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Internal linkage for outlier_variance
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@ -21,28 +21,34 @@
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#include <future>
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#endif
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namespace Catch {
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namespace Benchmark {
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namespace Detail {
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namespace {
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using Catch::Benchmark::Detail::sample;
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template <typename URng, typename Estimator>
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static sample resample(URng& rng, unsigned int resamples,
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static sample
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resample( URng& rng,
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unsigned int resamples,
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std::vector<double>::const_iterator first,
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std::vector<double>::const_iterator last,
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Estimator& estimator ) {
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auto n = static_cast<size_t>( last - first );
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std::uniform_int_distribution<decltype(n)> dist(0, n - 1);
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std::uniform_int_distribution<decltype( n )> dist( 0,
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n - 1 );
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sample out;
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out.reserve( resamples );
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// We allocate the vector outside the loop to avoid realloc per resample
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// We allocate the vector outside the loop to avoid realloc
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// per resample
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std::vector<double> resampled;
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resampled.reserve( n );
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for ( size_t i = 0; i < resamples; ++i ) {
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resampled.clear();
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for ( size_t s = 0; s < n; ++s ) {
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resampled.push_back(
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first[static_cast<std::ptrdiff_t>( dist( rng ) )] );
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first[static_cast<std::ptrdiff_t>(
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dist( rng ) )] );
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}
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const auto estimate =
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estimator( resampled.begin(), resampled.end() );
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@ -52,9 +58,42 @@ using Catch::Benchmark::Detail::sample;
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return out;
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}
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static double outlier_variance( Estimate<double> mean,
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Estimate<double> stddev,
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int n ) {
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double sb = stddev.point;
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double mn = mean.point / n;
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double mg_min = mn / 2.;
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double sg = (std::min)( mg_min / 4., sb / std::sqrt( n ) );
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double sg2 = sg * sg;
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double sb2 = sb * sb;
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double erf_inv(double x) {
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// Code accompanying the article "Approximating the erfinv function" in GPU Computing Gems, Volume 2
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auto c_max = [n, mn, sb2, sg2]( double x ) -> double {
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double k = mn - x;
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double d = k * k;
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double nd = n * d;
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double k0 = -n * nd;
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double k1 = sb2 - n * sg2 + nd;
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double det = k1 * k1 - 4 * sg2 * k0;
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return static_cast<int>( -2. * k0 /
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( k1 + std::sqrt( det ) ) );
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};
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auto var_out = [n, sb2, sg2]( double c ) {
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double nc = n - c;
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return ( nc / n ) * ( sb2 - nc * sg2 );
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};
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return (std::min)( var_out( 1 ),
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var_out(
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(std::min)( c_max( 0. ),
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c_max( mg_min ) ) ) ) /
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sb2;
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}
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static double erf_inv( double x ) {
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// Code accompanying the article "Approximating the erfinv
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// function" in GPU Computing Gems, Volume 2
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double w, p;
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w = -log( ( 1.0 - x ) * ( 1.0 + x ) );
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@ -128,10 +167,12 @@ using Catch::Benchmark::Detail::sample;
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return p * x;
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}
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double standard_deviation(std::vector<double>::const_iterator first,
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static double
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standard_deviation( std::vector<double>::const_iterator first,
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std::vector<double>::const_iterator last ) {
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auto m = Catch::Benchmark::Detail::mean( first, last );
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double variance = std::accumulate( first,
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double variance =
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std::accumulate( first,
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last,
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0.,
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[m]( double a, double b ) {
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@ -142,7 +183,10 @@ using Catch::Benchmark::Detail::sample;
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return std::sqrt( variance );
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}
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}
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} // namespace
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} // namespace Detail
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} // namespace Benchmark
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} // namespace Catch
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namespace Catch {
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namespace Benchmark {
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@ -234,34 +278,6 @@ namespace Catch {
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return result;
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}
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double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n) {
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double sb = stddev.point;
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double mn = mean.point / n;
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double mg_min = mn / 2.;
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double sg = (std::min)(mg_min / 4., sb / std::sqrt(n));
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double sg2 = sg * sg;
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double sb2 = sb * sb;
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auto c_max = [n, mn, sb2, sg2](double x) -> double {
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double k = mn - x;
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double d = k * k;
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double nd = n * d;
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double k0 = -n * nd;
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double k1 = sb2 - n * sg2 + nd;
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double det = k1 * k1 - 4 * sg2 * k0;
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return static_cast<int>(-2. * k0 / (k1 + std::sqrt(det)));
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};
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auto var_out = [n, sb2, sg2](double c) {
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double nc = n - c;
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return (nc / n) * (sb2 - nc * sg2);
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};
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return (std::min)(var_out(1), var_out((std::min)(c_max(0.), c_max(mg_min)))) / sb2;
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}
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bootstrap_analysis analyse_samples(double confidence_level,
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unsigned int n_resamples,
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std::vector<double>::iterator first,
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@ -108,8 +108,6 @@ namespace Catch {
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return { point, resample[lo], resample[hi], confidence_level };
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}
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double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n);
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struct bootstrap_analysis {
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Estimate<double> mean;
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Estimate<double> standard_deviation;
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