Optimisation for Topas

This repository enables users to transform any radiation transport model in TopasMC, into an optimisation problem, hence enabling users to apply the power of formal mathematical optimisation with the well established use cases for Monte Carlo modelling.

To install:

pip install TopasOpt

For help getting an appropriate environment set up, see here The quickest way to get started is to go through the worked examples.

Contents:

• Worked Examples
  • Geometry Optimisation Example
  • Phase space optmisation example
  • Handling noisy data
  • Development example
• Next steps
  • Designing objective functions
  • Convergence criteria
  • All Optimisers
  • BayesianOptimiser
  • NelderMeadOptimiser
• Environment set up
• Developer Notes
  • Additional requirements
  • Packaging instructions
  • Testing framework
  • Building documentation
  • Adding new optimisation algorithms
• Code documentation
  • Optimisers
  • TopasScriptGenerator
  • utilities

Indices and tables

• Index

• Module Index

• Search Page