#' Set spectral binning parameters
#' @description Selection of parameters to use for spectral binning.
#' @param scans numeric vector containing the scan indexes to use for binning
#' @param cls the column of class labels to use for aggregating accurate
#' mass data. Defaults to NULL where accurate mass data will be averaged
#' accross all samples
#' @return S4 object of class BinParameters
#' @examples
#' p <- binParameters(scans = 6:17)
#' @seealso \code{\link{BinParameters-class}}, \code{\link{scans}},
#' \code{\link{cls}}
#' @importFrom parallel detectCores
#' @export
binParameters <- function(scans = 5:12,
cls = character()){
p <- new('BinParameters',
scans = scans,
cls = cls
)
return(p)
}
#' Get and set spectral binning parameters
#' @rdname parameters
#' @description Get and set spectral binning parameters.
#' @param x S4 object of class BinParameters
#' @param value parameter value to set
#' @seealso \code{\link{BinParameters-class}}, \code{\link{binParameters}}
#' @export
setMethod('scans',signature = 'BinParameters',function(x){
x@scans
})
#' @rdname parameters
#' @export
setMethod('scans<-',signature = 'BinParameters',
function(x,value){
x@scans <- value
return(x)
})
#' @rdname parameters
#' @export
setMethod('cls',signature = 'BinParameters',function(x){
x@cls
})
#' @rdname parameters
#' @export
setMethod('cls<-',signature = 'BinParameters',function(x,value){
x@cls <- value
return(x)
})
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