Check shapes of coordinates and data during DataArray construction

xarray/core/dataarray.py

@@ -143,8 +143,16 @@ def _infer_coords_and_dims(
             var.dims = (dim,)
             new_coords[dim] = var.to_index_variable()
 
+    _check_shape_consistency(shape, new_coords, dims)
+    assert_unique_multiindex_level_names(new_coords)
+
+    return new_coords, dims
+
+
+def _check_shape_consistency(shape, coords, dims):
+    # moved from _infer_coords_and_dims
     sizes = dict(zip(dims, shape))
-    for k, v in new_coords.items():
+    for k, v in coords.items():
         if any(d not in dims for d in v.dims):
             raise ValueError(
                 f"coordinate {k} has dimensions {v.dims}, but these "
@@ -167,10 +175,6 @@ def _infer_coords_and_dims(
                 "matching the dimension size"
             )
 
-    assert_unique_multiindex_level_names(new_coords)
-
-    return new_coords, dims
-
 
 def _check_data_shape(data, coords, dims):
     if data is dtypes.NA:
@@ -2977,6 +2981,8 @@ def _result_name(self, other: Any = None) -> Optional[Hashable]:
 
     def __array_wrap__(self, obj, context=None) -> "DataArray":
         new_var = self.variable.__array_wrap__(obj, context)
+        if context is None:
+            _check_shape_consistency(new_var.shape, self._coords, new_var.dims)
         return self._replace(new_var)
 
     def __matmul__(self, obj):
@@ -2997,7 +3003,7 @@ def _unary_op(self, f: Callable, *args, **kwargs):
                 "ignore", r"Mean of empty slice", category=RuntimeWarning
             )
             with np.errstate(all="ignore"):
-                da = self.__array_wrap__(f(self.variable.data, *args, **kwargs))
+                da = self.__array_wrap__(f(self.variable.data, *args, **kwargs), -1)
             if keep_attrs:
                 da.attrs = self.attrs
             return da

xarray/tests/test_dataarray.py

@@ -413,6 +413,9 @@ def test_constructor_from_self_described(self):
         actual = DataArray(IndexVariable("foo", ["a", "b"]))
         assert_identical(expected, actual)
 
+        with pytest.raises(ValueError, match="conflicting sizes for dimension"):
+            np.insert(expected, 0, 0, axis=0)
+
     def test_constructor_from_0d(self):
         expected = Dataset({None: ([], 0)})[None]
         actual = DataArray(0)