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63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
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"""
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File: heap.py
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Created Time: 2023-02-23
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Author: Krahets (krahets@163.com)
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"""
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import sys, os.path as osp
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sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
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from include import *
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def test_push(heap, val, flag=1):
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heapq.heappush(heap, flag * val) # 元素入堆
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print(f"\n元素 {val} 入堆后")
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print_heap([flag * val for val in heap])
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def test_pop(heap, flag=1):
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val = flag * heapq.heappop(heap) # 堆顶元素出堆
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print(f"\n堆顶元素 {val} 出堆后")
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print_heap([flag * val for val in heap])
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if __name__ == "__main__":
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# 初始化小顶堆
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min_heap, flag = [], 1
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# 初始化大顶堆
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max_heap, flag = [], -1
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print("\n以下测试样例为大顶堆")
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# Python 的 heapq 模块默认实现小顶堆
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# 考虑将“元素取负”后再入堆，这样就可以将大小关系颠倒，从而实现大顶堆
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# 在本示例中，flag = 1 时对应小顶堆，flag = -1 时对应大顶堆
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""" 元素入堆 """
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test_push(max_heap, 1, flag)
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test_push(max_heap, 3, flag)
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test_push(max_heap, 2, flag)
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test_push(max_heap, 5, flag)
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test_push(max_heap, 4, flag)
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""" 获取堆顶元素 """
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peek = flag * max_heap[0]
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print(f"\n堆顶元素为 {peek}")
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""" 堆顶元素出堆 """
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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""" 获取堆大小 """
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size = len(max_heap)
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print(f"\n堆元素数量为 {size}")
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""" 判断堆是否为空 """
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is_empty = not max_heap
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print(f"\n堆是否为空 {is_empty}")
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""" 输入列表并建堆 """
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# 时间复杂度为 O(n) ，而非 O(nlogn)
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min_heap = [1, 3, 2, 5, 4]
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heapq.heapify(min_heap)
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print("\n输入列表并建立小顶堆后")
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print_heap(min_heap)
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