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    {
      "cell_type": "code",
      "execution_count": null,
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      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Colorbar tick labelling\n\nProduce custom labelling for a colorbar.\n\nContributed by Scott Sinclair\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib import cm\nfrom numpy.random import randn\n\n# Make plot with vertical (default) colorbar\nfig, ax = plt.subplots()\n\ndata = np.clip(randn(250, 250), -1, 1)\n\ncax = ax.imshow(data, interpolation=\"nearest\", cmap=cm.coolwarm)\nax.set_title(\"Gaussian noise with vertical colorbar\")\n\n# Add colorbar, make sure to specify tick locations to match desired ticklabels\ncbar = fig.colorbar(cax, ticks=[-1, 0, 1])\ncbar.ax.set_yticklabels([\"< -1\", \"0\", \"> 1\"])  # vertically oriented colorbar\n\n# Make plot with horizontal colorbar\nfig, ax = plt.subplots()\n\ndata = np.clip(randn(250, 250), -1, 1)\n\ncax = ax.imshow(data, interpolation=\"nearest\", cmap=cm.afmhot)\nax.set_title(\"Gaussian noise with horizontal colorbar\")\n\ncbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation=\"horizontal\")\ncbar.ax.set_xticklabels([\"Low\", \"Medium\", \"High\"])  # horizontal colorbar\n\nplt.show()"
      ]
    }
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