Given an array nums, we call (i, j) an important reverse pair if i < j and nums[i] > 2*nums[j].

You need to return the number of important reverse pairs in the given array.

Example1:

Input: [1,3,2,3,1]
Output: 2

Example2:

Input: [2,4,3,5,1]
Output: 3

Note:

1. The length of the given array will not exceed 50,000.
2. All the numbers in the input array are in the range of 32-bit integer.

# Solution 1: Using Binary Index Tree, which has O(nlogn) time complexity.

class BIT():
    def __init__(self, n):
        self.n = n + 1
        self.sums = [0] * self.n

    def update(self, i, delta):
        while i < self.n:
            self.sums[i] += delta
            i += i & (-i)

    def query(self, i):
        res = 0
        while i > 0:
            res += self.sums[i]
            i -= i & (-i)
        return res
    
class Solution:
    def reversePairs(self, nums: List[int]) -> int:
        sorted_nums = sorted(list(set(nums + [x * 2 for x in nums])))
        tree = BIT(len(sorted_nums))

        res = 0
        ranks = {}

        for i, n in enumerate(sorted_nums):
            ranks[n] = i + 1

        for n in nums[::-1]:
            res += tree.query(ranks[n] - 1)
            tree.update(ranks[n * 2], 1)

        return res

# Solution 2: At this time, we are going to use bisect. Got inspiration from Merge Sort (Divide and Conquer).

class Solution:
    def reversePairs(self, nums: List[int]) -> int:
        ranks = list()
        ans = 0

        for n in reverse(nums):
            ans += bisect.bisect_left(ranks, n)
            bisect.insort_left(ranks, n * 2)

        return ans