替换数组中的元素后，输出怎么还是原来的？
#include <stdio.h>#include <stdlib.h>
#include <math.h>
#define pi 3.141592653
int main()
{
double q1, q2, q3, q4=0;int i, j;
double T1 = { 1,0,0,q4,0,1,0,0,0,0,1,0,0,0,0,1 }；
scanf_s("lf", T1); 对T1的元素进行替换但是没有改变
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
printf("%lf ", T1);
}
printf("\n");
}
5（输入的改变值）
1.000000 0.000000 0.000000 0.000000
0.000000 1.000000 0.000000 0.000000 输出结果中没变
0.000000 0.000000 1.000000 0.000000
0.000000 0.000000 0.000000 1.000000
如何解决这个问题，q4的值，我想可以改变任何值，怎么实现？
return 0;
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#define pi 3.141592653
int main()
{
double q1, q2, q3, q4 = 0;
int i, j;
double T1 = {1, 0, 0, q4, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1};
scanf("%lf", &T1); // 修改
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
printf("%lf ", T1);
}
printf("\n");
}
} zltzlt 发表于 2020-8-6 16:17
5
1.000000 0.000000 0.000000 0.000000
0.000000 1.000000 0.000000 0.000000
0.000000 0.000000 1.000000 0.000000
0.000000 0.000000 0.000000 1.000000
还是这样的，我之前就是那样写的，和这个没关系 吴敌小白 发表于 2020-8-6 16:20
5
1.000000 0.000000 0.000000 0.000000
0.000000 1.000000 0.000000 0.000000
我这里测试不是这样的，你不是用的我那段代码吧？ scanf_s("%lf",&T1);
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
这不是可以吗？ zltzlt 发表于 2020-8-6 16:20
我这里测试不是这样的，你不是用的我那段代码吧？
我的程序改了以后还是原来的，
咱俩程序除了&符号，都一样啊 吴敌小白 发表于 2020-8-6 16:27
我的程序改了以后还是原来的，
咱俩程序除了&符号，都一样啊
scanf_s() 帮你改成了 scanf() baige 发表于 2020-8-6 16:23
对的了，我弄错了{:10_266:}
对的了，尴尬 scanf_s("lf", &T1); 少了个% baige 发表于 2020-8-6 16:33
scanf_s("lf", &T1); 少了个%
谢谢 baige 发表于 2020-8-6 16:33
scanf_s("lf", &T1); 少了个%
谢谢 baige 发表于 2020-8-6 16:33
scanf_s("lf", &T1); 少了个%
谢谢 baige 发表于 2020-8-6 16:33
scanf_s("lf", &T1); 少了个%
谢谢
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