Metadata-Version: 1.1
Name: scikit-fmm
Version: 0.0.7
Summary: An extension module implimenting the fast marching method
Home-page: https://github.com/scikit-fmm/
Author: Jason Furtney
Author-email: jkfurtney@gmail.com
License: BSD
Description: scikit-fmm is a Python extension module which implements the fast
        marching method.
        
        The fast marching method is used to model the evolution of boundaries
        and interfaces in a variety of application areas. More specifically,
        the fast marching method is a numerical technique for finding
        approximate solutions to boundary value problems of the Eikonal
        equation:
        
        F(x) | grad T(x) | = 1.
        
        Typically, such a problem describes the evolution of a closed curve as
        a function of time T with speed F(x)>0 in the normal direction at a
        point x on the curve. The speed function is specified, and the time at
        which the contour crosses a point x is obtained by solving the
        equation.
        
        scikit-fmm is a simple module which provides functions to calculate
        the signed distance and travel time to an interface described by the
        zero contour of the input array phi.
        
        >>> import skfmm
        >>> import numpy as np
        >>> phi = np.ones((3, 3))
        >>> phi[1, 1] = -1
        >>> skfmm.distance(phi)
        array([[ 1.20710678,  0.5       ,  1.20710678],
               [ 0.5       , -0.35355339,  0.5       ],
               [ 1.20710678,  0.5       ,  1.20710678]])
        
        >>> skfmm.travel_time(phi, speed = 3.0 * np.ones_like(phi))
        array([[ 0.40236893,  0.16666667,  0.40236893],
               [ 0.16666667,  0.11785113,  0.16666667],
               [ 0.40236893,  0.16666667,  0.40236893]])
        
        The input array can be of 1, 2, 3 or higher dimensions and can be a
        masked array. A function is provided to compute extension velocities.
        
        Documentation:
            Release Version:     http://packages.python.org/scikit-fmm
            Development Version: http://scikit-fmm.readthedocs.org/en/latest/
        
        PyPI: http://pypi.python.org/pypi/scikit-fmm
        
        Source Code: https://github.com/scikit-fmm/scikit-fmm
        
        Requirements: Numpy and a C/C++ compiler (gcc, MinGW, MSVC)
        
        Bugs, questions, patches, feature requests, discussion & cetera:
          Email list: http://groups.google.com/group/scikit-fmm
          Send an email to scikit-fmm+subscribe@googlegroups.com to subscribe.
        
        Installing:
         $ python setup.py install
        
        Testing (doctest):
          $ python -c "import skfmm; skfmm.test(True)"
        
        Building documentation (requires sphinx and numpydoc):
          $ make html
        
        Version History:
        
        0.0.1: February 13 2012
          Initial release
        
        0.0.2: February 26th 2012
          Including tests and docs in source distribution. Minor changes to
          documentation.
        
        0.0.3: August 4th 2012
          Extension velocities.
          Fixes for 64 bit platforms.
          Optional keyword argument for point update order.
          Bug reports and patches from three contributors.
        
        0.0.4: October 15th 2012
          Contributions from Daniel Wheeler:
           * Bug fixes in extension velocity.
           * Many additional tests and migration to doctest format.
           * Additional optional input to extension_velocities() for FiPy compatibly.
        
        0.0.5: May 12th 2014
           * Fix for building with MSVC (Jan Margeta).
           * Corrected second-order point update.
        
        0.0.6: February 20th 2015
           * Documentation clarification (Geordie McBain).
           * Python 3 port (Eugene Prilepin).
           * Python wrapper for binary min-heap.
           * Freeze equidistant narrow-band points simultaneously.
        
        0.0.7: October 21th 2015
           * Bug fix to upwind finite difference approximation for negative
             phi from Lester Hedges.
        
        :Copyright: Copyright 2015 The scikit-fmm team.
        :License: BSD-style license. See LICENSE.txt in the scipy source directory.
        
Keywords: fast marching method,Eikonal equation,interface,boundary
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: C++
