Merge pull request #530 from Sichao25/pp

Debug inverse norm

Author: Xiaojieqiu

dynamo/tools/metric_velocity.py

@@ -71,10 +71,10 @@ def cell_wise_confidence(
             adata.X if X_data is None else X_data,  ##### Check! inverse_norm for adata.X?
             adata.layers[vkey] if V_data is None else V_data,
         )
-        norm_method = adata.uns["pp"]["X_norm_method"].copy()
-        adata.uns["pp"]["X_norm_method"] = "log1p"
+        norm_method = adata.uns["pp"]["layers_norm_method"].copy()
+        adata.uns["pp"]["layers_norm_method"] = "log1p"
         X = inverse_norm(adata, X) if X_data is None else X_data
-        adata.uns["pp"]["X_norm_method"] = norm_method
+        adata.uns["pp"]["layers_norm_method"] = norm_method
     else:
         X, V = (
             adata.layers[ekey] if X_data is None else X_data,

dynamo/tools/utils.py

@@ -991,9 +991,6 @@ def inverse_norm(adata: AnnData, layer_x: Union[np.ndarray, sp.csr_matrix]) -> n
         The inverse normalized data.
     """
 
-    if layer_x == "X":
-        raise ValueError("The inverse normalization should be performed for layers, rather than for X.")
-
     if sp.issparse(layer_x):
         layer_x.data = (
             np.expm1(layer_x.data)