/
setup.cfg
128 lines (104 loc) · 2.46 KB
/
setup.cfg
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[metadata]
name = EnergyFlow
description = Python package for the Energy Flow suite of particle physics tools
author = Patrick T. Komiske III
author_email = pkomiske@mit.edu
license = GPL-3.0
license_file = LICENSE
long_description = file: README.md
long_description_content_type = text/markdown
url = https://energyflow.network
project_urls =
Source Code = https://github.com/pkomiske/EnergyFlow
Issues = https://github.com/pkomiske/EnergyFlow/issues
keywords =
energy flow
energyflow
physics
jets
correlator
multigraph
polynomial
EFP
EFN
EFM
PFN
EMD
Wasserstein
Energy Flow Polynomial
Energy Flow Moment
Energy Flow Network
Particle Flow Network
Earth Mover Distance
Deep Sets
architecture
neural network
metric
collider
CMS
open
Open Data
MOD
substructure
classifiers =
Development Status :: 5 - Production/Stable
Intended Audience :: Developers
Intended Audience :: Science/Research
License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Natural Language :: English
Operating System :: MacOS
Operating System :: Microsoft :: Windows
Operating System :: POSIX :: Linux
Operating System :: Unix
Programming Language :: C++
Programming Language :: Python
Programming Language :: Python :: 3
Programming Language :: Python :: 3 :: Only
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
Topic :: Scientific/Engineering
Topic :: Scientific/Engineering :: Information Analysis
Topic :: Scientific/Engineering :: Mathematics
Topic :: Scientific/Engineering :: Physics
Topic :: Software Development :: Libraries :: Python Modules
[options]
packages = find:
python_requires =
>= 3.7
install_requires =
numpy >= 1.12.0
six
h5py >= 2.9.0
wasserstein >= 1.0.1
setup_requires=
pytest-runner
[options.package_data]
* =
data/*
[options.extras_require]
generation =
python-igraph
examples =
tensorflow >= 2.5.0
scikit-learn
matplotlib
archs =
tensorflow >= 2.5.0
scikit-learn
tests =
pot >= 0.8.0
pytest
python-igraph
python-igraph == 0.8.3; python_version=='2.7'
tensorflow >= 2.5.0
scikit-learn
all =
python-igraph
tensorflow >= 2.5.0
scikit-learn
[bdist_wheel]
universal = 1
[aliases]
test = pytest