You can only delete the first element in the heap, after which it's "re-sorted". Heaps "re-sort" themselves after an element is added or removed so that the smallest element is always in the first position. Note: This in no way means that heaps are sorted arrays. The fact that ever...
in range(last_root,-1,-1): buildHeap(sortList, lenS, i) # 取出堆顶元素,进行排序 for end in range(lenS-1, 0, -1): sortList[0], sortList[end] = sortList[end], sortList[0] # end每次都会减1,所以就自动排除后面已经排序好的数据了 buildHeap(sortList, end, 0) return sortList ...
importheapq defheap_sort(arr):heapq.heapify(arr)sorted_arr=[heapq.heappop(arr)for_inrange(len(arr))]returnsorted_arr # 示例 unsorted_array=[3,1,4,1,5,9,2,6,5,3,5]sorted_array=heap_sort(unsorted_array)print("Unsorted Array:",unsorted_array)print("Sorted Array:",sorted_array) 总结...
第一个示例:heap= [] heapq.heappush(heap,i)heap_sort(temp_tab)指纹: 第二个示例 浏览4提问于2015-04-26得票数2 回答已采纳 1回答 如何将堆分成两个子堆,并以堆排序为目的? 、、、 我将使用一些auxiliar函数在python中创建一个HeapSort函数。我正在尝试按照我的图书说明,并使用一些函数(如fixHeap )来...
# 从最后一个非叶子点进行 SiftDown for n in range((len(data) - 1) >> 1, -1, -1): sift_down(data, n, len(data)) def heap_sort(list data not None, bint reverse=False): # 首先将其整理成堆的形状 heapify(data) # 然后挨个出数 cdef Py_ssize_t i for i in range(len(data) ...
堆排序(HeapSort) 堆排序 详见大话数据结构p3961 // 堆排序分为两个步骤: 2 // 第一:将我们现有的序列构造成为大顶堆的形式; 自下而上,从右向左 3 // 第二:正式进行排序; 4 5 //堆排序的时间复杂度为 O(nlogn) 6 7 8
400007 function calls in 0.071 seconds Ordered by: internal time ncalls tottime percall cumtime percall filename:lineno(function) 1 0.025 0.025 0.071 0.071 t.py:11(sort2) 1 0.018 0.018 0.018 0.018 {method 'sort' of 'list' objects} 100000 0.011 0.000 0.019 0.000 random.py:172...
sort_heap(myvec.begin(), myvec.end()); for(std::vector<int>::iterator it = myvec.begin();it != myvec.end();it++){ std::cout<<*it<<" ,"; } std::cout<<"\n"<<"now the example is end..."<<std::endl; return 0; } 标签: C++ , heap 好文要顶 关注我 收藏该文 微...
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def heap_sort(self) -> None: size = self.heap_size for j in range(size - 1, 0, -1): self.h[0], self.h[j] = self.h[j], self.h[0] self.heap_size -= 1 self.max_heapify(0) self.heap_size = size if __name__ == "__main__": import doctest # run ...