Resources

Software, data, and demos from the lab that are ready for others to use. Code and data for individual papers are linked from the publications list.

Interactive demos

Software

Demixing model Python package

A normative computational model of inter-item biases in memory and perception. It generates predictions for attraction and repulsion as a function of similarity and noise, and fits the model to data (GPU recommended).

Papers: Chetverikov (2023) Chetverikov & Hansmann-Roth (2026)

circhelp R package

Helper functions for circular data in cognitive studies of orientation, motion direction and other circular features — descriptive statistics, angular differences, correlation, and a correction for cardinal biases in human estimates.

apastats2 R package

Formats statistical results in APA style (apa() for many test and model objects), with helpers for confidence intervals, summaries, and point-range plots with within-subject intervals.

JAX L-BFGS-B Python package

A JAX implementation of the L-BFGS-B bound-constrained optimiser that runs many independent starts as one vectorised batch on CPU or GPU, validated against reference test cases.

Data

Visual Search Database Database

A database of visual search datasets pooled across studies and labs, for re-use and for testing computational models on many datasets at once. A web app shows the data without setting up the database.

Teaching

Power analysis via simulations in R Tutorial

A short tutorial on power analysis by simulation, from t-tests and ANOVAs to hierarchical models, with practical exercises. First run at the TCTS graduate school for cognitive science students in 2020.