How to extract progression from an array with numpy?

Question

I know that one can generate an (arithmetic) progression with numpy like so:

>>> import numpy as np
>>> np.arange(10, 60, 10)
array([10, 20, 30, 40, 50])

So my question is can I call something that will do the reverse ?

E.g. :

>>> progression(np.array([10, 20, 30, 40, 50]))
(10, 60, 10)

This is most probably not trivial, but it would be nice if there's something in numpy/scipy that can do an approximation. Also bonus points if it can recognize the type of progression without specifying.

Note: I'm aware there are similar questions already asked, but this one specifically hasn't been answered, I think.

Ivan · Accepted Answer · 2021-07-30 07:58:51Z

1

Since np.arange works with [start, end-step] with a step size. You can infer the parameters by hand:

def progression(x):
    step = x[1] - x[0]
    return x[0], x[-1] + step, step

This of course assumes the input array follows a sequential arangement!

answered Jul 30, 2021 at 7:58

Ivan

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Martin Gergov Over a year ago

Correct, this will satisfy the example I gave. It won't work for anything else, however. Maybe I formulated it badly, but my question was more about advanced inputs, e.g. 1, 11, 2, 22, 3, 33 has a step of n,11*n. Closest I could find is the OEIS, but that's just a database. So I was wondering if there's something in numpy/scipy that can attempt to recognize progressions.

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