diff toolboxes/FullBNT-1.0.7/bnt/general/mk_mutilated_samples.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/general/mk_mutilated_samples.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,38 @@
+function [data, clamped] = mk_mutilated_samples(bnet, ncases, max_clamp, usecell)
+% GEN_MUTILATED_SAMPLES Do random interventions and then draw random samples
+% [data, clamped] = gen_mutilated_samples(bnet, ncases, max_clamp, usecell)
+%
+% At each step, we pick a random subset of size 0 .. max_clamp, and 
+% clamp these nodes to random values.
+%
+% data(i,m) is the value of node i in case m.
+% clamped(i,m) = 1 if node i in case m was set by intervention.
+
+if nargin < 4, usecell = 1; end
+
+ns = bnet.node_sizes;
+n = length(bnet.dag);
+if usecell
+  data = cell(n, ncases);
+else
+  data = zeros(n, ncases);
+end
+clamped = zeros(n, ncases);
+
+csubsets = subsets(1:n, max_clamp, 0); % includes the empty set
+distrib_cset = normalise(ones(1, length(csubsets)));
+
+for m=1:ncases
+  cset = csubsets{sample_discrete(distrib_cset)};
+  nvals = prod(ns(cset));
+  distrib_cvals = normalise(ones(1, nvals));
+  cvals = ind2subv(ns(cset), sample_discrete(distrib_cvals));
+  mutilated_bnet = do_intervention(bnet, cset, cvals);
+  ev = sample_bnet(mutilated_bnet);
+  if usecell
+    data(:,m) = ev;
+  else
+    data(:,m) = cell2num(ev);
+  end
+  clamped(cset,m) = 1;
+end