This is a toolbox implementing the algorithm introduced in . Documentation, examples, and user guide are found here.
The package is a model analysis tool. It finds functional relationships between model parameters that best preserve model behaviour.
You provide a differentiable cost function that maps parameters to 'how bad the model behaviour is'. You also provide a locally optimal set of parameters θ*.
The package will generate curves in parameter space, emanating from θ*. Each point on the curve corresponds to a set of model parameters. These curves are 'minimally disruptive' with respect to the cost function (i.e. model behaviour).
These curves can be used to better understand interdependencies between model parameters, as detailed in the documentation.
 Raman, Dhruva V., James Anderson, and Antonis Papachristodoulou. "Delineating parameter unidentifiabilities in complex models." Physical Review E 95.3 (2017): 032314.