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/3936#issuecomment-651317938,https://api.github.com/repos/pydata/xarray/issues/3936,651317938,MDEyOklzc3VlQ29tbWVudDY1MTMxNzkzOA==,2448579,2020-06-29T19:36:28Z,2020-06-29T19:36:28Z,MEMBER,Thanks @johnomotani . This is a significant contribution.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-650297994,https://api.github.com/repos/pydata/xarray/issues/3936,650297994,MDEyOklzc3VlQ29tbWVudDY1MDI5Nzk5NA==,14808389,2020-06-26T17:19:34Z,2020-06-26T17:19:34Z,MEMBER,"well, we'd need to somehow be able to use `sel` to index every variable in a `Dataset` differently. While that would probably be possible it would make `sel` way too complicated, so I agree that an error would be good here.

I think no further changes to the `pint` tests should be required (except refactoring, but I can do that in a new PR after this one has been merged).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-650221609,https://api.github.com/repos/pydata/xarray/issues/3936,650221609,MDEyOklzc3VlQ29tbWVudDY1MDIyMTYwOQ==,14808389,2020-06-26T14:51:51Z,2020-06-26T14:51:51Z,MEMBER,"I noticed a few issues while debugging:
- calling on a array with missing values raises `ValueError: All-NaN slice encountered` (try `ds = xr.tutorial.open_dataset(""rasm""); ds.argmin(dim=""y"")`)
- `ds.argmin(dim=...)` returns a single index (the same result as `ds.argmin()`) but `ds.Tair.argmin(dim=...)` returns something different from `ds.Tair.argmin()`. Is that intentional?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-649204113,https://api.github.com/repos/pydata/xarray/issues/3936,649204113,MDEyOklzc3VlQ29tbWVudDY0OTIwNDExMw==,1217238,2020-06-25T04:10:50Z,2020-06-25T04:10:50Z,MEMBER,"I'm going to wait a little while before merging in case anyone else has comment, but otherwise will merge in a day or two (definitely before the next release)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-617381475,https://api.github.com/repos/pydata/xarray/issues/3936,617381475,MDEyOklzc3VlQ29tbWVudDYxNzM4MTQ3NQ==,14808389,2020-04-21T19:57:27Z,2020-04-21T20:48:41Z,MEMBER,"you could mark the `function(""argmin"")` / `function(""argmax"")` with `xfail` (or `skip`?). We can decide on what to do with them when we close #3917","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-617002459,https://api.github.com/repos/pydata/xarray/issues/3936,617002459,MDEyOklzc3VlQ29tbWVudDYxNzAwMjQ1OQ==,1217238,2020-04-21T07:23:11Z,2020-04-21T07:23:27Z,MEMBER,"I notice that some of your new deprecation warnings get issued when running your tests. Please silence these methods, e.g., using `pytest.mark.filterwarnings`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-616998622,https://api.github.com/repos/pydata/xarray/issues/3936,616998622,MDEyOklzc3VlQ29tbWVudDYxNjk5ODYyMg==,1217238,2020-04-21T07:14:10Z,2020-04-21T07:14:10Z,MEMBER,"> I eventually found that the cause of the errors I was getting was that the `argmin` and `argmax` methods did not have an `out` argument. In order for the methods to be wrapped by `numpy` (and I guess `dask` is the same), the call signature of `np.argmin()` has to be supported, which means `axis` and `out` arguments are needed.

I guess this would happen if somebody calls `np.argmin(xarray_object)`? Does this happen from inside xarray somewhere, or in external code?

If it's the former, then we should just fix xarray not to do this. If it's only in external code, I would still consider breaking this behavior.

The override mechanism that NumPy uses in argmin/argmax is really old/fragile, and it's not something we ever intended to support. There's no way we could write an `argmin`/`argmax` method with an incompatible signature that would work with these functions.

The better way to do overrides in NumPy is probably with `__array_function__` now, but I'm not sure we want the trouble...","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-610516784,https://api.github.com/repos/pydata/xarray/issues/3936,610516784,MDEyOklzc3VlQ29tbWVudDYxMDUxNjc4NA==,1217238,2020-04-07T17:23:24Z,2020-04-07T17:23:24Z,MEMBER,"Also, feel free to rewrite to avoid using inject_all_ops_and_reduce_methods() for argmin/argmax at all. Method injection is pretty hacky, and generally not worthwhile, e.g., see [this note](https://github.com/pydata/xarray/blob/c97e7998b69c5b41e863dfb0a43450491fb8de45/xarray/core/ops.py#L3) about removing it.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609607223,https://api.github.com/repos/pydata/xarray/issues/3936,609607223,MDEyOklzc3VlQ29tbWVudDYwOTYwNzIyMw==,5821660,2020-04-06T07:13:00Z,2020-04-06T07:13:00Z,MEMBER,@johnomotani FYI: For #3871 (merged) there is #3922 (yet unmerged) to fix dask-handling. ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609605888,https://api.github.com/repos/pydata/xarray/issues/3936,609605888,MDEyOklzc3VlQ29tbWVudDYwOTYwNTg4OA==,5821660,2020-04-06T07:09:45Z,2020-04-06T07:09:45Z,MEMBER,"> > reduce over all given dimensions?
> 
> By this do you mean find the minimum as if the array were first (partially or totally) flattened along the given dims somehow? I'm not sure we provide that kind of behaviour anywhere in the current API.

@TomNicholas Probably I was bit confused by the current docstring. I think I understand now and there should be no problem at all.
","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609598095,https://api.github.com/repos/pydata/xarray/issues/3936,609598095,MDEyOklzc3VlQ29tbWVudDYwOTU5ODA5NQ==,35968931,2020-04-06T06:49:18Z,2020-04-06T06:49:18Z,MEMBER,"> how should we discern (at least for argmin/argmax), if the user wants to...

That's a good question @kmuehlbauer, and the distinction probably needs to be clearer in the docs in general.

> reduce over all given dimensions?

By this do you mean find the minimum as if the array were first (partially or totally) flattened along the given dims somehow? I'm not sure we provide that kind of behaviour anywhere in the current API.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609591692,https://api.github.com/repos/pydata/xarray/issues/3936,609591692,MDEyOklzc3VlQ29tbWVudDYwOTU5MTY5Mg==,5821660,2020-04-06T06:31:12Z,2020-04-06T06:31:22Z,MEMBER,"+1 for making `argmin`/`argmax` (and `idxmin`/`idxmax`) work, when given multiple dimensions.

According to the current docstring it should already work that way for `argmin`/'argmax`:

**Reduce this DataArray’s data by applying argmin along some dimension(s).**

**Returns: New DataArray/Dataset object with `argmin` applied to it's data and the indicated dimension(s) removed**

But this behaviour is broken currently (works only for one given dim).

My main concern for changing the API as suggested above is, how should we discern (at least for `argmin`/`argmax`), if the user want's to:

1. reduce **over all** given dimensions? (current behaviour according to docstring)
2. reduce **along all** given dimensions? (suggested behaviour by @johnomotani [please correct if I'm wrong])","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609488771,https://api.github.com/repos/pydata/xarray/issues/3936,609488771,MDEyOklzc3VlQ29tbWVudDYwOTQ4ODc3MQ==,35968931,2020-04-05T21:39:19Z,2020-04-05T21:39:19Z,MEMBER,"> Another option would be to overload `argmin`

+1 for overloading `argmin` (and later `idxmin`). IMO we should never have one function for a 1D operation and one for an N-D operation if we can avoid it, everything should be N-dimensional.

I also really like how neat this resultant property is
```python
da.isel(da.argmin(list_of_dim)) == da.min(list_of_dim)
```
we could even use a [hypothesis](https://github.com/HypothesisWorks/hypothesis) test to check it...

> I think returning a dict of indices would be much more useful, but it does change existing behaviour (more useful because you can then do da.isel(da.argmin())).

Although it's breaking and would require a deprecation cycle, I think this is what we should aim for.

> there's a not-very-helpful exception

Yes let's take the time to make that clearer for users - this will be a commonly-used function.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646
https://github.com/pydata/xarray/pull/3936#issuecomment-609468040,https://api.github.com/repos/pydata/xarray/issues/3936,609468040,MDEyOklzc3VlQ29tbWVudDYwOTQ2ODA0MA==,1217238,2020-04-05T19:19:41Z,2020-04-05T19:19:41Z,MEMBER,"This looks really comprehensive, thank you!

Before doing a really careful review here, I'd like to try to work out the full API design we want. I'll write out some of my thoughts here, but your thoughts would also be very welcome!

Here's my summary of the current situation:
1. We have two pairs of methods, `argmin`/`argmax` and the new `idxmin`/`idxmax` for calculating integer positions or coordinate labels of the minimum/maximum along _one_ dimension.
2. We would like to have a way to do a similar calculation in multiple dimensions, which should return a dictionary of DataArray objects suitable for feeding into `isel`/`sel`.

This PR implements the multidimensional equivalent of `argmin`/`argmax`. It's fine to save the multidimensional equivalent of `idxmin`/`idxmax` for later, but we'll want to copy whatever design we pick here.

My first concern is about the name: it isn't obvious to me whether `indices_min` refers to integer positions or coordinate labels. I think a name based on `argmin`/`argmax` could help, e.g., perhaps `argmin_nd` or `argmin_dict`.

Another option would be to overload `argmin`/`argmax` to _also_ support return a dictionary, depending on the type of the arguments. If you pass a `list` of dimensions over which to calculate the min or max locations, you would get a dictionary back:
- `array.argmin('x')` would return a single `DataArray`
- `array.argmin(['x', 'y'])` would return a dict of `DataArray` objects with keys `{'x', 'y'}`
- `array.argmin(['x'])` would also return a dict `{'x': ...}`

I think I like this last option best but I would be curious what others think! @pydata/xarray any thoughts on this?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,594594646