y3-deep-lss/pyproject.toml at main · des-science/y3-deep-lss · GitHub

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

[project]
name = "deep_lss"
version = "0.1.0"
description = "Neural networks for informative summary statistics from DES Y3-like weak lensing and galaxy clustering maps"
readme = "README.md"
requires-python = ">=3.8"
license = {text = "MIT"}
authors = [
    {name = "Arne Thomsen", email = "athomsen@phys.ethz.ch"}
]
keywords = ["cosmology", "deep-learning", "neural-networks", "weak-lensing", "galaxy-clustering", "summary-statistics", "mutual-information"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering :: Astronomy",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.8",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
]

dependencies = [
    "numpy",
    "scipy",
    "healpy",
    "scikit-learn",
    "h5py",
    "pyyaml",
    "wandb",
    "icecream",
]

[project.optional-dependencies]
# Only for environments where TensorFlow/Horovod are not pre-installed
tf = [
    "tensorflow>=2.0",
    "tensorflow-probability",
    "horovod[tensorflow]",
]

# Development tools
dev = [
    "pytest",
    "pytest-cov",
    "black",
    "flake8",
    "ipython",
    "jupyter",
    "matplotlib",
]

[project.urls]
Repository = "https://github.com/des-science/y3-deep-lss"
Documentation = "https://arxiv.org/abs/2511.04681"

[tool.setuptools]
packages = ["deep_lss"]

[tool.setuptools.package-data]
deep_lss = ["*.yaml", "*.yml"]

[tool.black]
line-length = 119
target-version = ['py38', 'py39', 'py310', 'py311']

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = "test_*.py"
python_classes = "Test*"
python_functions = "test_*"