Plotting huge number of lines in R - r

Question

I have written a code to plot nearly 100000 lines in a graph with different colors depending on different conditions. The code is as following.
for(i in c(160000:260000)){
if(data[i,]$Char1 == 'A' & data[i,]$Char2 == 'S'){
if(data[i,]$Q1 < data[i,]$Q2){
lines(c(i,i),c(data[i,]$P + 2,data[i,]$P + 22),col="green")
}else{
lines(c(i,i),c(data[i,]$P - 2,data[i,]$P - 22),col="green")
}
}
if(data[i,]$Char1 == "B" & data[i,]$Char2 == 'S'){
lines(c(i,i),c(data[i,]$P + 2,data[i,]$P + 22),col='blue')
}
}
I have Plotted a normal graph before that. Which is
plot(data$P,type="l")
I ran the code and for more than 2-3 hours it kept on running till the point I stopped it. Is there any way to do this task easily and with less amount of time?

Answer 1

You may be able to save some computation time by not actually displaying the plot. Running
library(scales)
n <- 100000
m <- 20
system.time({
plot(0, 0, type = 'n', xlim = c(0, 10), ylim = c(0, 10), xlab = '', ylab = '')
for (i in 1:n) lines(sort(runif(m, max = 10)), sort(runif(m, max = 10)),
col = ifelse(i %% 10 == 0, 'red', alpha('lightblue', 0.1)),
lwd = 0.2)
})
vs.
system.time({
png('plot.png')
plot(0, 0, type = 'n', xlim = c(0, 10), ylim = c(0, 10), xlab = '', ylab = '')
for (i in 1:n) lines(sort(runif(m, max = 10)), sort(runif(m, max = 10)),
col = ifelse(i %% 10 == 0, 'red', alpha('lightblue', 0.1)),
lwd = 0.2)
dev.off()
})
gives
user system elapsed
44.415 0.704 45.435
vs.
user system elapsed
23.115 0.294 23.585
on my machine.
Update
Using CathG's answer brings down the computation time drastically when plotting lines:
n <- 100000
data <- data.frame(x0 = runif(n), y0 = runif(n), x1 = runif(n),
y1 = runif(n), col = 1:10)
system.time({
png('plot.png', 640, 640)
plot(0, 0, type = 'n', xlab = '', ylab = '', xlim = c(0, 1), ylim = c(0, 1))
for (i in 1:n) lines(data[i, c(1, 3)], data[i, c(2, 4)], col = data$col,
lwd = 0.1)
dev.off()
})
system.time({
png('plot.png', 640, 640)
plot(0, 0, type = 'n', xlab = '', ylab = '', xlim = c(0, 1), ylim = c(0, 1))
segments(data$x0, data$y0, data$x1, data$y1, col = data$col, lwd = 0.1)
dev.off()
})
gives
user system elapsed
119.682 0.822 121.525
vs.
user system elapsed
2.267 0.020 2.303

Answer 2

I think you should compute the different x and y (and color) first and then plot them all in one call with segments and I also think you should directly plot them using png for example and not in the window device:
data2 <- data[160000:260000, ]
data2$x0 <- data2$x1 <- 160000:260000
cond1 <- (data2$Char1=="A") & (data2$Char2 == "S") & (data2$Q1 < data2$Q2)
cond2 <- (data2$Char1=="A") & (data2$Char2 == "S") & (data2$Q1 >= data2$Q2)
cond3 <- (data2$Char1=="B") & (data2$Char2 == "S")
data2$y0[cond1] <- data2$P[cond1] + 2
data2$y0[cond2] <- data2$P[cond2] - 2
data2$y0[cond3] <- data2$P[cond3] + 2
data2$y1[cond1] <- data2$P[cond1] + 22
data2$y1[cond2] <- data2$P[cond2] - 22
data2$y1[cond3] <- data2$P[cond3] + 22
data2$color[cond1] <- "green"
data2$color[cond2] <- "green"
data2$color[cond3] <- "blue"
png("nameofyourfile.png")
plot(data$P,type="l")
segments(data2$x0, data2$y0, data2$x1, data2$y1, col=data2$color)
dev.off()