CST_Threshold {CSIndicators} | R Documentation |
Absolute value of a relative threshold (percentile)
Description
Frequently, thresholds are defined by a percentile that may correspond to a different absolute value depending on the variable, gridpoint and also julian day (time). This function calculates the corresponding value of a percentile given a dataset.
Usage
CST_Threshold(
data,
threshold,
start = NULL,
end = NULL,
time_dim = "time",
memb_dim = "member",
sdate_dim = "sdate",
na.rm = FALSE,
ncores = NULL
)
Arguments
data |
An 's2dv_cube' object as provided function |
threshold |
A single scalar or vector indicating the relative threshold(s). It must contain values between 0 and 1. |
start |
An optional parameter to defined the initial date of the period
to selectfrom 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
|
end |
An optional parameter to defined 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 |
time_dim |
A character string indicating the name of the temporal
dimension. By default, it is set to 'time'. More than one dimension name
matching the dimensions provided in the object |
memb_dim |
A character string indicating the name of the dimension in which the ensemble members are stored. When set it to NULL, threshold is computed for individual members. |
sdate_dim |
A character string indicating the name of the dimension in which the initialization dates are stored. |
na.rm |
A logical value indicating whether to ignore NA values (TRUE) or not (FALSE). |
ncores |
An integer indicating the number of cores to use in parallel computation. |
Value
An ’s2dv_cube’ object containing the corresponding values of a
percentile in the element data
.
Examples
threshold <- 0.9
exp <- NULL
exp$data <- array(rnorm(5 * 3 * 214 * 2),
c(member = 5, sdate = 3, time = 214, lon = 2))
exp$attrs$Dates <- c(seq(as.Date("01-05-2000", format = "%d-%m-%Y"),
as.Date("30-11-2000", format = "%d-%m-%Y"), by = 'day'),
seq(as.Date("01-05-2001", format = "%d-%m-%Y"),
as.Date("30-11-2001", format = "%d-%m-%Y"), by = 'day'),
seq(as.Date("01-05-2002", format = "%d-%m-%Y"),
as.Date("30-11-2002", format = "%d-%m-%Y"), by = 'day'))
dim(exp$attrs$Dates) <- c(sdate = 3, time = 214)
class(exp) <- 's2dv_cube'
exp_probs <- CST_Threshold(exp, threshold, start = list(21, 4), end = list(21, 6))