Home > marsbar > @mardo_2 > apply_filter.m

apply_filter

PURPOSE ^

applies filter in design to data

SYNOPSIS ^

function Y = apply_filter(D, Y, flags)

DESCRIPTION ^

 applies filter in design to data
 FORMAT Y = apply_filter(D, Y, flags)

 D      - design, which includes a filter
 Y      - data to filter (2D matrix or marsy data object)
 flags  - string specifying one option, or cell array specifying more
          than one option, or struct with fields specifying options.
          Values for strings, cell contents or field names are
          'no_whitening'  - specifies not to use whitening matrix even
                            if present in model
          'sessions'      - when used as struct field, value for field
                            specifies sessions to apply filter for. The
                            data size must match the length of the
                            included sessions.

 Returns
 Y      - filtered data

 $Id$

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function Y = apply_filter(D, Y, flags)
0002 % applies filter in design to data
0003 % FORMAT Y = apply_filter(D, Y, flags)
0004 %
0005 % D      - design, which includes a filter
0006 % Y      - data to filter (2D matrix or marsy data object)
0007 % flags  - string specifying one option, or cell array specifying more
0008 %          than one option, or struct with fields specifying options.
0009 %          Values for strings, cell contents or field names are
0010 %          'no_whitening'  - specifies not to use whitening matrix even
0011 %                            if present in model
0012 %          'sessions'      - when used as struct field, value for field
0013 %                            specifies sessions to apply filter for. The
0014 %                            data size must match the length of the
0015 %                            included sessions.
0016 %
0017 % Returns
0018 % Y      - filtered data
0019 %
0020 % $Id$
0021   
0022 if nargin < 2
0023   error('Need data to filter');
0024 end
0025 if nargin < 3
0026   flags = [];
0027 end
0028 if ~isempty(flags)
0029   if ischar(flags), flags = {flags}; end
0030   if iscell(flags)
0031     flags = cell2struct(repmat({''}, size(flags)), flags, 1);
0032   end
0033 end
0034 if ~is_fmri(D)
0035   return
0036 end
0037 if ~has_filter(D)
0038   error('This FMRI design does not contain a filter');
0039 end
0040 
0041 SPM = des_struct(D);
0042 K = SPM.xX.K;
0043 if ~has_whitener(D) | isfield(flags, 'no_whitening')
0044   W = eye(n_time_points(D));
0045 else
0046   W = SPM.xX.W;
0047 end
0048 
0049 % Filtering from subset of sessions
0050 if isfield(flags, 'sessions')
0051   ss = flags.sessions;
0052   if ~isempty(ss)
0053     blk_rows = block_rows(D);
0054     if any(ss < 1 | ss > length(blk_rows))
0055       error('Sessions appear to be out of range');
0056     end
0057     K = K(ss);
0058     K.row = blk_rows{ss} - blk_rows{ss}(1) + 1; 
0059     W = W(blk_rows{ss}, blk_rows{ss});
0060   end
0061 end
0062 
0063 if isa(Y, 'marsy')  % marsy object
0064   rd = region_data(Y);
0065   for r = 1:length(rd)
0066     rd{r} = pr_spm_filter(K, W*rd{r});
0067   end
0068   Y = region_data(Y, [], rd);
0069 else                % 2D matrix
0070   Y = pr_spm_filter(K, W*Y);
0071 end

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