However these routines still generate quite noisy results. This is documented here, Differentiation_function.pdf, and the full set of files is here ( IgorDifferentiation.zip. So at the moment (2006-2010) we have been using a simple technique: fit a straight line to the data, and take the slope of that line to get the differential. The simplest option, to take the difference between two adjacent points, generates huge noise. However differentiating noisy data is non-trivial. Often we need to differentiate data with Igor - e.g.
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