R/eventStatisticsByDay.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 store in validDays, derive event statistics (meals, medication and exercise).
# Returns a data frame containing the event statistics for each day, and average across days.
eventStatisticsByDay <- function(validDays, rs, participantID) {

	mtVDs = data.frame()
	exVDs = data.frame()
	medVDs = data.frame()	

        cnamesMT=c()
	cnamesEx=c()
	cnamesMed=c()

	allEvents = data.frame(dayidx=c(), time=c(), time_to_peak=c(), postprand_1hr=c(), postprand_2hr=c())

        count=1
        for (vd in validDays) {

		events = vd@events

		if (is.null(events)) {
			next
		}

		raw = getDayGlucoseValues(vd)

                # event (meals, exercise, medication) statistics of this valid day only
		mealEvents = mealtimeStatistics(events, raw)

		if (nrow(mealEvents@events)>0) {
			mealEvents@events = cbind(dayidx = vd@dayidx, mealEvents@events)
			mealEvents@events$event = 'meal'
			allEvents = rbind(allEvents, mealEvents@events)
		}
		
		exEvents = exerciseStatistics(events, raw)

		if (nrow(exEvents@events)>0) {
			exEvents@events = cbind(dayidx = vd@dayidx, exEvents@events)
			exEvents@events$event = 'exercise'
			allEvents = rbind(allEvents, exEvents@events)
		}

		medEvents = medicationStatistics(events, raw)

		if (nrow(medEvents@events)>0) {
			medEvents@events = cbind(dayidx = vd@dayidx, medEvents@events)
			medEvents@events$event = 'medication'
			allEvents = rbind(allEvents, medEvents@events)
		}

		if (count==1) {
			mtVDs = data.frame(mealEvents@meantimetopeak, mealEvents@meanpp1, mealEvents@meanpp2)
			exVDs = data.frame(exEvents@meanpp1, exEvents@meanpp2)
			medVDs = data.frame(medEvents@meanpp1, medEvents@meanpp2)
		} else {
			mtVDs = cbind.data.frame(mtVDs, data.frame(mealEvents@meantimetopeak, mealEvents@meanpp1, mealEvents@meanpp2))
			exVDs = cbind.data.frame(exVDs, data.frame(exEvents@meanpp1, exEvents@meanpp2))
			medVDs = cbind.data.frame(medVDs, data.frame(medEvents@meanpp1, medEvents@meanpp2))
		}

	        cnamesMT = append(cnamesMT, c(paste("meal_timeToPeak_day", count, sep=""), paste("meal_1hr_postprandial_day", count, sep=""), paste("meal_2hr_postprandial_day", count, sep="")))
		cnamesEx = append(cnamesEx, c(paste("exerc_1hr_postprandial_day", count, sep=""), paste("exerc_2hr_postprandial_day", count, sep="")))
		cnamesMed = append(cnamesMed, c(paste("medic_1hr_postprandial_day", count, sep=""), paste("medic_2hr_postprandial_day", count, sep="")))

                count=count+1

        }

	saveEventData(allEvents, participantID, rs)



	# average each statistic across days
	colnames(mtVDs) = cnamesMT
	colnames(exVDs)	= cnamesEx
	colnames(medVDs) = cnamesMed

	mt_ttp = meanAcrossDays("meal_timeToPeak_day", mtVDs)
	mt_pp1 = meanAcrossDays("meal_1hr_postprandial_day", mtVDs)
	mt_pp2 = meanAcrossDays("meal_2hr_postprandial_day", mtVDs)
	ex_pp1 = meanAcrossDays("exerc_1hr_postprandial_day", exVDs)
       	ex_pp2 = meanAcrossDays("exerc_2hr_postprandial_day", exVDs)
	med_pp1 = meanAcrossDays("medic_1hr_postprandial_day", medVDs)
       	med_pp2 = meanAcrossDays("medic_2hr_postprandial_day", medVDs)


	res = NULL
	if (nrow(mtVDs)>0 | nrow(exVDs)>0 | nrow(medVDs)>0) {

		othervars = c(mt_ttp, mt_pp1, mt_pp2, ex_pp1, ex_pp2, med_pp1, med_pp2)
	  	othervars = rbind(othervars)
		colnames(othervars) = c("mean_meal_timeToPeak", "mean_meal_pp1", "mean_meal_pp2", "mean_exerc_pp1", "mean_exerc_pp2", "mean_medic_pp1", "mean_medic_pp2")

		res = cbind(mtVDs, exVDs, medVDs, othervars)
		
	}

        return(res)

}