R/mean_sd.R

In GegznaV/hyperSpec2: Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

## make generic functions without default
##' @noRd
setGeneric ("mean_sd", function (x, na.rm = TRUE, ...) standardGeneric ("mean_sd"))
##' @noRd
setGeneric ("mean_pm_sd", function (x, na.rm = TRUE, ...) standardGeneric ("mean_pm_sd"))

##' Mean and Standard Deviation
##' Calculate mean and standard deviation, and mean, mean \eqn{\pm}{+-} one
##' standard deviation, respectively.
##' 
##' These functions are provided for convenience.
##' 
##' @aliases mean_sd
##' @rdname mean_sd
##' @param x a numeric vector
##' @param na.rm handed to \code{\link[base]{mean}} and \code{\link[stats]{sd}}
##' @param ... ignored (needed to make function generic)
##' @return \code{mean_sd} returns a vector with two values (mean and standard
##'   deviation) of \code{x}.
##' @seealso \code{\link[base]{mean}}, \code{\link[stats]{sd}}
##' @keywords multivar
##' @export
##' @examples
##' 
##' mean_sd (flu [,, 405 ~ 410])
setMethod ("mean_sd", signature = signature (x = "numeric"),
           function (x, na.rm = TRUE, ...) {
             c (mean = mean (x, na.rm = na.rm),
                sd   = sd   (x, na.rm = na.rm)
                )
           }
           )

##' @rdname mean_sd
##' @return \code{mean_sd (matrix)} returns a matrix with the mean spectrum in the first row and the standard deviation in the 2nd.
##' @export
##' @examples
##' 
##' mean_sd (flu$spc)
setMethod ("mean_sd", signature = signature (x = "matrix"),
           function (x, na.rm = TRUE, ...) {
             m <- colMeans (x, na.rm = na.rm)
             s <- apply (x, 2, sd, na.rm = na.rm)
             rbind (mean = m, sd = s)
           })

##' @rdname mean_sd
##' @return \code{mean_sd} returns a hyperSpec object with the mean spectrum in the first row and the standard deviation in the 2nd.
##' @author C. Beleites
##' @seealso \code{\link[base]{mean}}, \code{\link[stats]{sd}}
##' @keywords univar
##' @export
##' @examples
##' 
##' mean_sd (flu)
setMethod ("mean_sd", signature = signature (x = "hyperSpec"),
           function (x, na.rm = TRUE, ...) {
             decomposition (x, mean_sd (x@data$spc), scores = FALSE)
           })


##' @aliases mean_pm_sd
##' @rdname mean_sd
##' @return
##'  
##' \code{mean_pm_sd} returns a vector with 3 values: mean - 1 sd, mean, mean + 1 sd
##' @export
##' @examples
##' 
##'   mean_pm_sd (flu$c)
setMethod ("mean_pm_sd", signature = signature (x = "numeric"),
           function (x, na.rm = TRUE, ...){
             m <- mean (x, na.rm = na.rm)
             s <- sd (x, na.rm = na.rm)
             c("mean.minus.sd" = m - s, "mean" = m, "mean.plus.sd" = m + s)
           })

##' @rdname mean_sd
##' @return \code{mean_pm_sd (matrix)} returns a matrix containing mean - sd, mean, and mean + sd
##' rows.
##' @export
##' @examples
##' 
##' mean_pm_sd (flu$spc)
setMethod ("mean_pm_sd", signature = signature (x = "matrix"),
           function (x, na.rm = TRUE, ...) {
             m <- colMeans (x, na.rm = na.rm)
             s <- apply    (x, 2, sd, na.rm = na.rm)
             rbind ("mean - sd" = m - s, mean = m, "mean + sd"= m + s)
           })

##' @rdname mean_sd
##' @return For hyperSpec objects, \code{mean_pm_sd} returns a hyperSpec object containing mean - sd,
##' mean, and mean + sd spectra.
##' @export
##' @examples
##' 
##' mean_pm_sd (flu)
setMethod ("mean_pm_sd", signature = signature (x = "hyperSpec"),
           function (x, na.rm = TRUE, ...) {
             decomposition (x, mean_pm_sd (x@data$spc))
           })

##' @rdname mean_sd
##' @return For hyperSpec object, \code{mean} returns a hyperSpec object containing the mean
##' spectrum.
##' @export
##' @examples
##' 
##' plot (mean (chondro))
setMethod ("mean", signature = signature (x = "hyperSpec"),
					 function (x, na.rm = TRUE, ...){
					 	m <- structure (colMeans (x@data$spc), 
					 									dim = c (1, length (x@wavelength)),
					 									dimnames = list ("mean", NULL))
					 	decomposition (x, m)
					 })