R/numPeaks.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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# Finds the nearest subsequent SG peak, after idxMeal in raw.
# Returns the time in minutes, from the timepoint at idxMeal to this peak.
# Where the peak is a plateau (multiple consecutive timepoints have the same SG value) then the time to the earliest timepoint of the plateau is used.
# Where no peak is found before the end of the sequence is reached, NA is returned.
numPeaks <- function(raw, eventTime) {


	numPeaks=0

	start = raw$sgReading[1]

	# the index at which we are checking for a peak
	currentIdx1 = 2

	# the index we are looking at if we are on a plateau (to see if, at the end of the plateau there is a decrease indicating that the position currentIdx1 is a peak)
	currentIdx2 = NA

	# loop to the end of the sequence but stop early if we find a peak
	while (currentIdx1<nrow(raw) & (is.na(currentIdx2) | currentIdx2<nrow(raw))) {

		current = raw$sgReading[currentIdx1]

		# no plateau
		if (is.na(currentIdx2)) {
			nextIdx = currentIdx1+1
		} else {
			nextIdx = currentIdx2+1
		}
		nextx = raw$sgReading[nextIdx]

		if (current>nextx & current > start) {

                        # time peak after occurs
                        peakTime = raw$time[currentIdx1]
			numPeaks = numPeaks + 1

			start=raw$sgReading[nextIdx]
			currentIdx1 = nextIdx+1
                        currentIdx2 = NA
		
                }
		else if (current == nextx) {
			# in a plateau so set end idx of this plateau
			currentIdx2 = nextIdx
		}
		else {
			# not in a plateau so just set the current position we are looking at
			currentIdx1 = nextIdx
			currentIdx2 = NA
			start=raw$sgReading[nextIdx-1]
		}

	}

	return(numPeaks)

}