335 lines
8.9 KiB
Python
335 lines
8.9 KiB
Python
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#!/usr/bin/python2.5
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#
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# Copyright 2009, The Android Open Source Project
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""plot_sdcard: A module to plot the results of an sdcard perf test.
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Requires Gnuplot python v 1.8
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Typical usage:
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-t x axis is time
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-i x axis is iteration
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-p profile data generated by profile_sdcard.sh
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./plot_sdcard.py -t /tmp/data.txt
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./plot_sdcard.py -i /tmp/data.txt
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./plot_sdcard.py -p
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python interpreter
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>>> import plot_sdcard as p
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>>> (metadata, data) = p.Parse('/tmp/data.txt')
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>>> p.PlotIterations(metadata, data)
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>>> p.PlotTimes(metadata, data)
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"""
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import getopt
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from itertools import izip
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import re
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import sys
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import Gnuplot
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import numpy
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class DataSet(object):
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"""Dataset holds the summary and data (time,value pairs)."""
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def __init__(self, line):
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res = re.search(('# StopWatch ([\w]+) total/cumulative '
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'duration ([0-9.]+). Samples: ([0-9]+)'), line)
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self.time = []
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self.data = []
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self.name = res.group(1)
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self.duration = float(res.group(2))
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self.iteration = int(res.group(3))
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self.summary = re.match('([a-z_]+)_total', self.name)
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def __repr__(self):
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return str(zip(self.time, self.data))
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def Add(self, time, value):
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self.time.append(time)
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self.data.append(value)
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def RescaleTo(self, length):
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factor = len(self.data) / length
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if factor > 1:
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new_time = []
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new_data = []
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accum = 0.0
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idx = 1
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for t, d in izip(self.time, self.data):
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accum += d
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if idx % factor == 0:
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new_time.append(t)
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new_data.append(accum / factor)
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accum = 0
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idx += 1
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self.time = new_time
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self.data = new_data
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class Metadata(object):
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def __init__(self):
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self.kernel = ''
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self.command_line = ''
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self.sched = ''
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self.name = ''
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self.fadvise = ''
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self.iterations = 0
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self.duration = 0.0
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self.complete = False
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def Parse(self, line):
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if line.startswith('# Kernel:'):
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self.kernel = re.search('Linux version ([0-9.]+-[^ ]+)', line).group(1)
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elif line.startswith('# Command:'):
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self.command_line = re.search('# Command: [/\w_]+ (.*)', line).group(1)
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self.command_line = self.command_line.replace(' --', '-')
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self.command_line = self.command_line.replace(' -d', '')
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self.command_line = self.command_line.replace('--test=', '')
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elif line.startswith('# Iterations'):
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self.iterations = int(re.search('# Iterations: ([0-9]+)', line).group(1))
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elif line.startswith('# Fadvise'):
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self.fadvise = re.search('# Fadvise: ([\w]+)', line).group(1)
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elif line.startswith('# Sched'):
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self.sched = re.search('# Sched features: ([\w]+)', line).group(1)
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self.complete = True
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def AsTitle(self):
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return '%s-duration:%f\\n-%s\\n%s' % (
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self.kernel, self.duration, self.command_line, self.sched)
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def UpdateWith(self, dataset):
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self.duration = max(self.duration, dataset.duration)
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self.name = dataset.name
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def Parse(filename):
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"""Parse a file with the collected data.
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The data must be in 2 rows (x,y).
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Args:
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filename: Full path to the file.
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"""
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f = open(filename, 'r')
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metadata = Metadata()
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data = [] # array of dataset
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dataset = None
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for num, line in enumerate(f):
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try:
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line = line.strip()
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if not line: continue
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if not metadata.complete:
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metadata.Parse(line)
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continue
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if re.match('[a-z_]', line):
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continue
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if line.startswith('# StopWatch'): # Start of a new dataset
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if dataset:
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if dataset.summary:
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metadata.UpdateWith(dataset)
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else:
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data.append(dataset)
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dataset = DataSet(line)
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continue
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if line.startswith('#'):
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continue
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# must be data at this stage
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try:
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(time, value) = line.split(None, 1)
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except ValueError:
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print 'skipping line %d: %s' % (num, line)
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continue
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if dataset and not dataset.summary:
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dataset.Add(float(time), float(value))
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except Exception:
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print 'Error parsing line %d' % num, sys.exc_info()[0]
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raise
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data.append(dataset)
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if not metadata.complete:
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print """Error missing metadata. Did you mount debugfs?
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[adb shell mount -t debugfs none /sys/kernel/debug]"""
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sys.exit(1)
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return (metadata, data)
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def PlotIterations(metadata, data):
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"""Plot the duration of the ops against iteration.
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If you are plotting data with widely different runtimes you probably want to
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use PlotTimes instead.
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For instance when readers and writers are in the same mix, the
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readers will go thru 100 iterations much faster than the
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writers. The load test tries to be smart about that but the final
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iterations of the writers will likely be done w/o any influence from
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the readers.
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Args:
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metadata: For the graph's title.
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data: pair of to be plotted.
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"""
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gp = Gnuplot.Gnuplot(persist=1)
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gp('set data style lines')
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gp.clear()
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gp.xlabel('iterations')
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gp.ylabel('duration in second')
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gp.title(metadata.AsTitle())
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styles = {}
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line_style = 1
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for dataset in data:
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dataset.RescaleTo(metadata.iterations)
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x = numpy.arange(len(dataset.data), dtype='int_')
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if not dataset.name in styles:
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styles[dataset.name] = line_style
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line_style += 1
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d = Gnuplot.Data(x, dataset.data,
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title=dataset.name,
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with_='lines ls %d' % styles[dataset.name])
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else: # no need to repeat a title that exists already.
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d = Gnuplot.Data(x, dataset.data,
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with_='lines ls %d' % styles[dataset.name])
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gp.replot(d)
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gp.hardcopy('/tmp/%s-%s-%f.png' %
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(metadata.name, metadata.kernel, metadata.duration),
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terminal='png')
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def PlotTimes(metadata, data):
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"""Plot the duration of the ops against time elapsed.
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Args:
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metadata: For the graph's title.
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data: pair of to be plotted.
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"""
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gp = Gnuplot.Gnuplot(persist=1)
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gp('set data style impulses')
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gp('set xtics 1')
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gp.clear()
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gp.xlabel('seconds')
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gp.ylabel('duration in second')
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gp.title(metadata.AsTitle())
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styles = {}
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line_style = 1
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for dataset in data:
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x = numpy.array(dataset.time, dtype='float_')
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if not dataset.name in styles:
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styles[dataset.name] = line_style
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line_style += 1
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d = Gnuplot.Data(x, dataset.data,
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title=dataset.name,
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with_='impulses ls %d' % styles[dataset.name])
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else: # no need to repeat a title that exists already.
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d = Gnuplot.Data(x, dataset.data,
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with_='impulses ls %d' % styles[dataset.name])
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gp.replot(d)
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gp.hardcopy('/tmp/%s-%s-%f.png' %
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(metadata.name, metadata.kernel, metadata.duration),
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terminal='png')
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def PlotProfile():
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"""Plot the time of a run against the number of processes."""
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(metadata, data) = Parse('/tmp/sdcard-scalability.txt')
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gp = Gnuplot.Gnuplot(persist=1)
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gp('set data style impulses')
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gp('set xtics 1')
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gp('set pointsize 2')
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gp.clear()
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gp.xlabel('writer process')
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gp.ylabel('duration in second')
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gp.title(metadata.AsTitle())
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dataset = data[0]
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x = numpy.array(dataset.time, dtype='int_')
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d = Gnuplot.Data(x, dataset.data,
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title=dataset.name,
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with_='linespoints')
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gp.replot(d)
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gp.hardcopy('/tmp/%s-%s-%f.png' %
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(metadata.name, metadata.kernel, metadata.duration),
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terminal='png')
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def Usage():
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"""Print this module's usage."""
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print """
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To plot the result using the iter number of the x axis:
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plot_sdcard.py -i /tmp/data.txt
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To plot the result using time for the x axis:
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plot_sdcard.py -t /tmp/data.txt
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To plot the result from the profiler:
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profile_sdcard.sh
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plot_sdcard.py -p
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"""
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sys.exit(2)
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def main(argv):
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try:
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(optlist, args) = getopt.getopt(argv[1:],
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'itp', ['iteration', 'time', 'profile'])
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except getopt.GetoptError, err:
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print str(err)
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Usage()
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for flag, val in optlist:
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if flag in ('-i', '--iteration'):
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(metadata, data) = Parse(args[0])
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PlotIterations(metadata, data)
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sys.exit(0)
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elif flag in ('-t', '--time'):
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(metadata, data) = Parse(args[0])
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PlotTimes(metadata, data)
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sys.exit(0)
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elif flag in ('-p', '--profile'):
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PlotProfile()
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sys.exit(0)
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Usage()
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if __name__ == '__main__':
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if Gnuplot.__version__ != "1.8":
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print "Gnuplot should be 1.8. See REAME file"
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sys.exit(2)
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main(sys.argv)
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