clsa

Fast min/max sliding window algorithm on unevenly spaced data. Impemented for use in R (R wrapper functions call C code for speed).

Details are available in the paper: Informed baseline subtraction of proteomic mass spectrometry data aided by a novel sliding window algorithm. Specifically, Figure 7 contains the details of the CLSA algorithm.

Installation

To install and load in R, run:

library(devtools) # see http://cran.r-project.org/web/packages/devtools/README.html
devtools::install_github('tystan/clsa')
library(clsa)
### see help file to run example
?clsa_min

Example usage

set.seed(12345)
n <- 100 # number of points
x <- sort(runif(n)) # location of points
f <- rchisq(n, 10) # signal at points
this_win <- 0.1 # the size of the window passed over the points

# rolling/moving minimum (erosion in morphology)
mins_f <- clsa_min(x, f, this_win)
# rolling/moving maximum (dilation in morphology)
maxs_f <- clsa_max(x, f, this_win)
# this is a morphological opening (dilation of the erosion)
mo_f   <- clsa_max(x, mins_f, this_win)

# plot data, erosion, dilation and opening
plot(x, f, type = "l", bty = "n")
lines(x, mins_f, col = "navy")
lines(x, maxs_f, col = "firebrick4")
lines(x,   mo_f, col = "forestgreen")