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I would like to know if there is an automized or fast way to numerically derivate a large number of tab-delimited files (derived from the program kaleidagraph) and to automatically extract some key information from it?

It is a longitudinal growth study and i'm currently testing some non-parametric models. I have a tab delimited file with time in column 1 and size in column 2.

I wonder if there is a program that for every file can give me the second derivate numerically (that would be column 3) and the following parameters. - the maximum growth obtained (end of the curve) - the time T2 when velocity V2 is maximum and the corresponding velocity and size - the time T1 when velocity is minimum and T1

Since i have over a 1000 files and more i wondered if some tool or program could do the trick for me.

Thanks in advance



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Sounds like something that would be perfect for Matlab (or Octave) or NumPy/SciPy if you like. This could even be done in a spreadsheet program like Excel, I imagine. – horchler Jun 4 '13 at 0:18
In Matlab you'll want to used the diff function to compute second order finite differences. Taking derivatives (especially second derivatives) will amplify any noise in the data. You can attempt to mitigate this by instead applying a smoothing derivative filter. Savitzky-Golay is a popular technique for this and Matlab has a builtin function for it: sgolay. – horchler Jun 4 '13 at 0:26

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