+++ /dev/null
-#' Plot curves
-#'
-#' Plot a range of curves in data
-#'
-#' @param data Object of class Data
-#' @param indices Range of indices (integers or dates)
-#'
-#' @export
-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,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
- if (i < length(indices))
- par(new=TRUE)
- }
-}
-
-#' Plot error
-#'
-#' Draw error graphs, potentially from several runs of \code{computeForecast}
-#'
-#' @param err Error as returned by \code{computeError}
-#' @param cols Colors for each error (default: 1,2,3,...)
-#'
-#' @seealso \code{\link{plotCurves}}, \code{\link{plotPredReal}},
-#' \code{\link{plotSimils}}, \code{\link{plotFbox}},
-#' \code{\link{computeFilaments}, }\code{\link{plotFilamentsBox}}, \code{\link{plotRelVar}}
-#'
-#' @export
-plotError <- function(err, cols=seq_along(err))
-{
- if (!is.null(err$abs))
- err = list(err)
- par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
- L = length(err)
- yrange = range( sapply(1:L, function(i) ( err[[i]]$abs$day ) ), na.rm=TRUE )
- for (i in seq_len(L))
- {
- plot(err[[i]]$abs$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
- ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
- if (i < L)
- par(new=TRUE)
- }
- yrange = range( sapply(1:L, function(i) ( err[[i]]$abs$indices ) ), na.rm=TRUE )
- for (i in seq_len(L))
- {
- plot(err[[i]]$abs$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
- ylab=ifelse(i==1,"Moyenne |y - y_hat|",""), ylim=yrange, col=cols[i])
- if (i < L)
- par(new=TRUE)
- }
- yrange = range( sapply(1:L, function(i) ( err[[i]]$MAPE$day ) ), na.rm=TRUE )
- for (i in seq_len(L))
- {
- plot(err[[i]]$MAPE$day, type="l", xlab=ifelse(i==1,"Temps (heures)",""),
- ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
- if (i < L)
- par(new=TRUE)
- }
- yrange = range( sapply(1:L, function(i) ( err[[i]]$MAPE$indices ) ), na.rm=TRUE )
- for (i in seq_len(L))
- {
- plot(err[[i]]$MAPE$indices, type="l", xlab=ifelse(i==1,"Temps (jours)",""),
- ylab=ifelse(i==1,"MAPE moyen",""), ylim=yrange, col=cols[i])
- if (i < L)
- par(new=TRUE)
- }
-}
-
-#' Plot measured / predicted
-#'
-#' Plot measured curve (in black) and predicted curve (in blue)
-#'
-#' @param data Object return by \code{getData}
-#' @param pred Object as returned by \code{computeForecast}
-#' @param index Index in forecasts (integer or date)
-#'
-#' @export
-plotPredReal <- function(data, pred, index)
-{
- horizon = length(pred$getSerie(1))
- measure = data$getSerie( pred$getIndexInData(index)+1 )[1:horizon]
- prediction = pred$getSerie(index)
- yrange = range(measure, prediction)
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
- plot(measure, type="l", ylim=yrange, xlab="Temps (en heures)", ylab="PM10")
- par(new=TRUE)
- plot(prediction, type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
-}
-
-#' Plot similarities
-#'
-#' Plot histogram of similarities (weights)
-#'
-#' @param pred Object as returned by \code{computeForecast}
-#' @param index Index in forecasts (integer or date)
-#'
-#' @export
-plotSimils <- function(pred, index)
-{
- weights = pred$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)$weights, nclass=20, xlab="Poids", ylab="Effectif")
-}
-
-#' Functional boxplot
-#'
-#' Draw the functional boxplot on the left, and bivariate plot on the right
-#'
-#' @param data Object return by \code{getData}
-#' @param indices integer or date indices to process
-#' @param plot_bivariate Should the bivariate plot appear?
-#'
-#' @export
-plotFbox <- function(data, indices=seq_len(data$getSize()))
-{
- if (!requireNamespace("rainbow", quietly=TRUE))
- stop("Functional boxplot requires the rainbow package")
-
- series_matrix = data$getSeries(indices)
- # Remove series with NAs
- no_NAs_indices = sapply( 1:ncol(series_matrix),
- function(i) all(!is.na(series_matrix[,i])) )
- series_matrix = series_matrix[,no_NAs_indices]
-
- series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
- rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Temps (heures)", ylab="PM10",
- plotlegend=FALSE, lwd=2)
- rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
-}
-
-#' Compute filaments
-#'
-#' Get similar days in the past, as black as distances are small
-#'
-#' @param data Object as returned by \code{getData}
-#' @param pred Object of class Forecast
-#' @param index Index in forecast (integer or date)
-#' @param limit Number of neighbors to consider
-#' @param plot Should the result be plotted?
-#'
-#' @return A list with
-#' \itemize{
-#' \item index : index of the current serie ('today')
-#' \item neighb_indices : indices of its neighbors
-#' \item colors : colors of neighbors curves (shades of gray)
-#' }
-#'
-#' @export
-computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
-{
- ref_serie = data$getCenteredSerie( pred$getIndexInData(index) )
- if (any(is.na(ref_serie)))
- stop("computeFilaments requires a serie without NAs")
-
- # Compute colors for each neighbor (from darkest to lightest)
- sorted_dists = sort(-log(pred$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( pred$getIndexInData(index)+1 ))
- centered_series = rbind(
- data$getCenteredSeries( pred$getParams(index)$indices ),
- data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
- yrange = range( ref_serie, quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
- for (i in nn:1)
- {
- plot(centered_series[,sorted_dists$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
- plot(ref_serie, ylim=yrange, type="l", col="#FF0000", xlab="", ylab="")
- abline(v=24, lty=2, col=colors()[56], lwd=1)
- }
-
- list(
- "index"=pred$getIndexInData(index),
- "neighb_indices"=pred$getParams(index)$indices[sorted_dists$ix[1:nn]],
- "colors"=colors)
-}
-
-#' Functional boxplot on filaments
-#'
-#' Draw the functional boxplot on filaments obtained by \code{computeFilaments}
-#'
-#' @param data Object return by \code{getData}
-#' @param fil Output of \code{computeFilaments}
-#'
-#' @export
-plotFilamentsBox = function(data, fil, ...)
-{
- 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) )
- 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="Temps (heures)", ylab="PM10",
- plotlegend=FALSE, lwd=2)
-
- # "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
- usr <- par("usr")
- yr <- (usr[4] - usr[3]) / 27
- 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])
-}
-
-#' Plot relative conditional variability / absolute variability
-#'
-#' Draw the relative conditional variability / absolute variability based on filaments
-#' obtained by \code{computeFilaments}
-#'
-#' @param data Object return by \code{getData}
-#' @param fil Output of \code{computeFilaments}
-#'
-#' @export
-plotRelVar = function(data, fil, ...)
-{
- 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$index-1)
- global_var = c( apply(data$getSeries(fdays),1,sd), apply(data$getSeries(fdays+1),1,sd) )
-
- yrange = range(ref_var, global_var)
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
- plot(ref_var, type="l", col=1, lwd=3, ylim=yrange,
- xlab="Temps (heures)", ylab="Écart-type")
- par(new=TRUE)
- plot(global_var, type="l", col=2, lwd=3, ylim=yrange, xlab="", ylab="")
- abline(v=24, lty=2, col=colors()[56])
-}
projects / talweg.git / blobdiff