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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% EVALUATEMODEL evaluate a curvefit model. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: EVALUATEMODEL evaluate a curvefit model. % % CALL: b = evaluateModel(a, pl) % % INPUTS: a - input AO(s) containing parameter values. The parameter % values are collected from the Y data of all input cdata % AOs. The most common approach would be one AO per % parameter, or a single AO with all parameters in. % pl - parameter list (see below) % % OUTPUTs: b - an AO containing the model evaluated at the give X % values, with the given parameter values. % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'evaluateModel')">Parameters Description</a> % % VERSION: $Id: evaluateModel.m,v 1.14 2011/04/08 08:56:13 hewitson Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = evaluateModel(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'running %s/%s', mfilename('class'), mfilename); warning(['The method ''ao/curvefit'' and ''ao/evaluateModel'' have been replaced by ''ao/xfit'' and ''pest/eval''.' ... 'They are no longer maintained and will be removed from future releases of LTPDA Toolbox.']); % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin,in_names{ii} =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); pl = utils.helper.collect_objects(varargin(:), 'plist', in_names); %%% Decide on a deep copy or a modify bs = copy(as, nargout); % Each of the input AOs should be a cdata AO; from these we get the % parameter values P = []; for kk=1:numel(bs) if isa(bs(kk).data, 'cdata') P = [P; bs(kk).data.y(:)]; else warning('!!! AO %s is not a cdata AO. Not using for parameter values.', bs(kk).name); end end % combine plists pl = parse(pl, getDefaultPlist()); % Extract necessary parameters targetFcn = find(pl, 'Function'); ADDP = find(pl, 'ADDP'); dtype = find(pl, 'dtype'); Xdata = find(pl, 'Xdata'); if isa(Xdata, 'ao') Xdata = Xdata.x; end if ~iscell(ADDP) ADDP = {ADDP}; end % Check parameters if isempty(targetFcn) error('### Please specify a target function'); end if isempty(P) error('### Please give values for the parameters'); end % Make an anonymous function of the target function cmd = sprintf('tfunc = @(P,Xdata,ADDP)(%s);', targetFcn); eval(cmd); % Evaluate function at best fit Y = tfunc(P, Xdata, ADDP); if isa(Y, 'ao') Y = Y.y; end % Make new output AO switch lower(dtype) case 'tsdata' out = ao(tsdata(Xdata,Y)); out.data.setXunits('s'); case 'fsdata' out = ao(fsdata(Xdata,Y)); out.data.setXunits('Hz'); case 'xydata' out = ao(xydata(Xdata,Y)); otherwise error('### Unknown data type specified. Choose from xydata, fsdata, or tsdata'); end % Set output AO name name = sprintf('eval(%s,', targetFcn); for kk=1:numel(bs) name = [name bs(kk).name ',']; end name = [name(1:end-1) ')']; out.name = name; % Add history out.addHistory(getInfo('None'), pl, ao_invars, [bs(:).hist]); % 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, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: evaluateModel.m,v 1.14 2011/04/08 08:56:13 hewitson 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(); % Function p = param({'Function', ['The function to evaluate. <br>'... 'The function should be parameterized by the vector of '... 'parameters P, the cell-array ADDP, and the '... 'x-vector Xdata.'... ]}, paramValue.EMPTY_STRING); pl.append(p); % ADDP p = param({'ADDP', 'A cell-array of additional parameters to pass to the target function'}, ... {1, {{}}, paramValue.OPTIONAL}); pl.append(p); % DTYPE p = param({'dtype', 'The data type to interpret this model as.'}, {1, {'xydata', 'fsdata', 'tsdata'}, paramValue.SINGLE}); pl.append(p); % XDATA p = param({'Xdata', ['The X values to evaluate the model at.<br>'... 'This can be a vector or an AO (from which the Xdata will '... 'be extracted).']}, paramValue.EMPTY_DOUBLE); pl.append(p); end % END