+
−% CORR estimate linear correlation coefficients.
+
−%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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−%
+
−% DESCRIPTION: CORR estimate linear correlation coefficients.
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−%
+
−%              The method returns a P-by-P matrix containing the pairwise
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−%              linear correlation coefficient between each pair of columns
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−%              in the N-by-P matrix X formed from the length-N vectors of
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−%              the P input AOs. The coefficients are calculated using
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−%              Pearson's product-moment method.
+
−%
+
−% CALL:        >> c = corr(a,b)
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−%              >> c = corr(a,b,c,...)
+
−%
+
−% INPUTS:      a,b,c,...  - input analysis objects
+
−%
+
−% OUTPUTS:     c    - output analysis object containing the correlation matrix.
+
−%
+
−% <a href="matlab:utils.helper.displayMethodInfo('ao', 'corr')">Parameters Description</a>
+
−%
+
−% VERSION:     $Id: corr.m,v 1.9 2011/04/08 08:56:18 hewitson Exp $
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−%
+
−%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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−
+
−function varargout = corr(varargin)
+
−  
+
−  % Check if this is a call for parameters
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−  if utils.helper.isinfocall(varargin{:})
+
−    varargout{1} = getInfo(varargin{3});
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−    return
+
−  end
+
−  
+
−  import utils.const.*
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−  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+
−  
+
−  % Collect input variable names
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−  in_names = cell(size(varargin));
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−  for ii = 1:nargin,in_names{ii} = inputname(ii);end
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−  
+
−  % Collect all AOs and plists
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−  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+
−  
+
−  if nargout == 0
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−    error('### corr cannot be used as a modifier. Please give an output variable.');
+
−  end
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−  
+
−  if numel(as) < 2
+
−    error('### corr requires at least two input AOs to work.');
+
−  end
+
−  
+
−  % Convolute the data
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−  smat = [];
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−  inunits = unit;
+
−  name = '';
+
−  desc = '';
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−  for jj=1:numel(as)
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−    smat = [smat as(jj).data.getY];
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−    inunits = inunits .* as(jj).data.yunits;
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−    name = strcat(name, [',' ao_invars{jj}]);
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−    desc = strcat(desc, [' ' as(jj).description]);
+
−  end
+
−  desc = strtrim(desc);
+
−  
+
−  % compute the sample correlation using Pearson's product-moment coefficient
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−  Cv = cov(smat);
+
−  C = zeros(size(Cv));
+
−  for ii=1:size(Cv, 1)
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−    for kk=1:size(Cv,2)
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−      C(ii,kk) = Cv(ii,kk) ./ (sqrt(Cv(ii,ii))*sqrt(Cv(kk,kk)));
+
−    end
+
−  end
+
−  
+
−  bs = ao(cdata(C));
+
−  bs.name = sprintf('corr(%s)', name(2:end));
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−  bs.description = desc;
+
−  bs.data.setYunits(inunits);
+
−  bs.addHistory(getInfo('None'), getDefaultPlist, ao_invars, [as(:).hist]);
+
−  
+
−  % Set output
+
−  if nargout == numel(bs)
+
−    % List of outputs
+
−    for ii = 1:numel(bs)
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−      varargout{ii} = bs(ii);
+
−    end
+
−  else
+
−    % Single output
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−    varargout{1} = bs;
+
−  end
+
−end
+
−
+
−%--------------------------------------------------------------------------
+
−% Get Info Object
+
−%--------------------------------------------------------------------------
+
−function ii = getInfo(varargin)
+
−  if nargin == 1 && strcmpi(varargin{1}, 'None')
+
−    sets = {};
+
−    pls  = [];
+
−  else
+
−    sets = {'Default'};
+
−    pls  = getDefaultPlist;
+
−  end
+
−  % Build info object
+
−  ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: corr.m,v 1.9 2011/04/08 08:56:18 hewitson Exp $', sets, pls);
+
−  ii.setModifier(false);
+
−  ii.setArgsmin(2);
+
−end
+
−
+
−%--------------------------------------------------------------------------
+
−% Get Default Plist
+
−%--------------------------------------------------------------------------
+
−
+
−function plout = getDefaultPlist()
+
−  persistent pl;  
+
−  if exist('pl', 'var')==0 || isempty(pl)
+
−    pl = buildplist();
+
−  end
+
−  plout = pl;  
+
−end
+
−
+
−function pl_default = buildplist()
+
−  pl_default = plist.EMPTY_PLIST;
+
−end
+
−