Reproduce the python environment using the requirements.txt.
2. Run cookiecutter to create the template:
cookiecutter template
3.Enter your model's information: You will be asked for the following information:
"example_name": "example_name",
"author_name": "Your name (or your organization/team)",
"description": "A short description of the example.",
"dataset_path": "The local path to the dataset being used"
"model_json_path": "Path to the json describing the model",
"scan_length": "Scan length. Can be inferred from the images if these are
availiable",
"derivatives": "Path to the fmriprep derivatives. If no derivatives are
availiable type None."
Note: To use this cookiecutter you will need to have already downloaded the data
that you want to analyze and have already defined a model.json that describes
the BIDS Stats Models.
4. This cookiecutter create the following directory tree:
{example_name}
├── README.md
├── data
└── data -> symbolic link to the data
├── model
│ └── model-{example_name}_smdl.json -> symbolic link to the passed model file
└── report.py