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, 52 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/examples/static/HME/gen_data.m b/sourcecodes/bnt-master/BNT/examples/static/HME/gen_data.m
new file mode 100644
index 00000000..c37f9d28
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/HME/gen_data.m
@@ -0,0 +1,52 @@
+function [data, ndata1, ndata2, targets]=gen_data(ndata, seed)
+% Generate data from three classes in 2d
+% Setting 'seed' for reproducible results
+% OUTPUT
+% data : data set
+% ndata1, ndata2: separator
+
+if nargin<1,
+   error('Missing data size');
+end
+
+input_dim = 2;
+num_classes = 3;
+
+if nargin==2,
+   % Fix seeds for reproducible results
+   randn('state', seed);
+   rand('state', seed);
+end
+
+% Generate mixture of three Gaussians in two dimensional space
+data = randn(ndata, input_dim);
+targets = zeros(ndata, 3);
+
+% Priors for the clusters
+prior(1) = 0.4;
+prior(2) = 0.3;
+prior(3) = 0.3;
+
+% Cluster centres
+c = [2.0, 2.0; 0.0, 0.0; 1, -1];
+
+ndata1 = round(prior(1)*ndata);
+ndata2 = round((prior(1) + prior(2))*ndata);
+% Put first cluster at (2, 2)
+data(1:ndata1, 1) = data(1:ndata1, 1) * 0.5 + c(1,1);
+data(1:ndata1, 2) = data(1:ndata1, 2) * 0.5 + c(1,2);
+targets(1:ndata1, 1) = 1;
+
+% Leave second cluster at (0,0)
+data((ndata1 + 1):ndata2, :) = data((ndata1 + 1):ndata2, :);
+targets((ndata1+1):ndata2, 2) = 1;
+
+data((ndata2+1):ndata, 1) = data((ndata2+1):ndata,1) *0.6 + c(3, 1);
+data((ndata2+1):ndata, 2) = data((ndata2+1):ndata,2) *0.6 + c(3, 2);
+targets((ndata2+1):ndata, 3) = 1;
+
+if 0
+  ndata = 1;
+  data = x;
+  targets = [1 0 0];
+end