentPass++)e.passRequired(t.currentPass)&&(e.preCapturePass(t.currentPass),t.captureZValues&&t.currentPass===Wp.ACTOR_PASS&&"function"==typeof n[0].requestDepth&&"function"==typeof n[0].getFramebuffer?(n[0].requestDepth(),t._openGLRenderWindow.traverseAllPasses()):t._openGLRenderWindow.traverseAllPasses(),e.postCapturePass(t.currentPass),e.savePixelBuffer(t.currentPass),r.push(t.currentPass));return r.forEach((n=>{t.currentPass=n,e.processPixelBuffers()})),t.currentPass=Wp.MAX_KNOWN_PASS,e.endSelection(),t._renderer.setBackground(t.originalBackground),e.invokeEvent({type:"EndEvent"}),!0},e.processPixelBuffers=()=>{t.props.forEach(((n,r)=>{e.isPropHit(r)&&n.processSelectorPixelBuffers(e,t.propPixels[r])}))},e.passRequired=e=>{if(e===Wp.ID_HIGH24){if(t.fieldAssociation===Xp.FIELD_ASSOCIATION_POINTS)return t.maximumPointId>16777215;if(t.fieldAssociation===Xp.FIELD_ASSOCIATION_CELLS)return t.maximumCellId>16777215}return!0},e.savePixelBuffer=n=>{if(t.pixBuffer[n]=t._openGLRenderWindow.getPixelData(t.area[0],t.area[1],t.area[2],t.area[3]),!t.rawPixBuffer[n]){const e=(t.area[2]-t.area[0]+1)*(t.area[3]-t.area[1]+1)*4;t.rawPixBuffer[n]=new Uint8Array(e),t.rawPixBuffer[n].set(t.pixBuffer[n])}if(n===Wp.ACTOR_PASS){if(t.captureZValues){const e=t._openGLRenderWindow.getRenderPasses();if("function"==typeof e[0].requestDepth&&"function"==typeof e[0].getFramebuffer){const n=e[0].getFramebuffer();n.saveCurrentBindingsAndBuffers(),n.bind(),t.zBuffer=t._openGLRenderWindow.getPixelData(t.area[0],t.area[1],t.area[2],t.area[3]),n.restorePreviousBindingsAndBuffers()}}e.buildPropHitList(t.rawPixBuffer[n])}},e.buildPropHitList=e=>{let n=0;for(let r=0;r<=t.area[3]-t.area[1];r++)for(let o=0;o<=t.area[2]-t.area[0];o++){let a=Qp(o,r,e,t.area,"buildPropHitList");a>0&&(a--,a in t.hitProps||(t.hitProps[a]=!0,t.propPixels[a]=[]),t.propPixels[a].push(4*n)),++n}},e.renderProp=n=>{t.currentPass===Wp.ACTOR_PASS&&(e.setPropColorValueFromInt(t.props.length+1),t.props.push(n))},e.renderCompositeIndex=n=>{t.currentPass===Wp.COMPOSITE_INDEX_PASS&&e.setPropColorValueFromInt(n+1)},e.renderAttributeId=e=>{e<0||(t.maxAttributeId=e>t.maxAttributeId?e:t.maxAttributeId)},e.passTypeToString=e=>sn.enumToString(Wp,e),e.isPropHit=e=>Boolean(t.hitProps[e]),e.setPropColorValueFromInt=e=>{t.propColorValue[0]=e%256/255,t.propColorValue[1]=Math.floor(e/256)%256/255,t.propColorValue[2]=Math.floor(e/65536)%256/255},e.getPixelInformation=(n,r,o)=>{const a=r<0?0:r;if(Yp("getPixelInformation called",a),0===a){if(o[0]=n[0],o[1]=n[1],n[0]<t.area[0]||n[0]>t.area[2]||n[1]<t.area[1]||n[1]>t.area[3])return null;Yp(n),Yp(t.area);const e=[n[0]-t.area[0],n[1]-t.area[1]];Yp("adjusted displayPosition",e);const r=Qp(e[0],e[1],t.pixBuffer[Wp.ACTOR_PASS],t.area,"getPixelInformation");if(Yp("actorid",r),r<=0||r-1>=t.props.length)return null;const a={valid:!0};a.propID=r-1,a.prop=t.props[a.propID];let i=Qp(e[0],e[1],t.pixBuffer[Wp.COMPOSITE_INDEX_PASS],t.area,"getPixelInformation2");if((i<0||i>16777215)&&(i=0),a.compositeID=i-1,t.captureZValues){const r=4*(e[1]*(t.area[2]-t.area[0]+1)+e[0]);a.zValue=(256*t.zBuffer[r]+t.zBuffer[r+1])/65535,a.displayPosition=n}if(t.pixBuffer[Wp.ID_LOW24]&&0===Zp(e[0],e[1],t.pixBuffer[Wp.ID_LOW24],t.area))return a;const s=Qp(e[0],e[1],t.pixBuffer[Wp.ID_LOW24],t.area,"getPixelInformation3"),l=Qp(e[0],e[1],t.pixBuffer[Wp.ID_HIGH24],t.area,"getPixelInformation4");return a.attributeID=$p(s,l),a}const i=[n[0],n[1]],s=[0,0];let l=e.getPixelInformation(n,0,o);if(l&&l.valid)return l;for(let t=1;t<a;++t){for(let n=i[1]>t?i[1]-t:0;n<=i[1]+t;++n){if(s[1]=n,i[0]>=t&&(s[0]=i[0]-t,l=e.getPixelInformation(s,0,o),l&&l.valid))return l;if(s[0]=i[0]+t,l=e.getPixelInformation(s,0,o),l&&l.valid)return l}for(let n=i[0]>=t?i[0]-(t-1):0;n<=i[0]+(t-1);++n){if(s[0]=n,i[1]>=t&&(s[1]=i[1]-t,l=e.getPixelInformation(s,0,o),l&&l.valid))return l;if(s[1]=i[1]+t,l=e.getPixelInformation(s,0,o),l&&l.valid)return l}}return o[0]=n[0],o[1]=n[1],null},e.generateSelection=(n,r,o,a)=>{const i=Math.floor(n),s=Math.floor(r),l=Math.floor(o),c=Math.floor(a),u=new Map,d=[0,0];for(let n=s;n<=c;n++)for(let r=i;r<=l;r++){const o=[r,n],a=e.getPixelInformation(o,0,d);if(a&&a.valid){const e=Jp(a);if(u.has(e)){const n=u.get(e);n.pixelCount++,t.captureZValues&&a.zValue<n.info.zValue&&(n.info=a),-1===n.attributeIDs.indexOf(a.attributeID)&&n.attributeIDs.push(a.attributeID)}else u.set(e,{info:a,pixelCount:1,attributeIDs:[a.attributeID]})}}return tf(t.fieldAssociation,u,t.captureZValues,t._renderer,t._openGLRenderWindow)},e.getRawPixelBuffer=e=>t.rawPixBuffer[e],e.getPixelBuffer=e=>t.pixBuffer[e],e.attach=(e,n)=>{t._openGLRenderWindow=e,t._renderer=n};const n=e.setArea;e.setArea=(...e)=>!!n(...e)&&(t.area[0]=Math.floor(t.area[0]),t.area[1]=Math.floor(t.area[1]),t.area[2]=Math.floor(t.area[2]),t.area[3]=Math.floor(t.area[3]),!0)}const rf={area:void 0,currentPass:-1,propColorValue:null,props:null,maximumPointId:0,maximumCellId:0,idOffset:1};function of(e,t,n={}){Object.assign(t,rf,n),Fp.extend(e,t,n),t.propColorValue=[0,0,0],t.props=[],t.area||(t.area=[0,0,0,0]),sn.setGetArray(e,t,["area"],4),sn.setGet(e,t,["_renderer","currentPass","_openGLRenderWindow","maximumPointId","maximumCellId"]),sn.setGetArray(e,t,["propColorValue"],3),sn.moveToProtected(e,t,["renderer","openGLRenderWindow"]),sn.event(e,t,"event"),nf(e,t)}var af={newInstance:sn.newInstance(of,"vtkOpenGLHardwareSelector"),extend:of,...Fl};const{vtkErrorMacro:sf}=ln,{Representation:lf}=us,{ObjectType:cf}=nd,{PassTypes:uf}=af,df={type:"StartEvent"},pf={type:"EndEvent"};const ff={normalMatrix:null,mcpcMatrix:null,mcwcMatrix:null};const gf=Xt((function(e,t,n={}){Object.assign(t,ff,n),up.extend(e,t,n),t.tmpMat3=c(new Float64Array(9)),t.normalMatrix=c(new Float64Array(9)),t.mcpcMatrix=x(new Float64Array(16)),t.mcvcMatrix=x(new Float64Array(16)),t.tmpColor=[],t.glyphBOBuildTime={},Vt(t.glyphBOBuildTime,{mtime:0}),function(e,t){t.classHierarchy.push("vtkOpenGLGlyph3DMapper");const n={...e};e.renderPiece=(n,r)=>{if(e.invokeEvent(df),t.renderable.getStatic()||t.renderable.update(),t.currentInput=t.renderable.getInputData(1),e.invokeEvent(pf),!t.currentInput)return void sf("No input!");if(!t.currentInput.getPoints||!t.currentInput.getPoints().getNumberOfValues())return;const o=t.context;t._openGLRenderWindow.getWebgl2()?(t.hardwareSupport=!0,t.extension=null):t.extension||(t.extension=t.context.getExtension("ANGLE_instanced_arrays"),t.hardwareSupport=!!t.extension);const a=r.getProperty().getBackfaceCulling(),i=r.getProperty().getFrontfaceCulling();a||i?i?(t._openGLRenderWindow.enableCullFace(),o.cullFace(o.FRONT)):(t._openGLRenderWindow.enableCullFace(),o.cullFace(o.BACK)):t._openGLRenderWindow.disableCullFace(),e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r)},e.multiply4x4WithOffset=(e,t,n,r)=>{const o=t[0],a=t[1],i=t[2],s=t[3],l=t[4],c=t[5],u=t[6],d=t[7],p=t[8],f=t[9],g=t[10],m=t[11],h=t[12],v=t[13],T=t[14],x=t[15];let y=n[r],b=n[r+1],A=n[r+2],C=n[r+3];e[0]=y*o+b*l+A*p+C*h,e[1]=y*a+b*c+A*f+C*v,e[2]=y*i+b*u+A*g+C*T,e[3]=y*s+b*d+A*m+C*x,y=n[r+4],b=n[r+5],A=n[r+6],C=n[r+7],e[4]=y*o+b*l+A*p+C*h,e[5]=y*a+b*c+A*f+C*v,e[6]=y*i+b*u+A*g+C*T,e[7]=y*s+b*d+A*m+C*x,y=n[r+8],b=n[r+9],A=n[r+10],C=n[r+11],e[8]=y*o+b*l+A*p+C*h,e[9]=y*a+b*c+A*f+C*v,e[10]=y*i+b*u+A*g+C*T,e[11]=y*s+b*d+A*m+C*x,y=n[r+12],b=n[r+13],A=n[r+14],C=n[r+15],e[12]=y*o+b*l+A*p+C*h,e[13]=y*a+b*c+A*f+C*v,e[14]=y*i+b*u+A*g+C*T,e[15]=y*s+b*d+A*m+C*x},e.replaceShaderNormal=(e,r,o)=>{if(t.hardwareSupport&&t.lastBoundBO.getReferenceByName("lastLightComplexity")>0){let n=e.Vertex;t.lastBoundBO.getCABO().getNormalOffset()&&(n=vd.substitute(n,"//VTK::Normal::Dec",["attribute vec3 normalMC;","attribute mat3 gNormal;","uniform mat3 normalMatrix;","varying vec3 normalVCVSOutput;"]).result,n=vd.substitute(n,"//VTK::Normal::Impl",["normalVCVSOutput = normalMatrix * gNormal * normalMC;"]).result),e.Vertex=n}n.replaceShaderNormal(e,r,o)},e.replaceShaderClip=(e,r,o)=>{if(t.hardwareSupport){let n=e.Vertex,r=e.Fragment;if(t.renderable.getNumberOfClippingPlanes()){const e=t.renderable.getNumberOfClippingPlanes();n=vd.substitute(n,"//VTK::Clip::Dec",["uniform int numClipPlanes;",`uniform vec4 clipPlanes[${e}];`,`varying float clipDistancesVSOutput[${e}];`]).result,n=vd.substitute(n,"//VTK::Clip::Impl",[`for (int planeNum = 0; planeNum < ${e}; planeNum++)`,"    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    vec4 gVertex = gMatrix * vertexMC;","    clipDistancesVSOutput[planeNum] = dot(clipPlanes[planeNum], gVertex);","    }"]).result,r=vd.substitute(r,"//VTK::Clip::Dec",["uniform int numClipPlanes;",`varying float clipDistancesVSOutput[${e}];`]).result,r=vd.substitute(r,"//VTK::Clip::Impl",[`for (int planeNum = 0; planeNum < ${e}; planeNum++)`,"    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    if (clipDistancesVSOutput[planeNum] < 0.0) discard;","    }"]).result}e.Vertex=n,e.Fragment=r}n.replaceShaderClip(e,r,o)},e.replaceShaderColor=(e,r,o)=>{if(t.hardwareSupport&&t.renderable.getColorArray()){let n=e.Vertex,r=e.Geometry,o=e.Fragment;const a=t.lastBoundBO.getReferenceByName("lastLightComplexity");let i=["uniform float ambient;","uniform float diffuse;","uniform float specular;","uniform float opacityUniform; // the fragment opacity"];a&&(i=i.concat(["uniform vec3 specularColorUniform;","uniform float specularPowerUniform;"]));let s=["vec3 ambientColor;","  vec3 diffuseColor;","  float opacity;"];a&&(s=s.concat(["  vec3 specularColor;","  float specularPower;"])),s=s.concat(["  opacity = opacityUniform;"]),a&&(s=s.concat(["  specularColor = specularColorUniform;","  specularPower = specularPowerUniform;"])),t.drawingEdges||(i=i.concat(["varying vec4 vertexColorVSOutput;"]),n=vd.substitute(n,"//VTK::Color::Dec",["attribute vec4 gColor;","varying vec4 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gMatrix;","uniform mat4 MCPCMatrix;","uniform mat4 MCVCMatrix;"]).result):(n=vd.substitute(n,"//VTK::Camera::Dec",["attribute mat4 gMatrix;","uniform mat4 MCPCMatrix;"]).result,n=vd.substitute(n,"//VTK::PositionVC::Impl",["vec4 gVertexMC = gMatrix * vertexMC;","  gl_Position = MCPCMatrix * gVertexMC;"]).result),e.Vertex=n}n.replaceShaderPositionVC(e,r,o)},e.replaceShaderPicking=(e,r,o)=>{if(t.hardwareSupport){let t=e.Fragment,n=e.Vertex;n=vd.substitute(n,"//VTK::Picking::Dec",["attribute vec3 mapperIndexVS;","varying vec3 mapperIndexVSOutput;"]).result,n=vd.substitute(n,"//VTK::Picking::Impl","  mapperIndexVSOutput = mapperIndexVS;").result,e.Vertex=n,t=vd.substitute(t,"//VTK::Picking::Dec",["varying vec3 mapperIndexVSOutput;","uniform vec3 mapperIndex;","uniform int picking;"]).result,t=vd.substitute(t,"//VTK::Picking::Impl",["  vec4 pickColor = picking == 2 ? vec4(mapperIndexVSOutput,1.0) : vec4(mapperIndex,1.0);","  gl_FragData[0] = picking != 0 ? pickColor : gl_FragData[0];"]).result,e.Fragment=t}else n.replaceShaderPicking(e,r,o)},e.updateGlyphShaderParameters=(n,r,o,a,i,s,l,c)=>{const u=o.getProgram();if(n){const e=t.normalMatrix,n=s,r=9*l,o=t.tmpMat3,a=e[0],i=e[1],c=e[2],d=e[3],p=e[4],f=e[5],g=e[6],m=e[7],h=e[8],v=n[r],T=n[r+1],x=n[r+2],y=n[r+3],b=n[r+4],A=n[r+5],C=n[r+6],S=n[r+7],P=n[r+8];o[0]=v*a+T*d+x*g,o[1]=v*i+T*p+x*m,o[2]=v*c+T*f+x*h,o[3]=y*a+b*d+A*g,o[4]=y*i+b*p+A*m,o[5]=y*c+b*f+A*h,o[6]=C*a+S*d+P*g,o[7]=C*i+S*p+P*m,o[8]=C*c+S*f+P*h,u.setUniformMatrix3x3("normalMatrix",t.tmpMat3)}if(e.multiply4x4WithOffset(t.tmpMat4,t.mcpcMatrix,i,16*l),u.setUniformMatrix("MCPCMatrix",t.tmpMat4),r&&(e.multiply4x4WithOffset(t.tmpMat4,t.mcvcMatrix,i,16*l),u.setUniformMatrix("MCVCMatrix",t.tmpMat4)),a){const e=a.getData();t.tmpColor[0]=e[4*l]/255,t.tmpColor[1]=e[4*l+1]/255,t.tmpColor[2]=e[4*l+2]/255,u.setUniform3fArray("ambientColorUniform",t.tmpColor),u.setUniform3fArray("diffuseColorUniform",t.tmpColor)}c&&u.setUniform3fArray("mapperIndex",c.getPropColorValue())},e.renderPieceDraw=(n,r)=>{const o=r.getProperty().getRepresentation(),a=t.context,i=r.getProperty().getEdgeVisibility()&&o===lf.SURFACE,s=t.openGLCamera.getKeyMatrices(n),l=t.openGLActor.getKeyMatrices();p(t.normalMatrix,s.normalMatrix,l.normalMatrix),A(t.mcpcMatrix,s.wcpc,l.mcwc),A(t.mcvcMatrix,s.wcvc,l.mcwc);const c=t.renderable.getMatrixArray(),u=t.renderable.getNormalArray(),d=t.renderable.getColorArray(),f=c.length/16;let g=!1;t._openGLRenderer.getSelector()&&t._openGLRenderer.getSelector().getCurrentPass()===uf.COMPOSITE_INDEX_PASS&&(g=!0);for(let s=t.primTypes.Start;s<t.primTypes.End;s++){const l=t.primitives[s].getCABO();if(l.getElementCount()){t.drawingEdges=i&&(s===t.primTypes.TrisEdges||s===t.primTypes.TriStripsEdges),t.lastBoundBO=t.primitives[s],t.primitives[s].updateShaders(n,r,e);const p=t.primitives[s].getProgram(),m=t.primitives[s].getOpenGLMode(o),h=p.isUniformUsed("normalMatrix"),v=p.isUniformUsed("MCVCMatrix");if(t.hardwareSupport)t.extension?t.extension.drawArraysInstancedANGLE(m,0,l.getElementCount(),f):a.drawArraysInstanced(m,0,l.getElementCount(),f);else for(let n=0;n<f;++n)g&&t._openGLRenderer.getSelector().renderCompositeIndex(n),e.updateGlyphShaderParameters(h,v,t.primitives[s],d,c,u,n,g?t._openGLRenderer.getSelector():null),a.drawArrays(m,0,l.getElementCount())}}},e.setMapperShaderParameters=(e,r,o)=>{if(e.getCABO().getElementCount()&&(t.glyphBOBuildTime.getMTime()>e.getAttributeUpdateTime().getMTime()||e.getShaderSourceTime().getMTime()>e.getAttributeUpdateTime().getMTime()))return e.getProgram().isAttributeUsed("gMatrix")?e.getVAO().addAttributeMatrixWithDivisor(e.getProgram(),t.matrixBuffer,"gMatrix",0,64,t.context.FLOAT,4,!1,1)||sf("Error setting gMatrix in shader VAO."):e.getVAO().removeAttributeArray("gMatrix"),e.getProgram().isAttributeUsed("gNormal")?e.getVAO().addAttributeMatrixWithDivisor(e.getProgram(),t.normalBuffer,"gNormal",0,36,t.context.FLOAT,3,!1,1)||sf("Error setting gNormal in shader VAO."):e.getVAO().removeAttributeArray("gNormal"),e.getProgram().isAttributeUsed("gColor")?e.getVAO().addAttributeArrayWithDivisor(e.getProgram(),t.colorBuffer,"gColor",0,4,t.context.UNSIGNED_BYTE,4,!0,1,!1)||sf("Error setting gColor in shader VAO."):e.getVAO().removeAttributeArray("gColor"),e.getProgram().isAttributeUsed("mapperIndexVS")?e.getVAO().addAttributeArrayWithDivisor(e.getProgram(),t.pickBuffer,"mapperIndexVS",0,4,t.context.UNSIGNED_BYTE,4,!0,1,!1)||sf("Error setting mapperIndexVS in shader VAO."):e.getVAO().removeAttributeArray("mapperIndexVS"),n.setMapperShaderParameters(e,r,o),void e.getAttributeUpdateTime().modified();n.setMapperShaderParameters(e,r,o)},e.getNeedToRebuildBufferObjects=(e,r)=>(t.renderable.buildArrays(),t.VBOBuildTime.getMTime()<t.renderable.getBuildTime().getMTime()||n.getNeedToRebuildBufferObjects(e,r)),e.getNeedToRebuildShaders=(e,r,o)=>!!(n.getNeedToRebuildShaders(e,r,o)||e.getShaderSourceTime().getMTime()<t.renderable.getMTime()||e.getShaderSourceTime().getMTime()<t.currentInput.getMTime()),e.buildBufferObjects=(e,r)=>{const o=t.renderable.getMatrixArray(),a=t.renderable.getInputData(0).getPoints(),{useShiftAndScale:i,coordShift:s,coordScale:l}=rd(a);if(t.hardwareSupport){const e=t.renderable.getNormalArray(),n=t.renderable.getColorArray();if(t.matrixBuffer||(t.matrixBuffer=nd.newInstance(),t.matrixBuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.normalBuffer=nd.newInstance(),t.normalBuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.colorBuffer=nd.newInstance(),t.colorBuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.pickBuffer=nd.newInstance(),t.pickBuffer.setOpenGLRenderWindow(t._openGLRenderWindow)),i){const e=o.buffer,t=od(s,l);b(t,t);for(let n=0;n<o.byteLength;n+=64){const r=new Float32Array(e,n,16);A(r,t,r)}}if(t.renderable.getBuildTime().getMTime()>t.glyphBOBuildTime.getMTime()){t.matrixBuffer.upload(o,cf.ARRAY_BUFFER),t.normalBuffer.upload(e,cf.ARRAY_BUFFER),n?t.colorBuffer.upload(n.getData(),cf.ARRAY_BUFFER):t.colorBuffer.releaseGraphicsResources();const r=o.length/16,a=new Uint8Array(4*r);for(let e=0;e<r;++e){let t=e+1;const n=4*e;a[n]=t%256,t-=a[n],t/=256,a[n+1]=t%256,t-=a[n+1],t/=256,a[n+2]=t%256,a[n+3]=255}t.pickBuffer.upload(a,cf.ARRAY_BUFFER),t.glyphBOBuildTime.modified()}}if(n.buildBufferObjects(e,r),i)for(let e=bd.Start;e<bd.End;e++)t.primitives[e].getCABO().setCoordShiftAndScale(s,l)}}(e,t)}),"vtkOpenGLGlyph3DMapper");vn("vtkGlyph3DMapper",gf);const{vtkErrorMacro:mf}=sn;class hf{constructor(){this.segmentMapping={},this.segments=[null],this.faces=[]}addSegment(e){const t=e[0],n=e[e.length-1];if(t===n||e.length<2)return;const r=this.segmentMapping[t],o=this.segmentMapping[n];if(void 0!==r&&void 0!==o)if(Math.abs(r)===Math.abs(o)){const a=r<o?o:r,i=this.segments[a];if(r>0)for(let t=1;t<e.length-1;t++)i.push(e[t]);else for(let t=1;t<e.length-1;t++)i.unshift(e[e.length-1-t]);this.faces.push(i),this.segments[a]=null,this.segmentMapping[t]=void 0,this.segmentMapping[n]=void 0}else{const 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Tf(e,t,n={}){Object.assign(t,vf,n),sn.obj(e,t),sn.algo(e,t,1,1),function(e,t){t.classHierarchy.push("vtkClosedPolyLineToSurfaceFilter"),e.requestData=(e,t)=>{const n=e[0];if(!n)return void mf("Invalid or missing input");const r=t[0]?.initialize()||Ru.newInstance();r.shallowCopy(n);const o=new hf,a=n.getLines().getData();let i=0;for(;i<a.length;){const e=a[i++],t=[];for(let n=0;n<e;n++)t.push(a[i+n]);o.addSegment(t),i+=e}const{faces:s}=o;let l=s.length;for(let e=0;e<s.length;e++)l+=s[e].length;const c=new Uint16Array(l);i=0;for(let e=0;e<s.length;e++){const t=s[e];c[i++]=t.length;for(let e=0;e<t.length;e++)c[i++]=t[e]}r.setPolys(oc.newInstance({values:c,name:"faces"})),t[0]=r}}(e,t)}var xf={newInstance:sn.newInstance(Tf,"vtkClosedPolyLineToSurfaceFilter"),extend:Tf};const{vtkErrorMacro:yf}=ln;function bf(e,t){t.classHierarchy.push("vtkCutter");const n={...e};function r(e,n){const 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Ef(e,t,n={}){Object.assign(t,Df,n),sn.obj(e,t),sn.setGet(e,t,["xLength","yLength","zLength","generate3DTextureCoordinates","generateFaces","generateLines"]),sn.setGetArray(e,t,["center","rotations"],3),sn.setGetArray(e,t,["matrix"],16),t._polys=oc.newInstance({values:Uint16Array.from(Mf)}),t._lineCells=oc.newInstance({values:Uint16Array.from(Rf)}),sn.moveToProtected(e,t,["polys","lineCells"]),sn.algo(e,t,0,1),function(e,t){t.classHierarchy.push("vtkCubeSource"),e.requestData=(e,n)=>{const r=n[0]?.initialize()||Ru.newInstance();n[0]=r;const o=sn.newTypedArray(t.pointType,72);r.getPoints().setData(o,3);const a=sn.newTypedArray(t.pointType,72),i=Is.newInstance({name:"Normals",values:a,numberOfComponents:3});r.getPointData().setNormals(i);let s=2;!0===t.generate3DTextureCoordinates&&(s=3);const l=sn.newTypedArray(t.pointType,24*s),c=Is.newInstance({name:"TextureCoordinates",values:l,numberOfComponents:s});r.getPointData().setTCoords(c);const u=[0,0,0],d=[0,0,0],p=[0,0];let 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n=s[t].getData(),r=l[t].getData();d[0]=n[3*x],d[1]=n[3*x+1],d[2]=n[3*x+2],f.set(d),e.transformVector(d,d),r[3*x]=d[0],r[3*x+1]=d[1],r[3*x+2]=d[2],za.arrayEqual(f,d)||T.includes(t)||T.push(t)}}m&&n.modified(),h&&i.modified(),v&&o.modified(),T.forEach((e=>l[e].modified()))}}(e,t)}Gf=sn.newInstance(_f,"vtkTransform");var Kf={newInstance:Gf,extend:_f};function zf(e,t,n){return e.length>0?`${e.map((e=>e?.getMTime()??"x")).join("/")}-${t}-${n}`:"0"}function Wf(e,t){return`${t.getMTime()}`}const Hf={NEAREST:0,LINEAR:1};var jf={InterpolationType:Hf};const{vtkErrorMacro:Xf}=ln,qf=e=>e.split("\n").map((e=>e.trim())).filter(Boolean);function Yf(e,t,n){return t.identity(n),e.reduce(((e,n,r)=>0===r?n?t.copy(e,n):t.identity(e):n?t.multiply(e,e,n):e),n)}function Jf(e,t){t.classHierarchy.push("vtkOpenGLImageResliceMapper");const n=new Map;function r(t,r,o){r!==o&&(function(t,r){if(!r)return;const o=(n.get(r)??0)-1;o<=0?(t.unregisterGraphicsResourceUser(r,e),n.delete(r)):n.set(r,o)}(t,r),function(t,r){if(!r)return;const o=n.get(r)??0,a=o+1;n.set(r,a),o<=0&&t.registerGraphicsResourceUser(r,e)}(t,o))}function o(t){[...n.keys()].forEach((n=>t.unregisterGraphicsResourceUser(n,e)))}function a(e,n,r,o,a){const i=e.map((e=>e.join("-"))).join("|");i!==t[o]&&(t[o]=i,t[a]&&t[a].releaseGraphicsResources(),t[a]=function(e,n,r){let o=t.renderable.getLabelOutlineTextureWidth();o<=0&&(o=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const a=e.length,i=new n(o*a);for(let t=0;t<a;t++){const n=e[t];for(let e=0;e<o;e++)i[t*o+e]=n[e]??n[0]}const s=Hd.newInstance({resizable:!1});return s.setOpenGLRenderWindow(t._openGLRenderWindow),s.resetFormatAndType(),s.setMinificationFilter(wd.NEAREST),s.setMagnificationFilter(wd.NEAREST),s.create2DFromRaw({width:o,height:a,numComps:1,dataType:r,data:i}),s}(e,n,r))}e.buildPass=n=>{if(n){t.currentRenderPass=null,t._openGLImageSlice=e.getFirstAncestorOfType("vtkOpenGLImageSlice"),t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer");const n=t._openGLRenderer.getRenderable();t._openGLCamera=t._openGLRenderer.getViewNodeFor(n.getActiveCamera(),t.openGLCamera);const r=t._openGLRenderWindow;t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow"),r&&!r.isDeleted()&&r!==t._openGLRenderWindow&&o(r),t.context=t._openGLRenderWindow.getContext(),t.tris.setOpenGLRenderWindow(t._openGLRenderWindow)}},e.translucentPass=(n,r)=>{n&&(t.currentRenderPass=r,e.render())},e.zBufferPass=n=>{n&&(t.haveSeenDepthRequest=!0,t.renderDepth=!0,e.render(),t.renderDepth=!1)},e.opaqueZBufferPass=t=>e.zBufferPass(t),e.opaquePass=t=>{t&&e.render()},e.getCoincidentParameters=(e,n)=>t.renderable.getResolveCoincidentTopology()==Pl.PolygonOffset?t.renderable.getCoincidentTopologyPolygonOffsetParameters():null,e.render=()=>{const n=t._openGLImageSlice.getRenderable(),r=t._openGLRenderer.getRenderable();e.renderPiece(r,n)},e.renderPiece=(n,r)=>{e.invokeEvent({type:"StartEvent"}),t.renderable.update();const o=t.renderable.getNumberOfInputPorts();t.currentValidInputs=[];for(let e=0;e<o;++e){const n=t.renderable.getInputData(e);n&&!n.isDeleted()&&t.currentValidInputs.push({imageData:n,inputIndex:e})}const a=t.currentValidInputs.length;if(a<=0)return void Xf("No input!");t.labelOutlineProperties=function(e,t){const n=[];for(let r=0;r<t.length;r++){const o=e.getProperty(t[r].inputIndex);o?.getUseLabelOutline()&&n.push({property:o,arrayIndex:r})}return n}(r,t.currentValidInputs);const i=t.currentValidInputs[0].imageData.getPointData().getScalars();t.multiTexturePerVolumeEnabled=a>1,t.numberOfComponents=t.multiTexturePerVolumeEnabled?a:i.getNumberOfComponents(),e.updateResliceGeometry(),e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r),e.invokeEvent({type:"EndEvent"})},e.renderPieceStart=(n,r)=>{e.updateBufferObjects(n,r);const o=r.getProperties();t.currentValidInputs.forEach((({inputIndex:e},n)=>{const r=o[e],a=t.scalarTextures[n];if(!r||!a)return;r.getInterpolationType()===Hf.NEAREST?(a.setMinificationFilter(wd.NEAREST),a.setMagnificationFilter(wd.NEAREST)):(a.setMinificationFilter(wd.LINEAR),a.setMagnificationFilter(wd.LINEAR))}));const a=t.currentValidInputs[0],i=o[a.inputIndex],s=i?.getInterpolationType();s===Hf.NEAREST?(t.colorTexture.setMinificationFilter(wd.NEAREST),t.colorTexture.setMagnificationFilter(wd.NEAREST),t.pwfTexture.setMinificationFilter(wd.NEAREST),t.pwfTexture.setMagnificationFilter(wd.NEAREST)):(t.colorTexture.setMinificationFilter(wd.LINEAR),t.colorTexture.setMagnificationFilter(wd.LINEAR),t.pwfTexture.setMinificationFilter(wd.LINEAR),t.pwfTexture.setMagnificationFilter(wd.LINEAR)),t.lastBoundBO=null},e.renderPieceDraw=(n,r)=>{const o=t.context,a=t.labelOutlineProperties.length>0,i=[...t.scalarTextures,t.colorTexture,t.pwfTexture];a&&(i.push(t.labelOutlineThicknessTexture),i.push(t.labelOutlineOpacityTexture)),i.forEach((e=>e.activate())),e.updateShaders(t.tris,n,r),o.drawArrays(o.TRIANGLES,0,t.tris.getCABO().getElementCount()),t.tris.getVAO().release(),i.forEach((e=>e.deactivate()))},e.renderPieceFinish=(e,t)=>{},e.updateBufferObjects=(t,n)=>{e.getNeedToRebuildBufferObjects(t,n)&&e.buildBufferObjects(t,n)},e.getNeedToRebuildBufferObjects=(n,r)=>{const o=r.getProperty(t.currentValidInputs[0].inputIndex),a=t.labelOutlineProperties.length>0;return t.VBOBuildTime.getMTime()<e.getMTime()||t.VBOBuildTime.getMTime()<r.getMTime()||t.VBOBuildTime.getMTime()<t.renderable.getMTime()||t.VBOBuildTime.getMTime()<o?.getMTime()||t.currentValidInputs.some((({imageData:e})=>t.VBOBuildTime.getMTime()<e.getMTime()))||t.VBOBuildTime.getMTime()<t.resliceGeom.getMTime()||t.scalarTextures.length!==t.currentValidInputs.length||!t.scalarTextures.every((e=>!!e?.getHandle()))||!t.colorTexture?.getHandle()||!t.pwfTexture?.getHandle()||a&&(!t.labelOutlineThicknessTexture?.getHandle()||!t.labelOutlineOpacityTexture?.getHandle())},e.buildBufferObjects=(n,o)=>{const a=o.getProperties();t.currentValidInputs.forEach((({imageData:e,inputIndex:n},o)=>{const i=e.getPointData().getScalars(),s=t._openGLRenderWindow.getGraphicsResourceForObject(i),l=Wf(0,i),c=!s?.oglObject?.getHandle()||s?.hash!==l,u=a[n],d=u?.getUpdatedExtents()??[],p=!!d.length;if(c&&!p){const n=Hd.newInstance();n.setOpenGLRenderWindow(t._openGLRenderWindow);const r=e.getDimensions();n.setOglNorm16Ext(t.context.getExtension("EXT_texture_norm16")),n.resetFormatAndType(),n.create3DFilterableFromDataArray({width:r[0],height:r[1],depth:r[2],dataArray:i}),t._openGLRenderWindow.setGraphicsResourceForObject(i,n,l),t.scalarTextures[o]=n}else t.scalarTextures[o]=s.oglObject;if(p){u.setUpdatedExtents([]);const n=e.getDimensions();t.scalarTextures[o].create3DFilterableFromDataArray({width:n[0],height:n[1],depth:n[2],dataArray:i,updatedExtents:d})}r(t._openGLRenderWindow,t._scalarTexturesCore[o],i),t._scalarTexturesCore[o]=i}));const i=t.currentValidInputs[0],s=a[i.inputIndex];if(!s)return void Xf("Missing property for first input");const l=s.getIndependentComponents(),c=l?t.numberOfComponents:1,u=l?2*c:1,d=[];for(let e=0;e<c;++e)if(t.multiTexturePerVolumeEnabled){const n=t.currentValidInputs[e],r=n?a[n.inputIndex]:null;d.push(r?.getRGBTransferFunction()||null)}else d.push(s.getRGBTransferFunction(e));const p=zf(d,l,c),f=s.getRGBTransferFunction(),g=t._openGLRenderWindow.getGraphicsResourceForObject(f);if(!g?.oglObject?.getHandle()||g?.hash!==p){let e=t.renderable.getColorTextureWidth();e<=0&&(e=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const n=new Uint8ClampedArray(e*u*3),r=Hd.newInstance();if(r.setOpenGLRenderWindow(t._openGLRenderWindow),f){const t=new Float32Array(3*e);for(let r=0;r<c;r++){const o=d[r];if(o){const a=o.getRange();if(o.getTable(a[0],a[1],e,t,1),l)for(let o=0;o<3*e;o++)n[r*e*6+o]=255*t[o],n[r*e*6+o+3*e]=255*t[o];else for(let o=0;o<3*e;o++)n[r*e*3+o]=255*t[o]}}r.resetFormatAndType(),r.create2DFromRaw({width:e,height:u,numComps:3,dataType:ms.UNSIGNED_CHAR,data:n})}else{for(let t=0;t<3*e;++t){const r=255*t/(3*(e-1));for(let o=0;o<u;++o)n[o*e*3+t+0]=r,n[o*e*3+t+1]=r,n[o*e*3+t+2]=r}r.resetFormatAndType(),r.create2DFromRaw({width:e,height:1,numComps:3,dataType:ms.UNSIGNED_CHAR,data:n})}f&&t._openGLRenderWindow.setGraphicsResourceForObject(f,r,p),t.colorTexture=r}else t.colorTexture=g.oglObject;r(t._openGLRenderWindow,t._colorTextureCore,f),t._colorTextureCore=f;const m=[];for(let e=0;e<c;++e)if(t.multiTexturePerVolumeEnabled){const n=t.currentValidInputs[e],r=n?a[n.inputIndex]:null;m.push(r?.getPiecewiseFunction()||null)}else m.push(s.getPiecewiseFunction(e));const h=zf(m,l,c),v=s.getPiecewiseFunction(),T=t._openGLRenderWindow.getGraphicsResourceForObject(v);if(!T?.oglObject?.getHandle()||T?.hash!==h){let e=t.renderable.getOpacityTextureWidth();e<=0&&(e=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const n=e*u,r=new Uint8ClampedArray(n),o=Hd.newInstance();if(o.setOpenGLRenderWindow(t._openGLRenderWindow),v){const t=new Float32Array(n),r=new Float32Array(e);for(let n=0;n<c;++n){const o=m[n];if(null===o)t.fill(1);else{const a=o.getRange();if(o.getTable(a[0],a[1],e,r,1),l)for(let o=0;o<e;o++)t[n*e*2+o]=r[o],t[n*e*2+o+e]=r[o];else for(let n=0;n<e;n++)t[n]=r[n]}}o.resetFormatAndType(),o.create2DFromRaw({width:e,height:u,numComps:1,dataType:ms.FLOAT,data:t})}else r.fill(255),o.resetFormatAndType(),o.create2DFromRaw({width:e,height:u,numComps:1,dataType:ms.UNSIGNED_CHAR,data:r});v&&t._openGLRenderWindow.setGraphicsResourceForObject(v,o,h),t.pwfTexture=o}else t.pwfTexture=T.oglObject;r(t._openGLRenderWindow,t._pwfTextureCore,v),t._pwfTextureCore=v,t.labelOutlineProperties.length>0&&(e.updateLabelOutlineThicknessTexture(t.labelOutlineProperties),e.updateLabelOutlineOpacityTexture(t.labelOutlineProperties));const x=`${t.resliceGeom.getMTime()}A${t.renderable.getSlabThickness()}`;if(!t.tris.getCABO().getElementCount()||t.VBOBuildString!==x){const e=Is.newInstance({numberOfComponents:3,values:t.resliceGeom.getPoints().getData()});e.setName("points");const n=Is.newInstance({numberOfComponents:1,values:t.resliceGeom.getPolys().getData()}),r={points:e,cellOffset:0};if(t.renderable.getSlabThickness()>0){const e=t.resliceGeom.getPointData().getNormals();e?r.normals=e:Xf("Slab mode requested without normals")}t.tris.getCABO().createVBO(n,"polys",rs.SURFACE,r)}t.VBOBuildString=x,t.VBOBuildTime.modified()},e.updateShaders=(n,r,o)=>{if(t.lastBoundBO=n,e.getNeedToRebuildShaders(n,r,o)){const a={Vertex:null,Fragment:null,Geometry:null};e.buildShaders(a,r,o);const i=t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(a.Vertex,a.Fragment,a.Geometry);i!==n.getProgram()&&(n.setProgram(i),n.getVAO().releaseGraphicsResources()),n.getShaderSourceTime().modified()}else t._openGLRenderWindow.getShaderCache().readyShaderProgram(n.getProgram());n.getVAO().bind(),e.setMapperShaderParameters(n,r,o),e.setCameraShaderParameters(n,r,o),e.setPropertyShaderParameters(n,r,o)},e.setMapperShaderParameters=(n,r,o)=>{const a=n.getProgram(),i=t.currentValidInputs[0].imageData;if(n.getCABO().getElementCount()&&(t.VBOBuildTime.getMTime()>n.getAttributeUpdateTime().getMTime()||n.getShaderSourceTime().getMTime()>n.getAttributeUpdateTime().getMTime())){t.scalarTextures.forEach(((e,t)=>{a.setUniformi(`volumeTexture[${t}]`,e.getTextureUnit())})),a.isAttributeUsed("vertexWC")&&(n.getVAO().addAttributeArray(a,n.getCABO(),"vertexWC",n.getCABO().getVertexOffset(),n.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||Xf("Error setting vertexWC in shader VAO.")),a.isAttributeUsed("normalWC")&&(n.getVAO().addAttributeArray(a,n.getCABO(),"normalWC",n.getCABO().getNormalOffset(),n.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||Xf("Error setting normalWC in shader VAO.")),a.isUniformUsed("slabThickness")&&a.setUniformf("slabThickness",t.renderable.getSlabThickness()),a.isUniformUsed("spacing")&&a.setUniform3fv("spacing",i.getSpacing()),a.isUniformUsed("slabType")&&a.setUniformi("slabType",t.renderable.getSlabType()),a.isUniformUsed("slabTrapezoid")&&a.setUniformi("slabTrapezoid",t.renderable.getSlabTrapezoidIntegration());const e=n.getCABO().getCoordShiftAndScaleEnabled()?n.getCABO().getInverseShiftAndScaleMatrix():null;for(let n=0;n<t.currentValidInputs.length;n++){const r=`WCTCMatrix${n}`;if(a.isUniformUsed(r)){const o=t.currentValidInputs[n].imageData,i=o.getDimensions();T(t.tmpMat4,o.getIndexToWorld()),C(t.tmpMat4,t.tmpMat4,[-.5,-.5,-.5]),S(t.tmpMat4,t.tmpMat4,i),b(t.tmpMat4,t.tmpMat4),e&&A(t.tmpMat4,t.tmpMat4,e),a.setUniformMatrix(r,t.tmpMat4)}}a.isUniformUsed("vboScaling")&&a.setUniform3fv("vboScaling",n.getCABO().getCoordScale()??[1,1,1]),n.getAttributeUpdateTime().modified()}if(t.haveSeenDepthRequest&&n.getProgram().setUniformi("depthRequest",t.renderDepth?1:0),n.getProgram().isUniformUsed("coffset")){const t=e.getCoincidentParameters(r,o);n.getProgram().setUniformf("coffset",t.offset),n.getProgram().isUniformUsed("cfactor")&&n.getProgram().setUniformf("cfactor",t.factor)}},e.setCameraShaderParameters=(e,n,r)=>{const o=t._openGLCamera.getKeyMatrices(n),a=t._openGLImageSlice.getKeyMatrices(),i=e.getCABO().getCoordShiftAndScaleEnabled()?e.getCABO().getInverseShiftAndScaleMatrix():null,s=e.getProgram();s.isUniformUsed("MCPCMatrix")&&(x(t.tmpMat4),s.setUniformMatrix("MCPCMatrix",Yf([o.wcpc,a.mcwc,i],H,t.tmpMat4))),s.isUniformUsed("MCVCMatrix")&&(x(t.tmpMat4),s.setUniformMatrix("MCVCMatrix",Yf([o.wcvc,a.mcwc,i],H,t.tmpMat4)))},e.setPropertyShaderParameters=(e,n,r)=>{const o=e.getProgram(),a=r.getProperty(t.currentValidInputs[0].inputIndex),i=t.multiTexturePerVolumeEnabled?1:a.getOpacity();o.setUniformf("opacity",i);const s=t.numberOfComponents,c=a.getIndependentComponents(),u=t.multiTexturePerVolumeEnabled,p=r.getProperties();if(c)for(let e=0;e<s;++e){const n=u?p[t.currentValidInputs[e].inputIndex]:a;o.setUniformf(`mix${e}`,n.getComponentWeight(0))}for(let e=0;e<s;e++){const n=u?e:0,r=u?0:e,i=t.scalarTextures[n].getVolumeInfo(),s=i.scale[r],l=i.offset[r],d=c?e:0,f=u?p[t.currentValidInputs[e].inputIndex]:a;let g=f.getColorWindow(),m=f.getColorLevel();const h=f.getRGBTransferFunction(u?0:d);if(h&&f.getUseLookupTableScalarRange()){const e=h.getRange();g=e[1]-e[0],m=.5*(e[1]+e[0])}const v=s/g,T=(l-m)/g+.5;o.setUniformf(`cshift${e}`,T),o.setUniformf(`cscale${e}`,v);let x=1,y=0;const b=f.getPiecewiseFunction(u?0:d);if(b){const e=b.getRange(),t=e[1]-e[0];x=s/t,y=(l-.5*(e[0]+e[1]))/t+.5}o.setUniformf(`pwfshift${e}`,y),o.setUniformf(`pwfscale${e}`,x)}const f=t.colorTexture.getTextureUnit();o.setUniformi("colorTexture1",f);const g=t.pwfTexture.getTextureUnit();if(o.setUniformi("pwfTexture1",g),o.setUniform4fv("backgroundColor",t.renderable.getBackgroundColor()),t.labelOutlineProperties.length>0){const e=t.labelOutlineThicknessTexture.getTextureUnit();o.setUniformi("labelOutlineThicknessTexture",e);const n=t.labelOutlineOpacityTexture.getTextureUnit();o.setUniformi("labelOutlineOpacityTexture",n);let r=t.renderable.getLabelOutlineTextureWidth();r<=0&&(r=t.context.getParameter(t.context.MAX_TEXTURE_SIZE)),o.setUniformf("labelOutlineTextureWidth",r),o.setUniformf("numLabelmaps",t.labelOutlineProperties.length);const a=t.renderable.getSlicePlane();if(t._tmpTangent1.fill(0),t._tmpTangent2.fill(0),a){const e=a.getNormal();za.perpendiculars(e,t._tmpTangent1,t._tmpTangent2,0)}else t._tmpTangent1[0]=1,t._tmpTangent2[1]=1;for(let e=0;e<t.currentValidInputs.length;e++){const n=t.currentValidInputs[e].imageData;l(t._tmpMat3,...n.getDirection()),d(t._tmpMat3,t._tmpMat3),ae(t._tmpVec3a,t._tmpTangent1,t._tmpMat3),ae(t._tmpVec3b,t._tmpTangent2,t._tmpMat3);const r=`outlineTangent1_${e}`,a=`outlineTangent2_${e}`;o.isUniformUsed(r)&&o.setUniform3fv(r,t._tmpVec3a),o.isUniformUsed(a)&&o.setUniform3fv(a,t._tmpVec3b)}for(let e=0;e<t.currentValidInputs.length;e++){const n=`texelSize${e}`;if(o.isUniformUsed(n)){const r=t.currentValidInputs[e].imageData,a=r.getDimensions(),i=r.getSpacing(),s=Math.min(Math.abs(i[0]),Math.abs(i[1]),Math.abs(i[2]));t._tmpTexelSize[0]=s/(a[0]*Math.abs(i[0])),t._tmpTexelSize[1]=s/(a[1]*Math.abs(i[1])),t._tmpTexelSize[2]=s/(a[2]*Math.abs(i[2])),o.setUniform3fv(n,t._tmpTexelSize)}}}},e.getNeedToRebuildShaders=(e,n,r)=>{const o=r.getProperty(t.currentValidInputs[0].inputIndex).getIndependentComponents(),a=t.labelOutlineProperties.length>0,i=t.renderable.getSlabThickness(),s=t.renderable.getSlabType(),l=t.renderable.getSlabTrapezoidIntegration();let c=!1;(!t.currentRenderPass&&t.lastRenderPassShaderReplacement||t.currentRenderPass&&t.currentRenderPass.getShaderReplacement()!==t.lastRenderPassShaderReplacement)&&(c=!0);const u=t.currentValidInputs?.length??0;return!(!c&&t.lastHaveSeenDepthRequest===t.haveSeenDepthRequest&&t.lastNumberOfComponents===t.numberOfComponents&&t.lastMultiTexturePerVolumeEnabled===t.multiTexturePerVolumeEnabled&&0!==e.getProgram()?.getHandle()&&t.lastIndependentComponents===o&&t.lastUseLabelOutline===a&&t.lastNumValidInputs===u&&t.lastSlabThickness===i&&t.lastSlabType===s&&t.lastSlabTrapezoidIntegration===l)&&(t.lastHaveSeenDepthRequest=t.haveSeenDepthRequest,t.lastNumberOfComponents=t.numberOfComponents,t.lastMultiTexturePerVolumeEnabled=t.multiTexturePerVolumeEnabled,t.lastIndependentComponents=o,t.lastUseLabelOutline=a,t.lastNumValidInputs=u,t.lastSlabThickness=i,t.lastSlabType=s,t.lastSlabTrapezoidIntegration=l,!0)},e.getShaderTemplate=(e,t,n)=>{e.Vertex="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkImageResliceMapperVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\n// all variables that represent positions or directions have a suffix\n// indicating the coordinate system they are in. The possible values are\n// MC - Model coordinates\n// WC - World coordinates\n// VC - View coordinates\n// DC - Display coordinates\n// TC - Texture coordinates\n\n// frag position in VC\n//VTK::PositionVC::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// picking support\n//VTK::Picking::Dec\n\n// camera and actor matrix values\n//VTK::Camera::Dec\n\nvoid main()\n{\n  //VTK::PositionVC::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Picking::Impl\n}\n",e.Fragment="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkImageResliceMapperFS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n// Template for the gpu image mapper fragment shader\n\n// VC position of this fragment\n//VTK::PositionVC::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\n// picking support\n//VTK::Picking::Dec\n\n// handle coincident offsets\n//VTK::Coincident::Dec\n\n//VTK::ZBuffer::Dec\n\n// the output of this shader\n//VTK::Output::Dec\n\nvoid main()\n{\n  // VC position of this fragment. This should not branch/return/discard.\n  //VTK::PositionVC::Impl\n\n  // Place any calls that require uniform flow (e.g. dFdx) here.\n  //VTK::UniformFlow::Impl\n\n  // Set gl_FragDepth here (gl_FragCoord.z by default)\n  //VTK::Depth::Impl\n\n  // Early depth peeling abort:\n  //VTK::DepthPeeling::PreColor\n\n  //VTK::TCoord::Impl\n\n  if (gl_FragData[0].a <= 0.0)\n    {\n    discard;\n    }\n\n  //VTK::DepthPeeling::Impl\n\n  //VTK::Picking::Impl\n\n  // handle coincident offsets\n  //VTK::Coincident::Impl\n\n  //VTK::ZBuffer::Impl\n\n  //VTK::RenderPassFragmentShader::Impl\n}\n",e.Geometry=""},e.replaceShaderValues=(n,r,o)=>{if(e.replaceShaderTCoord(n,r,o),e.replaceShaderPositionVC(n,r,o),t.haveSeenDepthRequest){let e=n.Fragment;e=vd.substitute(e,"//VTK::ZBuffer::Dec","uniform int depthRequest;").result,e=vd.substitute(e,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float iz = floor(gl_FragCoord.z*65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); }"]).result,n.Fragment=e}e.replaceShaderCoincidentOffset(n,r,o)},e.replaceShaderTCoord=(e,n,r)=>{let o=e.Vertex;const a=e.Geometry;let i=e.Fragment;const s=t.labelOutlineProperties.length>0,l=t.renderable.getSlabThickness();o=vd.substitute(o,"//VTK::TCoord::Dec",[]).result,o=vd.substitute(o,"//VTK::TCoord::Impl",[]).result;const c=t.numberOfComponents,u=r.getProperty(t.currentValidInputs[0].inputIndex).getIndependentComponents(),d=t.scalarTextures.length;let p=[`uniform highp sampler3D volumeTexture[${d}];`,"uniform float cshift0;","uniform float cscale0;","uniform float pwfshift0;","uniform float pwfscale0;","uniform sampler2D colorTexture1;","uniform sampler2D pwfTexture1;","uniform float opacity;","uniform vec4 backgroundColor;"];for(let e=0;e<d;e++)p.push(`uniform mat4 WCTCMatrix${e};`);if(s){p=p.concat(["uniform sampler2D labelOutlineThicknessTexture;","uniform sampler2D labelOutlineOpacityTexture;","uniform float labelOutlineTextureWidth;","uniform float numLabelmaps;"]);for(let e=0;e<d;e++)p.push(`uniform vec3 outlineTangent1_${e};`),p.push(`uniform vec3 outlineTangent2_${e};`),p.push(`uniform vec3 texelSize${e};`)}if(p.push("vec4 rawSampleTexture(vec3 worldPos) {"),t.multiTexturePerVolumeEnabled){p.push("vec4 rawSample;");for(let e=0;e<d;++e)p.push(`vec3 tc${e} = (WCTCMatrix${e} * vec4(worldPos, 1.0)).xyz;`,`rawSample[${e}] = texture(volumeTexture[${e}], tc${e})[0];`);p.push("return rawSample;","}")}else p.push("vec3 tc0 = (WCTCMatrix0 * vec4(worldPos, 1.0)).xyz;","return texture(volumeTexture[0], tc0);","}");if(u){for(let e=1;e<c;e++)p=p.concat([`uniform float cshift${e};`,`uniform float cscale${e};`,`uniform float pwfshift${e};`,`uniform float pwfscale${e};`]);switch(c){case 1:p=p.concat(["uniform float mix0;","#define height0 0.5"]);break;case 2:p=p.concat(["uniform float mix0;","uniform float mix1;","#define height0 0.25","#define height1 0.75"]);break;case 3:p=p.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","#define height0 0.17","#define height1 0.5","#define height2 0.83"]);break;case 4:p=p.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","uniform float mix3;","#define height0 0.125","#define height1 0.375","#define height2 0.625","#define height3 0.875"]);break;default:Xf("Unsupported number of independent coordinates.")}}l>0&&(p=p.concat(["uniform vec3 spacing;","uniform float slabThickness;","uniform int slabType;","uniform int slabTrapezoid;","uniform vec3 vboScaling;"]),p=p.concat(["vec4 compositeValue(vec4 currVal, vec4 valToComp, int trapezoid)","{","  vec4 retVal = vec4(1.0);","  if (slabType == 0) // min","  {","    retVal = min(currVal, valToComp);","  }","  else if (slabType == 1) // max","  {","    retVal = max(currVal, valToComp);","  }","  else if (slabType == 3) // sum","  {","    retVal = currVal + (trapezoid > 0 ? 0.5 * valToComp : valToComp); ","  }","  else // mean","  {","    retVal = currVal + (trapezoid > 0 ? 0.5 * valToComp : valToComp); ","  }","  return retVal;","}"])),i=vd.substitute(i,"//VTK::TCoord::Dec",p).result;let f=["vec3 fragWorldPos = vertexWCVSOutput.xyz;","vec3 fragTexCoord = (WCTCMatrix0 * vec4(fragWorldPos, 1.0)).xyz;","if (any(greaterThan(fragTexCoord, vec3(1.0))) || any(lessThan(fragTexCoord, vec3(0.0))))","{","  // set the background color and exit","  gl_FragData[0] = backgroundColor;","  return;","}","vec4 tvalue = rawSampleTexture(fragWorldPos);"];if(l>0&&(f=f.concat(["// Get the first and last samples","int numSlices = 1;","float scaling = min(min(spacing.x, spacing.y), spacing.z) * 0.5;","vec3 normalxspacing = scaling * normalWCVSOutput;","float distTraveled = length(normalxspacing);","int trapezoid = 0;","while (distTraveled < slabThickness * 0.5)","{","  distTraveled += length(normalxspacing);","  float fnumSlices = float(numSlices);","  if (distTraveled > slabThickness * 0.5)","  {","    // Before stepping outside the slab, sample at the boundaries","    normalxspacing = normalWCVSOutput * slabThickness * 0.5 / fnumSlices;","    trapezoid = slabTrapezoid;","  }","  vec3 worldPosNeg = vertexWCVSOutput.xyz - fnumSlices * normalxspacing * vboScaling;","  vec3 fragTCoordNeg = (WCTCMatrix0 * vec4(worldPosNeg, 1.0)).xyz;","  if (!any(greaterThan(fragTCoordNeg, vec3(1.0))) && !any(lessThan(fragTCoordNeg, vec3(0.0))))","  {","    vec4 newVal = rawSampleTexture(worldPosNeg);","    tvalue = compositeValue(tvalue, newVal, trapezoid);","    numSlices += 1;","  }","  vec3 worldPosPos = vertexWCVSOutput.xyz + fnumSlices * normalxspacing * vboScaling;","  vec3 fragTCoordPos = (WCTCMatrix0 * vec4(worldPosPos, 1.0)).xyz;","  if (!any(greaterThan(fragTCoordPos, vec3(1.0))) && !any(lessThan(fragTCoordPos, vec3(0.0))))","  {","    vec4 newVal = rawSampleTexture(worldPosPos);","    tvalue = compositeValue(tvalue, newVal, trapezoid);","    numSlices += 1;","  }","}","// Finally, if slab type is *mean*, divide the sum by the numSlices","if (slabType == 2)","{","  tvalue = tvalue / float(numSlices);","}"])),u){const e=["r","g","b","a"];for(let t=0;t<c;++t)f=f.concat([`vec3 tcolor${t} = texture2D(colorTexture1, vec2(tvalue.${e[t]} * cscale${t} + cshift${t}, height${t})).rgb;`,`float compWeight${t} = mix${t} * texture2D(pwfTexture1, vec2(tvalue.${e[t]} * pwfscale${t} + pwfshift${t}, height${t})).r;`]);const n=[];if(s)for(let e=0;e<c;e++){const o=r.getProperty(t.currentValidInputs[e].inputIndex);o?.getUseLabelOutline()&&n.push(e)}const o=e=>{if(1===e)return["gl_FragData[0] = vec4(tcolor0.rgb, compWeight0 * opacity);"];const t=Array.from({length:e},((e,t)=>t)),n=t.map((e=>`compWeight${e}`)).join(" + "),r=t.map((e=>`(tcolor${e}.rgb * (compWeight${e} / weightSum))`)).join(" + ");return[`float weightSum = ${n};`,`gl_FragData[0] = vec4(vec3(${r}), opacity);`]};f=n.length>0?f.concat(function(e,t){const n=["r","g","b","a"],r=Array.from({length:t},((e,t)=>t)),o=r.filter((t=>!e.includes(t))),a=e.map((e=>`vec3 labelTexCoord${e} = (WCTCMatrix${e} * vec4(fragWorldPos, 1.0)).xyz;`)).join("\n                "),i=0===e.length?"":`float neighborLabel = ${e.map(((e,t)=>0===t?`(labelInputIdx == ${t}) ? texture(volumeTexture[${e}], neighborTexCoord).r`:` : (labelInputIdx == ${t}) ? texture(volumeTexture[${e}], neighborTexCoord).r`)).join("")} : 0.0;`,s=[...o,...e].map((t=>{const r=e.includes(t),o=e.indexOf(t);return r?`\n        // Process input ${t} as labelmap\n        {\n          float labelValue = tvalue.${n[t]};\n          int segmentIndex = int(labelValue * 255.0);\n\n          if (segmentIndex > 0) {\n            float textureCoordinate = float(segmentIndex - 1) / labelOutlineTextureWidth;\n            float labelmapRow = (float(${o}) + 0.5) / numLabelmaps;\n            float thicknessValue = texture2D(labelOutlineThicknessTexture, vec2(textureCoordinate, labelmapRow)).r;\n            float labelOutlineOpacityValue = texture2D(labelOutlineOpacityTexture, vec2(textureCoordinate, labelmapRow)).r;\n            int actualThickness = int(thicknessValue * 255.0);\n\n            vec3 currentLabelTC = labelTexCoord${t};\n            vec3 currentTexelSize = texelSize${t};\n            vec3 currentTangent1 = outlineTangent1_${t};\n            vec3 currentTangent2 = outlineTangent2_${t};\n\n            bool pixelOnBorder = false;\n            int labelInputIdx = ${o};\n            for (int i = -actualThickness; i <= actualThickness; i++) {\n              for (int j = -actualThickness; j <= actualThickness; j++) {\n                if (i == 0 && j == 0) continue;\n                vec3 neighborTexCoord = currentLabelTC + float(i) * currentTangent1 * currentTexelSize + float(j) * currentTangent2 * currentTexelSize;\n                if (any(greaterThan(neighborTexCoord, vec3(1.0))) || any(lessThan(neighborTexCoord, vec3(0.0)))) {\n                  pixelOnBorder = true;\n                  break;\n                }\n                ${i}\n                if (neighborLabel != labelValue) {\n                  pixelOnBorder = true;\n                  break;\n                }\n              }\n              if (pixelOnBorder) break;\n            }\n\n            if (pixelOnBorder) {\n              convergentColor.rgb = mix(convergentColor.rgb, tcolor${t}.rgb, labelOutlineOpacityValue);\n              convergentColor.a = max(convergentColor.a, labelOutlineOpacityValue);\n            } else if (compWeight${t} > 0.0) {\n              float fillAlpha = compWeight${t} * opacity;\n              convergentColor.rgb = mix(convergentColor.rgb, tcolor${t}.rgb, fillAlpha);\n              convergentColor.a = max(convergentColor.a, fillAlpha);\n            }\n          }\n        }`:`\n        // Process input ${t} as background image\n        {\n          float bgAlpha = compWeight${t} * opacity;\n          convergentColor.rgb = mix(convergentColor.rgb, tcolor${t}.rgb, bgAlpha);\n          convergentColor.a = max(convergentColor.a, bgAlpha);\n        }`})).join("\n        "),l=e.length>0?`labelmaps at input${e.length>1?"s":""} ${e.join(", ")}`:"no labelmaps",c=o.length>0?`background at input${o.length>1?"s":""} ${o.join(", ")}`:"no background";return qf(`\n      // Multi-texture mode: ${l}, ${c}\n      vec4 convergentColor = vec4(0.0, 0.0, 0.0, 0.0);\n\n      // Compute labelmap texture coordinates\n      ${a}\n\n      // Process each input in order\n      ${s}\n\n      gl_FragData[0] = convergentColor;\n    `)}(n,c)):f.concat(o(c))}else switch(c){case 1:f=s?f.concat([...qf("\n                // Label outline mode for single component\n                float centerValue = tvalue.r;\n                int segmentIndex = int(centerValue * 255.0);\n\n                // Skip background (segment 0)\n                if (segmentIndex == 0) {\n                  gl_FragData[0] = vec4(0.0, 0.0, 0.0, 0.0);\n                  return;\n                }\n\n                // Get outline parameters for this segment (row 0 for single labelmap)\n                float textureCoordinate = float(segmentIndex - 1) / labelOutlineTextureWidth;\n                float labelmapRow = 0.5 / numLabelmaps;\n                float thicknessValue = texture2D(labelOutlineThicknessTexture, vec2(textureCoordinate, labelmapRow)).r;\n                float outlineOpacity = texture2D(labelOutlineOpacityTexture, vec2(textureCoordinate, labelmapRow)).r;\n                int actualThickness = int(thicknessValue * 255.0);\n\n                // Get color for this segment\n                vec3 tColor = texture2D(colorTexture1, vec2(centerValue * cscale0 + cshift0, 0.5)).rgb;\n                float scalarOpacity = texture2D(pwfTexture1, vec2(centerValue * pwfscale0 + pwfshift0, 0.5)).r;\n                float opacityToUse = scalarOpacity * opacity;\n\n                // Check neighbors for border detection\n                bool pixelOnBorder = false;\n                for (int i = -actualThickness; i <= actualThickness; i++) {\n                  for (int j = -actualThickness; j <= actualThickness; j++) {\n                    if (i == 0 && j == 0) {\n                      continue;\n                    }\n                    // Sample neighbor using tangent vectors in texture space\n                    vec3 neighborTexCoord = fragTexCoord + float(i) * outlineTangent1_0 * texelSize0 + float(j) * outlineTangent2_0 * texelSize0;\n\n                    // Skip if outside texture bounds\n                    if (any(greaterThan(neighborTexCoord, vec3(1.0))) || any(lessThan(neighborTexCoord, vec3(0.0)))) {\n                      pixelOnBorder = true;\n                      break;\n                    }\n\n                    float neighborValue = texture(volumeTexture[0], neighborTexCoord).r;\n                    if (neighborValue != centerValue) {\n                      pixelOnBorder = true;\n                      break;\n                    }\n                  }\n                  if (pixelOnBorder) {\n                    break;\n                  }\n                }\n\n                if (pixelOnBorder) {\n                  gl_FragData[0] = vec4(tColor, outlineOpacity);\n                } else {\n                  gl_FragData[0] = vec4(tColor, opacityToUse);\n                }\n              ")]):f.concat(["// Dependent components","float intensity = tvalue.r;","vec3 tcolor = texture2D(colorTexture1, vec2(intensity * cscale0 + cshift0, 0.5)).rgb;","float scalarOpacity = texture2D(pwfTexture1, vec2(intensity * pwfscale0 + pwfshift0, 0.5)).r;","gl_FragData[0] = vec4(tcolor, scalarOpacity * opacity);"]);break;case 2:f=f.concat(["float intensity = tvalue.r*cscale0 + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(intensity, 0.5)).rgb, pwfscale0*tvalue.g + pwfshift0);"]);break;case 3:f=f.concat(["vec4 tcolor = cscale0*tvalue + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, opacity);"]);break;default:f=f.concat(["vec4 tcolor = cscale0*tvalue + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, tcolor.a);"])}i=vd.substitute(i,"//VTK::TCoord::Impl",f).result,e.Vertex=o,e.Fragment=i,e.Geometry=a},e.replaceShaderPositionVC=(n,r,o)=>{let a=n.Vertex;const i=n.Geometry;let s=n.Fragment;const l=t.renderable.getSlabThickness();let c=["attribute vec4 vertexWC;","varying vec4 vertexWCVSOutput;"];c=c.concat([`//${e.getMTime()}${t.resliceGeomUpdateString}`]),l>0&&(c=c.concat(["attribute vec3 normalWC;","varying vec3 normalWCVSOutput;"])),a=vd.substitute(a,"//VTK::PositionVC::Dec",c).result;let u=["gl_Position = MCPCMatrix * vertexWC;","vertexWCVSOutput = vertexWC;"];l>0&&(u=u.concat(["normalWCVSOutput = normalWC;"])),a=vd.substitute(a,"//VTK::PositionVC::Impl",u).result,a=vd.substitute(a,"//VTK::Camera::Dec",["uniform mat4 MCPCMatrix;","uniform mat4 MCVCMatrix;"]).result;let d=["varying vec4 vertexWCVSOutput;"];l>0&&(d=d.concat(["varying vec3 normalWCVSOutput;"])),s=vd.substitute(s,"//VTK::PositionVC::Dec",d).result,n.Vertex=a,n.Geometry=i,n.Fragment=s},e.updateResliceGeometry=()=>{let e="";const n=t.currentValidInputs[0].imageData,r=n?.getBounds();let o=!0,a=2;const s=t.renderable.getSlicePolyData(),c=t.renderable.getSlicePlane();if(s)e=e.concat(`PolyData${s.getMTime()}`);else if(c){e=e.concat(`Plane${c.getMTime()}`);const t=i();n&&(e=e.concat(`Image${n.getMTime()}`),l(t,...n.getDirection()),d(t,t));const r=[...c.getNormal()];ae(r,r,t),[o,a]=function(e){za.normalize(e);const t=[0,0,0];for(let r=0;r<3;++r){(n=t)[0]=0,n[1]=0,n[2]=0,t[r]=1;const o=za.dot(e,t);if(o<-.999999||o>.999999)return[!0,r]}var n;return[!1,2]}(r)}else{const o=ai.newInstance();o.setNormal(0,0,1);let a=[0,1,0,1,0,1];n&&(a=r),o.setOrigin(a[0],a[2],.5*(a[5]+a[4])),t.renderable.setSlicePlane(o),e=e.concat(`Plane${c?.getMTime()}`),n&&(e=e.concat(`Image${n.getMTime()}`))}if(!t.resliceGeom||t.resliceGeomUpdateString!==e){if(s)t.resliceGeom||(t.resliceGeom=Ru.newInstance()),t.resliceGeom.getPoints().setData(s.getPoints().getData(),3),t.resliceGeom.getPolys().setData(s.getPolys().getData(),1),t.resliceGeom.getPointData().setNormals(s.getPointData().getNormals());else if(c)if(o){const e=new Float32Array(12),r=n.worldToIndex(c.getOrigin(),[0,0,0]),o=[(a+1)%3,(a+2)%3].sort(),i=n.getSpatialExtent();let s=0;for(let t=0;t<2;++t)for(let n=0;n<2;++n)e[s+a]=r[a],e[s+o[0]]=i[2*o[0]+n],e[s+o[1]]=i[2*o[1]+t],s+=3;t.transform.setMatrix(n.getIndexToWorld()),t.transform.transformPoints(e,e);const l=new Uint16Array(8);l[0]=3,l[1]=0,l[2]=1,l[3]=3,l[4]=3,l[5]=0,l[6]=3,l[7]=2;const u=c.getNormal();za.normalize(u);const d=new Float32Array(12);for(let e=0;e<4;++e)d[3*e]=u[0],d[3*e+1]=u[1],d[3*e+2]=u[2];t.resliceGeom||(t.resliceGeom=Ru.newInstance()),t.resliceGeom.getPoints().setData(e,3),t.resliceGeom.getPolys().setData(l,1);const p=Is.newInstance({numberOfComponents:3,values:d,name:"Normals"});t.resliceGeom.getPointData().setNormals(p)}else{t.outlineFilter.setInputData(n),t.cutter.setInputConnection(t.outlineFilter.getOutputPort()),t.cutter.setCutFunction(c),t.lineToSurfaceFilter.setInputConnection(t.cutter.getOutputPort()),t.lineToSurfaceFilter.update(),t.resliceGeom||(t.resliceGeom=Ru.newInstance());const e=t.lineToSurfaceFilter.getOutputData();t.resliceGeom.getPoints().setData(e.getPoints().getData(),3),t.resliceGeom.getPolys().setData(e.getPolys().getData(),1),t.resliceGeom.getPointData().setNormals(e.getPointData().getNormals());const r=c.getNormal(),o=t.resliceGeom.getNumberOfPoints();za.normalize(r);const a=new Float32Array(3*o);for(let e=0;e<o;++e)a[3*e]=r[0],a[3*e+1]=r[1],a[3*e+2]=r[2];const i=Is.newInstance({numberOfComponents:3,values:a,name:"Normals"});t.resliceGeom.getPointData().setNormals(i)}else Xf("Something went wrong.","A default slice plane should have been created in the beginning of","updateResliceGeometry.");t.resliceGeomUpdateString=e,t.resliceGeom?.modified()}},e.updateLabelOutlineThicknessTexture=e=>{a(e.map((({property:e})=>e.getLabelOutlineThicknessByReference())),Uint8Array,ms.UNSIGNED_CHAR,"_labelOutlineThicknessHash","labelOutlineThicknessTexture")},e.updateLabelOutlineOpacityTexture=e=>{a(e.map((({property:e})=>{let t=e.getLabelOutlineOpacity();return"number"==typeof t&&(t=[t]),t})),Float32Array,ms.FLOAT,"_labelOutlineOpacityHash","labelOutlineOpacityTexture")},e.setScalarTextures=e=>{t.scalarTextures=[...e],t._externalOpenGLTexture=!0},e.delete=qt((()=>{t._openGLRenderWindow&&o(t._openGLRenderWindow),t.labelOutlineThicknessTexture&&(t.labelOutlineThicknessTexture.releaseGraphicsResources(),t.labelOutlineThicknessTexture=null),t.labelOutlineOpacityTexture&&(t.labelOutlineOpacityTexture.releaseGraphicsResources(),t.labelOutlineOpacityTexture=null)}),e.delete)}const Zf={VBOBuildTime:{},VBOBuildString:null,haveSeenDepthRequest:!1,lastHaveSeenDepthRequest:!1,lastIndependentComponents:!1,lastUseLabelOutline:!1,lastNumValidInputs:0,lastNumberOfComponents:0,lastMultiTexturePerVolumeEnabled:!1,lastSlabThickness:0,lastSlabTrapezoidIntegration:0,lastSlabType:-1,scalarTextures:[],_scalarTexturesCore:[],colorTexture:null,_colorTextureCore:null,pwfTexture:null,_pwfTextureCore:null,labelOutlineProperties:[],labelOutlineThicknessTexture:null,_labelOutlineThicknessHash:null,labelOutlineOpacityTexture:null,_labelOutlineOpacityHash:null,_externalOpenGLTexture:!1,resliceGeom:null,resliceGeomUpdateString:null,tris:null};vn("vtkImageResliceMapper",Xt((function(e,t,n={}){Object.assign(t,Zf,n),pn.extend(e,t,n),qd.implementReplaceShaderCoincidentOffset(e,t,n),qd.implementBuildShadersWithReplacements(e,t,n),t.tris=Sd.newInstance(),t.scalarTextures=[],t.colorTexture=null,t.pwfTexture=null,t.VBOBuildTime={},Vt(t.VBOBuildTime),t.tmpMat4=x(new Float64Array(16)),t._tmpMat3=i(),t._tmpVec3a=j(),t._tmpVec3b=j(),t._tmpTangent1=[0,0,0],t._tmpTangent2=[0,0,0],t._tmpTexelSize=[0,0,0],t.outlineFilter=Nf.newInstance(),t.outlineFilter.setGenerateFaces(!0),t.outlineFilter.setGenerateLines(!1),t.cubePolyData=Ru.newInstance(),t.cutter=Sf.newInstance(),t.lineToSurfaceFilter=xf.newInstance(),t.transform=Kf.newInstance(),Bt(e,t,["scalarTextures"]),Jf(e,t)}),"vtkOpenGLImageResliceMapper"));var Qf={SlicingMode:{NONE:-1,I:0,J:1,K:2,X:3,Y:4,Z:5}};const{vtkErrorMacro:$f}=ln,{SlicingMode:eg}=Qf;function tg(e){const t=e.split("\n"),n=[];for(let e=0;e<t.length;++e){const r=t[e].trim();r.length>0&&n.push(r)}return n}const ng={VBOBuildTime:0,VBOBuildString:null,openGLTexture:null,tris:null,imagemat:null,imagematinv:null,colorTexture:null,pwfTexture:null,labelOutlineThicknessTexture:null,labelOutlineOpacityTexture:null,lastHaveSeenDepthRequest:!1,haveSeenDepthRequest:!1,lastTextureComponents:0};const rg=Xt((function(e,t,n={}){Object.assign(t,ng,n),pn.extend(e,t,n),qd.implementReplaceShaderCoincidentOffset(e,t,n),qd.implementBuildShadersWithReplacements(e,t,n),t.tris=Sd.newInstance(),t.imagemat=x(new Float64Array(16)),t.imagematinv=x(new Float64Array(16)),t.projectionToWorld=x(new Float64Array(16)),t.idxToView=x(new Float64Array(16)),t.idxNormalMatrix=c(new Float64Array(9)),t.modelToView=x(new Float64Array(16)),t.projectionToView=x(new Float64Array(16)),Gt(e,t,[]),t.VBOBuildTime={},Vt(t.VBOBuildTime),function(e,t){function n(n){t.openGLTexture.releaseGraphicsResources(n),[t._colorTransferFunc,t._pwFunc,t._labelOutlineThicknessArray,t._labelOutlineOpacity].forEach((t=>n.unregisterGraphicsResourceUser(t,e)))}t.classHierarchy.push("vtkOpenGLImageMapper"),e.buildPass=r=>{if(r){t.currentRenderPass=null,t.openGLImageSlice=e.getFirstAncestorOfType("vtkOpenGLImageSlice"),t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer");const r=t._openGLRenderWindow;t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow"),r&&!r.isDeleted()&&r!==t._openGLRenderWindow&&n(r),t.context=t._openGLRenderWindow.getContext(),t.tris.setOpenGLRenderWindow(t._openGLRenderWindow);const o=t._openGLRenderer.getRenderable();t.openGLCamera=t._openGLRenderer.getViewNodeFor(o.getActiveCamera(),t.openGLCamera),t.renderable.isA("vtkImageMapper")&&t.renderable.getSliceAtFocalPoint()&&t.renderable.setSliceFromCamera(o.getActiveCamera())}},e.translucentPass=(n,r)=>{n&&(t.currentRenderPass=r,e.render())},e.zBufferPass=n=>{n&&(t.haveSeenDepthRequest=!0,t.renderDepth=!0,e.render(),t.renderDepth=!1)},e.opaqueZBufferPass=t=>e.zBufferPass(t),e.opaquePass=t=>{t&&e.render()},e.getCoincidentParameters=(e,n)=>t.renderable.getResolveCoincidentTopology()==Pl.PolygonOffset?t.renderable.getCoincidentTopologyPolygonOffsetParameters():null,e.render=()=>{const n=t.openGLImageSlice.getRenderable(),r=t._openGLRenderer.getRenderable();e.renderPiece(r,n)},e.getShaderTemplate=(e,t,n)=>{e.Vertex=jd,e.Fragment=Xd,e.Geometry=""},e.replaceShaderValues=(n,r,o)=>{let a=n.Vertex,i=n.Fragment;a=vd.substitute(a,"//VTK::Camera::Dec",["uniform mat4 MCPCMatrix;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Impl",["  gl_Position = MCPCMatrix * vertexMC;"]).result,a=vd.substitute(a,"//VTK::TCoord::Impl","tcoordVCVSOutput = tcoordMC;").result,a=vd.substitute(a,"//VTK::TCoord::Dec","attribute vec2 tcoordMC; varying vec2 tcoordVCVSOutput;").result;const s=t.openGLTexture.getComponents(),l=o.getProperty().getIndependentComponents();let c=["varying vec2 tcoordVCVSOutput;","uniform float cshift0;","uniform float cscale0;","uniform float pwfshift0;","uniform float pwfscale0;","uniform sampler2D texture1;","uniform sampler2D colorTexture1;","uniform sampler2D pwfTexture1;","uniform float opacity;"];if(o.getProperty().getUseLabelOutline()&&(c=c.concat(["uniform sampler2D labelOutlineTexture1;","uniform sampler2D labelOutlineOpacityTexture1;"])),l){for(let e=1;e<s;e++)c=c.concat([`uniform float cshift${e};`,`uniform float cscale${e};`,`uniform float pwfshift${e};`,`uniform float pwfscale${e};`]);switch(s){case 1:c=c.concat(["uniform float mix0;","#define height0 0.5"]);break;case 2:c=c.concat(["uniform float mix0;","uniform float mix1;","#define height0 0.25","#define height1 0.75"]);break;case 3:c=c.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","#define height0 0.17","#define height1 0.5","#define height2 0.83"]);break;case 4:c=c.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","uniform float mix3;","#define height0 0.125","#define height1 0.375","#define height2 0.625","#define height3 0.875"]);break;default:$f("Unsupported number of independent coordinates.")}}if(i=vd.substitute(i,"//VTK::TCoord::Dec",c).result,!0===o.getProperty().getUseLabelOutline()&&(i=vd.substitute(i,"//VTK::LabelOutline::Dec",["uniform float vpWidth;","uniform float vpHeight;","uniform float vpOffsetX;","uniform float vpOffsetY;","uniform mat4 PCWCMatrix;","uniform mat4 vWCtoIDX;","uniform ivec3 imageDimensions;","uniform int sliceAxis;"]).result,i=vd.substitute(i,"//VTK::ImageLabelOutlineOn","#define vtkImageLabelOutlineOn").result,i=vd.substitute(i,"//VTK::LabelOutlineHelperFunction",["#ifdef vtkImageLabelOutlineOn","vec3 fragCoordToIndexSpace(vec4 fragCoord) {","  vec4 pcPos = vec4(","    (fragCoord.x / vpWidth - vpOffsetX - 0.5) * 2.0,","    (fragCoord.y / vpHeight - vpOffsetY - 0.5) * 2.0,","    (fragCoord.z - 0.5) * 2.0,","    1.0);","","  vec4 worldCoord = PCWCMatrix * pcPos;","  vec4 vertex = (worldCoord/worldCoord.w);","","  vec3 index = (vWCtoIDX * vertex).xyz;","","  // half voxel fix for labelmapOutline","  return (index + vec3(0.5)) / vec3(imageDimensions);","}","vec2 getSliceCoords(vec3 coord, int axis) {","  if (axis == 0) return coord.yz;","  if (axis == 1) return coord.xz;","  if (axis == 2) return coord.xy;","}","#endif"]).result),l){const e=["r","g","b","a"];let t=["vec4 tvalue = texture2D(texture1, tcoordVCVSOutput);"];for(let n=0;n<s;n++)t=t.concat([`vec3 tcolor${n} = mix${n} * texture2D(colorTexture1, vec2(tvalue.${e[n]} * cscale${n} + cshift${n}, height${n})).rgb;`,`float compWeight${n} = mix${n} * texture2D(pwfTexture1, vec2(tvalue.${e[n]} * pwfscale${n} + pwfshift${n}, height${n})).r;`]);switch(s){case 1:t=t.concat(["gl_FragData[0] = vec4(tcolor0.rgb, opacity);"]);break;case 2:t=t.concat(["float weightSum = compWeight0 + compWeight1;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum))), opacity);"]);break;case 3:t=t.concat(["float weightSum = compWeight0 + compWeight1 + compWeight2;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum)) + (tcolor2.rgb * (compWeight2 / weightSum))), opacity);"]);break;case 4:t=t.concat(["float weightSum = compWeight0 + compWeight1 + compWeight2 + compWeight3;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum)) + (tcolor2.rgb * (compWeight2 / weightSum)) + (tcolor3.rgb * (compWeight3 / weightSum))), opacity);"]);break;default:$f("Unsupported number of independent coordinates.")}i=vd.substitute(i,"//VTK::TCoord::Impl",t).result}else switch(s){case 1:i=vd.substitute(i,"//VTK::TCoord::Impl",[...tg("\n                #ifdef vtkImageLabelOutlineOn\n                  vec3 centerPosIS = fragCoordToIndexSpace(gl_FragCoord);\n                  float centerValue = texture2D(texture1, getSliceCoords(centerPosIS, sliceAxis)).r;\n                  bool pixelOnBorder = false;\n                  vec3 tColor = texture2D(colorTexture1, vec2(centerValue * cscale0 + cshift0, 0.5)).rgb;\n                  float scalarOpacity = texture2D(pwfTexture1, vec2(centerValue * pwfscale0 + pwfshift0, 0.5)).r;\n                  float opacityToUse = scalarOpacity * opacity;\n                  int segmentIndex = int(centerValue * 255.0);\n                  float textureCoordinate = float(segmentIndex - 1) / 1024.0;\n                  float textureValue = texture2D(labelOutlineTexture1, vec2(textureCoordinate, 0.5)).r;\n                  float outlineOpacity = texture2D(labelOutlineOpacityTexture1, vec2(textureCoordinate, 0.5)).r;\n                  int actualThickness = int(textureValue * 255.0);\n\n                  if (segmentIndex == 0){\n                    gl_FragData[0] = vec4(0.0, 0.0, 0.0, 0.0);\n                    return;\n                  }\n\n                  for (int i = -actualThickness; i <= actualThickness; i++) {\n                    for (int j = -actualThickness; j <= actualThickness; j++) {\n                      if (i == 0 && j == 0) {\n                        continue;\n                      }\n                      vec4 neighborPixelCoord = vec4(gl_FragCoord.x + float(i),\n                        gl_FragCoord.y + float(j),\n                        gl_FragCoord.z, gl_FragCoord.w);\n                      vec3 neighborPosIS = fragCoordToIndexSpace(neighborPixelCoord);\n                      float value = texture2D(texture1, getSliceCoords(neighborPosIS, sliceAxis)).r;\n                      if (value != centerValue) {\n                        pixelOnBorder = true;\n                        break;\n                      }\n                    }\n                    if (pixelOnBorder == true) {\n                      break;\n                    }\n                  }\n                  if (pixelOnBorder == true) {\n                    gl_FragData[0] = vec4(tColor, outlineOpacity);\n                  }\n                  else {\n                    gl_FragData[0] = vec4(tColor, opacityToUse);\n                  }\n                #else\n                  float intensity = texture2D(texture1, tcoordVCVSOutput).r;\n                  vec3 tcolor = texture2D(colorTexture1, vec2(intensity * cscale0 + cshift0, 0.5)).rgb;\n                  float scalarOpacity = texture2D(pwfTexture1, vec2(intensity * pwfscale0 + pwfshift0, 0.5)).r;\n                  gl_FragData[0] = vec4(tcolor, scalarOpacity * opacity);\n                #endif\n                ")]).result;break;case 2:i=vd.substitute(i,"//VTK::TCoord::Impl",["vec4 tcolor = texture2D(texture1, tcoordVCVSOutput);","float intensity = tcolor.r*cscale0 + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(intensity, 0.5)).rgb, pwfscale0*tcolor.g + pwfshift0);"]).result;break;case 3:i=vd.substitute(i,"//VTK::TCoord::Impl",["vec4 tcolor = cscale0*texture2D(texture1, tcoordVCVSOutput.st) + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, opacity);"]).result;break;default:i=vd.substitute(i,"//VTK::TCoord::Impl",["vec4 tcolor = cscale0*texture2D(texture1, tcoordVCVSOutput.st) + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, tcolor.a);"]).result}t.haveSeenDepthRequest&&(i=vd.substitute(i,"//VTK::ZBuffer::Dec","uniform int depthRequest;").result,i=vd.substitute(i,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float iz = floor(gl_FragCoord.z*65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); }"]).result),n.Vertex=a,n.Fragment=i,e.replaceShaderClip(n,r,o),e.replaceShaderCoincidentOffset(n,r,o)},e.replaceShaderClip=(e,n,r)=>{let o=e.Vertex,a=e.Fragment;if(t.renderable.getNumberOfClippingPlanes()){let e=t.renderable.getNumberOfClippingPlanes();e>6&&(Tt("OpenGL has a limit of 6 clipping planes"),e=6),o=vd.substitute(o,"//VTK::Clip::Dec",["uniform int numClipPlanes;","uniform vec4 clipPlanes[6];","varying float clipDistancesVSOutput[6];"]).result,o=vd.substitute(o,"//VTK::Clip::Impl",["for (int planeNum = 0; planeNum < 6; planeNum++)","    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    clipDistancesVSOutput[planeNum] = dot(clipPlanes[planeNum], vertexMC);","    }"]).result,a=vd.substitute(a,"//VTK::Clip::Dec",["uniform int numClipPlanes;","varying float clipDistancesVSOutput[6];"]).result,a=vd.substitute(a,"//VTK::Clip::Impl",["for (int planeNum = 0; planeNum < 6; planeNum++)","    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    if (clipDistancesVSOutput[planeNum] < 0.0) discard;","    }"]).result}e.Vertex=o,e.Fragment=a},e.getNeedToRebuildShaders=(e,n,r)=>{const o=t.openGLTexture.getComponents(),a=r.getProperty().getIndependentComponents();let i=!1;return(!t.currentRenderPass&&t.lastRenderPassShaderReplacement||t.currentRenderPass&&t.currentRenderPass.getShaderReplacement()!==t.lastRenderPassShaderReplacement)&&(i=!0),!!(i||t.lastHaveSeenDepthRequest!==t.haveSeenDepthRequest||0===e.getProgram()?.getHandle()||e.getShaderSourceTime().getMTime()<t.renderable.getMTime()||e.getShaderSourceTime().getMTime()<t.currentInput.getMTime()||e.getShaderSourceTime().getMTime()<r.getProperty().getMTime()||t.lastTextureComponents!==o||t.lastIndependentComponents!==a)&&(t.lastHaveSeenDepthRequest=t.haveSeenDepthRequest,t.lastTextureComponents=o,t.lastIndependentComponents=a,!0)},e.updateShaders=(n,r,o)=>{if(t.lastBoundBO=n,e.getNeedToRebuildShaders(n,r,o)){const a={Vertex:null,Fragment:null,Geometry:null};e.buildShaders(a,r,o);const i=t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(a.Vertex,a.Fragment,a.Geometry);i!==n.getProgram()&&(n.setProgram(i),n.getVAO().releaseGraphicsResources()),n.getShaderSourceTime().modified()}else t._openGLRenderWindow.getShaderCache().readyShaderProgram(n.getProgram());n.getVAO().bind(),e.setMapperShaderParameters(n,r,o),e.setCameraShaderParameters(n,r,o),e.setPropertyShaderParameters(n,r,o)},e.setMapperShaderParameters=(n,r,o)=>{n.getCABO().getElementCount()&&(t.VBOBuildTime>n.getAttributeUpdateTime().getMTime()||n.getShaderSourceTime().getMTime()>n.getAttributeUpdateTime().getMTime())&&(n.getProgram().isAttributeUsed("vertexMC")&&(n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),"vertexMC",n.getCABO().getVertexOffset(),n.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||$f("Error setting vertexMC in shader VAO.")),n.getProgram().isAttributeUsed("tcoordMC")&&n.getCABO().getTCoordOffset()&&(n.getVAO().addAttributeArray(n.getProgram(),n.getCABO(),"tcoordMC",n.getCABO().getTCoordOffset(),n.getCABO().getStride(),t.context.FLOAT,n.getCABO().getTCoordComponents(),t.context.FALSE)||$f("Error setting tcoordMC in shader VAO.")),n.getAttributeUpdateTime().modified());const a=t.openGLTexture.getTextureUnit();n.getProgram().setUniformi("texture1",a);const i=t.openGLTexture.getComponents(),s=o.getProperty().getIndependentComponents();if(s)for(let e=0;e<i;e++)n.getProgram().setUniformf(`mix${e}`,o.getProperty().getComponentWeight(e));const l=t.openGLTexture.getShiftAndScale();for(let e=0;e<i;e++){let t=o.getProperty().getColorWindow(),r=o.getProperty().getColorLevel();const a=s?e:0,i=o.getProperty().getRGBTransferFunction(a);if(i&&o.getProperty().getUseLookupTableScalarRange()){const e=i.getRange();t=e[1]-e[0],r=.5*(e[1]+e[0])}const c=l.scale/t,u=(l.shift-r)/t+.5;n.getProgram().setUniformf(`cshift${e}`,u),n.getProgram().setUniformf(`cscale${e}`,c)}for(let e=0;e<i;e++){let t=1,r=0;const a=s?e:0,i=o.getProperty().getPiecewiseFunction(a);if(i){const e=i.getRange(),n=e[1]-e[0],o=.5*(e[0]+e[1]);t=l.scale/n,r=(l.shift-o)/n+.5}n.getProgram().setUniformf(`pwfshift${e}`,r),n.getProgram().setUniformf(`pwfscale${e}`,t)}if(t.haveSeenDepthRequest&&n.getProgram().setUniformi("depthRequest",t.renderDepth?1:0),n.getProgram().isUniformUsed("coffset")){const t=e.getCoincidentParameters(r,o);n.getProgram().setUniformf("coffset",t.offset),n.getProgram().isUniformUsed("cfactor")&&n.getProgram().setUniformf("cfactor",t.factor)}const c=t.colorTexture.getTextureUnit();n.getProgram().setUniformi("colorTexture1",c);const u=t.pwfTexture.getTextureUnit();if(n.getProgram().setUniformi("pwfTexture1",u),o.getProperty().getUseLabelOutline()){const e=t.labelOutlineThicknessTexture.getTextureUnit();n.getProgram().setUniformi("labelOutlineTexture1",e);const r=t.labelOutlineOpacityTexture.getTextureUnit();n.getProgram().setUniformi("labelOutlineOpacityTexture1",r)}if(t.renderable.getNumberOfClippingPlanes()){let e=t.renderable.getNumberOfClippingPlanes();e>6&&(Tt("OpenGL has a limit of 6 clipping planes"),e=6);const r=n.getCABO().getCoordShiftAndScaleEnabled()?n.getCABO().getInverseShiftAndScaleMatrix():null,a=r?T(t.imagematinv,o.getMatrix()):o.getMatrix();r&&(y(a,a),A(a,a,r),y(a,a)),y(t.imagemat,t.currentInput.getIndexToWorld()),A(t.imagematinv,a,t.imagemat);const i=[];for(let n=0;n<e;n++){const e=[];t.renderable.getClippingPlaneInDataCoords(t.imagematinv,n,e);for(let t=0;t<4;t++)i.push(e[t])}n.getProgram().setUniformi("numClipPlanes",e),n.getProgram().setUniform4fv("clipPlanes",i)}},e.setCameraShaderParameters=(n,r,o)=>{const a=n.getProgram(),i=t.openGLImageSlice.getKeyMatrices(),s=t.currentInput,l=s.getIndexToWorld();A(t.imagemat,i.mcwc,l);const c=t.openGLCamera.getKeyMatrices(r);if(A(t.imagemat,c.wcpc,t.imagemat),n.getCABO().getCoordShiftAndScaleEnabled()){const e=n.getCABO().getInverseShiftAndScaleMatrix();A(t.imagemat,t.imagemat,e)}if(a.setUniformMatrix("MCPCMatrix",t.imagemat),!0===o.getProperty().getUseLabelOutline()){const n=s.getWorldToIndex(),o=s.getDimensions();let i=t.renderable.getClosestIJKAxis().ijkMode;i===eg.NONE&&(i=eg.K),a.setUniform3i("imageDimensions",o[0],o[1],o[2]),a.setUniformi("sliceAxis",i),a.setUniformMatrix("vWCtoIDX",n);const l=t.openGLCamera.getKeyMatrices(r);b(t.projectionToWorld,l.wcpc),t.openGLCamera.getKeyMatrices(r),a.setUniformMatrix("PCWCMatrix",t.projectionToWorld);const c=e.getRenderTargetSize();a.setUniformf("vpWidth",c[0]),a.setUniformf("vpHeight",c[1]);const u=e.getRenderTargetOffset();a.setUniformf("vpOffsetX",u[0]/c[0]),a.setUniformf("vpOffsetY",u[1]/c[1])}},e.setPropertyShaderParameters=(e,t,n)=>{const r=e.getProgram(),o=n.getProperty().getOpacity();r.setUniformf("opacity",o)},e.renderPieceStart=(n,r)=>{e.updateBufferObjects(n,r),t.lastBoundBO=null},e.renderPieceDraw=(n,r)=>{const o=t.context;t.openGLTexture.activate(),t.colorTexture.activate(),r.getProperty().getUseLabelOutline()&&(t.labelOutlineThicknessTexture.activate(),t.labelOutlineOpacityTexture.activate()),t.pwfTexture.activate(),t.tris.getCABO().getElementCount()&&(e.updateShaders(t.tris,n,r),o.drawArrays(o.TRIANGLES,0,t.tris.getCABO().getElementCount()),t.tris.getVAO().release()),t.openGLTexture.deactivate(),t.colorTexture.deactivate(),r.getProperty().getUseLabelOutline()&&(t.labelOutlineThicknessTexture.deactivate(),t.labelOutlineOpacityTexture.deactivate()),t.pwfTexture.deactivate()},e.renderPieceFinish=(e,t)=>{},e.renderPiece=(n,r)=>{e.invokeEvent({type:"StartEvent"}),t.renderable.update(),t.currentInput=t.renderable.getCurrentImage(),e.invokeEvent({type:"EndEvent"}),t.currentInput?(e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r)):$f("No input!")},e.updateBufferObjects=(t,n)=>{e.getNeedToRebuildBufferObjects(t,n)&&e.buildBufferObjects(t,n)},e.getNeedToRebuildBufferObjects=(n,r)=>t.VBOBuildTime.getMTime()<e.getMTime()||t.VBOBuildTime.getMTime()<r.getMTime()||t.VBOBuildTime.getMTime()<t.renderable.getMTime()||t.VBOBuildTime.getMTime()<r.getProperty().getMTime()||t.VBOBuildTime.getMTime()<t.currentInput.getMTime()||!t.openGLTexture?.getHandle()||!t.colorTexture?.getHandle()||r.getProperty().getUseLabelOutline()&&(!t.labelOutlineThicknessTexture?.getHandle()||!t.labelOutlineOpacityTexture?.getHandle())||!t.pwfTexture?.getHandle(),e.buildBufferObjects=(n,r)=>{const o=t.currentInput;if(!o)return;const a=o.getPointData()&&o.getPointData().getScalars();if(!a)return;const i=a.getDataType(),s=a.getNumberOfComponents(),l=r.getProperty(),c=l.getInterpolationType(),u=l.getIndependentComponents(),d=u?s:1,p=u?2*d:1,f=[];for(let e=0;e<d;++e)f.push(l.getRGBTransferFunction(e));const g=zf(f,u,d),m=l.getRGBTransferFunction(),h=t._openGLRenderWindow.getGraphicsResourceForObject(m);if(h?.oglObject?.getHandle()&&h?.hash===g)t.colorTexture=h.oglObject;else{t.colorTexture=Hd.newInstance({resizable:!0}),t.colorTexture.setOpenGLRenderWindow(t._openGLRenderWindow);let n=t.renderable.getColorTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=new Uint8ClampedArray(n*p*3);if(c===Hf.NEAREST?(t.colorTexture.setMinificationFilter(wd.NEAREST),t.colorTexture.setMagnificationFilter(wd.NEAREST)):(t.colorTexture.setMinificationFilter(wd.LINEAR),t.colorTexture.setMagnificationFilter(wd.LINEAR)),m){const e=new Float32Array(3*n);for(let t=0;t<d;t++){const o=l.getRGBTransferFunction(t),a=o.getRange();if(o.getTable(a[0],a[1],n,e,1),u)for(let o=0;o<3*n;o++)r[t*n*6+o]=255*e[o],r[t*n*6+o+3*n]=255*e[o];else for(let o=0;o<3*n;o++)r[t*n*6+o]=255*e[o]}t.colorTexture.resetFormatAndType(),t.colorTexture.create2DFromRaw({width:n,height:p,numComps:3,dataType:ms.UNSIGNED_CHAR,data:r})}else{for(let e=0;e<3*n;++e)r[e]=255*e/(3*(n-1)),r[e+1]=255*e/(3*(n-1)),r[e+2]=255*e/(3*(n-1));t.colorTexture.create2DFromRaw({width:n,height:1,numComps:3,dataType:ms.UNSIGNED_CHAR,data:r})}m&&(t._openGLRenderWindow.setGraphicsResourceForObject(m,t.colorTexture,g),m!==t._colorTransferFunc&&(t._openGLRenderWindow.registerGraphicsResourceUser(m,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._colorTransferFunc,e)),t._colorTransferFunc=m)}const v=[];for(let e=0;e<d;++e)v.push(l.getPiecewiseFunction(e));const T=zf(v,u,d),x=l.getPiecewiseFunction(),y=t._openGLRenderWindow.getGraphicsResourceForObject(x);if(y?.oglObject?.getHandle()&&y?.hash===T)t.pwfTexture=y.oglObject;else{let n=t.renderable.getOpacityTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=n*p,o=new Uint8ClampedArray(r);if(t.pwfTexture=Hd.newInstance({resizable:!0}),t.pwfTexture.setOpenGLRenderWindow(t._openGLRenderWindow),c===Hf.NEAREST?(t.pwfTexture.setMinificationFilter(wd.NEAREST),t.pwfTexture.setMagnificationFilter(wd.NEAREST)):(t.pwfTexture.setMinificationFilter(wd.LINEAR),t.pwfTexture.setMagnificationFilter(wd.LINEAR)),x){const e=new Float32Array(r),o=new Float32Array(n);for(let t=0;t<d;++t){const r=l.getPiecewiseFunction(t);if(null===r)e.fill(1);else{const a=r.getRange();if(r.getTable(a[0],a[1],n,o,1),u)for(let r=0;r<n;r++)e[t*n*2+r]=o[r],e[t*n*2+r+n]=o[r];else for(let r=0;r<n;r++)e[t*n*2+r]=o[r]}}t.pwfTexture.resetFormatAndType(),t.pwfTexture.create2DFromRaw({width:n,height:p,numComps:1,dataType:ms.FLOAT,data:e})}else o.fill(255),t.pwfTexture.create2DFromRaw({width:n,height:1,numComps:1,dataType:ms.UNSIGNED_CHAR,data:o});x&&(t._openGLRenderWindow.setGraphicsResourceForObject(x,t.pwfTexture,T),x!==t._pwFunc&&(t._openGLRenderWindow.registerGraphicsResourceUser(x,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._pwFunc,e)),t._pwFunc=x)}r.getProperty().getUseLabelOutline()&&(e.updatelabelOutlineThicknessTexture(r),e.updateLabelOutlineOpacityTexture(r));const{ijkMode:b}=t.renderable.getClosestIJKAxis();let A=t.renderable.getSlice();b!==t.renderable.getSlicingMode()&&(A=t.renderable.getSliceAtPosition(A));const C=t.renderable.isA("vtkImageArrayMapper")?t.renderable.getSubSlice():Math.round(A),S=o.getExtent();let P;b===eg.I&&(P=C-S[0]),b===eg.J&&(P=C-S[2]),b!==eg.K&&b!==eg.NONE||(P=C-S[4]);const w=`${A}A${o.getMTime()}A${a.getMTime()}B${e.getMTime()}C${t.renderable.getSlicingMode()}D${r.getProperty().getInterpolationType()}`;if(t.VBOBuildString!==w){const e=o.getDimensions();t.openGLTexture||(t.openGLTexture=Hd.newInstance({resizable:!0})),t.openGLTexture.setOpenGLRenderWindow(t._openGLRenderWindow),t.openGLTexture.setOglNorm16Ext(t.context.getExtension("EXT_texture_norm16")),c===Hf.NEAREST?(new Set([1,3,4]).has(s)&&i===ms.UNSIGNED_CHAR&&!u?(t.openGLTexture.setGenerateMipmap(!0),t.openGLTexture.setMinificationFilter(wd.NEAREST)):t.openGLTexture.setMinificationFilter(wd.NEAREST),t.openGLTexture.setMagnificationFilter(wd.NEAREST)):(4!==s||i!==ms.UNSIGNED_CHAR||u?t.openGLTexture.setMinificationFilter(wd.LINEAR):(t.openGLTexture.setGenerateMipmap(!0),t.openGLTexture.setMinificationFilter(wd.LINEAR_MIPMAP_LINEAR)),t.openGLTexture.setMagnificationFilter(wd.LINEAR)),t.openGLTexture.setWrapS(Pd.CLAMP_TO_EDGE),t.openGLTexture.setWrapT(Pd.CLAMP_TO_EDGE);const n=e[0]*e[1]*s,r=new Float32Array(12),l=new Float32Array(8);for(let e=0;e<4;e++)l[2*e]=e%2?1:0,l[2*e+1]=e>1?1:0;const d=[eg.X,eg.Y,eg.Z].includes(t.renderable.getSlicingMode())?A:C,p=o.getSpatialExtent(),f=a.getData();let g=null;if(b===eg.I){g=new f.constructor(e[2]*e[1]*s);let t=0;for(let n=0;n<e[2];n++)for(let r=0;r<e[1];r++){let o=(P+r*e[0]+n*e[0]*e[1])*s;t=(n*e[1]+r)*s;const a=o+s;for(;o<a;)g[t++]=f[o++]}e[0]=e[1],e[1]=e[2],r[0]=d,r[1]=p[2],r[2]=p[4],r[3]=d,r[4]=p[3],r[5]=p[4],r[6]=d,r[7]=p[2],r[8]=p[5],r[9]=d,r[10]=p[3],r[11]=p[5]}else if(b===eg.J){g=new f.constructor(e[2]*e[0]*s);let t=0;for(let n=0;n<e[2];n++)for(let r=0;r<e[0];r++){let o=(r+P*e[0]+n*e[0]*e[1])*s;t=(n*e[0]+r)*s;const a=o+s;for(;o<a;)g[t++]=f[o++]}e[1]=e[2],r[0]=p[0],r[1]=d,r[2]=p[4],r[3]=p[1],r[4]=d,r[5]=p[4],r[6]=p[0],r[7]=d,r[8]=p[5],r[9]=p[1],r[10]=d,r[11]=p[5]}else b===eg.K||b===eg.NONE?(g=f.subarray(P*n,(P+1)*n),r[0]=p[0],r[1]=p[2],r[2]=d,r[3]=p[1],r[4]=p[2],r[5]=d,r[6]=p[0],r[7]=p[3],r[8]=d,r[9]=p[1],r[10]=p[3],r[11]=d):$f("Reformat slicing not yet supported.");const m=a.getRanges();t.openGLTexture.resetFormatAndType(),t.openGLTexture.create2DFilterableFromRaw({width:e[0],height:e[1],numComps:s,dataType:a.getDataType(),data:g,preferSizeOverAccuracy:!!t.renderable.getPreferSizeOverAccuracy?.(),ranges:m}),t.openGLTexture.activate(),t.openGLTexture.sendParameters(),t.openGLTexture.deactivate();const h=Is.newInstance({numberOfComponents:3,values:r});h.setName("points");const v=Is.newInstance({numberOfComponents:2,values:l});v.setName("tcoords");const T=new Uint16Array(8);T[0]=3,T[1]=0,T[2]=1,T[3]=3,T[4]=3,T[5]=0,T[6]=3,T[7]=2;const x=Is.newInstance({numberOfComponents:1,values:T});t.tris.getCABO().createVBO(x,"polys",rs.SURFACE,{points:h,tcoords:v,cellOffset:0}),t.VBOBuildTime.modified(),t.VBOBuildString=w}},e.updateLabelOutlineOpacityTexture=n=>{let r=n.getProperty().getLabelOutlineOpacity();"number"==typeof r&&(r=t._cachedLabelOutlineOpacityObj?.[0]===r?t._cachedLabelOutlineOpacityObj:[r],t._cachedLabelOutlineOpacityObj=r);const o=t._openGLRenderWindow.getGraphicsResourceForObject(r),a=`${r.join("-")}`;if(o?.oglObject?.getHandle()&&o?.hash===a)t.labelOutlineOpacityTexture=o.oglObject;else{let n=t.renderable.getLabelOutlineTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const o=1,i=new Float32Array(n*o);for(let e=0;e<n;++e)i[e]=r[e]??r[0];t.labelOutlineOpacityTexture=Hd.newInstance({resizable:!1}),t.labelOutlineOpacityTexture.setOpenGLRenderWindow(t._openGLRenderWindow),t.labelOutlineOpacityTexture.resetFormatAndType(),t.labelOutlineOpacityTexture.setMinificationFilter(wd.NEAREST),t.labelOutlineOpacityTexture.setMagnificationFilter(wd.NEAREST),t.labelOutlineOpacityTexture.create2DFromRaw({width:n,height:o,numComps:1,dataType:ms.FLOAT,data:i}),r&&(t._openGLRenderWindow.setGraphicsResourceForObject(r,t.labelOutlineOpacityTexture,a),r!==t._labelOutlineOpacity&&(t._openGLRenderWindow.registerGraphicsResourceUser(r,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._labelOutlineOpacity,e)),t._labelOutlineOpacity=r)}},e.updatelabelOutlineThicknessTexture=n=>{const r=n.getProperty().getLabelOutlineThicknessByReference(),o=t._openGLRenderWindow.getGraphicsResourceForObject(r),a=`${r.join("-")}`;if(o?.oglObject?.getHandle()&&o?.hash===a)t.labelOutlineThicknessTexture=o.oglObject;else{let n=t.renderable.getLabelOutlineTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const o=1,i=new Uint8Array(n*o);for(let e=0;e<n;++e){const t=void 0!==r[e]?r[e]:r[0];i[e]=t}t.labelOutlineThicknessTexture=Hd.newInstance({resizable:!1}),t.labelOutlineThicknessTexture.setOpenGLRenderWindow(t._openGLRenderWindow),t.labelOutlineThicknessTexture.resetFormatAndType(),t.labelOutlineThicknessTexture.setMinificationFilter(wd.NEAREST),t.labelOutlineThicknessTexture.setMagnificationFilter(wd.NEAREST),t.labelOutlineThicknessTexture.create2DFromRaw({width:n,height:o,numComps:1,dataType:ms.UNSIGNED_CHAR,data:i}),r&&(t._openGLRenderWindow.setGraphicsResourceForObject(r,t.labelOutlineThicknessTexture,a),r!==t._labelOutlineThicknessArray&&(t._openGLRenderWindow.registerGraphicsResourceUser(r,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._labelOutlineThicknessArray,e)),t._labelOutlineThicknessArray=r)}},e.getRenderTargetSize=()=>{if(t._useSmallViewport)return[t._smallViewportWidth,t._smallViewportHeight];const{usize:e,vsize:n}=t._openGLRenderer.getTiledSizeAndOrigin();return[e,n]},e.getRenderTargetOffset=()=>{const{lowerLeftU:e,lowerLeftV:n}=t._openGLRenderer.getTiledSizeAndOrigin();return[e,n]},e.delete=qt((()=>{t._openGLRenderWindow&&n(t._openGLRenderWindow)}),e.delete)}(e,t)}),"vtkOpenGLImageMapper");vn("vtkAbstractImageMapper",rg);const og=0,ag=1,ig=2,{vtkErrorMacro:sg}=sn;const lg={currentRenderPass:null,volumeTexture:null,colorTexture:null,pwfTexture:null,tris:null,lastHaveSeenDepthRequest:!1,haveSeenDepthRequest:!1,lastTextureComponents:0,lastIndependentComponents:0,imagemat:null,imagematinv:null};const cg=sn.newInstance((function(e,t,n={}){Object.assign(t,lg,n),pn.extend(e,t,n),qd.implementReplaceShaderCoincidentOffset(e,t,n),sn.algo(e,t,2,0),t.tris=Sd.newInstance(),t.volumeTexture=null,t.colorTexture=null,t.pwfTexture=null,t.imagemat=x(new Float64Array(16)),t.imagematinv=x(new Float64Array(16)),t.VBOBuildTime={},sn.obj(t.VBOBuildTime,{mtime:0}),function(e,t){function n(n){[t._scalars,t._colorTransferFunc,t._pwFunc].forEach((t=>n.unregisterGraphicsResourceUser(t,e)))}t.classHierarchy.push("vtkOpenGLImageCPRMapper"),e.buildPass=r=>{if(r){t.currentRenderPass=null,t.openGLImageSlice=e.getFirstAncestorOfType("vtkOpenGLImageSlice"),t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer");const r=t._openGLRenderWindow;t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow"),r&&!r.isDeleted()&&r!==t._openGLRenderWindow&&n(r),t.context=t._openGLRenderWindow.getContext(),t.openGLCamera=t._openGLRenderer.getViewNodeFor(t._openGLRenderer.getRenderable().getActiveCamera(),t.openGLCamera),t.tris.setOpenGLRenderWindow(t._openGLRenderWindow)}},e.opaquePass=(n,r)=>{n&&(t.currentRenderPass=r,e.render())},e.opaqueZBufferPass=n=>{n&&(t.haveSeenDepthRequest=!0,t.renderDepth=!0,e.render(),t.renderDepth=!1)},e.getCoincidentParameters=(e,n)=>t.renderable.getResolveCoincidentTopology()===Pl.PolygonOffset?t.renderable.getCoincidentTopologyPolygonOffsetParameters():null,e.render=()=>{const n=t.openGLImageSlice.getRenderable(),r=t._openGLRenderer.getRenderable();e.renderPiece(r,n)},e.renderPiece=(n,r)=>{e.invokeEvent({type:"StartEvent"}),t.renderable.update(),e.invokeEvent({type:"EndEvent"}),t.renderable.preRenderCheck()&&(t.currentImageDataInput=t.renderable.getInputData(0),t.currentCenterlineInput=t.renderable.getOrientedCenterline(),e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r))},e.renderPieceStart=(t,n)=>{e.updateBufferObjects(t,n)},e.renderPieceDraw=(n,r)=>{const o=t.context;t.volumeTexture.activate(),t.colorTexture.activate(),t.pwfTexture.activate(),t.tris.getCABO().getElementCount()&&(e.updateShaders(t.tris,n,r),o.drawArrays(o.TRIANGLES,0,t.tris.getCABO().getElementCount()),t.tris.getVAO().release()),t.volumeTexture.deactivate(),t.colorTexture.deactivate(),t.pwfTexture.deactivate()},e.renderPieceFinish=(e,t)=>{},e.updateBufferObjects=(n,r)=>{e.getNeedToRebuildBufferObjects(n,r)&&e.buildBufferObjects(n,r),r.getProperty().getInterpolationType()===Hf.NEAREST?(t.volumeTexture.setMinificationFilter(wd.NEAREST),t.volumeTexture.setMagnificationFilter(wd.NEAREST),t.colorTexture.setMinificationFilter(wd.NEAREST),t.colorTexture.setMagnificationFilter(wd.NEAREST),t.pwfTexture.setMinificationFilter(wd.NEAREST),t.pwfTexture.setMagnificationFilter(wd.NEAREST)):(t.volumeTexture.setMinificationFilter(wd.LINEAR),t.volumeTexture.setMagnificationFilter(wd.LINEAR),t.colorTexture.setMinificationFilter(wd.LINEAR),t.colorTexture.setMagnificationFilter(wd.LINEAR),t.pwfTexture.setMinificationFilter(wd.LINEAR),t.pwfTexture.setMagnificationFilter(wd.LINEAR))},e.getNeedToRebuildBufferObjects=(n,r)=>{const o=t.VBOBuildTime.getMTime();return o<e.getMTime()||o<t.renderable.getMTime()||o<r.getMTime()||o<t.currentImageDataInput.getMTime()||o<t.currentCenterlineInput.getMTime()||!t.volumeTexture?.getHandle()},e.buildBufferObjects=(n,r)=>{const o=t.currentImageDataInput,a=t.currentCenterlineInput,i=r.getProperty(),s=o?.getPointData()?.getScalars();if(!s)return;const l=t._openGLRenderWindow.getGraphicsResourceForObject(s),c=Wf(0,s),u=!l?.oglObject?.getHandle()||l?.hash!==c,d=i.getUpdatedExtents(),p=!!d.length;if(u){t.volumeTexture=Hd.newInstance(),t.volumeTexture.setOpenGLRenderWindow(t._openGLRenderWindow);const n=o.getDimensions();t.volumeTexture.setOglNorm16Ext(t.context.getExtension("EXT_texture_norm16")),t.volumeTexture.resetFormatAndType(),t.volumeTexture.create3DFilterableFromDataArray({width:n[0],height:n[1],depth:n[2],dataArray:s,preferSizeOverAccuracy:t.renderable.getPreferSizeOverAccuracy()}),t._openGLRenderWindow.setGraphicsResourceForObject(s,t.volumeTexture,c),s!==t._scalars&&(t._openGLRenderWindow.registerGraphicsResourceUser(s,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._scalars,e)),t._scalars=s}else t.volumeTexture=l.oglObject;if(p){i.setUpdatedExtents([]);const e=o.getDimensions();t.volumeTexture.create3DFilterableFromDataArray({width:e[0],height:e[1],depth:e[2],dataArray:s,updatedExtents:d})}const f=s.getNumberOfComponents(),g=r.getProperty(),m=g.getIndependentComponents(),h=m?f:1,v=m?2*h:1,T=[];for(let e=0;e<h;++e)T.push(g.getRGBTransferFunction(e));const x=zf(T,m,h),y=g.getRGBTransferFunction(),b=t._openGLRenderWindow.getGraphicsResourceForObject(y);if(b?.oglObject?.getHandle()&&b?.hash===x)t.colorTexture=b.oglObject;else{let n=t.renderable.getColorTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=new Uint8ClampedArray(n*v*3);if(t.colorTexture=Hd.newInstance(),t.colorTexture.setOpenGLRenderWindow(t._openGLRenderWindow),y){const e=new Float32Array(3*n);for(let t=0;t<h;t++){const o=g.getRGBTransferFunction(t),a=o.getRange();if(o.getTable(a[0],a[1],n,e,1),m)for(let o=0;o<3*n;o++)r[t*n*6+o]=255*e[o],r[t*n*6+o+3*n]=255*e[o];else for(let o=0;o<3*n;o++)r[t*n*6+o]=255*e[o]}t.colorTexture.resetFormatAndType(),t.colorTexture.create2DFromRaw({width:n,height:v,numComps:3,dataType:ms.UNSIGNED_CHAR,data:r})}else{for(let e=0;e<3*n;++e)r[e]=255*e/(3*(n-1)),r[e+1]=255*e/(3*(n-1)),r[e+2]=255*e/(3*(n-1));t.colorTexture.resetFormatAndType(),t.colorTexture.create2DFromRaw({width:n,height:1,numComps:3,dataType:ms.UNSIGNED_CHAR,data:r})}y&&(t._openGLRenderWindow.setGraphicsResourceForObject(y,t.colorTexture,x),y!==t._colorTransferFunc&&(t._openGLRenderWindow.registerGraphicsResourceUser(y,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._colorTransferFunc,e)),t._colorTransferFunc=y)}const A=[];for(let e=0;e<h;++e)A.push(g.getPiecewiseFunction(e));const C=zf(A,m,h),S=g.getPiecewiseFunction(),P=t._openGLRenderWindow.getGraphicsResourceForObject(S);if(P?.oglObject?.getHandle()&&P?.hash===C)t.pwfTexture=P.oglObject;else{let n=t.renderable.getOpacityTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=n*v,o=new Uint8ClampedArray(r);if(t.pwfTexture=Hd.newInstance(),t.pwfTexture.setOpenGLRenderWindow(t._openGLRenderWindow),S){const e=new Float32Array(r),o=new Float32Array(n);for(let t=0;t<h;++t){const r=g.getPiecewiseFunction(t);if(null===r)e.fill(1);else{const a=r.getRange();if(r.getTable(a[0],a[1],n,o,1),m)for(let r=0;r<n;r++)e[t*n*2+r]=o[r],e[t*n*2+r+n]=o[r];else for(let r=0;r<n;r++)e[t*n*2+r]=o[r]}}t.pwfTexture.resetFormatAndType(),t.pwfTexture.create2DFromRaw({width:n,height:v,numComps:1,dataType:ms.FLOAT,data:e})}else o.fill(255),t.pwfTexture.resetFormatAndType(),t.pwfTexture.create2DFromRaw({width:n,height:1,numComps:1,dataType:ms.UNSIGNED_CHAR,data:o});S&&(t._openGLRenderWindow.setGraphicsResourceForObject(S,t.pwfTexture,C),S!==t._pwFunc&&(t._openGLRenderWindow.registerGraphicsResourceUser(S,e),t._openGLRenderWindow.unregisterGraphicsResourceUser(t._pwFunc,e)),t._pwFunc=S)}if(t.VBOBuildTime.getMTime()<t.renderable.getMTime()||t.VBOBuildTime.getMTime()<a.getMTime()){const e=a.getNumberOfPoints(),n=e<=1?0:e-1,r=a.getDistancesToFirstPoint(),o=t.renderable.getHeight(),i=4*n,s=new Float32Array(3*i),l=t.renderable.getWidth();for(let e=0,t=0;e<n;++e)s.set([0,o-r[e],0],t),t+=3,s.set([l,o-r[e],0],t),t+=3,s.set([l,o-r[e+1],0],t),t+=3,s.set([0,o-r[e+1],0],t),t+=3;const c=Is.newInstance({numberOfComponents:3,values:s});c.setName("points");const u=new Uint16Array(5*n);for(let e=0,t=0,r=0;e<n;++e)u.set([4,r+3,r+2,r+1,r],t),t+=5,r+=4;const d=Is.newInstance({numberOfComponents:1,values:u}),p=a.getPoints(),f=new Float32Array(3*i),g=new Array(3),m=new Array(3);for(let e=0,t=0;e<n;++e)p.getPoint(e,g),p.getPoint(e+1,m),f.set(g,t),t+=3,f.set(g,t),t+=3,f.set(m,t),t+=3,f.set(m,t),t+=3;const h=Is.newInstance({numberOfComponents:3,values:f,name:"centerlinePosition"}),v=new Float32Array(i);for(let e=0,t=0;e<n;++e)v.set([0,1,3,2],t),t+=4;const T=[h,Is.newInstance({numberOfComponents:1,values:v,name:"quadIndex"})];if(!t.renderable.getUseUniformOrientation()){const e=t.renderable.getOrientedCenterline().getOrientations()??[],r=new Float32Array(4*i),o=new Float32Array(4*i);for(let t=0;t<n;++t){const n=e[t],a=e[t+1];for(let e=0;e<4;++e){const i=4*(e+4*t);r.set(n,i),o.set(a,i)}}const a=Is.newInstance({numberOfComponents:4,values:r,name:"centerlineTopOrientation"}),s=Is.newInstance({numberOfComponents:4,values:o,name:"centerlineBotOrientation"});T.push(a,s)}t.tris.getCABO().createVBO(d,"polys",rs.SURFACE,{points:c,customAttributes:T}),t.VBOBuildTime.modified()}},e.getNeedToRebuildShaders=(e,n,r)=>{const o=t.volumeTexture.getComponents(),a=r.getProperty().getIndependentComponents(),i=!!t.renderable.getCenterPoint(),s=t.renderable.getUseUniformOrientation(),l=t.renderable.isProjectionEnabled()&&t.renderable.getProjectionMode();return(0===e.getProgram()||t.lastUseCenterPoint!==i||t.lastUseUniformOrientation!==s||t.lastProjectionMode!==l||t.lastHaveSeenDepthRequest!==t.haveSeenDepthRequest||t.lastTextureComponents!==o||t.lastIndependentComponents!==a)&&(t.lastUseCenterPoint=i,t.lastUseUniformOrientation=s,t.lastProjectionMode=l,t.lastHaveSeenDepthRequest=t.haveSeenDepthRequest,t.lastTextureComponents=o,t.lastIndependentComponents=a,!0)},e.buildShaders=(t,n,r)=>{e.getShaderTemplate(t,n,r),e.replaceShaderValues(t,n,r)},e.replaceShaderValues=(n,r,o)=>{let a=n.Vertex,i=n.Fragment;const s=["vec3 applyQuaternionToVec(vec4 q, vec3 v) {","  float uvx = q.y * v.z - q.z * v.y;","  float uvy = q.z * v.x - q.x * v.z;","  float uvz = q.x * v.y - q.y * v.x;","  float uuvx = q.y * uvz - q.z * uvy;","  float uuvy = q.z * uvx - q.x * uvz;","  float uuvz = q.x * uvy - q.y * uvx;","  float w2 = q.w * 2.0;","  uvx *= w2;","  uvy *= w2;","  uvz *= w2;","  uuvx *= 2.0;","  uuvy *= 2.0;","  uuvz *= 2.0;","  return vec3(v.x + uvx + uuvx, v.y + uvy + uuvy, v.z + uvz + uuvz);","}"];a=vd.substitute(a,"//VTK::Camera::Dec",["uniform mat4 MCPCMatrix;"]).result,a=vd.substitute(a,"//VTK::PositionVC::Impl",["  gl_Position = MCPCMatrix * vertexMC;"]).result;const l=["attribute vec3 centerlinePosition;","attribute float quadIndex;","uniform float width;","out vec2 quadOffsetVSOutput;","out vec3 centerlinePosVSOutput;"],c=t.renderable.isProjectionEnabled(),u=t.renderable.getUseUniformOrientation();u?(l.push("out vec3 samplingDirVSOutput;","uniform vec4 centerlineOrientation;","uniform vec3 tangentDirection;",...s),c&&l.push("out vec3 projectionDirVSOutput;","uniform vec3 bitangentDirection;")):l.push("out vec4 centerlineTopOrientationVSOutput;","out vec4 centerlineBotOrientationVSOutput;","attribute vec4 centerlineTopOrientation;","attribute vec4 centerlineBotOrientation;"),a=vd.substitute(a,"//VTK::Color::Dec",l).result;const d=["quadOffsetVSOutput = vec2(width * (mod(quadIndex, 2.0) == 0.0 ? -0.5 : 0.5), quadIndex > 1.0 ? 0.0 : 1.0);","centerlinePosVSOutput = centerlinePosition;"];u?(d.push("samplingDirVSOutput = applyQuaternionToVec(centerlineOrientation, tangentDirection);"),c&&d.push("projectionDirVSOutput = applyQuaternionToVec(centerlineOrientation, bitangentDirection);")):d.push("centerlineTopOrientationVSOutput = centerlineTopOrientation;","centerlineBotOrientationVSOutput = centerlineBotOrientation;"),a=vd.substitute(a,"//VTK::Color::Impl",d).result;const p=t.volumeTexture.getComponents(),f=o.getProperty().getIndependentComponents();let g=["uniform mat4 MCTCMatrix; // Model coordinates to texture coordinates","in vec2 quadOffsetVSOutput;","in vec3 centerlinePosVSOutput;","uniform highp sampler3D volumeTexture;","uniform sampler2D colorTexture1;","uniform sampler2D pwfTexture1;","uniform float opacity;","uniform vec4 backgroundColor;","uniform float cshift0;","uniform float cscale0;","uniform float pwfshift0;","uniform float pwfscale0;"];c&&g.push("uniform vec3 volumeSizeMC;","uniform int projectionSlabNumberOfSamples;","uniform float projectionConstantOffset;","uniform float projectionStepLength;"),u?(g.push("in vec3 samplingDirVSOutput;"),c&&g.push("in vec3 projectionDirVSOutput;")):(g.push("uniform vec3 tangentDirection;","in vec4 centerlineTopOrientationVSOutput;","in vec4 centerlineBotOrientationVSOutput;",...s),c&&g.push("uniform vec3 bitangentDirection;"));const m=t.renderable.getCenterPoint();if(m&&g.push("uniform vec3 globalCenterPoint;"),f){for(let e=1;e<p;e++)g=g.concat([`uniform float cshift${e};`,`uniform float cscale${e};`,`uniform float pwfshift${e};`,`uniform float pwfscale${e};`]);switch(p){case 1:g=g.concat(["uniform float mix0;","#define height0 0.5"]);break;case 2:g=g.concat(["uniform float mix0;","uniform float mix1;","#define height0 0.25","#define height1 0.75"]);break;case 3:g=g.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","#define height0 0.17","#define height1 0.5","#define height2 0.83"]);break;case 4:g=g.concat(["uniform float mix0;","uniform float mix1;","uniform float mix2;","uniform float mix3;","#define height0 0.125","#define height1 0.375","#define height2 0.625","#define height3 0.875"]);break;default:sg("Unsupported number of independent coordinates.")}}i=vd.substitute(i,"//VTK::TCoord::Dec",g).result;let h=[];if(u?(h.push("vec3 samplingDirection = samplingDirVSOutput;"),c&&h.push("vec3 projectionDirection = projectionDirVSOutput;")):(h.push("vec4 q0 = centerlineBotOrientationVSOutput;","vec4 q1 = centerlineTopOrientationVSOutput;","float qCosAngle = dot(q0, q1);","vec4 interpolatedOrientation;","if (qCosAngle > 0.999 || qCosAngle < -0.999) {","  // Use LERP instead of SLERP when the two quaternions are close or opposite","  interpolatedOrientation = normalize(mix(q0, q1, quadOffsetVSOutput.y));","} else {","  float omega = acos(qCosAngle);","  interpolatedOrientation = normalize(sin((1.0 - quadOffsetVSOutput.y) * omega) * q0 + sin(quadOffsetVSOutput.y * omega) * q1);","}","vec3 samplingDirection = applyQuaternionToVec(interpolatedOrientation, tangentDirection);"),c&&h.push("vec3 projectionDirection = applyQuaternionToVec(interpolatedOrientation, bitangentDirection);")),m?h.push("float baseOffset = dot(samplingDirection, globalCenterPoint - centerlinePosVSOutput);","float horizontalOffset = quadOffsetVSOutput.x + baseOffset;"):h.push("float horizontalOffset = quadOffsetVSOutput.x;"),h.push("vec3 volumePosMC = centerlinePosVSOutput + horizontalOffset * samplingDirection;","vec3 volumePosTC = (MCTCMatrix * vec4(volumePosMC, 1.0)).xyz;","if (any(lessThan(volumePosTC, vec3(0.0))) || any(greaterThan(volumePosTC, vec3(1.0))))","{","  // set the background color and exit","  gl_FragData[0] = backgroundColor;","  return;","}"),c){const e=t.renderable.getProjectionMode();switch(e===ag?h.push("const vec4 initialProjectionTextureValue = vec4(1.0);"):h.push("const vec4 initialProjectionTextureValue = vec4(0.0);"),h.push("vec3 projectionScaledDirection = projectionDirection / volumeSizeMC;","vec3 projectionStep = projectionStepLength * projectionScaledDirection;","vec3 projectionStartPosition = volumePosTC + projectionConstantOffset * projectionScaledDirection;","vec4 tvalue = initialProjectionTextureValue;","for (int projectionSampleIdx = 0; projectionSampleIdx < projectionSlabNumberOfSamples; ++projectionSampleIdx) {","  vec3 projectionSamplePosition = projectionStartPosition + float(projectionSampleIdx) * projectionStep;","  vec4 sampledTextureValue = texture(volumeTexture, projectionSamplePosition);"),e){case og:h.push("  tvalue = max(tvalue, sampledTextureValue);");break;case ag:h.push("  tvalue = min(tvalue, sampledTextureValue);");break;default:h.push("  tvalue = tvalue + sampledTextureValue;")}h.push("}"),e===ig&&h.push("tvalue = tvalue / float(projectionSlabNumberOfSamples);")}else h.push("vec4 tvalue = texture(volumeTexture, volumePosTC);");if(f){const e=["r","g","b","a"];for(let t=0;t<p;++t)h=h.concat([`vec3 tcolor${t} = mix${t} * texture2D(colorTexture1, vec2(tvalue.${e[t]} * cscale${t} + cshift${t}, height${t})).rgb;`,`float compWeight${t} = mix${t} * texture2D(pwfTexture1, vec2(tvalue.${e[t]} * pwfscale${t} + pwfshift${t}, height${t})).r;`]);switch(p){case 1:h=h.concat(["gl_FragData[0] = vec4(tcolor0.rgb, compWeight0 * opacity);"]);break;case 2:h=h.concat(["float weightSum = compWeight0 + compWeight1;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum))), opacity);"]);break;case 3:h=h.concat(["float weightSum = compWeight0 + compWeight1 + compWeight2;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum)) + (tcolor2.rgb * (compWeight2 / weightSum))), opacity);"]);break;case 4:h=h.concat(["float weightSum = compWeight0 + compWeight1 + compWeight2 + compWeight3;","gl_FragData[0] = vec4(vec3((tcolor0.rgb * (compWeight0 / weightSum)) + (tcolor1.rgb * (compWeight1 / weightSum)) + (tcolor2.rgb * (compWeight2 / weightSum)) + (tcolor3.rgb * (compWeight3 / weightSum))), opacity);"]);break;default:sg("Unsupported number of independent coordinates.")}}else switch(p){case 1:h=h.concat(["// Dependent components","float intensity = tvalue.r;","vec3 tcolor = texture2D(colorTexture1, vec2(intensity * cscale0 + cshift0, 0.5)).rgb;","float scalarOpacity = texture2D(pwfTexture1, vec2(intensity * pwfscale0 + pwfshift0, 0.5)).r;","gl_FragData[0] = vec4(tcolor, scalarOpacity * opacity);"]);break;case 2:h=h.concat(["float intensity = tvalue.r*cscale0 + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(intensity, 0.5)).rgb, pwfscale0*tvalue.g + pwfshift0);"]);break;case 3:h=h.concat(["vec4 tcolor = cscale0*tvalue + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, opacity);"]);break;default:h=h.concat(["vec4 tcolor = cscale0*tvalue + cshift0;","gl_FragData[0] = vec4(texture2D(colorTexture1, vec2(tcolor.r,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.g,0.5)).r,","  texture2D(colorTexture1, vec2(tcolor.b,0.5)).r, tcolor.a);"])}i=vd.substitute(i,"//VTK::TCoord::Impl",h).result,t.haveSeenDepthRequest&&(i=vd.substitute(i,"//VTK::ZBuffer::Dec","uniform int depthRequest;").result,i=vd.substitute(i,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float iz = floor(gl_FragCoord.z*65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); }"]).result),n.Vertex=a,n.Fragment=i,e.replaceShaderClip(n,r,o),e.replaceShaderCoincidentOffset(n,r,o)},e.replaceShaderClip=(e,n,r)=>{let o=e.Vertex,a=e.Fragment;if(t.renderable.getNumberOfClippingPlanes()){let e=t.renderable.getNumberOfClippingPlanes();e>6&&(sn.vtkErrorMacro("OpenGL has a limit of 6 clipping planes"),e=6),o=vd.substitute(o,"//VTK::Clip::Dec",["uniform int numClipPlanes;","uniform vec4 clipPlanes[6];","varying float clipDistancesVSOutput[6];"]).result,o=vd.substitute(o,"//VTK::Clip::Impl",["for (int planeNum = 0; planeNum < 6; planeNum++)","    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    clipDistancesVSOutput[planeNum] = dot(clipPlanes[planeNum], vertexMC);","    }"]).result,a=vd.substitute(a,"//VTK::Clip::Dec",["uniform int numClipPlanes;","varying float clipDistancesVSOutput[6];"]).result,a=vd.substitute(a,"//VTK::Clip::Impl",["for (int planeNum = 0; planeNum < 6; planeNum++)","    {","    if (planeNum >= numClipPlanes)","        {","        break;","        }","    if (clipDistancesVSOutput[planeNum] < 0.0) discard;","    }"]).result}e.Vertex=o,e.Fragment=a},e.getShaderTemplate=(e,t,n)=>{e.Vertex=jd,e.Fragment=Xd,e.Geometry=""},e.setMapperShaderParameters=(n,r,o)=>{const a=n.getProgram(),i=n.getCABO();i.getElementCount()&&(t.VBOBuildTime.getMTime()>n.getAttributeUpdateTime().getMTime()||n.getShaderSourceTime().getMTime()>n.getAttributeUpdateTime().getMTime())&&(a.isAttributeUsed("vertexMC")&&(n.getVAO().addAttributeArray(a,i,"vertexMC",i.getVertexOffset(),i.getStride(),t.context.FLOAT,3,t.context.FALSE)||sg("Error setting vertexMC in shader VAO.")),n.getCABO().getCustomData().forEach((e=>{e&&a.isAttributeUsed(e.name)&&!n.getVAO().addAttributeArray(a,i,e.name,e.offset,i.getStride(),t.context.FLOAT,e.components,t.context.FALSE)&&sg(`Error setting ${e.name} in shader VAO.`)})),n.getAttributeUpdateTime().modified());const s=t.volumeTexture.getTextureUnit();if(a.setUniformi("volumeTexture",s),a.setUniformf("width",t.renderable.getWidth()),n.getProgram().setUniform4fv("backgroundColor",t.renderable.getBackgroundColor()),a.isUniformUsed("tangentDirection")){const e=t.renderable.getTangentDirection();n.getProgram().setUniform3fArray("tangentDirection",e)}if(a.isUniformUsed("bitangentDirection")){const e=t.renderable.getBitangentDirection();n.getProgram().setUniform3fArray("bitangentDirection",e)}if(a.isUniformUsed("centerlineOrientation")){const e=t.renderable.getUniformOrientation();n.getProgram().setUniform4fv("centerlineOrientation",e)}if(a.isUniformUsed("globalCenterPoint")){const e=t.renderable.getCenterPoint();a.setUniform3fArray("globalCenterPoint",e)}if(t.renderable.isProjectionEnabled()){const e=t.currentImageDataInput,n=e.getSpacing(),r=e.getDimensions(),o=t.renderable.getProjectionSlabThickness(),i=t.renderable.getProjectionSlabNumberOfSamples(),s=ce([],n,r);a.setUniform3fArray("volumeSizeMC",s),a.setUniformi("projectionSlabNumberOfSamples",i);const l=-.5*o;a.setUniformf("projectionConstantOffset",l);const c=o/(i-1);a.setUniformf("projectionStepLength",c)}const l=t.currentImageDataInput,c=l.getWorldToIndex(),u=M(new Float32Array(16),ee([],l.getDimensions())),d=z(u,u,c);if(a.setUniformMatrix("MCTCMatrix",d),t.haveSeenDepthRequest&&n.getProgram().setUniformi("depthRequest",t.renderDepth?1:0),t.renderable.getNumberOfClippingPlanes()){let e=t.renderable.getNumberOfClippingPlanes();e>6&&(sn.vtkErrorMacro("OpenGL has a limit of 6 clipping planes"),e=6);const n=i.getCoordShiftAndScaleEnabled()?i.getInverseShiftAndScaleMatrix():null,r=n?T(t.imagematinv,o.getMatrix()):o.getMatrix();n&&(y(r,r),A(r,r,n),y(r,r)),y(t.imagemat,t.currentImageDataInput.getIndexToWorld()),A(t.imagematinv,r,t.imagemat);const s=[];for(let n=0;n<e;n++){const e=[];t.renderable.getClippingPlaneInDataCoords(t.imagematinv,n,e);for(let t=0;t<4;t++)s.push(e[t])}a.setUniformi("numClipPlanes",e),a.setUniform4fv("clipPlanes",s)}if(a.isUniformUsed("coffset")){const t=e.getCoincidentParameters(r,o);a.setUniformf("coffset",t.offset),a.isUniformUsed("cfactor")&&a.setUniformf("cfactor",t.factor)}},e.setCameraShaderParameters=(e,n,r)=>{const o=t.openGLImageSlice.getKeyMatrices().mcwc,a=t.openGLCamera.getKeyMatrices(n).wcpc;if(A(t.imagemat,a,o),e.getCABO().getCoordShiftAndScaleEnabled()){const n=e.getCABO().getInverseShiftAndScaleMatrix();A(t.imagemat,t.imagemat,n)}e.getProgram().setUniformMatrix("MCPCMatrix",t.imagemat)},e.setPropertyShaderParameters=(e,n,r)=>{const o=e.getProgram(),a=r.getProperty(),i=a.getOpacity();o.setUniformf("opacity",i);const s=t.volumeTexture.getComponents(),l=a.getIndependentComponents();if(l)for(let e=0;e<s;++e)o.setUniformf(`mix${e}`,a.getComponentWeight(e));const c=t.volumeTexture.getVolumeInfo();for(let e=0;e<s;e++){let t=a.getColorWindow(),n=a.getColorLevel();const r=l?e:0,i=a.getRGBTransferFunction(r);if(i&&a.getUseLookupTableScalarRange()){const e=i.getRange();t=e[1]-e[0],n=.5*(e[1]+e[0])}const s=c.scale[e]/t,u=(c.offset[e]-n)/t+.5;o.setUniformf(`cshift${e}`,u),o.setUniformf(`cscale${e}`,s)}const u=t.colorTexture.getTextureUnit();o.setUniformi("colorTexture1",u);for(let e=0;e<s;e++){let t=1,n=0;const r=l?e:0,i=a.getPiecewiseFunction(r);if(i){const r=i.getRange(),o=r[1]-r[0],a=.5*(r[0]+r[1]);t=c.scale[e]/o,n=(c.offset[e]-a)/o+.5}o.setUniformf(`pwfshift${e}`,n),o.setUniformf(`pwfscale${e}`,t)}const d=t.pwfTexture.getTextureUnit();o.setUniformi("pwfTexture1",d)},e.updateShaders=(n,r,o)=>{if(e.getNeedToRebuildShaders(n,r,o)){const a={Vertex:null,Fragment:null,Geometry:null};e.buildShaders(a,r,o);const i=t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(a.Vertex,a.Fragment,a.Geometry);i!==n.getProgram()&&(n.setProgram(i),n.getVAO().releaseGraphicsResources()),n.getShaderSourceTime().modified()}else t._openGLRenderWindow.getShaderCache().readyShaderProgram(n.getProgram());n.getVAO().bind(),e.setMapperShaderParameters(n,r,o),e.setCameraShaderParameters(n,r,o),e.setPropertyShaderParameters(n,r,o)},e.delete=sn.chain((()=>{t._openGLRenderWindow&&n(t._openGLRenderWindow)}),e.delete)}(e,t)}),"vtkOpenGLImageCPRMapper");vn("vtkImageCPRMapper",cg);const ug={context:null,keyMatrixTime:null,keyMatrices:null};vn("vtkImageSlice",Xt((function(e,t,n={}){Object.assign(t,ug,n),pn.extend(e,t,n),t.keyMatrixTime={},Vt(t.keyMatrixTime,{mtime:0}),t.keyMatrices={mcwc:x(new Float64Array(16))},Gt(e,t,["context"]),function(e,t){t.classHierarchy.push("vtkOpenGLImageSlice"),e.buildPass=n=>{if(t.renderable&&t.renderable.getVisibility()&&n){if(!t.renderable)return;t._openGLRenderWindow=e.getLastAncestorOfType("vtkOpenGLRenderWindow"),t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t.context=t._openGLRenderWindow.getContext(),e.prepareNodes(),e.addMissingNode(t.renderable.getMapper()),e.removeUnusedNodes()}},e.traverseZBufferPass=n=>{t.renderable&&t.renderable.getNestedVisibility()&&(!t._openGLRenderer.getSelector()||t.renderable.getNestedPickable())&&(e.apply(n,!0),t.children.forEach((e=>{e.traverse(n)})),e.apply(n,!1))},e.traverseOpaqueZBufferPass=t=>e.traverseOpaquePass(t),e.traverseOpaquePass=n=>{t.renderable&&t.renderable.getNestedVisibility()&&t.renderable.getIsOpaque()&&(!t._openGLRenderer.getSelector()||t.renderable.getNestedPickable())&&(e.apply(n,!0),t.children.forEach((e=>{e.traverse(n)})),e.apply(n,!1))},e.traverseTranslucentPass=n=>{!t.renderable||!t.renderable.getNestedVisibility()||t.renderable.getIsOpaque()||t._openGLRenderer.getSelector()&&!t.renderable.getNestedPickable()||(e.apply(n,!0),t.children.forEach((e=>{e.traverse(n)})),e.apply(n,!1))},e.queryPass=(e,n)=>{if(e){if(!t.renderable||!t.renderable.getVisibility())return;t.renderable.getIsOpaque()?n.incrementOpaqueActorCount():n.incrementTranslucentActorCount()}},e.zBufferPass=(t,n)=>e.opaquePass(t,n),e.opaqueZBufferPass=(t,n)=>e.opaquePass(t,n),e.opaquePass=(e,n)=>{e&&t.context.depthMask(!0)},e.translucentPass=(e,n)=>{t.context.depthMask(!e)},e.getKeyMatrices=()=>(t.renderable.getMTime()>t.keyMatrixTime.getMTime()&&(T(t.keyMatrices.mcwc,t.renderable.getMatrix()),y(t.keyMatrices.mcwc,t.keyMatrices.mcwc),t.keyMatrixTime.modified()),t.keyMatrices)}(e,t)}),"vtkOpenGLImageSlice"));const dg={};vn("vtkVolume",Xt((function(e,t,n={}){Object.assign(t,dg,n),pn.extend(e,t,n),t.keyMatrixTime={},Vt(t.keyMatrixTime,{mtime:0}),t.normalMatrix=new Float64Array(9),t.MCWCMatrix=new Float64Array(16),Gt(e,t,["context"]),function(e,t){t.classHierarchy.push("vtkOpenGLVolume"),e.buildPass=n=>{t.renderable&&t.renderable.getVisibility()&&n&&(t._openGLRenderWindow=e.getLastAncestorOfType("vtkOpenGLRenderWindow"),t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t.context=t._openGLRenderWindow.getContext(),e.prepareNodes(),e.addMissingNode(t.renderable.getMapper()),e.removeUnusedNodes())},e.queryPass=(e,n)=>{if(e){if(!t.renderable||!t.renderable.getVisibility())return;n.incrementVolumeCount()}},e.traverseVolumePass=n=>{t.renderable&&t.renderable.getNestedVisibility()&&(!t._openGLRenderer.getSelector()||t.renderable.getNestedPickable())&&(e.apply(n,!0),t.children[0].traverse(n),e.apply(n,!1))},e.volumePass=e=>{t.renderable&&t.renderable.getVisibility()&&t.context.depthMask(!e)},e.getKeyMatrices=()=>(t.renderable.getMTime()>t.keyMatrixTime.getMTime()&&(t.renderable.computeMatrix(),T(t.MCWCMatrix,t.renderable.getMatrix()),y(t.MCWCMatrix,t.MCWCMatrix),t.renderable.getIsIdentity()?c(t.normalMatrix):(s(t.normalMatrix,t.MCWCMatrix),d(t.normalMatrix,t.normalMatrix),u(t.normalMatrix,t.normalMatrix)),t.keyMatrixTime.modified()),{mcwc:t.MCWCMatrix,normalMatrix:t.normalMatrix})}(e,t)}),"vtkOpenGLVolume"));const pg={NEAREST:0,LINEAR:1,FAST_LINEAR:2},fg={FRACTIONAL:0,PROPORTIONAL:1},gg={DEFAULT:0,ADDITIVE:1,COLORIZE:2,CUSTOM:3};var mg={InterpolationType:pg,OpacityMode:fg,ColorMixPreset:gg,FilterMode:{OFF:0,NORMALIZED:1,RAW:2}};const hg={COMPOSITE_BLEND:0,MAXIMUM_INTENSITY_BLEND:1,MINIMUM_INTENSITY_BLEND:2,AVERAGE_INTENSITY_BLEND:3,ADDITIVE_INTENSITY_BLEND:4,RADON_TRANSFORM_BLEND:5,LABELMAP_EDGE_PROJECTION_BLEND:6};var vg={BlendMode:hg};const{vtkWarningMacro:Tg,vtkErrorMacro:xg}=ln,yg={idxToView:x(new Float64Array(16)),vecISToVCMatrix:c(new Float64Array(9)),modelToView:x(new Float64Array(16)),projectionToView:x(new Float64Array(16)),projectionToWorld:x(new Float64Array(16))};function bg(e,t){function n(e){return e.getUseLabelOutline()||t.renderable.getBlendMode()===hg.LABELMAP_EDGE_PROJECTION_BLEND}t.classHierarchy.push("vtkOpenGLVolumeMapper");const r=new Map;function o(t,n,o){n!==o&&(function(t,n){if(!n)return;const o=(r.get(n)??0)-1;o<=0?(t.unregisterGraphicsResourceUser(n,e),r.delete(n)):r.set(n,o)}(t,n),function(t,n){if(!n)return;const o=r.get(n)??0,a=o+1;r.set(n,a),o<=0&&t.registerGraphicsResourceUser(n,e)}(t,o))}function a(t){[...r.keys()].forEach((n=>t.unregisterGraphicsResourceUser(n,e)))}e.buildPass=()=>{t.zBufferTexture=null},e.zBufferPass=(e,n)=>{if(e){const e=n.getZBufferTexture();e!==t.zBufferTexture&&(t.zBufferTexture=e)}},e.opaqueZBufferPass=(t,n)=>e.zBufferPass(t,n),e.volumePass=(n,r)=>{if(n){const n=t._openGLRenderWindow;t._openGLRenderWindow=e.getLastAncestorOfType("vtkOpenGLRenderWindow"),n&&!n.isDeleted()&&n!==t._openGLRenderWindow&&a(n),t.context=t._openGLRenderWindow.getContext(),t.tris.setOpenGLRenderWindow(t._openGLRenderWindow),t.jitterTexture.setOpenGLRenderWindow(t._openGLRenderWindow),t.framebuffer.setOpenGLRenderWindow(t._openGLRenderWindow),t.openGLVolume=e.getFirstAncestorOfType("vtkOpenGLVolume");const r=t.openGLVolume.getRenderable();t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer");const o=t._openGLRenderer.getRenderable();t.openGLCamera=t._openGLRenderer.getViewNodeFor(o.getActiveCamera(),t.openGLCamera),e.renderPiece(o,r)}},e.getShaderTemplate=(e,t,n)=>{e.Vertex="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkVolumeVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\nattribute vec4 vertexDC;\n\nvarying vec3 vertexVCVSOutput;\nuniform mat4 PCVCMatrix;\n\nuniform float dcxmin;\nuniform float dcxmax;\nuniform float dcymin;\nuniform float dcymax;\n\nvoid main()\n{\n  // dcsmall is the device coords reduced to the\n  // x y area covered by the volume\n  vec4 dcsmall = vec4(\n    dcxmin + 0.5 * (vertexDC.x + 1.0) * (dcxmax - dcxmin),\n    dcymin + 0.5 * (vertexDC.y + 1.0) * (dcymax - dcymin),\n    vertexDC.z,\n    vertexDC.w);\n  vec4 vcpos = PCVCMatrix * dcsmall;\n  vertexVCVSOutput = vcpos.xyz/vcpos.w;\n  gl_Position = dcsmall;\n}\n",e.Fragment="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkVolumeFS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n// Template for the volume mappers fragment shader\n\nconst float infinity = 3.402823466e38;\n\n// the output of this shader\n//VTK::Output::Dec\n\nin vec3 vertexVCVSOutput;\n\n// From Sources\\Rendering\\Core\\VolumeProperty\\Constants.js\n#define COMPOSITE_BLEND 0\n#define MAXIMUM_INTENSITY_BLEND 1\n#define MINIMUM_INTENSITY_BLEND 2\n#define AVERAGE_INTENSITY_BLEND 3\n#define ADDITIVE_INTENSITY_BLEND 4\n#define RADON_TRANSFORM_BLEND 5\n#define LABELMAP_EDGE_PROJECTION_BLEND 6\n\n#define vtkNumberOfLights //VTK::NumberOfLights\n#define vtkMaxLaoKernelSize //VTK::MaxLaoKernelSize\n#define vtkNumberOfComponents //VTK::NumberOfComponents\n#define vtkBlendMode //VTK::BlendMode\n#define vtkMaximumNumberOfSamples //VTK::MaximumNumberOfSamples\n\n//VTK::EnabledColorFunctions\n\n//VTK::EnabledLightings\n\n//VTK::EnabledMultiTexturePerVolume\n\n//VTK::EnabledGradientOpacity\n\n//VTK::EnabledIndependentComponents\n\n//VTK::vtkProportionalComponents\n\n//VTK::vtkForceNearestComponents\n\nuniform int twoSidedLighting;\n\n#if vtkMaxLaoKernelSize > 0\n  vec2 kernelSample[vtkMaxLaoKernelSize];\n#endif\n\n// Textures\n#ifdef EnabledMultiTexturePerVolume\n  #define vtkNumberOfVolumeTextures vtkNumberOfComponents\n#else\n  #define vtkNumberOfVolumeTextures 1\n#endif\nuniform highp sampler3D volumeTexture[vtkNumberOfVolumeTextures];\nuniform sampler2D colorTexture;\nuniform sampler2D opacityTexture;\nuniform sampler2D jtexture;\nuniform sampler2D labelOutlineThicknessTexture;\n\nstruct Volume {\n  // ---- Volume geometry settings ----\n\n  vec3 originVC;          // in VC\n  vec3 spacing;           // in VC per IC\n  vec3 inverseSpacing;    // 1/spacing\n  ivec3 dimensions;       // in IC\n  vec3 inverseDimensions; // 1/vec3(dimensions)\n  mat3 vecISToVCMatrix;   // convert from IS to VC without translation\n  mat3 vecVCToISMatrix;   // convert from VC to IS without translation\n  mat4 PCWCMatrix;\n  mat4 worldToIndex;\n  float diagonalLength; // in VC, this is: length(size)\n\n  // ---- Texture settings ----\n\n  // Texture shift and scale\n  vec4 colorTextureScale;\n  vec4 colorTextureShift;\n  vec4 opacityTextureScale;\n  vec4 opacityTextureShift;\n\n  // The heights defined below are the locations for the up to four components\n  // of the transfer functions. The transfer functions have a height of (2 *\n  // numberOfComponents) pixels so the values are computed to hit the middle of\n  // the two rows for that component\n  vec4 transferFunctionsSampleHeight;\n\n  // ---- Mode specific settings ----\n\n  // Independent component default preset settings per component\n  vec4 independentComponentMix;\n\n  // Additive / average blending mode settings\n  vec4 ipScalarRangeMin;\n  vec4 ipScalarRangeMax;\n\n  // ---- Rendering settings ----\n\n  // Lighting\n  float ambient;\n  float diffuse;\n  float specular;\n  float specularPower;\n  int computeNormalFromOpacity;\n\n  // Gradient opacity\n  vec4 gradientOpacityScale;\n  vec4 gradientOpacityShift;\n  vec4 gradientOpacityMin;\n  vec4 gradientOpacityMax;\n\n  // Volume shadow\n  float volumetricScatteringBlending;\n  float globalIlluminationReach;\n  float anisotropy;\n  float anisotropySquared;\n\n  // LAO\n  int kernelSize;\n  int kernelRadius;\n\n  // Label outline\n  float outlineOpacity;\n};\nuniform Volume volume;\n\nstruct Light {\n  vec3 color;\n  vec3 positionVC;\n  vec3 directionVC; // normalized\n  vec3 halfAngleVC;\n  vec3 attenuation;\n  float exponent;\n  float coneAngle;\n  int isPositional;\n};\n#if vtkNumberOfLights > 0\n  uniform Light lights[vtkNumberOfLights];\n#endif\n\nuniform float vpWidth;\nuniform float vpHeight;\nuniform float vpOffsetX;\nuniform float vpOffsetY;\n\n// Bitmasks for label outline\nconst int MAX_SEGMENT_INDEX = 256; // Define as per expected maximum\n#define MAX_SEGMENTS 256\n#define UINT_SIZE 32\n// We add UINT_SIZE - 1, as we want the ceil of the division instead of the\n// floor\n#define BITMASK_SIZE ((MAX_SEGMENTS + UINT_SIZE - 1) / UINT_SIZE)\nuint labelOutlineBitmasks[BITMASK_SIZE];\n\n// Set the corresponding bit in the bitmask\nvoid setLabelOutlineBit(int segmentIndex) {\n  int arrayIndex = segmentIndex / UINT_SIZE;\n  int bitIndex = segmentIndex % UINT_SIZE;\n  labelOutlineBitmasks[arrayIndex] |= 1u << bitIndex;\n}\n\n// Check if a bit is set in the bitmask\nbool isLabelOutlineBitSet(int segmentIndex) {\n  int arrayIndex = segmentIndex / UINT_SIZE;\n  int bitIndex = segmentIndex % UINT_SIZE;\n  return ((labelOutlineBitmasks[arrayIndex] & (1u << bitIndex)) != 0u);\n}\n\n// if you want to see the raw tiled\n// data in webgl1 uncomment the following line\n// #define debugtile\n\n// camera values\nuniform float camThick;\nuniform float camNear;\nuniform float camFar;\nuniform int cameraParallel;\n\n//VTK::ClipPlane::Dec\n\n// A random number between 0 and 1 that only depends on the fragment\n// It uses the jtexture, so this random seed repeats by blocks of 32 fragments\n// in screen space\nfloat fragmentSeed;\n\n// sample texture is global\nuniform float sampleDistance;\nuniform float volumeShadowSampleDistance;\n\n// declaration for intermixed geometry\n//VTK::ZBuffer::Dec\n\n//=======================================================================\n// global and custom variables (a temporary section before photorealistics\n// rendering module is complete)\nvec3 rayDirVC;\n\n#define INV4PI 0.0796\n#define EPSILON 0.001\n#define PI 3.1415\n#define PI2 9.8696\n\nvec4 rawSampleTexture(vec3 pos) {\n  #ifdef EnabledMultiTexturePerVolume\n    vec4 rawSample;\n    rawSample[0] = texture(volumeTexture[0], pos)[0];\n  #if vtkNumberOfComponents > 1\n    rawSample[1] = texture(volumeTexture[1], pos)[0];\n  #endif\n  #if vtkNumberOfComponents > 2\n    rawSample[2] = texture(volumeTexture[2], pos)[0];\n  #endif\n  #if vtkNumberOfComponents > 3\n    rawSample[3] = texture(volumeTexture[3], pos)[0];\n  #endif\n    return rawSample;\n  #else\n    return texture(volumeTexture[0], pos);\n  #endif\n}\n\nvec4 rawFetchTexture(ivec3 pos) {\n  #ifdef EnabledMultiTexturePerVolume\n    vec4 rawSample;\n    #if vtkNumberOfComponents > 0\n      rawSample[0] = texelFetch(volumeTexture[0], pos, 0)[0];\n    #endif\n    #if vtkNumberOfComponents > 1\n      rawSample[1] = texelFetch(volumeTexture[1], pos, 0)[0];\n    #endif\n    #if vtkNumberOfComponents > 2\n      rawSample[2] = texelFetch(volumeTexture[2], pos, 0)[0];\n    #endif\n    #if vtkNumberOfComponents > 3\n      rawSample[3] = texelFetch(volumeTexture[3], pos, 0)[0];\n    #endif\n    return rawSample;\n  #else\n    return texelFetch(volumeTexture[0], pos, 0);\n  #endif\n}\n\nvec4 getTextureValue(vec3 pos) {\n  vec4 tmp = rawSampleTexture(pos);\n\n  // Force nearest\n  #if defined(vtkComponent0ForceNearest) || \\\n      defined(vtkComponent1ForceNearest) || \\\n      defined(vtkComponent2ForceNearest) || \\\n      defined(vtkComponent3ForceNearest)\n    vec3 nearestPos = (floor(pos * vec3(volume.dimensions)) + 0.5) *\n                      volume.inverseDimensions;\n    vec4 nearestValue = rawSampleTexture(nearestPos);\n    #ifdef vtkComponent0ForceNearest\n      tmp[0] = nearestValue[0];\n    #endif\n    #ifdef vtkComponent1ForceNearest\n      tmp[1] = nearestValue[1];\n    #endif\n    #ifdef vtkComponent2ForceNearest\n      tmp[2] = nearestValue[2];\n    #endif\n    #ifdef vtkComponent3ForceNearest\n      tmp[3] = nearestValue[3];\n    #endif\n  #endif\n\n  // Set alpha when using dependent components\n  #ifndef EnabledIndependentComponents\n    #if vtkNumberOfComponents == 1\n      tmp.a = tmp.r;\n    #endif\n    #if vtkNumberOfComponents == 2\n      tmp.a = tmp.g;\n    #endif\n    #if vtkNumberOfComponents == 3\n      tmp.a = length(tmp.rgb);\n    #endif\n  #endif\n\n  return tmp;\n}\n\n// `height` is usually `volume.transferFunctionsSampleHeight[component]`\n// when using independent component and `0.5` otherwise. Don't move the if\n// statement in these function, as the callers usually already knows if it is\n// using independent component or not\nfloat getOpacityFromTexture(float scalar, int component, float height) {\n  float scaledScalar = scalar * volume.opacityTextureScale[component] +\n                       volume.opacityTextureShift[component];\n  return texture2D(opacityTexture, vec2(scaledScalar, height)).r;\n}\nvec3 getColorFromTexture(float scalar, int component, float height) {\n  float scaledScalar = scalar * volume.colorTextureScale[component] +\n                       volume.colorTextureShift[component];\n  return texture2D(colorTexture, vec2(scaledScalar, height)).rgb;\n}\n\n//=======================================================================\n// transformation between VC and IS space\n\n// convert vector position from idx to vc\nvec3 posIStoVC(vec3 posIS) {\n  return volume.vecISToVCMatrix * posIS + volume.originVC;\n}\n\n// convert vector position from vc to idx\nvec3 posVCtoIS(vec3 posVC) {\n  return volume.vecVCToISMatrix * (posVC - volume.originVC);\n}\n\n// Rotate vector to view coordinate\nvec3 vecISToVC(vec3 dirIS) {\n  return volume.vecISToVCMatrix * dirIS;\n}\n\n// Rotate vector to idx coordinate\nvec3 vecVCToIS(vec3 dirVC) {\n  return volume.vecVCToISMatrix * dirVC;\n}\n\n//=======================================================================\n// Given a normal compute the gradient opacity factors\nfloat computeGradientOpacityFactor(float normalMag, int component) {\n  float goscale = volume.gradientOpacityScale[component];\n  float goshift = volume.gradientOpacityShift[component];\n  float gomin = volume.gradientOpacityMin[component];\n  float gomax = volume.gradientOpacityMax[component];\n  return clamp(normalMag * goscale + goshift, gomin, gomax);\n}\n\n#ifdef vtkClippingPlanesOn\n  bool isPointClipped(vec3 posVC) {\n    for (int i = 0; i < clip_numPlanes; ++i) {\n      if (dot(vec3(vClipPlaneOrigins[i] - posVC), vClipPlaneNormals[i]) > 0.0) {\n        return true;\n      }\n    }\n    return false;\n  }\n#endif\n\n//=======================================================================\n// compute the normal and gradient magnitude for a position, uses forward\n// difference\n\n// The output normal is in VC\nvec4 computeDensityNormal(vec3 opacityUCoords[2], float opacityTextureHeight,\n                          float gradientOpacity, int component) {\n  // Pass the scalars through the opacity functions\n  vec4 opacityG;\n  opacityG.x += getOpacityFromTexture(opacityUCoords[0].x, component,\n                                      opacityTextureHeight);\n  opacityG.y += getOpacityFromTexture(opacityUCoords[0].y, component,\n                                      opacityTextureHeight);\n  opacityG.z += getOpacityFromTexture(opacityUCoords[0].z, component,\n                                      opacityTextureHeight);\n  opacityG.x -= getOpacityFromTexture(opacityUCoords[1].x, component,\n                                      opacityTextureHeight);\n  opacityG.y -= getOpacityFromTexture(opacityUCoords[1].y, component,\n                                      opacityTextureHeight);\n  opacityG.z -= getOpacityFromTexture(opacityUCoords[1].z, component,\n                                      opacityTextureHeight);\n\n  // Divide by spacing and convert to VC\n  opacityG.xyz *= gradientOpacity * volume.inverseSpacing;\n  opacityG.w = length(opacityG.xyz);\n  if (opacityG.w == 0.0) {\n    return vec4(0.0);\n  }\n\n  // Normalize\n  opacityG.xyz = normalize(vecISToVC(opacityG.xyz));\n\n  return opacityG;\n}\n\n// The output normal is in VC\nvec4 computeNormalForDensity(vec3 posIS, out vec3 scalarInterp[2],\n                             const int opacityComponent) {\n  vec3 offsetedPosIS;\n  for (int axis = 0; axis < 3; ++axis) {\n    // Positive direction\n    offsetedPosIS = posIS;\n    offsetedPosIS[axis] += volume.inverseDimensions[axis];\n    scalarInterp[0][axis] =\n        getTextureValue(offsetedPosIS)[opacityComponent];\n    #ifdef vtkClippingPlanesOn\n      if (isPointClipped(posIStoVC(offsetedPosIS))) {\n        scalarInterp[0][axis] = 0.0;\n      }\n    #endif\n\n    // Negative direction\n    offsetedPosIS = posIS;\n    offsetedPosIS[axis] -= volume.inverseDimensions[axis];\n    scalarInterp[1][axis] =\n        getTextureValue(offsetedPosIS)[opacityComponent];\n    #ifdef vtkClippingPlanesOn\n      if (isPointClipped(posIStoVC(offsetedPosIS))) {\n        scalarInterp[1][axis] = 0.0;\n      }\n    #endif\n  }\n\n  vec4 result;\n  result.xyz = (scalarInterp[0] - scalarInterp[1]) * volume.inverseSpacing;\n  result.w = length(result.xyz);\n  if (result.w == 0.0) {\n    return vec4(0.0);\n  }\n  result.xyz = normalize(vecISToVC(result.xyz));\n  return result;\n}\n\nvec4 fragCoordToPCPos(vec4 fragCoord) {\n  return vec4((fragCoord.x / vpWidth - vpOffsetX - 0.5) * 2.0,\n              (fragCoord.y / vpHeight - vpOffsetY - 0.5) * 2.0,\n              (fragCoord.z - 0.5) * 2.0, 1.0);\n}\n\nvec4 pcPosToWorldCoord(vec4 pcPos) {\n  return volume.PCWCMatrix * pcPos;\n}\n\nvec3 fragCoordToIndexSpace(vec4 fragCoord) {\n  vec4 pcPos = fragCoordToPCPos(fragCoord);\n  vec4 worldCoord = pcPosToWorldCoord(pcPos);\n  vec4 vertex = (worldCoord / worldCoord.w);\n\n  vec3 index = (volume.worldToIndex * vertex).xyz;\n\n  // half voxel fix for labelmapOutline\n  return (index + vec3(0.5)) * volume.inverseDimensions;\n}\n\nvec3 fragCoordToWorld(vec4 fragCoord) {\n  vec4 pcPos = fragCoordToPCPos(fragCoord);\n  vec4 worldCoord = pcPosToWorldCoord(pcPos);\n  return worldCoord.xyz;\n}\n\n//=======================================================================\n// Compute the normals and gradient magnitudes for a position for independent\n// components The output normals are in VC\nmat4 computeMat4Normal(vec3 posIS, vec4 tValue) {\n  vec3 xvec = vec3(volume.inverseDimensions.x, 0.0, 0.0);\n  vec3 yvec = vec3(0.0, volume.inverseDimensions.y, 0.0);\n  vec3 zvec = vec3(0.0, 0.0, volume.inverseDimensions.z);\n\n  vec4 distX = getTextureValue(posIS + xvec) - getTextureValue(posIS - xvec);\n  vec4 distY = getTextureValue(posIS + yvec) - getTextureValue(posIS - yvec);\n  vec4 distZ = getTextureValue(posIS + zvec) - getTextureValue(posIS - zvec);\n\n  // divide by spacing\n  distX *= 0.5 * volume.inverseSpacing.x;\n  distY *= 0.5 * volume.inverseSpacing.y;\n  distZ *= 0.5 * volume.inverseSpacing.z;\n\n  mat4 result;\n\n  // optionally compute the 1st component\n  #if vtkNumberOfComponents > 0 && !defined(vtkComponent0Proportional)\n    {\n      const int component = 0;\n      vec3 normal = vec3(distX[component], distY[component], distZ[component]);\n      float normalLength = length(normal);\n      if (normalLength > 0.0) {\n        normal = normalize(vecISToVC(normal));\n      }\n      result[component] = vec4(normal, normalLength);\n    }\n  #endif\n\n  // optionally compute the 2nd component\n  #if vtkNumberOfComponents > 1 && !defined(vtkComponent1Proportional)\n    {\n      const int component = 1;\n      vec3 normal = vec3(distX[component], distY[component], distZ[component]);\n      float normalLength = length(normal);\n      if (normalLength > 0.0) {\n        normal = normalize(vecISToVC(normal));\n      }\n      result[component] = vec4(normal, normalLength);\n    }\n  #endif\n\n  // optionally compute the 3rd component\n  #if vtkNumberOfComponents > 2 && !defined(vtkComponent2Proportional)\n    {\n      const int component = 2;\n      vec3 normal = vec3(distX[component], distY[component], distZ[component]);\n      float normalLength = length(normal);\n      if (normalLength > 0.0) {\n        normal = normalize(vecISToVC(normal));\n      }\n      result[component] = vec4(normal, normalLength);\n    }\n  #endif\n\n  // optionally compute the 4th component\n  #if vtkNumberOfComponents > 3 && !defined(vtkComponent3Proportional)\n    {\n      const int component = 3;\n      vec3 normal = vec3(distX[component], distY[component], distZ[component]);\n      float normalLength = length(normal);\n      if (normalLength > 0.0) {\n        normal = normalize(vecISToVC(normal));\n      }\n      result[component] = vec4(normal, normalLength);\n    }\n  #endif\n\n  return result;\n}\n\n//=======================================================================\n// global shadow - secondary ray\n\n// henyey greenstein phase function\nfloat phaseFunction(float cos_angle) {\n  // divide by 2.0 instead of 4pi to increase intensity\n  float anisotropy = volume.anisotropy;\n  if (abs(anisotropy) <= EPSILON) {\n    // isotropic scatter returns 0.5 instead of 1/4pi to increase intensity\n    return 0.5;\n  }\n  float anisotropy2 = volume.anisotropySquared;\n  return ((1.0 - anisotropy2) /\n          pow(1.0 + anisotropy2 - 2.0 * anisotropy * cos_angle, 1.5)) /\n         2.0;\n}\n\n// Compute the two intersection distances of the ray with the volume in VC\n// The entry point is `rayOriginVC + distanceMin * rayDirVC` and the exit point\n// is `rayOriginVC + distanceMax * rayDirVC` If distanceMin < distanceMax, the\n// volume is not intersected The ray origin is inside the box when distanceMin <\n// 0.0 < distanceMax\nvec2 rayIntersectVolumeDistances(vec3 rayOriginVC, vec3 rayDirVC) {\n  // Compute origin and direction in IS\n  vec3 rayOriginIS = posVCtoIS(rayOriginVC);\n  vec3 rayDirIS = vecVCToIS(rayDirVC);\n  // Don't check for infinity as the min/max combination afterward will always\n  // find an intersection before infinity\n  vec3 invDir = 1.0 / rayDirIS;\n\n  // We have: bound = origin + t * dir\n  // So: t = (1/dir) * (bound - origin)\n  vec3 distancesTo0 = invDir * (vec3(0.0) - rayOriginIS);\n  vec3 distancesTo1 = invDir * (vec3(1.0) - rayOriginIS);\n  // Min and max distances to plane intersection per plane\n  vec3 dMinPerAxis = min(distancesTo0, distancesTo1);\n  vec3 dMaxPerAxis = max(distancesTo0, distancesTo1);\n  // Overall first and last intersection\n  float distanceMin = max(dMinPerAxis.x, max(dMinPerAxis.y, dMinPerAxis.z));\n  float distanceMax = min(dMaxPerAxis.x, min(dMaxPerAxis.y, dMaxPerAxis.z));\n  return vec2(distanceMin, distanceMax);\n}\n\n//=======================================================================\n// local ambient occlusion\n#if vtkMaxLaoKernelSize > 0\n\n  // Return a random point on the unit sphere\n  vec3 sampleDirectionUniform(int rayIndex) {\n    // Each ray of each fragment should be different, two sources of randomness\n    // are used. Only depends on ray index\n    vec2 rayRandomness = kernelSample[rayIndex];\n    // Only depends on fragment\n    float fragmentRandomness = fragmentSeed;\n    // Merge both source of randomness in a single uniform random variable using\n    // the formula (x+y < 1 ? x+y : x+y-1). The simpler formula (x+y)/2 doesn't\n    // result in a uniform distribution\n    vec2 mergedRandom = rayRandomness + vec2(fragmentRandomness);\n    mergedRandom -= vec2(greaterThanEqual(mergedRandom, vec2(1.0)));\n\n    // Insipred by:\n    // https://karthikkaranth.me/blog/generating-random-points-in-a-sphere/#better-choice-of-spherical-coordinates\n    float u = mergedRandom[0];\n    float v = mergedRandom[1];\n    float theta = u * 2.0 * PI;\n    float phi = acos(2.0 * v - 1.0);\n    float sinTheta = sin(theta);\n    float cosTheta = cos(theta);\n    float sinPhi = sin(phi);\n    float cosPhi = cos(phi);\n    return vec3(sinPhi * cosTheta, sinPhi * sinTheta, cosPhi);\n  }\n\n  float computeLAO(vec3 posVC, vec4 normalVC, float originalOpacity) {\n    // apply LAO only at selected locations, otherwise return full brightness\n    if (normalVC.w <= 0.0 || originalOpacity <= 0.05) {\n      return 1.0;\n    }\n\n    #ifdef EnabledGradientOpacity\n      float gradientOpacityFactor = computeGradientOpacityFactor(normalVC.w, 0);\n    #endif\n\n    float visibilitySum = 0.0;\n    float weightSum = 0.0;\n    for (int i = 0; i < volume.kernelSize; i++) {\n      // Only sample on an hemisphere around the normalVC.xyz axis, so\n      // normalDotRay should be negative\n      vec3 rayDirectionVC = sampleDirectionUniform(i);\n      float normalDotRay = dot(normalVC.xyz, rayDirectionVC);\n      if (normalDotRay > 0.0) {\n        // Flip rayDirectionVC when it is in the wrong hemisphere\n        rayDirectionVC = -rayDirectionVC;\n        normalDotRay = -normalDotRay;\n      }\n\n      vec3 currPosIS = posVCtoIS(posVC);\n      float visibility = 1.0;\n      vec3 randomDirStepIS = vecVCToIS(rayDirectionVC * sampleDistance);\n      for (int j = 0; j < volume.kernelRadius; j++) {\n        currPosIS += randomDirStepIS;\n        // If out of the volume, we are done\n        if (any(lessThan(currPosIS, vec3(0.0))) ||\n            any(greaterThan(currPosIS, vec3(1.0)))) {\n          break;\n        }\n        float opacity = getOpacityFromTexture(getTextureValue(currPosIS).r, 0, 0.5);\n        #ifdef EnabledGradientOpacity\n          opacity *= gradientOpacityFactor;\n        #endif\n        visibility *= 1.0 - opacity;\n        // If visibility is less than EPSILON, consider it to be 0\n        if (visibility < EPSILON) {\n          visibility = 0.0;\n          break;\n        }\n      }\n      float rayWeight = -normalDotRay;\n      visibilitySum += visibility * rayWeight;\n      weightSum += rayWeight;\n    }\n\n    // If no sample, LAO factor is one\n    if (weightSum == 0.0) {\n      return 1.0;\n    }\n\n    // LAO factor is the average visibility:\n    // - visibility low => ambient low\n    // - visibility high => ambient high\n    float lao = visibilitySum / weightSum;\n\n    // Reduce variance by clamping\n    return clamp(lao, 0.3, 1.0);\n  }\n#endif\n\n//=======================================================================\n// Volume shadows\n#if vtkNumberOfLights > 0\n\n  // Non-memoised version\n  float computeVolumeShadowWithoutCache(vec3 posVC, vec3 lightDirNormVC) {\n    // modify sample distance with a random number between 1.5 and 3.0\n    float rayStepLength =\n        volumeShadowSampleDistance * mix(1.5, 3.0, fragmentSeed);\n\n    // in case the first sample near surface has a very tiled light ray, we need\n    // to offset start position\n    vec3 initialPosVC = posVC + rayStepLength * lightDirNormVC;\n\n    #ifdef vtkClippingPlanesOn\n      float clippingPlanesMaxDistance = infinity;\n      for (int i = 0; i < clip_numPlanes; ++i) {\n        // Find distance of intersection with the plane\n        // Points are clipped when:\n        // dot(planeOrigin - (rayOrigin + distance * rayDirection), planeNormal) > 0\n        // This is equivalent to:\n        // dot(planeOrigin - rayOrigin, planeNormal) - distance * dot(rayDirection,\n        // planeNormal) > 0.0\n        // We precompute the dot products, so we clip ray points when:\n        // dotOrigin - distance * dotDirection > 0.0\n        float dotOrigin =\n            dot(vClipPlaneOrigins[i] - initialPosVC, vClipPlaneNormals[i]);\n        if (dotOrigin > 0.0) {\n          // The initialPosVC is clipped by this plane\n          return 1.0;\n        }\n        float dotDirection = dot(lightDirNormVC, vClipPlaneNormals[i]);\n        if (dotDirection < 0.0) {\n          // We only hit the plane if dotDirection is negative, as (distance is\n          // positive)\n          float intersectionDistance =\n              dotOrigin / dotDirection; // negative divided by negative => positive\n          clippingPlanesMaxDistance =\n              min(clippingPlanesMaxDistance, intersectionDistance);\n        }\n      }\n    #endif\n\n    vec2 intersectionDistances =\n        rayIntersectVolumeDistances(initialPosVC, lightDirNormVC);\n\n    if (intersectionDistances[1] <= intersectionDistances[0] ||\n        intersectionDistances[1] <= 0.0) {\n      // Volume not hit or behind the ray\n      return 1.0;\n    }\n\n    // When globalIlluminationReach is 0, no sample at all\n    // When globalIlluminationReach is 1, the ray will go through the whole\n    // volume\n    float maxTravelDistance = mix(0.0, volume.diagonalLength,\n                                  volume.globalIlluminationReach);\n    float startDistance = max(intersectionDistances[0], 0.0);\n    float endDistance = min(intersectionDistances[1], startDistance + maxTravelDistance);\n    #ifdef vtkClippingPlanesOn\n      endDistance = min(endDistance, clippingPlanesMaxDistance);\n    #endif\n    if (endDistance - startDistance < 0.0) {\n      return 1.0;\n    }\n\n    // These two variables are used to compute posIS, without having to call\n    // VCtoIS at each step\n    vec3 initialPosIS = posVCtoIS(initialPosVC);\n    // The light dir is scaled and rotated, but not translated, as it is a\n    // vector (w = 0)\n    vec3 scaledLightDirIS = vecVCToIS(lightDirNormVC);\n\n    float shadow = 1.0;\n    for (float currentDistance = startDistance; currentDistance <= endDistance;\n          currentDistance += rayStepLength) {\n      vec3 posIS = initialPosIS + currentDistance * scaledLightDirIS;\n      vec4 scalar = getTextureValue(posIS);\n      float opacity = getOpacityFromTexture(scalar.r, 0, 0.5);\n      #if defined(EnabledGradientOpacity) && !defined(EnabledIndependentComponents)\n        vec3 scalarInterp[2];\n        vec4 normal = computeNormalForDensity(posIS, scalarInterp, 3);\n        float opacityFactor = computeGradientOpacityFactor(normal.w, 0);\n        opacity *= opacityFactor;\n      #endif\n      shadow *= 1.0 - opacity;\n\n      // Early termination if shadow coeff is near 0.0\n      if (shadow < EPSILON) {\n        return 0.0;\n      }\n    }\n    return shadow;\n  }\n\n  // Some cache for volume shadows\n  struct {\n    vec3 posVC;\n    float shadow;\n  } cachedShadows[vtkNumberOfLights];\n\n  // Memoised version\n  float computeVolumeShadow(vec3 posVC, vec3 lightDirNormVC, int lightIdx) {\n    if (posVC == cachedShadows[lightIdx].posVC) {\n      return cachedShadows[lightIdx].shadow;\n    }\n    float shadow = computeVolumeShadowWithoutCache(posVC, lightDirNormVC);\n    cachedShadows[lightIdx].posVC = posVC;\n    cachedShadows[lightIdx].shadow = shadow;\n    return shadow;\n  }\n\n#endif\n\n//=======================================================================\n// surface light contribution\n#if vtkNumberOfLights > 0\n  vec3 applyLighting(vec3 tColor, vec4 normalVC) {\n    vec3 diffuse = vec3(0.0, 0.0, 0.0);\n    vec3 specular = vec3(0.0, 0.0, 0.0);\n    for (int lightIdx = 0; lightIdx < vtkNumberOfLights; lightIdx++) {\n      float df = dot(normalVC.xyz, lights[lightIdx].directionVC);\n      if (df > 0.0) {\n        diffuse += df * lights[lightIdx].color;\n        float sf = dot(normalVC.xyz, -lights[lightIdx].halfAngleVC);\n        if (sf > 0.0) {\n          specular += pow(sf, volume.specularPower) * lights[lightIdx].color;\n        }\n      }\n    }\n    return tColor * (diffuse * volume.diffuse + volume.ambient) +\n          specular * volume.specular;\n  }\n\n  vec3 applySurfaceShadowLighting(vec3 tColor, float alpha, vec3 posVC,\n                                  vec4 normalVC) {\n    // everything in VC\n    vec3 diffuse = vec3(0.0);\n    vec3 specular = vec3(0.0);\n    for (int ligthIdx = 0; ligthIdx < vtkNumberOfLights; ligthIdx++) {\n      vec3 vertLightDirection;\n      float attenuation;\n      if (lights[ligthIdx].isPositional == 1) {\n        vertLightDirection = posVC - lights[ligthIdx].positionVC;\n        float lightDistance = length(vertLightDirection);\n        // Normalize with precomputed length\n        vertLightDirection = vertLightDirection / lightDistance;\n        // Base attenuation\n        vec3 attenuationPolynom = lights[ligthIdx].attenuation;\n        attenuation =\n            1.0 / (attenuationPolynom[0] +\n                  lightDistance * (attenuationPolynom[1] +\n                                    lightDistance * attenuationPolynom[2]));\n        // Cone attenuation\n        float coneDot = dot(vertLightDirection, lights[ligthIdx].directionVC);\n        // Per OpenGL standard cone angle is 90 or less for a spot light\n        if (lights[ligthIdx].coneAngle <= 90.0) {\n          if (coneDot >= cos(radians(lights[ligthIdx].coneAngle))) {\n            // Inside the cone\n            attenuation *= pow(coneDot, lights[ligthIdx].exponent);\n          } else {\n            // Outside the cone\n            attenuation = 0.0;\n          }\n        }\n      } else {\n        vertLightDirection = lights[ligthIdx].directionVC;\n        attenuation = 1.0;\n      }\n\n      float ndotL = dot(normalVC.xyz, vertLightDirection);\n      if (ndotL < 0.0 && twoSidedLighting == 1) {\n        ndotL = -ndotL;\n      }\n      if (ndotL > 0.0) {\n        // Diffuse\n        diffuse += ndotL * attenuation * lights[ligthIdx].color;\n        // Specular\n        float vdotR =\n            dot(-rayDirVC, normalize(vertLightDirection - 2.0 * ndotL * normalVC.xyz));\n        if (vdotR > 0.0) {\n          specular += pow(vdotR, volume.specularPower) * attenuation *\n                      lights[ligthIdx].color;\n        }\n      }\n    }\n    #if vtkMaxLaoKernelSize > 0\n      float laoFactor = computeLAO(posVC, normalVC, alpha);\n    #else\n      const float laoFactor = 1.0;\n    #endif\n    return tColor * (diffuse * volume.diffuse +\n                    volume.ambient * laoFactor) +\n          specular * volume.specular;\n  }\n\n  vec3 applyVolumeShadowLighting(vec3 tColor, vec3 posVC) {\n    // Here we have no effect of cones and no attenuation\n    vec3 diffuse = vec3(0.0);\n    for (int lightIdx = 0; lightIdx < vtkNumberOfLights; lightIdx++) {\n      vec3 lightDirVC = lights[lightIdx].isPositional == 1\n                            ? normalize(lights[lightIdx].positionVC - posVC)\n                            : -lights[lightIdx].directionVC;\n      float shadowCoeff = computeVolumeShadow(posVC, lightDirVC, lightIdx);\n      float phaseAttenuation = phaseFunction(dot(rayDirVC, lightDirVC));\n      diffuse += phaseAttenuation * shadowCoeff * lights[lightIdx].color;\n    }\n    return tColor * (diffuse * volume.diffuse + volume.ambient);\n  }\n#endif\n\n// LAO of surface shadows and volume shadows only work with dependent components\nvec3 applyAllLightning(vec3 tColor, float alpha, vec3 posVC,\n                       vec4 surfaceNormalVC) {\n  #if vtkNumberOfLights > 0\n    // 0 <= volCoeff < EPSILON => only surface shadows\n    // EPSILON <= volCoeff < 1 - EPSILON => mix of surface and volume shadows\n    // 1 - EPSILON <= volCoeff => only volume shadows\n    float volCoeff = volume.volumetricScatteringBlending *\n                    (1.0 - alpha / 2.0) *\n                    (1.0 - atan(surfaceNormalVC.w) * INV4PI);\n\n    // Compute surface lighting if needed\n    vec3 surfaceShadedColor = tColor;\n    #ifdef EnableSurfaceLighting\n      if (volCoeff < 1.0 - EPSILON) {\n        surfaceShadedColor =\n            applySurfaceShadowLighting(tColor, alpha, posVC, surfaceNormalVC);\n      }\n    #endif\n\n    // Compute volume lighting if needed\n    vec3 volumeShadedColor = tColor;\n    #ifdef EnableVolumeLighting\n      if (volCoeff >= EPSILON) {\n        volumeShadedColor = applyVolumeShadowLighting(tColor, posVC);\n      }\n    #endif\n\n    // Return the right mix\n    if (volCoeff < EPSILON) {\n      // Surface shadows\n      return surfaceShadedColor;\n    }\n    if (volCoeff >= 1.0 - EPSILON) {\n      // Volume shadows\n      return volumeShadedColor;\n    }\n    // Mix of surface and volume shadows\n    return mix(surfaceShadedColor, volumeShadedColor, volCoeff);\n  #endif\n  return tColor;\n}\n\nvec4 getColorForLabelOutline() {\n  vec3 centerPosIS =\n      fragCoordToIndexSpace(gl_FragCoord); // pos in texture space\n  vec4 centerValue = getTextureValue(centerPosIS);\n  bool pixelOnBorder = false;\n  vec4 tColor = vec4(getColorFromTexture(centerValue.r, 0, 0.5),\n                     getOpacityFromTexture(centerValue.r, 0, 0.5));\n\n  int segmentIndex = int(centerValue.r * 255.0);\n\n  // Use texture sampling for outlineThickness\n  float textureCoordinate = float(segmentIndex - 1) / 1024.0;\n  float textureValue =\n      texture2D(labelOutlineThicknessTexture, vec2(textureCoordinate, 0.5)).r;\n  int actualThickness = int(textureValue * 255.0);\n\n  // If it is the background (segment index 0), we should quickly bail out.\n  // Previously, this was determined by tColor.a, which was incorrect as it\n  // prevented the outline from appearing when the fill is 0.\n  if (segmentIndex == 0) {\n    return vec4(0, 0, 0, 0);\n  }\n\n  // Only perform outline check on fragments rendering voxels that aren't\n  // invisible. Saves a bunch of needless checks on the background.\n  // TODO define epsilon when building shader?\n  for (int i = -actualThickness; i <= actualThickness; i++) {\n    for (int j = -actualThickness; j <= actualThickness; j++) {\n      if (i == 0 && j == 0) {\n        continue;\n      }\n\n      vec4 neighborPixelCoord =\n          vec4(gl_FragCoord.x + float(i), gl_FragCoord.y + float(j),\n               gl_FragCoord.z, gl_FragCoord.w);\n\n      vec3 neighborPosIS = fragCoordToIndexSpace(neighborPixelCoord);\n      vec4 value = getTextureValue(neighborPosIS);\n\n      // If any of my neighbours are not the same value as I\n      // am, this means I am on the border of the segment.\n      // We can break the loops\n      if (any(notEqual(value, centerValue))) {\n        pixelOnBorder = true;\n        break;\n      }\n    }\n\n    if (pixelOnBorder == true) {\n      break;\n    }\n  }\n\n  // If I am on the border, I am displayed at full opacity\n  if (pixelOnBorder == true) {\n    tColor.a = volume.outlineOpacity;\n  }\n\n  return tColor;\n}\n\nvec4 getColorForAdditivePreset(vec4 tValue, vec3 posVC, vec3 posIS) {\n  // compute normals\n  mat4 normalMat = computeMat4Normal(posIS, tValue);\n  vec4 normalLights[2];\n  normalLights[0] = normalMat[0];\n  normalLights[1] = normalMat[1];\n  #if vtkNumberOfLights > 0\n    if (volume.computeNormalFromOpacity == 1) {\n      for (int component = 0; component < 2; ++component) {\n        vec3 scalarInterp[2];\n        float height = volume.transferFunctionsSampleHeight[component];\n        computeNormalForDensity(posIS, scalarInterp, component);\n        normalLights[component] =\n            computeDensityNormal(scalarInterp, height, 1.0, component);\n      }\n    }\n  #endif\n\n  // compute opacities\n  float opacities[2];\n  opacities[0] = getOpacityFromTexture(\n      tValue[0], 0, volume.transferFunctionsSampleHeight[0]);\n  opacities[1] = getOpacityFromTexture(\n      tValue[1], 1, volume.transferFunctionsSampleHeight[1]);\n  #ifdef EnabledGradientOpacity\n    for (int component = 0; component < 2; ++component) {\n      opacities[component] *=\n          computeGradientOpacityFactor(normalMat[component].a, component);\n    }\n  #endif\n  float opacitySum = opacities[0] + opacities[1];\n  if (opacitySum <= 0.0) {\n    return vec4(0.0);\n  }\n\n  // mix the colors and opacities\n  vec3 colors[2];\n  for (int component = 0; component < 2; ++component) {\n    float sampleHeight = volume.transferFunctionsSampleHeight[component];\n    vec3 color = getColorFromTexture(tValue[component], component, sampleHeight);\n    color = applyAllLightning(color, opacities[component], posVC,\n                              normalLights[component]);\n    colors[component] = color;\n  }\n  vec3 mixedColor =\n      (opacities[0] * colors[0] + opacities[1] * colors[1]) / opacitySum;\n  return vec4(mixedColor, min(1.0, opacitySum));\n}\n\nvec4 getColorForColorizePreset(vec4 tValue, vec3 posVC, vec3 posIS) {\n  // compute normals\n  mat4 normalMat = computeMat4Normal(posIS, tValue);\n  vec4 normalLight = normalMat[0];\n  #if vtkNumberOfLights > 0\n    if (volume.computeNormalFromOpacity == 1) {\n      vec3 scalarInterp[2];\n      float height = volume.transferFunctionsSampleHeight[0];\n      computeNormalForDensity(posIS, scalarInterp, 0);\n      normalLight = computeDensityNormal(scalarInterp, height, 1.0, 0);\n    }\n  #endif\n\n  // compute opacities\n  float opacity = getOpacityFromTexture(\n      tValue[0], 0, volume.transferFunctionsSampleHeight[0]);\n  #ifdef EnabledGradientOpacity\n    opacity *= computeGradientOpacityFactor(normalMat[0].a, 0);\n  #endif\n\n  // colorizing component\n  vec3 colorizingColor = getColorFromTexture(\n      tValue[0], 1, volume.transferFunctionsSampleHeight[1]);\n  float colorizingOpacity = getOpacityFromTexture(\n      tValue[1], 1, volume.transferFunctionsSampleHeight[1]);\n\n  // mix the colors and opacities\n  vec3 color =\n      getColorFromTexture(tValue[0], 0,\n                          volume.transferFunctionsSampleHeight[0]) *\n      mix(vec3(1.0), colorizingColor, colorizingOpacity);\n  color = applyAllLightning(color, opacity, posVC, normalLight);\n  return vec4(color, opacity);\n}\n\nvec4 getColorForDefaultIndependentPreset(vec4 tValue, vec3 posIS) {\n\n  // compute the normal vectors as needed\n  #if defined(EnabledGradientOpacity) || vtkNumberOfLights > 0\n    mat4 normalMat = computeMat4Normal(posIS, tValue);\n  #endif\n\n  // process color and opacity for each component\n  // initial value of alpha is determined by wether the first component is\n  // proportional or not\n  #if defined(vtkComponent0Proportional)\n    // when it is proportional, it starts at 1 (neutral for multiplications)\n    float alpha = 1.0;\n  #else\n    // when it is not proportional, it starts at 0 (neutral for additions)\n    float alpha = 0.0;\n  #endif\n\n  vec3 mixedColor = vec3(0.0);\n  #if vtkNumberOfComponents > 0\n    {\n      const int component = 0;\n      vec3 color = getColorFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      float opacity = getOpacityFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      #if !defined(vtkComponent0Proportional)\n        float alphaContribution = volume.independentComponentMix[component] * opacity;\n        #ifdef EnabledGradientOpacity\n          alphaContribution *= computeGradientOpacityFactor(normalMat[component].a, component);\n        #endif\n        alpha += alphaContribution;\n        #if vtkNumberOfLights > 0\n          color = applyLighting(color, normalMat[component]);\n        #endif\n      #else\n        color *= opacity;\n        alpha *= mix(opacity, 1.0,\n                    (1.0 - volume.independentComponentMix[component]));\n      #endif\n      mixedColor += volume.independentComponentMix[component] * color;\n    }\n  #endif\n  #if vtkNumberOfComponents > 1\n    {\n      const int component = 1;\n      vec3 color = getColorFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      float opacity = getOpacityFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      #if !defined(vtkComponent1Proportional)\n        float alphaContribution = volume.independentComponentMix[component] * opacity;\n        #ifdef EnabledGradientOpacity\n          alphaContribution *= computeGradientOpacityFactor(normalMat[component].a, component);\n        #endif\n        alpha += alphaContribution;\n        #if vtkNumberOfLights > 0\n          color = applyLighting(color, normalMat[component]);\n        #endif\n      #else\n        color *= opacity;\n        alpha *= mix(opacity, 1.0,\n                    (1.0 - volume.independentComponentMix[component]));\n      #endif\n      mixedColor += volume.independentComponentMix[component] * color;\n    }\n  #endif\n  #if vtkNumberOfComponents > 2\n    {\n      const int component = 2;\n      vec3 color = getColorFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      float opacity = getOpacityFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      #if !defined(vtkComponent2Proportional)\n        float alphaContribution = volume.independentComponentMix[component] * opacity;\n        #ifdef EnabledGradientOpacity\n          alphaContribution *= computeGradientOpacityFactor(normalMat[component].a, component);\n        #endif\n        alpha += alphaContribution;\n        #if vtkNumberOfLights > 0\n          color = applyLighting(color, normalMat[component]);\n        #endif\n      #else\n        color *= opacity;\n        alpha *= mix(opacity, 1.0,\n                    (1.0 - volume.independentComponentMix[component]));\n      #endif\n      mixedColor += volume.independentComponentMix[component] * color;\n    }\n  #endif\n  #if vtkNumberOfComponents > 3\n    {\n      const int component = 3;\n      vec3 color = getColorFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      float opacity = getOpacityFromTexture(\n          tValue[component], component,\n          volume.transferFunctionsSampleHeight[component]);\n      #if !defined(vtkComponent3Proportional)\n        float alphaContribution = volume.independentComponentMix[component] * opacity;\n        #ifdef EnabledGradientOpacity\n          alphaContribution *= computeGradientOpacityFactor(normalMat[component].a, component);\n        #endif\n        alpha += alphaContribution;\n        #if vtkNumberOfLights > 0\n          color = applyLighting(color, normalMat[component]);\n        #endif\n      #else\n        color *= opacity;\n        alpha *= mix(opacity, 1.0,\n                    (1.0 - volume.independentComponentMix[component]));\n      #endif\n      mixedColor += volume.independentComponentMix[component] * color;\n    }\n  #endif\n\n  return vec4(mixedColor, alpha);\n}\n\nvec4 getColorForDependentComponents(vec4 tValue, vec3 posVC, vec3 posIS) {\n  #if defined(EnabledGradientOpacity) || vtkNumberOfLights > 0\n    // use component 3 of the opacity texture as getTextureValue() sets alpha to\n    // the opacity value\n    vec3 scalarInterp[2];\n    vec4 normal0 = computeNormalForDensity(posIS, scalarInterp, 3);\n    float gradientOpacity = computeGradientOpacityFactor(normal0.a, 0);\n  #endif\n\n  // get color and opacity\n  #if vtkNumberOfComponents == 1\n    vec3 tColor = getColorFromTexture(tValue.r, 0, 0.5);\n    float alpha = getOpacityFromTexture(tValue.r, 0, 0.5);\n  #endif\n  #if vtkNumberOfComponents == 2\n    vec3 tColor = vec3(tValue.r * volume.colorTextureScale[0] +\n                  volume.colorTextureShift[0]);\n    float alpha = getOpacityFromTexture(tValue.a, 1, 0.5);\n  #endif\n  #if vtkNumberOfComponents == 3\n      vec3 tColor = tValue.rgb * volume.colorTextureScale.rgb +\n              volume.colorTextureShift.rgb;\n      float alpha = getOpacityFromTexture(tValue.a, 0, 0.5);\n  #endif\n  #if vtkNumberOfComponents == 4\n      vec3 tColor = tValue.rgb * volume.colorTextureScale.rgb +\n              volume.colorTextureShift.rgb;\n      float alpha = getOpacityFromTexture(tValue.a, 3, 0.5);\n  #endif\n\n  // Apply gradient opacity\n  #if defined(EnabledGradientOpacity)\n    alpha *= gradientOpacity;\n  #endif\n\n  #if vtkNumberOfComponents == 1\n    if (alpha < EPSILON) {\n      return vec4(0.0);\n    }\n  #endif\n\n  // lighting\n  #if vtkNumberOfLights > 0\n    vec4 normalLight;\n    if (volume.computeNormalFromOpacity == 1) {\n      if (normal0[3] != 0.0) {\n        normalLight =\n            computeDensityNormal(scalarInterp, 0.5, gradientOpacity, 0);\n        if (normalLight[3] == 0.0) {\n          normalLight = normal0;\n        }\n      }\n    } else {\n      normalLight = normal0;\n    }\n    tColor = applyAllLightning(tColor, alpha, posVC, normalLight);\n  #endif\n\n  return vec4(tColor, alpha);\n}\n\nvec4 getColorForValue(vec4 tValue, vec3 posVC, vec3 posIS) {\n  #ifdef EnableColorForValueFunctionId0\n    return getColorForDependentComponents(tValue, posVC, posIS);\n  #endif\n\n  #ifdef EnableColorForValueFunctionId1\n    return getColorForAdditivePreset(tValue, posVC, posIS);\n  #endif\n\n  #ifdef EnableColorForValueFunctionId2\n    return getColorForColorizePreset(tValue, posVC, posIS);\n  #endif\n\n  #ifdef EnableColorForValueFunctionId3\n    /*\n      * Mix the color information from all the independent components to get a\n      * single rgba output. See other shader functions like\n      * `getColorForAdditivePreset` to learn how to create a custom color mix.\n      * The custom color mix should return a value, but if it doesn't, it will\n      * fallback on the default shading\n      */\n    //VTK::CustomColorMix\n  #endif\n\n  #if defined(EnableColorForValueFunctionId4) || defined(EnableColorForValueFunctionId3)\n    return getColorForDefaultIndependentPreset(tValue, posIS);\n  #endif\n\n  #ifdef EnableColorForValueFunctionId5\n    return getColorForLabelOutline();\n  #endif\n}\n\nbool valueWithinScalarRange(vec4 val) {\n  #if vtkNumberOfComponents > 1 && !defined(EnabledIndependentComponents)\n    return false;\n  #endif\n  vec4 rangeMin = volume.ipScalarRangeMin;\n  vec4 rangeMax = volume.ipScalarRangeMax;\n  for (int component = 0; component < vtkNumberOfComponents; ++component) {\n    if (val[component] < rangeMin[component] ||\n        rangeMax[component] < val[component]) {\n      return false;\n    }\n  }\n  return true;\n}\n\n#if vtkBlendMode == LABELMAP_EDGE_PROJECTION_BLEND\n  bool checkOnEdgeForNeighbor(int xFragmentOffset, int yFragmentOffset,\n                              int segmentIndex, vec3 stepIS) {\n    vec3 volumeDimensions = vec3(volume.dimensions);\n    vec4 neighborPixelCoord = vec4(gl_FragCoord.x + float(xFragmentOffset),\n                                  gl_FragCoord.y + float(yFragmentOffset),\n                                  gl_FragCoord.z, gl_FragCoord.w);\n    vec3 originalNeighborPosIS = fragCoordToIndexSpace(neighborPixelCoord);\n\n    vec3 neighborPosIS = originalNeighborPosIS;\n    for (int k = 0; k < vtkMaximumNumberOfSamples / 2; ++k) {\n      ivec3 texCoord = ivec3(neighborPosIS * volumeDimensions);\n      vec4 texValue = rawFetchTexture(texCoord);\n      if (int(texValue.g) == segmentIndex) {\n        // not on edge\n        return false;\n      }\n      neighborPosIS += stepIS;\n    }\n\n    neighborPosIS = originalNeighborPosIS;\n    for (int k = 0; k < vtkMaximumNumberOfSamples / 2; ++k) {\n      ivec3 texCoord = ivec3(neighborPosIS * volumeDimensions);\n      vec4 texValue = rawFetchTexture(texCoord);\n      if (int(texValue.g) == segmentIndex) {\n        // not on edge\n        return false;\n      }\n      neighborPosIS -= stepIS;\n    }\n\n    // onedge\n    float sampleHeight = volume.transferFunctionsSampleHeight[1];\n    vec3 tColorSegment =\n        getColorFromTexture(float(segmentIndex), 1, sampleHeight);\n    float pwfValueSegment =\n        getOpacityFromTexture(float(segmentIndex), 1, sampleHeight);\n    gl_FragData[0] = vec4(tColorSegment, pwfValueSegment);\n    return true;\n  }\n#endif\n\nvec4 getColorAtPos(vec3 posVC) {\n  vec3 posIS = posVCtoIS(posVC);\n  vec4 texValue = getTextureValue(posIS);\n  return getColorForValue(texValue, posVC, posIS);\n}\n\n//=======================================================================\n// Apply the specified blend mode operation along the ray's path.\n//\nvoid applyBlend(vec3 rayOriginVC, vec3 rayDirVC, float minDistance,\n                float maxDistance) {\n  // start slightly inside and apply some jitter\n  vec3 stepVC = rayDirVC * sampleDistance;\n  float raySteps = (maxDistance - minDistance) / sampleDistance;\n\n  // Avoid 0.0 jitter\n  float jitter = 0.01 + 0.99 * fragmentSeed;\n\n  #if vtkBlendMode == COMPOSITE_BLEND\n    // now map through opacity and color\n    vec3 firstPosVC = rayOriginVC + minDistance * rayDirVC;\n    vec4 firstColor = getColorAtPos(firstPosVC);\n\n    // handle very thin volumes\n    if (raySteps <= 1.0) {\n      firstColor.a = 1.0 - pow(1.0 - firstColor.a, raySteps);\n      gl_FragData[0] = firstColor;\n      return;\n    }\n\n    // first color only counts for `jitter` factor of the step\n    firstColor.a = 1.0 - pow(1.0 - firstColor.a, jitter);\n    vec4 color = vec4(firstColor.rgb * firstColor.a, firstColor.a);\n    vec3 posVC = firstPosVC + jitter * stepVC;\n    float stepsTraveled = jitter;\n\n    for (int i = 0; i < vtkMaximumNumberOfSamples; ++i) {\n      // If we have reached the last step, break\n      if (stepsTraveled + 1.0 >= raySteps) {\n        break;\n      }\n      vec4 tColor = getColorAtPos(posVC);\n\n      color = color + vec4(tColor.rgb * tColor.a, tColor.a) * (1.0 - color.a);\n      stepsTraveled++;\n      posVC += stepVC;\n      if (color.a > 0.99) {\n        color.a = 1.0;\n        break;\n      }\n    }\n\n    if (color.a < 0.99 && (raySteps - stepsTraveled) > 0.0) {\n      vec3 endPosVC = rayOriginVC + maxDistance * rayDirVC;\n      vec4 tColor = getColorAtPos(endPosVC);\n      tColor.a = 1.0 - pow(1.0 - tColor.a, raySteps - stepsTraveled);\n\n      float mix = (1.0 - color.a);\n      color = color + vec4(tColor.rgb * tColor.a, tColor.a) * mix;\n    }\n\n    gl_FragData[0] = vec4(color.rgb / color.a, color.a);\n  #endif\n\n  #if vtkBlendMode == MAXIMUM_INTENSITY_BLEND ||                                 \\\n      vtkBlendMode == MINIMUM_INTENSITY_BLEND\n    // Find maximum/minimum intensity along the ray.\n\n    // Define the operation we will use (min or max)\n    #if vtkBlendMode == MAXIMUM_INTENSITY_BLEND\n      #define OP max\n    #else\n      #define OP min\n    #endif\n\n    vec3 posVC = rayOriginVC + minDistance * rayDirVC;\n    float stepsTraveled = 0.0;\n\n    // Find a value to initialize the selected variables\n    vec4 selectedValue;\n    vec3 selectedPosVC;\n    vec3 selectedPosIS;\n    {\n      vec3 posIS = posVCtoIS(posVC);\n      selectedValue = getTextureValue(posIS);\n      selectedPosVC = posVC;\n      selectedPosIS = posIS;\n    }\n\n    // If the clipping range is shorter than the sample distance\n    // we can skip the sampling loop along the ray.\n    if (raySteps <= 1.0) {\n      gl_FragData[0] = getColorForValue(selectedValue, selectedPosVC, selectedPosIS);\n      return;\n    }\n\n    posVC += jitter * stepVC;\n    stepsTraveled += jitter;\n\n    // Sample along the ray until vtkMaximumNumberOfSamples,\n    // ending slightly inside the total distance\n    for (int i = 0; i < vtkMaximumNumberOfSamples; ++i) {\n      // If we have reached the last step, break\n      if (stepsTraveled + 1.0 >= raySteps) {\n        break;\n      }\n\n      // Get selected values\n      vec3 posIS = posVCtoIS(posVC);\n      vec4 previousSelectedValue = selectedValue;\n      vec4 currentValue = getTextureValue(posIS);\n      selectedValue = OP(selectedValue, currentValue);\n      if (previousSelectedValue != selectedValue) {\n        selectedPosVC = posVC;\n        selectedPosIS = posIS;\n      }\n\n      // Otherwise, continue along the ray\n      stepsTraveled++;\n      posVC += stepVC;\n    }\n\n    // Perform the last step along the ray using the\n    // residual distance\n    posVC = rayOriginVC + maxDistance * rayDirVC;\n    {\n      vec3 posIS = posVCtoIS(posVC);\n      vec4 previousSelectedValue = selectedValue;\n      vec4 currentValue = getTextureValue(posIS);\n      selectedValue = OP(selectedValue, currentValue);\n      if (previousSelectedValue != selectedValue) {\n        selectedPosVC = posVC;\n        selectedPosIS = posIS;\n      }\n    }\n\n    gl_FragData[0] = getColorForValue(selectedValue, selectedPosVC, selectedPosIS);\n  #endif\n\n  #if vtkBlendMode == ADDITIVE_INTENSITY_BLEND ||                                \\\n      vtkBlendMode == AVERAGE_INTENSITY_BLEND\n    vec4 sum = vec4(0.);\n    #if vtkBlendMode == AVERAGE_INTENSITY_BLEND\n      float totalWeight = 0.0;\n    #endif\n    vec3 posVC = rayOriginVC + minDistance * rayDirVC;\n    float stepsTraveled = 0.0;\n\n    vec3 posIS = posVCtoIS(posVC);\n    vec4 value = getTextureValue(posIS);\n\n    if (raySteps <= 1.0) {\n      gl_FragData[0] = getColorForValue(value * raySteps, posVC, posIS);\n      return;\n    }\n\n    if (valueWithinScalarRange(value)) {\n      sum += value * jitter;\n      #if vtkBlendMode == AVERAGE_INTENSITY_BLEND\n        totalWeight += jitter;\n      #endif\n    }\n    posVC += jitter * stepVC;\n    stepsTraveled += jitter;\n\n    // Sample along the ray until vtkMaximumNumberOfSamples,\n    // ending slightly inside the total distance\n    for (int i = 0; i < vtkMaximumNumberOfSamples; ++i) {\n      // If we have reached the last step, break\n      if (stepsTraveled + 1.0 >= raySteps) {\n        break;\n      }\n\n      posIS = posVCtoIS(posVC);\n      value = getTextureValue(posIS);\n      // One can control the scalar range by setting the AverageIPScalarRange to\n      // disregard scalar values, not in the range of interest, from the average\n      // computation. Notes:\n      // - We are comparing all values in the texture to see if any of them\n      //   are outside of the scalar range. In the future we might want to allow\n      //   scalar ranges for each component.\n      if (valueWithinScalarRange(value)) {\n        sum += value;\n        #if vtkBlendMode == AVERAGE_INTENSITY_BLEND\n          totalWeight++;\n        #endif\n      }\n\n      stepsTraveled++;\n      posVC += stepVC;\n    }\n\n    // Perform the last step along the ray using the\n    // residual distance\n    posVC = rayOriginVC + maxDistance * rayDirVC;\n    posIS = posVCtoIS(posVC);\n    value = getTextureValue(posIS);\n    if (valueWithinScalarRange(value)) {\n      sum += value;\n      #if vtkBlendMode == AVERAGE_INTENSITY_BLEND\n        totalWeight += raySteps - stepsTraveled;\n      #endif\n    }\n\n    #if vtkBlendMode == AVERAGE_INTENSITY_BLEND\n      sum /= vec4(totalWeight, totalWeight, totalWeight, 1.0);\n    #endif\n\n    gl_FragData[0] = getColorForValue(sum, posVC, posIS);\n  #endif\n\n  #if vtkBlendMode == RADON_TRANSFORM_BLEND\n    float normalizedRayIntensity = 1.0;\n    vec3 posVC = rayOriginVC + minDistance * rayDirVC;\n    float stepsTraveled = 0.0;\n\n    // handle very thin volumes\n    if (raySteps <= 1.0) {\n      vec3 posIS = posVCtoIS(posVC);\n      vec4 tValue = getTextureValue(posIS);\n      normalizedRayIntensity -= raySteps * sampleDistance *\n                                getOpacityFromTexture(tValue.r, 0, 0.5);\n      gl_FragData[0] =\n          vec4(getColorFromTexture(normalizedRayIntensity, 0, 0.5), 1.0);\n      return;\n    }\n\n    posVC += jitter * stepVC;\n    stepsTraveled += jitter;\n\n    for (int i = 0; i < vtkMaximumNumberOfSamples; ++i) {\n      if (stepsTraveled + 1.0 >= raySteps) {\n        break;\n      }\n\n      vec3 posIS = posVCtoIS(posVC);\n      vec4 value = getTextureValue(posIS);\n      // Convert scalar value to normalizedRayIntensity coefficient and\n      // accumulate normalizedRayIntensity\n      normalizedRayIntensity -=\n          sampleDistance * getOpacityFromTexture(value.r, 0, 0.5);\n\n      posVC += stepVC;\n      stepsTraveled++;\n    }\n\n    // map normalizedRayIntensity to color\n    gl_FragData[0] =\n        vec4(getColorFromTexture(normalizedRayIntensity, 0, 0.5), 1.0);\n  #endif\n\n  #if vtkBlendMode == LABELMAP_EDGE_PROJECTION_BLEND\n    // Only works with a single volume\n    vec3 posVC = rayOriginVC + minDistance * rayDirVC;\n    float stepsTraveled = 0.0;\n    vec3 posIS = posVCtoIS(posVC);\n    vec4 tValue = getTextureValue(posIS);\n    if (raySteps <= 1.0) {\n      gl_FragData[0] = getColorForValue(tValue, posVC, posIS);\n      return;\n    }\n\n    vec3 stepIS = vecVCToIS(stepVC);\n    vec4 value = tValue;\n    posIS += jitter * stepIS;\n    stepsTraveled += jitter;\n    vec3 maxPosIS = posIS; // Store the position of the max value\n    int segmentIndex = int(value.g);\n    bool originalPosHasSeenNonZero = false;\n\n    if (segmentIndex != 0) {\n      // Tried using the segment index in an boolean array but reading\n      // from the array by dynamic indexing was horrondously slow\n      // so use bit masking instead and assign 1 to the bit corresponding to the\n      // segment index and later check if the bit is set via bit operations\n      setLabelOutlineBit(segmentIndex);\n    }\n\n    // Sample along the ray until vtkMaximumNumberOfSamples,\n    // ending slightly inside the total distance\n    for (int i = 0; i < vtkMaximumNumberOfSamples; ++i) {\n      // If we have reached the last step, break\n      if (stepsTraveled + 1.0 >= raySteps) {\n        break;\n      }\n\n      // compute the scalar\n      tValue = getTextureValue(posIS);\n      segmentIndex = int(tValue.g);\n\n      if (segmentIndex != 0) {\n        originalPosHasSeenNonZero = true;\n        setLabelOutlineBit(segmentIndex);\n      }\n\n      if (tValue.r > value.r) {\n        value = tValue;   // Update the max value\n        maxPosIS = posIS; // Update the position where max occurred\n      }\n\n      // Otherwise, continue along the ray\n      stepsTraveled++;\n      posIS += stepIS;\n    }\n\n    // Perform the last step along the ray using the\n    // residual distance\n    posIS = posVCtoIS(rayOriginVC + maxDistance * rayDirVC);\n    tValue = getTextureValue(posIS);\n\n    if (tValue.r > value.r) {\n      value = tValue;   // Update the max value\n      maxPosIS = posIS; // Update the position where max occurred\n    }\n\n    // If we have not seen any non-zero segments, we can return early\n    // and grab color from the actual center value first component (image)\n    if (!originalPosHasSeenNonZero) {\n      vec3 maxPosVC = posIStoVC(maxPosIS);\n      gl_FragData[0] = getColorForValue(value, maxPosVC, maxPosIS);\n      return;\n    }\n\n    vec3 neighborRayStepsIS = stepIS;\n    float neighborRaySteps = raySteps;\n    bool shouldLookInAllNeighbors = false;\n\n    vec3 volumeSpacings = volume.spacing;\n    float minVoxelSpacing =\n        min(volumeSpacings[0], min(volumeSpacings[1], volumeSpacings[2]));\n    vec4 base =\n        vec4(gl_FragCoord.x, gl_FragCoord.y, gl_FragCoord.z, gl_FragCoord.w);\n\n    vec4 baseXPlus = vec4(gl_FragCoord.x + 1.0, gl_FragCoord.y, gl_FragCoord.z,\n                          gl_FragCoord.w);\n    vec4 baseYPlus = vec4(gl_FragCoord.x, gl_FragCoord.y + 1.0, gl_FragCoord.z,\n                          gl_FragCoord.w);\n\n    vec3 baseWorld = fragCoordToWorld(base);\n    vec3 baseXPlusWorld = fragCoordToWorld(baseXPlus);\n    vec3 baseYPlusWorld = fragCoordToWorld(baseYPlus);\n\n    float XPlusDiff = length(baseXPlusWorld - baseWorld);\n    float YPlusDiff = length(baseYPlusWorld - baseWorld);\n\n    float minFragSpacingWorld = min(XPlusDiff, YPlusDiff);\n\n    for (int s = 1; s < MAX_SEGMENT_INDEX; s++) {\n      // bail out quickly if the segment index has not\n      // been seen by the center segment\n      if (!isLabelOutlineBitSet(s)) {\n        continue;\n      }\n\n      // Use texture sampling for outlineThickness so that we can have\n      // per segment thickness\n      float textureCoordinate = float(s - 1) / 1024.0;\n      float textureValue =\n          texture2D(labelOutlineThicknessTexture, vec2(textureCoordinate, 0.5)).r;\n\n      int actualThickness = int(textureValue * 255.0);\n\n      // check the extreme points in the neighborhood since there is a better\n      // chance of finding the edge there, so that we can bail out\n      // faster if we find the edge\n      bool onEdge = checkOnEdgeForNeighbor(-actualThickness, -actualThickness, s,\n                                          stepIS) ||\n                    checkOnEdgeForNeighbor(actualThickness, actualThickness, s,\n                                          stepIS) ||\n                    checkOnEdgeForNeighbor(actualThickness, -actualThickness, s,\n                                          stepIS) ||\n                    checkOnEdgeForNeighbor(-actualThickness, +actualThickness, s,\n                                          stepIS);\n\n      if (onEdge) {\n        return;\n      }\n\n      // since the next step is computationally expensive, we need to perform\n      // some optimizations to avoid it if possible. One of the optimizations\n      // is to check the whether the minimum of the voxel spacing is greater than\n      // the 2 * the thickness of the outline segment. If that is the case\n      // then we can safely skip the next step since we can be sure that the\n      // the previous 4 checks on the extreme points would caught the entirety\n      // of the all the fragments inside. i.e., this happens when we zoom out,\n      if (minVoxelSpacing >\n          (2.0 * float(actualThickness) - 1.0) * minFragSpacingWorld) {\n        continue;\n      }\n\n      // Loop through the rest, skipping the processed extremes and the center\n      for (int i = -actualThickness; i <= actualThickness; i++) {\n        for (int j = -actualThickness; j <= actualThickness; j++) {\n          if (i == 0 && j == 0)\n            continue; // Skip the center\n          if (abs(i) == actualThickness && abs(j) == actualThickness)\n            continue; // Skip corners\n          if (checkOnEdgeForNeighbor(i, j, s, stepIS)) {\n            return;\n          }\n        }\n      }\n    }\n\n    float sampleHeight = volume.transferFunctionsSampleHeight[0];\n    vec3 tColor0 = getColorFromTexture(value.r, 0, sampleHeight);\n    float pwfValue0 = getOpacityFromTexture(value.r, 0, sampleHeight);\n    gl_FragData[0] = vec4(tColor0, pwfValue0);\n  #endif\n}\n\n//=======================================================================\n// given a\n// - ray direction (rayDir)\n// - starting point (vertexVCVSOutput)\n// - bounding planes of the volume\n// - optionally depth buffer values\n// - far clipping plane\n// compute the start/end distances of the ray we need to cast\nvec2 computeRayDistances(vec3 rayOriginVC, vec3 rayDirVC) {\n  vec2 dists = rayIntersectVolumeDistances(rayOriginVC, rayDirVC);\n\n  //VTK::ClipPlane::Impl\n\n  // do not go behind front clipping plane\n  dists.x = max(0.0, dists.x);\n\n  // do not go PAST far clipping plane\n  float farDist = -camThick / rayDirVC.z;\n  dists.y = min(farDist, dists.y);\n\n  // Do not go past the zbuffer value if set\n  // This is used for intermixing opaque geometry\n  //VTK::ZBuffer::Impl\n\n  return dists;\n}\n\nfloat getFragmentSeed() {\n  // This first noise has a diagonal pattern\n  float firstNoise =\n      fract(sin(dot(gl_FragCoord.xy, vec2(12.9898, 78.233))) * 43758.5453);\n  // This second noise is made out of blocks of CPU generated noise\n  float secondNoise = texture2D(jtexture, gl_FragCoord.xy / 32.0).r;\n  // Combine the two sources of noise in a way that the distribution is uniform\n  // in [0,1[\n  float noiseSum = firstNoise + secondNoise;\n  return noiseSum < 1.0 ? noiseSum : noiseSum - 1.0;\n}\n\nvoid main() {\n  fragmentSeed = getFragmentSeed();\n\n  if (cameraParallel == 1) {\n    // Camera is parallel, so the rayDir is just the direction of the camera.\n    rayDirVC = vec3(0.0, 0.0, -1.0);\n  } else {\n    // camera is at 0,0,0 so rayDir for perspective is just the vc coord\n    rayDirVC = normalize(vertexVCVSOutput);\n  }\n\n  vec3 rayOriginVC = vertexVCVSOutput;\n  vec2 rayStartEndDistancesVC = computeRayDistances(rayOriginVC, rayDirVC);\n  if (rayStartEndDistancesVC[1] <= rayStartEndDistancesVC[0] ||\n      rayStartEndDistancesVC[1] <= 0.0) {\n    // Volume not hit or behind the ray\n    discard;\n  }\n\n  // Perform the blending operation along the ray\n  applyBlend(rayOriginVC, rayDirVC, rayStartEndDistancesVC[0], rayStartEndDistancesVC[1]);\n}\n",e.Geometry=""},e.replaceShaderValues=(e,n,r)=>{let o=e.Fragment;o=vd.substitute(o,"//VTK::EnabledColorFunctions",`#define EnableColorForValueFunctionId${t.previousState.colorForValueFunctionId}`).result;const a=[];t.previousState.surfaceLightingEnabled&&a.push("Surface"),t.previousState.volumeLightingEnabled&&a.push("Volume"),o=vd.substitute(o,"//VTK::EnabledLightings",a.map((e=>`#define Enable${e}Lighting`))).result,t.previousState.multiTexturePerVolumeEnabled&&(o=vd.substitute(o,"//VTK::EnabledMultiTexturePerVolume","#define EnabledMultiTexturePerVolume").result),t.previousState.useIndependentComponents&&(o=vd.substitute(o,"//VTK::EnabledIndependentComponents","#define EnabledIndependentComponents").result),t.previousState.gradientOpacityEnabled&&(o=vd.substitute(o,"//VTK::EnabledGradientOpacity","#define EnabledGradientOpacity").result),o=vd.substitute(o,"//VTK::vtkProportionalComponents",t.previousState.proportionalComponents.map((e=>`#define vtkComponent${e}Proportional`)).join("\n")).result,o=vd.substitute(o,"//VTK::vtkForceNearestComponents",t.previousState.forceNearestComponents.map((e=>`#define vtkComponent${e}ForceNearest`)).join("\n")).result,t.previousState.hasZBufferTexture&&(o=vd.substitute(o,"//VTK::ZBuffer::Dec",["uniform sampler2D zBufferTexture;","uniform float vpZWidth;","uniform float vpZHeight;"]).result,o=vd.substitute(o,"//VTK::ZBuffer::Impl",["vec4 depthVec = texture2D(zBufferTexture, vec2(gl_FragCoord.x / vpZWidth, gl_FragCoord.y/vpZHeight));","float zdepth = (depthVec.r*256.0 + depthVec.g)/257.0;","zdepth = zdepth * 2.0 - 1.0;","if (cameraParallel == 0) {","zdepth = -2.0 * camFar * camNear / (zdepth*(camFar-camNear)-(camFar+camNear)) - camNear;}","else {","zdepth = (zdepth + 1.0) * 0.5 * (camFar - camNear);}\n","zdepth = -zdepth/rayDirVC.z;","dists.y = min(zdepth,dists.y);"]).result),o=vd.substitute(o,"//VTK::BlendMode",`${t.previousState.blendMode}`).result,o=vd.substitute(o,"//VTK::NumberOfLights",`${t.previousState.numberOfLights}`).result,o=vd.substitute(o,"//VTK::MaxLaoKernelSize",`${t.previousState.maxLaoKernelSize}`).result,o=vd.substitute(o,"//VTK::NumberOfComponents",`${t.previousState.numberOfComponents}`).result,o=vd.substitute(o,"//VTK::MaximumNumberOfSamples",`${t.previousState.maximumNumberOfSamples}`).result,e.Fragment=o;const i=t.previousState.numberOfClippingPlanes;i>0&&(o=vd.substitute(o,"//VTK::ClipPlane::Dec",["uniform vec3 vClipPlaneNormals[6];","uniform float vClipPlaneDistances[6];","uniform vec3 vClipPlaneOrigins[6];","uniform int clip_numPlanes;","//VTK::ClipPlane::Dec","#define vtkClippingPlanesOn"],!1).result,o=vd.substitute(o,"//VTK::ClipPlane::Impl",[`for(int i = 0; i < ${i}; i++) {`,"  float rayDirRatio = dot(rayDirVC, vClipPlaneNormals[i]);","  float equationResult = dot(vertexVCVSOutput, vClipPlaneNormals[i]) + vClipPlaneDistances[i];","  if (rayDirRatio == 0.0)","  {","    if (equationResult < 0.0) dists.x = dists.y;","    continue;","  }","  float result = -1.0 * equationResult / rayDirRatio;","  if (rayDirRatio < 0.0) dists.y = min(dists.y, result);","  else dists.x = max(dists.x, result);","}","//VTK::ClipPlane::Impl"],!1).result),e.Fragment=o},e.getNeedToRebuildShaders=(r,o,a)=>{const i=!!t.zBufferTexture,s=t.currentValidInputs.length,l=t.numberOfLights,c=t.numberOfComponents,u=t.useIndependentComponents,d=a.getProperties(),p=t.currentValidInputs[0],f=d[p.inputIndex],g=s>1,m=p.imageData.getBounds(),h=Hi.getDiagonalLength(m),v=Math.ceil(h/e.getCurrentSampleDistance(o));v>t.renderable.getMaximumSamplesPerRay()&&Tg(`The number of steps required ${v} is larger than the specified maximum number of steps ${t.renderable.getMaximumSamplesPerRay()}.\nPlease either change the volumeMapper sampleDistance or its maximum number of samples.`);const T=u?c:1;let x=!1;for(let e=0;e<T;++e)if(f.getUseGradientOpacity(e)){x=!0;break}let y=0;const b=f.getLAOKernelSize();b>y&&f.getLocalAmbientOcclusion()&&f.getAmbient()>0&&(y=b);const A=t.renderable.getClippingPlanes().length,C=t.renderable.getViewSpecificProperties().OpenGL?.ShaderReplacements,S=t.currentRenderPass?.getShaderReplacement(),P=t.renderable.getBlendMode(),w=(()=>{if(P!==hg.LABELMAP_EDGE_PROJECTION_BLEND&&n(f))return 5;if(u)switch(f.getColorMixPreset()){case gg.ADDITIVE:return 1;case gg.COLORIZE:return 2;case gg.CUSTOM:return 3;default:return 4}return 0})(),I=f.getVolumetricScatteringBlending()<1,O=f.getVolumetricScatteringBlending()>0;let R=!1;for(let e=0;e<c;++e)if(f.getForceNearestInterpolation(e)){R=!0;break}const M=[],D=[];for(let e=0;e<c;e++)f.getOpacityMode(e)===fg.PROPORTIONAL&&M.push(e),f.getForceNearestInterpolation(e)&&D.push(e);const E={numberOfComponents:c,useIndependentComponents:u,proportionalComponents:M,forceNearestComponents:D,blendMode:P,numberOfLights:l,numberOfValidInputs:s,maximumNumberOfSamples:v,hasZBufferTexture:i,maxLaoKernelSize:y,numberOfClippingPlanes:A,mapperShaderReplacements:C,renderPassShaderReplacements:S,colorForValueFunctionId:w,surfaceLightingEnabled:I,volumeLightingEnabled:O,forceNearestInterpolationEnabled:R,multiTexturePerVolumeEnabled:g,gradientOpacityEnabled:x};return(0===r.getProgram()?.getHandle()||!t.previousState||!xe(t.previousState,E))&&(t.previousState=E,!0)},e.updateShaders=(n,r,o)=>{if(e.getNeedToRebuildShaders(n,r,o)){const a={Vertex:null,Fragment:null,Geometry:null};e.buildShaders(a,r,o);const i=t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(a.Vertex,a.Fragment,a.Geometry);i!==n.getProgram()&&(n.setProgram(i),n.getVAO().releaseGraphicsResources()),n.getShaderSourceTime().modified()}else t._openGLRenderWindow.getShaderCache().readyShaderProgram(n.getProgram());n.getVAO().bind(),e.setMapperShaderParameters(n,r,o),e.setCameraShaderParameters(n,r,o),e.setPropertyShaderParameters(n,r,o),e.getClippingPlaneShaderParameters(n,r,o)},e.setMapperShaderParameters=(n,r,o)=>{const a=n.getProgram();n.getCABO().getElementCount()&&(t.VBOBuildTime.getMTime()>n.getAttributeUpdateTime().getMTime()||n.getShaderSourceTime().getMTime()>n.getAttributeUpdateTime().getMTime())&&(a.isAttributeUsed("vertexDC")&&(n.getVAO().addAttributeArray(a,n.getCABO(),"vertexDC",n.getCABO().getVertexOffset(),n.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||xg("Error setting vertexDC in shader VAO.")),n.getAttributeUpdateTime().modified());const i=e.getCurrentSampleDistance(r);a.setUniformf("sampleDistance",i);const s=i*t.renderable.getVolumeShadowSamplingDistFactor();a.setUniformf("volumeShadowSampleDistance",s),t.scalarTextures.forEach(((e,t)=>{a.setUniformi(`volumeTexture[${t}]`,e.getTextureUnit())}));const l=o.getProperties()[t.currentValidInputs[0].inputIndex].getIpScalarRange(),c=new Float32Array(4),u=new Float32Array(4),d=(e,t,n)=>{t?.dataComputedScale?.length&&(c[e]=l[0]*t.dataComputedScale[n]+t.dataComputedOffset[n],u[e]=l[1]*t.dataComputedScale[n]+t.dataComputedOffset[n],c[e]=(c[e]-t.offset[n])/t.scale[n],u[e]=(u[e]-t.offset[n])/t.scale[n])};if(t.previousState.multiTexturePerVolumeEnabled)t.scalarTextures.forEach(((e,t)=>{const n=e.getVolumeInfo();d(t,n,0)}));else{const e=t.scalarTextures[0].getVolumeInfo();for(let t=0;t<4;++t)d(t,e,t)}const p="volume";if(a.setUniform4f(`${p}.ipScalarRangeMin`,c[0],c[1],c[2],c[3]),a.setUniform4f(`${p}.ipScalarRangeMax`,u[0],u[1],u[2],u[3]),null!==t.zBufferTexture){a.setUniformi("zBufferTexture",t.zBufferTexture.getTextureUnit());const e=t._useSmallViewport?[t._smallViewportWidth,t._smallViewportHeight]:t._openGLRenderWindow.getFramebufferSize();a.setUniformf("vpZWidth",e[0]),a.setUniformf("vpZHeight",e[1])}},e.setCameraShaderParameters=(r,o,a)=>{const{idxToView:i,vecISToVCMatrix:s,modelToView:l,projectionToView:c,projectionToWorld:u}=yg,f=t.openGLCamera.getKeyMatrices(o),g=t.openGLVolume.getKeyMatrices();A(l,f.wcvc,g.mcwc);const m=r.getProgram(),h=t.openGLCamera.getRenderable(),v=h.getParallelProjection(),T=h.getClippingRange();m.setUniformf("camThick",T[1]-T[0]),m.setUniformf("camNear",T[0]),m.setUniformf("camFar",T[1]),m.setUniformi("cameraParallel",v);const x=t.currentValidInputs[0],y=x.imageData.getBounds(),C=Hi.getCorners(y,[]).map((e=>{if(oe(e,e,l),!v){$(e,e,-T[0]/(e[2]*X(e)))}return oe(e,e,f.vcpc),e})),S=Hi.addPoints([...Hi.INIT_BOUNDS],C);m.setUniformf("dcxmin",S[0]),m.setUniformf("dcxmax",S[1]),m.setUniformf("dcymin",S[2]),m.setUniformf("dcymax",S[3]);const P=e.getRenderTargetSize();m.setUniformf("vpWidth",P[0]),m.setUniformf("vpHeight",P[1]);const w=e.getRenderTargetOffset();m.setUniformf("vpOffsetX",w[0]/P[0]),m.setUniformf("vpOffsetY",w[1]/P[1]),b(c,f.vcpc),m.setUniformMatrix("PCVCMatrix",c),m.setUniformi("twoSidedLighting",o.getTwoSidedLighting());const I=new Array(2*t.previousState.maxLaoKernelSize);for(let e=0;e<t.previousState.maxLaoKernelSize;e++)I[2*e]=Math.random(),I[2*e+1]=Math.random();if(m.setUniform2fv("kernelSample",I),t.numberOfLights>0){let e=0;o.getLights().forEach((t=>{if(t.getSwitch()>0){const n=`lights[${e}]`,r=$([],t.getColor(),t.getIntensity());m.setUniform3fv(`${n}.color`,r);const o=t.getTransformedPosition();oe(o,o,l),m.setUniform3fv(`${n}.positionVC`,o);const a=[...t.getDirection()];ae(a,a,f.normalMatrix),te(a,a),m.setUniform3fv(`${n}.directionVC`,a);const i=[-.5*a[0],-.5*a[1],-.5*(a[2]-1)];m.setUniform3fv(`${n}.halfAngleVC`,i);const s=t.getAttenuationValues();m.setUniform3fv(`${n}.attenuation`,s);const c=t.getExponent();m.setUniformf(`${n}.exponent`,c);const u=t.getConeAngle();m.setUniformf(`${n}.coneAngle`,u);const d=t.getPositional();m.setUniformi(`${n}.isPositional`,d),e++}}))}const O="volume",R=a.getProperties()[x.inputIndex],M=x.imageData,D=M.getSpatialExtent(),E=M.getSpacing(),V=M.getDimensions(),L=M.getIndexToWorld(),B=M.getWorldToIndex(),F=M.getDirectionByReference();A(i,l,L),m.setUniform3fv(`${O}.spacing`,E);const N=ee([],E);m.setUniform3fv(`${O}.inverseSpacing`,N),m.setUniform3iv(`${O}.dimensions`,V),m.setUniform3fv(`${O}.inverseDimensions`,ee([],V)),m.setUniformMatrix(`${O}.worldToIndex`,B),s.fill(0);const k=Q(new Float64Array(3),V,E);s[0]=k[0],s[4]=k[1],s[8]=k[2],p(s,F,s),p(s,g.normalMatrix,s),p(s,f.normalMatrix,s),m.setUniformMatrix3x3(`${O}.vecISToVCMatrix`,s),m.setUniformMatrix3x3(`${O}.vecVCToISMatrix`,d(new Float32Array(9),s));const G=q(D[0],D[2],D[4]),U=oe(new Float64Array(3),G,i);m.setUniform3fv(`${O}.originVC`,U);const _=X(k);if(m.setUniformf(`${O}.diagonalLength`,_),n(R)){const e=h.getDistance();h.setClippingRange(e,e+.1);b(u,t.openGLCamera.getKeyMatrices(o).wcpc),h.setClippingRange(T[0],T[1]),t.openGLCamera.getKeyMatrices(o),m.setUniformMatrix(`${O}.PCWCMatrix`,u)}if(R.getVolumetricScatteringBlending()>0&&(m.setUniformf(`${O}.globalIlluminationReach`,R.getGlobalIlluminationReach()),m.setUniformf(`${O}.volumetricScatteringBlending`,R.getVolumetricScatteringBlending()),m.setUniformf(`${O}.anisotropy`,R.getAnisotropy()),m.setUniformf(`${O}.anisotropySquared`,R.getAnisotropy()**2)),R.getLocalAmbientOcclusion()&&R.getAmbient()>0){const e=R.getLAOKernelSize();m.setUniformi(`${O}.kernelSize`,e);const t=R.getLAOKernelRadius();m.setUniformi(`${O}.kernelRadius`,t)}else m.setUniformi(`${O}.kernelSize`,0)},e.setPropertyShaderParameters=(e,n,r)=>{const o=e.getProgram();o.setUniformi("jtexture",t.jitterTexture.getTextureUnit());const a=r.getProperties();o.setUniformi("labelOutlineThicknessTexture",t.labelOutlineThicknessTexture.getTextureUnit()),o.setUniformi("opacityTexture",t.opacityTexture.getTextureUnit()),o.setUniformi("colorTexture",t.colorTexture.getTextureUnit());const i="volume",s=a[t.currentValidInputs[0].inputIndex],l=t.previousState.numberOfComponents,c=t.previousState.useIndependentComponents;if(c){const e=new Float32Array(4);for(let t=0;t<l;t++)e[t]=s.getComponentWeight(t);o.setUniform4fv(`${i}.independentComponentMix`,e);const t=new Float32Array(4),n=1/l;for(let e=0;e<l;++e)t[e]=(e+.5)*n;o.setUniform4fv(`${i}.transferFunctionsSampleHeight`,t)}const u=t.colorForValueFunctionId;o.setUniformi(`${i}.colorForValueFunctionId`,u);const d=s.getComputeNormalFromOpacity();o.setUniformi(`${i}.computeNormalFromOpacity`,d);const p=new Float32Array(4),f=new Float32Array(4),g=new Float32Array(4),m=new Float32Array(4);for(let e=0;e<l;e++){const n=t.previousState.multiTexturePerVolumeEnabled,r=n?e:0,o=n?0:e,a=t.scalarTextures[r].getVolumeInfo(),i=c?e:0,l=a.scale[o],u=s.getRGBTransferFunction(i).getRange();p[e]=l/(u[1]-u[0]),f[e]=(a.offset[o]-u[0])/(u[1]-u[0]);const d=s.getScalarOpacity(i).getRange();g[e]=l/(d[1]-d[0]),m[e]=(a.offset[o]-d[0])/(d[1]-d[0])}if(o.setUniform4fv(`${i}.colorTextureScale`,p),o.setUniform4fv(`${i}.colorTextureShift`,f),o.setUniform4fv(`${i}.opacityTextureScale`,g),o.setUniform4fv(`${i}.opacityTextureShift`,m),t.previousState.gradientOpacityEnabled){const e=new Array(4),n=new Array(4),r=new Array(4),a=new Array(4);if(c)for(let o=0;o<l;++o){const i=t.previousState.multiTexturePerVolumeEnabled,l=i?o:0,c=i?0:o,u=t.scalarTextures[l].getVolumeInfo().scale[c];if(s.getUseGradientOpacity(o)){const t=[s.getGradientOpacityMinimumOpacity(o),s.getGradientOpacityMaximumOpacity(o)],i=[s.getGradientOpacityMinimumValue(o),s.getGradientOpacityMaximumValue(o)];r[o]=t[0],a[o]=t[1],e[o]=u*(t[1]-t[0])/(i[1]-i[0]),n[o]=-i[0]*(t[1]-t[0])/(i[1]-i[0])+t[0]}else r[o]=1,a[o]=1,e[o]=0,n[o]=1}else{const o=l-1,i=t.previousState.multiTexturePerVolumeEnabled,c=i?o:0,u=i?0:o,d=t.scalarTextures[c].getVolumeInfo().scale[u],p=[s.getGradientOpacityMinimumOpacity(0),s.getGradientOpacityMaximumOpacity(0)],f=[s.getGradientOpacityMinimumValue(0),s.getGradientOpacityMaximumValue(0)];r[0]=p[0],a[0]=p[1],e[0]=d*(p[1]-p[0])/(f[1]-f[0]),n[0]=-f[0]*(p[1]-p[0])/(f[1]-f[0])+p[0]}o.setUniform4f(`${i}.gradientOpacityScale`,e),o.setUniform4f(`${i}.gradientOpacityShift`,n),o.setUniform4f(`${i}.gradientOpacityMin`,r),o.setUniform4f(`${i}.gradientOpacityMax`,a)}const h=s.getLabelOutlineOpacity();if(o.setUniformf(`${i}.outlineOpacity`,h),t.numberOfLights>0){o.setUniformf(`${i}.ambient`,s.getAmbient()),o.setUniformf(`${i}.diffuse`,s.getDiffuse()),o.setUniformf(`${i}.specular`,s.getSpecular());const e=s.getSpecularPower();o.setUniformf(`${i}.specularPower`,0===e?1:e)}},e.getClippingPlaneShaderParameters=(e,n,r)=>{if(t.renderable.getClippingPlanes().length>0){const r=t.openGLCamera.getKeyMatrices(n),o=[],a=[],i=[],s=t.renderable.getClippingPlanes(),l=s.length;for(let e=0;e<l;++e){const t=s[e].getNormal(),n=s[e].getOrigin();ae(t,t,r.normalMatrix),oe(n,n,r.wcvc);const l=-1*ne(n,t);o.push(t[0]),o.push(t[1]),o.push(t[2]),a.push(l),i.push(n[0]),i.push(n[1]),i.push(n[2])}const c=e.getProgram();c.setUniform3fv("vClipPlaneNormals",o),c.setUniformfv("vClipPlaneDistances",a),c.setUniform3fv("vClipPlaneOrigins",i),c.setUniformi("clip_numPlanes",l)}},e.delete=qt((()=>{t._animationRateSubscription&&(t._animationRateSubscription.unsubscribe(),t._animationRateSubscription=null)}),(()=>{t._openGLRenderWindow&&a(t._openGLRenderWindow)}),e.delete),e.getRenderTargetSize=()=>{if(t._useSmallViewport)return[t._smallViewportWidth,t._smallViewportHeight];const{usize:e,vsize:n}=t._openGLRenderer.getTiledSizeAndOrigin();return[e,n]},e.getRenderTargetOffset=()=>{const{lowerLeftU:e,lowerLeftV:n}=t._openGLRenderer.getTiledSizeAndOrigin();return[e,n]},e.getCurrentSampleDistance=e=>{const n=e.getVTKWindow().getInteractor(),r=t.renderable.getSampleDistance();if(n.isAnimating()){return r*t.renderable.getInteractionSampleDistanceFactor()}return r},e.renderPieceStart=(n,r)=>{const o=n.getVTKWindow().getInteractor();if(t._lastScale||(t._lastScale=t.renderable.getInitialInteractionScale()),t._useSmallViewport=!1,o.isAnimating()&&t._lastScale>1.5&&(t._useSmallViewport=!0),t._animationRateSubscription||(t._animationRateSubscription=o.onAnimationFrameRateUpdate((()=>{if(t.renderable.getAutoAdjustSampleDistances()){const e=o.getRecentAnimationFrameRate(),n=o.getDesiredUpdateRate()/e;(n>1.15||n<.85)&&(t._lastScale*=n),t._lastScale>400&&(t._lastScale=400),t._lastScale<1.5&&(t._lastScale=1.5)}else t._lastScale=t.renderable.getImageSampleDistance()*t.renderable.getImageSampleDistance()}))),t._useSmallViewport){const e=t._openGLRenderWindow.getFramebufferSize(),n=1/Math.sqrt(t._lastScale);if(t._smallViewportWidth=Math.ceil(n*e[0]),t._smallViewportHeight=Math.ceil(n*e[1]),t._smallViewportHeight>e[1]&&(t._smallViewportHeight=e[1]),t._smallViewportWidth>e[0]&&(t._smallViewportWidth=e[0]),t.framebuffer.saveCurrentBindingsAndBuffers(),null===t.framebuffer.getGLFramebuffer())t.framebuffer.create(e[0],e[1]),t.framebuffer.populateFramebuffer();else{const n=t.framebuffer.getSize();n&&n[0]===e[0]&&n[1]===e[1]||(t.framebuffer.create(e[0],e[1]),t.framebuffer.populateFramebuffer())}t.framebuffer.bind();const r=t.context;r.clearColor(0,0,0,0),r.colorMask(!0,!0,!0,!0),r.clear(r.COLOR_BUFFER_BIT),r.viewport(0,0,t._smallViewportWidth,t._smallViewportHeight),t.fvp=[t._smallViewportWidth/e[0],t._smallViewportHeight/e[1]]}t.context.disable(t.context.DEPTH_TEST),e.updateBufferObjects(n,r);const a=r.getProperties();t.currentValidInputs.forEach((({inputIndex:e})=>{const n=a[e].getInterpolationType(),r=t.scalarTextures[e];n===pg.NEAREST?(r.setMinificationFilter(wd.NEAREST),r.setMagnificationFilter(wd.NEAREST)):(r.setMinificationFilter(wd.LINEAR),r.setMagnificationFilter(wd.LINEAR))})),null!==t.zBufferTexture&&t.zBufferTexture.activate()},e.renderPieceDraw=(n,r)=>{const o=t.context,a=[...t.scalarTextures,t.colorTexture,t.opacityTexture,t.labelOutlineThicknessTexture,t.jitterTexture];a.forEach((e=>e.activate())),e.updateShaders(t.tris,n,r),o.drawArrays(o.TRIANGLES,0,t.tris.getCABO().getElementCount()),t.tris.getVAO().release(),a.forEach((e=>e.deactivate()))},e.renderPieceFinish=(e,n)=>{if(null!==t.zBufferTexture&&t.zBufferTexture.deactivate(),t._useSmallViewport){if(t.framebuffer.restorePreviousBindingsAndBuffers(),null===t.copyShader){t.copyShader=t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(["//VTK::System::Dec","attribute vec4 vertexDC;","uniform vec2 tfactor;","varying vec2 tcoord;","void main() { tcoord = vec2(vertexDC.x*0.5 + 0.5, vertexDC.y*0.5 + 0.5) * tfactor; gl_Position = vertexDC; }"].join("\n"),["//VTK::System::Dec","//VTK::Output::Dec","uniform sampler2D texture1;","varying vec2 tcoord;","void main() { gl_FragData[0] = texture2D(texture1,tcoord); }"].join("\n"),"");const e=t.copyShader;t.copyVAO=yd.newInstance(),t.copyVAO.setOpenGLRenderWindow(t._openGLRenderWindow),t.tris.getCABO().bind(),t.copyVAO.addAttributeArray(e,t.tris.getCABO(),"vertexDC",t.tris.getCABO().getVertexOffset(),t.tris.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE)||xg("Error setting vertexDC in copy shader VAO.")}else t._openGLRenderWindow.getShaderCache().readyShaderProgram(t.copyShader);const e=t._openGLRenderWindow.getFramebufferSize();t.context.viewport(0,0,e[0],e[1]);const n=t.framebuffer.getColorTexture();n.activate(),t.copyShader.setUniformi("texture",n.getTextureUnit()),t.copyShader.setUniform2f("tfactor",t.fvp[0],t.fvp[1]);const r=t.context;r.blendFuncSeparate(r.ONE,r.ONE_MINUS_SRC_ALPHA,r.ONE,r.ONE_MINUS_SRC_ALPHA),t.context.drawArrays(t.context.TRIANGLES,0,t.tris.getCABO().getElementCount()),n.deactivate(),r.blendFuncSeparate(r.SRC_ALPHA,r.ONE_MINUS_SRC_ALPHA,r.ONE,r.ONE_MINUS_SRC_ALPHA)}},e.renderPiece=(n,r)=>{e.invokeEvent({type:"StartEvent"}),t.renderable.update();const o=t.renderable.getNumberOfInputPorts();t.currentValidInputs=[];for(let e=0;e<o;++e){const n=t.renderable.getInputData(e);n&&!n.isDeleted()&&t.currentValidInputs.push({imageData:n,inputIndex:e})}let a=0;if(t.currentValidInputs.length>0){const e=r.getProperties(),o=t.currentValidInputs[0],i=o.imageData.getPointData().getScalars(),s=e[o.inputIndex];s.getShade()&&t.renderable.getBlendMode()===hg.COMPOSITE_BLEND&&n.getLights().forEach((e=>{e.getSwitch()>0&&a++}));const l=t.currentValidInputs.length,c=l>1;t.numberOfComponents=c?l:i.getNumberOfComponents(),t.useIndependentComponents=function(e,t){const n=e.getIndependentComponents(),r=e.getColorMixPreset();return n&&t>=2||!!r}(s,t.numberOfComponents)}a!==t.numberOfLights&&(t.numberOfLights=a,e.modified()),e.invokeEvent({type:"EndEvent"}),0!==t.currentValidInputs.length&&(e.renderPieceStart(n,r),e.renderPieceDraw(n,r),e.renderPieceFinish(n,r))},e.updateBufferObjects=(t,n)=>{e.getNeedToRebuildBufferObjects(t,n)&&e.buildBufferObjects(t,n)},e.getNeedToRebuildBufferObjects=(n,r)=>t.VBOBuildTime.getMTime()<e.getMTime()||t.VBOBuildTime.getMTime()<r.getMTime()||t.VBOBuildTime.getMTime()<r.getProperty(t.currentValidInputs[0].inputIndex)?.getMTime()||t.VBOBuildTime.getMTime()<t.renderable.getMTime()||t.currentValidInputs.some((({imageData:e})=>t.VBOBuildTime.getMTime()<e.getMTime()))||t.scalarTextures.length!==t.currentValidInputs.length||!t.scalarTextures.every((e=>!!e?.getHandle()))||!t.colorTexture?.getHandle()||!t.opacityTexture?.getHandle()||!t.labelOutlineThicknessTexture?.getHandle()||!t.jitterTexture?.getHandle(),e.buildBufferObjects=(n,r)=>{if(!t.jitterTexture.getHandle()){const e=new Float32Array(1024);for(let t=0;t<1024;++t)e[t]=Math.random();t.jitterTexture.setMinificationFilter(wd.NEAREST),t.jitterTexture.setMagnificationFilter(wd.NEAREST),t.jitterTexture.create2DFromRaw({width:32,height:32,numComps:1,dataType:ms.FLOAT,data:e})}const a=r.getProperties(),i=t.currentValidInputs[0],s=a[i.inputIndex],l=t.numberOfComponents,c=t.useIndependentComponents,u=c?l:1,d=[];for(let e=0;e<u;++e)d.push(s.getScalarOpacity(e));const p=zf(d,c,u),f=s.getScalarOpacity(),g=t._openGLRenderWindow.getGraphicsResourceForObject(f);if(!g?.oglObject?.getHandle()||g.hash!==p){const r=Hd.newInstance();r.setOpenGLRenderWindow(t._openGLRenderWindow);let o=t.renderable.getOpacityTextureWidth();o<=0&&(o=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const a=2*o*u,i=new Float32Array(a),l=new Float32Array(o);for(let t=0;t<u;++t){const r=s.getScalarOpacity(t),a=e.getCurrentSampleDistance(n)/s.getScalarOpacityUnitDistance(t),c=r.getRange();r.getTable(c[0],c[1],o,l,1);for(let e=0;e<o;++e)i[t*o*2+e]=1-(1-l[e])**a,i[t*o*2+e+o]=i[t*o*2+e]}if(r.resetFormatAndType(),r.setMinificationFilter(wd.LINEAR),r.setMagnificationFilter(wd.LINEAR),t._openGLRenderWindow.getWebgl2()||t.context.getExtension("OES_texture_float")&&t.context.getExtension("OES_texture_float_linear"))r.create2DFromRaw({width:o,height:2*u,numComps:1,dataType:ms.FLOAT,data:i});else{const e=new Uint8ClampedArray(a);for(let t=0;t<a;++t)e[t]=255*i[t];r.create2DFromRaw({width:o,height:2*u,numComps:1,dataType:ms.UNSIGNED_CHAR,data:e})}f&&t._openGLRenderWindow.setGraphicsResourceForObject(f,r,p),t.opacityTexture=r}else t.opacityTexture=g.oglObject;o(t._openGLRenderWindow,t._opacityTextureCore,f),t._opacityTextureCore=f;const m=[];for(let e=0;e<u;++e)m.push(s.getRGBTransferFunction(e));const h=zf(m,c,u),v=s.getRGBTransferFunction(),T=t._openGLRenderWindow.getGraphicsResourceForObject(v);if(!T?.oglObject?.getHandle()||T?.hash!==h){const e=Hd.newInstance();e.setOpenGLRenderWindow(t._openGLRenderWindow);let n=t.renderable.getColorTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=new Uint8ClampedArray(2*n*u*3),o=new Float32Array(3*n);for(let e=0;e<u;++e){const t=s.getRGBTransferFunction(e),a=t.getRange();t.getTable(a[0],a[1],n,o,1);for(let t=0;t<3*n;++t)r[e*n*6+t]=255*o[t],r[e*n*6+t+3*n]=255*o[t]}e.resetFormatAndType(),e.setMinificationFilter(wd.LINEAR),e.setMagnificationFilter(wd.LINEAR),e.create2DFromRaw({width:n,height:2*u,numComps:3,dataType:ms.UNSIGNED_CHAR,data:r}),t._openGLRenderWindow.setGraphicsResourceForObject(v,e,h),t.colorTexture=e}else t.colorTexture=T.oglObject;o(t._openGLRenderWindow,t._colorTextureCore,v),t._colorTextureCore=v,t.currentValidInputs.forEach((({imageData:e,inputIndex:n},r)=>{const i=a[n],s=e.getPointData().getScalars(),l=t._openGLRenderWindow.getGraphicsResourceForObject(s),c=Wf(0,s),u=!l?.oglObject?.getHandle()||l?.hash!==c,d=i.getUpdatedExtents(),p=!!d.length;if(u&&!p){const n=Hd.newInstance();n.setOpenGLRenderWindow(t._openGLRenderWindow);const o=e.getDimensions();n.setOglNorm16Ext(t.context.getExtension("EXT_texture_norm16")),n.resetFormatAndType(),n.create3DFilterableFromDataArray({width:o[0],height:o[1],depth:o[2],dataArray:s,preferSizeOverAccuracy:i.getPreferSizeOverAccuracy()}),t._openGLRenderWindow.setGraphicsResourceForObject(s,n,c),t.scalarTextures[r]=n}else t.scalarTextures[r]=l.oglObject;if(p){i.setUpdatedExtents([]);const n=e.getDimensions();t.scalarTextures[r].create3DFilterableFromDataArray({width:n[0],height:n[1],depth:n[2],dataArray:s,updatedExtents:d})}o(t._openGLRenderWindow,t._scalarTexturesCore[r],s),t._scalarTexturesCore[r]=s}));const x=s.getLabelOutlineThickness(),y=t._openGLRenderWindow.getGraphicsResourceForObject(x),b=x.join("-");if(!y?.oglObject?.getHandle()||y?.hash!==b){const e=Hd.newInstance();e.setOpenGLRenderWindow(t._openGLRenderWindow);let n=t.renderable.getLabelOutlineTextureWidth();n<=0&&(n=t.context.getParameter(t.context.MAX_TEXTURE_SIZE));const r=1,o=new Uint8Array(n*r);for(let e=0;e<n;++e){const t=void 0!==x[e]?x[e]:x[0];o[e]=t}e.resetFormatAndType(),e.setMinificationFilter(wd.NEAREST),e.setMagnificationFilter(wd.NEAREST),e.create2DFromRaw({width:n,height:r,numComps:1,dataType:ms.UNSIGNED_CHAR,data:o}),x&&t._openGLRenderWindow.setGraphicsResourceForObject(x,e,b),t.labelOutlineThicknessTexture=e}else t.labelOutlineThicknessTexture=y.oglObject;if(o(t._openGLRenderWindow,t._labelOutlineThicknessTextureCore,x),t._labelOutlineThicknessTextureCore=x,!t.tris.getCABO().getElementCount()){const e=new Float32Array(12);for(let t=0;t<4;t++)e[3*t]=t%2*2-1,e[3*t+1]=t>1?1:-1,e[3*t+2]=-1;const n=new Uint16Array(8);n[0]=3,n[1]=0,n[2]=1,n[3]=3,n[4]=3,n[5]=0,n[6]=3,n[7]=2;const r=Is.newInstance({numberOfComponents:3,values:e});r.setName("points");const o=Is.newInstance({numberOfComponents:1,values:n});t.tris.getCABO().createVBO(o,"polys",rs.SURFACE,{points:r,cellOffset:0})}t.VBOBuildTime.modified()}}const Ag={context:null,VBOBuildTime:null,scalarTextures:[],_scalarTexturesCore:[],opacityTexture:null,_opacityTextureCore:null,colorTexture:null,_colorTextureCore:null,labelOutlineThicknessTexture:null,_labelOutlineThicknessTextureCore:null,jitterTexture:null,tris:null,framebuffer:null,copyShader:null,copyVAO:null,lastXYF:1,targetXYF:1,zBufferTexture:null,lastZBufferTexture:null,fullViewportTime:1,idxToView:null,vecISToVCMatrix:null,modelToView:null,projectionToView:null,avgWindowArea:0,avgFrameTime:0};vn("vtkVolumeMapper",Xt((function(e,t,n={}){Object.assign(t,Ag,n),pn.extend(e,t,n),qd.implementBuildShadersWithReplacements(e,t,n),t.VBOBuildTime={},Vt(t.VBOBuildTime,{mtime:0}),t.tris=Sd.newInstance(),t.jitterTexture=Hd.newInstance(),t.jitterTexture.setWrapS(Pd.REPEAT),t.jitterTexture.setWrapT(Pd.REPEAT),t.framebuffer=Gp.newInstance(),Gt(e,t,["context"]),bg(e,t)}),"vtkOpenGLVolumeMapper"));const{vtkDebugMacro:Cg}=ln;const Sg={};vn("vtkPixelSpaceCallbackMapper",Xt((function(e,t,n={}){Object.assign(t,Sg,n),pn.extend(e,t,n),function(e,t){t.classHierarchy.push("vtkOpenGLPixelSpaceCallbackMapper"),e.opaquePass=(n,r)=>{t._openGLRenderer=e.getFirstAncestorOfType("vtkOpenGLRenderer"),t._openGLRenderWindow=t._openGLRenderer.getLastAncestorOfType("vtkOpenGLRenderWindow");const o=t._openGLRenderer.getAspectRatio(),a=t._openGLRenderer?t._openGLRenderer.getRenderable().getActiveCamera():null,i=t._openGLRenderer.getTiledSizeAndOrigin();let s=null;if(t.renderable.getUseZValues()){const e=r.getZBufferTexture(),n=Math.floor(e.getWidth()),o=Math.floor(e.getHeight()),a=t._openGLRenderWindow.getContext();e.bind();const i=r.getFramebuffer();i?i.saveCurrentBindingsAndBuffers():Cg("No framebuffer to save/restore");const l=a.createFramebuffer();a.bindFramebuffer(a.FRAMEBUFFER,l),a.framebufferTexture2D(a.FRAMEBUFFER,a.COLOR_ATTACHMENT0,a.TEXTURE_2D,e.getHandle(),0),a.checkFramebufferStatus(a.FRAMEBUFFER)===a.FRAMEBUFFER_COMPLETE&&(s=new Uint8Array(n*o*4),a.viewport(0,0,n,o),a.readPixels(0,0,n,o,a.RGBA,a.UNSIGNED_BYTE,s)),i&&i.restorePreviousBindingsAndBuffers(),a.deleteFramebuffer(l)}t.renderable.invokeCallback(t.renderable.getInputData(),a,o,i,s)},e.queryPass=(e,n)=>{e&&t.renderable.getUseZValues()&&n.requestDepth()}}(e,t)}),"vtkOpenGLPixelSpaceCallbackMapper"));var Pg="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtktextureObjectVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n\nattribute vec4 vertexDC;\nattribute vec2 tcoordDC;\nvarying vec2 tcoordVC;\n\nvoid main()\n{\n  tcoordVC = tcoordDC;\n  gl_Position = vertexDC;\n}\n";const{Representation:wg}=us;function Ig(e,[t,n],r,o){const a=e.getContext(),i=Hd.newInstance({autoParameters:!1,wrapS:o,wrapT:o,minificationFilter:r,magnificationFilter:r,generateMipmap:!1,openGLDataType:a.FLOAT,baseLevel:0,maxLevel:0});return i.setOpenGLRenderWindow(e),i.setInternalFormat(a.RGBA32F),i.create2DFromRaw({width:t,height:n,numComps:4,dataType:"Float32Array",data:null}),i.activate(),i.sendParameters(),i.deactivate(),i}function Og(e,t){return Ig(e,t,Hd.Filter.NEAREST,Hd.Wrap.CLAMP_TO_EDGE)}function Rg(e,t){var n,r;(t.classHierarchy.push("vtkLICPingPongBufferManager"),t._openGLRenderWindow)?(t.quad=function(e){const t=Sd.newInstance();t.setOpenGLRenderWindow(e);const n=new Float32Array(12);for(let e=0;e<4;e++)n[3*e]=e%2*2-1,n[3*e+1]=e>1?1:-1,n[3*e+2]=0;const r=new Float32Array([0,0,1,0,0,1,1,1]),o=new Uint16Array(8);o[0]=3,o[1]=0,o[2]=1,o[3]=3,o[4]=3,o[5]=0,o[6]=3,o[7]=2;const a=Is.newInstance({numberOfComponents:3,values:n});a.setName("points");const i=Is.newInstance({numberOfComponents:1,values:o}),s=Is.newInstance({numberOfComponents:2,values:r});return t.getCABO().createVBO(i,"polys",wg.SURFACE,{points:a,cellOffset:0,tcoords:s}),t}(t._openGLRenderWindow),t.context=t._openGLRenderWindow.getContext(),t.licTexture0=Og(t._openGLRenderWindow,t.size),t.seedTexture0=Og(t._openGLRenderWindow,t.size),t.licTexture1=Og(t._openGLRenderWindow,t.size),t.seedTexture1=Og(t._openGLRenderWindow,t.size),t.eeTexture=t.doEEPass?(n=t._openGLRenderWindow,r=t.size,Ig(n,r,Hd.Filter.NEAREST,Hd.Wrap.CLAMP_TO_EDGE)):null,t.imageVectorTexture=t.doVTPass?function(e,t){return Ig(e,t,Hd.Filter.LINEAR,Hd.Wrap.CLAMP_TO_EDGE)}(t._openGLRenderWindow,t.size):null,t.pingTextures[0]=t.licTexture0,t.pingTextures[1]=t.seedTexture0,t.pongTextures[0]=t.licTexture1,t.pongTextures[1]=t.seedTexture1,t.textures[0]=t.pingTextures,t.textures[1]=t.pongTextures,e.swap=()=>{t.readIndex=1-t.readIndex},e.renderQuad=(e,n)=>{const r=t.quad,o=t.context;let a=t.quadVAO;a||(a=yd.newInstance(),a.setOpenGLRenderWindow(t._openGLRenderWindow),t.quadVAO=a),t.previousProgramHash!==n.getMd5Hash()&&(a.shaderProgramChanged(),r.getCABO().bind(),a.addAttributeArray(n,r.getCABO(),"vertexDC",r.getCABO().getVertexOffset(),r.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE),a.addAttributeArray(n,r.getCABO(),"tcoordDC",r.getCABO().getTCoordOffset(),r.getCABO().getStride(),t.context.FLOAT,2,t.context.FALSE),t.previousProgramHash=n.getMd5Hash()),o.drawArrays(o.TRIANGLES,0,r.getCABO().getElementCount()),a.release()},e.getLastLICBuffer=()=>0===t.readIndex?t.licTexture0:t.licTexture1,e.getLastSeedBuffer=()=>0===t.readIndex?t.seedTexture0:t.seedTexture1,e.getLICBuffer=()=>1-t.readIndex==0?t.licTexture0:t.licTexture1,e.getSeedBuffer=()=>1-t.readIndex==0?t.seedTexture0:t.seedTexture1,e.getLICTextureUnit=()=>{const e=t.textures[t.readIndex][0];return e.activate(),e.getTextureUnit()},e.getSeedTextureUnit=()=>{const e=t.textures[t.readIndex][1];return e.activate(),e.getTextureUnit()},e.getNoiseTextureUnit=(e=0)=>0===e?(t.noiseTexture.activate(),t.noiseTexture.getTextureUnit()):(t.eeTexture.activate(),t.eeTexture.getTextureUnit()),e.getVectorTextureUnit=()=>(t.vectorTexture.activate(),t.vectorTexture.getTextureUnit()),e.getImageVectorTextureUnit=()=>t.imageVectorTexture?(t.imageVectorTexture.activate(),t.imageVectorTexture.getTextureUnit()):e.getVectorTextureUnit(),e.getMaskVectorTextureUnit=()=>t.maskVectorTexture?(t.maskVectorTexture.activate(),t.maskVectorTexture.getTextureUnit()):e.getImageVectorTextureUnit(),e.clearBuffers=(e=!1)=>{const n=t.framebuffer,r=t.context;n.removeColorBuffer(0),n.removeColorBuffer(1),n.removeColorBuffer(2),n.removeColorBuffer(3),n.setColorBuffer(t.licTexture0,0),n.setColorBuffer(t.seedTexture0,1),n.setColorBuffer(t.licTexture1,2),n.setColorBuffer(t.seedTexture1,3);const o=[r.COLOR_ATTACHMENT0,r.COLOR_ATTACHMENT1,r.COLOR_ATTACHMENT2,r.COLOR_ATTACHMENT3];e&&(n.removeColorBuffer(4),n.setColorBuffer(t.eeTexture,4),o.push(r.COLOR_ATTACHMENT4)),r.drawBuffers(o),r.clearColor(0,1,0,0),r.disable(r.SCISSOR_TEST),r.disable(r.BLEND),r.clear(r.COLOR_BUFFER_BIT),n.removeColorBuffer(0),n.removeColorBuffer(1),n.removeColorBuffer(2),n.removeColorBuffer(3),e&&n.removeColorBuffer(4),r.drawBuffers([r.NONE])},e.clearBuffer=e=>{const n=t.framebuffer,r=t.context;n.removeColorBuffer(0),n.setColorBuffer(e,0),r.drawBuffers([r.COLOR_ATTACHMENT0]),r.clearColor(0,1,0,0),r.disable(r.SCISSOR_TEST),r.disable(r.BLEND),r.clear(r.COLOR_BUFFER_BIT),n.removeColorBuffer(e,0),r.drawBuffers([r.NONE])},e.activateVectorTextures=()=>{t.imageVectorTexture?t.imageVectorTexture.activate():t.vectorTexture.activate(),t.maskVectorTexture&&t.maskVectorTexture.activate()},e.deactivateVectorTextures=()=>{t.imageVectorTexture?t.imageVectorTexture.deactivate():t.vectorTexture.deactivate(),t.maskVectorTexture&&t.maskVectorTexture.deactivate()},e.activateNoiseTexture=(e=0)=>{switch(e){case 0:t.noiseTexture.activate();break;case 1:t.eeTexture.activate();break;default:console.error("Wrong LIC pass number")}},e.deactivateNoiseTexture=(e=0)=>{switch(e){case 0:t.noiseTexture.deactivate();break;case 1:t.eeTexture.deactivate();break;default:console.error("Wrong LIC pass number")}},e.attachLICBuffers=()=>{const e=t.textures[t.readIndex],n=t.textures[1-t.readIndex],r=t.framebuffer,o=t.context;e[0].activate(),e[1].activate(),r.removeColorBuffer(0),r.removeColorBuffer(1),r.setColorBuffer(n[0],0),r.setColorBuffer(n[1],1),o.drawBuffers([o.COLOR_ATTACHMENT0,o.COLOR_ATTACHMENT1])},e.detachLICBuffers=()=>{const e=t.textures[t.readIndex],n=t.context,r=t.framebuffer;e[0].deactivate(),e[1].deactivate(),r.removeColorBuffer(0),r.removeColorBuffer(1),n.drawBuffers([n.NONE])},e.attachImageVectorBuffer=()=>{const e=t.framebuffer,n=t.context;t.vectorTexture.activate(),e.removeColorBuffer(0),e.setColorBuffer(t.imageVectorTexture,0),n.drawBuffers([n.COLOR_ATTACHMENT0])},e.detachImageVectorBuffer=()=>{const e=t.context,n=t.framebuffer;t.vectorTexture.deactivate(),n.removeColorBuffer(0),e.drawBuffers([e.NONE])},e.attachEEBuffer=()=>{t.textures[t.readIndex][0].activate(),t.framebuffer.removeColorBuffer(0),t.framebuffer.setColorBuffer(t.eeTexture,0);const e=t.context;e.drawBuffers([e.COLOR_ATTACHMENT0])},e.detachEEBuffer=()=>{const e=t.context;t.framebuffer.removeColorBuffer(0),e.drawBuffers([e.NONE]);t.textures[t.readIndex][0].deactivate()},e.detachBuffers=()=>{const e=t.context,n=t.framebuffer;n.removeColorBuffer(0),n.removeColorBuffer(1),e.drawBuffers([e.NONE]);const r=t.textures[t.readIndex],o=t.textures[1-t.readIndex];r[0]&&r[0].deactivate(),r[1]&&r[1].deactivate(),o[0]&&o[0].deactivate(),o[1]&&o[1].deactivate(),t.eeTexture&&t.eeTexture.deactivate(),t.noiseTexture&&t.noiseTexture.deactivate()},e.getWriteIndex=()=>1-t.readIndex,e.detachBuffers()):console.error("Pass renderwindow to ping pong manager")}const Mg={vectorTexture:null,maskVectorTexture:null,noiseTexture:null,doEEPass:!1,doVTPass:!1,readIndex:0,quad:null,lastProgramHash:null,framebuffer:null,size:null,pingTextures:[],pongTextures:[],textures:[]};function Dg(e,t,n={}){Object.assign(t,Mg,n),sn.obj(e,t),sn.get(e,t,["readIndex"]),sn.setGet(e,t,["doEEPass","doVTPass","_openGLRenderWindow","vectorTexture","maskVectorTexture","noiseTexture","framebuffer","size"]),sn.moveToProtected(e,t,["openGLRenderWindow"]),Rg(e,t)}var Eg={newInstance:sn.newInstance(Dg,"vtkLICPingPongBufferManager"),extend:Dg};const Vg=0,Lg=1,Bg=2,Fg=3,Ng=1;const kg={shadersNeedBuild:!0,stepSize:1,numberOfSteps:10,enhancedLIC:!0,enhanceContrast:!1,lowContrastEnhancementFactor:0,highContrastEnhancementFactor:0,antiAlias:0,componentIds:[0,1],normalizeVectors:!0,maskThreshold:0,transformVectors:!0,bufs:null,isComposite:!0};function Gg(e,t,n={}){Object.assign(t,kg,n),sn.obj(e,t),sn.setGet(e,t,["context","_openGLRenderWindow","nuberOfSteps","stepSize","normalizeVectors","maskThreshold","enhancedLIC","enhanceContrast","lowLICContrastEnhancementFactor","highLICContrastEnhancementFactor","antiAlias","componentIds","isComposite"]),sn.moveToProtected(e,t,["openGLRenderWindow"]),function(e,t){function n(e,t){e.setUniformi("texLIC",t.getLICTextureUnit()),e.setUniformi("texSeedPts",t.getSeedTextureUnit())}function r(e,t,n){e.attachLICBuffers(),e.renderQuad(t,n),e.detachLICBuffers(),e.swap()}t.classHierarchy.push("vtkLineIntegralConvolution2D"),e.buildAShader=e=>t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(Pg,e,""),e.dumpTextureValues=(e,[n,r],o=t.context,a=t._openGLRenderWindow,i=4)=>{const s=Gp.newInstance(),l=o;let c=null;return s.setOpenGLRenderWindow(a),s.saveCurrentBindingsAndBuffers(),s.create(n,r),s.populateFramebuffer(),s.setColorBuffer(e),c=new Float32Array(n*r*i),l.readPixels(0,0,n,r,4===i?l.RGBA:l.RGB,l.FLOAT,c),s.restorePreviousBindingsAndBuffers(),c},e.getTextureMinMax=(n,r,o=t.context,a=t._openGLRenderWindow)=>{const i=e.dumpTextureValues(n,r,o,a,4);let s=Number.MAX_VALUE,l=Number.MIN_VALUE;for(let e=0;e<i.length;e+=4)if(0===i[e+1]){const t=i[e];t<s&&(s=t),t>l&&(l=t)}return{min:s,max:l}},e.getComponentSelectionProgram=e=>{const t="xyzw";return`.${t[e[0]]}${t[e[1]]}`},e.buildShaders=()=>{t.LIC0ShaderProgram=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_LIC0.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n/**\nThis shader initializes the convolution for the LIC computation.\n*/\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\nuniform sampler2D texMaskVectors;\nuniform sampler2D texNoise;\nuniform sampler2D texLIC;\n\nuniform int   uStepNo;         // in step 0 initialize lic and seeds, else just seeds\nuniform int   uPassNo;         // in pass 1 hpf of pass 0 is convolved.\nuniform float uMaskThreshold;  // if |V| < uMaskThreshold render transparent\nuniform vec2  uNoiseBoundsPt1; // tc of upper right pt of noise texture\n\nin vec2 tcoordVC;\n\n// convert from vector coordinate space to noise coordinate space.\n// the noise texture is tiled across the *whole* domain\nvec2 VectorTCToNoiseTC(vec2 vectc)\n{\n  return vectc/uNoiseBoundsPt1;\n}\n\n// get the texture coordidnate to lookup noise value. this\n// depends on the pass number.\nvec2 getNoiseTC(vec2 vectc)\n{\n  // in pass 1 : convert from vector tc to noise tc\n  // in pass 2 : use vector tc\n  if (uPassNo == 0)\n    {\n    return VectorTCToNoiseTC(vectc);\n    }\n  else\n    {\n    return vectc;\n    }\n}\n\n// look up noise value at the given location. The location\n// is supplied in vector texture coordinates, hence the\n// need to convert to noise texture coordinates.\nfloat getNoise(vec2 vectc)\n{\n  return texture2D(texNoise, getNoiseTC(vectc)).r;\n}\n\nvoid main(void)\n{\n  vec2 vectc = tcoordVC.st;\n\n  // lic => (convolution, mask, 0, step count)\n  if (uStepNo == 0)\n    {\n    float maskCriteria = length(texture2D(texMaskVectors, vectc).xyz);\n    float maskFlag;\n    if (maskCriteria <= uMaskThreshold)\n      {\n      maskFlag = 1.0;\n      }\n    else\n      {\n      maskFlag = 0.0;\n      }\n    float noise = getNoise(vectc);\n    LICOutput = vec4(noise, maskFlag, 0.0, 1.0);\n    }\n  else\n    {\n    LICOutput = texture2D(texLIC, vectc);\n    }\n\n  // initial seed\n  SeedOutput = vec4(vectc, 0.0, 1.0);\n}\n");const n=vd.substitute("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_VT.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// move vector field to normalized image space\n// pre-processing for vtkLineIntegralConvolution2D\n\n// the output of this shader\n//VTK::Output::Dec\n\n// Fragment shader used by the gaussian blur filter render pass.\n\nuniform sampler2D texVectors; // input texture\nuniform vec2      uTexSize;   // size of texture\n\nin vec2 tcoordVC;\n\nvoid main(void)\n{\n  //VTK::LICComponentSelection::Impl\n  V = V/uTexSize;\n  gl_FragData[0] = vec4(V, 0.0, 1.0);\n}\n","//VTK::LICComponentSelection::Impl",`vec2 V = texture2D(texVectors, tcoordVC.st)${e.getComponentSelectionProgram(t.componentIds)};`).result;t.VTProgram=e.buildAShader(n);const r=vd.substitute("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_fs1.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\nuniform sampler2D  texVectors;\nuniform sampler2D  texNoise;\nuniform sampler2D  texLIC;\nuniform sampler2D  texSeedPts;\n\nuniform int   uPassNo;          // in pass 1 hpf of pass 0 is convolved.\nuniform float uStepSize;        // step size in parametric space\n\nuniform vec2  uNoiseBoundsPt1;  // tc of upper right pt of noise texture\n\nin vec2 tcoordVC;\n\n//VTK::LICVectorLookup::Impl\n\n// We need to do this manually since CLAMP_TO_BORDER and and borderColor\n// are very poorly supported in webgl\nvec2 clampToBorder(vec2 uv){\n  if(uv.x < 0.0 || uv.x > 1.0 || uv.y < 0.0 || uv.y > 1.0)\n  {\n    return vec2(0.0, 0.0);\n  }\n  return getVector(uv);\n}\n\n// convert from vector coordinate space to noise coordinate space.\n// the noise texture is tiled across the whole domain\nvec2 VectorTCToNoiseTC(vec2 vectc)\n{\n  return vectc/uNoiseBoundsPt1;\n}\n\n// get the texture coordidnate to lookup noise value.\n// in pass 1 repeatedly tile the noise texture across\n// the computational domain.\nvec2 getNoiseTC(vec2 tc)\n{\n  if (uPassNo == 0)\n    {\n    return VectorTCToNoiseTC(tc);\n    }\n  else\n    {\n    return tc;\n    }\n}\n\n// look up noise value at the given location. The location\n// is supplied in vector texture coordinates, hence the need\n// to convert to either noise or lic texture coordinates in\n// pass 1 and 2 respectively.\nfloat getNoise(vec2 vectc)\n{\n  return texture2D(texNoise, getNoiseTC(vectc)).r;\n}\n\n// fourth-order Runge-Kutta streamline integration\n// no bounds checks are made, therefore it's essential\n// to have the entire texture initialized to 0\n// and set clamp to border and have border color 0\n// an integer is set if the step was taken, keeping\n// an accurate step count is necessary to prevent\n// boundary artifacts. Don't count the step if\n// all vector lookups are identically 0. This is\n// a proxy for \"stepped outside valid domain\"\nvec2 rk4(vec2 pt0, float dt, out bool count)\n{\n  count=true;\n  float dtHalf = dt * 0.5;\n  vec2 pt1;\n\n  vec2 v0 = clampToBorder(pt0);\n  pt1 = pt0 + v0 * dtHalf;\n\n  vec2 v1 = clampToBorder(pt1);\n  pt1 = pt0 + v1 * dtHalf;\n\n  vec2 v2 = clampToBorder(pt1);\n  pt1 = pt0 + v2 * dt;\n\n  vec2 v3 = clampToBorder(pt1);\n  vec2 vSum = v0 + v1 + v1 + v2 + v2 + v3;\n\n  if (vSum == vec2(0.0, 0.0))\n    {\n      count = false;\n    }\n\n  pt1 = pt0 + (vSum) * (dt * (1.0/6.0));\n\n return pt1;\n}\n\nvoid main(void)\n{\n  vec2 lictc = tcoordVC.st;\n  vec4 lic = texture2D(texLIC, lictc);\n  vec2 pt0 = texture2D(texSeedPts, lictc).st;\n\n  bool count;\n  vec2 pt1 = rk4(pt0, uStepSize, count);\n\n  if (count)\n    {\n    // accumulate lic step\n    // (lic, mask, 0, step count)\n    float noise = getNoise(pt1);\n    LICOutput = vec4(lic.r + noise, lic.g, 0.0, lic.a + 1.0);\n    SeedOutput = vec4(pt1, 0.0, 1.0);\n    }\n  else\n    {\n    // keep existing values\n    LICOutput = lic;\n    SeedOutput = vec4(pt0, 0.0, 1.0);\n    }\n}\n","//VTK::LICVectorLookup::Impl",function(e=!0){return e?"\n    vec2 getVector( vec2 vectc )\n\n      {\n\n      vec2 V = texture2D( texVectors, vectc ).xy;\n\n      // normalize if |V| not 0\n\n      float lenV = length( V );\n\n      if ( lenV > 1.0e-8 )\n\n        {\n\n        return V/lenV;\n\n        }\n\n      else\n\n        {\n\n        return vec2( 0.0, 0.0 );\n\n        }\n\n      }\n\n    ":"\n    vec2 getVector( vec2 vectc )\n\n      {\n\n      return texture2D( texVectors, vectc ).xy;\n\n      }\n\n    "}(t.normalizeVectors),!0).result;t.LICIShaderProgram=e.buildAShader(r),t.LICNShaderProgram=e.buildAShader(" //VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_LICN.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\n/**\nThis shader finalizes the convolution for the LIC computation\napplying the normalization. eg. if box kernel is used the this\nis the number of steps taken.\n*/\n\nuniform sampler2D texLIC;\n\nin vec2 tcoordVC;\n\nvoid main(void)\n{\n  vec4 conv = texture2D(texLIC, tcoordVC.st);\n  conv.r = conv.r/conv.a;\n  // lic => (convolution, mask, 0, 1)\n  LICOutput = vec4(conv.rg , 0.0, 1.0);\n  SeedOutput = vec4(0.0, 0.0, 0.0, 0.0);\n}\n"),t.CEProgram=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_CE.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// gray scale contrast enhance stage implemented via histogram stretching\n// if the min and max are tweaked it can generate out-of-range values\n// these will be clamped in 0 to 1\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\n\nuniform sampler2D texLIC;  // most recent lic pass\nuniform float uMin;        // min gray scale color value\nuniform float uMaxMinDiff; // max-min\n\nin vec2 tcoordVC;\n\nvoid main( void )\n{\n  vec4 lic = texture2D(texLIC, tcoordVC.st);\n  if (lic.g!=0.0)\n    {\n    LICOutput = lic;\n    }\n  else\n    {\n    float CElic = clamp((lic.r - uMin)/uMaxMinDiff, 0.0, 1.0);\n    LICOutput = vec4(CElic, lic.gb, 1.0);\n    }\n    SeedOutput = vec4(0.0, 0.0, 0.0, 0.0);\n}\n"),t.EEProgram=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_fs2.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// high-pass filter stage employed by vtkLineIntegralConvolution2D\n// between LIC pass 1 and LIC pass 2. filtered LIC pass 1, becomes\n// noise for pass2.\n\n// the output of this shader\nlayout(location = 0) out vec4 EEOutput;\n\nuniform sampler2D texLIC; // most recent lic pass\nuniform float     uDx;    // fragment size\nuniform float     uDy;    // fragment size\n\nin vec2 tcoordVC;\n\n// kernel for simple laplace edge enhancement.\n// p=Laplace(p)+p\nfloat K[9] = float[9](\n  -1.0, -1.0, -1.0,\n  -1.0,  9.0, -1.0,\n  -1.0, -1.0, -1.0\n  );\n\n// determine if the fragment was masked\nbool Masked(float val) { return val != 0.0; }\n\nvoid main(void)\n{\n  // tex coord neighbor offsets\n  vec2 fragDx[9] = vec2[9](\n    vec2(-uDx, uDy), vec2(0.0, uDy), vec2(uDx, uDy),\n    vec2(-uDx, 0.0), vec2(0.0, 0.0), vec2(uDx, 0.0),\n    vec2(-uDx,-uDy), vec2(0.0,-uDy), vec2(uDx,-uDy)\n    );\n\n  vec2 lictc = tcoordVC.st;\n\n  // compute the convolution but don't use convovled values if\n  // any masked fragments on the stencil. Fragments outside\n  // the valid domain are masked during initialization, and\n  // texture wrap parameters are clamp to border with border\n  // color that contains masked flag\n  float conv = 0.0;\n  bool dontUse = false;\n  for (int i=0; i<9; ++i)\n    {\n    vec2 tc = lictc + fragDx[i];\n    vec4 lic = texture2D(texLIC, tc);\n    dontUse = dontUse || Masked(lic.g);\n    conv = conv + K[i] * lic.r;\n    }\n\n  if (dontUse)\n    {\n    EEOutput = vec4(texture2D(texLIC, lictc).rg, 0.0, 1.0);\n    }\n  else\n    {\n    conv = clamp(conv, 0.0, 1.0);\n    EEOutput = vec4(conv,texture2D(texLIC, lictc).g, 0.0, 1.0);\n    }\n\n}\n"),t.AAHProgram=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_AAH.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// Anti-alias stage in vtkLineIntegralConvolution2D\n// horizontal pass of a Gaussian convolution\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\nuniform sampler2D texLIC; // input texture\nuniform float     uDx;    // fragment size\n\nin vec2 tcoordVC;\n\n// factored 3x3 Gaussian kernel\n// K^T*K = G\nfloat K[3] = float[3](0.141421356, 0.707106781, 0.141421356);\n\n// determine if the fragment was masked\nbool Masked(float val){ return val != 0.0; }\n\nvoid main(void)\n{\n// neighbor offsets\nvec2 fragDx[3] = vec2[3](vec2(-uDx,0.0), vec2(0.0,0.0), vec2(uDx,0.0));\n\n  vec2 lictc = tcoordVC.st;\n  vec4 lic[3];\n  bool dontUse = false;\n  float conv = 0.0;\n  for (int i=0; i<3; ++i)\n    {\n    vec2 tc = lictc + fragDx[i];\n    lic[i] = texture2D(texLIC, tc);\n    dontUse = dontUse || Masked(lic[i].g);\n    conv = conv + K[i] * lic[i].r;\n    }\n  // output is (conv, mask, skip, 1)\n  if (dontUse)\n    {\n    LICOutput = vec4(lic[1].rg, 1.0, 1.0);\n    }\n  else\n    {\n    LICOutput = vec4(conv, lic[1].gb, 1.0);\n    }\n  SeedOutput = vec4(0.0, 0.0, 0.0, 0.0);\n}\n"),t.AAVProgram=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkLineIntegralConvolution2D_AAV.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// Anti-alias stage in vtkLineIntegralConvolution2D\n// vertical pass of a Gaussian convolution\n\n// the output of this shader\nlayout(location = 0) out vec4 LICOutput;\nlayout(location = 1) out vec4 SeedOutput;\n\nuniform sampler2D texLIC; // input texture\nuniform float     uDy;    // fragment size\n\nin vec2 tcoordVC;\n\n\n// factored 3x3 Gaussian kernel\n// K^T*K = G\nfloat K[3] = float[3](0.141421356, 0.707106781, 0.141421356);\n\n// determine if the fragment was masked\nbool Masked(float val){ return val != 0.0; }\n\nvoid main(void)\n{\n// neighbor offsets\nvec2 fragDy[3] = vec2[3](vec2(0.0,-uDy), vec2(0.0,0.0), vec2(0.0,uDy));\n\n\n  vec2 lictc = tcoordVC.st;\n  vec4 lic[3];\n  bool dontUse = false;\n  float conv = 0.0;\n  for (int i=0; i<3; ++i)\n    {\n    vec2 tc = lictc + fragDy[i];\n    lic[i] = texture2D(texLIC, tc);\n    dontUse = dontUse || Masked(lic[i].g);\n    conv = conv + K[i] * lic[i].r;\n    }\n  // output is (conv, mask, skip, 1)\n  if (dontUse)\n    {\n    LICOutput = vec4(lic[1].rg, 1.0, 1.0);\n    }\n  else\n    {\n    LICOutput = vec4(conv, lic[1].gb, 1.0);\n    }\n  SeedOutput = vec4(0.0, 0.0, 0.0, 0.0);\n}\n")},e.executeLIC=(o,a,i,s,l,c)=>{if(t._openGLRenderWindow=l,t.context=l.getContext(),Object.assign(t,c),o[0]<=0||o[1]<=0)return null;const u=[1/o[0],1/o[1]];let d=t.stepSize*Math.sqrt(u[0]*u[0]+u[1]*u[1]);d<=0&&(d=1e-10);const p=t.context;let f=t.framebuffer;const g=f?.getSize();f&&g&&o[0]===g&&o[1]===g||(f=Gp.newInstance(),f.setOpenGLRenderWindow(t._openGLRenderWindow),f.saveCurrentBindingsAndBuffers(),f.create(...o),f.populateFramebuffer(),f.restorePreviousBindingsAndBuffers(),t.framebuffer=f),f.saveCurrentBindingsAndBuffers(),f.bind(),p.viewport(0,0,...o),p.scissor(0,0,...o),t.shadersNeedBuild&&(e.buildShaders(),t.shadersNeedBuild=!1),t.bufs?(t.bufs.setVectorTexture(a),t.bufs.setMaskVectorTexture(i),t.bufs.setNoiseTexture(s)):t.bufs=Eg.newInstance({openGLRenderWindow:l,doEEPass:t.enhancedLIC,doVTPass:t.transformVectors,vectorTexture:a,maskVectorTexture:i,noiseTexture:s,framebuffer:f,size:o});const m=[(s.getWidth()+1)/o[0],(s.getHeight()+1)/o[1]],h=1/o[0],v=1/o[1],T=t._openGLRenderWindow.getShaderCache();if(t.transformVectors){const e=t.VTProgram;T.readyShaderProgram(e),t.bufs.attachImageVectorBuffer(),e.setUniform2f("uTexSize",...o),e.setUniformi("texVectors",t.bufs.getVectorTextureUnit()),p.clearColor(0,0,0,0),p.clear(p.COLOR_BUFFER_BIT),t.bufs.renderQuad(o,e),t.bufs.detachImageVectorBuffer()}t.bufs.clearBuffers(t.enhancedLIC),t.bufs.activateVectorTextures(),t.bufs.activateNoiseTexture(0);const{LIC0ShaderProgram:x}=t;T.readyShaderProgram(x),x.setUniformi("uStepNo",0),x.setUniformi("uPassNo",0),x.setUniformf("uMaskThreshold",t.maskThreshold),x.setUniform2f("uNoiseBoundsPt1",...m),x.setUniformi("texMaskVectors",t.bufs.getMaskVectorTextureUnit()),x.setUniformi("texLIC",t.bufs.getLICTextureUnit()),x.setUniformi("texNoise",t.bufs.getNoiseTextureUnit(0)),r(t.bufs,o,x);const{LICIShaderProgram:y}=t;T.readyShaderProgram(y),y.setUniformi("uPassNo",0),y.setUniformf("uStepSize",-d),y.setUniform2f("uNoiseBoundsPt1",...m),y.setUniformi("texVectors",t.bufs.getImageVectorTextureUnit()),y.setUniformi("texNoise",t.bufs.getNoiseTextureUnit(0));for(let e=0;e<t.numberOfSteps;++e)n(y,t.bufs),r(t.bufs,o,y);T.readyShaderProgram(x),x.setUniformi("uStepNo",1),n(x,t.bufs),r(t.bufs,o,x),T.readyShaderProgram(y),y.setUniformf("uStepSize",d);for(let e=0;e<t.numberOfSteps;++e)n(y,t.bufs),r(t.bufs,o,y);t.bufs.deactivateNoiseTexture(0),t.bufs.deactivateVectorTextures();const{LICNShaderProgram:b}=t;if(T.readyShaderProgram(b),b.setUniformi("texLIC",t.bufs.getLICTextureUnit()),r(t.bufs,o,b),t.enhancedLIC){t.enhanceContrast!==Lg&&t.enhanceContrast!==Fg||e.contrastEnhance(!1,o),t.bufs.attachEEBuffer();const{EEProgram:a}=t;T.readyShaderProgram(a),a.setUniformi("texLIC",t.bufs.getLICTextureUnit()),a.setUniformf("uDx",h),a.setUniformf("uDy",v),t.bufs.renderQuad(o,a),t.bufs.detachEEBuffer(),t.bufs.detachBuffers(),t.bufs.clearBuffers(!1),t.bufs.activateVectorTextures(),t.bufs.activateNoiseTexture(1),T.readyShaderProgram(x),x.setUniformi("uStepNo",0),x.setUniformi("uPassNo",1),n(x,t.bufs),x.setUniformi("texNoise",t.bufs.getNoiseTextureUnit(1)),r(t.bufs,o,x),T.readyShaderProgram(y),y.setUniformi("uPassNo",1),y.setUniformf("uStepSize",-d),y.setUniformi("texNoise",t.bufs.getNoiseTextureUnit(1));const i=t.numberOfSteps/2;for(let e=0;e<i;++e)n(y,t.bufs),r(t.bufs,o,y);T.readyShaderProgram(x),x.setUniformi("uStepNo",1),n(x,t.bufs),r(t.bufs,o,x),T.readyShaderProgram(y),y.setUniformf("uStepSize",d);for(let e=0;e<i;++e)n(y,t.bufs),r(t.bufs,o,y);t.bufs.deactivateNoiseTexture(1),t.bufs.deactivateVectorTextures(),T.readyShaderProgram(b),b.setUniformi("texLIC",t.bufs.getLICTextureUnit()),b.setUniformi("texSeedPts",t.bufs.getSeedTextureUnit()),r(t.bufs,o,b)}if(t.antiAlias){const e=t.AAHProgram;T.readyShaderProgram(e),e.setUniformi("texLIC",t.bufs.getLICTextureUnit()),e.setUniformf("uDx",h);const a=t.AAVProgram;T.readyShaderProgram(a),a.setUniformi("texLIC",t.bufs.getLICTextureUnit()),a.setUniformf("uDy",v);for(let i=0;i<t.antiAlias;++i)T.readyShaderProgram(e),n(e,t.bufs),r(t.bufs,o,e),T.readyShaderProgram(a),n(a,t.bufs),r(t.bufs,o,a)}return t.enhanceContrast!==Lg&&t.enhanceContrast!==Fg||e.contrastEnhance(!0,o),t.bufs.detachBuffers(),f.restorePreviousBindingsAndBuffers(),t.bufs.getLastLICBuffer()},e.contrastEnhance=(n,o)=>{const a=t._openGLRenderWindow.getShaderCache();let{min:i,max:s}=e.getTextureMinMax(t.bufs.getLastLICBuffer(),o,t.context,t._openGLRenderWindow);(s<=i||s>1||i<0)&&(console.error("Invalid color range: ",i,s),i=0,s=1);let l=s-i;n&&(i+=l*t.lowLICContrastEnhancementFactor,s-=l*t.highLICContrastEnhancementFactor,l=s-i);const{CEProgram:c}=t;a.readyShaderProgram(c),c.setUniformi("texLIC",t.bufs.getLICTextureUnit()),c.setUniformf("uMin",i),c.setUniformf("uMaxMinDiff",l),r(t.bufs,o,c)}}(e,t)}var Ug={newInstance:sn.newInstance(Gg,"vtkLineIntegralConvolution2D"),extend:Gg};const _g={enableLIC:!1,nuberOfSteps:40,stepSize:.25,transformVectors:!0,normalizeVectors:!0,maskOnSurface:!1,maskThreshold:0,maskColor:[0,0,0],maskIntensity:0,enhancedLIC:!0,enhanceContrast:Vg,lowLICContrastEnhancementFactor:0,highLICContrastEnhancementFactor:0,lowColorContrastEnhancementFactor:0,highColorContrastEnhancementFactor:0,antiAlias:0,colorMode:0,LICIntensity:1,mapModeBias:0,noiseTextureSize:200,noiseTextureType:Ng,noiseGrainSize:8,noiseImpulseProbability:.1,noiseImpulseBackgroundValue:0,noiseGeneratorSeed:0,minNoiseValue:0,maxNoiseValue:1,numberOfNoiseLevels:2,shadersNeedBuilding:!0,reallocateTextures:!0,rebuildNoiseTexture:!1,viewPortScale:1};function Kg(e,t,n={}){Object.assign(t,_g,n),sn.obj(e,t),sn.setGet(e,t,["enableLIC","numberOfSteps","stepSize","normalizeVectors","transformVectors","maskOnSurface","maskThreshold","maskColor","maskIntensity","enhancedLIC","enhanceContrast","lowLICContrastEnhancementFactor","highLICContrastEnhancementFactor","lowColorContrastEnhancementFactor","highColorContrastEnhancementFactor","antiAlias","colorMode","LICIntensity","mapModeBias","noiseTextureSize","noiseTextureType","noiseGrainSize","minNoiseValue","maxNoiseValue","numberOfNoiseLevels","noiseImpulseProbability","noiseImpulseBackgroundValue","noiseGeneratorSeed","viewPortScale","rebuildNoiseTexture"]),function(e,t){t.classHierarchy.push("vtkSurfaceLICInterface")}(0,t)}var zg={newInstance:sn.newInstance(Kg,"vtkSurfaceLICInterface"),extend:Kg};const{Representation:Wg}=us;function Hg(e,t){t.classHierarchy.push("vtkOpenGLSurfaceLICInterface"),e.renderQuad=(e,n)=>{const r=t.licQuad,o=t.context;let a=t.licQuadVAO;a||(a=yd.newInstance(),a.setOpenGLRenderWindow(t._openGLRenderWindow),t.licQuadVAO=a),t.previousProgramHash!==n.getMd5Hash()&&(a.shaderProgramChanged(),r.getCABO().bind(),a.addAttributeArray(n,r.getCABO(),"vertexDC",r.getCABO().getVertexOffset(),r.getCABO().getStride(),t.context.FLOAT,3,t.context.FALSE),a.addAttributeArray(n,r.getCABO(),"tcoordDC",r.getCABO().getTCoordOffset(),r.getCABO().getStride(),t.context.FLOAT,2,t.context.FALSE),t.previousProgramHash=n.getMd5Hash()),o.drawArrays(o.TRIANGLES,0,r.getCABO().getElementCount()),a.release()},e.generateNoiseTexture=e=>{if(!t.noiseTexture||t.licInterface.getRebuildNoiseTexture()){t.licInterface.setRebuildNoiseTexture(!1),t.noiseTexture&&t.noiseTexture.releaseGraphicsResources(),mo(t.noiseGeneratorSeed,{global:!0});let n=[];const{noiseTextureType:r,noiseGrainSize:o,numberOfNoiseLevels:a,noiseImpulseProbability:i,noiseImpulseBackgroundValue:s,minNoiseValue:l,maxNoiseValue:c}=t.licInterface.get("noiseTextureType","noiseGrainSize","numberOfNoiseLevels","noiseImpulseProbability","noiseImpulseBackgroundValue","minNoiseValue","maxNoiseValue");if(r===Ng)n=function(e,t,n,r,o,a){const i=Math.max(0,Math.min(1,n)),s=Float32Array.from({length:e*e},(()=>{let e=0;if(1===i||Math.random()>1-i)for(let t=0;t<2048;++t)e+=Math.random();return e}));let l=0,c=2049;s.forEach((e=>{c=1===i?e<c?e:c:e<c&&e>0?e:c,l=e>l?e:l}));let u=l-c;0===u&&(c=0,u=0===l?1:l);const d=t-1,p=0!==d?1/d:0,f=a-o;return s.map((e=>{const n=e<c?e:(e-c)/u,i=Math.floor(n*t);return e>=c?1===t?a:o+(i>d?d:i)*p*f:r}))}(Math.floor(e/o),a,i,s,l,c);else n=function([e,t],n,r,o){const a=o-r;return Float32Array.from({length:e*t},(()=>{let e=Math.random();return e=Math.floor(e*n)/n,e=e*a+r,e>1?1:e<0?0:e}))}([Math.ceil(e/o),Math.ceil(e/o)],a,l,c);const u=1/o,d=Float32Array.from({length:e*e*4},((t,r)=>{const a=r/4;if(r%4==0){const t=Math.floor(a%e*u),r=Math.floor(a/e*u);return n[r*(e/o)+t]}return r%4==1||r%4==3?1:0})),p=Hd.newInstance({wrapS:Hd.Wrap.REPEAT,wrapT:Hd.Wrap.REPEAT,minificationFilter:Hd.Filter.NEAREST,magnificationFilter:Hd.Filter.NEAREST,generateMipMap:!1,openGLDataType:t.context.FLOAT,baseLevel:0,maxLevel:0,autoParameters:!1});p.setOpenGLRenderWindow(t._openGLRenderWindow),p.create2DFromRaw({width:e,height:e,numComps:4,dataType:"Float32Array",data:d}),p.activate(),p.sendParameters(),p.deactivate(),t.noiseTexture=p}},e.buildAShader=e=>t._openGLRenderWindow.getShaderCache().readyShaderProgramArray(Pg,e,""),e.allocateTextures=()=>{const n=Hd.Filter.NEAREST,r=Hd.Filter.LINEAR,o=t._openGLRenderWindow;t.geometryImage||(t.geometryImage=e.allocateTexture(o,n)),t.vectorImage||(t.vectorImage=e.allocateTexture(o,r)),t.maskVectorImage||(t.maskVectorImage=e.allocateTexture(o,r)),t.LICImage||(t.LICImage=e.allocateTexture(o,n)),t.RGBColorImage||(t.RGBColorImage=e.allocateTexture(o,n)),t.HSLColorImage||(t.HSLColorImage=e.allocateTexture(o,n)),t.depthTexture||(t.depthTexture=e.allocateDepthTexture(o))},e.allocateTexture=(e,n)=>{const r=t.context,o=Hd.newInstance({wrapS:Hd.Wrap.CLAMP_TO_EDGE,wrapT:Hd.Wrap.CLAMP_TO_EDGE,minificationFilter:n,magnificationFilter:n,generateMipmap:!1,openGLDataType:r.FLOAT,baseLevel:0,maxLevel:0,autoParameters:!1});return o.setOpenGLRenderWindow(e),o.setInternalFormat(r.RGBA32F),o.create2DFromRaw({width:t.size[0],height:t.size[1],numComps:4,dataType:"Float32Array",data:null}),o.activate(),o.sendParameters(),o.deactivate(),o},e.allocateDepthTexture=e=>{const n=t.context,r=Hd.newInstance({generateMipmap:!1,openGLDataType:n.FLOAT,autoParameters:!1});return r.setOpenGLRenderWindow(e),r.createDepthFromRaw({width:t.size[0],height:t.size[1],dataType:"Float32Array",data:null}),r.activate(),r.sendParameters(),r.deactivate(),r},e.createFBO=()=>{if(!t.framebuffer){t.licHelper=null;const e=Gp.newInstance();e.setOpenGLRenderWindow(t._openGLRenderWindow),e.saveCurrentBindingsAndBuffers(),e.create(...t.size),e.populateFramebuffer(),t.framebuffer=e,e.restorePreviousBindingsAndBuffers()}},e.completedGeometry=()=>{const e=t.context,n=t.framebuffer;n.removeColorBuffer(0),n.removeColorBuffer(1),n.removeColorBuffer(2),n.removeDepthBuffer(),e.drawBuffers([e.NONE]),n.restorePreviousBindingsAndBuffers()},e.buildAllShaders=()=>{t.shadersNeedBuilding&&(t.licColorPass=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkSurfaceLICMapper_fs2.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// This shader combines surface geometry, LIC, and  scalar colors.\n\n// the output of this shader\nlayout(location = 0) out vec4 RGBOutput;\nlayout(location = 1) out vec4 HSLOutput;\n\nuniform sampler2D texVectors;       // vectors, depth\nuniform sampler2D texGeomColors;    // scalar colors + lighting\nuniform sampler2D texLIC;           // image lic\nuniform int       uScalarColorMode; // select between blend, and map shader\nuniform float     uLICIntensity;    // blend shader: blending factor for lic'd colors\nuniform float     uMapBias;         // map shader: adjust the brightness of the result\nuniform float     uMaskIntensity;   // blending factor for mask color\nuniform vec3      uMaskColor;       // color for the masked out fragments\n\nin vec2 tcoordVC;\n\n/**\nConvert from RGB color space into HSL colorspace.\n*/\nvec3 RGBToHSL(vec3 RGB)\n{\n  vec3 HSL = vec3(0.0, 0.0, 0.0);\n\n  float RGBMin = min(min(RGB.r, RGB.g), RGB.b);\n  float RGBMax = max(max(RGB.r, RGB.g), RGB.b);\n  float RGBMaxMinDiff = RGBMax - RGBMin;\n\n  HSL.z = (RGBMax + RGBMin) / 2.0;\n\n  if (RGBMaxMinDiff == 0.0)\n    {\n    // Gray scale\n    HSL.x = 0.0;\n    HSL.y = 0.0;\n    }\n  else\n    {\n    // Color\n    if (HSL.z < 0.5)\n      HSL.y = RGBMaxMinDiff / (RGBMax + RGBMin);\n    else\n      HSL.y = RGBMaxMinDiff / (2.0 - RGBMax - RGBMin);\n\n    float dR\n      = (((RGBMax - RGB.r) / 6.0) + (RGBMaxMinDiff / 2.0)) / RGBMaxMinDiff;\n    float dG\n      = (((RGBMax - RGB.g) / 6.0) + (RGBMaxMinDiff / 2.0)) / RGBMaxMinDiff;\n    float dB\n      = (((RGBMax - RGB.b) / 6.0) + (RGBMaxMinDiff / 2.0)) / RGBMaxMinDiff;\n\n    if (RGB.r == RGBMax)\n      HSL.x = dB - dG;\n    else\n    if (RGB.g == RGBMax)\n      HSL.x = (1.0 / 3.0) + dR - dB;\n    else\n    if (RGB.b == RGBMax)\n      HSL.x = (2.0 / 3.0) + dG - dR;\n\n    if (HSL.x < 0.0)\n      HSL.x += 1.0;\n\n    if (HSL.x > 1.0)\n      HSL.x -= 1.0;\n    }\n\n  return HSL;\n}\n\n/**\nHelper for HSL to RGB conversion.\n*/\nfloat Util(float v1, float v2, float vH)\n{\n  if (vH < 0.0)\n    vH += 1.0;\n\n  if (vH > 1.0)\n     vH -= 1.0;\n\n  if ((6.0 * vH) < 1.0)\n    return (v1 + (v2 - v1) * 6.0 * vH);\n\n  if ((2.0 * vH) < 1.0)\n    return (v2);\n\n  if ((3.0 * vH) < 2.0)\n    return (v1 + (v2 - v1) * ((2.0 / 3.0) - vH) * 6.0);\n\n  return v1;\n}\n\n/**\nConvert from HSL space into RGB space.\n*/\nvec3 HSLToRGB(vec3 HSL)\n{\n  vec3 RGB;\n  if (HSL.y == 0.0)\n    {\n    // Gray\n    RGB.r = HSL.z;\n    RGB.g = HSL.z;\n    RGB.b = HSL.z;\n    }\n  else\n    {\n    // Chromatic\n    float v2;\n    if (HSL.z < 0.5)\n      v2 = HSL.z * (1.0 + HSL.y);\n    else\n      v2 = (HSL.z + HSL.y) - (HSL.y * HSL.z);\n\n    float v1 = 2.0 * HSL.z - v2;\n\n    RGB.r = Util(v1, v2, HSL.x + (1.0 / 3.0));\n    RGB.g = Util(v1, v2, HSL.x);\n    RGB.b = Util(v1, v2, HSL.x - (1.0 / 3.0));\n    }\n\n  return RGB.rgb;\n}\n\nvoid main()\n{\n  vec4 lic = texture2D(texLIC, tcoordVC.st);\n  vec4 geomColor = texture2D(texGeomColors, tcoordVC.st);\n\n  // depth is used to determine which fragment belong to us\n  // and we can change\n  float depth = texture2D(texVectors, tcoordVC.st).a;\n\n  vec3 fragColorRGB;\n  float valid;\n  if (depth > 1.0e-3)\n    {\n    // we own it\n    // shade LIC'ed geometry, or apply mask\n    if (lic.g!=0.0)\n      {\n      // it's masked\n      // apply fragment mask\n      fragColorRGB = uMaskIntensity * uMaskColor + (1.0 - uMaskIntensity) * geomColor.rgb;\n      valid = 0.0;\n      }\n    else\n      {\n      if (uScalarColorMode==0)\n        {\n        // blend with scalars\n        fragColorRGB = lic.rrr * uLICIntensity + geomColor.rgb * (1.0 - uLICIntensity);\n        }\n      else\n        {\n        // multiply with scalars\n        fragColorRGB = geomColor.rgb * clamp((uMapBias + lic.r), 0.0, 1.0);\n        }\n      if (lic.b != 0.0)\n        {\n        // didn't have the required guard pixels\n        // don't consider it in min max estimation\n        // for histpgram stretching\n        valid = 0.0;\n        }\n      else\n        {\n        // ok to use in min/max estimates for histogram\n        // stretching\n        valid = 1.0;\n        }\n      }\n    }\n  else\n    {\n    // we don't own it\n    // pass through scalars\n    fragColorRGB = geomColor.rgb;\n    valid = 0.0;\n    }\n\n  // if no further stages this texture is\n  // copied to the screen\n  RGBOutput = vec4(fragColorRGB, geomColor.a);\n\n  // if further stages, move to hsl space for contrast\n  // enhancement. encoding validity saves moving a texture to the cpu\n  vec3 fragColorHSL = RGBToHSL(fragColorRGB);\n  HSLOutput = vec4(fragColorHSL, valid);\n}\n"),t.licCopyPass=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkSurfaceLICMapper_DCpy.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// This shader copies fragments and depths to the output buffer\n\n// the output of this shader\n//VTK::Output::Dec\n\nuniform sampler2D texDepth;     // z values from vertex shader\nuniform sampler2D texRGBColors; // final rgb LIC colors\n\nin vec2 tcoordVC;\n\nvoid main()\n{\n  gl_FragDepth = texture2D(texDepth, tcoordVC).x;\n  gl_FragData[0] = texture2D(texRGBColors, tcoordVC);\n\n  // since we render a screen aligned quad\n  // we're going to be writing fragments\n  // not touched by the original geometry\n  // it's critical not to modify those\n  // fragments.\n  if (gl_FragDepth == 1.0)\n    {\n    discard;\n    }\n}\n"),t.enhanceContrastPass=e.buildAShader("//VTK::System::Dec\n\n//=========================================================================\n//\n//  Program:   Visualization Toolkit\n//  Module:    vtkSurfaceLICMapper_CE.glsl\n//\n//  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n//  All rights reserved.\n//  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n//\n//     This software is distributed WITHOUT ANY WARRANTY; without even\n//     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n//     PURPOSE.  See the above copyright notice for more information.\n//\n//=========================================================================\n\n// color contrast enhance stage implemented via histogram stretching\n// on lightness channel. if the min and max are tweaked it can generate\n// out-of-range values these will be clamped in 0 to 1\n\n// the output of this shader\n//VTK::Output::Dec\n\nuniform sampler2D texGeomColors; // scalars + lighting\nuniform sampler2D texLIC;        // image lic, mask\nuniform sampler2D texHSLColors;  // hsla colors\n\nuniform float     uLMin;         // min lightness over all fragments\nuniform float     uLMaxMinDiff;  // max - min lightness over all fragments\n\nin vec2 tcoordVC;\n\nvec3 HSLToRGB(vec3 HSL)\n{\n  vec3 RGB;\n  float v;\n  float h = HSL.x;\n  float sl = HSL.y;\n  float l = HSL.z;\n\n  v = (l <= 0.5) ? (l * (1.0 + sl)) : (l + sl - l * sl);\n  if (v <= 0.0) {\n    RGB = vec3(0.0,0.0,0.0);\n  } else {\n    float m;\n    int sextant;\n    float fract, vsf, mid1, mid2;\n\n    m = l + l - v;\n    h *= 6.0;\n    sextant = int(h);\n    fract = h - float(sextant);\n\n    vsf = (v - m) * fract;\n    mid1 = m + vsf;\n    mid2 = v - vsf;\n    switch (sextant) {\n      case 0: RGB.r = v; RGB.g = mid1; RGB.b = m; break;\n      case 1: RGB.r = mid2; RGB.g = v; RGB.b = m; break;\n      case 2: RGB.r = m; RGB.g = v; RGB.b = mid1; break;\n      case 3: RGB.r = m; RGB.g = mid2; RGB.b = v; break;\n      case 4: RGB.r = mid1; RGB.g = m; RGB.b = v; break;\n      case 5: RGB.r = v; RGB.g = m; RGB.b = mid2; break;\n    }\n  }\n  return RGB;\n}\n\nvoid main()\n{\n  // lookup hsl color , mask\n  vec4 fragColor = texture2D(texHSLColors, tcoordVC.st);\n\n  // don't modify masked fragments (masked => lic.g==1)\n  vec4 lic = texture2D(texLIC, tcoordVC.st);\n  if (lic.g==0.0)\n    {\n    // normalize lightness channel\n    fragColor.z = clamp((fragColor.z - uLMin)/uLMaxMinDiff, 0.0, 1.0);\n    }\n\n  // back into rgb space\n  fragColor.rgb = HSLToRGB(fragColor.xyz);\n\n  // add alpha\n  vec4 geomColor = texture2D(texGeomColors, tcoordVC.st);\n  fragColor.a = geomColor.a;\n\n  gl_FragData[0] = fragColor;\n}\n"),t.shadersNeedBuilding=!1)},e.initializeResources=()=>{e.createFBO(),e.generateNoiseTexture(t.licInterface.getNoiseTextureSize()),e.allocateTextures(),e.buildAllShaders(),t.licQuad||(t.licQuad=function(e){const t=Sd.newInstance();t.setOpenGLRenderWindow(e);const n=new Float32Array(12);for(let e=0;e<4;e++)n[3*e]=e%2*2-1,n[3*e+1]=e>1?1:-1,n[3*e+2]=0;const r=new Float32Array([0,0,1,0,0,1,1,1]),o=new Uint16Array(8);o[0]=3,o[1]=0,o[2]=1,o[3]=3,o[4]=3,o[5]=0,o[6]=3,o[7]=2;const a=Is.newInstance({numberOfComponents:3,values:n});a.setName("points");const i=Is.newInstance({numberOfComponents:1,values:o}),s=Is.newInstance({numberOfComponents:2,values:r});return t.getCABO().createVBO(i,"polys",Wg.SURFACE,{points:a,cellOffset:0,tcoords:s}),t}(t._openGLRenderWindow)),t.licHelper||(t.licHelper=Ug.newInstance())},e.prepareForGeometry=()=>{const e=t.framebuffer;e.saveCurrentBindingsAndBuffers(),e.bind(),t.geometryImage.activate(),t.vectorImage.activate(),t.maskVectorImage.activate(),e.removeColorBuffer(0),e.removeColorBuffer(2),e.removeColorBuffer(3),e.setColorBuffer(t.geometryImage,0),e.setColorBuffer(t.vectorImage,2),e.setColorBuffer(t.maskVectorImage,3),e.setDepthBuffer(t.depthTexture);const n=t.context;n.drawBuffers([n.COLOR_ATTACHMENT0,n.NONE,n.COLOR_ATTACHMENT2,n.COLOR_ATTACHMENT3]),n.viewport(0,0,...t.size),n.scissor(0,0,...t.size),n.disable(n.BLEND),n.disable(n.DEPTH_TEST),n.disable(n.SCISSOR_TEST),n.clearColor(0,0,0,0),n.clear(n.DEPTH_BUFFER_BIT|n.COLOR_BUFFER_BIT)},e.copyToScreen=n=>{t.RGBColorImage.activate(),t.depthTexture.activate(),t.licCopyPass||e.initializeResources();const r=t.licCopyPass;t._openGLRenderWindow.getShaderCache().readyShaderProgram(r);const o=t.context;o.viewport(0,0,...n),o.scissor(0,0,...n),o.disable(o.BLEND),o.enable(o.DEPTH_TEST),o.disable(o.SCISSOR_TEST),r.setUniformi("texDepth",t.depthTexture.getTextureUnit()),r.setUniformi("texRGBColors",t.RGBColorImage.getTextureUnit()),e.renderQuad(n,r),t.RGBColorImage.deactivate(),t.depthTexture.deactivate()},e.combineColorsAndLIC=()=>{const n=t.context,r=t.framebuffer;r.saveCurrentBindingsAndBuffers(),r.bind(),r.create(...t.size),r.removeColorBuffer(0),r.removeColorBuffer(1),r.setColorBuffer(t.RGBColorImage,0),r.setColorBuffer(t.HSLColorImage,1),n.drawBuffers([n.COLOR_ATTACHMENT0,n.COLOR_ATTACHMENT1]),n.disable(n.DEPTH_TEST),n.clearColor(0,0,0,0),n.clear(n.COLOR_BUFFER_BIT),t.vectorImage.activate(),t.geometryImage.activate(),t.LICImage.activate(),t.licColorPass||e.initializeResources();const o=t.licColorPass;t._openGLRenderWindow.getShaderCache().readyShaderProgram(o),o.setUniformi("texVectors",t.vectorImage.getTextureUnit()),o.setUniformi("texGeomColors",t.geometryImage.getTextureUnit());const{colorMode:a,LICIntensity:i,mapModeBias:s,maskIntensity:l,maskColor:c,enhanceContrast:u,lowColorContrastEnhancementFactor:d,highColorContrastEnhancementFactor:p}=t.licInterface.get("colorMode","LICIntensity","mapModeBias","maskIntensity","maskColor","enhanceContrast","lowColorContrastEnhancementFactor","highColorContrastEnhancementFactor");if(o.setUniformi("texLIC",t.LICImage.getTextureUnit()),o.setUniformi("uScalarColorMode",a),o.setUniformf("uLICIntensity",i),o.setUniformf("uMapBias",s),o.setUniformf("uMaskIntensity",l),o.setUniform3f("uMaskColor",...c),e.renderQuad(t.size,o),t.vectorImage.deactivate(),t.geometryImage.deactivate(),t.LICImage.deactivate(),r.removeColorBuffer(0),r.removeColorBuffer(1),n.drawBuffers([n.NONE]),u===Bg||u===Fg){let o=0,a=1,i=a-o;o+=i*d,a-=i*p,i=a-o,r.setColorBuffer(t.RGBColorImage),n.drawBuffers([n.COLOR_ATTACHMENT0]),t.geometryImage.activate(),t.HSLColorImage.activate(),t.LICImage.activate(),t.enhanceContrastPass||e.initializeResources();const{enhanceContrastPass:s}=t;t._openGLRenderWindow.getShaderCache().readyShaderProgram(s),s.setUniformi("texGeomColors",t.geometryImage.getTextureUnit()),s.setUniformi("texHSLColors",t.HSLColorImage.getTextureUnit()),s.setUniformi("texLIC",t.LICImage.getTextureUnit()),s.setUniformf("uLMin",o),s.setUniformf("uLMaxMinDiff",i),e.renderQuad(t.size,s),t.geometryImage.deactivate(),t.HSLColorImage.deactivate(),t.LICImage.deactivate(),r.removeColorBuffer(0),n.drawBuffers([n.NONE])}r.restorePreviousBindingsAndBuffers()},e.applyLIC=()=>{const e=t.licInterface.get("stepSize","numberOfSteps","enhancedLIC","enhanceContrast","lowLICContrastEnhancementFactor","highLICContrastEnhancementFactor","antiAlias","normalizeVectors","maskThreshold","transformVectors"),n=t.licHelper.executeLIC(t.size,t.vectorImage,t.maskVectorImage,t.noiseTexture,t._openGLRenderWindow,e);if(!n)return console.error("Failed to compute image LIC"),void(t.LICImage=null);t.LICImage=n},e.setSize=n=>{Array.isArray(n)&&2===n.length&&(t.size&&t.size[0]===n[0]&&t.size[1]===n[1]||(t.size=n,e.releaseGraphicsResources()))},e.releaseGraphicsResources=()=>{t.geometryImage&&(t.geometryImage.releaseGraphicsResources(),t.geometryImage=null),t.vectorImage&&(t.vectorImage.releaseGraphicsResources(),t.vectorImage=null),t.maskVectorImage&&(t.maskVectorImage.releaseGraphicsResources(),t.maskVectorImage=null),t.LICImage&&(t.LICImage.releaseGraphicsResources(),t.LICImage=null),t.RGBColorImage&&(t.RGBColorImage.releaseGraphicsResources(),t.RGBColorImage=null),t.HSLColorImage&&(t.HSLColorImage.releaseGraphicsResources(),t.HSLColorImage=null),t.depthTexture&&(t.depthTexture.releaseGraphicsResources(),t.depthTexture=null),t.framebuffer&&(t.framebuffer.releaseGraphicsResources(),t.framebuffer=null)}}const jg={context:null,shadersNeedBuilding:!0,reallocateTextures:!0,size:null,licInterface:null};function Xg(e,t,n={}){Object.assign(t,jg,n),zg.extend(e,t,n),sn.obj(e,t),sn.setGet(e,t,["context","_openGLRenderWindow","reallocateTextures","licInterface","size"]),sn.moveToProtected(e,t,["openGLRenderWindow"]),Hg(e,t)}var qg={newInstance:sn.newInstance(Xg,"vtkSurfaceLICInterface"),extend:Xg};const{vtkErrorMacro:Yg}=ln;const Jg={canDrawLIC:!1,rebuildLICShaders:!1,rebuildLICBuffers:!1,openGLLicInterface:null};const Zg=Xt((function(e,t,n={}){Object.assign(t,Jg,n),up.extend(e,t,n),function(e,t){t.classHierarchy.push("vtkOpenGLSurfaceLICMapper");const n={...e};e.getNeedToRebuildShaders=(e,r,o)=>t.rebuildLICShaders||n.getNeedToRebuildShaders(e,r,o),e.replaceShaderValues=(e,r,o)=>{const a=t.lastBoundBO.getReferenceByName("lastLightComplexity");let i=e.Vertex,s=e.Fragment;const l=t.renderable.getInputArrayToProcess(0);if(l&&t.canDrawLIC){s=vd.substitute(s,"//VTK::Output::Dec",["//VTK::Output::Dec","layout(location = 2) out vec4 vectorTexture;","layout(location = 3) out vec4 maskVectorTexture;"]).result;const n=`${l.getName()}MC`;0===a&&t.lastBoundBO.set({lastLightComplexity:1},!0),i=vd.substitute(i,"//VTK::TCoord::Dec",[`attribute vec3 ${n};`,"out vec3 licOutput;","//VTK::TCoord::Dec"]).result,i=vd.substitute(i,"//VTK::TCoord::Impl",[`licOutput = ${n};`,"//VTK::TCoord::Impl"]).result,s=vd.substitute(s,"//VTK::TCoord::Dec",["uniform int uMaskOnSurface;","uniform mat3 normalMatrix;","in vec3 licOutput;","//VTK::TCoord::Dec"]).result,s=vd.substitute(s,"//VTK::TCoord::Impl",["// projected vectors","  vec3 tcoordLIC = normalMatrix * licOutput;","  vec3 normN = normalize(normalVCVSOutput);","  float k = dot(tcoordLIC, normN);","  vec3 projected = (tcoordLIC - k*normN);","  vectorTexture = vec4(projected.x, projected.y, 0.0 , 1.0);","// vectors for fragment masking","  if (uMaskOnSurface == 0)","    {","    maskVectorTexture = vec4(licOutput, 1.0);","    }","  else","    {","    maskVectorTexture = vec4(projected.x, projected.y, 0.0 , 1.0);","    }","//VTK::TCoord::Impl"],!1).result,e.Vertex=i}t.rebuildLICShaders=!1,e.Fragment=s,n.replaceShaderValues(e,r,o),a>0&&t.lastBoundBO.set({lastLightComplexity:a},!0)},e.setMapperShaderParameters=(e,r,o)=>{n.setMapperShaderParameters(e,r,o),t.canDrawLIC&&e.getProgram().setUniformi("uMaskOnSurface",t.maskOnSurface)},e.getNeedToRebuildBufferObjects=(e,r)=>t.rebuildLICBuffers||n.getNeedToRebuildBufferObjects(e,r),e.buildBufferObjects=(e,r)=>{if(t.canDrawLIC){const e=t.renderable.getInputArrayToProcess(0);e&&e.getNumberOfComponents()>1&&t.renderable.setCustomShaderAttributes([e.getName()])}t.rebuildLICBuffers=!1,n.buildBufferObjects(e,r)},e.pushState=e=>{t.stateCache={[e.BLEND]:e.isEnabled(e.BLEND),[e.DEPTH_TEST]:e.isEnabled(e.DEPTH_TEST),[e.SCISSOR_TEST]:e.isEnabled(e.SCISSOR_TEST),[e.CULL_FACE]:e.isEnabled(e.CULL_FACE)}},e.popState=e=>{const n=n=>t.stateCache[n]?e.enable(n):e.disable(n);n(e.BLEND),n(e.DEPTH_TEST),n(e.SCISSOR_TEST),n(e.CULL_FACE)},e.renderPiece=(r,o)=>{let a=!0;t._openGLRenderWindow.getWebgl2()||(Yg("SurfaceLICMapper Requires WebGL 2"),a=!1),t.context.getExtension("EXT_color_buffer_float")&&t.context.getExtension("OES_texture_float_linear")||(Yg("SurfaceLICMapper requires the EXT_color_buffer_float and OES_texture_float_linear WebGL2 extensions."),a=!1),t.currentInput=t.renderable.getInputData(),t.currentInput||(Yg("No input"),a=!1);let i=t.renderable.getLicInterface();i||(i=zg.newInstance(),t.renderable.setLicInterface(i)),t.openGLLicInterface||(t.openGLLicInterface=qg.newInstance()),i!==t.openGLLicInterface.getLicInterface()&&t.openGLLicInterface.setLicInterface(i);const s=t.renderable.getInputArrayToProcess(0);if(i.getEnableLIC()&&(!s||s.getNumberOfComponents()<2)&&(Yg("No vector input array"),a=!1),i.getEnableLIC()||(a=!1),t.canDrawLIC!==a&&(t.rebuildLICShaders=!0,t.rebuildLICBuffers=!0),t.canDrawLIC=a,!a||!i.getEnableLIC())return void n.renderPiece(r,o);const l=t.context,c=o.getProperty().getBackfaceCulling(),u=o.getProperty().getFrontfaceCulling();c||u?u?(t._openGLRenderWindow.enableCullFace(),l.cullFace(l.FRONT)):(t._openGLRenderWindow.enableCullFace(),l.cullFace(l.BACK)):t._openGLRenderWindow.disableCullFace();const d=t._openGLRenderWindow.getSize(),p=d.map((e=>Math.round(e*i.getViewPortScale())));t.openGLLicInterface.setSize(p),t.openGLLicInterface.setOpenGLRenderWindow(t._openGLRenderWindow),t.openGLLicInterface.setContext(t.context),e.pushState(t.context),t.openGLLicInterface.initializeResources(),t.openGLLicInterface.prepareForGeometry(),e.popState(t.context),n.renderPieceStart(r,o),n.renderPieceDraw(r,o),n.renderPieceFinish(r,o),e.pushState(t.context),t.VBOBuildTime.modified(),t.openGLLicInterface.completedGeometry(),t.context.disable(t.context.CULL_FACE),t.openGLLicInterface.applyLIC(),t.openGLLicInterface.combineColorsAndLIC(),t.openGLLicInterface.copyToScreen(d),e.popState(t.context)}}(e,t),Gt(e,t,["openGLLicInterface"])}),"vtkOpenGLSurfaceLICMapper");vn("vtkSurfaceLICMapper",Zg);const{vtkErrorMacro:Qg}=ln;const $g={};const em=Xt((function(e,t,n={}){Object.assign(t,$g,n),up.extend(e,t,n),function(e,t){t.classHierarchy.push("vtkOpenGLSphereMapper");const n={...e};e.getShaderTemplate=(e,t,n)=>{e.Vertex="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkSphereMapperVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n// this shader implements imposters in OpenGL for Spheres\n\nattribute vec4 vertexMC;\nattribute vec2 offsetMC;\n\n// optional normal declaration\n//VTK::Normal::Dec\n\n//VTK::Picking::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\nuniform mat3 normalMatrix; // transform model coordinate directions to view coordinates\n\n// material property values\n//VTK::Color::Dec\n\n// clipping plane vars\n//VTK::Clip::Dec\n\n// camera and actor matrix values\n//VTK::Camera::Dec\n\nvarying vec4 vertexVCVSOutput;\nvarying float radiusVCVSOutput;\nvarying vec3 centerVCVSOutput;\n\nuniform int cameraParallel;\nuniform float scaleFactor;\n\nvoid main()\n{\n  //VTK::Picking::Impl\n\n  //VTK::Color::Impl\n\n  //VTK::Normal::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Clip::Impl\n\n  // compute the projected vertex position\n  vec2 scaledOffsetMC = scaleFactor * offsetMC;\n  vertexVCVSOutput = MCVCMatrix * vertexMC;\n  centerVCVSOutput = vertexVCVSOutput.xyz;\n  radiusVCVSOutput = length(scaledOffsetMC)*0.5;\n\n  // make the triangle face the camera\n  if (cameraParallel == 0)\n    {\n    vec3 dir = normalize(-vertexVCVSOutput.xyz);\n    vec3 base2 = normalize(cross(dir,vec3(1.0,0.0,0.0)));\n    vec3 base1 = cross(base2,dir);\n    vertexVCVSOutput.xyz = vertexVCVSOutput.xyz + scaledOffsetMC.x*base1 + scaledOffsetMC.y*base2;\n    }\n  else\n    {\n    // add in the offset\n    vertexVCVSOutput.xy = vertexVCVSOutput.xy + scaledOffsetMC;\n    }\n\n  gl_Position = VCPCMatrix * vertexVCVSOutput;\n}\n",e.Fragment=Xd,e.Geometry=""},e.replaceShaderValues=(e,r,o)=>{let a=e.Vertex,i=e.Fragment;a=vd.substitute(a,"//VTK::Camera::Dec",["uniform mat4 VCPCMatrix;\n","uniform mat4 MCVCMatrix;"]).result,i=vd.substitute(i,"//VTK::PositionVC::Dec",["varying vec4 vertexVCVSOutput;"]).result,i=vd.substitute(i,"//VTK::PositionVC::Impl",["vec4 vertexVC = vertexVCVSOutput;\n"]).result,i=vd.substitute(i,"//VTK::Normal::Dec",["uniform float invertedDepth;\n","uniform int cameraParallel;\n","varying float radiusVCVSOutput;\n","varying vec3 centerVCVSOutput;\n","uniform mat4 VCPCMatrix;\n"]).result;let s="";t.context.getExtension("EXT_frag_depth")&&(s="gl_FragDepthEXT = (pos.z / pos.w + 1.0) / 2.0;\n"),t._openGLRenderWindow.getWebgl2()&&(s="gl_FragDepth = (pos.z / pos.w + 1.0) / 2.0;\n"),i=vd.substitute(i,"//VTK::Depth::Impl",["  vec3 EyePos;\n","  vec3 EyeDir;\n","  if (cameraParallel != 0) {\n","    EyePos = vec3(vertexVC.x, vertexVC.y, vertexVC.z + 3.0*radiusVCVSOutput);\n","    EyeDir = vec3(0.0,0.0,-1.0); }\n","  else {\n","    EyeDir = vertexVC.xyz;\n","    EyePos = vec3(0.0,0.0,0.0);\n","    float lengthED = length(EyeDir);\n","    EyeDir = normalize(EyeDir);\n","    if (lengthED > radiusVCVSOutput*3.0) {\n","      EyePos = vertexVC.xyz - EyeDir*3.0*radiusVCVSOutput; }\n","    }\n","  EyePos = EyePos - centerVCVSOutput;\n","  EyePos = EyePos/radiusVCVSOutput;\n","  float b = 2.0*dot(EyePos,EyeDir);\n","  float c = dot(EyePos,EyePos) - 1.0;\n","  float d = b*b - 4.0*c;\n","  vec3 normalVCVSOutput = vec3(0.0,0.0,1.0);\n","  if (d < 0.0) { discard; }\n","  else {\n","    float t = (-b - invertedDepth*sqrt(d))*0.5;\n","    normalVCVSOutput = invertedDepth*normalize(EyePos + t*EyeDir);\n","    vertexVC.xyz = normalVCVSOutput*radiusVCVSOutput + centerVCVSOutput;\n","    }\n","  vec4 pos = VCPCMatrix * vertexVC;\n",s]).result,i=vd.substitute(i,"//VTK::Normal::Impl","").result,t.haveSeenDepthRequest&&(i=vd.substitute(i,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float computedZ = (pos.z / pos.w + 1.0) / 2.0;","float iz = floor(computedZ * 65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); }"]).result),e.Vertex=a,e.Fragment=i,n.replaceShaderValues(e,r,o)},e.setMapperShaderParameters=(e,r,o)=>{if(e.getCABO().getElementCount()&&(t.VBOBuildTime>e.getAttributeUpdateTime().getMTime()||e.getShaderSourceTime().getMTime()>e.getAttributeUpdateTime().getMTime())&&e.getProgram().isAttributeUsed("offsetMC")&&(e.getVAO().addAttributeArray(e.getProgram(),e.getCABO(),"offsetMC",12,e.getCABO().getStride(),t.context.FLOAT,2,!1)||Qg("Error setting 'offsetMC' in shader VAO.")),e.getProgram().isUniformUsed("invertedDepth")&&e.getProgram().setUniformf("invertedDepth",t.invert?-1:1),e.getProgram().isUniformUsed("scaleFactor")){const n=t.currentInput.getPointData();null!=t.renderable.getScaleArray()&&n.hasArray(t.renderable.getScaleArray())?e.getProgram().setUniformf("scaleFactor",t.renderable.getScaleFactor()):e.getProgram().setUniformf("scaleFactor",1)}n.setMapperShaderParameters(e,r,o)},e.setCameraShaderParameters=(e,n,r)=>{const o=e.getProgram(),a=n.getActiveCamera(),i=t.openGLCamera.getKeyMatrices(n);o.isUniformUsed("VCPCMatrix")&&o.setUniformMatrix("VCPCMatrix",i.vcpc);const s=new Float64Array(16);if(o.isUniformUsed("MCVCMatrix"))if(r.getIsIdentity())T(s,i.wcvc),e.getCABO().getCoordShiftAndScaleEnabled()&&A(s,s,e.getCABO().getInverseShiftAndScaleMatrix()),o.setUniformMatrix("MCVCMatrix",s);else{const n=t.openGLActor.getKeyMatrices();A(s,i.wcvc,n.mcwc),e.getCABO().getCoordShiftAndScaleEnabled()&&A(s,s,e.getCABO().getInverseShiftAndScaleMatrix()),o.setUniformMatrix("MCVCMatrix",s)}o.isUniformUsed("cameraParallel")&&e.getProgram().setUniformi("cameraParallel",a.getParallelProjection())},e.getOpenGLMode=(e,n)=>t.context.TRIANGLES,e.buildBufferObjects=(e,n)=>{const r=t.currentInput;if(null===r)return;t.renderable.mapScalars(r,1);const o=t.renderable.getColorMapColors(),a=t.primitives[t.primTypes.Tris].getCABO(),i=r.getPointData(),s=r.getPoints(),l=s.getNumberOfPoints(),c=s.getData();let u=null;null!=t.renderable.getScaleArray()&&i.hasArray(t.renderable.getScaleArray())&&(u=i.getArray(t.renderable.getScaleArray()).getData());let d=null,p=0,f=null;o?(p=o.getNumberOfComponents(),a.setColorOffset(0),a.setColorBOStride(4),d=o.getData(),f=new Uint8Array(3*l*4),a.getColorBO()||a.setColorBO(nd.newInstance()),a.getColorBO().setOpenGLRenderWindow(t._openGLRenderWindow)):a.getColorBO()&&a.setColorBO(null),a.setColorComponents(p);const g=new Float32Array(5*l*3);a.setStride(20);const m=Math.cos(wo(30));let h=0,v=0;const{useShiftAndScale:T,coordShift:x,coordScale:y}=rd(s);T&&a.setCoordShiftAndScale(x,y);let b=0,A=0;for(let e=0;e<l;++e){let n=t.renderable.getRadius();u&&(n=u[e]),h=3*e;const r=(c[h++]-x[0])*y[0],o=(c[h++]-x[1])*y[1],a=(c[h++]-x[2])*y[2];g[b++]=r,g[b++]=o,g[b++]=a,g[b++]=-2*n*m,g[b++]=-n,d&&(v=e*p,f[A++]=d[v],f[A++]=d[v+1],f[A++]=d[v+2],f[A++]=d[v+3]),g[b++]=r,g[b++]=o,g[b++]=a,g[b++]=2*n*m,g[b++]=-n,d&&(f[A++]=d[v],f[A++]=d[v+1],f[A++]=d[v+2],f[A++]=d[v+3]),g[b++]=r,g[b++]=o,g[b++]=a,g[b++]=0,g[b++]=2*n,d&&(f[A++]=d[v],f[A++]=d[v+1],f[A++]=d[v+2],f[A++]=d[v+3])}a.setElementCount(b/5),a.upload(g,Zu.ARRAY_BUFFER),o&&a.getColorBO().upload(f,Zu.ARRAY_BUFFER),t.VBOBuildTime.modified()}}(e,t)}),"vtkOpenGLSphereMapper");vn("vtkSphereMapper",em);const{vtkErrorMacro:tm}=ln;const nm={};const rm=Xt((function(e,t,n={}){Object.assign(t,nm,n),up.extend(e,t,n),function(e,t){t.classHierarchy.push("vtkOpenGLStickMapper");const n={...e};e.getShaderTemplate=(e,t,n)=>{e.Vertex="//VTK::System::Dec\n\n/*=========================================================================\n\n  Program:   Visualization Toolkit\n  Module:    vtkStickMapperVS.glsl\n\n  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen\n  All rights reserved.\n  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.\n\n     This software is distributed WITHOUT ANY WARRANTY; without even\n     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR\n     PURPOSE.  See the above copyright notice for more information.\n\n=========================================================================*/\n// this shader implements imposters in OpenGL for Sticks\n\nattribute vec4 vertexMC;\nattribute vec3 orientMC;\nattribute vec4 offsetMC;\nattribute float radiusMC;\n\n// optional normal declaration\n//VTK::Normal::Dec\n\n//VTK::Picking::Dec\n\n// Texture coordinates\n//VTK::TCoord::Dec\n\nuniform mat3 normalMatrix; // transform model coordinate directions to view coordinates\n\n// material property values\n//VTK::Color::Dec\n\n// clipping plane vars\n//VTK::Clip::Dec\n\n// camera and actor matrix values\n//VTK::Camera::Dec\n\nvarying vec4 vertexVCVSOutput;\nvarying float radiusVCVSOutput;\nvarying float lengthVCVSOutput;\nvarying vec3 centerVCVSOutput;\nvarying vec3 orientVCVSOutput;\n\nuniform int cameraParallel;\n\nvoid main()\n{\n  //VTK::Picking::Impl\n\n  //VTK::Color::Impl\n\n  //VTK::Normal::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Clip::Impl\n\n  vertexVCVSOutput = MCVCMatrix * vertexMC;\n  centerVCVSOutput = vertexVCVSOutput.xyz;\n  radiusVCVSOutput = radiusMC;\n  lengthVCVSOutput = length(orientMC);\n  orientVCVSOutput = normalMatrix * normalize(orientMC);\n\n  // make sure it is pointing out of the screen\n  if (orientVCVSOutput.z < 0.0)\n    {\n    orientVCVSOutput = -orientVCVSOutput;\n    }\n\n  // make the basis\n  vec3 xbase;\n  vec3 ybase;\n  vec3 dir = vec3(0.0,0.0,1.0);\n  if (cameraParallel == 0)\n    {\n    dir = normalize(-vertexVCVSOutput.xyz);\n    }\n  if (abs(dot(dir,orientVCVSOutput)) == 1.0)\n    {\n    xbase = normalize(cross(vec3(0.0,1.0,0.0),orientVCVSOutput));\n    ybase = cross(xbase,orientVCVSOutput);\n    }\n  else\n    {\n    xbase = normalize(cross(orientVCVSOutput,dir));\n    ybase = cross(orientVCVSOutput,xbase);\n    }\n\n  vec3 offsets = offsetMC.xyz*2.0-1.0;\n  vertexVCVSOutput.xyz = vertexVCVSOutput.xyz +\n    radiusVCVSOutput*offsets.x*xbase +\n    radiusVCVSOutput*offsets.y*ybase +\n    0.5*lengthVCVSOutput*offsets.z*orientVCVSOutput;\n\n  gl_Position = VCPCMatrix * vertexVCVSOutput;\n}\n",e.Fragment=Xd,e.Geometry=""},e.replaceShaderValues=(e,r,o)=>{let a=e.Vertex,i=e.Fragment;a=vd.substitute(a,"//VTK::Camera::Dec",["uniform mat4 VCPCMatrix;\n","uniform mat4 MCVCMatrix;"]).result,i=vd.substitute(i,"//VTK::PositionVC::Dec","varying vec4 vertexVCVSOutput;").result,i=vd.substitute(i,"//VTK::PositionVC::Impl","  vec4 vertexVC = vertexVCVSOutput;\n").result,i=vd.substitute(i,"//VTK::Normal::Dec",["uniform int cameraParallel;\n","varying float radiusVCVSOutput;\n","varying vec3 orientVCVSOutput;\n","varying float lengthVCVSOutput;\n","varying vec3 centerVCVSOutput;\n","uniform mat4 VCPCMatrix;\n"]).result;let s="";t.context.getExtension("EXT_frag_depth")&&(s="  gl_FragDepthEXT = (pos.z / pos.w + 1.0) / 2.0;\n"),t._openGLRenderWindow.getWebgl2()&&(s="gl_FragDepth = (pos.z / pos.w + 1.0) / 2.0;\n"),i=vd.substitute(i,"//VTK::Depth::Impl",["  vec3 EyePos;\n","  vec3 EyeDir;\n","  if (cameraParallel != 0) {\n","    EyePos = vec3(vertexVC.x, vertexVC.y, vertexVC.z + 3.0*radiusVCVSOutput);\n","    EyeDir = vec3(0.0,0.0,-1.0); }\n","  else {\n","    EyeDir = vertexVC.xyz;\n","    EyePos = vec3(0.0,0.0,0.0);\n","    float lengthED = length(EyeDir);\n","    EyeDir = normalize(EyeDir);\n","    if (lengthED > radiusVCVSOutput*3.0) {\n","      EyePos = vertexVC.xyz - EyeDir*3.0*radiusVCVSOutput; }\n","    }\n","  EyePos = EyePos - centerVCVSOutput;\n","  vec3 base1;\n","  if (abs(orientVCVSOutput.z) < 0.99) {\n","    base1 = normalize(cross(orientVCVSOutput,vec3(0.0,0.0,1.0))); }\n","  else {\n","    base1 = normalize(cross(orientVCVSOutput,vec3(0.0,1.0,0.0))); }\n","  vec3 base2 = cross(orientVCVSOutput,base1);\n","  EyePos = vec3(dot(EyePos,base1),dot(EyePos,base2),dot(EyePos,orientVCVSOutput));\n","  EyeDir = vec3(dot(EyeDir,base1),dot(EyeDir,base2),dot(EyeDir,orientVCVSOutput));\n","  EyePos = EyePos/radiusVCVSOutput;\n","  float a = EyeDir.x*EyeDir.x + EyeDir.y*EyeDir.y;\n","  float b = 2.0*(EyePos.x*EyeDir.x + EyePos.y*EyeDir.y);\n","  float c = EyePos.x*EyePos.x + EyePos.y*EyePos.y - 1.0;\n","  float d = b*b - 4.0*a*c;\n","  vec3 normalVCVSOutput = vec3(0.0,0.0,1.0);\n","  if (d < 0.0) { discard; }\n","  else {\n","    float t =  (-b - sqrt(d))/(2.0*a);\n","    float tz = EyePos.z + t*EyeDir.z;\n","    vec3 iPoint = EyePos + t*EyeDir;\n","    if (abs(iPoint.z)*radiusVCVSOutput > lengthVCVSOutput*0.5) {\n","      float t2 = (-b + sqrt(d))/(2.0*a);\n","      float tz2 = EyePos.z + t2*EyeDir.z;\n","      if (tz2*radiusVCVSOutput > lengthVCVSOutput*0.5 || tz*radiusVCVSOutput < -0.5*lengthVCVSOutput) { discard; }\n","      else {\n","        normalVCVSOutput = orientVCVSOutput;\n","        float t3 = (lengthVCVSOutput*0.5/radiusVCVSOutput - EyePos.z)/EyeDir.z;\n","        iPoint = EyePos + t3*EyeDir;\n","        vertexVC.xyz = radiusVCVSOutput*(iPoint.x*base1 + iPoint.y*base2 + iPoint.z*orientVCVSOutput) + centerVCVSOutput;\n","        }\n","      }\n","    else {\n","      normalVCVSOutput = iPoint.x*base1 + iPoint.y*base2;\n","      vertexVC.xyz = radiusVCVSOutput*(normalVCVSOutput + iPoint.z*orientVCVSOutput) + centerVCVSOutput;\n","      }\n","    }\n","  vec4 pos = VCPCMatrix * vertexVC;\n",s]).result,i=vd.substitute(i,"//VTK::Normal::Impl","").result,t.haveSeenDepthRequest&&(i=vd.substitute(i,"//VTK::ZBuffer::Impl",["if (depthRequest == 1) {","float computedZ = (pos.z / pos.w + 1.0) / 2.0;","float iz = floor(computedZ * 65535.0 + 0.1);","float rf = floor(iz/256.0)/255.0;","float gf = mod(iz,256.0)/255.0;","gl_FragData[0] = vec4(rf, gf, 0.0, 1.0); 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n=[3];Wo(t.physicalViewNorth,t.physicalViewUp,n),e[0]=n[0],e[1]=n[1],e[2]=n[2],e[4]=t.physicalViewUp[0],e[5]=t.physicalViewUp[1],e[6]=t.physicalViewUp[2],e[8]=-t.physicalViewNorth[0],e[9]=-t.physicalViewNorth[1],e[10]=-t.physicalViewNorth[2],y(e,e),Y(s,1/t.physicalScale,1/t.physicalScale,1/t.physicalScale),S(e,e,s),C(e,e,t.physicalTranslation)},e.computeViewParametersFromViewMatrix=i=>{b(a,i),oe(s,n,a),e.computeDistance();const u=t.distance;e.setPosition(s[0],s[1],s[2]),oe(l,r,a),Z(l,l,s),te(l,l),e.setDirectionOfProjection(l[0],l[1],l[2]),oe(c,o,a),Z(c,c,s),te(c,c),e.setViewUp(c[0],c[1],c[2]),e.setDistance(u)},e.computeViewParametersFromPhysicalMatrix=t=>{e.getWorldToPhysicalMatrix(a),A(a,t,a),e.computeViewParametersFromViewMatrix(a)},e.setModelTransformMatrix=e=>{t.modelTransformMatrix=e},e.getModelTransformMatrix=()=>t.modelTransformMatrix,e.setViewMatrix=n=>{t.viewMatrix=n,t.viewMatrix&&(T(a,t.viewMatrix),e.computeViewParametersFromViewMatrix(a),y(t.viewMatrix,t.viewMatrix))},e.getViewMatrix=()=>{if(t.viewMatrix)return t.modelTransformMatrix?(A(a,t.viewMatrix,t.modelTransformMatrix),a):t.viewMatrix;_(a,t.position,t.focalPoint,t.viewUp),y(a,a);const e=new Float64Array(16);return t.modelTransformMatrix?A(e,a,t.modelTransformMatrix):T(e,a),e},e.setProjectionMatrix=e=>{t.projectionMatrix=e},e.getProjectionMatrix=(e,n,r)=>{const o=new Float64Array(16);if(x(o),t.projectionMatrix){const e=1/t.physicalScale;return Y(s,e,e,e),T(o,t.projectionMatrix),S(o,o,s),y(o,o),o}x(a);const i=t.clippingRange[1]-t.clippingRange[0],l=[t.clippingRange[0]+(n+1)*i/2,t.clippingRange[0]+(r+1)*i/2];if(t.parallelProjection){const n=t.parallelScale*e,r=t.parallelScale,o=(t.windowCenter[0]-1)*n,i=(t.windowCenter[0]+1)*n,s=(t.windowCenter[1]-1)*r,c=(t.windowCenter[1]+1)*r;U(a,o,i,s,c,l[0],l[1]),y(a,a)}else{if(t.useOffAxisProjection)throw new Error("Off-Axis projection is not supported at this time");{const n=Math.tan(wo(t.viewAngle)/2);let r,o;!0===t.useHorizontalViewAngle?(r=t.clippingRange[0]*n,o=t.clippingRange[0]*n/e):(r=t.clippingRange[0]*n*e,o=t.clippingRange[0]*n);const i=(t.windowCenter[0]-1)*r,s=(t.windowCenter[0]+1)*r,c=(t.windowCenter[1]-1)*o,u=(t.windowCenter[1]+1)*o,d=l[0],p=l[1];a[0]=2*d/(s-i),a[5]=2*d/(u-c),a[2]=(i+s)/(s-i),a[6]=(c+u)/(u-c),a[10]=-(d+p)/(p-d),a[14]=-1,a[11]=-2*d*p/(p-d),a[15]=0}}return T(o,a),o},e.getCompositeProjectionMatrix=(t,n,r)=>{const 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fh(e,t,n={}){Object.assign(t,ph,n),sn.obj(e,t),sn.setGet(e,t,["intensity","switch","positional","exponent","coneAngle","coneFalloff","transformMatrix","lightType","shadowAttenuation","attenuationValues"]),sn.setGetArray(e,t,["color","position","focalPoint","attenuationValues"],3),function(e,t){t.classHierarchy.push("vtkLight");const n=new Float64Array(3);e.getTransformedPosition=()=>(t.transformMatrix?oe(n,t.position,t.transformMatrix):Y(n,t.position[0],t.position[1],t.position[2]),n),e.getTransformedFocalPoint=()=>(t.transformMatrix?oe(n,t.focalPoint,t.transformMatrix):Y(n,t.focalPoint[0],t.focalPoint[1],t.focalPoint[2]),n),e.getDirection=()=>(t.directionMTime<t.mtime&&(le(t.direction,t.focalPoint,t.position),jo(t.direction),t.directionMTime=t.mtime),t.direction),e.setDirection=e=>{const n=new Float64Array(3);le(n,t.position,e),t.focalPoint=n},e.setDirectionAngle=(t,n)=>{const r=wo(t),o=wo(n);e.setPosition(Math.cos(r)*Math.sin(o),Math.sin(r),Math.cos(r)*Math.cos(o)),e.setFocalPoint(0,0,0),e.setPositional(0)},e.setLightTypeToHeadLight=()=>{e.setLightType("HeadLight")},e.setLightTypeToCameraLight=()=>{e.setLightType("CameraLight")},e.setLightTypeToSceneLight=()=>{e.setTransformMatrix(null),e.setLightType("SceneLight")},e.lightTypeIsHeadLight=()=>"HeadLight"===t.lightType,e.lightTypeIsSceneLight=()=>"SceneLight"===t.lightType,e.lightTypeIsCameraLight=()=>"CameraLight"===t.lightType}(e,t)}var gh={newInstance:sn.newInstance(fh,"vtkLight"),extend:fh,LIGHT_TYPES:["HeadLight","CameraLight","SceneLight"]};const{vtkErrorMacro:mh}=sn;function hh(e,t){function n(e,t=[]){t.push(e);const r=e.getNestedProps();if(r&&r.length)for(let e=0;e<r.length;e++)n(r[e],t);return t}var r;t.classHierarchy.push("vtkViewport"),e.getViewProps=()=>t.props,e.hasViewProp=e=>t.props.includes(e),e.addViewProp=n=>{n&&!e.hasViewProp(n)&&t.props.push(n)},e.removeViewProp=e=>{const n=t.props.filter((t=>t!==e));t.props.length!==n.length&&(t.props=n)},e.removeAllViewProps=()=>{t.props=[]},e.getViewPropsWithNestedProps=()=>{let e=[];t.actors2D=[];for(let r=0;r<t.props.length;r++){const o=t.props[r].getActors2D();o&&(!Array.isArray(o)||o.length>0)?t.actors2D=t.actors2D.concat(o):n(t.props[r],e)}return t.actors2D.sort(((e,t)=>e.getLayerNumber()-t.getLayerNumber())),e=e.concat(t.actors2D),e},e.addActor2D=e.addViewProp,e.removeActor2D=t=>{e.removeViewProp(t)},e.getActors2D=()=>(t.actors2D=[],t.props.forEach((e=>{t.actors2D=t.actors2D.concat(e.getActors2D())})),t.actors2D),e.displayToView=()=>mh("call displayToView on your view instead"),e.viewToDisplay=()=>mh("callviewtodisplay on your view instead"),e.getSize=()=>mh("call getSize on your View instead"),e.normalizedDisplayToProjection=(t,n,r)=>{const o=e.normalizedDisplayToNormalizedViewport(t,n,r);return e.normalizedViewportToProjection(o[0],o[1],o[2])},e.normalizedDisplayToNormalizedViewport=(e,n,r)=>{const o=[t.viewport[2]-t.viewport[0],t.viewport[3]-t.viewport[1]];return[(e-t.viewport[0])/o[0],(n-t.viewport[1])/o[1],r]},e.normalizedViewportToProjection=(e,t,n)=>[2*e-1,2*t-1,2*n-1],e.projectionToNormalizedDisplay=(t,n,r)=>{const o=e.projectionToNormalizedViewport(t,n,r);return e.normalizedViewportToNormalizedDisplay(o[0],o[1],o[2])},e.normalizedViewportToNormalizedDisplay=(e,n,r)=>{const o=[t.viewport[2]-t.viewport[0],t.viewport[3]-t.viewport[1]];return[e*o[0]+t.viewport[0],n*o[1]+t.viewport[1],r]},e.projectionToNormalizedViewport=(e,t,n)=>[.5*(e+1),.5*(t+1),.5*(n+1)],e.PickPropFrom=(r="PickPropFrom",()=>mh(`vtkViewport::${r} - NOT IMPLEMENTED`))}const vh={background:[0,0,0],background2:[.2,.2,.2],gradientBackground:!1,viewport:[0,0,1,1],aspect:[1,1],pixelAspect:[1,1],props:[],actors2D:[]};function Th(e,t,n={}){Object.assign(t,vh,n),sn.obj(e,t),sn.event(e,t,"event"),sn.setGetArray(e,t,["viewport"],4),sn.setGetArray(e,t,["background","background2"],3),hh(e,t)}var xh={newInstance:sn.newInstance(Th,"vtkViewport"),extend:Th};const{vtkDebugMacro:yh,vtkErrorMacro:bh,vtkWarningMacro:Ah}=ln;function Ch(e){return()=>bh(`vtkRenderer::${e} - NOT IMPLEMENTED`)}const Sh={pickedProp:null,activeCamera:null,allBounds:[],ambient:[1,1,1],allocatedRenderTime:100,timeFactor:1,automaticLightCreation:!0,twoSidedLighting:!0,lastRenderTimeInSeconds:-1,renderWindow:null,lights:[],actors:[],volumes:[],lightFollowCamera:!0,numberOfPropsRendered:0,propArray:null,pathArray:null,layer:0,preserveColorBuffer:!1,preserveDepthBuffer:!1,computeVisiblePropBounds:Ga(),interactive:!0,nearClippingPlaneTolerance:0,clippingRangeExpansion:.05,erase:!0,draw:!0,useShadows:!1,useDepthPeeling:!1,occlusionRatio:0,maximumNumberOfPeels:4,selector:null,delegate:null,texturedBackground:!1,backgroundTexture:null,environmentTexture:null,environmentTextureDiffuseStrength:1,environmentTextureSpecularStrength:1,useEnvironmentTextureAsBackground:!1,pass:0};function Ph(e,t,n={}){for(Object.assign(t,Sh,n),xh.extend(e,t,n),t.background||(t.background=[0,0,0,1]);t.background.length<3;)t.background.push(0);3===t.background.length&&t.background.push(1),Bt(e,t,["_renderWindow","allocatedRenderTime","timeFactor","lastRenderTimeInSeconds","numberOfPropsRendered","lastRenderingUsedDepthPeeling","selector"]),Gt(e,t,["twoSidedLighting","lightFollowCamera","automaticLightCreation","erase","draw","nearClippingPlaneTolerance","clippingRangeExpansion","backingStore","interactive","layer","preserveColorBuffer","preserveDepthBuffer","useDepthPeeling","occlusionRatio","maximumNumberOfPeels","delegate","backgroundTexture","texturedBackground","environmentTexture","environmentTextureDiffuseStrength","environmentTextureSpecularStrength","useEnvironmentTextureAsBackground","useShadows","pass"]),Ut(e,t,["actors","volumes","lights"]),Kt(e,t,["background"],4,1),zt(0,t,["renderWindow"]),function(e,t){t.classHierarchy.push("vtkRenderer");const n={type:"ComputeVisiblePropBoundsEvent",renderer:e},r={type:"ResetCameraClippingRangeEvent",renderer:e},o={type:"ResetCameraEvent",renderer:e};e.updateCamera=()=>(t.activeCamera||(yh("No cameras are on, creating one."),e.getActiveCameraAndResetIfCreated()),t.activeCamera.render(e),!0),e.updateLightsGeometryToFollowCamera=()=>{const n=e.getActiveCameraAndResetIfCreated();t.lights.forEach((e=>{e.lightTypeIsSceneLight()||(e.lightTypeIsHeadLight()?(e.setPositionFrom(n.getPositionByReference()),e.setFocalPointFrom(n.getFocalPointByReference()),e.modified(n.getMTime())):e.lightTypeIsCameraLight()?e.setTransformMatrix(n.getCameraLightTransformMatrix(v())):bh("light has unknown light type",e.get()))}))},e.updateLightGeometry=()=>!t.lightFollowCamera||e.updateLightsGeometryToFollowCamera(),e.allocateTime=Ch("allocateTime"),e.updateGeometry=Ch("updateGeometry"),e.getVTKWindow=()=>t._renderWindow,e.setLayer=n=>{yh(e.getClassName(),e,"setting Layer to 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a=e.normalizedDisplayToProjection(t,n,r);return a=e.projectionToView(a[0],a[1],a[2],o),e.viewToWorld(a[0],a[1],a[2])},e.worldToNormalizedDisplay=(t,n,r,o)=>{let a=e.worldToView(t,n,r);return a=e.viewToProjection(a[0],a[1],a[2],o),e.projectionToNormalizedDisplay(a[0],a[1],a[2])},e.viewToWorld=(e,n,r)=>{if(null===t.activeCamera)return bh("ViewToWorld: no active camera, cannot compute view to world, returning 0,0,0"),[0,0,0];const o=t.activeCamera.getViewMatrix();b(o,o),y(o,o);const a=new Float64Array([e,n,r]);return oe(a,a,o),a},e.projectionToView=(e,n,r,o)=>{if(null===t.activeCamera)return bh("ProjectionToView: no active camera, cannot compute projection to view, returning 0,0,0"),[0,0,0];const a=t.activeCamera.getProjectionMatrix(o,-1,1);b(a,a),y(a,a);const i=new Float64Array([e,n,r]);return oe(i,i,a),i},e.worldToView=(e,n,r)=>{if(null===t.activeCamera)return bh("WorldToView: no active camera, cannot compute view to world, returning 0,0,0"),[0,0,0];const 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Ih[e]&&Ih[e](t)}const Mh={defaultViewAPI:"WebGL",renderers:[],views:[],interactor:null,neverRendered:!0,numberOfLayers:1,childRenderWindows:[]};function 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jh(e){const t=Object.create(null);return e.forEach((({pointerId:e,position:n})=>{t[e]=n})),t}const Xh={renderWindow:null,interactorStyle:null,picker:null,pickingManager:null,initialized:!1,enabled:!1,enableRender:!0,currentRenderer:null,lightFollowCamera:!0,desiredUpdateRate:30,stillUpdateRate:2,container:null,recognizeGestures:!0,currentGesture:"Start",animationRequest:null,lastFrameTime:.1,recentAnimationFrameRate:10,wheelTimeoutID:0,moveTimeoutID:0,lastGamepadValues:{},preventDefaultOnPointerDown:!1,preventDefaultOnPointerUp:!1,mouseScrollDebounceByPass:!1};function qh(e,t,n={}){Object.assign(t,Xh,n),sn.obj(e,t),t._animationExtendedEnd=0,sn.event(e,t,"RenderEvent"),Wh.forEach((n=>sn.event(e,t,n))),sn.get(e,t,["initialized","interactorStyle","lastFrameTime","recentAnimationFrameRate","_view"]),sn.setGet(e,t,["container","lightFollowCamera","enabled","enableRender","recognizeGestures","desiredUpdateRate","stillUpdateRate","picker","preventDefaultOnPointerDown","preventDefaultOnPointerUp","mouseScrollDebounceByPass"]),sn.moveToProtected(e,t,["view"]),function(e,t){t.classHierarchy.push("vtkRenderWindowInteractor");const n={...e},r=new Set,o=new Map;let a=1,i=0;function s(n,r){t._forcedRenderer||(t.currentRenderer=e.findPokedRenderer(n,r))}e.start=()=>{(t.initialized||(e.initialize(),t.initialized))&&e.startEventLoop()},e.setRenderWindow=e=>{Gh("you want to call setView(view) instead of setRenderWindow on a vtk.js 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p=()=>{if(null===t.container)return;const{container:n}=t;n.addEventListener("contextmenu",Hh),n.addEventListener("wheel",e.handleWheel),n.addEventListener("DOMMouseScroll",e.handleWheel),n.addEventListener("pointerenter",e.handlePointerEnter),n.addEventListener("pointerleave",e.handlePointerLeave),n.addEventListener("pointermove",e.handlePointerMove,{passive:!1}),n.addEventListener("pointerdown",e.handlePointerDown,{passive:!1}),n.addEventListener("pointerup",e.handlePointerUp),n.addEventListener("pointercancel",e.handlePointerCancel),n.addEventListener("keypress",e.handleKeyPress),n.addEventListener("keydown",e.handleKeyDown),document.addEventListener("keyup",e.handleKeyUp),document.addEventListener("pointerlockchange",e.handlePointerLockChange),n.tabIndex=0,n.style.touchAction="none",n.style.userSelect="none",n.style.webkitTapHighlightColor="rgba(0,0,0,0)"};e.bindEvents=e=>{null!==e&&n.setContainer(e)&&p()};const 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o=Date.now()+n;t._animationExtendedEnd=Math.max(t._animationExtendedEnd,o),t.animationRequest||0!==r.size||t.xrAnimation||(t._animationStartTime=Date.now(),t._animationFrameCount=0,t.animationRequest=requestAnimationFrame(e.handleAnimation),e.startAnimationEvent())},e.isAnimating=()=>t.xrAnimation||null!==t.animationRequest,e.cancelAnimation=(n,o=!1)=>{if(r.has(n))r.delete(n),t.animationRequest&&0===r.size&&Date.now()>t._animationExtendedEnd&&(cancelAnimationFrame(t.animationRequest),t.animationRequest=null,e.endAnimationEvent(),e.render());else if(!o){const e=n&&n.getClassName?n.getClassName():n;kh(`${e} did not request an animation`)}},e.switchToXRAnimation=()=>{t.animationRequest&&(cancelAnimationFrame(t.animationRequest),t.animationRequest=null),t.xrAnimation=!0},e.returnFromXRAnimation=()=>{t.xrAnimation=!1,0!==r.size&&(t.recentAnimationFrameRate=10,t.animationRequest=requestAnimationFrame(e.handleAnimation))},e.updateXRGamepads=(n,r,o)=>{n.inputSources.forEach((n=>{const 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t.lastGamepadValues[s.index][l].buttons||(t.lastGamepadValues[s.index][l].buttons[r]=!1),t.lastGamepadValues[s.index][l].buttons[r]!==s.buttons[r].pressed&&null!=a&&(e.button3DEvent({gamepad:s,position:a.transform.position,orientation:a.transform.orientation,targetPosition:i.transform.position,targetOrientation:i.transform.orientation,pressed:s.buttons[r].pressed,device:"left"===n.handedness?Fh.LeftController:Fh.RightController,input:zh[s.mapping]&&zh[s.mapping][r]?zh[s.mapping][r]:Nh.Trigger}),t.lastGamepadValues[s.index][l].buttons[r]=s.buttons[r].pressed),t.lastGamepadValues[s.index][l].buttons[r]&&null!=a&&e.move3DEvent({gamepad:s,position:a.transform.position,orientation:a.transform.orientation,targetPosition:i.transform.position,targetOrientation:i.transform.orientation,device:"left"===n.handedness?Fh.LeftController:Fh.RightController})}}))},e.handleMouseMove=n=>{const r={...c(n),position:l(n),deviceType:d(n)};0===t.moveTimeoutID?e.startMouseMoveEvent(r):(e.mouseMoveEvent(r),clearTimeout(t.moveTimeoutID)),t.moveTimeoutID=setTimeout((()=>{e.endMouseMoveEvent(),t.moveTimeoutID=0}),200)},e.handleAnimation=()=>{const n=Date.now();t._animationFrameCount++,n-t._animationStartTime>1e3&&t._animationFrameCount>1&&(t.recentAnimationFrameRate=1e3*(t._animationFrameCount-1)/(n-t._animationStartTime),t.lastFrameTime=1/t.recentAnimationFrameRate,e.animationFrameRateUpdateEvent(),t._animationStartTime=n,t._animationFrameCount=1),e.animationEvent(),m(),r.size>0||Date.now()<t._animationExtendedEnd?t.animationRequest=requestAnimationFrame(e.handleAnimation):(cancelAnimationFrame(t.animationRequest),t.animationRequest=null,e.endAnimationEvent(),e.render())},e.handleWheel=n=>{Hh(n);const r={...Uh(n),...c(n),position:l(n),deviceType:d(n)};0===t.wheelTimeoutID&&(a=Math.abs(r.spinY)>=.3?Math.abs(r.spinY):1),r.spinY/=a,0===t.wheelTimeoutID?(e.startMouseWheelEvent(r),e.mouseWheelEvent(r)):(e.mouseWheelEvent(r),clearTimeout(t.wheelTimeoutID)),t.mouseScrollDebounceByPass?(e.extendAnimation(600),e.endMouseWheelEvent(),t.wheelTimeoutID=0):t.wheelTimeoutID=setTimeout((()=>{e.extendAnimation(600),e.endMouseWheelEvent(),t.wheelTimeoutID=0}),200)},e.handleMouseUp=t=>{const n={...c(t),position:l(t),deviceType:d(t)};switch(t.button){case 0:e.leftButtonReleaseEvent(n);break;case 1:e.middleButtonReleaseEvent(n);break;case 2:e.rightButtonReleaseEvent(n);break;default:Gh(`Unknown mouse button released: ${t.button}`)}},e.handleTouchStart=n=>{const r=[...o.values()];if(t.recognizeGestures&&r.length>1){const t=jh(o);if(2===r.length){const t={...c(Kh),position:r[0].position,deviceType:d(n)};e.leftButtonReleaseEvent(t)}e.recognizeGesture("TouchStart",t)}else if(1===r.length){const t={...c(Kh),position:l(n),deviceType:d(n)};e.leftButtonPressEvent(t)}},e.handleTouchMove=n=>{const r=[...o.values()];if(t.recognizeGestures&&r.length>1){const t=jh(o);e.recognizeGesture("TouchMove",t)}else if(1===r.length){const t={...c(Kh),position:r[0].position,deviceType:d(n)};e.mouseMoveEvent(t)}},e.handleTouchEnd=n=>{const r=[...o.values()];if(t.recognizeGestures)if(0===r.length){const t={...c(Kh),position:l(n),deviceType:d(n)};e.leftButtonReleaseEvent(t)}else if(1===r.length){const t=jh(o);e.recognizeGesture("TouchEnd",t);const a={...c(Kh),position:r[0].position,deviceType:d(n)};e.leftButtonPressEvent(a)}else{const t=jh(o);e.recognizeGesture("TouchMove",t)}else if(1===r.length){const t={...c(Kh),position:r[0].position,deviceType:d(n)};e.leftButtonReleaseEvent(t)}},e.setView=n=>{t._view!==n&&(t._view=n,t._view.getRenderable().setInteractor(e),e.modified())},e.getFirstRenderer=()=>t._view?.getRenderable()?.getRenderersByReference()?.[0],e.findPokedRenderer=(e=0,n=0)=>{if(!t._view)return null;const r=t._view?.getRenderable()?.getRenderers();if(!r||0===r.length)return null;r.sort(((e,t)=>e.getLayer()-t.getLayer()));let o=null,a=null,i=null,s=r.length;for(;s--;){const l=r[s];if(t._view.isInViewport(e,n,l)&&l.getInteractive()){i=l;break}null===o&&l.getInteractive()&&(o=l),null===a&&t._view.isInViewport(e,n,l)&&(a=l)}return null===i&&(i=o),null===i&&(i=a),null==i&&(i=r[0]),i},e.render=()=>{e.isAnimating()||t.inRender||m()},Wh.forEach((n=>{const r=n.charAt(0).toLowerCase()+n.slice(1);e[`${r}Event`]=r=>{if(!t.enabled)return;if(!e.getCurrentRenderer())return void _h("\n          Can not forward events without a current renderer on the interactor.\n        ");const o={type:n,pokedRenderer:t.currentRenderer,firstRenderer:e.getFirstRenderer(),...r};e[`invoke${n}`](o)}})),e.recognizeGesture=(n,r)=>{if(Object.keys(r).length>2)return;if(t.startingEventPositions||(t.startingEventPositions={}),"TouchStart"===n)return Object.keys(r).forEach((e=>{t.startingEventPositions[e]=r[e]})),void(t.currentGesture="Start");if("TouchEnd"===n)return"Pinch"===t.currentGesture&&(e.render(),e.endPinchEvent()),"Rotate"===t.currentGesture&&(e.render(),e.endRotateEvent()),"Pan"===t.currentGesture&&(e.render(),e.endPanEvent()),t.currentGesture="Start",void(t.startingEventPositions={});let o=0;const a=[],i=[];Object.keys(r).forEach((e=>{a[o]=r[e],i[o]=t.startingEventPositions[e],o++}));const s=Math.sqrt((i[0].x-i[1].x)*(i[0].x-i[1].x)+(i[0].y-i[1].y)*(i[0].y-i[1].y)),l=Math.sqrt((a[0].x-a[1].x)*(a[0].x-a[1].x)+(a[0].y-a[1].y)*(a[0].y-a[1].y));let c=Io(Math.atan2(i[1].y-i[0].y,i[1].x-i[0].x)),u=Io(Math.atan2(a[1].y-a[0].y,a[1].x-a[0].x)),d=u-c;u=u+180>=360?u-180:u+180,c=c+180>=360?c-180:c+180,Math.abs(u-c)<Math.abs(d)&&(d=u-c);const p=[];if(p[0]=(a[0].x-i[0].x+a[1].x-i[1].x)/2,p[1]=(a[0].y-i[0].y+a[1].y-i[1].y)/2,"TouchMove"===n)if("Start"===t.currentGesture){let n=.01*Math.sqrt(t.container.clientWidth*t.container.clientWidth+t.container.clientHeight*t.container.clientHeight);n<15&&(n=15);const o=Math.abs(l-s),a=3.1415926*l*Math.abs(d)/360,i=Math.sqrt(p[0]*p[0]+p[1]*p[1]);if(o>n&&o>a&&o>i){t.currentGesture="Pinch";const n={scale:1,touches:r};e.startPinchEvent(n)}else if(a>n&&a>i){t.currentGesture="Rotate";const n={rotation:0,touches:r};e.startRotateEvent(n)}else if(i>n){t.currentGesture="Pan";const n={translation:[0,0],touches:r};e.startPanEvent(n)}}else{if("Rotate"===t.currentGesture){const t={rotation:d,touches:r};e.rotateEvent(t)}if("Pinch"===t.currentGesture){const t={scale:l/s,touches:r};e.pinchEvent(t)}if("Pan"===t.currentGesture){const t={translation:p,touches:r};e.panEvent(t)}}},e.handleVisibilityChange=()=>{t._animationStartTime=Date.now(),t._animationFrameCount=0},e.setCurrentRenderer=e=>{t._forcedRenderer=!!e,t.currentRenderer=e},e.setContainer=e=>{f();const t=n.setContainer(e??null);return t&&p(),t},e.delete=()=>{for(;r.size;)e.cancelAnimation(r.values().next().value);void 0!==document.hidden&&document.removeEventListener("visibilitychange",e.handleVisibilityChange),t.container&&e.setContainer(null),n.delete()},void 0!==document.hidden&&document.addEventListener("visibilitychange",e.handleVisibilityChange,!1)}(e,t)}var Yh={newInstance:sn.newInstance(qh,"vtkRenderWindowInteractor"),extend:qh,handledEvents:Wh,...Bh};const{vtkErrorMacro:Jh,VOID:Zh}=sn;const Qh={computeWorldToDisplay:function(e,t,n,r){return e.getRenderWindow().getViews()[0].worldToDisplay(t,n,r,e)},computeDisplayToWorld:function(e,t,n,r){return e.getRenderWindow().getViews()[0].displayToWorld(t,n,r,e)}};const $h={enabled:!0,priority:0,processEvents:!0,subscribedEvents:[]};function ev(e,t,n={}){Object.assign(t,$h,n),sn.obj(e,t),sn.event(e,t,"InteractionEvent"),sn.event(e,t,"StartInteractionEvent"),sn.event(e,t,"EndInteractionEvent"),sn.get(e,t,["_interactor","enabled"]),sn.setGet(e,t,["priority","processEvents"]),sn.moveToProtected(e,t,["interactor"]),function(e,t){t.classHierarchy.push("vtkInteractorObserver");const n={...e};function r(){for(;t.subscribedEvents.length;)t.subscribedEvents.pop().unsubscribe()}function o(){Yh.handledEvents.forEach((n=>{e[`handle${n}`]&&t.subscribedEvents.push(t._interactor[`on${n}`]((r=>t.processEvents?e[`handle${n}`](r):Zh),t.priority))}))}e.setInteractor=n=>{n!==t._interactor&&(r(),t._interactor=n,n&&t.enabled&&o(),e.modified())},e.setEnabled=n=>{n!==t.enabled&&(r(),n&&(t._interactor?o():Jh("\n          The interactor must be set before subscribing to events\n        ")),t.enabled=n,e.modified())},e.computeDisplayToWorld=(e,n,r,o)=>e?t._interactor.getView().displayToWorld(n,r,o,e):null,e.computeWorldToDisplay=(e,n,r,o)=>e?t._interactor.getView().worldToDisplay(n,r,o,e):null,e.setPriority=e=>{n.setPriority(e)&&t._interactor&&(r(),o())}}(e,t)}var tv={newInstance:sn.newInstance(ev,"vtkInteractorObserver"),extend:ev,...Qh};var nv={States:{IS_START:0,IS_NONE:0,IS_ROTATE:1,IS_PAN:2,IS_SPIN:3,IS_DOLLY:4,IS_CAMERA_POSE:11,IS_WINDOW_LEVEL:1024,IS_SLICE:1025}};const{States:rv}=nv,ov={Rotate:rv.IS_ROTATE,Pan:rv.IS_PAN,Spin:rv.IS_SPIN,Dolly:rv.IS_DOLLY,CameraPose:rv.IS_CAMERA_POSE,WindowLevel:rv.IS_WINDOW_LEVEL,Slice:rv.IS_SLICE};const av={state:rv.IS_NONE,handleObservers:1,autoAdjustCameraClippingRange:1};function iv(e,t,n={}){Object.assign(t,av,n),tv.extend(e,t,n),sn.setGet(e,t,["focusedRenderer"]),function(e,t){t.classHierarchy.push("vtkInteractorStyle"),Object.keys(ov).forEach((n=>{sn.event(e,t,`Start${n}Event`),e[`start${n}`]=()=>{t.state===rv.IS_NONE&&(t.state=ov[n],t._interactor.requestAnimation(e),e.invokeStartInteractionEvent({type:"StartInteractionEvent"}),e[`invokeStart${n}Event`]({type:`Start${n}Event`}))},sn.event(e,t,`End${n}Event`),e[`end${n}`]=()=>{t.state===ov[n]&&(t.state=rv.IS_NONE,t._interactor.cancelAnimation(e),e.invokeEndInteractionEvent({type:"EndInteractionEvent"}),e[`invokeEnd${n}Event`]({type:`End${n}Event`}),t._interactor.render())}})),t.getRenderer=e=>t.focusedRenderer||e.pokedRenderer,e.handleKeyPress=e=>{const n=t._interactor;let r=null;switch(e.key){case"r":case"R":t.getRenderer(e).resetCamera(),n.render();break;case"w":case"W":r=t.getRenderer(e).getActors(),r.forEach((e=>{const t=e.getProperty();t.setRepresentationToWireframe&&t.setRepresentationToWireframe()})),n.render();break;case"s":case"S":r=t.getRenderer(e).getActors(),r.forEach((e=>{const t=e.getProperty();t.setRepresentationToSurface&&t.setRepresentationToSurface()})),n.render();break;case"v":case"V":r=t.getRenderer(e).getActors(),r.forEach((e=>{const t=e.getProperty();t.setRepresentationToPoints&&t.setRepresentationToPoints()})),n.render()}}}(e,t)}var sv={newInstance:sn.newInstance(iv,"vtkInteractorStyle"),extend:iv,...nv};const{States:lv}=nv;const cv={motionFactor:10,zoomFactor:10};function uv(e,t,n={}){Object.assign(t,cv,n),sv.extend(e,t,n),sn.setGet(e,t,["motionFactor","zoomFactor"]),function(e,t){t.classHierarchy.push("vtkInteractorStyleTrackballCamera"),e.handleMouseMove=n=>{const r=n.position,o=t.getRenderer(n);switch(t.state){case lv.IS_ROTATE:e.handleMouseRotate(o,r),e.invokeInteractionEvent({type:"InteractionEvent"});break;case lv.IS_PAN:e.handleMousePan(o,r),e.invokeInteractionEvent({type:"InteractionEvent"});break;case lv.IS_DOLLY:e.handleMouseDolly(o,r),e.invokeInteractionEvent({type:"InteractionEvent"});break;case lv.IS_SPIN:e.handleMouseSpin(o,r),e.invokeInteractionEvent({type:"InteractionEvent"})}t.previousPosition=r},e.handleButton3D=n=>{!n||!n.pressed||n.device!==Vh.RightController||n.input!==Lh.Trigger&&n.input!==Lh.TrackPad?!n||n.pressed||n.device!==Vh.RightController||n.input!==Lh.Trigger&&n.input!==Lh.TrackPad||t.state!==lv.IS_CAMERA_POSE||e.endCameraPose():e.startCameraPose()},e.handleMove3D=n=>{t.state===lv.IS_CAMERA_POSE&&e.updateCameraPose(n)},e.updateCameraPose=e=>{const n=t.getRenderer(e).getActiveCamera(),r=n.getPhysicalTranslation(),o=.025*n.getPhysicalScale(),a=n.physicalOrientationToWorldDirection([e.orientation.x,e.orientation.y,e.orientation.z,e.orientation.w]);n.setPhysicalTranslation(r[0]+a[0]*o,r[1]+a[1]*o,r[2]+a[2]*o)},e.handleLeftButtonPress=n=>{const r=n.position;t.previousPosition=r,n.shiftKey?n.controlKey||n.altKey?e.startDolly():e.startPan():n.controlKey||n.altKey?e.startSpin():e.startRotate()},e.handleLeftButtonRelease=()=>{switch(t.state){case lv.IS_DOLLY:e.endDolly();break;case lv.IS_PAN:e.endPan();break;case lv.IS_SPIN:e.endSpin();break;case lv.IS_ROTATE:e.endRotate()}},e.handleStartMouseWheel=()=>{e.startDolly()},e.handleEndMouseWheel=()=>{e.endDolly()},e.handleStartPinch=n=>{t.previousScale=n.scale,e.startDolly()},e.handleEndPinch=()=>{e.endDolly()},e.handleStartRotate=n=>{t.previousRotation=n.rotation,e.startRotate()},e.handleEndRotate=()=>{e.endRotate()},e.handleStartPan=n=>{t.previousTranslation=n.translation,e.startPan()},e.handleEndPan=()=>{e.endPan()},e.handlePinch=n=>{e.dollyByFactor(t.getRenderer(n),n.scale/t.previousScale),t.previousScale=n.scale},e.handlePan=n=>{const r=t.getRenderer(n).getActiveCamera();let o=r.getFocalPoint();o=e.computeWorldToDisplay(t.getRenderer(n),o[0],o[1],o[2]);const a=o[2],i=n.translation,s=t.previousTranslation,l=e.computeDisplayToWorld(t.getRenderer(n),o[0]+i[0]-s[0],o[1]+i[1]-s[1],a),c=e.computeDisplayToWorld(t.getRenderer(n),o[0],o[1],a),u=[];u[0]=c[0]-l[0],u[1]=c[1]-l[1],u[2]=c[2]-l[2],o=r.getFocalPoint();const d=r.getPosition();r.setFocalPoint(u[0]+o[0],u[1]+o[1],u[2]+o[2]),r.setPosition(u[0]+d[0],u[1]+d[1],u[2]+d[2]),t._interactor.getLightFollowCamera()&&t.getRenderer(n).updateLightsGeometryToFollowCamera(),r.orthogonalizeViewUp(),t.previousTranslation=n.translation},e.handleRotate=e=>{const n=t.getRenderer(e).getActiveCamera();n.roll(e.rotation-t.previousRotation),n.orthogonalizeViewUp(),t.previousRotation=e.rotation},e.handleMouseRotate=(e,n)=>{if(!t.previousPosition)return;const r=t._interactor,o=n.x-t.previousPosition.x,a=n.y-t.previousPosition.y,i=r.getView().getViewportSize(e);let s=-.1,l=-.1;i[0]&&i[1]&&(s=-20/i[1],l=-20/i[0]);const c=o*l*t.motionFactor,u=a*s*t.motionFactor,d=e.getActiveCamera();Number.isNaN(c)||Number.isNaN(u)||(d.azimuth(c),d.elevation(u),d.orthogonalizeViewUp()),t.autoAdjustCameraClippingRange&&e.resetCameraClippingRange(),r.getLightFollowCamera()&&e.updateLightsGeometryToFollowCamera()},e.handleMouseSpin=(e,n)=>{if(!t.previousPosition)return;const r=t._interactor,o=e.getActiveCamera(),a=r.getView().getViewportCenter(e),i=Io(Math.atan2(t.previousPosition.y-a[1],t.previousPosition.x-a[0])),s=Io(Math.atan2(n.y-a[1],n.x-a[0]))-i;Number.isNaN(s)||(o.roll(s),o.orthogonalizeViewUp())},e.handleMousePan=(n,r)=>{if(!t.previousPosition)return;const o=n.getActiveCamera();let a=o.getFocalPoint();a=e.computeWorldToDisplay(n,a[0],a[1],a[2]);const i=a[2],s=e.computeDisplayToWorld(n,r.x,r.y,i),l=e.computeDisplayToWorld(n,t.previousPosition.x,t.previousPosition.y,i),c=[];c[0]=l[0]-s[0],c[1]=l[1]-s[1],c[2]=l[2]-s[2],a=o.getFocalPoint();const u=o.getPosition();o.setFocalPoint(c[0]+a[0],c[1]+a[1],c[2]+a[2]),o.setPosition(c[0]+u[0],c[1]+u[1],c[2]+u[2]),t._interactor.getLightFollowCamera()&&n.updateLightsGeometryToFollowCamera()},e.handleMouseDolly=(n,r)=>{if(!t.previousPosition)return;const o=r.y-t.previousPosition.y,a=t._interactor.getView().getViewportCenter(n),i=t.motionFactor*o/a[1];e.dollyByFactor(n,1.1**i)},e.handleMouseWheel=n=>{const r=1-n.spinY/t.zoomFactor;e.dollyByFactor(t.getRenderer(n),r)},e.dollyByFactor=(e,n)=>{if(Number.isNaN(n))return;const r=e.getActiveCamera();r.getParallelProjection()?r.setParallelScale(r.getParallelScale()/n):(r.dolly(n),t.autoAdjustCameraClippingRange&&e.resetCameraClippingRange()),t._interactor.getLightFollowCamera()&&e.updateLightsGeometryToFollowCamera()}}(e,t)}var dv={newInstance:sn.newInstance(uv,"vtkInteractorStyleTrackballCamera"),extend:uv};function pv(e){return e}function fv(e){return null===e||"null"===e?null:"true"===e||"false"!==e&&(void 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hv(e,t,n={}){Object.assign(t,mv,n),sn.obj(e,t),sn.get(e,t,["currentOperation"]),sn.setGet(e,t,["delegates","_currentParent","preDelegateOperations","postDelegateOperations"]),sn.moveToProtected(e,t,["currentParent"]),function(e,t){t.classHierarchy.push("vtkRenderPass"),e.getOperation=()=>t.currentOperation,e.setCurrentOperation=e=>{t.currentOperation=e,t.currentTraverseOperation=`traverse${sn.capitalize(t.currentOperation)}`},e.getTraverseOperation=()=>t.currentTraverseOperation,e.traverse=(n,r=null)=>{t.deleted||(t._currentParent=r,t.preDelegateOperations.forEach((t=>{e.setCurrentOperation(t),n.traverse(e)})),t.delegates.forEach((t=>{t.traverse(n,e)})),t.postDelegateOperations.forEach((t=>{e.setCurrentOperation(t),n.traverse(e)})))}}(e,t)}var vv={newInstance:sn.newInstance(hv,"vtkRenderPass"),extend:hv};const{Representation:Tv}=us,{vtkErrorMacro:xv}=sn;function yv(e){const t=vd.substitute(e.Fragment,"//VTK::RenderPassFragmentShader::Impl","\n      float weight = gl_FragData[0].a * 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n=e.getSize(),r=e.getContext();t.framebuffer=Gp.newInstance(),t.framebuffer.setOpenGLRenderWindow(e),t.framebuffer.create(...n),t.framebuffer.saveCurrentBindingsAndBuffers(),t.framebuffer.bind(),t.translucentRGBATexture=Hd.newInstance(),t.translucentRGBATexture.setInternalFormat(r.RGBA16F),t.translucentRGBATexture.setFormat(r.RGBA),t.translucentRGBATexture.setOpenGLDataType(r.HALF_FLOAT),t.translucentRGBATexture.setOpenGLRenderWindow(e),t.translucentRGBATexture.create2DFromRaw({width:n[0],height:n[1],numComps:4,dataType:"Float32Array",data:null}),t.translucentRTexture=Hd.newInstance(),t.translucentRTexture.setInternalFormat(r.R16F),t.translucentRTexture.setFormat(r.RED),t.translucentRTexture.setOpenGLDataType(r.HALF_FLOAT),t.translucentRTexture.setOpenGLRenderWindow(e),t.translucentRTexture.create2DFromRaw({width:n[0],height:n[1],numComps:1,dataType:"Float32Array",data:null}),t.translucentZTexture=Hd.newInstance(),t.translucentZTexture.setOpenGLRenderWindow(e),t.translucentZTexture.createDepthFromRaw({width:n[0],height:n[1],dataType:"Float32Array",data:null}),t.framebuffer.setColorBuffer(t.translucentRGBATexture,0),t.framebuffer.setColorBuffer(t.translucentRTexture,1),t.framebuffer.setDepthBuffer(t.translucentZTexture)},e.createCopyShader=e=>{t.copyShader=e.getShaderCache().readyShaderProgramArray(["//VTK::System::Dec","attribute vec4 vertexDC;","attribute vec2 tcoordTC;","varying vec2 tcoord;","void main() { tcoord = tcoordTC; gl_Position = vertexDC; }"].join("\n"),"//VTK::System::Dec\n\nin vec2 tcoord;\n\nuniform sampler2D translucentRTexture;\nuniform sampler2D translucentRGBATexture;\n\n// the output of this shader\n//VTK::Output::Dec\n\nvoid main()\n{\n  vec4 t1Color = texture(translucentRGBATexture, tcoord);\n  float t2Color = texture(translucentRTexture, tcoord).r;\n  gl_FragData[0] = vec4(t1Color.rgb/max(t2Color,0.01), 1.0 - t1Color.a);\n}\n","")},e.createVBO=n=>{const r=n.getContext();t.tris.setOpenGLRenderWindow(n),e.createVertexBuffer();const o=t.copyShader;t.tris.getCABO().bind(),t.copyVAO.addAttributeArray(o,t.tris.getCABO(),"vertexDC",t.tris.getCABO().getVertexOffset(),t.tris.getCABO().getStride(),r.FLOAT,3,r.FALSE)||xv("Error setting vertexDC in copy shader VAO."),t.copyVAO.addAttributeArray(o,t.tris.getCABO(),"tcoordTC",t.tris.getCABO().getTCoordOffset(),t.tris.getCABO().getStride(),r.FLOAT,2,r.FALSE)||xv("Error setting vertexDC in copy shader VAO.")},e.traverse=(n,r,o)=>{if(t.deleted)return;const a=n.getSize(),i=n.getContext();if(t._supported=!1,r.getSelector()||!i||!n.getWebgl2()||!i.getExtension("EXT_color_buffer_half_float")&&!i.getExtension("EXT_color_buffer_float"))return e.setCurrentOperation("translucentPass"),void r.traverse(e);if(t._supported=!0,null===t.framebuffer)e.createFramebuffer(n);else{const 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s=r.getTiledSizeAndOrigin();i.scissor(s.lowerLeftU,s.lowerLeftV,s.usize,s.vsize),i.viewport(s.lowerLeftU,s.lowerLeftV,s.usize,s.vsize)},e.getShaderReplacement=()=>t._supported?yv:null,e.releaseGraphicsResources=n=>{t.framebuffer&&(t.framebuffer.releaseGraphicsResources(n),t.framebuffer=null),t.translucentRGBATexture&&(t.translucentRGBATexture.releaseGraphicsResources(n),t.translucentRGBATexture=null),t.translucentRTexture&&(t.translucentRTexture.releaseGraphicsResources(n),t.translucentRTexture=null),t.translucentZTexture&&(t.translucentZTexture.releaseGraphicsResources(n),t.translucentZTexture=null),t.copyVAO&&(t.copyVAO.releaseGraphicsResources(n),t.copyVAO=null),t.copyShader&&(t.copyShader.releaseGraphicsResources(n),t.copyShader=null),t.tris&&(t.tris.releaseGraphicsResources(n),t.tris=null),e.modified()}}(e,t)}var Cv={newInstance:sn.newInstance(Av,"vtkOpenGLOrderIndependentTranslucentPass"),extend:Av};const Sv={opaqueActorCount:0,translucentActorCount:0,volumeCount:0,overlayActorCount:0,framebuffer:null,depthRequested:!1};function Pv(e,t,n={}){Object.assign(t,Sv,n),vv.extend(e,t,n),sn.get(e,t,["framebuffer","opaqueActorCount","translucentActorCount","volumeCount"]),function(e,t){t.classHierarchy.push("vtkForwardPass"),e.traverse=(n,r=null)=>{if(t.deleted)return;t._currentParent=r,e.setCurrentOperation("buildPass"),n.traverse(e);const o=n.getRenderable().getNumberOfLayers(),a=n.getRenderable().getRenderersByReference();for(let r=0;r<o;r++)for(let o=0;o<a.length;o++){const i=a[o],s=n.getViewNodeFor(i);if(i.getDraw()&&i.getLayer()===r){if(t.opaqueActorCount=0,t.translucentActorCount=0,t.volumeCount=0,t.overlayActorCount=0,e.setCurrentOperation("queryPass"),s.traverse(e),(t.opaqueActorCount>0||t.translucentActorCount>0)&&t.volumeCount>0||t.depthRequested){const 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uT={type:null,hash:null,code:null,outputNames:null,outputTypes:null};function dT(e,t,n={}){Object.assign(t,uT,n),t.outputNames=[],t.outputTypes=[],t.outputInterpolations=[],t.builtinOutputNames=[],t.builtinOutputTypes=[],t.builtinInputNames=[],t.builtinInputTypes=[],sn.obj(e,t),sn.setGet(e,t,["type","hash","code"]),sn.getArray(e,t,["outputTypes","outputNames","outputInterpolations"]),function(e,t){t.classHierarchy.push("vtkWebGPUShaderDescription"),e.hasOutput=e=>t.outputNames.includes(e),e.addOutput=(e,n,r=void 0)=>{t.outputTypes.push(e),t.outputNames.push(n),t.outputInterpolations.push(r)},e.addBuiltinOutput=(e,n)=>{t.builtinOutputTypes.push(e),t.builtinOutputNames.push(n)},e.addBuiltinInput=(e,n)=>{t.builtinInputTypes.push(e),t.builtinInputNames.push(n)},e.replaceShaderCode=(e,n)=>{const r=[];let o=[];if(n&&r.push(n.getShaderCode()),e||t.builtinInputNames.length){const n=[];if(n.push(`struct ${t.type}Input\n{`),e){const 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 //VTK::RenderEncoder::Impl\n  return output;\n}\n",t.vertexShaderTemplate=t.vertexShaderTemplate||"\n//VTK::Renderer::Dec\n\n//VTK::Color::Dec\n\n//VTK::Normal::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::Select::Dec\n\n//VTK::Mapper::Dec\n\n//VTK::IOStructs::Dec\n\n@vertex\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output : vertexOutput;\n\n  // var vertex: vec4<f32> = vertexBC;\n\n  //VTK::Color::Impl\n\n  //VTK::Normal::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::Select::Impl\n\n  //VTK::Position::Impl\n\n  return output;\n}\n",t.shaderReplacements=new Map,sn.get(e,t,["pipeline","vertexInput"]),sn.setGet(e,t,["additionalBindables","device","fragmentShaderTemplate","interpolate","numberOfInstances","numberOfVertices","pipelineHash","shaderReplacements","SSBO","textureViews","topology","UBO","vertexShaderTemplate","WebGPURenderer"]),function(e,t){t.classHierarchy.push("vtkWebGPUSimpleMapper"),e.generateShaderDescriptions=(n,r,o)=>{const 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pipeline ${n.depthStencil.format} while encoder has ${e}`),console.trace())}t.boundPipeline=e},e.replaceShaderCode=e=>{t.replaceShaderCodeFunction(e)},e.setColorTextureView=(e,n)=>{t.colorTextureViews[e]!==n&&(t.colorTextureViews[e]=n)},e.activateBindGroup=e=>{const n=t.boundPipeline.getDevice(),r=t.boundPipeline.getBindGroupLayoutCount(e.getLabel());t.handle.setBindGroup(r,e.getBindGroup(n));const o=n.getBindGroupLayoutDescription(e.getBindGroupLayout(n)),a=n.getBindGroupLayoutDescription(t.boundPipeline.getBindGroupLayout(r));o!==a&&(console.log(`renderEncoder ${t.pipelineHash} mismatched bind group layouts bind group has\n${o}\n versus pipeline\n${a}\n`),console.trace())},e.attachTextureViews=()=>{for(let e=0;e<t.colorTextureViews.length;e++)t.description.colorAttachments[e]?t.description.colorAttachments[e].view=t.colorTextureViews[e].getHandle():t.description.colorAttachments[e]={view:t.colorTextureViews[e].getHandle()};t.depthTextureView&&(t.description.depthStencilAttachment.view=t.depthTextureView.getHandle())},e.registerDrawCallback=(e,n)=>{for(let r=0;r<t.drawCallbacks.length;r++)if(t.drawCallbacks[r].pipeline===e)return void t.drawCallbacks[r].callbacks.push(n);t.drawCallbacks.push({pipeline:e,callbacks:[n]})};for(let n=0;n<PT.length;n++)e[PT[n]]=(...e)=>t.handle[PT[n]](...e)}(e,t)}var OT={newInstance:Xt(IT,"vtkWebGPURenderEncoder"),extend:IT};const RT={device:null,handle:null,label:null,options:null};function MT(e,t,n={}){Object.assign(t,RT,n),sn.obj(e,t),t.options={},t.bindGroupLayoutEntry={visibility:GPUShaderStage.VERTEX|GPUShaderStage.FRAGMENT,sampler:{}},t.bindGroupTime={},sn.obj(t.bindGroupTime,{mtime:0}),sn.get(e,t,["bindGroupTime","handle","options"]),sn.setGet(e,t,["bindGroupLayoutEntry","device","label"]),function(e,t){t.classHierarchy.push("vtkWebGPUSampler"),e.create=(e,n={})=>{t.device=e,t.options.addressModeU=n.addressModeU?n.addressModeU:"clamp-to-edge",t.options.addressModeV=n.addressModeV?n.addressModeV:"clamp-to-edge",t.options.addressModeW=n.addressModeW?n.addressModeW:"clamp-to-edge",t.options.magFilter=n.magFilter?n.magFilter:"nearest",t.options.minFilter=n.minFilter?n.minFilter:"nearest",t.options.mipmapFilter=n.mipmapFilter?n.mipmapFilter:"nearest",t.options.label=t.label,t.handle=t.device.getHandle().createSampler(t.options),t.bindGroupTime.modified()},e.getShaderCode=(e,n)=>`@binding(${e}) @group(${n}) var ${t.label}: sampler;`,e.getBindGroupEntry=()=>({resource:t.handle})}(e,t)}var DT={newInstance:sn.newInstance(MT),extend:MT};const ET={texture:null,handle:null,sampler:null,label:null};function VT(e,t,n={}){Object.assign(t,ET,n),sn.obj(e,t),t.bindGroupLayoutEntry={visibility:GPUShaderStage.VERTEX|GPUShaderStage.FRAGMENT,texture:{sampleType:"float",viewDimension:"2d"}},t.bindGroupTime={},sn.obj(t.bindGroupTime,{mtime:0}),sn.get(e,t,["bindGroupTime","texture"]),sn.setGet(e,t,["bindGroupLayoutEntry","label","sampler"]),function(e,t){t.classHierarchy.push("vtkWebGPUTextureView"),e.create=(e,n)=>{t.texture=e,t.options=n,t.options.dimension=t.options.dimension||"2d",t.options.label=t.label,t.textureHandle=e.getHandle(),t.handle=t.textureHandle.createView(t.options),t.bindGroupLayoutEntry.texture.viewDimension=t.options.dimension;const r=gT.getDetailsFromTextureFormat(t.texture.getFormat());t.bindGroupLayoutEntry.texture.sampleType=r.sampleType},e.createFromTextureHandle=(e,n)=>{t.texture=null,t.options=n,t.options.dimension=t.options.dimension||"2d",t.options.label=t.label,t.textureHandle=e,t.handle=t.textureHandle.createView(t.options),t.bindGroupLayoutEntry.texture.viewDimension=t.options.dimension;const r=gT.getDetailsFromTextureFormat(n.format);t.bindGroupLayoutEntry.texture.sampleType=r.sampleType,t.bindGroupTime.modified()},e.getBindGroupEntry=()=>({resource:e.getHandle()}),e.getShaderCode=(e,n)=>{let r="f32";"sint"===t.bindGroupLayoutEntry.texture.sampleType?r="i32":"uint"===t.bindGroupLayoutEntry.texture.sampleType&&(r="u32");let o=`@binding(${e}) @group(${n}) var ${t.label}: texture_${t.options.dimension}<${r}>;`;return"depth"===t.bindGroupLayoutEntry.texture.sampleType&&(o=`@binding(${e}) @group(${n}) var ${t.label}: texture_depth_${t.options.dimension};`),o},e.addSampler=(n,r)=>{const o=DT.newInstance({label:`${t.label}Sampler`});o.create(n,r),e.setSampler(o)},e.getBindGroupTime=()=>(t.texture&&t.texture.getHandle()!==t.textureHandle&&(t.textureHandle=t.texture.getHandle(),t.handle=t.textureHandle.createView(t.options),t.bindGroupTime.modified()),t.bindGroupTime),e.getHandle=()=>(t.texture&&t.texture.getHandle()!==t.textureHandle&&(t.textureHandle=t.texture.getHandle(),t.handle=t.textureHandle.createView(t.options),t.bindGroupTime.modified()),t.handle)}(e,t)}var LT={newInstance:sn.newInstance(VT),extend:VT};const{vtkErrorMacro:BT}=sn;function FT(e,t){t.classHierarchy.push("vtkWebGPUTexture");const n=(e,n,r,o)=>{const a=gT.getDetailsFromTextureFormat(t.format),i=n*a.numComponents,s=i*r*o,l=2===a.elementSize&&"float"===a.sampleType;if(!e?.length&&s>0)return BT("Texture upload failed: missing nativeArray data."),null;if(e.length<s)return BT(`Texture upload failed: expected ${s} values but received ${e.length}.`),null;const c=e.length>s?e.subarray(0,s):e,u=c.BYTES_PER_ELEMENT||a.elementSize,d=n*a.stride,p=256*Math.floor((d+255)/256),f=((e,t)=>{if(2===e.elementSize&&"float"===e.sampleType)return"Uint16Array";if("sint"===e.sampleType){if(1===e.elementSize)return"Int8Array";if(2===e.elementSize)return"Int16Array";if(4===e.elementSize)return"Int32Array"}else if("unfilterable-float"===e.sampleType){if(4===e.elementSize)return"Float32Array"}else{if(1===e.elementSize)return"Uint8Array";if(2===e.elementSize)return"Uint16Array";if(4===e.elementSize)return"Uint32Array"}return t})(a,c.constructor.name),g=p/(l?2:sn.newTypedArray(f,0).BYTES_PER_ELEMENT),m=i*u;if(!(l||c.constructor.name!==f||m!==p))return{data:c,bytesPerRow:p};const h=r*o,v=sn.newTypedArray(f,g*h);if(l)for(let e=0;e<h;e++){const t=e*i,n=e*g;for(let e=0;e<i;e++)v[n+e]=Md.toHalf(c[t+e])}else if(g===i)v.set(c);else for(let 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a=n=>{t.device.getHandle().queue.copyExternalImageToTexture({source:n,flipY:r.flip},{texture:t.handle,premultipliedAlpha:!0,mipLevel:0,origin:{x:0,y:0,z:0}},[n.width,n.height,t.depth]),3!==e.getDimensionality()&&t.mipLevel>0&&Eu.generateMipmaps(t.device.getHandle(),t.handle,t.mipLevel+1),t.ready=!0};if(r.canvas)return void a(r.canvas);if(r.imageBitmap)return r.width=r.imageBitmap.width,r.height=r.imageBitmap.height,r.depth=1,r.format="rgba8unorm",r.flip=!0,void a(r.imageBitmap);if(r.jsImageData)return r.width=r.jsImageData.width,r.height=r.jsImageData.height,r.depth=1,r.format="rgba8unorm",r.flip=!0,void a(r.jsImageData);if(r.image)return r.width=r.image.width,r.height=r.image.height,r.depth=1,r.format="rgba8unorm",r.flip=!0,void a(r.image);r.nativeArray&&(o=r.nativeArray);const i=3===e.getDimensionality(),s=n(o,t.width,t.height,i?t.depth:1);if(!s)return;const 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d=n(u,s,l,c);d&&(t.device.getHandle().queue.writeTexture({texture:t.handle,mipLevel:0,origin:{x:o,y:a,z:i}},d.data,{offset:0,bytesPerRow:d.bytesPerRow,rowsPerImage:l},{width:s,height:l,depthOrArrayLayers:c}),3!==e.getDimensionality()&&t.mipLevel>0&&Eu.generateMipmaps(t.device.getHandle(),t.handle,t.mipLevel+1),t.ready=!0)},e.getScale=()=>{const e=gT.getDetailsFromTextureFormat(t.format);return 2===e.elementSize&&"float"===e.sampleType?1:255},e.getNumberOfComponents=()=>gT.getDetailsFromTextureFormat(t.format).numComponents,e.getDimensionality=()=>{let e=0;return t.width>1&&e++,t.height>1&&e++,t.depth>1&&e++,e},e.resizeToMatch=e=>{e.getWidth()===t.width&&e.getHeight()===t.height&&e.getDepth()===t.depth||(t.width=e.getWidth(),t.height=e.getHeight(),t.depth=e.getDepth(),t.handle=t.device.getHandle().createTexture({size:[t.width,t.height,t.depth],format:t.format,usage:t.usage,label:t.label}))},e.resize=(e,n,r=1)=>{e===t.width&&n===t.height&&r===t.depth||(t.width=e,t.height=n,t.depth=r,t.handle=t.device.getHandle().createTexture({size:[t.width,t.height,t.depth],format:t.format,usage:t.usage,label:t.label}))},e.createView=(n,r={})=>{r.dimension||(r.dimension=1===t.depth?"2d":"3d");const o=LT.newInstance({label:n});return o.create(e,r),o}}const NT={device:null,handle:null,buffer:null,ready:!1,label:null};function kT(e,t,n={}){Object.assign(t,NT,n),sn.obj(e,t),sn.get(e,t,["handle","ready","width","height","depth","format","usage"]),sn.setGet(e,t,["device","label"]),FT(e,t)}var GT={newInstance:sn.newInstance(kT),extend:kT};const UT={renderEncoder:null,colorTexture:null,depthTexture:null};function _T(e,t,n={}){Object.assign(t,UT,n),vv.extend(e,t,n),sn.get(e,t,["colorTexture","depthTexture"]),function(e,t){t.classHierarchy.push("vtkWebGPUOpaquePass"),e.traverse=(n,r)=>{if(t.deleted)return;t._currentParent=r;const o=r.getDevice();if(t.renderEncoder)t.colorTexture.resize(r.getCanvas().width,r.getCanvas().height),t.depthTexture.resize(r.getCanvas().width,r.getCanvas().height);else{e.createRenderEncoder(),t.colorTexture=GT.newInstance({label:"opaquePassColor"}),t.colorTexture.create(o,{width:r.getCanvas().width,height:r.getCanvas().height,format:"rgba16float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_SRC});const n=t.colorTexture.createView("opaquePassColorTexture");t.renderEncoder.setColorTextureView(0,n),t.depthFormat="depth32float",t.depthTexture=GT.newInstance({label:"opaquePassDepth"}),t.depthTexture.create(o,{width:r.getCanvas().width,height:r.getCanvas().height,format:t.depthFormat,usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_SRC});const a=t.depthTexture.createView("opaquePassDepthTexture");t.renderEncoder.setDepthTextureView(a)}t.renderEncoder.attachTextureViews(),e.setCurrentOperation("opaquePass"),n.setRenderEncoder(t.renderEncoder),n.traverse(e)},e.getColorTextureView=()=>t.renderEncoder.getColorTextureViews()[0],e.getDepthTextureView=()=>t.renderEncoder.getDepthTextureView(),e.createRenderEncoder=()=>{t.renderEncoder=OT.newInstance({label:"OpaquePass"}),t.renderEncoder.setPipelineHash("op")}}(e,t)}var KT={newInstance:sn.newInstance(_T,"vtkWebGPUOpaquePass"),extend:_T};const zT={colorTextureView:null,depthTextureView:null};function WT(e,t,n={}){Object.assign(t,zT,n),vv.extend(e,t,n),sn.setGet(e,t,["colorTextureView","depthTextureView"]),function(e,t){t.classHierarchy.push("vtkWebGPUOrderIndependentTranslucentPass"),e.traverse=(n,r)=>{if(t.deleted)return;t._currentParent=r;const o=r.getDevice();if(t.translucentRenderEncoder)t.translucentColorTexture.resizeToMatch(t.colorTextureView.getTexture()),t.translucentAccumulateTexture.resizeToMatch(t.colorTextureView.getTexture());else{e.createRenderEncoder(),e.createFinalEncoder(),t.translucentColorTexture=GT.newInstance({label:"translucentPassColor"}),t.translucentColorTexture.create(o,{width:r.getCanvas().width,height:r.getCanvas().height,format:"rgba16float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING});const n=t.translucentColorTexture.createView("oitpColorTexture");t.translucentRenderEncoder.setColorTextureView(0,n),t.translucentAccumulateTexture=GT.newInstance({label:"translucentPassAccumulate"}),t.translucentAccumulateTexture.create(o,{width:r.getCanvas().width,height:r.getCanvas().height,format:"r16float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING});const a=t.translucentAccumulateTexture.createView("oitpAccumTexture");t.translucentRenderEncoder.setColorTextureView(1,a),t.fullScreenQuad=ST.newInstance(),t.fullScreenQuad.setDevice(r.getDevice()),t.fullScreenQuad.setPipelineHash("oitpfsq"),t.fullScreenQuad.setTextureViews(t.translucentRenderEncoder.getColorTextureViews()),t.fullScreenQuad.setFragmentShaderTemplate("\n//VTK::Mapper::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::RenderEncoder::Dec\n\n//VTK::IOStructs::Dec\n\n@fragment\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output: fragmentOutput;\n\n  var tcoord: vec2<i32> = vec2<i32>(i32(input.fragPos.x), i32(input.fragPos.y));\n  var reveal: f32 = textureLoad(oitpAccumTexture, tcoord, 0).r;\n  if (reveal == 1.0) { discard; }\n  var tcolor: vec4<f32> = textureLoad(oitpColorTexture, tcoord, 0);\n  var total: f32 = max(tcolor.a, 0.01);\n  var computedColor: vec4<f32> = vec4<f32>(tcolor.r/total, tcolor.g/total, tcolor.b/total, 1.0 - reveal);\n\n  //VTK::RenderEncoder::Impl\n  return output;\n}\n")}t.translucentRenderEncoder.setDepthTextureView(t.depthTextureView),t.translucentRenderEncoder.attachTextureViews(),e.setCurrentOperation("translucentPass"),n.setRenderEncoder(t.translucentRenderEncoder),n.traverse(e),e.finalPass(r,n)},e.finalPass=(e,n)=>{t.translucentFinalEncoder.setColorTextureView(0,t.colorTextureView),t.translucentFinalEncoder.attachTextureViews(),t.translucentFinalEncoder.begin(e.getCommandEncoder()),n.scissorAndViewport(t.translucentFinalEncoder),t.fullScreenQuad.prepareAndDraw(t.translucentFinalEncoder),t.translucentFinalEncoder.end()},e.getTextures=()=>[t.translucentColorTexture,t.translucentAccumulateTexture],e.createRenderEncoder=()=>{t.translucentRenderEncoder=OT.newInstance({label:"translucentRender"});const e=t.translucentRenderEncoder.getDescription();e.colorAttachments=[{view:void 0,clearValue:[0,0,0,0],loadOp:"clear",storeOp:"store"},{view:void 0,clearValue:[1,0,0,0],loadOp:"clear",storeOp:"store"}],e.depthStencilAttachment={view:void 0,depthLoadOp:"load",depthStoreOp:"store"},t.translucentRenderEncoder.setReplaceShaderCodeFunction((e=>{const t=e.getShaderDescription("fragment");t.addOutput("vec4<f32>","outColor"),t.addOutput("f32","outAccum"),t.addBuiltinInput("vec4<f32>","@builtin(position) fragPos");let n=t.getCode();n=rT.substitute(n,"//VTK::RenderEncoder::Impl",["var w: f32 = computedColor.a * pow(0.1 + input.fragPos.z, 2.0);","output.outColor = vec4<f32>(computedColor.rgb*w, w);","output.outAccum = computedColor.a;"]).result,t.setCode(n)})),t.translucentRenderEncoder.setPipelineHash("oitpr"),t.translucentRenderEncoder.setPipelineSettings({primitive:{cullMode:"none"},depthStencil:{depthWriteEnabled:!1,depthCompare:"greater",format:"depth32float"},fragment:{targets:[{format:"rgba16float",blend:{color:{srcFactor:"one",dstFactor:"one"},alpha:{srcFactor:"one",dstFactor:"one"}}},{format:"r16float",blend:{color:{srcFactor:"zero",dstFactor:"one-minus-src"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}})},e.createFinalEncoder=()=>{t.translucentFinalEncoder=OT.newInstance({label:"translucentFinal"}),t.translucentFinalEncoder.setDescription({colorAttachments:[{view:null,loadOp:"load",storeOp:"store"}]}),t.translucentFinalEncoder.setReplaceShaderCodeFunction((e=>{const t=e.getShaderDescription("fragment");t.addOutput("vec4<f32>","outColor"),t.addBuiltinInput("vec4<f32>","@builtin(position) fragPos");let n=t.getCode();n=rT.substitute(n,"//VTK::RenderEncoder::Impl",["output.outColor = vec4<f32>(computedColor.rgb, computedColor.a);"]).result,t.setCode(n)})),t.translucentFinalEncoder.setPipelineHash("oitpf"),t.translucentFinalEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:"rgba16float",blend:{color:{srcFactor:"src-alpha",dstFactor:"one-minus-src-alpha"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}})}}(e,t)}var HT={newInstance:sn.newInstance(WT,"vtkWebGPUOrderIndependentTranslucentPass"),extend:WT};var jT={BufferUsage:{Verts:0,Lines:1,Triangles:2,Strips:3,LinesFromStrips:4,LinesFromTriangles:5,Points:6,UniformArray:7,PointArray:8,NormalsFromPoints:9,Texture:10,RawVertex:11,Storage:12,Index:13},PrimitiveTypes:{Start:0,Points:0,Lines:1,Triangles:2,TriangleStrips:3,TriangleEdges:4,TriangleStripEdges:5,End:6}};const XT=["getMappedRange","mapAsync","unmap"];function qT(e,t){t.classHierarchy.push("vtkWebGPUBuffer"),e.create=(e,n)=>{t.handle=t.device.getHandle().createBuffer({size:e,usage:n,label:t.label}),t.sizeInBytes=e,t.usage=n},e.write=e=>{!function(e,t,n,r){const o=r.byteLength,a=e.createBuffer({size:o,usage:GPUBufferUsage.COPY_SRC,mappedAtCreation:!0}),i=a.getMappedRange(0,o);new Uint8Array(i).set(new Uint8Array(r)),a.unmap();const s=e.createCommandEncoder();s.copyBufferToBuffer(a,0,t,n,o);const l=s.finish();e.queue.submit([l]),a.destroy()}(t.device.getHandle(),t.handle,0,e.buffer)},e.createAndWrite=(e,n)=>{const r=4*Math.ceil(e.byteLength/4);t.handle=t.device.getHandle().createBuffer({size:r,usage:n,mappedAtCreation:!0,label:t.label}),t.sizeInBytes=r,t.usage=n,new Uint8Array(t.handle.getMappedRange()).set(new Uint8Array(e.buffer)),t.handle.unmap()};for(let n=0;n<XT.length;n++)e[XT[n]]=(...e)=>t.handle[XT[n]](...e)}const YT={device:null,handle:null,sizeInBytes:0,strideInBytes:0,arrayInformation:null,usage:null,label:null,sourceTime:null};function JT(e,t,n={}){Object.assign(t,YT,n),sn.obj(e,t),sn.get(e,t,["handle","sizeInBytes","usage"]),sn.setGet(e,t,["strideInBytes","device","arrayInformation","label","sourceTime"]),qT(e,t)}var ZT={newInstance:sn.newInstance(JT),extend:JT,...jT};const{Representation:QT}=us,{PrimitiveTypes:$T}=jT;class ex{constructor(){this.keys=new Uint32Array(10),this.values=new Uint32Array(10),this.count=0}clear(){this.count=0}has(e){for(let t=0;t<this.count;t++)if(this.keys[t]===e)return!0}get(e){for(let t=0;t<this.count;t++)if(this.keys[t]===e)return this.values[t]}set(e,t){this.count<9&&(this.keys[this.count]=e,this.values[this.count++]=t)}}function tx(e,t,n){let r=e.pointIdToFlatId[t];return r<0&&(r=e.flatId,e.pointIdToFlatId[t]=r,e.flatIdToPointId[e.flatId]=t,e.flatIdToCellId[e.flatId]=n,e.flatId++),r}function nx(e,t,n){const r=e.length;for(let o=0;o<r;o++){let a=e[o];if(n.cellProvokedMap.has(a)){n.ibo[n.iboId++]=n.cellProvokedMap.get(a);for(let i=o+1;i<o+r;i++){a=e[i%r];const o=tx(n,a,t);n.ibo[n.iboId++]=o}return}}for(let o=0;o<r;o++){let a=e[o];if(!n.provokedPointIds[a]){let i=tx(n,a,t);n.provokedPointIds[a]=1,n.cellProvokedMap.set(a,i),n.flatIdToCellId[i]=t,n.ibo[n.iboId++]=i;for(let s=o+1;s<o+r;s++)a=e[s%r],i=tx(n,a,t),n.ibo[n.iboId++]=i;return}}let o=e[0],a=n.flatId;n.cellProvokedMap.set(o,a),n.flatIdToPointId[n.flatId]=o,n.flatIdToCellId[n.flatId]=t,n.flatId++,n.ibo[n.iboId++]=a;for(let i=1;i<r;i++)o=e[i],a=tx(n,o,t),n.ibo[n.iboId++]=a}function rx(e,t,n){const r=e.length;n.iboSize+=r;for(let t=0;t<r;t++){const r=e[t];if(n.cellProvokedMap.has(r))return}for(let t=0;t<r;t++){const r=e[t];if(!n.provokedPointIds[r])return n.provokedPointIds[r]=1,void n.cellProvokedMap.set(r,1)}n.cellProvokedMap.set(e[0],1),n.extraPoints++}let ox;const ax=new Uint32Array(1),ix=new Uint32Array(2),sx=new Uint32Array(3),lx={anythingToPoints(e,t,n,r,o){for(let a=0;a<e;++a)ax[0]=t[n+a],ox(ax,r,o)},linesToWireframe(e,t,n,r,o){for(let a=0;a<e-1;++a)ix[0]=t[n+a],ix[1]=t[n+a+1],ox(ix,r,o)},polysToWireframe(e,t,n,r,o){if(e>2)for(let a=0;a<e;++a)ix[0]=t[n+a],ix[1]=t[n+(a+1)%e],ox(ix,r,o)},stripsToWireframe(e,t,n,r,o){if(e>2){for(let a=0;a<e-1;++a)ix[0]=t[n+a],ix[1]=t[n+a+1],ox(ix,r,o);for(let a=0;a<e-2;a++)ix[0]=t[n+a],ix[1]=t[n+a+2],ox(ix,r,o)}},polysToSurface(e,t,n,r,o){for(let a=0;a<e-2;a++)sx[0]=t[n],sx[1]=t[n+a+1],sx[2]=t[n+a+2],ox(sx,r,o)},stripsToSurface(e,t,n,r,o){for(let a=0;a<e-2;a++)sx[0]=t[n+a],sx[1]=t[n+a+1+a%2],sx[2]=t[n+a+1+(a+1)%2],ox(sx,r,o)}};function cx(e,t){t.classHierarchy.push("vtkWebGPUIndexBuffer"),e.buildIndexBuffer=e=>{const n=e.cells,r=e.primitiveType,o=e.representation,a=e.cellOffset,i=n.getData(),s=i.length,l=function(e){switch(e){case $T.Points:return"points";case $T.Lines:return"lines";case $T.Triangles:case $T.TriangleEdges:return"polys";case $T.TriangleStripEdges:case $T.TriangleStrips:return"strips";default:return""}}(r),c=e.numberOfPoints,u={provokedPointIds:new Uint8Array(c),extraPoints:0,iboSize:0,flatId:0,iboId:0,cellProvokedMap:new ex};let d=null;d=o===QT.POINTS||r===$T.Points?lx.anythingToPoints:o===QT.WIREFRAME||r===$T.Lines?lx[`${l}ToWireframe`]:lx[`${l}ToSurface`],ox=rx;let p=a||0;for(let e=0;e<s;)u.cellProvokedMap.clear(),d(i[e],i,e+1,p,u),e+=i[e]+1,p++;u.flatIdToPointId=c<=65535?new Uint16Array(c+u.extraPoints):new Uint32Array(c+u.extraPoints),c+u.extraPoints<36863?u.pointIdToFlatId=new Int16Array(c):u.pointIdToFlatId=new Int32Array(c),c+u.extraPoints<=65535?(u.ibo=new Uint16Array(u.iboSize),e.format="uint16"):(u.ibo=new Uint32Array(u.iboSize),e.format="uint32"),u.flatIdToCellId=p<=65535?new Uint16Array(c+u.extraPoints):new Uint32Array(c+u.extraPoints),u.pointIdToFlatId.fill(-1),u.provokedPointIds.fill(0),ox=nx,p=a||0;for(let e=0;e<s;)u.cellProvokedMap.clear(),d(i[e],i,e+1,p,u),e+=i[e]+1,p++;delete u.provokedPointIds,delete u.pointIdToFlatId,e.nativeArray=u.ibo,t.flatIdToPointId=u.flatIdToPointId,t.flatIdToCellId=u.flatIdToCellId,t.flatSize=u.flatId,t.indexCount=u.iboId}}const ux={flatIdToPointId:null,flatIdToCellId:null,flatSize:0,indexCount:0};function dx(e,t,n={}){Object.assign(t,ux,n),ZT.extend(e,t,n),sn.setGet(e,t,["flatIdToPointId","flatIdToCellId","flatSize","indexCount"]),cx(e,t)}var px={newInstance:sn.newInstance(dx),extend:dx,...jT};const{BufferUsage:fx}=jT,{vtkErrorMacro:gx}=ln,{VtkDataTypes:mx}=Is;function hx(e,t,n,r,o){const a={},i=e.getFlatSize();if(!i)return a;let s=[0,0,0,0];o.shift&&(o.shift.length?s=o.shift:s.fill(o.shift));let l=[1,1,1,1];o.scale&&(o.scale.length?l=o.scale:l.fill(o.scale));const c=!!Object.prototype.hasOwnProperty.call(o,"packExtra")&&o.packExtra;let u,d=0;const p=Ct(r,i*(n+(c?1:0)));let f=e.getFlatIdToPointId();o.cellData&&(f=e.getFlatIdToCellId()),1===n?u=function(e){p[d++]=l[0]*t[e]+s[0]}:2===n?u=function(e){p[d++]=l[0]*t[e]+s[0],p[d++]=l[1]*t[e+1]+s[1]}:3!==n||c?3===n&&c?u=function(e){p[d++]=l[0]*t[e]+s[0],p[d++]=l[1]*t[e+1]+s[1],p[d++]=l[2]*t[e+2]+s[2],p[d++]=1*l[3]+s[3]}:4===n&&(u=function(e){p[d++]=l[0]*t[e]+s[0],p[d++]=l[1]*t[e+1]+s[1],p[d++]=l[2]*t[e+2]+s[2],p[d++]=l[3]*t[e+3]+s[3]}):u=function(e){p[d++]=l[0]*t[e]+s[0],p[d++]=l[1]*t[e+1]+s[1],p[d++]=l[2]*t[e+2]+s[2]};for(let e=0;e<i;e++){u(n*f[e])}return a.nativeArray=p,a}function vx(e,t,n,r){const o=[];return Wo([e[3*r]-e[3*n],e[3*r+1]-e[3*n+1],e[3*r+2]-e[3*n+2]],[e[3*t]-e[3*n],e[3*t+1]-e[3*n+1],e[3*t+2]-e[3*n+2]],o),jo(o),o}function Tx(e,t){function n(e){let n,r;if(e.dataArray&&!e.nativeArray&&(e.nativeArray=e.dataArray.getData()),e.usage===fx.Index&&(n=px.newInstance({label:e.label}),n.setDevice(t.device),r=GPUBufferUsage.INDEX|GPUBufferUsage.COPY_DST,n.buildIndexBuffer(e),n.createAndWrite(e.nativeArray,r),n.setArrayInformation([{format:e.format}])),n||(n=ZT.newInstance({label:e.label}),n.setDevice(t.device)),e.usage===fx.UniformArray&&(r=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,n.createAndWrite(e.nativeArray,r)),e.usage===fx.Storage&&(r=GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_DST,n.createAndWrite(e.nativeArray,r)),e.usage===fx.Texture&&(r=GPUBufferUsage.COPY_SRC,n.createAndWrite(e.nativeArray,r)),e.usage===fx.PointArray){r=GPUBufferUsage.VERTEX;const t=gT.getNativeTypeFromBufferFormat(e.format),o=hx(e.indexBuffer,e.dataArray.getData(),e.dataArray.getNumberOfComponents(),t,{packExtra:e.packExtra,shift:e.shift,scale:e.scale,cellData:e.cellData,cellOffset:e.cellOffset});n.createAndWrite(o.nativeArray,r),n.setStrideInBytes(gT.getByteStrideFromBufferFormat(e.format)),n.setArrayInformation([{offset:0,format:e.format,interpolation:e.cellData?"flat":"perspective"}])}if(e.usage===fx.NormalsFromPoints){r=GPUBufferUsage.VERTEX;const t=gT.getNativeTypeFromBufferFormat(e.format),o=function(e,t){const n=t.getData(),r=e.getData();if(!r||!n)return null;const o=new Int8Array(4*e.getNumberOfCells()),a=r.length;let i=0;for(let e=0;e<a;){const t=vx(n,r[e+1],r[e+2],r[e+3]);o[i++]=127*t[0],o[i++]=127*t[1],o[i++]=127*t[2],o[i++]=127,e+=r[e]+1}return o}(e.cells,e.dataArray),a=hx(e.indexBuffer,o,4,t,{cellData:!0});n.createAndWrite(a.nativeArray,r),n.setStrideInBytes(gT.getByteStrideFromBufferFormat(e.format)),n.setArrayInformation([{offset:0,format:e.format,interpolation:"flat"}])}return e.usage===fx.RawVertex&&(r=GPUBufferUsage.VERTEX,n.createAndWrite(e.nativeArray,r),n.setStrideInBytes(gT.getByteStrideFromBufferFormat(e.format)),n.setArrayInformation([{offset:0,format:e.format}])),n.setSourceTime(e.time),n}t.classHierarchy.push("vtkWebGPUBufferManager"),e.hasBuffer=e=>t.device.hasCachedObject(e),e.getBuffer=e=>e.hash?t.device.getCachedObject(e.hash,n,e):n(e),e.getBufferForPointArray=(t,n)=>{const r=function(e){let t;switch(e.getDataType()){case mx.UNSIGNED_CHAR:t="uint8";break;case mx.FLOAT:t="float32";break;case mx.UNSIGNED_INT:t="uint32";break;case mx.INT:t="sint32";break;case mx.DOUBLE:t="float32";break;case mx.UNSIGNED_SHORT:t="uint16";break;case mx.SHORT:t="sin16";break;default:t="float32"}switch(e.getNumberOfComponents()){case 2:t+="x2";break;case 3:t.includes("32")||gx(`unsupported x3 type for ${t}`),t+="x3";break;case 4:t+="x4"}return t}(t),o={hash:`${t.getMTime()}I${n.getMTime()}${r}`,usage:fx.PointArray,format:r,dataArray:t,indexBuffer:n};return e.getBuffer(o)},e.getFullScreenQuadBuffer=()=>{if(t.fullScreenQuadBuffer)return t.fullScreenQuadBuffer;t.fullScreenQuadBuffer=ZT.newInstance(),t.fullScreenQuadBuffer.setDevice(t.device);const e=new Float32Array([-1,-1,0,1,-1,0,1,1,0,-1,-1,0,1,1,0,-1,1,0]);return t.fullScreenQuadBuffer.createAndWrite(e,GPUBufferUsage.VERTEX),t.fullScreenQuadBuffer.setStrideInBytes(12),t.fullScreenQuadBuffer.setArrayInformation([{offset:0,format:"float32x3"}]),t.fullScreenQuadBuffer}}const xx={device:null,fullScreenQuadBuffer:null};function yx(e,t,n={}){Object.assign(t,xx,n),Vt(e,t),Gt(e,t,["device"]),Tx(e,t)}var bx={newInstance:Xt(yx),extend:yx,...jT};const{BufferUsage:Ax}=bx,{vtkErrorMacro:Cx}=sn;const Sx={bufferEntries:null,bufferEntryNames:null,sizeInBytes:0,label:null,bindGroupLayoutEntry:null,bindGroupEntry:null};function Px(e,t,n={}){Object.assign(t,Sx,n),sn.obj(e,t),t._bufferEntryNames=new Map,t.bufferEntries=[],t.bindGroupLayoutEntry=t.bindGroupLayoutEntry||{buffer:{type:"uniform"}},t.sendTime={},sn.obj(t.sendTime,{mtime:0}),t.bindGroupTime={},sn.obj(t.bindGroupTime,{mtime:0}),t.sendDirty=!0,t.sortDirty=!0,sn.get(e,t,["binding","bindGroupTime"]),sn.setGet(e,t,["bindGroupLayoutEntry","device","label","sizeInBytes"]),function(e,t){t.classHierarchy.push("vtkWebGPUUniformBuffer"),e.addEntry=(e,n)=>{t._bufferEntryNames.has(e)?Cx(`entry named ${e} already exists`):(t.sortDirty=!0,t._bufferEntryNames.set(e,t.bufferEntries.length),t.bufferEntries.push({name:e,type:n,sizeInBytes:gT.getByteStrideFromShaderFormat(n),offset:-1,nativeType:gT.getNativeTypeFromShaderFormat(n),packed:!1}))},e.sortBufferEntries=()=>{if(!t.sortDirty)return;let e=0;const n=[];let r=4;for(let e=0;e<t.bufferEntries.length;e++){const n=t.bufferEntries[e];n.sizeInBytes%16==0&&(r=Math.max(16,r)),n.sizeInBytes%8==0&&(r=Math.max(8,r))}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];!1===o.packed&&o.sizeInBytes%16==0&&(o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes)}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];if(!1===o.packed&&12===o.sizeInBytes)for(let r=0;r<t.bufferEntries.length;r++){const a=t.bufferEntries[r];if(!1===a.packed&&4===a.sizeInBytes){o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes,a.packed=!0,a.offset=e,n.push(a),e+=a.sizeInBytes;break}}}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];if(!o.packed&&o.sizeInBytes%8==0)for(let a=r+1;a<t.bufferEntries.length;a++){const r=t.bufferEntries[a];if(!r.packed&&r.sizeInBytes%8==0){o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes,r.packed=!0,r.offset=e,n.push(r),e+=r.sizeInBytes;break}}}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];if(!o.packed&&o.sizeInBytes%8==0){let r=!1;for(let a=0;!r&&a<t.bufferEntries.length;a++){const i=t.bufferEntries[a];if(!i.packed&&4===i.sizeInBytes)for(let s=a+1;s<t.bufferEntries.length;s++){const a=t.bufferEntries[s];if(!a.packed&&4===a.sizeInBytes){o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes,i.packed=!0,i.offset=e,n.push(i),e+=i.sizeInBytes,a.packed=!0,a.offset=e,n.push(a),e+=a.sizeInBytes,r=!0;break}}}}}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];!o.packed&&o.sizeInBytes>4&&(o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes)}for(let r=0;r<t.bufferEntries.length;r++){const o=t.bufferEntries[r];o.packed||(o.packed=!0,o.offset=e,n.push(o),e+=o.sizeInBytes)}t.bufferEntries=n,t._bufferEntryNames.clear();for(let e=0;e<t.bufferEntries.length;e++)t._bufferEntryNames.set(t.bufferEntries[e].name,e);t.sizeInBytes=e,t.sizeInBytes=r*Math.ceil(t.sizeInBytes/r),t.sortDirty=!1},e.sendIfNeeded=e=>{if(!t.UBO){const n={nativeArray:t.Float32Array,usage:Ax.UniformArray,label:t.label};t.UBO=e.getBufferManager().getBuffer(n),t.bindGroupTime.modified(),t.sendDirty=!1}t.sendDirty&&(e.getHandle().queue.writeBuffer(t.UBO.getHandle(),0,t.arrayBuffer,0,t.sizeInBytes),t.sendDirty=!1),t.sendTime.modified()},e.createView=e=>{e in t==0&&(t.arrayBuffer||(t.arrayBuffer=new ArrayBuffer(t.sizeInBytes)),t[e]=sn.newTypedArray(e,t.arrayBuffer))},e.setValue=(n,r)=>{e.sortBufferEntries();const o=t._bufferEntryNames.get(n);if(void 0===o)return void Cx(`entry named ${n} not found in UBO`);const a=t.bufferEntries[o];e.createView(a.nativeType);const i=t[a.nativeType];a.lastValue!==r&&(i[a.offset/i.BYTES_PER_ELEMENT]=r,t.sendDirty=!0),a.lastValue=r},e.setArray=(n,r)=>{e.sortBufferEntries();const o=t._bufferEntryNames.get(n);if(void 0===o)return void Cx(`entry named ${n} not found in UBO`);const a=t.bufferEntries[o];e.createView(a.nativeType);const i=t[a.nativeType];let s=!1;for(let e=0;e<r.length;e++)a.lastValue&&a.lastValue[e]===r[e]||(i[a.offset/i.BYTES_PER_ELEMENT+e]=r[e],s=!0);s&&(t.sendDirty=!0,a.lastValue=[...r])},e.getBindGroupEntry=()=>({resource:{buffer:t.UBO.getHandle()}}),e.getSendTime=()=>t.sendTime.getMTime(),e.getShaderCode=(n,r)=>{e.sortBufferEntries();const o=[`struct ${t.label}Struct\n{`];for(let e=0;e<t.bufferEntries.length;e++){const n=t.bufferEntries[e];o.push(`  ${n.name}: ${n.type},`)}return o.push(`};\n@binding(${n}) @group(${r}) var<uniform> ${t.label}: ${t.label}Struct;`),o.join("\n")}}(e,t)}var wx={newInstance:sn.newInstance(Px,"vtkWebGPUUniformBuffer"),extend:Px};const{BufferUsage:Ix}=bx,{vtkErrorMacro:Ox}=sn;const Rx={bufferEntries:null,bufferEntryNames:null,sizeInBytes:0,label:null,numberOfInstances:1};function Mx(e,t,n={}){Object.assign(t,Rx,n),sn.obj(e,t),t._bufferEntryNames=new Map,t.bufferEntries=[],t._sendTime={},sn.obj(t._sendTime,{mtime:0}),t.bindGroupTime={},sn.obj(t.bindGroupTime,{mtime:0}),t.bindGroupLayoutEntry=t.bindGroupLayoutEntry||{buffer:{type:"read-only-storage"}},sn.get(e,t,["bindGroupTime"]),sn.setGet(e,t,["device","bindGroupLayoutEntry","label","numberOfInstances","sizeInBytes"]),function(e,t){t.classHierarchy.push("vtkWebGPUStorageBuffer"),e.addEntry=(e,n)=>{if(t._bufferEntryNames.has(e))return void Ox(`entry named ${e} already exists`);t._bufferEntryNames.set(e,t.bufferEntries.length);const r=gT.getByteStrideFromShaderFormat(n);t.bufferEntries.push({name:e,type:n,sizeInBytes:r,offset:t.sizeInBytes,nativeType:gT.getNativeTypeFromShaderFormat(n)}),t.sizeInBytes+=r},e.send=e=>{if(!t._buffer){const n={nativeArray:t.Float32Array,usage:Ix.Storage,label:t.label};return t._buffer=e.getBufferManager().getBuffer(n),t.bindGroupTime.modified(),void t._sendTime.modified()}e.getHandle().queue.writeBuffer(t._buffer.getHandle(),0,t.arrayBuffer,0,t.sizeInBytes*t.numberOfInstances),t._sendTime.modified()},e.createView=e=>{e in t==0&&(t.arrayBuffer||(t.arrayBuffer=new ArrayBuffer(t.sizeInBytes*t.numberOfInstances)),t[e]=sn.newTypedArray(e,t.arrayBuffer))},e.setValue=(n,r,o)=>{const a=t._bufferEntryNames.get(n);if(void 0===a)return void Ox(`entry named ${n} not found in UBO`);const i=t.bufferEntries[a];e.createView(i.nativeType);const s=t[i.nativeType];s[(i.offset+r*t.sizeInBytes)/s.BYTES_PER_ELEMENT]=o},e.setArray=(n,r,o)=>{const a=t._bufferEntryNames.get(n);if(void 0===a)return void Ox(`entry named ${n} not found in UBO`);const i=t.bufferEntries[a];e.createView(i.nativeType);const s=t[i.nativeType],l=(i.offset+r*t.sizeInBytes)/s.BYTES_PER_ELEMENT;for(let e=0;e<o.length;e++)s[l+e]=o[e]},e.setAllInstancesFromArray=(n,r)=>{const o=t._bufferEntryNames.get(n);if(void 0===o)return void Ox(`entry named ${n} not found in UBO`);const a=t.bufferEntries[o];e.createView(a.nativeType);const i=t[a.nativeType],s=r.length/t.numberOfInstances;for(let e=0;e<t.numberOfInstances;e++){const n=(a.offset+e*t.sizeInBytes)/i.BYTES_PER_ELEMENT;for(let t=0;t<s;t++)i[n+t]=r[e*s+t]}},e.setAllInstancesFromArrayColorToFloat=(n,r)=>{const o=t._bufferEntryNames.get(n);if(void 0===o)return void Ox(`entry named ${n} not found in UBO`);const a=t.bufferEntries[o];e.createView(a.nativeType);const i=t[a.nativeType],s=r.length/t.numberOfInstances;for(let e=0;e<t.numberOfInstances;e++){const n=(a.offset+e*t.sizeInBytes)/i.BYTES_PER_ELEMENT;for(let t=0;t<s;t++)i[n+t]=r[e*s+t]/255}},e.setAllInstancesFromArray3x3To4x4=(n,r)=>{const o=t._bufferEntryNames.get(n);if(void 0===o)return void Ox(`entry named ${n} not found in UBO`);const a=t.bufferEntries[o];e.createView(a.nativeType);const i=t[a.nativeType];for(let e=0;e<t.numberOfInstances;e++){const n=(a.offset+e*t.sizeInBytes)/i.BYTES_PER_ELEMENT;for(let t=0;t<3;t++)for(let o=0;o<3;o++)i[n+4*t+o]=r[9*e+3*t+o]}},e.getSendTime=()=>t._sendTime.getMTime(),e.getShaderCode=(e,n)=>{const r=[`struct ${t.label}StructEntry\n{`];for(let e=0;e<t.bufferEntries.length;e++){const n=t.bufferEntries[e];r.push(`  ${n.name}: ${n.type},`)}return r.push(`\n};\nstruct ${t.label}Struct\n{\n  values: array<${t.label}StructEntry>,\n};\n@binding(${e}) @group(${n}) var<storage, read> ${t.label}: ${t.label}Struct;\n`),r.join("\n")},e.getBindGroupEntry=()=>({resource:{buffer:t._buffer.getHandle()}}),e.clearData=()=>{t.numberOfInstances=0,t.sizeInBytes=0,t.bufferEntries=[],t._bufferEntryNames=new Map,t._buffer=null,delete t.arrayBuffer,delete t.Float32Array}}(e,t)}var Dx={newInstance:sn.newInstance(Mx,"vtkWebGPUStorageBuffer"),extend:Mx};function Ex(e,t,n){const r=e.getClippingPlanes().length;for(let o=0;o<r;o++)e.getClippingPlaneInCoords(t,o,n[o]);return r}const Vx=`\n//VTK::Renderer::Dec\n\n//VTK::Mapper::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::Volume::TraverseDec\n\n//VTK::RenderEncoder::Dec\n\n//VTK::IOStructs::Dec\n\nfn getTextureValue(vTex: texture_3d<f32>, tpos: vec4<f32>) -> f32\n{\n  // todo multicomponent support\n  return textureSampleLevel(vTex, clampSampler, tpos.xyz, 0.0).r;\n}\n\nfn intersectRayBoundsWithClipPlanes(vNum: i32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>, rayBounds: vec2<f32>) -> vec2<f32>\n{\n  var result: vec2<f32> = rayBounds;\n  let clipCount: i32 = i32(volumeSSBO.values[vNum].clipPlaneStates.x);\n  if (clipCount <= 0)\n  {\n    return result;\n  }\n\n  ${Array.from({length:6},((e,t)=>`\n  if (clipCount > ${t})\n  {\n    let clipPlane${t}: vec4<f32> = volumeSSBO.values[vNum].clipPlane${t};\n    let rayDirRatio${t}: f32 = dot(rayStepSC, clipPlane${t});\n    let equationResult${t}: f32 = dot(minPosSC, clipPlane${t});\n\n    let absRayDirRatio${t}: f32 = abs(rayDirRatio${t});\n    if (absRayDirRatio${t} > 1e-6)\n    {\n      let intersection${t}: f32 = -equationResult${t} / rayDirRatio${t};\n      result.x = select(result.x, max(result.x, intersection${t}), rayDirRatio${t} > 0.0);\n      result.y = select(result.y, min(result.y, intersection${t}), rayDirRatio${t} < 0.0);\n    }\n    else if (equationResult${t} < 0.0)\n    {\n      result.x = result.y;\n    }\n\n    if (result.x >= result.y)\n    {\n      return result;\n    }\n  }`)).join("\n")}\n\n  return result;\n}\n\nfn getGradient(vTex: texture_3d<f32>, tpos: vec4<f32>, vNum: i32, scalar: f32) -> vec4<f32>\n{\n  var result: vec4<f32>;\n\n  var tstep: vec4<f32> = volumeSSBO.values[vNum].tstep;\n  result.x = getTextureValue(vTex, tpos + vec4<f32>(tstep.x, 0.0, 0.0, 1.0)) - scalar;\n  result.y = getTextureValue(vTex, tpos + vec4<f32>(0.0, tstep.y, 0.0, 1.0)) - scalar;\n  result.z = getTextureValue(vTex, tpos + vec4<f32>(0.0, 0.0, tstep.z, 1.0)) - scalar;\n  result.w = 0.0;\n\n  // divide by spacing as that is our delta\n  result = result / volumeSSBO.values[vNum].spacing;\n  // now we have a gradient in unit tcoords\n\n  var grad: f32 = length(result.xyz);\n  if (grad > 0.0)\n  {\n    // rotate to View Coords, needed for lighting and shading\n    var nMat: mat4x4<f32> = rendererUBO.SCVCMatrix * volumeSSBO.values[vNum].planeNormals;\n    result = nMat * result;\n    result = result / length(result);\n  }\n\n  // store gradient magnitude in .w\n  result.w = grad;\n\n  return result;\n}\n\nfn processVolume(vTex: texture_3d<f32>, vNum: i32, cNum: i32, posSC: vec4<f32>, tfunRows: f32) -> vec4<f32>\n{\n  var outColor: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0);\n\n  // convert to tcoords and reject if outside the volume\n  var tpos: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*posSC;\n  if (tpos.x < 0.0 || tpos.y < 0.0 || tpos.z < 0.0 ||\n      tpos.x > 1.0 || tpos.y > 1.0 || tpos.z > 1.0) { return outColor; }\n\n  var scalar: f32 = getTextureValue(vTex, tpos);\n\n  var coord: vec2<f32> =\n    vec2<f32>(scalar * componentSSBO.values[cNum].cScale + componentSSBO.values[cNum].cShift,\n      (0.5 + 2.0 * f32(vNum)) / tfunRows);\n  var color: vec4<f32> = textureSampleLevel(tfunTexture, clampSampler, coord, 0.0);\n\n  var gofactor: f32 = 1.0;\n  var normal: vec4<f32> = vec4<f32>(0.0,0.0,0.0,0.0);\n  if (componentSSBO.values[cNum].gomin <  1.0 || volumeSSBO.values[vNum].shade[0] > 0.0)\n  {\n    normal = getGradient(vTex, tpos, vNum, scalar);\n    if (componentSSBO.values[cNum].gomin <  1.0)\n    {\n      gofactor = clamp(normal.a*componentSSBO.values[cNum].goScale + componentSSBO.values[cNum].goShift,\n      componentSSBO.values[cNum].gomin, componentSSBO.values[cNum].gomax);\n    }\n  }\n\n  coord.x = (scalar * componentSSBO.values[cNum].oScale + componentSSBO.values[cNum].oShift);\n  var opacity: f32 = textureSampleLevel(ofunTexture, clampSampler, coord, 0.0).r;\n\n  if (volumeSSBO.values[vNum].shade[0] > 0.0)\n  {\n    color = color*abs(normal.z);\n  }\n\n  outColor = vec4<f32>(color.rgb, gofactor * opacity);\n\n  return outColor;\n}\n\n// adjust the start and end point of a raycast such that it intersects the unit cube.\n// This function is used to take a raycast starting point and step vector\n// and numSteps and return the startijng and ending steps for intersecting the\n// unit cube. Recall for a 3D texture, the unit cube is the range of texture coordsinates\n// that have valid values. So this funtion can be used to take a ray in texture coordinates\n// and bound it to intersecting the texture.\n//\nfn adjustBounds(tpos: vec4<f32>, tstep: vec4<f32>, numSteps: f32) -> vec2<f32>\n{\n  var result: vec2<f32> = vec2<f32>(0.0, numSteps);\n  var tpos2: vec4<f32> = tpos + tstep*numSteps;\n\n  // move tpos to the start of the volume\n  var adjust: f32 =\n    min(\n      max(tpos.x/tstep.x, (tpos.x - 1.0)/tstep.x),\n      min(\n        max((tpos.y - 1.0)/tstep.y, tpos.y/tstep.y),\n        max((tpos.z - 1.0)/tstep.z, tpos.z/tstep.z)));\n  if (adjust < 0.0)\n  {\n    result.x = result.x - adjust;\n  }\n\n  // adjust length to the end\n  adjust =\n    max(\n      min(tpos2.x/tstep.x, (tpos2.x - 1.0)/tstep.x),\n      max(\n        min((tpos2.y - 1.0)/tstep.y, tpos2.y/tstep.y),\n        min((tpos2.z - 1.0)/tstep.z, tpos2.z/tstep.z)));\n  if (adjust > 0.0)\n  {\n    result.y = result.y - adjust;\n  }\n\n  return result;\n}\n\nfn getSimpleColor(scalar: f32, vNum: i32, cNum: i32) -> vec4<f32>\n{\n  // how many rows (tfuns) do we have in our tfunTexture\n  var tfunRows: f32 = f32(textureDimensions(tfunTexture).y);\n\n  var coord: vec2<f32> =\n    vec2<f32>(scalar * componentSSBO.values[cNum].cScale + componentSSBO.values[cNum].cShift,\n      (0.5 + 2.0 * f32(vNum)) / tfunRows);\n  var color: vec4<f32> = textureSampleLevel(tfunTexture, clampSampler, coord, 0.0);\n  coord.x = (scalar * componentSSBO.values[cNum].oScale + componentSSBO.values[cNum].oShift);\n  var opacity: f32 = textureSampleLevel(ofunTexture, clampSampler, coord, 0.0).r;\n  return vec4<f32>(color.rgb, opacity);\n}\n\nfn traverseMax(vTex: texture_3d<f32>, vNum: i32, cNum: i32, rayLengthSC: f32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>)\n{\n  // convert to tcoords and reject if outside the volume\n  var numSteps: f32 = rayLengthSC/mapperUBO.SampleDistance;\n  var tpos: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*minPosSC;\n  var tpos2: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*(minPosSC + rayStepSC);\n  var tstep: vec4<f32> = tpos2 - tpos;\n\n  var rayBounds: vec2<f32> = intersectRayBoundsWithClipPlanes(\n    vNum,\n    minPosSC,\n    rayStepSC,\n    adjustBounds(tpos, tstep, numSteps));\n\n  // did we hit anything\n  if (rayBounds.x >= rayBounds.y)\n  {\n    traverseVals[vNum] = vec4<f32>(0.0,0.0,0.0,0.0);\n    return;\n  }\n\n  tpos = tpos + tstep*rayBounds.x;\n  var curDist: f32 = rayBounds.x;\n  var maxVal: f32 = -1.0e37;\n  loop\n  {\n    var scalar: f32 = getTextureValue(vTex, tpos);\n    if (scalar > maxVal)\n    {\n      maxVal = scalar;\n    }\n\n    // increment position\n    curDist = curDist + 1.0;\n    tpos = tpos + tstep;\n\n    // check if we have reached a terminating condition\n    if (curDist > rayBounds.y) { break; }\n  }\n\n  // process to get the color and opacity\n  traverseVals[vNum] = getSimpleColor(maxVal, vNum, cNum);\n}\n\nfn traverseMin(vTex: texture_3d<f32>, vNum: i32, cNum: i32, rayLengthSC: f32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>)\n{\n  // convert to tcoords and reject if outside the volume\n  var numSteps: f32 = rayLengthSC/mapperUBO.SampleDistance;\n  var tpos: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*minPosSC;\n  var tpos2: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*(minPosSC + rayStepSC);\n  var tstep: vec4<f32> = tpos2 - tpos;\n\n  var rayBounds: vec2<f32> = intersectRayBoundsWithClipPlanes(\n    vNum,\n    minPosSC,\n    rayStepSC,\n    adjustBounds(tpos, tstep, numSteps));\n\n  // did we hit anything\n  if (rayBounds.x >= rayBounds.y)\n  {\n    traverseVals[vNum] = vec4<f32>(0.0,0.0,0.0,0.0);\n    return;\n  }\n\n  tpos = tpos + tstep*rayBounds.x;\n  var curDist: f32 = rayBounds.x;\n  var minVal: f32 = 1.0e37;\n  loop\n  {\n    var scalar: f32 = getTextureValue(vTex, tpos);\n    if (scalar < minVal)\n    {\n      minVal = scalar;\n    }\n\n    // increment position\n    curDist = curDist + 1.0;\n    tpos = tpos + tstep;\n\n    // check if we have reached a terminating condition\n    if (curDist > rayBounds.y) { break; }\n  }\n\n  // process to get the color and opacity\n  traverseVals[vNum] = getSimpleColor(minVal, vNum, cNum);\n}\n\nfn traverseAverage(vTex: texture_3d<f32>, vNum: i32, cNum: i32, rayLengthSC: f32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>)\n{\n  // convert to tcoords and reject if outside the volume\n  var numSteps: f32 = rayLengthSC/mapperUBO.SampleDistance;\n  var tpos: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*minPosSC;\n  var tpos2: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*(minPosSC + rayStepSC);\n  var tstep: vec4<f32> = tpos2 - tpos;\n\n  var rayBounds: vec2<f32> = intersectRayBoundsWithClipPlanes(\n    vNum,\n    minPosSC,\n    rayStepSC,\n    adjustBounds(tpos, tstep, numSteps));\n\n  // did we hit anything\n  if (rayBounds.x >= rayBounds.y)\n  {\n    traverseVals[vNum] = vec4<f32>(0.0,0.0,0.0,0.0);\n    return;\n  }\n\n  let ipRange: vec4<f32> = volumeSSBO.values[vNum].ipScalarRange;\n  tpos = tpos + tstep*rayBounds.x;\n  var curDist: f32 = rayBounds.x;\n  var avgVal: f32 = 0.0;\n  var sampleCount: f32 = 0.0;\n  loop\n  {\n    var sample: f32 = getTextureValue(vTex, tpos);\n    // right now leave filtering off until WebGL changes get merged\n    // if (ipRange.z == 0.0 || sample >= ipRange.x && sample <= ipRange.y)\n    // {\n      avgVal = avgVal + sample;\n      sampleCount = sampleCount + 1.0;\n    // }\n\n    // increment position\n    curDist = curDist + 1.0;\n    tpos = tpos + tstep;\n\n    // check if we have reached a terminating condition\n    if (curDist > rayBounds.y) { break; }\n  }\n\n  if (sampleCount <= 0.0)\n  {\n    traverseVals[vNum] = vec4<f32>(0.0,0.0,0.0,0.0);\n    return;\n  }\n\n  // process to get the color and opacity\n  traverseVals[vNum] = getSimpleColor(avgVal/sampleCount, vNum, cNum);\n}\n\nfn traverseAdditive(vTex: texture_3d<f32>, vNum: i32, cNum: i32, rayLengthSC: f32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>)\n{\n  // convert to tcoords and reject if outside the volume\n  var numSteps: f32 = rayLengthSC/mapperUBO.SampleDistance;\n  var tpos: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*minPosSC;\n  var tpos2: vec4<f32> = volumeSSBO.values[vNum].SCTCMatrix*(minPosSC + rayStepSC);\n  var tstep: vec4<f32> = tpos2 - tpos;\n\n  var rayBounds: vec2<f32> = intersectRayBoundsWithClipPlanes(\n    vNum,\n    minPosSC,\n    rayStepSC,\n    adjustBounds(tpos, tstep, numSteps));\n\n  // did we hit anything\n  if (rayBounds.x >= rayBounds.y)\n  {\n    traverseVals[vNum] = vec4<f32>(0.0,0.0,0.0,0.0);\n    return;\n  }\n\n  let ipRange: vec4<f32> = volumeSSBO.values[vNum].ipScalarRange;\n  tpos = tpos + tstep*rayBounds.x;\n  var curDist: f32 = rayBounds.x;\n  var sumVal: f32 = 0.0;\n  loop\n  {\n    var sample: f32 = getTextureValue(vTex, tpos);\n    // right now leave filtering off until WebGL changes get merged\n    // if (ipRange.z == 0.0 || sample >= ipRange.x && sample <= ipRange.y)\n    // {\n      sumVal = sumVal + sample;\n    // }\n    // increment position\n    curDist = curDist + 1.0;\n    tpos = tpos + tstep;\n\n    // check if we have reached a terminating condition\n    if (curDist > rayBounds.y) { break; }\n  }\n\n  // process to get the color and opacity\n  traverseVals[vNum] = getSimpleColor(sumVal, vNum, cNum);\n}\n\nfn composite(rayLengthSC: f32, minPosSC: vec4<f32>, rayStepSC: vec4<f32>) -> vec4<f32>\n{\n  // initial ray position is at the beginning\n  var rayPosSC: vec4<f32> = minPosSC;\n\n  // how many rows (tfuns) do we have in our tfunTexture\n  var tfunRows: f32 = f32(textureDimensions(tfunTexture).y);\n\n  var curDist: f32 = 0.0;\n  var computedColor: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0);\n  var sampleColor: vec4<f32>;\n  var numSteps: f32 = rayLengthSC/mapperUBO.SampleDistance;\n//VTK::Volume::TraverseCalls\n//VTK::Volume::TraverseInit\n\n  loop\n  {\n    // for each volume, sample and accumulate color\n//VTK::Volume::CompositeCalls\n\n    // increment position\n    curDist = curDist + mapperUBO.SampleDistance;\n    rayPosSC = rayPosSC + rayStepSC;\n\n    // check if we have reached a terminating condition\n    if (curDist > rayLengthSC) { break; }\n    if (computedColor.a > 0.98) { break; }\n  }\n  return computedColor;\n}\n\n@fragment\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output: fragmentOutput;\n\n  var rayMax: f32 = textureSampleLevel(maxTexture, clampSampler, input.tcoordVS, 0.0).r;\n  var rayMin: f32 = textureSampleLevel(minTexture, clampSampler, input.tcoordVS, 0.0).r;\n\n  // discard empty rays\n  if (rayMax <= rayMin) { discard; }\n  else\n  {\n    // compute start and end ray positions in view coordinates\n    var minPosSC: vec4<f32> = rendererUBO.PCSCMatrix*vec4<f32>(2.0 * input.tcoordVS.x - 1.0, 1.0 - 2.0 * input.tcoordVS.y, rayMax, 1.0);\n    minPosSC = minPosSC * (1.0 / minPosSC.w);\n    var maxPosSC: vec4<f32> = rendererUBO.PCSCMatrix*vec4<f32>(2.0 * input.tcoordVS.x - 1.0, 1.0 - 2.0 * input.tcoordVS.y, rayMin, 1.0);\n    maxPosSC = maxPosSC * (1.0 / maxPosSC.w);\n\n    var rayLengthSC: f32 = distance(minPosSC.xyz, maxPosSC.xyz);\n    var rayStepSC: vec4<f32> = (maxPosSC - minPosSC)*(mapperUBO.SampleDistance/rayLengthSC);\n    rayStepSC.w = 0.0;\n\n    var computedColor: vec4<f32>;\n\n//VTK::Volume::Loop\n\n//VTK::RenderEncoder::Impl\n  }\n\n  return output;\n}\n`,Lx=new Float64Array(16),Bx=new Float64Array(16);const Fx={volumes:null,rowLength:1024,lastVolumeLength:0};function Nx(e,t,n={}){Object.assign(t,Fx,n),ST.extend(e,t,n),t.fragmentShaderTemplate=Vx,t.UBO=wx.newInstance({label:"mapperUBO"}),t.UBO.addEntry("SampleDistance","f32"),t.SSBO=Dx.newInstance({label:"volumeSSBO"}),t.componentSSBO=Dx.newInstance({label:"componentSSBO"}),t.lutBuildTime={},sn.obj(t.lutBuildTime,{mtime:0}),t.clipPlanes=Array.from({length:6},(()=>[0,0,0,0])),function(e,t){t.classHierarchy.push("vtkWebGPUVolumePassFSQ"),e.replaceShaderPosition=(e,t,n)=>{const r=t.getShaderDescription("vertex");r.addBuiltinOutput("vec4<f32>","@builtin(position) Position");let o=r.getCode();o=rT.substitute(o,"//VTK::Position::Impl",["output.tcoordVS = vec2<f32>(vertexBC.x * 0.5 + 0.5, 1.0 - vertexBC.y * 0.5 - 0.5);","output.Position = vec4<f32>(vertexBC, 1.0);"]).result,r.setCode(o),t.getShaderDescription("fragment").addBuiltinInput("vec4<f32>","@builtin(position) fragPos")},t.shaderReplacements.set("replaceShaderPosition",e.replaceShaderPosition),e.replaceShaderVolume=(e,n,r)=>{const o=n.getShaderDescription("fragment");let a=o.getCode();const i=[],s=[],l=[];for(let e=0;e<t.volumes.length;e++)t.volumes[e].getRenderable().getMapper().getBlendMode()===hg.COMPOSITE_BLEND?(s.push(`  var tpos${e}: vec4<f32> = volumeSSBO.values[${e}].SCTCMatrix*minPosSC;`),s.push(`  var tpos2_${e}: vec4<f32> = volumeSSBO.values[${e}].SCTCMatrix*(minPosSC + rayStepSC);`),s.push(`  var tstep${e}: vec4<f32> = tpos2_${e} - tpos${e};`),s.push(`  var rayBounds${e}: vec2<f32> = intersectRayBoundsWithClipPlanes(${e}, minPosSC, rayStepSC, adjustBounds(tpos${e}, tstep${e}, numSteps));`),i.push(`    if (curDist >= rayBounds${e}.x * mapperUBO.SampleDistance && curDist <= rayBounds${e}.y * mapperUBO.SampleDistance) {`),i.push(`      sampleColor = processVolume(volTexture${e}, ${e}, ${t.rowStarts[e]}, rayPosSC, tfunRows);`),i.push("    computedColor = vec4<f32>(\n          sampleColor.a * sampleColor.rgb * (1.0 - computedColor.a) + computedColor.rgb,\n          (1.0 - computedColor.a)*sampleColor.a + computedColor.a);"),i.push("    }")):(l.push(`  sampleColor = traverseVals[${e}];`),l.push("  computedColor = vec4<f32>(\n          sampleColor.a * sampleColor.rgb * (1.0 - computedColor.a) + computedColor.rgb,\n          (1.0 - computedColor.a)*sampleColor.a + computedColor.a);"));a=rT.substitute(a,"//VTK::Volume::CompositeCalls",i).result,a=rT.substitute(a,"//VTK::Volume::TraverseCalls",l).result,a=rT.substitute(a,"//VTK::Volume::TraverseInit",s).result,a=rT.substitute(a,"//VTK::Volume::TraverseDec",[`var<private> traverseVals: array<vec4<f32>,${t.volumes.length}>;`]).result;let c=!1;for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable().getMapper().getBlendMode();n===hg.COMPOSITE_BLEND?c=!0:n===hg.MAXIMUM_INTENSITY_BLEND?a=rT.substitute(a,"//VTK::Volume::Loop",[`    traverseMax(volTexture${e}, ${e}, ${e}, rayLengthSC, minPosSC, rayStepSC);`,`    computedColor = traverseVals[${e}];`,"//VTK::Volume::Loop"]).result:n===hg.MINIMUM_INTENSITY_BLEND?a=rT.substitute(a,"//VTK::Volume::Loop",[`    traverseMin(volTexture${e}, ${e}, ${e}, rayLengthSC, minPosSC, rayStepSC);`,`    computedColor = traverseVals[${e}];`,"//VTK::Volume::Loop"]).result:n===hg.AVERAGE_INTENSITY_BLEND?a=rT.substitute(a,"//VTK::Volume::Loop",[`    traverseAverage(volTexture${e}, ${e}, ${e}, rayLengthSC, minPosSC, rayStepSC);`,`    computedColor = traverseVals[${e}];`,"//VTK::Volume::Loop"]).result:n===hg.ADDITIVE_INTENSITY_BLEND&&(a=rT.substitute(a,"//VTK::Volume::Loop",[`    traverseAdditive(volTexture${e}, ${e}, ${e}, rayLengthSC, minPosSC, rayStepSC);`,`    computedColor = traverseVals[${e}];`,"//VTK::Volume::Loop"]).result)}c&&(a=rT.substitute(a,"//VTK::Volume::Loop",["    computedColor = composite(rayLengthSC, minPosSC, rayStepSC);"]).result),o.setCode(a)},t.shaderReplacements.set("replaceShaderVolume",e.replaceShaderVolume),e.updateLUTImage=n=>{let r=e.getMTime();for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable(),o=n.getMapper().getInputData();r=Math.max(r,n.getMTime(),o.getMTime())}if(r<t.lutBuildTime.getMTime())return;t.numRows=0,t.rowStarts=[];for(let e=0;e<t.volumes.length;e++){t.rowStarts.push(t.numRows);const n=t.volumes[e].getRenderable(),r=n.getMapper(),o=n.getProperty(),a=r.getInputData(),i=(a.getPointData()&&a.getPointData().getScalars()).getNumberOfComponents(),s=o.getIndependentComponents()?i:1;t.numRows+=s}const o=new Uint8ClampedArray(2*t.numRows*t.rowLength*4),a=new Float32Array(2*t.numRows*t.rowLength);let i=0;const s=new Float32Array(3*t.rowLength),l=t.rowLength;for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable(),r=n.getMapper(),c=n.getProperty(),u=r.getInputData(),d=(u.getPointData()&&u.getPointData().getScalars()).getNumberOfComponents(),p=c.getIndependentComponents()?d:1;for(let e=0;e<p;++e){const n=c.getRGBTransferFunction(e),r=n.getRange();n.getTable(r[0],r[1],l,s,1);let u=i*l*4;for(let e=0;e<l;++e){o[u+4*e]=255*s[3*e],o[u+4*e+1]=255*s[3*e+1],o[u+4*e+2]=255*s[3*e+2],o[u+4*e+3]=255;for(let t=0;t<4;t++)o[u+4*(l+e)+t]=o[u+4*e+t]}const d=c.getScalarOpacity(e),p=t.sampleDist/c.getScalarOpacityUnitDistance(e),f=d.getRange();d.getTable(f[0],f[1],l,s,1),u=i*l;for(let e=0;e<l;++e)a[u+e]=1-(1-s[e])**p,a[u+e+l]=a[u+e];i+=2}}{const e={nativeArray:o,width:t.rowLength,height:2*t.numRows,depth:1,format:"rgba8unorm"},r=n.getTextureManager().getTexture(e).createView("tfunTexture");t.textureViews[2]=r}{const e={nativeArray:a,width:t.rowLength,height:2*t.numRows,depth:1,format:"r16float"},r=n.getTextureManager().getTexture(e).createView("ofunTexture");t.textureViews[3]=r}t.lutBuildTime.modified()},e.updateSSBO=n=>{let r=Math.max(e.getMTime(),t.WebGPURenderer.getStabilizedTime());for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable(),o=n.getMapper(),a=o.getInputData();r=Math.max(r,n.getMTime(),a.getMTime(),o.getMTime(),o.getClippingPlanesMTime())}if(r<t.SSBO.getSendTime())return;const o=t.WebGPURenderer.getStabilizedCenterByReference();t.SSBO.clearData(),t.SSBO.setNumberOfInstances(t.volumes.length);const a=new Float64Array(16*t.volumes.length),i=new Float64Array(16*t.volumes.length),s=Array.from({length:6},(()=>new Float64Array(4*t.volumes.length))),l=new Float64Array(4*t.volumes.length),c=new Float64Array(4*t.volumes.length),u=new Float64Array(4*t.volumes.length),d=new Float64Array(4*t.volumes.length),p=new Float64Array(4*t.volumes.length);for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable(),r=n.getMapper(),f=r.getInputData();x(Lx),C(Lx,Lx,o);const g=n.getMatrix();y(Bx,g),b(Bx,Bx),A(Lx,Bx,Lx);const m=f.getWorldToIndex();A(Lx,m,Lx);const h=f.getDimensions();x(Bx),S(Bx,Bx,[1/h[0],1/h[1],1/h[2]]),A(Lx,Bx,Lx);for(let t=0;t<16;t++)a[16*e+t]=Lx[t];b(Lx,Lx);for(let t=0;t<4;t++)i[16*e+4*t]=Lx[4*t],i[16*e+4*t+1]=Lx[4*t+1],i[16*e+4*t+2]=Lx[4*t+2],i[16*e+4*t+3]=0;c[4*e]=1/h[0],c[4*e+1]=1/h[1],c[4*e+2]=1/h[2],c[4*e+3]=1,u[4*e]=n.getProperty().getShade()?1:0;const v=f.getSpacing();d[4*e]=v[0],d[4*e+1]=v[1],d[4*e+2]=v[2],d[4*e+3]=1;const T=t.textureViews[e+4].getTexture().getScale(),P=n.getProperty().getIpScalarRange();p[4*e]=P[0]/T,p[4*e+1]=P[1]/T,p[4*e+2]=n.getProperty().getFilterMode(),R(Bx,[-o[0],-o[1],-o[2]]);const w=Ex(r,Bx,t.clipPlanes);l[4*e]=w;for(let n=0;n<w;n++){const r=4*e;s[n][r]=t.clipPlanes[n][0],s[n][r+1]=t.clipPlanes[n][1],s[n][r+2]=t.clipPlanes[n][2],s[n][r+3]=t.clipPlanes[n][3]}}t.SSBO.addEntry("SCTCMatrix","mat4x4<f32>"),t.SSBO.addEntry("planeNormals","mat4x4<f32>"),t.SSBO.addEntry("shade","vec4<f32>"),t.SSBO.addEntry("tstep","vec4<f32>"),t.SSBO.addEntry("spacing","vec4<f32>"),t.SSBO.addEntry("ipScalarRange","vec4<f32>"),function(e,t){for(let n=0;n<6;n++)e.addEntry(`${t}${n}`,"vec4<f32>")}(t.SSBO,"clipPlane"),t.SSBO.addEntry("clipPlaneStates","vec4<f32>"),t.SSBO.setAllInstancesFromArray("SCTCMatrix",a),t.SSBO.setAllInstancesFromArray("planeNormals",i),t.SSBO.setAllInstancesFromArray("shade",u),t.SSBO.setAllInstancesFromArray("tstep",c),t.SSBO.setAllInstancesFromArray("spacing",d),t.SSBO.setAllInstancesFromArray("ipScalarRange",p);for(let e=0;e<6;e++)t.SSBO.setAllInstancesFromArray(`clipPlane${e}`,s[e]);t.SSBO.setAllInstancesFromArray("clipPlaneStates",l),t.SSBO.send(n),t.componentSSBO.clearData(),t.componentSSBO.setNumberOfInstances(t.numRows);const f=new Float64Array(t.numRows),g=new Float64Array(t.numRows),m=new Float64Array(t.numRows),h=new Float64Array(t.numRows),v=new Float64Array(t.numRows),T=new Float64Array(t.numRows),P=new Float64Array(t.numRows),w=new Float64Array(t.numRows);let I=0;for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable(),r=n.getMapper(),o=n.getProperty(),a=r.getInputData(),i=(a.getPointData()&&a.getPointData().getScalars()).getNumberOfComponents(),s=o.getIndependentComponents(),l=t.textureViews[e+4].getTexture().getFormat(),c=gT.getDetailsFromTextureFormat(l),u={scale:[255],offset:[0]};2===c.elementSize&&"float"===c.sampleType&&(u.scale[0]=1);for(let e=0;e<i;e++){const t=s?e:0,n=u.scale[e],r=o.getScalarOpacity(t).getRange(),a=n/(r[1]-r[0]),i=(u.offset[e]-r[0])/(r[1]-r[0]);h[I]=i,m[I]=a;const l=o.getRGBTransferFunction(t).getRange();if(g[I]=(u.offset[e]-l[0])/(l[1]-l[0]),f[I]=n/(l[1]-l[0]),o.getUseGradientOpacity(t)){const e=o.getGradientOpacityMinimumOpacity(t),r=o.getGradientOpacityMaximumOpacity(t);v[I]=e,T[I]=r;const a=[o.getGradientOpacityMinimumValue(t),o.getGradientOpacityMaximumValue(t)];w[I]=n*(r-e)/(a[1]-a[0]),P[I]=-a[0]*(r-e)/(a[1]-a[0])+e}else v[I]=1,T[I]=1,w[I]=0,P[I]=1;I++}}t.componentSSBO.addEntry("cScale","f32"),t.componentSSBO.addEntry("cShift","f32"),t.componentSSBO.addEntry("oScale","f32"),t.componentSSBO.addEntry("oShift","f32"),t.componentSSBO.addEntry("goShift","f32"),t.componentSSBO.addEntry("goScale","f32"),t.componentSSBO.addEntry("gomin","f32"),t.componentSSBO.addEntry("gomax","f32"),t.componentSSBO.setAllInstancesFromArray("cScale",f),t.componentSSBO.setAllInstancesFromArray("cShift",g),t.componentSSBO.setAllInstancesFromArray("oScale",m),t.componentSSBO.setAllInstancesFromArray("oShift",h),t.componentSSBO.setAllInstancesFromArray("goScale",w),t.componentSSBO.setAllInstancesFromArray("goShift",P),t.componentSSBO.setAllInstancesFromArray("gomin",v),t.componentSSBO.setAllInstancesFromArray("gomax",T),t.componentSSBO.send(n)};const n=e.updateBuffers;e.updateBuffers=()=>{n();let r=t.volumes[0].getRenderable().getMapper().getSampleDistance();for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable().getMapper().getSampleDistance();n<r&&(r=n)}t.sampleDist!==r&&(t.sampleDist=r,t.UBO.setValue("SampleDistance",r),t.UBO.sendIfNeeded(t.device));for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable().getMapper().getInputData(),r=t.device.getTextureManager().getTextureForImageData(n);if(!t.textureViews[e+4]||t.textureViews[e+4].getTexture()!==r){const n=r.createView(`volTexture${e}`);t.textureViews[e+4]=n}}if(t.volumes.length<t.lastVolumeLength)for(let e=t.volumes.length;e<t.lastVolumeLength;e++)t.textureViews.pop();t.lastVolumeLength=t.volumes.length,e.updateLUTImage(t.device),e.updateSSBO(t.device),t.clampSampler||(t.clampSampler=DT.newInstance({label:"clampSampler"}),t.clampSampler.create(t.device,{minFilter:"linear",magFilter:"linear"}))},e.computePipelineHash=()=>{t.pipelineHash="volfsq";for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable().getMapper().getBlendMode();t.pipelineHash+=`${n}`}},e.setVolumes=n=>{if(!t.volumes||t.volumes.length!==n.length)return t.volumes=[...n],void e.modified();for(let r=0;r<n.length;r++)if(n[r]!==t.volumes[r])return t.volumes=[...n],void e.modified()};const r=e.getBindables;e.getBindables=()=>{const e=r();return e.push(t.componentSSBO),e.push(t.clampSampler),e}}(e,t)}var kx={newInstance:sn.newInstance(Nx,"vtkWebGPUVolumePassFSQ"),extend:Nx};const{Representation:Gx}=us,{BufferUsage:Ux,PrimitiveTypes:_x}=bx,Kx=[[0,4,6],[0,6,2],[1,3,7],[1,7,5],[0,5,4],[0,1,5],[2,6,7],[2,7,3],[0,3,1],[0,2,3],[4,5,7],[4,7,6]];const zx={colorTextureView:null,depthTextureView:null,volumes:null};function Wx(e,t,n={}){Object.assign(t,zx,n),vv.extend(e,t,n),t._mapper=bT.newInstance(),t._mapper.setFragmentShaderTemplate("\n//VTK::Renderer::Dec\n\n//VTK::Select::Dec\n\n//VTK::VolumePass::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::RenderEncoder::Dec\n\n//VTK::Mapper::Dec\n\n//VTK::IOStructs::Dec\n\n@fragment\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output : fragmentOutput;\n\n  //VTK::Select::Impl\n\n  //VTK::TCoord::Impl\n\n  //VTK::VolumePass::Impl\n\n  // use the maximum (closest) of the current value and the zbuffer\n  // the blend func will then take the min to find the farthest stop value\n  var stopval: f32 = max(input.fragPos.z, textureLoad(opaquePassDepthTexture, vec2<i32>(i32(input.fragPos.x), i32(input.fragPos.y)), 0));\n\n  //VTK::RenderEncoder::Impl\n  return output;\n}\n"),t._mapper.getShaderReplacements().set("replaceShaderVolumePass",((e,t,n)=>{t.getShaderDescription("fragment").addBuiltinInput("vec4<f32>","@builtin(position) fragPos")})),t._boundsPoly=Ru.newInstance(),t._lastMTimes=[],sn.setGet(e,t,["colorTextureView","depthTextureView"]),function(e,t){t.classHierarchy.push("vtkWebGPUVolumePass"),e.initialize=n=>{t._clearEncoder||e.createClearEncoder(n),t._mergeEncoder||e.createMergeEncoder(n),t._copyEncoder||e.createCopyEncoder(n),t._depthRangeEncoder||e.createDepthRangeEncoder(n),t.fullScreenQuad||(t.fullScreenQuad=kx.newInstance(),t.fullScreenQuad.setDevice(n.getDevice()),t.fullScreenQuad.setTextureViews([...t._depthRangeEncoder.getColorTextureViews()])),t._volumeCopyQuad||(t._volumeCopyQuad=ST.newInstance(),t._volumeCopyQuad.setPipelineHash("volpassfsq"),t._volumeCopyQuad.setDevice(n.getDevice()),t._volumeCopyQuad.setFragmentShaderTemplate("\n//VTK::Renderer::Dec\n\n//VTK::Mapper::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::RenderEncoder::Dec\n\n//VTK::IOStructs::Dec\n\n@fragment\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output: fragmentOutput;\n\n  var computedColor: vec4<f32> = textureSample(volumePassColorTexture,\n    volumePassColorTextureSampler, mapperUBO.tscale*input.tcoordVS);\n\n  //VTK::RenderEncoder::Impl\n  return output;\n}\n"),t._copyUBO=wx.newInstance({label:"mapperUBO"}),t._copyUBO.addEntry("tscale","vec2<f32>"),t._volumeCopyQuad.setUBO(t._copyUBO),t._volumeCopyQuad.setTextureViews([t._colorTextureView]))},e.traverse=(n,r)=>{if(t.deleted)return;t._currentParent=r,e.initialize(r),e.computeTiming(r),e.renderDepthBounds(n,r),t._firstGroup=!0;const o=r.getDevice(),a=o.getHandle().limits.maxSampledTexturesPerShaderStage-4;if(t.volumes.length>a){const o=n.getRenderable().getActiveCamera().getPosition(),i=[];for(let e=0;e<t.volumes.length;e++){const n=t.volumes[e].getRenderable().getBounds(),r=[.5*(n[1]+n[0]),.5*(n[3]+n[2]),.5*(n[5]+n[4])];i[e]=Yo(r,o)}const s=[...Array(t.volumes.length).keys()];s.sort(((e,t)=>i[t]-i[e]));let l=[],c=s.length%a;for(let o=0;o<s.length;o++)l.push(t.volumes[s[o]]),l.length>=c&&(e.rayCastPass(r,n,l),l=[],c=a,t._firstGroup=!1)}else e.rayCastPass(r,n,t.volumes);if(t._volumeCopyQuad.setWebGPURenderer(n),t._useSmallViewport){const e=t._colorTextureView.getTexture().getWidth(),n=t._colorTextureView.getTexture().getHeight();t._copyUBO.setArray("tscale",[t._smallViewportWidth/e,t._smallViewportHeight/n])}else t._copyUBO.setArray("tscale",[1,1]);t._copyUBO.sendIfNeeded(o),t._copyEncoder.setColorTextureView(0,t.colorTextureView),t._copyEncoder.attachTextureViews(),t._copyEncoder.begin(r.getCommandEncoder()),n.scissorAndViewport(t._copyEncoder),t._volumeCopyQuad.prepareAndDraw(t._copyEncoder),t._copyEncoder.end()},e.delete=sn.chain((()=>{t._animationRateSubscription&&(t._animationRateSubscription.unsubscribe(),t._animationRateSubscription=null)}),e.delete),e.computeTiming=e=>{const n=e.getRenderable().getInteractor();if(null==t._lastScale){const e=t.volumes[0].getRenderable().getMapper();t._lastScale=e.getInitialInteractionScale()||1}t._useSmallViewport=!1,n.isAnimating()&&t._lastScale>1.5&&(t._useSmallViewport=!0),t._colorTexture.resize(e.getCanvas().width,e.getCanvas().height),t._animationRateSubscription||(t._animationRateSubscription=n.onAnimationFrameRateUpdate((()=>{const e=t.volumes[0].getRenderable().getMapper();if(e.getAutoAdjustSampleDistances()){const e=n.getRecentAnimationFrameRate(),r=t._lastScale*n.getDesiredUpdateRate()/e;t._lastScale=r,t._lastScale>400&&(t._lastScale=400)}else t._lastScale=e.getImageSampleDistance()*e.getImageSampleDistance();t._lastScale<1.5&&(t._lastScale=1.5)})))},e.rayCastPass=(e,n,r)=>{const o=t._firstGroup?t._clearEncoder:t._mergeEncoder;o.attachTextureViews(),o.begin(e.getCommandEncoder());let a=t._colorTextureView.getTexture().getWidth(),i=t._colorTextureView.getTexture().getHeight();if(t._useSmallViewport){const n=e.getCanvas(),r=1/Math.sqrt(t._lastScale);t._smallViewportWidth=Math.ceil(r*n.width),t._smallViewportHeight=Math.ceil(r*n.height),a=t._smallViewportWidth,i=t._smallViewportHeight}o.getHandle().setViewport(0,0,a,i,0,1),o.getHandle().setScissorRect(0,0,a,i),t.fullScreenQuad.setWebGPURenderer(n),t.fullScreenQuad.setVolumes(r),t.fullScreenQuad.prepareAndDraw(o),o.end()},e.renderDepthBounds=(n,r)=>{e.updateDepthPolyData(n);const o=t._boundsPoly,a=o.getPoints(),i=o.getPolys();let s={hash:`vp${i.getMTime()}`,usage:Ux.Index,cells:i,numberOfPoints:a.getNumberOfPoints(),primitiveType:_x.Triangles,representation:Gx.SURFACE};const l=r.getDevice().getBufferManager().getBuffer(s);t._mapper.getVertexInput().setIndexBuffer(l),s={usage:Ux.PointArray,format:"float32x4",hash:`vp${a.getMTime()}${i.getMTime()}`,dataArray:a,indexBuffer:l,packExtra:!0};const c=r.getDevice().getBufferManager().getBuffer(s);t._mapper.getVertexInput().addBuffer(c,["vertexBC"]),t._mapper.setNumberOfVertices(c.getSizeInBytes()/c.getStrideInBytes()),e.drawDepthRange(n,r)},e.updateDepthPolyData=e=>{let n=!1;for(let e=0;e<t.volumes.length;e++){const r=t.volumes[e].getMTime();t._lastMTimes[e]&&r===t._lastMTimes[e]||(n=!0,t._lastMTimes[e]=r)}const r=e.getStabilizedTime();if((t._lastMTimes.length<=t.volumes.length||r!==t._lastMTimes[t.volumes.length])&&(n=!0,t._lastMTimes[t.volumes.length]=r),!n)return;const o=e.getStabilizedCenterByReference(),a=8*t.volumes.length,i=new Float64Array(3*a),s=12*t.volumes.length,l=new Uint16Array(4*s);for(let e=0;e<t.volumes.length;e++){t.volumes[e].getBoundingCubePoints(i,24*e);let n=12*e*4;const r=8*e;for(let e=0;e<12;e++)l[n++]=3,l[n++]=r+Kx[e][0],l[n++]=r+Kx[e][1],l[n++]=r+Kx[e][2]}for(let e=0;e<i.length;e+=3)i[e]-=o[0],i[e+1]-=o[1],i[e+2]-=o[2];t._boundsPoly.getPoints().setData(i,3),t._boundsPoly.getPoints().modified(),t._boundsPoly.getPolys().setData(l,1),t._boundsPoly.getPolys().modified(),t._boundsPoly.modified()},e.drawDepthRange=(n,r)=>{t._depthRangeTexture.resizeToMatch(t.colorTextureView.getTexture()),t._depthRangeTexture2.resizeToMatch(t.colorTextureView.getTexture()),t._depthRangeEncoder.attachTextureViews(),e.setCurrentOperation("volumeDepthRangePass"),n.setRenderEncoder(t._depthRangeEncoder),n.volumeDepthRangePass(!0),t._mapper.setWebGPURenderer(n),t._mapper.prepareToDraw(t._depthRangeEncoder),t._mapper.registerDrawCallback(t._depthRangeEncoder),n.volumeDepthRangePass(!1)},e.createDepthRangeEncoder=e=>{const n=e.getDevice();t._depthRangeEncoder=OT.newInstance({label:"VolumePass DepthRange"}),t._depthRangeEncoder.setPipelineHash("volr"),t._depthRangeEncoder.setReplaceShaderCodeFunction((e=>{const t=e.getShaderDescription("fragment");t.addOutput("vec4<f32>","outColor1"),t.addOutput("vec4<f32>","outColor2");let n=t.getCode();n=rT.substitute(n,"//VTK::RenderEncoder::Impl",["output.outColor1 = vec4<f32>(input.fragPos.z, 0.0, 0.0, 0.0);","output.outColor2 = vec4<f32>(stopval, 0.0, 0.0, 0.0);"]).result,t.setCode(n)})),t._depthRangeEncoder.setDescription({colorAttachments:[{view:null,clearValue:[0,0,0,0],loadOp:"clear",storeOp:"store"},{view:null,clearValue:[1,1,1,1],loadOp:"clear",storeOp:"store"}]}),t._depthRangeEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:"r16float",blend:{color:{srcFactor:"one",dstFactor:"one",operation:"max"},alpha:{srcFactor:"one",dstFactor:"one",operation:"max"}}},{format:"r16float",blend:{color:{srcFactor:"one",dstFactor:"one",operation:"min"},alpha:{srcFactor:"one",dstFactor:"one",operation:"min"}}}]}}),t._depthRangeTexture=GT.newInstance({label:"volumePassMaxDepth"}),t._depthRangeTexture.create(n,{width:e.getCanvas().width,height:e.getCanvas().height,format:"r16float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING});const r=t._depthRangeTexture.createView("maxTexture");t._depthRangeEncoder.setColorTextureView(0,r),t._depthRangeTexture2=GT.newInstance({label:"volumePassDepthMin"}),t._depthRangeTexture2.create(n,{width:e.getCanvas().width,height:e.getCanvas().height,format:"r16float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING});const o=t._depthRangeTexture2.createView("minTexture");t._depthRangeEncoder.setColorTextureView(1,o),t._mapper.setDevice(e.getDevice()),t._mapper.setTextureViews([t.depthTextureView])},e.createClearEncoder=e=>{t._colorTexture=GT.newInstance({label:"volumePassColor"}),t._colorTexture.create(e.getDevice(),{width:e.getCanvas().width,height:e.getCanvas().height,format:"bgra8unorm",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_SRC}),t._colorTextureView=t._colorTexture.createView("volumePassColorTexture"),t._colorTextureView.addSampler(e.getDevice(),{minFilter:"linear",magFilter:"linear"}),t._clearEncoder=OT.newInstance({label:"VolumePass Clear"}),t._clearEncoder.setColorTextureView(0,t._colorTextureView),t._clearEncoder.setDescription({colorAttachments:[{view:null,clearValue:[0,0,0,0],loadOp:"clear",storeOp:"store"}]}),t._clearEncoder.setPipelineHash("volpf"),t._clearEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:"bgra8unorm",blend:{color:{srcFactor:"src-alpha",dstFactor:"one-minus-src-alpha"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}})},e.createCopyEncoder=e=>{t._copyEncoder=OT.newInstance({label:"volumePassCopy"}),t._copyEncoder.setDescription({colorAttachments:[{view:null,loadOp:"load",storeOp:"store"}]}),t._copyEncoder.setPipelineHash("volcopypf"),t._copyEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:"rgba16float",blend:{color:{srcFactor:"one",dstFactor:"one-minus-src-alpha"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}})},e.createMergeEncoder=e=>{t._mergeEncoder=OT.newInstance({label:"volumePassMerge"}),t._mergeEncoder.setColorTextureView(0,t._colorTextureView),t._mergeEncoder.setDescription({colorAttachments:[{view:null,loadOp:"load",storeOp:"store"}]}),t._mergeEncoder.setReplaceShaderCodeFunction((e=>{const t=e.getShaderDescription("fragment");t.addOutput("vec4<f32>","outColor");let n=t.getCode();n=rT.substitute(n,"//VTK::RenderEncoder::Impl",["output.outColor = vec4<f32>(computedColor.rgb, computedColor.a);"]).result,t.setCode(n)})),t._mergeEncoder.setPipelineHash("volpf"),t._mergeEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:"bgra8unorm",blend:{color:{srcFactor:"src-alpha",dstFactor:"one-minus-src-alpha"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}})},e.setVolumes=n=>{if(!t.volumes||t.volumes.length!==n.length)return t.volumes=[...n],void e.modified();for(let r=0;r<n.length;r++)if(n[r]!==t.volumes[r])return t.volumes=[...n],void e.modified()}}(e,t)}var Hx={newInstance:sn.newInstance(Wx,"vtkWebGPUVolumePass"),extend:Wx};const jx={opaqueActorCount:0,translucentActorCount:0,volumes:null,opaqueRenderEncoder:null,translucentPass:null,volumePass:null};function Xx(e,t,n={}){Object.assign(t,jx,n),vv.extend(e,t,n),sn.setGet(e,t,["opaquePass","translucentPass","volumePass"]),function(e,t){t.classHierarchy.push("vtkForwardPass"),e.traverse=(n,r=null)=>{if(t.deleted)return;t._currentParent=r,e.setCurrentOperation("buildPass"),n.traverse(e),t.opaquePass||(t.opaquePass=KT.newInstance());const o=n.getRenderable().getNumberOfLayers(),a=n.getChildren();for(let r=0;r<o;r++)for(let o=0;o<a.length;o++){const i=a[o],s=n.getRenderable().getRenderers()[o];s.getDraw()&&s.getLayer()===r&&(t.opaqueActorCount=0,t.translucentActorCount=0,t.volumes=[],e.setCurrentOperation("queryPass"),i.traverse(e),e.setCurrentOperation("cameraPass"),i.traverse(e),t.opaquePass.traverse(i,n),t.translucentActorCount>0&&(t.translucentPass||(t.translucentPass=HT.newInstance()),t.translucentPass.setColorTextureView(t.opaquePass.getColorTextureView()),t.translucentPass.setDepthTextureView(t.opaquePass.getDepthTextureView()),t.translucentPass.traverse(i,n)),t.volumes.length>0&&(t.volumePass||(t.volumePass=Hx.newInstance()),t.volumePass.setColorTextureView(t.opaquePass.getColorTextureView()),t.volumePass.setDepthTextureView(t.opaquePass.getDepthTextureView()),t.volumePass.setVolumes(t.volumes),t.volumePass.traverse(i,n)),e.finalPass(n,i))}},e.finalPass=(n,r)=>{t._finalBlitEncoder||e.createFinalBlitEncoder(n),t._finalBlitOutputTextureView.createFromTextureHandle(n.getCurrentTexture(),{depth:1,format:n.getPresentationFormat()}),t._finalBlitEncoder.attachTextureViews(),t._finalBlitEncoder.begin(n.getCommandEncoder()),r.scissorAndViewport(t._finalBlitEncoder),t._fullScreenQuad.prepareAndDraw(t._finalBlitEncoder),t._finalBlitEncoder.end()},e.createFinalBlitEncoder=e=>{t._finalBlitEncoder=OT.newInstance({label:"forwardPassBlit"}),t._finalBlitEncoder.setDescription({colorAttachments:[{view:null,loadOp:"load",storeOp:"store"}]}),t._finalBlitEncoder.setPipelineHash("fpf"),t._finalBlitEncoder.setPipelineSettings({primitive:{cullMode:"none"},fragment:{targets:[{format:e.getPresentationFormat(),blend:{color:{srcFactor:"src-alpha",dstFactor:"one-minus-src-alpha"},alpha:{srcFactor:"one",dstFactor:"one-minus-src-alpha"}}}]}}),t._fsqSampler=DT.newInstance({label:"finalPassSampler"}),t._fsqSampler.create(e.getDevice(),{minFilter:"linear",magFilter:"linear"}),t._fullScreenQuad=ST.newInstance(),t._fullScreenQuad.setDevice(e.getDevice()),t._fullScreenQuad.setPipelineHash("fpfsq"),t._fullScreenQuad.setTextureViews([t.opaquePass.getColorTextureView()]),t._fullScreenQuad.setAdditionalBindables([t._fsqSampler]),t._fullScreenQuad.setFragmentShaderTemplate("\n//VTK::Mapper::Dec\n\n//VTK::TCoord::Dec\n\n//VTK::RenderEncoder::Dec\n\n//VTK::IOStructs::Dec\n\n@fragment\nfn main(\n//VTK::IOStructs::Input\n)\n//VTK::IOStructs::Output\n{\n  var output: fragmentOutput;\n\n  var computedColor: vec4<f32> = clamp(textureSampleLevel(opaquePassColorTexture, finalPassSampler, input.tcoordVS, 0.0),vec4<f32>(0.0),vec4<f32>(1.0));\n\n  //VTK::RenderEncoder::Impl\n  return output;\n}\n"),t._finalBlitOutputTextureView=LT.newInstance(),t._finalBlitEncoder.setColorTextureView(0,t._finalBlitOutputTextureView)},e.incrementOpaqueActorCount=()=>t.opaqueActorCount++,e.incrementTranslucentActorCount=()=>t.translucentActorCount++,e.addVolume=e=>{t.volumes.push(e)}}(e,t)}var qx={newInstance:sn.newInstance(Xx,"vtkForwardPass"),extend:Xx};const{VtkDataTypes:Yx}=Is;const Jx={handle:null,device:null};function Zx(e,t,n={}){Object.assign(t,Jx,n),sn.obj(e,t),sn.setGet(e,t,["device"]),function(e,t){function n(e){if(e.imageData){e.dataArray=e.imageData.getPointData().getScalars(),e.time=e.dataArray.getMTime(),e.nativeArray=e.dataArray.getData();const t=e.imageData.getDimensions();switch(e.width=t[0],e.height=t[1],e.depth=t[2],e.dataArray.getNumberOfComponents()){case 1:e.format="r";break;case 2:e.format="rg";break;default:e.format="rgba"}switch(e.dataArray.getDataType()){case Yx.UNSIGNED_CHAR:e.format+="8unorm";break;case Yx.FLOAT:case Yx.UNSIGNED_INT:case Yx.INT:case Yx.DOUBLE:case Yx.UNSIGNED_SHORT:case Yx.SHORT:default:e.format+="16float"}}e.image&&(e.width=e.image.width,e.height=e.image.height,e.depth=1,e.format="rgba8unorm",e.flip=!0,e.usage=GPUTextureUsage.STORAGE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.RENDER_ATTACHMENT),e.jsImageData&&(e.width=e.jsImageData.width,e.height=e.jsImageData.height,e.depth=1,e.format="rgba8unorm",e.flip=!0,e.nativeArray=e.jsImageData.data,e.usage=GPUTextureUsage.STORAGE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.RENDER_ATTACHMENT),e.imageBitmap&&(e.width=e.imageBitmap.width,e.height=e.imageBitmap.height,e.depth=1,e.format="rgba8unorm",e.flip=!0,e.usage=GPUTextureUsage.STORAGE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.RENDER_ATTACHMENT),e.canvas&&(e.width=e.canvas.width,e.height=e.canvas.height,e.depth=1,e.format="rgba8unorm",e.flip=!0,e.usage=GPUTextureUsage.STORAGE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.RENDER_ATTACHMENT)}function r(e){const n=GT.newInstance({label:e.label});return n.create(t.device,{width:e.width,height:e.height,depth:e.depth,format:e.format,usage:e.usage,mipLevel:e.mipLevel}),(e.nativeArray||e.image||e.canvas||e.imageBitmap)&&n.writeImageData(e),n}t.classHierarchy.push("vtkWebGPUTextureManager"),e.getTexture=e=>e.hash?t.device.getCachedObject(e.hash,r,e):r(e),e.getTextureForImageData=e=>{const r={time:e.getMTime()};return r.imageData=e,n(r),r.hash=r.time+r.format+r.mipLevel,t.device.getTextureManager().getTexture(r)},e.getTextureForVTKTexture=(e,r=void 0)=>{const o={time:e.getMTime(),label:r};return e.getInputData()?o.imageData=e.getInputData():e.getImage()?o.image=e.getImage():e.getJsImageData()?o.jsImageData=e.getJsImageData():e.getImageBitmap()?o.imageBitmap=e.getImageBitmap():e.getCanvas()&&(o.canvas=e.getCanvas()),n(o),o.mipLevel=e.getMipLevel(),o.hash=o.time+o.format+o.mipLevel,t.device.getTextureManager().getTexture(o)}}(e,t)}var Qx={newInstance:sn.newInstance(Zx),extend:Zx};class $x extends Map{constructor(){super(),this.registry=new FinalizationRegistry((e=>{const t=super.get(e);t&&t.deref&&void 0===t.deref()&&super.delete(e)}))}getValue(e){const t=super.get(e);if(t){const n=t.deref();if(void 0!==n)return n;super.delete(e)}}setValue(e,t){let n;return t&&"object"==typeof t&&(n=new WeakRef(t),this.registry.register(t,e),super.set(e,n)),n}}const ey={handle:null,pipelines:null,shaderCache:null,bindGroupLayouts:null,bufferManager:null,textureManager:null};function ty(e,t,n={}){Object.assign(t,ey,n),Vt(e,t),Gt(e,t,["handle"]),Bt(e,t,["bufferManager","shaderCache","textureManager"]),t.objectCache=new $x,t.shaderCache=rT.newInstance(),t.shaderCache.setDevice(e),t.bindGroupLayouts=[],t.bufferManager=bx.newInstance(),t.bufferManager.setDevice(e),t.textureManager=Qx.newInstance(),t.textureManager.setDevice(e),t.pipelines={},function(e,t){t.classHierarchy.push("vtkWebGPUDevice"),e.initialize=e=>{t.handle=e},e.createCommandEncoder=()=>t.handle.createCommandEncoder(),e.submitCommandEncoder=e=>{t.handle.queue.submit([e.finish()])},e.getShaderModule=e=>t.shaderCache.getShaderModule(e),e.getBindGroupLayout=e=>{if(!e.entries)return null;for(let t=0;t<e.entries.length;t++){const n=e.entries[t];n.binding=n.binding||0,n.visibility=n.visibility||GPUShaderStage.VERTEX|GPUShaderStage.FRAGMENT}const n=JSON.stringify(e);for(let e=0;e<t.bindGroupLayouts.length;e++)if(t.bindGroupLayouts[e].sval===n)return t.bindGroupLayouts[e].layout;const r=t.handle.createBindGroupLayout(e);return t.bindGroupLayouts.push({sval:n,layout:r}),r},e.getBindGroupLayoutDescription=e=>{for(let n=0;n<t.bindGroupLayouts.length;n++)if(t.bindGroupLayouts[n].layout===e)return t.bindGroupLayouts[n].sval;return vtkErrorMacro("layout not found"),console.trace(),null},e.getPipeline=e=>e in t.pipelines?t.pipelines[e]:null,e.createPipeline=(n,r)=>{r.initialize(e,n),t.pipelines[n]=r},e.onSubmittedWorkDone=()=>t.handle.queue.onSubmittedWorkDone(),e.hasCachedObject=e=>t.objectCache.getValue(e),e.getCachedObject=(e,n,...r)=>{if(!e)return vtkErrorMacro("attempt to cache an object without a hash"),null;const o=t.objectCache.getValue(e);if(o)return o;const a=n(...r);return t.objectCache.setValue(e,a),a}}(e,t)}var ny={newInstance:Xt(ty,"vtkWebGPUDevice"),extend:ty};const ry={selectionRenderEncoder:null,colorTexture:null,depthTexture:null};function oy(e,t,n={}){Object.assign(t,ry,n),vv.extend(e,t,n),sn.get(e,t,["colorTexture","depthTexture"]),function(e,t){t.classHierarchy.push("vtkWebGPUHardwareSelectionPass"),e.traverse=(n,r)=>{if(t.deleted)return;t._currentParent=null,e.setCurrentOperation("buildPass"),n.traverse(e);const o=n.getDevice();if(t.selectionRenderEncoder)t.colorTexture.resize(n.getCanvas().width,n.getCanvas().height),t.depthTexture.resizeToMatch(t.colorTexture);else{e.createRenderEncoder(),t.colorTexture=GT.newInstance({label:"hardwareSelectorColor"}),t.colorTexture.create(o,{width:n.getCanvas().width,height:n.getCanvas().height,format:"rgba32uint",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC});const r=t.colorTexture.createView("hardwareSelectColorTexture");t.selectionRenderEncoder.setColorTextureView(0,r),t.depthTexture=GT.newInstance({label:"hardwareSelectorDepth"}),t.depthTexture.create(o,{width:n.getCanvas().width,height:n.getCanvas().height,format:"depth32float",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC});const a=t.depthTexture.createView("hardwareSelectDepthTexture");t.selectionRenderEncoder.setDepthTextureView(a)}t.selectionRenderEncoder.attachTextureViews(),r.setRenderEncoder(t.selectionRenderEncoder),e.setCurrentOperation("cameraPass"),r.traverse(e),e.setCurrentOperation("opaquePass"),r.traverse(e)},e.createRenderEncoder=()=>{t.selectionRenderEncoder=OT.newInstance({label:"HardwareSelectionPass"}),t.selectionRenderEncoder.setPipelineHash("sel"),t.selectionRenderEncoder.setReplaceShaderCodeFunction((e=>{const t=e.getShaderDescription("fragment");t.addOutput("vec4<u32>","outColor");let n=t.getCode();n=rT.substitute(n,"//VTK::RenderEncoder::Impl",["output.outColor = vec4<u32>(mapperUBO.PropID, compositeID, 0u, 0u);"]).result,t.setCode(n)})),t.selectionRenderEncoder.getDescription().colorAttachments[0].clearValue=[0,0,0,0],t.selectionRenderEncoder.setPipelineSettings({primitive:{cullMode:"none"},depthStencil:{depthWriteEnabled:!0,depthCompare:"greater",format:"depth32float"},fragment:{targets:[{format:"rgba32uint",blend:void 0}]}})}}(e,t)}var ay={newInstance:sn.newInstance(oy,"vtkWebGPUHardwareSelectionPass"),extend:oy};const{SelectionContent:iy,SelectionField:sy}=zp,{FieldAssociations:ly}=Qs,{vtkErrorMacro:cy}=sn;function uy(e){return`${e.propID} ${e.compositeID}`}function dy(e,t,n,r){const o=4*((n.height-t-1)*n.colorBufferWidth+e)+r;return n.colorValues[o]}function py(e,t,n,r){const o=n<0?0:n;if(0===o){if(r[0]=t[0],r[1]=t[1],t[0]<0||t[0]>=e.width||t[1]<0||t[1]>=e.height)return null;const n=dy(t[0],t[1],e,0);if(n<=0)return null;const o={};o.propID=n;let a=dy(t[0],t[1],e,1);if((a<0||a>16777215)&&(a=0),o.compositeID=a,e.captureZValues){const n=(e.height-t[1]-1)*e.zbufferBufferWidth+t[0];o.zValue=e.depthValues[n],o.zValue=e.webGPURenderer.convertToOpenGLDepth(o.zValue),o.displayPosition=t}return o}const a=[t[0],t[1]],i=[0,0];let s=py(e,t,0,r);if(s)return s;for(let t=1;t<o;++t){for(let n=a[1]>t?a[1]-t:0;n<=a[1]+t;++n){if(i[1]=n,a[0]>=t&&(i[0]=a[0]-t,s=py(e,i,0,r),s))return s;if(i[0]=a[0]+t,s=py(e,i,0,r),s)return s}for(let n=a[0]>=t?a[0]-(t-1):0;n<=a[0]+(t-1);++n){if(i[0]=n,a[1]>=t&&(i[1]=a[1]-t,s=py(e,i,0,r),s))return s;if(i[1]=a[1]+t,s=py(e,i,0,r),s)return s}}return r[0]=t[0],r[1]=t[1],null}function fy(e,t,n,r,o){const a=Math.floor(t),i=Math.floor(n),s=Math.floor(r),l=Math.floor(o),c=new Map,u=[0,0];for(let t=i;t<=l;t++)for(let n=a;n<=s;n++){const r=py(e,[n,t],0,u);if(r){const t=uy(r);if(c.has(t)){const n=c.get(t);n.pixelCount++,e.captureZValues&&r.zValue<n.info.zValue&&(n.info=r),-1===n.attributeIDs.indexOf(r.attributeID)&&n.attributeIDs.push(r.attributeID)}else c.set(t,{info:r,pixelCount:1,attributeIDs:[r.attributeID]})}}return function(e,t,n){const r=[];let o=0;return t.forEach(((t,a)=>{const i=zp.newInstance();switch(i.setContentType(iy.INDICES),e){case ly.FIELD_ASSOCIATION_CELLS:i.setFieldType(sy.CELL);break;case ly.FIELD_ASSOCIATION_POINTS:i.setFieldType(sy.POINT);break;default:cy("Unknown field association")}i.getProperties().propID=t.info.propID;const s=n.webGPURenderer.getPropFromID(t.info.propID);i.getProperties().prop=s.getRenderable(),i.getProperties().compositeID=t.info.compositeID,i.getProperties().pixelCount=t.pixelCount,n.captureZValues&&(i.getProperties().displayPosition=[t.info.displayPosition[0],t.info.displayPosition[1],t.info.zValue],i.getProperties().worldPosition=n.webGPURenderWindow.displayToWorld(t.info.displayPosition[0],t.info.displayPosition[1],t.info.zValue,n.renderer)),i.setSelectionList(t.attributeIDs),r[o]=i,o++})),r}(e.fieldAssociation,c,e)}const gy={};function my(e,t,n={}){Object.assign(t,gy,n),Fp.extend(e,t,n),t._selectionPass=ay.newInstance(),sn.setGet(e,t,["_WebGPURenderWindow"]),sn.moveToProtected(e,t,["WebGPURenderWindow"]),function(e,t){t.classHierarchy.push("vtkWebGPUHardwareSelector"),e.endSelection=()=>{t.WebGPURenderer.setSelector(null)},e.getSourceDataAsync=async e=>{if(!e||!t._WebGPURenderWindow)return cy("Renderer and view must be set before calling Select."),!1;t._WebGPURenderWindow.getRenderable().preRender(),t._WebGPURenderWindow.getInitialized()||(t._WebGPURenderWindow.initialize(),await new Promise((e=>{t._WebGPURenderWindow.onInitialized(e)})));const n=t._WebGPURenderWindow.getViewNodeFor(e);if(!n)return!1;const r=n.getSuppressClear();n.setSuppressClear(!0),t._selectionPass.traverse(t._WebGPURenderWindow,n),n.setSuppressClear(r);const o=t._WebGPURenderWindow.getDevice(),a=t._selectionPass.getColorTexture(),i=t._selectionPass.getDepthTexture(),s={area:[0,0,a.getWidth()-1,a.getHeight()-1],captureZValues:t.captureZValues,fieldAssociation:t.fieldAssociation,renderer:e,webGPURenderer:n,webGPURenderWindow:t._WebGPURenderWindow,width:a.getWidth(),height:a.getHeight()};s.colorBufferWidth=16*Math.floor((s.width+15)/16),s.colorBufferSizeInBytes=s.colorBufferWidth*s.height*4*4;const l=ZT.newInstance({label:"hardwareSelectColorBuffer"});l.setDevice(o),l.create(s.colorBufferSizeInBytes,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);const c=t._WebGPURenderWindow.getCommandEncoder();let u;c.copyTextureToBuffer({texture:a.getHandle()},{buffer:l.getHandle(),bytesPerRow:16*s.colorBufferWidth,rowsPerImage:s.height},{width:s.width,height:s.height,depthOrArrayLayers:1}),t.captureZValues&&(s.zbufferBufferWidth=64*Math.floor((s.width+63)/64),u=ZT.newInstance({label:"hardwareSelectDepthBuffer"}),u.setDevice(o),s.zbufferSizeInBytes=s.height*s.zbufferBufferWidth*4,u.create(s.zbufferSizeInBytes,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),c.copyTextureToBuffer({texture:i.getHandle(),aspect:"depth-only"},{buffer:u.getHandle(),bytesPerRow:4*s.zbufferBufferWidth,rowsPerImage:s.height},{width:s.width,height:s.height,depthOrArrayLayers:1})),o.submitCommandEncoder(c);const d=l.mapAsync(GPUMapMode.READ);if(t.captureZValues){const e=u.mapAsync(GPUMapMode.READ);await Promise.all([d,e]),s.depthValues=new Float32Array(u.getMappedRange().slice()),u.unmap()}else await d;return s.colorValues=new Uint32Array(l.getMappedRange().slice()),l.unmap(),s.generateSelection=(e,t,n,r)=>fy(s,e,t,n,r),s}}(e,t)}var hy={newInstance:sn.newInstance(my,"vtkWebGPUHardwareSelector"),extend:my};const vy=Object.create(null);const Ty={};function xy(e,t,n={}){Object.assign(t,Ty,n),t.overrides=vy,mn.extend(e,t,n),function(e,t){t.classHierarchy.push("vtkWebGPUViewNodeFactory")}(0,t)}var yy={newInstance:sn.newInstance(xy,"vtkWebGPUViewNodeFactory"),extend:xy};const{vtkErrorMacro:by}=sn,Ay={position:"absolute",top:0,left:0,width:"100%",height:"100%"};function Cy(e,t){t.classHierarchy.push("vtkWebGPURenderWindow"),e.getViewNodeFactory=()=>t.myFactory;const n=[0,0];e.onModified((function(){t.renderable&&(t.size[0]===n[0]&&t.size[1]===n[1]||(n[0]=t.size[0],n[1]=t.size[1],t.canvas.setAttribute("width",t.size[0]),t.canvas.setAttribute("height",t.size[1]),e.recreateSwapChain())),t.viewStream&&t.viewStream.setSize(t.size[0],t.size[1]),t.canvas.style.display=t.useOffScreen?"none":"block",t.el&&(t.el.style.cursor=t.cursorVisibility?t.cursor:"none"),t.containerSize=null})),e.recreateSwapChain=()=>{t.context&&(t.context.unconfigure(),t.presentationFormat=navigator.gpu.getPreferredCanvasFormat(t.adapter),t.context.configure({device:t.device.getHandle(),format:t.presentationFormat,alphaMode:"premultiplied",usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_DST,width:t.size[0],height:t.size[1]}),t._configured=!0)},e.getCurrentTexture=()=>t.context.getCurrentTexture(),e.buildPass=n=>{if(n){if(!t.renderable)return;e.prepareNodes(),e.addMissingNodes(t.renderable.getRenderersByReference()),e.removeUnusedNodes(),e.initialize()}else t.initialized&&(t._configured||e.recreateSwapChain(),t.commandEncoder=t.device.createCommandEncoder())},e.initialize=()=>{if(!t.initializing){if(t.initializing=!0,!navigator.gpu)return void by("WebGPU is not enabled.");e.create3DContextAsync().then((()=>{t.initialized=!0,t.deleted||e.invokeInitialized()}))}},e.setContainer=n=>{t.el&&t.el!==n&&(t.canvas.parentNode!==t.el&&by("Error: canvas parent node does not match container"),t.el.removeChild(t.canvas),t.el.contains(t.bgImage)&&t.el.removeChild(t.bgImage)),t.el!==n&&(t.el=n,t.el&&(t.el.appendChild(t.canvas),t.useBackgroundImage&&t.el.appendChild(t.bgImage)),e.modified())},e.getContainer=()=>t.el,e.getContainerSize=()=>{if(!t.containerSize&&t.el){const{width:e,height:n}=t.el.getBoundingClientRect();t.containerSize=[e,n]}return t.containerSize||t.size},e.getFramebufferSize=()=>t.size,e.create3DContextAsync=async()=>{t.adapter=await navigator.gpu.requestAdapter({powerPreference:"high-performance"}),t.deleted||(t.device=ny.newInstance(),t.device.initialize(await t.adapter.requestDevice({requiredLimits:{maxBufferSize:t.adapter.limits.maxBufferSize,maxStorageBufferBindingSize:t.adapter.limits.maxStorageBufferBindingSize,maxUniformBufferBindingSize:t.adapter.limits.maxUniformBufferBindingSize}})),t.deleted?t.device=null:t.context=t.canvas.getContext("webgpu"))},e.releaseGraphicsResources=()=>{const n=vv.newInstance();n.setCurrentOperation("Release"),n.traverse(e,null),t.adapter=null,t.device=null,t.context=null,t.initialized=!1,t.initializing=!1},e.setBackgroundImage=e=>{t.bgImage.src=e.src},e.setUseBackgroundImage=e=>{t.useBackgroundImage=e,t.useBackgroundImage&&!t.el.contains(t.bgImage)?t.el.appendChild(t.bgImage):!t.useBackgroundImage&&t.el.contains(t.bgImage)&&t.el.removeChild(t.bgImage)},e.captureNextImage=(n="image/png",{resetCamera:r=!1,size:o=null,scale:a=1}={})=>{if(t.deleted)return null;t.imageFormat=n;const i=t.notifyStartCaptureImage;return t.notifyStartCaptureImage=!0,t._screenshot={size:o||1!==a?o||t.size.map((e=>e*a)):null},new Promise(((n,o)=>{const a=e.onImageReady((o=>{if(null===t._screenshot.size)t.notifyStartCaptureImage=i,a.unsubscribe(),t._screenshot.placeHolder&&(t.size=t._screenshot.originalSize,e.modified(),t._screenshot.cameras&&t._screenshot.cameras.forEach((({restoreParamsFn:e,arg:t})=>e(t))),e.traverseAllPasses(),t.el.removeChild(t._screenshot.placeHolder),t._screenshot.placeHolder.remove(),t._screenshot=null),n(o);else{const n=document.createElement("img");if(n.style=Ay,n.src=o,t._screenshot.placeHolder=t.el.appendChild(n),t.canvas.style.display="none",t._screenshot.originalSize=t.size,t.size=t._screenshot.size,t._screenshot.size=null,e.modified(),r){const e=!0!==r;t._screenshot.cameras=t.renderable.getRenderers().map((t=>{const n=t.getActiveCamera(),o=n.get("focalPoint","position","parallelScale");return{resetCameraArgs:e?{renderer:t}:void 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6:t.nodes.push({x:n.getComponent(e,0),r:n.getComponent(e,1),g:n.getComponent(e,2),b:n.getComponent(e,3),midpoint:n.getComponent(e,4),sharpness:n.getComponent(e,5)})}e.sortAndUpdateRange()},e.buildFunctionFromTable=(n,r,o,a)=>{let i=0;e.removeAllPoints(),o>1&&(i=(r-n)/(o-1));for(let e=0;e<o;e++){const r={x:n+i*e,r:a[3*e],g:a[3*e+1],b:a[3*e+2],sharpness:0,midpoint:.5};t.nodes.push(r)}e.sortAndUpdateRange()},e.getNodeValue=(e,n)=>e<0||e>=t.nodes.length?(Gy("Index out of range!"),-1):(n[0]=t.nodes[e].x,n[1]=t.nodes[e].r,n[2]=t.nodes[e].g,n[3]=t.nodes[e].b,n[4]=t.nodes[e].midpoint,n[5]=t.nodes[e].sharpness,1),e.setNodeValue=(n,r)=>{if(n<0||n>=t.nodes.length)return Gy("Index out of range!"),-1;const o=t.nodes[n].x;return t.nodes[n].x=r[0],t.nodes[n].r=r[1],t.nodes[n].g=r[2],t.nodes[n].b=r[3],t.nodes[n].midpoint=r[4],t.nodes[n].sharpness=r[5],o!==r[0]?e.sortAndUpdateRange():e.modified(),1},e.getNumberOfAvailableColors=()=>{if(t.indexedLookup&&e.getSize())return e.getSize();if(t.tableSize)return t.tableSize;const n=t.nodes?.length??0;return Math.max(4094,n)},e.getIndexedColor=(t,n)=>{const r=e.getSize();if(r>0&&t>=0){const o=[];e.getNodeValue(t%r,o);for(let e=0;e<3;++e)n[e]=o[e+1];return void(n[3]=1)}const o=e.getNanColorByReference();n[0]=o[0],n[1]=o[1],n[2]=o[2],n[3]=1},e.fillFromDataPointer=(t,n)=>{if(!(t<=0)&&n){e.removeAllPoints();for(let r=0;r<t;r++)e.addRGBPoint(n[4*r],n[4*r+1],n[4*r+2],n[4*r+3])}},e.setMappingRange=(n,r)=>{const o=[n,r],a=[n,r],i=e.getRange(),s=e.logScaleEnabled();if(i[1]===o[1]&&i[0]===o[0])return;if(o[1]===o[0])return void Gy("attempt to set zero width color range");s&&(o[0]<=0?console.warn("attempt to set log scale color range with non-positive minimum"):(a[0]=Math.log10(o[0]),a[1]=Math.log10(o[1])));const l=(a[1]-a[0])/(i[1]-i[0]),c=a[0]-i[0]*l;for(let e=0;e<t.nodes.length;++e)t.nodes[e].x=t.nodes[e].x*l+c;t.mappingRange[0]=o[0],t.mappingRange[1]=o[1],e.modified()},e.adjustRange=n=>{const r=e.getRange(),o=[];r[0]<n[0]?(e.getColor(n[0],o),e.addRGBPoint(n[0],o[0],o[1],o[2])):(e.getColor(r[0],o),e.addRGBPoint(n[0],o[0],o[1],o[2])),r[1]>n[1]?(e.getColor(n[1],o),e.addRGBPoint(n[1],o[0],o[1],o[2])):(e.getColor(r[1],o),e.addRGBPoint(n[1],o[0],o[1],o[2])),e.sortAndUpdateRange();for(let e=0;e<t.nodes.length;)t.nodes[e].x>=n[0]&&t.nodes[e].x<=n[1]?t.nodes.splice(e,1):++e;return 1},e.estimateMinNumberOfSamples=(t,n)=>{const r=e.findMinimumXDistance();return Math.ceil((n-t)/r)},e.findMinimumXDistance=()=>{if(t.nodes.length<2)return-1;let e=Number.MAX_VALUE;for(let n=0;n<t.nodes.length-1;n++){const r=t.nodes[n+1].x-t.nodes[n].x;r<e&&(e=r)}return e},e.mapScalarsThroughTable=(n,r,o,a)=>{0!==e.getSize()?t.indexedLookup?e.mapDataIndexed(n,r,o,a):e.mapData(n,r,o,a):ky("Transfer Function Has No Points!")},e.mapData=(t,n,r,o)=>{if(0===e.getSize())return void Uy("Transfer Function Has No Points!");const a=Math.floor(255*e.getAlpha()+.5),i=t.getNumberOfTuples(),s=t.getNumberOfComponents(),l=n.getData(),c=t.getData(),u=[];if(r===Ny.RGBA)for(let t=0;t<i;t++){const n=c[t*s+o];e.getColor(n,u),l[4*t]=Math.floor(255*u[0]+.5),l[4*t+1]=Math.floor(255*u[1]+.5),l[4*t+2]=Math.floor(255*u[2]+.5),l[4*t+3]=a}if(r===Ny.RGB)for(let t=0;t<i;t++){const n=c[t*s+o];e.getColor(n,u),l[3*t]=Math.floor(255*u[0]+.5),l[3*t+1]=Math.floor(255*u[1]+.5),l[3*t+2]=Math.floor(255*u[2]+.5)}if(r===Ny.LUMINANCE)for(let t=0;t<i;t++){const n=c[t*s+o];e.getColor(n,u),l[t]=Math.floor(76.5*u[0]+150.45*u[1]+28.05*u[2]+.5)}if(r===Ny.LUMINANCE_ALPHA)for(let t=0;t<i;t++){const n=c[t*s+o];e.getColor(n,u),l[2*t]=Math.floor(76.5*u[0]+150.45*u[1]+28.05*u[2]+.5),l[2*t+1]=a}},e.applyColorMap=n=>{const r=JSON.stringify(t.colorSpace);n.ColorSpace&&(t.colorSpace=By[n.ColorSpace.toUpperCase()],void 0===t.colorSpace&&(Gy(`ColorSpace ${n.ColorSpace} not supported, using RGB instead`),t.colorSpace=By.RGB));let 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Zy={orient:!0,orientationMode:qy.DIRECTION,orientationArray:null,scaling:!0,scaleFactor:1,scaleMode:Yy.SCALE_BY_MAGNITUDE,scaleArray:null,matrixArray:null,normalArray:null,colorArray:null};function Qy(e,t,n={}){Object.assign(t,Zy,n),Ql.extend(e,t,n),sn.algo(e,t,2,0),t.buildTime={},sn.obj(t.buildTime,{mtime:0}),sn.setGet(e,t,["orient","orientationMode","orientationArray","scaleArray","scaleFactor","scaleMode","scaling"]),sn.get(e,t,["colorArray","matrixArray","normalArray","buildTime"]),function(e,t){t.classHierarchy.push("vtkGlyph3DMapper"),e.getOrientationModeAsString=()=>sn.enumToString(qy,t.orientationMode),e.setOrientationModeToDirection=()=>e.setOrientationMode(qy.DIRECTION),e.setOrientationModeToRotation=()=>e.setOrientationMode(qy.ROTATION),e.setOrientationModeToMatrix=()=>e.setOrientationMode(qy.MATRIX),e.getOrientationArrayData=()=>{const n=e.getInputData(0);return n&&n.getPointData()?t.orientationArray?n.getPointData().getArray(t.orientationArray):n.getPointData().getVectors():null},e.getScaleModeAsString=()=>sn.enumToString(Yy,t.scaleMode),e.setScaleModeToScaleByMagnitude=()=>e.setScaleMode(Yy.SCALE_BY_MAGNITUDE),e.setScaleModeToScaleByComponents=()=>e.setScaleMode(Yy.SCALE_BY_COMPONENTS),e.setScaleModeToScaleByConstant=()=>e.setScaleMode(Yy.SCALE_BY_CONSTANT),e.getScaleArrayData=()=>{const n=e.getInputData(0);return n&&n.getPointData()?t.scaleArray?n.getPointData().getArray(t.scaleArray):n.getPointData().getScalars():null},e.computeBounds=()=>e.buildArrays(),e.buildArrays=()=>{const n=e.getInputData(0),r=e.getInputData(1);if(n&&r){if(t.buildTime.getMTime()<r.getMTime()||t.buildTime.getMTime()<n.getMTime()||t.buildTime.getMTime()<e.getMTime()){const o=n.getPoints().getData();let a=e.getScaleArrayData(),i=null,l=0;a&&(i=a.getData(),l=a.getNumberOfComponents()),t.scaling&&a&&t.scaleMode===Yy.SCALE_BY_COMPONENTS&&3!==a.getNumberOfComponents()&&(Jy("Cannot scale by components since scale array does not have 3 components."),a=null);const c=r.getBounds(),p=[];Hi.getCorners(c,p),Hi.reset(t.bounds);const f=new Float64Array(3),g=e.getOrientationArrayData(),m=x(new Float64Array(16)),h=[],v=[],T=o.length/3;t.matrixArray=new Float32Array(16*T);const y=t.matrixArray.buffer;t.normalArray=new Float32Array(9*T);const b=t.normalArray.buffer,R=[],M=[];for(let e=0;e<T;++e){const n=new Float32Array(y,64*e,16);if(h[0]=o[3*e],h[1]=o[3*e+1],h[2]=o[3*e+2],C(n,m,h),g)switch(g.getTuple(e,M),t.orientationMode){case qy.MATRIX:A(n,n,[...M.slice(0,3),0,...M.slice(3,6),0,...M.slice(6,9),0,0,0,0,1]);break;case qy.ROTATION:O(n,n,M[2]),w(n,n,M[0]),I(n,n,M[1]);break;case qy.DIRECTION:if(0===M[1]&&0===M[2])M[0]<0&&I(n,n,3.1415926);else{const 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rb={newInstance:sn.newInstance(nb,"vtkPiecewiseFunction"),extend:nb};const{InterpolationType:ob,OpacityMode:ab,FilterMode:ib,ColorMixPreset:sb}=mg,{vtkErrorMacro:lb}=sn;function cb(e,t,n={}){if(Object.assign(t,(e=>({colorMixPreset:sb.DEFAULT,independentComponents:!0,interpolationType:ob.FAST_LINEAR,shade:!1,ambient:.1,diffuse:.7,specular:.2,specularPower:10,useLabelOutline:!1,labelOutlineThickness:[1],labelOutlineOpacity:1,ipScalarRange:[-1e6,1e6],filterMode:ib.OFF,preferSizeOverAccuracy:!1,computeNormalFromOpacity:!1,volumetricScatteringBlending:0,globalIlluminationReach:0,anisotropy:0,localAmbientOcclusion:!1,LAOKernelSize:15,LAOKernelRadius:7,updatedExtents:[],...e}))(n)),sn.obj(e,t),!t.componentData){t.componentData=[];for(let 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r=0;r<4;r++)1===t.componentData[r].colorChannels?t.componentData[r].grayTransferFunction&&(e=t.componentData[r].grayTransferFunction.getMTime(),n=n>e?n:e):3===t.componentData[r].colorChannels&&t.componentData[r].rGBTransferFunction&&(e=t.componentData[r].rGBTransferFunction.getMTime(),n=n>e?n:e),t.componentData[r].scalarOpacity&&(e=t.componentData[r].scalarOpacity.getMTime(),n=n>e?n:e),t.componentData[r].gradientOpacity&&(t.componentData[r].disableGradientOpacity||(e=t.componentData[r].gradientOpacity.getMTime(),n=n>e?n:e));return n},e.getColorChannels=e=>e<0||e>3?(lb("Bad index - must be between 0 and 3"),0):t.componentData[e].colorChannels,e.setGrayTransferFunction=(n=0,r=null)=>{let o=!1;return 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lb("Invalid index"),!1;const o=Math.min(1,Math.max(0,r));return t.componentData[n].componentWeight!==o&&(t.componentData[n].componentWeight=o,e.modified(),!0)},e.getComponentWeight=(e=0)=>e<0||e>=4?(lb("Invalid index"),0):t.componentData[e].componentWeight,e.setInterpolationTypeToNearest=()=>e.setInterpolationType(ob.NEAREST),e.setInterpolationTypeToLinear=()=>e.setInterpolationType(ob.LINEAR),e.setInterpolationTypeToFastLinear=()=>e.setInterpolationType(ob.FAST_LINEAR),e.getInterpolationTypeAsString=()=>sn.enumToString(ob,t.interpolationType),["useGradientOpacity","scalarOpacityUnitDistance","gradientOpacityMinimumValue","gradientOpacityMinimumOpacity","gradientOpacityMaximumValue","gradientOpacityMaximumOpacity","opacityMode","forceNearestInterpolation"].forEach((n=>{const r=sn.capitalize(n);e[`set${r}`]=(r,o)=>t.componentData[r][`${n}`]!==o&&(t.componentData[r][`${n}`]=o,e.modified(),!0)})),["useGradientOpacity","scalarOpacityUnitDistance","gradientOpacityMinimumValue","gradientOpacityMinimumOpacity","gradientOpacityMaximumValue","gradientOpacityMaximumOpacity","opacityMode","forceNearestInterpolation"].forEach((n=>{const r=sn.capitalize(n);e[`get${r}`]=e=>t.componentData[e][`${n}`]})),e.setAverageIPScalarRange=(t,n)=>{console.warn("setAverageIPScalarRange is deprecated use 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n=t.mapper.getMTime();e=n>e?n:e,null!==t.mapper.getInput()&&(t.mapper.getInputAlgorithm().update(),n=t.mapper.getInput().getMTime(),e=n>e?n:e)}return e}}(e,t)}var fb={newInstance:sn.newInstance(pb,"vtkVolume"),extend:pb};const{BlendMode:gb}=vg;const mb=["getAnisotropy","getComputeNormalFromOpacity","getFilterMode","getFilterModeAsString","getGlobalIlluminationReach","getIpScalarRange","getIpScalarRangeByReference","getLAOKernelRadius","getLAOKernelSize","getLocalAmbientOcclusion","getPreferSizeOverAccuracy","getVolumetricScatteringBlending","setAnisotropy","setAverageIPScalarRange","setComputeNormalFromOpacity","setFilterMode","setFilterModeToNormalized","setFilterModeToOff","setFilterModeToRaw","setGlobalIlluminationReach","setIpScalarRange","setIpScalarRangeFrom","setLAOKernelRadius","setLAOKernelSize","setLocalAmbientOcclusion","setPreferSizeOverAccuracy","setVolumetricScatteringBlending"],hb={createRadonTransferFunction:function(e,t,n,r,o){let a=null;return o?(a=o,a.removeAllPoints()):a=rb.newInstance(),a.addPointLong(-1024,0,1,1),a.addPoint(e,t),a.addPoint(n,r),a}};function vb(e,t,n={}){Object.assign(t,(e=>({bounds:[...Hi.INIT_BOUNDS],sampleDistance:1,imageSampleDistance:1,maximumSamplesPerRay:1e3,autoAdjustSampleDistances:!0,initialInteractionScale:1,interactionSampleDistanceFactor:1,blendMode:gb.COMPOSITE_BLEND,volumeShadowSamplingDistFactor:5,colorTextureWidth:1024,opacityTextureWidth:1024,labelOutlineTextureWidth:1024,...e}))(n)),Ls.extend(e,t,n),sn.setGet(e,t,["sampleDistance","imageSampleDistance","maximumSamplesPerRay","autoAdjustSampleDistances","initialInteractionScale","interactionSampleDistanceFactor","blendMode","volumeShadowSamplingDistFactor","colorTextureWidth","opacityTextureWidth","labelOutlineTextureWidth"]),sn.event(e,t,"lightingActivated"),function(e,t){t.classHierarchy.push("vtkVolumeMapper");const n={...e};e.computeBounds=()=>{const 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It is a rendering property that has been moved to the volume property. Replace your code with:\nvolumeActor.getProperty().${t}()\n`)}}))}(e,t)}var Tb={newInstance:sn.newInstance(vb,"vtkVolumeMapper"),extend:vb,...hb};const{InterpolationType:xb}=jf,{vtkErrorMacro:yb}=sn;function bb(e,t,n={}){if(Object.assign(t,(e=>({independentComponents:!1,interpolationType:xb.LINEAR,colorWindow:255,colorLevel:127.5,ambient:1,diffuse:0,opacity:1,useLookupTableScalarRange:!1,useLabelOutline:!1,labelOutlineThickness:[1],labelOutlineOpacity:1,updatedExtents:[],...e}))(n)),sn.obj(e,t),!t.componentData){t.componentData=[];for(let e=0;e<4;e++)t.componentData.push({rGBTransferFunction:null,piecewiseFunction:null,componentWeight:1})}sn.setGet(e,t,["independentComponents","interpolationType","colorWindow","colorLevel","ambient","diffuse","opacity","useLookupTableScalarRange","useLabelOutline","labelOutlineOpacity","updatedExtents"]),sn.setGetArray(e,t,["labelOutlineThickness"]),function(e,t){t.classHierarchy.push("vtkImageProperty"),e.getMTime=()=>{let e,n=t.mtime;for(let r=0;r<4;r++)t.componentData[r].rGBTransferFunction&&(e=t.componentData[r].rGBTransferFunction.getMTime(),n=n>e?n:e),t.componentData[r].piecewiseFunction&&(e=t.componentData[r].piecewiseFunction.getMTime(),n=n>e?n:e);return n},e.setRGBTransferFunction=(n=0,r=null)=>{let o=n,a=r;return Number.isInteger(n)||(a=n,o=0),t.componentData[o].rGBTransferFunction!==a&&(t.componentData[o].rGBTransferFunction=a,e.modified(),!0)},e.getRGBTransferFunction=(e=0)=>t.componentData[e].rGBTransferFunction,e.setPiecewiseFunction=(n=0,r=null)=>{let o=n,a=r;return Number.isInteger(n)||(a=n,o=0),t.componentData[o].piecewiseFunction!==a&&(t.componentData[o].piecewiseFunction=a,e.modified(),!0)},e.getPiecewiseFunction=(e=0)=>t.componentData[e].piecewiseFunction,e.setScalarOpacity=(t=0,n=null)=>{let r=t,o=n;return Number.isInteger(t)||(o=t,r=0),e.setPiecewiseFunction(r,o)},e.getScalarOpacity=(t=0)=>e.getPiecewiseFunction(t),e.setComponentWeight=(n=0,r=1)=>{if(n<0||n>=4)return yb("Invalid index"),!1;const 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n=n&&(!t.mapper||t.mapper.getIsOpaque()),n},e.hasTranslucentPolygonalGeometry=()=>!1,e.makeProperty=Ab.newInstance,e.getBoundsForSlice=(n,r)=>{const o=t.mapper.getBoundsForSlice(n,r);if(!Hi.isValid(o))return o;e.computeMatrix();const a=new Float64Array(16);return y(a,t.matrix),Hi.transformBounds(o,a)},e.getMinXBound=()=>e.getBoundsByReference()[0],e.getMaxXBound=()=>e.getBoundsByReference()[1],e.getMinYBound=()=>e.getBoundsByReference()[2],e.getMaxYBound=()=>e.getBoundsByReference()[3],e.getMinZBound=()=>e.getBoundsByReference()[4],e.getMaxZBound=()=>e.getBoundsByReference()[5],e.getRedrawMTime=()=>{let e=t.mtime;if(null!==t.mapper){let n=t.mapper.getMTime();e=n>e?n:e,null!==t.mapper.getInput()&&(t.mapper.getInputAlgorithm().update(),n=t.mapper.getInput().getMTime(),e=n>e?n:e)}return t.properties.forEach((t=>{e=Math.max(e,t.getMTime());const n=t.getRGBTransferFunction();null!==n&&(e=Math.max(e,n.getMTime()))})),e},e.getSupportsSelection=()=>!!t.mapper&&t.mapper.getSupportsSelection()}(e,t)}var Pb={newInstance:sn.newInstance(Sb,"vtkImageSlice"),extend:Sb};const wb={slice:0,customDisplayExtent:[0,0,0,0,0,0],useCustomExtents:!1,backgroundColor:[0,0,0,1],colorTextureWidth:1024,opacityTextureWidth:1024,labelOutlineTextureWidth:1024};var Ib={extend:function(e,t,n={}){Object.assign(t,wb,n),Ls.extend(e,t,n),sn.setGet(e,t,["slice","useCustomExtents","colorTextureWidth","opacityTextureWidth","labelOutlineTextureWidth"]),sn.setGetArray(e,t,["customDisplayExtent"],6),sn.setGetArray(e,t,["backgroundColor"],4),function(e,t){t.classHierarchy.push("vtkAbstractImageMapper"),e.getIsOpaque=()=>!0,e.getCurrentImage=()=>null,e.getBoundsForSlice=()=>(sn.vtkErrorMacro("vtkAbstractImageMapper.getBoundsForSlice - NOT IMPLEMENTED"),Ga())}(e,t)}};function Ob(e,t,n){const r=n.getCurrentImage(),o=r.getExtent(),a=[o[0],o[2],o[4]],{ijkMode:i}=n.getClosestIJKAxis();let s=n.isA("vtkImageArrayMapper")?n.getSubSlice():n.getSlice();i!==n.getSlicingMode()&&(s=n.getSliceAtPosition(s)),a[i]+=s;const l=[0,0,0];r.indexToWorld(a,l),a[i]+=1;const c=[0,0,0];r.indexToWorld(a,c),c[0]-=l[0],c[1]-=l[1],c[2]-=l[2],te(c,c);const u=ai.intersectWithLine(e,t,l,c);if(u.intersection){const e=u.x,t=[0,0,0];return r.worldToIndex(e,t),{t:u.t,absoluteIJK:t}}return null}const{staticOffsetAPI:Rb,otherStaticMethods:Mb}=Ll,{SlicingMode:Db}=Qf;function Eb(e,t){function n(){let n;switch(t.slicingMode){case Db.X:n=0;break;case Db.Y:n=1;break;case Db.Z:n=2;break;default:return void(t.closestIJKAxis={ijkMode:t.slicingMode,flip:!1})}const r=Ua(e.getCurrentImage().getDirection());let o=0;for(;o<3&&0===r[n+3*o];++o);const a=r[n+3*o]<0;t.closestIJKAxis={ijkMode:o,flip:a}}t.classHierarchy.push("vtkImageMapper"),e.getSliceAtPosition=n=>{const r=e.getCurrentImage();let o;if(3===n.length)o=n;else 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Db.Z:e.setSlice(r[2])}},e.setXSlice=t=>{e.setSlicingMode(Db.X),e.setSlice(t)},e.setYSlice=t=>{e.setSlicingMode(Db.Y),e.setSlice(t)},e.setZSlice=t=>{e.setSlicingMode(Db.Z),e.setSlice(t)},e.setISlice=t=>{e.setSlicingMode(Db.I),e.setSlice(t)},e.setJSlice=t=>{e.setSlicingMode(Db.J),e.setSlice(t)},e.setKSlice=t=>{e.setSlicingMode(Db.K),e.setSlice(t)},e.getSlicingModeNormal=()=>{const n=[0,0,0],r=e.getCurrentImage().getDirection();switch(t.slicingMode){case Db.X:n[0]=1;break;case Db.Y:n[1]=1;break;case Db.Z:n[2]=1;break;case Db.I:$o(r,[1,0,0],n);break;case Db.J:$o(r,[0,1,0],n);break;case Db.K:$o(r,[0,0,1],n)}return n},e.setSlicingMode=r=>{t.slicingMode!==r&&(t.slicingMode=r,e.getCurrentImage()&&n(),e.modified())},e.getClosestIJKAxis=()=>(void 0!==t.closestIJKAxis&&t.closestIJKAxis.ijkMode!==Db.NONE||!e.getCurrentImage()||n(),t.closestIJKAxis),e.computeBounds=()=>{const n=e.getCurrentImage();if(!n)return void Hi.reset(t.bounds);if(!t.useCustomExtents)return void 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o=t.getPointData();o?(g=g&&null!==o.getNormals(),m=m&&null!==o.getTCoords(),h=h&&null!==o.getScalars()):(g=!1,m=!1,h=!1)}t.outputPointsPrecision===Us.SINGLE?s=ms.FLOAT:t.outputPointsPrecision===Us.DOUBLE&&(s=ms.DOUBLE);const v=lc.newInstance({dataType:s});v.setNumberOfPoints(i);const T=v.getData(),x=new Uint32Array(u),y=new Uint32Array(d),b=new Uint32Array(p),A=new Uint32Array(f);let C=null,S=null,P=null;const w=n[o-1];if(g){const e=w.getPointData().getNormals();C=Is.newInstance({numberOfComponents:3,numberOfTuples:i,size:3*i,dataType:e.getDataType(),name:e.getName()})}if(m){const e=w.getPointData().getTCoords();S=Is.newInstance({numberOfComponents:2,numberOfTuples:i,size:2*i,dataType:e.getDataType(),name:e.getName()})}if(h){const e=w.getPointData().getScalars();P=Is.newInstance({numberOfComponents:e.getNumberOfComponents(),numberOfTuples:i,size:i*e.getNumberOfComponents(),dataType:e.getDataType(),name:e.getName()})}i=0,u=0,d=0,p=0,f=0;for(let e=0;e<o;e++){const t=n[e];T.set(t.getPoints().getData(),3*i),Nb(x,t.getVerts().getData(),i,u),u+=t.getVerts().getNumberOfValues(),Nb(y,t.getLines().getData(),i,d),d+=t.getLines().getNumberOfValues(),Nb(b,t.getStrips().getData(),i,p),p+=t.getStrips().getNumberOfValues(),Nb(A,t.getPolys().getData(),i,f),f+=t.getPolys().getNumberOfValues();const r=t.getPointData();if(g){const e=r.getNormals();C.getData().set(e.getData(),3*i)}if(m){const e=r.getTCoords();S.getData().set(e.getData(),2*i)}if(h){const e=r.getScalars();P.getData().set(e.getData(),i*P.getNumberOfComponents())}i+=t.getPoints().getNumberOfPoints()}a.setPoints(v),a.getVerts().setData(x),a.getLines().setData(y),a.getStrips().setData(b),a.getPolys().setData(A),C&&a.getPointData().setNormals(C),S&&a.getPointData().setTCoords(S),P&&a.getPointData().setScalars(P),r[0]=a}}(e,t)}var Ub={newInstance:sn.newInstance(Gb,"vtkAppendPolyData"),extend:Gb};const _b={height:1,radius:.5,resolution:6,center:[0,0,0],direction:[1,0,0],capping:!0,pointType:"Float64Array"};function Kb(e,t,n={}){Object.assign(t,_b,n),sn.obj(e,t),sn.setGet(e,t,["height","radius","resolution","capping"]),sn.setGetArray(e,t,["center","direction"],3),sn.algo(e,t,0,1),function(e,t){t.classHierarchy.push("vtkConeSource"),e.requestData=(e,n)=>{const r=2*Math.PI/t.resolution,o=-t.height/2,a=t.resolution+1,i=4*t.resolution+1+t.resolution;let s=0;const l=sn.newTypedArray(t.pointType,3*a);let c=0;const u=new Uint32Array(i);l[0]=t.height/2,l[1]=0,l[2]=0,t.capping&&(u[c++]=t.resolution);for(let e=0;e<t.resolution;e++)s++,l[3*s+0]=o,l[3*s+1]=t.radius*Math.cos(e*r),l[3*s+2]=t.radius*Math.sin(e*r),t.capping&&(u[t.resolution-c+++1]=s);for(let e=0;e<t.resolution;e++)u[c++]=3,u[c++]=0,u[c++]=e+1,u[c++]=e+2>t.resolution?1:e+2;Of.buildFromRadian().translate(...t.center).rotateFromDirections([1,0,0],t.direction).apply(l);const 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Float32Array(2*o),p=Is.newInstance({numberOfComponents:2,values:d,name:"TCoords"}),f=[0,0,0],g=[0,0,0],m=[0,0,0],h=[0,0,0],v=[0,0],T=[0,0],x=null==t.otherRadius?t.radius:t.otherRadius;for(let e=0;e<t.resolution;e++){f[0]=Math.cos(e*r+t.initAngle),g[0]=f[0],m[0]=t.radius*f[0]+t.center[0],h[0]=m[0],v[0]=Math.abs(2*e/t.resolution-1),T[0]=v[0],m[1]=.5*t.height+t.center[1],h[1]=-.5*t.height+t.center[1],v[1]=0,T[1]=1,f[2]=-Math.sin(e*r+t.initAngle),g[2]=f[2],m[2]=x*f[2]+t.center[2],h[2]=m[2];const n=2*e;for(let e=0;e<3;e++)c[3*n+e]=f[e],c[3*(n+1)+e]=g[e],i[3*n+e]=m[e],i[3*(n+1)+e]=h[e],e<2&&(d[2*n+e]=v[e],d[2*(n+1)+e]=T[e])}for(let e=0;e<t.resolution;e++){l[s++]=4,l[s++]=2*e,l[s++]=2*e+1;const n=(2*e+3)%(2*t.resolution);l[s++]=n,l[s++]=n-1}if(t.capping){for(let e=0;e<t.resolution;e++){m[0]=t.radius*Math.cos(e*r+t.initAngle),h[0]=m[0],v[0]=m[0],T[0]=m[0],m[0]+=t.center[0],h[0]+=t.center[0],f[1]=1,g[1]=-1,m[1]=.5*t.height+t.center[1],h[1]=-.5*t.height+t.center[1],m[2]=-x*Math.sin(e*r+t.initAngle),h[2]=m[2],v[1]=m[2],T[1]=m[2],m[2]+=t.center[2],h[2]+=t.center[2];const n=2*t.resolution+e,o=3*t.resolution+t.resolution-e-1;for(let e=0;e<3;e++)c[3*n+e]=f[e],c[3*o+e]=g[e],i[3*n+e]=m[e],i[3*o+e]=h[e],e<2&&(d[2*n+e]=v[e],d[2*o+e]=T[e])}l[s++]=t.resolution;for(let e=0;e<t.resolution;e++)l[s++]=2*t.resolution+e;l[s++]=t.resolution;for(let e=0;e<t.resolution;e++)l[s++]=3*t.resolution+e}Of.buildFromRadian().translate(...t.center).rotateFromDirections([0,1,0],t.direction).translate(...t.center.map((e=>-1*e))).apply(i);const y=n[0]?.initialize()||Ru.newInstance();y.getPoints().setData(i,3),y.getPolys().setData(l,1),y.getPointData().setNormals(u),y.getPointData().setTCoords(p),n[0]=y}}(e,t)}var jb={newInstance:sn.newInstance(Hb,"vtkCylinderSource"),extend:Hb};const Xb={tipResolution:6,tipRadius:.1,tipLength:.35,shaftResolution:6,shaftRadius:.03,invert:!1,direction:[1,0,0],pointType:"Float64Array"};function qb(e,t,n={}){Object.assign(t,Xb,n),sn.obj(e,t),sn.setGet(e,t,["tipResolution","tipRadius","tipLength","shaftResolution","shaftRadius","invert"]),sn.setGetArray(e,t,["direction"],3),sn.algo(e,t,0,1),function(e,t){t.classHierarchy.push("vtkArrowSource"),e.requestData=(e,n)=>{const r=jb.newInstance({capping:!0});r.setResolution(t.shaftResolution),r.setRadius(t.shaftRadius),r.setHeight(1-t.tipLength),r.setCenter(0,.5*(1-t.tipLength),0);const o=r.getOutputData(),a=o.getPoints().getData(),i=o.getPointData().getNormals().getData();Of.buildFromDegree().rotateZ(-90).apply(a).apply(i);const s=zb.newInstance();s.setResolution(t.tipResolution),s.setHeight(t.tipLength),s.setRadius(t.tipRadius);const l=s.getOutputData(),c=l.getPoints().getData();Of.buildFromRadian().translate(1-.5*t.tipLength,0,0).apply(c);const u=Ub.newInstance();u.setInputData(o),u.addInputData(l);const d=u.getOutputData(),p=d.getPoints().getData();Of.buildFromRadian().translate(.5*t.tipLength-.5,0,0).apply(p),t.invert?(Of.buildFromRadian().rotateFromDirections([1,0,0],t.direction).scale(-1,-1,-1).apply(p),n[0]=d):(Of.buildFromRadian().rotateFromDirections([1,0,0],t.direction).scale(1,1,1).apply(p),n[0]=u.getOutputData())}}(e,t)}var Yb={newInstance:sn.newInstance(qb,"vtkArrowSource"),extend:qb};function Jb(e){const t=e.getPoints().getBounds(),n=[.5*-(t[0]+t[1]),.5*-(t[2]+t[3]),.5*-(t[4]+t[5])];Of.buildFromDegree().translate(...n).apply(e.getPoints().getData())}function Zb(e,t,n=!1){const r=e.getPoints().getBounds(),o=[0,0,0];o[t]=n?-r[2*t+1]:-r[2*t],Of.buildFromDegree().translate(...o).apply(e.getPoints().getData())}function Qb(e,t,n,r){const o=e.getPoints().getData().length,a=new Uint8ClampedArray(o);let 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a=Yb.newInstance({direction:[0,0,1],...e}).getOutputData();t.config.recenter?Jb(a):Zb(a,2,e.invert),Qb(a,...e.color);const i=Ub.newInstance();i.setInputData(r),i.addInputData(o),i.addInputData(a),n.setInputConnection(i.getOutputPort())},e.update();const r=sn.debounce(e.update,0);e.setXAxisColor=t=>e.setXConfig({...e.getXConfig(),color:t}),e.setYAxisColor=t=>e.setYConfig({...e.getYConfig(),color:t}),e.setZAxisColor=t=>e.setZConfig({...e.getZConfig(),color:t}),e.getXAxisColor=()=>t.getXConfig().color,e.getYAxisColor=()=>t.getYConfig().color,e.getZAxisColor=()=>t.getZConfig().color,t._onConfigChanged=r,t._onXConfigChanged=r,t._onYConfigChanged=r,t._onZConfigChanged=r}(e,t)}var eA={newInstance:sn.newInstance($b,"vtkAxesActor"),extend:$b};const tA="resetcamera",nA="orientation",rA={MODE_RESET_CAMERA:tA,MODE_ORIENTATION:nA,MODE_SAME:"same"};function oA(e,t){t.classHierarchy.push("vtkCameraSynchronizer");const n=new Float64Array(9),r=new Float64Array(3),o=[];function a(){for(;o.length;)o.pop().unsubscribe();if(!t.srcRenderer||!t.dstRenderer)return;const n=t.srcRenderer.getActiveCamera(),r=t.srcRenderer.getRenderWindow().getInteractor();o.push(n.onModified((()=>{r.isAnimating()||e.update()}))),o.push(r.onAnimation(e.update)),o.push(r.onEndAnimation(e.update))}t._onSrcRendererChanged=a,t._onDstRendererChanged=a,e.update=()=>{if(!t.active||!t.srcRenderer||!t.dstRenderer)return;const e=t.srcRenderer.getActiveCamera(),o=t.dstRenderer.getActiveCamera(),a=function(e,t,r){return(n[0]!==e[0]||n[1]!==e[1]||n[2]!==e[2]||n[3]!==t[0]||n[4]!==t[1]||n[5]!==t[2]||n[6]!==r[0]||n[7]!==r[1]||n[8]!==r[2])&&(n[0]=e[0],n[1]=e[1],n[2]=e[2],n[3]=t[0],n[4]=t[1],n[5]=t[2],n[6]=r[0],n[7]=r[1],n[8]=r[2],n)}(e.getReferenceByName("position"),e.getReferenceByName("focalPoint"),e.getReferenceByName("viewUp"));a&&(t.mode===nA?(r[0]=a[0]-a[3],r[1]=a[1]-a[4],r[2]=a[2]-a[5],jo(r),o.setPosition(t.focalPoint[0]+t.distance*r[0],t.focalPoint[1]+t.distance*r[1],t.focalPoint[2]+t.distance*r[2]),o.setFocalPoint(t.focalPoint[0],t.focalPoint[1],t.focalPoint[2]),o.setViewUp(a[6],a[7],a[8])):(o.setPosition(a[0],a[1],a[2]),o.setFocalPoint(a[3],a[4],a[5]),o.setViewUp(a[6],a[7],a[8])),t.mode===tA&&t.dstRenderer.resetCamera())},e.delete=qt((()=>e.setSrcRenderer(null)),e.delete),a()}const aA={mode:nA,focalPoint:[0,0,0],distance:6.8,active:!0};function iA(e,t,n={}){Object.assign(t,aA,n),Vt(e,t),Gt(e,t,["mode","active","srcRenderer","dstRenderer","distance"]),Kt(e,t,["focalPoint"],3,0),oA(e,t)}var sA={newInstance:Xt(iA,"vtkCameraSynchronizer"),extend:iA,SynchronizationMode:rA};const lA={};const cA={CameraSync:class{constructor(e,t){this.ctx=e,this.behavior=sA.newInstance(this.getProperties(t)),this.behavior.update()}getProperties({actorBounds:e,srcRenderer:t,dstRenderer:n}){return{distance:3.4*Math.max(e[1]-e[0],e[3]-e[2],e[5]-e[4]),focalPoint:[.5*(e[0]+e[1]),.5*(e[2]+e[3]),.5*(e[4]+e[5])],mode:sA.SynchronizationMode.MODE_ORIENTATION,srcRenderer:this.ctx.getInstance(t),dstRenderer:this.ctx.getInstance(n)}}update(e){this.behavior.set(this.getProperties(e)),this.behavior.update()}delete(){this.behavior.delete()}}};var uA={applyBehaviors:function(e,t,n){const r=e.get("synchronizedViewId").synchronizedViewId;if(!t.behaviors||!r)return;lA[r]||(lA[r]={});const o=lA[r];if(t.behaviors.autoOrientation){const 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UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH/1v7+KKKKACiiigDgvij4Qj8e/D3V/CLgFr22dY89pV+aI/g4U1+CkE1xYXaXERMcsLhlPQhlOR+Rr+iivwq+PHhoeEvjB4g0WNdkYu3mjXsEnxKgHsFcCvEzin8Mz8D8bss92hjY7q8X+a/U+kf22Eh1n/hEPHlqPk1SwcAj+6Nkq/8Ao04qt+yhIbv4bfEnR35V9NBA/wB6G5U/0qL40S/25+yr4A8QHn7M4s8/7kbx4/8AINVf2RJNujePUb7p0gk/gsv+NY74lS7r9Dwfac3E8K62qQ5v/AqTv+J8N6ucaVdH/pk//oJr6r/YH8CaLoVn4g/aO8ZgJYaBDLDbOwztZY99xIv+0sZCLjrvYda+T9cbZo10f+mTj8xivtD483J+DH7E/hD4WWR8q88RiOa6A4YqcXU4J6kiR40/3eOlffcDuUsFPDQetSaXySu/wObwvpxgq2LmtKevz2X4n59fFb4j678XfiFqPjvXCTNfykxxZyIohxHEvsq4Huck8k1+nMM1n+w3+zHHcKiDxv4oAOGALJKVzyD/AAWqN05Blb0aviv9jH4axfEr49aXBfRiSy0gNqVwpGQRAR5YPYgysmQeozUv7Z3xUl+J/wAcdSjtpS+naGx061XPy/uiRK47HfLuwe6hfSv1HHUI18RTwEV7kVzS/KKPtsBXlh8PUx8n+8k+WP8A7czx34beAfFnxv8AiRa+E9Ldp7/VJmee4ly+xSd0s0hPJwMk5OWPA5Ir+jb4Z/Djwx8J/Bll4G8JQ+VaWa4LHG+WQ/fkkPd2PJP4DAAA+Jf+CeHwgh8MfD64+K2qRD7fr7GK2JHKWkTY47jzJASfUKhr9Fq+F4zzl16/1eD92H4v/gbH3PBmTKhQ+sTXvT/Bf8HcKKKK+LPtAooooAK/LL/gpp4r8rRvC/geJs+fNPfSr6eUoijP4+ZJ+VfqbX4N/wDBQHxX/wAJD+0LcaSjbo9Fsre0GOm5lM7fjmXB+mO1fWcFYb2mPjL+VN/p+p8nxrifZ4CS/maX6/ofEdfe3/BOzwp/bfx0m8RSrmPRdPmlVvSWYrCo/FHf8q+Ca/Y7/gmh4U+x+BvEfjWRcNqF7HaIT/dto95x7EzY+o9q/SuK8V7LAVH30+//AIB+bcJ4b2uPprtr93/BP0yr8tf2xv2yv7J+1fCX4R3X+lfNFqGoxN/quzQwMP4+zuPu9F+bJWv+2N+2X9i+1fCX4RXf7/mLUdShb7nZoYGH8XZ3H3furzkj8ka+T4U4TvbFYpei/V/oj6viviy18LhX6v8ARfqwJzya1NF0XV/EerW+haDbSXl5duI4YYlLO7N0AA61q+C/BXif4heJLbwl4Ps3vr+7bbHGg/NmJ4VVHLMSAByTX7yfsyfsq+GPgJpI1W/2ah4luUxcXmPliB6xQZGQnq3DP3wMKPr8+4gpYGGusnsv8/I+RyHh6rjp6aRW7/y8zhv2U/2OtI+D1vD438eJHe+J5Fyi8PFZBh92M9Gl7NJ26Lxkt92UUV+J5hmFXFVXVrO7/rY/a8Bl9LDUlSoqy/rcKrT2VndENdQpIR03KDj8was1+SPiL/gpR4h07xBfafpHhy0uLSC4ljhladwXjVyEYgLjJUA8V0ZXk+Ixbaw6vbfoYZnnGHwiTxDtfyufq7/ZGk/8+sP/AHwv+FWYLS1tQRaxJFu67VAz+QFfkD/w808Zf9CtZf8AgRJ/8TX6xeDdW1LXvCGl67rEC213e2kM80KElY5JEDMgJ5IUnGT6VpmmSYrCRTxCtfzuZ5ZnWFxcmsO728rHSVla7q9p4f0S816/OILGCS4kP+xEpdv0Ffnp8fv269Y+EPxU1H4eaFoltqEWnCIPNJM6kvJGsjDCgj5dwH1Br5n+In/BQbxl4+8Dar4JOgWtkuq20lq80czsypKNr4BABypI/GvQwXCGMqqFTl912e62Z5+N4uwVJzhze8rrZ7r5HwTrGqXeuavda1fndPeTPPIfV5GLMfzNQWFjc6nfQ6bZLvmuJFijUd2cgAfiTVSup8D+JR4M8ZaV4vNst4dLuorsQOSqyNC4dVYjPBIGa/bJXUXyI/E42lJc7P6evC+hW3hbwzp3hmy/1OnWsNrH2+WFAg/QVu1+PP8Aw808Zf8AQrWX/gRJ/wDE19Sfsr/tWeKv2h/FOp6PqWiW+nWmnWomaaKV3YyO4VEwwAwRvOfavw7HcL42jCVetHRb6o/ccDxPga040KMtXto/8j7ior5H/au/aN1/9new0TUdH0qHU49TknjkM0jJ5bRhCmNoOdwZs59K+Mf+HmnjL/oVrL/wIk/+JrPA8MYzE0lWpRun5o0x3E2Dw1V0a0rNeT/yP2Gor4o/ZU/at1b9obWtX0fV9Kg01tOgimQwyM+8OxVs7gMY4/OvtevLx+AqYaq6NZWaPUwOOpYmkq1F3TCiiuC+KHxA0n4WeANV8fa1zBpsDSBM4Mkh+WOMH1dyFH1rnpUpTkoRWrOirUjCLnJ6I72ivx5/4eaeMv8AoVrL/wACJP8A4mj/AIeaeMv+hWsv/AiT/wCJr6f/AFKzD+Rfej5j/XTL/wCf8H/kfsNRXjXwA+KVx8ZvhPpnxFvLZLOa+M6vBGxdUMUzxDBIBOQoP417LXzVehKlOVOe6dn8j6WhXjVhGpDZq6+YUUV8oftT/tN237O+j6aLC0j1LVdTlbZbyOUVYIx88jFQT94qqjvzz8prTB4OpiKio0ldszxmMp4em6tV2SPq+ivx5/4eaeMv+hWsv/AiT/4mvpb9mL9qz4g/tC+MLnSZPD1rY6Xp8Pm3V0kruVZ8iKNQQBucgnn+FW717OL4VxtCm6tWKSXmjxsJxVgq9RUqUm2/J/5H3hRXhXxx/aH8AfADTbO98a/aJZdR8wW0Fqgd5PK27+WZVUDevJbvxmvz58W/8FMvEcztH4E8M21so+7JfzPMT7lIvKx9N5+tc+X8O4zFR56UNO+yN8w4iweFk4VZ69t2fr3RX4Kal+3/APtH3zl7W+s7IHtDaRkD/v75hqjaft5/tLW0okm1i3uB/dks7cD/AMcRT+te2uAsba94/e/8jxHx7gr2tL7l/mfvzRX48+BP+Clni60uEg+I+g217bkgNLYM0EoHrskMiufYFB71+mnwo+M3w9+NOgnX/AV8LhY8CeBxsngY9FkjPI6HBGVODtJxXh5lw/i8IuatHTutUe5lvEGFxb5aMtez0f8AXoepUUUV4p7QUV8I/tSfthap8APG9l4N0bSINSa4slu5WllZNm+R0VQFB/uE/jXzP/w808Zf9CtZf+BEn/xNfR4ThTG16aq046PzR87i+KsFQqOlUnqvJ/5H7DUV86/s9/G69+LXwmk+KPjC1t9FgWedciQ+UIYAN0jO+MfNuB7ACvj74zf8FGbPTL6XQ/gtYR3wjJU6jehhEx9YoQVYj0Z2X/dI5PNhuH8VWrSoQjrHR9l8zpxPEGFo0Y15y0lt3fyP1Lor8BW/bz/aXa4M41mBVJz5Ys7faPblC361+23wj1jxJ4h+GGgeIfGBRtTv7GC5uPLXYoaZA+NvOMAgH3rXOOHK+Bip1mte3/DGOT8R0MdJwop6d/8Ahz0Sio5poreJp52CIgLMzHAAHJJJ6AV8IfFz9v8A+FPgO4l0fwTE/ia+j4LwOI7RT/13IYvj/YUqf71edgctr4mXJQjdnpY7MaGGjzV5JI+86K/C7xJ/wUP+PerzsdEXT9Jiz8qwweawHu0zOCfoo+lcvaft6ftLW0okm1i3uAP4ZLO3A/8AHEU/rX08OA8a1duK+b/yPmJceYFOyUn8v+CfvzRX5BeAP+ClniO3uI7b4naDBdQEgNPpzNFIo9fKlZ1c+29BX6bfDH4s+AvjB4fHiTwFfpeQAhZU+7LC5GdskZ+ZT6dj1BI5rw8zyDFYTWtHTutV/Xqe5luf4XFu1GWvbZ/16Ho9FFFeMewFFFFAH//X/v4ooooAKKKKACvyY/bg0X+z/i3baqg+W/0+JyfV43dD/wCOha/Wevzg/b6sFW68MaovV1u4m/4CYmX/ANCNefmcb0Wfmvi1hlUySpL+Vxf42/U8612X7f8AsS6Krf8ALlrLqPxac/8AtSqf7MReHwR8Srxf+WWhSc+/lzEfyqOWTP7F0StxjX8D3+Qmm/AdzpfwN+J2sPwslnb2yn3kEqEfjvFeZB2qQfl+jPyHDT/4UsLUfShf7qcv8j46vLH+1Fi0kHBvJoYB/wBtZFT+tfS3/BSbWfM+J+geFYeINP0oSqo6K08zqRj/AHYlr5vhvo7DxHocshwo1O1Zv91ZAx/lXsX/AAUSWQftAoX6HS7Yr9N8n9c1+peHGGsqUn1c2vuijr4KjyZLXkvtTj92p6b+ws0fgP4SfEb4yOAZbG28uEkfxW8LzFR/vM0Y/AV+bWl6fqHiTXLfSrXMt1fzpEm4klpJWCjJ68k1+iHwwm/sn/gnb43vYPvT6mUbH/TR7OI/oa+Wf2V9Hj1z9ojwjZSjITUI58H1twZh+qV+g4KryzxeJfR2/wDAY/8ABPrsdS5oYTDLqr/+BSP6IfCfhyw8H+F9O8KaUNttpttFbR8Y+WJAgP1OMn3roKKK/EZScm5M/bYxUUooKKKKkoKKKKACv5hPi74r/wCE5+KXiHxcrbk1DULiaM9f3ZkPlj8EwK/op+N/iv8A4Qf4QeJfFStsktNOnaI/9NWQrF+blRX8yNfpvh5htKlZ+S/V/ofmXiHidadFeb/RfqFfaFz+0xP4C/Z50f4JfC6Voby5ikm1fUEyrK1w7P5EJ6hghVXftjC85I+NIYZrmZLe3RpJJGCqqglmYnAAA5JJ6Coq/QMVgqdflVRXSd7eZ+f4XG1KHM6bs2rX8gr0b4W/Crxn8YfFkPg/wTame4k+aSRsiKGPPMkrfwqPzJ4AJIFec1/Rv+y74Q+Fnhn4QaXf/ClN9nqcKTzXMmDPNLjD+cw/iRty7R8qkED38jiTO3gaKnGN29F2Xqevw1kax1dwlKyWr7/In/Z+/Z18GfADw3/Z+iqLvVLlR9t1B1AklI52qOdkYP3UB9ySea+gqKK/EMTiqlabqVXds/b8NhqdGCp0lZIKKKKwNzzb4x+K/wDhBvhR4i8Wq2ySx0+4kiP/AE12ERj8XIFfzEV+8H/BQTxX/wAI/wDs+TaPG2H1q9t7TA67UJnb8P3QB+uO9fg/X65wBhuXDSqv7T/L+mfkfH+J5sTGkvsr8/8Ahkdr8NvC7eNviFofg9QSNTvre2bHZZJFVj+AJJr+olVVFCIAFAwAOABX4F/sGeFP+El/aM069dd0ej29xfOO3CeSh/B5VI9xX77V4XiBiubEQpLor/f/AMMe94f4blw86vd2+7/hz+bP4taN8QPHPxQ8QeLl0TUGTUNQuJoz9ml/1bSHyx93smBXkWreH9e0FkTXbK4smkBKCeNoywHXG4DOK/qpr8M/+CiXiz+3PjrF4dibMei6fDCy+ksxMzH8UdPyr3+G+KJYqqsMqdkl37fI+f4k4XhhaTxLqXbfbv8AM+C62dJ8O+INf8z+wrC4vfKxv8iJ5Nu7ON20HGcHGeuKxq/bX/gnD4T/ALI+Duo+KpVxJrGoMFPrFboEX/x8yV9Dn2bfUsO61rvRWPnshyn67iFRvZau5+Pf/Cu/iB/0AtQ/8BZf/ia/Xr/gnP8AD/VPC3gDXvEmuWktnc6lfJAEnRo3MVtHlWwwBwWlYfhX6K0V+Z5zxjPGUHQ5LX8/+AfpuTcHQwddV1O9r9O/zPz7/wCCj+ifb/gjp+roMtYatESfRJIpUP8A49tr8Q6/oZ/bU0T+3P2avEsajL2yQXK+3lTxsx/743V/PNX2HAdbmwTj2b/Rnx3HlHlxql3S/VH6Ef8ABNzU/svxt1PTXOFutHlwPVkmhYf+O7q/bivwE/YN1P7B+0to1tnAvILuE/hA8n80r9+6+Q47p8uOv3S/VH2HAlTmwNuzf6P9Qr8hf+Cjfxi+36vYfBfRpf3VjtvdQ2nrK6/uYz/uoS5HQ71PUV+o3xF8c6P8NPA2qeO9dOLbTIGmZc4LsOEjH+07kKvuRX8y3i/xTrHjfxRqHi/X5PNvNSne4lbtuc5wB2UdAOwAFdHAuVe1rvEzWkdvX/gL9Dn46zX2VBYaD1lv6f8ABf6nOUV7r4Q+Dt3rvwQ8W/GW9DLa6I9rbW3YSTzTxLIfcRxuMj1cHtXhVfq1LEQm5KL+F2frZP8AU/KKuHnBRcl8SuvS7X6H7x/8E+r/AO2fs629vnP2W/uovplhJ/7PX27X53/8E17/AM74M6xp5OTBrMjfQPbwY/VTX6IV+EcSQ5cdVXmfu/Dc+bA0n5EF1dW1lbSXt46xQwqXd2OFVVGSST0AHJr+bn9o34u3Pxr+LGpeMtzfYg32awRv4LWIkJwehckuw7Mxr9UP2/8A4z/8IL8NU+HOjy7dS8Shkl2nmOzX/Wn28w4jGeq7/Svw8r7ngPKeWDxc1q9F6dX8/wBD4bjzNuaawkHotX69Pu/Umt7ee7nS1tUaSWVgiIoyzMxwAAOSSegr+jT9mH4MQfBD4UWXhu4Rf7Uuv9K1Fxzm4kAyme6xrhB2OCe5r8y/2APgh/wnPj9/ihrsO7TPDrjyNw+WS9Iyn18kfOfRilft1XBx3nHNNYOD0Wr9eiO/gTJ+WDxk1q9F6dWfir/wUm8Sf2h8WdH8MxtlNO00SMPSS4lbI/75RDXxP4T+FfxK8dgP4N0G/wBTQnHmW9vI8Y+rgbR+Jr+iK++Avwo1fx7dfEvxBo8OpavciMeZdjzkjWJAiiOJsovTOdu7JJz6euxxxwxrFEoVVGAAMAAdABWOE40jhcNChQhdpat9+v8AWhti+C5YrFTr1p2Tey7dP61P55rT9iz9py9iEsPhaRQf+elzaxn8nmBrgvG37PHxt+HVo+o+L/Dd5a20Yy86qJokHq0kJdFHuSK/pZprKrqUcAqRgg8gilT8QcSpe/CLXzX6v8h1PD7DcvuTlf5f5L8z+UGvUvg58V/EfwY8e2Xjjw5I2YGC3EOcLPASPMiftgjof4Www5Fe2ftv/Dfw78NPjpPZ+FoVtbTVLSLUBBGMJE8jOjqgHRS0ZYAcDOBgYA+Qa/TMPVp4vDqbXuyW3qfmmIpVMJiHBP3ovdeR/VZoes6f4j0Sz8Q6S/mWt/BHcQv/AHo5VDqfxBFalfO37Jd5cX37OPhKa6JLLZeWM/3Y3ZF/8dUV9B3E8NrA91csEjjUszHoFAySfoK/n7F0PZ1pUl0bX3M/oDCV/aUY1X1Sf3o/n0/ba8TjxN+0hr5ibdFp/k2Se3kxLvH/AH8L18oV03jTxFN4v8Yar4ruM+Zqd5PdNnrmaRn/AK1zNf0Jl+H9jQhS7JI/nvMMR7avOr3bZ9K/Ef40X83wm8NfAnwtMYtH020S4vyh/wCPm7uGNwyse6QtJt2/3wSc4XHzVX0J+z9+zj42/aB157LQsWemWhH2u/lUmOPPRVUY3yEchQR6kgYr9cfBv7B37PHhexSLVtOm1u5A+ae8nkGT3xHEyIB6ZBI9e9eDjs/wWXfunrLdpb3et2e/gsgxuY/vVpHZN7WWlkfhb4P8PXHi7xbpfhS0z5up3cNqmOu6aRUH86/qGurrRvC2hPeXskdnYafCWd3O1I4ol5JJ6BVFeD6R+yV8AfD3imw8ZeHtBWx1DTZlnheKabbvXplGdkODz0zmviX/AIKH/Hi4a7i+BXhubbGipc6qynlmOGhgPsBiRh3ynoRXyOY4xZ1iaVGgmkr3v07n1uXYN5Lhqtau027Wt17HgH7U37XniH40ajP4U8ISyWHhaJtqxjKSXmP45u+zusfQcFstjb8T0V+k37DP7LmlePy3xb+IlqLjSraQx2FrIMx3EqHDySA8NGh+UL0Zs54XB+8q1MNlmFulaK+9v/M+DpQxOaYqzd5P7kv8j478Dfs+/Gj4k2q6h4M8OXl3bP8AdnKiKFv92WUojfgTXT+J/wBk39onwhp76rrfha68iMbna3aK5KgcklYHkIA7nHFf0aRxxxRrFEoVVAAAGAAOgAp9fBS8QsRz3jTVvnf7/wDgH30PD3D8lpVHf5W+7/gn8n9erfBr4veKfgp45tfGnhmQ/uyFubckhLiAn543HuOVOPlbBHSvpv8A4KB/DHRvAvxctvEegQrbweIbY3EsaDC/aY22ysAOBvBRj6sWPevg6v0fCYiljcMpte7Jbfmj84xeHq4LFOCfvRe/5H9T/hLxPpHjXwxYeLtBk82z1KBLiFu+2RQQCOcEZwR2ORXQ18L/APBPTxPca98AP7KuWLHR9RuLVM8kRsEnH4bpWA+lfdFfg+Z4P6viJ0ezP3jLMZ9Yw8K3dBRRRXAdx//Q/v4ooooAKKKKACvgT9vaJT4Z8PT91upl/wC+kU/0r77r4G/b1kA8L+H4e7XUx/JB/jXHmH8GR8N4lW/sPEX7L/0pHzprMn2X9jvSID1uvEEjj/dSKUH9QKd4ec6H+yDr91J8ra1rUNqnusSxy/zRvyrP+JMn9mfs4fD7RW+/dS6hdsPYS7VP4h6k+Jsh8Pfs7+A/CJ4lv3utUlHsXKxH8Uc/lXiN2u+0V+Nv8z8DrVPZzqTf2MPFfOcYq3/k7PhTx3ePFc2sULFXjzJkdjkYP6Gvrr9vl4/E2reCPiraj/R/EGhRlSOhKN5pH1AnANeY/Hr4Kan4S+Gvg/4qqpMGswPFc+iSmSSWA/8AbSE8f7h9a7WW5/4W/wDsUrbp+91b4cX4Ljq5sLokAj2DHHssVfvHDFKNLA4OtHZXT/7ev/7dY+s4cwM6OAnhKis5RU1/6V+Tf3HUfCGb+3P2B/iH4cT5pbLUI7oj0j3Wsg/WJjXhv7Gc8dv+0z4VkkOAZp1/FraVR+pr1P8AYev4PEM/jT4J3jhV8WaNKkG48efErqMeh2ys3/AK+ZPg3r7+AvjN4d13UMwjT9Ut/tAbgqglCyg+4XcK99UX/tdBddV/29G35pntOsv9kxD6aP8A7dlf8mj+mqiiivw8/bwooooAKKKKAPhX/goX4r/sH4BHQo2w+tX8FuV7mOPM7H6Bo1H41+FNfp//AMFMvFf2nxV4Z8ERtxaWs17IB3Nw4jTP0ELY+tfmBX7dwZhvZ4CL/mu/6+SPxLjPFe0x8l/LZfr+p9Lfsf8AhT/hL/2i/DNlIu6K0uDfOew+yo0qk/8AA1UfU1037Z/wR/4U/wDFia80iHy9F17fd2e0YWN8/voR/uMcgdkZRXuP/BNHwp9u8f8AiHxnIuV06xjtVJ7PdSbsj3CwkfQ+9foX+1B8GIfjd8Jr3w5bIDqlp/penOcZE8YOEz6SLlD2GQe1eTmXEP1fN1Fv3bJP563+V18j1st4e+sZQ5Je9dtfLS3zs/mfzj1+k3/BPj47/wDCMeKJfg14jmxY6w5lsGY8R3eOY+egmUcf7YAAyxr83p4Jrad7a5QxyRsVZWGCrA4IIPIINSWd5dafdxX9jI0M8DrJHIhIZHU5VgRyCCMg19hmmXwxdCVGfX8+jPj8rzGeErxrQ6fiuqP6t6K+e/2ZfjXa/HL4W2niWRlGqW2LbUYhgbbhAMuB2WQYdewyV6qa+hK/n7FYadGpKlUVmtD+gMNiYVqcatN3T1CiiisDc/In/gpp4r87XfC/geJsfZ4J76RfXzmEcZP08t8fWvy1r6z/AG3vFX/CU/tHa4sbbodNENjH7eVGC4/CVnr5Mr994cw3ssDSh5X+/X9T8C4kxPtcdVn52+7T9D9YP+CZXhT/AJGnxxMv/PvYwt/31LKP/RdfrBXxt+wb4U/4Rn9nTTrx12S6xcXF8478v5SH8UiUj2NfZNfkHE+J9rj6kuzt92h+v8MYb2WApx7q/wB+oV/M18efFn/CcfGbxN4oVt8dzqE4iPrFGxji/wDHFWv6Jvit4r/4Qb4Z6/4wDbX06wuJ4/eRIyUH1LYA+tfy/kknJ6mvrfDzDa1Kz8l+r/Q+S8Q8VpTorzf6L9RK/pP/AGafCf8AwhPwG8K6Ay7JFsI55F7iS5zO4PuGkIr+d3wF4Zl8aeONH8IQ53apewWvHbzZFQn8Ac1/UfDFFbxLBCoVEAVVHQAcACtfEPE+5Torzf6L82ZeHmG9+pWfkv1f5Ikooor8vP1A81+Mui/8JH8I/E+hAbmutKvI0H+2YW2n8Gwa/mJr+ryWKOeJoJhuRwVYHuDwRX8rXiDSpNB16+0Ob79lcSwNn1jYqf5V+n+Hlb3atP0f5n5h4h0fepVPVfke1fsqan/ZP7RPhG6zjfqCQ/8Af8GL/wBnr+j+v5ffhTqf9i/FHw3rOcfZNVs5s/7k6N/Sv6VvHfjLR/h74O1Lxtr7bbTTIHnk9W2jhF/2nbCqO5Irk4/oOWIpOK1at+P/AATr4ArqOHqqT0Tv+H/APzB/4KO/GLzrnT/gpo0vyw7b7Udp/iIPkRH6AmQj3Q9q/LnSdL1DXNUttF0mJp7q8lSCGNerySMFVR7kkCtrxx4w1j4geL9S8a6+++71Od55PQFjwq/7KjCqOwAr7l/4J5/B/wD4S34iXHxP1aLdY+Hhtt9w4e8lBA9j5aZY+jFDX2FGEMry/wB77K+9v/g/gfH1pzzXMfd+0/uS/wCB+J9o/FP4S6f8M/2ItW+HNgFZrDTklndf+Wk6ypNLJ68uDjPQYHavwfr+mX4+2H9pfA7xhZgZLaNfFR/tLA7L+oFfzNV5HAmJlUo1ZTerlf70evx3ho061JQWijb7mfr7/wAEyL/zPDPi3TM/6m6tZcf9dEkX/wBkr9OL+/s9LsZtT1GVYbe2jaWWRzhURAWZiewAGTX5Kf8ABMa/8vXPF+mZ/wBdBZy4/wCubTL/AOz17T/wUH+M/wDwh3w/h+FujS7dQ8RAtcbTylmh+b/v642e6hxXy+eZZLEZxKhD7Vvusrs+oyPMo4fJ415/Zv8Afd2R+WXx/wDixefGj4qan44nLC2kfybONv8AlnbR5Ea47EjLN/tMa808N+HtX8W+ILLwxoEJnvdQmSCGMfxO52j6Dnk9hzWJX6q/8E6/gh59zc/HHX4fki32mlhh1YjbPMPoP3an3fuBX6VmOMp5fhHJLSKsl+R+a5dg6mYYxRb1k7t/mfo98HfhjpHwf+HOmeAdHwws4/30oGDNO/zSyHv8zE4B6LgdBXptFfk7+2L+2XrWn61d/CX4R3RtfsrGHUNRiOJPMHDQwMPu7Dw7j5t2QpAGW/GMvy+vmGIcY6t6t/qftGYZhh8vw6lLRLRJfkfffxI/aF+DnwmZrfxvrkFvdKM/ZY8zXHPTMUYZlz2LAD3r5C8Sf8FLPhrZSNH4W0DUNQ28Bp3jtlP0wZWx9QD7V+M800txK087F5HJZmY5JJ5JJPJJrqvB/gLxr8QdR/snwTpVzqlwMFlto2faD3cgYUe7ECv0fDcDYKlHmrty762X9fM/N8TxzjasuWglHtpd/wBfI/Rq+/4KceIJGJ03wjbxDsJbx5P5RJWOf+CmPj/Py+GtPx/11lryDRP2BP2j9WiWW70+007d2ubqMkfUReZj+ddV/wAO4vjzt3NfaKPrcTf/ACPSeEyGOl4/e3+pSxefS1tL7kv0Pmz47/GrW/jz43XxtrtpFZSx20dqsUJYqEjLNnLc5Jc14vVi7gFrdSWwkWURuy70JKtg4ypIBweoyK2fCWgzeKvFemeGLbPmaldw2q467pnVB+pr7OlSp0aajBWij4yrVqVqjlN3k2f0hfALQm8N/BLwpo0g2yRaVamQejvGruP++iay/wBpbxT/AMIb8BPFWuq2xxp8kEbeklziBCPcM4xXtdvbw2lulrbqEjjUIqjoABgD8q+Av+Cjfir+yPgrZeGomxJq+oxqy+sUCtI35P5dfhGWU3icfC/2pX/G7P3fM6iw2Anb7MbL7rI/EKtnw7oOp+KtfsvDOix+beahPHbQp6ySsFUfmaxq+3f2APBUfin4/Q6xdJvh0K0mvOenmHEMf4gyFh7rmv3HMsYsPh51n0Vz8Ny3BvEYiFFdXY/Zr4R/DLQfhB8P9O8B+H1Hl2cY82XGGmmbmSVvdm/IYA4Ar0miiv54q1ZVJOc3ds/oelSjCKhBWSMzWtWstA0a713UW229lDJPK3okalmP5Cv5evG3izU/Hfi/U/GWsNuudTuZLl+c4MjE7R7KOB6ACv6E/wBq/VpdF/Z08W3kJwz2LQfhOywn9HNfziV+neHuGSp1K3W9v1/U/MfELEt1KdHpa/6foFfrd4G/4KAfCDwB4O0zwVonhzU1tdMt47dOYAW2DBY/P95jlmPck1+S0ME9zIIrdGkY9lBJ/IVd/sbWP+fSb/vhv8K+xzTKcPi0o19l52PjsrzbEYRuVDd+Vz9h/wDh5f8ADX/oXtT/AO+of/iqP+Hl/wANf+he1P8A76h/+Kr8eP7G1j/n0m/74b/Cj+xtY/59Jv8Avhv8K8b/AFMy7t+LPZ/1zzHv+CPqj9rT9o3Qv2htZ0a+0CwuLCHS4ZY2W4KFmaVlORsJGMKK+Ra0v7G1j/n0m/74b/Cj+xtY/wCfSb/vhv8ACvosFhqWHpKjS2R87jcTVxFV1qu7P2X/AOCakDr8INbuT919YdR9Vt4Sf/QhX6L18ZfsFeGbjw7+zrY3F1GYpNTu7q7KsMN9/wAkZB9RECPbFfZtfhvEdVTx1Vrv+Wh+5cOUnDA0k+356hRRRXintH//0f7+KKKKACiiigAr86P2+r7jwvpqn/n7lYf9+Qv9a/RevzL/AGvYZPGHx08NeBLckmWCCHjs9zcMp/8AHQprhzJ/uml1PzzxSm/7GnSjvNxS/wDAk/0PHPj5BOk3gn4f2alprHQ7NGQdftFySzLj3+X86vfH6wk8RfGTSvhXoJ3jSbWw0SHb93eAMnHsXwfpXUQS2Hjz9ri9166IXS9BuJLqVhyqW+lIFU4/ulo1/Orn7K+i3fxN+POo/EnVU3JZNNfPnkefcswjX8AXYf7oryeTmlyrq/wR+LPBfXMTLC0/+XtVRX+CmrN/c0/+3T9AvH3wj8MeP/hXcfCfUV2WL2qW8LgAtC0QHkyL7oVBx36Hgmvw6+Herav+zD8bL7wb8TbUtpl0kmlazb8lJrOcY81P7wwRIh6lcjjJr+hivlH9qT9mPRfj/wCHFu7ApZ+I7BCLO6bhXXr5M2OShPQ8lCcjILA/p3DWdQoc2GxH8OX4Pv8A16n9AcRZHKrGNfCr34bea7f16H43Xttrv7MPx5tdR0+UXS6Tcx3lnOh+S8sZRlGVhwVmhYq2MgEsM8Vt/tYeD9M0X4nHxt4WIk0HxhCusWEijjFx80yHsGWTOV/hBAqlrMGsrpx+BvxghbS9a0FmXSbq5woiDnLWkzng28p+aGXJWNjnPlsxXR8D6ovjbwVcfs5eOWFnqFncPceH57j5PIvTxLZSFvux3PRc4Cy4JyDx+oJyjKOIerSs/OPSS9N/K78r/mTUXGWHWibuvKXWL9dvkvO37W/s2/EqP4r/AAY0PxY0nmXfkC2vOeRcwfJIT6biN49mFe51+Iv7C3xql+FHxGuvhR40LWljrU3lATfJ9mv0OwBgfu+Zjy2zzuCZ4Br9uq/JOJMreFxUor4XqvT/AIB+t8OZosVhYyfxLR+q/wA9wooorwD3gooqpqF9baXYT6netsht42lkb0VAWJ/ACmlfRCbtqz+fL9tLxWPFn7R3iGSJt0OnvHYx+32eNVkH/f3fXyvW54m1258UeJNQ8S3v+u1G5lupP96Zy5/U1h1/RuBw3saEKXZJH8547E+2rzq922fuJ/wTo8Kf2L8ELnxJKuJNZ1CWRW9YoFWJR+DiT86+/K8a/Z48Kf8ACE/A/wALeHGXZJFp8Mkq+ksw82Qf99u1ey1+CZ1ifbYupU7t/d0P3rJcN7HCU6fZL/gn4e/t+fBH/hAviIvxJ0OHbpfiNmaXaPljvQMyD280fvB6tv7CvgGv6avjZ8LNL+Mvw01PwFqW1Guo91vKRnyrhOYpPXAbhsdVJHev5qtd0TVPDWtXfh7W4Wt7yxmeCeNuqSRsVYH6EV+q8G5x9Yw3spv3oafLp/kflXGWT/VsT7WC92evz6/5n0j+yN8c3+CPxShudTlK6Jq2211AH7qKT+7mx6xMcn/YLAcmv6GEdJUEkZDKwyCOQQe4r+UGv3D/AGCfjv8A8LC8BH4a+IZt2r+HY1WIsctNZfdQ+5iOIz7bO5NeRx1kvNFYymtVo/0f6Hr8C51yyeDqPR6r9V+p9+1BdXMFlbSXl0wSKJS7segVRkn8BU9eC/tQeK/+EM+AHirW1bY5sXtoz3D3RECke4Mmfwr81wtB1asaa6tL7z9KxVdUqUqj6Jv7j+d3xl4in8X+LtV8V3WfM1O7numz1zNIzn+dc6iNIwRAWZjgAckk02vZP2evCn/CbfG/wv4bZd8c2owvKvrFC3myD/vhGr+iqs40aTl0ivyP51pQlWqqPWT/ADP6J/hv4XXwT8PtD8HqADpljb2zY7tFGqsfxIJNdrRRX841KjnJyluz+jqcFGKjHZHx1+3hrz6L+zdq1tGdrajPa2oPfBlWRh+KxkfSvwEr9zf+Ci1vcTfAGCSEZWHVrZ5PZTHMv/oTCvwyr9h4DglgW11b/Q/HuPJt45J9Ir9T66/Ya8OReIf2kdFe4G6PT0uLwj3SJlT8nZT+Ff0DV/OB+zF8XLD4KfF/T/GmsxtJp5WS2uhGMusUoxuUdyrBWx3AIHJr9w4v2pP2eZtPXU08X6cI3G4BpdsmPeMgOD7Fc187xzgsRUxUZxi3G1tFfqz6LgbG4enhZQlJJ3vq7dEe+UV5z8Nfiv4H+LumXWt/D+6a+srS4Nq8/lvGjSqquwXzFUnAYZOMc8V6NXwNWlKEnCas0ffUqsZxU4O6YV/N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";
-
-OfflineLocalView.load(container, { base64Str });
-</script>
-  </body>
-</html>
diff --git a/docs/examples/index.md b/docs/examples/index.md
index 2ac5c50..4b7e923 100644
--- a/docs/examples/index.md
+++ b/docs/examples/index.md
@@ -7,36 +7,176 @@ Palace configuration, simulation, and post-processing.
 
 ## Antennas
 
-| Example | Description |
-|:--------|:------------|
-| [Horn Antenna](horn_antenna.ipynb) | WR-90 rectangular waveguide transition to a horn antenna with waveport boundaries. |
-| [Dipole Antenna Mesh](dipole_antenna_mesh.ipynb) | Half-wave dipole geometry and mesh generation workflow. |
-| [Monopole Antenna](monopole_antenna.ipynb) | Quarter-wave monopole example with meshing and Palace setup. |
-| [L Antenna](l_antenna.ipynb) | Bent-wire L-shaped antenna workflow including geometry and driven simulation setup. |
-| [Patch Antenna](patch_antenna.ipynb) | Rectangular patch antenna model with substrate, feed, and boundary setup. |
-| [Vivaldi Antenna](vivaldi_antenna.ipynb) | Tapered-slot (Vivaldi) antenna geometry and simulation example. |
+<div class="ptk-gallery-grid">
+	<a class="ptk-gallery-link" href="horn_antenna.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Horn Antenna preview">
+			<h3>Horn Antenna</h3>
+			<p>WR-90 rectangular waveguide transition to a horn antenna with waveport boundaries.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="dipole_antenna_mesh.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Dipole Antenna Mesh preview">
+			<h3>Dipole Antenna Mesh</h3>
+			<p>Half-wave dipole geometry and mesh generation workflow.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="monopole_antenna.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Monopole Antenna preview">
+			<h3>Monopole Antenna</h3>
+			<p>Quarter-wave monopole example with meshing and Palace setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="l_antenna.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="L Antenna preview">
+			<h3>L Antenna</h3>
+			<p>Bent-wire L-shaped antenna workflow including geometry and driven simulation setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="patch_antenna.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Patch Antenna preview">
+			<h3>Patch Antenna</h3>
+			<p>Rectangular patch antenna model with substrate, feed, and boundary setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="vivaldi_antenna.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Vivaldi Antenna preview">
+			<h3>Vivaldi Antenna</h3>
+			<p>Tapered-slot (Vivaldi) antenna geometry and simulation example.</p>
+		</article>
+	</a>
+</div>
 
 ## Planar Microwave Circuits
 
-| Example | Description |
-|:--------|:------------|
-| [Coax](coax.ipynb) | Coaxial line baseline example for geometry, mesh, and configuration setup. |
-| [Coax to Waveguide Transition](coax_to_waveguide.ipynb) | Driven coax-to-waveguide transition example including geometry, mesh, and setup. |
-| [Open-ended Stub](open_ended_stub.ipynb) | Open-ended microstrip stub component with geometry and simulation setup. |
-| [Step in Width](step_in_width.ipynb) | Microstrip step-discontinuity example for meshing and EM analysis. |
+<div class="ptk-gallery-grid">
+	<a class="ptk-gallery-link" href="coax.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Coax preview">
+			<h3>Coax</h3>
+			<p>Coaxial line baseline example for geometry, mesh, and configuration setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="coax_to_waveguide.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Coax to Waveguide Transition preview">
+			<h3>Coax to Waveguide Transition</h3>
+			<p>Driven coax-to-waveguide transition example including geometry, mesh, and setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="open_ended_stub.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Open-ended Stub preview">
+			<h3>Open-ended Stub</h3>
+			<p>Open-ended microstrip stub component with geometry and simulation setup.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="step_in_width.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Step in Width preview">
+			<h3>Step in Width</h3>
+			<p>Microstrip step-discontinuity example for meshing and EM analysis.</p>
+		</article>
+	</a>
+</div>
 
 ## Waveguide Structures
 
-| Example | Description |
-|:--------|:------------|
-| [Waveguide Box](waveguide_box.ipynb) | Closed waveguide cavity/box example including full 3D setup and analysis. |
+<div class="ptk-gallery-grid">
+	<a class="ptk-gallery-link" href="waveguide_box.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Waveguide Box preview">
+			<h3>Waveguide Box</h3>
+			<p>Closed waveguide cavity/box example including full 3D setup and analysis.</p>
+		</article>
+	</a>
+</div>
 
 ## Waveguide Mode Solver
 
-| Example | Description |
-|:--------|:------------|
-| [Hollow Rectangular Waveguide Modes](hollow_waveguide_modes.ipynb) | PEC waveguide eigenmodes compared with analytic TE/TM propagation constants. |
-| [Dielectric Waveguide Modes](dielectric_waveguide_modes.ipynb) | Rectangular dielectric core in cladding with guided-mode classification and field plots. |
-| [Microstrip Modes](microstrip_modes.ipynb) | Boxed 2D microstrip cross-section with PEC strip and outer conductor boundaries for hybrid mode analysis. |
-| [Slotline Modes](slotline_modes.ipynb) | Boxed 2D slotline cross-section with two PEC slot conductors and open outer boundaries. |
-| [Differential Microstrip Modes](differential_microstrip_modes.ipynb) | Boxed 2D differential microstrip with ground plane and two PEC strips for coupled-mode analysis. |
+<div class="ptk-gallery-grid">
+	<a class="ptk-gallery-link" href="hollow_waveguide_modes.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Hollow Rectangular Waveguide Modes preview">
+			<h3>Hollow Rectangular Waveguide Modes</h3>
+			<p>PEC waveguide eigenmodes compared with analytic TE/TM propagation constants.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="dielectric_waveguide_modes.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Dielectric Waveguide Modes preview">
+			<h3>Dielectric Waveguide Modes</h3>
+			<p>Rectangular dielectric core in cladding with guided-mode classification and field plots.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="microstrip_modes.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Microstrip Modes preview">
+			<h3>Microstrip Modes</h3>
+			<p>Boxed 2D microstrip cross-section with PEC strip and outer conductor boundaries for hybrid mode analysis.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="slotline_modes.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Slotline Modes preview">
+			<h3>Slotline Modes</h3>
+			<p>Boxed 2D slotline cross-section with two PEC slot conductors and open outer boundaries.</p>
+		</article>
+	</a>
+	<a class="ptk-gallery-link" href="differential_microstrip_modes.html">
+		<article class="ptk-gallery-card">
+			<img src="../_static/patch.png" alt="Differential Microstrip Modes preview">
+			<h3>Differential Microstrip Modes</h3>
+			<p>Boxed 2D differential microstrip with ground plane and two PEC strips for coupled-mode analysis.</p>
+		</article>
+	</a>
+</div>
+
+```{toctree}
+:caption: Antennas
+:maxdepth: 1
+:hidden:
+
+horn_antenna
+dipole_antenna_mesh
+monopole_antenna
+l_antenna
+patch_antenna
+vivaldi_antenna
+```
+
+```{toctree}
+:caption: Planar Microwave Circuits
+:maxdepth: 1
+:hidden:
+
+coax
+coax_to_waveguide
+open_ended_stub
+step_in_width
+```
+
+```{toctree}
+:caption: Waveguide Structures
+:maxdepth: 1
+:hidden:
+
+waveguide_box
+```
+
+```{toctree}
+:caption: Waveguide Mode Solver
+:maxdepth: 1
+:hidden:
+
+hollow_waveguide_modes
+dielectric_waveguide_modes
+microstrip_modes
+slotline_modes
+differential_microstrip_modes
+```
diff --git a/docs/examples/microstrip_modes.ipynb b/docs/examples/microstrip_modes.ipynb
index 3db4015..bc4bf62 100644
--- a/docs/examples/microstrip_modes.ipynb
+++ b/docs/examples/microstrip_modes.ipynb
@@ -14,7 +14,7 @@
     "tags": []
    },
    "source": [
-    "# Microstrip Modes (2D Cross-Section)\n",
+    "# Microstrip Modes\n",
     "\n",
     "This notebook builds a simple boxed microstrip cross-section (substrate + air + PEC strip conductor), solves eigenmodes with `WaveguideModeSolver`, and plots the first fields."
    ]
diff --git a/docs/examples/slotline_modes.ipynb b/docs/examples/slotline_modes.ipynb
index 240f261..108158f 100644
--- a/docs/examples/slotline_modes.ipynb
+++ b/docs/examples/slotline_modes.ipynb
@@ -14,7 +14,7 @@
     "tags": []
    },
    "source": [
-    "# Slotline Modes (2D Cross-Section)\n",
+    "# Slotline Modes\n",
     "\n",
     "This notebook builds a boxed slotline cross-section (substrate + air + two PEC slot conductors), solves eigenmodes with `WaveguideModeSolver`, and plots mode fields."
    ]
diff --git a/docs/full-course.md b/docs/full-course.md
index 4278153..7a41248 100644
--- a/docs/full-course.md
+++ b/docs/full-course.md
@@ -37,7 +37,7 @@ design workflows.
 ---
 
 <div style="text-align: center; margin: 2em 0;">
-<a href="https://www.epsilonforge.com/#course" class="md-button md-button--primary" style="font-size: 1.2em; padding: 0.8em 2em;">
+<a href="https://www.epsilonforge.com/#course" class="ptk-cta-button" style="font-size: 1.2em; padding: 0.8em 2em;">
     Get the Full Course →
 </a>
 </div>
diff --git a/docs/getting-started/geometry-and-meshing.md b/docs/getting-started/geometry-and-meshing.md
index 2001f77..b3d820e 100644
--- a/docs/getting-started/geometry-and-meshing.md
+++ b/docs/getting-started/geometry-and-meshing.md
@@ -45,9 +45,10 @@ The pipeline:
 5. **Assigns physical groups** — volumes get their entity name; surfaces
    at material interfaces are auto-labelled (e.g. `"conductor__dielectric"`).
 
-!!! tip
-    The `mesh_order` controls which material wins at overlapping regions.
-    Think of it as a z-index: small number = highest priority = never cut.
+```{tip}
+The `mesh_order` controls which material wins at overlapping regions.
+Think of it as a z-index: small number = highest priority = never cut.
+```
 
 ## Mesh generation
 
diff --git a/docs/getting-started/index.md b/docs/getting-started/index.md
index 5c36630..6c866ee 100644
--- a/docs/getting-started/index.md
+++ b/docs/getting-started/index.md
@@ -73,3 +73,11 @@ python -c "from palacetoolkit.simulation import set_palace_path; set_palace_path
 
 See the dedicated Ubuntu build guide and compatibility policy for details.
 
+```{toctree}
+:maxdepth: 1
+
+geometry-and-meshing
+simulation-setup
+post-processing
+```
+
diff --git a/docs/getting-started/simulation-setup.md b/docs/getting-started/simulation-setup.md
index 60bc70d..d718c78 100644
--- a/docs/getting-started/simulation-setup.md
+++ b/docs/getting-started/simulation-setup.md
@@ -76,8 +76,8 @@ A typical Palace JSON config has these top-level keys:
 {
   "Problem": { "Type": "Driven" },
   "Model": { "Mesh": "model.msh", "L0": 1e-3 },
-  "Domains": { "Materials": [...] },
-  "Boundaries": { "PEC": {...}, "LumpedPort": [...], "Absorbing": {...} },
+  "Domains": { "Materials": [] },
+  "Boundaries": { "PEC": {}, "LumpedPort": [], "Absorbing": {} },
   "Solver": { "Driven": { "MinFreq": 1.0, "MaxFreq": 10.0, "FreqStep": 0.5 } }
 }
 ```
diff --git a/docs/index.md b/docs/index.md
index 958a940..be197d5 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,12 +1,12 @@
 <div style="text-align: center; margin-bottom: 1em;">
-  <img src="PalaceToolkit.png" alt="PalaceToolkit" style="max-width: 320px;">
+  <img src="_static/PalaceToolkit.png" alt="PalaceToolkit" style="max-width: 320px;">
 </div>
 
 # PalaceToolkit
 
-A lightweight Python package that integrates
+PalaceToolkit is a lightweight Python package that integrates
 [Palace](https://awslabs.github.io/palace/) and
-[Gmsh](https://gmsh.info/) into a unified simulation workflow.
+[Gmsh](https://gmsh.info/) into a unified open-source electromagnetic FEM simulation workflow.
 
 ---
 
@@ -33,3 +33,12 @@ electromagnetic solving.  In a single Python script you can:
 | [Full Course](full-course.md) | Structured video lectures |
 | [Palace docs](https://awslabs.github.io/palace/) | Upstream Palace reference |
 | [Gmsh docs](https://gmsh.info/doc/texinfo/gmsh.html) | Upstream Gmsh reference |
+
+```{toctree}
+:maxdepth: 2
+:hidden:
+
+getting-started/index
+examples/index
+full-course
+```
diff --git a/docs/javascripts/mathjax.js b/docs/javascripts/mathjax.js
index 68dbff0..dc16d4e 100644
--- a/docs/javascripts/mathjax.js
+++ b/docs/javascripts/mathjax.js
@@ -1,16 +1,3 @@
-window.MathJax = {
-  tex: {
-    inlineMath: [["$", "$"], ["\\(", "\\)"]],
-    displayMath: [["$$", "$$"], ["\\[", "\\]"]],
-    processEscapes: true,
-    processEnvironments: true,
-  },
-  options: {
-    ignoreHtmlClass: "tex2jax_ignore|mathjax_ignore",
-    processHtmlClass: "arithmatex|jp-RenderedHTMLCommon|jp-RenderedMarkdown",
-  },
-};
-
 (() => {
   const mathTargetSelector = [
     ".arithmatex",
@@ -31,21 +18,16 @@ window.MathJax = {
     });
   };
 
-  // Run once after all scripts are loaded.
-  window.addEventListener("load", typesetMath);
-
-  // Re-typeset after Material for MkDocs instant navigation updates the DOM.
-  const subscribeToInstantNavigation = () => {
-    if (typeof document$ !== "undefined" && document$.subscribe) {
-      document$.subscribe(() => {
-        window.requestAnimationFrame(typesetMath);
-      });
-    }
-  };
-
-  if (document.readyState === "complete") {
-    subscribeToInstantNavigation();
+  if (document.readyState === "complete" || document.readyState === "interactive") {
+    window.requestAnimationFrame(typesetMath);
   } else {
-    window.addEventListener("load", subscribeToInstantNavigation);
+    window.addEventListener("DOMContentLoaded", () => {
+      window.requestAnimationFrame(typesetMath);
+    });
   }
+
+  // Some browsers restore page state from bfcache on history navigation.
+  window.addEventListener("pageshow", () => {
+    window.requestAnimationFrame(typesetMath);
+  });
 })();
diff --git a/docs/stylesheets/interactive.css b/docs/stylesheets/interactive.css
index 34e412d..1291701 100644
--- a/docs/stylesheets/interactive.css
+++ b/docs/stylesheets/interactive.css
@@ -1,3 +1,11 @@
+/* Theme variable bridge: Material (old) + PyData (new). */
+:root {
+  --ptk-border-color: var(--pst-color-border, var(--md-default-fg-color--lightest, #d1d5db));
+  --ptk-muted-text-color: var(--pst-color-text-muted, var(--md-default-fg-color--light, #6b7280));
+  --ptk-text-color: var(--pst-color-text-base, var(--md-default-fg-color, #1f2937));
+  --ptk-code-bg: var(--pst-color-surface, var(--md-code-bg-color, #fafafa));
+}
+
 /* Side-by-side interactive 3D viewer iframes */
 .mesh-viewer-row {
   display: flex;
@@ -10,7 +18,7 @@
   flex: 1 1 48%;
   min-width: 300px;
   height: 450px;
-  border: 1px solid var(--md-default-fg-color--lightest);
+  border: 1px solid var(--ptk-border-color);
   border-radius: 8px;
 }
 
@@ -18,7 +26,7 @@
   width: 100%;
   text-align: center;
   font-style: italic;
-  color: var(--md-default-fg-color--light);
+  color: var(--ptk-muted-text-color);
   margin-top: 0.25rem;
 }
 
@@ -37,25 +45,35 @@
   max-height: calc(var(--ptk-output-visible-lines, 10) * var(--ptk-output-line-height, 1.35) * 1em);
   overflow: auto;
   padding: 0.75rem;
-  border: 1px solid var(--md-default-fg-color--lightest);
+  border: 1px solid var(--ptk-border-color);
   border-radius: 8px;
-  background: var(--md-code-bg-color, #fafafa);
+  background: var(--ptk-code-bg);
   line-height: var(--ptk-output-line-height, 1.35);
   white-space: pre;
 }
 
-/* mkdocs-jupyter text outputs: clamp to ~10 lines and scroll vertically. */
-.jupyter-wrapper .jp-OutputArea .jp-RenderedText.jp-OutputArea-output > pre {
+/* Notebook text outputs: clamp to ~10 lines and scroll vertically. */
+.jupyter-wrapper .jp-OutputArea .jp-RenderedText.jp-OutputArea-output > pre,
+.nboutput .output_area .output pre,
+.nboutput .output_area pre,
+.cell_output .output.stream pre,
+.cell_output .output.stderr pre,
+.cell_output .output.text_plain pre,
+.cell-output .output.stream pre,
+.cell-output .output.stderr pre,
+.cell-output .output.text_plain pre,
+.cell_output pre[id^="codecell"],
+.cell-output pre[id^="codecell"] {
   max-height: calc(var(--ptk-notebook-output-lines, 10) * 1.35em) !important;
   overflow-y: auto !important;
   overflow-x: auto;
   display: block;
   line-height: 1.35;
   box-sizing: border-box;
-  border: 1px solid var(--md-default-fg-color--lightest);
+  border: 1px solid var(--ptk-border-color);
   border-radius: 6px;
   background: #ffffff !important;
-  color: var(--md-default-fg-color, #1f2937) !important;
+  color: var(--ptk-text-color) !important;
   padding: 0.75rem;
   margin: 0;
   white-space: pre;
@@ -63,10 +81,111 @@
 
 /* Keep HTML/interactive outputs full-size with no clipping by default. */
 .jupyter-wrapper .jp-OutputArea .jp-RenderedHTMLCommon.jp-OutputArea-output,
-.jupyter-wrapper .jp-OutputArea .jp-RenderedHTMLCommon.jp-OutputArea-output * {
+.jupyter-wrapper .jp-OutputArea .jp-RenderedHTMLCommon.jp-OutputArea-output *,
+.nboutput .output_area .output_html,
+.nboutput .output_area .output_html *,
+.cell_output .output.text_html,
+.cell_output .output.text_html *,
+.cell-output .output.text_html,
+.cell-output .output.text_html * {
   max-height: none !important;
 }
 
-.jupyter-wrapper .jp-OutputArea .jp-RenderedHTMLCommon.jp-OutputArea-output {
+.jupyter-wrapper .jp-OutputArea .jp-RenderedHTMLCommon.jp-OutputArea-output,
+.nboutput .output_area .output_html,
+.cell_output .output.text_html,
+.cell-output .output.text_html {
   overflow: visible !important;
 }
+
+.ptk-cta-button {
+  display: inline-block;
+  border-radius: 999px;
+  border: 1px solid var(--ptk-text-color);
+  color: var(--ptk-text-color);
+  text-decoration: none;
+  font-weight: 600;
+}
+
+.ptk-cta-button:hover {
+  text-decoration: none;
+  opacity: 0.9;
+}
+
+.ptk-gallery-card {
+  height: 100%;
+  border: 1px solid var(--ptk-border-color);
+  border-radius: 10px;
+  background: #ffffff;
+  overflow: hidden;
+  transition: transform 0.16s ease, box-shadow 0.16s ease;
+}
+
+.ptk-gallery-link {
+  text-decoration: none;
+  color: inherit;
+}
+
+.ptk-gallery-link:hover {
+  text-decoration: none;
+}
+
+.ptk-gallery-link:hover .ptk-gallery-card {
+  transform: translateY(-2px);
+  box-shadow: 0 8px 20px rgba(0, 0, 0, 0.08);
+}
+
+.ptk-gallery-grid {
+  display: grid;
+  grid-template-columns: repeat(3, minmax(0, 1fr));
+  gap: 1rem;
+  margin: 0.5rem 0 1.5rem;
+}
+
+@media (max-width: 1100px) {
+  .ptk-gallery-grid {
+    grid-template-columns: repeat(2, minmax(0, 1fr));
+  }
+}
+
+@media (max-width: 700px) {
+  .ptk-gallery-grid {
+    grid-template-columns: 1fr;
+  }
+}
+
+.ptk-gallery-card .sd-card-img-top {
+  height: 140px;
+  object-fit: contain;
+  padding: 0.75rem;
+  background: var(--ptk-code-bg);
+  border-bottom: 1px solid var(--ptk-border-color);
+}
+
+.ptk-gallery-card .sd-card-title {
+  min-height: 2.6em;
+}
+
+.ptk-gallery-card img {
+  display: block;
+  width: 100%;
+  height: 96px;
+  object-fit: contain;
+  padding: 0.5rem;
+  background: var(--ptk-code-bg);
+  border-bottom: 1px solid var(--ptk-border-color);
+}
+
+.ptk-gallery-card h3 {
+  margin: 0;
+  padding: 0.6rem 0.7rem 0.25rem;
+  font-size: 0.95rem;
+}
+
+.ptk-gallery-card p {
+  margin: 0;
+  padding: 0 0.7rem 0.7rem;
+  color: var(--ptk-muted-text-color);
+  font-size: 0.88rem;
+  line-height: 1.4;
+}
diff --git a/docs/stylesheets/patch.png b/docs/stylesheets/patch.png
new file mode 100644
index 0000000..1800160
Binary files /dev/null and b/docs/stylesheets/patch.png differ
diff --git a/justfile b/justfile
index 5d8d817..b2f4379 100644
--- a/justfile
+++ b/justfile
@@ -14,13 +14,20 @@ nbrun: ipykernel
         {{python}} -m papermill "$nb" "$nb" -k palacetoolkit --cwd {{examples}}; \
     done
 
-# Step 2: Build MkDocs site (renders notebooks directly via mkdocs-jupyter)
+# Step 2: Build Sphinx site (renders notebooks via myst-nb)
 nbdocs:
-    @echo "Notebook conversion is not required; MkDocs renders .ipynb directly."
+    @echo "Notebook conversion is not required; Sphinx renders .ipynb directly."
 
-# Step 3: Build MkDocs site
+# Step 3: Build Sphinx site
 docs:
-    {{python}} -m mkdocs build
+    rm -rf site
+    {{python}} -m sphinx -W --keep-going -b html docs site
+
+# Alias used by contributors coming from MkDocs-style workflows
+build: docs
+
+# Explicit docs build alias for CI/local parity
+docs-build: docs
 
 # All three steps in sequence
 docs-full: nbrun nbdocs docs
@@ -36,7 +43,15 @@ install-local:
 
 # Dev server
 serve:
-    {{python}} -m mkdocs serve -a localhost:8080
+    {{python}} -m sphinx_autobuild docs site --host localhost --port 8080 \
+        --ignore "site/*" \
+        --ignore "jupyter_execute/*" \
+        --ignore ".jupyter_cache/*" \
+        --re-ignore "docs/examples/postpro/.*" \
+        --re-ignore "docs/examples/.*\\.(msh|json|config|conf)$"
+
+# Explicit docs serve alias
+docs-serve: serve
 
 # Strip outputs from notebooks before committing
 nbclean:
diff --git a/mkdocs.yml b/mkdocs.yml
deleted file mode 100644
index df87776..0000000
--- a/mkdocs.yml
+++ /dev/null
@@ -1,79 +0,0 @@
-site_name: PalaceToolkit
-site_description: Electromagnetic simulation with Palace and Gmsh.
-site_url: https://www.epsilonforge.com/palace-toolkit/
-
-theme:
-  name: material
-  logo: PalaceToolkit.png
-  favicon: PalaceToolkit.png
-  features:
-    - content.code.copy
-    - navigation.instant
-    - navigation.tabs
-    - navigation.top
-  palette:
-    - scheme: default
-      primary: indigo
-      accent: deep orange
-
-markdown_extensions:
-  - admonition
-  - pymdownx.superfences
-  - pymdownx.highlight:
-      anchor_linenums: true
-  - pymdownx.arithmatex:
-      generic: true
-  - attr_list
-  - md_in_html
-  - tables
-  - toc:
-      permalink: true
-
-plugins:
-  - search
-  - mkdocs-jupyter:
-      execute: false
-      include_source: true
-      ignore_h1_titles: true
-
-# Prevent MkDocs from warning about .htm viewer files not in nav
-not_in_nav: |
-  examples/img/**
-
-extra_javascript:
-  - https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.6/require.min.js
-  - javascripts/mathjax.js
-  - https://unpkg.com/mathjax@3/es5/tex-mml-chtml.js
-
-extra_css:
-  - stylesheets/interactive.css
-
-nav:
-  - Home: index.md
-  - Getting Started:
-      - getting-started/index.md
-      - Geometry & Meshing: getting-started/geometry-and-meshing.md
-      - Simulation Setup: getting-started/simulation-setup.md
-      - Post-processing: getting-started/post-processing.md
-  - Examples:
-      - Overview: examples/index.md
-      - Antennas:
-        - Horn Antenna: examples/horn_antenna.ipynb
-        - Dipole Antenna Mesh: examples/dipole_antenna_mesh.ipynb
-        - Monopole Antenna: examples/monopole_antenna.ipynb
-        - L Antenna: examples/l_antenna.ipynb
-        - Patch Antenna: examples/patch_antenna.ipynb
-        - Vivaldi Antenna: examples/vivaldi_antenna.ipynb
-      - Structures and Components:
-        - Coax: examples/coax.ipynb
-        - Coax to Waveguide Transition: examples/coax_to_waveguide.ipynb
-        - Open-ended Stub: examples/open_ended_stub.ipynb
-        - Step in Width: examples/step_in_width.ipynb
-        - Waveguide Box: examples/waveguide_box.ipynb
-      - 2D Mode solver:
-        - Hollow Rectangular Waveguide Modes: examples/hollow_waveguide_modes.ipynb
-        - Dielectric Waveguide Modes: examples/dielectric_waveguide_modes.ipynb
-        - Microstrip Modes: examples/microstrip_modes.ipynb
-        - Slotline Modes: examples/slotline_modes.ipynb
-        - Differential Microstrip Modes: examples/differential_microstrip_modes.ipynb
-  - Full Course: full-course.md
diff --git a/pyproject.toml b/pyproject.toml
index 4abcec5..2562404 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,9 +18,14 @@ dependencies = [
 plot = ["pandas", "matplotlib"]
 palace-cpu = []
 docs = [
-    "mkdocs",
-    "mkdocs-material",
-    "mkdocs-jupyter",
+    "sphinx",
+    "pydata-sphinx-theme",
+    "myst-parser",
+    "myst-nb",
+    "sphinx-copybutton",
+    "sphinx-design",
+    "sphinx-autobuild",
+    "linkify-it-py",
     "pyvista[jupyter]",
     "nbconvert",
     "ipykernel",
diff --git a/sst.config.ts b/sst.config.ts
index 2763fca..0e36084 100644
--- a/sst.config.ts
+++ b/sst.config.ts
@@ -35,7 +35,7 @@ export default $config({
     const docs = new sst.aws.StaticSite("PalaceToolkitDocs", {
       path: ".",
       build: {
-        command: "mkdocs build",
+        command: "python -m sphinx -W --keep-going -b html docs site",
         output: "site",
       },
       router: {
diff --git a/tests/test_docs_build.py b/tests/test_docs_build.py
index 450feed..ceb2492 100644
--- a/tests/test_docs_build.py
+++ b/tests/test_docs_build.py
@@ -19,7 +19,17 @@ def test_docs_build_has_no_errors() -> None:
     env["DOCS_BUILD"] = "1"
 
     result = subprocess.run(
-        [sys.executable, "-m", "mkdocs", "build", "--strict"],
+        [
+            sys.executable,
+            "-m",
+            "sphinx",
+            "-W",
+            "--keep-going",
+            "-b",
+            "html",
+            "docs",
+            "site",
+        ],
         cwd=ROOT,
         env=env,
         capture_output=True,
@@ -30,7 +40,7 @@ def test_docs_build_has_no_errors() -> None:
     if result.returncode != 0:
         output = "\n".join([result.stdout.strip(), result.stderr.strip()]).strip()
         pytest.fail(
-            "mkdocs build failed in strict mode.\n"
+            "sphinx-build failed in strict mode.\n"
             f"exit_code={result.returncode}\n"
             f"{output}"
         )
\ No newline at end of file