- distances = sapply(fdays_indices, function(i) {
- sqrt( sum( (ref_serie - data$getCenteredSerie(i))^2 ) / L )
- })
- indices = sort(distances, index.return=TRUE)$ix[1:min(limit,length(distances))]
- yrange = quantile( c(ref_serie, sapply( indices, function(i) {
- ii = fdays_indices[i]
- serie = c(data$getCenteredSerie(ii), data$getCenteredSerie(ii+1))
- if (!all(is.na(serie)))
- return (range(serie, na.rm=TRUE))
- c()
- }) ), probs=c(0.05,0.95) )
- grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
- min_dist = min(distances[indices])
- max_dist = max(distances[indices])
- color_values = floor( 19.5 * (distances[indices]-min_dist) / (max_dist-min_dist) ) + 1
- plot_order = sort(color_values, index.return=TRUE, decreasing=TRUE)$ix
- colors = c(grays[ color_values[plot_order] ], "#FF0000")
- if (plot)
- {
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
- for ( i in seq_len(length(indices)+1) )
- {
- ii = ifelse(i<=length(indices), fdays_indices[ indices[plot_order[i]] ], index)
- plot(c(data$getCenteredSerie(ii),data$getCenteredSerie(ii+1)),
- ylim=yrange, type="l", col=colors[i],
- xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
- if (i <= length(indices))
- par(new=TRUE)
- }
- abline(v=24, lty=2, col=colors()[56])
- }
- list("indices"=c(fdays_indices[ indices[plot_order] ],index), "colors"=colors)
+ 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")
+ par(new=TRUE)
+ plot(prediction, type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")