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Description
If I have a log scaled axis, I get an error when I try to specify minor tick marks using a numpy array. The issue does not occur when I use a list instead of a numpy array.
Code for reproduction
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 2, 50)
y = np.exp(3*x)
plt.plot(x,y)
ax = plt.gca()
minor_ticks = np.array([2,3,4])
ax.set_yscale('log', basey = 10.0, subsy = list(minor_ticks))
ax.set_yscale('log', basey = 10.0, subsy = minor_ticks)Actual outcome
File "/Users/Ben/Desktop/test.py", line 21, in <module>
ax.set_yscale('log', basey = 10.0, subsy = minor_ticks)
File "/Users/Ben/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 3224, in set_yscale
ax.yaxis._set_scale(value, **kwargs)
File "/Users/Ben/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/axis.py", line 710, in _set_scale
self._scale.set_default_locators_and_formatters(self)
File "/Users/Ben/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/scale.py", line 254, in set_default_locators_and_formatters
labelOnlyBase=bool(self.subs)))
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Expected outcome
This code is expected to run without any errors. I believe it used to run in matplotlib v1.5.1, but I think that used an earlier version of numpy. At that time, I think numpy printed a warning message to the screen.
Matplotlib version
- Matplotlib 2.0.0, Python 2.7.6, OSX
- Matplotlib installed via Enthought Canopy
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