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, 38 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/gpcovar.m b/sourcecodes/bnt-master/netlab3.3/gpcovar.m
new file mode 100644
index 00000000..f71fa4db
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/gpcovar.m
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+function [cov, covf] = gpcovar(net, x)
+%GPCOVAR Calculate the covariance for a Gaussian Process.
+%
+%	Description
+%
+%	COV = GPCOVAR(NET, X) takes  a Gaussian Process data structure NET
+%	together with a matrix X of input vectors, and computes the
+%	covariance matrix COV.  The inverse of this matrix is used when
+%	calculating the mean and variance of the predictions made by NET.
+%
+%	[COV, COVF] = GPCOVAR(NET, X) also generates the covariance matrix
+%	due to the covariance function specified by NET.COVARFN as calculated
+%	by GPCOVARF.
+%
+%	See also
+%	GP, GPPAK, GPUNPAK, GPCOVARP, GPCOVARF, GPFWD, GPERR, GPGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'gp', x);
+if ~isempty(errstring);
+  error(errstring);
+end
+
+ndata = size(x, 1);
+
+% Compute prior covariance
+if nargout >= 2
+  [covp, covf] = gpcovarp(net, x, x);
+else
+  covp = gpcovarp(net, x, x);
+end
+
+% Add output noise variance
+cov = covp + (net.min_noise + exp(net.noise))*eye(ndata);
+