Fixed the bug in generalized procrustes analysis

src/paste3/visualization.py

@@ -254,13 +254,16 @@ def generalized_procrustes_analysis(
     assert target_coordinates.shape[1] == 2
 
     weighted_source = pi.sum(axis=1).matmul(source_coordinates)
-    weighted_targed = pi.sum(axis=0).matmul(target_coordinates)
-    source_coordinates = source_coordinates - weighted_source
-    target_coordinates = target_coordinates - weighted_targed
+    weighted_target = pi.sum(axis=0).matmul(target_coordinates)
+
     if is_partial:
         m = torch.sum(pi)
-        source_coordinates = source_coordinates * (1.0 / m)
-        target_coordinates = target_coordinates * (1.0 / m)
+        weighted_source = weighted_source * (1.0 / m)
+        weighted_target = weighted_target * (1.0 / m)
+
+    source_coordinates = source_coordinates - weighted_source
+    target_coordinates = target_coordinates - weighted_target
+
     covariance_matrix = target_coordinates.T.matmul(pi.T.matmul(source_coordinates))
     U, S, Vt = torch.linalg.svd(covariance_matrix, full_matrices=True)
     rotation_matrix = Vt.T.matmul(U.T)
@@ -275,14 +278,14 @@ def generalized_procrustes_analysis(
             target_coordinates,
             rotation_angle,
             weighted_source,
-            weighted_targed,
+            weighted_target,
         )
     if return_params and return_as_matrix:
         return (
             source_coordinates,
             target_coordinates,
             rotation_matrix,
             weighted_source,
-            weighted_targed,
+            weighted_target,
         )
     return source_coordinates, target_coordinates

tests/test_visualization.py

@@ -165,27 +165,16 @@ def test_partial_stack_slices_pairwise(slices):
         )
 
 
-def test_partial_procrustes_analysis(slices):
-    center_slice = sc.read_h5ad(input_dir / "center_slice.h5ad")
+def test_partial_procrustes_analysis(slices2):
+    data = np.load(output_dir / "partial_procrustes_analysis.npz")
 
-    pairwise_info = torch.Tensor(
-        np.genfromtxt(input_dir / "center_slice1_pairwise.csv", delimiter=",")
-    ).double()
+    assert torch.sum(torch.Tensor(data["pi"])) < 0.99999999
 
-    aligned_center, aligned_slice = generalized_procrustes_analysis(
-        torch.Tensor(center_slice.obsm["spatial"]).double(),
-        torch.Tensor(slices[0].obsm["spatial"]).double(),
-        pairwise_info,
+    x_aligned, y_aligned = generalized_procrustes_analysis(
+        torch.Tensor(slices2[0].obsm["spatial"]).double(),
+        torch.Tensor(slices2[1].obsm["spatial"]).double(),
+        torch.Tensor(data["pi"]).double(),
         is_partial=True,
     )
-
-    assert_frame_equal(
-        pd.DataFrame(aligned_center, columns=["0", "1"]),
-        pd.read_csv(output_dir / "aligned_center.csv"),
-        atol=1e-6,
-    )
-    assert_frame_equal(
-        pd.DataFrame(aligned_slice, columns=["0", "1"]),
-        pd.read_csv(output_dir / "aligned_slice.csv"),
-        atol=1e-6,
-    )
+    assert np.allclose(x_aligned.cpu().numpy(), data["x_aligned"])
+    assert np.allclose(y_aligned.cpu().numpy(), data["y_aligned"], atol=1e-06)