main.cpp

#include <cstdio>

/**
 * DESCRIPTION OF THE FILE
 *
 * @author Michal Kravčenko
 * @date 14.6.18 -
 */

#include "Network/NeuralNetwork.h"

#include "Neuron/NeuronLinear.h"

#include "NetConnection/Connection.h"

#include "NetConnection/ConnectionWeightIdentity.h"

//TODO prepsat tak, aby neuronova sit managovala destruktory vsech potrebnych objektu (kvuli serializaci)
/**
 * Test of simple neural network
 * Network should evaluate the function f(x) = x + 1
 */
void test1(){
    std::vector<double> in(1);
    std::vector<double> out(1);

    NeuralNetwork net;
    NeuronLinear* u1 = new NeuronLinear(1.0, 1.0); //f(x) = x + 1.0
    NeuronLinear* u2 = new NeuronLinear(0.0, 1.0); //f(x) = x
    int idx1 = net.add_neuron(u1);
    int idx2 = net.add_neuron(u2);
////////////////////// SIMPLE EDGE WEIGHT ////////////////////////////////////////
//    net.add_connection_simple(idx1, idx2, -1, 1.0);
////////////////////// END SIMPLE EDGE WEIGHT ////////////////////////////////////////

/////////////////////////BEGIN OF COMPLEX EDGE WEIGHT//////////////////////////////
//TODO vyresit memleak
   std::function<double(double **, int)> weight_function = [](double ** params, int n_params){
        //w(x, y) = x + y
        double a = (*(params[0]));
        double b = (*(params[1]));
        printf("eval: %f, %f\n",  a, b);
        return (a + 0.0 * b);
    };
    int  weight_indices [2]= {0, -1};
    double weight_values [2] = {1.0, 5.0};
    net.add_connection_general(idx1, idx2, &weight_function, weight_indices, weight_values, 2);
/////////////////////////END OF COMPLEX EDGE WEIGHT//////////////////////////////
    for(int i = 0; i < 20; ++i){
        in[0] = 0.05 * i;
        net.eval_single(in, out);

        printf("x = %3.2f, f(x) = %3.2f, expected output = %3.2f\n", in[0], out[0], in[0] + 1.0);
    }

    //clean-up phase
    delete u1;
    delete u2;
}

int main(int argc, char** argv){

    test1();

    printf("hello biatch\n");

    return 0;
}