pyproject.toml

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "inverse-canopy"
version = "0.0.22"
description = "Tensorflow based library for back-fitting event tree conditional/functional event probability distributions to match target end-state frequencies."
readme = "README.md"
authors = [{name = "Arjun Earthperson", email = "a.earthperson@openpra.org"}]
license = {file = "LICENSE"}
requires-python = ">=3.10"
keywords = ["tensorflow", "probability", "event tree", "fault tree", "scientific"]
classifiers = [
    "Development Status :: 2 - Pre-Alpha",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",
    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Software Development :: Libraries",
    "Topic :: Scientific/Engineering",
    "Typing :: Typed"
]

dependencies = [
"tensorflow>=2.17.0",
"tensorflow-probability>=0.24.0",
"tf-keras>=2.17.0",
"numpy>=1.26.4",
"scipy>=1.14.0",
"matplotlib>=3.9.2"
]


[project.optional-dependencies]
cuda = [
    "tensorflow[and-cuda]"
]
metal = [
    "tensorflow==2.13.1",
    "tensorflow-metal==1.0.0",
    "tensorflow-probability==0.21.0"
]
test = [
    "pytest-xdist",
    "pytest",
    "pytest-cov",
    "ruff"
]
dev = [
    "build",
    "pytest-xdist",
    "pytest",
    "pytest-cov",
    "ruff",
    "twine"
]

[project.urls]
Homepage = "https://openpra.org"
Repository = "https://github.com/openpra-org/inverse-canopy"
Documentation = "https://docs.openpra.org"


[project.scripts]

[tool.pytest.ini_options]
addopts = "-ra -v --strict-markers"
testpaths = [
    "tests"
]


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