Quantitative Image Analysis of Porous Materials¶
What is PoreSpy? ¶
PoreSpy is a collection of image analysis functions used to extract information
from 3D images of porous materials (typically obtained from X-ray
tomography). There are other packages that offer generalized image analysis
tools (i.e skimage
and scipy.ndimage
in the Python environment, ImageJ,
MatLab’s Image Processing Toolbox), but they all require building up
complex scripts or macros to accomplish tasks of specific use to porous
media. Porespy includes predefined functions to accomplish many of these
routine analyses rapidly and conveniently.
Capabilities¶
PoreSpy consists of the following modules:
generators
: Routines for generating artificial images of porous materials useful for testing and illustrationfilters
: Functions that accept an image and return an altered imagemetrics
: Tools for quantifying properties of imagesnetworks
: Algorithms and tools for analyzing images as pore networkssimulations
: Functions for performing physics-based simulations on imagestools
: Various useful tools for working with imagesvisualization
: Helper functions for creating useful views of the imageio
: Functions for outputting image data in various formats for use in common software
Gallery¶
How To Cite¶
If you use PoreSpy in a publication, please add the following citation:
Citation
Gostick J, Khan ZA, Tranter TG, Kok MDR, Agnaou M, Sadeghi MA, Jervis R. PoreSpy: A Python Toolkit for Quantitative Analysis of Porous Media Images. Journal of Open Source Software, 2019. doi:10.21105/joss.01296