From f22e4221a1c2f2fb381c6df7ceafe0e5195ef428 Mon Sep 17 00:00:00 2001
From: Michael Mandl <mandlm@molez.net>
Date: Thu, 22 Oct 2015 16:02:27 +0200
Subject: [PATCH] Fixed feed-forward algo

---
 Layer.cpp  |  9 ++++-----
 Neuron.cpp | 20 ++++++++++++++++++++
 Neuron.h   |  5 +++++
 3 files changed, 29 insertions(+), 5 deletions(-)

diff --git a/Layer.cpp b/Layer.cpp
index a38ba24..76d524a 100644
--- a/Layer.cpp
+++ b/Layer.cpp
@@ -23,11 +23,10 @@ void Layer::setOutputValues(const std::vector<double> & outputValues)
 }
 
 void Layer::feedForward(const Layer &inputLayer)
-{
-	int neuronNumber = 0;
-	for (auto neuronIt = begin(); neuronIt != end(); ++neuronIt)
+{	
+	for (int neuronNumber = 0; neuronNumber < sizeWithoutBiasNeuron(); ++neuronNumber)
 	{
-		neuronIt->feedForward(inputLayer.getWeightedSum(neuronNumber++));
+		at(neuronNumber).feedForward(inputLayer.getWeightedSum(neuronNumber));
 	}
 }
 
@@ -47,7 +46,7 @@ void Layer::connectTo(const Layer & nextLayer)
 {
 	for (Neuron &neuron : *this)
 	{
-		neuron.createRandomOutputWeights(nextLayer.size());
+		neuron.createOutputWeights(nextLayer.sizeWithoutBiasNeuron(), 0.5);
 	}
 }
 
diff --git a/Neuron.cpp b/Neuron.cpp
index 7083f99..2e2cff8 100644
--- a/Neuron.cpp
+++ b/Neuron.cpp
@@ -50,6 +50,26 @@ void Neuron::createRandomOutputWeights(size_t numberOfWeights)
 	}
 }
 
+void Neuron::createOutputWeights(std::list<double> weights)
+{
+	outputWeights.clear();
+
+	for (const double &weight : weights)
+	{
+		outputWeights.push_back(weight);
+	}
+}
+
+void Neuron::createOutputWeights(size_t numberOfWeights, double weight)
+{
+	outputWeights.clear();
+
+	for (unsigned int i = 0; i < numberOfWeights; ++i)
+	{
+		outputWeights.push_back(weight);
+	}
+}
+
 double Neuron::getOutputValue() const
 {
 	return outputValue;
diff --git a/Neuron.h b/Neuron.h
index c0356d3..b5e13c2 100644
--- a/Neuron.h
+++ b/Neuron.h
@@ -1,6 +1,7 @@
 #pragma once
 
 #include <vector>
+#include <list>
 
 class Layer;
 
@@ -17,7 +18,11 @@ public:
 	void setOutputValue(double value);
 	void feedForward(double inputValue);
 	double getWeightedOutputValue(unsigned int outputNeuron) const;
+	
 	void createRandomOutputWeights(size_t numberOfWeights);
+	void createOutputWeights(std::list<double> weights);
+	void createOutputWeights(size_t numberOfWeights, double weight);
+
 	double getOutputValue() const;
 
 	void calcOutputGradients(double targetValue);