issue_comments: 1446096001

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https://github.com/pydata/xarray/issues/4061#issuecomment-1446096001 https://api.github.com/repos/pydata/xarray/issues/4061 1446096001 IC_kwDOAMm_X85WMayB 60435591 2023-02-27T10:43:51Z 2023-02-27T11:16:59Z CONTRIBUTOR

As suggested by https://github.com/pydata/xarray/pull/7553#discussion_r1117264787, pass levels=bounds instead of norm=norm to data.plot(). Your example code results in a plot as expected. Would this solve your issue?

``` 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', levels=bounds, add_colorbar=False) ```

 
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