include/benchmark/complexity.h

// 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>

namespace benchmark {

// BigO is passed to a benchmark in order to specify the asymptotic computational 
// complexity for the benchmark. In case oAuto is selected, complexity will be 
// calculated automatically to the best fit.
enum BigO {
  oNone,
  o1,
  oN,
  oNSquared,
  oNCubed,
  oLogN,
  oNLogN,
  oAuto
};

// 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);

// Find the coefficient for the high-order term in the running time, by
// minimizing the sum of squares of relative error.
LeastSq MinimalLeastSq(const std::vector<int>& n,
                       const std::vector<double>& time,
                       const BigO complexity = oAuto);

} // end namespace benchmark
#endif // COMPLEXITY_H_