clear all;
close all;
clc
X = load('/Users/marialukasova/Downloads/CD_ИАД_2019-3/ЛР_6/Data_Lab6/data4.txt');

figure;
plot(X(:,1), X(:,2), '*');

numNeuron = 2;
C = zeros(numNeuron,2);
mnX = min(X(:,1));
mxX = max(X(:,1));
mnY = min(X(:,2));
mxY = max(X(:,2));

C(1,1) = mnX + (mxX-mnX).*rand();
C(2,1) = mnX + (mxX-mnX).*rand();
C(1,2) = mnY + (mxY-mnY).*rand();
C(2,2) = mnY + (mxY-mnY).*rand();

k_max = 1000;
h=0.01;


R = zeros(1,numNeuron);

for k = 1:k_max

    num = ceil(1+(length(X)-1).*rand());

    for n = 1 : numNeuron
         R(n) = pdist([X(num , :) ; C(n , :)],'euclidean');
    end

    nC = C;

    for n = 1 : numNeuron
        if R(n) == min(R)
          nC(n,1) = C(n,1)+ h*(X(num,1)-C(n,1));
          nC(n,2) = C(n,2)+ h*(X(num,2)-C(n,2));
        end
    end

    C = nC;

end

U = zeros(length(X));
for i = 1 : length(X)
        for n = 1 : numNeuron
        P(n) = pdist([X(i , :) ; C(n , :)],'euclidean');
        end

        for n = 1 : numNeuron
            if P(n) == min(P)
                U(i) = n;

            end
        end
end




figure
scatter(C(:,1),C(:,2),'*')
hold on
gscatter(X(:,1), X(:,2), U(:,1))