{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Triinterp Demo\n\nInterpolation from triangular grid to quad grid.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nimport matplotlib.tri as mtri\n\n# Create triangulation.\nx = np.asarray([0, 1, 2, 3, 0.5, 1.5, 2.5, 1, 2, 1.5])\ny = np.asarray([0, 0, 0, 0, 1.0, 1.0, 1.0, 2, 2, 3.0])\ntriangles = [[0, 1, 4], [1, 2, 5], [2, 3, 6], [1, 5, 4], [2, 6, 5], [4, 5, 7],\n             [5, 6, 8], [5, 8, 7], [7, 8, 9]]\ntriang = mtri.Triangulation(x, y, triangles)\n\n# Interpolate to regularly-spaced quad grid.\nz = np.cos(1.5 * x) * np.cos(1.5 * y)\nxi, yi = np.meshgrid(np.linspace(0, 3, 20), np.linspace(0, 3, 20))\n\ninterp_lin = mtri.LinearTriInterpolator(triang, z)\nzi_lin = interp_lin(xi, yi)\n\ninterp_cubic_geom = mtri.CubicTriInterpolator(triang, z, kind='geom')\nzi_cubic_geom = interp_cubic_geom(xi, yi)\n\ninterp_cubic_min_E = mtri.CubicTriInterpolator(triang, z, kind='min_E')\nzi_cubic_min_E = interp_cubic_min_E(xi, yi)\n\n# Set up the figure\nfig, axs = plt.subplots(nrows=2, ncols=2)\naxs = axs.flatten()\n\n# Plot the triangulation.\naxs[0].tricontourf(triang, z)\naxs[0].triplot(triang, 'ko-')\naxs[0].set_title('Triangular grid')\n\n# Plot linear interpolation to quad grid.\naxs[1].contourf(xi, yi, zi_lin)\naxs[1].plot(xi, yi, 'k-', lw=0.5, alpha=0.5)\naxs[1].plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5)\naxs[1].set_title(\"Linear interpolation\")\n\n# Plot cubic interpolation to quad grid, kind=geom\naxs[2].contourf(xi, yi, zi_cubic_geom)\naxs[2].plot(xi, yi, 'k-', lw=0.5, alpha=0.5)\naxs[2].plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5)\naxs[2].set_title(\"Cubic interpolation,\\nkind='geom'\")\n\n# Plot cubic interpolation to quad grid, kind=min_E\naxs[3].contourf(xi, yi, zi_cubic_min_E)\naxs[3].plot(xi, yi, 'k-', lw=0.5, alpha=0.5)\naxs[3].plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5)\naxs[3].set_title(\"Cubic interpolation,\\nkind='min_E'\")\n\nfig.tight_layout()\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. admonition:: References\n\n   The use of the following functions, methods, classes and modules is shown\n   in this example:\n\n   - `matplotlib.axes.Axes.tricontourf` / `matplotlib.pyplot.tricontourf`\n   - `matplotlib.axes.Axes.triplot` / `matplotlib.pyplot.triplot`\n   - `matplotlib.axes.Axes.contourf` / `matplotlib.pyplot.contourf`\n   - `matplotlib.axes.Axes.plot` / `matplotlib.pyplot.plot`\n   - `matplotlib.tri`\n   - `matplotlib.tri.LinearTriInterpolator`\n   - `matplotlib.tri.CubicTriInterpolator`\n   - `matplotlib.tri.Triangulation`\n\n"
      ]
    }
  ],
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      "file_extension": ".py",
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      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
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