findpeaks

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

findpeaks(
  x,
  nups = 1,
  ndowns = nups,
  zero = "0",
  peakpat = NULL,
  minpeakheight = -Inf,
  minpeakdistance = 1,
  h_min = 0,
  h_max = 0,
  npeaks = 0,
  sortstr = FALSE,
  include_gregexpr = FALSE,
  IsPlot = F
)

Arguments

x

Numeric vector.

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.

h_min

h is defined as the difference of peak value to the adjacent left and right trough value (h_left and h_right respectively). The real peaks should follow min(h_left, h_right) >= h_min.

h_max

Similar as h_min, the real peaks should follow max(h_left, h_right) >= h_min.

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?

include_gregexpr

Boolean (default FALSE), whether to include the matched gregexpr?

IsPlot

Boolean, whether to plot?

Note

In versions before v0.3.4, findpeaks(c(1, 2, 3, 4, 4, 3, 1)) failed to detect peaks when a flat pattern exit in the middle.

From version v0.3.4, the peak pattern was changed from [+]{%d,}[-]{%d,} to [+]{%d,}[0]{0,}[-]{%d,}. The latter can escape the flat part successfully.

Examples

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, h_min=4, sortstr=TRUE)
points(val~pos, x$X, pch=20, col="maroon")