diff options
Diffstat (limited to 'src/complexity.cc')
| -rw-r--r-- | src/complexity.cc | 43 |
1 files changed, 29 insertions, 14 deletions
diff --git a/src/complexity.cc b/src/complexity.cc index 825c573..eee3122 100644 --- a/src/complexity.cc +++ b/src/complexity.cc @@ -37,12 +37,14 @@ BigOFunc* FittingCurve(BigO complexity) { return [](IterationCount n) -> double { return std::pow(n, 3); }; case oLogN: /* Note: can't use log2 because Android's GNU STL lacks it */ - return - [](IterationCount n) { return kLog2E * log(static_cast<double>(n)); }; + return [](IterationCount n) { + return kLog2E * std::log(static_cast<double>(n)); + }; case oNLogN: /* Note: can't use log2 because Android's GNU STL lacks it */ return [](IterationCount n) { - return kLog2E * n * log(static_cast<double>(n)); + return kLog2E * static_cast<double>(n) * + std::log(static_cast<double>(n)); }; case o1: default: @@ -75,12 +77,12 @@ std::string GetBigOString(BigO complexity) { // given by the lambda expression. // - n : Vector containing the size of the benchmark tests. // - time : Vector containing the times for the benchmark tests. -// - fitting_curve : lambda expression (e.g. [](int64_t n) {return n; };). +// - fitting_curve : lambda expression (e.g. [](ComplexityN n) {return n; };). // For a deeper explanation on the algorithm logic, please refer to // https://en.wikipedia.org/wiki/Least_squares#Least_squares,_regression_analysis_and_statistics -LeastSq MinimalLeastSq(const std::vector<int64_t>& n, +LeastSq MinimalLeastSq(const std::vector<ComplexityN>& n, const std::vector<double>& time, BigOFunc* fitting_curve) { double sigma_gn_squared = 0.0; @@ -105,12 +107,12 @@ LeastSq MinimalLeastSq(const std::vector<int64_t>& n, double rms = 0.0; for (size_t i = 0; i < n.size(); ++i) { double fit = result.coef * fitting_curve(n[i]); - rms += pow((time[i] - fit), 2); + rms += std::pow((time[i] - fit), 2); } // Normalized RMS by the mean of the observed values - double mean = sigma_time / n.size(); - result.rms = sqrt(rms / n.size()) / mean; + double mean = sigma_time / static_cast<double>(n.size()); + result.rms = std::sqrt(rms / static_cast<double>(n.size())) / mean; return result; } @@ -122,7 +124,7 @@ LeastSq MinimalLeastSq(const std::vector<int64_t>& n, // - complexity : If different than oAuto, the fitting curve will stick to // this one. If it is oAuto, it will be calculated the best // fitting curve. -LeastSq MinimalLeastSq(const std::vector<int64_t>& n, +LeastSq MinimalLeastSq(const std::vector<ComplexityN>& n, const std::vector<double>& time, const BigO complexity) { BM_CHECK_EQ(n.size(), time.size()); BM_CHECK_GE(n.size(), 2); // Do not compute fitting curve is less than two @@ -162,7 +164,7 @@ std::vector<BenchmarkReporter::Run> ComputeBigO( if (reports.size() < 2) return results; // Accumulators. - std::vector<int64_t> n; + std::vector<ComplexityN> n; std::vector<double> real_time; std::vector<double> cpu_time; @@ -171,8 +173,10 @@ std::vector<BenchmarkReporter::Run> ComputeBigO( BM_CHECK_GT(run.complexity_n, 0) << "Did you forget to call SetComplexityN?"; n.push_back(run.complexity_n); - real_time.push_back(run.real_accumulated_time / run.iterations); - cpu_time.push_back(run.cpu_accumulated_time / run.iterations); + real_time.push_back(run.real_accumulated_time / + static_cast<double>(run.iterations)); + cpu_time.push_back(run.cpu_accumulated_time / + static_cast<double>(run.iterations)); } LeastSq result_cpu; @@ -182,8 +186,19 @@ std::vector<BenchmarkReporter::Run> ComputeBigO( result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity_lambda); result_real = MinimalLeastSq(n, real_time, reports[0].complexity_lambda); } else { - result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity); - result_real = MinimalLeastSq(n, real_time, result_cpu.complexity); + const BigO* InitialBigO = &reports[0].complexity; + const bool use_real_time_for_initial_big_o = + reports[0].use_real_time_for_initial_big_o; + if (use_real_time_for_initial_big_o) { + result_real = MinimalLeastSq(n, real_time, *InitialBigO); + InitialBigO = &result_real.complexity; + // The Big-O complexity for CPU time must have the same Big-O function! + } + result_cpu = MinimalLeastSq(n, cpu_time, *InitialBigO); + InitialBigO = &result_cpu.complexity; + if (!use_real_time_for_initial_big_o) { + result_real = MinimalLeastSq(n, real_time, *InitialBigO); + } } // Drop the 'args' when reporting complexity. |