enter_evidence.m

来自「Bayes网络工具箱」· M 代码 · 共 46 行

function [engine, loglik] = enter_evidence(engine, evidence, filter)
% ENTER_EVIDENCE Add the specified evidence to the network (bk_fast)
% [engine, loglik] = enter_evidence(engine, evidence, filter)
%
% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector)
% If filter = 1, we do filtering, else smoothing. (Default: filter = 0.)

if nargin < 3, filter = 0; end
  
[ss T] = size(evidence);
observed = ~isemptycell(evidence);
bnet = bnet_from_engine(engine);

onodes = find(observed);
onodes2 = unroll_set(engine.onodes_slice, ss, T);
assert(isequal(onodes(:), onodes2(:)));

cnodes = unroll_set(bnet.cnodes(:), ss, T);
big_dag = unroll_dbn_topology(bnet.intra1, bnet.intra, bnet.inter, T);
pot_type = determine_pot_type(onodes, cnodes, big_dag);
assert(pot_type == 'd');


% Convert CPDs of instantiated nodes to potential form
CPDpot = cell(ss,T);      
ns = repmat(bnet.node_sizes_slice(:), 1, T);
t = 1;
for n=1:ss
  fam = family(bnet.dag, n);
  e = bnet.equiv_class(n, 1);
  CPDpot{n,t} = CPD_to_table(bnet.CPD{e}, fam, ns, cnodes, evidence(:,1));
end
for n=1:ss
  fam = family(bnet.dag, n, 2);
  doms = unroll_set(fam, ss, T-1);
  e = bnet.equiv_class(n, 2);
  CPDpot(n,2:T) = CPD_to_tables(bnet.CPD{e}, doms, ns, cnodes, evidence);
end

[engine.cltables, loglik] = enter_soft_evidence(engine, CPDpot, observed, filter);

engine.filter = filter;
engine.T = T;