mpib_memoreye/task/create_sequence_210311_BSJL.m

function [sequence_ready distrot] = create_sequence_210311_BSJL(nobject, nrot, contestdif, nblocks)

%This function is made for the firs version of Memoreye. Compare to
%Pingball, all trials would be CONCRETE.

%This function combine part of code written by B. Spitzer and J.
%Linde-Domingo

%We will obtainend a matrix where each row is a trial and each column:
  
% Column 1 = Object 1
% Column 2 = Object 2
% Column 3 =  Rotation Object 1
% Column 4 =  Rotarion Object 2
% Column 5 =  Target: 1 or 2
% Column 6 =  Target Object (id)
% Column 7 =  Type of task  (1= concrete/perceptual; 2=continuous/abstract)
% Column 8 =  Object memory test
% Column 9 =  Rotation Object memory test
% Column 10 =  Block number
% Column 11 =  Rotation target
% Column 12 = Testing uncued (True / False)                                  
% Column 13 =  Object memory test 2                                          
% Column 14 =  Rotation Object memory test 2                                 
% Column 15 =  Rotation UNCUED                                               

% % nrot=16
% % contestdif=3.5
% % nobject=3
% % nblocks=8

%% ~ Original B's code -

%smallest unit 
noris=nrot;                                                                   %- CHANGE THIS, REASON: HARD CODING -
ori1=repmat([1:noris]',noris,1); % cued
ori2=sort(ori1);                 % uncued
 
%double it
ori1=repmat(ori1,2,1);  % cued
ori2=repmat(ori2,2,1);  % uncued
 
%one set with uncued-test, the other without
unctest=[ones(noris^2,1); zeros(noris^2,1)];
ntrials=length(unctest);
 
%quasi uniform allocation of pictures 1-3 

pairs=nchoosek(1:nobject,2);
pairs=[pairs;[pairs(:,2),pairs(:,1)]];

stim1=repmat(pairs(:,1),86,1);  % make this vector slightly 'too long'       - CHANGE THIS, REASON: HARD CODING -
stim2=repmat(pairs(:,2),86,1);

% randomize (and shorten
pe=randperm(ntrials);
stim1=stim1(pe); 
stim2=stim2(pe);
 
% independently balance and randomize presentation as S1 or S2 
presord=[ones(noris^2,1); 2*ones(noris^2,1)];
presord=presord(randperm(ntrials));
 
%assemble stimulus set
trials=[ori1 stim1 ori2 stim2 unctest presord];
% and randomize trial order 
trials=trials(randperm(ntrials),:);

%% Modifying the variable "trials" to match the output matrix (see line 8)

distrot=360/nrot;
listofrotations=(distrot/2):distrot:(360-(distrot/2));

trialsperblock=size(trials,1)/nblocks;

for ttt = 1:size(trials,1)
    
% Column 1 = Object 1   
% Column 2 = Object 2
% Column 3 =  Rotation Object 1
% Column 4 =  Rotarion Object 2
% Column 5 =  Target: 1 or 2
% Column 6 =  Target Object (id)
% Column 7 =  Type of task  (1= concrete/perceptual; 2=continuous/abstract)
% Column 8 =  Object memory test
% Column 9 =  Rotation Object memory test
% Column 10 =  Block number
% Column 11 =  Rotation target
% Column 12 = Testing uncued (True / False)  
% Column 13 =  Object memory test 2
% Column 14 =  Rotation Object memory test 2
% Column 15 =  Rotation UNCUED

    trials_recon(ttt,5) = trials(ttt,6);     % Column 5 =  Target: 1 or 2
    
    if trials(ttt,6) == 1 % If the cued item is presented first
        
        f_col_id = 2; % column for 1st item id
        f_col_rot = 1; % column for 1st item rot        
        s_col_id = 4 ;% column for 2nd item id
        s_col_rot = 3; % column for 2nd item rot
        
    elseif trials(ttt,6) == 2 % If the cued item is presented second

        f_col_id = 4; % column for 1st item id
        f_col_rot = 3; % column for 1st item rot        
        s_col_id = 2; % column for 2nd item id
        s_col_rot = 1; % column for 2nd item rot
        
    end
        
        trials_recon(ttt,1) = trials(ttt,f_col_id); % Column 1 = Object 1 (item presented 1st)
        trials_recon(ttt,2) = trials(ttt,s_col_id); % Column 2 = Object 2 (item presented 1st)
        
        trials_recon(ttt,3) = listofrotations(trials(ttt,f_col_rot)); % Column 3 =  Rotation Object 1
        trials_recon(ttt,4) = listofrotations(trials(ttt,s_col_rot)); % Column 4 =  Rotarion Object 2
        
        trials_recon(ttt,6) = trials(ttt,2); % Column 6 =  Target Object - CUE (id)
        trials_recon(ttt,7) = 1;             % Column 7 =  Type of task  (1= concrete/perceptual; 2=continuous/abstract) - HERE IT IS ALWAYS CONCRETE
        
        trials_recon(ttt,8) = trials(ttt,2); % Column 8 =  Object memory test CUE - HERE IT IS ALWAYS THE SAME COS IT IS A CONCRETE TASK
        
        % Column 9 =  Rotation Object
        % memory test (below)
        
        if randi([0, 1], [1, 1])
            trials_recon(ttt,9)= listofrotations(trials(ttt,1))+(distrot/contestdif);%target position + one test position
        else
            trials_recon(ttt,9)= listofrotations(trials(ttt,1))-(distrot/contestdif);%target position - one test position
        end
               
        trials_recon(ttt,10)= ceil(ttt/trialsperblock); % Column 10 =  Block number (we will add this later)
        
        trials_recon(ttt,11)= listofrotations(trials(ttt,1));% Column 11 =  Rotation target (CUE)
        trials_recon(ttt,12)= trials(ttt,5); %Column 12 = Testing uncued (True / False)  
        
        trials_recon(ttt,13)= trials(ttt,4);% Column 13 =  Object memory test 2 (it will be always the same uncued item)
        
        % Column 14 =  Rotation Object memory test 2
        
         if randi([0, 1], [1, 1])
            trials_recon(ttt,14)= listofrotations(trials(ttt,3))+(distrot/contestdif);%target position + one test position
        else
            trials_recon(ttt,14)= listofrotations(trials(ttt,3))-(distrot/contestdif);%target position - one test position
        end                
                        
        trials_recon(ttt,15)= listofrotations(trials(ttt,3)); % Column 15 =  Rotation UNCUE
        
            
end

%Outputs

sequence_ready = trials_recon;

end