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, 24 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/KPMtools/extend_domain_table.m b/sourcecodes/bnt-master/KPMtools/extend_domain_table.m
new file mode 100644
index 00000000..4ed0b2cd
--- /dev/null
+++ b/sourcecodes/bnt-master/KPMtools/extend_domain_table.m
@@ -0,0 +1,24 @@
+function B = extend_domain_table(A, smalldom, smallsz, bigdom, bigsz)
+% EXTEND_DOMAIN_TABLE Expand an array so it has the desired size.
+% B = extend_domain_table(A, smalldom, smallsz, bigdom, bigsz)
+%
+% A is the array with domain smalldom and sizes smallsz.
+% bigdom is the desired domain, with sizes bigsz.
+%
+% Example:
+% smalldom = [1 3], smallsz = [2 4], bigdom = [1 2 3 4], bigsz = [2 1 4 5],
+% so B(i,j,k,l) = A(i,k) for i in 1:2, j in 1:1, k in 1:4, l in 1:5
+
+if isequal(size(A), [1 1]) % a scalar
+  B = A; % * myones(bigsz);
+  return;
+end
+
+map = find_equiv_posns(smalldom, bigdom);
+sz = ones(1, length(bigdom));
+sz(map) = smallsz;
+B = myreshape(A, sz); % add dimensions for the stuff not in A
+sz = bigsz;
+sz(map) = 1; % don't replicate along A's dimensions
+B = myrepmat(B, sz(:)');
+