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#!/usr/bin/env python
"""
This script parses logs/bench.log and create plots for each case with
the timings function of time (date plot). It also creates a web page
index.html for easy viewing of the generated plots.
"""
# Copyright (C) 2010 Johannes Ring
#
# This file is part of DOLFIN.
#
# DOLFIN is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# DOLFIN is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with DOLFIN. If not, see <http://www.gnu.org/licenses/>.
#
# First added: 2010-04-06
# Last changed: 2010-04-13
import os
import re
import time
import datetime
import textwrap
import numpy
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
# Change some of the default Matplotlib parameters
plt.rcParams.update({'figure.figsize': [6, 4],
'font.size' : 10,
'axes.labelsize' : 10,
'axes.grid': True,
'text.fontsize' : 10,
'legend.fontsize' : 8,
'xtick.labelsize' : 8,
'ytick.labelsize' : 8,
})
# Write to web page index.html
outfile = open("index.html", "w")
outfile.write("<h1><big>DOLFIN Benchmarks</big></h1>\n")
outfile.write("Last updated: %s.\n\n" % time.asctime())
# Open and read in logs/bench.log
benchlog = "logs/bench.log"
lines = open(benchlog, 'r').readlines()
benchmarks = {}
pattern = "\((.*)\)\s+(.*)\s+(.*)\s+\"(.*)\""
# Extract data from logfile
print "Parsing %s..." % benchlog
for line in lines:
match = re.search(pattern, line)
if match:
year, month, day, hour, minute, second = \
[int(i) for i in match.group(1).split(',')]
#date = datetime.datetime(year, month, day, hour, minute, second)
date = datetime.date(year, month, day)
name = match.group(2)
elapsed_time = float(match.group(3))
description = match.group(4)
if not name in benchmarks:
benchmarks[name] = [[date], [elapsed_time], description]
else:
benchmarks[name][0].append(date)
benchmarks[name][1].append(elapsed_time)
# Open and read in logs/milestones.log
milestones = []
milestoneslog = "logs/milestones.log"
if os.path.isfile(milestoneslog):
lines = open(milestoneslog, 'r').readlines()
for line in lines:
date = datetime.datetime.strptime(line.split()[0], "%Y-%m-%d")
progname = ' '.join(line.split()[1:])
milestones.append([date, progname])
# Get Matplotlib line markers for use later
markers = []
for m in plt.Line2D.markers:
try:
if len(m) == 1 and m != ' ':
markers.append(m)
except TypeError:
pass
year = datetime.timedelta(days=365)
month = datetime.timedelta(days=30)
week = datetime.timedelta(days=7)
today = datetime.date.today()
lasts = ['week', 'month', 'year', 'five years']
locators = [mdates.DayLocator(), mdates.DayLocator(interval=2),
mdates.MonthLocator(), mdates.YearLocator()]
date_fmts = ['%Y-%m-%d', '%d %b', '%b %Y', '%Y']
xmins = [today - week, today - month, today - year, today - 5*year]
outfile.write("<h2>All benchmarks</h2><p>\n")
outfile.write("<center>\n")
outfile.write("<table border=\"0\">\n")
def get_maxtime(dates, min_date, max_date, run_timings):
"""Return the maximum time between min_date and max_date"""
max_time = 0
for i, date in enumerate(dates):
if date < min_date:
continue
elif date > max_date:
break
else:
if max_time < run_timings[i]:
max_time = run_timings[i]
return max_time
# Create normalized plots with all benchmarks in same plot for
# last week, last month, last year, and last five years
print "Generating plots for all benchmarks..."
for last, locator, date_fmt, xmin in zip(lasts, locators, date_fmts, xmins):
fig = plt.figure()
ax = fig.gca()
num = 0
ymax = 0
for benchmark, values in benchmarks.items():
num += 1
dates = values[0]
run_timings = values[1]/numpy.linalg.norm(values[1])
ax.plot(dates, run_timings,
marker=markers[num % len(markers)], markersize=3,
label=benchmark)
ax.hold(True)
maxtime = get_maxtime(dates, xmin, today, run_timings)
if maxtime > ymax:
ymax = maxtime
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(mdates.DateFormatter(date_fmt))
ax.set_xlim(xmin, today)
ax.set_ylim(0, ymax)
# Add milestones to plot
for milestone in milestones:
milestone_num = mdates.date2num(milestone[0])
ax.annotate(milestone[1], xy=(milestone_num, 0.1E-10),
xycoords='data', xytext=(0, 30),
textcoords='offset points',
horizontalalignment='center',
verticalalignment='bottom',
style='italic', fontsize=6,
alpha=0.7, rotation='vertical',
arrowprops=dict(arrowstyle="->", alpha=0.3)
)
lgd = plt.legend(loc='best')
fig.autofmt_xdate()
plt.title("All benchmarks (last %s)" % last)
filename = "all_last_%s.png" % last.replace(' ', '_')
plt.savefig(filename, facecolor='#eeeeee')
# Add plots to web page
if last in ['week', 'year']:
outfile.write(" <tr><td><img src=\"%s\" /></td>\n" % filename)
else:
outfile.write(" <td><img src=\"%s\" /></td></tr>\n" % filename)
outfile.write("</table>\n")
outfile.write("</center>\n")
# Now create separate plots for every benchmark
for benchmark, values in benchmarks.items():
print "Generating plots for %s..." % benchmark
outfile.write("<h2>%s</h2><p>\n" % benchmark)
outfile.write("<center>\n")
outfile.write("<table border=\"0\">\n")
dates = values[0]
run_timings = values[1]
description = values[2]
# Wrap the lines in the description
description = textwrap.fill(description, width=30)
# Create plots for last week, last month, last year, and last five years
for last, locator, date_fmt, xmin in zip(lasts, locators, date_fmts, xmins):
fig = plt.figure()
ax = fig.gca()
ax.plot(dates, run_timings, marker='o', markersize=3)
ax.set_ylabel("time (seconds)")
maxtime = get_maxtime(dates, xmin, today, run_timings)
ax.set_ylim(0, maxtime + maxtime/2)
ax.legend((description,), loc='best')
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(mdates.DateFormatter(date_fmt))
ax.set_xlim(xmin, today)
# Add milestones to plot
for milestone in milestones:
milestone_num = mdates.date2num(milestone[0])
ax.annotate(milestone[1], xy=(milestone_num, 0.1E-10),
xycoords='data', xytext=(0, 30),
textcoords='offset points',
horizontalalignment='center',
verticalalignment='bottom',
style='italic', fontsize=6,
alpha=0.7, rotation='vertical',
arrowprops=dict(arrowstyle="->", alpha=0.3)
)
fig.autofmt_xdate()
plt.title("%s (last %s)" % (benchmark, last))
filename = "%s_last_%s.png" % (benchmark, last.replace(' ', '_'))
plt.savefig(filename, facecolor='#eeeeee')
# Add plots to web page
if last in ['week', 'year']:
outfile.write(" <tr><td><img src=\"%s\" /></td>\n" % filename)
else:
outfile.write(" <td><img src=\"%s\" /></td></tr>\n" % filename)
outfile.write("</table>\n")
outfile.write("</center>\n")
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