--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/polyfit.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,191 @@
+% POLYFIT overloads polyfit() function of MATLAB for Analysis Objects.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: POLYFIT overloads polyfit() function of MATLAB for Analysis
+%              Objects. It finds the coefficients of a polynomial P(X) of
+%              degree N that fits the data Y best in a least-squares sense:
+%              P(1)*X^N + P(2)*X^(N-1) +...+ P(N)*X + P(N+1)
+%
+% CALL:        bs = polyfit(a1, a2, a3, ..., pl)
+%              bs = polyfit(as,pl)
+%              bs = as.polyfit(pl)
+%
+% INPUTS:      aN   - input analysis objects with data to be fitted.
+%                   X will be a.x
+%                   Y will be a.y
+%              as   - input analysis objects array
+%              pl   - input parameter list
+%
+% OUTPUTs:     bs  - An array of pest objects, each with the N+1 fitting coefficients P(j)
+%
+% <a href="matlab:utils.helper.displayMethodInfo('ao', 'polyfit')">Parameters Description</a>
+%
+% VERSION:     $Id: polyfit.m,v 1.48 2011/05/12 03:37:08 mauro Exp $
+%
+% EXAMPLES:
+% 
+%   %% Make fake AO from polyval
+%   nsecs = 100;
+%   fs    = 10;
+%   
+%   u = unit('fm s^-2');
+%   
+%   pl = plist('nsecs', nsecs, 'fs', fs, ...
+%     'tsfcn', 'polyval([3 2 1 ], t) + 1000*randn(size(t))', ...
+%     'xunits', 's', 'yunits', u);
+% 
+%   a1 = ao(pl);
+%   
+%   %% Fit a polynomial
+%   N = 3;
+%   p1 = polyfit(a1, plist('N', N));
+%   p2 = polyfit(a1, plist('N', N, 'rescale', true));
+%
+%   %% Compute fit: evaluating pest
+%   %% Here we need to specify that we want to use the 'x' field of 
+%   %% the AO a to build the output AO
+%   
+%   b1 = p1.eval(plist('type', 'tsdata', 'XData', a1, 'Xfield', 'x'));
+%   b2 = p2.eval(a1, plist('type', 'tsdata', 'Xfield', 'x'));
+%   
+%   %% Plot fit
+%   iplot(a1, b1, plist('LineStyles', {'', '--'}));
+%
+%   %% Remove polynomial
+%   c = a1-b1;
+%   iplot(c)
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = polyfit(varargin)
+  
+  % Check if this is a call for parameters
+  if utils.helper.isinfocall(varargin{:})
+    varargout{1} = getInfo(varargin{3});
+    return
+  end
+  
+  import utils.const.*
+  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+  
+  % Collect input variable names
+  in_names = cell(size(varargin));
+  for ii = 1:nargin,in_names{ii} = inputname(ii);end
+  
+  % Collect all AOs and plists
+  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+  pl              = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+  
+  if nargout == 0
+    error('### polyfit can not be used as a modifier method. Please give at least one output');
+  end
+  
+  % Combine plists
+  use_pl = parse(pl, getDefaultPlist);
+  
+  % Degree of polynomial to fit
+  N       = find(use_pl, 'N');
+  
+  % Center and rescale the data
+  rescale = utils.prog.yes2true(find(use_pl, 'rescale'));
+  
+  % Loop over input AOs
+  for jj = 1 : numel(as)
+        
+    if isa(as(jj).data, 'cdata')
+      warning('!!! Can''t fit to cdata objects. Skipping AO %s', ao_invars{jj});
+      bs = [];
+    else      
+      % Fit polynomial
+      mu = [];
+      if rescale
+        [p,s,mu] = polyfit(as(jj).x, as(jj).y, N);
+      else
+        [p,s] = polyfit(as(jj).x, as(jj).y, N);
+      end
+            
+      % prepare models, units, names
+      model = [];
+      for kk = 1:N+1        
+        names{kk} = ['P' num2str(kk)];        
+        units{kk} = as(jj).yunits ./ ((as(jj).xunits).^(N-kk+1)); 
+        if kk == 1
+          model = [model 'P' num2str(kk) '*X.^' num2str(N-kk+1)];
+        else
+          model = [model ' + P' num2str(kk) '*X.^' num2str(N-kk+1)];
+        end
+      end
+      model = smodel(plist('expression', model, ...
+        'params', names, ...
+        'values', p, ...
+        'xvar', 'X', ...
+        'xunits', as(jj).xunits, ...
+        'yunits', as(jj).yunits ...
+        ));
+      
+      % Build new pest objects from these N+1 coefficients
+      bs(jj) = pest;
+      bs(jj).setY(p);
+      bs(jj).setDof(s.df);
+      bs(jj).setNames(names{:});
+      bs(jj).setYunits(units);
+      bs(jj).setModels(model);
+      bs(jj).name = sprintf('polyfit(%s)', ao_invars{jj});
+      bs(jj).addHistory(getInfo('None'), use_pl, ao_invars(jj), as(jj).hist);
+      % Set procinfo object with some data
+      bs(jj).procinfo = plist('S', s, 'mu', mu);
+      
+    end
+    
+  end
+  
+  % Set output
+  varargout = utils.helper.setoutputs(nargout, bs);
+
+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, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: polyfit.m,v 1.48 2011/05/12 03:37:08 mauro Exp $', sets, pl);
+  ii.setModifier(false);
+  ii.setArgsmin(1);
+end
+
+%--------------------------------------------------------------------------
+% Get Default Plist
+%--------------------------------------------------------------------------
+function plout = getDefaultPlist()
+  persistent pl;  
+  if ~exist('pl', 'var') || isempty(pl)
+    pl = buildplist();
+  end
+  plout = pl;  
+end
+
+function pl = buildplist()
+  pl = plist();
+  
+  % N
+  p = param({'N','Degree of polynomial to fit.'}, {2, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}, paramValue.SINGLE});
+  pl.append(p);
+  
+  % Rescale
+  p = param({'rescale',['set to ''true'' or ''false'' to center and ', ...
+    'rescale the data before fitting.<br>', ...
+    'See "help polyfit" for further details.']}, paramValue.FALSE_TRUE);  
+  pl.append(p);
+  
+end
+
+% END
+