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annotate m-toolbox/test/test_ao_linlsqsvd.m @ 51:9d5c88356247 database-connection-manager

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Make unit tests database connection parameters configurable
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:24:37 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % TEST_AO_LINLSQSVD tests the linlsqsvd method of the AO class.
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 % L Ferraioli 10-11-2010
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4 %
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5 % $Id: test_ao_linlsqsvd.m,v 1.2 2011/02/18 16:15:28 luigi Exp $
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6 %
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7 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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8
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9 %% 1) Determine the coefficients of a linear combination of noises and
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10 %% comapre with lscov:
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11 %
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12 % Make some data
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13 fs = 10;
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14 nsecs = 10;
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15 B1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
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16 B1.setName;
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17 B2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
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18 B2.setName;
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19 B3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
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20 B3.setName;
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21 n = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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22 c = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/T')) ao(3,plist('yunits','m T^-1'))];
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23 y = c(1)*B1 + c(2)*B2 + c(3)*B3 + n;
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24 y.simplifyYunits;
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25 %%% Get a fit with linlsqsvd
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26 pobj1 = linlsqsvd(B1, B2, B3, y);
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27 % do linear combination: using lincom
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28 yfit1 = lincom(B1, B2, B3, pobj1);
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29 yfit1.simplifyYunits;
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30 %%% do fit using lscov
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31 pobj2 = lscov(B1, B2, B3, y);
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32 % do linear combination: using lincom
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33 yfit2 = lincom(B1, B2, B3, pobj2);
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34 yfit2.simplifyYunits;
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35
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36 %%% do linear combination: using eval
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 yfit3 = pobj1.eval(B1, B2, B3);
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38
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39
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40 % Plot (compare data with fit)
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41 iplot(y, yfit1, yfit2, yfit3)
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42
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43 %% 2) Determine the coefficients of a linear combination of noises:
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44 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % Make some data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 fs = 10;
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47 nsecs = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 x1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
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49 x1.setName;
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50 x2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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51 x2.setName;
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52 x3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'C'));
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53 x3.setName;
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54 n = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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55 c = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/m')) ao(3,plist('yunits','m C^-1'))];
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56 y = c(1)*x1 + c(2)*x2 + c(3)*x3 + n;
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57 y.simplifyYunits;
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58
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59 %%% Get a fit for c
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60 pobj = linlsqsvd(x1, x2, x3, y);
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61 % do linear combination: using lincom
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62 yfit1 = lincom(x1, x2, x3, pobj);
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63
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64 %%% do linear combination: using eval
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65 pl_split = plist('times', [1 5]);
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66 yfit2 = pobj.eval(plist('Xdata', {split(x1, pl_split), split(x2, pl_split), split(x3, pl_split)}));
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67
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68 % Plot (compare data with fit)
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69 iplot(y, yfit1, yfit2, plist('Linestyles', {'-','--'}))
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