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Apply suggestions from code review
Co-authored-by: Tim Hoffmann <2836374+timhoffm@users.noreply.github.com>
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‎doc/api/next_api_changes/behavior/28061-JMK.rst

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imshow *interpolation_stage* default changed to 'auto'
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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``imshow`` *interpolation_stage* default changed to 'auto'
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The *interpolation_stage* keyword argument `~.Axes.imshow` has a new default
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The *interpolation_stage* parameter of `~.Axes.imshow` has a new default
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value 'auto'. For images that are up-sampled less than a factor of
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three or down-sampled, image interpolation will occur in 'rgba' space. For images
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that are up-sampled by more than a factor of 3, then image interpolation occurs
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that are up-sampled by a factor of 3 or more, then image interpolation occurs
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in 'data' space.
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The previous default was 'data', so down-sampled images may change subtly with
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the new default. However, the new default also avoids floating point artifacts
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at sharp boundaries in a colormap when down-sampling.
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The previous behavior can achieved by changing :rc:`image.interpolation_stage`.
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The previous behavior can achieved by setting the *interpolation_stage* parameter
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or :rc:`image.interpolation_stage` to 'data'.
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imshow default *interpolation* changed to 'auto'
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The *interpolation* keyword argument `~.Axes.imshow` has a new default
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The *interpolation* parameter of `~.Axes.imshow` has a new default
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value 'auto', changed from 'antialiased', for consistency with *interpolation_stage*
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and because the interpolation is only anti-aliasing during down-sampling. The
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'antialiased' string still works, and behaves exactly the same as 'auto'.
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and because the interpolation is only anti-aliasing during down-sampling. Passing
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'antialiased' still works, and behaves exactly the same as 'auto', but is discouraged.

‎lib/matplotlib/axes/_axes.py

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resize filter is controlled by the parameter *filternorm*.
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interpolation_stage : {'auto', 'data', 'rgba'}, default: 'auto'
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If 'data', interpolation is carried out on the data provided by the user,
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useful if interpolating between pixels during upsampling.
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If 'rgba', the interpolation is carried out in RGBA-space after the
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color-mapping has been applied, useful if downsampling and combining
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pixels visually. The default 'auto' is appropriate for most
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applications where 'rgba' is used when downsampling, or upsampling at a
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rate less than 3, and 'data' is used when upsampling at a higher rate.
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Supported values:
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- 'data': Interpolation is carried out on the data provided by the user
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This is useful if interpolating between pixels during upsampling.
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- 'rgba': The interpolation is carried out in RGBA-space after the
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color-mapping has been applied. This is useful if downsampling and
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combining pixels visually.
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- 'auto': Select a suitable interpolation stage automatically. This uses
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'rgba' when downsampling, or upsampling at a rate less than 3, and
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'data' when upsampling at a higher rate.
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See :doc:`/gallery/images_contours_and_fields/image_antialiasing` for
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a discussion of image antialiasing.
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‎lib/matplotlib/tests/test_png.py

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if data.ndim == 2:
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# keep grayscale images gray
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cmap = cm.gray
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# use the old default data interpolation stage
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# Using the old default data interpolation stage lets us
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# continue to use the existing reference image
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plt.imshow(data, extent=(i, i + 1, 0, 1), cmap=cmap,
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interpolation_stage='data')
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