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INSTALL.md

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How to install NARPS Open Pipelines ?

1 - Fork the repository

Fork the repository, so you have your own working copy of it.

2 - Clone the code

First, install Datalad. This will allow you to access the NARPS data easily, as it is included in the repository as datalad subdatasets.

Then, clone the project :

# Replace YOUR_GITHUB_USERNAME in the following command.
datalad install --recursive https://github.com/YOUR_GITHUB_USERNAME/narps_open_pipelines.git

Warning

It is still possible to clone the fork using git ; but by doing this, you will only get the code.

# Replace YOUR_GITHUB_USERNAME in the following command.
git clone https://github.com/YOUR_GITHUB_USERNAME/narps_open_pipelines.git

3 - Get the data

Now that you cloned the repository using Datalad, you are able to get the data :

# Move inside the root directory of the repository.
cd narps_open_pipelines

# Select the data you want to download. Here is an example to get data of subjects sub-001, sub-002, sub-003 and sub-004.
datalad get data/original/ds001734/sub-00[1-4] -J 12
datalad get data/original/ds001734/derivatives/fmriprep/sub-00[1-4] -J 12

# Here is an example to get original results data from team 08MQ
datalad get data/results/orig/4953_08MQ/* -J 12

Note

For further information and alternatives on how to get the data, see the corresponding documentation page docs/data.md. Also visit this page to get the whole dataset.

4 - Set up the environment

Install Docker then pull the nipype Docker image :

docker pull nipype/nipype:py38

Once it's done you can check the image is available on your system :

docker images
   REPOSITORY                 TAG       IMAGE ID        CREATED         SIZE
   docker.io/nipype/nipype    py38      0f3c74d28406    9 months ago    22.7 GB

Note

Feel free to read this documentation page docs/environment.md to get further information about this environment.

5 - Run the project

Start a Docker container from the Docker image :

# Replace PATH_TO_THE_REPOSITORY in the following command (e.g.: with /home/user/dev/narps_open_pipelines/)
docker run -it -v PATH_TO_THE_REPOSITORY:/work/ nipype/nipype:py38

Optionally edit the configuration file narps_open/utils/configuration/default_config.toml so that the referred paths match the ones inside the container. E.g.: if using the previous command line, the directories part of the configuration file should be :

# default_config.toml
# ...

[directories]
dataset = "/work/data/original/ds001734/"
reproduced_results = "/work/data/reproduced/"
narps_results = "/work/data/results/"

# ...

Note

Further information about configuration files can be found on the page docs/configuration.md.

Install NARPS Open Pipelines inside the container :

source activate neuro
cd /work/
pip install .

Finally, you are able to use the scripts of the project :

  • narps_open_runner: run pipelines
  • narps_open_tester: run a pipeline and test its results against original ones from the team
  • narps_open_correlations: compute and display correlation between results and original ones from the team
  • narps_description: get the textual description made by a team
  • narps_results: download the original results from teams
  • narps_open_status: get status information about the development process of the pipelines
# Run the pipeline for team 2T6S, with subjects sub-001, sub-002, sub-003 and sub-004
narps_open_runner -t 2T6S -s 1 2 3 4

# Run the pipeline for team 08MQ, compare results with original ones,
#   and produces a report with correlation values.
#   WARNING : this will run the pipeline on more than the 4 first subjects
narps_open_tester -t 08MQ

# Compute the correlation values between results of 2T6S reproduction on 60 subjects with original ones
#   WARNING : 2T6S must have been previously computed with a group of 60 subjects
narps_open_correlations -t 2T6S -n 60

# Get the description of team C88N in markdown formatting
narps_description -t C88N --md

# Download the results from team 2T6S
narps_results -t 2T6S

#  Get the pipeline work status information in json formatting
narps_open_status --json

Note

For further information about these command line tools, read the corresponding documentation pages.