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排序算法

排序算法

作者: _Haimei | 来源:发表于2018-10-24 21:08 被阅读22次
    1. 插入排序

      def inster_sort(lists):
          count = len(lists)
          for i in range (1,count):
              key = lists[i]
              j = i -1
              while j>=0:
                  if lists[j] > key:
                      lists[j+1] = lists[j]
                      lists[j] = key
                  j -= 1
           return lists
      # 时间复杂度O(n**2),空间复杂度O(1) ,稳定
      
    2. 希尔排序

      def shell_sort(lists):
          # 希尔排序
          count = len(lists)
          step = 2
          group = count / step
          while group > 0:
              for i in range(0, group):
                  j = i + group
                  while j < count:
                      k = j - group
                      key = lists[j]
                      while k >= 0:
                          if lists[k] > key:
                              lists[k + group] = lists[k]
                              lists[k] = key
                          k -= group
                      j += group
              group /= step
          return lists
      
    3. 冒泡排序

      def bubble_sort(lists):
          # 冒泡排序
          count = len(lists)
          for i in range(0, count):
              for j in range(i + 1, count):
                  if lists[i] > lists[j]:
                      lists[i], lists[j] = lists[j], lists[i]
          return lists
      # 时间复杂度O(n*2),空间复杂度O(nlog2N),稳定
      
    4. 快速排序

      def quick_sort(lists, left, right):
          # python 快速排序
          if left >= right:
              return lists
          key = lists[left]
          low = left
          high = right
          while left < right:
              while left < right and lists[right] >= key:
                  right -= 1
              lists[left] = lists[right]
              while left < right and lists[left] <= key:
                  left += 1
              lists[right] = lists[left]
          lists[right] = key
          quick_sort(lists, low, left - 1)
          quick_sort(lists, left + 1, high)
          return lists
      # 时间复杂度O(n*log2N),空间复杂度O(nlog2N),不稳定
      
      # include <stdio.h>
      # include <stdlib.h>
      # define BFU_SIZE 10
      # c 快速实现
      # 打印数组元素
      void display(int array[],int maxlen){
          int i ;
          for(i=0;i<maxlen;i++){
              printf("%-3d",array[i]);
          }
          printf("\n");
          return ;
      }
      
      # 执行交换两个数的值
      void swap(int *a,int *b){
          int temp;
          temp=*a;
          *a=*b;
          *b=temp;
          return;
      }
      
      # 快排算法
      void quicksort(int attay[],int maxlen,int begin,int end){
          int i,j;
          if(begin<end){
              i=begin+1;
              j=end;
              while(i<j){
                  if(array[i]>array[begin]){
                      swap(&array[i],&array[j]);
                      j--;
                  }
                  else{
                      i++;
                  }
              }
              # 此时数组分成了两个部分,进行比较,确定 基准数
              if(array[i]>=array[begin]){
                  i--;
              }
              swap(&array[begin],&array[i]);
              quicksort(array,maxlen,begin,i);
              quicksort(array,amxlen,j,end);
          }
      }
      
      int main(){
          int n;
          int array[BUF_SIZE]={}
          int maxlen=BUF_SIZE
          
          printf("排序之前");
          display(array,maxlen)
          
          quicksort(array,amxlen,0,maxxlen-1);
          printf("排序之后");
          display(araay,maxxlen);
      
          retunr 0;
      }
      
    5. 直接选择排序

      def select_sort(lists):
          # python 选择排序
          count = len(lists)
          for i in range(0, count):
              min = i
              for j in range(i + 1, count):
                  if lists[min] > lists[j]:
                      min = j
              lists[min], lists[i] = lists[i], lists[min]
          return lists
      # 时间复杂度O(n**2),空间复杂度O(1),不稳定
      
      # c 选择排序
      void selection_sort(int arr[],int n){
          int i,j,k;
          for(i=0;i<n;i++){
              k=-1;
              int m =arr[i];
              for(j=i;j<n;j++){
                  if(arr[j]<m){
                      m=arr[j];
                      k=j;
                  }
              }
              if(k!=1){
                  arr[k]=arr[i];
                  arr[i]=m;
              }
          }
          
      }
      
    6. 堆排序

      from collections import deque
      L=deque([34,23,32,45,67,87])
      l.appendleft(0)
      
      def element_exchange(numbers,low,high):
          temp=numbers[low]
          i=low
          j=2*i
          
          while j<=high:
              # 如果右节点较大,则j指向右节点
              if j<high and numbers[j]<numbers[j+1]:
                  j=j+1
              if temp>numbers[j]:
                  # 将numbers[j]放到双亲节点上
                  numbers[i]=numbers[j]
                  i=j
                  j=i*2
              else:
                  break;
          # 被调整节点放入最终位置        
          numbers[i]=temp
      
      def top_heap_sort(numbers):
          length=len(numbers)-1
          # 指定第一个元素的下标,是无序序列的第一个非叶子节点
          first_exchange_element=length/2
          # 建立初始堆
          print first_exchange_element
          for x in tange(first_exchange_element):
              element_exchange(numbers,first_exchange_element-x,length)
          # 将根节点放到最终位置,继续堆排序
          for y in range(length-1):
              temp=numbers[1]
              numbers[1]=numbers[length-y]
              numbers[length-y]=temp
              element_exchange(numbers,1,length-y-1)
      # 时间复杂度O(n*log2N),空间复杂度O(1),不稳定
      
    7. 归并排序

      # 进行拆分
      def merge_sort(lists):
          # 长度不足1,直接返回
          if len(lists) <= 1:
              return lists
          # 二分
          num = len(lists) / 2
          # 递归拆分
          left = merge_sort(lists[:num])
          right = merge_sort(lists[num:])
          # 执行比较
          return merge(left, right)
      # 进行比较合并
      def merge(a,b):
          c = []
          h=j=0
          while j<len(a) and h<len(b):
              # 小的进入
              if a[j] < b[h]:
                  c.append(a[j])
                  j+=1
              else:
                  c.append(b[h])
                  h+=1
          # a遍历完,插入b
          if j==len(a):
              for i in b[h:]:
                  c.append(b[i])
          # b遍历完,插入a
          if h==len(b):
              for i in a[j:]:
                  c.append(i)
          return c
      # 时间复杂度O(n*log2N),空间复杂度O(1),稳定
      
    8. 基数排序

      import math
      def radix_sort(lists, radix=10):
          k = int(math.ceil(math.log(max(lists), radix)))
          bucket = [[] for i in range(radix)]
          for i in range(1, k+1):
              for j in lists:
                  bucket[j/(radix**(i-1)) % (radix**i)].append(j)
              del lists[:]
              for z in bucket:
                  lists += z
                  del z[:]
          return lists
      
    9. 斐波那契数列

      # 递归实现
      def item( num ):
          if num == 0 :
              res = 0
          elif num == 1:
              res = 1
          else:
              res = item ( num - 1) + item (num -2)
          return res
      
      def printFibo( no ):
          i = 0
      
          while i < no:
              print item(i)
              i += 1
      
      # 迭代器实现,返回一个列表
      def fibo(num):
          numList = [0,1]
      
          for i in range(num - 2):
              numList.append(numList[-2] + numList[-1])
          return numList
      
    10. 深度遍历

      def DFS(nodes):
          # queue是堆栈
          # order是存放的具体路径
          queue,order=[],[]
          queue.append(nodes)
          while queue:
              v=queue.pop()
              order.append(v)
              for w in sequense[v]:
                  if w not in order and w not in queue:
                      queue.append(w)
          return order
      
    11. 广度遍历

      def BFS(node):
          queue,order=[],[]
          queueu.append(node)
          order.append(node)
          while queue:
              v=queue.pop()
              for w in sequense[v]:
                  if w not in order:
                      order.append(w)
                      queue.append(w)
          return order
      
    12. 二分查找

      def binary_search(find,list1):
          low=0
          high=len(list1)
          while low<high:
              mid=(low+high)/2
              if list1[mid]==find:
                  return mid
              elif list1[mid]>find:
                  high=mid-1
              else:
                  low=mid+1
          return -1
      

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