Mercurial > hg > ltpda

annotate m-toolbox/classes/@ao/spsdSubtraction.m @ 39:11e3ed9d2115 database-connection-manager

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Implement databases listing in database connection dialog
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % SPSDSUBTRACTION makes a sPSD-weighted least-square iterative fit
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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: SPSDSUBTRACTION makes a sPSD-weighted least-square iterative fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % CALL: [MPest, plOut, aoResiduum, aoP, aoPini] = spsdSubtraction(ao_Y, [ao_U1, ao_U2, ao_U3 ...]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % [MPest, plOut, aoResiduum, aoP, aoPini] = spsdSubtraction(ao_Y, [ao_U1, ao_U2, ao_U3 ...], pl);
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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 % The function finds the optimal M that minimizes the sum of the weighted sPSD of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % (ao_Y - M * [ao_U1 ao_U2 ao_U3 ...] )
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % if ao_Y is a vector of aos, the use the matrix/spsdSubtraction is
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % advised
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % OUTPUTS: - MPest: output PEST object with parameter estimates
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % - aoResiduum: residuum times series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % - plOut: plist containing data like the parameter estimates
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % - aoP: last weight used in the optimization (fater last
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % Maximization/Expectation step)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % - aoPini: initial weight used in the optimization (before first
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % Maximization/Expectation step)
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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 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'spsdSubtraction')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % VERSION : $Id: spsdSubtraction.m,v 1.6 2011/08/03 19:21:10 adrien Exp $
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 function varargout = spsdSubtraction(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % use the caller is method flag
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 callerIsMethod = utils.helper.callerIsMethod;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 end
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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 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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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 if ~nargin>1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 error('optSubtraction requires at least the two input aos as first and second entries')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 end
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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 %% retrieving the two input aos
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 [aos_in, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 aosY = varargin{1};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 aosU = varargin{2};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 if (~isa(aosY, 'ao')) || (~isa(aosU, 'ao'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 error('first two inputs should be two ao-arrays involved in the subtraction')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 end
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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 plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 pl = utils.helper.collect_objects(varargin(:), 'plist');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 % Get default parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 pl = combine(pl, getDefaultPlist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 %% checking data sizes
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 NY = numel(aosY);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 if NY==0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 error('Nothing to subtract to!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 NU = size(aosU,2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 if NU==0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 error('Nothing to subtract!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 if ~(size(aosY,2)==1)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 error('The input ao Y array should be a column vector')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 if ~(size(aosU,1)==NY)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 error('The fields ''subtracted'' should be an array of aos with the height of numel(initial)')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 end
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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 %% collecting history
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 if callerIsMethod
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 % we don't need the history of the input
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 inhist = [aosY(:).hist aosU(:).hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 %% retrieving general quantities
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 ndata = numel(aosY(1).y);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 Ts = 1/aosY(1).fs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 nFreqs = floor(ndata/2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 freqs = 1/(2*Ts) * linspace(0,1,nFreqs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 %% produce window
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 Win = find(pl, 'Win');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 if isa(Win, 'plist')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 Win = ao( combine(plist( 'length', ndata), Win) );
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 W = Win.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 elseif isa(Win, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 if ~isa(Win.data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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97 error('An ao window should be a time series')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 W = Win.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 if ~length(W)==ndata
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 error('signals and windows don''t have the same length')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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102 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 error('input option Win is not acceptable (not a plist nor an ao)!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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107 %% get initial M coefficient matrix
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 M = pl.find('coefs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 if isempty(M)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 M = zeros(1,NU);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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113 %% get criterion thinness
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 linCoef = pl.find('lincoef');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 logCoef = pl.find('logcoef');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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117 %% getting the input data Y and taking FFT
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 Y = zeros(NY, nFreqs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 YLocNorm = zeros(NY,1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 for ii=1:NY
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122 if isempty(aosY(ii).data)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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123 error('One ao for Y is empty!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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124 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125 if ~(length(aosY(ii).y)==ndata)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126 error('various Y vectors do not have the same length')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 yLoc = fft(aosY(ii).y .* W, ndata);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 YLocNorm(ii) = norm(aosY(ii).y .* W)/sqrt(ndata);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 Y(ii,:) = yLoc(1:nFreqs)/YLocNorm(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 %% getting the data U norm
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 ULocNorm = zeros(NY,NU);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 for iU=1:NU
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 for iY=1:NY
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 if ~isempty(aosU(iY,iU).data)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 ULocNorm(iY,iU,:) = norm(aosU(iY,iU).y .* W)/sqrt(ndata);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 ULocNorm = max(ULocNorm,[],1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 %% getting the input data U and taking FFT
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 U = zeros(NY,NU, nFreqs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 for iY=1:NY
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 for iU=1:NU
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 if ~isempty(aosU(iY,iU).data)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 if ~(length(aosU(iY,iU).y)==ndata)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 error('various U vectors do not have the same length as Y')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 uLoc = fft(aosU(iY,iU).y .* W, ndata);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 U(iY,iU,:) = uLoc(1:nFreqs)/ (YLocNorm(iY) * ULocNorm(iU));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 %% getting the weight powAvgWeight
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 weightingMethod =pl.find('weightingMethod');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
160 switch lower(weightingMethod)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
161 case 'pzmodel'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
162 weightModel =pl.find('pzmodelWeight');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163 if numel(weightModel)~=NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 error('there should be as many pzmodels as weighted entries')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 for ii=1:NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 weight = weightModel(ii).resp(freqs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 weight = abs(weight).^2;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 pow = [0 ; weight.y(2:nFreqs)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 [freqsAvg, powAvgs, nFreqsAvg, nDofs, binningMatrix] = ltpda_spsd(freqs, pow, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 powAvgWeight(ii,:) = powAvgs; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 case 'ao'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 weight = pl.find('aoWeight');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 if numel(weight)~=NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 error('there should be as many AOs as weighted entries')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 for ii=1:NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 if ~isa(weight(ii).data, 'fsdata')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180 error('if weight is an ao, it should be a FSdata')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181 elseif length(weight(ii).y)~=nFreqs
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 error(['length of FS weight is not length of the FFT vector : ' num2str(length(weight(ii).y)) ' instead of ' num2str(nFreqs)])
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 pow = weight(ii).y;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 [freqsAvg, powAvgs, nFreqsAvg, nDofs, binningMatrix] = ltpda_spsd(freqs, pow, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 powAvgWeight(ii,:) = powAvgs; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 %% add unit check here!!
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 case 'residual'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 [freqsAvg, powAvgWeight, nFreqsAvg, nDofs, binningMatrix] = computeWeight(Y, M, U, freqs, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 otherwise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 error('weighting method requested does not exist!')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 powAvgInv = (powAvgWeight.*(nFreqsAvg.')./(nDofs.')).^-1;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 %% get ME iterations termination conditions
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 iterMax = pl.find('iterMax');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 normCoefs = pl.find('normCoefs');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 normCriterion = pl.find('normCriterion');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 %% Maximization Expectation iterations loop
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 for i_iter = 1:iterMax
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 utils.helper.msg(utils.const.msg.PROC3, ['starting iteration ', num2str(i_iter)]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 %% initializing history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 if i_iter==1 % storing intial weight
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 Pini = powAvgWeight;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 MHist(1,:) = reshape(M, [1, numel(M)] );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 fValIni = optimalCriterion(Y, M, U, powAvgInv, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 %% solving LSQ problem
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 [M, hessian] = solveProblem(M, Y, U, powAvgInv, nFreqsAvg, binningMatrix);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 fval = optimalCriterion(Y, M, U, powAvgInv, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 %% store history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 fValHist(i_iter) = fval/fValIni; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 MHist(i_iter+1,:) = reshape(M, [1, numel(M)] ); %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 %% updating weight, recomputing residuum power
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 [freqsAvg, powAvgWeight, nFreqsAvg, nDofs] = computeWeight(Y, M, U, freqs, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 powAvgInv = (powAvgWeight.*(nFreqsAvg.')./(nDofs.')).^-1;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 %% deciding whether to pursue or not ME iterations
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 if strcmpi( weightingMethod, 'pzmodel')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 display('One iteration for Pzmodel weighting only')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 break
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 elseif strcmpi( weightingMethod, 'ao')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 display('One iteration for ao weighting only')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 break
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 elseif norm(fValHist(i_iter)-1) < normCriterion && norm(MHist(i_iter+1,:)-MHist(i_iter,:))<normCoefs
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 display(['Iterations stopped at iteration ' num2str(i_iter) ' because not enough progress was made (see parameter "normCriterion" and "normCoefs")'])
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 break
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 elseif i_iter == iterMax
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 display(['Iterations stopped at maximum number of iterations ' num2str(i_iter) ' (see parameter "iterMax")'])
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 break
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241 %% creating output pest
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 MVals = M * diag( ULocNorm.^-1 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 MStd = diag(diag(ULocNorm) * hessian * diag(ULocNorm)).^-0.5;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 MCov = diag(ULocNorm)^-1 * hessian^-1 * diag(ULocNorm)^-1;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 % prepare model, units, names
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 model = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 for jj = 1:NU
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 names{jj} = ['U' num2str(jj)]; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 units{jj} = aosY(1).yunits / aosU(1,jj).yunits; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 xunits{jj} = aosU(1,jj).yunits; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 MNames{jj} = ['M' num2str(jj)]; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 if jj == 1
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 model = ['M' num2str(jj) '*U' num2str(jj)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 model = [model ' + M' num2str(jj) '*U' num2str(jj)]; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 model = smodel(plist('expression', model, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 'params', MNames, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262 'values', MVals.', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 'xvar', names, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 'xunits', xunits, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 'yunits', aosY(1).yunits ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266 ));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 % collect inputs names
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 argsname = aosY(1).name;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270 for jj = 1:numel(NU)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271 argsname = [argsname ',' aosU(jj).name];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274 % Build the output pest object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275 MPest = pest;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
276 MPest.setY( MVals.' );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
277 MPest.setDy(MStd);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
278 MPest.setCov(MCov);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
279 MPest.setChi2(0);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
280 MPest.setNames(names{:});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
281 MPest.setYunits(units{:});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
282 MPest.setModels(model);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
283 MPest.name = sprintf('optSubtraction(%s)', argsname);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
284
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
285 % Set procinfo object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
286 MPest.procinfo = plist('MPsdE', 0);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
287 % Propagate 'plotinfo'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
288 plotinfo = [aosY(:).plotinfo aosU(:).plotinfo];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
289 if ~isempty(plotinfo)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
290 MPest.plotinfo = combine(plotinfo);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
291 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
292
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
293 %% creating output plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
294 plOut = plist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
295
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
296 p = param({ 'criterion' , 'last value of the criterion in the last optimization'}, fval );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
297 plOut.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
298 p = param({ 'M' , 'Best fitting value'}, MVals );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
299 plOut.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
300 p = param({ 'Mhist' , 'History of the best fit, through iteration'}, MHist * diag( ULocNorm.^-1 ) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
301 plOut.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
302 p = param({ 'fValHist' , 'History of the criterion value, through iteration'}, fValHist );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
303 plOut.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
304 p = param({ 'hessian' , 'fitting hessian'}, diag(ULocNorm) * hessian * diag(ULocNorm) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
305 plOut.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
306 %add history and use Mdata/Pest instead
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
307
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
308 %% creating aos for the weights used
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
309 if nargout>2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
310 aoP = ao.initObjectWithSize(NY, 1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
311 aoPini = ao.initObjectWithSize(NY, 1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
312 for ii=1:NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
313 aoP(ii).setData(fsdata( freqsAvg, YLocNorm(ii)^2 * powAvgWeight(ii,:) ));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
314 aoP(ii).setName('final weight');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
315 aoP(ii).setXunits('Hz');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
316 aoP(ii).setYunits(aosY(ii).yunits^2 * unit('Hz^-1'));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
317 aoP(ii).setDescription(['final weight in the channel "' aosY(ii).name '"']);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
318 aoP(ii).setT0(aosY(ii).t0);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
319 aoPini(ii).setData(fsdata( freqsAvg, YLocNorm(ii)^2 * Pini(ii,:) ));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
320 aoPini(ii).setName('initial weight');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
321 aoPini(ii).setXunits('Hz');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
322 aoPini(ii).setYunits(aosY(ii).yunits^2 * unit('Hz^-1'));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
323 aoPini(ii).setDescription(['initial weight in the channel "' aosY(ii).name '"']);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
324 aoPini(ii).setT0(aosY(ii).t0);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
325 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
326 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
327
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
328 %% creating residuum time-series
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
329 if nargout>2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
330 aoResiduum = ao.initObjectWithSize(NY,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
331 for ii=1:NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
332 aoResiduumValue = aosY(ii).y;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
333 for jj = 1:NU
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
334 aoResiduumValue = aoResiduumValue - MVals(jj)*aosU(ii,jj).y;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
335 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
336 aoResiduum(ii).setData(tsdata( aoResiduumValue, aosY(ii).fs ));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
337 aoResiduum(ii).setName(['residual in the channel "' aosY(ii).name '"' ]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
338 aoResiduum(ii).setXunits('s');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
339 aoResiduum(ii).setYunits(aosY(ii).yunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
340 aoResiduum(ii).setDescription(['residual corresponding to "' aosY(ii).description '"' ]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
341 aoResiduum(ii).setT0(aosY(ii).t0);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
342 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
343 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
344
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
345 %% adding history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
346 if callerIsMethod
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
347 % we don't need to set the history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
348 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
349 MPest.addHistory(getInfo('None'), pl, ao_invars, inhist);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
350 if nargout>2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
351 for ii=1:NY
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
352 aoP(ii).addHistory(getInfo('None'), pl, ao_invars, inhist);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
353 aoPini(ii).addHistory(getInfo('None'), pl, ao_invars, inhist);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
354 aoResiduum(ii).addHistory(getInfo('None'), pl, ao_invars, inhist);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
355 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
356 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
357 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
358
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
359 %% return coefficients and hessian and Jfinal and powAvgWeight
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
360 if nargout>2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
361 varargout = {MPest, plOut, aoResiduum, aoP, aoPini};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
362 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
363 varargout = {MPest, plOut};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
364 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
365 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
366
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
367 %% weight for optimal criterion
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
368 function [freqsAvg, powAvgWeight, nFreqsAvg, nDofs, binningMatrix] = computeWeight(Y, M, U, freqs, linCoef, logCoef)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
369 errDft = subtraction( Y, M, U);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
370 errPow = real(errDft).^2 + imag(errDft).^2;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
371 for ii=1:size(errDft,1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
372 [freqsAvg, powAvgs, nFreqsAvg, nDofs, binningMatrix] = ltpda_spsd(freqs, errPow, linCoef, logCoef);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
373 powAvgWeight(ii,:) = powAvgs; %#ok<AGROW>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
374 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
375 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
376
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
377 %% optimal criterion
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
378 function j = optimalCriterion(Y, M, U, powAvgInv, linCoef, logCoef)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
379 errDft = subtraction(Y, M, U);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
380 errPow = real(errDft).^2 + imag(errDft).^2;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
381 j = 0;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
382 for ii=1:size(errDft,1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
383 [freqsAvg, powAvgs, nFreqsAvg, nDofs] = ltpda_spsd([], errPow, linCoef, logCoef); %#ok<ASGLU>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
384 powSum = powAvgs .* nDofs; % binning frequencies as in sPSD
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
385 j = j + sum( powSum .* powAvgInv(:,ii) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
386 % alpha = 4;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
387 % logProbaDensityFactor = - nFreqsAvg * log(2) - gammaln(nFreqsAvg);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
388 % normlzChi2Sum = ((alpha*2)*powSum) .* powAvgInv(:,ii); % divide the sum by the expected average of each terms, so the chi2 is normalized
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
389 % logProbaDensities = logProbaDensityFactor + (nFreqsAvg-1).*log(normlzChi2Sum) - normlzChi2Sum/2 ; % here computing log of probability
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
390 % j = j - sum(logProbaDensities); % better than taking product of probabilities
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
391 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
392 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
393
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
394 %% time-series subtraction function
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
395 function Y = subtraction( Y, M, U)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
396 ndata = size(Y,2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
397 for ii=1:size(Y,1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
398 for j=1:numel(M)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
399 Y(ii,:) = Y(ii,:) - reshape( M(j)*U(ii,j,:) , [1,ndata] );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
400 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
401 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
402 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
403
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
404 %% Direct solver
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
405 function [M, hessian] = solveProblem(M, Y, U, powAvgInv, nFreqsAvg, binningMatrix)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
406 errDft = subtraction(Y, M, U);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
407 NU = size(U,2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
408 NFreqs = size(binningMatrix,2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
409 ATB = zeros(NU,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
410 ATA = zeros(NU,NU);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
411 % matrix for frequency binning & Weighting & Summing :
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
412 matBSW = powAvgInv * binningMatrix;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
413 for iiParam = 1:NU
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
414 Uii = reshape(U(1,iiParam,:), [1 NFreqs]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
415 ATB(iiParam) = 2 * ( matBSW * real( Uii .* conj(errDft) ).' );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
416 for jjParam = 1:NU
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
417 Ujj = reshape(U(1,jjParam,:), [1 NFreqs]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
418 ATA(iiParam,jjParam) = 2 * ( matBSW * real( Uii .* conj(Ujj) ).' );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
419 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
420 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
421 try
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
422 MUpdate = ATA^-1 * ATB;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
423 M = M + MUpdate.';
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
424 catch
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
425 warning('Numerical accuracy limited the number of iterations')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
426 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
427 hessian = ATA;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
428 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
429
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
430
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
431 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
432 % Get Info Object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
433 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
434 function ii = getInfo(varargin)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
435 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
436 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
437 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
438 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
439 sets = {'Default'};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
440 pl = getDefaultPlist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
441 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
442 % Build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
443 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.op, '$Id: spsdSubtraction.m,v 1.6 2011/08/03 19:21:10 adrien Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
444 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
445
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
446 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
447 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
448 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
449 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
450 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
451 if exist('pl', 'var')==0 || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
452 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
453 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
454 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
455 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
456
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
457 function pl = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
458 pl = plist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
459
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
460 % initial coefficients for subtraction initialization
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
461 p = param({ 'coefs' , 'initial subtracted coefficients, must be a nY*nU double array. If not provided zeros are assumed'}, [] );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
462 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
463
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
464 % weighting scheme
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
465 p = param({ 'weightingMethod' , 'choose to define a frequency weighting scheme'}, {1, {'residual', 'ao', 'pzmodel'}, paramValue.SINGLE} );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
466 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
467
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
468 p = param({ 'aoWeight' , 'ao to define a frequency weighting scheme (if chosen in ''weightingMethod'')'}, ao.initObjectWithSize(0,0) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
469 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
470
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
471 p = param({ 'pzmodelWeight' , 'pzmodel to define a frequency weighting scheme (if chosen in ''weightingMethod'')'}, pzmodel.initObjectWithSize(0,0) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
472 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
473
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
474 p = param({ 'lincoef' , 'linear coefficient for scaling frequencies in chi2'}, 5 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
475 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
476
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
477 p = param({ 'logcoef' , 'logarithmic coefficient for scaling frequencies in chi2'}, 0.3 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
478 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
479
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
480 % iterations convergence stop criterion
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
481 p = param({ 'iterMax' , 'max number of Mex/Exp iterations'}, 20 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
482 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
483
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
484 p = param({ 'normCoefs' , 'tolerance on inf norm of coefficient update (used depending on ''CVCriterion'')'}, 1e-15 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
485 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
486
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
487 p = param({ 'normCriterion' , 'tolerance on norm of criterion variation (used depending on ''CVCriterion'')'}, 1e-15 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
488 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
489
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
490 % windowing options
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
491 p = param({ 'win' , 'window to operate FFT, may be a plist/ao'}, plist('win', 'levelledHanning', 'PSLL', 200, 'levelOrder', 4 ) );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
492 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
493
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
494 % display
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
495 p = param({ 'display' , 'choose how much to display of the optimizer output'}, {1, {'off', 'iter', 'final'}, paramValue.SINGLE} );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
496 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
497
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
498 % optimizer options
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
499 p = param({ 'maxcall' , 'maximum number of calls to the criterion function'}, 5000 );
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
500 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
501
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
502 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
503
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
504