scil_tractogram_segment_with_recobundles

usage: __main__.py [-h]
                   [--tractogram_clustering_thr TRACTOGRAM_CLUSTERING_THR]
                   [--model_clustering_thr MODEL_CLUSTERING_THR]
                   [--pruning_thr PRUNING_THR] [--slr_threads SLR_THREADS]
                   [--seed SEED] [--inverse] [--no_empty]
                   [--in_pickle IN_PICKLE | --out_pickle OUT_PICKLE]
                   [--in_tractogram_ref IN_TRACTOGRAM_REF]
                   [--in_model_ref IN_MODEL_REF]
                   [-v [{DEBUG,INFO,WARNING,ERROR}]] [-f]
                   in_tractogram in_model in_transfo out_tractogram

Segment a single bundle by computing a simple Recobundles (single-atlas &
single-parameters).

For multiple bundles segmentation (using RecobundlesX / BundleSeg), see instead
>>> scil_tractogram_segment_with_bundleseg

Hints:
- The model needs to be cleaned and lightweight.
- The transform should come from ANTs: (using the --inverse flag)
  >>> AntsRegistrationSyNQuick.sh -d 3 -m MODEL_REF -f SUBJ_REF
  If you are unsure about the transformation 'direction', try with and without
  the --inverse flag. If you are not using the right transformation 'direction'
  a warning will pop up. If there is no warning in both cases, it means the
  transformation is very close to identity and both 'directions' will work.

-------------------------------------------------------------------------------
Reference:
[1] Garyfallidis, E., Cote, M. A., Rheault, F., ... & Descoteaux, M. (2018).
    Recognition of white matter bundles using local and global streamline-based
    registration and clustering. NeuroImage, 170, 283-295.
-------------------------------------------------------------------------------

positional arguments:
  in_tractogram         Input tractogram filename.
  in_model              Model bundle to use for recognition. (Ex, a .trk file.
  in_transfo            Path for the transformation to model space (.txt, .npy or .mat).
  out_tractogram        Output tractogram filename.

options:
  -h, --help            show this help message and exit
  --seed SEED           Random number generator seed [None].
  --inverse             Use the inverse transformation.
  --no_empty            Do not write file if there is no streamline.
  --in_pickle IN_PICKLE
                        Input pickle clusters map file.
                        Will override the tractogram_clustering_thr parameter.
  --out_pickle OUT_PICKLE
                        Output pickle clusters map file.
  --in_tractogram_ref IN_TRACTOGRAM_REF
                        Reference anatomy for in_tractogram (if tck/vtk/fib/dpy) file
                        support (.nii or .nii.gz).
  --in_model_ref IN_MODEL_REF
                        Reference anatomy for in_model (if tck/vtk/fib/dpy) file
                        support (.nii or .nii.gz).
  -v [{DEBUG,INFO,WARNING,ERROR}]
                        Produces verbose output depending on the provided level.
                        Default level is warning, default when using -v is info.
  -f                    Force overwriting of the output files.

Recobundles options:
  --tractogram_clustering_thr TRACTOGRAM_CLUSTERING_THR
                        Clustering threshold used for the whole brain. Default: 8.
  --model_clustering_thr MODEL_CLUSTERING_THR
                        Clustering threshold used for the model [4mm].
  --pruning_thr PRUNING_THR
                        MDF threshold used for final streamlines selection [6mm].
  --slr_threads SLR_THREADS
                        Number of threads for SLR [1].

2.2.2