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Code installation and dataset setup

The Nipoppy workflow comprises a Nipoppy codebase that operates on a Nipoppy dataset with a specific directory structure (initialized with a script).

Nipoppy code+env installation

  1. Change directory to where you want to clone this repo, e.g.: cd /home/<user>/projects/<my_project>/code/
  2. Create a new venv: python3 -m venv nipoppy_env
    • Alternatively (if using Anaconda/Miniconda), create a conda environment: conda create --name nipoppy_env python=3.9
  3. Activate your env: source nipoppy_env/bin/activate
    • If using Anaconda/Miniconda: conda activate nipoppy_env
  4. Clone this repo: git clone
  5. Change directory to nipoppy
  6. Install python dependencies: pip install -e .

Nipoppy dataset directory setup

Run nipoppy/ to create the Nipoppy dataset directory tree:

python nipoppy/ --nipoppy_root <DATASET_ROOT>

  • DATASET_ROOT: root (starting point) of the Nipoppy structured dataset


We suggest naming DATASET_ROOT directory after a study or a cohort.