best-meeting-point.py

# Time:  O(m * n)
# Space: O(m + n)

from random import randint

class Solution(object):
    def minTotalDistance(self, grid):
        """
        :type grid: List[List[int]]
        :rtype: int
        """
        x = [i for i, row in enumerate(grid) for v in row if v == 1]
        y = [j for row in grid for j, v in enumerate(row) if v == 1]
        mid_x = self.findKthLargest(x, len(x) / 2 + 1)
        mid_y = self.findKthLargest(y, len(y) / 2 + 1)
        
        return sum([abs(mid_x-i) + abs(mid_y-j) \
                   for i, row in enumerate(grid) for j, v in enumerate(row) if v == 1])
    
    def findKthLargest(self, nums, k):
        left, right = 0, len(nums) - 1
        while left <= right:
            pivot_idx = randint(left, right)
            new_pivot_idx = self.PartitionAroundPivot(left, right, pivot_idx, nums)
            if new_pivot_idx == k - 1:
                return nums[new_pivot_idx]
            elif new_pivot_idx > k - 1:
                right = new_pivot_idx - 1
            else:  # new_pivot_idx < k - 1.
                left = new_pivot_idx + 1
        
    def PartitionAroundPivot(self, left, right, pivot_idx, nums):
        pivot_value = nums[pivot_idx]
        new_pivot_idx = left
        nums[pivot_idx], nums[right] = nums[right], nums[pivot_idx]
        for i in xrange(left, right):
            if nums[i] > pivot_value:
                nums[i], nums[new_pivot_idx] =  nums[new_pivot_idx], nums[i]
                new_pivot_idx += 1
            
        nums[right], nums[new_pivot_idx] = nums[new_pivot_idx], nums[right]
        return new_pivot_idx