Mercurial > hg > ltpda
diff m-toolbox/test/test_ao_padded_sine_model.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_padded_sine_model.m Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,61 @@ +clear all; + +%% +fs = 100; +nsecs = 20; +t = [0:1/fs:nsecs-1/fs]; + +a = ao(plist('built-in', 'padded_sine', ... + 'f0', .1, ... + 'Timebase', t, ... + 'Tstart', 1.1, ... + 'Ncycles', 2.1, ... + 'phi', 90)) + +n = ao(plist('tsfcn', '0.1*randn(size(t))', 'fs', fs, 'nsecs', nsecs)); + +sw = a+n; + +sw.iplot + +%% Now try to fit this + +% [dc,A,f0,phi,Tstart,N] +af = ao(plist('built-in', 'padded_sine', ... + 'Timebase', sw, ... + 'f0', .1, ... + 'P', [0 1 .11 90 1 2])); + +iplot(sw, af) + +%% Now fit with simplex + +opts = optimset('Display', 'iter', ... + 'MaxFunEvals', 10000, ... + 'MaxIter', 10000, ... + 'TolX', 1e-15, ... + 'TolFun', 1e-15, ... + 'LargeScale', 'on'); + +r0 = [0 1 .11 90 1 2]; + +mksine = @(r)(ao(plist('built-in', 'padded_sine', ... + 'Timebase', sw, ... + 'P', r)).y); + +f = @(r)(sum((mksine(r)-sw.y).^2)); + +% Do a few iterative fits +% for kk=1:5 + x0 = fminsearch(f, r0, opts); +% end + + +%% + +afit = ao(plist('built-in', 'padded_sine', 'Timebase', sw, 'P', x0)); + +iplot(sw, afit) + + +