%% Fig. 2A-B_LinePlot
clear all
close all

% ==========================================================================
%% k-mean cluster lineplot
% ==========================================================================
%Prepare variables
load('Fig2AB_LinePlot.mat'); 

TimeWinFrame = [-15:1:120];% -0.5 s to 4.0 s 
fs = 30;

%Learning phase
initial  = 1;
reversal = 2;

%Learning stage
naive  = 1;
expert = 2;

for iLearning = 1:2    %1 = Initial, 2 = Reversal
    disp(['iLearning = ', num2str(iLearning)]);
    switch iLearning
        case 1
            f1 = figure('Name', 'Go-kmean cluster-Initial');
            f1.Position = [190 198 560 420];
            Mean =  LineMean_Initial;
            SEM  =  LineSEM_Initial;
        case 2
            f2 = figure('Name', 'Go-kmean cluster-Reversal');
            f2.Position = [200 250 560 420];
            Mean =  LineMean_Reversal;
            SEM  =  LineSEM_Reversal;
    end
    
    for iCluster = 1:6 %NofCluter is 6
        disp(['iCluster = ', num2str(iCluster)]);   
        subplot(2, 3, iCluster);
        
        %Naive-----------------------------------------------------------
        shadedErrorBar2(TimeWinFrame/fs, Mean(iCluster, :, 1), SEM(iCluster, :, 1), {'-','color', [0 0 1]});
        box off
        hold on;
        %Expert------------------------------------------------------------
        shadedErrorBar2(TimeWinFrame/fs, Mean(iCluster, :, 2), SEM(iCluster, :, 2), {'-','color', [1 0 0]});
        hline(0, 'k');

        % Adjust lims
        xlim([-0.5 4.0]);
        ylim([-1.0 1.0]);
        
        %title
        switch iCluster
            case 1
                title('Stable1')
            case 2
                title('Stable2')                
            case 3
                title('Up')
            case 4
                title('Down')                
            case 5
                title('Ramp-up')
            case 6
                title('Ramp-down')
        end
    end %iCluster
end %iLearning