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, 44 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/gpcovarf.m b/sourcecodes/bnt-master/netlab3.3/gpcovarf.m
new file mode 100644
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+++ b/sourcecodes/bnt-master/netlab3.3/gpcovarf.m
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+function covf = gpcovarf(net, x1, x2)
+%GPCOVARF Calculate the covariance function for a Gaussian Process.
+%
+%	Description
+%
+%	COVF = GPCOVARF(NET, X1, X2) takes  a Gaussian Process data structure
+%	NET together with two matrices X1 and X2 of input vectors,  and
+%	computes the matrix of the covariance function values COVF.
+%
+%	See also
+%	GP, GPCOVAR, GPCOVARP, GPERR, GPGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+errstring = consist(net, 'gp', x1);
+if ~isempty(errstring);
+  error(errstring);
+end
+
+if size(x1, 2) ~= size(x2, 2)
+  error('Number of variables in x1 and x2 must be the same');
+end
+
+n1 = size(x1, 1);
+n2 = size(x2, 1);
+beta = diag(exp(net.inweights));
+
+% Compute the weighted squared distances between x1 and x2
+z = (x1.*x1)*beta*ones(net.nin, n2) - 2*x1*beta*x2' ... 
+  + ones(n1, net.nin)*beta*(x2.*x2)';
+
+switch net.covar_fn
+
+  case 'sqexp'		% Squared exponential
+    covf = exp(net.fpar(1) - 0.5*z);
+
+  case 'ratquad'	% Rational quadratic
+    nu = exp(net.fpar(2));
+    covf = exp(net.fpar(1))*((ones(size(z)) + z).^(-nu));
+
+  otherwise
+    error(['Unknown covariance function ', net.covar_fn]);  
+end
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