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, 58 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/KPMtools/subsets.m b/sourcecodes/bnt-master/KPMtools/subsets.m
new file mode 100644
index 00000000..47f999f0
--- /dev/null
+++ b/sourcecodes/bnt-master/KPMtools/subsets.m
@@ -0,0 +1,58 @@
+function [T, bitv] = subsets(S, U, L, sorted, N)
+% SUBSETS Create a set of all the subsets of S which have cardinality <= U and >= L
+% T = subsets(S, U, L)
+% U defaults to length(S), L defaults to 0.
+% So subsets(S) generates the powerset of S.
+%
+% Example:
+% T = subsets(1:4, 2, 1) 
+% T{:} = 1, 2, [1 2], 3, [1 3], [2 3], 4, [1 4], [2 4], [3 4]
+%
+% T = subsets(S, U, L, sorted)
+% If sorted=1, return the subsets in increasing size
+%
+% Example:
+% T = subsets(1:4, 2, 1, 1) 
+% T{:} = 1, 2, 3, 4, [1 2], [1 3], [2 3], [1 4], [2 4], [3 4]
+%
+% [T, bitv] = subsets(S, U, L, sorted, N)
+% Row i of bitv is a bit vector representation of T{i},
+% where bitv has N columns (representing 1:N).
+% N defaults to max(S).
+%
+% Example:
+% [T,bitv] = subsets(2:4, 2^3, 0, 0, 5)
+% T{:} = [], 2, 3, [2 3], 4, [2 4], [3 4], [2 3 4]
+% bitv=
+%     0     0     0     0     0
+%     0     1     0     0     0
+%     0     0     1     0     0
+%     0     1     1     0     0
+%     0     0     0     1     0
+%     0     1     0     1     0
+%     0     0     1     1     0
+%     0     1     1     1     0
+
+n = length(S);
+
+if nargin < 2, U = n; end
+if nargin < 3, L = 0; end
+if nargin < 4, sorted = 0; end
+if nargin < 5, N = max(S); end
+
+bits = ind2subv(2*ones(1,n), 1:2^n)-1;
+sm = sum(bits,2);
+masks = bits((sm <= U) & (sm >= L), :);
+m = size(masks, 1);
+T = cell(1, m);
+for i=1:m
+  s = S(find(masks(i,:)));
+  T{i} = s;
+end
+
+if sorted 
+  T = sortcell(T);
+end
+
+bitv = zeros(m, N);
+bitv(:, S) = masks;