Add in-between steps into array of numbers (Python)

Question

I am looking for some function that takes an input array of numbers and adds steps (range) between these numbers. I need to specify the length of the output's array.

Example:

input_array = [1, 2, 5, 4]
output_array = do_something(input_array, output_length=10)

Result:

output_array => [1, 1.3, 1.6, 2, 3, 4, 5, 4.6, 4.3, 4]
len(output_array) => 10

Is there something like that, in Numpy for example?

I have a prototype of this function that uses dividing input array into pairs ([0,2], [2,5], [5,8]) and filling "spaces" between with np.linspace() but it don't work well: https://onecompiler.com/python/3xwcy3y7d

def do_something(input_array, output_length):

    import math
    import numpy as np

    output = []

    in_between_steps = math.ceil(output_length/len(input_array))

    prev_num = None

    for num in input_array:
        if prev_num is not None:
            for in_num in np.linspace(start=prev_num, stop=num, num=in_between_steps, endpoint=False):
                output.append(in_num)
        prev_num = num
    
    output.append(input_array[len(input_array)-1]) # manually add last item

    return output

How it works:

input_array = [1, 2, 5, 4]
print(len(do_something(input_array, output_length=10))) # result: 10 OK
print(len(do_something(input_array, output_length=20))) # result: 16 NOT OK
print(len(do_something(input_array, output_length=200))) # result: 151 NOT OK

I have an array [1, 2, 5, 4] and I need to "expand" a number of items in it but preserve the "shape":

can you explain by what logic did you get that output array? (in your question not comments) — Matiiss
– Matiiss, Commented Mar 17, 2022 at 10:31

Kevin · Accepted Answer · 2022-03-17 12:31:23Z

3

There is numpy.interp which might be what you are looking for.

import numpy as np

points = np.arange(4)
values = np.array([1,2,5,4])
x = np.linspace(0, 3, num=10)
np.interp(x, points, values)

output:

array([1.        , 1.33333333, 1.66666667, 2.        , 3.        ,
       4.        , 5.        , 4.66666667, 4.33333333, 4.        ])

answered Mar 17, 2022 at 12:31

Kevin

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2 Comments

rotten77 Over a year ago

Thanks a lot! With some arrays, the result is not as I expected - some values from the input array are missing or replaced (e.g. there is "4.8888" instead of "5"). But it is sufficient for my purposes.

Kevin Over a year ago

@rotten77 Not sure, the length of x might be an odd number which can cause discrepancy. Maybe try setting the endpoint=False keyword for np.linspace.

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