You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: demgmm1.m
    path of file: ./repos/bnt/netlab3.3
    
    the code of the file until where you have to start completion: %DEMGMM1 Demonstrate EM for Gaussian mixtures.
%
%	Description
%	This
    
function GMM. The Gaussian components can be displayed on the same')
disp('plot as the data by drawing a contour of constant probability density')
disp('for each component having radius equal to the corresponding standard')
disp('deviation. Component 1 is coloured red and component 2 is coloured')
disp('blue.')
disp(' ')
disp('Note that a particulary poor choice of initial parameters has been')
disp('made in order to illustrate more effectively the operation of the')
disp('EM algorithm.')
disp(' ')
disp('Press any key to see the initial configuration of the mixture model.')
pause;

% Set up mixture model
ncentres = 2; input_dim = 2;
mix = gmm(input_dim, ncentres, 'spherical');

% Initialise the mixture model
mix.centres = [0.2 0.8; 0.8, 0.2];
mix.covars = [0.01 0.01];

% Plot the initial model
ncirc = 30; theta = linspace(0, 2*pi, ncirc);
xs = cos(theta); ys = sin(theta);
xvals = mix.centres(:, 1)*ones(1,ncirc) + sqrt(mix.covars')*xs;
yvals = mix.centres(:, 2)*ones(1,ncirc) + sqrt(mix.covars')*ys;
hc(1)=line(xvals(1,:), yvals(1,:), 'color', 'r');
hc(2)=line(xvals(2,:), yvals(2,:), 'color', 'b');
set(ht, 'string', 'Initial Configuration');
figure(h);
disp(' ')
disp('Press any key to continue'); 
pause; clc;

disp('Now we adapt the parameters of the mixture model iteratively using the')
disp('EM algorithm. Each cycle of the EM algorithm consists of an E-step')
disp('followed by an M-step.  We start with the E-step, which involves the')
disp('evaluation of the posterior probabilities (responsibilities) which the')
disp('two components have for each of the data points.')
disp(' ')
disp('Since we have labelled the two components using the colours red and')
disp('blue, a convenient way to indicate the value of a posterior')
disp('probability for a given data point is to colour the point using a')
disp('scale ranging from pure red (corresponding to a posterior probability')
disp('of 1.0 for the red component and 0.0 for the blue component) through')
disp('to pure blue.')
disp(' ')
disp('Press any key to see the result of applying the first E-step.')
pause;

% Initial E-step.
set(ht, 'string', 'E-step');
post = gmmpost(mix, x);
dcols = [post(:,1), zeros(ndata, 1), post(:,2)];
delete(hd); 
for i = 1 : ndata
  hd(i) = plot(x(i, 1), x(i, 2), 'color', dcols(i,:), ...
          'marker', '.', 'markersize', 30);
end