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# Colorbar Tick Labelling Demo

Produce custom labelling for a colorbar.

Contributed by Scott Sinclair

    import matplotlib.pyplot as plt
    import numpy as np
    from matplotlib import cm
    from numpy.random import randn

    # Make plot with vertical (default) colorbar
    fig, ax = plt.subplots()

    data = np.clip(randn(250, 250), -1, 1)

    cax = ax.imshow(data, interpolation='nearest', cmap=cm.coolwarm)
    ax.set_title('Gaussian noise with vertical colorbar')

    # Add colorbar, make sure to specify tick locations to match desired ticklabels
    cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
    cbar.ax.set_yticklabels(['< -1', '0', '> 1'])  # vertically oriented colorbar

    # Make plot with horizontal colorbar
    fig, ax = plt.subplots()

    data = np.clip(randn(250, 250), -1, 1)

    cax = ax.imshow(data, interpolation='nearest', cmap=cm.afmhot)
    ax.set_title('Gaussian noise with horizontal colorbar')

    cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')
    cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])  # horizontal colorbar

    plt.show()

Total running time of the script: ( 0 minutes 0.101 seconds)

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