Init version
This commit is contained in:
352
DEC_GUI/Kolch_Shind/solver.cpp
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352
DEC_GUI/Kolch_Shind/solver.cpp
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#include "solver.h"
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#include "iostream"
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#include <QTextStream>
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Solver::Solver(QObject *parent) :
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QObject(parent)
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{
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}
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Solver::~Solver()
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{
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}
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//calculates function values and puts it into vectors(predatorSolveVal, preySolveVal)
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void Solver::solveModel(float c1, float c2, float c3, float c4, float c5, float sigC1, float sigC2, float sigC3, float sigC4, float sigC5,
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float e, float sigE, float sigX0, float delX0, float sigX, float Xopt, int popSize, int maxSteps, int N, int flag, int iter, int modelCount){
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itersFlag = flag;
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newIters = iter;
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modCount = modelCount;
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int k = 0;
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if (itersFlag == 0)
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{
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popVect.clear();
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singleModelHistory.clear();
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for (int i = 0; i < modelCount; i++)
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{
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k++;
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withFeedbackVect.clear();
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withoutFeedbackVect.clear();
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firstXVect.clear();
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maxWithFeedVal = 0;
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maxWithoutFeedVal = 0;
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//firstXVect.clear();
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meanE.clear();
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meanF.clear();
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meanC2.clear();
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individ.clear();
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individFeedback.clear();
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int POP_SIZE = popSize;
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int MAX_STEPS = maxSteps;
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addSteps = maxSteps;
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//float DELTA_Xopt = 0.0f;
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float DELTA_Xopt = delX0;
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//float DELTA_Xopt = 0.4f;
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//float DELTA_Xopt = 0.5f;
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//float DELTA_Xopt = 1.0f;
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N_forFeedback = N;
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population.resize(POP_SIZE);
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popVect.push_back(population);
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//Individ::initConstants();
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Individ::initConstantsFromGUI(c1, c2, c3, c4, c5, Xopt, sigX, sigE, sigC1, sigC2, sigC3, sigC4, sigC5);
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initialization(popVect[i], N_forFeedback);
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// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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for(int steps = 0; steps < MAX_STEPS; steps++) {
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//mutationSimple(population); // 1) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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mutationComplex(popVect[i]);
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selection(popVect[i], 0.02f); // 2) <20><><EFBFBD><EFBFBD><EFBFBD>
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printStatistics(popVect[i], i, 0, steps);
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firstXVect.push_back(steps);
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maxWithFeedVal = qMax(withFeedbackVect[steps], maxWithFeedVal);
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maxWithoutFeedVal = qMax(withoutFeedbackVect[steps], maxWithoutFeedVal);
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Individ::Xopt += DELTA_Xopt;
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} // (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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lastXopt = Individ::Xopt;
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vectors.withFeedbackVect = withFeedbackVect;
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vectors.withoutFeedbackVect = withoutFeedbackVect;
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vectors.individ = individ;
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vectors.individFeedback = individFeedback;
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vectors.meanE = meanE;
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vectors.meanC2 = meanC2;
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vectors.meanF = meanF;
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vectors.xRange = firstXVect;
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vectors.maxWithFeedVal = maxWithFeedVal;
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vectors.maxWithoutFeedVal = maxWithoutFeedVal;
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singleModelHistory.push_back(vectors);
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emit sendItersForProgressBar(i);
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}
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if (k == modelCount)
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{
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for (int m = 0; m < withFeedbackVectAvg.size(); m++)
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{
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withFeedbackVectAvg[m] /= modCount;
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withoutFeedbackVectAvg[m] /= modCount;
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individAvg[m] /= modCount;
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individFeedbackAvg[m] /= modCount;
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meanC2Avg[m] /= modCount;
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meanEAvg[m] /= modCount;
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meanFAvg[m] /= modCount;
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}
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vectors.withFeedbackVect = withFeedbackVectAvg;
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vectors.withoutFeedbackVect = withoutFeedbackVectAvg;
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vectors.individ = individAvg;
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vectors.individFeedback = individFeedbackAvg;
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vectors.meanE = meanEAvg;
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vectors.meanC2 = meanC2Avg;
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vectors.meanF = meanFAvg;
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singleModelHistory.push_back(vectors);
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emit sendItersForProgressBar(modCount);
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}
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emit sendHistory(singleModelHistory, addSteps);
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}
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if (itersFlag == 1)
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{
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int n = 0;
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float DELTA_Xopt = delX0;
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for (int i = 0; i < modelCount; i++)
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{
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n++;
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Individ::Xopt = lastXopt;
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//std::cout << Individ::Xopt << std::endl;
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N_forFeedback = N;
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// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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for(int steps = addSteps; steps < addSteps + newIters; steps++) {
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//mutationSimple(population); // 1) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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mutationComplex(popVect[i]);
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selection(popVect[i], 0.02f); // 2) <20><><EFBFBD><EFBFBD><EFBFBD>
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printStatistics(popVect[i], i, 1, steps);
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if (i == 0)
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{
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firstXVect.push_back(steps);
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}
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Individ::Xopt += DELTA_Xopt;
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maxWithFeedVal = qMax(withFeedbackVect[steps], maxWithFeedVal);
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maxWithoutFeedVal = qMax(withoutFeedbackVect[steps], maxWithoutFeedVal);
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} // (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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singleModelHistory[i].xRange = firstXVect;
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singleModelHistory[i].maxWithFeedVal = maxWithFeedVal;
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singleModelHistory[i].maxWithoutFeedVal = maxWithoutFeedVal;
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emit sendItersForProgressBar(i);
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}
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if (n == modCount) // index n - for last struct in history for averages
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{
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for (int m = addSteps; m < addSteps + newIters; m++)
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{
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singleModelHistory[modCount].withFeedbackVect[m] /= modCount;
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singleModelHistory[modCount].withoutFeedbackVect[m] /= modCount;
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singleModelHistory[modCount].individ[m] /= modCount;
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singleModelHistory[modCount].individFeedback[m] /= modCount;
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singleModelHistory[modCount].meanC2[m] /= modCount;
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singleModelHistory[modCount].meanE[m] /= modCount;
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singleModelHistory[modCount].meanF[m] /= modCount;
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}
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singleModelHistory[modCount].xRange = firstXVect;
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}
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lastXopt = Individ::Xopt;
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addSteps += newIters;
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emit sendItersForProgressBar(modCount);
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emit sendHistory(singleModelHistory, addSteps);
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}
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}
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void Solver::mutationSimple(std::vector<Individ*>& population){
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boost::normal_distribution<> norm(0.0, Individ::sigmaE);
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boost::mt19937 rng;
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boost::variate_generator<boost::mt19937&, boost::normal_distribution<> >
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generator(rng, norm); // glues randomness with mapping
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for(int i = 0; i < population.size(); i++){
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float deltaE = generator();
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//std::cout<<deltaE<<std::endl;
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population.at(i)->mutate(deltaE);
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}
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}
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void Solver::mutationComplex(std::vector<Individ*>& population){
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boost::normal_distribution<> normE(0.0, Individ::sigmaE);
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boost::normal_distribution<> normC2(0.0, Individ::sigmaC2);
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boost::mt19937 rng;
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boost::variate_generator<boost::mt19937&, boost::normal_distribution<> >
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generatorE(rng, normE);
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boost::variate_generator<boost::mt19937&, boost::normal_distribution<> >
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generatorC2(rng, normC2);
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for(int i = 0; i < population.size(); i++){
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float flag = generatorE();
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if(flag >= 0.0f){
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float deltaE = generatorE();
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population.at(i)->mutate(deltaE);
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}
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else{
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float deltaC2 = generatorC2();
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population.at(i)->mutateC2(deltaC2);
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}
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}
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}
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void Solver::selection(std::vector<Individ*>& population, float renewRate){
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std::sort(population.begin(),population.end(), compareOnFitness);
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int inds = population.size();
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float deathRate = renewRate;
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float birthRate = renewRate; //Settings::BirthRate;//0.02f;
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int toDie = int (inds* deathRate);
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std::vector<Individ*>::iterator start = population.begin();
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std::vector<Individ*>::iterator end = population.begin()+toDie;
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for(std::vector<Individ*>::iterator it = start; it != end; it++){
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delete *it;
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}
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population.erase(start, end);
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// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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int toBorn = int (inds * birthRate);
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inds = population.size();
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srand((unsigned int)time(NULL));
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for(int i = 0; i < toBorn; i++) {
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int parent = rand() % inds;
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Individ* ind;
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if(population.at(parent)->hasFeedBack()){
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ind = new IndividFeedBack(population.at(parent)->getE());
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ind->setC2(population.at(parent)->getC2());
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}
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else{
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ind = new Individ(population.at(parent)->getE());
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}
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// <20><><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD> <20> <20>.<2E>.
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population.push_back(ind);
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}
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} // (END) void selection(std::vector<Individ*>& population, float renewRate)
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void Solver::initialization(std::vector<Individ*>& population, int N_feedback){
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// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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int POP_SIZE = population.size();
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float E = Individ::getOptimalE();// Xopt*Individ::c[2]/Individ::c[0] - Individ::c[3];
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for(int i = 0; i < N_feedback; i++){
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Individ* ind = new Individ(E);
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population.at(i) = ind;
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}
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E = IndividFeedBack::getOptimalE();
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for(int i = N_feedback; i < POP_SIZE; i++){
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Individ* ind = new IndividFeedBack(E);
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population.at(i) = ind;
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}
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} // (END) void initialization(std::vector<Individ*>& population){
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void Solver::printStatistics(const std::vector<Individ*>& population, int i, int iters, int currentStep){
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// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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withFeedback = 0.f;
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withoutFeedback = 0.f;
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meanC2Feedback = 0.f;
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meanEFeedBack = 0.f;
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meanENonFeedBack = 0.f;
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for(int i = 0; i < population.size(); i++){
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if(population.at(i)->hasFeedBack()){
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withFeedback++;
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meanC2Feedback += population.at(i)->getC2();
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meanEFeedBack += population.at(i)->getE();
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}
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else{
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withoutFeedback++;
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meanENonFeedBack += population.at(i)->getE();
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}
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}
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if (iters == 1) //count average for additional iters
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{
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singleModelHistory[i].withFeedbackVect.push_back(withFeedback);
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singleModelHistory[i].withoutFeedbackVect.push_back(withoutFeedback);
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singleModelHistory[i].individ.push_back(Individ::getOptimalE());
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singleModelHistory[i].individFeedback.push_back(IndividFeedBack::getOptimalE());
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singleModelHistory[i].meanE.push_back(meanENonFeedBack/withoutFeedback);
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singleModelHistory[i].meanC2.push_back(meanC2Feedback/withFeedback);
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singleModelHistory[i].meanF.push_back(meanEFeedBack/withFeedback);
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if (i == 0)
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{
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singleModelHistory[modCount].withFeedbackVect.push_back(withFeedback);
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singleModelHistory[modCount].withoutFeedbackVect.push_back(withoutFeedback);
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singleModelHistory[modCount].meanE.push_back(meanENonFeedBack/withoutFeedback);
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singleModelHistory[modCount].meanF.push_back(meanEFeedBack/withFeedback);
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singleModelHistory[modCount].meanC2.push_back(meanC2Feedback/withFeedback);
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singleModelHistory[modCount].individ.push_back(Individ::getOptimalE());
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singleModelHistory[modCount].individFeedback.push_back(IndividFeedBack::getOptimalE());
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}
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else
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{
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singleModelHistory[modCount].withFeedbackVect[currentStep] += withFeedback;
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singleModelHistory[modCount].withoutFeedbackVect[currentStep] += withoutFeedback;
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singleModelHistory[modCount].meanE[currentStep] += meanENonFeedBack/withoutFeedback;
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singleModelHistory[modCount].meanF[currentStep] += meanEFeedBack/withFeedback;
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singleModelHistory[modCount].meanC2[currentStep] += meanC2Feedback/withFeedback;
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singleModelHistory[modCount].individ[currentStep] += Individ::getOptimalE();
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singleModelHistory[modCount].individFeedback[currentStep] += IndividFeedBack::getOptimalE();
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}
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}
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if (i == 0 && iters == 0) // count average for new calc
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{
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withFeedbackVectAvg.push_back(withFeedback);
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withoutFeedbackVectAvg.push_back(withoutFeedback);
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meanEAvg.push_back(meanENonFeedBack/withoutFeedback);
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meanFAvg.push_back(meanEFeedBack/withFeedback);
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meanC2Avg.push_back(meanC2Feedback/withFeedback);
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individAvg.push_back(Individ::getOptimalE());
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individFeedbackAvg.push_back(IndividFeedBack::getOptimalE());
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}
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else if (iters == 0)
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{
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withFeedbackVectAvg[currentStep] += withFeedback;
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withoutFeedbackVectAvg[currentStep] += withoutFeedback;
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meanEAvg[currentStep] += meanENonFeedBack/withoutFeedback;
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meanFAvg[currentStep] += meanEFeedBack/withFeedback;
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meanC2Avg[currentStep] += meanC2Feedback/withFeedback;
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individAvg[currentStep] += Individ::getOptimalE();
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individFeedbackAvg[currentStep] += IndividFeedBack::getOptimalE();
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}
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//add vectors for first calc
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withFeedbackVect.push_back(withFeedback);
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withoutFeedbackVect.push_back(withoutFeedback);
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meanE.push_back(meanENonFeedBack/withoutFeedback);
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meanF.push_back(meanEFeedBack/withFeedback);
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meanC2.push_back(meanC2Feedback/withFeedback);
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individ.push_back(Individ::getOptimalE());
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individFeedback.push_back(IndividFeedBack::getOptimalE());
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// std::cout<<"W/o fb\t"<<withoutFeedback<<"\tW/fb\t"<<withFeedback;
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// std::cout<<"\tOptE(w/o/fb)\t"<<Individ::getOptimalE();
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// std::cout<<"\tmE(w/o/fb)\t"<<meanENonFeedBack/withoutFeedback;
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// std::cout<<"\tOptE(w/fb)\t"<<IndividFeedBack::getOptimalE();
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// std::cout<<"\tmE(w/fb)\t"<<meanEFeedBack/withFeedback;
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// std::cout<<"\tmC2(w/fb)\t"<<meanC2Feedback/withFeedback;
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// std::cout<<std::endl;
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}
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