issue_comments: 451786609

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https://github.com/pydata/xarray/pull/2616#issuecomment-451786609 https://api.github.com/repos/pydata/xarray/issues/2616 451786609 MDEyOklzc3VlQ29tbWVudDQ1MTc4NjYwOQ== 35968931 2019-01-06T23:43:57Z 2019-01-07T01:09:53Z MEMBER

Okay so this is mostly done - I've completely rearranged the tests and they pass on my unmerged branch, there are just a few TODOs left.

~~However, when I tried to merge master in then everything failed again due to #2648, I don't understand what ReprObject does?~~ (Fixed with bfch4e3)

Some other questions:

1) We didn't decide whether the ability to infer concatenation dimensions (i.e. when concat_dim='_CONCAT_DIM_DEFAULT') should be retained or not. I'm not sure we need it at all any more - you're either using auto_combine, which will concatenate dimension coordinates and leave other dimensions alone, or you're using manual_combine, in which you're supposed to explicitly state all the dimensions you wish to concatenate along anyway. I think this is also related to a bug I don't properly understand (marked with an xfail in test_manual_concat_too_many_dims_at_once).

2) Ordering the datasets along one dimension according to the values in their dimension coordinates (done in _infer_order_1d) turned out to be a bit more complicated than I thought. Is the method using a Pandas.Series okay? Do we want to use natural sorting on strings? How should I deal with datetime objects? I also think it's probably easier to check that the coords can actually be arranged to be monotonic after all the concatenation has been done, not before.

3) Some input which previously wouldn't be valid now is (see the TODO in line 538 of test_combine.py), is that the desired behaviour in that case?

 
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