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annotate m-toolbox/classes/+utils/@math/xCovmat.m @ 50:7d2e2e065cf1 database-connection-manager

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Update unit tests
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:24:37 +0100
parents f0afece42f48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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 % Compute cross covariance matrix of two data series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % CALL
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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 % Get autocovariance
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % cmat = xCovmat(x)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % cmat = xCovmat(x,[])
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % cmat = xCovmat(x,[],'cutbefore',10,'cutafter',10)
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11 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % Get crosscovariance
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % cmat = xCovmat(x,y)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % cmat = xCovmat(x,y,'cutbefore',10,'cutafter',10)
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % INPUT
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17 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % - x, y, data series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % - cutbefore, followed by the data samples to cut at the starting of the
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20 % data series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % - cutafter, followed by the data samples to cut at the ending of the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % data series
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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 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % L Ferraioli 10-10-2010
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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 % $Id: xCovmat.m,v 1.1 2010/11/16 16:41:37 luigi Exp $
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28 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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30
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 function cmat = xCovmat(x,y,varargin)
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32
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 acov = true;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % willing to work with columns
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 if size(x,1)<size(x,2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 x = x.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % subtract the mean
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 x = x - mean(x);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 if nargin > 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 if ~isempty(y) % crosscovariance
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 acov = false;
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43 if size(y,1)<size(y,2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 y = y.';
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45 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 y = y - mean(y);
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47 end
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48 end
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 nx = size(x,1);
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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 cutbefore = [];
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53 cutafter = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 if ~isempty(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 for j=1:length(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 if strcmp(varargin{j},'cutbefore')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 cutbefore = varargin{j+1};
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58 end
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59 if strcmp(varargin{j},'cutafter')
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60 cutafter = varargin{j+1};
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61 end
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62 end
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63 end
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64
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 if acov % autocovariance
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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 % init trim matrix
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 trim = zeros(nx,nx);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 % fillin the trim matrix
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 for ii=1:nx
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 trim(1:nx-ii+1,ii) = x(ii:nx,1);
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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 %trim = sparse(trim);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 cmat = trim*conj(trim);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 % normalization
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 %nmat = sparse(triu(ones(nx,nx),0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 nmat = triu(ones(nx,nx),0);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 nmat = rot90(nmat);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 normat = nmat*nmat;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 cmat = cmat./normat;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 %cmat = full(cmat);
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82
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 if ~isempty(cutbefore)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 % cut rows
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 cmat(1:cutbefore,:)=[];
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86 % cut columns
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 cmat(:,1:cutbefore)=[];
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88 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 [nn,mm]=size(cmat);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 if ~isempty(cutafter)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 % cut rows
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 cmat(nn-cutafter:nn,:)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 % cut columns
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 cmat(:,mm-cutafter:mm)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 else % cross covariance
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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 % init trim matrix
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 trimx = zeros(nx,nx);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 trimy = zeros(nx,nx);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 % fillin the trim matrix
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 for ii=1:nx
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 trimx(1:nx-ii+1,ii) = x(ii:nx,1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 trimy(1:nx-ii+1,ii) = y(ii:nx,1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 cmat = trimx*conj(trimy);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 % normalization
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 nmat = triu(ones(nx,nx),0);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 nmat = rot90(nmat);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 normat = nmat*nmat;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 cmat = cmat./normat;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 if ~isempty(cutbefore)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 % cut rows
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 cmat(1:cutbefore,:)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 % cut columns
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 cmat(:,1:cutbefore)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 [nn,mm]=size(cmat);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 if ~isempty(cutafter)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 % cut rows
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 cmat(nn-cutafter:nn,:)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 % cut columns
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 cmat(:,mm-cutafter:mm)=[];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 end
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127
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128 end
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129
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130
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131
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132
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133
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134
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 end