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Bug report
Bug summary
Due to changes introduced in3dea5c7, trying to display some images with LogNorm will crash because vmin gets auto-adjusted to 0 (which is invalid for LogNorm).
Code for reproduction
importnumpyasnpimportmatplotlib.pyplotaspltfrommatplotlib.colorsimportLogNormdata=np.full((500,500),-1,dtype=np.float64)data[0:250, :]=1E20fig,ax=plt.subplots()im=ax.imshow(data,norm=LogNorm(vmin=100,vmax=data.max()))plt.show()
Actual outcome
File "C:\Python38\lib\site-packages\matplotlib\image.py", line 922, in make_image return self._make_image(self._A, bbox, transformed_bbox, clip, File "C:\Python38\lib\site-packages\matplotlib\image.py", line 541, in _make_image output = self.norm(resampled_masked) File "C:\Python38\lib\site-packages\matplotlib\colors.py", line 1193, in __call__ self._check_vmin_vmax() File "C:\Python38\lib\site-packages\matplotlib\colors.py", line 1182, in _check_vmin_vmax raise ValueError("minvalue must be positive")ValueError: minvalue must be positiveExpected outcome
Showed a plot in MPL 3.1 (and I believe every version until 3.3). The crash is coming from _make_image transforming vmin to be zero per changes added in3dea5c7. I guess perhaps the solution is "then don't try to plot that, use a vmin closer to your vmax" but kind of inconvenient for code that previously worked fine.
Matplotlib version: 3.3.1