Contour with vmin/ vmax differs from matplotlib

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:

https://github.com/pydata/xarray/blob/95e4f6c7a636878c94b892ee8d49866823d0748f/xarray/plot/utils.py#L265

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()

Start with the plotting logic linked in xarray/plot/utils.py around line 265, then run the MCVE to compare xarray's contour output with matplotlib's plt.contour output. Check the related contour handling and add coverage showing that vmin/vmax produce the expected levels and normalization.