Getting started

Installation

MIDAS is available from PyPI, so can be easily installed using pip as follows:

pip install midas-fusion

If pip is not available, you can clone from the GitHub source repository.

Structure of a MIDAS analysis

The high-level structure of a MIDAS analysis can be broken down as:

  • Create a DiagnosticModel object for each diagnostic which is to be included in the analysis.

  • Specify the prior distribution (or its components) using classes from the midas.priors module (or implement your own using the provided base-class.

  • Build the parametrisation for the posterior distribution by calling the PlasmaState.build_posterior() function.

  • Use the functions in the midas.posterior module to evaluate the posterior distribution, allowing for MAP estimation or sampling.

In subsequent pages we will cover each of these steps in more detail.

Jupyter notebook examples

Annotated example code is available as a jupyter notebook in our soft X-ray emission toy example. Additional example notebooks will be added as development progresses!