[tor-commits] [metrics-tasks/master] Add probability graphs (#1854).
karsten at torproject.org
karsten at torproject.org
Tue Nov 27 01:42:29 UTC 2012
commit ad05f28662ddb22c44c88111315ae5b3f2ae7f66
Author: Karsten Loesing <karsten.loesing at gmx.net>
Date: Mon Nov 26 20:41:29 2012 -0500
Add probability graphs (#1854).
---
task-1854/plot-entropy.R | 22 ++++++++++++++-
task-1854/pyextract.py | 10 +++++-
task-1854/pylinf.py | 66 +++++++++++++++++++++++++++++++++------------
3 files changed, 77 insertions(+), 21 deletions(-)
diff --git a/task-1854/plot-entropy.R b/task-1854/plot-entropy.R
index 95b8b18..d62657e 100644
--- a/task-1854/plot-entropy.R
+++ b/task-1854/plot-entropy.R
@@ -2,7 +2,27 @@ library(ggplot2)
library(reshape)
library(scales)
-e <- read.csv("extracted.csv", header = FALSE,
+p <- read.csv("prob-extracted.csv", header = FALSE,
+ col.names = c("validafter", "minadvbw", "advbw", "cumprob"),
+ stringsAsFactor = FALSE)
+p <- p[p$minadvbw >= 20480, ]
+c <- data.frame(x = p$advbw, y = p$cumprob,
+ colour = as.factor(p$minadvbw))
+ggplot(c, aes(x = x, y = y, colour = colour)) +
+geom_line() +
+scale_x_log10(name = "\nAdvertised bandwidth in B/s (log scale)") +
+scale_y_continuous(name = "Cumulated probability\n") +
+scale_colour_hue(name = "Adv. bw. cutoff in B/s") +
+opts(legend.position = "top")
+
+ggplot(c, aes(x = x, y = y, colour = colour)) +
+geom_line() +
+scale_x_log10(name = "\nAdvertised bandwidth in B/s (log scale)") +
+scale_y_log10(name = "Cumulated probability (log scale)\n") +
+scale_colour_hue(name = "Adv. bw. cutoff in B/s") +
+opts(legend.position = "top")
+
+e <- read.csv("linf-extracted.csv", header = FALSE,
col.names = c("validafter", "min_adv_bw", "relays", "linf",
"excl_adv_bw", "graph"), stringsAsFactor = FALSE)
diff --git a/task-1854/pyextract.py b/task-1854/pyextract.py
index 33614e2..bd11ea4 100644
--- a/task-1854/pyextract.py
+++ b/task-1854/pyextract.py
@@ -2,11 +2,11 @@ import os
import sys
def main():
- out_file = open('extracted.csv', 'w')
+ out_file = open('linf-extracted.csv', 'w')
prev_validafter, max_validafter = '', ''
max_lines = []
prev_relays, prev_min_adv_bw = 0, 0
- for line in open('entropy.csv'):
+ for line in open('linf.csv'):
parts = line.strip().split(',')
validafter = parts[0]
min_adv_bw = int(parts[1])
@@ -32,6 +32,12 @@ def main():
prev_min_adv_bw = min_adv_bw
for line in max_lines:
out_file.write(line + ",last\n")
+ out_file.close()
+ prob_out_file = open('prob-extracted.csv', 'w')
+ for line in open('prob.csv'):
+ if line.startswith(max_validafter):
+ prob_out_file.write(line.strip() + '\n')
+ prob_out_file.close()
if __name__ == '__main__':
main()
diff --git a/task-1854/pylinf.py b/task-1854/pylinf.py
index 88cc773..3bdd8a2 100644
--- a/task-1854/pylinf.py
+++ b/task-1854/pylinf.py
@@ -102,9 +102,12 @@ def load_server_desc(tar_file_path):
tar_fh.close()
def run(data):
+ """ Return tuple of two strings, one string containing linf values for
+ all possible advertised bandwidth cutoffs, and one containing
+ probability distributions for predefined cutoffs. """
routers = []
router = None
- result_string = []
+ linf_string, prob_string = [], []
Wed, Wee, Wgd, Wgg = 1, 1, 1, 1
# parse consensus
@@ -151,6 +154,8 @@ def run(data):
omitted_routers = 0
min_adv_bw = routers[0].advertised_bw
+ cutoffs = [10240, 20480, 51200, 102400, 204800, 512000, 1048576]
+
while(omitted_routers<len(routers)):
total_bw = 0
@@ -170,11 +175,29 @@ def run(data):
diff = abs(new_prob - router.prob)
prob_diff.append(diff)
- result_string.append(','.join([valid_after,
+ linf_string.append(','.join([valid_after,
str(min_adv_bw),
str(len(routers)-omitted_routers),
str(max(prob_diff))]))
+ while len(cutoffs) > 0 and min_adv_bw > cutoffs[0]:
+ cumulated_prob = 0.0
+ prev_advertised_bw = 0
+ for router in routers:
+ if router.advertised_bw > cutoffs[0] and \
+ prev_advertised_bw != router.advertised_bw:
+ prob_string.append(','.join([valid_after,
+ str(cutoffs[0]),
+ str(prev_advertised_bw),
+ str(cumulated_prob)]))
+ prev_advertised_bw = router.advertised_bw
+ cumulated_prob += float(router.bandwidth)/float(total_bw)
+ prob_string.append(','.join([valid_after,
+ str(cutoffs[0]),
+ str(prev_advertised_bw),
+ str(cumulated_prob)]))
+ cutoffs.pop(0)
+
# remove routers with min adv_bw
for router in routers:
if router.advertised_bw == min_adv_bw:
@@ -184,7 +207,7 @@ def run(data):
min_adv_bw = router.advertised_bw
break
- return '\n'.join(result_string)
+ return ('\n'.join(linf_string), '\n'.join(prob_string))
def parse_args():
usage = "Usage - python pyentropy.py [options]"
@@ -196,8 +219,10 @@ def parse_args():
help="Input AS GeoIP database")
parser.add_option("-s", "--server_desc", dest="server_desc",
default=False, help="Server descriptors directory")
- parser.add_option("-o", "--output", dest="output", default="entropy.csv",
- help="Output filename")
+ parser.add_option("-l", "--linf-output", dest="linf", default="linf.csv",
+ help="linf output filename")
+ parser.add_option("-r", "--prob-output", dest="prob", default="prob.csv",
+ help="Probabilities output filename")
parser.add_option("-c", "--consensus", dest="consensus", default="in/consensus",
help="Input consensus dir")
parser.add_option("-p", "--pickled_data", dest="pickled_data", default=False,
@@ -227,16 +252,21 @@ if __name__ == "__main__":
with open('data.pkl', 'wb') as output:
pickle.dump(descriptors, output)
- with open(options.output, 'w') as out_fh:
- for file_name in os.listdir(options.consensus):
- file_path = os.path.join(options.consensus, file_name)
- tar_fh = tarfile.open(file_path)
- for member in tar_fh:
- if not member.isfile():
- continue
- tar_file_data=tar_fh.extractfile(member)
- data=tar_file_data.read()
- output_string = run(data)
- if output_string:
- out_fh.write("%s\n" % (output_string))
- tar_fh.close()
+ linf_fh = open(options.linf, 'w')
+ prob_fh = open(options.prob, 'w')
+ for file_name in os.listdir(options.consensus):
+ file_path = os.path.join(options.consensus, file_name)
+ tar_fh = tarfile.open(file_path)
+ for member in tar_fh:
+ if not member.isfile():
+ continue
+ tar_file_data=tar_fh.extractfile(member)
+ data=tar_file_data.read()
+ (linf_string, prob_string) = run(data)
+ if linf_string:
+ linf_fh.write("%s\n" % (linf_string))
+ if prob_string:
+ prob_fh.write("%s\n" % (prob_string))
+ tar_fh.close()
+ linf_fh.close()
+ prob_fh.close()
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