牛客网 在线编程 数据流中的中位数

题目描述

如何得到一个数据流中的中位数？如果从数据流中读出奇数个数值，那么中位数就是所有数值排序之后位于中间的数值。如果从数据流中读出偶数个数值，那么中位数就是所有数值排序之后中间两个数的平均值。我们使用Insert()方法读取数据流，使用GetMedian()方法获取当前读取数据的中位数。

	
import java.util.*;
	public class Solution {

		public ArrayList<Integer> list = new ArrayList<>();

		public Solution() {
			// TODO Auto-generated constructor stub
		}

		public void Insert(Integer num) {
			int size = list.size();
			list.add(num);
			int index = bs(num);
			for (int i = size-1; i >= index; i--)
				swap(i+1, i);
		}

		public Double GetMedian() {
			int size = list.size() - 1;
			if (size % 2 == 1)
				return Double.valueOf((list.get(size / 2) + list.get(size / 2 + 1)) / 2.0);
			else
				return Double.valueOf(list.get(size / 2));
		}

		public int bs(int val) {
			int l = 0;
			int r = list.size() - 1;
			int mid = 0;
			while (l <= r) {
				mid = (l + r) >> 1;
				if (list.get(mid) <= val) {
					l = mid + 1;
				} else {
					r = mid - 1;
				}
			}
			return l;
		}

		public void swap(int i, int j) {
			int tmp = list.get(i);
			list.set(i, list.get(j));
			list.set(j, tmp);
		}

	}

用插入排序重新排序。这种做法比较垃圾。重新写了一个用优先级队列的方法。一个大根堆和一个小根堆

	
import java.util.*;
	public class Solution {

	public PriorityQueue<Integer> maxHeap;
	public PriorityQueue<Integer> minHeap;

	public Solution() {
		maxHeap = new PriorityQueue<Integer>(new Comparator<Integer>() {
			@Override
			public int compare(Integer o1, Integer o2) {
				return o2 - o1;
			}
		});

		minHeap = new PriorityQueue<>(new Comparator<Integer>() {
			@Override
			public int compare(Integer o1, Integer o2) {
				return o1 - o2;
			}
		});
	}

	public void Insert(Integer num) {
		if (this.maxHeap.isEmpty() || num <= this.maxHeap.peek()) {
			this.maxHeap.add(num);
		} else {
			this.minHeap.add(num);
		}
		while (Math.abs(this.maxHeap.size() - this.minHeap.size()) > 1) {
			if (this.maxHeap.size() > this.minHeap.size()) {
				this.minHeap.add(this.maxHeap.poll());
			} else {
				this.maxHeap.add(this.minHeap.poll());
			}
		}
	}

	public Double GetMedian() {
		int maxsize = this.maxHeap.size();
		int minsize = this.minHeap.size();
		if ((minsize + maxsize) % 2 == 0) {
			return Double.valueOf((this.maxHeap.peek() + this.minHeap.peek()) / 2.0);
		} else {
			if (maxsize > minsize) {
				return Double.valueOf(this.maxHeap.peek());
			} else {
				return Double.valueOf(this.minHeap.peek());
			}
		}
	}

	}