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Description
Bug report
When using the PowerNorm to normalize data with imshow, if you turn on the min end of the extend for the colorbar the colorbar will not render.
Code for reproduction
import numpy as np
import matplotlib
matplotlib.use('Agg')
#matplotlib.use('Qt4Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors
fig, ax = plt.subplots(2, 1)
test_data1 = np.zeros((100,100), ) # data at the bottom bound of the range
disp_obj1 = ax[0].imshow (test_data1, norm=colors.PowerNorm(gamma=0.5, vmin=0.0, vmax=1.0,),)
# ************ to reproduce the bug, use the line with 'both' or 'min' extends *************
#fig.colorbar(disp_obj1, ax=ax[0], )
fig.colorbar(disp_obj1, ax=ax[0], extend='max')
#fig.colorbar(disp_obj1, ax=ax[0], extend='min')
#fig.colorbar(disp_obj1, ax=ax[0], extend='both')
test_data2 = np.ones((100,100), ) * 0.25 # all positive data that's inside the range
disp_obj2 = ax[1].imshow (test_data2, norm=colors.PowerNorm(gamma=0.5, vmin=0.0, vmax=1.0,),)
# ************ to reproduce the bug, use the line with 'both' or 'min' extends *************
#fig.colorbar(disp_obj2, ax=ax[1], )
#fig.colorbar(disp_obj2, ax=ax[1], extend='max')
fig.colorbar(disp_obj2, ax=ax[1], extend='min')
#fig.colorbar(disp_obj2, ax=ax[1], extend='both')
fig.savefig("./test.png", )
plt.close(fig)Actual outcome
I see the following warning (or similar in different environments) when I trigger the bug:
celestia:temp_tests evas$ python -m test
/Users/evas/anaconda/envs/aitf_ql_3/lib/python3.6/site-packages/matplotlib/colors.py:1199: RuntimeWarning: invalid value encountered in power
np.power(resdat, gamma, resdat)
/Users/evas/anaconda/envs/aitf_ql_3/lib/python3.6/site-packages/matplotlib/colorbar.py:891: RuntimeWarning: invalid value encountered in true_divide
z = np.take(y, i0) + (xn - np.take(b, i0)) * dy / db
Expected outcome
I would expect the colorbar to render correctly with the triangle on the bottom.
Matplotlib version
I'm using MacOS 10.11.5 and my environments were set up using conda.
I have tested this with Qt4Agg in python 3.6 and with Agg in both python 3.6 and python 2.7 (the bug appears with both).
I have matplotlib 1.5.1 in my python 2.7 environment and matplotlib 2.1.2 in my python 3.6 environment (the bug appears with both).
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