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Predictive Clinical Neuroscience Toolkit

Documentation Status DOI

Github

Predictive Clinical Neuroscience software toolkit (formerly nispat).

Methods for normative modelling, spatial statistics and pattern recognition. Documentation, including tutorials can be found on readthedocs. Click on the docs button above to visit the site.

Basic installation (on a local machine)

Install anaconda3

using the download here: https://www.anaconda.com/download

Create environment

conda create -n <env_name> python==3.12

Activate environment

source activate <env_name>

Install PCNtoolkit

Using pip:

pip install pcntoolkit

Using a local clone of the repo:

python -m pip install .

Test installation

python -c "import pcntoolkit as pk;print(pk.__file__)"

Troubleshooting

Nutpie installation failure

On some older architectures, the installation of nutpie may fail due to a missing Rust compiler. If this is the case, you can install it manually using conda prior to installing PCNtoolkit:

# install nutpie
conda install -c conda-forge nutpie
# install PCNtoolkit
pip install pcntoolkit

Alternative installation (on a shared resource)

Make sure conda is available on the system.

Otherwise install it first from https://www.anaconda.com/

conda --version

Create a conda environment in a shared location

conda create -y python==3.12 --prefix=/shared/conda/<env_name>

Activate the conda environment

conda activate /shared/conda/<env_name>

Clone the repo

git clone https://github.com/amarquand/PCNtoolkit.git

Install in the conda environment

cd PCNtoolkit/
python -m pip install .

Test installation

python -c "import pcntoolkit as pk;print(pk.__file__)"

Quickstart usage

For normative modelling, functionality is handled by the normative.py script, which can be run from the command line, e.g.

# python normative.py -c /path/to/training/covariates -t /path/to/test/covariates -r /path/to/test/response/variables /path/to/my/training/response/variables

For more information, please see the following resources: