DMpy is a Python package for developing and fitting computational models of behaviour in decision making tasks.
Documentation can be found at http://dmpy.readthedocs.io/en/latest/
Its aim is to be transparent and modular, allowing simple coding of both learning and observation models, along with straightforward model fitting.
It aims to provide a range of model fitting techniques, including maximum-likelihood estimation (MLE), maximum a posteriori (MAP) estimation, variational Bayesian inference, and full MCMC-based sampling methods. Additionally, it provides a range of simulation functions to allow generation of data based on given models and parameter values.
The code here is currently under development and is unlikely to work properly!