Mercurial > hg > ltpda
view m-toolbox/classes/@ssm/simulate.m @ 0:f0afece42f48
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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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% SIMULATE simulates a discrete ssm with given inputs %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: SIMULATE simulates a discrete ssm with given inputs. % % CALL: [mat_out pl_out] = simulate(sys, pl) % % INPUTS: % - sys, (array of) ssm object % % OUTPUTS: % _ mat_out contains specified returned aos % _ pl_out contains 'lastX', the last state position % % <a href="matlab:utils.helper.displayMethodInfo('ssm', 'simulate')">Parameters Description</a> % % VERSION: $Id: simulate.m,v 1.104 2011/07/11 10:44:38 adrien Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % TO DO: options to be defined (NL case) % allow use of other LTPDA functions to generate white noise function varargout = simulate(varargin) %% starting initial checks % use the caller is method flag callerIsMethod = utils.helper.callerIsMethod; % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end utils.helper.msg(utils.const.msg.PROC3, ['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 plists [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()); %% begin function body tini = pl.find('t0'); if isempty(tini) tini = pl.find('tini'); % check for the old name if isempty(tini) tini = time; else warning('The use of the parameter ''tini'' is deprecated and will be removed in future releases. Use ''t0'' instead'); end end if isa(tini,'double') tini = time(tini); end %% retrieve system infos if numel(sys)~=1 error('simulate needs exactly one ssm as an input') end if ~sys.isnumerical error(['error because system ',sys.name,' is not numerical']); end timestep = sys.timestep; if timestep==0 error('timestep should not be 0 in simulate!!') end if callerIsMethod % we don't need the history of the input else inhist = sys.hist; end if pl.isparam('noise variable names') error('The noise option used must be split between "covariance" and "cpsd". "noise variable names" does not exist anymore!') end %% display time ? displayTime = find(pl, 'displayTime'); %% initial state ssini = find(pl,'ssini'); if isempty(ssini) initialize = find(pl, 'initialize'); if initialize ssini = sys.steadyState(pl); ssini = find(ssini, 'state'); else ssini = cell(sys.Nss,1); for i=1:sys.Nss ssini{i} = zeros(sys.sssizes(i),1); end end end ssSizesIni = sys.statesizes; SSini = double(ssm.blockMatFusion(ssini,ssSizesIni,1)); %% collecting simulation i/o data % values aos_in = find(pl, 'aos'); constants_in = find(pl, 'constants'); cov_in = find(pl, 'covariance'); cpsd_in = find(pl, 'CPSD'); noise_in = blkdiag(cov_in, cpsd_in/(timestep*2)); [U1,S1,V1] = svd(noise_in.'); %#ok<NASGU> if (sum(S1<0)>0) error('Covariance matrix is not positive definite') end noise_mat = U1*sqrt(S1); %% modifying system's ordering if find(pl, 'reorganize') sys = reorganize(sys, pl, 'set', 'for simulate', 'internal', 'internal'); end %% getting system's i/o sizes inputSizes = sys.inputsizes; outputSizes = sys.outputsizes; Naos_in = inputSizes(1); Nnoise = inputSizes(2); Nconstants = inputSizes(3); NstatesOut = outputSizes(1); NoutputsOut = outputSizes(2); if numel(aos_in)~=Naos_in error(['There are ' num2str(numel(aos_in)) ' input aos and ' num2str(Naos_in) ' corresponding inputs indexed.' ]) elseif numel(diag(noise_in))~=Nnoise error(['There are ' num2str(numel(diag(noise_in))) ' input noise variances and ' num2str(Nnoise) ' corresponding inputs indexed.' ]) elseif numel(constants_in)~=Nconstants error(['There are ' num2str(numel(constants_in)) ' input constants and ' num2str(Nconstants) ' corresponding inputs indexed.' ]) end A = sys.amats{1,1}; Coutputs = sys.cmats{2,1}; Cstates = sys.cmats{1,1}; Baos = sys.bmats{1,1}; Daos = sys.dmats{2,1}; Bnoise = sys.bmats{1,2} * noise_mat; Dnoise = sys.dmats{2,2} * noise_mat; Bcst = sys.bmats{1,3} * reshape(constants_in, Nconstants, 1); Dcst = sys.dmats{2,3} * reshape(constants_in, Nconstants, 1); %% getting correct number of samples Nsamples = find(pl, 'Nsamples'); f0 = 1/timestep; for i=1:Naos_in Nsamples = min(Nsamples,length(aos_in(i).y)); try if ~(f0==aos_in(i).fs) str = ['WARNING : ssm frequency is ',num2str(f0),... ' but sampling frequency of ao named ',... aos_in(i).name, ' is ', num2str(aos_in(i).fs) ]; utils.helper.msg(utils.const.msg.MNAME, str); end end % maybe tdata should be retrieved and verified to be equal, rather than this. end if Nsamples == inf % case there is no input! error('warning : no input option ''Nsamples'' providing simulation duration is available!!') Nsamples = 0; end %% termination condition if strcmp(find(pl, 'termincond'),''); doTerminate = false; terminationCond = ''; else doTerminate = true; terminationCond = find(pl, 'termincond'); end %% ao vector aos_vect = zeros(Naos_in, Nsamples); for j = 1:Naos_in aos_vect(j,:) = aos_in(j).y(1:Nsamples).'; end %% simulation loop [x, y, lastX] = ssm.doSimulate(... SSini, Nsamples, ... A, Baos, Coutputs, Cstates, Daos, Bnoise, Dnoise, Bcst, Dcst,... aos_vect, doTerminate, terminationCond, displayTime, timestep, pl.find('force complete')); %% saving in aos fs = 1/timestep; isysStr = sys.name; ao_out = ao.initObjectWithSize(1,NstatesOut+NoutputsOut); for i=1:NstatesOut ao_out(i).setData(tsdata( x(i,:), fs )); ao_out(i).setName(sys.outputs(1).ports(i).name); ao_out(i).setXunits('s'); ao_out(i).setYunits(sys.outputs(1).ports(i).units); ao_out(i).setDescription(... ['simulation for ' isysStr, ' : ', sys.outputs(1).ports(i).name,... ' ' sys.outputs(1).ports(i).description]); ao_out(i).setT0(tini); end for i=1:NoutputsOut ao_out(NstatesOut+i).setData(tsdata( y(i,:), fs )); ao_out(NstatesOut+i).setName(sys.outputs(2).ports(i).name); ao_out(NstatesOut+i).setXunits('s'); ao_out(NstatesOut+i).setYunits(sys.outputs(2).ports(i).units); ao_out(NstatesOut+i).setDescription(... ['simulation for, ' isysStr, ' : ', sys.outputs(2).ports(i).name, ... ' ', sys.outputs(2).ports(i).description]); ao_out(NstatesOut+i).setT0(tini); end %% construct output plist plist_out = plist('lastX', ssm.blockMatRecut(lastX,ssSizesIni,1) ); %% construct output matrix object out = matrix(ao_out); if callerIsMethod % do nothing else myinfo = getInfo('None'); out.addHistory(myinfo, pl , ssm_invars(1), inhist ); end %% Set output depending on nargout if nargout == 1; varargout = {out}; elseif nargout == 2; varargout = {out plist_out}; elseif nargout == 0; iplot(ao_out); else error('Wrong number of outputs') 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.op, '$Id: simulate.m,v 1.104 2011/07/11 10:44:38 adrien Exp $', sets, pl); end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function pl = getDefaultPlist() pl = ssm.getInfo('reorganize', 'for simulate').plists; pl.remove('set'); p = param({'covariance', 'The covariance of this noise between input ports for the <i>time-discrete</i> noise model.'}, []); pl.append(p); p = param({'CPSD', 'The one sided cross-psd of the white noise between input ports.'}, []); pl.append(p); p = param({'aos', 'An array of input AOs.'}, ao.initObjectWithSize(1,0)); pl.append(p); p = param({'constants', 'Array of DC values for the different corresponding inputs.'}, paramValue.DOUBLE_VALUE(zeros(0,1))); pl.append(p); p = param({'Nsamples', 'The maximum number of samples to simulate (AO length(s) overide this).'}, paramValue.DOUBLE_VALUE(inf)); pl.append(p); p = param({'ssini', 'A cell-array of vectors that give the initial position for simulation.'}, {}); pl.append(p); p = param({'initialize', 'When set to 1, a random state value is computed for the initial point.'}, paramValue.FALSE_TRUE); pl.append(p); p = param({'tini', 'Same as t0; kept for backwards compatibility.'}, paramValue.EMPTY_DOUBLE ); pl.append(p); p = param({'t0', 'The initial simulation time (seconds).'}, paramValue.EMPTY_DOUBLE ); pl.append(p); p = param({'displayTime', 'Switch off/on the display'}, paramValue.TRUE_FALSE); pl.append(p); p = param({'termincond', 'A string to evaluate a termination condition on the states in x (''lastX'') or outputs in y (''lastY'')'}, paramValue.EMPTY_STRING); pl.append(p); p = param({'reorganize', 'When set to 0, this means the ssm does not need be modified to match the requested i/o. Faster but dangerous!'}, paramValue.TRUE_FALSE); pl.append(p); p = param({'force complete', 'Force the use of the complete simulation code.'}, paramValue.FALSE_TRUE); pl.append(p); end