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annotate m-toolbox/classes/@matrix/linlsqsvd.m @ 12:86aabb42dd84 database-connection-manager

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Use utils.repository utilities
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % LINLSQSVD Linear least squares with singular value decomposition
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: Linear least square problem with singular value
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % decomposition
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % ALGORITHM: % It solves the problem
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % Y = HX
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % where X are the parameters, Y the measurements, and H the linear
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % equations relating the two.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % It is able to perform linear identification of the parameters of a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % multichannel systems. The results of different experiments on the same
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % system can be passed as input. The algorithm, thanks to the singular
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % value decomposition, extract the maximum amount of information from each
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % single channel and for each experiment. Total information is then
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % combined to get the final result.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % CALL: pars = linfitsvd(H1,...,HN,Y,pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % If the experiment is 1 then H1,...,HN and Y are aos.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % If the experiments are M, then H1,...,HN and Y are Mx1 matrix objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % with the aos relating to the given experiment in the proper position.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % INPUT:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 % - Hi represent the columns of H
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % - Y represent the measurement set
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % OUTPUT:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % - pars: a pest object containing parameter estimation
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % 09-11-2010 L Ferraioli
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % CREATION
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 % <a href="matlab:utils.helper.displayMethodInfo('matrix', 'linfitsvd')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % VERSION: $Id: linlsqsvd.m,v 1.9 2011/05/02 14:18:19 luigi Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 function varargout = linlsqsvd(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 %%% LTPDA stufs and get data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 utils.helper.msg(msg.OMNAME, 'running %s/%s', mfilename('class'), mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 % Collect all ltpdauoh objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 [mtxs, mtxs_invars] = utils.helper.collect_objects(varargin(:), 'matrix', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 [pl, invars] = utils.helper.collect_objects(varargin(:), 'plist');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 inhists = [mtxs(:).hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 %%% combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 pl = parse(pl, getDefaultPlist());
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 %%% collect inputs names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 argsname = mtxs(end).name;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 %%% get input params
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 kwnpars = find(pl,'KnownParams');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 sThreshold = find(pl,'sThreshold');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 %%% do fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 % if ~isempty(kwnpars) && isfield(kwnpars,'pos')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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80 % [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs,kwnpars);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 % else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 % [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 % end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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85 if ~isempty(kwnpars) && isfield(kwnpars,'pos')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 if ~isempty(sThreshold)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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87 [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs,sThreshold,kwnpars);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs,kwnpars);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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91 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 if ~isempty(sThreshold)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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93 [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs,sThreshold);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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95 [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = utils.math.linlsqsvd(mtxs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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96 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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97 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 fitparams = cell(1,numel(a));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 nmstr = '';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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101 for kk=1:numel(a)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 fitparams{kk} = sprintf('a%s',num2str(kk));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 units{kk} = mtxs(end).objs(1).yunits / mtxs(kk).objs(1).yunits;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 units{kk}.simplify;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105 if isempty(nmstr)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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106 nmstr = sprintf('%s*%s',fitparams{kk},mtxs(kk).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108 nmstr = [nmstr '+' sprintf('%s*%s',fitparams{kk},mtxs(kk).name)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 pe = pest();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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113 pe.setY(a);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 pe.setDy(sqrt(diag(Ca)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 pe.setCov(Ca);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 pe.setChi2(mse);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 pe.setNames(fitparams);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 pe.setDof(dof);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 pe.setYunits(units{:});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 pe.name = nmstr;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 pe.setModels(mtxs(1:end-1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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123 % set History
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 pe.addHistory(getInfo('None'), pl, [mtxs_invars(:)], [inhists(:)]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127 if nargout == 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 varargout{1} = pe;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 elseif nargout == 11
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 varargout{1} = pe;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 varargout{2} = a;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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132 varargout{3} = Ca;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 varargout{4} = Corra;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 varargout{5} = Vu;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 varargout{6} = bu;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 varargout{7} = Cbu;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 varargout{8} = Fbu;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 varargout{9} = mse;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 varargout{10} = dof;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 varargout{11} = ppm;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 error('invalid number of outputs!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 pl = getDefaultPlist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: linlsqsvd.m,v 1.9 2011/05/02 14:18:19 luigi Exp $', sets, pl);
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161 ii.setArgsmin(2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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162 ii.setOutmin(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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163 % ii.setOutmax(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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164 ii.setModifier(false);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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165 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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166
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Daniele Nicolodi <nicolodi@science.unitn.it>
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167 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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168 % Get Default Plist
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169 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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170 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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171 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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172 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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173 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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174 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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175 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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176 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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177
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Daniele Nicolodi <nicolodi@science.unitn.it>
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178 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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179
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Daniele Nicolodi <nicolodi@science.unitn.it>
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180 pl = plist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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181
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Daniele Nicolodi <nicolodi@science.unitn.it>
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182 p = param({'KnownParams', ['Known Parameters. A struct array with the fields:<ul>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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183 '<li> pos - a number indicating the corresponding position of the parameter (corresponding column of H)</li>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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184 '<li> value - the value for the parameter</li>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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185 '<li> err - the uncertainty associated to the parameter</li>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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186 '</ul>']}, paramValue.EMPTY_CELL);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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187 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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188
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Daniele Nicolodi <nicolodi@science.unitn.it>
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189 p = param({'sThreshold',['Fix upper treshold for singular values.'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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190 'Singular values larger than the value will be ignored.'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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191 'This correspon to consider only parameters combinations with error lower then the value']},...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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192 paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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193 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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194
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Daniele Nicolodi <nicolodi@science.unitn.it>
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195
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Daniele Nicolodi <nicolodi@science.unitn.it>
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196 end