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#!/usr/bin/env python
import sys
import optparse
from plot import Plot
from gnuplot import curve
COLS = {'beta-mean': 0,
'rel-rt-max-b': 1,
'rel-rt-mean-b': 2,
'misses-b': 3,
'new-misses-b': 4,
'rel-rt-max-c': 5,
'rel-rt-mean-c': 6,
'misses-c': 7,
'new-misses-c': 8,
'mean-misses-c': 9,
'miss-ratio-b': 10,
'miss-ratio-c': 11}
def parse_args():
p = optparse.OptionParser(description='make graphs')
p.add_option('--paper', dest='paper', action='store_true', default=False)
return p.parse_args()
def col(key):
"""Get the column in the data set."""
return COLS[key]
def g_col(key):
"""Gnuplot is 1-indexed."""
return 1 + col(key)
def get_y_label(metric):
LABELS = {'rel-rt-max': 'relative response time maximum',
'rel-rt-mean': 'relative response time mean',
'miss-ratio': 'deadline miss ratio'}
return LABELS[metric]
def set_plot_opts(opts, p):
p.rounded_caps = True
p.font = 'Helvetica'
if opts.paper:
ext = 'pdf'
p.size = ('8.5cm', '5.25cm')
line_width = 1.5
point_size = 0.3
p.font_size = '5pt'
else:
ext = 'png'
p.size = (1024, 768)
line_width = 3.0
point_size = 1.5
p.font_size = 'font "/usr/share/fonts/truetype/ttf-dejavu/DejaVuSans.ttf" 18'
p.output = '{0}.{1}'.format(p.output, ext)
p.format = ext
p.default_style = 'linespoints lw 2.5'
p.default_style += ' smooth bezier'
p.monochrome = False
p.ylog = True
p.key = 'off'
p.line_styles = [
(1, "lw {0} ps {1}".format(line_width, point_size)),
(2, "lw {0} ps {1}".format(line_width, point_size)),
(3, "lw {0} ps {1}".format(line_width, point_size)),
(4, "lw {0} ps {1}".format(line_width, point_size))]
for i, c in enumerate(p.curves):
c.style = "linespoints ls %d" % (i + 1)
def plot_metric(opts, dat_dir, metric, coin_prob, xr=None, for_jim=False):
"""Plot metric for each level, enforcement pair at the specified
probability.
"""
# each coin value gets a plot
p = Plot()
p.output = '{0}/beta-exp-metric={1}-prob={2}'.format(
dat_dir, metric, str(coin_prob).replace('.', ''))
if xr is not None:
p.output = '{0}_zoom=1'.format(p.output)
if for_jim:
p.output = '{0}-forjim=1'.format(p.output)
for (level, enforcement) in [(l, e) for l in ('c', 'b') for e in (1, 0)]:
fname = '{0}/beta_be={1}_prob={2}.csv'.format(dat_dir, enforcement, coin_prob)
ycol = g_col('{0}-{1}'.format(metric, level))
if enforcement == 1:
ti ='{0} {1}'.format(level.upper(), 'enforcement')
else:
ti ='{0} {1}'.format(level.upper(), 'no enforcement')
c = curve(fname=fname, xcol=g_col('beta-mean'), ycol=ycol, title=ti)
p.curves += [c]
p.xlabel = 'beta mean with probability {0}'.format(coin_prob)
p.ylabel = get_y_label(metric)
set_plot_opts(opts, p)
if xr is not None:
p.xrange = xr
# special formatting cases
if -1 != metric.find('ratio'):
p.ylog = False
p.yrange = (-0.01, 1.01)
if (metric == 'rel-rt-mean' and coin_prob == 0.1 and xr is None):
p.key = 'at 1, 100'
if for_jim:
p.title = 'relative response time mean, 10% abberant'
p.key = 'top left'
if xr is None:
p.key = 'at 1, 10'
p.gnuplot_exec()
def main():
opts, files = parse_args()
if len(files) < 1:
print >>sys.stderr, "missing directory"
sys.exit(1)
data_dir = files[0]
COIN_VALS = [0.1, 0.5]
for coin_val in COIN_VALS:
plot_metric(opts, data_dir, 'rel-rt-mean', coin_val)
plot_metric(opts, data_dir, 'rel-rt-mean', coin_val, xr=(0.02, 0.11))
plot_metric(opts, data_dir, 'miss-ratio', coin_val)
# not in paper
plot_metric(opts, data_dir, 'rel-rt-max', coin_val)
# for jim
plot_metric(opts, data_dir, 'rel-rt-mean', 0.1, for_jim=True)
plot_metric(opts, data_dir, 'rel-rt-mean', 0.1, xr=(0.02, 0.11), for_jim=True)
if __name__ == '__main__':
main()
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