issue_comments

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)

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.

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...

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 about removing it.

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?