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Slepi/Code/Utilities/spm12/spm_design_within_subject.m
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spm_design_within_subject.m
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function [I,P,cov] = spm_design_within_subject(fblock,cov)
% Set up within-subject design when specified subject by subject
% FORMAT [I,P,cov] = spm_design_within_subject(fblock,cov)
%
% fblock - Part of job structure containing within-subject design info
% cov - Part of job structure containing covariate info
%
% I - Nscan x 4 factor matrix
% P - List of scans
%__________________________________________________________________________
% Copyright (C) 2010-2012 Wellcome Trust Centre for Neuroimaging
% Will Penny
% $Id: spm_design_within_subject.m 4837 2012-08-13 18:10:04Z guillaume $
%-Specify design subject-by-subject
%--------------------------------------------------------------------------
P = {};
[I, subj] = deal([]);
for s = 1:numel(fblock.fsuball.fsubject)
P = [P; fblock.fsuball.fsubject(s).scans];
ns = length(fblock.fsuball.fsubject(s).scans);
cc = fblock.fsuball.fsubject(s).conds;
[ccr,ccc] = size(cc);
if ccr~=ns && ccc~=ns
error('Error for subject %d: conditions not specified for each scan',s);
elseif ccr~=ccc && ccc==ns
%warning('spm:transposingConditions',['Condition matrix ',...
% 'appears to be transposed. Transposing back to fix.\n',...
% 'Alert developers if it is not actually transposed.'])
cc=cc';
end
subj=[subj;s*ones(ns,1)];
% get real replications within each subject cell
[unused cci ccj] = unique(cc,'rows');
repl = zeros(ns, 1);
for k=1:max(ccj)
repl(ccj==k) = 1:sum(ccj==k);
end
I = [I; [repl cc]];
end
%-Handle keyword factors 'repl' and 'subject'
%--------------------------------------------------------------------------
nf = length(fblock.fac);
subject_factor = false;
for i=1:nf
if strcmpi(fblock.fac(i).name,'repl')
% Copy 'replications' column to create explicit 'replications' factor
I = [I(:,1:i) I(:,1) I(:,i+1:end)];
end
if strcmpi(fblock.fac(i).name,'subject')
% Create explicit 'subject' factor
I = [I(:,1:i) subj I(:,i+1:end)];
subject_factor = true;
end
end
%-Re-order scans conditions and covariates into standard format
% This is to ensure compatibility with how variance components are created
%--------------------------------------------------------------------------
if subject_factor
U=unique(I(:,2:nf+1),'rows');
Un=length(U);
Uc=zeros(Un,1);
r=1;rj=[];
for k=1:Un
for j=1:size(I,1)
match=sum(I(j,2:nf+1)==U(k,:))==nf;
if match
Uc(k)=Uc(k)+1;
Ir(r,:)=[Uc(k),I(j,2:end)];
r=r+1;
rj=[rj;j];
end
end
end
P=P(rj); % -scans
I=Ir; % -conditions
for k=1:numel(cov) % -covariates
cov(k).c = cov(k).c(rj);
end
end
%-Pad out factorial matrix to cover the four canonical factors
%--------------------------------------------------------------------------
I = [I ones(size(I,1),4-size(I,2))];
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