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#!/usr/bin/env python
import defapp
from plot import decode
from util import load_csv_file, write_csv_file
from math import ceil
from numpy import amin, amax, mean, median, std, histogram, zeros, arange
from os.path import splitext, basename
from optparse import make_option as o
from gnuplot import gnuplot, FORMATS, Plot, label, curve
options = [
# output options
o('-f', '--format', action='store', dest='format', type='choice',
choices=FORMATS, help='output format'),
o(None, '--save-script', action='store_true', dest='save_script'),
o('-p', '--prefix', action='store', dest='prefix'),
# formatting options
# These may or may not be supported by a particular experiment plotter.
o(None, '--smooth', action='store_true', dest='smooth'),
o(None, '--hist', action='store_true', dest='histogram'),
]
defaults = {
# output options
'format' : 'pdf',
'save_script' : False,
'prefix' : '',
# formatting options
'histogram' : False,
'smooth' : False,
}
def get_stats_label(samples):
avg = mean(samples)
med = median(samples)
dev = std(samples)
max = amax(samples)
min = amin(samples)
return "min=%.2f max=%.2f avg=%.2f median=%.2f std=%.2f" \
% (min, max, avg, med, dev)
class NetsecPlotter(defapp.App):
def __init__(self):
defapp.App.__init__(self, options, defaults, no_std_opts=True)
self.tmpfiles = []
def make_plot(self, fname=None):
p = Plot()
p.output = "%s%s.%s" % (self.options.prefix, fname, self.options.format)
p.format = self.options.format
return p
def setup_png(self, plot):
# standard png options; usually correct; never tweaked for paper
if self.options.format == 'png':
plot.font_size = 'large'
plot.size = (1024, 768)
plot.xticks = (0, 1)
plot.yticks = (0, 0.1)
plot.default_style = "linespoints"
return True
else:
return False
def write(self, data, name, ext='data'):
if self.options.save_script:
fname = "%s.%s" % (name, ext)
write_csv_file(fname, data)
return fname
else:
tmp = write_csv_file(None, data)
# keep a reference so that it isn't deleted
self.tmpfiles.append(tmp)
return tmp.name
def load(self, datafile):
data = load_csv_file(datafile)
print "loaded %d lines" % len(data)
return data
def write_histogram(self, samples, name):
max = amax(samples)
(hist, edges) = histogram(samples, bins=max,
range=(0.5,max+.5))
data = zeros((len(edges)-1, 3))
cumulative = 0
for i in xrange(len(hist)):
data[i, 0] = (edges[i] + edges[i + 1]) / 2.0
data[i, 1] = hist[i]
cumulative += hist[i]
data[i, 2] = cumulative
if len(hist) > 20:
label_freq = 10
else:
label_freq = 1
for_file = []
for i, row in enumerate(data):
label = '%d' % row[0] if row[0] % label_freq == 0 else ''
for_file.append([row[0], row[1], row[2], label])
return (data, self.write(for_file, name, ext='hist'))
def render(self, p):
if self.options.save_script:
p.gnuplot_save(p.output + '.plot')
else:
p.gnuplot_exec()
def plot_hchisto(self, datafile, name, conf):
data = self.load(datafile)
#max_val = amax(data[:,1])
if self.options.histogram:
name += '_hist'
p = self.make_plot(name)
# place a label on the graph
p.labels = [label(0.5, 0.9, get_stats_label(data[:,1]),
coord=['graph', 'screen'], align='center')]
(data, fname) = self.write_histogram(data[:,1], name)
p.xlabel = "hop count"
p.ylabel = "number of sources"
p.setup_histogram(gap=1, boxwidth=1.0)
p.title = "hop counts;"
if 'per-host' in conf:
p.title += " HC per-host: %s" % conf['per-host']
if 'as-num' in conf:
p.title += " AS=%s, IP/mask=%s/%s MB=%s Unique Hosts=%s" % \
(conf['as-num'], conf['as-str'], conf['as-mask'], \
conf['megabytes'], conf['num-hosts'])
# p.xrange = (0, ceil(max_cost))
p.xticks = (0, 10)
# p.yticks = (0, 1)
#p.yrange = (0, (ceil(amax(data[:,1]) / 100) * 100))
ymax = amax(data[:,1])
p.curves = [curve(histogram=fname, col=2, labels_col=4)]
p.yrange = (1, amax(data[:,1]) + 2)
if ymax > 10000:
p.ylog = True
#print "not implemented yet..."
#return
## plot raw samples
#p.title = "raw decoding cost; input=%s; host=%s" \
# % (conf['file'], conf['host'])
#p.ylabel = "decoding cost (ms)"
#p.xlabel = "frame number"
#p.xrange = (0, len(data))
##p.xticks = (0, 100)
#p.yticks = (0, 1)
#p.yrange = (1, ceil(max_cost) + 2)
#p.curves = [curve(fname=fname, xcol=2, ycol=1, title="decoding cost")]
#### Styling.
if not self.setup_png(p):
p.rounded_caps = True
p.font = 'Helvetica'
p.font_size = '10'
p.size = ('20cm', '10cm')
p.monochrome = False
p.dashed_lines = False
p.key = 'off'
p.default_style = 'points lw 1'
if self.options.smooth:
p.default_style += " smooth bezier"
self.render(p)
def plot_file(self, datafile):
bname = basename(datafile)
name, ext = splitext(bname)
conf = decode(name)
if 'per-host' in conf or 'as-num' in conf:
self.plot_hchisto(datafile, name, conf)
#for plot_type in plotters:
# if plot_type in conf:
# try:
# plotters[plot_type](datafile, name, conf)
# except IOError as err:
# self.err("Skipped '%s' (%s)." % err)
# break
#else:
# self.err("Skipped '%s'; unkown experiment type."
# % bname)
# release all tmp files
self.tmpfiles = []
def default(self, _):
for i, datafile in enumerate(self.args):
self.out("[%d/%d] Processing %s ..." % (i + 1, len(self.args), datafile))
self.plot_file(datafile)
if __name__ == "__main__":
NetsecPlotter().launch()
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