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, 43 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/rbfunpak.m b/sourcecodes/bnt-master/netlab3.3/rbfunpak.m
new file mode 100644
index 00000000..64b15a9a
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/rbfunpak.m
@@ -0,0 +1,43 @@
+function net = rbfunpak(net, w)
+%RBFUNPAK Separates a vector of RBF weights into its components.
+%
+%	Description
+%	NET = RBFUNPAK(NET, W) takes an RBF network data structure NET and  a
+%	weight vector W, and returns a network data structure identical to
+%	the input network, except that the centres C, the widths WI, the
+%	second-layer weight matrix W2 and the second-layer bias vector B2
+%	have all been set to the corresponding elements of W.
+%
+%	See also
+%	RBFPAK, RBF
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'rbf');
+if ~errstring
+  error(errstring);
+end
+
+if net.nwts ~= length(w)
+  error('Invalid length of weight vector')
+end
+
+nin 	= net.nin;
+nhidden = net.nhidden;
+nout 	= net.nout;
+
+mark1 = nin*nhidden;
+net.c = reshape(w(1:mark1), nhidden, nin);
+if strcmp(net.actfn, 'gaussian')
+  mark2 = mark1 + nhidden;
+  net.wi = reshape(w(mark1+1:mark2), 1, nhidden);
+else
+  mark2 = mark1;
+  net.wi = [];
+end
+mark3 = mark2 + nhidden*nout;
+net.w2 = reshape(w(mark2+1:mark3), nhidden, nout);
+mark4 = mark3 + nout;
+net.b2 = reshape(w(mark3+1:mark4), 1, nout);
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