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setup.py
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setup.py
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# -*- coding: utf-8 -*-
import os
os.environ["MPLCONFIGDIR"] = "."
from setuptools import setup, find_packages
DESCRIPTION = 'A python package for visualizing and manipulating high-dimensional data'
LONG_DESCRIPTION = """\
HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation).
For sample Jupyter notebooks using the package: https://github.com/ContextLab/hypertools-paper-notebooks
For more examples: https://github.com/ContextLab/hypertools/tree/master/examples
Some key features of HyperTools are:
- Functions for plotting high-dimensional datasets in 2/3D.
- Static and animated plots
- Simple API for customizing plot styles
- A set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more.
- Support for lists of Numpy arrays, Pandas dataframes, String, Geos or mixed lists.
"""
LICENSE = 'MIT'
setup(
name='hypertools',
version='0.5.0',
description=DESCRIPTION,
long_description=LONG_DESCRIPTION,
author='Contextual Dynamics Lab',
author_email='[email protected]',
url='https://github.com/ContextLab/hypertools',
download_url = 'https://github.com/ContextLab/hypertools',
license=LICENSE,
packages=find_packages(exclude=('images', 'examples', 'tests')),
install_requires=[
'PPCA>=0.0.2',
'scikit-learn>=0.19.1',
'pandas>=0.18.0',
'seaborn>=0.8.1',
'matplotlib>=1.5.1',
'scipy>=1.0.0',
'numpy>=1.10.4',
'hdbscan>=0.8.11',
'umap-learn>=0.1.5',
'future',
'requests',
'deepdish',
'six'
],
classifiers=[
'Intended Audience :: Science/Research',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3.4',
'Topic :: Scientific/Engineering :: Visualization',
'Topic :: Multimedia :: Graphics',
'Operating System :: POSIX',
'Operating System :: Unix',
'Operating System :: MacOS'],
)