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, 33 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/gauss.m b/sourcecodes/bnt-master/netlab3.3/gauss.m
new file mode 100644
index 00000000..33e23136
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/gauss.m
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+function y = gauss(mu, covar, x)
+%GAUSS	Evaluate a Gaussian distribution.
+%
+%	Description
+%
+%	Y = GAUSS(MU, COVAR, X) evaluates a multi-variate Gaussian  density
+%	in D-dimensions at a set of points given by the rows of the matrix X.
+%	The Gaussian density has mean vector MU and covariance matrix COVAR.
+%
+%	See also
+%	GSAMP, DEMGAUSS
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+[n, d] = size(x);
+
+[j, k] = size(covar);
+
+% Check that the covariance matrix is the correct dimension
+if ((j ~= d) | (k ~=d))
+  error('Dimension of the covariance matrix and data should match');
+end
+   
+invcov = inv(covar);
+mu = reshape(mu, 1, d);    % Ensure that mu is a row vector
+
+x = x - ones(n, 1)*mu;
+fact = sum(((x*invcov).*x), 2);
+
+y = exp(-0.5*fact);
+
+y = y./sqrt((2*pi)^d*det(covar));