-#' @param data Object return by \code{getData}
-#' @param pred Object as returned by \code{getForecast}
-#' @param index Index in forecasts
-#'
-#' @export
-plotPredReal <- function(data, pred, index)
-{
- horizon = length(pred$getSerie(1))
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
- measure = data$getSerie(pred$getIndexInData(index)+1)[1:horizon]
- yrange = range( pred$getSerie(index), measure )
- plot(measure, type="l", ylim=yrange, xlab="Temps (en heures)", ylab="PM10")
- par(new=TRUE)
- plot(pred$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
-}
-
-#' @title Compute filaments
-#'
-#' @description Get similar days in the past + "past tomorrow", as black as distances are small
-#'
-#' @param data Object as returned by \code{getData}
-#' @param index Index in data
-#' @param limit Number of neighbors to consider
-#' @param plot Should the result be plotted?
-#'
-#' @export
-computeFilaments <- function(data, index, limit=60, plot=TRUE)
-{
- index = dateIndexToInteger(index, data)
- ref_serie = data$getCenteredSerie(index)
- if (any(is.na(ref_serie)))
- stop("computeFilaments requires a serie without NAs")
- L = length(ref_serie)
- first_day = ifelse(length(data$getCenteredSerie(1)<L), 2, 1)
- distances = sapply(first_day:(index-1), function(i) {
- sqrt( sum( (ref_serie - data$getCenteredSerie(i))^2 ) / L )
- })
- # HACK to suppress NA effect while keeping indexation
- distances[is.na(distances)] = max(distances,na.rm=TRUE) + 1
- indices = sort(distances, index.return=TRUE)$ix[1:min(limit,index-first_day)]
- yrange = quantile( range( ref_serie, sapply( indices, function(i) {
- index = i - first_day + 1
- serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
- if (!all(is.na(serie)))
- return (range(serie, na.rm=TRUE))
- c()
- }) ), probs=c(0.1,0.9) )
- grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
- color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
- plot_order = sort(color_values, index.return=TRUE)$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 c(plot_order,length(indices)+1) )
- {
- ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
- plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+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)
- }
- }
- list("indices"=c(indices[plot_order]-first_day+1,index), "colors"=colors)
-}
-
-#' @title Plot similarities
-#'
-#' @description Plot histogram of similarities (weights)
-#'
-#' @param pred Object as returned by \code{getForecast}
-#' @param index Index in forecasts (not in data)
-#'
-#' @export
-plotSimils <- function(pred, index)
-{
- weights = pred$getParams(index)$weights
- if (is.null(weights))
- stop("plotSimils only works on 'Neighbors' forecasts")
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
- hist(pred$getParams(index)$weights, nclass=20, xlab="Poids", ylab="Effectif")
-}
-
-#' @title Plot error
-#'
-#' @description Draw error graphs, potentially from several runs of \code{getForecast}
-#'
-#' @param err Error as returned by \code{getError}