--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/linSubtract.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,216 @@
+% LINSUBTRACT subtracts a linear contribution from an input ao.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: LINSUBTRACT subtracts a linear contribution from an input ao.
+%              The methods assumes the input data to be synchronous. The
+%              user selects a filter to be applied to the data before
+%              fitting and a time segment where the fit is performed.
+%
+% CALL:        c = linSubtract(a,b1,b2,b3,...,bN, pl)
+%
+% INPUTS:      a  - AO from where subtract linear contributions
+%              b  - AOs with noise contributions
+%              pl - parameter list (see below)
+%
+% OUTPUTs:     c  - output AO with contributions subtracted (tsdata)
+%
+% <a href="matlab:utils.helper.displayMethodInfo('ao', 'linSubtract')">Parameters Description</a> 
+%
+% EXAMPLES:
+%
+% 1) Given the data (d):
+%
+%             d = a + c1*b1 + c2*(b2+b3)^2
+%
+%    where (bs) are noisy contributions added to a signal (a). To recover (a)
+%    in the [1 1e3] segment applying a [5e-2 0.1] 2nd order bandpass
+%    filter to the data, the call to the function would be
+%
+%            pl = plist('type','bandpass',...
+%                       'fc',[5e-2 0.1],...
+%                       'order',2,...
+%                       'times',[1 1e3],...
+%                       'coupling',{{'n(1)'},{'(n(2) + n(3)).^2'}});
+%
+%            a = linSubtract(d,b1,b2,b3, pl)
+%
+%
+% VERSION:     $Id: linSubtract.m,v 1.13 2011/04/08 08:56:15 hewitson Exp $
+%
+% TODO: option for parallel and serial subtraction
+%       handling errors
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = linSubtract(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);
+  
+  % Method can not be used as a modifier
+  if nargout == 0
+    error('### tfe cannot be used as a modifier. Please give an output variable.');
+  end
+  
+  % 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);
+  
+  % Decide on a deep copy or a modify
+  bs = copy(as, nargout);
+  
+  % Combine plists
+  pl = parse(pl, getDefaultPlist);
+  
+  
+  % get parameters
+  fc = find(pl,'fc');
+  if isempty(fc)
+    error('### Please define a cut-off frequency ''fc''');
+  end
+  times = find(pl,'times');
+  cp = find(pl,'coupling');
+  if isempty(cp)
+    error('### Please define a coupling model ''coupling''')
+  end
+  order = find(pl,'order');
+  type = find(pl,'type');
+  
+  % split in time
+  if ~isempty(times)
+    cs = split(bs,plist('times',times));
+  else
+    cs = bs;
+  end
+  
+  s = cs(1);
+  for i = 2:length(bs)
+    n(i-1) = cs(i);
+  end
+  
+  subt = ao();
+  % Loop noise sources
+  for i=1:length(cp)
+    % coupling
+    nterm = ao();
+    if numel(cp{i}) == 1
+      nterm = eval([char(cp{i}) ';']);
+    else
+      nn = numel(cp{i});
+      for j =1:nn
+        nterm(j) = eval([char(cp{i}{j}) ';']);
+      end
+    end
+    % bandpass filter
+    fbp  = miir(plist('type',type,'fc',fc,'order',order,'fs',s.fs));
+    sbp = filtfilt(s,fbp);
+    nterm_bp = filtfilt(nterm,fbp);
+    % linear fit
+    c = lscov(nterm_bp,sbp);
+    sn = lincom(nterm,c);
+    % subtract
+    s = s - sn;
+  end
+  
+  % new tsdata
+  fsd = tsdata(s.x,s.y,s.fs);
+  % make output analysis object
+  cs = ao(fsd);
+  % set name
+  cs.name = sprintf('linSubtract(%s)', ao_invars{1});
+  % t0
+  if ~isempty(times)
+    cs.setT0(times(1));
+  else
+    cs.setT0(bs(1).t0);
+  end
+  % Propagate 'plotinfo'
+  plotinfo = [as(:).plotinfo];
+  if ~isempty(plotinfo)
+    cs.plotinfo = combine(plotinfo);
+  end
+  % Add history
+  cs.addHistory(getInfo('None'), pl, [ao_invars(:)], [bs(:).hist]);
+  % Set output
+  varargout{1} = cs;
+  
+  
+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: linSubtract.m,v 1.13 2011/04/08 08:56:15 hewitson Exp $', sets, pl);
+end
+
+
+%--------------------------------------------------------------------------
+% Get Default Plist
+%--------------------------------------------------------------------------
+function plout = getDefaultPlist()
+  persistent pl;  
+  if exist('pl', 'var')==0 || isempty(pl)
+    pl = buildplist();
+  end
+  plout = pl;  
+end
+
+function pl = buildplist()
+  
+  pl = plist();
+  
+  % Type
+  p = param({'type', 'Sets the type of filter used to fit the data.'}, {1, {'bandpass', 'bandreject', 'highpass', 'lowpass'}, paramValue.SINGLE});
+  pl.append(p);
+  
+  % fc
+  p = param({'fc', 'Frequency cut-off of the filter.'}, paramValue.EMPTY_DOUBLE);
+  pl.append(p);
+  
+  % Order
+  p = param({'order', 'Order of the filter.'}, {1, {2}, paramValue.OPTIONAL});
+  pl.append(p);
+  
+  % Times
+  p = param({'times', 'A set of times where the fit+subtraction is applied.'}, paramValue.EMPTY_DOUBLE);
+  pl.append(p);
+  
+  % Coupling
+  p = param({'coupling', ['A cell-array defining the model of the noise<br>'...
+    'terms to be subtracted. In the cell expression<br>'...
+    '''s'' stands for the input ao and ''n(i)'' for the N<br>' ...
+    'N noise contributions.']}, {1, {'{}'}, paramValue.OPTIONAL});
+  pl.append(p);
+  
+end
+% PARAMETERS:
+%             'type'     - Sets the type of filter used to fit the data
+%                          (help miir).
+%             'fc'       - Frequency cut-off of the filter (help miir)'
+%             'order'    - Order of the filter (help miir).
+%             'times'    - Sets split times where the subtraction applies
+%                          (help split).
+%             'coupling' - A cell-array defining the model of the noise
+%                          terms to be subtracted. In the cell expression
+%                          's' stands for the input ao and 'n(i)' for the N
+%                          N noise contributions.