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hello-algo/codes/python/chapter_heap/my_heap.py

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"""
File: my_heap.py
Created Time: 2023-02-23
Author: krahets (krahets@163.com)
"""
import sys
from pathlib import Path
sys.path.append(str(Path(__file__).parent.parent))
from modules import print_heap
class MaxHeap:
"""大顶堆"""
def __init__(self, nums: list[int]):
"""构造方法,根据输入列表建堆"""
# 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:
"""获取左子节点的索引"""
return 2 * i + 1
def right(self, i: int) -> int:
"""获取右子节点的索引"""
return 2 * i + 2
def parent(self, i: int) -> int:
"""获取父节点的索引"""
return (i - 1) // 2 # 向下整除
def swap(self, i: int, j: int):
"""交换元素"""
self.max_heap[i], self.max_heap[j] = self.max_heap[j], self.max_heap[i]
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“节点无须修复”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
if self.is_empty():
raise IndexError("堆为空")
# 交换根节点与最右叶节点(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,则无须继续堆化,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}")