[ENH] Let _check_embedded_nifti_masker work with surface masker

examples/08_experimental/plot_surface_image_and_maskers.py

@@ -110,11 +110,6 @@ def adjust_screening_percentile(screening_percentile, *args, **kwargs):
 
     param_validation.adjust_screening_percentile = adjust_screening_percentile
 
-    def check_embedded_nifti_masker(estimator, *args, **kwargs):
-        return estimator.mask
-
-    decoding.decoder._check_embedded_nifti_masker = check_embedded_nifti_masker
-
 
 monkeypatch_masker_checks()
 

nilearn/decoding/decoder.py

@@ -46,6 +46,7 @@
 from nilearn._utils import CacheMixin, fill_doc
 from nilearn._utils.cache_mixin import _check_memory
 from nilearn._utils.param_validation import check_feature_screening
+from nilearn.experimental.surface import SurfaceMasker
 from nilearn.maskers._masker_validation import _check_embedded_nifti_masker
 from nilearn.regions.rena_clustering import ReNA
 
@@ -920,8 +921,12 @@
         return scores
 
     def _apply_mask(self, X):
-        # Nifti masking
-        self.masker_ = _check_embedded_nifti_masker(self, multi_subject=False)
+        masker_type = "nifti"
+        if isinstance(self.mask, SurfaceMasker):
+            masker_type = "surface"
+        self.masker_ = _check_embedded_nifti_masker(
+            self, masker_type=masker_type
+        )
         X = self.masker_.fit_transform(X)
         self.mask_img_ = self.masker_.mask_img_
 

nilearn/decoding/space_net.py

@@ -28,6 +28,7 @@
 from sklearn.utils import check_array, check_X_y
 from sklearn.utils.extmath import safe_sparse_dot
 
+from nilearn.experimental.surface import SurfaceMasker
 from nilearn.image import get_data
 from nilearn.maskers._masker_validation import _check_embedded_nifti_masker
 from nilearn.masking import _unmask_from_to_3d_array
@@ -850,8 +851,12 @@
         if self.verbose:
             tic = time.time()
 
-        # nifti masking
-        self.masker_ = _check_embedded_nifti_masker(self, multi_subject=False)
+        masker_type = "nifti"
+        if isinstance(self.mask, SurfaceMasker):
+            masker_type = "surface"
+        self.masker_ = _check_embedded_nifti_masker(
+            self, masker_type=masker_type
+        )
         X = self.masker_.fit_transform(X)
 
         X, y = check_X_y(

nilearn/maskers/_masker_validation.py

@@ -3,13 +3,15 @@
 
 import numpy as np
 
+from nilearn.experimental.surface import SurfaceMasker
+
 from .._utils.cache_mixin import _check_memory
 from .._utils.class_inspect import get_params
 from .multi_nifti_masker import MultiNiftiMasker
 from .nifti_masker import NiftiMasker
 
 
-def _check_embedded_nifti_masker(estimator, multi_subject=True):
+def _check_embedded_nifti_masker(estimator, masker_type="multi_nii"):
     """Create a masker from instance parameters.
 
     Base function for using a masker within a BaseEstimator class
@@ -38,11 +40,16 @@ def _check_embedded_nifti_masker(estimator, multi_subject=True):
         New masker
 
     """
-    masker_type = MultiNiftiMasker if multi_subject else NiftiMasker
+    if masker_type == "surface":
+        masker_type = SurfaceMasker
+    elif masker_type == "multi_nii":
+        masker_type = MultiNiftiMasker
+    else:
+        masker_type = NiftiMasker
     estimator_params = get_params(masker_type, estimator)
     mask = getattr(estimator, "mask", None)
 
-    if isinstance(mask, (NiftiMasker, MultiNiftiMasker)):
+    if isinstance(mask, (NiftiMasker, MultiNiftiMasker, SurfaceMasker)):
         # Creating (Multi)NiftiMasker from provided masker
         masker_params = get_params(masker_type, mask)
         new_masker_params = masker_params
@@ -52,7 +59,7 @@ def _check_embedded_nifti_masker(estimator, multi_subject=True):
         new_masker_params = estimator_params
         new_masker_params["mask_img"] = mask
     # Forwarding system parameters of instance to new masker in all case
-    if multi_subject and hasattr(estimator, "n_jobs"):
+    if masker_type == "multi_nii" and hasattr(estimator, "n_jobs"):
         # For MultiNiftiMasker only
         new_masker_params["n_jobs"] = estimator.n_jobs
 
@@ -86,7 +93,6 @@ def _check_embedded_nifti_masker(estimator, multi_subject=True):
             warning_msg.substitute(attribute="verbose", default_value="0")
         )
         new_masker_params["verbose"] = 0
-
     # Raising warning if masker override parameters
     conflict_string = ""
     for param_key in sorted(estimator_params):

nilearn/maskers/tests/test_masker_validation.py

@@ -4,6 +4,7 @@
 from joblib import Memory
 from sklearn.base import BaseEstimator
 
+from nilearn.experimental.surface import SurfaceMasker
 from nilearn.maskers import MultiNiftiMasker, NiftiMasker
 from nilearn.maskers._masker_validation import _check_embedded_nifti_masker
 
@@ -80,14 +81,13 @@ def test_check_embedded_nifti_masker():
     masker = _check_embedded_nifti_masker(owner)
     assert type(masker) is MultiNiftiMasker
 
-    for mask, multi_subject in (
-        (MultiNiftiMasker(), True),
-        (NiftiMasker(), False),
+    for mask, masker_type in (
+        (MultiNiftiMasker(), "multi_nii"),
+        (NiftiMasker(), "nii"),
+        (SurfaceMasker(), "surface"),
     ):
         owner = OwningClass(mask=mask)
-        masker = _check_embedded_nifti_masker(
-            owner, multi_subject=multi_subject
-        )
+        masker = _check_embedded_nifti_masker(owner, masker_type=masker_type)
         assert isinstance(masker, type(mask))
         for param_key in masker.get_params():
             if param_key not in [