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antialiased image check seems wrong when used on zoomed image #15517

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anntzer opened this issue Oct 25, 2019 · 4 comments · Fixed by #15519
Closed

antialiased image check seems wrong when used on zoomed image #15517

anntzer opened this issue Oct 25, 2019 · 4 comments · Fixed by #15519
Labels
Release critical For bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions. topic: images
Milestone
v3.2.0

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@anntzer
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anntzer commented Oct 25, 2019

Bug report

Bug summary

The new antialiased image code appears to not handle zoomed images correctly.

attn @jklymak

Code for reproduction

from pylab import *
plt.rcdefaults()
fig, axs = plt.subplots(1, 2)
axs[0].imshow(np.random.rand(10, 10))  # now defaults to interpolation="antialiased"
axs[1].imshow(np.random.rand(1000, 1000))
axs[1].set(xlim=(-.5, 9.5), ylim=(-.5, 9.5))
plt.show()

Actual outcome

Run with mpl master (or anything after #13724 was merged).

test

Expected outcome

The right image should also be rendered using "nearest" interpolation.

Matplotlib version

  • Operating system: linux
  • Matplotlib version: master
  • Matplotlib backend (print(matplotlib.get_backend())): qt5agg
  • Python version: 37
  • Jupyter version (if applicable): no
  • Other libraries:
@jklymak
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jklymak commented Oct 25, 2019

Fair enough, its because we use the actual data shape, not the visible data shape:

shape = list(data.shape)

I'm not quite sure how we can toggle between the two... I thought we had zooming working, but maybe I'm wrong...

@anntzer
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anntzer commented Oct 25, 2019

Indeed, I somehow remember that we did check zooming, but heh...

@jklymak
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jklymak commented Oct 25, 2019

The y transform isn't being applied properly. I'm just doing

shape = list(data.shape)
dispx, dispy = transform.transform([shape[1], shape[0]])

but I'm pretty sure shape[0] is not being transformed correctly to dispy

@jklymak
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jklymak commented Oct 25, 2019

Ooops, I think I fixed it, but need to add this as a test.

@jklymak jklymak added this to the v3.2.0 milestone Oct 25, 2019
@jklymak jklymak added the Release critical For bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions. label Oct 25, 2019
@jklymak jklymak mentioned this issue Oct 25, 2019
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Release critical For bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions. topic: images
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Milestone
v3.2.0
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FIX: fix anti-aliasing zoom bug jklymak/matplotlib
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@anntzer @jklymak