{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Contouring\n\nGenerate iso-lines or -surfaces for the scalars of a surface or volume.\n\n3D meshes can have 2D iso-surfaces of a scalar field extracted and 2D\nsurface meshes can have 1D iso-lines of a scalar field extracted.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import pyvista as pv\nfrom pyvista import examples"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Iso-Lines\n\nLet\\'s extract 1D iso-lines of a scalar field from a 2D surface mesh.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "mesh = examples.load_random_hills()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "help(mesh.contour)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "contours = ..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "pl = pv.Plotter()\npl.add_mesh(mesh, opacity=0.85)\npl.add_mesh(contours, color=\"white\", line_width=5)\npl.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Iso-Surfaces\n\nLet\\'s extract 2D iso-surfaces of a scalar field from a 3D mesh.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "mesh = examples.download_embryo()\nmesh"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "For this example dataset, let\\'s create 5 contour levels between the\nvalues of 50 and 200\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "contours = ..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "pl = pv.Plotter()\npl.add_mesh(mesh.outline(), color=\"k\")\npl.add_mesh(contours, opacity=0.25, clim=[0, 200])\npl.camera_position = [\n    (-130.99381142132086, 644.4868354828589, 163.80447435848686),\n    (125.21748748157661, 123.94368717158413, 108.83283586619626),\n    (0.2780372840777734, 0.03547871361794171, 0.9599148553609699),\n]\npl.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "```{=html}\n<center>\n  <a target=\"_blank\" href=\"https://colab.research.google.com/github/pyvista/pyvista-tutorial/blob/gh-pages/notebooks/tutorial/04_filters/exercises/d_contouring.ipynb\">\n    <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/ width=\"150px\">\n  </a>\n</center>\n```\n"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.11"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}