Skip to main content
Help us improve PyPI by participating in user testing. All experience levels needed!

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

aDDM-Toolbox supports Python 2.7 only and 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 (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: * 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.

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

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


Release history Release notifications

History Node

0.1.12

History Node

0.1.11

History Node

0.1.10

History Node

0.1.9

This version
History Node

0.1.8

History Node

0.1.7

History Node

0.1.6

Download files

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

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

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging CloudAMQP CloudAMQP RabbitMQ AWS AWS Cloud computing Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page