MESA is a python-based framework for automating the optimisation of simulation predictions to maximise a user-defined objective. MESA is designed to be extensible, such that new simulations and optimisation strategies can be added easily.
The initial goal of development is to autonomously match SOLPS-ITER predictions to experimental data using Gaussian-process optimisation provided by inference-tools.
MESA is still under development - package documentation and example code will be added as development progresses.