給衣服“貼上”NFC:揮下袖子就能安全支付,有效距離達 1.2 米
阿新 • • 發佈:2021-12-13
快排
import random from typing import List class QuickSortMethod: def quick_sort(self, nums): self.quick_sort_help(nums, 0, len(nums) - 1) return nums def quick_sort_help(self, nums, left, right): if left >= right: return nums if left < right: idx = random.randint(left, right) pivot = nums[idx] nums[idx], nums[left] = nums[left], nums[idx] i = left j = right while i < j: while i < j and nums[j] > pivot: j -= 1 nums[i] = nums[j] while i < j and nums[i] <= pivot: i += 1 nums[j] = nums[i] nums[i] = pivot self.quick_sort_help(nums, left, i - 1) self.quick_sort_help(nums, i + 1, right) return nums
歸併排序
class MergeSolution: def merge_sort(self, nums, l, r): if l == r: return mid = (l + r) // 2 self.merge_sort(nums, l, mid) self.merge_sort(nums, mid + 1, r) tmp = [] i, j = l, mid + 1 while i <= mid or j <= r: if i > mid or (j <= r and nums[j] < nums[i]): tmp.append(nums[j]) j += 1 else: tmp.append(nums[i]) i += 1 nums[l: r + 1] = tmp def sortArray(self, nums: List[int]) -> List[int]: self.merge_sort(nums, 0, len(nums) - 1) return nums
堆排序
class HeapSort: def sortArray(self, nums): self.heap_sort(nums) return nums def heap_sort(self, nums): self.heap_init(nums) for i in range(len(nums) - 1, -1, -1): nums[i], nums[0] = nums[0], nums[i] self.adjust_heap_down(nums, i - 1, 0) def heap_init(self, nums): n = len(nums) - 1 for i in range(n, -1, -1): self.adjust_heap_down(nums, n, i) def adjust_heap_down(self, nums, heap_size, idx): left = 2 * idx + 1 while left <= heap_size: child_idx = left right = left + 1 if right <= heap_size and nums[right] > nums[left]: child_idx = right if nums[child_idx] <= nums[idx]: break nums[idx], nums[child_idx] = nums[child_idx], nums[idx] idx = child_idx left = 2 * idx + 1
from collections import Counter
class Solution2:
def topKFrequent(self, nums: List[int], k: int) -> List[int]:
def site_up(arr, idx):
parent = (idx - 1) // 2
while parent >= 0:
if arr[parent][1] > arr[idx][1]:
arr[idx], arr[parent] = arr[parent], arr[idx]
idx = parent
parent = (idx - 1) // 2
else:
break
def site_down(arr, idx, size):
left_child = idx * 2 + 1
while left_child <= size:
child = left_child
right_child = left_child + 1
if right_child <= size and arr[right_child][1] < arr[left_child][1]:
child = right_child
if arr[child][1] < arr[idx][1]:
arr[idx], arr[child] = arr[child], arr[idx]
idx = child
left_child = 2 * idx + 1
else:
break
stat = Counter(nums)
stat = list(stat.items())
heap = []
for i in range(k):
heap.append(stat[i])
site_up(arr=heap, idx=len(heap) - 1)
for i in range(k, len(stat)):
if stat[i][1] > heap[0][1]:
heap[0] = stat[i]
site_down(heap, 0, k - 1)
return [item[0] for item in heap[:k]]
class Solution3:
def frequencySort(self, s: str) -> str:
c = Counter(s)
res = dict(sorted(c.items(), key=lambda x: -x[1]))
return ''.join(k * v for k, v in res.items())
import collections
import heapq
class Solution4:
def isPossible(self, nums: List[int]) -> bool:
mp = collections.defaultdict(list)
print(mp)
for x in nums:
print("mp:", mp.items())
if mp.get(x - 1):
queue = mp.get(x - 1)
prevLength = heapq.heappop(queue)
heapq.heappush(mp[x], prevLength + 1)
else:
heapq.heappush(mp[x], 1)
return not any(queue and queue[0] < 3 for queue in mp.values())
if __name__ == "__main__":
s = Solution4()
# nums = [5, -3, 9, 1, 7, 7, 9, 10, 2, 2, 10, 10, 3, -1, 3, 7, -9, -1, 3, 3]
# k = 3
s.isPossible([1, 2, 3, 3, 4, 4, 5, 5])