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For .isel(), I think the natural behavior would be to drop any datasets that don't have dimensions that match the isel arguments. I don't know what to do about datasets that have those dimensions but the isel() values exceed the extent. E.g. a collection with ds1 and ds2, where both have dims named lat and lon, but ds1 is 360x180 and ds2 is 50x50. Should collection.isel(lat=100) return a collection only containing ds1.isel(lat=100) and maybe a warning that ds2 could not be included?
The text was updated successfully, but these errors were encountered:
For
.isel()
, I think the natural behavior would be to drop any datasets that don't have dimensions that match the isel arguments. I don't know what to do about datasets that have those dimensions but theisel()
values exceed the extent. E.g. a collection withds1
andds2
, where both have dims namedlat
andlon
, butds1
is 360x180 andds2
is50x50
. Shouldcollection.isel(lat=100)
return a collection only containingds1.isel(lat=100)
and maybe a warning thatds2
could not be included?The text was updated successfully, but these errors were encountered: