Radial.cpp

#include "Radial.h"


Radial::Radial(point2 NeuronCenter, FILE* studyFile, FILE* gnuplot, double cs) {
    C = NeuronCenter;
    etaInput();
    gpipe = gnuplot;
    get_StudyData(studyFile);
    ClassValue = cs;
}

double Radial::TargetFunction(int p) {
    double y, d, tmp=0.;
    register int i;
    for(i=0; i<StudyMassSize; ++i) {
        y = ActivationFunction(StudyMass[i]);
        d = StudyMass[i].outValue;
        tmp += (y - d) * (y - d);
    }
    return 0.5 * tmp;
}

double Radial::GradientMethod() {

}

void Radial::get_StudyData(FILE *studyfile) {
    register int i=0;
    char str[255];
    StudyMassSize=0;

    while(fgets(str, 255, studyfile))
        StudyMassSize++;

    cout << "Read " << StudyMassSize << " lines from study file" << endl;

    StudyMass = new point2[StudyMassSize];

    fseek(studyfile, 0, SEEK_SET);

    while(fgets(str, 255, studyfile)) {
        sscanf(str, "%lf\t%lf\t%lf\n", &StudyMass[i].x, &StudyMass[i].y, &StudyMass[i].outValue);
        // Norm(&StudyMass[i]);
        i++;
    }
    fclose(studyfile);
}

void Radial::pltStudyMass() {
    register int i;

    fprintf(gpipe, "unset multiplot\nset multiplot\n");
    for(i=0; i<StudyMassSize; ++i) {
        if(StudyMass[i].outValue < 0.4) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 8\n");
        }
        if(StudyMass[i].outValue == 0.5) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 6\n");
        }
        if(StudyMass[i].outValue > 0.6) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 4\n");
        }
        fprintf(gpipe, "%lf\t%lf\n", StudyMass[i].x, StudyMass[i].y);

        fprintf(gpipe, "e\n");
    }
    fflush(gpipe);
}

void Radial::pltCenter() {
    fprintf(gpipe, "plot '-' u 1:2:3 with circles\n");
    fprintf(gpipe, "%f\t%f\t%lf\ne\n", C.x, C.y, 0.5);

    fprintf(gpipe, "plot '-' u 1:2 w points lt rgb \"black\"\n");
    fprintf(gpipe, "%f\t%f\ne\n", C.x, C.y);
}

void Radial::Norm(point2 *p) {
    double AuxNorm;
    if(p->x != 0 && p->y != 0) {
        AuxNorm = sqrt(p->x * p->x + p->y * p->y);
        p->x /= AuxNorm;
        p->y /= AuxNorm;
    }
}

void Radial::set_eta(double newValue) {
    this->eta = newValue;
}

void Radial::set_sigma(double newValue) {
    this->sigma = newValue;
}


void Radial::etaInput() {
    double eta;
    cout << "Введите число в интервале (0, 1)." << endl;
    cout << "Оно будет использовано как коэф-т обучения:" << endl;
    cin >> eta;
    if(eta <= 0 || eta >= 1) {
        cout << "Вы глупец." << endl;
        exit(-2);
    }
    set_eta(eta);
}

void Radial::StudyNeuron() {
    register int i, k=0, n;

    pltStudyMass();

    for(n=0; n < 5; ++n) {
        for(i=0; i<StudyMassSize; i++) {
            if(StudyMass[i].outValue == ClassValue) {
                // cout << StudyMass[i].outValue << endl;
                // cout << StudyMass[i].x << " " << StudyMass[i].y << endl;
                C.moveCenter(StudyMass[i], eta);
                // fprintf(gpipe, "unset multiplot\n");
                // fprintf(gpipe, "pause %lf \n", 1);
            }
            // C.printPoint();
            // PlotGreenPoint(i);
        }
        pltCenter();
        // fprintf(gpipe, "pause 1\n");
    }
    fflush(gpipe);
}

void Radial::PlotGreenPoint(int PointNum) {
    register int i;
    // fprintf(gpipe, "set multiplot\n");

    for(i=0; i<PointNum; ++i) {
        if(StudyMass[i].outValue < 0.4) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 8\n");
        }
        if(StudyMass[i].outValue == 0.5) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 6\n");
        }
        if(StudyMass[i].outValue > 0.6) {
            fprintf(gpipe, "plot '-' u 1:2 w points ls 4\n");
        }
        fprintf(gpipe, "%f\t%f\n", StudyMass[i].x, StudyMass[i].y);

        fprintf(gpipe, "e\n");
    }

    fprintf(gpipe, "plot '-' u 1:2:3 with circles\n");
    fprintf(gpipe, "%f\t%f\t%lf\nend\n", C.x, C.y, 0.5);

    fprintf(gpipe, "plot '-' u 1:2 w points lt rgb \"black\"\n");
    fprintf(gpipe, "%f\t%f\nend\n", C.x, C.y);
}

double Radial::ActivationFunction(point2 X_k) {
    double nom, den;
    nom = pow(EuclideanDistance(X_k, C), 2);
    den = 2 * pow(sigma, 2);
    return exp(-nom / den);
}

double Radial::ActivationFunctionWithSigma(point2 X_k, double newSigma) {
    double nom, den;
    nom = pow(EuclideanDistance(X_k, C), 2);
    den = 2 * pow(newSigma, 2);
    return exp(-nom / den);
}

int Radial::Test() {
    double outvalue;
    cout << "x = "; cin >> testPoint.x;
    cout << "y = "; cin >> testPoint.y;
    if(testPoint.x == 0. && testPoint.y == 0.)
        return 0;
    outvalue = ActivationFunction(testPoint);
    if (outvalue >= 0.5) {
        cout << ">= 0.5" << endl;
        fprintf(gpipe, "plot '-' u 1:2 w points lt rgb \"blue\"\n");
    }
    else {
        cout << "< 0.5" << endl;
        fprintf(gpipe, "plot '-' u 1:2 w points lt rgb \"red\"\n");
    }
    fprintf(gpipe, "%lf\t%lf\n", testPoint.x, testPoint.y);
    fprintf(gpipe, "end\n");
    return 1;
}

void Radial::StudySigmaOffline() {
    double etta = 0.1;
    int goodIterCount = 0;
    register int i;
    bool flag = true;

    fprintf(gpipe, "unset multiplot\nset multiplot\n");
    pltStudyMass();
    fprintf(gpipe, "set parametric\n");
    fprintf(gpipe, "plot [0:2*pi] %lf*sin(t)+%lf,%lf*cos(t)+%lf lw 4 notitle\n", getR(0.55), C.x, getR(0.55), C.y);
    fprintf(gpipe, "unset parametric\n");
    fprintf(gpipe, "plot '-' w p lc 'red' pt %d lw 3\n", 4);
    fprintf(gpipe, "%lf %lf\n", C.x, C.y);
    fprintf(gpipe, "e\n");
    fprintf(gpipe, "pause 0.5\n");
    fflush(gpipe);

    do {
        double gradE = 0.;
        for(i=0; i<StudyMassSize; ++i) {
            // if(StudyMass[i].outValue == ClassValue) {
            double f = ActivationFunction(StudyMass[i]);
            gradE += (f - StudyMass[i].outValue) * f * pow(EuclideanDistance(StudyMass[i], C), 2) / pow(sigma, 3);
            // }
        }
        double newSigma = sigma - etta * gradE;

        double oldE = 0.;
        for(int j=0; j<StudyMassSize; ++j) {
            // if(StudyMass[j].outValue == ClassValue) {
            double f = ActivationFunction(StudyMass[j]);
            oldE += pow((f - StudyMass[j].outValue), 2);
            // }
        }
        oldE /= 2.;

        double newE = 0.;
        for(int j=0; j<StudyMassSize; ++j) {
            // if(StudyMass[j].outValue == ClassValue) {
            double f = ActivationFunctionWithSigma(StudyMass[j], newSigma);
            newE += pow((f - StudyMass[j].outValue), 2);
            // }
        }
        newE /= 2.;

        double deltaE = oldE - newE;
        if(deltaE < 0) {
            etta /= 2.;
            goodIterCount = 0;
        }
        else {
            goodIterCount++;
            set_sigma(newSigma);
            if(deltaE < 1e-3)
                flag = false;
            if(goodIterCount == 4) {
                etta *= 2;
                goodIterCount = 0;
            }

            fprintf(gpipe, "unset multiplot\nset multiplot\n");
            pltStudyMass();
            fprintf(gpipe, "set parametric\n");
            fprintf(gpipe, "plot [0:2*pi] %lf*sin(t)+%lf,%lf*cos(t)+%lf lw 4 notitle\n", getR(0.55), C.x, getR(0.55), C.y);
            fprintf(gpipe, "unset parametric\n");
            fprintf(gpipe, "plot '-' w p lc 'red' pt %d lw 3\n", 4);
            fprintf(gpipe, "%lf %lf\n", C.x, C.y);
            fprintf(gpipe, "e\n");
            fprintf(gpipe, "pause 1\n");
            fflush(gpipe);
        }
    } while(flag);
    cout << "Sigma study finnished, Sigma = " << sigma << endl;
}

double Radial::getR(double val) {
    return sigma * sqrt(-2.0 * log(val));
}

int main(int argc, char* argv[]) {
    point2 NeuronCenter(0., 0.);
    if(argc != 2) {
        HelpMessage();
        return -1;
    }
    FILE *studyFile = fopen(argv[1], "r");
    if(studyFile == NULL) {
        cout << "Can't read file " << argv[1] << endl;
        return -2;
    }

    FILE *gpipe = popen("gnuplot -persist -geometry 700x700", "w");
    if(!gpipe) {
        cout << "Can't open gnuplot" << endl;
        return -3;
    }

    gnuplotInit(gpipe);

    double cv1 = 0., cv2 = 0.;

    Radial MyRadial1(NeuronCenter, studyFile, gpipe, cv1);
    MyRadial1.StudyNeuron();
    MyRadial1.StudySigmaOffline();

    // MyRadial1.StudySigmaOffline();

    // Radial MyRadial2(NeuronCenter, studyFile, gpipe, cv2);
    // MyRadial2.StudyNeuron();

    // cout << "Выполнено обучение нейрона на выборке из входного файла" << endl;

    // char ch;
    // cout << "Начать тестирование? (y/n)" << endl;
    // cin >> ch;

    // if(ch != 'y' && ch != 'Y')
    //     return 0;

    // cout << "Начало тестирования" << endl;

    // do
    //     fflush(gpipe);
    // while(MyRadial1.Test());
    fprintf(gpipe, "exit\n");
    fflush(gpipe);
    pclose(gpipe);
    return 0;
}