#! /usr/bin/Rscript

options(verbose=FALSE, warn=-1)

library(reshape)
library(ggplot2)

failure.probs = c(0.5, 0.2, 0.1, 0.05, 0.02, 0.01)
trials = 1:1000

results = matrix(0, nrow=length(trials), ncol=length(failure.probs))
colnames(results) = failure.probs

for (i in seq_along(failure.probs))
  for (j in trials)
    results[j,i] = 1 - binom.test(c(j, 0), p=1-failure.probs[i],
             alternative='greater')$p.value

# trim results to make the graph tidier
results[results > 0.9999] = NA

results.long = melt(results)
colnames(results.long) = c('trials', 'p.failure', 'p.fixed')
results.long$p.failure = ordered(results.long$p.failure)

# there *is* a more elegant way to do this but i can't find it right now
xbreaks = c(1,2,5,10,20,50,100,200,500,1000)
xlabels = as.character(xbreaks)
ybreaks = c(0.5, 0.75, 0.9, 0.95, 0.99, 1)
ylabels = c('0.5 ', '0.75', '0.9 ', '0.95', '0.99', '1   ')

graph = ggplot(results.long, aes(x=trials, y=p.fixed, colour=p.failure)) +
  geom_step() +
  scale_x_log10(name='Test runs after fix', breaks=xbreaks,
                labels=xlabels) +
  scale_y_continuous(name=expression(Pr(fixed)), limits=c(0.5, 1),
                     breaks=ybreaks, labels=ylabels) +
  scale_colour_discrete(name=expression(Pr(failure)))

png(filename="intermittent-failures.png", width=800, height=700)
print(graph)
dev.off()