#!/usr/bin/env python
# SPDX-License-Identifier: BSD-2-Clause
#
# Copyright (c) 2017 embedded brains GmbH. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
import re
import libxml2
from libxml2 import xmlNode
import matplotlib.pyplot as plt
data = open('smpopenmp01.scn').read()
data = re.sub(r'\*\*\*.*', '', data)
doc = libxml2.parseDoc(data)
ctx = doc.xpathNewContext()
plt.title('OpenMP Microbench')
plt.xlabel('Number of Threads')
plt.ylabel('Relative Duration')
def m(n):
return float(n.getContent())
def p(bench):
d = map(m, ctx.xpathEval('/SMPOpenMP01/Microbench/' + bench))
y = [x / d[0] for x in d]
x = range(1, len(y) + 1)
plt.xticks(x)
plt.plot(x, y, label = bench, marker = 'o')
p('BarrierBench')
p('ParallelBench')
p('StaticBench')
p('DynamicBench')
p('GuidedBench')
p('RuntimeBench')
p('SingleBench')
plt.legend(loc = 'best')
plt.show()
