findpeaks: findpeaks

Description Usage Arguments Examples

Description

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

Usage

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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
)

Arguments

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.

Examples

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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")

phenofit documentation built on April 2, 2020, 5:07 p.m.