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排序算法总结

时间:2020-02-20 13:19:44      阅读:75      评论:0      收藏:0      [点我收藏+]

标签:key   count   归并排序   class   nbsp   ret   的区别   反序   com   

技术图片

 

1、直接插入排序

def insert_sort(alist):
    """插入排序"""
    n = len(alist)
    for j in range(1,n):
        i = j
        while i > 0:
            if alist[i] < alist[i-1]:
                alist[i],alist[i-1] = alist[i-1],alist[i]
                i -= 1
            else:
                break

if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    insert_sort(l)
    print(l)

2、希尔排序

#Author:liuyang

def shell_sort(alist):
    """希尔排序"""
    n = len(alist)
    gap = n // 2
    while gap > 0:
        #插入算法,唯一的区别就是gap
        for j in range(gap,n):
            i = j
            while i > 0:
                if alist[i] < alist[i - gap]:
                    alist[i], alist[i - gap] = alist[i - gap], alist[i]
                    i -= gap
                else:
                    break
        gap //= 2

if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    shell_sort(l)
    print(l)

  

3、直接选择排序

# Author:liuyang
def select_sort(alist):
    """选择排序"""
    n = len(alist)
    for j in range(0, n - 1):  # j 0 ~ n-2
        min_index = j
        for i in range(j + 1, n):
            if alist[min_index] > alist[i]:
                min_index = i
        alist[j], alist[min_index] = alist[min_index], alist[j]

  

4、冒泡排序

#Author:liuyang

def bubble_sort(alist):
    """冒泡排序"""
    n = len(alist)
    for j in range(0,n-1):      #产生0到n-2,一共n-1个数
        count = 0
        for i in range(0,n-1-j):
            if alist[i] > alist[i+1]:
                alist[i],alist[i+1] = alist[i+1],alist[i]
                count += 1
        if count == 0:
            return


# i 0 ~ n-2 range(0,n-1) j = 0
# i 0 ~ n-3 range(0,n-1-1) j = 1
# i 0 ~ n-4 range(0,n-1-2) j = 2
# j = n   range(0,n-1-j)

if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    bubble_sort(l)
    print(l)

5、快速排序

#Author:liuyang
def quick_sort(alist,first,last):
    """快速排序"""
    if first >= last:
        return
    mid_value = alist[first]
    low = first
    high = last

    while low < high:
        while low < high and alist[high] >= mid_value:
            high -= 1
        alist[low] = alist[high]

        while low < high and alist[low] < mid_value:
            low += 1
        alist[high] = alist[low]

    alist[low] = mid_value

    #对左边进行快速排序
    quick_sort(alist,first,low-1)
    #对右边进行快速排序
    quick_sort(alist,high+1,last)

if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    quick_sort(l,0,len(l)-1)
    print(l)

  

#Author:liuyang
def quick_sort(alist):
    if len(alist) < 2:
        return alist        #基线条件
    else:
        pivot = alist[0]
        less = [i for i in alist[1:] if i <= pivot]    #所有小于基准值的子数组
        greater = [i for i in alist[1:] if i > pivot]    #所有大于基准值的子数组
        return quick_sort(less) + [pivot] + quick_sort(greater)


if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    print(quick_sort(l))

  

6、归并排序

#Author:liuyang
def merge_sort(alist):
    """归并排序"""
    n = len(alist)
    if n == 1:
        return alist
    mid = n // 2
    left_li = merge_sort(alist[:mid])
    right_li = merge_sort(alist[mid:])

    left_point,right_point = 0,0
    result = []

    while left_point < len(left_li) and right_point < len(right_li):
        if left_li[left_point] < right_li[right_point]:
            result.append(left_li[left_point])
            left_point += 1
        else:
            result.append(right_li[right_point])
            right_point += 1

    result += left_li[left_point:]
    result += right_li[right_point:]
    return result


if __name__ == "__main__":
    l = [451, 122, 12, 455, 48, 48, 524, 65, 99, 1225]
    print(l)
    new_list = merge_sort(l)
    print(l)
    print(new_list)

 

 技术图片

 

另附大佬实现的各种排序代码(此代码来源于:数据结构与算法 Python语言描述 作者:裘宗燕)

""" 排序算法
"""

from random import randrange, randint


class Record:
    def __init__(self, key, datum):
        self.key = key
        self.datum = datum

    def __str__(self):
        return "R(" + str(self.key) + ", " + str(self.datum) + ")"


def printR(lst):
    print("[" + ", ".join(map(str, lst)) + "]")

#### 简单插入排序
##def insert_sort(lst) :
##    for i in range(1, len(lst)): # 开始时片段[0:1]已排序
##        x = lst[i]
##        j = i
##        while j > 0 and lst[j-1].key > x.key:
##            lst[j] = lst[j-1]  # 反序逐个后移元素至确定插入位置
##            j -= 1
##        lst[j] = x
##
##
##def test1(n):
##    l1 = [Record(randint(1, 20), i) for i in range(n)]
##    printR(l1)
##    insert_sort(l1)
##    printR(l1)


#### 简单选择排序
# def select_sort(lst):
#    for i in range(len(lst)-1):
#        k = i
#        for j in range(i, len(lst)):
#            if lst[j].key < lst[k].key:
#                k = j
#        if i != k:
#            lst[i], lst[k] = lst[k], lst[i]
#
#
# def test2(n):
#    l1 = [Record(randint(1, 20), i) for i in range(n)]
#    printR(l1)
#    select_sort(l1)
#    printR(l1)


#### 简单起泡排序
##def bubble_sort(lst):
##    for i in range(len(lst)):
##        for j in range(1, len(lst)-i):
##            if lst[j-1].key > lst[j].key:
##                lst[j-1], lst[j] = lst[j], lst[j-1]


#### 起泡排序,无逆序时提前结束
# def bubble_sort(lst):
#    for i in range(len(lst)):
#        found = False
#        for j in range(1, len(lst)-i):
#            if lst[j-1].key > lst[j].key:
#                lst[j-1], lst[j] = lst[j], lst[j-1]
#                found = True
#        if not found:
#            break
#
#
# def test3(n):
#    l1 = [Record(randint(1, 20), i) for i in range(n)]
#    printR(l1)
#    bubble_sort(l1)
#    printR(l1)


#### 快速排序
# def quick_sort(lst):
#    def qsort_rec(lst, l, r):
#        if l >= r:
#            return      # 分段中无记录或只有一个记录
#        i, j = l, r
#        pivot = lst[i]
#        while i < j:    # 找 pivot 的最终位置
#            while i < j and lst[j].key >= pivot.key:
#                j -= 1  # 用 j 向左找小于 pivot 的记录移到左边
#            if i < j:
#                lst[i] = lst[j]
#                i += 1
#            while i < j and lst[i].key <= pivot.key:
#                i += 1  # 用 i 向右找大于 pivot 的记录移到右边
#            if i < j:
#                lst[j] = lst[i]
#                j -= 1
#        lst[i] = pivot          # 将 pivot 存入其最终位置
#        qsort_rec(lst, l, i-1)  # 递归处理左半区间
#        qsort_rec(lst, i+1, r)  # 递归处理右半区间
#
#    qsort_rec(lst, 0, len(lst)-1)  # 主函数调用 qsort_rec
#
#
# def test4(n):
#    l1 = [Record(randint(1, 20), i) for i in range(n)]
#    printR(l1)
#    quick_sort(l1)
#    printR(l1)


#### 快速排序的另一种实现
# def quick_sort1(lst):
#    def qsort(lst, begin, end):
#        if begin >= end:
#            return
#        pivot = lst[begin].key
#        i = begin
#        for j in range(begin + 1, end + 1):
#            if lst[j].key < pivot: # 发现一个小元素
#                i += 1
#                lst[i], lst[j] = lst[j], lst[i] # 小元素交换到前面
#        lst[begin], lst[i] = lst[i], lst[begin] # 枢轴元素就位
#        qsort(lst, begin, i - 1)
#        qsort(lst, i + 1, end)
#
#    qsort(lst, 0, len(lst) - 1)
#
#
# def test4(n):
#    l1 = [Record(randint(1, 20), i) for i in range(n)]
#    printR(l1)
#    quick_sort1(l1)
#    printR(l1)


#### 归并排序
# def merge_sort(lst):
#    slen, llen = 1, len(lst)
#    templst = [None] * llen
#    while slen <= llen:
#        merge_pass(lst, templst, llen, slen)
#        slen *= 2
#        merge_pass(templst, lst, llen, slen)  # 结果存回原位
#        slen *= 2
#
#
# def merge_pass(lfrom, lto, llen, slen):
#    i = 0
#    while i + 2 * slen < llen:  # 归并长slen的两段
#        merge(lfrom, lto, i, i + slen, i + 2 * slen)
#        i += 2 * slen
#    if i + slen < llen:  # 剩下两段,后段长度小于slen
#        merge(lfrom, lto, i, i + slen, llen)
#    else:   # 只剩下一段,复制到表lto
#        for j in range(i, llen):
#            lto[j] = lfrom[j]
#
#
# def merge(lfrom, lto, low, m, high):
#    i, j, k = low, m, low
#    while i < m and j < high:  # 反复复制两段首记录中较小的
#        if lfrom[i].key <= lfrom[j].key:
#            lto[k] = lfrom[i]
#            i += 1
#        else:
#            lto[k] = lfrom[j]
#            j += 1
#        k += 1
#    while i < m:     # 复制第一段剩余记录
#        lto[k] = lfrom[i]
#        i += 1
#        k += 1
#    while j < high:  # 复制第二段剩余记录
#        lto[k] = lfrom[j]
#        j += 1
#        k += 1
#
#
# def test5(n):
#    l1 = [Record(randint(1, 20), i) for i in range(n)]
#    printR(l1)
#    merge_sort(l1)
#    printR(l1)


#### 基数排序
#### 假设被排序仍是以记录类型 Record 为元素的表,其中
####   关键码是数字 0 到 9 的序列(元组),长度 r 为参数
#### 排序中用 10 个 list 存储各关键码元素对应的序列
#### 一遍分配后收集回到原表,r 遍分配和收集完成排序工作

# def radix_sort(lst, r):
#     rlists = [[] for i in range(10)]
#     llen = len(lst)
#     for d in range(-1, -r-1, -1):
#         for j in range(llen):
#             rlists[lst[j].key[d]].append(lst[j])
#         j = 0
#         for i in range(10):
#             tmp = rlists[i]
#             for k in range(len(tmp)):
#                 lst[j] = tmp[k]
#                 j += 1
#             rlists[i].clear()
#
#
# def test6(n):
#     lst = [Record(tuple((randrange(10) for j in range(3))),
#                   i) for i in range(n)]
#     printR(lst)
#     radix_sort(lst, 3)
#     printR(lst)
#     print()


# if __name__ == ‘__main__‘:
#     test1(15)

  

排序算法总结

标签:key   count   归并排序   class   nbsp   ret   的区别   反序   com   

原文地址:https://www.cnblogs.com/liuyangQAQ/p/12334976.html

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