diff options
Diffstat (limited to '')
| -rw-r--r-- | testsuites/tmtests/tmcontext01/plot.py | 104 |
1 files changed, 56 insertions, 48 deletions
diff --git a/testsuites/tmtests/tmcontext01/plot.py b/testsuites/tmtests/tmcontext01/plot.py index 431725c8ba..944a5962c2 100644 --- a/testsuites/tmtests/tmcontext01/plot.py +++ b/testsuites/tmtests/tmcontext01/plot.py @@ -1,51 +1,59 @@ +# SPDX-License-Identifier: BSD-2-Clause + +# Copyright (C) 2014, 2024 embedded brains GmbH & Co. KG # -# Copyright (c) 2014 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 json +import re +import matplotlib.pyplot as plt # type: ignore +from matplotlib import ticker # type: ignore + + +def _plot(data: dict) -> None: + _, axes = plt.subplots() + axes.set_title("Context Switch Timing Test") + axes.set_xlabel("Function Nest Level") + axes.set_ylabel("Context Switch Time [μs]") + x = list(range(0, len(data[0]["stats-by-function-nest-level"]))) + axes.xaxis.set_major_locator(ticker.FixedLocator(x)) + for samples in data: + y = [ + values[2] / 1000.0 + for values in samples["stats-by-function-nest-level"] + ] + axes.plot(x, y, label=samples["environment"], marker='o') + axes.legend(loc='best') + plt.savefig("tmcontext01.png") + plt.savefig("tmcontext01.pdf") + plt.close() + + +_JSON_DATA = re.compile( + r"\*\*\* BEGIN OF JSON DATA \*\*\*(.*)" + r"\*\*\* END OF JSON DATA \*\*\*", re.DOTALL) + +with open("tmcontext01.scn", "r", encoding="utf-8") as src: + match = _JSON_DATA.search(src.read()) + data = json.loads(match.group(1)) -import libxml2 -from libxml2 import xmlNode -import matplotlib.pyplot as plt -doc = libxml2.parseFile("tmcontext01.scn") -ctx = doc.xpathNewContext() - -colors = ['k', 'r', 'b', 'g', 'y', 'm'] - -def plot(y, color, label, first): - n=len(y) - x=range(0, n) - if first: - plt.plot(x, y, color=color, label=label) - else: - plt.plot(x, y, color=color) - -plt.title("context switch timing test") -plt.xlabel('function nest level') -plt.ylabel('context switch time [ns]') - -c = 0 -for e in ["normal", "dirty"]: - first = True - for i in ["Min", "Q1", "Q2", "Q3", "Max"]: - y=map(xmlNode.getContent, ctx.xpathEval("/Test/ContextSwitchTest[@environment='" + e + "' and not(@load)]/Sample/" + i)) - plot(y, colors[c], e, first) - first = False - c = c + 1 -load = 1 -while load > 0: - first = True - for i in ["Min", "Q1", "Q2", "Q3", "Max"]: - y=map(xmlNode.getContent, ctx.xpathEval("/Test/ContextSwitchTest[@environment='dirty' and @load='" + str(load) + "']/Sample/" + i)) - if len(y) > 0: - plot(y, colors[c], "load " + str(load), first) - first = False - else: - load = 0 - if load > 0: - load = load + 1 - c = c + 1 -plt.legend() -plt.show() +_plot(data) |