{
if (!is.null(err$abs))
err = list(err)
- par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5, lty=1)
+ par(mfrow=c(2,2), mar=c(4.7,5,1,1), cex.axis=1.5, cex.lab=1.5)
L = length(err)
yrange = range( sapply(1:L, function(i) ( err[[i]]$abs$day ) ), na.rm=TRUE )
matplot( sapply( seq_len(L), function(i) err[[i]]$abs$day ), type="l",
- xlab="Time (hours)", ylab="Mean |y - y_hat|", ylim=yrange, col=cols, lwd=2 )
+ xlab="Time (hours)", ylab="Mean |y - y_hat|", ylim=yrange, col=cols, lwd=2, lty=1 )
yrange = range( sapply(1:L, function(i) ( err[[i]]$abs$indices ) ), na.rm=TRUE )
matplot( sapply( seq_len(L), function(i) err[[i]]$abs$indices ), type="l",
- xlab="Time (days)", ylab="Mean |y - y_hat|", ylim=yrange, col=cols, lwd=2 )
+ xlab="Time (days)", ylab="Mean |y - y_hat|", ylim=yrange, col=cols, lwd=2, lty=1 )
yrange = range( sapply(1:L, function(i) ( err[[i]]$MAPE$day ) ), na.rm=TRUE )
matplot( sapply( seq_len(L), function(i) err[[i]]$MAPE$day ), type="l",
- xlab="Time (hours)", ylab="Mean MAPE", ylim=yrange, col=cols, lwd=2 )
+ xlab="Time (hours)", ylab="Mean MAPE", ylim=yrange, col=cols, lwd=2, lty=1 )
yrange = range( sapply(1:L, function(i) ( err[[i]]$MAPE$indices ) ), na.rm=TRUE )
matplot( sapply( seq_len(L), function(i) err[[i]]$MAPE$indices ), type="l",
- xlab="Time (days)", ylab="Mean MAPE", ylim=yrange, col=cols, lwd=2 )
+ xlab="Time (days)", ylab="Mean MAPE", ylim=yrange, col=cols, lwd=2, lty=1 )
}
#' Plot measured / predicted
measure = data$getSerie( pred$getIndexInData(index) )[1:length(pred$getForecast(1))]
# Remove the common part, where prediction == measure
- dot_mark <- ifelse(prediction[1]==measure[1], which.max(prediction==measure), 0)
+ dot_mark <- ifelse(prediction[1]==measure[1],
+ which.max(seq_along(prediction)[prediction==measure]), 0)
prediction = prediction[(dot_mark+1):length(prediction)]
measure = measure[(dot_mark+1):length(measure)]