SA Analysis

A series of functions to clean and prepare data for analysis for the dyscord lab's SA study.

Structure

This code weaves together output from the data collection protocol generated in the SA Stimulus repository.

Running

To run, raw data should be saved in a directory called data and in a subdirectory in that directory called raw. The data directory should be put in the top-level directory of this repo.

Open a Terminal window and navigate to the SA_Analysis directory. From there, type python run-sorting.py and return.

Data will be output in two new subdirectories within the data directory: processed (which includes a gaze_df.csv and a survey_df.csv file for each participant) and analysis (which includes an analysis_df.csv file for each participant).

To do

1. Make the timestamps of the gaze_positions match up with the .log file
   • This will help account for disruptions
2. For the exports folder, use the most recently updated one instead of highest number
3. Make the file searching interactive in command prompt