How reduce data from 3917x2 to 1868x2 without change the entire of graph?

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Bajdar Nouredine
Bajdar Nouredine 2024-8-23
评论： Walter Roberson 2024-8-23
I have zdata.mat contains data 3917x2 I need a way to reduce data to 1868x2 , (hint: first column refers to x axis, second column refers to y axis)

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John D'Errico
John D'Errico 2024-8-23
编辑：John D'Errico 2024-8-23
Ran in:
Just take every other data point, if you just want to roughly reduce the size. But you say you want a specific length. So then you would need to interpolate.
load zdata.mat
plot(z(:,1),z(:,2),'-')
x = z(:,1); y = z(:,2);
xnew = linspace(min(x),max(x),1868);
ynew = interp1(x,y,xnew);
length(ynew)
ans = 1868
plot(xnew,ynew,'-')
Finally, if you want to do some smoothing, you might try something like:
ysmooth = smooth(x,y);
ynewsmooth = interp1(x,ysmooth,xnew);
plot(xnew,ynewsmooth,'-')
And depending on the smoothing method you choose, you can adjust the amount of smoothing done. You could also use a smoothing spline. Something like this (fit requires the curve fitting toolbox.)
spl = fit(x,y,'smoothingspline');
ynewspl = spl(xnew);
plot(xnew,ynewspl,'-')
Remember that when you have a sharp spike as this curve shows, anything you do to downsample such a curve may miss exactly where that spike happens, and how far it extends. But that is a given. If you reduce the sampling frequency, then you also reduce the information content of your data.
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John D'Errico
John D'Errico 2024-8-23
Note that interp1 makes no presumption of a uniform stride between data points. This is also the case for fit, which does not give a hoot about uniformity of stride. Finally, while SOME of the methods offered in smooth do care, not all of them do.
Walter Roberson
Walter Roberson 2024-8-23
My note about the differences was after your original answer, but before you did the interpolation.

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