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root / _FullBNT / BNT / CPDs / @hhmmQ_CPD / Old / update_ess2.m @ 8:b5b38998ef3b

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function CPD = update_ess2(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
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% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
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% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
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% Figure out the node numbers associated with each parent
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dom = fmarginal.domain;
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self = dom(end); % by assumption
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old_self = dom(CPD.old_self_ndx);
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Fself = dom(CPD.Fself_ndx);
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Fbelow = dom(CPD.Fbelow_ndx);
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Qps = dom(CPD.Qps_ndx);
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Qsz = CPD.Qsz;
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Qpsz = CPD.Qpsz;
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fmarg = add_ev_to_dmarginal(fmarginal, evidence, ns);
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% hor_counts(old_self, Qps, self),
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% fmarginal(old_self, Fbelow, Fself, Qps, self)
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% hor_counts(i,k,j) = fmarginal(i,2,1,k,j) % below has finished, self has not
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% ver_counts(i,k,j) = fmarginal(i,2,2,k,j) % below has finished, and so has self (reset)
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% Since any of i,j,k may be observed, we write
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% hor_counts(counts_ndx{:}) = fmarginal(fmarg_ndx{:})
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% where e.g., counts_ndx = {1, ':', 2} if Qps is hidden but we observe old_self=1, self=2.
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% To create this counts_ndx, we write counts_ndx = mk_multi_ndx(3, obs_dim, obs_val)
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% where counts_obs_dim = [1 3], counts_obs_val = [1 2] specifies the values of dimensions 1 and 3.
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counts_obs_dim = [];
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fmarg_obs_dim = [];
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obs_val = []; 
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if hidden_bitv(self)
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  effQsz = Qsz;
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else
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  effQsz = 1;
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  counts_obs_dim = [counts_obs_dim 3];
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  fmarg_obs_dim = [fmarg_obs_dim 5];
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  obs_val = [obs_val evidence{self}];
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end
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% e.g., D=4, d=3, Qps = all Qs above, so dom = [Q3(t-1) F4(t-1) F3(t-1) Q1(t) Q2(t) Q3(t)].
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% so self = Q3(t), old_self = Q3(t-1), CPD.Qps = [1 2], Qps = [Q1(t) Q2(t)]
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dom = fmarginal.domain;
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self = dom(end);
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old_self = dom(1);
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Qps = dom(length(dom)-length(CPD.Qps):end-1);
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Qsz = CPD.Qsizes(CPD.d);
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Qpsz = prod(CPD.Qsizes(CPD.Qps));
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% If some of the Q nodes are observed (which happens during supervised training)
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% the counts will only be non-zero in positions
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% consistent with the evidence. We put the computed marginal responsibilities
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% into the appropriate slots of the big counts array.
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% (Recall that observed discrete nodes only have a single effective value.)
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% (A more general, but much slower, way is to call add_evidence_to_dmarginal.)
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% We assume the F nodes are never observed.
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obs_self = ~hidden_bitv(self);
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obs_Qps = (~isempty(Qps)) & (~any(hidden_bitv(Qps))); % we assume that all or none of the Q parents are observed
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if obs_self
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  self_val = evidence{self};
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  oldself_val = evidence{old_self};
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end
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if obs_Qps
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  Qps_val = subv2ind(Qpsz, cat(1, evidence{Qps}));
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  if Qps_val == 0
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    keyboard
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  end
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end
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if CPD.d==1 % no Qps from above
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  if ~CPD.F1toQ1 % no F from self
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    % marg(Q1(t-1), F2(t-1), Q1(t))                            
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    % F2(t-1) P(Q1(t)=j | Q1(t-1)=i)
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    % 1       delta(i,j)
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    % 2       transprob(i,j)
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    if obs_self
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      hor_counts = zeros(Qsz, Qsz);
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      hor_counts(oldself_val, self_val) = fmarginal.T(2);
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    else
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      marg = reshape(fmarginal.T, [Qsz 2 Qsz]);
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      hor_counts = squeeze(marg(:,2,:));
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    end
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  else
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    % marg(Q1(t-1), F2(t-1), F1(t-1), Q1(t))                            
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    % F2(t-1) F1(t-1)  P(Qd(t)=j| Qd(t-1)=i)
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    % ------------------------------------------------------
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    % 1        1         delta(i,j)
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    % 2        1         transprob(i,j)
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    % 1        2         impossible
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    % 2        2         startprob(j)
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    if obs_self
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      marg = myreshape(fmarginal.T, [1 2 2 1]);
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      hor_counts = zeros(Qsz, Qsz);
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      hor_counts(oldself_val, self_val) = marg(1,2,1,1);
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      ver_counts = zeros(Qsz, 1);
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      %ver_counts(self_val) = marg(1,2,2,1);
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      ver_counts(self_val) = marg(1,2,2,1) + marg(1,1,2,1);
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    else
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      marg = reshape(fmarginal.T, [Qsz 2 2 Qsz]);
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      hor_counts = squeeze(marg(:,2,1,:));
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      %ver_counts = squeeze(sum(marg(:,2,2,:),1)); % sum over i
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      ver_counts = squeeze(sum(marg(:,2,2,:),1)) + squeeze(sum(marg(:,1,2,:),1)); % sum i,b
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    end
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  end % F1toQ1
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else % d ~= 1
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  if CPD.d < CPD.D % general case
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    % marg(Qd(t-1), Fd+1(t-1), Fd(t-1), Qps(t), Qd(t))                            
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    % Fd+1(t-1) Fd(t-1)  P(Qd(t)=j| Qd(t-1)=i, Qps(t)=k)
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    % ------------------------------------------------------
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    % 1        1         delta(i,j)
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    % 2        1         transprob(i,k,j)
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    % 1        2         impossible
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    % 2        2         startprob(k,j)
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    if obs_Qps & obs_self
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      marg = myreshape(fmarginal.T, [1 2 2 1 1]);
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      k = 1;
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      hor_counts = zeros(Qsz, Qpsz, Qsz);
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      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 2,1, k,1);
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      ver_counts = zeros(Qpsz, Qsz);
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      %ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1);
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      ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1) + marg(1, 1,2, k,1);
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    elseif obs_Qps & ~obs_self
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      marg = myreshape(fmarginal.T, [Qsz 2 2 1 Qsz]);
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      k = 1;
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      hor_counts = zeros(Qsz, Qpsz, Qsz);
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      hor_counts(:, Qps_val, :) = marg(:, 2,1, k,:);
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      ver_counts = zeros(Qpsz, Qsz);
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      %ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1);
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      ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1) + sum(marg(:, 1,2, k,:), 1);
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    elseif ~obs_Qps & obs_self
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      error('not yet implemented')
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    else % everything is hidden
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      marg = reshape(fmarginal.T, [Qsz 2 2 Qpsz Qsz]);
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      hor_counts = squeeze(marg(:,2,1,:,:)); % i,k,j
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      %ver_counts = squeeze(sum(marg(:,2,2,:,:),1)); % sum over i
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      ver_counts = squeeze(sum(marg(:,2,2,:,:),1)) + squeeze(sum(marg(:,1,2,:,:),1)); % sum over i,b
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    end
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  else % d == D, so no F from below
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    % marg(QD(t-1), FD(t-1), Qps(t), QD(t))                            
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    % FD(t-1) P(QD(t)=j | QD(t-1)=i, Qps(t)=k)
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    % 1      transprob(i,k,j) 
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    % 2      startprob(k,j)
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    if obs_Qps & obs_self
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      marg = myreshape(fmarginal.T, [1 2 1 1]);
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      k = 1;
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      hor_counts = zeros(Qsz, Qpsz, Qsz);
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      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 1, k,1);
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      ver_counts = zeros(Qpsz, Qsz);
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      ver_counts(Qps_val, self_val) = marg(1, 2, k,1);
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    elseif obs_Qps & ~obs_self
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      marg = myreshape(fmarginal.T, [Qsz 2 1 Qsz]);
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      k = 1;
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      hor_counts = zeros(Qsz, Qpsz, Qsz);
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      hor_counts(:, Qps_val, :) = marg(:, 1, k,:);
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      ver_counts = zeros(Qpsz, Qsz);
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      ver_counts(Qps_val, :) = sum(marg(:, 2, k, :), 1);
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    elseif ~obs_Qps & obs_self
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      error('not yet implemented')
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    else % everything is hidden
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      marg = reshape(fmarginal.T, [Qsz 2 Qpsz Qsz]);
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      hor_counts = squeeze(marg(:,1,:,:));
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      ver_counts = squeeze(sum(marg(:,2,:,:),1)); % sum over i
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    end
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  end
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end
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CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
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if ~isempty(CPD.sub_CPD_start)
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  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
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end
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