normalizeDifferencesToAverage {aroma.light} | R Documentation |
Rescales channel vectors to get the same average.
## S3 method for class 'list' normalizeDifferencesToAverage(x, baseline=1, FUN=median, ...)
x |
|
baseline |
An |
FUN |
A |
... |
Additional arguments passed to the |
Returns a normalized list
of length K.
Henrik Bengtsson
# Simulate three shifted tracks of different lengths with same profiles ns <- c(A=2, B=1, C=0.25)*1000 xx <- lapply(ns, FUN=function(n) { seq(from=1, to=max(ns), length.out=n) }) zz <- mapply(seq_along(ns), ns, FUN=function(z,n) rep(z,n)) yy <- list( A = rnorm(ns["A"], mean=0, sd=0.5), B = rnorm(ns["B"], mean=5, sd=0.4), C = rnorm(ns["C"], mean=-5, sd=1.1) ) yy <- lapply(yy, FUN=function(y) { n <- length(y) y[1:(n/2)] <- y[1:(n/2)] + 2 y[1:(n/4)] <- y[1:(n/4)] - 4 y }) # Shift all tracks toward the first track yyN <- normalizeDifferencesToAverage(yy, baseline=1) # The baseline channel is not changed stopifnot(identical(yy[[1]], yyN[[1]])) # Get the estimated parameters fit <- attr(yyN, "fit") # Plot the tracks layout(matrix(1:2, ncol=1)) x <- unlist(xx) col <- unlist(zz) y <- unlist(yy) yN <- unlist(yyN) plot(x, y, col=col, ylim=c(-10,10)) plot(x, yN, col=col, ylim=c(-10,10))