reffactored and recurrent implementation

include/NeuralNetwork/Neuron.h

@@ -0,0 +1,71 @@
+#pragma once
+
+#include <string>
+
+namespace NeuralNetwork
+{
+	/**
+	 * @author Tomas Cernik (Tom.Cernik@gmail.com)
+	 * @brief Abstract class of neuron. All Neuron classes should derive from this on
+	 */
+	class Neuron
+	{
+		public:
+
+			/**
+			 * @brief returns unique id for neuron
+			 */
+			virtual unsigned long id() const =0;
+
+			/**
+			 * @brief virtual destructor for Neuron
+			 */
+			virtual ~Neuron() {};
+
+			/**
+			 * @brief This is a virtual function for storing network
+			 * @returns json describing network and it's state
+			 */
+			virtual std::string stringify(const std::string &prefix="") const =0;
+
+			/**
+			 * @brief Gets weight
+			 * @param n is neuron
+			 */
+			virtual float getWeight(const Neuron &n) const =0;
+
+			/**
+			 * @brief Sets weight
+			 * @param n is neuron
+			 * @param w is new weight for input neuron n
+			 */
+			virtual void setWeight(const Neuron& n ,const float &w) =0;
+
+			/**
+			 * @brief Returns output of neuron
+			 */
+			virtual float output() const =0;
+
+			/**
+			 * @brief Returns input of neuron
+			 */
+			virtual float value() const=0;
+
+			/**
+			 * @brief Returns value for derivation of activation function
+			 */
+//			virtual float derivatedOutput() const=0;
+
+			/**
+			 * @brief Function sets bias for neuron
+			 * @param bias is new bias (initial value for neuron)
+			 */
+			virtual void setBias(const float &bias)=0;
+
+			/**
+			 * @brief Function returns bias for neuron
+			 */
+			virtual float getBias() const=0;
+		protected:
+	};
+}