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/pull/731#issuecomment-192107773,https://api.github.com/repos/pydata/xarray/issues/731,192107773,MDEyOklzc3VlQ29tbWVudDE5MjEwNzc3Mw==,15167171,2016-03-04T05:09:54Z,2016-03-04T05:09:54Z,NONE,"Alright, I think it's ready!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-189476736,https://api.github.com/repos/pydata/xarray/issues/731,189476736,MDEyOklzc3VlQ29tbWVudDE4OTQ3NjczNg==,15167171,2016-02-26T20:44:05Z,2016-02-26T20:44:05Z,NONE,"Ready for review.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-183784767,https://api.github.com/repos/pydata/xarray/issues/731,183784767,MDEyOklzc3VlQ29tbWVudDE4Mzc4NDc2Nw==,15167171,2016-02-14T01:15:49Z,2016-02-14T01:15:49Z,NONE,"Alright I think I got rebase to work, apologies for the delay.
There were some comments I wasn't sure about how to integrate, I asked about them, but I figured the best way to keep moving forward was to push my best guess at what you meant. So we might need to go through one more round of comments. Thanks for being patient!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-178379984,https://api.github.com/repos/pydata/xarray/issues/731,178379984,MDEyOklzc3VlQ29tbWVudDE3ODM3OTk4NA==,15167171,2016-02-02T05:12:33Z,2016-02-02T05:12:33Z,NONE,"Thanks! Good comments, should help with my next pull request. : )
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-176955192,https://api.github.com/repos/pydata/xarray/issues/731,176955192,MDEyOklzc3VlQ29tbWVudDE3Njk1NTE5Mg==,15167171,2016-01-29T20:29:15Z,2016-01-29T20:29:15Z,NONE,"> That said, this is difficult to implement with numpy's dot/tensordot, so perhaps it's better to simply error or omit the dims argument entirely for now. Eventually, we might be able to do this using @/np.matmul (only in numpy 1.10 and newer).
Yeah I'm going to go for omitting the dims entirely for now, I think it makes the function easy to call, and really covers what I imagine most people would use the function for, getting the relationship between two DataArrays along their common dimensions. Thats all I'm going to use it for.
> I also wonder if perhaps we should rename this from tensordot to simply dot. I don't think we would want to use dot for anything else, and it might also be nice to support @ syntax as an alias for this in Python 3 (again, at some later point).
Yeah that makes sense. `tensordot` in xarray seems like it would be the function that allows more flexibility in how a sum product is applied, `dot` can be thought of as a reduced version of `tensordot` taking no `dims` argument.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-176571428,https://api.github.com/repos/pydata/xarray/issues/731,176571428,MDEyOklzc3VlQ29tbWVudDE3NjU3MTQyOA==,15167171,2016-01-29T04:44:25Z,2016-01-29T04:45:45Z,NONE,"I've implemented all your comments, except:
1. In the dask test I'm having a little trouble with:
`self.assertLazyAndAllClose(eager, lazy)`
working with the DataArrays I make. Does it only take transformations of:
```
self.eager_array
self.lazy_array
```
2 Your comment:
`Use the genetic type(self) instead`
Which I didn't understand.
3 Need to figure out how to edit the docs.
And I was thinking:
The default (when no dims arg is given) should be to tensordot over all shared dims between DataArrays.
And it should prevent you from not summing over all shared dims, since that will return a DataArray with repeated labels. I think it would be rare for people to want to tensor dot over different dimensions.
Thanks for all your help getting me going!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,129286220
https://github.com/pydata/xarray/pull/731#issuecomment-175905067,https://api.github.com/repos/pydata/xarray/issues/731,175905067,MDEyOklzc3VlQ29tbWVudDE3NTkwNTA2Nw==,15167171,2016-01-27T23:07:37Z,2016-01-27T23:07:37Z,NONE,"It seems in both unsuccesful cases it was trying to import dask and failed, I can't quite figure out what I could have changed to prevent dask from importing:
```
> da = da.chunk()
xarray/test/test_dataarray.py:1618:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xarray/core/dataarray.py:569: in chunk
ds = self._to_temp_dataset().chunk(chunks)
```
```
try:
from dask.base import tokenize
except ImportError:
> import dask # raise the usual error if dask is entirely missing
E ImportError: No module named 'dask'
```
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