Ensures drop=True case works with empty mask (#1342)

* Added test for where(mask, drop=True) [mask empty]

Ensures ds.where(mask, drop=True) works when the mask
is empty.

* Fix .get_index() for size 0 dimensions

This resolves issues with `where` with
`drop=True` with empty mask.

doc/whats-new.rst

@@ -51,6 +51,9 @@ Bug fixes
 - Fix ``sel`` with ``method='nearest'`` on Python 2.7 and 64-bit Windows
   (:issue:`1140`).
   `Stephan Hoyer <https://github.com/shoyer>`_.
+- Fixes ``where`` with ``drop='True'`` for empty masks (:issue:`1341`).
+  By `Stephan Hoyer <https://github.com/shoyer>`_ and
+  `Phillip J. Wolfram <https://github.com/pwolfram>`_.
 
 .. _whats-new.0.9.1:
 

xarray/core/common.py

@@ -243,7 +243,8 @@ def get_index(self, key):
         try:
             return self.indexes[key]
         except KeyError:
-            return pd.Index(range(self.sizes[key]), name=key)
+            # need to ensure dtype=int64 in case range is empty on Python 2
+            return pd.Index(range(self.sizes[key]), name=key, dtype=np.int64)
 
     def _calc_assign_results(self, kwargs):
         results = SortedKeysDict()

xarray/tests/test_dataarray.py

@@ -106,6 +106,13 @@ def test_get_index(self):
         with self.assertRaises(KeyError):
             array.get_index('z')
 
+    def test_get_index_size_zero(self):
+        array = DataArray(np.zeros((0,)), dims=['x'])
+        actual = array.get_index('x')
+        expected = pd.Index([], dtype=np.int64)
+        assert actual.equals(expected)
+        assert actual.dtype == expected.dtype
+
     def test_struct_array_dims(self):
         """
         This test checks subraction of two DataArrays for the case

xarray/tests/test_dataset.py

@@ -2659,6 +2659,15 @@ def test_where_drop(self):
         actual = ds.where(ds > 0, drop=True)
         self.assertDatasetIdentical(expected, actual)
 
+    def test_where_drop_empty(self):
+        # regression test for GH1341
+        array = DataArray(np.random.rand(100, 10),
+                          dims=['nCells', 'nVertLevels'])
+        mask = DataArray(np.zeros((100,), dtype='bool'), dims='nCells')
+        actual = array.where(mask, drop=True)
+        expected = DataArray(np.zeros((0, 10)), dims=['nCells', 'nVertLevels'])
+        self.assertDatasetIdentical(expected, actual)
+
     def test_reduce(self):
         data = create_test_data()