%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Compute log-likelihood in time domain for SSM objects
% 
% INPUT
% 
% - in, a vector of input signals aos
% - out, a vector of output data aos
% - parvals, a vector with parameters values
% - parnames, a cell array with parameters names
% - model, an ssm model
% - inNames, A cell-array of input port names corresponding to the
% different input AOs
% - outNames, A cell-array of output ports to return
% - cutbefore, followed by the data samples to cut at the starting of the
% data series
% - cutafter, followed by the data samples to cut at the ending of the
% data series
%
% L Ferraioli 10-10-2010
%
% $Id: chisquare_ssm_td.m,v 1.1 2010/11/16 16:41:37 luigi Exp $
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function chi2 = chisquare_ssm_td(xp,in,out,parnames,model,inNames,outNames,varargin)
% xn,in,out,noise,model,params,inNames,outNames
  cutbefore = [];
  cutafter = [];
  if ~isempty(varargin)
    for j=1:length(varargin)
      if strcmp(varargin{j},'cutbefore')
        cutbefore = varargin{j+1};
      end
      if strcmp(varargin{j},'cutafter')
        cutafter = varargin{j+1};
      end
    end
  end
  
  xp = double(xp);
  fs = out(1).fs;
  
  % set parameters in the model
  evalm = model.setParameters(plist('names',parnames,'values',xp));
  evalm.keepParameters();
  evalm.modifyTimeStep(plist('newtimestep',1/fs));
  
  %%% get expected outputs
  plsym = plist('AOS VARIABLE NAMES',inNames,...
    'RETURN OUTPUTS',outNames,...
    'AOS',in);
  eo = simulate(evalm,plsym);
  
  %%% get measurement noise
  res = out-eo;
  resy = res.y;
  if size(resy,2)>size(resy,1)
    resy = resy.';
  end
  
  if ~isempty(cutbefore)
    resy(1:cutbefore) = [];
  end
  if ~isempty(cutafter)
    resy(end-cutafter:end) = [];
  end
  
  chi2 = resy'*resy;
  chi2 = chi2/(numel(resy)-numel(xp));
  
  
  

end