#!/usr/bin/env python

from distutils.core import setup

setup(name='kmapper',
      version='1.1.0',
      description='Python implementation of mapper algorithm for Topological Data Analysis.',
      long_description='Python implementation of mapper algorithm. This implementation is intended to integrate into scikit-learn and be easily extendible.',
      author='HJ van Veen, Nathaniel Saul',
      author_email='info@mlwave.com, nat@saulgill.com',
      url='https://github.com/MLWAve/kepler-mapper',
      license='MIT',
      packages=['kmapper'],
      install_requires=[
        'scikit-learn',
        'numpy',
        'scipy',
        'Jinja2'
      ],
      test_requires=[
        'pytest'
      ],
      python_requires='>=2.7,!=3.1,!=3.2,!=3.3',
      classifiers=[
        # How mature is this project? Common values are
        #   3 - Alpha
        #   4 - Beta
        #   5 - Production/Stable
        'Development Status :: 3 - Alpha',

        # Indicate who your project is intended for
        'Intended Audience :: Science/Research',
        'Intended Audience :: Education',
        'Intended Audience :: Financial and Insurance Industry',
        'Intended Audience :: Healthcare Industry',
        'Topic :: Scientific/Engineering :: Information Analysis',
        'Topic :: Scientific/Engineering :: Mathematics',

        # Pick your license as you wish (should match "license" above)
         'License :: OSI Approved :: MIT License',

        # Specify the Python versions you support here. In particular, ensure
        # that you indicate whether you support Python 2, Python 3 or both.
        # 'Programming Language :: Python :: 2',
        # 'Programming Language :: Python :: 2.6',
        'Programming Language :: Python :: 2.7',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.4',
        'Programming Language :: Python :: 3.5',
        'Programming Language :: Python :: 3.6',
      ],
      keywords='mapper, topology data analysis, algebraic topology, unsupervised learning'


     )

#!/usr/bin/env python

from distutils.core import setup

setup(name='kmapper',
      version='1.1.1',
      description='Python implementation of Mapper algorithm for Topological Data Analysis.',
      long_description="""
This is a Python implementation of the TDA Mapper algorithm for visualization of high-dimensional data. For complete documentation, see https://MLWave.github.io/kepler-mapper.

KeplerMapper employs approaches based on the Mapper algorithm (Singh et al.) as first described in the paper "Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition".

KeplerMapper can make use of Scikit-Learn API compatible cluster and scaling algorithms.
""",
      author='HJ van Veen, Nathaniel Saul',
      author_email='info@mlwave.com, nat@saulgill.com',
      url='https://MLWave.github.io/kepler-mapper',
      license='MIT',
      packages=['kmapper'],
      install_requires=[
        'scikit-learn',
        'numpy',
        'scipy',
        'Jinja2'
      ],
      test_requires=[
        'pytest'
      ],
      python_requires='>=2.7,!=3.1,!=3.2,!=3.3',
      classifiers=[
        'Development Status :: 4 - Beta',
        'Intended Audience :: Science/Research',
        'Intended Audience :: Education',
        'Intended Audience :: Financial and Insurance Industry',
        'Intended Audience :: Healthcare Industry',
        'Topic :: Scientific/Engineering :: Information Analysis',
        'Topic :: Scientific/Engineering :: Mathematics',
        'License :: OSI Approved :: MIT License',
        'Programming Language :: Python :: 2.7',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.4',
        'Programming Language :: Python :: 3.5',
        'Programming Language :: Python :: 3.6',
      ],
      keywords='mapper, topology data analysis, algebraic topology, unsupervised learning'


     )

update setup with more details and new versions