add layer to pca params output

scverse · Aug 4, 2023 · c0077fa · c0077fa
1 parent e041f3e
commit c0077fa
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Showing 2 changed files with 26 additions and 15 deletions.
diff --git a/scanpy/preprocessing/_pca.py b/scanpy/preprocessing/_pca.py
@@ -234,18 +234,24 @@ def pca(
 
     if data_is_AnnData:
         adata.obsm['X_pca'] = X_pca
-        adata.uns['pca'] = {}
-        adata.uns['pca']['params'] = {
-            'zero_center': zero_center,
-            'use_highly_variable': use_highly_variable,
-        }
         if use_highly_variable:
             adata.varm['PCs'] = np.zeros(shape=(adata.n_vars, n_comps))
             adata.varm['PCs'][adata.var['highly_variable']] = pca_.components_.T
         else:
             adata.varm['PCs'] = pca_.components_.T
-        adata.uns['pca']['variance'] = pca_.explained_variance_
-        adata.uns['pca']['variance_ratio'] = pca_.explained_variance_ratio_
+
+        uns_entry = {
+            'params': {
+                'zero_center': zero_center,
+                'use_highly_variable': use_highly_variable,
+            },
+            'variance': pca_.explained_variance_,
+            'variance_ratio': pca_.explained_variance_ratio_,
+        }
+        if layer is not None:
+            uns_entry['params']['layer'] = layer
+        adata.uns['pca'] = uns_entry
+
         logg.info('    finished', time=logg_start)
         logg.debug(
             'and added\n'

diff --git a/scanpy/tests/test_pca.py b/scanpy/tests/test_pca.py
@@ -160,18 +160,23 @@ def test_pca_layer():
     """
     Tests that layers works the same way as .X
     """
-    pbmc = pbmc3k_normalized()
+    X_adata = pbmc3k_normalized()
+
+    layer_adata = X_adata.copy()
+    layer_adata.layers["counts"] = X_adata.X.copy()
+    del layer_adata.X
 
-    pbmc.layers["counts"] = pbmc.X.copy()
+    sc.pp.pca(X_adata, dtype=np.float64)
+    sc.pp.pca(layer_adata, layer="counts", dtype=np.float64)
 
-    X_pca = sc.pp.pca(pbmc, dtype=np.float64, copy=True)
-    layer_pca = sc.pp.pca(pbmc, layer="counts", dtype=np.float64, copy=True)
+    assert layer_adata.uns["pca"]["params"]["layer"] == "counts"
+    assert "layer" not in X_adata.uns["pca"]["params"]
 
     np.testing.assert_equal(
-        X_pca.uns["pca"]["variance"], layer_pca.uns["pca"]["variance"]
+        X_adata.uns["pca"]["variance"], layer_adata.uns["pca"]["variance"]
     )
     np.testing.assert_equal(
-        X_pca.uns["pca"]["variance_ratio"], layer_pca.uns["pca"]["variance_ratio"]
+        X_adata.uns["pca"]["variance_ratio"], layer_adata.uns["pca"]["variance_ratio"]
     )
-    np.testing.assert_equal(X_pca.obsm['X_pca'], layer_pca.obsm['X_pca'])
-    np.testing.assert_equal(X_pca.varm['PCs'], layer_pca.varm['PCs'])
+    np.testing.assert_equal(X_adata.obsm['X_pca'], layer_adata.obsm['X_pca'])
+    np.testing.assert_equal(X_adata.varm['PCs'], layer_adata.varm['PCs'])