scikit-fmm is an 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 two functions: distance(phi, dx=1.0) and travel_time(phi, speed, dx=1.0).
The functions 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.
Documentation: http://packages.python.org/scikit-fmm
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)
- Bugs, questions, patches, feature requests:
Please use the scikit-fmm Github issue tracker. https://github.com/scikit-fmm/scikit-fmm/issues
- Installing:
$ python setup.py install
- Testing (requires nose):
$ python tests/test_fmm.py
- Building documentation (required 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.
- Copyright:
Copyright 2012 The scikit-fmm team.
- License:
BSD-style license. See LICENSE.txt in the scipy source directory.
Release files for scikit-fmm 0.0.2
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