#' #do_something_with_pred
#' }}
#' @export
-computeForecast = function(data, indices, forecaster, pjump,
- memory=Inf, horizon=data$getStdHorizon(), ncores=3, ...)
+computeForecast = function(data, indices, forecaster, pjump, predict_from,
+ memory=Inf, horizon=length(data$getSerie(1)), ncores=3, ...)
{
# (basic) Arguments sanity checks
+ predict_from = as.integer(predict_from)[1]
+ if (! predict_from %in% 1:length(data$getSerie(1)))
+ stop("predict_from in [1,24] (hours)")
horizon = as.integer(horizon)[1]
- if (horizon<=0 || horizon>length(data$getCenteredSerie(1)))
- stop("Horizon too short or too long")
+ if (horizon<=predict_from || horizon>length(data$getSerie(1)))
+ stop("Horizon in [predict_from+1,24] (hours)")
integer_indices = sapply(indices, function(i) dateIndexToInteger(i,data))
if (any(integer_indices<=0 | integer_indices>data$getSize()))
stop("Indices out of range")
p <- parallel::mclapply(seq_along(integer_indices), function(i) {
list(
"forecast" = forecaster$predictSerie(
- data, integer_indices[i], memory, horizon, ...),
+ data, integer_indices[i], memory, predict_from, horizon, ...),
"params"= forecaster$getParameters(),
"index" = integer_indices[i] )
}, mc.cores=ncores)
p <- lapply(seq_along(integer_indices), function(i) {
list(
"forecast" = forecaster$predictSerie(
- data, integer_indices[i], memory, horizon, ...),
+ data, integer_indices[i], memory, predict_from, horizon, ...),
"params"= forecaster$getParameters(),
"index" = integer_indices[i] )
})