NARR Example CF Parsing

While I was working through examples, I noticed that the parse_cf
function, when applied to the full dataset of the NARR example, would
fail...the x and y coordinates would double in size, and many NaN's
appeared. This was because the lon and lat variables lacked a
grid_mapping attribute, and so, their x and y coordinates did not get
scaled from km to m like the other variables that did. Thus, they did
not line up when xarray tried to combine them back together in a
non-unit-aware fashion.

This commit fixes this by changing when _fixup_coords is called, so that
all x/y coordinates get scaled accordingly.

metpy/tests/test_xarray.py

@@ -386,3 +386,16 @@ def test_check_axis_regular_expression_match(test_ds_generic, test_tuple):
     """Test the variety of possibilities for check_axis in the regular expression match."""
     data = test_ds_generic.rename({'e': test_tuple[0]})
     assert data.metpy.check_axis(data[test_tuple[0]], test_tuple[1])
+
+
+def test_narr_example_variable_without_grid_mapping(test_ds):
+    """Test that NARR example is parsed correctly, with x/y coordinates scaled the same."""
+    data = test_ds.metpy.parse_cf()
+    # Make sure that x and y coordinates are parsed correctly, rather than having unequal
+    # scaling based on whether that variable has the grid_mapping attribute. This would
+    # otherwise double the coordinates's shapes since xarray tries to combine the coordinates
+    # with different scaling from differing units.
+    assert test_ds['x'].shape == data['lon'].metpy.x.shape
+    assert test_ds['y'].shape == data['lon'].metpy.y.shape
+    assert data['lon'].metpy.x.identical(data['Temperature'].metpy.x)
+    assert data['lon'].metpy.y.identical(data['Temperature'].metpy.y)

metpy/xarray.py

@@ -134,7 +134,8 @@ def parse_cf(self, varname=None, coordinates=None):
             else:
                 var.coords['crs'] = CFProjection(proj_var.attrs)
                 var.attrs.pop('grid_mapping')
-                self._fixup_coords(var)
+
+        self._fixup_coords(var)
 
         # Trying to guess whether we should be adding a crs to this variable's coordinates
         # First make sure it's missing CRS but isn't lat/lon itself
@@ -253,15 +254,17 @@ def check_axis(cls, var, *axes):
     def _fixup_coords(self, var):
         """Clean up the units on the coordinate variables."""
         for coord_name, data_array in var.coords.items():
-            if self.check_axis(data_array, 'x', 'y'):
+            if (self.check_axis(data_array, 'x', 'y') and
+                    not self.check_axis(data_array, 'lon', 'lat')):
                 try:
                     var.coords[coord_name].metpy.convert_units('meters')
                 except DimensionalityError:  # Radians!
-                    new_data_array = data_array.copy()
-                    height = var.coords['crs'].item()['perspective_point_height']
-                    scaled_vals = new_data_array.metpy.unit_array * (height * units.meters)
-                    new_data_array.metpy.unit_array = scaled_vals.to('meters')
-                    var.coords[coord_name] = new_data_array
+                    if 'crs' in var.coords:
+                        new_data_array = data_array.copy()
+                        height = var.coords['crs'].item()['perspective_point_height']
+                        scaled_vals = new_data_array.metpy.unit_array * (height * units.meters)
+                        new_data_array.metpy.unit_array = scaled_vals.to('meters')
+                        var.coords[coord_name] = new_data_array
 
     def _generate_coordinate_map(self, coords):
         """Generate a coordinate map via CF conventions and other methods."""