Geom_polygon gradient fill

Question

this code creates a chart with three polygons ...

I am creating a diagram with three polygons, I am not very interested in whether there are ways to draw polygons (usually these polygons represent events and the duration of these events).

First of all, I'm interested in the ability to fill each polygon with a gradient.

# library("ggplot2") # library(data.table) ## some vectors event.day <- c("A", "A", "B", "B") event.time <- c(1, 2, 1, 2) event.duration <- c(1,2,3,1) sys <- c(100, 50, 50, 100) ## the data data.frame df.event <- data.frame(event.day, event.time,event.duration,sys) # ordering the data.frame df.event <- df.event[with(df.event, order(event.day, event.time)), ] # sys values of the next event df.event$sys.end <- c(df.event$sys[-1], NA) df.event$sys.min <- min(df.event$sys) df.event$sys.minday <- ave(df.event$sys, list(event.day), FUN=function(x) {min(x)}) df.event$sys.max <- max(df.event$sys) df.event$sys.maxday <- ave(df.event$sys, list(event.day), FUN=function(x) {max(x)}) # count all events df.event$cntTotalNoOfEvents <- seq_along(df.event$sys) # count the events within one day df.event$cntTotalNoOfEventsByDay <- ave( 1:nrow(df.event), df.event$event.day,FUN=function(x) seq_along(x)) # aggregate the number or events within one day df.event$TotalNoOfEventsByDay <- do.call(c, lapply(df.event$event.day, function(foo){ sum(df.event$event.day==foo) })) # the successor event df.event$event.successor <- c(df.event$cntTotalNoOfEvents[-1], NA) df.event$event.day <- factor(df.event$event.day, levels = unique(df.event$event.day)) event.day.level <- levels(df.event$event.day) df.event$event.day.level.ordinal <- as.numeric(match(df.event$event.day, event.day.level)) ## the position data.frame df.position <- data.frame(event.polygon = rep(c(1:nrow(df.event)), each = 4), polygon.x = 1, polygon.y = 1) df.position$event.polygon.point <- ave( 1:nrow(df.position), df.position$event.polygon,FUN=function(x) seq_along(x)) ## merge of the data and the positition data.frame dt.polygon <- data.table(merge(df.event, df.position, by.x = "cntTotalNoOfEvents", by.y = "event.polygon")) ## calculating the points of the polygon dt.polygon[dt.polygon$event.polygon.point == 1, polygon.x := event.day.level.ordinal - .5 * sys / sys.max ] dt.polygon[dt.polygon$event.polygon.point == 1, polygon.y := cntTotalNoOfEventsByDay] dt.polygon[dt.polygon$event.polygon.point == 2, polygon.x := event.day.level.ordinal - .5 * sys.end / sys.max] dt.polygon[dt.polygon$event.polygon.point == 2, polygon.y := cntTotalNoOfEventsByDay + event.duration] dt.polygon[dt.polygon$event.polygon.point == 3, polygon.x := event.day.level.ordinal + .5 * sys.end / sys.max] dt.polygon[dt.polygon$event.polygon.point == 3, polygon.y := cntTotalNoOfEventsByDay + event.duration] dt.polygon[dt.polygon$event.polygon.point == 4, polygon.x := event.day.level.ordinal + .5 * sys / sys.max] dt.polygon[dt.polygon$event.polygon.point == 4, polygon.y := cntTotalNoOfEventsByDay] p <- ggplot() p <- p + geom_polygon(data = dt.polygon ,aes( x = polygon.x ,y = polygon.y ,fill = sys ,group = cntTotalNoOfEvents ) ) p <- p + theme( panel.background = element_rect(fill="white") ) p <- p + scale_fill_gradient(guide = "colourbar", low = "lightgrey", high = "red") p <- p + coord_flip() p 

creates this chart

What I'm trying to achieve is like this

do you have any ideas

As always, any hint is appreciated.

Tom

Answer 1

Hmm, I'm really not sure if it makes sense to answer my question ...

But due to the fact that I did not get any answer, my initial question was a bit silly.

However, on the last day I spent some time resolving my problem. Basically my solution is to add additional segments according to the duration of the event. I leave you my time calculations. This is because my initial interest was how to provide a gradient for a polygon.

Some of you may find my solution useful.

Cheers Tom

 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 

Using this code, I managed to create a diagram that looks like this: