// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Source project : https://github.com/ismaelJimenez/cpp.leastsq
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// Adapted to be used with google benchmark
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#ifndef COMPLEXITY_H_
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#define COMPLEXITY_H_
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#include <string>
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#include <vector>
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#include "benchmark/benchmark.h"
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namespace benchmark {
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// Return a vector containing the bigO and RMS information for the specified
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// list of reports. If 'reports.size() < 2' an empty vector is returned.
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std::vector<BenchmarkReporter::Run> ComputeBigO(
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const std::vector<BenchmarkReporter::Run>& reports);
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// This data structure will contain the result returned by MinimalLeastSq
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// - coef : Estimated coeficient for the high-order term as
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// interpolated from data.
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// - rms : Normalized Root Mean Squared Error.
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// - complexity : Scalability form (e.g. oN, oNLogN). In case a scalability
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// form has been provided to MinimalLeastSq this will return
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// the same value. In case BigO::oAuto has been selected, this
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// parameter will return the best fitting curve detected.
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struct LeastSq {
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LeastSq() : coef(0.0), rms(0.0), complexity(oNone) {}
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double coef;
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double rms;
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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(BigO complexity);
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} // end namespace benchmark
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#endif // COMPLEXITY_H_
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