《算法导论》第六章优先队列 python 实现

优先队列是堆排序的一个应用 ：

支持的操作：返回最大值，去掉并返回最大值，插入元素

def max_heapify(A, i, heap_size):
    l = 2 * i
    r = 2 * i + 1
    if l <= heap_size and A[l-1] > A[i-1]:
        largest = l
    else:
        largest = i
    if r <= heap_size and A[r-1] > A[largest-1]:
        largest = r
    if largest == i:
        return
    else:
        A[largest-1], A[i-1] = A[i-1], A[largest-1]
        max_heapify(A, largest, heap_size)

def heap_maximum(A):  # 返回最大值堆顶元素
    return A[0]

def heap_extract_max(A):  # 去掉并返回具有最大关键字的元素
    n = len(A)
    if n < 0:
        return "heap underflow"
    max = A[0]
    A[0] = A[n-1]
    n = n-1
    max_heapify(A, 0, n)
    return max

def heap_increase_key(A, i, key):  # 实现插入操作
    if key < A[i-1]:
        A[i - 1] = key
        return "new key is smaller than current key"
    A[i-1] = key
    while i > 1 and A[int(i/2)-1] < A[i-1]:
        A[i-1], A[int(i/2)-1] = A[int(i/2)-1], A[i-1]
        i = int(i/2)

def max_heap_insert(A, key):
    heap_size = len(A)+1
    A.append(float("-inf"))
    heap_increase_key(A, heap_size, key)

if __name__ == "__main__":
    # list = [16, 14, 10, 8, 7, 9, 3, 2, 4, 1]
    # print list
    # heap_increase_key(list, 9, 15)
    # print list
    list = [15, 13, 9, 5, 12, 8, 7, 4, 0, 6, 2, 1]
    print list
    max_heap_insert(list, 10)
    print list