How can I find the average of several lines whose datasets are different lengths?

I'm able to plot the various datasets altogether thanks to normalizing the x axis values, but I need to find the 'average line' per say.

I'm unable to use a mean function because the datasets are differing lengths, any ideas?

for i = 1:length(plot_limit)

frame = find((inverse_kin(:,1) >= plot_limit(i,1)) & (inverse_kin(:,1) <= plot_limit(i,2)));

x{i} = normalize(inverse_kin(frame,1),'range',[0 100]);

y{i} = inverse_kin(frame,9);

end

figure;

hold on

for i = 1:length(plot_limit)

graph(i) = plot(x{i},y{i});

end

hold off

Answer 1

[Image Analyst]

I suggest you resample each curve with interp1() so that all your curves are using a common set of x values. Then simply add them up and divide by the number. Something like (untested):

numPoints = 1000; % Whatever resolution you want.
xCommon = linspace(0, 100, numPoints);
ySum = zeros(1, numPoints);
for k = 1 : numberOfCurves
    % Somehow get this particular set of x and y
    thisx = 
    thisy = 
    % Interpolate y so that it's using a common x axis.
    yCommon = interp1(thisx, thisy, xCommon);
    % Add it in to the other curves.
    ySum = ySum + yCommon;
end
% Divide the sum by the number of curves to get the average curve.
yAverage = ySum / numberOfCurves;

[Trevor D Clark]

This method worked really well, thanks for your help!

Answer 2

[the cyclist]

One possible solution would be to interpolate (e.g. with spline function) using the interp1 function, to a common grid of points along the x-axis, then take the mean over those points.