Ensure hashable is a valid input for coordinate identifier

src/xarray_regrid/methods/conservative.py

@@ -91,7 +91,7 @@ def conservative_regrid(
 def conservative_regrid_dataset(
     data: xr.Dataset,
     coords: dict[Hashable, xr.DataArray],
-    latitude_coord: str,
+    latitude_coord: Hashable,
     skipna: bool,
     nan_threshold: float,
 ) -> xr.Dataset:
@@ -116,7 +116,7 @@ def conservative_regrid_dataset(
         weights = utils.create_dot_dataarray(
             nd_weights, str(coord), target_coords, source_coords
         )
-        if str(coord) == latitude_coord:
+        if coord == latitude_coord:
             weights = apply_spherical_correction(weights, latitude_coord)
 
         for array in data_vars.keys():
@@ -125,7 +125,7 @@ def conservative_regrid_dataset(
                 data_vars[array], valid_fracs[array] = apply_weights(
                     da=data_vars[array],
                     weights=weights,
-                    coord_name=str(coord),
+                    coord=coord,
                     valid_frac=valid_fracs[array],
                     skipna=skipna,
                     non_grid_dims=non_grid_dims,
@@ -157,7 +157,7 @@ def conservative_regrid_dataset(
 def apply_weights(
     da: xr.DataArray,
     weights: xr.DataArray,
-    coord_name: str,
+    coord: Hashable,
     valid_frac: xr.DataArray,
     skipna: bool,
     non_grid_dims: list[Hashable],
@@ -168,7 +168,7 @@ def apply_weights(
 def apply_weights(
     da: xr.DataArray,
     weights: xr.DataArray,
-    coord_name: str,
+    coord: Hashable,
     valid_frac: None,
     skipna: bool,
     non_grid_dims: list[Hashable],
@@ -178,13 +178,13 @@ def apply_weights(
 def apply_weights(
     da: xr.DataArray,
     weights: xr.DataArray,
-    coord_name: str,
+    coord: Hashable,
     valid_frac: xr.DataArray | None,
     skipna: bool,
     non_grid_dims: list[Hashable],
 ) -> tuple[xr.DataArray, xr.DataArray | None]:
     """Apply the weights to convert data to the new coordinates."""
-    coord_map = {f"target_{coord_name}": coord_name}
+    coord_map = {f"target_{coord}": coord}
     weights_norm = weights.copy()
 
     if skipna:
@@ -194,16 +194,16 @@ def apply_weights(
         # Renormalize the weights along this dim by the accumulated valid_frac
         # along previous dimensions
         if valid_frac is not None:
-            weights_norm = weights * valid_frac / valid_frac.mean(coord_name)
+            weights_norm = weights * valid_frac / valid_frac.mean(dim=[coord])
 
     da_reduced: xr.DataArray = xr.dot(
-        da.fillna(0), weights_norm, dim=coord_name, optimize=True
+        da.fillna(0), weights_norm, dim=[coord], optimize=True
     )
     da_reduced = da_reduced.rename(coord_map).transpose(*da.dims)
 
     if skipna:
         weights_valid_sum: xr.DataArray = xr.dot(
-            weights_norm, notnull, dim=coord_name, optimize=True
+            weights_norm, notnull, dim=[coord], optimize=True
         )
         weights_valid_sum = weights_valid_sum.rename(coord_map)
         da_reduced /= weights_valid_sum.clip(1e-6, None)
@@ -214,7 +214,7 @@ def apply_weights(
 
         else:
             # Update the valid points on this dimension
-            valid_frac = xr.dot(valid_frac, weights, dim=coord_name, optimize=True)
+            valid_frac = xr.dot(valid_frac, weights, dim=[coord], optimize=True)
             valid_frac = valid_frac.rename(coord_map)  # type: ignore
             valid_frac = valid_frac.clip(0, 1)
 
@@ -247,7 +247,7 @@ def get_weights(source_coords: np.ndarray, target_coords: np.ndarray) -> np.ndar
 
 
 def apply_spherical_correction(
-    dot_array: xr.DataArray, latitude_coord: str
+    dot_array: xr.DataArray, latitude_coord: Hashable
 ) -> xr.DataArray:
     """Apply a sperical earth correction on the prepared dot product weights."""
     da = dot_array.copy()