Fix/dask isnull

doc/whats-new.rst

@@ -167,6 +167,9 @@ Bug fixes
   match pandas (:issue:`1847`). A combination of strings/numbers or
   unicode/bytes now promote to object dtype, instead of strings or unicode.
   By `Stephan Hoyer <https://github.com/shoyer>`_.
+  - Fixed bug where :py:meth:`~xarray.DataArray.isnull` was loading data
+  stored as dask arrays (:issue:`1937`).
+  By `Joe Hamman <https://github.com/jhamman>`_.
 
 .. _whats-new.0.10.0:
 

xarray/core/ops.py

@@ -12,7 +12,6 @@
 import operator
 
 import numpy as np
-import pandas as pd
 
 from . import dtypes
 from . import duck_array_ops
@@ -320,7 +319,8 @@ def inject_all_ops_and_reduce_methods(cls, priority=50, array_only=True):
         setattr(cls, name, cls._unary_op(_method_wrapper(name)))
 
     for name in PANDAS_UNARY_FUNCTIONS:
-        f = _func_slash_method_wrapper(getattr(pd, name), name=name)
+        f = _func_slash_method_wrapper(
+            getattr(duck_array_ops, name), name=name)
         setattr(cls, name, cls._unary_op(f))
 
     f = _func_slash_method_wrapper(duck_array_ops.around, name='round')

xarray/tests/test_duck_array_ops.py

@@ -9,11 +9,12 @@
 from xarray.core.duck_array_ops import (
     first, last, count, mean, array_notnull_equiv, where, stack, concatenate
 )
+from xarray.core.pycompat import dask_array_type
 from xarray import DataArray
-from xarray.testing import assert_allclose
+from xarray.testing import assert_allclose, assert_equal
 from xarray import concat
 
-from . import TestCase, raises_regex, has_dask
+from . import TestCase, raises_regex, has_dask, requires_dask
 
 
 class TestOps(TestCase):
@@ -194,23 +195,19 @@ def series_reduce(da, func, dim, **kwargs):
 def test_reduce(dim_num, dtype, dask, func, skipna, aggdim):
 
     if aggdim == 'y' and dim_num < 2:
-        return
+        pytest.skip('dim not in this test')
 
     if dtype == np.bool_ and func == 'mean':
-        return  # numpy does not support this
+        pytest.skip('numpy does not support this')
 
     if dask and not has_dask:
-        return
+        pytest.skip('requires dask')
 
     rtol = 1e-04 if dtype == np.float32 else 1e-05
 
     da = construct_dataarray(dim_num, dtype, contains_nan=True, dask=dask)
     axis = None if aggdim is None else da.get_axis_num(aggdim)
 
-    if dask and not skipna and func in ['var', 'std'] and dtype == np.bool_:
-        # TODO this might be dask's bug
-        return
-
     if (LooseVersion(np.__version__) >= LooseVersion('1.13.0') and
             da.dtype.kind == 'O' and skipna):
         # Numpy < 1.13 does not handle object-type array.
@@ -269,19 +266,17 @@ def test_argmin_max(dim_num, dtype, contains_nan, dask, func, skipna, aggdim):
     # just make sure da[da.argmin()] == da.min()
 
     if aggdim == 'y' and dim_num < 2:
-        return
+        pytest.skip('dim not in this test')
 
     if dask and not has_dask:
-        return
+        pytest.skip('requires dask')
 
     if contains_nan:
         if not skipna:
-            # numpy's argmin (not nanargmin) does not handle object-dtype
-            return
+            pytest.skip("numpy's argmin (not nanargmin) does not handle "
+                        "object-dtype")
         if skipna and np.dtype(dtype).kind in 'iufc':
-            # numpy's nanargmin raises ValueError for all nan axis
-            return
-
+            pytest.skip("numpy's nanargmin raises ValueError for all nan axis")
     da = construct_dataarray(dim_num, dtype, contains_nan=contains_nan,
                              dask=dask)
 
@@ -302,3 +297,10 @@ def test_argmin_max_error():
     da = construct_dataarray(2, np.bool_, contains_nan=True, dask=False)
     with pytest.raises(ValueError):
         da.argmin(dim='y')
+
+
+@requires_dask
+def test_isnull_with_dask():
+    da = construct_dataarray(2, np.float32, contains_nan=True, dask=True)
+    assert isinstance(da.isnull().data, dask_array_type)
+    assert_equal(da.isnull().load(), da.load().isnull())