add an option to switch on the support for subclasses

xarray/core/options.py

@@ -8,6 +8,7 @@
 CMAP_SEQUENTIAL = 'cmap_sequential'
 CMAP_DIVERGENT = 'cmap_divergent'
 KEEP_ATTRS = 'keep_attrs'
+ENABLE_EXPERIMENTAL_NDARRAY_SUBCLASS_SUPPORT = 'enable_experimental_ndarray_subclass_support'
 
 
 OPTIONS = {
@@ -18,7 +19,8 @@
     WARN_FOR_UNCLOSED_FILES: False,
     CMAP_SEQUENTIAL: 'viridis',
     CMAP_DIVERGENT: 'RdBu_r',
-    KEEP_ATTRS: 'default'
+    KEEP_ATTRS: 'default',
+    ENABLE_EXPERIMENTAL_NDARRAY_SUBCLASS_SUPPORT: False,
 }
 
 _JOIN_OPTIONS = frozenset(['inner', 'outer', 'left', 'right', 'exact'])
@@ -34,7 +36,8 @@ def _positive_integer(value):
     ENABLE_CFTIMEINDEX: lambda value: isinstance(value, bool),
     FILE_CACHE_MAXSIZE: _positive_integer,
     WARN_FOR_UNCLOSED_FILES: lambda value: isinstance(value, bool),
-    KEEP_ATTRS: lambda choice: choice in [True, False, 'default']
+    KEEP_ATTRS: lambda choice: choice in [True, False, 'default'],
+    ENABLE_EXPERIMENTAL_NDARRAY_SUBCLASS_SUPPORT: lambda value: isinstance(value, bool),
 }
 
 
@@ -96,6 +99,9 @@ class set_options:
       attrs, ``False`` to always discard them, or ``'default'`` to use original
       logic that attrs should only be kept in unambiguous circumstances.
       Default: ``'default'``.
+    - ``enable_experimental_ndarray_subclass_support``: whether or not
+      to enable the support for subclasses of numpy's ndarray.
+      Default: ``False``.
 
     You can use ``set_options`` either as a context manager:
 

xarray/core/variable.py

@@ -14,7 +14,7 @@
 from .indexing import (
     BasicIndexer, OuterIndexer, PandasIndexAdapter, VectorizedIndexer,
     as_indexable)
-from .options import _get_keep_attrs
+from .options import _get_keep_attrs, OPTIONS
 from .pycompat import TYPE_CHECKING, dask_array_type, integer_types
 from .utils import (
     OrderedSet, decode_numpy_dict_values, either_dict_or_kwargs,
@@ -183,7 +183,10 @@ def as_compatible_data(data, fastpath=False):
             data = np.asarray(data)
 
     # validate whether the data is valid data types
-    data = np.asanyarray(data)
+    if OPTIONS["enable_experimental_ndarray_subclass_support"]:
+        data = np.asanyarray(data)
+    else:
+        data = np.asarray(data)
 
     if isinstance(data, np.ndarray):
         if data.dtype.kind == 'O':
@@ -308,8 +311,10 @@ def _in_memory(self):
     def data(self):
         if isinstance(self._data, dask_array_type):
             return self._data
-        else:
+        elif OPTIONS["enable_experimental_ndarray_subclass_support"]:
             return _as_any_array_or_item(self._data)
+        else:
+            return self.values
 
     @data.setter
     def data(self, data):

xarray/tests/test_quantities.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from xarray import DataArray
+from xarray import DataArray, set_options
 
 try:
     import quantities as pq
@@ -15,6 +15,9 @@
 )
 
 
+set_options(enable_experimental_ndarray_subclass_support=True)
+
+
 def assert_equal_with_units(a, b):
     a = a if not isinstance(a, DataArray) else a.data
     b = b if not isinstance(b, DataArray) else b.data
@@ -69,6 +72,12 @@ def with_keys(mapping, keys):
     }
 
 
+def test_without_subclass_support():
+    with set_options(enable_experimental_ndarray_subclass_support=False):
+        data_array = create_data_array()
+        assert not hasattr(data_array.data, "units")
+
+
 def test_units_in_data_and_coords():
     data_array = create_data_array()