BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 80 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/demgauss.m b/sourcecodes/bnt-master/netlab3.3/demgauss.m
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+%DEMGAUSS Demonstrate sampling from Gaussian distributions.
+%
+%	Description
+%
+%	DEMGAUSS provides a simple illustration of the generation of data
+%	from Gaussian distributions. It first samples from a one-dimensional
+%	distribution using RANDN, and then plots a normalized histogram
+%	estimate of the distribution using HISTP together with the true
+%	density calculated using GAUSS.
+%
+%	DEMGAUSS then demonstrates sampling from a Gaussian distribution in
+%	two dimensions. It creates a mean vector and a covariance matrix, and
+%	then plots contours of constant density using the function GAUSS. A
+%	sample of points drawn from this distribution, obtained using the
+%	function GSAMP, is then superimposed on the contours.
+%
+%	See also
+%	GAUSS, GSAMP, HISTP
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+clc
+mean = 2; var = 5; nsamp = 3000;
+xmin = -10; xmax = 10; nbins = 30;
+disp('Demonstration of sampling from a uni-variate Gaussian with mean')
+dstring = [num2str(mean), ' and variance ', num2str(var), '.  ', ...
+    num2str(nsamp), ' samples are taken.'];
+disp(dstring);
+x = mean + sqrt(var)*randn(nsamp, 1);
+fh1 = figure;
+histp(x, xmin, xmax, nbins);
+hold on;
+axis([xmin xmax 0 0.2]);
+plotvals = linspace(xmin, xmax, 200)';
+probs = gauss(mean, var, plotvals);
+plot(plotvals, probs, '-r');
+xlabel('X')
+ylabel('Density')
+
+disp(' ')
+disp('Press any key to continue')
+pause; 
+mu = [3 2];
+lam1 = 0.5;
+lam2 = 5.0;
+Sigma = lam1*[1,1]'*[1,1] + lam2*[1,-1]'*[1,-1];
+disp(' ')
+disp('Demonstration of sampling from a bi-variate Gaussian.  The mean is')
+dstring = ['[', num2str(mu(1)), ', ', num2str(mu(2)), ...
+      '] and the covariance matrix is'];
+disp(dstring)
+disp(Sigma);
+ngrid = 40;
+cmin = -5; cmax = 10; 
+cvals = linspace(cmin, cmax, ngrid);
+[X1, X2] = meshgrid(cvals, cvals);
+XX = [X1(:), X2(:)];
+probs = gauss(mu, Sigma, XX);
+probs = reshape(probs, ngrid, ngrid);
+
+fh2 = figure;
+contour(X1, X2, probs, 'b');
+hold on
+
+nsamp = 300;
+dstring = [num2str(nsamp), ' samples are generated.'];
+disp('The plot shows the sampled data points with a contour plot of their density.')
+samples = gsamp(mu, Sigma, nsamp);
+plot(samples(:,1), samples(:,2), 'or');
+xlabel('X1')
+ylabel('X2')
+grid off;
+
+disp(' ')
+disp('Press any key to end')
+pause; 
+close(fh1);
+close(fh2);
+clear all; 
\ No newline at end of file