int main(void){
struct parameters *params = NULL;
struct chromosome *chromoA = NULL;
struct chromosome *chromoB = NULL;
struct chromosome *chromoC = NULL;
struct dataSet *trainingData = NULL;
double testInputs[NUMINPUTS];
params = initialiseParameters(NUMINPUTS, NUMNODES, NUMOUTPUTS, ARITY);
addNodeFunction(params, "add,sub,mul,sq,cube,sin");
trainingData = initialiseDataSetFromFile("./dataSets/symbolic.data");
chromoA = initialiseChromosome(params);
chromoB = initialiseChromosome(params);
setChromosomeFitness(params, chromoA, trainingData);
mutateChromosome(params,chromoA);
copyChromosome(chromoB, chromoA);
removeInactiveNodes(chromoB);
printf("chromoA with inactive nodes.\n");
printChromosome(chromoA, 0);
printf("chromoB without inactive nodes.\n");
printChromosome(chromoB, 1);
saveChromosome(chromoB, "chromoB.chromo");
chromoC = initialiseChromosomeFromFile("chromoB.chromo");
testInputs[0] = 3;
executeChromosome(chromoC, testInputs);
printf("Applied input: %f\n", testInputs[0]);
printf("Generated output: %f\n", getChromosomeOutput(chromoC, 0));
freeChromosome(chromoA);
freeChromosome(chromoB);
freeChromosome(chromoC);
freeDataSet(trainingData);
freeParameters(params);
return 0;
}
int main(void){
struct parameters *params = NULL;
struct chromosome *chromo = NULL;
int numInputs = 1;
int numNodes = 20;
int numOutputs = 1;
int nodeArity = 5;
int numGens = 25000;
double targetFitness = 0.5;
int updateFrequency = 500;
double weightRange = 5;
params = initialiseParameters(numInputs, numNodes, numOutputs, nodeArity);
setTargetFitness(params, targetFitness);
setUpdateFrequency(params, updateFrequency);
setConnectionWeightRange(params, weightRange);
setCustomFitnessFunction(params, sinWave, "sinWave");
addNodeFunction(params, "tanh,softsign");
chromo = runCGP(params, NULL, numGens);
printChromosome(chromo, 1);
freeChromosome(chromo);
freeParameters(params);
return 0;
}
int main(){
//printf(" *** Real time multiprocessor allocator***\n");
int i;
int maxGen = MAXGEN+1;
int nrGen = 0; // Number of generations
ga * ga = (struct ga *) malloc(sizeof(struct ga));
FILE * fitnessFile;
FILE * chromosomeFile;
remove("chromosome0mut0crossElitism.txt");
remove("fitness0mut0crossElitism.txt");
fitnessFile = fopen("fitness0mut0crossElitism.txt", "w");
chromosomeFile = fopen("chromosome0mut0crossElitism.txt", "w");
fprintf(fitnessFile, "%s", "Number of generations, Best Machine, Best fitness, Average fitness \n");
fprintf(chromosomeFile, "%s", "Machine number, TDF, PHYSICAL CORE id, U, Vcore id, Slice, Period, Pcore\n");
srand(time(NULL));
//printf("Initializing GA\n");
initGA(ga);
//printf("Evaluating fitness\n");
evaluateFitness(ga);
fprintf(fitnessFile, "%d, %d, %f, %f\n", nrGen, ga->bestMachineIndex,ga->bestFitness, ga->avgFitness);
fprintf(chromosomeFile, "%s", "Generation 0\n");
for (i = 0; i < ga->populationSize; i++)
printChromosome(&(ga->population[i]), chromosomeFile);
nrGen++;
//for (i = 0; i < ga->populationSize; i++)
// printMachineParameters(&(ga->population[i]));
//while(nrGen < maxGen && ga->bestFitness<1.0 ){
while(nrGen < maxGen && ga->bestFitness<1.0 ){
printf("Selection for gen %d ...\n", nrGen);
selection(ga);
printf("Mutation for gen %d ...\n", nrGen);
mutation(ga);
printf("Crossover for gen %d ...\n", nrGen);
crossover(ga);
printf("Evaluating fitness for gen %d ...\n", nrGen);
evaluateFitness(ga);
fprintf(fitnessFile, "%d, %d, %f, %f\n", nrGen, ga->bestMachineIndex, ga->bestFitness, ga->avgFitness);
fprintf(chromosomeFile, "Generation %d", nrGen);
for (i = 0; i < ga->populationSize; i++)
printChromosome(&(ga->population[i]), chromosomeFile);
/* printf("Number of generations %d, ", nrGen);
printf("Best fitness: %f, ", ga->bestFitness);
printf("Average fitness: %f \n", ga->avgFitness);
//for (i = 0; i < ga->populationSize; i++)
// printMachineParameters(&(ga->population[i]));
*/
nrGen++;
} // end while
fclose(chromosomeFile);
fclose(fitnessFile);
freeGA(ga);
return 0;
}
