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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
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% TEST_AO_LINFIT tests the linfit method of the AO class.
%
% M Hueller 02-03-10
%
% $Id: test_ao_linfit.m,v 1.6 2011/05/15 22:52:57 mauro Exp $
%
% function test_ao_linfit()


%% Make fake AO from polyval
nsecs = 100;
fs    = 10;

unit_list = unit.supportedUnits;
u1 = unit(cell2mat(utils.math.randelement(unit_list,1)));
u2 = unit(cell2mat(utils.math.randelement(unit_list,1)));

pl1 = plist('nsecs', nsecs, 'fs', fs, ...
  'tsfcn', 'polyval([10 1], t) + randn(size(t))', ...
  'xunits', 's', 'yunits', u1);

pl2 = plist('nsecs', nsecs, 'fs', fs, ...
  'tsfcn', 'polyval([-5 0.2], t) + randn(size(t))', ...
  'xunits', 's', 'yunits', u2);

a1 = ao(pl1);
a2 = ao(pl2);
a = scatterData(a1, a2);

%% Fit with a straight line

p11 = linfit(a1, plist(...
  ));
p12 = linfit(a1, plist(...
  'dy', 0.1));
p22 = linfit(a1, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', [0 0]));
p13 = linfit(a1, plist(...
  'dy', 0.1*ones(size(a1.y))));
p23 = linfit(a1, plist(...
  'dx', 0.1*ones(size(a1.x)), 'dy', 0.1*ones(size(a1.y)), 'P0', [0 0]));
p14 = linfit(a1, plist(...
  'dy', ao(0.1, plist('yunits', a1.yunits))));
p24 = linfit(a1, plist(...
  'dx', ao(0.1, plist(...
  'yunits', a1.xunits)), 'dy', ao(0.1, plist('yunits', a1.yunits)), 'P0', [0 0]));
p15 = linfit(a1, plist(...
  'dy', ao(0.1*ones(size(a1.y)), plist('yunits', a1.yunits))));
p25 = linfit(a1, plist(...
  'dx', ao(0.1*ones(size(a1.x)), plist('yunits', a1.xunits)), 'dy', ao(0.1*ones(size(a1.y)), plist('yunits', a1.yunits)), 'P0', [0 0]));
p26 = linfit(a1, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', ao([0 0])));
p27 = linfit(a1, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', p11));

%% Compute fit: evaluating pest

b11 = p11.eval(plist('type', 'tsdata', 'XData', a1, 'xfield', 'x'));
b12 = p12.eval(plist('XData', a1, 'xfield', 'x'));
b22 = p22.eval(a1, plist('xfield', 'x'));
b13 = p13.eval(plist('XData', a1, 'xfield', 'x'));
b23 = p23.eval(a1, plist('type', 'tsdata', 'xfield', 'x'));
b14 = p14.eval(plist('XData', a1, 'xfield', 'x'));
b24 = p24.eval(a1, plist('type', 'tsdata', 'xfield', 'x'));
b15 = p15.eval(a1, plist('xfield', 'x'));
b25 = p25.eval(plist('XData', a1, 'xfield', 'x'));
b26 = p26.eval(plist('type', 'tsdata', 'XData', a1.x));
b27 = p27.eval(plist('type', 'tsdata', 'XData', a1.x));

%% Plot fit
iplot(a1, b11, b12, b13, b14, b15, b26, b27, ...
  b22, b23, b24, b25, ...
  plist('LineStyles', {'', '--'}));

%% Remove linear trend
c = a1-b11;
iplot(c)

plot(c.hist)

%% Reproduce from history
disp('Try rebuilding')
a_out = rebuild(c);
iplot(a_out)
plot(a_out.hist)

%% Fit with a straight line

p = linfit(a, plist(...
  ));

%% Compute fit: evaluating pest

b1 = p.eval(plist('XData', a, 'xfield', 'x'));
b2 = p.eval(a, plist('xfield', 'x'));
b3 = p.eval(plist('type', 'xydata', 'XData', a.x, 'xunits', a.xunits));
b4 = p.eval(plist('XData', a.x, 'xunits', a.xunits));

%% Plot fit
iplot(a, b1, b2, b3, b4,  ...
  plist('LineStyles', {'', '--'}));

%% Fit with a straight line

p11 = linfit(a1, a2, plist(...
  ));
p12 = linfit(a1, a2, plist(...
  'dy', 0.1));
p22 = linfit(a1, a2, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', [0 0]));
p13 = linfit(a1, a2, plist(...
  'dy', 0.1*ones(size(a1.x))));
p23 = linfit(a1, a2, plist(...
  'dx', 0.1*ones(size(a1.x)), 'dy', 0.1*ones(size(a1.x)), 'P0', [0 0]));
p14 = linfit(a1, a2, plist(...
  'dy', ao(0.1, plist('yunits', a2.yunits))));
p24 = linfit(a1, a2, plist(...
  'dx', ao(0.1, plist('yunits', a1.yunits)), 'dy', ao(0.1, plist('yunits', a2.yunits)), 'P0', [0 0]));
p15 = linfit(a1, a2, plist(...
  'dy', ao(0.1*ones(size(a2.y)), plist('yunits', a2.yunits))));
p25 = linfit(a1, a2, plist(...
  'dx', ao(0.1*ones(size(a1.y)), plist('yunits', a1.yunits)), 'dy', ao(0.1*ones(size(a2.y)), plist('yunits', a2.yunits)), 'P0', [0 0]));
p26 = linfit(a1, a2, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', ao([0 0])));
p27 = linfit(a1, a2, plist(...
  'dx', 0.1, 'dy', 0.1, 'P0', p11));

%% Compute fit: evaluating pest

b11 = p11.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
b12 = p12.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
b22 = p22.eval(a1, plist('type', 'xydata'));
b13 = p13.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
b23 = p23.eval(a1, plist('type', 'xydata'));
b14 = p14.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
b24 = p24.eval(a1, plist('type', 'xydata'));
b15 = p15.eval(a1, plist('type', 'xydata'));
b25 = p25.eval(plist('type', 'xydata', 'XData', a1.y));
b26 = p26.eval(plist('type', 'xydata', 'XData', a1.y));
b27 = p27.eval(plist('type', 'xydata', 'XData', a1.y));

% Build reference object
a12 = ao(plist('xvals', a1.y, 'yvals', a2.y, ...
  'xunits', a1.yunits, 'yunits', a2.yunits));
%% Plot fit
iplot(b22, b23, b24, b15, ...
  b12, b13, b14, b11, ...
  plist('LineStyles', {'', '--'}));

%% Plot fit
iplot(b25, b26, b27, ...
  plist('LineStyles', {'', '--'}));

%% Remove linear trend
c = a12-b27;
iplot(c)

plot(c.hist)

%% Reproduce from history
disp('Try rebuilding')
a_out = rebuild(c);
iplot(a_out)
plot(a_out.hist)

% end
% END