diff m-toolbox/classes/@ssm/cpsdForIndependentInputs.m @ 0:f0afece42f48

Import.
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ssm/cpsdForIndependentInputs.m	Wed Nov 23 19:22:13 2011 +0100
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+% CPSDFORINDEPENDENTINPUTS computes the output theoretical CPSD shape with given inputs.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: cpsdForIndependentInputs computes the output theoretical
+%              CPSD or PSD shape for given input shapes.
+%              It returns summed and individual contributions and takes
+%              input vectors of objects (instead of square matrices)
+%
+% CALL:        [mat_outSum, mat_out] = PSD(sys, pl)
+%
+% INPUTS:
+%               sys - (array of) ssm object
+%
+% OUTPUTS:
+%              mat_outSum - contains specified returned aos, noise is
+%                           summed over all the specified input noises
+%              mat_out    - contains specified returned aos
+%
+% <a href="matlab:utils.helper.displayMethodInfo('ssm', 'cpsdForIndependentInputs')">Parameters Description</a>
+%
+% VERSION: $Id: cpsdForIndependentInputs.m,v 1.2 2011/05/23 14:18:20 adrien Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = cpsdForIndependentInputs(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.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 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());
+  
+  %%% Internal call: Only one object + don't look for a plist
+  internal = strcmp(varargin{end}, 'internal');
+  
+  %% begin function body
+  
+  %% retrieve system infos
+  
+  if numel(sys)~=1
+    error('noisespectrum needs exactly one ssm as an input')
+  end
+  if ~sys.isnumerical
+    error(['error because system ',sys.name,' is not numerical']);
+  end
+  if ~sys.isStable
+    error('input ssm is not stable!')
+  end
+  if sys.timestep==0
+    timestep = 1;
+  else
+    timestep = sys.timestep;
+  end
+  if ~internal
+    inhist  = sys.hist;
+  end
+  
+  %% modifying system's ordering
+  if find(pl, 'reorganize')
+    sys = reorganize(sys, pl, 'set', 'for cpsdForIndependentInputs', 'internal', 'internal');
+  end
+  
+  %% collecting functions i/o data
+  aos_in = find(pl, 'aos');
+  PZ_in = find(pl, 'PZmodels');
+  cov_in = find(pl, 'variance');
+  cpsd_in = find(pl, 'PSD');
+  
+  noise_mat = [...
+    reshape(cov_in, [numel(cov_in),1]) ; ...
+    reshape(cpsd_in, [numel(cpsd_in),1]) / (timestep*2)];
+  if sum(noise_mat<0) > 0
+    error('input PSD is not positive!')
+  end
+  
+  %% getting system's i/o sizes
+  inputSizes = sys.inputsizes;
+  outputSizes = sys.outputsizes; %#ok<NASGU>
+  
+  Naos_in = inputSizes(1);
+  Nnoise = inputSizes(2);
+  NPZmodels = inputSizes(3);
+  
+  %% retrieving frequency vector
+  if isempty(Naos_in)==0
+    f1 = find(pl,'f1');
+    f2 = find(pl,'f2');
+    NFreqs = find(pl,'nf');
+    if isempty(f1) || isempty(f2)|| isempty(NFreqs)
+      error('### Please specify frequency vector a start and stop frequency .');
+    else
+      freqs = 10 .^ linspace(log10(f1), log10(f2), NFreqs);
+    end
+  else
+    freqs = aos_in(1).x;
+  end
+  
+  %% checking frequency vector
+  for i=2:numel(aos_in)
+    if ~isequal(freqs,aos_in(i).x)
+      error('there exist different frequency vectors');
+    end
+  end
+  
+  %% reshape pzmodels and aos for input cross-spectra
+  if numel(PZ_in)==NPZmodels
+    PZdata = zeros(NPZmodels,NFreqs);
+    for i=1:NPZmodels
+      a = resp(PZ_in(i), freqs);
+      PZdata(i,:) = reshape(a.y,[1,NFreqs]) ;
+    end
+  else
+    error('Wrong size for field PZ_in')
+  end
+  
+  if numel(aos_in)==Naos_in
+    AOdata = zeros(Naos_in,NFreqs);
+    for i=1:Naos_in
+      AOdata(i,:) = reshape(aos_in(i).y,[1,NFreqs]) ;
+    end
+  else
+    error('Wrong size for field aos_in')
+  end
+  
+  %% SSM Transfer function
+  [a, b, c, d, Ts, InputName, StateName, OutputName,...
+    inputvarunits, ssvarunits, outputvarunits] = double(sys); %#ok<ASGLU>
+  resps    = ssm.doBode(a, b, c, d, 2*pi*freqs, Ts);
+  Noutputs = numel(OutputName);
+  
+  %% power for each frequency with SVD computation
+  diagOnly = pl.find('DIAGONAL ONLY');
+  if diagOnly
+    Result = zeros(Noutputs, Nnoise+Naos_in+NPZmodels, NFreqs);
+  else
+    Result = zeros(Noutputs, Noutputs, Nnoise+Naos_in+NPZmodels, NFreqs);
+  end
+  
+  for ff=1:NFreqs
+    for ii = 1:(Nnoise+Naos_in+NPZmodels)
+      powWhiteNoise = zeros(1,Nnoise);
+      powAO = zeros(1, Naos_in);
+      powPZ = zeros(1,NPZmodels);
+      if ii<Nnoise+1,
+        %% contribution from white noise
+        powWhiteNoise(ii) = noise_mat(ii) ;
+      elseif ii<Nnoise+Naos_in+1
+        %% contribution from aos
+        i_input2 = ii-Nnoise;
+        if AOdata(i_input2,ff)<0
+          error('input PSD is not positive!')
+        end
+        powAO(i_input2) = AOdata(i_input2,ff);
+      else
+        %% contribution from PZmodels
+        i_input2 = ii-Nnoise-Naos_in;
+        if PZdata(i_input2,ff)<0
+          error('input PSD is not positive!')
+        end
+        powPZ(i_input2) = real( PZdata(i_input2,ff) * conj( PZdata(i_input2,ff)) );
+      end
+      %% computing CPSD
+      pow = diag([powAO; powWhiteNoise; powPZ]);
+      RespLoc = squeeze(resps(:,:,ff));
+      noise = RespLoc * pow * RespLoc' * (2*timestep);
+      if diagOnly
+        Result(:,ii,ff) = real(diag(noise));
+      else
+        Result(:,:,ii,ff) = noise;
+      end
+      
+    end
+  end
+  
+  %% saving in aos
+  if diagOnly
+    ao_outSum = ao.initObjectWithSize(Noutputs, 1);
+    %% sum of all inputs
+    for oo=1:Noutputs
+      ao_outSum(oo,1).setData(fsdata(freqs, squeeze(sum(Result(oo,:,:),2)) ));
+      ao_outSum(oo,1).setName( ['PSD of ' , OutputName{oo} ' due to all contributions']);
+      ao_outSum(oo,1).setXunits('Hz');
+      ao_outSum(oo,1).setYunits(outputvarunits(oo)^2/unit('Hz'));
+      ao_outSum(oo,1).setDescription( ['PSD of ' , OutputName{oo} ' due to all contributions']);
+    end
+    if nargout ~= 1;
+      ao_out = ao.initObjectWithSize(Noutputs, Nnoise+Naos_in+NPZmodels);
+      %% individual inputs
+      for oo=1:Noutputs
+        for ii=1:(Nnoise+Naos_in+NPZmodels)
+          ao_out(oo,ii).setData(fsdata(freqs, squeeze(Result(oo,ii,:)) ));
+          ao_out(oo,ii).setName( ['PSD of ' , OutputName{oo} ' due to ' InputName{ii}]);
+          ao_out(oo,ii).setXunits('Hz');
+          ao_out(oo,ii).setYunits(outputvarunits(oo)^2/unit('Hz'));
+          ao_out(oo,ii).setDescription( ['PSD of ' , OutputName{oo} ' due to ' InputName{ii}]);
+        end
+      end
+    end
+  else
+    ao_outSum = ao.initObjectWithSize(Noutputs, Noutputs);
+    %% sum of all inputs
+    for oo=1:Noutputs
+      for pp=1:Noutputs
+        ao_outSum(oo,pp).setData(fsdata(freqs, squeeze(sum(Result(oo,pp,:,:),3)) ));
+        ao_outSum(oo,pp).setXunits('Hz');
+        ao_outSum(oo,pp).setYunits(outputvarunits(oo)^2/unit('Hz'));
+        if oo~=pp
+          ao_outSum(oo,pp).setName( ['Cross PSD of ', OutputName{oo}, ' and ', OutputName{pp} ' due to all contributions']);
+          ao_outSum(oo,pp).setDescription( ['Cross PSD of ', OutputName{oo}, ' and ', OutputName{pp} ' due to all contributions']);
+        else
+          ao_outSum(oo,pp).setName( ['PSD of ' , OutputName{oo}]);
+          ao_outSum(oo,pp).setDescription( ['PSD of ' , OutputName{oo}]);
+        end
+      end
+    end
+    if nargout ~= 1;
+      ao_out = ao.initObjectWithSize(Noutputs, Noutputs, Nnoise+Naos_in+NPZmodels);
+      %% individual inputs
+      for oo=1:Noutputs
+        for pp=1:Noutputs
+          for ii=1:(Nnoise+Naos_in+NPZmodels)
+            ao_out(oo,pp,ii).setData(fsdata(freqs, squeeze(Result(oo,pp,ii,:)) ));
+            ao_out(oo,pp,ii).setXunits('Hz');
+            ao_out(oo,pp,ii).setYunits(outputvarunits(oo)^2/unit('Hz'));
+            if oo~=pp
+              ao_out(oo,pp,ii).setName( ['Cross PSD of ', OutputName{oo}, ' and ', OutputName{pp} ' due to ' InputName{ii}]);
+              ao_out(oo,pp,ii).setDescription( ['Cross PSD of ', OutputName{oo}, ' and ', OutputName{pp} ' due to ' InputName{ii}]);
+            else
+              ao_out(oo,pp,ii).setName( ['PSD of ' , OutputName{oo} ' due to ' InputName{ii}]);
+              ao_out(oo,pp,ii).setDescription( ['PSD of ' , OutputName{oo} ' due to ' InputName{ii}]);
+            end
+          end
+        end
+      end
+    end
+  end
+  
+  
+  
+  %% construct output matrix object
+  if nargout ~= 1;
+    out = matrix(ao_out);
+  end
+  outSum = matrix(ao_outSum);
+  if callerIsMethod
+    % do nothing
+  else
+    myinfo = getInfo('None');
+    if nargout ~= 1;
+      out.addHistory(myinfo, pl , ssm_invars(1), inhist );
+    end
+    outSum.addHistory(myinfo, pl , ssm_invars(1), inhist );
+  end
+  
+  %% Set output depending on nargout
+  if nargout == 1;
+    varargout = {outSum};
+  elseif nargout == 2;
+    varargout = {outSum out };
+  elseif nargout == 0;
+    iplot(ao_outSum, 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: cpsdForIndependentInputs.m,v 1.2 2011/05/23 14:18:20 adrien Exp $', sets, pl);
+  
+end
+
+%--------------------------------------------------------------------------
+% Get Default Plist
+%--------------------------------------------------------------------------
+function pl = getDefaultPlist()
+  pl = ssm.getInfo('reorganize', 'for cpsdForIndependentInputs').plists;
+  pl.remove('set');
+  
+  p = param({'variance', 'The variance vector of this noise between input ports for the <i>time-discrete</i> noise model. '}, []);
+  pl.append(p);
+  
+  p = param({'PSD', 'The one sided psd vector of the white noise between input ports.'}, []);
+  pl.append(p);
+  
+  p = param({'aos', 'A vector of input PSD AOs, The spectrum of this noise between input ports for the <i>time-continuous</i> noise model.'}, ao.initObjectWithSize(1,0));
+  pl.append(p);
+  
+  p = param({'PZmodels', 'vector of noise shape filters for the different corresponding inputs.'}, paramValue.DOUBLE_VALUE(zeros(0,1)));
+  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({'f2', 'The maximum frequency. Default is Nyquist or 1Hz.'}, paramValue.EMPTY_DOUBLE);
+  pl.append(p);
+  
+  p = param({'f1', 'The minimum frequency. Default is f2*1e-5.'}, paramValue.EMPTY_DOUBLE);
+  pl.append(p);
+  
+  p = param({'nf', 'The number of frequency bins. Frequencies are scale logarithmically'}, paramValue.DOUBLE_VALUE(200));
+  pl.append(p);
+  
+  p = param({'diagonal only', 'Set to true if you want the PSD instead of the CPSD'}, paramValue.TRUE_FALSE);
+  pl.append(p);
+  
+end
+