如何減少執行此三元組計數 function 所需的復雜性/時間？

Question

目前想知道如何降低這個三元組計數 function 的復雜性/時間？

這個解決方案有效，但是傳遞HackerRank太慢了

def count_triplets(arr, r):
    left_map = {}
    right_map = {}
    for item in arr:
        right_map[item] = arr.count(item)  # store frequency of occurences of each item.

    count = 0
    for i in range(0, len(arr)):
        mid_term = arr[i]
        c1 = 0
        c3 = 0
        right_map[mid_term] -= 1
        left_term = mid_term / r
        if left_term in left_map and mid_term % r == 0:
            c1 = left_map.get(left_term)

        right_term = mid_term * r
        if right_term in right_map:
            c3 = right_map.get(right_term)

        count += c1 * c3

        if mid_term in left_map:
            left_map[mid_term] += 1
        else: 
            left_map[mid_term] = 1

    return count


if __name__ == '__main__':
    r = 3
    arr = [1,3,9,9,9,27,81]  # returns 9 as solution
    # arr = [1,3,9,9,27,81] # returns 6 as solution
    result = count_triplets(arr, r)
    print("result = ", result)

Answer 1

這段代碼：

    right_map = {}
    for item in arr:
        right_map[item] = arr.count(item)  # store frequency of occurences of each item.

是 O(n^2) 復雜度，因為arr.count本身是 O(n)，這可能是你的問題。 您可以使用Counter計算O(n)中的所有項目，這通常也有助於簡化您的代碼：

from collections import Counter


def count_triplets(arr, r):
    left_map = Counter()
    right_map = Counter(arr)

    count = 0
    for mid_term in arr:
        right_map[mid_term] -= 1
        if mid_term % r == 0:
            left_term = mid_term / r
            c1 = left_map[left_term]
        else:
            c1 = 0

        right_term = mid_term * r
        c3 = right_map[right_term]

        count += c1 * c3
        left_map[mid_term] += 1

    return count


def test():
    r = 3
    assert count_triplets([1, 3, 9, 9, 9, 27, 81], r) == 9
    assert count_triplets([1, 3, 9, 9, 27, 81], r) == 6


if __name__ == '__main__':
    test()