answer em comments

scilpy/tractanalysis/mrds_along_streamlines.py

@@ -9,7 +9,7 @@ def mrds_metrics_along_streamlines(sft, mrds_pdds,
                                    metrics, max_theta,
                                    length_weighting):
     """
-    Compute mean map for a given lobe-specific metric along streamlines.
+    Compute mean map for a given fixel-specific metric along streamlines.
 
     Parameters
     ----------
@@ -34,7 +34,7 @@ def mrds_metrics_along_streamlines(sft, mrds_pdds,
 
     all_metric = mrds_sum[0]
     for curr_metric in mrds_sum[1:]:
-        all_metric += curr_metric
+        all_metric += np.abs(curr_metric)
 
     non_zeros = np.nonzero(all_metric)
     weights_nz = weights[non_zeros]
@@ -56,7 +56,7 @@ def mrds_metric_sums_along_streamlines(sft, mrds_pdds, metrics,
     mrds_pdds : ndarray (X, Y, Z, 3*N_TENSORS)
         MRDS principal diffusion directions (PDDs) of the tensors
     metrics : list of ndarray (X, Y, Z, N_TENSORS)
-        The fixel-specific metric of interest.
+        Fixel-specific metrics.
     max_theta : float
         Maximum angle in degrees between the fiber direction and the
         MRDS principal diffusion direction.
@@ -66,7 +66,7 @@ def mrds_metric_sums_along_streamlines(sft, mrds_pdds, metrics,
     Returns
     -------
     metric_sum_map : np.array
-        fixel-specific metric sum map.
+        fixel-specific metrics sum map.
     weight_map : np.array
         Segment lengths.
     """

scripts/scil_bundle_mean_fixel_mrds_metric.py

@@ -13,12 +13,15 @@
 diffusivity (fixel-MD), radial diffusivity (fixel-RD) and
 axial diffusivity (fixel-AD).
 
-Fixel-specific metrics are metrics extracted from Bingham distributions fitted
-to fODF. Their are as many values per voxel as there are lobes extracted. The
+Fixel-specific metrics are metrics extracted from
+Multi-Resolution Discrete-Search (MRDS) solutions.
+There are as many values per voxel as there are fixels extracted. The
 values chosen for a given voxel is the one belonging to the lobe better aligned
 with the current streamline segment.
 
-Output metrics will be name: [prefix]_mrds_f[metric_name].nii.gz
+Input files come from scil_mrds_metrics.py command.
+
+Output metrics will be name: [prefix]_mrds_[metric_name].nii.gz
 
 Please use a bundle file rather than a whole tractogram.
 """
@@ -63,7 +66,7 @@ def _build_arg_parser():
                         'segment lengths. [%(default)s]')
 
     p.add_argument('--max_theta', default=60, type=float,
-                   help='Maximum angle (in degrees) condition on lobe '
+                   help='Maximum angle (in degrees) condition on fixel '
                         'alignment. [%(default)s]')
 
     add_reference_arg(p)
@@ -80,15 +83,15 @@ def main():
     if args.fa is not None:
         in_metrics.append(args.fa)
         out_metrics.append('{}_mrds_fFA.nii.gz'.format(args.prefix))
-    if args.md is not None:
-        in_metrics.append(args.md)
-        out_metrics.append('{}_mrds_fMD.nii.gz'.format(args.prefix))
-    if args.rd is not None:
-        in_metrics.append(args.rd)
-        out_metrics.append('{}_mrds_fRD.nii.gz'.format(args.prefix))
     if args.ad is not None:
         in_metrics.append(args.ad)
         out_metrics.append('{}_mrds_fAD.nii.gz'.format(args.prefix))
+    if args.rd is not None:
+        in_metrics.append(args.rd)
+        out_metrics.append('{}_mrds_fRD.nii.gz'.format(args.prefix))
+    if args.md is not None:
+        in_metrics.append(args.md)
+        out_metrics.append('{}_mrds_fMD.nii.gz'.format(args.prefix))
 
     if in_metrics == []:
         parser.error('At least one metric is required.')
@@ -114,7 +117,6 @@ def main():
                                        args.length_weighting)
 
     for metric_id, curr_metric in enumerate(fixel_metrics):
-
         nib.Nifti1Image(curr_metric.astype(np.float32),
                         affine=affine,
                         header=header,