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 (and Python 3.6 tentatively -- please report any bugs). The following libraries are required:

• deap
• future
• matplotlib
• numpy
• pandas
• scipy

$ pip install addm_toolbox

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

$ addm_toolbox_tests

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

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:

• 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.

If you get errors while using the toolbox under Python 3, try it with Python 2.7.

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

• Gabriela Tavares - [email protected], goptavares

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.