R/baseline_correction_pupil.R

In dmirman/gazer: Tools for Processing Eye Tracking Data

#' Performs linear (sub) or divisive baseline correction relative to desired stim_onset and off_set
#' @param datafile raw pupil data
#' @param pupil_colname name of your pupil colname you want baseline corrected
#' @param baseline_window user-specified threshold for baseline window.
#' @param baseline correction method. Default is sub but can also include divisive
#' @return data frame containing baseline corrected data from event of interest
#' @export
baseline_correction_pupil<-function(datafile, pupil_colname="pupil", baseline_window=NA, baseline_method="sub")
{

  if (baseline_method=="sub") {
    message("Calculating median baseline from",":", baseline_window[1], "-", baseline_window[2])
    message("Merging baseline")
    baseline <- datafile  %>%
      dplyr::filter(time > baseline_window[1],
                    time < baseline_window[2]) %>%
      dplyr::group_by(subject, trial) %>%
      dplyr::rename(pupil_avg = pupil_colname) %>%
      dplyr::summarise(baseline = median(pupil_avg, na.rm=TRUE)) %>%
      dplyr::full_join(., datafile) %>% # merge median pupil size with raw dataset
      ungroup()
    

    message("Performing subtractive baseline correction")

    corrected_baseline <- baseline %>%
      dplyr::rename(pupil_avg = pupil_colname) %>%
      dplyr::mutate(baselinecorrectedp = pupil_avg - baseline) %>%
      dplyr::rename(pup_interp = pupil_avg) %>%
      dplyr::arrange(subject, trial, time)
  }

  if (baseline_method=="div") {
    message("Calculating median baseline from",":", baseline_window[1], "-", baseline_window[2])
    message("Merging baseline")
    baseline <- datafile  %>%
      dplyr::filter(time > baseline_window[1],
                    time < baseline_window[2]) %>%
      dplyr::group_by(subject) %>%
      dplyr::rename(pupil_avg = pupil_colname) %>%
      dplyr::summarise(baseline = median(pupil_avg, na.rm=TRUE)) %>%
      dplyr::full_join(., datafile) %>% # merge median pupil size with raw dataset
       ungroup()  
   #use grand average baseline instead of individual trial baseline to minimize bias
    
    message("Performing divisive baseline correction")

    corrected_baseline <- baseline %>%
      dplyr::rename(pupil_avg = pupil_colname) %>%
      dplyr::mutate(baselinecorrectedp = (pupil_avg - baseline)/baseline) %>%
      dplyr::rename(pup_interp = pupil_avg) %>%
      dplyr::arrange(subject, trial, time)

  }

  return(corrected_baseline)

}