set_boundary removes data from axis on faceting plots

[markusritschel]

I experienced that when using FacetGrid plots and if I want to apply a boundary to the axes, the data from the plots get removed.

A short example to illustrate this:

import xarray as xr
import matplotlib.path as mpath
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np

ds = xr.tutorial.load_dataset('air_temperature')

data = ds.air.isel(time=range(0,2))
p = data.plot(transform=ccrs.PlateCarree(),
            y="lat", x="lon",
            col='time', col_wrap=2,
            subplot_kws={'projection': ccrs.NorthPolarStereo()}
)

theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)

for ax in p.axes.flat:
    ax.coastlines()
    ax.gridlines()
    ax.set_extent([-180,180, 50,90], crs=ccrs.PlateCarree())
    #ax.set_boundary(circle, transform=ax.transAxes)

With the last line I want to have a circle as a boundary of each axis. This works but the data are not shown anymore:

Commenting the last line in the example shows the data as expected but without the boundary of course:

Any hints on why this isn't working?

Cheers,
Markus

[dcherian]

Does this work if you avoid xarray and just use plain matplotlib?

[markusritschel]

Yes, sorry. I should've mentioned that. On a single plot this works, but only iff you apply the set_boundary command before the data plotting, i.e.:

import xarray as xr
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np

ds = xr.tutorial.load_dataset('air_temperature')

ax = plt.subplot(projection=ccrs.NorthPolarStereo())
ax.set_boundary(circle, transform=ax.transAxes)  # works

data = ds.air.isel(time=0)
p = data.plot(transform=ccrs.PlateCarree(),
            y="lat", x="lon",
            ax=ax
)

theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)

ax.coastlines()
ax.gridlines()
ax.set_extent([-180,180, 50,90], crs=ccrs.PlateCarree())
# ax.set_boundary(circle, transform=ax.transAxes)   # wouldn't work

[markusritschel]

With pure matplotlib (avoiding the xarray.plot function) both versions show the data. However, calling set_boundary at the end would leave the data unrestricted.

import xarray as xr
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np

ds = xr.tutorial.load_dataset('air_temperature')

ax = plt.subplot(projection=ccrs.NorthPolarStereo())
# ax.set_boundary(circle, transform=ax.transAxes)  # works and "cuts" also the data as in the example above

data = ds.air.isel(time=0)

ax.pcolor(data.lon, data.lat, data, transform=ccrs.PlateCarree())

theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)

ax.coastlines()
ax.gridlines()
ax.set_extent([-180,180, 50,90], crs=ccrs.PlateCarree())
ax.set_boundary(circle, transform=ax.transAxes)   # works for the axis border but not for the data

PS.: can I somehow append images of the plots?

[kmuehlbauer]

@markusritschel For adding images etc please have a look here: https://help.github.com/en/github/managing-your-work-on-github/file-attachments-on-issues-and-pull-requests

[markusritschel]

Hey @kmuehlbauer, alles klar? :-)
Ah, yes, there's even the hint on the bottom. Didn't see this. Thanks!
I updated my previous comments.

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