Contour with vmin/ vmax differs from matplotlib

[mathause]

MCVE Code Sample

import numpy as np
import xarray as xr
import matplotlib as mpl
import matplotlib.pyplot as plt

data = xr.DataArray(np.arange(24).reshape(4, 6))

data.plot.contour(vmax=10, add_colorbar=True)

Expected Output

h = plt.contour(data.values, vmax=10)
plt.colorbar(h)

Problem Description

A contour(vmax=vmax) plot differs between xarray and matplotlib. I think the problem is here:

xarray/xarray/plot/utils.py

Line 265 in 95e4f6c

levels = np.linspace(vmin, vmax, levels)

xarray calculates the levels from vmax while matplotlib (probably) calculates the levels from data.max() and uses vmax only for the norm. For contourf and pcolormesh this is not so relevant as the capped values are then drawn with the over color. However, there may also be a good reason for this behavior.

Output of xr.show_versions()

INSTALLED VERSIONS

commit: 4c96d53
python: 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.12.14-lp151.28.36-default
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.6.2

xarray: 999 (master)
pandas: 0.25.3
numpy: 1.17.3
scipy: 1.4.1
netCDF4: 1.5.1.2
pydap: installed
h5netcdf: 0.7.4
h5py: 2.10.0
Nio: 1.5.5
zarr: 2.4.0
cftime: 1.0.4.2
nc_time_axis: 1.2.0
PseudoNetCDF: installed
rasterio: 1.1.0
cfgrib: 0.9.7.6
iris: 2.2.0
bottleneck: 1.3.1
dask: 2.9.2
distributed: 2.9.2
matplotlib: 3.1.2
cartopy: 0.17.0
seaborn: 0.9.0
numbagg: installed
setuptools: 45.0.0.post20200113
pip: 19.3.1
conda: None
pytest: 5.3.3
IPython: 7.11.1
sphinx: None