+
−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)
+
−
+
−
+
−