Mauch MIREX 2010

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