pyproject.toml

[tool.poetry]
name = "cg-gnn"
version = "0.3.2"
description = "Train a graph neural network on cell graphs."
license = "AGPL-3.0-or-later"
authors = ["Carlin Liao <liaoc2@mskcc.org>"]
readme = "README.md"
repository = "https://github.com/nadeemlab/cg-gnn"
keywords = ["gnn", "pathology", "omics", "single-cell", "graph", "network", "deep-learning", "machine-learning", "cancer", "predictive-modeling", "predictive-medicine", "precision-medicine", "precision-oncology", "precision-pathology", "precision-health", "precision-healthcare"]
packages = [{include = "cggnn"}]

[tool.poetry.dependencies]
h5py = "*"
matplotlib = "*"
numpy = "*"
pandas = "*"
tables = "*"
python = "^3.10"
scikit-learn = "*"
scipy = "*"
tqdm = "*"

[tool.poetry.scripts]
cg-gnn-train = 'cggnn.scripts.train:main'
cg-gnn-separability = 'cggnn.scripts.separability:main'

[tool.poetry.group.dev]
optional = true

[tool.poetry.group.dev.dependencies]
autopep8 = "*"
pycodestyle = "*"
pydocstyle = "*"
dgl-cu118 = {url = "https://data.dgl.ai/wheels/cu118/repo.html"}
torch = {url = "https://download.pytorch.org/whl/cu118/torch-2.0.1%2Bcu118-cp311-cp311-linux_x86_64.whl"}