Remove means vector

meyer-lab · Nov 25, 2024 · ca12a46 · ca12a46
1 parent d63937e
commit ca12a46
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Showing 2 changed files with 1 addition and 6 deletions.
diff --git a/cellcommunicationpf2/cc_pf2.py b/cellcommunicationpf2/cc_pf2.py
@@ -22,7 +22,6 @@ def project_tensor(tensor: np.ndarray, proj_matrix: np.ndarray) -> np.ndarray:
 
 def project_data(
     X_list: list,
-    means: np.ndarray,
     factors: list[np.ndarray],
     weights: np.ndarray = None,
     full_tensor: np.ndarray = None,

diff --git a/cellcommunicationpf2/tests/test_OP.py b/cellcommunicationpf2/tests/test_OP.py
@@ -19,9 +19,6 @@ def test_project_data():
     # Generate random X_list
     X_list = [np.random.rand(cells, cells, LR) for _ in range(num_tensors)]
 
-    # Generate random means matrix
-    means = np.random.rand(cells)
-
     # Generate random factors: A (obs x rank), B (C x rank), C (C x rank), D (LR x rank)
     A = np.random.rand(obs, rank)
     B = np.random.rand(rank, rank)
@@ -30,7 +27,7 @@ def test_project_data():
     factors = [A, B, C, D]
 
     # Call the project_data method
-    projections, projected_X = project_data(X_list, means, factors)
+    projections, projected_X = project_data(X_list, factors)
 
     # Assertions
     assert len(projections) == num_tensors
@@ -70,7 +67,6 @@ def test_project_data_output():
     # Call the project_data method using the recreated tensors to get the projected_X that gets solved by our method
     projections_recreated, _ = project_data(
         recreated_tensors,
-        np.zeros(cells),
         [
             np.zeros((obs, rank)),
             np.zeros((rank, rank)),