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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.


aDDM-Toolbox supports Python 2.7 only and requires the following libraries: * deap * matplotlib * numpy * pandas * scipy


$ pip install addm_toolbox

Running tests

To make sure everything is working correctly after installation, try (from a UNIX shell, not the Python interpreter):

$ 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

Here is a list of useful scripts which can be similarly run from a UNIX shell: * addm_demo * ddm_pta_test * addm_pta_test * addm_pta_mle * addm_pta_map * addm_simulate_true_distributions * addm_basinhopping * addm_genetic_algorithm * ddm_mla * addm_mla

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

Common issues

Make sure you are using the toolbox under Python 2.7, not Python 3.

If you get a Python RuntimeError with the message “Python is not installed as a framework.”, try creating the file ~/.matplotlib/matplotlibrc and adding the following code:

backend: TkAgg



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


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

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Filename, size & hash SHA256 hash help File type Python version Upload date
addm_toolbox-0.1.8-py2-none-any.whl (1.0 MB) Copy SHA256 hash SHA256 Wheel py2 Oct 12, 2017
addm_toolbox-0.1.8.tar.gz (1.0 MB) Copy SHA256 hash SHA256 Source None Oct 12, 2017

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