setup.py

"""
Author: Dr. John T. Hwang <hwangjt@umich.edu>
        Dr. Mohamed A. Bouhlel <mbouhlel@umich.edu>
        Remi Lafage <remi.lafage@onera.fr>
        Lucas Alber <lucasd.alber@gmail.com>

This package is distributed under New BSD license.
"""
from setuptools import setup, Extension
import sys
import numpy as np
from Cython.Build import cythonize

from smt import __version__

CLASSIFIERS = """\
Development Status :: 5 - Production/Stable
Intended Audience :: Science/Research
Intended Audience :: Developers
License :: OSI Approved :: BSD License
Programming Language :: C++
Programming Language :: Python
Programming Language :: Python :: 3
Programming Language :: Python :: 3.7
Programming Language :: Python :: Implementation :: CPython
Topic :: Software Development
Topic :: Scientific/Engineering
Operating System :: Microsoft :: Windows
Operating System :: Unix
Operating System :: MacOS
"""

LONG_DESCRIPTION = """
The surrogate modeling toolbox (SMT) is a Python package that contains 
a collection of surrogate modeling methods, sampling techniques, and 
benchmarking functions. This package provides a library of surrogate 
models that is simple to use and facilitates the implementation of additional methods. 

SMT is different from existing surrogate modeling libraries because of 
its emphasis on derivatives, including training derivatives used for 
gradient-enhanced modeling, prediction derivatives, and derivatives 
with respect to the training data. It also includes new surrogate models 
that are not available elsewhere: kriging by partial-least squares reduction 
and energy-minimizing spline interpolation.
"""

extra_compile_args = []
if not sys.platform.startswith("win"):
    extra_compile_args.append("-std=c++11")

ext = (
    cythonize(
        Extension(
            "smt.surrogate_models.rbfclib",
            sources=["smt/src/rbf/rbf.cpp", "smt/src/rbf/rbfclib.pyx"],
            language="c++",
            extra_compile_args=extra_compile_args,
            include_dirs=[np.get_include()],
        )
    )
    + cythonize(
        Extension(
            "smt.surrogate_models.idwclib",
            sources=["smt/src/idw/idw.cpp", "smt/src/idw/idwclib.pyx"],
            language="c++",
            extra_compile_args=extra_compile_args,
            include_dirs=[np.get_include()],
        )
    )
    + cythonize(
        Extension(
            "smt.surrogate_models.rmtsclib",
            sources=[
                "smt/src/rmts/rmtsclib.pyx",
                "smt/src/rmts/utils.cpp",
                "smt/src/rmts/rmts.cpp",
                "smt/src/rmts/rmtb.cpp",
                "smt/src/rmts/rmtc.cpp",
            ],
            language="c++",
            extra_compile_args=extra_compile_args,
            include_dirs=[np.get_include()],
        )
    )
)


metadata = dict(
    name="smt",
    version=__version__,
    description="The Surrogate Modeling Toolbox (SMT)",
    long_description=LONG_DESCRIPTION,
    author="Mohamed Amine Bouhlel et al.",
    author_email="mbouhlel@umich.edu",
    license="BSD-3",
    classifiers=[_f for _f in CLASSIFIERS.split("\n") if _f],
    packages=[
        "smt",
        "smt.surrogate_models",
        "smt.problems",
        "smt.sampling_methods",
        "smt.utils",
        "smt.utils.neural_net",
        "smt.applications",
    ],
    install_requires=[
        "scikit-learn",
        "pyDOE2",
        "scipy",
    ],
    extras_require={
        "numba": [  # pip install smt[numba]
            "numba~=0.56.4",
        ],
    },
    python_requires=">=3.7",
    zip_safe=False,
    ext_modules=ext,
    url="https://github.com/SMTorg/smt",  # use the URL to the github repo
    download_url="https://github.com/SMTorg/smt/releases",
)

setup(**metadata)