// N->Array length, input->Input Array, output->Output Array
fftw_plan plan = fftw3_r2r_1d(N, input, output, FFTW_RODFT, FFTW_ESTIMATE);
fftw_execute(plan);
//使用output...
fftw_destroy_plan(plan);
fftw_cleanup();

//x->第一个带有一些值的数组
//y->FFT输入数组
//z->FFT输出数组
//n->第一个数组（x）的大小
#define REAL 0
#define IMAG 1
function_Name(){
const int n = 1000;
double x[n][2];
//用一些值填充x
for(i){
x[i][REAL]=i+1;
x[i][IMAG]=0;
}
fftw_complex y[(n+1)*2];
fftw_complex z[(n+1)*2];
y[0][REAL]=0;
y[0][IMAG]=0;
for(){
//从第2个元素(y[1])开始将x添加到y
}
y[n+1][REAL]=0;
y[n+1][IMAG]=0;
for(){
//反转x并乘以"-"，然后添加到y
}
fftw_plan plan = fftw_plan_dft_1d((n+1)*2, y, z, FFTW_FORWARD, FFTW_ESTIMATE);
fftw_execute(plan);
**//你可以使用z，但首先必须反转它（在MATLAB中使用fliplr），然后只取前n个元素和仅取IMAG部分。**
fftw_destroy_plan(plan);
fftw_cleanup();
}
我知道这个算法不是完美的，但我正在努力优化它并使其更加清晰。MATLAB fft()函数和FFTW的FFT函数之间的速度差异仍然是一个问题。我将另外提出一个新的问题来讨论这个问题。
<details>
<summary>英文:</summary>
I found a way to calculate Discrete Sine Transform with FFTW3&#39;s FFT library function. **But i should say it still slower than MATLAB dst() function (and i still don&#39;t know why)**. Let me simply explain what i did:
    //x-&gt;Your first array with some values
    //y-&gt;FFT input array
    //z-&gt;FFT output array
    //n-&gt;First array(x) size
    #define REAL 0
    #define IMAG 1
    
    function_Name(){
    const int n = 1000;
    double x[n][2];
    
    //Fill x with some value
    for(i){
    x[i][REAL]=i+1;
    x[i][IMAG]=0;
    }
    
    fftw_complex y[(n+1)*2];
    fftw_complex z[(n+1)*2];
    
    y[0][REAL]=0;
    y[0][IMAG]=0;
    
    for(){
    //Add x to y from 2. element(y[1])
    }
    
    y[n+1][REAL]=0;
    y[n+1][IMAG]=0;
    
    for(){
    //Invert x and multiply by &quot;-&quot; and add to y
    }
    
    fftw_plan plan = fftw_plan_dft_1d((n+1)*2, y, z, FFTW_FORWARD, FFTW_ESTIMATE);
    
    fftw_execute(plan);
    
    **//You can use z but first you have to Invert (fliplr in MATLAB) it and take only first n elements and only IMAG parts.**
    
    fftw_destroy_plan(plan);
    fftw_cleanup();
    }
I know this algorithm isn&#39;t perfect but I&#39;m working on it to speed up and to make a clean. For speed difference between MATLAB fft() function and FFTW&#39;s FFT function is still a problem. I will open a new question about it.  
</details>