fix compute_gene_trends tests

tests/presults.py

@@ -2,11 +2,14 @@
 import pandas as pd
 import palantir
 
+
 def test_PResults():
     # Create some dummy data
     pseudotime = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
     entropy = None
-    branch_probs = pd.DataFrame({'branch1': [0.1, 0.2, 0.3, 0.4, 0.5], 'branch2': [0.5, 0.4, 0.3, 0.2, 0.1]})
+    branch_probs = pd.DataFrame(
+        {"branch1": [0.1, 0.2, 0.3, 0.4, 0.5], "branch2": [0.5, 0.4, 0.3, 0.2, 0.1]}
+    )
     waypoints = None
 
     # Initialize PResults object
@@ -18,6 +21,7 @@ def test_PResults():
     assert presults.waypoints is None
     assert np.array_equal(presults.branch_probs, branch_probs.values)
 
+
 def test_gam_fit_predict():
     # Create some dummy data
     x = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
@@ -28,8 +32,10 @@ def test_gam_fit_predict():
     spline_order = 2
 
     # Call the function
-    y_pred, stds = palantir.presults.gam_fit_predict(x, y, weights, pred_x, n_splines, spline_order)
+    y_pred, stds = palantir.presults.gam_fit_predict(
+        x, y, weights, pred_x, n_splines, spline_order
+    )
 
     # Asserts to check the output
     assert isinstance(y_pred, np.ndarray)
-    assert isinstance(stds, np.ndarray)
+    assert isinstance(stds, np.ndarray)

tests/presults_compute_gene_trends.py

@@ -1,12 +1,12 @@
 import pytest
+import pandas as pd
+import numpy as np
+from anndata import AnnData
 import palantir
 
+
 @pytest.fixture
 def mock_adata():
-    import pandas as pd
-    import numpy as np
-    from anndata import AnnData
-
     n_cells = 10
 
     # Create mock data
@@ -18,21 +18,41 @@ def mock_adata():
         ),
         var=pd.DataFrame(index=[f"gene_{i}" for i in range(3)]),
     )
-    
+
     adata.obsm["branch_masks"] = pd.DataFrame(
         np.random.randint(2, size=(n_cells, 2)),
         columns=["branch_1", "branch_2"],
         index=adata.obs_names,
+    ).astype(bool)
+
+    return adata
+
+
+@pytest.fixture
+def custom_mock_adata():
+    n_cells = 10
+
+    # Create mock data
+    adata = AnnData(
+        X=np.random.rand(n_cells, 3),
+        obs=pd.DataFrame(
+            {"custom_time": np.random.rand(n_cells)},
+            index=[f"cell_{i}" for i in range(n_cells)],
+        ),
+        var=pd.DataFrame(index=[f"gene_{i}" for i in range(3)]),
     )
 
+    adata.obsm["custom_masks"] = pd.DataFrame(
+        np.random.randint(2, size=(n_cells, 2)),
+        columns=["branch_1", "branch_2"],
+        index=adata.obs_names,
+    ).astype(bool)
+
     return adata
 
+
 @pytest.fixture
 def mock_adata_old():
-    import pandas as pd
-    import numpy as np
-    from anndata import AnnData
-
     n_cells = 10
 
     # Create mock data
@@ -46,13 +66,16 @@ def mock_adata_old():
     )
 
     # Create mock branch_masks in obsm
-    adata.obsm["branch_masks"] = pd.DataFrame(np.random.randint(2, size=(n_cells, 2))
+    adata.obsm["branch_masks"] = np.random.randint(2, size=(n_cells, 2)).astype(bool)
     adata.uns["branch_masks_columns"] = ["branch_1", "branch_2"]
 
     return adata
-
-@pytest.mark.parametrize("adata", [mock_adata, mock_adata_old])
-def test_compute_gene_trends(adata):
+
+
+@pytest.mark.parametrize("adata_fixture", ["mock_adata", "mock_adata_old"])
+def test_compute_gene_trends(request, adata_fixture):
+    adata = request.getfixturevalue(adata_fixture)
+
     # Call the function with default keys
     res = palantir.presults.compute_gene_trends(adata)
 
@@ -65,9 +88,11 @@ def test_compute_gene_trends(adata):
     assert "gene_0" in res["branch_1"]["trends"].index
     assert adata.varm["gene_trends_branch_1"].shape == (3, 500)
 
+
+def test_compute_gene_trends_custom_anndata(custom_mock_adata):
     # Call the function with custom keys
     res = palantir.presults.compute_gene_trends(
-        adata,
+        custom_mock_adata,
         masks_key="custom_masks",
         pseudo_time_key="custom_time",
         gene_trend_key="custom_trends",
@@ -80,5 +105,4 @@ def test_compute_gene_trends(adata):
     assert isinstance(res["branch_1"], dict)
     assert isinstance(res["branch_1"]["trends"], pd.DataFrame)
     assert "gene_0" in res["branch_1"]["trends"].index
-    assert adata.varm["custom_trends_branch_1"].shape == (3, 500)
-
+    assert custom_mock_adata.varm["custom_trends_branch_1"].shape == (3, 500)