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        "\n# Hillshading\n\nDemonstrates a few common tricks with shaded plots.\n"
      ]
    },
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        "import matplotlib.pyplot as plt\nimport numpy as np\n\nfrom matplotlib.colors import LightSource, Normalize\n\n\ndef display_colorbar():\n    \"\"\"Display a correct numeric colorbar for a shaded plot.\"\"\"\n    y, x = np.mgrid[-4:2:200j, -4:2:200j]\n    z = 10 * np.cos(x**2 + y**2)\n\n    cmap = plt.cm.copper\n    ls = LightSource(315, 45)\n    rgb = ls.shade(z, cmap)\n\n    fig, ax = plt.subplots()\n    ax.imshow(rgb, interpolation='bilinear')\n\n    # Use a proxy artist for the colorbar...\n    im = ax.imshow(z, cmap=cmap)\n    im.remove()\n    fig.colorbar(im, ax=ax)\n\n    ax.set_title('Using a colorbar with a shaded plot', size='x-large')\n\n\ndef avoid_outliers():\n    \"\"\"Use a custom norm to control the displayed z-range of a shaded plot.\"\"\"\n    y, x = np.mgrid[-4:2:200j, -4:2:200j]\n    z = 10 * np.cos(x**2 + y**2)\n\n    # Add some outliers...\n    z[100, 105] = 2000\n    z[120, 110] = -9000\n\n    ls = LightSource(315, 45)\n    fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(8, 4.5))\n\n    rgb = ls.shade(z, plt.cm.copper)\n    ax1.imshow(rgb, interpolation='bilinear')\n    ax1.set_title('Full range of data')\n\n    rgb = ls.shade(z, plt.cm.copper, vmin=-10, vmax=10)\n    ax2.imshow(rgb, interpolation='bilinear')\n    ax2.set_title('Manually set range')\n\n    fig.suptitle('Avoiding Outliers in Shaded Plots', size='x-large')\n\n\ndef shade_other_data():\n    \"\"\"Demonstrates displaying different variables through shade and color.\"\"\"\n    y, x = np.mgrid[-4:2:200j, -4:2:200j]\n    z1 = np.sin(x**2)  # Data to hillshade\n    z2 = np.cos(x**2 + y**2)  # Data to color\n\n    norm = Normalize(z2.min(), z2.max())\n    cmap = plt.cm.RdBu\n\n    ls = LightSource(315, 45)\n    rgb = ls.shade_rgb(cmap(norm(z2)), z1)\n\n    fig, ax = plt.subplots()\n    ax.imshow(rgb, interpolation='bilinear')\n    ax.set_title('Shade by one variable, color by another', size='x-large')\n\ndisplay_colorbar()\navoid_outliers()\nshade_other_data()\nplt.show()"
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