Welcome to cat12 BIDS app documentation!

Command line API

BIDS app for CAT12.

usage: common_parser [-h] [--version]
                     bids_dir output_dir {participant,group}
                     {help,view,copy,segment} ...

Positional Arguments

bids_dir

Fullpath to the directory with the input dataset formatted according to the BIDS standard.

output_dir

Fullpath to the directory where the output files will be stored.

analysis_level

Possible choices: participant, group

Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel) using the same output_dir.

Default: 'participant'

command

Possible choices: help, view, copy, segment

Choose a sub-command

Named Arguments

--version

Show program’s version number and exit.

Sub-commands

help

Show cat12 script help.

common_parser help [-h]

view

View batch.

common_parser view [-h] [--verbose {0,1,2,3}]
                   {segment,simple,segment_long,segment_enigma,resample,get_IQR,get_TIV,get_quality,get_ROI_values}

Positional Arguments

target

Possible choices: segment, simple, segment_long, segment_enigma, resample, get_IQR, get_TIV, get_quality, get_ROI_values

Batch name

Named Arguments

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

copy

Copy batch to output_dir.

common_parser copy [-h] [--verbose {0,1,2,3}]
                   {segment,simple,segment_long,segment_enigma,resample,get_IQR,get_TIV,get_quality,get_ROI_values}

Positional Arguments

target

Possible choices: segment, simple, segment_long, segment_enigma, resample, get_IQR, get_TIV, get_quality, get_ROI_values

Batch name

Named Arguments

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

segment

segment

common_parser segment [-h]
                      [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
                      [--verbose {0,1,2,3}]
                      [--bids_filter_file BIDS_FILTER_FILE]
                      [--skip_validation] [--reset_database]
                      [--type {default,simple,long_0,long_1,long_2,long_3,enigma}]

Named Arguments

--participant_label

The label(s) of the participant(s) that should be analyzed. The label corresponds to sub-<participant_label> from the BIDS spec (so it does not include “sub-“).

If this parameter is not provided, all subjects will be analyzed. Multiple participants can be specified with a space separated list.

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

--bids_filter_file

A JSON file describing custom BIDS input filters using PyBIDS. For further details, please check out TBD.

--skip_validation

Do not run the bids validation.

Default: False

--reset_database

Resets the database of the input dataset.

Default: False

--type

Possible choices: default, simple, long_0, long_1, long_2, long_3, enigma

Type of segmentation.

default: default CAT12 preprocessing batch; simple: simple processing batch; long_0 - longitudinal developmental; long_1 - longitudinal plasticity/learning; long_2 - longitudinal aging; long_3 - longitudinal save models 1 and 2; enigma - enigma segmentation

Default: 'default'

BIDS app for CAT12.

usage: common_parser [-h] [--version]
                     bids_dir output_dir {participant,group}
                     {help,view,copy,segment} ...

Positional Arguments

bids_dir

Fullpath to the directory with the input dataset formatted according to the BIDS standard.

output_dir

Fullpath to the directory where the output files will be stored.

analysis_level

Possible choices: participant, group

Level of the analysis that will be performed. Multiple participant level analyses can be run independently (in parallel) using the same output_dir.

Default: 'participant'

command

Possible choices: help, view, copy, segment

Choose a sub-command

Named Arguments

--version

Show program’s version number and exit.

Sub-commands

help

Show cat12 script help.

common_parser help [-h]

view

View batch.

common_parser view [-h] [--verbose {0,1,2,3}]
                   {segment,simple,segment_long,segment_enigma,resample,get_IQR,get_TIV,get_quality,get_ROI_values}

Positional Arguments

target

Possible choices: segment, simple, segment_long, segment_enigma, resample, get_IQR, get_TIV, get_quality, get_ROI_values

Batch name

Named Arguments

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

copy

Copy batch to output_dir.

common_parser copy [-h] [--verbose {0,1,2,3}]
                   {segment,simple,segment_long,segment_enigma,resample,get_IQR,get_TIV,get_quality,get_ROI_values}

Positional Arguments

target

Possible choices: segment, simple, segment_long, segment_enigma, resample, get_IQR, get_TIV, get_quality, get_ROI_values

Batch name

Named Arguments

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

segment

segment

common_parser segment [-h]
                      [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
                      [--verbose {0,1,2,3}]
                      [--bids_filter_file BIDS_FILTER_FILE]
                      [--skip_validation] [--reset_database]
                      [--type {default,simple,long_0,long_1,long_2,long_3,enigma}]

Named Arguments

--participant_label

The label(s) of the participant(s) that should be analyzed. The label corresponds to sub-<participant_label> from the BIDS spec (so it does not include “sub-“).

If this parameter is not provided, all subjects will be analyzed. Multiple participants can be specified with a space separated list.

--verbose

Possible choices: 0, 1, 2, 3

Verbosity level.

Default: 2

--bids_filter_file

A JSON file describing custom BIDS input filters using PyBIDS. For further details, please check out TBD.

--skip_validation

Do not run the bids validation.

Default: False

--reset_database

Resets the database of the input dataset.

Default: False

--type

Possible choices: default, simple, long_0, long_1, long_2, long_3, enigma

Type of segmentation.

default: default CAT12 preprocessing batch; simple: simple processing batch; long_0 - longitudinal developmental; long_1 - longitudinal plasticity/learning; long_2 - longitudinal aging; long_3 - longitudinal save models 1 and 2; enigma - enigma segmentation

Default: 'default'