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// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
// Copyright 2017 Roman Lebedev. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "benchmark/benchmark.h"
#include <algorithm>
#include <cmath>
#include <string>
#include <vector>
#include <numeric>
#include "check.h"
#include "statistics.h"
namespace benchmark {
auto StatisticsSum = [](const std::vector<double>& v) {
return std::accumulate(v.begin(), v.end(), 0.0);
};
double StatisticsMean(const std::vector<double>& v) {
if (v.size() == 0) return 0.0;
return StatisticsSum(v) * (1.0 / v.size());
}
double StatisticsMedian(const std::vector<double>& v) {
if (v.size() < 3) return StatisticsMean(v);
std::vector<double> partial;
// we need roundDown(count/2)+1 slots
partial.resize(1 + (v.size() / 2));
std::partial_sort_copy(v.begin(), v.end(), partial.begin(), partial.end());
// did we have odd number of samples?
// if yes, then the last element of partially-sorted vector is the median
// it no, then the average of the last two elements is the median
if(v.size() % 2 == 1)
return partial.back();
return (partial[partial.size() - 2] + partial[partial.size() - 1]) / 2.0;
}
// Return the sum of the squares of this sample set
auto SumSquares = [](const std::vector<double>& v) {
return std::inner_product(v.begin(), v.end(), v.begin(), 0.0);
};
auto Sqr = [](const double dat) { return dat * dat; };
auto Sqrt = [](const double dat) {
// Avoid NaN due to imprecision in the calculations
if (dat < 0.0) return 0.0;
return std::sqrt(dat);
};
double StatisticsStdDev(const std::vector<double>& v) {
const auto mean = StatisticsMean(v);
if (v.size() == 0) return mean;
// Sample standard deviation is undefined for n = 1
if (v.size() == 1)
return 0.0;
const double avg_squares = SumSquares(v) * (1.0 / v.size());
return Sqrt(v.size() / (v.size() - 1.0) * (avg_squares - Sqr(mean)));
}
std::vector<BenchmarkReporter::Run> ComputeStats(
const std::vector<BenchmarkReporter::Run>& reports) {
typedef BenchmarkReporter::Run Run;
std::vector<Run> results;
auto error_count =
std::count_if(reports.begin(), reports.end(),
[](Run const& run) { return run.error_occurred; });
if (reports.size() - error_count < 2) {
// We don't report aggregated data if there was a single run.
return results;
}
// Accumulators.
std::vector<double> real_accumulated_time_stat;
std::vector<double> cpu_accumulated_time_stat;
std::vector<double> bytes_per_second_stat;
std::vector<double> items_per_second_stat;
real_accumulated_time_stat.reserve(reports.size());
cpu_accumulated_time_stat.reserve(reports.size());
bytes_per_second_stat.reserve(reports.size());
items_per_second_stat.reserve(reports.size());
// All repetitions should be run with the same number of iterations so we
// can take this information from the first benchmark.
int64_t const run_iterations = reports.front().iterations;
// create stats for user counters
struct CounterStat {
Counter c;
std::vector<double> s;
};
std::map< std::string, CounterStat > counter_stats;
for(Run const& r : reports) {
for(auto const& cnt : r.counters) {
auto it = counter_stats.find(cnt.first);
if(it == counter_stats.end()) {
counter_stats.insert({cnt.first, {cnt.second, std::vector<double>{}}});
it = counter_stats.find(cnt.first);
it->second.s.reserve(reports.size());
} else {
CHECK_EQ(counter_stats[cnt.first].c.flags, cnt.second.flags);
}
}
}
// Populate the accumulators.
for (Run const& run : reports) {
CHECK_EQ(reports[0].benchmark_name, run.benchmark_name);
CHECK_EQ(run_iterations, run.iterations);
if (run.error_occurred) continue;
real_accumulated_time_stat.emplace_back(run.real_accumulated_time);
cpu_accumulated_time_stat.emplace_back(run.cpu_accumulated_time);
items_per_second_stat.emplace_back(run.items_per_second);
bytes_per_second_stat.emplace_back(run.bytes_per_second);
// user counters
for(auto const& cnt : run.counters) {
auto it = counter_stats.find(cnt.first);
CHECK_NE(it, counter_stats.end());
it->second.s.emplace_back(cnt.second);
}
}
// Only add label if it is same for all runs
std::string report_label = reports[0].report_label;
for (std::size_t i = 1; i < reports.size(); i++) {
if (reports[i].report_label != report_label) {
report_label = "";
break;
}
}
for(const auto& Stat : *reports[0].statistics) {
// Get the data from the accumulator to BenchmarkReporter::Run's.
Run data;
data.benchmark_name = reports[0].benchmark_name + "_" + Stat.name_;
data.report_label = report_label;
data.iterations = run_iterations;
data.real_accumulated_time = Stat.compute_(real_accumulated_time_stat);
data.cpu_accumulated_time = Stat.compute_(cpu_accumulated_time_stat);
data.bytes_per_second = Stat.compute_(bytes_per_second_stat);
data.items_per_second = Stat.compute_(items_per_second_stat);
data.time_unit = reports[0].time_unit;
// user counters
for(auto const& kv : counter_stats) {
const auto uc_stat = Stat.compute_(kv.second.s);
auto c = Counter(uc_stat, counter_stats[kv.first].c.flags);
data.counters[kv.first] = c;
}
results.push_back(data);
}
return results;
}
} // end namespace benchmark
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