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PRF-Analyze PRFPY

This app is part of a validation framework for fMRI analysis tools. It builds upon the BIDS file structure and can be used to verify the integrity in terms of reproduction of ground truth of e.g. prf-models.

This app is an alternative implementation to this validation framework, i.e. the prfanalyze part is taking over here. Hence, the prfsynth dockerimage should be used to synthesize data in order to know the ground truth. After using this app, the prfreport dockerimage can be used to create meaningful and insightful visual reports about the goodness of fit achieved by this and/or other analysis tools.

Description

This app will apply a user-specified analysis to a given BIDS dataset.

Usage

This App has the following command line arguments:

	usage: run.py [-h]
	              [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
	              bids_dir config_file

	prfanalyze-prfpy entry point script.

	positional arguments:
	  bids_dir              The directory with the input dataset formatted
	                        according to the BIDS standard.
	  config_file			The path to a yaml file containing all necessary information to perform the 							  prf-fitting

	optional arguments:
	  -h, --help            show this help message and exit
	  --participant_label PARTICIPANT_LABEL [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.

To run it in (for one participant):

docker run -i --rm \
	-v $basedir/BIDS:/bids_dataset \
	-v analyze-prfpy/default_config.yml:/config.yml \
	niklasmueller/prfanalyze-prfpy \
	/bids_dataset \
	/config.yml --participant_label 01

About

This an example app that can serve as a template.

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  • Python 90.6%
  • Dockerfile 6.7%
  • Shell 2.7%