// Copyright 2016 Ismael Jimenez Martinez. 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. // Source project : https://github.com/ismaelJimenez/cpp.leastsq // Adapted to be used with google benchmark #ifndef COMPLEXITY_H_ #define COMPLEXITY_H_ #include <string> #include <vector> #include "benchmark/benchmark.h" namespace benchmark { // Return a vector containing the bigO and RMS information for the specified // list of reports. If 'reports.size() < 2' an empty vector is returned. std::vector<BenchmarkReporter::Run> ComputeBigO( const std::vector<BenchmarkReporter::Run>& reports); // This data structure will contain the result returned by MinimalLeastSq // - coef : Estimated coefficient for the high-order term as // interpolated from data. // - rms : Normalized Root Mean Squared Error. // - complexity : Scalability form (e.g. oN, oNLogN). In case a scalability // form has been provided to MinimalLeastSq this will return // the same value. In case BigO::oAuto has been selected, this // parameter will return the best fitting curve detected. struct LeastSq { … }; // Function to return an string for the calculated complexity std::string GetBigOString(BigO complexity); } // end namespace benchmark #endif // COMPLEXITY_H_