排序和二分查找(Python)

诈胡艺术 2020-11-13 03:19:55
Python 二分 排序 查找


目录

[排序]

归并排序

快速排序:

插入排序:

冒泡排序

选择排序

相关练习:

[查找]

二分查找:

模糊二分查找:

相关练习


[排序]

归并排序

#归并
def mSort(nums): #分为两个列表,分别排序
if len(nums)<=1:
return nums
else:
m = len(nums)//2
print 'len(nums): ',len(nums)
print 'nums: ',nums
print 'm: ',m
left = mSort(nums[:m])
right = mSort(nums[m:])
ret = merge(left,right)
return ret
def merge(left,right):#合并两个列表
i = 0
j = 0
k = 0
ret =[]
print '--------'
print 'left: ',left
print 'right: ',right
while i<len(left) and j< len(right):
if left[i]<right[j]:
ret.append(left[i])
i += 1
else:
ret.append(right[j])
j += 1
ret += left[i:]
ret += right[j:]
return ret

快速排序:

#快排、
def quickSort(nums):
qSort(nums,0,len(nums)-1)
def qSort(nums,low,high):
if low<high:
pivot = partition(nums,low,high)
qSort(nums,low,pivot-1)#低位排序
qSort(nums,pivot+1,high)#高位排序
def partition(nums,low,high):#枢纽点
pivotkey = nums[low]
while low<high:
while low<high and nums[high]>=pivotkey:
high -= 1
nums[low],nums[high] = nums[high],nums[low]
while low<high and nums[low]<=pivotkey:
low += 1
nums[low],nums[high] = nums[high],nums[low]
return low

插入排序:

#插入排序、
def insertOrder(nums):
if not nums:
return
ret = [nums[0]]
for n in nums[1:]:
print 'for: ',n
print 'ret: ',ret
if n <= ret[0]:
ret.insert(0,n)
continue
i = 1
while i<len(ret):
if n>ret[i-1] and n<=ret[i]:
break
i+=1
ret.insert(i,n)
return ret

冒泡排序

#冒泡、
def paopao(nums):
flag = False
for i in range(len(nums)):
for j in range(len(nums)-1,i,-1):
if nums[j]<nums[j-1]:
flag = True
nums[j],nums[j-1] = nums[j-1],nums[j]
if not flag:
break
return nums

选择排序

#选择、
def selectOrder(nums):
for i in range(len(nums)):
minindex = len(nums)-1
for j in range(len(nums)-1,i-1,-1):
if nums[j]<nums[minindex]:
minindex = j
nums[i],nums[minindex] = nums[minindex],nums[i]
return nums

相关练习:

[滑动窗口最大值]

给定一个数组 nums,有一个大小为 的滑动窗口从数组的最左侧移动到数组的最右侧。你只可以看到在滑动窗口 k 内的数字。滑动窗口每次只向右移动一位。返回滑动窗口最大值。

class Solution(object):
def maxSlidingWindow(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: List[int]
"""
if nums==[] or k==1:
return nums
ret = []
now_max = max(nums[:k])
ret.append(now_max)
for i in range(1,len(nums)-k+1):
if nums[i+k-1] >= now_max:
now_max = nums[i+k-1]
elif nums[i-1]==now_max:
now_max = max(nums[i:i+k])
ret.append(now_max)
return ret

[查找]

二分查找:

#二分查找
def halfSearch(nums,num):
if not nums:
return
if num>nums[-1] or num<nums[0]:
return
if num == nums[0]:
return 0
elif num == nums[-1]:
return len(nums)-1
low = 0
high = len(nums)-1
while low <= high:
medim = (high+low)/2
print 'm: ',medim
if num>nums[medim]:
low = medim+1
elif num < nums[medim]:
high = medim-1
else:
return medim
return

模糊二分查找:

(找到数组中大于等于目标元素的第一个元素的位置)

#模糊二分[大于等于给定值的第一个元素的位置]
def fuzzyHalfSearch(nums,num):
if not nums:
return
if num>nums[-1]:
return
if num <= nums[0]:
return 0
elif num == nums[-1]:
return len(nums)-1
low = 0
high = len(nums)-2
while low <= high:
medim = (high+low)/2
if num>nums[medim] and num<=nums[medim+1]:
return medim+1
elif num > nums[medim+1]:
low = medim+1
elif num <= nums[medim]:
high = medim
return

相关练习

[x 的平方根]

计算并返回 x 的平方根,其中 是非负整数。由于返回类型是整数,结果只保留整数的部分,小数部分将被舍去。

方法1:

class Solution(object):
def mySqrt(self, x):
"""
:type x: int
:rtype: int
"""
if x==0 or x==1:
return x
low =1
high = x-1
ans = 1
while low <= high:
medim = (low+high)/2
if x>medim*medim:
low = medim+1
ans = medim
elif x< medim*medim:
high = medim-1
else:
return medim
return ans

方法2:

牛顿法:https://en.wikipedia.org/wiki/Integer_square_root#Algorithm_using_Newton's_method

class Solution(object):
def mySqrt(self, x):
"""
:type x: int
:rtype: int
"""
if x <= 1:
return x
r = x
while r > x / r:
r = (r + x / r) // 2
return int(r)

 

版权声明
本文为[诈胡艺术]所创,转载请带上原文链接,感谢
https://blog.csdn.net/m0_38019841/article/details/88235655

  1. 利用Python爬虫获取招聘网站职位信息
  2. Using Python crawler to obtain job information of recruitment website
  3. Several highly rated Python libraries arrow, jsonpath, psutil and tenacity are recommended
  4. Python装饰器
  5. Python实现LDAP认证
  6. Python decorator
  7. Implementing LDAP authentication with Python
  8. Vscode configures Python development environment!
  9. In Python, how dare you say you can't log module? ️
  10. 我收藏的有关Python的电子书和资料
  11. python 中 lambda的一些tips
  12. python中字典的一些tips
  13. python 用生成器生成斐波那契数列
  14. python脚本转pyc踩了个坑。。。
  15. My collection of e-books and materials about Python
  16. Some tips of lambda in Python
  17. Some tips of dictionary in Python
  18. Using Python generator to generate Fibonacci sequence
  19. The conversion of Python script to PyC stepped on a pit...
  20. Python游戏开发,pygame模块,Python实现扫雷小游戏
  21. Python game development, pyGame module, python implementation of minesweeping games
  22. Python实用工具,email模块,Python实现邮件远程控制自己电脑
  23. Python utility, email module, python realizes mail remote control of its own computer
  24. 毫无头绪的自学Python,你可能连门槛都摸不到!【最佳学习路线】
  25. Python读取二进制文件代码方法解析
  26. Python字典的实现原理
  27. Without a clue, you may not even touch the threshold【 Best learning route]
  28. Parsing method of Python reading binary file code
  29. Implementation principle of Python dictionary
  30. You must know the function of pandas to parse JSON data - JSON_ normalize()
  31. Python实用案例,私人定制,Python自动化生成爱豆专属2021日历
  32. Python practical case, private customization, python automatic generation of Adu exclusive 2021 calendar
  33. 《Python实例》震惊了,用Python这么简单实现了聊天系统的脏话,广告检测
  34. "Python instance" was shocked and realized the dirty words and advertisement detection of the chat system in Python
  35. Convolutional neural network processing sequence for Python deep learning
  36. Python data structure and algorithm (1) -- enum type enum
  37. 超全大厂算法岗百问百答(推荐系统/机器学习/深度学习/C++/Spark/python)
  38. 【Python进阶】你真的明白NumPy中的ndarray吗?
  39. All questions and answers for algorithm posts of super large factories (recommended system / machine learning / deep learning / C + + / spark / Python)
  40. [advanced Python] do you really understand ndarray in numpy?
  41. 【Python进阶】Python进阶专栏栏主自述:不忘初心,砥砺前行
  42. [advanced Python] Python advanced column main readme: never forget the original intention and forge ahead
  43. python垃圾回收和缓存管理
  44. java调用Python程序
  45. java调用Python程序
  46. Python常用函数有哪些?Python基础入门课程
  47. Python garbage collection and cache management
  48. Java calling Python program
  49. Java calling Python program
  50. What functions are commonly used in Python? Introduction to Python Basics
  51. Python basic knowledge
  52. Anaconda5.2 安装 Python 库(MySQLdb)的方法
  53. Python实现对脑电数据情绪分析
  54. Anaconda 5.2 method of installing Python Library (mysqldb)
  55. Python implements emotion analysis of EEG data
  56. Master some advanced usage of Python in 30 seconds, which makes others envy it
  57. python爬取百度图片并对图片做一系列处理
  58. Python crawls Baidu pictures and does a series of processing on them
  59. python链接mysql数据库
  60. Python link MySQL database