%% define a new subject 
s(1) = PDSubject('/Users/marsman/Documents/Werk/NIC/Teaching/Studenten/Nora_Parigi/data/Subject 5');
s(2) = PDSubject('/Users/marsman/Documents/Werk/NIC/Teaching/Studenten/Nora_Parigi/data/Subject 4')
%% load data

s(1) = s(1).loadData();
s(2) = s(2).loadData();


%% define trial markers
s = s.setPattern('trial start', 'Fixation6s starting');
s = s.setPatternRelativeToPattern('trial start', 'trial end', +10.5e3); % dependency of trial_start

%s = s.setPattern('trial end',   'Fixation15s starting');
s = s.setPattern('stimulus onset',  'Stimulus Presentation');
s = s.setPattern('stimulus offset', 'Fixation15s ending');

s = s.setLabel('information', 'Valence %s');
s = s.setLabel('information', 'TRIAL_VAR stim %s');

% s = s.setPattern('baseline start');
% s = s.setPattern('baseline end');

%% parse trials
s = s.rebuild;


% baseline is defined based on minimum value for baseline signal

e = PDExperiment(s, 'Min');

% baseline is defined based on average value for baseline signal
% e = PDExperiment(s, 'Average');

% calculate baseline corrected and filtered signals
e = PDExperiment(s, 'Average');
e = e.preprocess();


plot(e); %% plot trials of the experiment

e = build_averages(e);