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1 function T = convert_to_table(CPD, domain, evidence)
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2 % CONVERT_TO_TABLE Convert a softmax CPD to a table, incorporating any evidence
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3 % T = convert_to_table(CPD, domain, evidence)
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4
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5 self = domain(end);
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6 ps = domain(1:end-1);
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7 cnodes = domain(CPD.cpndx);
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8 cps = myintersect(ps, cnodes);
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9 dps = domain(CPD.dpndx);
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10 dps_as_cps = domain(CPD.dps_as_cps.ndx);
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11 all_dps = union(dps,dps_as_cps);
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12 odom = domain(~isemptycell(evidence(domain)));
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13 if ~isempty(cps), assert(myismember(cps, odom)); end % all cts parents must be observed
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14
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15 ns = zeros(1, max(domain));
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16 ns(domain) = CPD.sizes;
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17 ens = ns; % effective node sizes
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18 ens(odom) = 1;
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19
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20 % dpsize >= glimsz because the glm parameters are tied across the dps_as_cps parents
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21 dpsize = prod(ens(all_dps)); % size of ALL self'discrete parents
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22 dpvals = cat(1, evidence{myintersect(all_dps, odom)});
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23 cpvals = cat(1, evidence{cps});
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24 if ~isempty(dps_as_cps),
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25 separator = CPD.dps_as_cps.separator;
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26 dp_as_cpmap = find_equiv_posns(dps_as_cps, all_dps);
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27 dops_map = find_equiv_posns(myintersect(all_dps, odom), all_dps);
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28 puredp_map = find_equiv_posns(dps, all_dps);
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29 subs = ind2subv(ens(all_dps), 1:prod(ens(all_dps)));
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30 if ~isempty(dops_map), subs(:,dops_map) = subs(:,dops_map)+repmat(dpvals(:)',[size(subs,1) 1])-1; end
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31 end
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32
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33 [w,b] = extract_params(CPD);
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34 T = zeros(dpsize, ns(self));
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35 for i=1:dpsize,
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36 active_glm = i;
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37 dp_as_cpvals=zeros(1,sum(ns(dps_as_cps)));
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38 if ~isempty(dps_as_cps),
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39 active_glm = max([1,subv2ind(ns(dps), subs(i,puredp_map))]);
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40 % Extract the params compatible with the observations (if any) on the 'pure' discrete parents (if any)
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41 where_one = separator + subs(i,dp_as_cpmap);
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42 % and get in the dp_as_cp parents...
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43 dp_as_cpvals(where_one)=1;
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44 end
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45 T(i,:) = normalise(exp([dp_as_cpvals(:); cpvals(:)]'*w(:,:,active_glm) + b(:,active_glm)'));
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46 end
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47 if myismember(self, odom)
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48 r = evidence{self};
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49 T = T(:,r);
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50 end
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51
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52 T = myreshape(T, ens(domain));
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