--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/corr.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,123 @@
+% CORR estimate linear correlation coefficients.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: CORR estimate linear correlation coefficients.
+%
+%              The method returns a P-by-P matrix containing the pairwise
+%              linear correlation coefficient between each pair of columns
+%              in the N-by-P matrix X formed from the length-N vectors of
+%              the P input AOs. The coefficients are calculated using
+%              Pearson's product-moment method.
+%
+% CALL:        >> c = corr(a,b)
+%              >> 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 $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = corr(varargin)
+  
+  % Check if this is a call for parameters
+  if utils.helper.isinfocall(varargin{:})
+    varargout{1} = getInfo(varargin{3});
+    return
+  end
+  
+  import utils.const.*
+  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+  
+  % Collect input variable names
+  in_names = cell(size(varargin));
+  for ii = 1:nargin,in_names{ii} = inputname(ii);end
+  
+  % Collect all AOs and plists
+  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+  
+  if nargout == 0
+    error('### corr cannot be used as a modifier. Please give an output variable.');
+  end
+  
+  if numel(as) < 2
+    error('### corr requires at least two input AOs to work.');
+  end
+  
+  % Convolute the data
+  smat = [];
+  inunits = unit;
+  name = '';
+  desc = '';
+  for jj=1:numel(as)
+    smat = [smat as(jj).data.getY];
+    inunits = inunits .* as(jj).data.yunits;
+    name = strcat(name, [',' ao_invars{jj}]);
+    desc = strcat(desc, [' ' as(jj).description]);
+  end
+  desc = strtrim(desc);
+  
+  % compute the sample correlation using Pearson's product-moment coefficient
+  Cv = cov(smat);
+  C = zeros(size(Cv));
+  for ii=1:size(Cv, 1)
+    for kk=1:size(Cv,2)
+      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));
+  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)
+      varargout{ii} = bs(ii);
+    end
+  else
+    % Single output
+    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
+