From 8070dc963753142bb86c4ed698d91fd623ed28e7 Mon Sep 17 00:00:00 2001
From: ziejd2
Date: Thu, 28 Sep 2017 15:04:40 -0500
Subject: 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
---
 .../bnt-master/BNT/learning/learn_params_dbn.m     | 36 ++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 sourcecodes/bnt-master/BNT/learning/learn_params_dbn.m

(limited to 'sourcecodes/bnt-master/BNT/learning/learn_params_dbn.m')

diff --git a/sourcecodes/bnt-master/BNT/learning/learn_params_dbn.m b/sourcecodes/bnt-master/BNT/learning/learn_params_dbn.m
new file mode 100644
index 00000000..4d0dc501
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/learning/learn_params_dbn.m
@@ -0,0 +1,36 @@
+function bnet = learn_params_dbn(bnet, data)
+% LEARN_PARAM_DBN Estimate params of a DBN for a fully observed model
+% bnet = learn_params_dbn(bnet, data)
+%
+% data(i,t) is the value of node i in slice t (can be a cell array)
+% We currently assume there is a single time series
+%
+% We set bnet.CPD{i} to its ML/MAP estimate.
+%
+% Currently we assume each node in the first 2 slices has its own CPD (no param tying);
+% all nodes in slices >2 share their params with slice 2 as usual.
+
+[ss T] = size(data);
+
+% slice 1
+for j=1:ss
+  if adjustable_CPD(bnet.CPD{j})
+    fam = family(bnet.dag,j);
+    bnet.CPD{j} = learn_params(bnet.CPD{j}, data(fam,1));
+  end
+end
+
+
+% slices 2:T
+% data2(:,t) contains [data(:,t-1); data(:,t)].
+% Then we extract out the rows corresponding to the parents in the current and previous slice.
+data2 = [data(:,1:T-1);
+	 data(:,2:T)];
+for j=1:ss
+  j2 = j+ss;
+  if adjustable_CPD(bnet.CPD{j2})
+    fam = family(bnet.dag,j2);
+    bnet.CPD{j2} = learn_params(bnet.CPD{j2}, data2(fam,:));
+  end
+end
+
-- 
cgit 1.4.1