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mean

PURPOSE ^

MEAN overloads the mean operator for Analysis objects. Compute the mean value.

SYNOPSIS ^

function ao_out = mean (varargin)

DESCRIPTION ^

 MEAN overloads the mean operator for Analysis objects. Compute the mean value.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

 DESCRIPTION: MEAN overloads the mean operator for Analysis objects.
              Compute the mean value.
              MEAN(ao) is the mean value of the elements in ao.data.

 CALL: ao_out = mean(ao_in);
       ao_out = mean(ao_in, dim);
       ao_out = mean(ao_in, pl);
       ao_out = mean(ao1, pl1, ao_vector, ao_matrix, pl2);

 POSSIBLE VALUES: ao_in  = [ao2 ao3]
                  ao_in  = ao_vector
                  ao_in  = ao_matrix

 PARAMETER LIST:  <key>           <value>             <description>
                  'dim'          1 or 2 or 3 ...    takes the mean along the
                                                    dimension dim
                          tsdata  fsdata  xydata
                 'xdata'   't'     'f'      'x'     compute the mean of the x-axis
                 'ydata'   'x'     'xx'     'y'     compute the mean of the y-axis

 The following call returns a parameter list object that contains the
 default parameter values:

 >> pl = mean(ao, 'Params')

 HISTORY: 23-05-2007 Diepholz
             Creation

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SUBFUNCTIONS ^

SOURCE CODE ^

0001 function ao_out = mean (varargin)
0002 % MEAN overloads the mean operator for Analysis objects. Compute the mean value.
0003 %
0004 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0005 %
0006 % DESCRIPTION: MEAN overloads the mean operator for Analysis objects.
0007 %              Compute the mean value.
0008 %              MEAN(ao) is the mean value of the elements in ao.data.
0009 %
0010 % CALL: ao_out = mean(ao_in);
0011 %       ao_out = mean(ao_in, dim);
0012 %       ao_out = mean(ao_in, pl);
0013 %       ao_out = mean(ao1, pl1, ao_vector, ao_matrix, pl2);
0014 %
0015 % POSSIBLE VALUES: ao_in  = [ao2 ao3]
0016 %                  ao_in  = ao_vector
0017 %                  ao_in  = ao_matrix
0018 %
0019 % PARAMETER LIST:  <key>           <value>             <description>
0020 %                  'dim'          1 or 2 or 3 ...    takes the mean along the
0021 %                                                    dimension dim
0022 %                          tsdata  fsdata  xydata
0023 %                 'xdata'   't'     'f'      'x'     compute the mean of the x-axis
0024 %                 'ydata'   'x'     'xx'     'y'     compute the mean of the y-axis
0025 %
0026 % The following call returns a parameter list object that contains the
0027 % default parameter values:
0028 %
0029 % >> pl = mean(ao, 'Params')
0030 %
0031 % HISTORY: 23-05-2007 Diepholz
0032 %             Creation
0033 %
0034 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0035 
0036 VERSION  = '$Id: mean.m,v 1.12 2007/11/26 14:48:13 ingo Exp $';
0037 ao_out   = [];
0038 
0039 %% Check if this is a call for parameters
0040 if nargin == 2
0041   if isa(varargin{1}, 'ao') && ischar(varargin{2})
0042     in = char(varargin{2});
0043     if strcmp(in, 'Params')
0044       ao_out = getDefaultPL();
0045       return
0046     elseif strcmp(in, 'Version')
0047       ao_out = VERSION;
0048       return
0049     end
0050   end
0051 end
0052 
0053 %% Collect input ao's, plist's and ao variable names
0054 in_names = {};
0055 ps       = plist();
0056 for ii = 1:nargin
0057   in_names{end+1} = inputname(ii);
0058 
0059   if isnumeric(varargin{ii})
0060     ps = [ps plist(param('dim', varargin{ii}))];
0061   end
0062 end
0063 
0064 [ao_set, pl, invars] = collect_inputs(varargin, in_names);
0065 
0066 pl = combine(pl, ps);
0067 
0068 %% go through analysis objects
0069 for j=1:numel(ao_set)
0070   a = ao_set(j);
0071 
0072   [h, mean_data] = single_operation(a.data, 'mean', pl);
0073 
0074   %% Add the history from the ao object to the history
0075   h = set(h, 'inhists', [a.hist]);
0076 
0077   %% Set the var_name to the history
0078   h = set(h, 'invars', cellstr(invars{j}));
0079 
0080   % convert to cdata type
0081   mean_x    = [];
0082   mean_y    = [];
0083 
0084   do_xdata = find(pl, 'xdata');
0085   do_ydata = find(pl, 'ydata');
0086 
0087   %% Is no axis entry in the parameter list
0088   %% then set the default axis = xdata
0089   if isempty(do_xdata) && isempty(do_ydata)
0090     do_ydata = 'yes';
0091   end
0092 
0093   %% Get the operation result. It is stored in the individual axis
0094   pl_get_axis = plist([param('xdata', do_xdata) param('ydata', do_ydata)]);
0095   [mean_x, mean_y] = get_xy_values(mean_data, pl_get_axis);
0096 
0097   mean_cdata = cdata([mean_x mean_y]);
0098   mean_cdata = set (mean_cdata, 'name', mean_data.name);
0099   mean_cdata = set (mean_cdata, 'xunits', mean_data.xunits);
0100   mean_cdata = set (mean_cdata, 'yunits', mean_data.yunits);
0101 
0102   %% create a new analysis objects
0103   new_ao = ao  (mean_cdata, h);
0104   new_ao = setnh(new_ao, 'name', sprintf('mean(%s)',invars{j}) );
0105 
0106   ao_out = [ao_out new_ao];
0107 
0108 end
0109 
0110 % Reshape the ouput to the same size of the input
0111 ao_out = reshape(ao_out, size(ao_set));
0112 
0113 
0114 %% Get default params
0115 function pl_default = getDefaultPL()
0116 
0117   pl_default = plist([param('dim',    '')
0118                       param('xdata',  '')
0119                       param('ydata',  '')]);
0120 
0121 % END

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