pyGLUE 0.0.4 (experimental)

A Python framework to conduct GLUE analyses

Generalised Likelihood Uncertainty Estimation (GLUE) Framework Joost Delsman, Deltares, 2011

Generic Python framework to conduct GLUE analyses NOTE: Package is still under construction and undocumented

Necessary: 1) model parameters, that: - hold the statistical properties of the a priori parameter space - hold the statistical properties of the a posteriori parameter space - can return a random value based on the a priori parameter space - can accept an evaluated parameter + behavioural / non-behavioural

statement from the evaluator

2) a model, that: - returns a result set based on a parameter set - can be called successively to explore the parameter space - resides outside GLUE - (can even be outside python) - function or wrapper must return a dict with parameters and

their values, recognised by the evaluator

3) a model evaluator, that: - evaluates the model result by a prescribed set of rules - assigns behavioural / non-behavioural

4) a framework that: - initializes a monte-carlo sequence - for each run:

• get parameter values
• run the model
• evaluate the model
• store behavioural runs