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setup.py
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setup.py
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from setuptools import setup
meta = {}
with open("pydmd/meta.py") as fp:
exec(fp.read(), meta)
# Package meta-data.
NAME = meta['__title__']
DESCRIPTION = 'Python Dynamic Mode Decomposition.'
URL = 'https://github.com/mathLab/PyDMD'
MAIL = meta['__mail__']
AUTHOR = meta['__author__']
VERSION = meta['__version__']
KEYWORDS = 'dynamic-mode-decomposition dmd mrdmd fbdmd cdmd'
REQUIRED = [
'future', 'numpy', 'scipy', 'matplotlib', 'ezyrb'
]
EXTRAS = {
'docs': ['Sphinx==1.4', 'sphinx_rtd_theme'],
'test': ['pytest', 'pytest-cov'],
}
LDESCRIPTION = (
"PyDMD is a Python package that uses Dynamic Mode Decomposition for "
"a data-driven model simplification based on spatiotemporal coherent "
"structures.\n"
"\n"
"Dynamic Mode Decomposition (DMD) is a model reduction algorithm "
"developed by Schmid (see 'Dynamic mode decomposition of numerical and "
"experimental data'). Since then has emerged as a powerful tool for "
"analyzing the dynamics of nonlinear systems. DMD relies only on the "
"high-fidelity measurements, like experimental data and numerical "
"simulations, so it is an equation-free algorithm. Its popularity is "
"also due to the fact that it does not make any assumptions about the "
"underlying system. See Kutz ('Dynamic Mode Decomposition: "
"Data-Driven Modeling of Complex Systems') for a comprehensive "
"overview of the algorithm and its connections to the Koopman-operator "
"analysis, initiated in Koopman ('Hamiltonian systems and "
"transformation in Hilbert space'), along with examples in "
"computational fluid dynamics.\n"
"\n"
"In the last years many variants arose, such as multiresolution DMD, "
"compressed DMD, forward backward DMD, and higher order DMD among "
"others, in order to deal with noisy data, big dataset, or spurius "
"data for example.\n"
"\n"
"In PyDMD we implemented the majority of the variants mentioned above "
"with a user friendly interface.\n"
"\n"
"The research in the field is growing both in computational fluid "
"dynamic and in structural mechanics, due to the equation-free nature "
"of the model.\n"
)
setup(
name=NAME,
version=VERSION,
description=DESCRIPTION,
long_description=LDESCRIPTION,
author=AUTHOR,
author_email=MAIL,
classifiers=[
'Development Status :: 5 - Production/Stable',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering :: Mathematics'
],
keywords=KEYWORDS,
url=URL,
license='MIT',
packages=[NAME],
install_requires=REQUIRED,
extras_require=EXTRAS,
include_package_data=True,
zip_safe=False,
)