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ce2560ca95
Changes done to Nonius: * Moved things into "Catch::Benchmark" namespace * Benchmarks were integrated with `TEST_CASE`/`SECTION`/`GENERATE` macros * Removed Nonius's parameters for benchmarks, Generators should be used instead * Added relevant methods to the reporter interface (default-implemented, to avoid breaking existing 3rd party reporters) * Async processing is guarded with `_REENTRANT` macro for GCC/Clang, used by default on MSVC * Added a macro `CATCH_CONFIG_DISABLE_BENCHMARKING` that removes all traces of benchmarking from Catch
79 lines
3.1 KiB
C++
79 lines
3.1 KiB
C++
/*
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* Created by Joachim on 16/04/2019.
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* Adapted from donated nonius code.
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*
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* Distributed under the Boost Software License, Version 1.0. (See accompanying
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* file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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*/
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// Run and analyse one benchmark
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#ifndef TWOBLUECUBES_CATCH_DETAIL_ANALYSE_HPP_INCLUDED
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#define TWOBLUECUBES_CATCH_DETAIL_ANALYSE_HPP_INCLUDED
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#include "../catch_clock.hpp"
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#include "../catch_sample_analysis.hpp"
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#include "catch_stats.hpp"
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#include <algorithm>
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#include <iterator>
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#include <vector>
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namespace Catch {
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namespace Benchmark {
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namespace Detail {
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template <typename Duration, typename Iterator>
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SampleAnalysis<Duration> analyse(const IConfig &cfg, Environment<Duration>, Iterator first, Iterator last) {
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if (!cfg.benchmarkNoAnalysis()) {
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std::vector<double> samples;
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samples.reserve(last - first);
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std::transform(first, last, std::back_inserter(samples), [](Duration d) { return d.count(); });
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auto analysis = Catch::Benchmark::Detail::analyse_samples(cfg.benchmarkConfidenceInterval(), cfg.benchmarkResamples(), samples.begin(), samples.end());
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auto outliers = Catch::Benchmark::Detail::classify_outliers(samples.begin(), samples.end());
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auto wrap_estimate = [](Estimate<double> e) {
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return Estimate<Duration> {
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Duration(e.point),
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Duration(e.lower_bound),
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Duration(e.upper_bound),
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e.confidence_interval,
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};
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};
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std::vector<Duration> samples2;
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samples2.reserve(samples.size());
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std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](double d) { return Duration(d); });
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return {
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std::move(samples2),
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wrap_estimate(analysis.mean),
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wrap_estimate(analysis.standard_deviation),
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outliers,
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analysis.outlier_variance,
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};
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} else {
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std::vector<Duration> samples;
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samples.reserve(last - first);
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Duration mean = Duration(0);
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int i = 0;
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for (auto it = first; it < last; ++it, ++i) {
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samples.push_back(Duration(*it));
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mean += Duration(*it);
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}
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mean /= i;
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return {
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std::move(samples),
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Estimate<Duration>{mean, mean, mean, 0.0},
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Estimate<Duration>{Duration(0), Duration(0), Duration(0), 0.0},
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OutlierClassification{},
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0.0
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};
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}
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}
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} // namespace Detail
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} // namespace Benchmark
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} // namespace Catch
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#endif // TWOBLUECUBES_CATCH_DETAIL_ANALYSE_HPP_INCLUDED
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