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Init version

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This commit is contained in:
Aleksey M. Mukhin
2024-10-03 18:43:04 +07:00
commit f80052961f
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125
processor/KolchShindyalov.cpp Normal file
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#include "Settings.h"
#include "../population/Population.h"
#include "../individual/Phenotype.h"
#include "../individual/genome/strategies/GenotypeToPhenotypeStrategy.h"
#include <fstream>
#include <string>
#include <sstream>
#include "KolchShindyalov.h"
void KolchShindyalov::test01(){
std::ofstream statFile("statFile.txt");
std::string stat;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
int maxGenerations = Settings::Iterations;
long initPopSize = Settings::InitPopSize;
float ratioBetweenPops = Settings::InitRatioBetweenPops;
long int maxIndivids = Settings::KMaxParameter;
Position3D<double> position(0, 0, 0, 1000, 1000, 1000);
Region region(position, maxIndivids);
srand(0);
int RANGE = 1000;
int PRECISION = 10;
float gValue;
std::vector<Individual*> individs;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
for(int i = 0; i < initPopSize; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD>
std::vector<Chromosome> fGenome;
std::vector<Chromosome> mGenome;
std::vector<Chromosome> chroms;
for(int j = 0; j < 2; j++){
//float gValue
// <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
RANGE = 10;
gValue = -(float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF1(Gene::Continious, "C1", gValue);
gValue = -(float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF2(Gene::Continious, "C2", gValue);
PRECISION=1;
RANGE = 2;
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF3(Gene::Continious, "C3", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF4(Gene::Continious, "C4", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF5(Gene::Continious, "C5", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF6(Gene::Continious, "E", gValue);
gValue = rand()%2;
Gene geneF7(Gene::Discrete,"Feedback", gValue);
Chromosome chromF("Chrom 1"); // <20><><EFBFBD><EFBFBD> / <20><><EFBFBD><EFBFBD>
chromF.insertGeneToEnd(geneF1);
chromF.insertGeneToEnd(geneF2);
chromF.insertGeneToEnd(geneF3);
chromF.insertGeneToEnd(geneF4);
chromF.insertGeneToEnd(geneF5);
chromF.insertGeneToEnd(geneF6);
chromF.insertGeneToEnd(geneF7);
chroms.push_back(chromF);
} // (END) for(int i = 0; i < 2; i++)
fGenome.push_back(chroms.at(0));
mGenome.push_back(chroms.at(1));
Genotype* genotype = new Genotype(fGenome, mGenome);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Trait trait1(Trait::Continious, "X", 10.0f);
Trait trait2(Trait::Continious, "Xopt", 10.0f);
Trait trait3(Trait::Continious, "sigmaX", 3.0f);
Phenotype* phenotype = new Phenotype(trait1);
phenotype->addTrait(trait2);
phenotype->addTrait(trait3);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Individual* newInd = new Individual(genotype, phenotype, 0, Individual::hermaphrodite, 0);
newInd->setGenToPhenStrategy(GenotypeToPhenotypeStrategies::getInstance("kolchan_shindyal_gen_to_phen"));
newInd->setPhenToFitnessStrategy(PhenotypeToFitnessStrategy::getInstance("kolch_shindyal_phen_to_fit"));
individs.push_back(newInd);
} // (END) for(int i = 0; i < size; i++)
AsexualPopulation population(individs);
population.setBreedingStrategy(PopulationBreedingStrategy::getInstance("kolchan_shindyal_breeding"));
population.setRegion(&region);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
for(int i = 0; i < maxGenerations; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.breedAll();
//--- <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ---
stat = population.getSatistics();
statFile<<stat<<std::endl;
if(Settings::WRITE_FULL_STATISTICS_TO_FILE){
std::stringstream ss;
std::stringstream ss2;
std::stringstream ss3;
ss<<"generation."<<(i)<<".xls";
ss2<<"generation."<<(i)<<".txt";
ss3<<"gmaxAB."<<(i)<<".txt";
std::ofstream genFile(ss.str().c_str());
std::ofstream genFile2(ss2.str().c_str());
std::ofstream genFile3(ss3.str().c_str());
population.putGeneticStatisticsToStream(genFile);
population.putGeneticSimpleStatisticsToStream(genFile2);
population.putGeneticMaxModuleStatisticsToStream(genFile3);
genFile.close();
genFile2.close();
genFile3.close();
}
//------------------
}
statFile.close();
}

6
processor/KolchShindyalov.h Normal file
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#pragma once
class KolchShindyalov{
public:
static void test01(/*int, int*/);
};

372
processor/Processor.cpp Normal file
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#include "Processor.h"
#include "Settings.h"
#include "../population/Population.h"
#include "../individual/Phenotype.h"
#include "../individual/genome/strategies/GenotypeToPhenotypeStrategy.h"
#include <fstream>
#include <string>
#include <sstream>
void Processor::test(/*int initPSize, int steps*/){
std::ofstream statFile("statFile.txt");
std::string stat;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
int maxGenerations = Settings::Iterations;
int initPopSize = Settings::InitPopSize;
AsexualPopulation population(initPopSize);
population.setBreedingStrategy(PopulationBreedingStrategy::getInstance(Settings::BreedingStrategy));
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
for(int i = 0; i < maxGenerations; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD>)
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
population.calculateFitnessAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.breedAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.mutationAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD> <20><><EFBFBD>)
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20>.<2E>.)
population.selectionAll();
//--- <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ---
stat = population.getSatistics();
statFile<<stat<<std::endl;
if(Settings::WRITE_FULL_STATISTICS_TO_FILE){
std::stringstream ss;
ss<<"generation."<<(i)<<".txt";
std::ofstream genFile(ss.str().c_str());
population.putGeneticStatisticsToStream(genFile);
genFile.close();
}
//------------------
}
statFile.close();
}
void Processor::test01(/*int initPSize, int steps*/){
std::ofstream statFile("statFile.txt");
std::string stat;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
int maxGenerations = Settings::Iterations;
long initPopSize = Settings::InitPopSize;
long int maxIndivids = Settings::KMaxParameter;
Position3D<double> position(0, 0, 0, 1000, 1000, 1000);
Region region(position, maxIndivids);
AsexualPopulation population(initPopSize);
population.setBreedingStrategy(PopulationBreedingStrategy::getInstance(Settings::BreedingStrategy));
population.setRegion(&region);
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
for(int i = 0; i < maxGenerations; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD>)
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
population.calculateFitnessAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.breedAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.mutationAll();
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD> <20><><EFBFBD>)
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20>.<2E>.)
population.selectionAll();
//--- <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ---
stat = population.getSatistics();
statFile<<stat<<std::endl;
if(Settings::WRITE_FULL_STATISTICS_TO_FILE){
std::stringstream ss;
ss<<"generation."<<(i)<<".txt";
std::ofstream genFile(ss.str().c_str());
population.putGeneticStatisticsToStream(genFile);
genFile.close();
}
//------------------
}
statFile.close();
}
///
void Processor::testInOutBreeding01(){
std::ofstream statFile("statFile.txt");
std::string stat;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
int maxGenerations = Settings::Iterations;
long initPopSize = Settings::InitPopSize;
long int maxIndivids = Settings::KMaxParameter;
Position3D<double> position(0, 0, 0, 1000, 1000, 1000);
Region region(position, maxIndivids);
srand(0);
int RANGE = 1000;
int PRECISION = 10;
float gValue;
std::vector<Individual*> individs;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
for(int i = 0; i < maxIndivids/2; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD>
std::vector<Chromosome> fGenome;
std::vector<Chromosome> mGenome;
std::vector<Chromosome> chroms;
for(int j = 0; j < 2; j++){
// <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
RANGE = 10;
gValue = (float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF1(Gene::Continious, "A coadaptive", gValue);
gValue = (float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF2(Gene::Continious, "B coadaptive", gValue);
RANGE = 2;
gValue = (rand()%(RANGE + 1)) / (float) RANGE;
Gene geneF3(Gene::Continious, "C disease", gValue);
gValue = (rand()%(RANGE + 1)) / (float) RANGE;
Gene geneF4(Gene::Continious, "D disease", gValue);
gValue = (rand()%(RANGE + 1)) / (float) RANGE;
Gene geneF5(Gene::Continious, "E disease", gValue);
gValue = (rand()%(RANGE + 1)) / (float) RANGE;
Gene geneF6(Gene::Continious, "F disease", gValue);
Chromosome chromF("Chrom 1"); // <20><><EFBFBD><EFBFBD> / <20><><EFBFBD><EFBFBD>
chromF.insertGeneToEnd(geneF1);
chromF.insertGeneToEnd(geneF2);
chromF.insertGeneToEnd(geneF3);
chromF.insertGeneToEnd(geneF4);
chromF.insertGeneToEnd(geneF5);
chromF.insertGeneToEnd(geneF6);
chroms.push_back(chromF);
} // (END) for(int i = 0; i < 2; i++)
fGenome.push_back(chroms.at(0));
mGenome.push_back(chroms.at(1));
Genotype* genotype = new Genotype(fGenome, mGenome);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Trait trait1(Trait::Continious, "coadaptive", 0.0f);
Trait trait2(Trait::Continious, "disease", 0.0f);
Phenotype* phenotype = new Phenotype(trait1);
phenotype->addTrait(trait2);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
InnerSubstratesPool* subPool = 0;
// (END) <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Individual* newInd = new Individual(genotype, phenotype, subPool, Individual::hermaphrodite, 0);
newInd->setGenToPhenStrategy(GenotypeToPhenotypeStrategies::getInstance("inoutbreeding"));
individs.push_back(newInd);
} // (END) for(int i = 0; i < size; i++)
AsexualPopulation population(individs);
population.setBreedingStrategy(PopulationBreedingStrategy::getInstance("inoutbreeding"));
population.setRegion(&region);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
for(int i = 0; i < maxGenerations; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.breedAll();
//--- <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ---
stat = population.getSatistics();
statFile<<stat<<std::endl;
if(Settings::WRITE_FULL_STATISTICS_TO_FILE){
std::stringstream ss;
std::stringstream ss2;
ss<<"generation."<<(i)<<".xls";
ss2<<"generation."<<(i)<<".txt";
std::ofstream genFile(ss.str().c_str());
std::ofstream genFile2(ss2.str().c_str());
population.putGeneticStatisticsToStream(genFile);
population.putGeneticSimpleStatisticsToStream(genFile2);
genFile.close();
genFile2.close();
}
//------------------
}
statFile.close();
}
/////////////////////////////////////////////////////
void Processor::testInOutBreeding02(){
std::ofstream statFile("statFile.txt");
std::string stat;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
int maxGenerations = Settings::Iterations;
long initPopSize = Settings::InitPopSize;
float ratioBetweenPops = Settings::InitRatioBetweenPops;
long int maxIndivids = Settings::KMaxParameter;
Position3D<double> position(0, 0, 0, 1000, 1000, 1000);
Region region(position, maxIndivids);
srand(0);
int RANGE = 1000;
int PRECISION = 10;
float gValue;
std::vector<Individual*> individs;
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> - <20><><EFBFBD><EFBFBD><EFBFBD> 1
for(int i = 0; i < initPopSize*ratioBetweenPops; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD>
std::vector<Chromosome> fGenome;
std::vector<Chromosome> mGenome;
std::vector<Chromosome> chroms;
for(int j = 0; j < 2; j++){
// <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
RANGE = 10;
gValue = (float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF1(Gene::Continious, "A coadaptive", gValue);
gValue = (float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF2(Gene::Continious, "B coadaptive", gValue);
RANGE = 2;
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF3(Gene::Continious, "C disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF4(Gene::Continious, "D disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF5(Gene::Continious, "E disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF6(Gene::Continious, "F disease", gValue);
Chromosome chromF("Chrom 1"); // <20><><EFBFBD><EFBFBD> / <20><><EFBFBD><EFBFBD>
chromF.insertGeneToEnd(geneF1);
chromF.insertGeneToEnd(geneF2);
chromF.insertGeneToEnd(geneF3);
chromF.insertGeneToEnd(geneF4);
chromF.insertGeneToEnd(geneF5);
chromF.insertGeneToEnd(geneF6);
chroms.push_back(chromF);
} // (END) for(int i = 0; i < 2; i++)
fGenome.push_back(chroms.at(0));
mGenome.push_back(chroms.at(1));
Genotype* genotype = new Genotype(fGenome, mGenome);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Trait trait1(Trait::Continious, "coadaptive", 0.0f);
Trait trait2(Trait::Continious, "disease", 0.0f);
Phenotype* phenotype = new Phenotype(trait1);
phenotype->addTrait(trait2);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Individual* newInd = new Individual(genotype, phenotype, 0, Individual::hermaphrodite, 0);
newInd->setGenToPhenStrategy(GenotypeToPhenotypeStrategies::getInstance("inoutbreeding"));
individs.push_back(newInd);
} // (END) for(int i = 0; i < size; i++)
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> - <20><><EFBFBD><EFBFBD><EFBFBD> 2
for(int i = 0; i < initPopSize; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD>
std::vector<Chromosome> fGenome;
std::vector<Chromosome> mGenome;
std::vector<Chromosome> chroms;
for(int j = 0; j < 2; j++){
// <20><><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
RANGE = 10;
gValue = -(float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF1(Gene::Continious, "A coadaptive", gValue);
gValue = -(float)(rand()%(RANGE*PRECISION+1))/PRECISION;
Gene geneF2(Gene::Continious, "B coadaptive", gValue);
PRECISION=1;
RANGE = 2;
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF3(Gene::Continious, "C disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF4(Gene::Continious, "D disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF5(Gene::Continious, "E disease", gValue);
gValue = (rand()%(RANGE*PRECISION + 1)) / (float) RANGE / PRECISION;
Gene geneF6(Gene::Continious, "F disease", gValue);
Chromosome chromF("Chrom 1"); // <20><><EFBFBD><EFBFBD> / <20><><EFBFBD><EFBFBD>
chromF.insertGeneToEnd(geneF1);
chromF.insertGeneToEnd(geneF2);
chromF.insertGeneToEnd(geneF3);
chromF.insertGeneToEnd(geneF4);
chromF.insertGeneToEnd(geneF5);
chromF.insertGeneToEnd(geneF6);
chroms.push_back(chromF);
} // (END) for(int i = 0; i < 2; i++)
fGenome.push_back(chroms.at(0));
mGenome.push_back(chroms.at(1));
Genotype* genotype = new Genotype(fGenome, mGenome);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Trait trait1(Trait::Continious, "coadaptive", 0.0f);
Trait trait2(Trait::Continious, "disease", 0.0f);
Phenotype* phenotype = new Phenotype(trait1);
phenotype->addTrait(trait2);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
Individual* newInd = new Individual(genotype, phenotype, 0, Individual::hermaphrodite, 0);
newInd->setGenToPhenStrategy(GenotypeToPhenotypeStrategies::getInstance("inoutbreeding"));
individs.push_back(newInd);
} // (END) for(int i = 0; i < size; i++)
AsexualPopulation population(individs);
population.setBreedingStrategy(PopulationBreedingStrategy::getInstance("inoutbreeding"));
population.setRegion(&region);
// (END) <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
for(int i = 0; i < maxGenerations; i++){
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
population.breedAll();
//--- <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ---
stat = population.getSatistics();
statFile<<stat<<std::endl;
if(Settings::WRITE_FULL_STATISTICS_TO_FILE){
std::stringstream ss;
std::stringstream ss2;
std::stringstream ss3;
ss<<"generation."<<(i)<<".xls";
ss2<<"generation."<<(i)<<".txt";
ss3<<"gmaxAB."<<(i)<<".txt";
std::ofstream genFile(ss.str().c_str());
std::ofstream genFile2(ss2.str().c_str());
std::ofstream genFile3(ss3.str().c_str());
population.putGeneticStatisticsToStream(genFile);
population.putGeneticSimpleStatisticsToStream(genFile2);
population.putGeneticMaxModuleStatisticsToStream(genFile3);
genFile.close();
genFile2.close();
genFile3.close();
}
//------------------
}
statFile.close();
}

11
processor/Processor.h Normal file
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#pragma once
class Processor{
public:
static void test(/*int, int*/);
static void test01(/*int, int*/);
static void testInOutBreeding01();
static void testInOutBreeding02();
};

163
processor/Settings.cpp Normal file
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#include "Settings.h"
#include <vector>
#include <iostream>
#include <fstream>
#include <cstdio>
#include <boost/algorithm/string.hpp>
#include <boost/tokenizer.hpp>
#ifdef LINUX
#define sscanf_s sscanf
#endif
// Default parameters
bool Settings::WRITE_FULL_STATISTICS_TO_FILE = false;
int Settings::Iterations = 10;
long int Settings::InitPopSize = 10;
float Settings::InitRatioBetweenPops = 1.f;
double Settings::BirthRate = 0.01;
double Settings::NaturalDeathRate = 0.01;
long int Settings::KMaxParameter = 10000;
int Settings::OffspringsMean = 3;
float Settings::CoadaptiveThreshold = 0;
float Settings::CoadaptiveMinimumP = 0.2f;
float Settings::CoadaptiveMaximumTrait = 15.f;
float Settings::DiseaseThreshold = 1;
std::string Settings::CoadaptiveGenesInteraction = "onechromosome";
std::string Settings::DiseaseGenesInteraction = "add";
std::string Settings::BreedingStrategy = "default";
std::string Settings::GenToPhenStrategy = "default";
std::string Settings::PhenToFitStrategy = "default";
std::string Settings::RecombinationStrategy = "default";
double Settings::ProbMtDNARecomb = 0.0;
int Settings::PopulationHomoInitSize = 1000;
int Settings::PopulationAncientInitSize = 1000;
double Settings::migrationPartHomoToAncient = 0.1;
double Settings::migrationPartAncientToHomo = 0.1;
int Settings::generationsPerMigration = 100;
int Settings::locusLength = 60;
double Settings::percentDiffLoci = 0.1;
int Settings::numLoci = 50;
// (END) Default parameters
void Settings::initScript(std::string fileName){
std::vector<std::string> script;
std::ifstream file(fileName.c_str());
std::string str;
while(getline(file,str)){
if(str.length() > 2)
script.push_back(str);
}
file.close();
// process Script
unsigned int curLine;
for(curLine = 0; curLine < script.size(); curLine++){
if(script.at(curLine).at(0) == '/' || script.at(curLine).at(0) == '#')
continue;
std::vector<std::string > tokensVector; // Search for tokens
boost::split(tokensVector, script.at(curLine), boost::is_any_of("=") );
std::string instr = tokensVector.at(0);
boost::to_lower(instr);
boost::trim(instr);
// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
if(instr == "fullstat"){
int flag = 0;
sscanf_s(tokensVector.at(1).c_str(),"%d", &flag);
if(flag != 0)
Settings::WRITE_FULL_STATISTICS_TO_FILE = true;
}
else if(instr == "generations" || instr == "iterations" ){
int iter = Settings::Iterations;
sscanf_s(tokensVector.at(1).c_str(),"%d", &iter);
Settings::Iterations = iter;
}
else if(instr == "initpopsize" || instr == "init_pop_size" || instr == "popsize" ){
long int size = Settings::InitPopSize;
sscanf_s(tokensVector.at(1).c_str(),"%ld", &size);
Settings::InitPopSize = size;
}
else if(instr == "initratio" || instr == "init_ratio" || instr == "init_ratio_between_pop_size" ){
float size = Settings::InitRatioBetweenPops;
sscanf_s(tokensVector.at(1).c_str(),"%f", &size);
Settings::InitRatioBetweenPops = size;
}
else if(instr == "birth" || instr == "birthrate" || instr == "birth_rate" ){
double rate = Settings::BirthRate;
sscanf_s(tokensVector.at(1).c_str(),"%lg", &rate);
Settings::BirthRate = rate;
}
else if(instr == "death" || instr == "deathrate" || instr == "death_rate" ){
double rate = Settings::NaturalDeathRate;
sscanf_s(tokensVector.at(1).c_str(),"%lg", &rate);
Settings::NaturalDeathRate = rate;
}
else if(instr == "kmax"){
long int kMax = Settings::KMaxParameter;
sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
Settings::KMaxParameter = kMax;
}
else if(instr == "offsprings" || instr == "offsprings_mean" ){
int offsprings = Settings::OffspringsMean;
sscanf_s(tokensVector.at(1).c_str(),"%d", &offsprings);
Settings::OffspringsMean = offsprings;
}
else if(instr == "coadaptivet" || instr == "coadaptive_threshold" ){
float coadaptive = Settings::CoadaptiveThreshold;
sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
Settings::CoadaptiveThreshold = coadaptive;
}
else if(instr == "coadaptivemax" || instr == "coadaptive_maximum_trait" ){
float coadaptive = Settings::CoadaptiveMaximumTrait;
sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
Settings::CoadaptiveMaximumTrait = coadaptive;
}
else if(instr == "coadaptivemin" || instr == "coadaptive_minimum_p" ){
float coadaptive = Settings::CoadaptiveMinimumP;
sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
Settings::CoadaptiveMinimumP = coadaptive;
}
else if(instr == "diseaset" || instr == "disease_threshold" ){
float disease = Settings::DiseaseThreshold;
sscanf_s(tokensVector.at(1).c_str(),"%f", &disease);
Settings::DiseaseThreshold = disease;
}
else if(instr == "coadaptivegenesinteract" || instr == "cgi"){
//long int kMax = Settings::KMaxParameter;
//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
std::string cgi = tokensVector.at(1);
boost::to_lower(cgi);
boost::trim(cgi);
Settings::CoadaptiveGenesInteraction = cgi;
}
else if(instr == "diseasegenesinteract" || instr == "dgi"){
//long int kMax = Settings::KMaxParameter;
//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
std::string dgi = tokensVector.at(1);
boost::to_lower(dgi);
boost::trim(dgi);
Settings::DiseaseGenesInteraction = dgi;
}
//*****************************
else if(instr == "breedings"){
//long int kMax = Settings::KMaxParameter;
//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
std::string strategy = tokensVector.at(1);
boost::to_lower(strategy);
boost::trim(strategy);
Settings::BreedingStrategy = strategy;
}
} // (END) for(curLine = 0; curLine < script.size(); curLine++)
}

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processor/Settings.h Normal file
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#pragma once
#include <string>
class Settings {
public:
static bool WRITE_FULL_STATISTICS_TO_FILE;
static int Iterations;
static long int InitPopSize;
static float InitRatioBetweenPops;
// Common breeding strategies parameters
static double BirthRate;
static double NaturalDeathRate;
// Verhulst breeding strategy default parameters
static long int KMaxParameter; // r*X*(1 - X/KMax)
// Inbreeding/Outbreeding model parameters
static int OffspringsMean;
static float CoadaptiveThreshold;
static float CoadaptiveMinimumP;
static float CoadaptiveMaximumTrait;
static float DiseaseThreshold;
static std::string CoadaptiveGenesInteraction;
static std::string DiseaseGenesInteraction;
static std::string BreedingStrategy;
static std::string GenToPhenStrategy;
static std::string PhenToFitStrategy;
static std::string RecombinationStrategy;
static double ProbMtDNARecomb;
static int PopulationHomoInitSize;
static int PopulationAncientInitSize;
static double migrationPartHomoToAncient;
static double migrationPartAncientToHomo;
static int generationsPerMigration;
static int locusLength;
static double percentDiffLoci;
static int numLoci;
public:
static void initScript(std::string fileName);
};