line source
+ − % computes Probability Density Function from a pest object
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ − %
+ − % DESCRIPTION: computes Probability Density Function from a pest object.
+ − %
+ − % CALL: p = computePdf(p,pl)
+ − % p.computePdf(pl)
+ − %
+ − % INPUTS: p - pest object
+ − % pl - parameter list (BurnIn,nbins)
+ − %
+ − % OUTPUTs: p - pest object with the computed normilized pdf
+ − %
+ − % <a href="matlab:utils.helper.displayMethodInfo('pest', 'computePdf')">Parameters Description</a>
+ − %
+ − % VERSION: $Id: computePdf.m,v 1.2 2011/06/06 14:02:12 nikos Exp $
+ − %
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ −
+ − function varargout = computePdf(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
+ − [pests, pest_invars] = utils.helper.collect_objects(varargin(:), 'pest', in_names);
+ − pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+ −
+ − % Decide on a deep copy or a modify
+ − p = copy(pests, nargout);
+ −
+ − % combine plists
+ − pl = parse(pl, getDefaultPlist());
+ − BurnIn = find(pl, 'BurnIn');
+ − nbins = find(pl, 'nbins');
+ −
+ − if ~all(isa(pests, 'pest'))
+ − error('### computePdf must be only applied to pest objects.');
+ − end
+ −
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ −
+ − N = numel(p);
+ −
+ − for ii=1:N
+ − a=p(ii).chain;
+ − D=size(a);
+ − [n(1,:),xout(1,:)]=hist(a(BurnIn:D(1),1),nbins);
+ − sumbins = sum(n(1,:));
+ − PDF = [xout(1,:) ; n(1,:)/sumbins]';
+ −
+ − for jj=2:D(2)
+ − % creating histograms
+ − [n(jj,:),xout(jj,:)]=hist(a(BurnIn:D(1),jj),nbins);
+ − sumbins = sum(n(jj,:));
+ − PDF = [PDF xout(jj,:)' (n(jj,:)')/sumbins];
+ − end
+ − PDFn(:,:,ii)= PDF;
+ − end
+ −
+ − %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ −
+ − % Output pest/pdf
+ − if nargout == 1
+ − for ii=1:N
+ − p(ii).setPdf(PDFn(:,:,ii));
+ − end
+ − out = p;
+ − elseif nargout == 0
+ − for ii=1:N
+ − p(ii).setPdf(PDFn(:,:,ii));
+ − end
+ − out = p;
+ − out.addHistory(getInfo('None'), pl, pest_invars(:), [pests(:).hist]);
+ − else
+ − error('### The number of output arguments must be a one or zero');
+ − end
+ −
+ − name = p(1).name;
+ − if N>1
+ − for ii=2:N
+ − name = [name ',' p(ii).name];
+ − end
+ − end
+ −
+ − % Set outputs
+ − if nargout > 0
+ − varargout{1} = out;
+ − end
+ −
+ − end
+ −
+ −
+ − %--------------------------------------------------------------------------
+ − % Get Info Object
+ − %--------------------------------------------------------------------------
+ − function ii = getInfo(varargin)
+ − if nargin == 1 && strcmpi(varargin{1}, 'None')
+ − sets = {};
+ − pl = [];
+ − else
+ − sets = {'Default'};
+ − pl = getDefaultPlist;
+ − end
+ − % Build info object
+ − ii = minfo(mfilename, 'pest', 'ltpda', utils.const.categories.helper, '$Id: computePdf.m,v 1.2 2011/06/06 14:02:12 nikos Exp $', sets, pl);
+ − end
+ −
+ −
+ − %--------------------------------------------------------------------------
+ − % Get Default Plist
+ − %--------------------------------------------------------------------------
+ − function plout = getDefaultPlist()
+ − persistent pl;
+ − if exist('pl', 'var')==0 || isempty(pl)
+ − pl = buildplist();
+ − end
+ − plout = pl;
+ − end
+ −
+ − function pl = buildplist()
+ − pl = plist();
+ −
+ − p = param({'BurnIn','Number of samples (of the chains) to be discarded'}, paramValue.DOUBLE_VALUE(1));
+ − pl.append(p);
+ −
+ − p = param({'nbins','Number of bins of the pdf histogram computed for every parameter'}, paramValue.DOUBLE_VALUE(10));
+ − pl.append(p);
+ −
+ − end
+ −