view m-toolbox/classes/@ao/corr.m @ 44:409a22968d5e
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Add unit tests
author
Daniele Nicolodi <nicolodi@science.unitn.it>
date
Tue, 06 Dec 2011 18:42:11 +0100 (2011-12-06)
parents
f0afece42f48
children
line source
+ − % 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
+ −