Mercurial > hg > ltpda
view m-toolbox/test/test_ao_dispersion.m @ 0:f0afece42f48
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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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% A test script for ao/dispersion % % M Nofrarias 07-05-09 % % $Id: test_ao_dispersion.m,v 1.2 2009/05/08 13:15:36 miquel Exp $ % function test_ao_dispersion() fs =10; f = logspace(-5,log10(fs/2),100)'; %% nominal plist pl = plist( 'f', f,... 'fs', fs,... 'wp1',0.0010488*1i,... % sqrt(-11e-7) 'wp2',0.0014832*1i,... % sqrt(-22e-7) 'Cdf',0.8,... 'Clfs',1.15,... 'dS',1.35e-4,... 'p_ifo1',[3.6e-12 10e-3 4.2 1.8e-3 8],... 'p_tm1',[7e-15 5e-3 3 4e-4 9],... 'p_ifo2', [3.6e-12 10e-3 4.2 1.8e-3 8],... 'p_tm2', [7e-15 5e-3 3 4e-4 9],... 'p_sc', [2.5e-10 12e-3 3.8 1e-3 8],... 'nsecs', 1e4,... 'fsgen', 50); %% Compute transfer function tf1 = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',1),pl); % tf2 = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',3),pl); % tf3 = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',4),pl); % matched stiffness case % % plx = pset(pl,param('wp1',0.00154919*i)) % sqrt(-24e-7) % plx = pset(plx,param('wp2',0.00154919*i)) % sqrt(-24e-7) % % tf1x = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',1),plx); % tf2x = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',3),plx); % tf3x = ao(plist('built-in','mdc2r2_fd_ifo2ifo','index',4),plx); a = ao(fsdata(f,(f'.^2).*ones(1,length(f)))); a2 = ao(fsdata(f,(1./f'.^2).*ones(1,length(f)))); %% dispersion function disp = dispersion(a,plist('model','mdc2r2','channel','i1o1'),pl); disp2 = dispersion(a2,plist('model','mdc2r2','channel','i1o1'),pl); %% plot iplot(abs(tf1),disp,disp2) %% compute transfer function error noise_in = length(f)*fs/2*noise_param(f,7e-15,5e-3,3,4e-4,9) noise_out = length(f)*fs/2*noise_param(f,3.6e-12,10e-3,4.2,1.8e-3,8) varTF = disp.*(noise_in.*abs(tf1) + noise_out) varTF.setName varTF2 = disp2.*(noise_in.*abs(tf1) + noise_out) varTF2.setName % iplot(abs(tf1),plist('YErrU',sqrt(varTF))) iplot(abs(tf1),sqrt(varTF),sqrt(varTF2)) end %-------------------------------------------------------------------------- % Parametric function for noise contributions %-------------------------------------------------------------------------- function o = noise_param(varargin) f = varargin{1}; p1 = varargin{2}; p2 = varargin{3}; p3 = varargin{4}; p4 = varargin{5}; p5 = varargin{6}; % Description of the noise fcn = p1^2*(1 + 1./(f./p2).^p3 + 1./(f./p4).^p5).^(1/2) ; % Build AO from plist o = ao(fsdata(f,fcn)); end