Mercurial > hg > ltpda
view m-toolbox/classes/@ssm/parameterDiff.m @ 28:01b86b780ba7 database-connection-manager
Remove LTPDARepositoryManager implementation. Java code
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children |
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% PARAMETERDIFF Makes a ssm that produces the output and state derivatives. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: PARAMETERDIFF Makes a ssm that produces the output % and state derivative in regard with specified parameters, for a specificed variation. % % CALL: obj = obj.parameterDiff({'key1', ...}, [val1, ...]); % obj = obj.parameterDiff(plist); % obj = obj.parameterDiff('key', val); % % <a href="matlab:utils.helper.displayMethodInfo('ssm', 'parameterDiff')">Parameters Description</a> % % VERSION: $Id: parameterDiff.m,v 1.9 2011/04/08 08:56:22 hewitson Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = parameterDiff(varargin) % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end %% starting initial checks utils.helper.msg(utils.const.msg.MNAME, ['running ', mfilename]); % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin, in_names{ii} = inputname(ii); end % Collect all SSMs and options [sys, ssm_invars, rest] = utils.helper.collect_objects(varargin(:), 'ssm', in_names); [pl, invars2, rest] = utils.helper.collect_objects(rest(:), 'plist'); if ~isempty(rest) pl = combine(pl, plist(rest{:})); end pl = combine(pl, getDefaultPlist()); %%% Internal call: Only one object + don't look for a plist internal = strcmp(varargin{end}, 'internal'); %% processing input names = pl.find('names'); if ischar(names) names = {names}; elseif ~iscellstr(names) error('### Parameter names must be a cell-array of strings') end values = pl.find('values'); if ~isa(values, 'double') error('### param values should be a double') end Nsys = numel(sys); sys_out = ssm.initObjectWithSize(Nsys,1); %% checking data Ndiff = length(names); if ~(Ndiff== length(values)) error(['### The number of parameter names is ' num2str(Ndiff) ' and the number of parameter values is ' num2str(length(values))]); end if ~isa(values, 'double') error(['### Parameter ''values'' is not a double array but of class ' class(values)]); end for i_sys = 1:Nsys %% getting matrix sizes Nss = sys(i_sys).Nstates; Ninputs = sys(i_sys).Ninputs; Noutputs = sys(i_sys).Noutputs; sssizes = sys(i_sys).statesizes; inputsizes = sys(i_sys).inputsizes; outputsizes = sys(i_sys).outputsizes; %% setting matrix sizes amats = cell(Nss*(Ndiff+1), Nss*(Ndiff+1)); bmats = cell(Nss*(Ndiff+1), Ninputs); cmats = cell(Noutputs*(Ndiff+1), Nss*(Ndiff+1)); dmats = cell(Noutputs*(Ndiff+1), Ninputs); sys_num = sys(i_sys).keepParameters; %% assigning system matrices for nominal values amats(1:Nss,1:Nss) = sys_num.amats; bmats(1:Nss,1:Ninputs) = sys_num.bmats; cmats(1:Noutputs,1:Nss) = sys_num.cmats; dmats(1:Noutputs,1:Ninputs) = sys_num.dmats; outputs = sys(i_sys).outputs; states = sys(i_sys).states; %% loop over parameters for i_p = 1:Ndiff % computing ssm derivative sys_loc = copy(sys(i_sys), true); value_loc = sys(i_sys).params.find(names{i_p}) + values(i_p); sys_loc.doSetParameters(names(i_p), value_loc); sys_loc.keepParameters; % computing derivatives of matrices dAmats = ssm.blockMatRecut( ( ssm.blockMatFusion(sys_loc.amats, sssizes, sssizes) - ssm.blockMatFusion(sys_num.amats, sssizes, sssizes) )/ values(i_p) , sssizes, sssizes); dBmats = ssm.blockMatRecut( ( ssm.blockMatFusion(sys_loc.bmats, sssizes, inputsizes) - ssm.blockMatFusion(sys_num.bmats, sssizes, inputsizes) )/ values(i_p) , sssizes, inputsizes); dCmats = ssm.blockMatRecut( ( ssm.blockMatFusion(sys_loc.cmats, outputsizes, sssizes) - ssm.blockMatFusion(sys_num.cmats, outputsizes, sssizes) )/ values(i_p) , outputsizes, sssizes); dDmats = ssm.blockMatRecut( ( ssm.blockMatFusion(sys_loc.dmats, outputsizes, inputsizes) - ssm.blockMatFusion(sys_num.dmats, outputsizes, inputsizes) )/ values(i_p) , outputsizes, inputsizes); % assigning matrices for derivatives amats( (1+i_p*Nss):((i_p+1)*Nss), (1+i_p*Nss):((i_p+1)*Nss) ) = sys_num.amats; amats( (1+i_p*Nss):((i_p+1)*Nss), 1:Nss ) = dAmats; bmats( (1+i_p*Nss):((i_p+1)*Nss), 1:Ninputs ) = dBmats; cmats( (1+i_p*Noutputs):((i_p+1)*Noutputs), (1+i_p*Nss):((i_p+1)*Nss) ) = sys_num.cmats; dmats( (1+i_p*Noutputs):((i_p+1)*Noutputs), 1:Ninputs ) = dDmats; cmats( (1+i_p*Noutputs):((i_p+1)*Noutputs), 1:Nss ) = dCmats; % assigning outputs outputs((1+i_p*Noutputs):((i_p+1)*Noutputs)) = sys_loc.outputs ; % renaming outputs for i=(1+i_p*Noutputs):((i_p+1)*Noutputs) outputs(i).setBlockNames( [outputs(i).name '_DIFF_' names{i_p}] ); end % assigning states states((1+i_p*Nss):((i_p+1)*Nss)) = sys_loc.states ; % renaming states for i=(1+i_p*Nss):((i_p+1)*Nss) states(i).setBlockNames( [states(i).name '_DIFF_' names{i_p}] ); end clear sys_loc end %% proceeding parameters update sys_out(i_sys).amats = amats; sys_out(i_sys).bmats = bmats; sys_out(i_sys).cmats = cmats; sys_out(i_sys).dmats = dmats; sys_out(i_sys).timestep = sys(i_sys).timestep; sys_out(i_sys).name = sys(i_sys).name; sys_out(i_sys).description = sys(i_sys).description; sys_out(i_sys).params = plist; sys_out(i_sys).outputs = outputs; sys_out(i_sys).inputs = sys(i_sys).inputs; sys_out(i_sys).states = states; sys_out(i_sys).validate; %% history and output arguments if ~internal sys_out(i_sys).addHistory(ssm.getInfo(mfilename), pl , {''}, sys(i_sys).hist ); end end if nargout == numel(sys_out) for ii = 1:numel(sys_out) varargout{ii} = sys_out(ii); end else varargout{1} = sys_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, 'ssm', 'ltpda', utils.const.categories.helper, '$Id: parameterDiff.m,v 1.9 2011/04/08 08:56:22 hewitson Exp $', sets, pl); end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function pl = getDefaultPlist() pl = plist(); p = param({'names', 'A cell-array of parameter names for numerical differentiations.'}, {}); pl.append(p); p = param({'values', 'An array of parameter values for numerical step size.'}, []); pl.append(p); end