The behaviour when specifying "norm" for a colormap normalisation does not work as anticipated.

Below I use the example code from matplotlib and apply the same normalisation to the DataArray version of the data but get very different results.

MCVE Code Sample

```python import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as colors import xarray

example from https://matplotlib.org/3.1.1/tutorials/colors/colormapnorms.html

for colormap normalisation

N = 100 X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)] Z1 = np.exp(-X2 - Y2) Z2 = np.exp(-(X - 1)2 - (Y - 1)2) Z = (Z1 - Z2) * 2

fig, ax = plt.subplots(2, 1, figsize=(8, 8)) ax = ax.flatten()

bounds = np.linspace(-1, 1, 10) norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)

ax[0].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r')

now add data into dataset and plot it using same normalisation

data = xarray.DataArray(Z, dims=('x', 'y'), coords={'x': X[:,0], 'y': Y[0,:]}) data.plot(ax=ax[1], x='x', y='y', norm=norm, add_colorbar=False)

plt.show() ```

Expected Output

Top is expected, bottom is actual

Problem Description

Colormap normalisation appears to be broken in xarray

Versions

Output of <tt>xr.show_versions()</tt>

xarray.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-957.21.3.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.15.1 pandas: 0.25.1 numpy: 1.17.2 scipy: 1.3.1 netCDF4: 1.5.1.2 pydap: None h5netcdf: None h5py: 2.9.0 Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudoNetCDF: None rasterio: 1.0.28 cfgrib: None iris: 2.2.0 bottleneck: None dask: 2.5.2 distributed: 2.5.2 matplotlib: 3.1.1 cartopy: 0.17.0 seaborn: 0.9.0 numbagg: None setuptools: 41.4.0 pip: 19.2.3 conda: None pytest: None IPython: 7.8.0 sphinx: None