compare.m

剑桥大学用于线性和双线性动力学系统辨识的工具箱

function [y,fit] = compare(model,data,INIT)
%BILIN/COMPARE    Compares simulated output data with the measured data.
%
%   [YH,FIT] = compare(M,DATA)
%   [YH,FIT] = compare(M,DATA,INIT)
%
%   M is the bilinear model as a BILIN object and DATA is the input-output
%   data, given as an IDDATA object.
%
%   The argument INIT determines how to deal with initial conditions:
%     - INIT = 'estimate' results in the initial state being chosen so
%         that the norm of the prediction error is minimized (default).
%     - INIT = 'model' uses M.X0 as the initial state.
%     - INIT = 'zero' sets the initial state to zero.
%     - if INIT is a column vector, then INIT is used as the initial state. 
%
%   YH is the resulting simulated/predicted output returned as an IDDATA
%   object. FIT is an optional output vector containing the percentage of
%   the measured output that is explained by the model, with FIT(1) being
%   the percentage fit of the first output, etc.
%
%   In the absence of output arguments, compare(M,DATA) outputs the
%   percentage fit to the workspace and produces plots comparing the
%   measured and simulated outputs.
%
%   See also BILIN, BILIN/SIM, BILIN/PE, IDDATA, IDDATA/PLOT.
%
% CUED System Identification Toolbox.
% Cambridge University Engineering Department.
% Copyright (C) 1998-2002. All Rights Reserved.

% Version 1.00, Date: 01/06/2002
% Created by H. Chen and E.C. Kerrigan.

if nargin <= 1 | nargin >= 4
  error('Incorrect number of input arguments.')
end

if nargin == 3
  if isempty(INIT)
	[E,X0] = pe(model,data,'estimate');
  else
	n = size(model.A,1);
	if isa(INIT,'char')
	  switch lower(INIT)
	   case {'z','zero'}
		X0 = zeros(n,1);
	   case {'m','model'}
		X0 =  model.X0;
	   case {'e','estimate'}
		[E,X0] = pe(model,data,INIT);
	   otherwise
		error('Invalid choice for INIT.')
	  end
	elseif isa(INIT,'numeric')
	  X0 = INIT;
	  if size(X0,1) ~= n | size(X0,2) ~= 1
		error('X0 should be an n-dimensional column vector.')
	  end
	else
	  error('Invalid choice for INIT.')
	end
  end
else
  [E,X0] = pe(model,data,'estimate');
end

[y,x,yu] = sim(model,data,X0);

deviation = y.y;
p = size(deviation,2);
fit = zeros(p,1);
for i = 1:p
  deviation(:,i)  = deviation(:,i)-mean(y.y(:,i));
  fit(i) = 100*(1-norm(data.y(:,i)-y.y(:,i))/norm(deviation));
end

if nargout == 0
  disp(' ')
  disp('Percentage Fit:')  
  for i = 1:p
	disp(sprintf('   %s - %0.4g%%',data.OutputName{i},fit(i)))
  end
  disp(' ')
  for i = 1:p
	plot(data(:,i,[]),yu(:,i,[]))
	legend('Measured Output',sprintf('Simulated Fit: %0.4g%%',fit(i)))
	if i < p
	  pause
	end
  end
  clear y fit
end

% *** last line of compare.m ***