diff options
Diffstat (limited to 'testsuites/smptests/smplock01/smplock01fair.py')
| -rwxr-xr-x | testsuites/smptests/smplock01/smplock01fair.py | 118 |
1 files changed, 65 insertions, 53 deletions
diff --git a/testsuites/smptests/smplock01/smplock01fair.py b/testsuites/smptests/smplock01/smplock01fair.py index 378dfd8028..a3851ad4c6 100755 --- a/testsuites/smptests/smplock01/smplock01fair.py +++ b/testsuites/smptests/smplock01/smplock01fair.py @@ -1,59 +1,71 @@ -#!/usr/bin/env python +# SPDX-License-Identifier: BSD-2-Clause +# Copyright (C) 2016, 2024 embedded brains GmbH & Co. KG # -# Copyright (c) 2016 embedded brains GmbH. All rights reserved. -# -# The license and distribution terms for this file may be -# found in the file LICENSE in this distribution or at -# http://www.rtems.org/license/LICENSE. +# 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 +import json import math +import re import statistics -from libxml2 import xmlNode -import matplotlib.pyplot as plt -data = open('smplock01.scn').read() -data = re.sub(r'\*\*\*.*\*\*\*', '', data) -doc = libxml2.parseDoc(data) -ctx = doc.xpathNewContext() - -plt.title('SMP Lock Fairness') -plt.xlabel('Active Workers') -plt.ylabel('Normed Coefficient of Variation') - -i = 1 -ticket = [] -mcs = [] -tas = [] -ttas = [] - -def m(n): - return int(xmlNode.getContent(n)) - -def normedCoefficientOfVariation(name, i): - y = map(m, ctx.xpathEval('/SMPLock01/' + name + '[@activeWorker=' + str(i) + ']/LocalCounter')) - if len(y) == 0: - raise - return (statistics.stdev(y) / statistics.mean(y)) / math.sqrt(len(y)) - -try: - while True: - i = i + 1 - ticket.append(normedCoefficientOfVariation('GlobalTicketLockWithLocalCounter', i)) - mcs.append(normedCoefficientOfVariation('GlobalMCSLockWithLocalCounter', i)) - tas.append(normedCoefficientOfVariation('GlobalTASLockWithLocalCounter', i)) - ttas.append(normedCoefficientOfVariation('GlobalTTASLockWithLocalCounter', i)) -except: - pass - -x = range(2, len(ticket) + 2) -plt.xticks(x) -plt.yscale('symlog', linthreshy = 1e-6) -plt.plot(x, ticket, label = 'Ticket Lock', marker = 'o') -plt.plot(x, mcs, label = 'MCS Lock', marker = 'o') -plt.plot(x, tas, label = 'TAS Lock', marker = 'o') -plt.plot(x, ttas, label = 'TTAS Lock', marker = 'o') -plt.legend(loc = 'best') -plt.show() +import matplotlib.pyplot as plt # type: ignore +from matplotlib import ticker # type: ignore + + +def _normed_coefficient_of_variation(counter: list[int]) -> float: + return (statistics.stdev(counter) / statistics.mean(counter)) / math.sqrt( + len(counter)) + + +def _plot(data: dict) -> None: + _, axes = plt.subplots() + axes.set_title("SMP Lock Fairness") + axes.set_xlabel("Active Workers") + axes.set_ylabel("Normed Coefficient of Variation") + axes.set_yscale("symlog", linthresh=1e-6) + x = list(range(2, len(data[0]["results"]) + 1)) + axes.xaxis.set_major_locator(ticker.FixedLocator(x)) + for samples in data: + if samples["lock-object"] != "global": + continue + if samples["section-type"] != "local counter": + continue + y = [ + _normed_coefficient_of_variation(results["counter"]) + for results in samples["results"][1:] + ] + axes.plot(x, y, label=samples["lock-type"], marker="o") + axes.legend(loc="best") + plt.savefig("smplock01fair.png") + plt.savefig("smplock01fair.pdf") + plt.close() + + +_JSON_DATA = re.compile( + r"\*\*\* BEGIN OF JSON DATA \*\*\*(.*)" + r"\*\*\* END OF JSON DATA \*\*\*", re.DOTALL) + +with open("smplock01.scn", "r", encoding="utf-8") as src: + match = _JSON_DATA.search(src.read()) + data = json.loads(match.group(1)) + +_plot(data) |