ScaleTime

Fast linear interpolation of equally spaced data (C-MEX and M)

ScaleTime - fast linear matrix interpolation

Yi = ScaleTime(Y, T)
Where T is a vector with values between 1 and size(Y,1). This is equivalent to
Yi = interp1(1:size(Y, 1), Y, T, 'linear')
If T is defined by uniform steps: T = linspace(Ti, Tf, Tn) this is faster:
Yi = ScaleTime(Y, Ti, Tf, Tn)

For nun-uniform input use the 2nd function:
Yi = ScaleTimeNU(X, Y, Xi)

I have recorded timeseries of e.g. size [100'000 x 10] and cut out chunks of about 100 frames according to some events and normalize them to 101 frames.
The direct approach with Matlab's INTERP1 works, but it is slow:
interp1(1:size(Y, 1), Y, Ti, '*linear')

Therefore I've created the function ScaleTime for:
- linear interpolation
- equally spaced input data
- equally or non-equally spaced interpolation steps
- matrix input
- no handling of NaNs, no extrapolation.

To my surprise, ScaleTime is remarkably faster than INTERP1 and even the modern griddedInterpolant.
The functions lininterp1f and qinterp1 from the FEX do not accept matrices and they are significantly slower than the MEX ScaleTime:
http://www.mathworks.com/matlabcentral/fileexchange/8627
http://www.mathworks.com/matlabcentral/fileexchange/10286
If you have installed these tools, their speed is compared in uTest_ScaleTime.

Included: M-source, C-source.
Compilation: Automatically at running ScaleTime the first time, or:
mex -O ScaleTime.c
Pre-compiled mex function coming soon on: http://n-simon.de/mex