old_contents: # -*- coding: utf-8 -*-
  import os
  import subprocess
  import sys
  from setuptools import setup, find_packages
  from setuptools.command.install import install
  
  
  os.environ["MPLCONFIGDIR"] = "."
  
  NAME = 'hypertools'
  VERSION = '0.7.0'
  AUTHOR = 'Contextual Dynamics Lab'
  AUTHOR_EMAIL = 'contextualdynamics@gmail.com'
  URL = 'https://github.com/ContextLab/hypertools'
  DOWNLOAD_URL = URL
  LICENSE = 'MIT'
  REQUIRES_PYTHON = '>=3.5'
  PACKAGES = find_packages(exclude=('images', 'examples', 'tests'))
  with open('requirements.txt', 'r') as f:
      REQUIREMENTS = f.read().splitlines()
  
  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.
  """
  CLASSIFIERS = [
      'Intended Audience :: Science/Research',
      'Programming Language :: Python :: 3.5',
      'Programming Language :: Python :: 3.6',
      'Programming Language :: Python :: 3.7',
      'Programming Language :: Python :: 3.8',
      'Topic :: Scientific/Engineering :: Visualization',
      'Topic :: Multimedia :: Graphics',
      'Operating System :: POSIX',
      'Operating System :: Unix',
      'Operating System :: MacOS'
  ]
  
  setup(
      name=NAME,
      version=VERSION,
      description=DESCRIPTION,
      long_description=LONG_DESCRIPTION,
      author=AUTHOR,
      author_email=AUTHOR_EMAIL,
      url=URL,
      download_url = DOWNLOAD_URL,
      license=LICENSE,
      python_requires=REQUIRES_PYTHON,
      packages=PACKAGES,
      install_requires=REQUIREMENTS,
      classifiers=CLASSIFIERS
  )
  
new_contents: # -*- coding: utf-8 -*-
  import os
  import subprocess
  import sys
  from setuptools import setup, find_packages
  from setuptools.command.install import install
  
  
  os.environ["MPLCONFIGDIR"] = "."
  
  NAME = 'hypertools'
  VERSION = '0.8.0'
  AUTHOR = 'Contextual Dynamics Lab'
  AUTHOR_EMAIL = 'contextualdynamics@gmail.com'
  URL = 'https://github.com/ContextLab/hypertools'
  DOWNLOAD_URL = URL
  LICENSE = 'MIT'
  REQUIRES_PYTHON = '>=3.5'
  PACKAGES = find_packages(exclude=('images', 'examples', 'tests'))
  with open('requirements.txt', 'r') as f:
      REQUIREMENTS = f.read().splitlines()
  
  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.
  """
  CLASSIFIERS = [
      'Intended Audience :: Science/Research',
      'Programming Language :: Python :: 3.5',
      'Programming Language :: Python :: 3.6',
      'Programming Language :: Python :: 3.7',
      'Programming Language :: Python :: 3.8',
      'Topic :: Scientific/Engineering :: Visualization',
      'Topic :: Multimedia :: Graphics',
      'Operating System :: POSIX',
      'Operating System :: Unix',
      'Operating System :: MacOS'
  ]
  
  setup(
      name=NAME,
      version=VERSION,
      description=DESCRIPTION,
      long_description=LONG_DESCRIPTION,
      author=AUTHOR,
      author_email=AUTHOR_EMAIL,
      url=URL,
      download_url = DOWNLOAD_URL,
      license=LICENSE,
      python_requires=REQUIRES_PYTHON,
      packages=PACKAGES,
      install_requires=REQUIREMENTS,
      classifiers=CLASSIFIERS
  )
  
subject: bump version