1 | itload('iter_cond_debug3.it'); |
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2 | |
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3 | ndat = 1000; % check if true! |
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4 | |
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5 | prop_mean=zeros(3,40); |
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6 | prop_var=zeros(3,40); |
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7 | for it=0:39 |
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8 | si = num2str(it); |
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9 | eval(['eff_w(it+1) = 1/(w' si '''*w' si ');']); |
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10 | eval(['prop_mean(1:3,it+1) = Mpred_mean' si ';']); |
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11 | eval(['prop_var(1:3,it+1) = Mpred_var' si '(1:3);']); |
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12 | end |
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13 | |
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14 | figure(2) |
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15 | subplot(1,2,1) |
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16 | hold off |
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17 | plot(eff_w) |
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18 | xlabel('iteration'); |
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19 | title('Effective sample size'); |
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20 | %title('Non-normalized importance weights') |
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21 | |
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22 | subplot(1,2,2); |
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23 | hold off |
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24 | plot(prop_mean'); |
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25 | hold on |
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26 | plot(prop_mean'+2*sqrt(prop_var'),'.'); |
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27 | plot(prop_mean'-2*sqrt(prop_var'),'.'); |
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28 | |
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29 | %plot(ones(size(prop_mean,2),1)*[3 2],'--') |
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30 | xlabel('iteration'); |
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31 | title('Mean value of the joint merger $\tilde{f}(\bm{x})$'); |
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32 | |
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33 | % itload('../merger_iter_test.it'); |
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34 | % XG = reshape(Grid(1,:),Npoints,Npoints); |
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35 | % YG = reshape(Grid(2,:),Npoints,Npoints); |
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36 | % |
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37 | % figure(2); |
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38 | % M1 = reshape(exp(Res1),Npoints,Npoints); |
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39 | % contour(XG,YG,M1,7); |
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40 | % |
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41 | % figure(3); |
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42 | % hold off |
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43 | % mm = max(max(Res2)); |
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44 | % for i=1:size(Res2,1) |
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45 | % M2 = reshape(Res2(i,:),Npoints,Npoints); |
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46 | % contour(XG,YG,M2,[0:mm/7:mm]); |
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47 | % hold on |
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48 | % end |
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49 | |
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