issues: 277441150

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
277441150 MDU6SXNzdWUyNzc0NDExNTA= 1743 Assigning data to vector-indexed data doesn't seem to work 167802 closed 0     4 2017-11-28T16:06:56Z 2022-02-23T12:23:42Z 2017-12-09T03:29:35Z CONTRIBUTOR      

Code Sample

```python import xarray as xr import numpy as np import dask.array as da

arr = np.arange(25).reshape((5, 5))

l_indices = xr.DataArray(np.array(((0, 1), (2, 3))), dims=['lines', 'cols']) c_indices = xr.DataArray(np.array(((1, 3), (0, 2))), dims=['lines', 'cols'])

xarr = xr.DataArray(da.from_array(arr, chunks=10), dims=['y', 'x'])

print(xarr[l_indices, c_indices])

xarr[l_indices, c_indices] = 2 ```

Problem description

This crashes on the last line with a IndexError: Unlabeled multi-dimensional array cannot be used for indexing: [[0 1] [2 3]] I'm expecting to be able to do assignment this way, and it doesn't work.

Expected Output

Expected output is the modified array with 2's in the indicated positions

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 2.7.5.final.0 python-bits: 64 OS: Linux OS-release: 3.10.0-693.2.2.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: None.None xarray: 0.10.0 pandas: 0.21.0 numpy: 1.13.3 scipy: 0.18.1 netCDF4: 1.1.8 h5netcdf: 0.4.2 Nio: None bottleneck: None cyordereddict: None dask: 0.15.4 matplotlib: 1.2.0 cartopy: None seaborn: None setuptools: 36.2.1 pip: 9.0.1 conda: None pytest: 3.1.3 IPython: 5.1.0 sphinx: 1.3.6 
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   completed 13221727 issue

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