www.pudn.com > FitFunc.zip > build_mix_2D_gaussian.m

function [X,N] = build_mix_2D_gaussian( u_c,covar_c,p_c,N ) 
%
% build_mix_2D_gaussian - build a distribution of a mixed gaussian 
% 
% format:   [X,N] = build_mix_2D_gaussian( u_c,covar_c,p_c,N )
%
% input:    u_c     - 2xM matrix, mean of the gaussians in the distribution 
%           covar_c - 2x2xM matirx, covariance of the gaussians 
%           p_c     - 1xM vector, ratio between the gaussians in the distribution 
%           N       - total number of samples, this number might change a little
%
% output:   X       - the random variable matrix Nx2 
%           N       - the length of the given 2D vector
% 
 
% initialize 
M           = length(p_c);                  % the number of mixed gaussians 
p_c         = round( p_c / sum(p_c) * N );  % number of samples for each gaussian 
N           = sum( p_c );                   % total number of samples 
X           = zeros(N,2);                   % initialize output samples 2D vector 
idx         = 1;                            % counter 
actual_cov  = zeros(2,2,M);                 % the actual covariance calculated from the samples 
actual_mean = zeros(2,M);                   % the actual mean calculated from the samples 
 
% build distribution 
for m = 1:M 
    if (idx>1) 
        span = sum(p_c(1:idx-1)):sum(p_c(1:idx)); 
    else 
        span = 1:p_c(1); 
    end 
    X(span,:) = mvnrnd( u_c(:,idx),covar_c(:,:,idx),length( span ) ); 
    idx       = idx + 1; 
    actual_cov(:,:,m) = cov( X(span,:) ); 
    actual_mean(:,m)  = mean( X(span,:) )'; 
end 
 
% plot the ACTUAL distribution 
plot_mix_gaussian( actual_mean,actual_cov,p_c/sum(p_c),X );