test constrcution

nilearn/regions/tests/test_parcellations.py

@@ -230,24 +230,26 @@ def test_parcellations_transform_with_multi_confounds_multi_images(
     assert signals[0].shape == (10, n_parcel)
 
 
+@pytest.mark.parametrize("method", METHODS)
+@pytest.mark.parametrize("n_parcel", [5])
+def test_constructor(method, n_parcel, test_image_2):
+    parcellator = Parcellations(method=method, n_parcels=n_parcel, verbose=0)
+    assert parcellator.labels_img_ is not None
+    if method not in ["kmeans", "rena", "hierarchical_kmeans"]:
+        assert parcellator.connectivity_ is not None
+    assert parcellator.masker_ is not None
+
+
 @pytest.mark.skip("Skip to see if CI passes without it.")
 @pytest.mark.parametrize("method", METHODS)
 @pytest.mark.parametrize("n_parcel", [5])
-def test_fit_transform(method, n_parcel, test_image_2):
+def test_fit_transform_with_confounds(method, n_parcel, test_image_2):
     rng = np.random.RandomState(42)
     fmri_imgs = [test_image_2] * 3
     confounds = rng.standard_normal(size=(10, 3))
     confounds_list = [confounds] * 3
 
     parcellator = Parcellations(method=method, n_parcels=n_parcel, verbose=0)
-    signals = parcellator.fit_transform(fmri_imgs)
-
-    assert parcellator.labels_img_ is not None
-    if method not in ["kmeans", "rena", "hierarchical_kmeans"]:
-        assert parcellator.connectivity_ is not None
-    assert parcellator.masker_ is not None
-
-    # fit_transform with confounds
     signals = parcellator.fit_transform(fmri_imgs, confounds=confounds_list)
 
     assert isinstance(signals, list)