#' @export
plotCurves <- function(data, indices)
{
- yrange = range( sapply( indices, function(i) {
+ yrange = quantile( range( sapply( indices, function(i) {
serie = c(data$getCenteredSerie(i))
if (!all(is.na(serie)))
range(serie, na.rm=TRUE)
c()
- }) )
+ }) ), probs=c(0.05,0.95) )
par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
for (i in seq_along(indices))
{
plot(pred$getSerie(index), type="l", col="#0000FF", ylim=yrange, xlab="", ylab="")
}
-#' @title Plot filaments
+#' @title Compute filaments
#'
-#' @description Plot similar days in the past + "past tomorrow", as black as distances are small
+#' @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
-plotFilaments <- function(data, index, limit=60)
+computeFilaments <- function(data, index, limit=60, plot=TRUE)
{
index = dateIndexToInteger(index, data)
ref_serie = data$getCenteredSerie(index)
if (any(is.na(ref_serie)))
- stop("plotFilaments requires a serie without NAs")
+ stop("computeFilaments requires a serie without NAs")
L = length(ref_serie)
first_day = ifelse(length(data$getCenteredSerie(1)<L), 2, 1)
distances = sapply(first_day:(index-1), function(i) {
# HACK to suppress NA effect while keeping indexation
distances[is.na(distances)] = max(distances,na.rm=TRUE) + 1
indices = sort(distances, index.return=TRUE)$ix[1:min(limit,index-first_day)]
- yrange = range( ref_serie, sapply( indices, function(i) {
+ yrange = quantile( range( ref_serie, sapply( indices, function(i) {
index = i - first_day + 1
serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
if (!all(is.na(serie)))
return (range(serie, na.rm=TRUE))
c()
- }) )
+ }) ), probs=c(0.1,0.9) )
grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number
- colors = c(
- grays[ floor( 20.5 * distances[indices] / (1+max(distances[indices])) ) ], "#FF0000")
- par(mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lwd=2)
- for (i in seq_len(length(indices)+1))
+ color_values = floor( 20.5 * distances[indices] / (1+max(distances[indices])) )
+ plot_order = sort(color_values, index.return=TRUE)$ix
+ colors = c(grays[ color_values[plot_order] ], "#FF0000")
+ if (plot)
{
- 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)
+ 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
#'
#' @param data Object return by \code{getData}
#' @param fiter Optional filter: return TRUE on indices to process
+#' @param plot_bivariate Should the bivariate plot appear?
#'
#' @export
-plotFbox <- function(data, filter=function(index) TRUE)
+plotFbox <- function(data, filter=function(index) TRUE, plot_bivariate=TRUE)
{
if (!requireNamespace("rainbow", quietly=TRUE))
stop("Functional boxplot requires the rainbow package")
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)
+ if (plot_bivariate)
+ par(mfrow=c(1,2))
+ 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)
+ if (plot_bivariate)
+ rainbow::fboxplot(series_fds, "bivariate", "hdr", plotlegend=FALSE)
+}
+
+#' @title Functional boxplot on filaments
+#'
+#' @description Draw the functional boxplot on filaments obtained by \code{computeFilaments}
+#'
+#' @param data Object return by \code{getData}
+#' @param indices Indices as output by \code{computeFilaments}
+#'
+#' @export
+plotFilamentsBox = function(data, indices, ...)
+{
+ past_neighbs_indices = head(indices,-1)
+ plotFbox(data, function(i) i %in% past_neighbs_indices, plot_bivariate=FALSE)
+ par(new=TRUE)
+ # "Magic" found at http://stackoverflow.com/questions/13842560/get-xlim-from-a-plot-in-r
+ usr <- par("usr")
+ yr <- (usr[4] - usr[3]) / 27
+ plot(data$getSerie(tail(indices,1)), type="l", lwd=2, lty=2,
+ ylim=c(usr[3] + yr, usr[4] - yr), xlab="", ylab="")
}
projects / talweg.git / blobdiff