a few simplifications in computeFilaments, prepare markdown report

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

diff --git a/pkg/R/plot.R b/pkg/R/plot.R
index 372abf0..eb0c81a 100644 (file)
--- 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