findpeaks: findpeaks
In phenofit: Extract Remote Sensing Vegetation Phenology

Find peaks (maxima) in a time series. This function is modified from pracma::findpeaks.

findpeaks(
  x,
  IsDiff = TRUE,
  nups = 1,
  ndowns = nups,
  zero = "0",
  peakpat = NULL,
  minpeakheight = -Inf,
  minpeakdistance = 1,
  y_min = 0,
  y_max = 0,
  npeaks = 0,
  sortstr = FALSE,
  IsPlot = F
)

`x`	Numeric vector.
`IsDiff`	If want to find extreme values, `IsDiff` should be true; If just want to find the continue negative or positive values, just set `IsDiff` as false.
`nups`	minimum number of increasing steps before a peak is reached
`ndowns`	minimum number of decreasing steps after the peak
`zero`	can be `+`, `-`, or `0`; how to interprete succeeding steps of the same value: increasing, decreasing, or special
`peakpat`	define a peak as a regular pattern, such as the default pattern `[+]{1,}[-]{1,}`; if a pattern is provided, the parameters `nups` and `ndowns` are not taken into account
`minpeakheight`	The minimum (absolute) height a peak has to have to be recognized as such
`minpeakdistance`	The minimum distance (in indices) peaks have to have to be counted. If the distance of two maximum extreme value less than `minpeakdistance`, only the real maximum value will be left.
`y_min`	Threshold is defined as the difference of peak value with trough value. There are two threshold (left and right). The minimum threshold should be greater than `y_min`.
`y_max`	Similar as `y_min`, The maximum threshold should be greater than `y_max`.
`npeaks`	the number of peaks to return. If `sortstr` = true, the largest npeaks maximum values will be returned; If `sortstr` = false, just the first npeaks are returned in the order of index.
`sortstr`	Boolean, Should the peaks be returned sorted in decreasing oreder of their maximum value?
`IsPlot`	Boolean.

x <- seq(0, 1, len = 1024)
pos <- c(0.1, 0.13, 0.15, 0.23, 0.25, 0.40, 0.44, 0.65, 0.76, 0.78, 0.81)
hgt <- c(4, 5, 3, 4, 5, 4.2, 2.1, 4.3, 3.1, 5.1, 4.2)
wdt <- c(0.005, 0.005, 0.006, 0.01, 0.01, 0.03, 0.01, 0.01, 0.005, 0.008, 0.005)
pSignal <- numeric(length(x))
for (i in seq(along=pos)) {
    pSignal <- pSignal + hgt[i]/(1 + abs((x - pos[i])/wdt[i]))^4
}

plot(pSignal, type="l", col="navy"); grid()
x <- findpeaks(pSignal, npeaks=3, y_min=4, sortstr=TRUE)
points(val~pos, x$X, pch=20, col="maroon")