X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2Fplot.R;h=eb0c81afe7c49a2772c35404ef7108e87dadde91;hp=372abf0a99e086cceb9fec1dc5f9da9c5907da90;hb=8f84543c2d469933d0fc122543d3eeb824970011;hpb=360a5d41bee019d4c0e39f0f9b26be4f35b243ad

diff --git a/pkg/R/plot.R b/pkg/R/plot.R
index 372abf0..eb0c81a 100644
--- a/pkg/R/plot.R
+++ b/pkg/R/plot.R
@@ -142,7 +142,8 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 #' Get similar days in the past, as black as distances are small
 #'
 #' @param data Object as returned by \code{getData}
-#' @param index Index in data (integer or date)
+#' @param pred Object of class Forecast
+#' @param index Index in forecast (integer or date)
 #' @param limit Number of neighbors to consider
 #' @param plot Should the result be plotted?
 #'
@@ -154,40 +155,33 @@ plotFbox <- function(data, indices=seq_len(data$getSize()))
 #' }
 #'
 #' @export
-computeFilaments <- function(data, index, limit=60, plot=TRUE)
+computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
 {
-	ref_serie = data$getCenteredSerie(index)
+	ref_serie = data$getCenteredSerie( pred$getIndexInData(index) )
 	if (any(is.na(ref_serie)))
 		stop("computeFilaments requires a serie without NAs")
 
-	# Determine indices of no-NAs days followed by no-NAs tomorrows
-	fdays = getNoNA2(data, 1, dateIndexToInteger(index,data)-1)
-	# Series + tomorrows in columns, ref_serie first
-	centered_series = data$getCenteredSeries(fdays)
-
-	# Obtain neighbors (closest for euclidian norm)
-	L = length(ref_serie)
-	distances = sqrt( colSums( (centered_series - ref_serie)^2 / L ) )
-	sorted_distances = sort(distances, index.return=TRUE)
-
 	# Compute colors for each neighbor (from darkest to lightest)
-	nn = min(limit, length(distances))
-	min_dist = min(sorted_distances$x[1:nn])
-	max_dist = max(sorted_distances$x[1:nn])
-	color_values = floor( 19.5 * (sorted_distances$x[1:nn]-min_dist) / (max_dist-min_dist) ) + 1
+	sorted_dists = sort(-log(pred$getParams(index)$weights), index.return=TRUE)
+	nn = min(limit, length(sorted_dists$x))
+	min_dist = min(sorted_dists$x[1:nn])
+	max_dist = max(sorted_dists$x[1:nn])
+	color_values = floor(19.5*(sorted_dists$x[1:nn]-min_dist)/(max_dist-min_dist)) + 1
 	colors = gray.colors(20,0.1,0.9)[color_values] #TODO: 20 == magic number
 
 	if (plot)
 	{
 		# Complete series with (past and present) tomorrows
-		ref_serie = c(ref_serie,data$getCenteredSerie(index+1))
-		centered_series = rbind( centered_series, data$getCenteredSeries(fdays+1) )
-		yrange = quantile(cbind(ref_serie,centered_series), probs=c(0.025,0.975), na.rm=TRUE)
+		ref_serie = c(ref_serie, data$getCenteredSerie( pred$getIndexInData(index)+1 ))
+		centered_series = rbind(
+			data$getCenteredSeries( pred$getParams(index)$indices ),
+			data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
+		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)
 		for (i in nn:1)
 		{
-			plot(centered_series[,sorted_distances$ix[i]], ylim=yrange, type="l", col=colors[i],
-				xlab=ifelse(i==nn,"Temps (en heures)",""), ylab=ifelse(i==nn,"PM10 centré",""))
+			plot(centered_series[,sorted_dists$ix[i]], ylim=yrange, type="l", col=colors[i],
+				xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
 			par(new=TRUE)
 		}
 		# Also plot ref curve, in red
@@ -195,7 +189,10 @@ computeFilaments <- function(data, index, limit=60, plot=TRUE)
 		abline(v=24, lty=2, col=colors()[56], lwd=1)
 	}
 
-	list("index"=index,"neighb_indices"=fdays[sorted_distances$ix[1:nn]],"colors"=colors)
+	list(
+		"index"=pred$getIndexInData(index),
+		"neighb_indices"=pred$getParams(index)$indices[sorted_dists$ix[1:nn]],
+		"colors"=colors)
 }
 
 #' Functional boxplot on filaments