I'm trying to produce a graph with points within shaded areas: "low_risk", "mid_risk" or "high_risk".
I tried using geom_curves for the borders but don't know how to shade between them in yellow, orange and red.
library("dplyr")
library("ggplot2")
Likelihood <- c(2,1,2,1,1,2,2,3,2,1,3,2,1,1,2,4,4,2,2,2,2,3,2,2,1,1,2,2,2)
Impact <- c(4,3,2,2,2,3,1,2,2,3,2,3,3,4,3,2,2,2,2,4,3,1,1,4,4,4,3,2,4)
RISK <- c("Reg","Con","Strat","Con","Rep","Reg","Reg","Op","Op","L","Op","Strat","Strat","Op","Con","Reg","Reg","Op","Strat","Op","Reg","Rep","Op","Con","Op","Reg","Strat","Op","Con")
Weight <- Likelihood*Impact/64
df = data.frame(RISK,Likelihood,Impact,Weight)
low_risk <- geom_curve(aes(x = 1, xend = 4, y = 4, yend = 1), color = "yellow", size = 1)
mid_risk <- geom_curve(aes(x = 2, xend = 4, y = 4, yend = 2), color = "orange", size = 1)
high_risk <- geom_curve(aes(x = 3, xend = 4, y = 4, yend = 3), color = "red", size = 1)
Graph <- ggplot(data = df, aes(x = Likelihood, y = Impact, color = RISK, size = Weight, fill = RISK)) +
geom_jitter(width = 0.2, height = 0.2, shape = 21, stroke = 2) +
scale_size_continuous(range = c(4, 16)) +
scale_x_continuous(limits = c(.8, 4.2)) + scale_y_continuous(limits = c(.8, 4.2)) +
low_risk + mid_risk + high_risk
NOTE: Managed to do it in a more convoluted way and still wondered if there is a more elegant solution...
library("dplyr")
library("ggplot2")
high_zone <- function(x) {
12/x
}
mid_zone <- function(x) {
8/x}
low_zone <- function(x) {
4/x
}
Likelihood <- c(2,1,2,1,1,2,2,3,2,1,3,2,1,1,2,4,4,2,2,2,2,3,2,2,1,1,2,2,2)
Impact <- c(4,3,2,2,2,3,1,2,2,3,2,3,3,4,3,2,2,2,2,4,3,1,1,4,4,4,3,2,4)
RISK <- c("Reg","Con","Strat","Con","Rep","Reg","Reg","Op","Op","L","Op","Strat","Strat","Op","Con","Reg","Reg","Op","Strat","Op","Reg","Rep","Op","Con","Op","Reg","Strat","Op","Con")
Weight <- Likelihood*Impact/64
Graph <- ggplot(data = Weight) +
geom_jitter(aes(x = Likelihood, y = Impact, size = Weight, fill = RISK), stroke = 1.2, color = "black", shape = 21, width = 0.20, height = 0.20) +
scale_size_continuous(range = c(4, 16)) +
stat_function(fun = high_zone, geom = "line", color = "red", size = 0.8, alpha = 0.5) +
stat_function(fun = mid_zone, geom = "line", color = "orange", size = 0.8) +
stat_function(fun = low_zone, geom = "line", color = "yellow", size = 0.8) +
scale_x_continuous(limits = c(0.8,4.2)) + scale_y_continuous(limits = c(0.8,4.2))
gg1 <- ggplot_build(Graph)
df1 <- data.frame(low_like = gg1$data[[4]]$x,
low_like_min = gg1$data[[4]]$y,
mid_like_max = gg1$data[[3]]$y)
df2 <- data.frame(mid_like1 = gg1$data[[3]]$x[40:101],
mid_like_min1 = gg1$data[[3]]$y[40:101],
high_like_max1 = gg1$data[[2]]$y[40:101])
top_boundary <- function(x) {
4.18
}
Graph1 <- Graph + stat_function(fun = top_boundary, geom = "line", color = "red", size = 0.0001, alpha = 0.0001)
Graph2 <- Graph1 + geom_ribbon(data = df1, aes(x = low_like, ymin = low_like_min, ymax = mid_like_max),
fill = "yellow", alpha = 0.3)
gg2 <- ggplot_build(Graph2)
df12 <- data.frame(lows = gg2$data[[5]]$x[1:34],
low_line = gg2$data[[4]]$y[1:34],
bounds = gg2$data[[5]]$y[1:34])
df22 <- data.frame(lows1 = gg2$data[[5]]$x[34:62],
low_line1 = gg2$data[[3]]$y[34:62],
bounds1 = gg2$data[[5]]$y[34:62])
df32 <- data.frame(lows2 = gg2$data[[5]]$x[62:101],
low_line2 = gg2$data[[2]]$y[62:101],
bounds2 = gg2$data[[5]]$y[62:101])
Graph3 <- Graph2 + geom_ribbon(data = df12, aes(x = lows, ymin = low_line, ymax = bounds),
fill = "yellow", alpha = 0.3) +
geom_ribbon(data = df2, aes(x = mid_like1, ymin = mid_like_min1, ymax = high_like_max1),
fill = "orange", alpha = 0.3) +
geom_ribbon(data = df22, aes(x = lows1, ymin = low_line1, ymax = bounds1),
fill = "orange", alpha = 0.3) +
geom_ribbon(data = df32, aes(x = lows2, ymin = low_line2, ymax = bounds2),
fill = "red", alpha = 0.3)
