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% TEST Fitting procedure in 2dim z-domain VDFIT
% At the end you have 4 stable transfer functions in partial fractions
% 
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% HISTORY:     02-10-2008 L Ferraioli
%                 Creation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% VERSION

'$Id: test_2dim_vdfit.m,v 1.1 2009/04/23 10:11:26 luigi Exp $';

%% Clear

clear all

%% Loading spectra

load ..\m-toolbox\test\mpsd.mat % load mpsd.mat first column is f then psd1, csd and psd2

f = mpsd(:,1);
csd11 = mpsd(:,2);
csd12 = mpsd(:,3);
csd21 = [];
csd22 = mpsd(:,4);

fs = 10;


%% Eigendecomposition

[tf11,tf12,tf21,tf22] = utils.math.eigcsd(csd11,csd12,csd21,csd22,'USESYM',0,'DIG',50,'OTP','TF');

%% Constructing vector

f1 = [tf11 tf21];
f2 = [tf12 tf22];

%% VDFIT
tic;

clear mlr1 mlr2

N = 32; %Order of approximation 


% Max Iteration
Nmaxiter = 40;

% mlr1 = zeros(Nmaxiter,1);
% mlr2 = zeros(Nmaxiter,1);

% Fitting params
fitin.stable = 0;
fitin.dterm = 0;
fitin.plot = 0;
fitin.fs = fs;

weight = utils.math.wfun(f1,2);
% weight = 1./abs(f1);

pparams = struct('spolesopt',3, 'type','DISC', 'pamp', 0.98);
poles1 = utils.math.startpoles(N,f,pparams);
for hh = 1:Nmaxiter
  [res1,poles1,dterm1,mresp1,rdl1,sqe1] = utils.math.vdfit(f1,f,poles1,weight,fitin); % Fitting
  disp(['Iter' num2str(hh)])

  % Stop condition checking
  mlr1(hh) = sqe1(:,1);
  mlr2(hh) = sqe1(:,2);
%   [ext1,msg1] = utils.math.stopfit(f1(:,1),rdl1(:,1),mlr1,'lrsrmse',2,15);
%   [ext2,msg2] = utils.math.stopfit(f1(:,2),rdl1(:,2),mlr2,'lrsrmse',2,15);
  
%   order = length(poles1);
%   mlr1(hh) = mean(log10(abs(f1(:,1)))-log10(abs(rdl1(:,1))));
%   mlr2(hh) = mean(log10(abs(f1(:,2)))-log10(abs(rdl1(:,2))));
%   [ext1,msg1] = utils.math.stopfit(f1(:,1),rdl1(:,1),mlr1,order,'lrs',1,0.0001,2);
%   [ext2,msg2] = utils.math.stopfit(f1(:,2),rdl1(:,2),mlr2,order,'lrs',1,0.0001,2);

%   if ext1 && ext2
%     disp(msg1)
%     break
%   end

end
elpstime = toc;

% plotting squared error
figure()
semilogy(mlr1,'-ok')
hold on
grid on
semilogy(mlr2,'-or')

% % plotting RMS error variation
% figure()
% semilogy(abs(diff(sqrt(mlr1))),'-ok')
% hold on
% grid on
% semilogy(abs(diff(sqrt(mlr2))),'-or')

% plotting squared error variation
figure()
semilogy(abs(diff(mlr1)./mlr1(1,end-1)),'-ok')
hold on
grid on
semilogy(abs(diff(mlr2)./mlr2(1,end-1)),'-or')

%% All Passing

% [np1,resp1] = pfallpz(res1,poles1,dterm1,mresp1,f,fs);
[nr1,np1,nd1,resp1] = utils.math.pfallpsymz(res1,poles1,dterm1,mresp1,f,fs);


figure()
subplot(2,1,1);
p1 = loglog(f,abs(mresp1),'k');
hold on
p2 = loglog(f,abs(resp1),'r');
xlabel('Frequency [Hz]')
ylabel('Amplitude')
legend([p1(1) p2(1)],'VDFIT','Stabilized')
hold off

subplot(2,1,2);
p4 = semilogx(f,(180/pi).*unwrap(angle(mresp1)),'k');
hold on
p5 = semilogx(f,(180/pi).*unwrap(angle(resp1)),'r');
xlabel('Frequency [Hz]')
ylabel('Phase [Deg]')
legend([p4(1) p5(1)],'VDFIT', 'Stabilized')
hold off

%% VDFIT

clear mlr3 mlr4 ext1 ext2
N = 24; %Order of approximation


% Max Iteration
Nmaxiter = 70;

% Fitting params
fitin.stable = 0;
fitin.dterm = 0;
fitin.plot = 1;
fitin.fs = fs;

weight = utils.math.wfun(f2,2);

pparams = struct('spolesopt',2, 'type','DISC', 'pamp', 0.98);
poles2 = utils.math.startpoles(N,f,pparams);

for hh = 1:Nmaxiter
  [res2,poles2,dterm2,mresp2,rdl2,rmse2] = utils.math.vdfit(f2,f,poles2,weight,fitin); % Fitting
  disp(['Iter' num2str(hh)])

  % Stop condition checking
  mlr3(hh) = rmse2(:,1);
  mlr4(hh) = rmse2(:,2);
  [ext1,msg1] = utils.math.stopfit(f2(:,1),rdl2(:,1),mlr3,'lrsrmse',2,15);
  [ext2,msg2] = utils.math.stopfit(f2(:,2),rdl2(:,2),mlr4,'lrsrmse',2,15);

  if ext1 && ext2
    disp(msg1)
    break
  end

end

% plotting RMS error
figure()
semilogy(mlr3,'-ok')
hold on
grid on
semilogy(mlr4,'-or')

%%
% params = struct('spolesopt',2, 'Nmaxiter',250, 'minorder',30,...
%   'maxorder',60, 'weightparam',1, 'plot',0,...
%   'ctp','lrs','lrscond',1,'lrsvarcond',1,'nrmsecond',2,...
%   'stabfit',0,'dterm',0,'spy',0);
% 
% [res2,poles2,dterm2,mresp2,rdl2] = autodfit(f2,f,fs,params);