#!/usr/bin/env python3
from setuptools import setup, find_packages
import pathlib

repo = pathlib.Path(__file__).parent.resolve()
long_description = (repo / "README.md").read_text(encoding="utf-8")
version = (repo / "version").read_text(encoding="utf-8")

setup(
    name="nhsmm",
    author="AWA",
    version=version,
    license="Apache 2.0",
    author_email="dev@awa.si",
    long_description=long_description,
    url="https://github.com/awa-si/NHSMM",
    long_description_content_type="text/markdown",
    description="Neural Hidden Semi-Markov Models with contextual duration, transition and emission modeling.",
    packages=find_packages(exclude=("tests", "examples", "notebooks", "docs")),
    python_requires=">=3.9",
    install_requires=[
        "torch>=2.0",
        "numpy>=1.24",
        "scipy>=1.10",
        "scikit-learn>=1.2",
        "tqdm>=4.66",
        "optuna>=3.0",
        "matplotlib>=3.9",
        "typing_extensions>=4.11",
    ],
    extras_require={
        "dev": [
            "pytest>=8.0",
            "black>=24.0",
            "ruff>=0.6",
            "mypy>=1.11",
            "polars>=1.36",
            "build",
            "twine",
        ],
        "notebooks": [
            "jupyterlab",
            "seaborn",
        ],
    },
    classifiers=[
        "Development Status :: 3 - Alpha",
        "Intended Audience :: Science/Research",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Information Analysis",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
    ],
    keywords="neural-hsmm, hidden-semi-markov-model, probabilistic, deep-learning, pytorch, regime-detection",
    include_package_data=True,
    zip_safe=False,
)
