X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FcomputeForecast.R;h=ef46dd3b7f516c23ef91430a923652224c924e1f;hb=638f27f4296727aff62b56643beb9f42aa5b57ef;hp=a4a539aaf83a8e48411a5a81a268898bd36e351e;hpb=3ddf1c12af0c167fe7d3bb59e63258550270cfc5;p=talweg.git diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R index a4a539a..ef46dd3 100644 --- a/pkg/R/computeForecast.R +++ b/pkg/R/computeForecast.R @@ -49,13 +49,18 @@ #' #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$getSerie(1))) + stop("predict_from in [1,24] (hours)") + if (hasArg("opera") && !list(...)$opera && memory < Inf) + memory <- Inf #finite memory in training mode makes no sense 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$getSize())) stop("Indices out of range") @@ -68,27 +73,20 @@ computeForecast = function(data, indices, forecaster, pjump, forecaster = forecaster_class_name$new( #.pjump = getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")) - if (ncores > 1 && requireNamespace("parallel",quietly=TRUE)) + computeOneForecast <- function(i) { - p <- parallel::mclapply(seq_along(integer_indices), function(i) { - list( - "forecast" = forecaster$predictSerie( - data, integer_indices[i], memory, horizon, ...), - "params"= forecaster$getParameters(), - "index" = integer_indices[i] ) - }, mc.cores=ncores) - } - else - { - p <- lapply(seq_along(integer_indices), function(i) { - list( - "forecast" = forecaster$predictSerie( - data, integer_indices[i], memory, horizon, ...), - "params"= forecaster$getParameters(), - "index" = integer_indices[i] ) - }) + list( + "forecast" = forecaster$predictSerie(data,i,memory,predict_from,horizon,...), + "params" = forecaster$getParameters(), + "index" = i ) } + p <- + if (ncores > 1 && requireNamespace("parallel",quietly=TRUE)) + parallel::mclapply(integer_indices, computeOneForecast, mc.cores=ncores) + else + lapply(integer_indices, computeOneForecast) + # TODO: find a way to fill pred in //... for (i in seq_along(integer_indices)) {