Python学习笔记19（算法）

1.二分查找

只能用二分查找查找有序列表

def bin_search(data,val):  #data为被查找的列表，val是要查找的值
    low = 0
    high = len(data) - 1
    while low <= high:
        mid = (low+high)//2
        if data[mid] == val:
            return mid           #找到了，返回val所在的索引
        elif data[mid] < val:
            low = mid + 1
        else:
            high = mid - 1
    return                        #未找到，返回None

二分查找

2.冒泡排序

def bubble_sort(data):                   #data传需要排序的列表
    for i in range(len(data)-1):
        FLAG = 0
        for j in range(len(data)-i-1):
            if data[j] > data[j+1]:
                data[j],data[j+1] = data[j+1],data[j]
                FLAG = 1
        if FLAG == 0:
            break

冒泡排序

3.选择排序

def select_sort(data):
    for i in range(len(data)-1):
        min = i
        for j in range(i+1,len(data)):
            if data[j] < data[min]:
                min = j
        data[i],data[min] = data[min],data[i]

选择排序

4.插入排序

def insert_sort(data):
    for i in range(1,len(data)):
        tmp = data[i]
        j = i - 1
        while j >= 0 and data[j] > tmp:
            data[j+1] = data[j]
            j = j - 1
        data[j + 1] = tmp

插入排序

5.快速排序

def quick_sort(data,left,right):
    if left < right:
        mid = partition(data,left,right)
        quick_sort(data,left,mid - 1)
        quick_sort(data,mid + 1,right)

def partition(data,left,right):
    tmp = data[left]
    while left < right:
        while left < right and data[right] >= tmp:
            right -= 1
        data[left] = data[right]
        while left < right and data[left] <= tmp:
            left += 1
        data[right] = data[left]
    data[left] = tmp
    return left

快速排序

6.堆排序

def sift(data,low,high):
    i = low
    j = 2 * i +1
    tmp = data[i]
    while j <= high:
        if j + 1 <= high and data[j] < data[j+1]:
            j += 1
        if data[j] > tmp:
            data[i] = data[j]
            i = j
            j = 2 * i + 1
        else:
            break
    data[i] = tmp

def heap_sort(data):
    n = len(data)
    for i in range(n // 2 - 1 ,-1 ,-1):
        sift(data,i,n-1)
    for i in range(n-1,-1,-1):
        data[0],data[i] = data[i],data[0]
        sift(data,0,i-1)

堆排序

7.归并排序

def merge(data,low,mid,high):
    i = low
    j = mid+1
    tmp = []
    while i <= mid and j <= high:
        if data[i] < data[j]:
            tmp.append(data[i])
            i += 1
        else:
            tmp.append(data[j])
            j += 1
    while i <= mid:
        tmp.append(data[i])
        i += 1
    while j <= high:
        tmp.append(data[j])
        j += 1
    data[low:high+1] = tmp

def mergesort(data,low,high):
    if low < high:
        mid = (low+high)//2
        mergesort(data,low,mid)
        mergesort(data,mid+1,high)
        merge(data,low,mid,high)

归并排序