Method crossover

src/GeneticAlgo.cpp:19–53

}

void GeneticAlgo::crossover(net::NeuralNet mom, net::NeuralNet dad, net::NeuralNet *offspring1, net::NeuralNet *offspring2) {
	float crossoverDeterminer = (float)rand() / (float)RAND_MAX;
	if(crossoverDeterminer > crossoverRate) {
		*offspring1 = mom;
		*offspring2 = dad;
		return;
	}

	std::vector<double> offspring1Weights;
	std::vector<double> offspring2Weights;
	std::vector<double> momWeights = mom.getWeights();
	std::vector<double> dadWeights = dad.getWeights();

	/// Crossover index must be a minimum of 1 and a maxiumum of the second to last index of the weights
	int crossoverIndex = (rand() % (momWeights.size() - 2)) + 1;

	for(int a = 0; a < crossoverIndex; a++) {
		offspring1Weights.push_back(momWeights[a]);
		offspring2Weights.push_back(dadWeights[a]);
	}
	for(unsigned int a = crossoverIndex; a < momWeights.size(); a++) {
		offspring1Weights.push_back(dadWeights[a]);
		offspring2Weights.push_back(momWeights[a]);
	}

	*offspring1 = net::NeuralNet(mom);
	offspring1->setWeights(offspring1Weights);
	*offspring2 = net::NeuralNet(dad);
	offspring2->setWeights(offspring2Weights);

	std::vector<double>().swap(offspring1Weights);
	std::vector<double>().swap(offspring2Weights);
	std::vector<double>().swap(momWeights);
	std::vector<double>().swap(dadWeights);
}

void GeneticAlgo::mutate(net::NeuralNet *net) {
	std::vector<double> weights = net->getWeights();