html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/3810#issuecomment-592737661,https://api.github.com/repos/pydata/xarray/issues/3810,592737661,MDEyOklzc3VlQ29tbWVudDU5MjczNzY2MQ==,7441788,2020-02-28T21:29:58Z,2020-02-28T21:31:31Z,CONTRIBUTOR,"Note that with the `apply_ufunc` implementation we're only reshaping `dims`-sized `ndarray`s, not (necessarily) the whole DataArray, so maybe it's not too bad? It might be better to first sort `dims` to be in the same order as `self.dims`. i.e. `dims = [dim_ for dim_ in self.dims if dim_ in dims]`. But I'm just speculating.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592715925,https://api.github.com/repos/pydata/xarray/issues/3810,592715925,MDEyOklzc3VlQ29tbWVudDU5MjcxNTkyNQ==,7441788,2020-02-28T20:33:43Z,2020-02-28T20:35:57Z,CONTRIBUTOR,"A few minor tweaks needed:
```
In [20]: import bottleneck        

In [21]: xr.apply_ufunc( 
    ...:     lambda x: bottleneck.rankdata(x).reshape(x.shape), 
    ...:     d, 
    ...:     input_core_dims=[['xyz', 'abc']], 
    ...:     output_core_dims=[['xyz', 'abc']], 
    ...:     vectorize=True 
    ...: ).transpose(*d.dims)                                                                                                                                                                                                                      
Out[21]: 
<xarray.DataArray (abc: 4, xyz: 3)>
array([[ 1.,  2.,  3.],
       [ 4.,  5.,  6.],
       [ 7.,  8.,  9.],
       [10., 11., 12.]])
Dimensions without coordinates: abc, xyz
```

Despite what the docs say, `bottleneck.{nan}rankdata(a)` returns a 1-dimensional ndarray, not an array with the same shape as `a`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592672463,https://api.github.com/repos/pydata/xarray/issues/3810,592672463,MDEyOklzc3VlQ29tbWVudDU5MjY3MjQ2Mw==,7441788,2020-02-28T18:51:18Z,2020-02-28T18:52:29Z,CONTRIBUTOR,"What's wrong with the following? (Still need to deal with `pct` and `keep_attrs`.)
 ````
apply_ufunc(
    bottleneck.{nan}rankdata,
    self,
    input_core_dims=[dims],
    output_core_dims=[dims],
    vectorize=True
)
 ````

Per https://kwgoodman.github.io/bottleneck-doc/reference.html#bottleneck.rankdata, ""The default (axis=None) is to rank the elements of the flattened array.""","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480
https://github.com/pydata/xarray/issues/3810#issuecomment-592654794,https://api.github.com/repos/pydata/xarray/issues/3810,592654794,MDEyOklzc3VlQ29tbWVudDU5MjY1NDc5NA==,7441788,2020-02-28T18:06:57Z,2020-02-28T18:06:57Z,CONTRIBUTOR,"Assuming `dims` is a non-empty list of dimensions, the following code seems to work:
```
    temp_dim = '__temp_dim__'
    return da.stack(**{temp_dim: dims}).\
        rank(temp_dim, pct=pct, keep_attrs=keep_attrs).\
        unstack(temp_dim).transpose(*da.dims).\
        drop_vars([dim_ for dim_ in dims if dim_ not in da.coords])
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,572875480