R/aucByDay.R

In MRCIEU/GLU: Derives Summary Variables from Continuous Glucose Monitoring (CGM) data

# The MIT License (MIT)
# Copyright (c) 2018 Louise AC Millard, MRC Integrative Epidemiology Unit, University of Bristol
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# For each valid day in validDays, generate the auc
# Returns a data frame - the auc values of each day, and the average across all days overall.
aucByDay <- function(validDays) {

	aucs = c()

	# column names for each auc value we generate	
	cnames = c()

	count=1

	# for each valid day, calculate the auc
	for (vd in validDays) {
		
		# sequence of timepoints for this day

		# auc of this day only
		aucVD = auc(getDayGlucoseValues(vd, interp=TRUE))

		# nighttime, daytime aucs
		aucVDn = auc(getDayGlucoseValues(vd, night=TRUE, interp=TRUE))
		aucVDd = auc(getDayGlucoseValues(vd, day=TRUE, interp=TRUE))

		aucs = append(aucs, c(aucVD, aucVDn, aucVDd))
		cnames = append(cnames, c(paste("auc_day", count, sep=""), paste("auc_nt_day", count, sep=""), paste("auc_dt_day", count, sep="")))

                count=count+1
	}

	# set column names for auc values
	res = rbind(aucs)
	colnames(res) = cnames

	aucAv = meanAcrossDays("auc_day", res)
	aucAvN = meanAcrossDays("auc_nt_day", res)
	aucAvD = meanAcrossDays("auc_dt_day", res)

	othervars = c(aucAv, aucAvN, aucAvD)
  	othervars = rbind(othervars)
	colnames(othervars) = c("meanAUCperDay", "meanAUCperDay_nt", "meanAUCperDay_dt")

	res = cbind(res, othervars)

	return(res)

}