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Hmm, I actually I'm not sure if it makes sense to answer my own question ... But due to the fact that I received no answer, mayby my initial question was a little bit stupid. Nevertheless, in the last day I spent some time to solve my issue. Basically my solution is to add additional segements according to the duration of the event. I spare you my calculations for the duration. This is because my initial interest was in how to provide a gradient to a polygon. Maybe some of you find my solution useful Cheers Tom <pre><code>library(ggplot2) library(reshape) event.day <- c("A", "A", "A", "A", "B", "B") event <- c(1, 2, 3, 4, 5, 6) sys <- c(120, 160, 100, 180, 100, 180) duration <- c(50, 100, 50, 150, 350, 0) df <- data.frame(event.day, event, sys, duration) df$end <- c(df$sys[-1], NA) ## replacing na values df.value.na <- is.na(df$end) df[df.value.na,]$end <- df[df.value.na,]$sys ## calculating the slope df$slope <- df$end / df$sys ## creating rows for each event depending on the duration event.id <- vector() segment.id <- vector() for(i in 1:nrow(df)) { event.id <- c(event.id, rep(df[i,]$event, each = df[i,]$duration)) segment.id <- c(segment.id,c(1:df[i,]$duration)) } ## merging the original dataframe with the additional segments df.segments <- data.frame(event.id, segment.id) df <- merge(df, df.segments, by.x = c("event"), by.y = c("event.id")) ## calculate the start and end values for the newly created segements df$segment.start <- df$sys + (df$segment.id - 1) * (df$end - df$sys) / df$duration df$segment.end <- df$sys + (df$segment.id) * (df$end - df$sys) / df$duration ## just a simple calculation value.max <- max(df$sys) df$high <- 1 + 0.45 * df$segment.end / value.max df$low <- 1 - 0.45 * df$segment.end / value.max df$percent <- df$segment.end / value.max df$id <- seq_along(df$sys) df$idByDay <- ave( 1:nrow(df), df$event.day,FUN=function(x) seq_along(x)) ## how many events in total, necessary newevents <- nrow(df) ## subsetting the original data.frame df <- df[,c("event.day", "id", "idByDay", "segment.id", "segment.start", "duration", "segment.end", "high", "low", "percent")] ## melting the data.frame df.melted <- melt(df, id.vars = c("event.day", "id", "idByDay", "segment.id", "segment.start", "duration", "segment.end","percent")) df.melted <- df.melted[order(df.melted$id,df.melted$segment.id),] ## this is a tricky one, basically this a self join, of two tables # every event is available twice, this is due to melt in the previous section # a dataframe is produced where every event is contained 4 times, except the first and last 2 rows, # the first row marks the start of the first polygon # the last row marks the end of the last polygon df.melted <- rbind(df.melted[1:(nrow(df.melted)-2),],df.melted[3:nrow(df.melted),]) df.melted <- df.melted[order(df.melted$id,df.melted$segment.id),] ## grouping, necessary for drawing the polygons # the 1st polygon spans from the 1st event, and the first 2 rows from 2nd event # the 2nd polygon spans from last 2 rows of the 2nd event and the first 2 rows from 3rd event # ... # the last polygon spans from the last 2 rows of the next to last event and the 2 rows of the last event df.melted$grouping <- rep (1:(newevents-1), each=4) df.melted <- df.melted[order(df.melted$id, df.melted$grouping, df.melted$variable), ] ## adding a 4 point for each group df.melted$point <- rep(c(1,2,4,3),(newevents-1)) df.melted <- df.melted[order(df.melted$grouping,df.melted$point), ] ## drawing the polygons p <- ggplot() p <- p + geom_polygon(data = df.melted ,aes( x = value ,y =idByDay ,group = grouping ,fill = percent ) ) p <- p + labs(x = "something", y="something else") p <- p + theme( panel.background = element_blank() #,panel.grid.minor = element_blank() #axis.title.x=element_blank() #,axis.text.x=element_text(size=12, face=2, color="darkgrey") #,axis.title.y=element_blank() #,axis.ticks.y = element_blank() #,axis.text.y = element_blank() ) p <- p + scale_fill_gradient( low = "lightgrey" ,high = "red" ,guide = guide_legend( title = "Sys" ,order = 1 ,reverse = FALSE ,ncol = 2 ,override.aes = list(alpha = NA) ) ) p <- p + facet_wrap(~event.day, ncol=2) p </code></pre> Using this code I was able to create a chart that look like this: <img src="https://i.stack.imgur.com/WcCSE.png" alt="enter image description here">
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1. COoptimized the loop over the data.frame by just using vectors without a 2nd loop about the duration
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2. COAnswering your own question is [strongly encouraged](http://stackoverflow.com/help/self-answer). Thanks for sharing what you learned!
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