[310] | 1 | itload('iter_cond_debug.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 | XL = [-3 3]; |
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| 6 | YL= XL; |
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| 7 | |
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| 8 | iters =[];% [0 2 39] |
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| 9 | |
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| 10 | figure(1); |
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| 11 | niters = length(iters); |
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| 12 | noi = 1; |
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| 13 | for it=iters |
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| 14 | % figure(it+1) |
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| 15 | subplot(5,niters,noi); |
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| 16 | si = num2str(it); |
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| 17 | eval(['contour_2(Smp' si '(1,:),Smp' si '(2,:),exp(Mpdf' si '''))']); |
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| 18 | if it==iters(1), |
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| 19 | ylabel('Proposal density '); |
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| 20 | end |
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| 21 | set(gca,'XLim',XL); |
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| 22 | set(gca,'YLim',YL); |
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| 23 | |
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| 24 | subplot(5,niters,noi+niters); |
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| 25 | eval(['contour_2(Smp' si '(1,:),Smp' si '(2,:),exp(lW' si '(1,:)))']); |
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| 26 | if it==iters(1), |
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| 27 | ylabel('First source'); |
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| 28 | end |
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| 29 | set(gca,'XLim',XL); |
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| 30 | set(gca,'YLim',YL); |
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| 31 | |
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| 32 | subplot(5,niters,noi+2*niters); |
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| 33 | eval(['contour_2(Smp' si '(1,:),Smp' si '(2,:),exp(lW' si '(2,:)))']); |
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| 34 | if it==iters(1), |
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| 35 | ylabel('Second source'); |
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| 36 | end |
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| 37 | set(gca,'XLim',XL); |
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| 38 | set(gca,'YLim',YL); |
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| 39 | |
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| 40 | |
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| 41 | subplot(5,niters,noi+3*niters); |
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| 42 | hold off |
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| 43 | eval(['contour_2(Smp' si '(1,:),Smp' si '(2,:),w' si ''')']); |
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| 44 | if it==iters(1), |
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| 45 | ylabel('Merged density'); |
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| 46 | end |
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| 47 | set(gca,'XLim',XL); |
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| 48 | set(gca,'YLim',YL); |
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| 49 | |
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| 50 | subplot(5,niters,noi+4*niters); |
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| 51 | hold off |
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| 52 | eval(['contour_2(Smp' si '(1,:),Smp' si '(2,:),exp(lw_m' si '''))']); |
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| 53 | if it==iters(1), |
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| 54 | ylabel('Importance density'); |
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| 55 | end |
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| 56 | set(gca,'XLim',XL); |
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| 57 | set(gca,'YLim',YL); |
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| 58 | noi = noi+1; |
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| 59 | end |
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| 60 | |
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| 61 | prop_mean=zeros(2,40); |
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| 62 | prop_var=zeros(2,40); |
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| 63 | for it=0:39 |
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| 64 | si = num2str(it); |
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| 65 | eval(['eff_w(it+1) = 1/(w' si '''*w' si ');']); |
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| 66 | eval(['prop_mean(1:2,it+1) = Mpred_mean' si ';']); |
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| 67 | eval(['prop_var(1:2,it+1) = Mpred_var' si '(1:2);']); |
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| 68 | end |
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| 69 | |
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| 70 | figure(2) |
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| 71 | subplot(1,2,1) |
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| 72 | hold off |
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| 73 | plot(eff_w) |
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| 74 | xlabel('iteration'); |
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| 75 | ylabel('Effective sample size'); |
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| 76 | %title('Non-normalized importance weights') |
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| 77 | |
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| 78 | subplot(1,2,2); |
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| 79 | hold off |
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| 80 | plot(prop_mean'); |
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| 81 | hold on |
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| 82 | plot(prop_mean'+2*sqrt(prop_var'),'.'); |
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| 83 | plot(prop_mean'-2*sqrt(prop_var'),'.'); |
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| 84 | |
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| 85 | %plot(ones(size(prop_mean,2),1)*[3 2],'--') |
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| 86 | xlabel('iteration'); |
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| 87 | title('Mean value of the joint merger $\tilde{f}(\bm{x})$'); |
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| 88 | |
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| 89 | % itload('../merger_iter_test.it'); |
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| 90 | % XG = reshape(Grid(1,:),Npoints,Npoints); |
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| 91 | % YG = reshape(Grid(2,:),Npoints,Npoints); |
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| 92 | % |
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| 93 | % figure(2); |
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| 94 | % M1 = reshape(exp(Res1),Npoints,Npoints); |
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| 95 | % contour(XG,YG,M1,7); |
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| 96 | % |
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| 97 | % figure(3); |
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| 98 | % hold off |
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| 99 | % mm = max(max(Res2)); |
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| 100 | % for i=1:size(Res2,1) |
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| 101 | % M2 = reshape(Res2(i,:),Npoints,Npoints); |
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| 102 | % contour(XG,YG,M2,[0:mm/7:mm]); |
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| 103 | % hold on |
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| 104 | % end |
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| 105 | |
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