Neuron change

src/NeuralNetwork/FeedForward/Layer.cpp

@@ -4,7 +4,7 @@ void NeuralNetwork::FeedForward::Layer::solve(const std::vector<float> &input, s
 	output.resize(neurons.size());
 
 	for(auto &neuron:neurons) {
-		output[neuron.id()]=neuron(input);
+		output[neuron->id()]=neuron->operator()(input);
 	}
 
 }

src/NeuralNetwork/FeedForward/Network.cpp

@@ -2,15 +2,27 @@
 
 std::vector<float> NeuralNetwork::FeedForward::Network::computeOutput(const std::vector<float>& input) {
 	// this is here for simple swapping between input and output
-	std::vector<float> partial1=input;
+	std::vector<float> partial1=std::vector<float>(input.size()+1);
 	std::vector<float> partial2;
 	std::vector<float> *partialInputPtr = &partial1;
 	std::vector<float> *partialOutputPtr = &partial2;
 
-	for(int i=1;i<layers.size();i++) {
+	// 0 is bias
+	partial1[0]=1.0;
+	for(int i=0;i<input.size();i++) {
+		partial1[i+1]=input[i];
+	}
+
+	for(std::size_t i=1;i<layers.size();i++) {
 		layers[i].solve(*partialInputPtr,*partialOutputPtr);
 		std::swap(partialInputPtr,partialOutputPtr);
 	}
 
+	for(int i=0;i<partialInputPtr->size()-1;i++) {
+		partialInputPtr->operator[](i)=partialInputPtr->operator[](i+1);
+	}
+
+	partialInputPtr->resize(partialInputPtr->size()-1);
+
 	return std::vector<float>(*partialInputPtr);
 }