#' @param cols Colors for each error (default: 1,2,3,...)
#'
#' @seealso \code{\link{plotCurves}}, \code{\link{plotPredReal}},
#' @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}}
+#' \code{\link{plotSimils}}, \code{\link{plotFbox}}, \code{\link{computeFilaments}},
+#' \code{\link{plotFilamentsBox}}, \code{\link{plotRelVar}}
#' @param index Index in forecasts (integer or date)
#'
#' @export
plotPredReal <- function(data, pred, index)
{
#' @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)
+ prediction = pred$getForecast(index)
+ measure = data$getSerie( pred$getIndexInData(index) )[length(prediction)]
yrange = range(measure, prediction)
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
plot(measure, type="l", ylim=yrange, xlab="Time (hours)", ylab="PM10")
yrange = range(measure, prediction)
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=3)
plot(measure, type="l", ylim=yrange, xlab="Time (hours)", ylab="PM10")
#' @param index Index in forecast (integer or date)
#' @param limit Number of neighbors to consider
#' @param plot Should the result be plotted?
#' @param index Index in forecast (integer or date)
#' @param limit Number of neighbors to consider
#' @param plot Should the result be plotted?
-computeFilaments <- function(data, pred, index, limit=60, plot=TRUE)
+computeFilaments <- function(data, pred, index, predict_from, limit=60, plot=TRUE)
stop("computeFilaments requires a serie without NAs")
# Compute colors for each neighbor (from darkest to lightest)
stop("computeFilaments requires a serie without NAs")
# Compute colors for each neighbor (from darkest to lightest)
- ref_serie = c(ref_serie, data$getCenteredSerie( pred$getIndexInData(index)+1 ))
+ ref_serie = c( data$getCenteredSerie( pred$getIndexInData(index)-1 ),
+ data$getCenteredSerie( pred$getIndexInData(index) ) )
centered_series = rbind(
data$getCenteredSeries( pred$getParams(index)$indices ),
data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
centered_series = rbind(
data$getCenteredSeries( pred$getParams(index)$indices ),
data$getCenteredSeries( pred$getParams(index)$indices+1 ) )
- yrange = range( ref_serie, quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
+ yrange = range( ref_serie,
+ quantile(centered_series, probs=c(0.025,0.975), na.rm=TRUE) )
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
for (i in nn:1)
{
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
for (i in nn:1)
{
}
# Also plot ref curve, in red
plot(ref_serie, ylim=yrange, type="l", col="#FF0000", xlab="", ylab="")
}
# Also plot ref curve, in red
plot(ref_serie, ylim=yrange, type="l", col="#FF0000", xlab="", ylab="")
- abline(v=24, lty=2, col=colors()[56], lwd=1)
+ abline(v=24+predict_from-0.5, lty=2, col=colors()[56], lwd=1)
{
if (!requireNamespace("rainbow", quietly=TRUE))
stop("Functional boxplot requires the rainbow package")
{
if (!requireNamespace("rainbow", quietly=TRUE))
stop("Functional boxplot requires the rainbow package")
rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Time (hours)", ylab="PM10",
plotlegend=FALSE, lwd=2)
rainbow::fboxplot(series_fds, "functional", "hdr", xlab="Time (hours)", ylab="PM10",
plotlegend=FALSE, lwd=2)
usr <- par("usr")
yr <- (usr[4] - usr[3]) / 27
par(new=TRUE)
plot(c(data$getSerie(fil$index),data$getSerie(fil$index+1)), type="l", lwd=2, lty=2,
ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
usr <- par("usr")
yr <- (usr[4] - usr[3]) / 27
par(new=TRUE)
plot(c(data$getSerie(fil$index),data$getSerie(fil$index+1)), type="l", lwd=2, lty=2,
ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
}
#' Plot relative conditional variability / absolute variability
#'
#' Draw the relative conditional variability / absolute variability based on filaments
}
#' Plot relative conditional variability / absolute variability
#'
#' Draw the relative conditional variability / absolute variability based on filaments
{
ref_var = c( apply(data$getSeries(fil$neighb_indices),1,sd),
apply(data$getSeries(fil$neighb_indices+1),1,sd) )
{
ref_var = c( apply(data$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) )
+ 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)
yrange = range(ref_var, global_var)
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
xlab="Time (hours)", ylab="Standard deviation")
par(new=TRUE)
plot(global_var, type="l", col=2, lwd=3, ylim=yrange, xlab="", ylab="")
xlab="Time (hours)", ylab="Standard deviation")
par(new=TRUE)
plot(global_var, type="l", col=2, lwd=3, ylim=yrange, xlab="", ylab="")