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Add known repositories list to LTPDAPreferences
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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% AVERAGE averages aos point-by-point
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DESCRIPTION: AVERAGE averages aos point-by-point. 
%              For each point, an average is taken over all the input objects.
%              The uncertainty is calculated as the standard deviation of the mean. 
%              The objects must have the same length and yunits.
%
%         s1:   2 1 2 5 2 3 3
%         s2:   7 2 3 4 2 1 1
%         s3:   0 0 7 6 5 5 5
%         ===================
%         out:  3 1 4 5 3 3 3
%
% CALL:        b = average(a1, a2, a3, ..., pl)
%
% EXAMPLES:
%
% a1 = ao(plist('waveform','noise', 'nsecs', 1000,'fs',1,'yunits','m'));
% a2 = ao(plist('waveform','noise', 'nsecs', 1000,'fs',1,'yunits','m'));
% a3 = ao(plist('waveform','noise', 'nsecs', 1000,'fs',1,'yunits','m'));
% a4 = average(a1,a2,a3);
%
% <a href="matlab:utils.helper.displayMethodInfo('ao', 'average')">Parameters Description</a>
%
% VERSION:     $Id: average.m,v 1.5 2011/04/08 08:56:12 hewitson Exp $
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

function varargout = average(varargin)
  
  % Check if this is a call for parameters
  if utils.helper.isinfocall(varargin{:})
    varargout{1} = getInfo(varargin{3});
    return
  end
  
  % Check if the method was called by another method
  callerIsMethod = utils.helper.callerIsMethod;

  import utils.const.*
  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
  
  if nargout == 0
    error('### average 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);
    
  % Combine plists
  pl = combine(pl, getDefaultPlist);
  
  % Make a copy of the input objects history
  inhists = [as(:).hist];
  
  % Copy the input objects so we inherit all properties
  b  = copy(as(1), true);
  
  % Collect the data, and check that:
  % - all objects belong to the same class
  % - all objects have the same yunits
  % - all objects have the same length
  
  Nobj = numel(as);
  data_class   = class(as(1).data);
  data_yunits  = as(1).yunits;
  data_matrix  = as(1).data.getY;
  data_length  = numel(data_matrix);
  
  
  for jj = 2:Nobj
    % - all objects should belong to the same class
    if ~strcmp(class(as(jj).data), data_class)
      error('### The first ao data object is a %s, while the %dth is a %s. The data must all belong to the same class!', ...
        data_class, jj, class(as(jj).data));
    end
    
    % - all objects should have the same yunits
    if  as(jj).yunits ~= data_yunits
      error('### The first ao data object has yunits = %s, while the %dth has yunits = %s. The data must all have the same yunits!', ...
        char(data_yunits), jj, char(as(jj).yunits));
    end
    
    % - all objects should have the same length
    try 
      % The data.getY methods always give columns, so this syntax should give a proper matrix
      data_matrix = [data_matrix as(jj).data.getY];
    catch ME
      switch ME.identifier
        case 'MATLAB:catenate:dimensionMismatch'
          error('### The first ao data object has %d points, while the %dth has %d points. The data must all have the same size!', ...
            data_length, jj, numel(as(jj).data.getY));
        otherwise
          error('### Something went wrong while concatenating the data. Stopping.');
      end
      
    end
  end    
  
  % Go for the actual calculation.
  if Nobj > 1
    % The data.getY methods always give columns, so we just need to operate on the second dimension
    dim = 2;
    b.data.setY(mean(data_matrix, dim));
    b.data.setDy(std(data_matrix, 0, dim) / sqrt(Nobj));
  else
    % Nothing to do in this case
  end

  if ~callerIsMethod
    % create new output history    
    b.addHistory(getInfo('None'), pl, [ao_invars(:)], inhists);
    % set name
    b.name = sprintf('average(%s)', [ao_invars{:}]);
  end
  
  % Set output
  varargout{1} = b;
  
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: average.m,v 1.5 2011/04/08 08:56:12 hewitson Exp $', sets, pl);
  ii.setModifier(false);
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.EMPTY_PLIST;
  
end