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