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# Copyright 2017 The PDFium Authors
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Classes that draw conclusions out of a comparison and represent them."""
from collections import Counter
FORMAT_RED = '\033[01;31m{0}\033[00m'
FORMAT_GREEN = '\033[01;32m{0}\033[00m'
FORMAT_MAGENTA = '\033[01;35m{0}\033[00m'
FORMAT_CYAN = '\033[01;36m{0}\033[00m'
FORMAT_NORMAL = '{0}'
RATING_FAILURE = 'failure'
RATING_REGRESSION = 'regression'
RATING_IMPROVEMENT = 'improvement'
RATING_NO_CHANGE = 'no_change'
RATING_SMALL_CHANGE = 'small_change'
RATINGS = [
RATING_FAILURE, RATING_REGRESSION, RATING_IMPROVEMENT, RATING_NO_CHANGE,
RATING_SMALL_CHANGE
]
RATING_TO_COLOR = {
RATING_FAILURE: FORMAT_MAGENTA,
RATING_REGRESSION: FORMAT_RED,
RATING_IMPROVEMENT: FORMAT_CYAN,
RATING_NO_CHANGE: FORMAT_GREEN,
RATING_SMALL_CHANGE: FORMAT_NORMAL,
}
class ComparisonConclusions:
"""All conclusions drawn from a comparison.
This is initialized empty and then processes pairs of results for each test
case, determining the rating for that case, which can be:
"failure" if either or both runs for the case failed.
"regression" if there is a significant increase in time for the test case.
"improvement" if there is a significant decrease in time for the test case.
"no_change" if the time for the test case did not change at all.
"small_change" if the time for the test case changed but within the threshold.
"""
def __init__(self, threshold_significant):
"""Initializes an empty ComparisonConclusions.
Args:
threshold_significant: Float with the tolerance beyond which changes in
measurements are considered significant.
The change is considered as a multiplication rather than an addition
of a fraction of the previous measurement, that is, a
threshold_significant of 1.0 will flag test cases that became over
100% slower (> 200% of the previous time measured) or over 100% faster
(< 50% of the previous time measured).
threshold_significant 0.02 -> 98.04% to 102% is not significant
threshold_significant 0.1 -> 90.9% to 110% is not significant
threshold_significant 0.25 -> 80% to 125% is not significant
threshold_significant 1 -> 50% to 200% is not significant
threshold_significant 4 -> 20% to 500% is not significant
"""
self.threshold_significant = threshold_significant
self.threshold_significant_negative = (1 / (1 + threshold_significant)) - 1
self.params = {'threshold': threshold_significant}
self.summary = ComparisonSummary()
self.case_results = {}
def ProcessCase(self, case_name, before, after):
"""Feeds a test case results to the ComparisonConclusions.
Args:
case_name: String identifying the case.
before: Measurement for the "before" version of the code.
after: Measurement for the "after" version of the code.
"""
# Switch 0 to None to simplify the json dict output. All zeros are
# considered failed runs, so they will be represented by "null".
if not before:
before = None
if not after:
after = None
if not before or not after:
ratio = None
rating = RATING_FAILURE
else:
ratio = (float(after) / before) - 1.0
if ratio > self.threshold_significant:
rating = RATING_REGRESSION
elif ratio < self.threshold_significant_negative:
rating = RATING_IMPROVEMENT
elif ratio == 0:
rating = RATING_NO_CHANGE
else:
rating = RATING_SMALL_CHANGE
case_result = CaseResult(case_name, before, after, ratio, rating)
self.summary.ProcessCaseResult(case_result)
self.case_results[case_name] = case_result
def GetSummary(self):
"""Gets the ComparisonSummary with consolidated totals."""
return self.summary
def GetCaseResults(self):
"""Gets a dict mapping each test case identifier to its CaseResult."""
return self.case_results
def GetOutputDict(self):
"""Returns a conclusions dict with all the conclusions drawn.
Returns:
A serializable dict with the format illustrated below:
{
"version": 1,
"params": {
"threshold": 0.02
},
"summary": {
"total": 123,
"failure": 1,
"regression": 2,
"improvement": 1,
"no_change": 100,
"small_change": 19
},
"comparison_by_case": {
"testing/resources/new_test.pdf": {
"before": None,
"after": 1000,
"ratio": None,
"rating": "failure"
},
"testing/resources/test1.pdf": {
"before": 100,
"after": 120,
"ratio": 0.2,
"rating": "regression"
},
"testing/resources/test2.pdf": {
"before": 100,
"after": 2000,
"ratio": 19.0,
"rating": "regression"
},
"testing/resources/test3.pdf": {
"before": 1000,
"after": 1005,
"ratio": 0.005,
"rating": "small_change"
},
"testing/resources/test4.pdf": {
"before": 1000,
"after": 1000,
"ratio": 0.0,
"rating": "no_change"
},
"testing/resources/test5.pdf": {
"before": 1000,
"after": 600,
"ratio": -0.4,
"rating": "improvement"
}
}
}
"""
output_dict = {}
output_dict['version'] = 1
output_dict['params'] = {'threshold': self.threshold_significant}
output_dict['summary'] = self.summary.GetOutputDict()
output_dict['comparison_by_case'] = {
cr.case_name.decode('utf-8'): cr.GetOutputDict()
for cr in self.GetCaseResults().values()
}
return output_dict
class ComparisonSummary:
"""Totals computed for a comparison."""
def __init__(self):
self.rating_counter = Counter()
def ProcessCaseResult(self, case_result):
self.rating_counter[case_result.rating] += 1
def GetTotal(self):
"""Gets the number of test cases processed."""
return sum(self.rating_counter.values())
def GetCount(self, rating):
"""Gets the number of test cases processed with a given rating."""
return self.rating_counter[rating]
def GetOutputDict(self):
"""Returns a dict that can be serialized with all the totals."""
result = {'total': self.GetTotal()}
for rating in RATINGS:
result[rating] = self.GetCount(rating)
return result
class CaseResult:
"""The conclusion for the comparison of a single test case."""
def __init__(self, case_name, before, after, ratio, rating):
"""Initializes an empty ComparisonConclusions.
Args:
case_name: String identifying the case.
before: Measurement for the "before" version of the code.
after: Measurement for the "after" version of the code.
ratio: Difference between |after| and |before| as a fraction of |before|.
rating: Rating for this test case.
"""
self.case_name = case_name
self.before = before
self.after = after
self.ratio = ratio
self.rating = rating
def GetOutputDict(self):
"""Returns a dict with the test case's conclusions."""
return {
'before': self.before,
'after': self.after,
'ratio': self.ratio,
'rating': self.rating
}
def PrintConclusionsDictHumanReadable(conclusions_dict, colored, key=None):
"""Prints a conclusions dict in a human-readable way.
Args:
conclusions_dict: Dict to print.
colored: Whether to color the output to highlight significant changes.
key: String with the CaseResult dictionary key to sort the cases.
"""
# Print header
print('=' * 80)
print('{0:>11s} {1:>15s} {2}'.format('% Change', 'Time after', 'Test case'))
print('-' * 80)
color = FORMAT_NORMAL
# Print cases
if key is not None:
case_pairs = sorted(
conclusions_dict['comparison_by_case'].iteritems(),
key=lambda kv: kv[1][key])
else:
case_pairs = sorted(conclusions_dict['comparison_by_case'].iteritems())
for case_name, case_dict in case_pairs:
if colored:
color = RATING_TO_COLOR[case_dict['rating']]
if case_dict['rating'] == RATING_FAILURE:
print(u'{} to measure time for {}'.format(
color.format('Failed'), case_name).encode('utf-8'))
continue
print(u'{0} {1:15,d} {2}'.format(
color.format('{:+11.4%}'.format(case_dict['ratio'])),
case_dict['after'], case_name).encode('utf-8'))
# Print totals
totals = conclusions_dict['summary']
print('=' * 80)
print('Test cases run: %d' % totals['total'])
if colored:
color = FORMAT_MAGENTA if totals[RATING_FAILURE] else FORMAT_GREEN
print('Failed to measure: %s' % color.format(totals[RATING_FAILURE]))
if colored:
color = FORMAT_RED if totals[RATING_REGRESSION] else FORMAT_GREEN
print('Regressions: %s' % color.format(totals[RATING_REGRESSION]))
if colored:
color = FORMAT_CYAN if totals[RATING_IMPROVEMENT] else FORMAT_GREEN
print('Improvements: %s' % color.format(totals[RATING_IMPROVEMENT]))