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, 39 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/mlpunpak.m b/sourcecodes/bnt-master/netlab3.3/mlpunpak.m
new file mode 100644
index 00000000..c2b16b5f
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/mlpunpak.m
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+function net = mlpunpak(net, w)
+%MLPUNPAK Separates weights vector into weight and bias matrices. 
+%
+%	Description
+%	NET = MLPUNPAK(NET, W) takes an mlp network data structure NET and  a
+%	weight vector W, and returns a network data structure identical to
+%	the input network, except that the first-layer weight matrix W1, the
+%	first-layer bias vector B1, 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
+%	MLP, MLPPAK, MLPFWD, MLPERR, MLPBKP, MLPGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'mlp');
+if ~isempty(errstring);
+  error(errstring);
+end
+
+if net.nwts ~= length(w)
+  error('Invalid weight vector length')
+end
+
+nin = net.nin;
+nhidden = net.nhidden;
+nout = net.nout;
+
+mark1 = nin*nhidden;
+net.w1 = reshape(w(1:mark1), nin, nhidden);
+mark2 = mark1 + nhidden;
+net.b1 = reshape(w(mark1 + 1: mark2), 1, nhidden);
+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);