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, 75 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/examples/dynamic/Old/cmp_inference.m b/sourcecodes/bnt-master/BNT/examples/dynamic/Old/cmp_inference.m
new file mode 100644
index 00000000..b5c936f0
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/dynamic/Old/cmp_inference.m
@@ -0,0 +1,75 @@
+function [err, time, engine] = cmp_inference(bnet, engine, exact, T, filter, singletons, maximize)
+% CMP_INFERENCE Compare several inference engines on a DBN
+% [err, time, engine] = cmp_inference(bnet, engine, exact, T, filter, singletons, maximize)
+%
+% engine{i} is the i'th inference engine.
+% 'exact' specifies which engines do exact inference - 
+%   we check that these all give the same results.
+% 'T' is the length of the random sequence we generate.
+% If filter=1, we do filtering, else smoothing (default: smoothing)
+% If singletons=1, we compare marginal_nodes, else marginal_family (default: family)
+%
+% err(e,n,t) = sum_i | Pr_exact(X(n,t)=i) - Pr_e(X(n,t)=i) |
+%   where Pr_e = prob. according to engine e
+% time(e) = elapsed time for doing inference with engine e
+
+err = [];
+
+if nargin < 5, filter = 0; end
+if nargin < 6, singletons = 0; end
+if nargin < 7, maximize = 0; end
+
+check_ll = 1;
+
+assert(~maximize);
+
+E = length(engine);
+ref = exact(1); % reference
+
+ss = length(bnet.intra);
+ev = sample_dbn(bnet, 'length', T);
+evidence = cell(ss,T);
+onodes = bnet.observed;
+evidence(onodes,:) = ev(onodes, :);
+
+assert(~filter);
+for i=1:E
+  tic;
+  %[engine{i}, ll(i)] = enter_evidence(engine{i}, evidence, 'maximize', maximize);
+  [engine{i}, ll(i)] = enter_evidence(engine{i}, evidence);
+  time(i)=toc;
+  fprintf('engine %d took %6.4f seconds\n', i, time(i));
+end
+
+cmp = mysetdiff(exact, ref);
+if check_ll
+for i=cmp(:)'
+  if ~approxeq(ll(ref), ll(i))
+    error(['engine ' num2str(i) ' has wrong ll'])
+  end
+end
+end
+ll
+
+hnodes = mysetdiff(1:ss, onodes);
+m = cell(1,E);
+for t=1:T
+  for n=hnodes(:)'
+    for e=1:E
+      if singletons
+	m{e} = marginal_nodes(engine{e}, n, t);
+      else
+	m{e} = marginal_family(engine{e}, n, t);
+      end
+    end
+    for e=1:E
+      assert(isequal(m{e}.domain, m{ref}.domain));
+    end
+    for e=cmp(:)'
+      if ~approxeq(m{ref}.T(:), m{e}.T(:))
+	str= sprintf('engine %d is wrong; n=%d, t=%d', e, n, t);
+	error(str)
+      end
+    end
+  end
+end