[tor-commits] [metrics-tasks/master] Graphing code for fast exits graphs (#6498).

[karsten at torproject.org]

commit 80c885ec4b89986374c699939ff9611cbfebc07e
Author: Karsten Loesing <karsten.loesing at gmx.net>
Date:   Thu Aug 2 19:04:02 2012 +0200

    Graphing code for fast exits graphs (#6498).
---
 task-6498/.gitignore |    2 +
 task-6498/plot.R     |   77 ++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 79 insertions(+), 0 deletions(-)

diff --git a/task-6498/.gitignore b/task-6498/.gitignore
index 9dc71c8..707150a 100644
--- a/task-6498/.gitignore
+++ b/task-6498/.gitignore
@@ -4,4 +4,6 @@ lib/
 bin/
 in/
 results.csv
+Rplots.pdf
+*.png
 
diff --git a/task-6498/plot.R b/task-6498/plot.R
new file mode 100644
index 0000000..9f7763d
--- /dev/null
+++ b/task-6498/plot.R
@@ -0,0 +1,77 @@
+# uncomment for 2+ years
+#CUTOFF <- "2010-05-26"
+#DETAIL <- "week"
+CUTOFF <- "2012-06-02"
+DETAIL <- "day"
+
+require(ggplot2)
+require(reshape)
+require(RColorBrewer)
+data <- read.csv("results.csv", stringsAsFactors = FALSE)
+data <- data[data$valid_after >= paste(CUTOFF, "00:00:00"), ]
+
+r <- data
+r <- r[r$min_rate == 11875 & r$ports == "80-443-554-1755" &
+  r$min_advbw == 5000, ]
+r <- aggregate(list(relays = r$relays, P_exit = 100 * r$exit_prob),
+  by = list(date = as.Date(cut.Date(as.Date(r$valid_after), DETAIL))),
+  FUN = median)
+r <- melt(r, id.vars = c("date"))
+r <- data.frame(r, type = ifelse(r$variable == "P_exit",
+  "Total exit probability (in %)", "Number of relays"))
+ggplot(r, aes(x = date, y = value)) +
+geom_line(colour = "purple", size = 0.75) +
+facet_grid(type ~ ., scales = "free_y") +
+scale_x_date(name = "") +
+scale_y_continuous(name = "") +
+scale_colour_manual(values = c("purple", "orange")) +
+opts(title = paste("Fast relays (95+ Mbit/s configured bandwidth rate,\n",
+  "5000+ KB/s advertised bandwidth capacity,\n",
+  "exit to ports 80, 443, 554, and 1755,\n",
+  "at most 2 relays per /24 network)\n", sep = ""))
+ggsave("fast-exits.png", width = 8, height = 6, dpi = 100)
+
+s <- data
+s <- s[s$min_rate == 11875 & s$ports == "80-443-554-1755", ]
+s <- aggregate(list(relays = s$relays, P_exit = 100 * s$exit_prob),
+  by = list(date = as.Date(cut.Date(as.Date(s$valid_after), DETAIL)),
+  min_advbw = s$min_advbw), FUN = median)
+s <- melt(s, id.vars = c("date", "min_advbw"))
+s <- data.frame(s, type = ifelse(s$variable == "P_exit",
+  "Total exit probability (in %)", "Number of relays"))
+ggplot(s, aes(x = date, y = value, colour = as.factor(min_advbw))) +
+geom_line() +
+facet_grid(type ~ ., scales = "free_y") +
+scale_x_date(name = "") +
+scale_y_continuous(name = "") +
+scale_colour_manual(name = "Advertised bandwidth (in KB/s)",
+  values = brewer.pal(6, "Purples")[2:6]) +
+opts(title = paste("Relays meeting the fast-exit requirements\nwith",
+  "varying minimum advertised bandwidth capacities"),
+  legend.position = "top")
+ggsave("advertised-bandwidths-requirement.png", width = 8, height = 6,
+  dpi = 100)
+
+t <- data
+t1 <- t[t$min_rate == 11875 & t$ports == "80-443-554-1755" &
+  t$min_advbw == 5000, ]
+t2 <- t[t$min_rate == 10000 & t$ports == "80-443" &
+  t$min_advbw == 2000, ]
+t <- rbind(data.frame(t1, var = "95+ Mbit/s, 5000+ KB/s, 80/443/554/1755"),
+  data.frame(t2, var = "80+ Mbit/s, 2000+ KB/s, 80/443"))
+t <- aggregate(list(relays = t$relays, P_exit = 100 * t$exit_prob),
+  by = list(date = as.Date(cut.Date(as.Date(t$valid_after), DETAIL)),
+  var = t$var), FUN = median)
+t <- melt(t, id.vars = c("date", "var"))
+t <- data.frame(t, type = ifelse(t$variable == "P_exit",
+  "Total exit probability (in %)", "Number of relays"))
+ggplot(t, aes(x = date, y = value, colour = var)) +
+geom_line(size = 0.75) +
+facet_grid(type ~ ., scales = "free_y") +
+scale_x_date(name = "") +
+scale_y_continuous(name = "") +
+scale_colour_manual(name = "", values = c("purple", "orange")) +
+opts(title = "Relays almost meeting the fast-exit requirements",
+  legend.position = "top")
+ggsave("almost-fast-exits.png", width = 8, height = 6, dpi = 100)
+