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我正在使用 FFTW 高级数据布局 API 处理批处理 2D FFT。

根据FFTW Advanced Complex DFT文档：

为 nembed 参数传递NULL等效于传递n。

inembed = onembed = NULL但是，使用vs.时我得到了不同的结果inembed = onembed = n。什么可能导致结果不匹配？

让我们举个例子...

设置

int howMany = 2;
int nRows = 4;
int nCols = 4;
int n[2] = {nRows, nCols};
float* h_in = (float*)malloc(sizeof(float) * nRows*nCols*howMany);
for(int i=0; i<(nRows*nCols*howMany); i++){ //initialize h_in to [0 1 2 3 4 ...]
    h_in[i] = (float)i;
    printf("h_in[%d] = %f \n", i, h_in[i]);
}

FFTW 计划使用inembed == onembed == NULL

fftwf_plan forwardPlan = fftwf_plan_many_dft_r2c(2, //rank
                            n, //dimensions = {nRows, nCols}
                            howMany, //howmany
                            h_in, //in
                            NULL, //inembed
                            howMany, //istride
                            1, //idist
                            h_freq, //out
                            NULL, //onembed
                            howMany, //ostride
                            1, //odist
                            FFTW_PATIENT /*flags*/);

我还用inembed = onembed = n = {nRows, nCols}.

结果

请注意，使用NULLorn给出相同的数值结果，但在内存中的顺序不同：

版本 1：inembed == onembed == NULL

result[0][0,1] = 240, 0 
result[1][0,1] = 256, 0 
result[2][0,1] = -16, 16 
result[3][0,1] = -16, 16 
result[4][0,1] = -16, 0 
result[5][0,1] = -16, 0  //this line and above match the other version
result[6][0,1] = -64, 64  //this line and below don't match (data is in a different order)
result[7][0,1] = -64, 64  
result[8][0,1] = 0, 0 
result[9][0,1] = 0, 0 
result[10][0,1] = 0, 0 
result[11][0,1] = 0, 0 
result[12][0,1] = -64, 0 
result[13][0,1] = -64, 0 
result[14][0,1] = 0, 0 
result[15][0,1] = 0, 0 
result[16][0,1] = 0, 0 
result[17][0,1] = 0, 0 
result[18][0,1] = -64, -64 
result[19][0,1] = -64, -64 
result[20][0,1] = 0, 0 
result[21][0,1] = 0, 0 
result[22][0,1] = 0, 0 
result[23][0,1] = 0, 0 
result[24][0,1] = 0, 0 
result[25][0,1] = 0, 0 
result[26][0,1] = 0, 0 
result[27][0,1] = 0, 0 
result[28][0,1] = 0, 0 
result[29][0,1] = 0, 0 
result[30][0,1] = 0, 0 
result[31][0,1] = 0, 0

版本 2：inembed = onembed = n = {nRows, nCols}

result[0][0,1] = 240, 0 
result[1][0,1] = 256, 0 
result[2][0,1] = -16, 16 
result[3][0,1] = -16, 16 
result[4][0,1] = -16, 0 
result[5][0,1] = -16, 0 
result[6][0,1] = 0, 0  
result[7][0,1] = 0, 0  
result[8][0,1] = -64, 64 
result[9][0,1] = -64, 64 
result[10][0,1] = 0, 0 
result[11][0,1] = 0, 0 
result[12][0,1] = 0, 0 
result[13][0,1] = 0, 0 
result[14][0,1] = 0, 0 
result[15][0,1] = 0, 0 
result[16][0,1] = -64, 0 
result[17][0,1] = -64, 0 
result[18][0,1] = 0, 0 
result[19][0,1] = 0, 0 
result[20][0,1] = 0, 0 
result[21][0,1] = 0, 0 
result[22][0,1] = 0, 0 
result[23][0,1] = 0, 0 
result[24][0,1] = -64, -64 
result[25][0,1] = -64, -64 
result[26][0,1] = 0, 0 
result[27][0,1] = 0, 0 
result[28][0,1] = 0, 0 
result[29][0,1] = 0, 0 
result[30][0,1] = 0, 0 
result[31][0,1] = 0, 0

这是这个实验的一个工作实现。

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1 回答 1

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解决方案：
上面例子中的 不合适embed != NULL的例子是通过设置inembed = {nRows, nCols}和来解决的onembed = {nRows, (nCols/2 + 1)}。

细节：

在仔细阅读 FFTW 文档并从Matteo Frigo获得一些帮助后，我解决了这个问题。你可以在这里追溯我的步骤：

根据FFTW 手册中的4.4.2 Advanced Real-data DFTs：If an nembed parameter is NULL, it is interpreted as what it would be in the basic interface.

假设我们输入的真实数据是维度的nx * ny。对于 FFTW 基本接口，2.4 Multi-Dimensional DFTs of Real Data解释了2D real-to-complex FFTs的以下内容inembed和约定：onembed

if out-of-place:
    inembed = [ny, nx]
    onembed = [ny, (nx/2 + 1)]

if in-place:
    inembed = [ny, 2(nx/2 + 1)]
    onembed = [ny, (nx/2 + 1)]

所以，当我们使用简单的 FFTWr2c接口或者使用带有 的高级接口时embed=NULL，FFTW 默认使用上述embed参数。我们可以embed=NULL使用上述embed参数重现数值结果。

事实证明，该声明Passing NULL for an nembed parameter is equivalent to passing n来自FFTW complex-to-complex手册页。但是，我们在上面的示例中进行了实数到复数的转换。实数到复数变换与 和 的复数变换有不同的inembed约定onembed。

于 2013-07-11T00:37:23.357 回答