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1 function CPD = maximize_params(CPD, temp)
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2 % MAXIMIZE_PARAMS Set the params of a CPD to their ML values (Gaussian)
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3 % CPD = maximize_params(CPD, temperature)
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4 %
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5 % Temperature is currently ignored.
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6
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7 if ~adjustable_CPD(CPD), return; end
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8
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9
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10 if CPD.clamped_mean
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11 cl_mean = CPD.mean;
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12 else
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13 cl_mean = [];
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14 end
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15
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16 if CPD.clamped_cov
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17 cl_cov = CPD.cov;
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18 else
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19 cl_cov = [];
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20 end
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21
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22 if CPD.clamped_weights
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23 cl_weights = CPD.weights;
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24 else
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25 cl_weights = [];
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26 end
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27
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28 [ssz psz Q] = size(CPD.weights);
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29
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30 [ss cpsz dpsz] = size(CPD.weights); % ss = self size = ssz
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31 if cpsz > CPD.nsamples
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32 fprintf('gaussian_CPD/maximize_params: warning: input dimension (%d) > nsamples (%d)\n', ...
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33 cpsz, CPD.nsamples);
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34 end
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35
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36 prior = repmat(CPD.cov_prior_weight*eye(ssz,ssz), [1 1 Q]);
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37
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38
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39 [CPD.mean, CPD.cov, CPD.weights] = ...
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40 clg_Mstep(CPD.Wsum, CPD.WYsum, CPD.WYYsum, [], CPD.WXsum, CPD.WXXsum, CPD.WXYsum, ...
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41 'cov_type', CPD.cov_type, 'clamped_mean', cl_mean, ...
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42 'clamped_cov', cl_cov, 'clamped_weights', cl_weights, ...
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43 'tied_cov', CPD.tied_cov, ...
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44 'cov_prior', prior);
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45
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46 if 0
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47 CPD.mean = reshape(CPD.mean, [ss dpsz]);
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48 CPD.cov = reshape(CPD.cov, [ss ss dpsz]);
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49 CPD.weights = reshape(CPD.weights, [ss cpsz dpsz]);
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50 end
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51
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52 % Bug fix 11 May 2003 KPM
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53 % clg_Mstep collapses all discrete parents into one mega-node
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54 % but convert_to_CPT needs access to each parent separately
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55 sz = CPD.sizes;
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56 ss = sz(end);
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57
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58 % Bug fix KPM 20 May 2003:
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59 cpsz = sum(sz(CPD.cps));
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60 %if isempty(CPD.cps)
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61 % cpsz = 0;
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62 %else
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63 % cpsz = sz(CPD.cps);
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64 %end
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65 dpsz = sz(CPD.dps);
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66 CPD.mean = myreshape(CPD.mean, [ss dpsz]);
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67 CPD.cov = myreshape(CPD.cov, [ss ss dpsz]);
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68 CPD.weights = myreshape(CPD.weights, [ss cpsz dpsz]);
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