#' A function to get the L2 norm.
#' @title getL2norm
#' @aliases getL2norm
#' @keywords trace L2 norm RNA
#' @usage getL2norm(sample, base=sample[1,], margin=1)
#' @param sample A numeric matrix containing values to be compared (e.g. a set of mutant SHAPE traces).
#' @param base An optional numeric vector containing the values to which the samples are to be compared (e.g. a wildtype SHAPE trace). Default is the first trace in sample.
#' @param margin An optional number indicating if the samples are organized by rows or columns, where 1 indicates rows and 2 indicates columns. Default is 1.
#' @export
#' @details This function calculates the L2 norm between the base vector and each row (or column) in sample.
#' @return A numeric vector of L2 norm values.
#' @author Chanin Tolson
#' @seealso \code{\link{getFeatures}}
#' @examples #sample data
#' sample = matrix(sample(1:100), ncol=10)
#' #normalize
#' samp_norm = normalize(sample)
#' #reduce noise
#' samp_nreduce = reduceNoise(samp_norm, trim=1, high=4)
#' #get trace difference
#' l2norm = getL2norm(samp_nreduce)
getL2norm = function(sample, base=sample[1,], margin=1){
#set optional paramater margin
if(missing(margin)) {
margin = 1
} else {
if(!(margin %in% c(1,2))){
warning("Margin value not valid. Margin set to default.")
margin = 1
}
if(margin==2){
sample = t(sample)
}
}
#set optional paramater base
if(missing(base)) {
base = sample[1,]
} else {
base = base
}
#calculate L2 norm
norm = function(sample, base){
l2 = sqrt(sum(((as.numeric(sample)-as.numeric(base))^2), na.rm=TRUE))
return(l2)
}
l2norm = apply(sample, 1, norm, base=base)
#return L2 norm
return(l2norm)
}
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