std::vector<ParseTree*> XPathTokenElement::evaluate(ParseTree* t) {
// return all children of t that match nodeName
std::vector<ParseTree*> nodes;
for (auto c : t->children) {
if (antlrcpp::is<TerminalNode*>(c)) {
TerminalNode* tnode = dynamic_cast<TerminalNode*>(c);
if ((tnode->getSymbol()->getType() == _tokenType && !_invert) ||
(tnode->getSymbol()->getType() != _tokenType && _invert)) {
nodes.push_back(tnode);
}
}
}
return nodes;
}
int GpModel::main( int argc, char** argv ) {
GpModel model(30);
model.setCrossoverOperator(new RegularAndFairSizeCrossover(200));
model.setMutationOperator(new RegularMutation());
model.setReproductionOperator(new RegularReproduction());
model.getTreeGenerator().setPreferredDepth(2);
model.getTreeGenerator().setPreferredMethod(TreeGenerator::M_RAMPED);
model.setLowerFitnessBetter(true);
model.create();
model.setProbabilityCrossover(1.0);
model.setProbabilityMutation(0.01);
model.setProbabilityReproduction(1 - (model.getProbabilityCrossover() + model.getProbabilityMutation()));
TestFunctionListener listener;
// for (int i = 0; i < 1000; ++i) {
int i = 0;
while (true) {
++i;
double average_fitness = 0.0;
double average_size = 0.0;
for (int j = 0; j < model.getPopulationSize(); ++j) {
TerminalNode* node = model.evaluate(model.getTree(j), listener);
int fitness = node->getValue();
delete node;
model.getTree(j).setFitness(abs(fitness));
average_fitness += abs(fitness);
average_size += model.getTree(j).getSize();
}
BDEBUG("avg-size=" + TO_STRING(average_size / model.getPopulationSize()) + "\tavg-fitness=" + TO_STRING(average_fitness / model.getPopulationSize()) + "\tepoch=" + TO_STRING(i) + "");
model.step();
// model.crossover();
}
return 0;
}
