LeetCode-in-All

295. Find Median from Data Stream

Hard

The median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value and the median is the mean of the two middle values.

Implement the MedianFinder class:

Example 1:

Input

["MedianFinder", "addNum", "addNum", "findMedian", "addNum", "findMedian"]
[[], [1], [2], [], [3], []]

Output: [null, null, null, 1.5, null, 2.0]

Explanation:

MedianFinder medianFinder = new MedianFinder();
medianFinder.addNum(1); // arr = [1]
medianFinder.addNum(2); // arr = [1, 2]
medianFinder.findMedian(); // return 1.5 (i.e., (1 + 2) / 2)
medianFinder.addNum(3); // arr[1, 2, 3]
medianFinder.findMedian(); // return 2.0 

Constraints:

Follow up:

Solution

import HeapModule

class MedianFinder {
    var leftHeap: Heap<Int>
    var rightHeap: Heap<Int>

    init() {
        leftHeap = []
        rightHeap = []
    }
    
    func addNum(_ num: Int) {
        leftHeap.insert(num)
        while let rightMin = rightHeap.min, rightMin < leftHeap.max! {
            leftHeap.insert(rightHeap.removeMin())
            rightHeap.insert(leftHeap.removeMax())
        }
        let mid = (leftHeap.count + rightHeap.count) / 2
        while rightHeap.count < mid {
            rightHeap.insert(leftHeap.removeMax())
        }
    }
    
    func findMedian() -> Double {
        let count = leftHeap.count + rightHeap.count
        if count % 2 == 0 {
            return Double(leftHeap.max! + rightHeap.min!) / 2
        } else {
            return Double(leftHeap.max!)
        }
    }
}

/*
 * Your MedianFinder object will be instantiated and called as such:
 * let obj = MedianFinder()
 * obj.addNum(num)
 * let ret_2: Double = obj.findMedian()
 */