multi-dwpc/pyproject.toml at eb0a84eddeee556b64296e2850affcae5267f683 · greenelab/multi-dwpc · GitHub

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[project]
name = "multi-dwpc"
version = "0.1.0"
description = "Scripts testing aggregate degree weighted path count (DWPC) statistics"
readme = "README.md"
license = "BSD-2-Clause-Patent"
requires-python = ">=3.13"
dependencies = [
    "pandas",
    "numpy",
    "scipy",
    "scikit-learn",
    "statsmodels",
    "matplotlib",
    "seaborn",
    "jupyterlab",
    "jupytext",
    "tqdm",
    "httpx",
    "pyarrow",
    "hetmatpy==0.1.0",
    "hetnetpy @ git+https://github.com/hetio/hetio.git@0a81e9ea675e2c20f235f5d74598053c1332cb85",
    "hetnet-analysis @ git+https://github.com/CU-DBMI/hetionet-analysis.git@f371064da1498ac984aa6ec6ed0ba2739c7b0259",
]

[project.optional-dependencies]
dev = [
    "jupytext",
    "poethepoet",
]

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[tool.setuptools.packages.find]
where = ["."]
include = ["src*"]

[tool.poe.tasks]
# Individual pipeline steps
load-data = "python scripts/load_data.py"
filter-change = "python scripts/percent_change_and_filtering.py"
go-hierarchy-analysis = "python scripts/go_hierarchy_analysis.py"
filter-jaccard = "python scripts/jaccard_similarity_and_filtering.py"
gen-permutation = "python scripts/permutation_null_datasets.py"
gen-random = "python scripts/random_null_datasets.py"

# DWPC computation
# Option A: Direct matrix computation (no Docker required)
compute-dwpc-direct = "python scripts/compute_dwpc_direct.py"

# Testing
test-dwpc-accuracy = "python scripts/test_dwpc_accuracy.py"
benchmark-dwpc = "python scripts/benchmark_dwpc_methods.py"

# Grouped tasks
pipeline-production = "python scripts/pipeline_production.py"
pipeline-null = ["gen-permutation", "gen-random"]