.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/plot_11_image_interpolation.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_plot_11_image_interpolation.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_plot_11_image_interpolation.py:


Image Interpolation Methods
===========================

:meth:`matplotview.view` and :meth:`matplotview.inset_zoom_axes` support specifying an
image interpolation method via the `image_interpolation` parameter. This image interpolation
method is used to resize images when displaying them in the view.

.. GENERATED FROM PYTHON SOURCE LINES 9-31

.. code-block:: default
   :lineno-start: 9

    import matplotlib.pyplot as plt
    from matplotview import view
    import numpy as np

    fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)

    fig.suptitle("Different interpolations when zoomed in on the bottom left corner.")

    ax1.set_title("Original")
    ax1.imshow(np.random.rand(100, 100), cmap="Blues", origin="lower")
    ax1.add_patch(plt.Rectangle((0, 0), 10, 10, ec="red", fc=(0, 0, 0, 0)))

    for ax, interpolation, title in zip([ax2, ax3, ax4], ["nearest", "bilinear", "bicubic"], ["Nearest (Default)", "Bilinear", "Cubic"]):
        ax.set_title(title)
        ax.set_xlim(0, 10)
        ax.set_ylim(0, 10)
        ax.set_aspect("equal")
        view(ax, ax1, image_interpolation=interpolation)

    fig.tight_layout()
    fig.show()




.. image-sg:: /examples/images/sphx_glr_plot_11_image_interpolation_001.png
   :alt: Different interpolations when zoomed in on the bottom left corner., Original, Nearest (Default), Bilinear, Cubic
   :srcset: /examples/images/sphx_glr_plot_11_image_interpolation_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 32-33

If you want to avoid interpolation artifacts, you can use `pcolormesh` instead of `imshow`.

.. GENERATED FROM PYTHON SOURCE LINES 33-52

.. code-block:: default
   :lineno-start: 34


    import matplotlib.pyplot as plt
    from matplotview import view
    import numpy as np

    fig, (ax1, ax2) = plt.subplots(1, 2)

    ax1.set_title("Original")
    ax1.pcolormesh(np.random.rand(100, 100), cmap="Blues")
    ax1.add_patch(plt.Rectangle((0, 0), 10, 10, ec="red", fc=(0, 0, 0, 0)))
    ax1.set_aspect("equal")

    ax2.set_title("Zoomed in View")
    ax2.set_xlim(0, 10)
    ax2.set_ylim(0, 10)
    ax2.set_aspect("equal")
    view(ax2, ax1)

    fig.tight_layout()
    fig.show()


.. image-sg:: /examples/images/sphx_glr_plot_11_image_interpolation_002.png
   :alt: Original, Zoomed in View
   :srcset: /examples/images/sphx_glr_plot_11_image_interpolation_002.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 3.037 seconds)


.. _sphx_glr_download_examples_plot_11_image_interpolation.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example




    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_11_image_interpolation.py <plot_11_image_interpolation.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_11_image_interpolation.ipynb <plot_11_image_interpolation.ipynb>`


.. only:: html

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

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