--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/test/test_ao_noisegen1D.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,229 @@
+% A test script for ao/noisegen1D
+% 
+% L. Ferraioli 10-11-08
+% 
+% $Id: test_ao_noisegen1D.m,v 1.7 2010/05/04 13:30:35 luigi Exp $
+% 
+
+%% Make white noise and compare results %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+% Description:
+% 1) Generates a random series of data (white)
+% 2) Build a pzm
+% 3) Calculate equivalent one sided data psd from pzm response
+% 4) Generates a miir object from pzm
+% 5) Filer white data with miir to generate reference colored noise
+% 6) Generates colored noise with noisegen1D
+% 7) calculated psd of generated and reference data
+% 8) check result by plotting
+
+% 1)
+a = ao(plist('tsfcn', 'randn(size(t))', 'fs', 10, 'nsecs', 10000));
+
+% PSD model
+% 2)
+pzm = pzmodel(1, {0.01}, {0.1});
+% 3)
+mod = (abs(pzm.resp).^2).*(2/fs); % this corresponds to the theoretical one sided psd of the data
+% 4)
+fpzm = miir(pzm,plist('fs',fs));
+% 5)
+acr = filter(a,fpzm);
+
+% 6) Noise generation
+pl = plist(...
+    'model', mod, ...
+    'MaxIter', 10, ...
+    'PoleType', 3, ...
+    'MinOrder', 2, ...
+    'MaxOrder', 9, ...
+    'Weights', 2, ...
+    'Plot', false,...
+    'Disp', false,...
+    'MSEVARTOL', 1e-3,...
+    'FITTOL', 1e-5);
+
+ac = noisegen1D(a, pl);
+
+% 7)
+acxx = ac.psd;
+acrxx = acr.psd;
+% 8)
+iplot(acxx,acrxx,mod);
+
+%% Noise generation from fsdata model object - output time series %%%%%%%%
+
+% Description:
+% 1) Generates a fsdata object to be used as psd model
+% 2) Generates a random series of data (white)
+% 3) Generates colored noise with noisegen1D
+% 4) calculated psd of generated data
+% 5) check result by plotting
+
+% 1)
+fs = 10; % sampling frequency
+f = logspace(-6,log10(5),1000);
+pl_mod1 = plist('fsfcn', '0.01./(0.01+f)', 'f', f);
+mod1 = ao(pl_mod1); % fsdata model object
+
+% 2)
+% generating white noise
+a1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 10000));
+
+% 3) Noise generation
+
+pl1 = plist(...
+    'model', mod1, ...
+    'MaxIter', 30, ...
+    'PoleType', 2, ...
+    'MinOrder', 3, ...
+    'MaxOrder', 20, ...
+    'Weights', 3, ...
+    'Plot', false,...
+    'Disp', false,...
+    'MSEVARTOL', 1e-3,...
+    'FITTOL', 1e-5);
+
+ac1 = noisegen1D(a1, pl1);
+
+% 4)
+acxx1 = ac1.psd;
+% 5)
+iplot(acxx1, mod1);
+
+%% Noise generation from fsdata model object - output filter %%%%%%%%%%%%%
+
+% Description:
+% 1) Generates a fsdata object to be used as psd model
+% 2) Generates coloring filter with noisegen1D
+% 3) Generates white noise data
+% 4) filter data
+% 4) calculated psd of filtered data
+% 5) check result by plotting
+
+% 1) Generates a fsdata object to be used as psd model
+fs = 10; % sampling frequency
+f = logspace(-6,log10(5),1000);
+pl_mod = plist('fsfcn', '0.01./(0.01+f)', 'f', f);
+mod = ao(pl_mod); % fsdata model object
+
+% 2) noise coloring filter generation
+
+pl1 = plist(...
+    'fs', fs, ...
+    'Iunits', '', ...
+    'Ounits', 'm', ....
+    'MaxIter', 30, ...
+    'PoleType', 2, ...
+    'MinOrder', 3, ...
+    'MaxOrder', 20, ...
+    'Weights', 3, ...
+    'Plot', false,...
+    'Disp', false,...
+    'MSEVARTOL', 1e-3,...
+    'FITTOL', 1e-5);
+
+fil = noisegen1D(mod, pl1);
+
+% 3) generating white noise
+a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 1e5));
+
+% 4) filter white noise
+b = filter(a,fil);
+
+% 4) psd estimation
+bxx = b.psd(plist('navs',8,'olap',50,'order',1));
+% 5)
+iplot(bxx, mod);
+
+%% Noise generation from fsdata model object - output filter 2 %%%%%%%%%%%%%
+
+% Description:
+% 1) Generates a fsdata object to be used as psd model
+% 2) Generates coloring filter with noisegen1D
+% 3) Generates white noise data
+% 4) filter data
+% 4) calculated psd of filtered data
+% 5) check result by plotting
+
+% 1) Generates a fsdata object to be used as psd model
+fs = 10; % sampling frequency
+f = logspace(-6,log10(5),1000);
+pl_mod = plist('fsfcn', '0.01./(0.01+f)', 'f', f);
+mod = ao(pl_mod); % fsdata model object
+
+% 2) noise coloring filter generation
+
+pl1 = plist(...
+    'fs', fs, ...
+    'Iunits', '', ...
+    'Ounits', 'm', ....
+    'MaxIter', 30, ...
+    'PoleType', 2, ...
+    'MinOrder', 3, ...
+    'MaxOrder', 20, ...
+    'Weights', 3, ...
+    'Plot', false,...
+    'Disp', false,...
+    'MSEVARTOL', 1e-3,...
+    'FITTOL', 1e-5);
+
+fil = noisegen1D(mod, mod, pl1);
+
+% 3) generating white noise
+a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 1e5));
+
+% 4) filter white noise
+b = filter(a,fil(1));
+
+% 4) psd estimation
+bxx = b.psd(plist('navs',8,'olap',50,'order',1));
+% 5)
+iplot(bxx, mod);
+
+%% Noise generation from fsdata model object - output filter 3 %%%%%%%%%%%%%
+
+% Description:
+% 1) Generates a fsdata object to be used as psd model
+% 2) Generates coloring filter with noisegen1D
+% 3) Generates white noise data
+% 4) filter data
+% 4) calculated psd of filtered data
+% 5) check result by plotting
+
+% 1) Generates a fsdata object to be used as psd model
+fs = 10; % sampling frequency
+f = logspace(-6,log10(5),1000);
+pl_mod = plist('fsfcn', '0.01./(0.01+f)', 'f', f);
+mod = ao(pl_mod); % fsdata model object
+
+% 2) noise coloring filter generation
+
+pl1 = plist(...
+    'fs', fs, ...
+    'Iunits', '', ...
+    'Ounits', 'm', ....
+    'MaxIter', 30, ...
+    'PoleType', 2, ...
+    'MinOrder', 3, ...
+    'MaxOrder', 20, ...
+    'Weights', 3, ...
+    'Plot', false,...
+    'Disp', false,...
+    'MSEVARTOL', 1e-3,...
+    'FITTOL', 1e-5);
+
+[fil1, fil2] = noisegen1D(mod, mod, pl1);
+
+% 3) generating white noise
+a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 1e5));
+
+% 4) filter white noise
+b = filter(a,fil1);
+
+% 4) psd estimation
+bxx = b.psd(plist('navs',8,'olap',50,'order',1));
+% 5)
+iplot(bxx, mod);
+
+% END
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