""" File: my_heap.py Created Time: 2023-02-23 Author: Krahets (krahets@163.com) """ import sys, os.path as osp sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__)))) from modules import * class MaxHeap: """ 大顶堆 """ def __init__(self, nums: list[int]): """ 构造方法 """ # 将列表元素原封不动添加进堆 self.max_heap = nums # 堆化除叶节点以外的其他所有节点 for i in range(self.parent(self.size() - 1), -1, -1): self.sift_down(i) def left(self, i: int) -> int: """ 获取左子节点索引 """ return 2 * i + 1 def right(self, i: int) -> int: """ 获取右子节点索引 """ return 2 * i + 2 def parent(self, i: int) -> int: """ 获取父节点索引 """ return (i - 1) // 2 # 向下整除 def swap(self, i: int, j: int): """ 交换元素 """ a, b = self.max_heap[i], self.max_heap[j] self.max_heap[i], self.max_heap[j] = b, a def size(self) -> int: """ 获取堆大小 """ return len(self.max_heap) def is_empty(self) -> bool: """ 判断堆是否为空 """ return self.size() == 0 def peek(self) -> int: """ 访问堆顶元素 """ return self.max_heap[0] def push(self, val: int): """ 元素入堆 """ # 添加节点 self.max_heap.append(val) # 从底至顶堆化 self.sift_up(self.size() - 1) def sift_up(self, i: int): """ 从节点 i 开始,从底至顶堆化 """ while True: # 获取节点 i 的父节点 p = self.parent(i) # 当“越过根节点”或“节点无需修复”时,结束堆化 if p < 0 or self.max_heap[i] <= self.max_heap[p]: break # 交换两节点 self.swap(i, p) # 循环向上堆化 i = p def pop(self) -> int: """ 元素出堆 """ # 判空处理 assert not self.is_empty() # 交换根节点与最右叶节点(即交换首元素与尾元素) self.swap(0, self.size() - 1) # 删除节点 val = self.max_heap.pop() # 从顶至底堆化 self.sift_down(0) # 返回堆顶元素 return val def sift_down(self, i: int): """ 从节点 i 开始,从顶至底堆化 """ while True: # 判断节点 i, l, r 中值最大的节点,记为 ma l, r, ma = self.left(i), self.right(i), i if l < self.size() and self.max_heap[l] > self.max_heap[ma]: ma = l if r < self.size() and self.max_heap[r] > self.max_heap[ma]: ma = r # 若节点 i 最大或索引 l, r 越界,则无需继续堆化,跳出 if ma == i: break # 交换两节点 self.swap(i, ma) # 循环向下堆化 i = ma def print(self): """ 打印堆(二叉树) """ print_heap(self.max_heap) """ Driver Code """ if __name__ == "__main__": # 初始化大顶堆 max_heap = MaxHeap([9, 8, 6, 6, 7, 5, 2, 1, 4, 3, 6, 2]) print("\n输入列表并建堆后") max_heap.print() # 获取堆顶元素 peek = max_heap.peek() print(f"\n堆顶元素为 {peek}") # 元素入堆 val = 7 max_heap.push(val) print(f"\n元素 {val} 入堆后") max_heap.print() # 堆顶元素出堆 peek = max_heap.pop() print(f"\n堆顶元素 {peek} 出堆后") max_heap.print() # 获取堆大小 size = max_heap.size() print(f"\n堆元素数量为 {size}") # 判断堆是否为空 is_empty = max_heap.is_empty() print(f"\n堆是否为空 {is_empty}")