times <- read.csv(times.txt, sep=" ", header=FALSE)
times <- read.csv("times.txt", sep=" ", header=FALSE)
times
times <- read.csv("times.txt", sep="\t", header=FALSE)
times
times[1] - times[2]
times[2] - times[1]
data <- times[1], times[2], times[2] - times[1]
times[1], times[2], times[2] - times[1]
times[1] times[2], times[2] - times[1]
data
times
d <- times
d
d[3] <- (times[2] - times[1])
d
sort(d)
sort(d, d[3])
d
d[order(d[3])]
order(d[3])
d[1]
d[2]
d[3]
d[1,]
d[2,]
d[order(d[3]),]
d[order(d[3]),][1-2]
d2<- d[order(d[3]),]
d2
d2[1]
d2[1-2]
d2[1-1]
d2[1-3]
d2[2]
d2[1]
d2[1-2]
d2[0-1]
d2[1]
d2[2]
length(d)
length(d[1])
length(d[1,])
size
length(d[1])
length(d[1-2])
length(d2[1])
d
1..1342
seq(1, 1342)
xs <-seq(1, 1342)
d
plot(xs, d2)
xs <-seq(0, 1342)
plot(xs, d2)
length(xs)
xs <-seq(1, 1342)
plot(xs, d2[1])
d2[1]
d2[0]
d2[1]
d2[1]
stripchart(xs)
stripchart(d2)
boxplot(d2)
d2[1:2}
d2[1:2]
stripchart(d2[1:2])
boxplot(d2[1:2])
pairs(d2[1:2])
plot(xs, ds[3])
ds$V1
ds2$V1
d2[2]
d2[2][1]
d2[2][1,]
d2[2][1-,]
d2[2][1-100,]
d2[2][1-]
d2[2]
d2[2][]
d2[2][2
d2[2][2]
d2[2,]
d2[,2]
d2[,1]
d2[,2]
d2[,3]
d2[,1]
d2[,2]
d2[1:2]
d2[,1]
plot(xs, d2[,1])
plot(xs, d2[,2])
plot(xs, d2[,1])
plot(xs, d2[,2])
plot(xs, d2[,1])
d2
d22<-d2[1:2]
d22
pairs(d22)
d2[3]
boxplot(d2[3])
plot(xs, d[,1:2])
plot(xs, d[,1])
plot(xs, d[,2])
plot(xs, d[,1])
plot(xs, d[,3])
plot(xs, d[,1])
plot(xs, d[,2])
plot(xs, d[,1])
plot(xs, d[,2])
boxplot(d[,1])
boxplot(d[,2])
boxplot(d[,1])
boxplot(d[,2])
boxplot(d[,1])
boxplot(d[,2])
boxplot(d[,1])
x <- 10 + (1:20)/10
y <- x^2 + rnorm(length(x))     # Add Gaussian random number
plot(x, y)
curve(x^2, add=TRUE, lty=2)     # Add dashed line showing y=x^2
plot(x, y, type="l", col="blue")  # Plot as blue line (try 'type="o"')
plot(x, y, type="l", log="xy")   # Plot as line with log X & Y axes:
abline(v=11, lty=3)    # Add vertical dotted line
text(11.5, 120, "Hello")   # Add annotation
legend("topleft", inset=0.05, "data", pch=1, col="blue", bty="n")  # Add a legend
plot(x, y, pch=2, col="red") 
plot(x, y, pch=c(3, 20)
plot(x, y, pch=1:20) 
plot(x, d[,1], pch=2, col="green") 
plot(xs, d[,1], pch=2, col="green") 
plot(xs, d[,1], pch=1, col="red") 
plot(xs, d[,1], pch=3, col="red") 
plot(xs, d[,1], pch=4, col="red") 
plot(xs, d[,1], pch=5, col="red") 
plot(xs, d[,1], pch=6, col="red") 
plot(x, d[,1], pch=3, col="green") 
plot(xs, d[,1], pch=3, col="red") 
plot(xs, d2[,1], pch=3, col="red") 
plot(xs, d2[,2], pch=3, col="red") 
plot(xs, d2[,1], pch=3, col="red") 
plot(d2[,1], d2[,2], pch=3, col="red") 
plot(d[,1], d[,2], pch=3, col="red") 
plot(d2[,1], d2[,2], pch=3, col="red") 
plot(d[,1], d[,2], pch=3) 
plot(xs, d2[,3], pch=3) 
curve(0, add=TRUE)
curve(x=0, add=TRUE)
curve(x*0, add=TRUE)
boxplot(d2[,3])
boxplot(d[,1])
boxplot(d[,2])
boxplot(d[,1])
boxplot(d[,2])
times <- read.csv("slicing_times.txt", sep=" ", header=TRUE)
times
times.names
times.getNames()
times[,1]
times[1,]
times$sltime
boxplot(times$sltime)
boxplot(times$sltime, pch=3)
boxplot(times$sliceddg, pch=3)
boxplot(times$slicedmod, pch=3)
pairs(times[1:2])
plot(times$sltime, times$sliceddg, pch=3)
avg
sum(times$sltime)/length(times$sltime)
plot(times$sliceddg, times$slicedmod, pch=3)
scatterplot(times$sltime)
stripchart(times$sltime)
histogram(times$sltime)
hist(times$sltime)
hist(times$sltime, col=c("green", "red"))
hist(times$sltime, col=c("green", "red))
hist(times$sliceddg, col=c("green", "red))
hist(times$sliceddg)
hist(times$slicedmod)
hist(times$slicedmod, col=c("green", "blue", "red"))
hist(times$sliceddg, col=c("green", "blue", "red"))
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="% of sliced nodes")
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="% of sliced nodes", ylab = "number of benchmarks")
png(filename="hist_nodes.png")
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="% of sliced nodes", ylab = "number of benchmarks")
dev.off()
dev.print(pdf, "hist_nodes.pdf")
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="% of sliced nodes", ylab = "number of benchmarks", main="")
dev.print(pdf, "hist_nodes.pdf")
hist(times$slicedmod, col=c("green", "blue", "red"), xlab="size of sliced module [%]", ylab = "number of benchmarks", main="")
dev.print(pdf, "hist_mod.pdf")
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="size of sliced dependence graph [%]", ylab = "number of benchmarks")
dev.print(pdf, "hist_nodes.pdf")
hist(times$sliceddg, col=c("green", "blue", "red"), xlab="size of sliced dependence graph [%]", ylab = "number of benchmarks", main="")
dev.print(pdf, "hist_nodes.pdf")
hist(times$sltime, col=c("green", "blue", "red"), xlab="number of benchmarks", ylab = "time [s]", main="")
hist(times$sltime, col=c("green", "blue", "red"), ylab="number of benchmarks", xlab = "time [s]", main="")
dev.print(pdf, "hist_time.pdf")
