visualization & commandline interface bugfixes

Author: ClePol

CorpusCallosum/cc_visualization.py

@@ -119,13 +119,30 @@ def load_contours_from_template_dir(
 
     fsaverage_contour = None
     contours: list[CCContour] = []
+    # First pass: collect all indices to determine the range
+    indices = []
     for thickness_file in thickness_files:
+        try:
+            idx = int(thickness_file.stem.split("_")[-1])
+            indices.append(idx)
+        except ValueError:
+            # skip files that do not follow the expected naming
+            continue
+    
+    # Calculate z_positions centered around the middle slice
+    num_slices = len(indices)
+    middle_idx = num_slices // 2
+    
+    for i, thickness_file in enumerate(thickness_files):
         try:
             idx = int(thickness_file.stem.split("_")[-1])
         except ValueError:
             # skip files that do not follow the expected naming
             continue
 
+        # Calculate z_position: use the index offset from middle, scaled by resolution
+        z_position = (idx - indices[middle_idx]) * resolution
+        
         contour_file = template_dir / f"contour_{idx}.txt"
 
         if not contour_file.exists():
@@ -138,15 +155,11 @@ def load_contours_from_template_dir(
                 # create measurement points (points = 2 x levelpaths) according to number of thickness values
                 fsaverage_contour.create_levelpaths(num_points=num_thickness_values // 2, update_data=True)
             current_contour = fsaverage_contour.copy()
+            current_contour.z_position = z_position
             current_contour.load_thickness_values(thickness_file)
 
         else:
-            # this is kinda ugly - maybe we need to overload the constructor to load the contour and thickness values?
-            # FIXME: The z_position in from_contour is still incorrect, currently all Contours would be "registered" for
-            #        the midslice.
-            current_contour = CCContour.from_contour_file(contour_file, thickness_file, z_position=0.0)
-            # current_contour.load_contour(contour_file)
-            # current_contour.load_thickness_values(thickness_file)
+            current_contour = CCContour.from_contour_file(contour_file, thickness_file, z_position=z_position)
 
         current_contour.fill_thickness_values()
         contours.append(current_contour)

CorpusCallosum/fastsurfer_cc.py

@@ -148,6 +148,7 @@ def _set_help_sid(action):
     parser.add_argument(
         "--subdivisions",
         type=float,
+        nargs='*',
         metavar="FRAC",
         default=_FixFloatFormattingList([1 / 6, 1 / 2, 2 / 3, 3 / 4], ".3f"),
         help="List of subdivision fractions for the corpus callosum subsegmentation."

CorpusCallosum/shape/contour.py

@@ -714,20 +714,22 @@ def _load_thickness_values(
         else:
             raise ValueError("Thickness values file must contain a single column")
 
-        if len(values) != len(contour):
-            if original_thickness_vertices is None:
-                new_values = values
-            elif np.sum(~np.isnan(values)) == len(original_thickness_vertices):
-                new_values = np.full(len(contour), np.nan)
-                new_values[original_thickness_vertices] = values[~np.isnan(values)]
-            else:
-                raise ValueError(
-                    f"Number of thickness values {len(values)} does not match number of points in the contour "
-                    f"{len(contour)} and current number of measurement points {len(original_thickness_vertices)} does "
-                    f"not match the number of set thickness values {np.sum(~np.isnan(values))}."
-                )
+        if len(values) == len(contour):
+            # Perfect match - use values directly
+            new_values = values
+        elif original_thickness_vertices is None:
+            # No original vertices specified, use values as-is (may differ in length)
+            new_values = values
+        elif np.sum(~np.isnan(values)) == len(original_thickness_vertices):
+            # Values match the number of measurement points, map them to the contour
+            new_values = np.full(len(contour), np.nan)
+            new_values[original_thickness_vertices] = values[~np.isnan(values)]
         else:
-            raise ValueError(f"Number of thickness values in {input_path} does not match the vertices of the path!")
+            raise ValueError(
+                f"Number of thickness values {len(values)} does not match number of points in the contour "
+                f"{len(contour)} and current number of measurement points {len(original_thickness_vertices)} does "
+                f"not match the number of set thickness values {np.sum(~np.isnan(values))}."
+            )
 
         return new_values