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Description
Bug report
Bug summary
When setting the scale to log on an empty axis while having numpy error handling set to raise, a FloatingPointError is thrown. When plotting data beforehand, everything works fine.
This is an issue for me, because I'm trying to plot multiple subplots with shared y axes after each other, where this issue occurs as well. For some reason in that context the error handling seems to bet set to raise.
Issue #4285 is related but the stack trace is different and this issue is not dependent on data.
Code for reproduction
import matplotlib.pyplot as plt
import numpy as np
np.seterr(all="raise")
#plt.plot([1], [1])
plt.yscale("log")Actual outcome
Traceback (most recent call last):
File ".../.PyCharmCE2019.2/config/scratches/scratch_44.py", line 7, in <module>
plt.yscale("log")
File ".../venv/lib/python3.6/site-packages/matplotlib/pyplot.py", line 3088, in yscale
return gca().set_yscale(value, **kwargs)
File ".../venv/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 3711, in set_yscale
self.autoscale_view(scalex=False)
File ".../venv/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 2498, in autoscale_view
'minposy', self.yaxis, self._ymargin, y_stickies, self.set_ybound)
File ".../venv/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 2486, in handle_single_axis
x0, x1 = inverse_trans.transform([x0t, x1t])
File ".../venv/lib/python3.6/site-packages/matplotlib/transforms.py", line 1394, in transform
res = self.transform_affine(self.transform_non_affine(values))
File ".../venv/lib/python3.6/site-packages/matplotlib/scale.py", line 334, in transform_non_affine
return ma.power(self.base, a)
File ".../venv/lib/python3.6/site-packages/numpy/ma/core.py", line 6717, in power
result = np.where(m, fa, umath.power(fa, fb)).view(basetype)
FloatingPointError: underflow encountered in power
Matplotlib version
- Operating system: Ubuntu 18.04
- Matplotlib version: 3.1.1
- Matplotlib backend (
print(matplotlib.get_backend())): TkAgg - Python version: 3.6.8
- Other libraries: Numpy == 1.17.2
All packages were installed using pip.
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