Welcome to pyTAMS’s documentation!

Warning

pyTAMS documentation is under construction and fairly incomplete at this point.

pyTAMS is a modular implementation of the trajectory adaptive multilevel splitting (TAMS), an algorithm developed to evaluate the probability of rare events associated with a stochastic systems. In particular, TAMS can be used to evaluate the transition probability between two stable states of a multi-stable system. pyTAMS was developed to specifically handle (computationally) expensive stochastic models, where advancing the model can take hours to days on supercomputer and using a naive Monte-Carlo approach is unreasonable.

The documentation pages appearing hereafter are distributed with the code in the docs folder as “restructured text” files. The html is built automatically with certain pushes to the pyTAMS main branch on GitHub. A local version can also be built as follows

cd <pyTAMS_root_folder>/docs
make html

User corner:

• Theory
  • Introduction to TAMS
  • High-dimension considerations
• Implementation
  • Data structures & storage
  • Workers & parallelism
  • Algorithm
• A simple example: 2D double well
• Usage
• Running pyTAMS
• Controls
• Tutorials
  • Double-well 3D

Developer corner:

• pytams
  • Submodules

Indices and tables

• Index

• Module Index

• Search Page