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- %% 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
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