Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/bnt/CPDs/@mlp_CPD/convert_to_table.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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function T = convert_to_table(CPD, domain, evidence) % CONVERT_TO_TABLE Convert a mlp CPD to a table, incorporating any evidence % T = convert_to_table(CPD, domain, evidence) self = domain(end); ps = domain(1:end-1); % self' parents %cps = myintersect(ps, cnodes); % self' continous parents cnodes = domain(CPD.cpndx); cps = myintersect(ps, cnodes); odom = domain(~isemptycell(evidence(domain))); % obs nodes in the net assert(myismember(cps, odom)); % !ALL the CTS parents must be observed! ns(cps)=1; dps = mysetdiff(ps, cps); % self' discrete parents dobs = myintersect(dps, odom); % discrete obs parents % Extract the params compatible with the observations (if any) on the discrete parents (if any) if ~isempty(dobs), dvals = cat(1, evidence{dobs}); ns_eff= CPD.sizes; % effective node sizes ens=ns_eff; ens(dobs) = 1; S=prod(ens(dps)); subs = ind2subv(ens(dps), 1:S); mask = find_equiv_posns(dobs, dps); for i=1:length(mask), subs(:,mask(i)) = dvals(i); end support = subv2ind(ns_eff(dps), subs)'; else ns_eff= CPD.sizes; support=[1:prod(ns_eff(dps))]; end W1=[]; b1=[]; W2=[]; b2=[]; W1 = CPD.W1(:,:,support); b1= CPD.b1(support,:); W2 = CPD.W2(:,:,support); b2= CPD.b2(support,:); ns(odom) = 1; dpsize = prod(ns(dps)); % overall size of the self' discrete parents x = cat(1, evidence{cps}); ndata=size(x,2); if ~isempty(evidence{self}) % app=struct(CPD); % ns(self)=app.mlp{1}.nout; % pump up self to the original dimension if observed clear app; % end % T =zeros(dpsize, ns(self)); % for i=1:dpsize % W1app = W1(:,:,i); % b1app = b1(i,:); % W2app = W2(:,:,i); % b2app = b2(i,:); % for each of the dpsize combinations of self'parents values z = tanh(x(:)'*W1app + ones(ndata, 1)*b1app); % we tabulate the corrisponding glm model a = z*W2app + ones(ndata, 1)*b2app; % (element of the cell array CPD.glim) appoggio = normalise(exp(a)); % T(i,:)=appoggio; % W1app=[]; W2app=[]; b1app=[]; b2app=[]; % z=[]; a=[]; appoggio=[]; % end % if ~isempty(evidence{self}) appoggio=[]; % appoggio=zeros(1,ns(self)); % r = evidence{self}; %...if self is observed => in output there's only the probability of the 'true' class for i=1:dpsize % appoggio(i)=T(i,r); % end T=zeros(dpsize,1); for i=1:dpsize T(i,1)=appoggio(i); end clear appoggio; ns(self) = 1; end