+++ /dev/null
-#' @title plot curves
-#'
-#' @description 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)
-{
- yrange = range( sapply( indices, function(i) {
- serie = c(data$getCenteredSerie(i))
- if (!all(is.na(serie)))
- range(serie, na.rm=TRUE)
- c()
- }) )
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
- for (i in seq_along(indices))
- {
- plot(data$getSerie(indices[i]), type="l", ylim=yrange,
- xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10",""))
- if (ii < length(indices))
- par(new=TRUE)
- }
-}
-
-#' @title plot measured / predicted
-#'
-#' @description Plot measured curve (in black) and predicted curve (in red)
-#'
-#' @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$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
-}
-
-#' @title Plot filaments
-#'
-#' @description Plot similar days in the past + "past tomorrow", as black as distances are small
-#'
-#' @param data Object as returned by \code{getData}
-#' @param index Index in data
-#' @param limit Number of neighbors to consider
-#'
-#' @export
-plotFilaments <- function(data, index, limit=60)
-{
- index = dateIndexToInteger(index, data)
- ref_serie = data$getCenteredSerie(index)
- if (any(is.na(ref_serie)))
- stop("plotFilaments 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)$ix[1:min(limit,index-first_day)]
- yrange = range( ref_serie, sapply( indices, function(i) {
- index = i - first_day + 1
- serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
- if (!all(is.na(serie)))
- return (range(serie, na.rm=TRUE))
- c()
- }) )
- grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
- colors = c(
- grays[ floor( 20.5 * distances[indices] / (1+max(distances[indices])) ) ], "#FF0000")
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
- for (i in seq_len(length(indices)+1))
- {
- ind = ifelse(i<=length(indices), indices[i] - first_day + 1, index)
- plot(c(data$getCenteredSerie(ind),data$getCenteredSerie(ind+1)),
- ylim=yrange, type="l", col=colors[i],
- xlab=ifelse(i==1,"Temps (en heures)",""), ylab=ifelse(i==1,"PM10 centré",""))
- if (i <= length(indices))
- par(new=TRUE)
- }
-}
-
-#' @title Plot similarities
-#'
-#' @description Plot histogram of similarities (weights)
-#'
-#' @param pred Object as returned by \code{getForecast}
-#' @param index Index in forecasts (not in data)
-#'
-#' @export
-plotSimils <- function(pred, index)
-{
- weights = pred$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)$weights, nclass=20, xlab="Poids", ylab="Effectif")
-}
-
-#' @title Plot error
-#'
-#' @description Draw error graphs, potentially from several runs of \code{getForecast}
-#'
-#' @param err Error as returned by \code{getError}
-#' @param cols Colors for each error (default: 1,2,3,...)
-#'
-#' @seealso \code{\link{plotPredReal}}, \code{\link{plotFilaments}}, \code{\link{plotSimils}}
-#' \code{\link{plotFbox}}
-#'
-#' @export
-plotError <- function(err, cols=seq_along(err))
-{
- if (!is.null(err$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(index) ( err[[index]]$abs$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(index) ( err[[index]]$abs$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(index) ( err[[index]]$MAPE$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(index) ( err[[index]]$MAPE$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)
- }
-}
-
-#' @title Functional boxplot
-#'
-#' @description Draw the functional boxplot on the left, and bivariate plot on the right
-#'
-#' @param data Object return by \code{getData}
-#' @param fiter Optional filter: return TRUE on indices to process
-#'
-#' @export
-plotFbox <- function(data, filter=function(index) TRUE)
-{
- if (!requireNamespace("rainbow", quietly=TRUE))
- stop("Functional boxplot requires the rainbow package")
-
- start_index = 1
- end_index = data$getSize()
- if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(2)))
- {
- # Shifted start (7am, or 1pm, or...)
- start_index = 2
- end_index = data$getSize() - 1
- }
-
- series_matrix = sapply(start_index:end_index, function(index) {
- as.matrix(data$getSerie(index))
- })
- # Remove NAs. + filter TODO: merge with previous step: only one pass required...
- nas_indices = seq_len(ncol(series_matrix))[ sapply( 1:ncol(series_matrix),
- function(index) ( !filter(index) || any(is.na(series_matrix[,index])) ) ) ]
- series_matrix = series_matrix[,-nas_indices]
-
- series_fds = rainbow::fds(seq_len(nrow(series_matrix)), series_matrix)
- par(mfrow=c(1,2), 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)
-}
projects / talweg.git / blobdiff