% data is in object gsr and already preprocessed
% onsets are in variable onsets, data in channel 1
curves = cell(numel(onsets), 2);
for cc = 1:numel(onsets)
    curves{cc, 1} = sprintf('Onset %d, t=%.4f', cc, onsets(cc));
    curves{cc, 2} = [1, onsets(cc) - 2, onsets(cc) + 20];
end

% we define three spots of interest:
% - onset (time of stimulus),
% - delay of response (minimum before peak),
% - and peak of response (amplitude)
spotnames = {'onset', 'delay', 'peak'};
spottype = {'onset', 'min', 'max'};

% the spots are simply defined as the onsets (and added values)
spots = {onsets, onsets + 3, onsets + 7};

% then we define some variables of interest:
% - Latency (defined as x-diff between onset and delay)
% - Response time (defined as x-diff between delay and peak)
% - Base amplitude (defined as y-value at delay)
% - Peak amplitude (defined as y-value at peak)
% - Peak-to-peak response amplitude (defined as y-diff between delay and peak)
% additionally, we define that for the response amplitude, the log+1 transform
% should be applied after we're done
vars = struct( ...
    'name', {'Latency', 'Resp. time', 'Base ampl.', 'Peak ampl.', 'Resp. ampl.'}, ...
    'calc', {'dx', 'dx', 'y', 'y', 'dy'}, ...
    'spot', {[1,2], [2,3], [2], [3], [2,3]}, ...
    'trans', {'none', 'none', 'none', 'none', 'log+1'});

% options:
% - data is now in channel 10 (filtered!)
% - original data is in channel 1 (pre-filter)
% - variables and spots as defined
pcopts = struct( ...
    'var',       vars, ...
    'spot',      {spot}, ...
    'spotnames', {spotnames}, ...
    'spottype',  {spottype});

% now we call plotcurves
plotcurves(gsr, pcopts);