Fix optimize for chunked DataArray (#4432)

Previously we generated in invalidate Dask task graph, becuase the lines
removed here dropped keys that were referenced elsewhere in the task
graph. The original implementation had a
comment indicating that this was to cull:
https://github.com/pydata/xarray/blame/502a988ad5b87b9f3aeec3033bf55c71272e1053/xarray/core/variable.py#L384

Just spot-checking things, I think we're OK here though. Something like
`dask.visualize(arr[[0]], optimize_graph=True)` indicates that we're OK.

Closes #3698

Co-authored-by: Maximilian Roos <[email protected]>

Author: TomAugspurger

doc/whats-new.rst

@@ -84,11 +84,13 @@ Bug fixes
 - Fix `KeyError` when doing linear interpolation to an nd `DataArray`
   that contains NaNs (:pull:`4233`).
   By `Jens Svensmark <https://github.com/jenssss>`_
+- Fix ``dask.optimize`` on ``DataArray`` producing an invalid Dask task graph (:issue:`3698`)
 - Fix incorrect legend labels for :py:meth:`Dataset.plot.scatter` (:issue:`4126`).
   By `Peter Hausamann <https://github.com/phausamann>`_.
 - Fix indexing with datetime64 scalars with pandas 1.1 (:issue:`4283`).
   By `Stephan Hoyer <https://github.com/shoyer>`_ and
   `Justus Magin <https://github.com/keewis>`_.
+  
 
 Documentation
 ~~~~~~~~~~~~~

xarray/core/variable.py

@@ -501,9 +501,6 @@ def __dask_postpersist__(self):
 
     @staticmethod
     def _dask_finalize(results, array_func, array_args, dims, attrs, encoding):
-        if isinstance(results, dict):  # persist case
-            name = array_args[0]
-            results = {k: v for k, v in results.items() if k[0] == name}
         data = array_func(results, *array_args)
         return Variable(dims, data, attrs=attrs, encoding=encoding)
 

xarray/tests/test_dask.py

@@ -1607,3 +1607,10 @@ def test_more_transforms_pass_lazy_array_equiv(map_da, map_ds):
         assert_equal(map_da._from_temp_dataset(map_da._to_temp_dataset()), map_da)
         assert_equal(map_da.astype(map_da.dtype), map_da)
         assert_equal(map_da.transpose("y", "x", transpose_coords=False).cxy, map_da.cxy)
+
+
+def test_optimize():
+    a = dask.array.ones((10, 5), chunks=(1, 3))
+    arr = xr.DataArray(a).chunk(5)
+    (arr2,) = dask.optimize(arr)
+    arr2.compute()