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feat: add python and java solutions to lcci question: 17.20.Continuous Median
https://lc.netlify.app/#/lcci/17.20.Continuous%20Median/README
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‎lcci/17.20.Continuous Median/README.md

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Original file line numberDiff line numberDiff line change
@@ -31,20 +31,75 @@ findMedian() -> 2
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## 解法
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<!-- 这里可写通用的实现逻辑 -->
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- 创建大根堆、小根堆，其中：大根堆存放较小的一半元素，小根堆存放较大的一半元素。
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- 添加元素时，若两堆元素个数相等，放入小根堆（使得小根堆个数多1）；若不等，放入大根堆（使得大小根堆元素个数相等）
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- 取中位数时，若两堆元素个数相等，取两堆顶求平均值；若不等，取小根堆堆顶。
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### Python3
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```python
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class MedianFinder:
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def __init__(self):
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"""
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initialize your data structure here.
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"""
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self.max_heap = []
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self.min_heap = []
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def addNum(self, num: int) -> None:
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if len(self.max_heap) == len(self.min_heap):
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heapq.heappush(self.min_heap, -heapq.heappushpop(self.max_heap, -num))
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else:
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heapq.heappush(self.max_heap, -heapq.heappushpop(self.min_heap, num))
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def findMedian(self) -> float:
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return (-self.max_heap[0] + self.min_heap[0]) / 2 if len(self.max_heap) == len(self.min_heap) else self.min_heap[0]
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# Your MedianFinder object will be instantiated and called as such:
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# obj = MedianFinder()
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# obj.addNum(num)
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# param_2 = obj.findMedian()
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```
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### Java
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```java
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class MedianFinder {
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private Queue<Integer> minHeap;
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private Queue<Integer> maxHeap;
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/** initialize your data structure here. */
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public MedianFinder() {
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minHeap = new PriorityQueue<>();
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maxHeap = new PriorityQueue<>((a, b) -> b - a);
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}
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public void addNum(int num) {
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if (minHeap.size() == maxHeap.size()) {
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maxHeap.offer(num);
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minHeap.offer(maxHeap.poll());
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} else {
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minHeap.offer(num);
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maxHeap.offer(minHeap.poll());
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}
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}
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public double findMedian() {
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return minHeap.size() == maxHeap.size() ? (minHeap.peek() + maxHeap.peek()) / 2.0 : minHeap.peek();
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}
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}
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/**
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* Your MedianFinder object will be instantiated and called as such:
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* MedianFinder obj = new MedianFinder();
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* obj.addNum(num);
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* double param_2 = obj.findMedian();
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*/
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```
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### ...

‎lcci/17.20.Continuous Median/README_EN.md

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Original file line numberDiff line numberDiff line change
@@ -59,13 +59,66 @@ findMedian() -&gt; 2
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### Python3
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```python
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class MedianFinder:
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def __init__(self):
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"""
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initialize your data structure here.
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"""
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self.max_heap = []
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self.min_heap = []
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def addNum(self, num: int) -> None:
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if len(self.max_heap) == len(self.min_heap):
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heapq.heappush(self.min_heap, -heapq.heappushpop(self.max_heap, -num))
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else:
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heapq.heappush(self.max_heap, -heapq.heappushpop(self.min_heap, num))
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def findMedian(self) -> float:
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return (-self.max_heap[0] + self.min_heap[0]) / 2 if len(self.max_heap) == len(self.min_heap) else self.min_heap[0]
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# Your MedianFinder object will be instantiated and called as such:
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# obj = MedianFinder()
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# obj.addNum(num)
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# param_2 = obj.findMedian()
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```
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### Java
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```java
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class MedianFinder {
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private Queue<Integer> minHeap;
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private Queue<Integer> maxHeap;
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/** initialize your data structure here. */
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public MedianFinder() {
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minHeap = new PriorityQueue<>();
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maxHeap = new PriorityQueue<>((a, b) -> b - a);
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}
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public void addNum(int num) {
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if (minHeap.size() == maxHeap.size()) {
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maxHeap.offer(num);
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minHeap.offer(maxHeap.poll());
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} else {
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minHeap.offer(num);
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maxHeap.offer(minHeap.poll());
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}
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}
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public double findMedian() {
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return minHeap.size() == maxHeap.size() ? (minHeap.peek() + maxHeap.peek()) / 2.0 : minHeap.peek();
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}
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}
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/**
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* Your MedianFinder object will be instantiated and called as such:
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* MedianFinder obj = new MedianFinder();
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* obj.addNum(num);
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* double param_2 = obj.findMedian();
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*/
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```
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### ...

‎lcci/17.20.Continuous Median/Solution.java

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,31 @@
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class MedianFinder {
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private Queue<Integer> minHeap;
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private Queue<Integer> maxHeap;
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/** initialize your data structure here. */
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public MedianFinder() {
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minHeap = new PriorityQueue<>();
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maxHeap = new PriorityQueue<>((a, b) -> b - a);
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}
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public void addNum(int num) {
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if (minHeap.size() == maxHeap.size()) {
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maxHeap.offer(num);
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minHeap.offer(maxHeap.poll());
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} else {
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minHeap.offer(num);
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maxHeap.offer(minHeap.poll());
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}
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}
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public double findMedian() {
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return minHeap.size() == maxHeap.size() ? (minHeap.peek() + maxHeap.peek()) / 2.0 : minHeap.peek();
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}
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}
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/**
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* Your MedianFinder object will be instantiated and called as such:
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* MedianFinder obj = new MedianFinder();
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* obj.addNum(num);
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* double param_2 = obj.findMedian();
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*/

‎lcci/17.20.Continuous Median/Solution.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,24 @@
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class MedianFinder:
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def __init__(self):
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"""
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initialize your data structure here.
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"""
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self.max_heap = []
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self.min_heap = []
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def addNum(self, num: int) -> None:
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if len(self.max_heap) == len(self.min_heap):
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heapq.heappush(self.min_heap, -heapq.heappushpop(self.max_heap, -num))
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else:
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heapq.heappush(self.max_heap, -heapq.heappushpop(self.min_heap, num))
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def findMedian(self) -> float:
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return (-self.max_heap[0] + self.min_heap[0]) / 2 if len(self.max_heap) == len(self.min_heap) else self.min_heap[0]
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# Your MedianFinder object will be instantiated and called as such:
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# obj = MedianFinder()
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# obj.addNum(num)
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# param_2 = obj.findMedian()

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