removing potentials

src/NeuralNetwork/FeedForward.cpp

@@ -21,7 +21,7 @@ FFNeuron& FFLayer::operator[](const size_t& neuron)
 		neurons=new FFNeuron*[layerSize];
 		for(size_t i=0;i<layerSize;i++)
 		{
-			neurons[i]=new FFNeuron(potentials[i],weights[i],outputs[i],inputs[i],lambda,function);
+			neurons[i]=new FFNeuron(weights[i],outputs[i],inputs[i],lambda,function);
 		}
 	}
 
@@ -36,7 +36,6 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwar
 {
 	transfer = new ActivationFunction::ActivationFunction*[s.size()];
 	weights= new float**[s.size()];
-	potentials= new float*[s.size()];
 	layerSizes= new size_t[s.size()];
 	outputs= new float*[s.size()];
 	inputs= new float*[s.size()];
@@ -52,7 +51,6 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwar
 		}
 		layerSizes[i]=layeSize;
 		weights[i]= new float*[layeSize];
-		potentials[i]= new float[layeSize];
 		outputs[i]= new float[layeSize];
 		inputs[i]= new float[layeSize];
 
@@ -81,13 +79,11 @@ FeedForward::~FeedForward()
 					delete[] weights[i][j];
 			}
 			delete[] weights[i];
-			delete[] potentials[i];
 			delete[] outputs[i];
 			delete[] inputs[i];
 			delete transfer[i];
 		}
 		delete[] weights;
-		delete[] potentials;
 		delete[] layerSizes;
 		delete[] outputs;
 		delete[] inputs;
@@ -182,7 +178,7 @@ FFLayer& FeedForward::operator[](const size_t& l)
 		ffLayers=new FFLayer*[layers];
 		for(size_t i=0;i<layers;i++)
 		{
-			ffLayers[i]=new FFLayer(layerSizes[i],potentials[i],weights[i],outputs[i],inputs[i],lambda,*transfer[i]);
+			ffLayers[i]=new FFLayer(layerSizes[i],weights[i],outputs[i],inputs[i],lambda,*transfer[i]);
 		}
 	}
 

src/NeuralNetwork/FeedForward.h

@@ -31,15 +31,12 @@ namespace NeuralNetwork
 	class FFNeuron : public Neuron
 	{
 		public:
-			inline FFNeuron(float &pot, float *w, float &outputF, float &i,float lam,ActivationFunction::ActivationFunction &fun):function(fun),potential(pot),weights(w),out(outputF),inputs(i),lambda(lam) { }
+			inline FFNeuron(float *w, float &outputF, float &i,float lam,ActivationFunction::ActivationFunction &fun):function(fun),weights(w),out(outputF),inputs(i),lambda(lam) { }
 
 			FFNeuron() = delete;
 			FFNeuron(const FFNeuron&) = delete;
 			FFNeuron& operator=(const FFNeuron&) = delete;
 
-			inline virtual float getPotential() const override {return potential;}
-			inline virtual void setPotential(const float& p) override { potential=p;}
-
 			inline virtual float getWeight(const size_t& i ) const override { return weights[i];}
 			inline virtual void setWeight(const size_t& i,const float &p) override { weights[i]=p; }
 
@@ -48,7 +45,6 @@ namespace NeuralNetwork
 			inline virtual float derivatedOutput() const override { return function.derivatedOutput(inputs,out); }
 		protected:
 			ActivationFunction::ActivationFunction &function;
-			float &potential;
 			float *weights;
 			float &out;
 			float &inputs;
@@ -59,7 +55,7 @@ namespace NeuralNetwork
 	class FFLayer: public Layer
 	{
 		public:
-			inline FFLayer(size_t s, float *p,float **w,float *out,float *in,float lam,ActivationFunction::ActivationFunction &fun): function(fun), layerSize(s),potentials(p),weights(w),outputs(out),inputs(in),lambda(lam) {}
+			inline FFLayer(size_t s, float **w,float *out,float *in,float lam,ActivationFunction::ActivationFunction &fun): function(fun), layerSize(s),weights(w),outputs(out),inputs(in),lambda(lam) {}
 			~FFLayer();
 
 			FFLayer(const FFLayer &) = delete;
@@ -71,7 +67,6 @@ namespace NeuralNetwork
 			ActivationFunction::ActivationFunction &function;
 			FFNeuron **neurons=nullptr;
 			size_t layerSize;
-			float *potentials;
 			float **weights;
 			float *outputs;
 			float *inputs;

src/NeuralNetwork/Neuron.h

@@ -17,22 +17,6 @@ namespace NeuralNetwork
 			 */
 			virtual ~Neuron() {};
 
-			/**
-			 * @brief Returns potential of neuron
-			 */
-			virtual float getPotential() const =0;
-
-			/**
-			 * @brief Sets potential of neuron
-			 * @param p is new pontential
-			 */
-
-			virtual void setPotential(const float &p) =0;
-			/**
-			 * @brief Returns weight for w-th input neuron
-			 * @param w is weight of neuron number w
-			 */
-
 			virtual float getWeight(const size_t &w) const =0;
 
 			/**

tests/nn-05.cpp

@@ -10,7 +10,6 @@ int main()
 
 	srand(time(NULL));
 	NeuralNetwork::FeedForward ns({1,1});
-	ns[0][0].setPotential(0);
 	ns[1][1].setWeight(0,0);
 	ns[1][1].setWeight(1,1);