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view m-toolbox/classes/@matrix/linearize.m @ 40:977eb37f31cb database-connection-manager
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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 18:04:03 +0100 |
parents | f0afece42f48 |
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% LINEARIZE output the derivatives of the model relative to the parameters. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: LINEARIZE output the derivatives of the model relative to % the parameters. Output is a collection of models corresponding to the % derivative of input model for each parameter % % CALL: dmod = linearize(imod) % % <a href="matlab:utils.helper.displayMethodInfo('matrix', 'linearize')">Parameters Description</a> % % VERSION: $Id: linearize.m,v 1.14 2011/04/08 08:56:31 hewitson Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = linearize(varargin) % utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename); % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin in_names{ii} = inputname(ii); end % Collect all smodels and plists [as, matrix_invars, rest] = utils.helper.collect_objects(varargin(:), 'matrix', in_names); [pl, pl_invars, rest] = utils.helper.collect_objects(rest(:), 'plist', in_names); % Merge with default plist pl = parse(pl, getDefaultPlist); % get parameters and make sure we are working with a cell array pnames = find(pl,'Params'); if isa(pnames, 'char') pnames = {pnames}; end % decide if sorting sorting = find(pl,'Sorting'); if sorting pnames = sort(pnames); end % loop over input matrices dmod(numel(as),1)=collection; for ww=1:numel(as) imod=as(ww); if strcmpi(class(imod.objs(1)),'smodel') % a matrix of smodels is assumed % join params if isempty(pnames) % linearize with respect to all model parameters % store a common set of parameters for mod, it is needed for % the derivative [rw,cl] = size(imod.objs); % loop over dimensions mpars = {}; mvals = {}; for aa = 1:rw for bb = 1:cl obj = imod.objs(aa,bb); [mpars,id1,id2] = union(mpars,obj.params); nom1 = mvals(id1); nom2 = obj.values(id2); mvals = [nom1 nom2]; end end for ff = 1:numel(imod.objs) imod.objs(ff).setParams(mpars,mvals); end % it is assumed a common set of parameters for the matrix object pnames = imod.objs(1).params; end %isempty(pnames) % get matrix dimension [rw,cl] = size(imod.objs); % start linearization for ii = 1:numel(pnames) tmod = copy(imod,1); for jj = 1:rw for kk = 1:cl tmod.objs(jj,kk) = diff(imod.objs(jj,kk),pnames{ii}); % do symbolic derivative for smodel tmod.objs(jj,kk).setName(sprintf('d{%s}/d{%s}',imod.objs(jj,kk).name,pnames{ii})); end end % set the name of the parameter to the matrix, this is important to % identify automatically to what derivatives we are referring tmod.setName(pnames{ii}); % dmod.addObjects(tmod); dmod(ww).addObjects(tmod); end dmod(ww).setName(sprintf('linearize(%s)',imod.name)); else error('Only matrix of smodels supported at the moment') end %strcmpi(class(imod.objs(1)),'smodel') end if nargout == 1 varargout{1} = dmod; elseif nargout == numel(as) % List of outputs for ii = 1:numel(as) varargout{ii} = dmod.index(ii); end else error('Set at least one output value') 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, 'matrix', 'ltpda', utils.const.categories.op, '$Id: linearize.m,v 1.14 2011/04/08 08:56:31 hewitson Exp $', sets, pls); ii.setModifier(false); 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({'Params', ['Cell array with parameters names with respect to linearize. <br>' ... 'Leave it empty to linearize with respect to all model parameters']}, paramValue.EMPTY_DOUBLE); pl.append(p); p = param({'Sorting', ' Decide to sort the lits of input parameters'}, paramValue.TRUE_FALSE); pl.append(p); end