extremist {DecomposeR}

Gives local extrema and zero crossings intervals

Description

Gives local minimas, maximas and zero crossings. Optimised for large data sets; the sky is the limit (and by the sky I mean the ability of R and your computer to memorise large data sets; but within this limit the algorithm can handle millions of points quickly).

Usage

extremist(xy, bound = FALSE, local = TRUE, zc = TRUE)

Arguments

xy

the values where to find the local extremas

bound

whether to consider the first and last points as both minima and maxima, for special purposes. Default is F, has it should be.

local

whether to consider the first and last points as local minima and maxima, if TRUE by default, otherwise these first and last points will be ignored

zc

whether to return the zero crossings

Value

a list of the indexes of the left (l) and right (r) boundaries for the minima (minindex), maxima (maxindex) and zero crossing (cross), along with the number of extrema and zero crossings

Examples

# Function script ----

xy <- c(1,0,0,0,4,5,5,0.5,-0.5,0.5,0,2,2,1,-1,-1,1,1,0,0,-4,-2,2,1,0,0.5,0,
        NA, 0.5,0,-0.5,3,2,3,0,0.5,4,4,0)

impressme <- 0 # Increase up to 5 or 6 to be impressed (bugs if your system
               # can't handle the size of the data).
               # If you increase it, do not run the plot script.

xy <- rep(xy, round(10^impressme))

print(paste("You are running ", length(xy), " points", sep = ""))

res <- extremist(xy)



# Plot script: do not run if you increase the impressme parameter ----

mini <- unique(c(res$minindex[[1]], res$minindex[[2]]))
maxi <- unique(c(res$maxindex[[1]], res$maxindex[[2]]))
zeri <- unique(c(res$cross[[1]], res$cross[[2]]))

l <- length(xy)

opar <- par("mfrow")

par(mfrow = c(3,1))

plot(1:l, xy, type = "o",pch = 19)
points(mini, xy[mini], pch = 19, col = "blue")

plot(1:l, xy, type = "o",pch = 19)
points(maxi, xy[maxi], pch = 19, col = "red")

plot(1:l, xy, type = "o",pch = 19)
points(zeri, xy[zeri], pch = 19, col = "green")
abline(h = 0, col = "grey")

par(mfrow = opar)