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| // 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 coeficient 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 {
LeastSq() : coef(0.0), rms(0.0), complexity(oNone) {}
double coef;
double rms;
BigO complexity;
};
// Function to return an string for the calculated complexity
std::string GetBigOString(BigO complexity);
} // end namespace benchmark
#endif // COMPLEXITY_H_
|