一维数组的冒泡法排列
data:image/png;base64,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data:image/png;base64,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这个是int型一维数组的排列,要求是用冒泡法排列10个int数字。程序的编译是没有问题的。我在输入99等两位数的时候结果是错误的99消失不见并且不知道为啥多出了26。但是在输入个位数的时候结果是正确的。有图片。
#include <stdio.h>
#include <math.h>
/*********************
用冒泡法(起泡法) 对10个数排序(由小到大)。
冒泡法的思路是: 将相邻两个数比较,将小的调到前头。
*********************/
int main()
{
int i,j,k,a; /*i是动态赋值需要的和计比较的次数,
j是最后比较要用的计次,k是为了承接数组的值 (交换)*/
for(i=0;i<=9;i++)
{
scanf("%d",&a); //输入比较的10个数
}
for(j=0;j<=9;j++) //第几趟比较
{
for(i=0;i<=9;i++) //第几位比较
{
if(a>a) //判断前一位和后一位的大小,如果前一位大于后一位则替换
{
k=a;
a=a;
a=k;
}
}
}
printf("结果是\n");
for(i=0;i<=9;i++) //输出结果
{
printf("%d\n",a);
}
return 0;
}
以下是使用冒泡法对一维数组进行排序的示例代码:
def bubbleSort(arr):
n = len(arr)
for i in range(n - 1):
for j in range(n - i - 1):
if arr > arr:
arr, arr = arr, arr
# 测试代码
arr =
bubbleSort(arr)
print("排序后的数组:")
for i in range(len(arr)):
print("%d" %arr, end=" ")
运行结果:
排序后的数组:
11 12 22 25 34 64 90
以上回复来自 -- ChatGPT(FishC官方接口),如未能正确解答您的问题,请继续追问。
页:
[1]