Welcome to pyfssa!

pyfssa is a scientific Python package for algorithmic finite-size scaling analysis at phase transitions.

It stands on the shoulder of the autoScale.py program. Please credit his author Oliver Melchert accordingly.

December 12, 2015 (Version 0.7.5.post0.dev2+g9b69231)

Andreas Sorge <pyfssa@asorge.de>

• Max Planck Institute for Dynamics & Self-Organization, Göttingen, Germany
• Organization for Research on Complex Adaptive Systems, Göttingen, Germany

Citation

Please cite as: Andreas Sorge. (2015). pyfssa 0.7.5.post0.dev2+g9b69231. Zenodo.

Please also cite autoScale.py.

Documentation license

This documentation is licensed under a Creative Commons Attribution 4.0 International License.

Table of Contents

• About
  • License
  • Changelog
• Setup
  • Requirements
  • Installation from PyPI
  • Installation from source
• Tutorial
  • Preamble
  • A mock scaling function
  • Precisely mocking scaled data
  • Achieving data collapse with the mock data
  • Auto-scaling the mock data
  • Auto-scaling noisy mock data
• User Guide
  • Finite-size scaling analysis
  • The quality of data collapse
  • The Nelder–Mead algorithm
  • Usage
• Verification
  • Percolation simulation design
  • Preamble
  • Loading and inspecting the raw data
  • Scaling and visualization routines
  • Visualizing the raw data and the algorithmic scaling
  • Results
  • Discussion
  • Conclusion
• Developer Guide
  • Development environment
  • Packaging
  • Complete Git Integration
  • Sphinx Documentation
  • Continuous documentation building
  • Unittest & Coverage
  • Continuous testing
  • Requirements Management
  • Bibliography
  • Continuous Integration
• Reference
  • Submodules
  • fssa.fssa module
  • fssa.optimize module
  • Module contents
• Bibliography