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| a_max = np.float64(newmax) | ||
| if newmax is not None or newmin is not None: | ||
| A_scaled = np.clip(A_scaled, newmin, newmax) | ||
| vmin = self.norm.vmin if self.norm.vmin is not None else a_min |
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I would do if self.norm.vmin is None or self.norm.vmax is None: self.norm.autoscale_None(A)
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Sure - its OK to modify the norm here?
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don't even need the if-statement in that case.
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Please squash before merging.
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squashed and rebased.... |
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There seem to be a conflict, please backport manually |
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Does this want a backport to 2.2.x? |
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…rm-limits
FIX: image respect norm limits w/ None
Conflicts:
lib/matplotlib/image.py
- keep changes backported from master. Looks like conflict
was due to some white-space clean up done on master.
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PR Summary
Re-closes #10072
We are slowly suqishing the "big number" bugs in imshow.
This one was caused by only specifying vmax but not vmin. Algorithm is the same as before, but if vmin is None, then we scale by a_min.
Before
After
PR Checklist