scikit-fmm

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.

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
>>> phi = [-1,-1,-1,1,1,1]
>>> skfmm.distance(phi)
array([-2.5, -1.5, -0.5,  0.5,  1.5,  2.5])

>>> skfmm.travel_time(phi, [2,2,2,2,2,2])
array([ 1.25,  0.75,  0.25,  0.25,  0.75,  1.25])

The input array can be of 1, 2, 3 or higher dimensions and can be a masked array.

Requirements: Numpy and a C/C++ compiler (gcc/MinGW)

Release files for scikit-fmm 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for scikit-fmm 0.0.1
File	Size	Uploaded
scikit-fmm-0.0.1.tar.gz	9.7 kB	Feb 13, 2012	Details

Table of built distributions (wheels) for scikit-fmm 0.0.1
File	Interpreter	ABI	Platform	Reset
scikit-fmm-0.0.1.win32-py2.7.exe 225.2 kB Feb 13, 2012				Details

Total release size: 235.0 kB

Download URL	scikit-fmm-0.0.1.tar.gz
Size	9.7 kB
Tags	Source
SHA-256 checksum How to use checksums	`8f0f398deccca3ff6b4f994f4aacbe4684e62f0b7fcef3f293aa5b58567fabf1`
BLAKE2b-256 checksum How to use checksums	`fc80431d4542026a62ca2f45c9fa104b2a98df1761ea09acca658f4e46c52850`
Upload date	Feb 13, 2012
Uploaded using Trusted Publishing? What is trusted publishing?	No

Download URL	scikit-fmm-0.0.1.win32-py2.7.exe
Size	225.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`ac003b0bb85e6b23c9a1a23dde506e25c1668501c7580edaf90d5a04a2bd973e`
BLAKE2b-256 checksum How to use checksums	`c1c87b453990dcb7a7d08bc742177dd41f537d613469f3f5b62f520961688b13`
Upload date	Feb 13, 2012
Uploaded using Trusted Publishing? What is trusted publishing?	No