8000 Merge pull request #29827 from QuLogic/test-reduction · matplotlib/matplotlib@662239c · GitHub
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Merge pull request #29827 from QuLogic/test-reduction
TST: Remove unnecessary test images
2 parents 9f0cdfd + 44bc05c commit 662239c

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‎doc/api/next_api_changes/behavior/29827-ES.rst

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``matplotlib.testing.check_figures_equal`` defaults to PNG only
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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In most cases, checking that figures are equal with `.check_figures_equal` does not
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depend on the file format. Consequently, the *extensions* parameter now defaults to
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``['png']`` instead of ``['png', 'pdf', 'svg']``, reducing default test requirements.

‎doc/devel/testing.rst

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@@ -191,7 +191,7 @@ vs plotting the circle using the parametric equation of a circle ::
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@check_figures_equal()
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def test_parametric_circle_plot(fig_test, fig_ref):
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xo, yo= (.5, .5)
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xo = yo = 0.5
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radius = 0.4
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ax_test = fig_test.subplots()
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ax_ref.add_artist(red_circle_ref)
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for ax in [ax_ref, ax_test]:
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ax.set(xlim=(0,1), ylim=(0,1), aspect='equal')
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ax.set(xlim=(0, 1), ylim=(0, 1), aspect='equal')
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Both comparison decorators have a tolerance argument ``tol`` that is used to specify the
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tolerance for difference in color value between the two images, where 255 is the maximal

‎lib/matplotlib/testing/decorators.py

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savefig_kwargs=savefig_kwarg, style=style)
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def check_figures_equal(*, extensions=("png", "pdf", "svg"), tol=0):
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def check_figures_equal(*, extensions=("png", ), tol=0):
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"""
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Decorator for test cases that generate and compare two figures.
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Parameters
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----------
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extensions : list, default: ["png", "pdf", "svg"]
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The extensions to test.
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extensions : list, default: ["png"]
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The extensions to test. Supported extensions are "png", "pdf", "svg".
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Testing with the one default extension is sufficient if the output is not
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format dependent, e.g. if you test that a ``bar()`` plot yields the same
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result as some manually placed Rectangles. You should use all extensions
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if a renderer property is involved, e.g. correct alpha blending.
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tol : float
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The RMS threshold above which the test is considered failed.
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‎lib/matplotlib/tests/baseline_images/test_arrow_patches/fancyarrow_test_image.pdf

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