How to round floats to scaled integers?

Question

to further explain my title: I have an array of floats which I want to round, HOWEVER, I want to round the numbers to a number that isn't the closest integer. For example, let's say I want the numbers to be rounded to the nearest integer that is a multiple of 2. This is what I have:

Temp = np.around(data,0)

with data being an array of floats. The numbers are rounded to the closest integer, but I want them to be rounded to the closest multiple of 2. My goal:

0.9 -> 0

1.1 -> 2

etc.

Thanks!

Answer 1

A multiple of two is straightforward:

x = np.array([0.9, 1.1, 10.2, 7.4])

2*np.round(x/2)   # array([  0.,   2.,  10.,   8.])

But there's not a universal approach to this. For example there's no obvoius "round to the nearest Fibonacci number". Consider the formula for multiple of 2 as, given a function f(x)=2*x : 1) first apply the inverse of f (divide in this case), 2) then round , 3) then apply f to result. For this to work, f must exist, have an inverse, and the result must also be an int ; so it only works for a few functions.

Answer 2

Following is one way of doing it:

import math

data = [0.9, 1.1, 10.2, 7.4]

rounded_numbers = []

for num in data:

    rounded_up_num = math.ceil(num)

    if rounded_up_num % 2 == 0:
        rounded_num = rounded_up_num
    else:
        rounded_num = math.floor(num)

    rounded_numbers.append(int(rounded_num))

print rounded_numbers # [0, 2, 10, 8]