issue_comments

The missing operation here in sparse is indexing like x[y, z] where y and z are both arrays.

For reference, here's the traceback: ```

IndexError Traceback (most recent call last) <ipython-input-1-6547fa3d1500> in <module>() 17 'time':time}).to_dataset() 18 ---> 19 dataset1 = xr.merge([data_array1,data_array2])

9 frames /usr/local/lib/python3.6/dist-packages/xarray/core/merge.py in merge(objects, compat, join, fill_value) 780 dict_like_objects.append(obj) 781 --> 782 merge_result = merge_core(dict_like_objects, compat, join, fill_value=fill_value) 783 merged = Dataset._construct_direct(**merge_result._asdict()) 784 return merged

/usr/local/lib/python3.6/dist-packages/xarray/core/merge.py in merge_core(objects, compat, join, priority_arg, explicit_coords, indexes, fill_value) 537 coerced = coerce_pandas_values(objects) 538 aligned = deep_align( --> 539 coerced, join=join, copy=False, indexes=indexes, fill_value=fill_value 540 ) 541 collected = collect_variables_and_indexes(aligned)

/usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in deep_align(objects, join, copy, indexes, exclude, raise_on_invalid, fill_value) 403 indexes=indexes, 404 exclude=exclude, --> 405 fill_value=fill_value 406 ) 407

/usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in align(join, copy, indexes, exclude, fill_value, objects) 331 new_obj = obj.copy(deep=copy) 332 else: --> 333 new_obj = obj.reindex(copy=copy, fill_value=fill_value, *valid_indexers) 334 new_obj.encoding = obj.encoding 335 result.append(new_obj)

/usr/local/lib/python3.6/dist-packages/xarray/core/dataset.py in reindex(self, indexers, method, tolerance, copy, fill_value, **indexers_kwargs) 2430 tolerance, 2431 copy=copy, -> 2432 fill_value=fill_value, 2433 ) 2434 coord_names = set(self._coord_names)

/usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in reindex_variables(variables, sizes, indexes, indexers, method, tolerance, copy, fill_value) 581 582 if needs_masking: --> 583 new_var = var._getitem_with_mask(key, fill_value=fill_value) 584 elif all(is_full_slice(k) for k in key): 585 # no reindexing necessary

/usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in _getitem_with_mask(self, key, fill_value) 724 actual_indexer = indexer 725 --> 726 data = as_indexable(self._data)[actual_indexer] 727 mask = indexing.create_mask(indexer, self.shape, data) 728 data = duck_array_ops.where(mask, fill_value, data)

/usr/local/lib/python3.6/dist-packages/xarray/core/indexing.py in getitem(self, key) 1260 def getitem(self, key): 1261 array, key = self._indexing_array_and_key(key) -> 1262 return array[key] 1263 1264 def setitem(self, key, value):

/usr/local/lib/python3.6/dist-packages/sparse/_coo/indexing.py in getitem(x, index) 66 67 # Get the mask ---> 68 mask, adv_idx = _mask(x.coords, index, x.shape) 69 70 # Get the length of the mask

/usr/local/lib/python3.6/dist-packages/sparse/_coo/indexing.py in _mask(coords, indices, shape) 129 if len(adv_idx) != 0: 130 if len(adv_idx) != 1: --> 131 raise IndexError('Only indices with at most one iterable index are supported.') 132 133 adv_idx = adv_idx[0]

IndexError: Only indices with at most one iterable index are supported. ```

@El-minadero from the sparse API page I'm seeing two methods for combining data:

```python import sparse import numpy as np

A = sparse.COO.from_numpy(np.array([[1, 2], [3, 4]])) B = sparse.COO.from_numpy(np.array([[5, 9], [6, 8]])) sparse.stack([A,B]).todense()

Out[1]: array([[[1, 2], [3, 4]], [[5, 9], [6, 8]]])

sparse.concatenate([A,B]).todense()

Out[2]: array([[1, 2], [3, 4], [5, 9], [6, 8]]) `` Since this is an issue withsparse` and merging data doesn't seem to be supported at this time, you might consider closing this issue out here and raising it over at sparse.

Note that dataset1 = xr.concat([data_array1,data_array2],dim='source') or dim='receiver' seem to work, however, concat also fails if time is specified as the dimension.