# Monkilock This repository contains the codes and data for the Monkilock Project. ### Codes: - Monkilock_Data_Processing.ipynb: In this notebook, we processed raw fixation data of 5 macaques and explored the relationship between their fixation patterns and the "surprisal" of events in a trial - Analysis_Code_final.Rmd: Data processing, modeling, visualization - helper-lib.R: helper functions used in Analysis_Code_final.Rmd ### Data: - csv-combined.csv : one event (pop-up) per line for all trial files - csv-surprisal-prob.csv: output file with surprisal value generated by Monkilock_Data_Processing.ipynb - csv-surprisal-prob_updated.csv: ready for analysis data file generated by Analysis_Code_final.Rmd - AllSeq.csv: include event information of all 80 sequences #### Empty Values in Datasets: - There is no missing value in the original dataset "csv-combined.csv". Missing values (marked as NA in datasets) happen in columns "prev_active", "next_active", "already_there", "bisurprisal", "std_bisurprisal", "sq_std_bisurprisal" in "csv-surprisal-prob.csv" and "csv-surprisal-prob_updated.csv". - NAs in columns "prev_active" and "next_active" mean that the first or the last active object in the sequence/no active object before or after the currently active object in the sequence. When we analyzed the variable "already_there", we eliminated data that their "prev_active" variable is NA. - NAs in column "already there" mean that the subject never looks at the target object in the current event. When we analyzed the variable "already there", we eliminated data that their "already_there" variable is NA. - Missing values happen in columns "bisurprisal", "std_bisurprisal", "sq_std_bisurprisal" when it is the first event in the sequence and the transitional probability of the event cannot be computed because there's no event happening before in this sequence. When we fitted models for transitional statistics, we eliminated data that their "bisurprisal", "std_bisurprisal", and "sq_std_bisurprisal" are NAs.