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201 lines
6.6 KiB
Python
201 lines
6.6 KiB
Python
# Copyright 2013 The Chromium Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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import re
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import sys
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import json
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import logging
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import math
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import perf_result_data_type
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# Mapping from result type to test output
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RESULT_TYPES = {perf_result_data_type.UNIMPORTANT: 'RESULT ',
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perf_result_data_type.DEFAULT: '*RESULT ',
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perf_result_data_type.INFORMATIONAL: '',
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perf_result_data_type.UNIMPORTANT_HISTOGRAM: 'HISTOGRAM ',
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perf_result_data_type.HISTOGRAM: '*HISTOGRAM '}
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def _EscapePerfResult(s):
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"""Escapes |s| for use in a perf result."""
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return re.sub('[\:|=/#&,]', '_', s)
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def FlattenList(values):
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"""Returns a simple list without sub-lists."""
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ret = []
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for entry in values:
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if isinstance(entry, list):
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ret.extend(FlattenList(entry))
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else:
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ret.append(entry)
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return ret
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def GeomMeanAndStdDevFromHistogram(histogram_json):
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histogram = json.loads(histogram_json)
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# Handle empty histograms gracefully.
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if not 'buckets' in histogram:
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return 0.0, 0.0
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count = 0
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sum_of_logs = 0
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for bucket in histogram['buckets']:
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if 'high' in bucket:
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bucket['mean'] = (bucket['low'] + bucket['high']) / 2.0
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else:
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bucket['mean'] = bucket['low']
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if bucket['mean'] > 0:
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sum_of_logs += math.log(bucket['mean']) * bucket['count']
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count += bucket['count']
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if count == 0:
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return 0.0, 0.0
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sum_of_squares = 0
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geom_mean = math.exp(sum_of_logs / count)
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for bucket in histogram['buckets']:
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if bucket['mean'] > 0:
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sum_of_squares += (bucket['mean'] - geom_mean) ** 2 * bucket['count']
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return geom_mean, math.sqrt(sum_of_squares / count)
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def _ValueToString(v):
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# Special case for floats so we don't print using scientific notation.
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if isinstance(v, float):
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return '%f' % v
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else:
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return str(v)
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def _MeanAndStdDevFromList(values):
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avg = None
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sd = None
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if len(values) > 1:
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try:
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value = '[%s]' % ','.join([_ValueToString(v) for v in values])
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avg = sum([float(v) for v in values]) / len(values)
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sqdiffs = [(float(v) - avg) ** 2 for v in values]
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variance = sum(sqdiffs) / (len(values) - 1)
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sd = math.sqrt(variance)
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except ValueError:
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value = ', '.join(values)
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else:
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value = values[0]
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return value, avg, sd
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def PrintPages(page_list):
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"""Prints list of pages to stdout in the format required by perf tests."""
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print 'Pages: [%s]' % ','.join([_EscapePerfResult(p) for p in page_list])
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def PrintPerfResult(measurement, trace, values, units,
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result_type=perf_result_data_type.DEFAULT,
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print_to_stdout=True):
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"""Prints numerical data to stdout in the format required by perf tests.
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The string args may be empty but they must not contain any colons (:) or
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equals signs (=).
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This is parsed by the buildbot using:
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http://src.chromium.org/viewvc/chrome/trunk/tools/build/scripts/slave/process_log_utils.py
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Args:
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measurement: A description of the quantity being measured, e.g. "vm_peak".
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On the dashboard, this maps to a particular graph. Mandatory.
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trace: A description of the particular data point, e.g. "reference".
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On the dashboard, this maps to a particular "line" in the graph.
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Mandatory.
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values: A list of numeric measured values. An N-dimensional list will be
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flattened and treated as a simple list.
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units: A description of the units of measure, e.g. "bytes".
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result_type: Accepts values of perf_result_data_type.ALL_TYPES.
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print_to_stdout: If True, prints the output in stdout instead of returning
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the output to caller.
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Returns:
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String of the formated perf result.
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"""
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assert perf_result_data_type.IsValidType(result_type), \
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'result type: %s is invalid' % result_type
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trace_name = _EscapePerfResult(trace)
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if (result_type == perf_result_data_type.UNIMPORTANT or
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result_type == perf_result_data_type.DEFAULT or
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result_type == perf_result_data_type.INFORMATIONAL):
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assert isinstance(values, list)
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assert '/' not in measurement
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flattened_values = FlattenList(values)
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assert len(flattened_values)
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value, avg, sd = _MeanAndStdDevFromList(flattened_values)
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output = '%s%s: %s%s%s %s' % (
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RESULT_TYPES[result_type],
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_EscapePerfResult(measurement),
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trace_name,
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# Do not show equal sign if the trace is empty. Usually it happens when
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# measurement is enough clear to describe the result.
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'= ' if trace_name else '',
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value,
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units)
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else:
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assert perf_result_data_type.IsHistogram(result_type)
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assert isinstance(values, list)
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# The histograms can only be printed individually, there's no computation
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# across different histograms.
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assert len(values) == 1
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value = values[0]
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output = '%s%s: %s= %s %s' % (
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RESULT_TYPES[result_type],
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_EscapePerfResult(measurement),
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trace_name,
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value,
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units)
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avg, sd = GeomMeanAndStdDevFromHistogram(value)
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if avg:
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output += '\nAvg %s: %f%s' % (measurement, avg, units)
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if sd:
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output += '\nSd %s: %f%s' % (measurement, sd, units)
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if print_to_stdout:
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print output
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sys.stdout.flush()
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return output
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def ReportPerfResult(chart_data, graph_title, trace_title, value, units,
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improvement_direction='down', important=True):
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"""Outputs test results in correct format.
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If chart_data is None, it outputs data in old format. If chart_data is a
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dictionary, formats in chartjson format. If any other format defaults to
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old format.
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Args:
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chart_data: A dictionary corresponding to perf results in the chartjson
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format.
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graph_title: A string containing the name of the chart to add the result
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to.
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trace_title: A string containing the name of the trace within the chart
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to add the result to.
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value: The value of the result being reported.
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units: The units of the value being reported.
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improvement_direction: A string denoting whether higher or lower is
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better for the result. Either 'up' or 'down'.
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important: A boolean denoting whether the result is important or not.
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"""
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if chart_data and isinstance(chart_data, dict):
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chart_data['charts'].setdefault(graph_title, {})
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chart_data['charts'][graph_title][trace_title] = {
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'type': 'scalar',
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'value': value,
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'units': units,
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'improvement_direction': improvement_direction,
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'important': important
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}
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else:
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PrintPerfResult(graph_title, trace_title, [value], units)
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