undo style changes

ndcube/ndcube.py

@@ -467,40 +467,36 @@ def _generate_world_coords(self, pixel_corners, wcs, needed_axes=None, *, units)
         pixel_shape = self.data.shape[::-1]
         if pixel_corners:
             pixel_shape = tuple(np.array(pixel_shape) + 1)
-            pixel_ranges = [np.arange(i) - 0.5 for i in pixel_shape]
+            ranges = [np.arange(i) - 0.5 for i in pixel_shape]
         else:
-            pixel_ranges = [np.arange(i) for i in pixel_shape]
+            ranges = [np.arange(i) for i in pixel_shape]
 
         # Limit the pixel dimensions to the ones present in the ExtraCoords
         if isinstance(wcs, ExtraCoords):
-            pixel_ranges = [pixel_ranges[i] for i in wcs.mapping]
+            ranges = [ranges[i] for i in wcs.mapping]
             wcs = wcs.wcs
             if wcs is None:
                 return []
+
         # This value of zero will be returned as a throwaway for unneeded axes, and a numerical value is
         # required so values_to_high_level_objects in the calling function doesn't crash or warn
         world_coords = [0] * wcs.world_n_dim
         for (pixel_axes_indices, world_axes_indices) in _split_matrix(wcs.axis_correlation_matrix):
-            if (
-                needed_axes is not None
-                and len(needed_axes)
-                and all(
-                    world_axis not in needed_axes
-                    for world_axis in world_axes_indices
-                )
-            ):
+            if (needed_axes is not None
+                    and len(needed_axes)
+                    and not any(world_axis in needed_axes for world_axis in world_axes_indices)):
                 # needed_axes indicates which values in world_coords will be used by the calling
                 # function, so skip this iteration if we won't be producing any of those values
                 continue
             # First construct a range of pixel indices for this set of coupled dimensions
-            pixel_ranges_subset = [pixel_ranges[idx] for idx in pixel_axes_indices]
-            # Then get a set of non-correlated dimensions
+            sub_range = [ranges[idx] for idx in pixel_axes_indices]
+            # Then get a set of non correlated dimensions
             non_corr_axes = set(range(wcs.pixel_n_dim)) - set(pixel_axes_indices)
             # And inject 0s for those coordinates
             for idx in non_corr_axes:
-                pixel_ranges_subset.insert(idx, 0)
-            # Generate a grid of broadcast-able pixel indices for all pixel dimensions
-            grid = np.meshgrid(*pixel_ranges_subset, indexing='ij')
+                sub_range.insert(idx, 0)
+            # Generate a grid of broadcastable pixel indices for all pixel dimensions
+            grid = np.meshgrid(*sub_range, indexing='ij')
             # Convert to world coordinates
             world = wcs.pixel_to_world_values(*grid)
             # TODO: this isinstance check is to mitigate https://github.com/spacetelescope/gwcs/pull/332
@@ -513,6 +509,7 @@ def _generate_world_coords(self, pixel_corners, wcs, needed_axes=None, *, units)
                 array_slice[wcs.axis_correlation_matrix[idx]] = slice(None)
                 tmp_world = world[idx][tuple(array_slice)].T
                 world_coords[idx] = tmp_world
+
         if units:
             for i, (coord, unit) in enumerate(zip(world_coords, wcs.world_axis_units)):
                 world_coords[i] = coord << u.Unit(unit)
@@ -524,47 +521,61 @@ def axis_world_coords(self, *axes, pixel_corners=False, wcs=None):
         # Docstring in NDCubeABC.
         if isinstance(wcs, BaseHighLevelWCS):
             wcs = wcs.low_level_wcs
+
         orig_wcs = wcs
         if isinstance(wcs, ExtraCoords):
             wcs = wcs.wcs
             if not wcs:
                 return ()
+
         object_names = np.array([wao_comp[0] for wao_comp in wcs.world_axis_object_components])
         unique_obj_names = utils.misc.unique_sorted(object_names)
         world_axes_for_obj = [np.where(object_names == name)[0] for name in unique_obj_names]
+
         # Create a mapping from world index in the WCS to object index in axes_coords
         world_index_to_object_index = {}
         for object_index, world_axes in enumerate(world_axes_for_obj):
             for world_index in world_axes:
                 world_index_to_object_index[world_index] = object_index
+
         world_indices = utils.wcs.calculate_world_indices_from_axes(wcs, axes)
         object_indices = utils.misc.unique_sorted(
             [world_index_to_object_index[world_index] for world_index in world_indices]
         )
+
         axes_coords = self._generate_world_coords(pixel_corners, orig_wcs, world_indices, units=False)
+
         axes_coords = values_to_high_level_objects(*axes_coords, low_level_wcs=wcs)
+
         if not axes:
             return tuple(axes_coords)
+
         return tuple(axes_coords[i] for i in object_indices)
 
     @utils.cube.sanitize_wcs
     def axis_world_coords_values(self, *axes, pixel_corners=False, wcs=None):
         # Docstring in NDCubeABC.
         if isinstance(wcs, BaseHighLevelWCS):
             wcs = wcs.low_level_wcs
+
         orig_wcs = wcs
         if isinstance(wcs, ExtraCoords):
             wcs = wcs.wcs
             if not wcs:
                 return ()
+
         world_indices = utils.wcs.calculate_world_indices_from_axes(wcs, axes)
+
         axes_coords = self._generate_world_coords(pixel_corners, orig_wcs, world_indices, units=True)
+
         world_axis_physical_types = wcs.world_axis_physical_types
+
         # If user has supplied axes, extract only the
         # world coords that correspond to those axes.
         if axes:
             axes_coords = [axes_coords[i] for i in world_indices]
             world_axis_physical_types = tuple(np.array(world_axis_physical_types)[world_indices])
+
         # Return in array order.
         # First replace characters in physical types forbidden for namedtuple identifiers.
         identifiers = []