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      "source": [
        "\n# QuadMesh Demo\n\n`~.axes.Axes.pcolormesh` uses a `~matplotlib.collections.QuadMesh`,\na faster generalization of `~.axes.Axes.pcolor`, but with some restrictions.\n\nThis demo illustrates a bug in quadmesh with masked data.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np\n\nfrom matplotlib import pyplot as plt\n\nn = 12\nx = np.linspace(-1.5, 1.5, n)\ny = np.linspace(-1.5, 1.5, n * 2)\nX, Y = np.meshgrid(x, y)\nQx = np.cos(Y) - np.cos(X)\nQz = np.sin(Y) + np.sin(X)\nZ = np.sqrt(X**2 + Y**2) / 5\nZ = (Z - Z.min()) / (Z.max() - Z.min())\n\n# The color array can include masked values.\nZm = np.ma.masked_where(np.abs(Qz) < 0.5 * np.max(Qz), Z)\n\nfig, axs = plt.subplots(nrows=1, ncols=3)\naxs[0].pcolormesh(Qx, Qz, Z, shading='gouraud')\naxs[0].set_title('Without masked values')\n\n# You can control the color of the masked region.\ncmap = plt.colormaps[plt.rcParams['image.cmap']].with_extremes(bad='y')\naxs[1].pcolormesh(Qx, Qz, Zm, shading='gouraud', cmap=cmap)\naxs[1].set_title('With masked values')\n\n# Or use the default, which is transparent.\naxs[2].pcolormesh(Qx, Qz, Zm, shading='gouraud')\naxs[2].set_title('With masked values')\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.pcolormesh` / `matplotlib.pyplot.pcolormesh`\n\n"
      ]
    }
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