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%%%%%%%%  EE 156a %%%% S. Savarese - M. Welling %%%%%%% March 2000 %%%%%
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%%%%%%%%  routine to plot the estimated 2D gaussian given N_points %%%%%
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clear;
clf;

N_points_1 = input('Number of points you may want to select for the cluster (max 1000)= ');
xs_1=zeros(1,N_points_1);
ys_1=zeros(1,N_points_1);

figure(1);
axis([-100 100 -100 100]);
hold on; 

%%%%%%%% acquire points %%%%%%%%%%%%%%%%%%%
for i=1:N_points_1,

    fprintf(1,'%d - Select a point with the mouse: ',i);
    [x,y] = ginput2(1);
    fprintf(1,'(%3.3f,%3.3f)\n',x,y);
    plot(x,y,'r+');
    xs_1(i)=x;
    ys_1(i)=y;

end;
xs_1;
ys_1;

s_1=[xs_1; ys_1];
mu_x_1 = sum(xs_1)/N_points_1
mu_y_1 = sum(ys_1)/N_points_1

%%%%%% mean vector %%%%%%%%%%%%
mu_1= sum(s_1,2)/N_points_1

mat_1=ones(2,2,N_points_1);
for i=1:N_points_1,
    mat_1(:,:,i)= (s_1(:,i)-mu_1)*(s_1(:,i)-mu_1)';
end;

%mat_1(:,:,i)= (s_1(:,i)-mu_1)*(s_1(:,i)-mu_1)'

%%%%%%%%% covariance matrix
cov_1=sum(mat_1,3)/N_points_1

plotGauss(mu_1(1),mu_1(2),cov_1(1,1),cov_1(2,2),cov_1(1,2))

hold off;