refer to: https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html#sphx-glr-gallery-images-contours-and-fields-interpolation-methods-py

This example displays the difference between interpolation methods forimshow.

If interpolation is None, it defaults to the rcParams["image.interpolation"] (default: 'antialiased'). If the interpolation is 'none', then no interpolation is performed for the Agg, ps and pdf backends. Other backends will default to 'antialiased'.

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.

See Image antialiasing for a discussion on the default interpolation="antialiased" option.

import matplotlib.pyplot as pltimport numpy as npmethods = [None, 'none', 'nearest', 'bilinear', 'bicubic', 'spline16',
           'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',
           'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos']# Fixing random state for reproducibilitynp.random.seed(19680801)grid = np.random.rand(4, 4)fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(9, 6),
                        subplot_kw={'xticks': [], 'yticks': []})for ax, interp_method in zip(axs.flat, methods):
    ax.imshow(grid, interpolation=interp_method, cmap='viridis')
    ax.set_title(str(interp_method))plt.tight_layout()plt.show()

References

The use of the following functions, methods, classes and modules is shown in this example:

• matplotlib.axes.Axes.imshow / matplotlib.pyplot.imshow