Fix test_norm_power_group

Signed-off-by: Lukas Heumos <[email protected]>
theislab · Jan 31, 2025 · c8f5a12 · c8f5a12
1 parent 76e598a
commit c8f5a12
Showing 1 changed file with 8 additions and 8 deletions.
diff --git a/tests/preprocessing/test_normalization.py b/tests/preprocessing/test_normalization.py
@@ -604,13 +604,13 @@ def test_norm_power_group(array_type, adata_mini):
         with pytest.raises(KeyError):
             ep.pp.power_norm(adata_mini_casted, group_key="invalid_key", copy=True)
 
-        ep.pp.power_norm(
+        adata_mini_norm = ep.pp.power_norm(
             adata_mini_casted,
             vars=["sys_bp_entry", "dia_bp_entry"],
             group_key="disease",
             copy=True,
         )
-        np.array(
+        col1_norm = np.array(
             [
                 -1.34266204,
                 -0.44618949,
@@ -623,7 +623,7 @@ def test_norm_power_group(array_type, adata_mini):
             ],
             dtype=np.float32,
         )
-        np.array(
+        col2_norm = np.array(
             [
                 [
                     -1.3650659,
@@ -638,11 +638,11 @@ def test_norm_power_group(array_type, adata_mini):
             ],
             dtype=np.float32,
         )
-        # The tests are disabled because depending on weird dependency versions they currently give different results
-        assert adata_mini.X.dtype.kind == "f"
-        # assert np.allclose(adata_mini_norm.X[:, 0], adata_mini_casted.X[:, 0], rtol=1e-02, atol=1e-02)
-        # assert np.allclose(adata_mini_norm.X[:, 1], col1_norm, rtol=1e-02, atol=1e-02)
-        # assert np.allclose(adata_mini_norm.X[:, 2], col2_norm, rtol=1e-02, atol=1e-02)
+        # The tests are disabled (= tolerance set to 1)
+        # because depending on weird dependency versions they currently give different results
+        assert np.allclose(adata_mini_norm.X[:, 0], adata_mini_casted.X[:, 0], rtol=1, atol=1)
+        assert np.allclose(adata_mini_norm.X[:, 1], col1_norm, rtol=1, atol=1)
+        assert np.allclose(adata_mini_norm.X[:, 2], col2_norm, rtol=1, atol=1)
 
 
 @pytest.mark.parametrize(