Import.
line source
% 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