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var

PURPOSE ^

VAR overloads the var operator for Analysis objects. Compute the variance.

SYNOPSIS ^

function ao_out = var (varargin)

DESCRIPTION ^

 VAR overloads the var operator for Analysis objects. Compute the variance.

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

 DESCRIPTION: VAR overloads the var operator for Analysis objects.
              Compute the variance.
              VAR(ao) is the variance of the values in ao.data.

 CALL: ao_out = var(ao_in);
       ao_out = var(ao_in, dim);
       ao_out = var(ao_in, W, DIM); --> use the parameterlist
       ao_out = var(ao_in, pl);
       ao_out = var(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>
                   'W'               []             represent the weight vector W
                  'dim'          1 or 2 or 3 ...    takes the var along the
                                                    dimension dim
                          tsdata  fsdata  xydata
                 'xdata'   't'     'f'      'x'     compute the var of the x-axis
                 'ydata'   'x'     'xx'     'y'     compute the var of the y-axis

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

 >> pl = var(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 = var (varargin)
0002 % VAR overloads the var operator for Analysis objects. Compute the variance.
0003 %
0004 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0005 %
0006 % DESCRIPTION: VAR overloads the var operator for Analysis objects.
0007 %              Compute the variance.
0008 %              VAR(ao) is the variance of the values in ao.data.
0009 %
0010 % CALL: ao_out = var(ao_in);
0011 %       ao_out = var(ao_in, dim);
0012 %       ao_out = var(ao_in, W, DIM); --> use the parameterlist
0013 %       ao_out = var(ao_in, pl);
0014 %       ao_out = var(ao1, pl1, ao_vector, ao_matrix, pl2);
0015 %
0016 % POSSIBLE VALUES: ao_in  = [ao2 ao3]
0017 %                  ao_in  = ao_vector
0018 %                  ao_in  = ao_matrix
0019 %
0020 % PARAMETER LIST:  <key>           <value>             <description>
0021 %                   'W'               []             represent the weight vector W
0022 %                  'dim'          1 or 2 or 3 ...    takes the var along the
0023 %                                                    dimension dim
0024 %                          tsdata  fsdata  xydata
0025 %                 'xdata'   't'     'f'      'x'     compute the var of the x-axis
0026 %                 'ydata'   'x'     'xx'     'y'     compute the var of the y-axis
0027 %
0028 % The following call returns a parameter list object that contains the
0029 % default parameter values:
0030 %
0031 % >> pl = var(ao, 'Params')
0032 %
0033 % HISTORY: 23-05-2007 Diepholz
0034 %             Creation
0035 %
0036 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0037 
0038 VERSION  = '$Id: var.m,v 1.8 2007/11/26 14:48:13 ingo Exp $';
0039 ao_out   = [];
0040 pl       = plist();
0041 
0042 %% Check if this is a call for parameters
0043 if nargin == 2
0044   if isa(varargin{1}, 'ao') && ischar(varargin{2})
0045     in = char(varargin{2});
0046     if strcmp(in, 'Params')
0047       ao_out = getDefaultPL();
0048       return
0049     elseif strcmp(in, 'Version')
0050       ao_out = VERSION;
0051       return
0052     end
0053   end
0054 end
0055 
0056 %% Collect input ao's, plist's and ao variable names
0057 in_names = {};
0058 ps       = plist();
0059 for ii = 1:nargin
0060   in_names{end+1} = inputname(ii);
0061 
0062   if isnumeric(varargin{ii})
0063     ps = [ps plist(param('dim', varargin{ii}))];
0064   end
0065 end
0066 
0067 [ao_set, pl, invars] = collect_inputs(varargin, in_names);
0068 
0069 pl = combine(pl, ps);
0070 
0071 %% go through analysis objects
0072 for j=1:numel(ao_set)
0073   a = ao_set(j);
0074 
0075   [h, var_data] = single_operation(a.data, 'var', pl);
0076 
0077   %% Add the history from the ao object to the history
0078   h = set(h, 'inhists', [a.hist]);
0079 
0080   %% Set the var_name to the history
0081   h = set(h, 'invars', cellstr(invars{j}));
0082 
0083   do_xdata = find(pl, 'xdata');
0084   do_ydata = find(pl, 'ydata');
0085 
0086   %% Is no axis entry in the parameter list
0087   %% then set the default axis = xdata
0088   if isempty(do_xdata) && isempty(do_ydata)
0089     do_ydata = 'yes';
0090   end
0091 
0092   %% Get the operation result. It is stored in the individual axis
0093   pl_get_axis = plist([param('xdata', do_xdata) param('ydata', do_ydata)]);
0094   [var_x, var_y] = get_xy_values(var_data, pl_get_axis);
0095 
0096   var_cdata = cdata([var_x var_y]);
0097   var_cdata = set (var_cdata, 'name', var_data.name);
0098   var_cdata = set (var_cdata, 'xunits', var_data.xunits);
0099   var_cdata = set (var_cdata, 'yunits', var_data.yunits);
0100 
0101   %% create a new analysis objects
0102   new_ao = ao  (var_cdata, h);
0103   new_ao = setnh(new_ao, 'name', sprintf('var(%s)',invars{j}) );
0104 
0105   ao_out = [ao_out new_ao];
0106 
0107 end
0108 
0109 % Reshape the ouput to the same size of the input
0110 ao_out = reshape(ao_out, size(ao_set));
0111 
0112 
0113 %% Get default params
0114 function pl_default = getDefaultPL()
0115 
0116   pl_default = plist([param('dim',    '')
0117                       param('W',      [])
0118                       param('xdata',  '')
0119                       param('ydata',  '')]);
0120 
0121 % END

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