how-to-use-me.md

How to use this template

• How to use this template
  • Prerequisites
  • Get (install) this cooked repo on your computer with Datalad
  • Dataset structure
    • Set up automatically the subdatasets
  • DEMO

Prerequisites

• You will need to have datalad installed, check this for a crash course

Get (install) this cooked repo on your computer with Datalad

1. Click the green button Use this template.

2. Give a name to the repository you want to create. Something short that contains the name of your experiment: analysis_fMRI_FaceLocalizer.

3. Decide if you want this new repo to be public or private.

4. Click on Create repository from template

You now have a copy of the template on your Github account. You can then download the code and the pre-set dependencies like this.

1. Click on green Code button and copy the URL_to_your_repo that is shown there.
2. Open a terminal and type this:

datalad install --recursive URL_to_your_repo

This will set up everything automatically in your current directory.

Dataset structure

• All inputs (i.e. building blocks from other sources) are located in inputs/.
• All custom code is located in code/.
• All outputs will go in outputs/

Set up automatically the subdatasets

To do so, you need to:

1. create on GIN the empty repository for each of the (sub)subdataset
2. copy each (ssh) URL of the the just created GIN repo into dataladConfig.sh
3. run bash dataladSetUp.sh

Note that if any of the URLs in dataladConfig.sh is left empty then the subdatasets will still be created but no sibling will be added and you will have to set the siblings manually and set the url in the parent dataset. This can be quite annoying so we strongly recommend creating the remote repos first.

These scripts can be modified to everyone needs (eg also add into derivatives fmriprep or mriqc or freesurfer or etc.).

The script dataladSetUp.sh as it is will:

1. install a ready inputs/raw dataset from a URL (either from openneuro or GIN)
2. install
   • a subdataset outputs/derivatives
   • install sub-subdatasets for
     • outputs/derivatives/cpp_spm-preproc
     • outputs/derivatives/cpp_spm-preproc
3. make sure that the derivatives folders are datalad datasets and not pure git repos

.
└── derivatives
    ├── cpp_spm-preproc
    └── cpp_spm-stats

DEMO

Use this URL for the raw data set in dataladConfig.sh

[email protected]:/cpp-lln-lab/CPP_visMotion-raw.git

You will need to set up a proper alias to launch matlab from your mac or linux command line to tdo the next step:

matlab -nodisplay -nosplash -nodesktop -r "run('code/src/demoRunSpatialPrepro.m'); exit;"

# OR
matlab -nodisplay -nosplash -nodesktop -r 'run code/src/demoRunSpatialPrepro.m; exit;'

To make it easier to understand, when can use some bash variables

MATFLAGS="-nodisplay -nosplash -nodesktop"
cmd_to_run="run('code/src/demoRunSpatialPrepro.m'); exit;"
matlab $MATFLAGS -r "$cmd_to_run"

And now we insert in a datalad run command

# THIS DOES NOT WORK
datalad run -m "Try again to create a list of podcast titles" \
 --input "inputs/raw" \
 --output "outputs/derivatives" \
 "matlab -nodisplay -nosplash -nodesktop -r 'run code/src/demoRunSpatialPrepro.m; exit;'"

datalad run -m "Try again to create a list of podcast titles" \
   --input "inputs/raw" \
   --output "outputs/derivatives" \
  'matlab $MATFLAGS -r "$cmd_to_run"'