Generalized k mean algorithm ( 2 dimensional data-set) without using built-in function | MATLAB

%Code:

clc

clear all

close all

format bank;

x=input('Enter the x coordinate sequence:');

y=input('Enter the y coordinate sequence:');

k=input('Enter the number of clusters:');

cx=input('Enter the  initial means x coordinate:');%initial mean of x

cy=input('Enter the  initial means y coordinate:');%initial mean of y

mean_oldx=cx;

mean_newx=cx;

mean_oldy=cy;

mean_newy=cy;

outputx=cell(k,1);

outputy=cell(k,1);

temp=0;

while(temp==0)

    mean_oldx=mean_newx;

    mean_oldy=mean_newy;

    for ij=1:length(x)

        mina=[];

        mu=x(ij);

        nu=y(ij);

     for mk=1:length(cx)

         mina=[mina sqrt((mu-cx(mk))^2+(nu-cy(mk))^2)];

     end

     [gc index]=min(mina);

     outputx{index}=[outputx{index} mu];

     outputy{index}=[outputy{index} nu];

    end

    gmckx=[];

    gmcky=[];

    for i=1:k

        gmckx=[gmckx mean(outputx{i})];

        gmcky=[gmcky mean(outputy{i})];

    end

    cx=gmckx;

    cy=gmcky;

    mean_newx=cx;

        mean_newy=cy;

        gum=0;

        bum=0;

    if(mean_newx==mean_oldx)

        gum=1;

    end

    if(mean_newy==mean_oldy)

        bum=1;

    end

    if(gum==1 && bum==1)

        temp=1;

    else

            outputx=cell(k,1);

            outputy=cell(k,1);

    end

   

end

celldisp(outputx);

celldisp(outputy);

gm=rand(1,k);

tm=rand(1,k);

bm=rand(1,k);

bg=1;

for i=1:k

    x=outputx{i};

    y=outputy{i};

    for j=1:length(x)

        t=0:0.01:2*pi;

        a=x(j)+1000*cos(t);

        b=y(j)+1000*sin(t);

        patch(a,b,[gm(bg),tm(bg),bm(bg)]);

        axis square;

        hold on;

    end

    bg=bg+1;

    hold on;

    axis square;

    grid on;

end