295. Find Median from Data Stream

package LeetCode_295

import java.util.*

/**
 * 295. Find Median from Data Stream
 * https://leetcode.com/problems/find-median-from-data-stream/description/
 *
 * Median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle value.

For example,
[2,3,4], the median is 3
[2,3], the median is (2 + 3) / 2 = 2.5
Design a data structure that supports the following two operations:
void addNum(int num) - Add a integer number from the data stream to the data structure.
double findMedian() - Return the median of all elements so far.

Example:
addNum(1)
addNum(2)
findMedian() -> 1.5
addNum(3)
findMedian() -> 2

Follow up:
If all integer numbers from the stream are between 0 and 100, how would you optimize it?
If 99% of all integer numbers from the stream are between 0 and 100, how would you optimize it?
 * */


/*
* solution: Tow PriorityQueue, minHeap and maxHeap, Time complexity: O(nlogn), Space complexity:O(1)
* get element from PriorityQueu is O(1),
* add new element in PriorityQueu is O(logn)
* */
class MedianFinder() {

    /** initialize your data structure here. */
    //change to max heap, because PriorityQueue in kotlin default is Min Heap
    val leftHeap = PriorityQueue<Int>{ a, b -> b - a }
    //min heap
    val rightHeap = PriorityQueue<Int>()

    fun addNum(num: Int) {
        if (leftHeap.isEmpty() || num < leftHeap.peek()) {
            leftHeap.offer(num)
        } else {
            rightHeap.offer(num)
        }
        //balance minHeap and maxHeap
        //the size of minHeap just can larger than the size fo maxHeap by 1
        if (leftHeap.size < rightHeap.size) {
            leftHeap.offer(rightHeap.poll())
        } else if (leftHeap.size - rightHeap.size == 2) {
            rightHeap.offer(leftHeap.poll())
        }
    }

    fun findMedian(): Double {
        if (leftHeap.size>rightHeap.size){
            return leftHeap.peek().toDouble()
        } else {
            val left = leftHeap.peek().toDouble()
            val right = rightHeap.peek().toDouble()
            return (left+right)/2
        }
    }
}
/**
 * Your MedianFinder object will be instantiated and called as such:
 * var obj = MedianFinder()
 * obj.addNum(num)
 * var param_2 = obj.findMedian()
 */