Layer.h

#pragma once
 
 
#include <stdio.h>
#include <assert.h>
#include <iostream>
#include <ctgmath>
#include <cstdlib>
#include <cstdio>
#include <cassert>
#include <fstream>
#include <iostream>
#include <math.h>
#include <fstream>
#include <iostream>
#include <string>
#include <numeric>
#include <vector>
 
#include "Neuron.h"
 
class Layer {
public:
    Layer(int _nNeurons, int _nInputs, int _subject, string _trial);
    ~Layer();
 
    enum whichGradient {exploding = 0, average = 1, vanishing = 2};
 
    void initLayer(int _layerIndex, Neuron::weightInitMethod _wim, Neuron::biasInitMethod _bim, Neuron::actMethod _am);
    
    void setlearningRate(double _w_learningRate, double _b_learningRate);
    
    void setInputs(const double *_inputs, const double scale = 1.0, const unsigned int offset = 0, const int n = -1);
 
    void propInputs(int _index, double _value);
    
    void calcOutputs();
 
    void setError(double _error);
    
    double getGradient(whichGradient _whichGradient);
    
    void updateWeights();
 
    Neuron *getNeuron(int _neuronIndex);
    
    int getnNeurons();
    
    double getOutput(int _neuronIndex);
    
    double getSumOutput(int _neuronIndex);
    
    double getWeights(int _neuronIndex, int _weightIndex);
    
    double getWeightChange();
    
    double getWeightDistance();
    
    double getGlobalError(int _neuronIndex);
    
    double getInitWeight(int _neuronIndex, int _weightIndex);
    
    void saveWeights();
    
    void snapWeights(string prefix, string _trial, int _subject);
    
    void snapWeightsMatrixFormat(string prefix);
    
    void printLayer();
 
private:
    // initialisation:
    int nNeurons = 0;
    int nInputs = 0;
    double learningRate = 0;
    int myLayerIndex = 0;
    Neuron **neurons = 0;
    
    int layerHasReported = 0;
 
    //back propagation of error:
    double backwardError = 0;
 
    //exploding vasnishing gradient:
    double averageError = 0;
    double maxError = 0;
    double minError = 0;
 
    int subject = 0;
    string trial = "0";
 
    //learning:
    double weightChange=0;
};