Welcome to foamquant documentation

The pip installable Python library, foamquant, was primarily developed to study time-resolved X-ray tomograms of evolving liquid foams and their fundamental local physical behavior. However, we believe this library can be adapted to the broader class of cellular materials, using other imaging methods, and put to work on other scientific and engineering applications.

The toolbox has four main dependencies: numpy, scikit-image [vanderWalt2014], SPAM [Stamati2020], and porespy [Gostick2019].

Main objectives:

• Integrating standard image processing methods from scikit-image, SPAM, and porespy.

• Including new mechanical quantification methods specifically dedicated to studying evolving liquid foam structure: local elasticity and plasticity.

This website provides an API reference and ready-to-use jupyter notebooks image analysis pipelines.

• Modules overview
  • Typical analysis pipeline
  • Process
  • FromBinary
  • FromLabelled
  • FromContact
  • Tracking
  • T1
  • Passage, Average, Figure and Movie
  • References
• Python functions
  • Process
  • FromBinary
  • FromLabelled
  • Batchelor
  • Tracking
  • T1
  • VTK
  • Passage
  • Average
  • Figure
  • Movie
  • Helper
• Gallery
  • Image processing
  • Liquid fraction & Bubble radius
  • Strain & Stress fields
  • Flow field & Tracking
  • Plastic activity
  • Bread - Image Processing
• Binder tutorials

References

[vanderWalt2014]

van der Walt, S., et al. (2014) scikit-image: image processing in Python. PeerJ 2, e453.

[Stamati2020]

Stamati, H., et al. (2020). SPAM: Software for Practical Analysis of Materials, 5, 2286.

[Gostick2019]

Gostick, J. et al. (2019). PoreSpy: A Python toolkit for quantitative analysis of porous media images. Journal of Open Source Software, 4(37), 1296.

Note

FoamQuant requires Python 3.8 or higher.

• Make sure to install dependencies: numpy, scikit-image, SPAM, and porespy.

• Consider using a virtual environment to avoid conflicts.

• For more information or questions regarding this project please contact: Florian Schott or Rajmund Mokso.