nettest.cpp

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#include "NeuralNetwork.h"
#include <iostream>
#include <vector>
#include <string>
#include <algorithm>
#include <iterator>
#include "CNeuralConfig.h"
#include "UniformRNG.h"
using namespace std;

int main()
{
        UniformRNG Random;
        NeuralNetwork::ttypeVector typeVector;
        NeuralNetwork::ttypeArray typeArray;
                
        const int seglength = 2;
        const double maxinit = 0.1;
        const int maxit = 5;
        const int hlayers = 3;
        const int deslength = 1;
        const double mu = 1.0;
        vector<double> input(seglength,0), desired(deslength,0), output;
        
        typeVector.assign(seglength,SigmoidalNeuron::bipolar);
        for (int i = 0; i < hlayers; ++i)
        {
                typeArray.push_back(typeVector);
        }
        typeVector.assign(1,SigmoidalNeuron::bipolar);
        typeArray.push_back(typeVector);
        
        NeuralNetwork Network(seglength,deslength);
        Network.SetInput(input);
        Network.SetLayers(typeArray);
        Network.InitWeights(maxinit,maxinit);
        Network.SetMu(mu);
        
        for (int iterations = 0; iterations < maxit; ++iterations)
        {
                for (int i = 0; i < seglength; ++i)
                        input.at(i) = Random.GetNumber();
                Network.SetInput(input);
                for (int i = 0; i < deslength; ++i)
                        desired.at(i) = Random.GetNumber();
                Network.SetDesired(desired);
                output = Network.CalcOutput();
                Network.AdaptWeights();
                std::copy(output.begin(),output.end(),ostream_iterator<double>(cout," "));
                std::cout << std::endl;
                std::cout << "Weights: " << std::endl;
                Network.PrintWeights(std::cout);
                std::cout << std::endl;
        }
}

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