X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2Fplot.R;h=2488d81548202fa9af8e8e3e2a1f23f006914694;hb=4f3fdbb8e2ac4bd57a4e27539a58ef0e7ec2304c;hp=48b456cd1bebfff91a227a79c3ff0797af5f1199;hpb=102bcfda4afbb5cfee885cbee0f55545624168fd;p=talweg.git

diff --git a/pkg/R/plot.R b/pkg/R/plot.R
index 48b456c..2488d81 100644
--- a/pkg/R/plot.R
+++ b/pkg/R/plot.R
@@ -11,13 +11,7 @@ plotCurves <- function(data, indices=seq_len(data$getSize()))
 	series = data$getSeries(indices)
 	yrange = quantile(series, probs=c(0.025,0.975), na.rm=TRUE)
 	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
-	for (i in seq_along(indices))
-	{
-		plot(series[,i], type="l", ylim=yrange,
-			xlab=ifelse(i==1,"Time (hours)",""), ylab=ifelse(i==1,"PM10",""))
-		if (i < length(indices))
-			par(new=TRUE)
-	}
+	matplot(series, type="l", ylim=yrange, xlab="Time (hours)", ylab="PM10")
 }
 
 #' Plot error
@@ -82,9 +76,8 @@ 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) )[1: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 +137,7 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 #' @param index Index in forecast (integer or date)
 #' @param limit Number of neighbors to consider
 #' @param plot Should the result be plotted?
+#' @param predict_from First prediction instant
 #'
 #' @return A list with
 #' \itemize{
@@ -153,10 +147,9 @@ plotFbox <- function(data, indices=seq_len(data$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)
@@ -170,10 +163,11 @@ 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 ) )
+			data$getCenteredSeries( pred$getParams(index)$indices-1 ),
+			data$getCenteredSeries( pred$getParams(index)$indices ) )
 		yrange = range( ref_serie,
 			quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
 		par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
@@ -185,7 +179,7 @@ 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(
@@ -202,14 +196,15 @@ 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")
 
 	series_matrix = rbind(
-		data$getSeries(fil$neighb_indices), data$getSeries(fil$neighb_indices+1) )
+		data$getSeries(fil$neighb_indices-1), data$getSeries(fil$neighb_indices) )
 	series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
+
 	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
 	rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Time (hours)", ylab="PM10",
 		plotlegend=FALSE, lwd=2)
@@ -220,7 +215,7 @@ 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
@@ -232,14 +227,14 @@ 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) )
-	fdays = getNoNA2(data, 1, fil$index-1)
+	ref_var = c( apply(data$getSeries(fil$neighb_indices-1),1,sd),
+		apply(data$getSeries(fil$neighb_indices),1,sd) )
+	tdays = .getNoNA2(data, 2, fil$index)
 	global_var = c(
-		apply(data$getSeries(fdays),1,sd),
-		apply(data$getSeries(fdays+1),1,sd) )
+		apply(data$getSeries(tdays-1),1,sd),
+		apply(data$getSeries(tdays),1,sd) )
 
 	yrange = range(ref_var, global_var)
 	par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
@@ -247,5 +242,5 @@ 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])
 }