usage: __main__.py [-h] (--metrics_dir dir | --metrics file [file ...])
[--indent INDENT] [--sort_keys] [-v [{DEBUG,INFO,WARNING}]]
[-f]
in_labels in_labels_lut
Computes the information from the input metrics for each cortical region
(corresponding to an atlas). If more than one metric are provided, statistics are
computed separately for each.
Hint: For instance, this script could be useful if you have a seed map from a
specific bundle, to know from which regions it originated.
Formerly: scil_compute_seed_by_labels.py
positional arguments:
in_labels Path of the input label file.
in_labels_lut Path of the LUT file corresponding to labels,used to name the regions of interest.
options:
-h, --help show this help message and exit
-v [{DEBUG,INFO,WARNING}]
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.
Metrics input options:
--metrics_dir dir Name of the directory containing metrics files: we will
load all nifti files.
--metrics file [file ...]
Metrics nifti filename. List of the names of the metrics file,
in nifti format.
Json options:
--indent INDENT Indent for json pretty print.
--sort_keys Sort keys in output json.
Scilpy version: 2.0.2