[Python: Downsample] #downsample #matlab #itertools

downsample.py

import itertools

def downsample(x, n, phase=0, roll=False):
    """
    Downsampling compatible with Matlab's implementation, plus an
    additonal argument of roll to allow rolling the end of the iterable
    into the beginning when phase is greater than 0.
    
    Args:
        x: iterable to be downsampled
        n: downsampling factor
        phase: offset start(default: 0)
        roll: whether to roll x
    Return:
        list containing the downsampled iterable
    """

    if not isinstance(phase, int):
        raise ValueError("phase must be an integer")
    if not isinstance(n, int):
        raise ValueError("n must be an integer")
    if roll:
        if phase == 0:
            raise ValueError("phase must be set to enable roll")
        elif phase < 0:
            raise ValueError("phase must be a positve offset value")
        x = itertools.chain(x, x[:phase])
    y = itertools.islice(x, phase, None, n)
    return list(y)

downsample.pyi

from typing import *


def downsample(
    x: Iterable[Any], n: int, phase: int = ..., roll: bool = ...
) -> Iterable[Any]: ...

test.py

import unittest
import math
import itertools
form downsample import downsample

class TestDownsample(unittest.TestCase):
    def test_downsample(self):
        n = 3
        p = 1
        r = True
        a = [(x*10)-3 for x in range(17)]

        b1 = downsample(a, n, phase=p, roll=r)

        if r:
            i = [0, 1, 0]*(math.ceil(len(a)/n))
        else:
            i = [0, 1, 0]*(len(a)//n)
        b2 = list(itertools.compress(a, i))
        self.assertEqual(b1, b2)