Mercurial > hg > ltpda
diff m-toolbox/test/test_ao_tfe_variance_montecarlo.m @ 0:f0afece42f48
Import.
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/test/test_ao_tfe_variance_montecarlo.m Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,58 @@ +% test_ao_tfe_variance_montecarlo +% +% Tests that the standard deviation returned by ao.dy in one +% frequency bin is equivalent to the matlab's std taking +% considering all realisations +% +% M Nofrarias 22-07-09 +% +% $Id: test_ao_tfe_variance_montecarlo.m,v 1.1 2009/08/11 14:20:10 miquel Exp $ + +% function test_ao_tfe_variance_montecarlo() + + clear + + % data + nsecs = 200; + fs = 10; + pl = plist('nsecs', nsecs, 'fs', fs, 'tsfcn', 'sin(2*pi*2*t) + randn(size(t))'); + + + % Make a filter + f1 = miir(plist('type', 'highpass', 'fc', 4, 'fs', fs)); + + % Window + Nfft = 100; + win = specwin('Hanning', Nfft); + pl2 = plist('Nfft',Nfft, 'win',win,'Olap',-1) + + % loop + for i = 1:100 + a1 = ao(pl); + a2 = filter(a1,plist('filter', f1)); + t1(i) = tfe(a1,a2,pl2); + % matlab's + [txy, f] = tfestimate(a1.data.y, a2.data.y, win.win, Nfft/2, Nfft, a1.data.fs); + t2(i) = ao(fsdata(f.', txy.')); + end + + %% mean + index = 6; + + % compare mean + mn = [mean(t1(:).y(index)) mean(t2(:).y(index))] + % error + err = std(t1(:).y(index)) + % compare standard deviation + clear rel + for i =1:len(t1(1)) + mn(i) = [mean(t1(:).y(i))]; % both means are equal + rel(:,i) = [std(t1(:).y(i)) mean(t1(:).dy(i))]/abs(mn(i)); + end + + figure + loglog(t1(1).x,rel') + figure + loglog(t1(1).x,100*abs(rel(2,:)-rel(1,:))) + ylabel('difference (%)') + \ No newline at end of file