R/GVPByDay.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, derive the GVP 
# This is just for testing since GLU uses SGVP
# Returns the GVP for each day, and the average across all days overall.
GVPByDay <- function(validDays) {

	gvps = c()	

	cnames=c()
	count=1
	for (vd in validDays) {

		raw = getDayGlucoseValues(vd, interp=TRUE)

		# GVP for whole day, nighttime and daytime GVP
		gvpVD = SGVP(raw, FALSE)
		gvpVDn = SGVP(getDayGlucoseValues(vd, night=TRUE, interp=TRUE), FALSE)
		gvpVDd = SGVP(getDayGlucoseValues(vd, day=TRUE, interp=TRUE), FALSE)

		gvps = append(gvps, c(gvpVD, gvpVDn, gvpVDd))

		cnames = append(cnames, c(paste("GVP_day", count, sep=""), paste("GVP_nt_day", count, sep=""), paste("GVP_dt_day", count, sep="")))

                count=count+1
	}


	res = rbind(gvps)
        colnames(res) = cnames

	# '^' is needed so it doesn't match SGVP..
	gvpAv = meanAcrossDays("^GVP_day", res)
	gvpAvN = meanAcrossDays("^GVP_nt_day", res)
	gvpAvD = meanAcrossDays("^GVP_dt_day", res)

	othervars = c(gvpAv, gvpAvN, gvpAvD)
	othervars = rbind(othervars)
	colnames(othervars) = c("meanGVPPerDay", "meanGVPPerDay_nt","meanGVPPerDay_dt")
	res = cbind(res, othervars)

	return(res)

}