groupby doesn't work when a dimension is resized as part of apply

[shoyer]

In [60]: da = xarray.DataArray([1, 2, 3], dims='x', coords={'y': ('x', [1, 1, 1])})

In [61]: da.groupby('y').apply(lambda x: x[:2])
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-61-4c28a4712c34> in <module>()
----> 1 da.groupby('y').apply(lambda x: x[:2])

~/dev/xarray/xarray/core/groupby.py in apply(self, func, shortcut, **kwargs)
    516         applied = (maybe_wrap_array(arr, func(arr, **kwargs))
    517                    for arr in grouped)
--> 518         return self._combine(applied, shortcut=shortcut)
    519
    520     def _combine(self, applied, shortcut=False):

~/dev/xarray/xarray/core/groupby.py in _combine(self, applied, shortcut)
    526         else:
    527             combined = concat(applied, dim)
--> 528             combined = _maybe_reorder(combined, dim, positions)
    529
    530         if isinstance(combined, type(self._obj)):

~/dev/xarray/xarray/core/groupby.py in _maybe_reorder(xarray_obj, dim, positions)
    436         return xarray_obj
    437     else:
--> 438         return xarray_obj[{dim: order}]
    439
    440

~/dev/xarray/xarray/core/dataarray.py in __getitem__(self, key)
    476         else:
    477             # orthogonal array indexing
--> 478             return self.isel(**self._item_key_to_dict(key))
    479
    480     def __setitem__(self, key, value):

~/dev/xarray/xarray/core/dataarray.py in isel(self, drop, **indexers)
    710         DataArray.sel
    711         """
--> 712         ds = self._to_temp_dataset().isel(drop=drop, **indexers)
    713         return self._from_temp_dataset(ds)
    714

~/dev/xarray/xarray/core/dataset.py in isel(self, drop, **indexers)
   1172         for name, var in iteritems(self._variables):
   1173             var_indexers = dict((k, v) for k, v in indexers if k in var.dims)
-> 1174             new_var = var.isel(**var_indexers)
   1175             if not (drop and name in var_indexers):
   1176                 variables[name] = new_var

~/dev/xarray/xarray/core/variable.py in isel(self, **indexers)
    596             if dim in indexers:
    597                 key[i] = indexers[dim]
--> 598         return self[tuple(key)]
    599
    600     def squeeze(self, dim=None):

~/dev/xarray/xarray/core/variable.py in __getitem__(self, key)
    426         dims = tuple(dim for k, dim in zip(key, self.dims)
    427                      if not isinstance(k, integer_types))
--> 428         values = self._indexable_data[key]
    429         # orthogonal indexing should ensure the dimensionality is consistent
    430         if hasattr(values, 'ndim'):

~/dev/xarray/xarray/core/indexing.py in __getitem__(self, key)
    476     def __getitem__(self, key):
    477         key = self._convert_key(key)
--> 478         return self._ensure_ndarray(self.array[key])
    479
    480     def __setitem__(self, key, value):

IndexError: index 2 is out of bounds for axis 1 with size 2

This would be useful, for example, for grouped sampling:
https://stackoverflow.com/questions/46498247/how-to-downsample-xarray-dataset-using-groupby

To fix this, we will need to update our heuristics that decide if a groupby operation is a "transform" type operation that should have the output reordered to the original order:

xarray/xarray/core/groupby.py

Lines 293 to 299 in 24643ec

	def _infer_concat_args(self, applied_example):
	if self._group_dim in applied_example.dims:
	coord = self._group
	positions = self._group_indices
	else:
	coord = self._unique_coord
	positions = None

[dcherian]

Fixed by #3807