C++二维数组动态内存分配

对于二维数组和二维指针的内存的分配

这里首选说一下一维指针和一维数组的内存分配情况。

一维:

数组:形如int  a[5];这里定义了一个一维数组a,并且数组的元素个数是5,这里的a是这五个元素的整体表示,也就是通过a我们能找到这五个元素。注意:a是代表数组第一个元素的首地址。&a是代表数组的地址,虽然它们的值相同。

指针: int *p = NULL;这里p是一个指针,它指向的是计算

机内一块存储int类型的内存。P = a;就是让p等于刚才申请的数组的第一个元素的地址。所以通过p我们也能找到那5个元素所以P[i]跟a[i]的作用一样。

注意:

1:int *p = NULL; p的大小在32位机器是4,即使p=a;之后p的sizeof(p)仍然等于4。

2:在声明之后,数组必须分配内存进行初始化。而指针一般是动态分配其指向的内存。

3:不要混淆指针和数组,指针就是指针,数组就是数组,只是数组在一定条件下可以转换成指针。不要将指针和数组混淆。(例如:指针有++,--操作,数组则不可以)。

一维指针的动态内存分配:

int *p = NULL;

p = new int[N];

千万别忘了delete

delete [] p;

p = NULL;

二维数组的内存分配

int a[2][3];   这里分配了一个2X3=6个int大小的数组。二维数组的第二个维度3不能省略。

二维数组的内存在计算机内也是连续的一片地址,只不过每3个元素构成一个一维数组a[i],这里的a[i]代表维度为3的数组的第一个元素的地址。所以a[i][j]的访问跟a[i]的访问也就清楚了。这里的a[i]其实是一个一维数组的第一个元素的地址。

对于二维数组做实参,我们通常用一维指针处理,例如:

 #include <iostream>
void test(int *p)
{
for (int i = ;i<;++i)
{
for(int j = ;j<;++j)
{
std::cout<<*(p+*i+j); //一维处理
}
}
}
int main(void)
{
int a[][]={,,,,,,,,};
test((int*)a); //将二维数组当做一维处理
system("pause");
return ;
}

这些想必书上讲的都非常清楚。

二维数组的C++动态内存分配。

二维指针的动态数组分配:二维指针类似指针数组的分配

int **p;

 #include <iostream>
int main(void)
{
int **p = NULL; //这里申请一个3x4的二维数组
p = new int *[]; //分配一维指针,分配三个int* 类型的一维指针。
for (int i = ;i < ; ++i)
{
p[i] = new int[];
}
for (int i = ; i < ; ++i)
{
for(int j = ; j < ; ++j)
{
p[i][j] = i*j;
std::cout<<p[i][j]<<" ";
}
std::cout<<std::endl;
} for (int i = ;i < ;++i) //释放
{
delete [] p[i];
}
delete [] p;
system("pause");
return ;
}

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" alt="" />

指针数组的动态内存分配

指针数组的动态内存分配只需要对指针数组的数组元素指针分别分配内存即可,比二维指针的分配少了一个环节。

 #include <iostream>
int main(void)
{
int *a[]; //申请含有三个int* 类型的指针数组
//跟二维指针不同的是,这里数组a不用手动申请内存
for (int i = ;i < ;++i) //申请一个3x4的空间
{
a[i] = new int[];
}
for (int i = ; i< ;++i)
{
for (int j = ; j<; ++j)
{
a[i][j] = i*j;
std::cout<<a[i][j]<<" ";
}
std::cout<<std::endl;
} for (int i = ;i < ;++i) //分别释放三个指针元素,由于数组在栈区,会自动释放
{
delete [] a[i];
}
system("pause");
return ;
}

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" 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数组指针的动态内存分配

数组指针就是指向数组的指针,说白了就是指向一个数组整体,因此分配的时候直接申请一片内存地址即可。跟二维数组的静态分配类似。

1 // Karllen
int main(void)
{
int (*a)[]; //这里的4是第二维的维度,a的增量的基数为4个int
a = new int[][];
delete []a;
a = NULL;
return ;
}

用的最多的就是上面的几种方法。一次性分配二维数组的内存还有多种方法可以实现。我也是刚接触这些东西,希望大家能提出不正确的地方。共勉!!!

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