pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images

pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images

Given the huge advances in tomographic imaging capability in recent years, image analysis has become a powerful means of measuring transport and structural properties of porous materials. One of the most important material characteristics is the tortuosity, which is difficult to measure experimental...

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Main Authors: T.G. Tranter, M.D.R. Kok, M. Lam, J.T. Gostick
Format: Article
Language:English
Published: Elsevier 2019-07-01
Series:SoftwareX
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711019302286
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spelling doaj-47c39f4824d24c97aaa14189e77af24d2020-11-25T01:38:39ZengElsevierSoftwareX2352-71102019-07-0110pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of imagesT.G. Tranter0M.D.R. Kok1M. Lam2J.T. Gostick3Department of Chemical Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON, Canada; Electrochemical Innovation Lab, Department of Chemical Engineering, University College London, UKElectrochemical Innovation Lab, Department of Chemical Engineering, University College London, UKDepartment of Chemical Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON, CanadaDepartment of Chemical Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON, Canada; Corresponding author.Given the huge advances in tomographic imaging capability in recent years, image analysis has become a powerful means of measuring transport and structural properties of porous materials. One of the most important material characteristics is the tortuosity, which is difficult to measure experimentally. We present pytrax: (tortuosity from random axial movements) a simple and efficient random walk method implemented in python to calculate the average tortuosity and orthogonal directional tortuosity components of an image. The code works for both two and three-dimensional images and completes a statistically significant number of walks in parallel for large images in a few minutes using a standard desktop computer. By comparison, a Lattice Boltzmann or finite element simulation on similar sized images can take several hours. Keywords: Random walk, Directional tortuosity, Python, Image analysishttp://www.sciencedirect.com/science/article/pii/S2352711019302286
collection DOAJ
language English
format Article
sources DOAJ
author T.G. Tranter
M.D.R. Kok
M. Lam
J.T. Gostick
spellingShingle T.G. Tranter
M.D.R. Kok
M. Lam
J.T. Gostick
pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
SoftwareX
author_facet T.G. Tranter
M.D.R. Kok
M. Lam
J.T. Gostick
author_sort T.G. Tranter
title pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
title_short pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
title_full pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
title_fullStr pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
title_full_unstemmed pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images
title_sort pytrax: a simple and efficient random walk implementation for calculating the directional tortuosity of images
publisher Elsevier
series SoftwareX
issn 2352-7110
publishDate 2019-07-01
description Given the huge advances in tomographic imaging capability in recent years, image analysis has become a powerful means of measuring transport and structural properties of porous materials. One of the most important material characteristics is the tortuosity, which is difficult to measure experimentally. We present pytrax: (tortuosity from random axial movements) a simple and efficient random walk method implemented in python to calculate the average tortuosity and orthogonal directional tortuosity components of an image. The code works for both two and three-dimensional images and completes a statistically significant number of walks in parallel for large images in a few minutes using a standard desktop computer. By comparison, a Lattice Boltzmann or finite element simulation on similar sized images can take several hours. Keywords: Random walk, Directional tortuosity, Python, Image analysis
url http://www.sciencedirect.com/science/article/pii/S2352711019302286
work_keys_str_mv AT tgtranter pytraxasimpleandefficientrandomwalkimplementationforcalculatingthedirectionaltortuosityofimages
AT mdrkok pytraxasimpleandefficientrandomwalkimplementationforcalculatingthedirectionaltortuosityofimages
AT mlam pytraxasimpleandefficientrandomwalkimplementationforcalculatingthedirectionaltortuosityofimages
AT jtgostick pytraxasimpleandefficientrandomwalkimplementationforcalculatingthedirectionaltortuosityofimages
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