old_contents: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  
  """
  PyEMD
  =====
  
  PyEMD is a Python wrapper for Ofir Pele and Michael Werman's implementation of
  the Earth Mover's Distance (http://www.seas.upenn.edu/~ofirpele/FastEMD/code/)
  that integrates it with NumPy.
  
      >>> from pyemd import emd
      >>> import numpy as np
      >>> first_signature = np.array([0.0, 1.0])
      >>> second_signature = np.array([5.0, 3.0])
      >>> distance_matrix = np.array([[0.0, 0.5], [0.5, 0.0]])
      >>> emd(first_signature, second_signature, distance_matrix)
      3.5
  
  
  Limitations and Caveats:
  ------------------------
  
  - ``distance_matrix`` must be symmetric.
  - ``distance_matrix`` is assumed to represent a true metric. This must be
    enforced by the caller. See the documentation in lib/emd_hat.hpp.
  - The signatures and distance matrix must be numpy arrays of ``np.float``. The
    original C++ template function can accept any numerical C++ type, but this
    wrapper only instantiates the template with ``double`` (Cython converts
    ``np.float`` to ``double``). If there's demand, I can add support for other
    types.
  - The original C++ functions have optional parameters ``extra_mass_penalty``
    and ``F`` (for flows); this wrapper does not expose those parameters. See
    the documentation in lib/emd_hat.hpp.
  
  
  Credits
  -------
  
  - All credit for the actual algorithm and implementation goes to Ofir Pele and
    Michael Werman. See the `relevant paper
    <http://www.seas.upenn.edu/~ofirpele/publications/ICCV2009.pdf>`.
  - Thanks to the Cython devlopers for making this kind of wrapper relatively
    easy to write.
  
  
  :copyright: (c) 2014 by Will Mayner.
  :license: See the LICENSE file.
  
  """
  
  __title__ = 'pyemd'
  __version__ = '0.0.3'
  __author__ = 'Will Mayner'
  __author_email__ = 'wmayner@gmail.com'
  __license__ = 'MIT'
  __copyright__ = 'Copyright 2014 Will Mayner'
  
  from .emd import emd
  
new_contents: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  
  """
  PyEMD
  =====
  
  PyEMD is a Python wrapper for Ofir Pele and Michael Werman's implementation of
  the Earth Mover's Distance (http://www.seas.upenn.edu/~ofirpele/FastEMD/code/)
  that integrates it with NumPy.
  
      >>> from pyemd import emd
      >>> import numpy as np
      >>> first_signature = np.array([0.0, 1.0])
      >>> second_signature = np.array([5.0, 3.0])
      >>> distance_matrix = np.array([[0.0, 0.5], [0.5, 0.0]])
      >>> emd(first_signature, second_signature, distance_matrix)
      3.5
  
  
  Limitations and Caveats:
  ------------------------
  
  - ``distance_matrix`` must be symmetric.
  - ``distance_matrix`` is assumed to represent a true metric. This must be
    enforced by the caller. See the documentation in lib/emd_hat.hpp.
  - The signatures and distance matrix must be numpy arrays of ``np.float``. The
    original C++ template function can accept any numerical C++ type, but this
    wrapper only instantiates the template with ``double`` (Cython converts
    ``np.float`` to ``double``). If there's demand, I can add support for other
    types.
  - The original C++ functions have optional parameters ``extra_mass_penalty``
    and ``F`` (for flows); this wrapper does not expose those parameters. See
    the documentation in lib/emd_hat.hpp.
  
  
  Credits
  -------
  
  - All credit for the actual algorithm and implementation goes to Ofir Pele and
    Michael Werman. See the `relevant paper
    <http://www.seas.upenn.edu/~ofirpele/publications/ICCV2009.pdf>`.
  - Thanks to the Cython devlopers for making this kind of wrapper relatively
    easy to write.
  
  
  :copyright: (c) 2014 by Will Mayner.
  :license: See the LICENSE file.
  
  """
  
  __title__ = 'pyemd'
  __version__ = '0.0.4'
  __author__ = 'Will Mayner'
  __author_email__ = 'wmayner@gmail.com'
  __license__ = 'MIT'
  __copyright__ = 'Copyright 2014 Will Mayner'
  
  from .emd import emd
  
subject: Bump version