44 lines
1.2 KiB
Matlab
44 lines
1.2 KiB
Matlab
% fake some data
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x_data = 0:2*pi/10:2*pi;
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sym_data = sin(repmat(x_data, 10,1)) * 0.75 + (randn(10, length(x_data)) .* cos(repmat(x_data, 10,1)));
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asym_data = sin(repmat(x_data, 10,1)) * 0.75 + (randn(10, length(x_data)) .* cos(repmat(x_data, 10,1)) + 0.5);
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% get some data characteristics
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avg_sym = mean(sym_data, 1);
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err_sym = std(sym_data, [], 1);
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avg_asym = median(asym_data, 1);
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err_upper_asym = prctile(asym_data, 75, 1);
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err_lower_asym = prctile(asym_data, 25, 1);
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fig = figure();
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set(fig, 'paperunits', 'centimeters', 'papersize', [15 6.5], ...
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'paperposition', [0.0 0.0 15, 6.5], 'color', 'white')
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subplot(1,3,1)
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errorbar(x_data, avg_sym, err_sym, 'marker', 'o')
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xlim([-.5, 6.5])
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xlabel('x-data')
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ylabel('y-data')
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box('off')
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subplot(1,3,2)
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errorbar(x_data, avg_asym, err_lower_asym, err_upper_asym, 'marker', 'o')
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xlim([-.5, 6.5])
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yticklabels([])
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xlabel('x-data')
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box('off')
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subplot(1,3,3)
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hold on
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p = fill(cat(2, x_data, fliplr(x_data)), ...
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cat(2, avg_sym - err_sym, fliplr(avg_sym + err_sym)), ...
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'b');
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p.FaceAlpha = 0.125;
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p.EdgeColor = 'w';
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xlim([-.5, 6.5])
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yticklabels([])
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box('off')
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xlabel('x-data')
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plot(x_data, avg_sym, 'b', 'linewidth', 1.)
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saveas(fig, '../lecture/images/errorbars', 'pdf')
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