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  • xarray · 4 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
186868181 MDU6SXNzdWUxODY4NjgxODE= 1074 DataArray.apply is missing burnpanck 1310437 open 0     9 2016-11-02T17:30:45Z 2022-11-04T17:18:58Z   CONTRIBUTOR      

In essence, I'm looking for the functionality of xarray.core.utils.maybe_wrap_array. I guess you are waiting for #964 to unify such functionality?

 
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     xarray 13221727 issue
189129954 MDU6SXNzdWUxODkxMjk5NTQ= 1120 Creating a `Dataset` with a coordinate given by a `DataArray` may create an invalid dataset burnpanck 1310437 closed 0     3 2016-11-14T14:46:44Z 2017-09-06T00:07:08Z 2017-09-06T00:07:08Z CONTRIBUTOR      

Consider this: import xarray as xr import numpy as np ds = xr.Dataset( data_vars=dict( v = ('y',np.r_[0:10]), ), coords=dict( y=xr.DataArray(np.r_[:10]/10,dims='x'), ), ) The dataset ds will end up having dimensions ('x', 'y') because of the coordinate y having dimensions ('x',). This seems to violate some of the internal assumptions (ds.indexes['y'].name turns out to be 'x'), consequently ds.sel(y=0) will throw an exception (ValueError: cannot use a dict-like object for selection on a dimension that does not have a MultiIndex).

I came across this situation when trying to generate a dataset with a coordinate that is a copy of another pre-existing coordinate, but under a different name. My expectation was that the coordinate would be renamed (doing so manually also doesn't work out of the box due to #1116). Of course that is not the only possible interpretation of the construct above, arguably it should raise an exception instead (which is what DataArray currently does in the corresponding case).

 
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   completed xarray 13221727 issue
189415576 MDU6SXNzdWUxODk0MTU1NzY= 1121 Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing burnpanck 1310437 closed 0     3 2016-11-15T15:04:29Z 2016-11-15T17:36:26Z 2016-11-15T17:36:26Z CONTRIBUTOR      

I did not follow the code deeply, but there clearly seems to be a huge overhead when indexing such arrays. In particular, in the following code ```python import xarray as xr import numpy as np

a = xr.DataArray([None for k in range(100)],dims='c') for k in range(a.c.size): a[k] = xr.DataArray(np.random.randn(1000,5),dims=['a','b'])

%prun a[0] ``` the indexing operation takes about 1 second on my machine, or 2 seconds when running under the profiler. The profiler output shows lots of functions with a recursive call count exceeding 100'000 (most likely iterating through each row of the contained sub-arrays). However, there is really no reason to iterate through the nested elements.

 
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   completed xarray 13221727 issue
189081147 MDU6SXNzdWUxODkwODExNDc= 1116 `DataArray.rename` of a coordinate array fails to rename the coordinate name of it's own coordinate burnpanck 1310437 closed 0     1 2016-11-14T10:47:24Z 2016-11-15T16:18:03Z 2016-11-15T16:18:03Z CONTRIBUTOR      

The documentation of DataArray.rename states that it renames the name of the DataArray and/or associated coordinates. However, if a name happens to be simultaneously the name of the array and of a coordinate, it only renames the array. This situation particularly arises when one tries to create a renamed coordinate to use on a different (new) array/dataset, as in that case the name of the only dimension of the coordinate array is the name of the array itself. 

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   completed xarray 13221727 issue

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