skip to navigation
skip to content

Not Logged In

scikit-fmm 0.0.5

An extension module implimenting the fast marching method

Package Documentation

Latest Version: 0.0.6

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()”
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.
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.
Copyright:Copyright 2014 The scikit-fmm team.
License:BSD-style license. See LICENSE.txt in the scipy source directory.
 
File Type Py Version Uploaded on Size
scikit-fmm-0.0.5.tar.gz (md5) Source 2014-05-12 193KB
scikit-fmm-0.0.5.win32-py2.7.exe (md5) MS Windows installer 2.7 2014-05-12 225KB
  • Downloads (All Versions):
  • 48 downloads in the last day
  • 314 downloads in the last week
  • 1121 downloads in the last month