#' Standard Deviation of a collection of spectra
#'
#' A method to compute the standard deviation of values across members of a
#' collections of spectra. Computes the standard deviation at each wavelength
#' across all the spectra in the collection returning a spectral object.
#'
#' @param x An R object. Currently this package defines methods for collections
#' of spectral objects.
#' @param na.rm logical. A value indicating whether NA values should be stripped
#' before the computation proceeds.
#' @param ... Further arguments passed to or from other methods.
#'
#' @return If \code{x} is a collection spectral of objects, such as a
#' "filter_mspct" object, the returned object is of class "generic_spct",
#' containing the standard deviation among the spectra at each wavelength
#' in a column with name ending in ".sd".
#'
#' @note Omission of NAs is done separately at each wavelength. Interpolation is
#' not applied, so all spectra in \code{x} must share the same set of
#' wavelengths.
#'
#' Objects of classes raw_spct and cps_spct can contain data from multiple
#' scans. This functions are implemented for these classes only for the case
#' when all member spectra contain data for a single scan, or spliced into a
#' single column in the case of cps_spct members.
#'
#' @seealso See \code{\link[stats]{sd}} for details about \code{sd()} methods
#' for other classes.
#'
#' @export
#'
s_sd <- function(x, na.rm, ...)
UseMethod("s_sd")
#' @describeIn s_sd
#'
#' @export
#'
s_sd.default <- function(x, na.rm = FALSE, ...) {
warning("Metod 'sd()' not implementd for objects of class ",
class(x)[1],
".")
ifelse(is.any_mspct(x), generic_spct(), NA)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.filter_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_filter(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.source_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_source(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.response_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_response(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.reflector_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_reflector(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.calibration_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_calibration(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.cps_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_cps(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
#' @describeIn s_sd
#'
#' @export
#'
s_sd.raw_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_raw(
x = x,
.fun = stats::sd,
na.rm = na.rm,
col.name.tag = ".sd",
.fun.name = "Standard deviation for"
)
}
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