pepe-granular 1.2.6

Image analysis toolbox tailored towards granular photoelastic images

Photoelastic Python Environment

Photo- elastic Python Environment

This is a collection of tools for working with photoelastic particle images, including common analysis methods like particle tracking and community analysis.

Features

• Common analysis techniques (G², D²min, etc.)
• Particle tracking
• Masking and other preprocessing tools
• Synthetic photoelastic response generation
• Force solving (as in PeGS [1a, 1b])

Installation

The library is available on PyPi:

pip install pepe-granular

It can also be installed from the Github repository:

git clone https://github.com/Jfeatherstone/pepe
cd pepe
pip install .

Documentation

Available here.

Requirements

Python 3.11 is the recommended version to use, with the following packages:

• numpy
• matplotlib
• lmfit
• scikit-learn
• opencv
• Pillow
• numba
• tqdm
• rawpy

These can all be installed (alongside their dependencies) via pip:

git clone https://github.com/jfeatherstone/pepe
cd pepe
pip install -r requirements.txt

Usage

The wiki and documentation contain information about how to use the toolbox. Test notebooks can be found in the repo's notebooks directory, and unit tests can be found in the pepe.test directory.

Some of the test notebooks make use of the Matlab API to compare against Jonathan Kollmer's code [1a], but this is not required to use any functions in the library itself. Installing the Matlab API requires a local installation of Matlab proper; see here for more information.

Further Reading and References

[1] Daniels, K. E., Kollmer, J. E., & Puckett, J. G. (2017). Photoelastic force measurements in granular materials. Review of Scientific Instruments, 88(5), 051808. https://doi.org/10.1063/1.4983049

[1a] Jonathan Kollmer's implementation in Matlab: https://github.com/jekollmer/PEGS

[1b] Olivier Lantsoght's implementation in Python: https://git.immc.ucl.ac.be/olantsoght/pegs_py

[2] Abed Zadeh, A., Barés, J., Brzinski, T. A., Daniels, K. E., Dijksman, J., Docquier, N., Everitt, H. O., Kollmer, J. E., Lantsoght, O., Wang, D., Workamp, M., Zhao, Y., & Zheng, H. (2019). Enlightening force chains: A review of photoelasticimetry in granular matter. Granular Matter, 21(4), 83. https://doi.org/10.1007/s10035-019-0942-2

[3] Photoelastic methods wiki. https://git-xen.lmgc.univ-montp2.fr/PhotoElasticity/Main/-/wikis/home or https://photoelasticity.net/