CST_PeriodVariance {CSIndicators} | R Documentation |
Period Variance on 's2dv_cube' objects
Description
Period Variance computes the average (var) of a given variable in a period. Two bioclimatic indicators can be obtained by using this function:
'BIO4', (Providing temperature data) Temperature Seasonality (Standard Deviation). The amount of temperature variation over a given year (or averaged years) based on the standard deviation (variation) of monthly temperature averages.
'BIO15', (Providing precipitation data) Precipitation Seasonality (CV). This is a measure of the variation in monthly precipitation totals over the course of the year. This index is the ratio of the standard deviation of the monthly total precipitation to the mean monthly total precipitation (also known as the coefficient of variation) and is expressed as a percentage.
Usage
CST_PeriodVariance(
data,
start = NULL,
end = NULL,
time_dim = "time",
na.rm = FALSE,
ncores = NULL
)
Arguments
data |
An 's2dv_cube' object as provided function |
start |
An optional parameter to defined 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
|
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 dimension to
compute the indicator. By default, it is set to 'time'. More than one
dimension name matching the dimensions provided in the object
|
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 indicator in the element
data
with dimensions of the input parameter 'data' except the
dimension where the var has been computed (specified with 'time_dim'). 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$data <- array(rnorm(45), dim = c(member = 7, sdate = 4, time = 3))
Dates <- c(seq(as.Date("2000-11-01", "%Y-%m-%d", tz = "UTC"),
as.Date("2001-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
seq(as.Date("2001-11-01", "%Y-%m-%d", tz = "UTC"),
as.Date("2002-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
seq(as.Date("2002-11-01", "%Y-%m-%d", tz = "UTC"),
as.Date("2003-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
seq(as.Date("2003-11-01", "%Y-%m-%d", tz = "UTC"),
as.Date("2004-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"))
dim(Dates) <- c(sdate = 4, time = 3)
exp$attrs$Dates <- Dates
class(exp) <- 's2dv_cube'
res <- CST_PeriodVariance(exp, start = list(01, 12), end = list(01, 01))