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"""
=========================
Interpolations for imshow
=========================
This example displays the difference between interpolation methods for
`~.axes.Axes.imshow`.
If *interpolation* is None, it defaults to the :rc:`image.interpolation`.
If the interpolation is ``'none'``, then no interpolation is performed for the
Agg, ps and pdf backends. Other backends will default to ``'auto'``.
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 :doc:`/gallery/images_contours_and_fields/image_antialiasing` for a
discussion on the default ``interpolation='auto'`` option.
"""
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, 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()
# %%
#
# .. admonition:: References
#
# The use of the following functions, methods, classes and modules is shown
# in this example:
#
# - `matplotlib.axes.Axes.imshow` / `matplotlib.pyplot.imshow`
|
