%  test_ao_ltfe_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_lcpsd_variance_montecarlo.m,v 1.1 2009/08/11 14:20:10 miquel Exp $

% function test_ao_ltfe_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 = 1000;
win  = specwin('Hanning', Nfft);
pl2 = plist('Lmin',200,'win',win,'Olap',-1)

% loop
for  i = 1:100
  a1 = ao(pl);
  a2 = filter(a1,plist('filter', f1));
  t1(i) = lcpsd(a1,a2,pl2);
end

%% mean
index = 6;

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

k = find(t1(1).procinfo,'k')


figure
loglog(t1(1).x,rel')
figure
loglog(t1(1).x,abs(rel(2,:)-rel(1,:)))