This is the code used to produce the results and visualizations published in

Schmittwilken, L., & Maertens, M. (under submission). Ocular drift shakes the stationary view on pattern vision

Setup

Install all the libraries in requirements.txt.

pip install -r requirements.txt

Note: we have used an older version of python-psignifit here, which is not available anymore. Therefore, we decided to add it to the repo directly in the folder psignifit. You can find information on the newest version of psignifit here.

Description

The repository contains the following:

• The empirical edge sensitivity data by Schmittwilken, Wichmann, & Maertens (2024) who probed sensitivity to Cornsweet edges in different 2d noise patterns: experimental_data

• A Jupyter notebook which contains all simulations related to testing the effect of ocular drift on the stimulus spectra: heuristic_test

• Additional Jupyter notebooks with toy models as well as additional information about the spatial and temporal filters used: jupyter_notebooks

• All scripts related to implementing and optimizing the mechanistic models as well as visualizing their performances. In addition, it contains pickle-files with the optimized spatial and active models that we report in the manuscript: mechanistic_models

• An old version of python-psignifit: psignifit

Authors and acknowledgment

Code written by Lynn Schmittwilken (l.schmittwilken@tu-berlin.de)