.. _sphx_glr_gallery_images_contours_and_fields_interpolation_methods.py:


=================================
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.




.. image:: /gallery/images_contours_and_fields/images/sphx_glr_interpolation_methods_001.png
    :align: center





.. code-block:: python


    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()



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: interpolation_methods.py <interpolation_methods.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: interpolation_methods.ipynb <interpolation_methods.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_