Commit 0d6ec2d9 authored by Matt Traudt's avatar Matt Traudt
Browse files

Add scripts for comparing v3bw files

parent f8b895ca
#!/usr/bin/env python3
# File: plot-v3bw-xy.py
# Author: Matt Traudt
# License: CC0
#
# Requires matplotlib; pip install matplotlib
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
import matplotlib; matplotlib.use('Agg') # noqa; for systems without X11
from matplotlib.backends.backend_pdf import PdfPages
import pylab as plt
plt.rcParams.update({
'axes.grid': True,
})
def get_all_values_from_fd(fd):
values = []
for line in fd:
try:
x, y = line.strip().split()
x, y = str(x), float(y)
assert len(x) == 40
values.append((x, y))
except ValueError:
print('ignoring', line)
continue
return values
def common_elements(l1, l2):
ret = set()
for item in l1:
if item in l2:
ret.add(item)
return ret
def main(args, pdf):
plt.figure()
data = {}
# Read all data in
all_labels = []
for fname, label in args.input:
with open(fname, 'rt') as fd:
data[label] = {
'label': label,
'data': get_all_values_from_fd(fd)
}
all_labels.append(label)
# Determine what relay fingerprints have data from all input sources
common_fingerprints = None
for label1 in data:
fp_list1 = set([point[0] for point in data[label1]['data']])
for label2 in data:
if label2 == label1:
continue
fp_list2 = set([point[0] for point in data[label2]['data']])
fp_list1 = common_elements(fp_list1, fp_list2)
common_fingerprints = fp_list1
break
# Remove unneeded data, then
# sort by fingerprint
for label in data:
points = [p for p in data[label]['data']
if p[0] in common_fingerprints]
points = sorted(points, key=lambda p: p[0])
data[label]['data'] = points
# combine the y values for each fingerprint
# {
# 'fp1': {'label1': 10, 'label2': 30},
# 'fp2': {'label1': 20, 'label2': 15},
# }
# and change dict data's structure to that
new_data = {}
for fp in common_fingerprints:
new_data[fp] = {}
for label in data:
y = [p[1] for p in data[label]['data'] if p[0] == fp]
assert len(y) == 1
y = y[0]
new_data[fp].update({label: y})
data = new_data
sort_label = all_labels[0]
# Sort the data points such that sort_label's highest value is first.
# Assuming sort_label is label1, then turn into this list
# [
# {'label1': 20, 'label2': 15},
# {'label1': 10, 'label2': 30},
# ]
# and change dict data's structure to that
new_data = []
for fp in data:
new_data.append(data[fp])
new_data = sorted(new_data, key=lambda k: k[sort_label], reverse=True)
data = new_data
# Plot data
for label in all_labels:
x = []
y = []
for i, point in enumerate(data):
x.append(i)
y.append(point[label] / 1000)
plt.scatter(x, y, s=args.size, label=label)
plt.legend(loc='upper right')
plt.xlabel(args.xlabel)
plt.ylabel(args.ylabel)
plt.title(args.title)
pdf.savefig()
if __name__ == '__main__':
d = 'Takes one or more lists of (fingerprint, bandwidth) points, 1 per '\
'line, and plots a scatter plot of them. Data points are sorted by '\
'the first input\'s bandwidth values, thus this script can be used '\
'to visually determine how similar the results are from various '\
'instances of a bandwidth scanner, or even across different '\
'bandwidth scanning tools.'
parser = ArgumentParser(
formatter_class=ArgumentDefaultsHelpFormatter, description=d)
parser.add_argument(
'-i', '--input', nargs=2, metavar=('FNAME', 'LABEL'),
action='append', help='Specify a file to read values from and what '
'to label its points in the PDF. Can be given more than once.')
parser.add_argument('-o', '--output', default='temp.pdf')
parser.add_argument('-x', '--xlabel', type=str, default='Relay #',
help='What to label the X axis in the PDF')
parser.add_argument('-y', '--ylabel', type=str,
default='"Bandwidth" units (thousands)',
help='What to label the Y axis in the PDF')
parser.add_argument('-t', '--title', type=str,
default='Correlation of various bwscanning systems',
help='What to title the plot in the PDF')
parser.add_argument('-s', '--size', type=float, default=1,
help='Size of scatter plot points')
args = parser.parse_args()
with PdfPages(args.output) as pdf:
exit(main(args, pdf))
#!/usr/bin/env bash
# File: v3bw-into-xy.sh
# Author: Matt Traudt
# License: CC0
#
# Takes one or more v3bw files as arguments.
#
# Looks for lines that contain actual data. That means most of them, since most
# of them start with "node_id=" and those are the ones that are interesting.
#
# Extract the fingerprint and bandwidth values for each of those lines and put
# them on stdout, one per line. Effectively, after ignoring other lines, this:
# node_id=$AAAA...AAAA bw=12345
# becomes this:
# AAAA...AAAA 12345
#
# NOTE: If you specify more than v3bw file, this will do NOTHING to tell you
# when the output from one file stops and the next begins
set -e
while [ "$1" != "" ]
do
grep '^node_id=' "$1" |
sed -r 's|^node_id=([$A-Z0-9]+) bw=([0-9]+).*$|\1 \2|' |
sed 's|\$||g'
shift
done
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