html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/1972#issuecomment-371718795,https://api.github.com/repos/pydata/xarray/issues/1972,371718795,MDEyOklzc3VlQ29tbWVudDM3MTcxODc5NQ==,1562854,2018-03-09T05:38:23Z,2018-03-09T05:38:23Z,CONTRIBUTOR,"As pointed out on the matplotlib gitter:
If you run
```python
import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
for i in range(200):
xr.DataArray(np.array([[0, 0], [0, 0]], dtype=np.uint8)).plot.pcolormesh()
```
at step 165 you will get:
```
File ""/Users/jklymak/matplotlib/lib/matplotlib/figure.py"", line 236, in update
raise ValueError('left cannot be >= right')
ValueError: left cannot be >= right
```
Why? Because you have made a plot that if it displays looks like:
Are you sure your test isn't doing something similar? At some point there just isn't room for more colorbars! Adding a `plt.clf()` can cure the problem.
Its also is possible you are hitting floating point overflows with your test. At some point Matplotlib needs to be able to manipulate the data that comes in, and if you operate near the maximum number your data type can handle, you'll have problems. Just like you would if you just did
```python
a = 2*xr.DataArray(np.array([[0, 0], [0, 1e308]]))
```
you will get:
```
/Users/jklymak/anaconda3/envs/matplotlibdev/lib/python3.6/site-packages/xarray/core/variable.py:1165: RuntimeWarning: overflow encountered in multiply
```
So maybe your hypothesis tester could be constrained to stay away from floating point overflows?
Matplotlib indeed has flaws and quirks, but if you are finding bugs it would be good to isolate them.
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