题目:

题解:
class Solution:
def topKFrequent(self, nums: List[int], k: int) -> List[int]:
def sift_down(arr, root, k):
"""下沉log(k),如果新的根节点>子节点就一直下沉"""
val = arr[root] # 用类似插入排序的赋值交换
while root<<1 < k:
child = root << 1
# 选取左右孩子中小的与父节点交换
if child|1 < k and arr[child|1][1] < arr[child][1]:
child |= 1
# 如果子节点<新节点,交换,如果已经有序break
if arr[child][1] < val[1]:
arr[root] = arr[child]
root = child
else:
break
arr[root] = val
def sift_up(arr, child):
"""上浮log(k),如果新加入的节点<父节点就一直上浮"""
val = arr[child]
while child>>1 > 0 and val[1] < arr[child>>1][1]:
arr[child] = arr[child>>1]
child >>= 1
arr[child] = val
stat = collections.Counter(nums)
stat = list(stat.items())
heap = [(0,0)]
# 构建规模为k+1的堆,新元素加入堆尾,上浮
for i in range(k):
heap.append(stat[i])
sift_up(heap, len(heap)-1)
# 维护规模为k+1的堆,如果新元素大于堆顶,入堆,并下沉
for i in range(k, len(stat)):
if stat[i][1] > heap[1][1]:
heap[1] = stat[i]
sift_down(heap, 1, k+1)
return [item[0] for item in heap[1:]]
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