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How to run NARPS open pipelines ? 🏃

Using the runner application

The narps_open.runner module allows to run pipelines from the command line.

Tip

In the following examples, use narps_open_runner or python narps_open/runner.py indifferently to launch the command line tool.

narps_open_runner -h
	usage: runner.py [-h] -t TEAM (-r RANDOM | -s SUBJECTS [SUBJECTS ...]) [-g | -f]

	Run the pipelines from NARPS.

	options:
	  -h, --help            show this help message and exit
	  -t TEAM, --team TEAM  the team ID
	  -r RANDOM, --random RANDOM the number of subjects to be randomly selected
	  -s SUBJECTS [SUBJECTS ...], --subjects SUBJECTS [SUBJECTS ...] a list of subjects
	  -g, --group           run the group level only
	  -f, --first           run the first levels only (preprocessing + subjects + runs)
	  -c, --check           check pipeline outputs (runner is not launched)

narps_open_runner -t 2T6S -s 001 006 020 100
narps_open_runner -t 2T6S -r 4
narps_open_runner -t 2T6S -r 4 -f
narps_open_runner -t 2T6S -r 4 -f -c # Check the output files without launching the runner

Note

In this usecase, the paths where to store the outputs and to the dataset are picked by the runner from the configuration.

Using the PipelineRunner object

The class PipelineRunner is available from the narps_open.runner module. You can use it from inside python code, as follows :

from narps_open.runner import PipelineRunner

# Initialize a PipelineRunner by choosing the team ID
runner = PipelineRunner(team_id = '2T6S')

# Set input and output directories
runner.pipeline.directories.dataset_dir = '/data/ds001734/'
runner.pipeline.directories.results_dir = '/output/'
runner.pipeline.directories.set_output_dir_with_team_id(runner.team_id)
runner.pipeline.directories.set_working_dir_with_team_id(runner.team_id)

# Set participants / subjects
runner.subjects = ['001', '006', '020', '100']

# Alternatively, ask the runner to pick a random number of subjects
# runner.random_nb_subjects = 4

# Start the runner
runner.start()

# Or start the first level only (preprocessing + run level + subject level)
runner.start(True, False)

# Or start the second level only (group level)
runner.start(True, True)

# Get the list of missing files (if any) after the pipeline finished
runner.get_missing_first_level_outputs()
runner.get_missing_group_level_outputs()