Export of FSL statistical results using NIDM as specified at http://nidm.nidash.org/specs/nidm-results.html.
Project description
NIDM-Results for FSL
Export mass-univariate neuroimaging results computed in FSL (using FEAT) as NIDM-Results packs.
A NIDM-Results pack is a compressed file containing a NIDM-Results serialization and some or all of the referenced image data files in compliance with NIDM-Results specification.
Usage
usage: nidmfsl [-h] [-g GROUP_NAME NUM_SUBJECTS] [-o OUTPUT_NAME] [-d]
[-n NIDM_VERSION] [--version]
feat_dir
NIDM-Results exporter for FSL Feat.
positional arguments:
feat_dir Path to feat directory.
optional arguments:
-h, --help show this help message and exit
-g GROUP_NAME NUM_SUBJECTS, --group GROUP_NAME NUM_SUBJECTS
Group label followed by number of subjects
-o OUTPUT_NAME, --output_name OUTPUT_NAME
Name of the output. A ".nidm.zip" or ".nidm" (when -d
is used) suffix will be appended.
-d, --directory-output
Produces a .nidm directory rather than a .nidm.zip
file.
-n NIDM_VERSION, --nidm_version NIDM_VERSION
NIDM-Results version to use (default: latest).
--version show program's version number and exit
Installation
To install, run the below command in the bash terminal.
pip install nidmfsl
Compatible with
FSL version 5.0.9
Testing
Requirements
To run the tests for this repository, the following must be installed
-
Git LFS. Installation instructions for Git LFS can be found here.
-
The python packages
vcr
andddt
. These can be installed using the below commands in the bash terminal:
pip install vcrpy
pip install ddt
In addition, the test data must also be downloaded from the nidmresults-examples
repository to <path_to_this_repository>/test/data/nidmresults-examples
.
git lfs clone https://github.com/incf-nidash/nidmresults-examples.git <path_to_this_repository>/test/data/nidmresults-examples
Running the tests
The below command can be used to generate the test cases.
python <path_to_this_repository>/test/export_test_battery.py
Folowing this, the test cases can be verified against the ground truth provided in the nidmresults-examples
repository using the below command.
cd <path_to_this_repository>/test/
python -m unittest discover
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