Function "diff" and the loss of an element in the array (2024)

I didn't know about gradient. Thanks @Torsten !

@Bryan Ambrósio, compare the results from gradient() to the theoretical results for this signal, and to the results using diff(). An advantage of gradient() is that it gives estimates at the same locaitons as the sample locations, including at the edges. But you may not like its estimates at the edges. Your call.

And gradient allows you to specify the spacing between elements, which is important for getting the right scale on the derivatives.

And note that you can call diff with two or three inputs to avoid having to call diff with one input repeatedly.

I would advise using the three input syntax to avoid the case where you accidentally reduce the array to size 1 in the dimension over which your calls have been operating and start operating on a different dimension without intending to do so.

Did you expect the final M to have fewer columns than the original M?

"...but the location of the nth position corresponding to the initial vector does move down each successive operation..."

This explanation, like the original question, confuses data with indices.

I disagree @Stephen23; it simply notes that owing to the size differential, the indices to the locations of the original data are numerically lower than those to the original data from which the difference was computed to address the specifics of the original question as to which difference is stored where.

Of course, there are no other differences available to be stored, but that's somewhat different... :)

Yeah, @Steven Lord, I thought about adding in the alternate syntax but opted for brevity to keep to the original Q? only...sometimes one might need both differences in which case the three argument version doesn't help so much; you've got two calls either way.

I've thought of (but have never actually submitted it as formal enhancment request) it might be a worthwhile option to have a flag to return an array of successive differences as an alternative to the one n-th difference -- the problem and argument against being it makes it hard to deal with the higher dimension cases other than vector inputs.