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1201 lines
46 KiB
1201 lines
46 KiB
"""report.py - Utilities for reporting statistics about benchmark results
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"""
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import unittest
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import os
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import re
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import copy
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import random
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from scipy.stats import mannwhitneyu, gmean
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from numpy import array
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class BenchmarkColor(object):
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def __init__(self, name, code):
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self.name = name
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self.code = code
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def __repr__(self):
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return '%s%r' % (self.__class__.__name__,
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(self.name, self.code))
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def __format__(self, format):
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return self.code
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# Benchmark Colors Enumeration
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BC_NONE = BenchmarkColor('NONE', '')
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BC_MAGENTA = BenchmarkColor('MAGENTA', '\033[95m')
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BC_CYAN = BenchmarkColor('CYAN', '\033[96m')
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BC_OKBLUE = BenchmarkColor('OKBLUE', '\033[94m')
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BC_OKGREEN = BenchmarkColor('OKGREEN', '\033[32m')
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BC_HEADER = BenchmarkColor('HEADER', '\033[92m')
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BC_WARNING = BenchmarkColor('WARNING', '\033[93m')
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BC_WHITE = BenchmarkColor('WHITE', '\033[97m')
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BC_FAIL = BenchmarkColor('FAIL', '\033[91m')
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BC_ENDC = BenchmarkColor('ENDC', '\033[0m')
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BC_BOLD = BenchmarkColor('BOLD', '\033[1m')
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BC_UNDERLINE = BenchmarkColor('UNDERLINE', '\033[4m')
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UTEST_MIN_REPETITIONS = 2
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UTEST_OPTIMAL_REPETITIONS = 9 # Lowest reasonable number, More is better.
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UTEST_COL_NAME = "_pvalue"
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_TIME_UNIT_TO_SECONDS_MULTIPLIER = {
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"s": 1.0,
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"ms": 1e-3,
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"us": 1e-6,
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"ns": 1e-9,
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}
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def color_format(use_color, fmt_str, *args, **kwargs):
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"""
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Return the result of 'fmt_str.format(*args, **kwargs)' after transforming
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'args' and 'kwargs' according to the value of 'use_color'. If 'use_color'
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is False then all color codes in 'args' and 'kwargs' are replaced with
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the empty string.
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"""
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assert use_color is True or use_color is False
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if not use_color:
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args = [arg if not isinstance(arg, BenchmarkColor) else BC_NONE
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for arg in args]
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kwargs = {key: arg if not isinstance(arg, BenchmarkColor) else BC_NONE
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for key, arg in kwargs.items()}
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return fmt_str.format(*args, **kwargs)
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def find_longest_name(benchmark_list):
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"""
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Return the length of the longest benchmark name in a given list of
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benchmark JSON objects
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"""
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longest_name = 1
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for bc in benchmark_list:
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if len(bc['name']) > longest_name:
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longest_name = len(bc['name'])
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return longest_name
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def calculate_change(old_val, new_val):
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"""
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Return a float representing the decimal change between old_val and new_val.
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"""
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if old_val == 0 and new_val == 0:
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return 0.0
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if old_val == 0:
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return float(new_val - old_val) / (float(old_val + new_val) / 2)
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return float(new_val - old_val) / abs(old_val)
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def filter_benchmark(json_orig, family, replacement=""):
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"""
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Apply a filter to the json, and only leave the 'family' of benchmarks.
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"""
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regex = re.compile(family)
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filtered = {}
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filtered['benchmarks'] = []
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for be in json_orig['benchmarks']:
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if not regex.search(be['name']):
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continue
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filteredbench = copy.deepcopy(be) # Do NOT modify the old name!
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filteredbench['name'] = regex.sub(replacement, filteredbench['name'])
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filtered['benchmarks'].append(filteredbench)
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return filtered
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def get_unique_benchmark_names(json):
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"""
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While *keeping* the order, give all the unique 'names' used for benchmarks.
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"""
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seen = set()
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uniqued = [x['name'] for x in json['benchmarks']
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if x['name'] not in seen and
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(seen.add(x['name']) or True)]
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return uniqued
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def intersect(list1, list2):
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"""
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Given two lists, get a new list consisting of the elements only contained
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in *both of the input lists*, while preserving the ordering.
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"""
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return [x for x in list1 if x in list2]
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def is_potentially_comparable_benchmark(x):
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return ('time_unit' in x and 'real_time' in x and 'cpu_time' in x)
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def partition_benchmarks(json1, json2):
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"""
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While preserving the ordering, find benchmarks with the same names in
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both of the inputs, and group them.
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(i.e. partition/filter into groups with common name)
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"""
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json1_unique_names = get_unique_benchmark_names(json1)
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json2_unique_names = get_unique_benchmark_names(json2)
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names = intersect(json1_unique_names, json2_unique_names)
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partitions = []
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for name in names:
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time_unit = None
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# Pick the time unit from the first entry of the lhs benchmark.
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# We should be careful not to crash with unexpected input.
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for x in json1['benchmarks']:
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if (x['name'] == name and is_potentially_comparable_benchmark(x)):
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time_unit = x['time_unit']
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break
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if time_unit is None:
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continue
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# Filter by name and time unit.
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# All the repetitions are assumed to be comparable.
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lhs = [x for x in json1['benchmarks'] if x['name'] == name and
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x['time_unit'] == time_unit]
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rhs = [x for x in json2['benchmarks'] if x['name'] == name and
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x['time_unit'] == time_unit]
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partitions.append([lhs, rhs])
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return partitions
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def get_timedelta_field_as_seconds(benchmark, field_name):
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"""
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Get value of field_name field of benchmark, which is time with time unit
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time_unit, as time in seconds.
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"""
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timedelta = benchmark[field_name]
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time_unit = benchmark.get('time_unit', 's')
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return timedelta * _TIME_UNIT_TO_SECONDS_MULTIPLIER.get(time_unit)
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def calculate_geomean(json):
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"""
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Extract all real/cpu times from all the benchmarks as seconds,
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and calculate their geomean.
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"""
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times = []
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for benchmark in json['benchmarks']:
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if 'run_type' in benchmark and benchmark['run_type'] == 'aggregate':
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continue
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times.append([get_timedelta_field_as_seconds(benchmark, 'real_time'),
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get_timedelta_field_as_seconds(benchmark, 'cpu_time')])
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return gmean(times) if times else array([])
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def extract_field(partition, field_name):
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# The count of elements may be different. We want *all* of them.
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lhs = [x[field_name] for x in partition[0]]
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rhs = [x[field_name] for x in partition[1]]
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return [lhs, rhs]
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def calc_utest(timings_cpu, timings_time):
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min_rep_cnt = min(len(timings_time[0]),
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len(timings_time[1]),
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len(timings_cpu[0]),
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len(timings_cpu[1]))
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# Does *everything* has at least UTEST_MIN_REPETITIONS repetitions?
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if min_rep_cnt < UTEST_MIN_REPETITIONS:
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return False, None, None
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time_pvalue = mannwhitneyu(
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timings_time[0], timings_time[1], alternative='two-sided').pvalue
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cpu_pvalue = mannwhitneyu(
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timings_cpu[0], timings_cpu[1], alternative='two-sided').pvalue
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return (min_rep_cnt >= UTEST_OPTIMAL_REPETITIONS), cpu_pvalue, time_pvalue
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def print_utest(bc_name, utest, utest_alpha, first_col_width, use_color=True):
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def get_utest_color(pval):
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return BC_FAIL if pval >= utest_alpha else BC_OKGREEN
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# Check if we failed miserably with minimum required repetitions for utest
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if not utest['have_optimal_repetitions'] and utest['cpu_pvalue'] is None and utest['time_pvalue'] is None:
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return []
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dsc = "U Test, Repetitions: {} vs {}".format(
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utest['nr_of_repetitions'], utest['nr_of_repetitions_other'])
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dsc_color = BC_OKGREEN
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# We still got some results to show but issue a warning about it.
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if not utest['have_optimal_repetitions']:
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dsc_color = BC_WARNING
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dsc += ". WARNING: Results unreliable! {}+ repetitions recommended.".format(
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UTEST_OPTIMAL_REPETITIONS)
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special_str = "{}{:<{}s}{endc}{}{:16.4f}{endc}{}{:16.4f}{endc}{} {}"
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return [color_format(use_color,
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special_str,
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BC_HEADER,
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"{}{}".format(bc_name, UTEST_COL_NAME),
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first_col_width,
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get_utest_color(
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utest['time_pvalue']), utest['time_pvalue'],
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get_utest_color(
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utest['cpu_pvalue']), utest['cpu_pvalue'],
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dsc_color, dsc,
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endc=BC_ENDC)]
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def get_difference_report(
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json1,
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json2,
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utest=False):
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"""
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Calculate and report the difference between each test of two benchmarks
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runs specified as 'json1' and 'json2'. Output is another json containing
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relevant details for each test run.
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"""
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assert utest is True or utest is False
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diff_report = []
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partitions = partition_benchmarks(json1, json2)
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for partition in partitions:
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benchmark_name = partition[0][0]['name']
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label = partition[0][0]['label'] if 'label' in partition[0][0] else ''
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time_unit = partition[0][0]['time_unit']
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measurements = []
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utest_results = {}
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# Careful, we may have different repetition count.
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for i in range(min(len(partition[0]), len(partition[1]))):
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bn = partition[0][i]
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other_bench = partition[1][i]
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measurements.append({
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'real_time': bn['real_time'],
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'cpu_time': bn['cpu_time'],
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'real_time_other': other_bench['real_time'],
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'cpu_time_other': other_bench['cpu_time'],
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'time': calculate_change(bn['real_time'], other_bench['real_time']),
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'cpu': calculate_change(bn['cpu_time'], other_bench['cpu_time'])
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})
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# After processing the whole partition, if requested, do the U test.
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if utest:
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timings_cpu = extract_field(partition, 'cpu_time')
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timings_time = extract_field(partition, 'real_time')
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have_optimal_repetitions, cpu_pvalue, time_pvalue = calc_utest(
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timings_cpu, timings_time)
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if cpu_pvalue and time_pvalue:
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utest_results = {
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'have_optimal_repetitions': have_optimal_repetitions,
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'cpu_pvalue': cpu_pvalue,
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'time_pvalue': time_pvalue,
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'nr_of_repetitions': len(timings_cpu[0]),
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'nr_of_repetitions_other': len(timings_cpu[1])
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}
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# Store only if we had any measurements for given benchmark.
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# E.g. partition_benchmarks will filter out the benchmarks having
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# time units which are not compatible with other time units in the
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# benchmark suite.
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if measurements:
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run_type = partition[0][0]['run_type'] if 'run_type' in partition[0][0] else ''
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aggregate_name = partition[0][0]['aggregate_name'] if run_type == 'aggregate' and 'aggregate_name' in partition[0][0] else ''
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diff_report.append({
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'name': benchmark_name,
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'label': label,
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'measurements': measurements,
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'time_unit': time_unit,
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'run_type': run_type,
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'aggregate_name': aggregate_name,
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'utest': utest_results
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})
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lhs_gmean = calculate_geomean(json1)
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rhs_gmean = calculate_geomean(json2)
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if lhs_gmean.any() and rhs_gmean.any():
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diff_report.append({
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'name': 'OVERALL_GEOMEAN',
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'label': '',
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'measurements': [{
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'real_time': lhs_gmean[0],
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'cpu_time': lhs_gmean[1],
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'real_time_other': rhs_gmean[0],
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'cpu_time_other': rhs_gmean[1],
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'time': calculate_change(lhs_gmean[0], rhs_gmean[0]),
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'cpu': calculate_change(lhs_gmean[1], rhs_gmean[1])
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}],
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'time_unit': 's',
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'run_type': 'aggregate',
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'aggregate_name': 'geomean',
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'utest': {}
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})
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return diff_report
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def print_difference_report(
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json_diff_report,
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include_aggregates_only=False,
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utest=False,
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utest_alpha=0.05,
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use_color=True):
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"""
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Calculate and report the difference between each test of two benchmarks
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runs specified as 'json1' and 'json2'.
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"""
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assert utest is True or utest is False
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def get_color(res):
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if res > 0.05:
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return BC_FAIL
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elif res > -0.07:
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return BC_WHITE
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else:
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return BC_CYAN
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first_col_width = find_longest_name(json_diff_report)
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first_col_width = max(
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first_col_width,
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len('Benchmark'))
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first_col_width += len(UTEST_COL_NAME)
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first_line = "{:<{}s}Time CPU Time Old Time New CPU Old CPU New".format(
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'Benchmark', 12 + first_col_width)
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output_strs = [first_line, '-' * len(first_line)]
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fmt_str = "{}{:<{}s}{endc}{}{:+16.4f}{endc}{}{:+16.4f}{endc}{:14.0f}{:14.0f}{endc}{:14.0f}{:14.0f}"
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for benchmark in json_diff_report:
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# *If* we were asked to only include aggregates,
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# and if it is non-aggregate, then don't print it.
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if not include_aggregates_only or not 'run_type' in benchmark or benchmark['run_type'] == 'aggregate':
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for measurement in benchmark['measurements']:
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output_strs += [color_format(use_color,
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fmt_str,
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BC_HEADER,
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benchmark['name'],
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first_col_width,
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get_color(measurement['time']),
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measurement['time'],
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get_color(measurement['cpu']),
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measurement['cpu'],
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measurement['real_time'],
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measurement['real_time_other'],
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measurement['cpu_time'],
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measurement['cpu_time_other'],
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endc=BC_ENDC)]
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# After processing the measurements, if requested and
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# if applicable (e.g. u-test exists for given benchmark),
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# print the U test.
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if utest and benchmark['utest']:
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output_strs += print_utest(benchmark['name'],
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benchmark['utest'],
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utest_alpha=utest_alpha,
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first_col_width=first_col_width,
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use_color=use_color)
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return output_strs
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###############################################################################
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# Unit tests
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class TestGetUniqueBenchmarkNames(unittest.TestCase):
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def load_results(self):
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import json
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testInputs = os.path.join(
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os.path.dirname(
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os.path.realpath(__file__)),
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'Inputs')
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testOutput = os.path.join(testInputs, 'test3_run0.json')
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with open(testOutput, 'r') as f:
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json = json.load(f)
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return json
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def test_basic(self):
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expect_lines = [
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'BM_One',
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'BM_Two',
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'short', # These two are not sorted
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'medium', # These two are not sorted
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]
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json = self.load_results()
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output_lines = get_unique_benchmark_names(json)
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print("\n")
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print("\n".join(output_lines))
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self.assertEqual(len(output_lines), len(expect_lines))
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for i in range(0, len(output_lines)):
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self.assertEqual(expect_lines[i], output_lines[i])
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|
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|
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class TestReportDifference(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
|
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def load_results():
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import json
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testInputs = os.path.join(
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os.path.dirname(
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os.path.realpath(__file__)),
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'Inputs')
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testOutput1 = os.path.join(testInputs, 'test1_run1.json')
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testOutput2 = os.path.join(testInputs, 'test1_run2.json')
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with open(testOutput1, 'r') as f:
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json1 = json.load(f)
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with open(testOutput2, 'r') as f:
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json2 = json.load(f)
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return json1, json2
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json1, json2 = load_results()
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cls.json_diff_report = get_difference_report(json1, json2)
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|
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def test_json_diff_report_pretty_printing(self):
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expect_lines = [
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['BM_SameTimes', '+0.0000', '+0.0000', '10', '10', '10', '10'],
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['BM_2xFaster', '-0.5000', '-0.5000', '50', '25', '50', '25'],
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['BM_2xSlower', '+1.0000', '+1.0000', '50', '100', '50', '100'],
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['BM_1PercentFaster', '-0.0100', '-0.0100', '100', '99', '100', '99'],
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['BM_1PercentSlower', '+0.0100', '+0.0100', '100', '101', '100', '101'],
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['BM_10PercentFaster', '-0.1000', '-0.1000', '100', '90', '100', '90'],
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['BM_10PercentSlower', '+0.1000', '+0.1000', '100', '110', '100', '110'],
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['BM_100xSlower', '+99.0000', '+99.0000',
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'100', '10000', '100', '10000'],
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['BM_100xFaster', '-0.9900', '-0.9900',
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'10000', '100', '10000', '100'],
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['BM_10PercentCPUToTime', '+0.1000',
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'-0.1000', '100', '110', '100', '90'],
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['BM_ThirdFaster', '-0.3333', '-0.3334', '100', '67', '100', '67'],
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['BM_NotBadTimeUnit', '-0.9000', '+0.2000', '0', '0', '0', '1'],
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['BM_hasLabel', '+0.0000', '+0.0000', '1', '1', '1', '1'],
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['OVERALL_GEOMEAN', '-0.8113', '-0.7779', '0', '0', '0', '0']
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]
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output_lines_with_header = print_difference_report(
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self.json_diff_report, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(len(parts), 7)
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report_output(self):
|
|
expected_output = [
|
|
{
|
|
'name': 'BM_SameTimes',
|
|
'label': '',
|
|
'measurements': [{'time': 0.0000, 'cpu': 0.0000,
|
|
'real_time': 10, 'real_time_other': 10,
|
|
'cpu_time': 10, 'cpu_time_other': 10}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_2xFaster',
|
|
'label': '',
|
|
'measurements': [{'time': -0.5000, 'cpu': -0.5000,
|
|
'real_time': 50, 'real_time_other': 25,
|
|
'cpu_time': 50, 'cpu_time_other': 25}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_2xSlower',
|
|
'label': '',
|
|
'measurements': [{'time': 1.0000, 'cpu': 1.0000,
|
|
'real_time': 50, 'real_time_other': 100,
|
|
'cpu_time': 50, 'cpu_time_other': 100}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_1PercentFaster',
|
|
'label': '',
|
|
'measurements': [{'time': -0.0100, 'cpu': -0.0100,
|
|
'real_time': 100, 'real_time_other': 98.9999999,
|
|
'cpu_time': 100, 'cpu_time_other': 98.9999999}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_1PercentSlower',
|
|
'label': '',
|
|
'measurements': [{'time': 0.0100, 'cpu': 0.0100,
|
|
'real_time': 100, 'real_time_other': 101,
|
|
'cpu_time': 100, 'cpu_time_other': 101}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_10PercentFaster',
|
|
'label': '',
|
|
'measurements': [{'time': -0.1000, 'cpu': -0.1000,
|
|
'real_time': 100, 'real_time_other': 90,
|
|
'cpu_time': 100, 'cpu_time_other': 90}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_10PercentSlower',
|
|
'label': '',
|
|
'measurements': [{'time': 0.1000, 'cpu': 0.1000,
|
|
'real_time': 100, 'real_time_other': 110,
|
|
'cpu_time': 100, 'cpu_time_other': 110}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_100xSlower',
|
|
'label': '',
|
|
'measurements': [{'time': 99.0000, 'cpu': 99.0000,
|
|
'real_time': 100, 'real_time_other': 10000,
|
|
'cpu_time': 100, 'cpu_time_other': 10000}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_100xFaster',
|
|
'label': '',
|
|
'measurements': [{'time': -0.9900, 'cpu': -0.9900,
|
|
'real_time': 10000, 'real_time_other': 100,
|
|
'cpu_time': 10000, 'cpu_time_other': 100}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_10PercentCPUToTime',
|
|
'label': '',
|
|
'measurements': [{'time': 0.1000, 'cpu': -0.1000,
|
|
'real_time': 100, 'real_time_other': 110,
|
|
'cpu_time': 100, 'cpu_time_other': 90}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_ThirdFaster',
|
|
'label': '',
|
|
'measurements': [{'time': -0.3333, 'cpu': -0.3334,
|
|
'real_time': 100, 'real_time_other': 67,
|
|
'cpu_time': 100, 'cpu_time_other': 67}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_NotBadTimeUnit',
|
|
'label': '',
|
|
'measurements': [{'time': -0.9000, 'cpu': 0.2000,
|
|
'real_time': 0.4, 'real_time_other': 0.04,
|
|
'cpu_time': 0.5, 'cpu_time_other': 0.6}],
|
|
'time_unit': 's',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'BM_hasLabel',
|
|
'label': 'a label',
|
|
'measurements': [{'time': 0.0000, 'cpu': 0.0000,
|
|
'real_time': 1, 'real_time_other': 1,
|
|
'cpu_time': 1, 'cpu_time_other': 1}],
|
|
'time_unit': 's',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'OVERALL_GEOMEAN',
|
|
'label': '',
|
|
'measurements': [{'real_time': 3.1622776601683826e-06, 'cpu_time': 3.2130844755623912e-06,
|
|
'real_time_other': 1.9768988699420897e-07, 'cpu_time_other': 2.397447755209533e-07,
|
|
'time': -0.8112976497120911, 'cpu': -0.7778551721181174}],
|
|
'time_unit': 's',
|
|
'run_type': 'aggregate',
|
|
'aggregate_name': 'geomean', 'utest': {}
|
|
},
|
|
]
|
|
self.assertEqual(len(self.json_diff_report), len(expected_output))
|
|
for out, expected in zip(
|
|
self.json_diff_report, expected_output):
|
|
self.assertEqual(out['name'], expected['name'])
|
|
self.assertEqual(out['label'], expected['label'])
|
|
self.assertEqual(out['time_unit'], expected['time_unit'])
|
|
assert_utest(self, out, expected)
|
|
assert_measurements(self, out, expected)
|
|
|
|
|
|
class TestReportDifferenceBetweenFamilies(unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
def load_result():
|
|
import json
|
|
testInputs = os.path.join(
|
|
os.path.dirname(
|
|
os.path.realpath(__file__)),
|
|
'Inputs')
|
|
testOutput = os.path.join(testInputs, 'test2_run.json')
|
|
with open(testOutput, 'r') as f:
|
|
json = json.load(f)
|
|
return json
|
|
|
|
json = load_result()
|
|
json1 = filter_benchmark(json, "BM_Z.ro", ".")
|
|
json2 = filter_benchmark(json, "BM_O.e", ".")
|
|
cls.json_diff_report = get_difference_report(json1, json2)
|
|
|
|
def test_json_diff_report_pretty_printing(self):
|
|
expect_lines = [
|
|
['.', '-0.5000', '-0.5000', '10', '5', '10', '5'],
|
|
['./4', '-0.5000', '-0.5000', '40', '20', '40', '20'],
|
|
['Prefix/.', '-0.5000', '-0.5000', '20', '10', '20', '10'],
|
|
['Prefix/./3', '-0.5000', '-0.5000', '30', '15', '30', '15'],
|
|
['OVERALL_GEOMEAN', '-0.5000', '-0.5000', '0', '0', '0', '0']
|
|
]
|
|
output_lines_with_header = print_difference_report(
|
|
self.json_diff_report, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(len(parts), 7)
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report(self):
|
|
expected_output = [
|
|
{
|
|
'name': u'.',
|
|
'measurements': [{'time': -0.5, 'cpu': -0.5, 'real_time': 10, 'real_time_other': 5, 'cpu_time': 10, 'cpu_time_other': 5}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': u'./4',
|
|
'measurements': [{'time': -0.5, 'cpu': -0.5, 'real_time': 40, 'real_time_other': 20, 'cpu_time': 40, 'cpu_time_other': 20}],
|
|
'time_unit': 'ns',
|
|
'utest': {},
|
|
},
|
|
{
|
|
'name': u'Prefix/.',
|
|
'measurements': [{'time': -0.5, 'cpu': -0.5, 'real_time': 20, 'real_time_other': 10, 'cpu_time': 20, 'cpu_time_other': 10}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': u'Prefix/./3',
|
|
'measurements': [{'time': -0.5, 'cpu': -0.5, 'real_time': 30, 'real_time_other': 15, 'cpu_time': 30, 'cpu_time_other': 15}],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'OVERALL_GEOMEAN',
|
|
'measurements': [{'real_time': 2.213363839400641e-08, 'cpu_time': 2.213363839400641e-08,
|
|
'real_time_other': 1.1066819197003185e-08, 'cpu_time_other': 1.1066819197003185e-08,
|
|
'time': -0.5000000000000009, 'cpu': -0.5000000000000009}],
|
|
'time_unit': 's',
|
|
'run_type': 'aggregate',
|
|
'aggregate_name': 'geomean',
|
|
'utest': {}
|
|
}
|
|
]
|
|
self.assertEqual(len(self.json_diff_report), len(expected_output))
|
|
for out, expected in zip(
|
|
self.json_diff_report, expected_output):
|
|
self.assertEqual(out['name'], expected['name'])
|
|
self.assertEqual(out['time_unit'], expected['time_unit'])
|
|
assert_utest(self, out, expected)
|
|
assert_measurements(self, out, expected)
|
|
|
|
|
|
class TestReportDifferenceWithUTest(unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
def load_results():
|
|
import json
|
|
testInputs = os.path.join(
|
|
os.path.dirname(
|
|
os.path.realpath(__file__)),
|
|
'Inputs')
|
|
testOutput1 = os.path.join(testInputs, 'test3_run0.json')
|
|
testOutput2 = os.path.join(testInputs, 'test3_run1.json')
|
|
with open(testOutput1, 'r') as f:
|
|
json1 = json.load(f)
|
|
with open(testOutput2, 'r') as f:
|
|
json2 = json.load(f)
|
|
return json1, json2
|
|
|
|
json1, json2 = load_results()
|
|
cls.json_diff_report = get_difference_report(
|
|
json1, json2, utest=True)
|
|
|
|
def test_json_diff_report_pretty_printing(self):
|
|
expect_lines = [
|
|
['BM_One', '-0.1000', '+0.1000', '10', '9', '100', '110'],
|
|
['BM_Two', '+0.1111', '-0.0111', '9', '10', '90', '89'],
|
|
['BM_Two', '-0.1250', '-0.1628', '8', '7', '86', '72'],
|
|
['BM_Two_pvalue',
|
|
'1.0000',
|
|
'0.6667',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'2.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['short', '-0.1250', '-0.0625', '8', '7', '80', '75'],
|
|
['short', '-0.4325', '-0.1351', '8', '5', '77', '67'],
|
|
['short_pvalue',
|
|
'0.7671',
|
|
'0.2000',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'3.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['medium', '-0.3750', '-0.3375', '8', '5', '80', '53'],
|
|
['OVERALL_GEOMEAN', '+1.6405', '-0.6985', '0', '0', '0', '0']
|
|
]
|
|
output_lines_with_header = print_difference_report(
|
|
self.json_diff_report, utest=True, utest_alpha=0.05, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report_pretty_printing_aggregates_only(self):
|
|
expect_lines = [
|
|
['BM_One', '-0.1000', '+0.1000', '10', '9', '100', '110'],
|
|
['BM_Two_pvalue',
|
|
'1.0000',
|
|
'0.6667',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'2.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['short', '-0.1250', '-0.0625', '8', '7', '80', '75'],
|
|
['short', '-0.4325', '-0.1351', '8', '5', '77', '67'],
|
|
['short_pvalue',
|
|
'0.7671',
|
|
'0.2000',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'3.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['OVERALL_GEOMEAN', '+1.6405', '-0.6985', '0', '0', '0', '0']
|
|
]
|
|
output_lines_with_header = print_difference_report(
|
|
self.json_diff_report, include_aggregates_only=True, utest=True, utest_alpha=0.05, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report(self):
|
|
expected_output = [
|
|
{
|
|
'name': u'BM_One',
|
|
'measurements': [
|
|
{'time': -0.1,
|
|
'cpu': 0.1,
|
|
'real_time': 10,
|
|
'real_time_other': 9,
|
|
'cpu_time': 100,
|
|
'cpu_time_other': 110}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': u'BM_Two',
|
|
'measurements': [
|
|
{'time': 0.1111111111111111,
|
|
'cpu': -0.011111111111111112,
|
|
'real_time': 9,
|
|
'real_time_other': 10,
|
|
'cpu_time': 90,
|
|
'cpu_time_other': 89},
|
|
{'time': -0.125, 'cpu': -0.16279069767441862, 'real_time': 8,
|
|
'real_time_other': 7, 'cpu_time': 86, 'cpu_time_other': 72}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {
|
|
'have_optimal_repetitions': False, 'cpu_pvalue': 0.6666666666666666, 'time_pvalue': 1.0
|
|
}
|
|
},
|
|
{
|
|
'name': u'short',
|
|
'measurements': [
|
|
{'time': -0.125,
|
|
'cpu': -0.0625,
|
|
'real_time': 8,
|
|
'real_time_other': 7,
|
|
'cpu_time': 80,
|
|
'cpu_time_other': 75},
|
|
{'time': -0.4325,
|
|
'cpu': -0.13506493506493514,
|
|
'real_time': 8,
|
|
'real_time_other': 4.54,
|
|
'cpu_time': 77,
|
|
'cpu_time_other': 66.6}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {
|
|
'have_optimal_repetitions': False, 'cpu_pvalue': 0.2, 'time_pvalue': 0.7670968684102772
|
|
}
|
|
},
|
|
{
|
|
'name': u'medium',
|
|
'measurements': [
|
|
{'time': -0.375,
|
|
'cpu': -0.3375,
|
|
'real_time': 8,
|
|
'real_time_other': 5,
|
|
'cpu_time': 80,
|
|
'cpu_time_other': 53}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': 'OVERALL_GEOMEAN',
|
|
'measurements': [{'real_time': 8.48528137423858e-09, 'cpu_time': 8.441336246629233e-08,
|
|
'real_time_other': 2.2405267593145244e-08, 'cpu_time_other': 2.5453661413660466e-08,
|
|
'time': 1.6404861082353634, 'cpu': -0.6984640740519662}],
|
|
'time_unit': 's',
|
|
'run_type': 'aggregate',
|
|
'aggregate_name': 'geomean',
|
|
'utest': {}
|
|
}
|
|
]
|
|
self.assertEqual(len(self.json_diff_report), len(expected_output))
|
|
for out, expected in zip(
|
|
self.json_diff_report, expected_output):
|
|
self.assertEqual(out['name'], expected['name'])
|
|
self.assertEqual(out['time_unit'], expected['time_unit'])
|
|
assert_utest(self, out, expected)
|
|
assert_measurements(self, out, expected)
|
|
|
|
|
|
class TestReportDifferenceWithUTestWhileDisplayingAggregatesOnly(
|
|
unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
def load_results():
|
|
import json
|
|
testInputs = os.path.join(
|
|
os.path.dirname(
|
|
os.path.realpath(__file__)),
|
|
'Inputs')
|
|
testOutput1 = os.path.join(testInputs, 'test3_run0.json')
|
|
testOutput2 = os.path.join(testInputs, 'test3_run1.json')
|
|
with open(testOutput1, 'r') as f:
|
|
json1 = json.load(f)
|
|
with open(testOutput2, 'r') as f:
|
|
json2 = json.load(f)
|
|
return json1, json2
|
|
|
|
json1, json2 = load_results()
|
|
cls.json_diff_report = get_difference_report(
|
|
json1, json2, utest=True)
|
|
|
|
def test_json_diff_report_pretty_printing(self):
|
|
expect_lines = [
|
|
['BM_One', '-0.1000', '+0.1000', '10', '9', '100', '110'],
|
|
['BM_Two', '+0.1111', '-0.0111', '9', '10', '90', '89'],
|
|
['BM_Two', '-0.1250', '-0.1628', '8', '7', '86', '72'],
|
|
['BM_Two_pvalue',
|
|
'1.0000',
|
|
'0.6667',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'2.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['short', '-0.1250', '-0.0625', '8', '7', '80', '75'],
|
|
['short', '-0.4325', '-0.1351', '8', '5', '77', '67'],
|
|
['short_pvalue',
|
|
'0.7671',
|
|
'0.2000',
|
|
'U',
|
|
'Test,',
|
|
'Repetitions:',
|
|
'2',
|
|
'vs',
|
|
'3.',
|
|
'WARNING:',
|
|
'Results',
|
|
'unreliable!',
|
|
'9+',
|
|
'repetitions',
|
|
'recommended.'],
|
|
['medium', '-0.3750', '-0.3375', '8', '5', '80', '53'],
|
|
['OVERALL_GEOMEAN', '+1.6405', '-0.6985', '0', '0', '0', '0']
|
|
]
|
|
output_lines_with_header = print_difference_report(
|
|
self.json_diff_report,
|
|
utest=True, utest_alpha=0.05, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report(self):
|
|
expected_output = [
|
|
{
|
|
'name': u'BM_One',
|
|
'measurements': [
|
|
{'time': -0.1,
|
|
'cpu': 0.1,
|
|
'real_time': 10,
|
|
'real_time_other': 9,
|
|
'cpu_time': 100,
|
|
'cpu_time_other': 110}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
},
|
|
{
|
|
'name': u'BM_Two',
|
|
'measurements': [
|
|
{'time': 0.1111111111111111,
|
|
'cpu': -0.011111111111111112,
|
|
'real_time': 9,
|
|
'real_time_other': 10,
|
|
'cpu_time': 90,
|
|
'cpu_time_other': 89},
|
|
{'time': -0.125, 'cpu': -0.16279069767441862, 'real_time': 8,
|
|
'real_time_other': 7, 'cpu_time': 86, 'cpu_time_other': 72}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {
|
|
'have_optimal_repetitions': False, 'cpu_pvalue': 0.6666666666666666, 'time_pvalue': 1.0
|
|
}
|
|
},
|
|
{
|
|
'name': u'short',
|
|
'measurements': [
|
|
{'time': -0.125,
|
|
'cpu': -0.0625,
|
|
'real_time': 8,
|
|
'real_time_other': 7,
|
|
'cpu_time': 80,
|
|
'cpu_time_other': 75},
|
|
{'time': -0.4325,
|
|
'cpu': -0.13506493506493514,
|
|
'real_time': 8,
|
|
'real_time_other': 4.54,
|
|
'cpu_time': 77,
|
|
'cpu_time_other': 66.6}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {
|
|
'have_optimal_repetitions': False, 'cpu_pvalue': 0.2, 'time_pvalue': 0.7670968684102772
|
|
}
|
|
},
|
|
{
|
|
'name': u'medium',
|
|
'measurements': [
|
|
{'real_time_other': 5,
|
|
'cpu_time': 80,
|
|
'time': -0.375,
|
|
'real_time': 8,
|
|
'cpu_time_other': 53,
|
|
'cpu': -0.3375
|
|
}
|
|
],
|
|
'utest': {},
|
|
'time_unit': u'ns',
|
|
'aggregate_name': ''
|
|
},
|
|
{
|
|
'name': 'OVERALL_GEOMEAN',
|
|
'measurements': [{'real_time': 8.48528137423858e-09, 'cpu_time': 8.441336246629233e-08,
|
|
'real_time_other': 2.2405267593145244e-08, 'cpu_time_other': 2.5453661413660466e-08,
|
|
'time': 1.6404861082353634, 'cpu': -0.6984640740519662}],
|
|
'time_unit': 's',
|
|
'run_type': 'aggregate',
|
|
'aggregate_name': 'geomean',
|
|
'utest': {}
|
|
}
|
|
]
|
|
self.assertEqual(len(self.json_diff_report), len(expected_output))
|
|
for out, expected in zip(
|
|
self.json_diff_report, expected_output):
|
|
self.assertEqual(out['name'], expected['name'])
|
|
self.assertEqual(out['time_unit'], expected['time_unit'])
|
|
assert_utest(self, out, expected)
|
|
assert_measurements(self, out, expected)
|
|
|
|
|
|
class TestReportDifferenceForPercentageAggregates(
|
|
unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
def load_results():
|
|
import json
|
|
testInputs = os.path.join(
|
|
os.path.dirname(
|
|
os.path.realpath(__file__)),
|
|
'Inputs')
|
|
testOutput1 = os.path.join(testInputs, 'test4_run0.json')
|
|
testOutput2 = os.path.join(testInputs, 'test4_run1.json')
|
|
with open(testOutput1, 'r') as f:
|
|
json1 = json.load(f)
|
|
with open(testOutput2, 'r') as f:
|
|
json2 = json.load(f)
|
|
return json1, json2
|
|
|
|
json1, json2 = load_results()
|
|
cls.json_diff_report = get_difference_report(
|
|
json1, json2, utest=True)
|
|
|
|
def test_json_diff_report_pretty_printing(self):
|
|
expect_lines = [
|
|
['whocares', '-0.5000', '+0.5000', '0', '0', '0', '0']
|
|
]
|
|
output_lines_with_header = print_difference_report(
|
|
self.json_diff_report,
|
|
utest=True, utest_alpha=0.05, use_color=False)
|
|
output_lines = output_lines_with_header[2:]
|
|
print("\n")
|
|
print("\n".join(output_lines_with_header))
|
|
self.assertEqual(len(output_lines), len(expect_lines))
|
|
for i in range(0, len(output_lines)):
|
|
parts = [x for x in output_lines[i].split(' ') if x]
|
|
self.assertEqual(expect_lines[i], parts)
|
|
|
|
def test_json_diff_report(self):
|
|
expected_output = [
|
|
{
|
|
'name': u'whocares',
|
|
'measurements': [
|
|
{'time': -0.5,
|
|
'cpu': 0.5,
|
|
'real_time': 0.01,
|
|
'real_time_other': 0.005,
|
|
'cpu_time': 0.10,
|
|
'cpu_time_other': 0.15}
|
|
],
|
|
'time_unit': 'ns',
|
|
'utest': {}
|
|
}
|
|
]
|
|
self.assertEqual(len(self.json_diff_report), len(expected_output))
|
|
for out, expected in zip(
|
|
self.json_diff_report, expected_output):
|
|
self.assertEqual(out['name'], expected['name'])
|
|
self.assertEqual(out['time_unit'], expected['time_unit'])
|
|
assert_utest(self, out, expected)
|
|
assert_measurements(self, out, expected)
|
|
|
|
|
|
class TestReportSorting(unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
def load_result():
|
|
import json
|
|
testInputs = os.path.join(
|
|
os.path.dirname(
|
|
os.path.realpath(__file__)),
|
|
'Inputs')
|
|
testOutput = os.path.join(testInputs, 'test4_run.json')
|
|
with open(testOutput, 'r') as f:
|
|
json = json.load(f)
|
|
return json
|
|
|
|
cls.json = load_result()
|
|
|
|
def test_json_diff_report_pretty_printing(self):
|
|
import util
|
|
|
|
expected_names = [
|
|
"99 family 0 instance 0 repetition 0",
|
|
"98 family 0 instance 0 repetition 1",
|
|
"97 family 0 instance 0 aggregate",
|
|
"96 family 0 instance 1 repetition 0",
|
|
"95 family 0 instance 1 repetition 1",
|
|
"94 family 0 instance 1 aggregate",
|
|
"93 family 1 instance 0 repetition 0",
|
|
"92 family 1 instance 0 repetition 1",
|
|
"91 family 1 instance 0 aggregate",
|
|
"90 family 1 instance 1 repetition 0",
|
|
"89 family 1 instance 1 repetition 1",
|
|
"88 family 1 instance 1 aggregate"
|
|
]
|
|
|
|
for n in range(len(self.json['benchmarks']) ** 2):
|
|
random.shuffle(self.json['benchmarks'])
|
|
sorted_benchmarks = util.sort_benchmark_results(self.json)[
|
|
'benchmarks']
|
|
self.assertEqual(len(expected_names), len(sorted_benchmarks))
|
|
for out, expected in zip(sorted_benchmarks, expected_names):
|
|
self.assertEqual(out['name'], expected)
|
|
|
|
|
|
def assert_utest(unittest_instance, lhs, rhs):
|
|
if lhs['utest']:
|
|
unittest_instance.assertAlmostEqual(
|
|
lhs['utest']['cpu_pvalue'],
|
|
rhs['utest']['cpu_pvalue'])
|
|
unittest_instance.assertAlmostEqual(
|
|
lhs['utest']['time_pvalue'],
|
|
rhs['utest']['time_pvalue'])
|
|
unittest_instance.assertEqual(
|
|
lhs['utest']['have_optimal_repetitions'],
|
|
rhs['utest']['have_optimal_repetitions'])
|
|
else:
|
|
# lhs is empty. assert if rhs is not.
|
|
unittest_instance.assertEqual(lhs['utest'], rhs['utest'])
|
|
|
|
|
|
def assert_measurements(unittest_instance, lhs, rhs):
|
|
for m1, m2 in zip(lhs['measurements'], rhs['measurements']):
|
|
unittest_instance.assertEqual(m1['real_time'], m2['real_time'])
|
|
unittest_instance.assertEqual(m1['cpu_time'], m2['cpu_time'])
|
|
# m1['time'] and m1['cpu'] hold values which are being calculated,
|
|
# and therefore we must use almost-equal pattern.
|
|
unittest_instance.assertAlmostEqual(m1['time'], m2['time'], places=4)
|
|
unittest_instance.assertAlmostEqual(m1['cpu'], m2['cpu'], places=4)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|
|
|
|
# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
|
|
# kate: tab-width: 4; replace-tabs on; indent-width 4; tab-indents: off;
|
|
# kate: indent-mode python; remove-trailing-spaces modified;
|