old_contents: """ torsionfit: A toolkit for Bayesian torsion parameterization for molecular mechanics forcefields.
  
  This project provides tools for using Bayesian parameterization techniques and Markov chain Monte Carlo
  to fit molecular mechanics torsion Fourier terms to quantum chemical data.
  """
  
  from __future__ import print_function
  
  import os
  from os.path import relpath, join
  
  import numpy
  import versioneer
  
  from setuptools import setup, Extension, find_packages
  
  DOCLINES = __doc__.split("\n")
  
  ########################
  CLASSIFIERS = """\
  Development Status :: 3 - Alpha
  Intended Audience :: Science/Research
  Intended Audience :: Developers
  License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
  Programming Language :: Python
  Topic :: Scientific/Engineering :: Bio-Informatics
  Topic :: Scientific/Engineering :: Chemistry
  Operating System :: Microsoft :: Windows
  Operating System :: POSIX
  Operating System :: Unix
  Operating System :: MacOS
  """
  
  ################################################################################
  # USEFUL SUBROUTINES
  ################################################################################
  def find_package_data(data_root, package_root):
      files = []
      for root, dirnames, filenames in os.walk(data_root):
          for fn in filenames:
              files.append(relpath(join(root, fn), package_root))
      return files
  
  def package_files(directory):
      paths = []
      for (path, directories, filenames) in os.walk(directory):
          for filename in filenames:
              paths.append(os.path.join('..', path, filename))
      return paths
  
  ################################################################################
  # SETUP
  ################################################################################
  
  setup(
      name='torsionfit',
      author='Chaya Stern',
      author_email='chaya.stern@choderalab.org',
      description=DOCLINES[0],
      long_description="\n".join(DOCLINES[2:]),
      version=versioneer.get_version(),
      cmdclass=versioneer.get_cmdclass(),
      license='LGPL',
      url='https://github.com/choderalab/torsions',
      platforms=['Linux', 'Mac OS-X', 'Unix', 'Windows'],
      classifiers=CLASSIFIERS.splitlines(),
      packages=['torsionfit', 'torsionfit.tests', 'torsionfit.qmscan', 'torsionfit.backends', 'torsionfit.database'],
      package_data={'tests': package_files('torsionfit/tests/reference'), 'qmscan': package_files('torsionfit/qmscan')},
      zip_safe=False,
      install_requires=[
          'numpy',
          'mdtraj',
          'pymc',
          'pandas',
          'cclib',
          'openmm',
          'parmed'
          ],
      )
  
  
new_contents: """ torsionfit: A toolkit for Bayesian torsion parameterization for molecular mechanics forcefields.
  
  This project provides tools for using Bayesian parameterization techniques and Markov chain Monte Carlo
  to fit molecular mechanics torsion Fourier terms to quantum chemical data.
  """
  
  from __future__ import print_function
  
  import os
  from os.path import relpath, join
  
  import numpy
  import versioneer
  
  from setuptools import setup, Extension, find_packages
  
  DOCLINES = __doc__.split("\n")
  
  ########################
  CLASSIFIERS = """\
  Development Status :: 3 - Alpha
  Intended Audience :: Science/Research
  Intended Audience :: Developers
  License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
  Programming Language :: Python
  Topic :: Scientific/Engineering :: Bio-Informatics
  Topic :: Scientific/Engineering :: Chemistry
  Operating System :: Microsoft :: Windows
  Operating System :: POSIX
  Operating System :: Unix
  Operating System :: MacOS
  """
  
  ################################################################################
  # USEFUL SUBROUTINES
  ################################################################################
  def find_package_data(data_root, package_root):
      files = []
      for root, dirnames, filenames in os.walk(data_root):
          for fn in filenames:
              files.append(relpath(join(root, fn), package_root))
      return files
  
  def package_files(directory):
      paths = []
      for (path, directories, filenames) in os.walk(directory):
          for filename in filenames:
              paths.append(os.path.join('..', path, filename))
      return paths
  
  ################################################################################
  # SETUP
  ################################################################################
  
  setup(
      name='torsionfit',
      author='Chaya Stern',
      author_email='chaya.stern@choderalab.org',
      description=DOCLINES[0],
      long_description="\n".join(DOCLINES[2:]),
      version=versioneer.get_version(),
      cmdclass=versioneer.get_cmdclass(),
      license='LGPL',
      url='https://github.com/choderalab/torsions',
      platforms=['Linux', 'Mac OS-X', 'Unix', 'Windows'],
      classifiers=CLASSIFIERS.splitlines(),
      packages=['torsionfit', 'torsionfit.tests', 'torsionfit.qmscan', 'torsionfit.backends', 'torsionfit.database'],
      package_data={'torsionfit.tests': package_files('torsionfit/tests/reference'), 'torsionfit.qmscan': ['qmscan/fgroup_smarts.yml']},
      zip_safe=False,
      install_requires=[
          'numpy',
          'mdtraj',
          'pymc',
          'pandas',
          'cclib',
          'openmm',
          'parmed'
          ],
      )
  
  
subject: add package data