issue_comments

Third and final issue is when numpy.broadcast_to is applied to the output of zeros_like: ```

import sparse s = sparse.COO.from_numpy([0, 0, 1, 2]) np.broadcast_to(np.zeros_like(s.todense(), shape=()), (3, )) array([0, 0, 0]) np.broadcast_to(np.zeros_like(s, shape=()), (3, )) ValueError: The data length does not match the coordinates given. len(data) = 0, but 3 coords specified. ```

Ah, shape= was very recently added in 0.12.0. It wasn't there in 0.11.2.

[EDIT] It is not the only problem. Investigating further.

The second issue is that sparse.zeros_like doesn't accept the order= parameter, which is required by the same dask code linked above (it's in the kwargs in dask/wrap.py:133). This in turn triggers an unfortunate handling of TypeError on behalf of @curry, which obfuscates the exception.

da.zeros_like(a) internally invokes da.zeros(a.shape, meta=a._meta) which internally invokes np.broadcast(np.zeros_like(a._meta, shape=1), a.shape)

The problem is that sparse.zeros_like does not accept the shape= optional parameter, which is new in numpy 1.17.

This is where it gets triggered: https://github.com/dask/dask/blob/85f0b14bd36a5135ce51aeee067b6207374b00c4/dask/array/wrap.py#L128-L168

I don't think dask should write a workaround to this, and it should be just fixed upstream? CC @jrbourbeau for opinion.

Narrowed it down.

```python

import dask.array as da import sparse s = sparse.COO.from_numpy([0, 0, 1, 2]) a = da.from_array(s) z = da.zeros_like(a) z dask.array<zeros_like, shape=(4,), dtype=int64, chunksize=(4,), chunktype=sparse.COO> z.compute() <function _broadcast_trick_inner at 0x7fb8a3874e50> ``` numpy-1.20.1 dask-2021.3.0 sparse-0.11.2

I see now. I got really confused by the matplotlib issue which is what the opening post of this ticket is about. Would it be possible to have the two issues tracked by separate tickets?

I'm a bit lost. The failure in xarray/tests/test_sparse.py::test_chunk doesn't appear anywhere in recent CI runs and I can't reproduce it locally.

The ongoing failures in upstream-dev: FAILED xarray/tests/test_plot.py::TestFacetGrid::test_can_set_norm FAILED xarray/tests/test_plot.py::TestCFDatetimePlot::test_cfdatetime_line_plot FAILED xarray/tests/test_plot.py::TestCFDatetimePlot::test_cfdatetime_pcolormesh_plot FAILED xarray/tests/test_plot.py::TestCFDatetimePlot::test_cfdatetime_contour_plot Aren't in any way related to either sparse or dask; they appear when I upgrade matplotlib from 3.4.3 to 3.5.0b1.