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

5 files changed, 87 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Entries
new file mode 100644
index 00000000..a35185ea
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Entries
@@ -0,0 +1,3 @@
+/mk_hmm_obs_lik_matrix.m/1.1.1.1/Sun May  4 21:42:26 2003//
+/mk_hmm_obs_lik_vec.m/1.1.1.1/Thu Jan 23 18:50:10 2003//
+D
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Repository
new file mode 100644
index 00000000..20dfc6fd
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/inference/dynamic/@hmm_inf_engine/private
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_matrix.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_matrix.m
new file mode 100644
index 00000000..441f3c0a
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_matrix.m
@@ -0,0 +1,30 @@
+function obslik = mk_hmm_obs_lik_matrix(engine, evidence)
+
+T  = size(evidence,2);
+Q = length(engine.startprob);
+obslik = ones(Q, T);
+bnet = bnet_from_engine(engine);
+% P(o1,o2| Q1,Q2) = P(o1|Q1,Q2) * P(o2|Q1,Q2)
+onodes = bnet.observed;
+for i=1:length(onodes)
+  data = cell2num(evidence(onodes(i),:));
+  if bnet.auto_regressive(onodes(i))
+    params = engine.obsprob{i};
+    mu = params.big_mu;
+    Sigma = params.big_Sigma,
+    W = params.big_W;
+    mu0 = params.big_mu0;
+    Sigma0 = params.big_Sigma0;
+    %obslik_i = mk_arhmm_obs_lik(data, mu, Sigma, W, mu0, Sigma0
+    obslik_i = clg_prob(data(:,1:T-1), data(:,2:T), mu, Sigma, W);
+    obslik_i = [mixgauss_prob(data(:,1), mu0, Sigma0) obslik_i];
+  elseif myismember(onodes(i), bnet.dnodes)
+    %obslik_i = eval_pdf_cond_multinomial(data, engine.obsprob{i}.big_CPT);
+    obslik_i = multinomial_prob(data, engine.obsprob{i}.big_CPT);
+  else
+    %obslik_i = eval_pdf_cond_gauss(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma);
+    obslik_i = mixgauss_prob(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma);
+  end
+  obslik = obslik .* obslik_i;
+end
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_vec.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_vec.m
new file mode 100644
index 00000000..16d30aec
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/private/mk_hmm_obs_lik_vec.m
@@ -0,0 +1,52 @@
+function obslik = mk_hmm_obs_lik_vec(engine, evidence)
+
+% P(o1,o2| h) = P(o1|h) * P(o2|h) where h = Q1,Q2,...
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+onodes = bnet.observed;
+hnodes = mysetdiff(1:ss, onodes);
+ns = bnet.node_sizes(:);
+ns(onodes) = 1;
+
+Q = length(engine.startprob);
+obslik = ones(Q, 1);
+
+for i=1:length(onodes)
+  o = onodes(i);
+  %data = cell2num(evidence(o,1));
+  data = evidence{o,1};
+  if myismember(o, bnet.dnodes)
+    obslik_i = eval_pdf_cond_multinomial(data, engine.obsprob{i}.CPT);
+  else
+    if bnet.auto_regressive(o)
+      error('can''t handle AR nodes')
+    end
+    %% calling mk_ghmm_obs_lik, which calls gaussian_prob, is slow, so we inline it
+    %% and use the pre-computed  inverse matrix
+    %obslik_i = mk_ghmm_obs_lik(data, engine.obsprob{i}.mu, engine.obsprob{i}.Sigma);
+    x = data(:);
+    m = engine.obsprob{i}.mu;
+    Qi = size(m, 2);
+    obslik_i = size(Qi, 1);
+    invC = engine.obsprob{i}.inv_Sigma;
+    denom = engine.obsprob{i}.denom;
+    for j=1:Qi
+      numer = exp(-0.5 * (x-m(:,j))' * invC(:,:,j) * (x-m(:,j)));
+      obslik_i(j) = numer / denom(j);
+    end
+  end
+  % convert P(o|ps) into P(o|h) by multiplying onto a (h,o) potential of all 1s
+  ps = bnet.parents{o};
+  dom = [ps o];
+  obspot_i = dpot(dom, ns(dom), obslik_i);
+  dom = [hnodes o];
+  obspot = dpot(dom, ns(dom));
+  obspot = multiply_by_pot(obspot, obspot_i);
+  % compute p(oi|h) * p(oj|h)
+  S = struct(obspot);
+  obslik = obslik .* S.T(:);
+end
+
+
+