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initialized doubles to 0.0
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@ -48,23 +48,23 @@ enum BigO {
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struct LeastSq {
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LeastSq() :
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coef(0),
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rms(0),
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complexity(benchmark::oNone) {}
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coef(0.0),
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rms(0.0),
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complexity(oNone) {}
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double coef;
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double rms;
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benchmark::BigO complexity;
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BigO complexity;
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};
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// Function to return an string for the calculated complexity
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std::string GetBigOString(benchmark::BigO complexity);
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std::string GetBigOString(BigO complexity);
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// Find the coefficient for the high-order term in the running time, by
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// minimizing the sum of squares of relative error.
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LeastSq MinimalLeastSq(const std::vector<int>& n,
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const std::vector<double>& time,
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const benchmark::BigO complexity = benchmark::oAuto);
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const BigO complexity = oAuto);
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} // end namespace benchmark
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#endif // COMPLEXITY_H_
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@ -86,10 +86,10 @@ std::string GetBigOString(BigO complexity) {
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LeastSq CalculateLeastSq(const std::vector<int>& n,
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const std::vector<double>& time,
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std::function<double(int)> fitting_curve) {
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double sigma_gn = 0;
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double sigma_gn_squared = 0;
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double sigma_time = 0;
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double sigma_time_gn = 0;
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double sigma_gn = 0.0;
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double sigma_gn_squared = 0.0;
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double sigma_time = 0.0;
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double sigma_time_gn = 0.0;
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// Calculate least square fitting parameter
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for (size_t i = 0; i < n.size(); ++i) {
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@ -106,7 +106,7 @@ LeastSq CalculateLeastSq(const std::vector<int>& n,
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result.coef = sigma_time_gn / sigma_gn_squared;
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// Calculate RMS
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double rms = 0;
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double rms = 0.0;
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for (size_t i = 0; i < n.size(); ++i) {
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double fit = result.coef * fitting_curve(n[i]);
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rms += pow((time[i] - fit), 2);
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