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setup.py
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75 lines (66 loc) · 2.15 KB
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import os
import pathlib
from setuptools import setup
# =============================================================================
# CONSTANTS
# =============================================================================
PATH = pathlib.Path(os.path.abspath(os.path.dirname(__file__)))
REQUIREMENTS = [
"matplotlib==3.5.2",
"numpy==1.21.6",
"pandas==1.3.5",
"pyvalem==2.5.7",
"torch==1.11.0",
"scikit-learn==0.24.2",
"joblib==1.0.0",
]
with open(PATH / "ESPNN" / "__init__.py") as fp:
for line in fp.readlines():
if line.startswith("__version__ = "):
VERSION = line.split("=", 1)[-1].replace('"', "").strip()
break
with open("README.md", "r") as readme:
LONG_DESCRIPTION = readme.read()
# =============================================================================
# FUNCTIONS
# =============================================================================
setup(
name="ESPNN",
version=VERSION,
description="Electronic Stopping Power Neural Network predictor",
long_description=LONG_DESCRIPTION,
long_description_content_type="text/markdown",
author="""
Felipe Bivort Haiek,
Alejandra Mendez,
Claudia Montanari,
Darío Mitnik
""",
author_email="felipebihaiek@gmail.com, alemdz.7@gmail.com",
url="https://github.com/ale-mendez/SPNN",
packages=["ESPNN", "ESPNN.data"],
include_package_data=True,
install_requires=REQUIREMENTS,
license="The GPLv3 License",
keywords=[
"Stopping Power",
"Energy Loss",
"Atoms",
"Molecules",
"Ions",
"Machine Learning",
"Neural Network",
],
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Operating System :: OS Independent",
"Programming Language :: Python",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Topic :: Scientific/Engineering",
],
)