Skip to main content

A toolbox for data analysis using the attentional drift-diffusion model.

Project description

This toolbox can be used to perform model fitting and to generate simulations for the attentional drift-diffusion model (aDDM), as well as for the classic version of the drift-diffusion model (DDM) without an attentional component.

Prerequisites

This toolbox requires the following libraries: * deap * matplotlib * numpy * pandas * scipy

Installing

$ pip install addm_toolbox

Running tests

To make sure everything is working correctly after installation, try:

$ addm_run_tests

This should take a while to finish, so maybe go get a cup of tea :)

Getting started

To get a feel for how the algorithm works, try:

$ addm_demo --display-figures

You can see all the arguments available for the demo using:

$ addm_demo --help

You can also have a look at the code in the following modules: * addm.py contains the aDDM implementation, with functions to generate model simulations and obtain the likelihood for a given data trial. * ddm.py is equivalent to addm.py but for the DDM. * addm_pta_test.py generates an artificial data set for a given set of aDDM parameters and attempts to recover these parameters through maximum a posteriori estimation. * ddm_pta_test.py is equivalent to addm_pta_test.py but for the DDM. * addm_pta_mle.py fits the aDDM to a data set by performing maximum likelihood estimation. * addm_pta_map.py performs model comparison for the aDDM by obtaining a posterior distribution over a set of models. * simulate_addm_true_distributions.py generates aDDM simulations using empirical data for the fixations.

Authors

License

This project is licensed under the GNU GENERAL PUBLIC LICENSE - see the COPYING file for details.

Acknowledgments

This toolbox was developed as part of a research project in the Rangel Neuroeconomics Lab at the California Institute of Technology.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

addm_toolbox-0.1.6.tar.gz (1.0 MB view hashes)

Uploaded Source

Built Distribution

addm_toolbox-0.1.6-py2-none-any.whl (1.1 MB view hashes)

Uploaded Python 2

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page