updating layer management as in scverse#1667 for _highly_variable_pea…

…rson_residuals() as well

scanpy/preprocessing/_highly_variable_genes.py

@@ -181,7 +181,7 @@ def _highly_variable_pearson_residuals(
     clip: Union[Literal['auto', 'none'], float] = 'auto',
     chunksize: int = 100,
     subset: bool = False,
-    inplace: bool = True,
+    inplace: bool = True
 ) -> Optional[pd.DataFrame]:
     """\
     See `highly_variable_genes`.
@@ -211,7 +211,9 @@ def _highly_variable_pearson_residuals(
         in all batches
     """
 
-    X = adata.layers[layer] if layer is not None else adata.X
+    view_to_actual(adata)        
+    X = _get_obs_rep(adata, layer=layer)
+    computed_on = layer if layer else 'adata.X'
 
     # Check for raw counts
     if check_nonnegative_integers(X) is False:
@@ -325,7 +327,8 @@ def _highly_variable_pearson_residuals(
     df = df.loc[adata.var_names]
 
     if inplace or subset:
-        adata.uns['hvg'] = {'flavor': 'pearson_residuals'}
+        adata.uns['hvg'] = {'flavor': 'pearson_residuals',
+                            'computed_on':computed_on}
         logg.hint(
             'added\n'
             '    \'highly_variable\', boolean vector (adata.var)\n'

scanpy/preprocessing/_normalization.py

@@ -121,12 +121,8 @@ def normalize_pearson_residuals(
             )
         adata = adata.copy()
 
-    # TODO: is this needed and if yes what for?
-    # normalize_total() has it so I used it here
-    # TODO: add to other files as well?!
-    view_to_actual(adata)
-
-    X = _get_obs_rep(adata, layer=layer)  ## TODO add to other files as well!
+    view_to_actual(adata)        
+    X = _get_obs_rep(adata, layer=layer)
     computed_on = layer if layer else 'adata.X'
 
     msg = 'computing analytic Pearson residuals on %s' % computed_on