% 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; endend%--------------------------------------------------------------------------% 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();endplout = pl;endfunction 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