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comparison m-toolbox/test/test_ao_linfit.m @ 0:f0afece42f48

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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1 % TEST_AO_LINFIT tests the linfit method of the AO class.
2 %
3 % M Hueller 02-03-10
4 %
5 % $Id: test_ao_linfit.m,v 1.6 2011/05/15 22:52:57 mauro Exp $
6 %
7 % function test_ao_linfit()
8
9
10 %% Make fake AO from polyval
11 nsecs = 100;
12 fs = 10;
13
14 unit_list = unit.supportedUnits;
15 u1 = unit(cell2mat(utils.math.randelement(unit_list,1)));
16 u2 = unit(cell2mat(utils.math.randelement(unit_list,1)));
17
18 pl1 = plist('nsecs', nsecs, 'fs', fs, ...
19 'tsfcn', 'polyval([10 1], t) + randn(size(t))', ...
20 'xunits', 's', 'yunits', u1);
21
22 pl2 = plist('nsecs', nsecs, 'fs', fs, ...
23 'tsfcn', 'polyval([-5 0.2], t) + randn(size(t))', ...
24 'xunits', 's', 'yunits', u2);
25
26 a1 = ao(pl1);
27 a2 = ao(pl2);
28 a = scatterData(a1, a2);
29
30 %% Fit with a straight line
31
32 p11 = linfit(a1, plist(...
33 ));
34 p12 = linfit(a1, plist(...
35 'dy', 0.1));
36 p22 = linfit(a1, plist(...
37 'dx', 0.1, 'dy', 0.1, 'P0', [0 0]));
38 p13 = linfit(a1, plist(...
39 'dy', 0.1*ones(size(a1.y))));
40 p23 = linfit(a1, plist(...
41 'dx', 0.1*ones(size(a1.x)), 'dy', 0.1*ones(size(a1.y)), 'P0', [0 0]));
42 p14 = linfit(a1, plist(...
43 'dy', ao(0.1, plist('yunits', a1.yunits))));
44 p24 = linfit(a1, plist(...
45 'dx', ao(0.1, plist(...
46 'yunits', a1.xunits)), 'dy', ao(0.1, plist('yunits', a1.yunits)), 'P0', [0 0]));
47 p15 = linfit(a1, plist(...
48 'dy', ao(0.1*ones(size(a1.y)), plist('yunits', a1.yunits))));
49 p25 = linfit(a1, plist(...
50 '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]));
51 p26 = linfit(a1, plist(...
52 'dx', 0.1, 'dy', 0.1, 'P0', ao([0 0])));
53 p27 = linfit(a1, plist(...
54 'dx', 0.1, 'dy', 0.1, 'P0', p11));
55
56 %% Compute fit: evaluating pest
57
58 b11 = p11.eval(plist('type', 'tsdata', 'XData', a1, 'xfield', 'x'));
59 b12 = p12.eval(plist('XData', a1, 'xfield', 'x'));
60 b22 = p22.eval(a1, plist('xfield', 'x'));
61 b13 = p13.eval(plist('XData', a1, 'xfield', 'x'));
62 b23 = p23.eval(a1, plist('type', 'tsdata', 'xfield', 'x'));
63 b14 = p14.eval(plist('XData', a1, 'xfield', 'x'));
64 b24 = p24.eval(a1, plist('type', 'tsdata', 'xfield', 'x'));
65 b15 = p15.eval(a1, plist('xfield', 'x'));
66 b25 = p25.eval(plist('XData', a1, 'xfield', 'x'));
67 b26 = p26.eval(plist('type', 'tsdata', 'XData', a1.x));
68 b27 = p27.eval(plist('type', 'tsdata', 'XData', a1.x));
69
70 %% Plot fit
71 iplot(a1, b11, b12, b13, b14, b15, b26, b27, ...
72 b22, b23, b24, b25, ...
73 plist('LineStyles', {'', '--'}));
74
75 %% Remove linear trend
76 c = a1-b11;
77 iplot(c)
78
79 plot(c.hist)
80
81 %% Reproduce from history
82 disp('Try rebuilding')
83 a_out = rebuild(c);
84 iplot(a_out)
85 plot(a_out.hist)
86
87 %% Fit with a straight line
88
89 p = linfit(a, plist(...
90 ));
91
92 %% Compute fit: evaluating pest
93
94 b1 = p.eval(plist('XData', a, 'xfield', 'x'));
95 b2 = p.eval(a, plist('xfield', 'x'));
96 b3 = p.eval(plist('type', 'xydata', 'XData', a.x, 'xunits', a.xunits));
97 b4 = p.eval(plist('XData', a.x, 'xunits', a.xunits));
98
99 %% Plot fit
100 iplot(a, b1, b2, b3, b4, ...
101 plist('LineStyles', {'', '--'}));
102
103 %% Fit with a straight line
104
105 p11 = linfit(a1, a2, plist(...
106 ));
107 p12 = linfit(a1, a2, plist(...
108 'dy', 0.1));
109 p22 = linfit(a1, a2, plist(...
110 'dx', 0.1, 'dy', 0.1, 'P0', [0 0]));
111 p13 = linfit(a1, a2, plist(...
112 'dy', 0.1*ones(size(a1.x))));
113 p23 = linfit(a1, a2, plist(...
114 'dx', 0.1*ones(size(a1.x)), 'dy', 0.1*ones(size(a1.x)), 'P0', [0 0]));
115 p14 = linfit(a1, a2, plist(...
116 'dy', ao(0.1, plist('yunits', a2.yunits))));
117 p24 = linfit(a1, a2, plist(...
118 'dx', ao(0.1, plist('yunits', a1.yunits)), 'dy', ao(0.1, plist('yunits', a2.yunits)), 'P0', [0 0]));
119 p15 = linfit(a1, a2, plist(...
120 'dy', ao(0.1*ones(size(a2.y)), plist('yunits', a2.yunits))));
121 p25 = linfit(a1, a2, plist(...
122 '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]));
123 p26 = linfit(a1, a2, plist(...
124 'dx', 0.1, 'dy', 0.1, 'P0', ao([0 0])));
125 p27 = linfit(a1, a2, plist(...
126 'dx', 0.1, 'dy', 0.1, 'P0', p11));
127
128 %% Compute fit: evaluating pest
129
130 b11 = p11.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
131 b12 = p12.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
132 b22 = p22.eval(a1, plist('type', 'xydata'));
133 b13 = p13.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
134 b23 = p23.eval(a1, plist('type', 'xydata'));
135 b14 = p14.eval(plist('type', 'xydata', 'XData', a1.y, 'xunits', a1.yunits));
136 b24 = p24.eval(a1, plist('type', 'xydata'));
137 b15 = p15.eval(a1, plist('type', 'xydata'));
138 b25 = p25.eval(plist('type', 'xydata', 'XData', a1.y));
139 b26 = p26.eval(plist('type', 'xydata', 'XData', a1.y));
140 b27 = p27.eval(plist('type', 'xydata', 'XData', a1.y));
141
142 % Build reference object
143 a12 = ao(plist('xvals', a1.y, 'yvals', a2.y, ...
144 'xunits', a1.yunits, 'yunits', a2.yunits));
145 %% Plot fit
146 iplot(b22, b23, b24, b15, ...
147 b12, b13, b14, b11, ...
148 plist('LineStyles', {'', '--'}));
149
150 %% Plot fit
151 iplot(b25, b26, b27, ...
152 plist('LineStyles', {'', '--'}));
153
154 %% Remove linear trend
155 c = a12-b27;
156 iplot(c)
157
158 plot(c.hist)
159
160 %% Reproduce from history
161 disp('Try rebuilding')
162 a_out = rebuild(c);
163 iplot(a_out)
164 plot(a_out.hist)
165
166 % end
167 % END