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, 109 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/KPMtools/plotcov3.m b/sourcecodes/bnt-master/KPMtools/plotcov3.m
new file mode 100644
index 00000000..bacdcb27
--- /dev/null
+++ b/sourcecodes/bnt-master/KPMtools/plotcov3.m
@@ -0,0 +1,109 @@
+% PLOTCOV3 - Plots a covariance ellipsoid with axes for a trivariate
+%            Gaussian distribution.
+%
+% Usage:
+%   [h, s] = plotcov3(mu, Sigma[, OPTIONS]);
+% 
+% Inputs:
+%   mu    - a 3 x 1 vector giving the mean of the distribution.
+%   Sigma - a 3 x 3 symmetric positive semi-definite matrix giving
+%           the covariance of the distribution (or the zero matrix).
+%
+% Options:
+%   'conf'      - a scalar between 0 and 1 giving the confidence
+%                 interval (i.e., the fraction of probability mass to
+%                 be enclosed by the ellipse); default is 0.9.
+%   'num-pts'   - if the value supplied is n, then (n + 1)^2 points
+%                 to be used to plot the ellipse; default is 20.
+%   'plot-opts' - a cell vector of arguments to be handed to PLOT3
+%                 to contol the appearance of the axes, e.g., 
+%                 {'Color', 'g', 'LineWidth', 1}; the default is {}
+%   'surf-opts' - a cell vector of arguments to be handed to SURF
+%                 to contol the appearance of the ellipsoid
+%                 surface; a nice possibility that yields
+%                 transparency is: {'EdgeAlpha', 0, 'FaceAlpha',
+%                 0.1, 'FaceColor', 'g'}; the default is {}
+% 
+% Outputs:
+%   h     - a vector of handles on the axis lines
+%   s     - a handle on the ellipsoid surface object
+%
+% See also: PLOTCOV2
+
+% Copyright (C) 2002 Mark A. Paskin
+%
+% This program is free software; you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation; either version 2 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful, but
+% WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+% General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with this program; if not, write to the Free Software
+% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
+% USA.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function [h, s] = plotcov3(mu, Sigma, varargin)
+
+if size(Sigma) ~= [3 3], error('Sigma must be a 3 by 3 matrix'); end
+if length(mu) ~= 3, error('mu must be a 3 by 1 vector'); end
+
+[p, ...
+ n, ...
+ plot_opts, ...
+ surf_opts] = process_options(varargin, 'conf', 0.9, ...
+					'num-pts', 20, ...
+			                'plot-opts', {}, ...
+			                'surf-opts', {});
+h = [];
+holding = ishold;
+if (Sigma == zeros(3, 3))
+  z = mu;
+else
+  % Compute the Mahalanobis radius of the ellipsoid that encloses
+  % the desired probability mass.
+  k = conf2mahal(p, 3);
+  % The axes of the covariance ellipse are given by the eigenvectors of
+  % the covariance matrix.  Their lengths (for the ellipse with unit
+  % Mahalanobis radius) are given by the square roots of the
+  % corresponding eigenvalues.
+  if (issparse(Sigma))
+    [V, D] = eigs(Sigma);
+  else
+    [V, D] = eig(Sigma);
+  end
+  if (any(diag(D) < 0))
+    error('Invalid covariance matrix: not positive semi-definite.');
+  end
+  % Compute the points on the surface of the ellipsoid.
+  t = linspace(0, 2*pi, n);
+  [X, Y, Z] = sphere(n);
+  u = [X(:)'; Y(:)'; Z(:)'];
+  w = (k * V * sqrt(D)) * u;
+  z = repmat(mu(:), [1 (n + 1)^2]) + w;
+
+  % Plot the axes.
+  L = k * sqrt(diag(D));
+  h = plot3([mu(1); mu(1) + L(1) * V(1, 1)], ...
+	    [mu(2); mu(2) + L(1) * V(2, 1)], ...
+	    [mu(3); mu(3) + L(1) * V(3, 1)], plot_opts{:});
+  hold on;
+  h = [h; plot3([mu(1); mu(1) + L(2) * V(1, 2)], ...
+		[mu(2); mu(2) + L(2) * V(2, 2)], ...
+		[mu(3); mu(3) + L(2) * V(3, 2)], plot_opts{:})];
+  h = [h; plot3([mu(1); mu(1) + L(3) * V(1, 3)], ...
+		[mu(2); mu(2) + L(3) * V(2, 3)], ...
+		[mu(3); mu(3) + L(3) * V(3, 3)], plot_opts{:})];
+end
+
+s = surf(reshape(z(1, :), [(n + 1) (n + 1)]), ...
+	 reshape(z(2, :), [(n + 1) (n + 1)]), ...
+	 reshape(z(3, :), [(n + 1) (n + 1)]), ...
+	 surf_opts{:});
+
+if (~holding) hold off; end