minor docs fixes from copilot

Author: 36000

AFQ/api/bundle_dict.py

@@ -1351,8 +1351,8 @@ def transform_rois(
             Name of the bundle to be transformed.
         mapping : DiffeomorphicMap object
             A mapping between DWI space and a template.
-        new_affine : array
-            Affine of space transformed into.
+        new_img : Nifti1Image
+            Image of space transformed into.
         base_fname : str, optional
             Base file path to construct file path from. Additional BIDS
             descriptors will be added to this file path. If None,

AFQ/api/group.py

@@ -144,7 +144,7 @@ def __init__(
         api.GroupAFQ(my_path, csd_sh_order_max=4)
         api.GroupAFQ(
             my_path,
-            _spec="mni_t2", reg_subject_spec="b0")
+            reg_template_spec="mni_t2", reg_subject_spec="b0")
         """
         if bids_layout_kwargs is None:
             bids_layout_kwargs = {}

AFQ/data/fetch.py

@@ -1116,7 +1116,7 @@ def read_oton_templates(as_img=True, resample_to=False):
 
 
 def read_massp_templates(as_img=True, resample_to=False):
-    """Load AFQ MASSSP templates from file
+    """Load AFQ MASSP templates from file
 
     Parameters
     ----------
@@ -1135,15 +1135,15 @@ def read_massp_templates(as_img=True, resample_to=False):
     """
     logger = logging.getLogger("AFQ")
 
-    logger.debug("loading oton templates")
+    logger.debug("loading MASSP templates")
     tic = time.perf_counter()
 
     template_dict = _fetcher_to_template(
         fetch_massp_templates, as_img=as_img, resample_to=resample_to
     )
 
     toc = time.perf_counter()
-    logger.debug(f"MASSSP templates loaded in {toc - tic:0.4f} seconds")
+    logger.debug(f"MASSP templates loaded in {toc - tic:0.4f} seconds")
 
     return template_dict
 

AFQ/definitions/image.py

@@ -414,26 +414,22 @@ def _image_getter_helper(
                     rois.update(
                         dict.fromkeys(bundle_entry.get("include", []), "waypoint")
                     )
+
+                dist_to_waypoint, dist_to_atlas, _ = tolerance_mm_to_vox(
+                    data_imap["dwi"],
+                    segmentation_params["dist_to_waypoint"],
+                    segmentation_params["dist_to_atlas"],
+                )
                 for roi, roi_type in rois.items():
                     warped_roi = roi.get_fdata()
                     if image_data is None:
                         image_data = np.zeros(warped_roi.shape)
                     if self.dilate:
-                        dist_to_waypoint, dist_to_atlas, _ = tolerance_mm_to_vox(
-                            data_imap["dwi"],
-                            segmentation_params["dist_to_waypoint"],
-                            segmentation_params["dist_to_atlas"],
-                        )
                         edt = distance_transform_edt(np.where(warped_roi == 0, 1, 0))
                         if roi_type == "waypoint":
                             warped_roi = edt <= dist_to_waypoint
                         else:
                             warped_roi = edt <= dist_to_atlas
-                        warped_roi = (
-                            edt <= dist_to_waypoint
-                            if roi_type == "waypoint"
-                            else edt <= dist_to_atlas
-                        )
 
                     image_data = np.logical_or(image_data, warped_roi.astype(bool))
             if self.tissue_property is not None: