Remove keep_attrs keywords

Author: fujiisoup

xarray/core/dataarray.py

@@ -907,7 +907,7 @@ def reindex(self, indexers=None, method=None, tolerance=None, copy=True,
         return self._from_temp_dataset(ds)
 
     def interp(self, coords=None, method='linear', assume_sorted=False,
-               keep_attrs=False, kwargs={}, **coords_kwargs):
+               kwargs={}, **coords_kwargs):
         """ Multidimensional interpolation of variables.
 
         coords : dict, optional
@@ -922,10 +922,6 @@ def interp(self, coords=None, method='linear', assume_sorted=False,
             If False, values of x can be in any order and they are sorted
             first. If True, x has to be an array of monotonically increasing
             values.
-        keep_attrs : bool, optional
-            If True, the variable's attributes (`attrs`) will be copied from
-            the original object to the new one.  If False (default), the new
-            object will be returned without attributes.
         kwargs: dictionary
             Additional keyword passed to scipy's interpolator.
         **coords_kwarg : {dim: coordinate, ...}, optional
@@ -952,7 +948,7 @@ def interp(self, coords=None, method='linear', assume_sorted=False,
 
         ds = self._to_temp_dataset().interp(
             coords, method=method, kwargs=kwargs, assume_sorted=assume_sorted,
-            keep_attrs=keep_attrs, **coords_kwargs)
+            **coords_kwargs)
         return self._from_temp_dataset(ds)
 
     def rename(self, new_name_or_name_dict=None, **names):

xarray/core/dataset.py

@@ -1815,7 +1815,7 @@ def reindex(self, indexers=None, method=None, tolerance=None, copy=True,
         return self._replace_vars_and_dims(variables, coord_names)
 
     def interp(self, coords=None, method='linear', assume_sorted=False,
-               keep_attrs=False, kwargs={}, **coords_kwargs):
+               kwargs={}, **coords_kwargs):
         """ Multidimensional interpolation of Dataset.
 
         Parameters
@@ -1834,10 +1834,6 @@ def interp(self, coords=None, method='linear', assume_sorted=False,
             in any order and they are sorted first. If True, interpolated
             coordinates are assumed to be an array of monotonically increasing
             values.
-        keep_attrs : bool, optional
-            If True, the dataset's attributes (`attrs`) will be copied from
-            the original object to the new one.  If False (default), the new
-            object will be returned without attributes.
         kwargs: dictionary, optional
             Additional keyword passed to scipy's interpolator.
         **coords_kwarg : {dim: coordinate, ...}, optional
@@ -1879,15 +1875,14 @@ def maybe_variable(obj, k):
                     var_indexers = {k: (maybe_variable(obj, k), v) for k, v
                                     in indexers.items() if k in var.dims}
                     variables[name] = missing.interp(
-                        var, var_indexers, method, keep_attrs, **kwargs)
+                        var, var_indexers, method, **kwargs)
                 elif all(d not in indexers for d in var.dims):
                     # keep unrelated object array
                     variables[name] = var
 
         coord_names = set(variables).intersection(obj._coord_names)
-
-        selected = obj._replace_vars_and_dims(
-                variables, coord_names=coord_names)
+        selected = obj._replace_vars_and_dims(variables,
+                                              coord_names=coord_names)
         # attach indexer as coordinate
         variables.update(indexers)
         # Extract coordinates from indexers
@@ -1896,10 +1891,7 @@ def maybe_variable(obj, k):
         coord_names = (set(variables)
                        .intersection(obj._coord_names)
                        .union(coord_vars))
-
-        attrs = self.attrs if keep_attrs else None
-        return obj._replace_vars_and_dims(
-            variables, coord_names=coord_names, attrs=attrs)
+        return obj._replace_vars_and_dims(variables, coord_names=coord_names)
 
     def rename(self, name_dict=None, inplace=False, **names):
         """Returns a new object with renamed variables and dimensions.

xarray/core/missing.py

@@ -394,7 +394,7 @@ def _localize(var, indexes_coords):
     return var.isel(**indexes), indexes_coords
 
 
-def interp(var, indexes_coords, method, keep_attrs, **kwargs):
+def interp(var, indexes_coords, method, **kwargs):
     """ Make an interpolation of Variable
 
     Parameters
@@ -408,8 +408,6 @@ def interp(var, indexes_coords, method, keep_attrs, **kwargs):
         One of {'linear', 'nearest', 'zero', 'slinear', 'quadratic',
         'cubic'}. For multidimensional interpolation, only
         {'linear', 'nearest'} can be used.
-    keep_attrs: boolean
-        If True, variable's attributes (`attrs`) will be copied
     **kwargs:
         keyword arguments to be passed to scipy.interpolate
 
@@ -444,8 +442,7 @@ def interp(var, indexes_coords, method, keep_attrs, **kwargs):
     interped = interp_func(var.transpose(*original_dims).data,
                            x, destination, method, kwargs)
 
-    attrs = var.attrs if keep_attrs else {}
-    result = Variable(new_dims, interped, attrs=attrs)
+    result = Variable(new_dims, interped, attrs=var.attrs)
 
     # dimension of the output array
     out_dims = OrderedSet()

xarray/tests/test_interp.py

@@ -377,11 +377,7 @@ def test_dataset():
 
     assert not interpolated['var1'].equals(ds['var1'])
     assert not interpolated['var3'].equals(ds['var3'])
-    # attrs should not be tracked
-    assert 'foo' not in interpolated.attrs
-    assert 'buz' not in interpolated['var1'].attrs
-
-    interpolated = ds.interp(dim2=new_dim2, keep_attrs=True)
+    # attrs should be kept
     assert interpolated.attrs['foo'] == 'var'
     assert interpolated['var1'].attrs['buz'] == 'var2'