use keep_attrs in binary operations II

doc/whats-new.rst

@@ -40,6 +40,7 @@ Enhancements
   :py:class:`pandas.DatetimeIndex`), which avoids unnecessary copies.
   By `Stephan Hoyer <https://github.com/shoyer>`_
 
+
 Bug fixes
 ~~~~~~~~~
 
@@ -150,7 +151,9 @@ Enhancements
   to returning (and is now deprecated). This was changed in order to facilitate
   using tutorial datasets with dask.
   By `Joe Hamman <https://github.com/jhamman>`_.
-
+- ``DataArray`` can now use ``xr.set_option(keep_attrs=True)`` and retain attributes in binary operations, 
+  such as (``+, -, * ,/``). Default behaviour is unchanged (*Attributes will be dismissed*). By `Michael Blaschek <https://github.com/MBlaschek>`_
+
 Bug fixes
 ~~~~~~~~~
 

xarray/core/variable.py

@@ -1658,11 +1658,13 @@ def func(self, other):
             if isinstance(other, (xr.DataArray, xr.Dataset)):
                 return NotImplemented
             self_data, other_data, dims = _broadcast_compat_data(self, other)
+            keep_attrs = _get_keep_attrs(default=False)
+            attrs = self._attrs if keep_attrs else None
             with np.errstate(all='ignore'):
                 new_data = (f(self_data, other_data)
                             if not reflexive
                             else f(other_data, self_data))
-            result = Variable(dims, new_data)
+            result = Variable(dims, new_data, attrs=attrs)
             return result
         return func
 

xarray/tests/test_variable.py

@@ -28,6 +28,8 @@
     assert_allclose, assert_array_equal, assert_equal, assert_identical,
     raises_regex, requires_dask, source_ndarray)
 
+from xarray import set_options
+
 
 class VariableSubclassobjects(object):
     def test_properties(self):
@@ -1545,6 +1547,18 @@ def test_reduce_keep_attrs(self):
         assert len(vm.attrs) == len(_attrs)
         assert vm.attrs == _attrs
 
+    def test_binary_ops_keep_attrs(self):
+        _attrs = {'units': 'test', 'long_name': 'testing'}
+        a = Variable(['x', 'y'], np.random.randn(3, 3), _attrs)
+        b = Variable(['x', 'y'], np.random.randn(3, 3), _attrs)
+        # Test dropped attrs
+        d = a - b   # just one operation
+        assert d.attrs == OrderedDict()
+        # Test kept attrs
+        with set_options(keep_attrs=True):
+            d = a - b
+        assert d.attrs == _attrs
+
     def test_count(self):
         expected = Variable([], 3)
         actual = Variable(['x'], [1, 2, 3, np.nan]).count()