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#'Percentage of anomalies which agrees with the sign of the mean anomaly for
#'multidimensional arrays
#'
#'@description This function computes the mean and the percentage of agreement
#'between anomalies.
#'
#'@param ano A multidimensional array.
#'@param membersdim The dimension in which models are stored.
#'@param na.rm A logical indicating whether missing values should be removed. If
#' \code{na.rm} is FALSE an NA value in any of the arguments will cause a value
#' of NA to be returned, otherwise (TRUE by default) NA values are ignored.
#'@param ncores The number of cores to be used when computing the agreement.
#'
#'@return An array of one dimension less than the \code{ano} object, except for
#'one dimensional arrays or vectors, for which an array of dimension 1 called
#''var' is returned.
#'
#'@import multiApply
#'@examples
#'# Example with random sample:
#'a <- NULL
#'for(i in 1:20) { a <- c(a, rnorm(6)) }
#'dim(a) <- c(lat = 2, lon = 3, var = 4, mod = 5)
#'
#'agree <- AnoAgree(ano = a, membersdim = which(names(dim(a)) == 'mod'),
#' na.rm = TRUE, ncores = NULL)
#'print(agree)
#'
#'a <- rnorm(6)
#'agree <- AnoAgree(ano = a, membersdim = 1, na.rm = TRUE, ncores = NULL)
#'print(agree)
#'@export
AnoAgree <- function(ano, membersdim, na.rm = TRUE, ncores = NULL) {
if (is.null(ano)) {
stop("Parameter 'ano' cannot be NULL.")
}
if (!is.numeric(ano)) {
stop("Parameter 'ano' must be a numeric array.")
}
if (!is.numeric(membersdim)) {
stop("Parameter 'membersdim' must be an integer.")
}
if (is.null(dim(ano))) {
if (membersdim == 1) {
dim(ano) <- c(mod = length(ano), var = 1)
} else {
dim(ano) <- c(mod = length(ano), var = 1)
membersdim = 1
}
} else if (length(dim(ano)) == 1) {
if (membersdim == 1) {
dim(ano) <- c(dim(ano), var = 1)
} else {
dim(ano) <- c(dim(ano), var = 1)
membersdim = 1
}
}
if (!is.logical(na.rm)) {
stop("Parameter 'na.rm' must be logical.")
}
if (length(na.rm) > 1) {
na.rm = na.rm[1]
warning("Parameter 'na.rm' has length > 1 and only the first element will be used.")
}
if (!is.numeric(ncores) & !is.null(ncores)) {
stop("Parameter 'ncores' must be numeric.")
}
if (length(ncores) == 0 & !is.null(ncores)) {
stop("Parameter 'ncores' must be of length 1.")
}
if (length(ncores) > 1) {
ncores = ncores[1]
warning("Parameter 'ncores' has length > 1 and only the first element will be used.")
}
if (!is.null(ncores)) {
ncores <- round(ncores)
if (ncores == 0) {
ncores = NULL
}
}
margins <- 1 : length(dim(ano))
margins <- margins[-membersdim]
ano_agree <- Apply(data = list(ano), margins = list(margins),
fun = .AnoAgree,
na.rm = na.rm,
ncores = ncores)[[1]]
if (!is.null(names(dim(ano))) & length(dim(ano)) > 0) {
dim_names <- names(dim(ano))
names(dim(ano_agree)) <- dim_names[-membersdim]
}
ano_agree
}
.AnoAgree <- function(data, na.rm = na.rm) {
data <- unlist(data)
ano_mean <- mean(data, na.rm = na.rm)
if (!is.na(ano_mean)) {
if (ano_mean > 0) {
ano_agree <- 100 * sum(data[!is.na(data)] > 0) / length(data[!is.na(data)])
} else if (ano_mean < 0) {
ano_agree <- 100 * sum(data[!is.na(data)] < 0) / length(data[!is.na(data)])
} else if (ano_mean == 0) {
warning("Anomaly mean is equal to 0.")
}
} else {
ano_agree <- NA
}
return(ano_agree)
}
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