1 #' @include z_plotHelper.R
3 #' @title Plot forecasts/observations
5 #' @description Plot the measures at one station versus all experts forecasts.
7 #' @param r Output of \code{\link{runAlgorithm}}.
8 #' @param station Name or index of the station to consider. Default: the first one
9 #' @param interval Time interval for the plot. Default: all time range.
10 #' @param experts Subset of experts for the plot. Default: all experts.
11 #' @param ... Additional arguments to be passed to graphics::plot method.
14 plotCurves = function(r, station=1, interval=1:(nrow(r$data)/length(r$stations)), experts=r$experts, cols=rainbow(length(experts)), ...)
16 if (is.character(station))
17 station = match(station, r$stations)
18 if (is.numeric(experts))
19 experts = r$experts[experts]
21 XY = subset(r$data[interval,], subset = (Station == station), select = c(experts,"Measure"))
22 indices = getNoNAindices(XY)
24 X = as.matrix(XY[,names(XY) %in% experts])
28 par(mar=c(5,4.5,1,1), cex=1.5)
29 for (i in 1:length(experts))
31 plot(X[,i],ylim=yRange,type="l",lty="dotted",col=cols[i],xlab="",ylab="",xaxt="n",yaxt="n", lwd=2, ...)
34 plot(Y, type="l", ylim=yRange, xlab="", ylab="", lwd=2, cex.axis=1.5, ...)
35 title(xlab="Time",ylab="Forecasts / Measures", cex.lab=1.6)
36 legend("topright", title="Historical PM10",lwd=c(2,1),lty=c("solid","dotted"),horiz=TRUE,legend=c("Measures","Forecasts"))
41 #' @description Plot the absolute error over time at one station.
43 #' @param r Output of \code{\link{runAlgorithm}}.
44 #' @param station Name or index of the station to consider. Default: the first one
45 #' @param start First index to consider (too much variability in early errors)
46 #' @param noNA TRUE to show only errors associated with full lines (old behavior)
47 #' @param ... Additional arguments to be passed to graphics::plot method.
50 plotError = function(r, station=1, start=1, noNA=TRUE, ...)
52 if (is.character(station))
53 station = match(station, r$stations)
55 XY = subset(r$data, subset = (Station == station), select = c(r$experts,"Measure","Prediction"))
57 hatY = XY[,"Prediction"]
58 indices = !is.na(Y) & !is.na(hatY)
61 X = XY[,names(XY) %in% r$experts]
62 indices = indices & getNoNAindices(X)
68 par(mar=c(5,4.5,1,1), cex=1.5)
69 plot(error, type="l", xaxt="n", xlab="Time",ylab="L1 error", cex.lab=1.6, cex.axis=1.5, ...)
70 axis(side=1, at=(seq(from=start,to=length(Y),by=30) - start), labels=seq(from=start,to=length(Y),by=30), cex.axis=1.5)
75 #' @description Plot the regret over time at one station.
77 #' @param r Output of \code{\link{runAlgorithm}}.
78 #' @param vs Linear weights to compare with. Can be obtained by the \code{getBestXXX} methods, or by any other mean.
79 #' @param station Name or index of the station to consider. Default: the first one
80 #' @param start First index to consider (too much variability in early errors)
81 #' @param ... Additional arguments to be passed to graphics::plot method.
84 plotRegret = function(r, vs, station=1, start=1, ...)
86 if (is.character(station))
87 station = match(station, r$stations)
89 XY = subset(r$data, subset = (Station == station), select = c(r$experts,"Measure","Prediction"))
90 X = XY[,names(XY) %in% r$experts]
92 hatY = XY[,"Prediction"]
94 indices = !is.na(Y) & !is.na(hatY) & getNoNAindices(X)
95 X = as.matrix(X[indices,])
99 error2 = abs(Y - hatY)^2
100 vsError2 = abs(Y - X %*% vs)^2
101 cumErr2 = cumsum(error2) / seq_along(error2)
102 cumVsErr2 = cumsum(vsError2) / seq_along(vsError2)
103 regret = cumErr2 - cumVsErr2
105 par(mar=c(5,4.5,1,1), cex=1.5)
106 plot(regret, type="l", xaxt="n", xlab="Time", ylab="Regret", cex.lab=1.6, cex.axis=1.5, ...)
107 abline(a=0., b=0., col=2)
108 axis(side=1, at=(seq(from=start,to=length(Y),by=30) - start), labels=seq(from=start,to=length(Y),by=30), cex.axis=1.5)
111 #' @title Plot predicted/expected cloud
113 #' @description Plot the cloud of forecasts/observations + statistical indicators.
115 #' @param r Output of \code{\link{runAlgorithm}}.
116 #' @param thresh Threshold to consider for alerts (usually 30 or 50)
117 #' @param hintThresh thresholds to draw on the plot to help visualization. Often \code{c(30,50,80)}
118 #' @param station Name or index of the station to consider. Default: the first one
119 #' @param noNA TRUE to show only errors associated with full lines (old behavior)
120 #' @param ... Additional arguments to be passed to graphics::plot method.
123 plotCloud = function(r, thresh=30, hintThresh=c(30,50,80), station=1, noNA=TRUE, ...)
125 if (is.character(station))
126 station = match(station, r$stations)
128 XY = subset(r$data, subset = (Station == station), select = c(r$experts,"Measure","Prediction"))
130 hatY = XY[,"Prediction"]
131 indices = !is.na(Y) & !is.na(hatY)
134 X = XY[,names(XY) %in% r$experts]
135 indices = indices & getNoNAindices(X)
140 indics = getIndicators(r, thresh, station, noNA)
142 par(mar=c(5,5,3,2), cex=1.5)
143 plot(Y, hatY, xlab="Measured PM10", ylab="Predicted PM10",
144 cex.lab=1.6, cex.axis=1.5, xlim=c(0,120), ylim=c(0,120), ...)
145 abline(0,1,h=hintThresh,v=hintThresh,col=2,lwd=2)
146 # legend("topleft",legend=c(paste("EV ",indics$EV),paste("RMSE ",indics$RMSE)),cex=1.2)
147 legend("topleft",legend=paste("RMSE ",indics$RMSE))
148 legend("bottomright",legend=c(paste("TS ",indics$TS)))