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, 41 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/hintmat.m b/sourcecodes/bnt-master/netlab3.3/hintmat.m
new file mode 100644
index 00000000..24617921
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+++ b/sourcecodes/bnt-master/netlab3.3/hintmat.m
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+function [xvals, yvals, color] = hintmat(w);
+%HINTMAT Evaluates the coordinates of the patches for a Hinton diagram.
+%
+%	Description
+%	[xvals, yvals, color] = hintmat(w)
+%	  takes a matrix W and returns coordinates XVALS, YVALS for the
+%	patches comrising the Hinton diagram, together with a vector COLOR
+%	labelling the color (black or white) of the corresponding elements
+%	according to their sign.
+%
+%	See also
+%	HINTON
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Set scale to be up to 0.9 of maximum absolute weight value, where scale
+% defined so that area of box proportional to weight value.
+
+w = flipud(w);
+[nrows, ncols] = size(w);
+
+scale = 0.45*sqrt(abs(w)/max(max(abs(w))));
+scale = scale(:);
+color = 0.5*(sign(w(:)) + 3);
+
+delx = 1;
+dely = 1;
+[X, Y] = meshgrid(0.5*delx:delx:(ncols-0.5*delx), 0.5*dely:dely:(nrows-0.5*dely));
+
+% Now convert from matrix format to column vector format, and then duplicate
+% columns with appropriate offsets determined by normalized weight magnitudes. 
+
+xtemp = X(:);
+ytemp = Y(:);
+
+xvals = [xtemp-delx*scale, xtemp+delx*scale, ...
+         xtemp+delx*scale, xtemp-delx*scale];
+yvals = [ytemp-dely*scale, ytemp-dely*scale, ...
+         ytemp+dely*scale, ytemp+dely*scale];
+