simexp_gcn

The SIMEXP lab package for GCN

Installation

We recommend to install the package inside a python virtual environment.

python3 -m venv ~/.virtualenvs/gcn_package
source ~/.virtualenvs/gcn_package/bin/activate

Now install the package using pip.

git clone https://github.com/SIMEXP/gcn_package/edit/main/README.md
cd gcn_package
python3 -m pip install -r requirements.txt

Computecanada

Before creating the virtual environment, make sure you are using python3.

module load python/3.8

TODO:

• [ ] Tests for graph construction functions
• [ ] Tests for data util functions
• [ ] Tests for TimeWindows dataset
• [ ] Update notebook implementation to use src - (tutorial)
• [ ] Document functions
• [ ] Implement val loop
• [ ] Implement error throwing/valid input checks
• [ ] Implement padding in split timeseries
  • timeseries length can be flexible
  • window size won't need to be a divisor
• [ ] Command line tool for end-to-end training (optionnal)
  • Auto-encoder (target is the input) or classification (label)
  • agnostic timeseries-splitting and labelling:
    • Read participant condition (label) from paticipant file or phenotype.
    • Split and task-label based from task event file
    • file should contain at least id

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data               <- Input data directory
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── gcn_package        <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Modules for custom pytorch datasets & utils.
│   │   └── time_windows_dataset.py
│   │   └── data_loader.py
│   │   └── utils.py
│   │
│   ├── features       <- Modules for building features from data.
│   │   └── graph_construction.py
│   │
│   ├── models         <- Modules for different model architectures & utils to run them.
│   │   ├── gcn.py
│   │   └── utils.py
│   │
│   └── visualization  <- Modules to create exploratory and results oriented visualizations
│       └── visualize.py

Project based on the cookiecutter data science project template. #cookiecutterdatascience