From 26a51ce476c2304df7236628c3392327bd4489b0 Mon Sep 17 00:00:00 2001
From: Michael Mandl <mandlm@molez.net>
Date: Fri, 16 Oct 2015 23:23:27 +0200
Subject: [PATCH] Hidden neuron gradients complete

---
 Neuron.cpp | 11 ++++++++++-
 Neuron.h   |  2 ++
 2 files changed, 12 insertions(+), 1 deletion(-)

diff --git a/Neuron.cpp b/Neuron.cpp
index 5fc8944..29aebb4 100644
--- a/Neuron.cpp
+++ b/Neuron.cpp
@@ -1,6 +1,7 @@
 #pragma once
 
 #include "Neuron.h"
+#include "Layer.h"
 
 Neuron::Neuron(double value)
 	: outputValue(value)
@@ -64,7 +65,10 @@ double Neuron::sumDOW(const Layer & nextLayer) const
 {
 	double sum = 0;
 
-	// sum it up
+	for (size_t i = 0; i < nextLayer.size() - 1; ++i)
+	{
+		sum += outputWeights[i] * nextLayer[i].getGradient();
+	}
 
 	return sum;
 }
@@ -75,3 +79,8 @@ void Neuron::calcHiddenGradients(const Layer &nextLayer)
 	gradient = dow * transferFunctionDerivative(outputValue);
 }
 
+double Neuron::getGradient() const
+{
+	return gradient;
+}
+
diff --git a/Neuron.h b/Neuron.h
index 51d68ed..862c17d 100644
--- a/Neuron.h
+++ b/Neuron.h
@@ -23,6 +23,8 @@ public:
 	void calcOutputGradients(double targetValue);
 	void calcHiddenGradients(const Layer &nextLayer);
 
+	double getGradient() const;
+
 private:
 	static double transferFunction(double inputValue);
 	static double transferFunctionDerivative(double inputValue);