Nothing
#'Accumulation of a variable when Exceeding (not exceeding) a Threshold
#'
#'The accumulation (sum) of a variable in the days (or time steps) that the
#'variable is exceeding (or not exceeding) a threshold during a period. The
#'threshold provided must be in the same units than the variable units, i.e. to
#'use a percentile as a scalar, the function \code{Threshold} or
#'\code{QThreshold} may be needed. Providing mean daily temperature data, the
#'following agriculture indices for heat stress can be obtained by using this
#'function:
#'\itemize{
#' \item{'GDD', Summation of daily differences between daily average
#' temperatures and 10°C between April 1st and October 31st.}
#'}
#'
#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or
#' \code{CST_Load} in package CSTools.
#'@param threshold If only one threshold is used, it can be an 's2dv_cube'
#' object or a multidimensional array with named dimensions. It must be in the
#' same units and with the common dimensions of the same length as parameter
#' 'data'. It can also be a vector with the same length of 'time_dim' from
#' 'data' or a scalar. If we want to use two thresholds: it can be a vector
#' of two scalars, a list of two vectors with the same length of
#' 'time_dim' from 'data' or a list of two multidimensional arrays with the
#' common dimensions of the same length as parameter 'data'. If two thresholds
#' are used, parameter 'op' must be also a vector of two elements.
#'@param op An operator '>' (by default), '<', '>=' or '<='. If two thresholds
#' are used it has to be a vector of a pair of two logical operators:
#' c('<', '>'), c('<', '>='), c('<=', '>'), c('<=', '>='), c('>', '<'),
#' c('>', '<='), c('>=', '<'),c('>=', '<=')).
#'@param diff A logical value indicating whether to accumulate the difference
#' between data and threshold (TRUE) or not (FALSE by default). It can only be
#' TRUE if a unique threshold is used.
#'@param start An optional parameter to define the initial date of the period
#' to select from the data by providing a list of two elements: the initial
#' date of the period and the initial month of the period. By default it is
#' set to NULL and the indicator is computed using all the data provided in
#' \code{data}.
#'@param end An optional parameter to define the final date of the period to
#' select from the data by providing a list of two elements: the final day of
#' the period and the final month of the period. By default it is set to NULL
#' and the indicator is computed using all the data provided in \code{data}.
#'@param time_dim A character string indicating the name of the dimension to
#' compute the indicator. By default, it is set to 'time'. It can only
#' indicate one time dimension.
#'@param na.rm A logical value indicating whether to ignore NA values (TRUE)
#' or not (FALSE).
#'@param ncores An integer indicating the number of cores to use in parallel
#'computation.
#'
#'@return An 's2dv_cube' object containing the aggregated values in the element
#'\code{data} with dimensions of the input parameter 'data' except the dimension
#'where the indicator has been computed. The 'Dates' array is updated to
#'the dates corresponding to the beginning of the aggregated time period. A new
#'element called 'time_bounds' will be added into the 'attrs' element in the
#''s2dv_cube' object. It consists of a list containing two elements, the start
#'and end dates of the aggregated period with the same dimensions of 'Dates'
#'element.
#'
#'@examples
#'exp <- NULL
#'exp$data <- array(abs(rnorm(5 * 3 * 214 * 2)*100),
#' c(memb = 5, sdate = 3, time = 214, lon = 2))
#'class(exp) <- 's2dv_cube'
#'Dates <- c(seq(as.Date("01-05-2000", format = "%d-%m-%Y"),
#' as.Date("30-11-2000", format = "%d-%m-%Y"), by = 'day'),
#' seq(as.Date("01-05-2001", format = "%d-%m-%Y"),
#' as.Date("30-11-2001", format = "%d-%m-%Y"), by = 'day'),
#' seq(as.Date("01-05-2002", format = "%d-%m-%Y"),
#' as.Date("30-11-2002", format = "%d-%m-%Y"), by = 'day'))
#'dim(Dates) <- c(sdate = 3, time = 214)
#'exp$attrs$Dates <- Dates
#'AT <- CST_AccumulationExceedingThreshold(data = exp, threshold = 100,
#' start = list(21, 4),
#' end = list(21, 6))
#'
#'@import multiApply
#'@importFrom ClimProjDiags Subset
#'@export
CST_AccumulationExceedingThreshold <- function(data, threshold, op = '>', diff = FALSE,
start = NULL, end = NULL, time_dim = 'time',
na.rm = FALSE, ncores = NULL) {
# Check 's2dv_cube'
if (!inherits(data, 's2dv_cube')) {
stop("Parameter 'data' must be of the class 's2dv_cube'.")
}
# Dates subset
if (!is.null(start) && !is.null(end)) {
if (is.null(dim(data$attrs$Dates))) {
warning("Dimensions in 'data' element 'attrs$Dates' are missed and ",
"all data would be used.")
start <- NULL
end <- NULL
}
}
if (length(op) == 1) {
if (inherits(threshold, 's2dv_cube')) {
threshold <- threshold$data
}
} else if (length(op) == 2) {
if (inherits(threshold[[1]], 's2dv_cube')) {
threshold[[1]] <- threshold[[1]]$data
}
if (inherits(threshold[[2]], 's2dv_cube')) {
threshold[[2]] <- threshold[[2]]$data
}
}
Dates <- data$attrs$Dates
total <- AccumulationExceedingThreshold(data = data$data, dates = Dates,
threshold = threshold, op = op, diff = diff,
start = start, end = end, time_dim = time_dim,
na.rm = na.rm, ncores = ncores)
data$data <- total
data$dims <- dim(total)
data$coords[[time_dim]] <- NULL
if (!is.null(Dates)) {
if (!is.null(start) && !is.null(end)) {
Dates <- SelectPeriodOnDates(dates = Dates, start = start, end = end,
time_dim = time_dim, ncores = ncores)
}
if (is.null(dim(Dates))) {
warning("Element 'Dates' has NULL dimensions. They will not be ",
"subset and 'time_bounds' will be missed.")
data$attrs$Dates <- Dates
} else {
# Create time_bounds
time_bounds <- NULL
time_bounds$start <- ClimProjDiags::Subset(x = Dates, along = time_dim,
indices = 1, drop = 'selected')
time_bounds$end <- ClimProjDiags::Subset(x = Dates, along = time_dim,
indices = dim(Dates)[time_dim],
drop = 'selected')
# Add Dates in attrs
data$attrs$Dates <- time_bounds$start
data$attrs$time_bounds <- time_bounds
}
}
return(data)
}
#'Accumulation of a variable when Exceeding (not exceeding) a Threshold
#'
#'The accumulation (sum) of a variable in the days (or time steps) that the
#'variable is exceeding (or not exceeding) a threshold during a period. The
#'threshold provided must be in the same units than the variable units, i.e. to
#'use a percentile as a scalar, the function \code{Threshold} or
#'\code{QThreshold} may be needed. Providing mean daily temperature data, the
#'following agriculture indices for heat stress can be obtained by using this
#'function:
#'\itemize{
#' \item{'GDD', Summation of daily differences between daily average
#' temperatures and 10°C between April 1st and October 31st.}
#'}
#'
#'@param data A multidimensional array with named dimensions.
#'@param threshold If only one threshold is used: it can be a multidimensional
#' array with named dimensions. It must be in the same units and with the
#' common dimensions of the same length as parameter 'data'. It can also be a
#' vector with the same length of 'time_dim' from 'data' or a scalar. If we
#' want to use two thresholds: it can be a vector of two scalars, a list of
#' two vectors with the same length of 'time_dim' from 'data' or a list of
#' two multidimensional arrays with the common dimensions of the same length
#' as parameter 'data'. If two thresholds are used, parameter 'op' must be
#' also a vector of two elements.
#'@param op An operator '>' (by default), '<', '>=' or '<='. If two thresholds
#' are used it has to be a vector of a pair of two logical operators:
#' c('<', '>'), c('<', '>='), c('<=', '>'), c('<=', '>='), c('>', '<'),
#' c('>', '<='), c('>=', '<'),c('>=', '<=')).
#'@param diff A logical value indicating whether to accumulate the difference
#' between data and threshold (TRUE) or not (FALSE by default). It can only be
#' TRUE if a unique threshold is used.
#'@param dates A multidimensional array of dates with named dimensions matching
#' the temporal dimensions on parameter 'data'. By default it is NULL, to
#' select aperiod this parameter must be provided.
#'@param start An optional parameter to define the initial date of the period
#' to select from the data by providing a list of two elements: the initial
#' date of the period and the initial month of the period. By default it is
#' set to NULL and the indicator is computed using all the data provided in
#' \code{data}.
#'@param end An optional parameter to define the final date of the period to
#' select from the data by providing a list of two elements: the final day of
#' the period and the final month of the period. By default it is set to NULL
#' and the indicator is computed using all the data provided in \code{data}.
#'@param time_dim A character string indicating the name of the dimension to
#' compute the indicator. By default, it is set to 'time'. It can only
#' indicate one time dimension.
#'@param na.rm A logical value indicating whether to ignore NA values (TRUE)
#' or not (FALSE).
#'@param ncores An integer indicating the number of cores to use in parallel
#'computation.
#'
#'@return A multidimensional array with named dimensions containing the
#'aggregated values with dimensions of the input parameter 'data' except the
#'dimension where the indicator has been computed.
#'
#'@examples
#'# Assuming data is already (tasmax + tasmin)/2 - 10
#'data <- array(rnorm(5 * 3 * 214 * 2, mean = 25, sd = 3),
#' c(memb = 5, sdate = 3, time = 214, lon = 2))
#'GDD <- AccumulationExceedingThreshold(data, threshold = 0, start = list(1, 4),
#' end = list(31, 10))
#'@import multiApply
#'@export
AccumulationExceedingThreshold <- function(data, threshold, op = '>', diff = FALSE,
dates = NULL, start = NULL, end = NULL,
time_dim = 'time', na.rm = FALSE,
ncores = NULL) {
# data
if (is.null(data)) {
stop("Parameter 'data' cannot be NULL.")
}
if (!is.numeric(data)) {
stop("Parameter 'data' must be numeric.")
}
if (!is.array(data)) {
dim(data) <- length(data)
names(dim(data)) <- time_dim
}
if (is.null(names(dim(data)))) {
stop("Parameter 'data' must have named dimensions.")
}
# time_dim
if (!is.character(time_dim)) {
stop("Parameter 'time_dim' must be a character string.")
}
if (!all(time_dim %in% names(dim(data)))) {
stop("Parameter 'time_dim' is not found in 'data' dimension.")
}
if (length(time_dim) > 1) {
warning("Parameter 'time_dim' has length greater than 1 and ",
"only the first element will be used.")
time_dim <- time_dim[1]
}
# op
if (!is.character(op)) {
stop("Parameter 'op' must be a character.")
}
if (length(op) == 1) {
if (!(op %in% c('>', '<', '>=', '<=', '='))) {
stop("Parameter 'op' must be a logical operator.")
}
} else if (length(op) == 2) {
op_list <- list(c('<', '>'), c('<', '>='), c('<=', '>'), c('<=', '>='),
c('>', '<'), c('>', '<='), c('>=', '<'), c('>=', '<='))
if (!any(unlist(lapply(op_list, function(x) all(x == op))))) {
stop("Parameter 'op' is not an accepted pair of logical operators.")
}
} else {
stop("Parameter 'op' must be a logical operator with length 1 or 2.")
}
# threshold
if (is.null(unlist(threshold))) {
stop("Parameter 'threshold' cannot be NULL.")
}
if (!is.numeric(unlist(threshold))) {
stop("Parameter 'threshold' must be numeric.")
}
if (length(op) == 2) {
if (length(op) != length(threshold)) {
stop("If 'op' is a pair of logical operators parameter 'threshold' ",
"also has to be a pair of values.")
}
if (!is.numeric(threshold[[1]]) | !is.numeric(threshold[[2]])) {
stop("Parameter 'threshold' must be numeric.")
}
if (length(threshold[[1]]) != length(threshold[[2]])) {
stop("The pair of thresholds must have the same length.")
}
if (!is.array(threshold[[1]]) && length(threshold[[1]]) > 1) {
if (dim(data)[time_dim] != length(threshold[[1]])) {
stop("If parameter 'threshold' is a vector it must have the same ",
"length as data any time dimension.")
} else {
dim(threshold[[1]]) <- length(threshold[[1]])
dim(threshold[[2]]) <- length(threshold[[2]])
names(dim(threshold[[1]])) <- time_dim
names(dim(threshold[[2]])) <- time_dim
}
} else if (is.array(threshold[[1]]) && length(threshold[[1]]) > 1) {
if (is.null(names(dim(threshold[[1]])))) {
stop("If parameter 'threshold' is an array it must have named dimensions.")
}
if (!is.null(dim(threshold[[2]]))) {
if (!all(names(dim(threshold[[1]])) %in% names(dim(threshold[[2]])))) {
stop("The pair of thresholds must have the same dimension names.")
}
}
namedims <- names(dim(threshold[[1]]))
order <- match(namedims, names(dim(threshold[[2]])))
threshold[[2]] <- aperm(threshold[[2]], order)
if (!all(dim(threshold[[1]]) == dim(threshold[[2]]))) {
stop("The pair of thresholds must have the same dimensions.")
}
if (any(names(dim(threshold[[1]])) %in% names(dim(data)))) {
common_dims <- dim(threshold[[1]])[names(dim(threshold[[1]])) %in% names(dim(data))]
if (!all(common_dims == dim(data)[names(common_dims)])) {
stop("Parameter 'data' and 'threshold' must have same length of ",
"all common dimensions.")
}
}
} else if (length(threshold[[1]]) == 1) {
dim(threshold[[1]]) <- NULL
dim(threshold[[2]]) <- NULL
}
} else {
if (!is.array(threshold) && length(threshold) > 1) {
if (dim(data)[time_dim] != length(threshold)) {
stop("If parameter 'threshold' is a vector it must have the same ",
"length as data time dimension.")
} else {
dim(threshold) <- length(threshold)
names(dim(threshold)) <- time_dim
}
} else if (is.array(threshold) && length(threshold) > 1) {
if (is.null(names(dim(threshold)))) {
stop("If parameter 'threshold' is an array it must have named dimensions.")
}
if (any(names(dim(threshold)) %in% names(dim(data)))) {
common_dims <- dim(threshold)[names(dim(threshold)) %in% names(dim(data))]
if (!all(common_dims == dim(data)[names(common_dims)])) {
stop("Parameter 'data' and 'threshold' must have same length of ",
"all common dimensions.")
}
}
} else if (length(threshold) == 1) {
dim(threshold) <- NULL
}
}
# ncores
if (!is.null(ncores)) {
if (!is.numeric(ncores) | ncores %% 1 != 0 | ncores <= 0 |
length(ncores) > 1) {
stop("Parameter 'ncores' must be a positive integer.")
}
}
# dates
if (!is.null(dates)) {
if (!is.null(start) && !is.null(end)) {
if (!any(c(is.list(start), is.list(end)))) {
stop("Parameter 'start' and 'end' must be lists indicating the ",
"day and the month of the period start and end.")
}
if (length(op) == 1) {
if (time_dim %in% names(dim(threshold))) {
if (dim(threshold)[time_dim] == dim(data)[time_dim]) {
threshold <- SelectPeriodOnData(data = threshold, dates = dates,
start = start, end = end,
time_dim = time_dim,
ncores = ncores)
}
}
} else if (length(op) == 2) {
if (time_dim %in% names(dim(threshold[[1]]))) {
if (dim(threshold[[1]])[time_dim] == dim(data)[time_dim]) {
threshold[[1]] <- SelectPeriodOnData(data = threshold[[1]],
dates = dates, start = start,
end = end, time_dim = time_dim,
ncores = ncores)
threshold[[2]] <- SelectPeriodOnData(data = threshold[[2]], dates = dates,
start = start, end = end,
time_dim = time_dim,
ncores = ncores)
}
}
}
if (!is.null(dim(dates))) {
data <- SelectPeriodOnData(data = data, dates = dates, start = start,
end = end, time_dim = time_dim,
ncores = ncores)
} else {
warning("Parameter 'dates' must have named dimensions if 'start' and ",
"'end' are not NULL. All data will be used.")
}
}
}
# diff
if (length(op) == 2 & diff == TRUE) {
stop("Parameter 'diff' can't be TRUE if the parameter 'threshold' is a ",
"range of values.")
} else if (diff == TRUE) {
if (length(threshold) != 1) {
stop("Parameter 'diff' can't be TRUE if the parameter 'threshold' is not a scalar.")
}
data <- Apply(list(data, threshold),
target_dims = list(time_dim, NULL),
fun = function(x, y) {x - y}, ncores = ncores)$output1
dim(data) <- dim(data)[-length(dim(data))]
threshold <- 0
}
if (length(op) > 1) {
thres1 <- threshold[[1]]
thres2 <- threshold[[2]]
if (is.null(dim(thres1))) {
total <- Apply(list(data), target_dims = time_dim,
fun = .sumexceedthreshold,
y = thres1, y2 = thres2,
op = op, na.rm = na.rm,
ncores = ncores)$output1
} else if (any(time_dim %in% names(dim(thres1)))) {
total <- Apply(list(data, thres1, thres2),
target_dims = list(time_dim,
time_dim[time_dim %in% names(dim(thres1))],
time_dim[time_dim %in% names(dim(thres2))]),
fun = .sumexceedthreshold, op = op, na.rm = na.rm,
ncores = ncores)$output1
} else {
total <- Apply(list(data, thres1, thres2),
target_dims = list(time_dim, thres1 = NULL, thres2 = NULL),
fun = .sumexceedthreshold, op = op, na.rm = na.rm,
ncores = ncores)$output1
}
} else {
if (is.null(dim(threshold))) {
total <- Apply(list(data), target_dims = time_dim,
fun = .sumexceedthreshold,
y = threshold,
op = op, na.rm = na.rm,
ncores = ncores)$output1
} else if (any(time_dim %in% names(dim(threshold)))) {
total <- Apply(list(data, threshold),
target_dims = list(time_dim,
time_dim[time_dim %in% names(dim(threshold))]),
fun = .sumexceedthreshold, op = op, na.rm = na.rm,
ncores = ncores)$output1
} else {
total <- Apply(list(data, threshold),
target_dims = list(time_dim, NULL),
fun = .sumexceedthreshold, op = op, na.rm = na.rm,
ncores = ncores)$output1
}
}
return(total)
}
.sumexceedthreshold <- function(x, y, y2 = NULL, op, na.rm) {
y <- as.vector(y)
y2 <- as.vector(y2)
if (is.null(y2)) {
if (op == '>') {
res <- sum(x[x > y], na.rm = na.rm)
} else if (op == '<') {
res <- sum(x[x < y], na.rm = na.rm)
} else if (op == '<=') {
res <- sum(x[x <= y], na.rm = na.rm)
} else if (op == '>=') {
res <- sum(x[x >= y], na.rm = na.rm)
} else {
res <- sum(x[x = y], na.rm = na.rm)
}
} else {
if (all(op == c('<', '>'))) {
res <- sum(x[x < y & x > y2], na.rm = na.rm)
} else if (all(op == c('<', '>='))) {
res <- sum(x[x < y & x >= y2], na.rm = na.rm)
} else if (all(op == c('<=', '>'))) {
res <- sum(x[x <= y & x > y2], na.rm = na.rm)
} else if (all(op == c('<=', '>='))) {
res <- sum(x[x <= y & x >= y2], na.rm = na.rm)
} else if (all(op == c('>', '<'))) {
res <- sum(x[x > y & x < y2], na.rm = na.rm)
} else if (all(op == c('>', '<='))) {
res <- sum(x[x > y & x <= y2], na.rm = na.rm)
} else if (all(op == c('>=', '<'))) {
res <- sum(x[x >= y & x < y2], na.rm = na.rm)
} else if (all(op == c('>=', '<='))) {
res <- sum(x[x >= y & x <= y2], na.rm = na.rm)
}
}
return(res)
}
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