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#' Median of a collection of spectra
#'
#' Method to compute the "parallel" median of values across members of a
#' collection of spectra or of a spectral object containing multiple spectra in
#' long form.
#'
#' @details Method specializations compute the median at each wavelength across a
#' group of spectra stored in an object of one of the classes defined in
#' package 'photobiology'. 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. An error is triggered
#' if this condition is nor fulfilled.
#'
#' @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
#' \code{"filter_mspct"} object, the returned object is of same class as the
#' members of the collection, such as \code{"filter_spct"}, containing the
#' summary spectrum, with variables with names tagged for summaries other
#' than mean or median.
#'
#' @note Objects of classes \code{raw_spct} and \code{cps_spct} can contain data
#' from multiple scans in multiple variables or "columns". The methods accept
#' as arguments objects of these classes only if spectra contain data for a
#' single spectrometer scan. In the case of \code{cps_spct} objects, a single
#' column can also contain data from multiple scans spliced into a single
#' variable.
#'
#' @seealso See \code{\link[stats]{median}} for the \code{median()} method used
#' for the computations.
#'
#' @export
#'
#' @examples
#' s_median(sun_evening.mspct)
#'
s_median <- function(x, na.rm, ...) UseMethod("s_median")
#' @describeIn s_median
#'
#' @export
#'
s_median.default <- function(x, na.rm = FALSE, ...) {
warning("Metod 's_median()' not implementd for objects of class ", class(x)[1], ".")
ifelse(is.any_mspct(x), do.call(class(x[[1]])[1], args = list()), NA)
}
#' @describeIn s_median
#'
#' @export
#'
s_median.generic_spct <- function(x, na.rm = FALSE, ...) {
if (getMultipleWl(x) > 1) {
s_median(subset2mspct(x), na.rm = na.rm, ...)
} else {
x
}
}
#' @describeIn s_median
#'
#' @export
#'
s_median.source_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_source(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.response_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_response(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.filter_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_filter(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.reflector_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_reflector(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.calibration_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_calibration(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.cps_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_cps(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
#' @describeIn s_median
#'
#' @export
#'
s_median.raw_mspct <- function(x, na.rm = FALSE, ...) {
rowwise_raw(x = x, .fun = stats::median, na.rm = na.rm, .fun.name = "Median of")
}
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