Revert "fix layer use_raw"

docs/release-notes/1.10.3.md

@@ -10,7 +10,6 @@
 ```
 
 * Prevent empty control gene set in {func}`~scanpy.tl.score_genes` {pr}`2875` {smaller}`M Müller`
-* Prevent `raw` conflict with `layer` in {func}`~scanpy.tl.score_genes` {pr}`3150` {smaller}`S Dicks`
 * Fix `subset=True` of {func}`~scanpy.pp.highly_variable_genes` when `flavor` is `seurat` or `cell_ranger`, and `batch_key!=None` {pr}`3042` {smaller}`E Roellin`
 * Add compatibility with {mod}`numpy` 2.0 {pr}`3065` and {pr}`3115` {smaller}`P Angerer`
 

src/scanpy/_utils/__init__.py

@@ -247,18 +247,14 @@ def _check_array_function_arguments(**kwargs):
         )
 
 
-def _check_use_raw(
-    adata: AnnData, use_raw: None | bool, layer: str | None = None
-) -> bool:
+def _check_use_raw(adata: AnnData, use_raw: None | bool) -> bool:
     """
     Normalize checking `use_raw`.
 
     My intentention here is to also provide a single place to throw a deprecation warning from in future.
     """
     if use_raw is not None:
         return use_raw
-    if layer is not None:
-        return False
     return adata.raw is not None
 
 

src/scanpy/tools/_score_genes.py

@@ -122,7 +122,7 @@ def score_genes(
     """
     start = logg.info(f"computing score {score_name!r}")
     adata = adata.copy() if copy else adata
-    use_raw = _check_use_raw(adata, use_raw, layer)
+    use_raw = _check_use_raw(adata, use_raw)
     if is_backed_type(adata.X) and not use_raw:
         raise NotImplementedError(
             f"score_genes is not implemented for matrices of type {type(adata.X)}"

tests/test_score_genes.py

@@ -257,24 +257,6 @@ def test_layer():
     np.testing.assert_array_equal(adata.obs["X_score"], adata.obs["test_score"])
 
 
-def test_layer_with_raw():
-    adata = _create_adata(100, 1000, p_zero=0, p_nan=0)
-
-    sc.pp.normalize_per_cell(adata, counts_per_cell_after=1e4)
-    sc.pp.log1p(adata)
-
-    # score X
-    gene_set = adata.var_names[:10]
-    sc.tl.score_genes(adata, gene_set, score_name="X_score")
-    # score layer (`del` makes sure it actually uses the layer)
-    adata.layers["test"] = adata.X.copy()
-    adata.raw = adata
-    del adata.X
-    sc.tl.score_genes(adata, gene_set, score_name="test_score", layer="test")
-
-    np.testing.assert_array_equal(adata.obs["X_score"], adata.obs["test_score"])
-
-
 @pytest.mark.parametrize("gene_pool", [[], ["foo", "bar"]])
 def test_invalid_gene_pool(gene_pool):
     adata = _create_adata(100, 1000, p_zero=0, p_nan=0)