revise package structure: always predict from 1am to horizon, dataset not cut at...

[talweg.git] / pkg / R / plot.R

diff --git a/pkg/R/plot.R b/pkg/R/plot.R
index fe2fb4e..59a26a7 100644 (file)
--- a/pkg/R/plot.R
+++ b/pkg/R/plot.R
@@ -82,9 +82,8 @@ plotError <- function(err, cols=seq_along(err))
 #' @export
 plotPredReal <- function(data, pred, index)
 {
-       horizon = length(pred$getForecast(1))
-       measure = data$getSerie( pred$getIndexInData(index)+1 )[1:horizon]
        prediction = pred$getForecast(index)
+       measure = data$getSerie( pred$getIndexInData(index) )[length(prediction)]
        yrange = range(measure, prediction)
        par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
        plot(measure, type="l", ylim=yrange, xlab="Time (hours)", ylab="PM10")
@@ -144,6 +143,7 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 #' @param index Index in forecast (integer or date)
 #' @param limit Number of neighbors to consider
 #' @param plot Should the result be plotted?
+#' @param predict_from First prediction instant
 #'
 #' @return A list with
 #' \itemize{
@@ -153,10 +153,9 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 #' }
 #'
 #' @export
-computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
+computeFilaments <- function(data, pred, index, predict_from, limit=60, plot=TRUE)
 {
-       ref_serie = data$getCenteredSerie( pred$getIndexInData(index) )
-       if (any(is.na(ref_serie)))
+       if (is.null(pred$getParams(index)$weights) || is.na(pred$getParams(index)$weights[1]))
                stop("computeFilaments requires a serie without NAs")
 
        # Compute colors for each neighbor (from darkest to lightest)
@@ -170,7 +169,8 @@ computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
        if (plot)
        {
                # Complete series with (past and present) tomorrows
-               ref_serie = c(ref_serie, data$getCenteredSerie( pred$getIndexInData(index)+1 ))
+               ref_serie = c( data$getCenteredSerie( pred$getIndexInData(index)-1 ),
+                       data$getCenteredSerie( pred$getIndexInData(index) ) )
                centered_series = rbind(
                        data$getCenteredSeries( pred$getParams(index)$indices ),
                        data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
@@ -185,7 +185,7 @@ computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
                }
                # Also plot ref curve, in red
                plot(ref_serie, ylim=yrange, type="l", col="#FF0000", xlab="", ylab="")
-               abline(v=24, lty=2, col=colors()[56], lwd=1)
+               abline(v=24+predict_from-0.5, lty=2, col=colors()[56], lwd=1)
        }
 
        list(
@@ -202,7 +202,7 @@ computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
 #' @param fil Output of \code{computeFilaments}
 #'
 #' @export
-plotFilamentsBox = function(data, fil)
+plotFilamentsBox = function(data, fil, predict_from)
 {
        if (!requireNamespace("rainbow", quietly=TRUE))
                stop("Functional boxplot requires the rainbow package")
@@ -220,7 +220,7 @@ plotFilamentsBox = function(data, fil)
        par(new=TRUE)
        plot(c(data$getSerie(fil$index),data$getSerie(fil$index+1)), type="l", lwd=2, lty=2,
                ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
-       abline(v=24, lty=2, col=colors()[56])
+       abline(v=24+predict_from-0.5, lty=2, col=colors()[56])
 }
 
 #' Plot relative conditional variability / absolute variability
@@ -232,7 +232,7 @@ plotFilamentsBox = function(data, fil)
 #' @inheritParams plotFilamentsBox
 #'
 #' @export
-plotRelVar = function(data, fil)
+plotRelVar = function(data, fil, predict_from)
 {
        ref_var = c( apply(data$getSeries(fil$neighb_indices),1,sd),
                apply(data$getSeries(fil$neighb_indices+1),1,sd) )
@@ -247,5 +247,5 @@ plotRelVar = function(data, fil)
                xlab="Time (hours)", ylab="Standard deviation")
        par(new=TRUE)
        plot(global_var, type="l", col=2, lwd=3, ylim=yrange, xlab="", ylab="")
-       abline(v=24, lty=2, col=colors()[56])
+       abline(v=24+predict_from-0.5, lty=2, col=colors()[56])
 }