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setup.py
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52 lines (48 loc) · 2.23 KB
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import os
from setuptools import setup
from pySPACEOptimizer.framework import OPTIMIZER_ENTRY_POINT, TASK_ENTRY_POINT
directory_name = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(directory_name, "README.md"), "rb") as readme:
description = readme.read()
setup(
name="pySPACEOptimizer",
version="0.1.0",
description="Hyperparameter optimizer for pySPACE",
long_description=description,
author="Torben Hansing",
author_email="hansa@tzi.de",
url="https://gitlab.informatik.uni-bremen.de/hansa/pyspace_optimizer",
packages=["pySPACEOptimizer"],
# FIXME: Include pySPACE as dependency as soon as the setup.py of the package does install the software correctly
install_requires=["numpy", "hyperopt", 'scipy'],
extras_require={
"graphs": "matplotlib",
"performance_analysis": "PyQt4"
},
entry_points={
"console_scripts": [
"pySPACEOptimizer = pySPACEOptimizer.core.__main__:main"
],
"gui_scripts": [
"optimizerPerformanceAnalysis = pySPACEOptimizer.hyperopt.tools.performance_analysis:main"
],
OPTIMIZER_ENTRY_POINT: [
"HyperoptOptimizer = pySPACEOptimizer.hyperopt.optimizer:HyperoptOptimizer",
"SerialHyperoptOptimizer = pySPACEOptimizer.hyperopt.optimizer:SerialHyperoptOptimizer",
],
TASK_ENTRY_POINT: [
"classification = pySPACEOptimizer.hyperopt.classification_task:ClassificationTask",
"classificationWithoutScikit = pySPACEOptimizer.hyperopt.classification_task:ClassificationTaskWithoutScikit",
"regression = pySPACEOptimizer.hyperopt.regression_task:RegressionTask",
]
},
classifiers=["Development Status :: 2 - Pre-Alpha",
"Environment :: Console",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Programming Language :: Python :: 2.7",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Scientific/Engineering :: Information Analysis"],
)