DevianceDetectionHumanABR/Deviance Detection_Humans/Demo_FindRelDevStdOm.m

%% create artificial datasets and sequences
data_dev = [10,3,3,1;1,3,1,3;3,3,3,3]';
data_std = [2,11,2,2,4,2,4,2;2,2,4,2,4,2,2,2;2,4,2,2,4,4,4,2]';
n_files = size(data_dev,2);
n_dev = size(data_dev,1);
n_std = size(data_std,1);
n_stims = n_dev+n_std;
seq = [1,1,0,1,1,1,0,1,1,0,0,1;0,1,1,1,0,0,1,1,0,1,1,1;1,1,0,1,1,1,0,1,0,1,0,1]';
seqStd = logical(seq);
seqDev = ~seq;
%% shift dev and std sequence by one point and index into it with original std and dev sequence to obtain stds before devs and devs after stds

seqStd_ad = logical([zeros(1,n_files);seqDev(1:n_stims-1,:)]); % shift original dev sequences by 1 point (backwards)
seqStd_ad = reshape(seqStd_ad(seqStd),n_std,n_files); % index into shifted deviant sequences with original standard sequences to obtain stds after devs
seqDev_as = logical([zeros(1,n_files);seqStd(1:n_stims-1,:)]); % shift original std sequences by 1 point (backwards)
seqDev_as = reshape(seqDev_as(seqDev),n_dev,n_files); % index into shifted standard sequences with original dev sequences to obtain dev after stds

%% apply newly generated sequences on dev and std datasets

sample_std = cell(1,n_files);
sample_dev = cell(1,n_files);
for j = 1:n_files
    sample_std{1,j} = data_std(seqStd_ad(:,j),j);
    sample_dev{1,j} = data_dev(seqDev_as(:,j),j);
end

%% same approach with only one std/dev dataset

data_dev = [10,3,3,1];
data_std = [2,11,2,2,4,2,4,2];
seq = [1,1,0,1,1,1,0,1,1,0,0,1];
seq_std = logical(seq);
seq_dev = ~seq;
seq_std_bd_temp = logical([seq_dev(2:end),zeros(1,1)]);
seqStd_ad = seq_std_bd_temp(seq_std);
seq_dev_as_temp = logical([zeros(1,1),seq_std(1:end-1)]);
seqDev_as = seq_dev_as_temp(seq_dev);
sample_std = data_std(seqStd_ad)
sample_dev = data_dev(seqDev_as)

bla = 1;