This function changes the timestep of a table or an antaresData
object
and performs the required aggregation or desaggregation. We can specify
(des)aggregate functions by columns, see the param fun
.
Usage
changeTimeStep(x, newTimeStep, oldTimeStep, fun = "sum", opts = simOptions())
Arguments
- x
data.table with a column "timeId" or an object of class "antaresDataList"
- newTimeStep
Desired time step.The possible values are hourly, daily, weekly, monthly and annual.
- oldTimeStep
Current time step of the data. This argument is optional for an object of class
antaresData
because the time step of the data is stored inside the object- fun
Character vector with one element per column to (des)aggregate indicating the function to use ("sum", "mean", "min" or "max") for this column. It can be a single element, in that case the same function is applied to every columns.
- opts
list of simulation parameters returned by the function
setSimulationPath
Examples
if (FALSE) { # \dontrun{
setSimulationPath()
areasH <- readAntares(select = "LOAD", synthesis = FALSE, mcYears = 1)
areasD <- readAntares(select = "LOAD", synthesis = FALSE, mcYears = 1, timeStep ="daily")
areasDAgg <- changeTimeStep(areasH, "daily", "hourly")
all.equal(areasDAgg$LOAD, areasD$LOAD)
# Use different aggregation functions
mydata <- readAntares(select = c("LOAD", "MRG. PRICE"), timeStep = "monthly")
changeTimeStep(mydata, "annual", fun = c("sum", "mean"))
} # }