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  • markusritschel · 6 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
788753958 https://github.com/pydata/xarray/issues/4476#issuecomment-788753958 https://api.github.com/repos/pydata/xarray/issues/4476 MDEyOklzc3VlQ29tbWVudDc4ODc1Mzk1OA== markusritschel 3332539 2021-03-02T09:16:10Z 2021-03-02T09:18:39Z NONE

@zxdawn I am pretty sure it was possible in v0.15.1. But I would need to check that again.

edit: I just checked the old documentation from that version, and it confirms my memory: http://xarray.pydata.org/en/accessor-documentation/generated/xarray.core.groupby.DataArrayGroupBy.argmax.html 

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   Reimplement GroupBy.argmax 712217045
722034130 https://github.com/pydata/xarray/issues/4476#issuecomment-722034130 https://api.github.com/repos/pydata/xarray/issues/4476 MDEyOklzc3VlQ29tbWVudDcyMjAzNDEzMA== markusritschel 3332539 2020-11-04T23:42:38Z 2020-11-04T23:42:38Z NONE

This was definitely possible in the last versions (at least in v.0.15.1). Can we make this available again?

 
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   Reimplement GroupBy.argmax 712217045
676326130 https://github.com/pydata/xarray/issues/4240#issuecomment-676326130 https://api.github.com/repos/pydata/xarray/issues/4240 MDEyOklzc3VlQ29tbWVudDY3NjMyNjEzMA== markusritschel 3332539 2020-08-19T13:07:05Z 2020-08-19T13:07:05Z NONE

Would it be an option to consider the time stamp of the file's last change as a caching criterion?

 
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   jupyter repr caching deleted netcdf file 662505658
642534445 https://github.com/pydata/xarray/issues/4137#issuecomment-642534445 https://api.github.com/repos/pydata/xarray/issues/4137 MDEyOklzc3VlQ29tbWVudDY0MjUzNDQ0NQ== markusritschel 3332539 2020-06-11T09:38:06Z 2020-06-11T09:52:34Z NONE

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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   set_boundary removes data from axis on faceting plots 636200235
642086321 https://github.com/pydata/xarray/issues/4137#issuecomment-642086321 https://api.github.com/repos/pydata/xarray/issues/4137 MDEyOklzc3VlQ29tbWVudDY0MjA4NjMyMQ== markusritschel 3332539 2020-06-10T15:30:44Z 2020-06-11T09:51:48Z NONE

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.

```python 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?

 
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   set_boundary removes data from axis on faceting plots 636200235
642075928 https://github.com/pydata/xarray/issues/4137#issuecomment-642075928 https://api.github.com/repos/pydata/xarray/issues/4137 MDEyOklzc3VlQ29tbWVudDY0MjA3NTkyOA== markusritschel 3332539 2020-06-10T15:14:11Z 2020-06-11T09:49:56Z NONE

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.:

```python 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

```

 
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   set_boundary removes data from axis on faceting plots 636200235

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