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# Interpolations for imshow/matshow

This example displays the difference between interpolation methods for imshow and matshow.

If `interpolation` is None, it defaults to the rc image.interpolation parameter. If the interpolation is `none`, then no interpolation is performed for the Agg, ps and pdf backends. Other backends will default to ‘nearest’.

For the Agg, ps and pdf backends, interpolation = ‘none’ works well when a big image is scaled down, while interpolation = ‘nearest’ works well when a small image is scaled up.

    import matplotlib.pyplot as plt
    import numpy as np

    methods = [None, 'none', 'nearest', 'bilinear', 'bicubic', 'spline16',
               'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',
               'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos']

    # Fixing random state for reproducibility
    np.random.seed(19680801)

    grid = np.random.rand(4, 4)

    fig, axes = plt.subplots(3, 6, figsize=(12, 6),
                             subplot_kw={'xticks': [], 'yticks': []})

    fig.subplots_adjust(hspace=0.3, wspace=0.05)

    for ax, interp_method in zip(axes.flat, methods):
        ax.imshow(grid, interpolation=interp_method, cmap='viridis')
        ax.set_title(interp_method)

    plt.show()

Total running time of the script: ( 0 minutes 0.683 seconds)

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