嗨,我试图对一个信号进行简单的一维FFT变换。这就是我试过的:
import numpy as np
from scipy.signal import hilbert, chirp
duration = 1.0
fs = 400.0
samples = int(fs*duration)
t = np.arange(samples) / fs
signal = chirp(t, 20.0, t[-1], 100.0)import pycuda.autoinit
from pycuda import gpuarray
import numpy as np
from skcuda import fftdef fft_gpu1(signal):
  x_gpu = gpuarray.to_gpu(signal)
  x_hat = gpuarray.empty_like(x_gpu, dtype=np.complex64)
  plan = fft.Plan(x_gpu.shape,np.float32,np.complex64)
  fft.fft(x_gpu, x_hat, plan)
  return x_hat.get()print(fft_gpu1(signal))然而,我得到的结果是:
[nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj
 nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj
 nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj
 nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj nan+nanj
...
  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j
  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j
  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j  0. +0.j]如果能了解我为什么会得到这个问题,我们将不胜感激。
发布于 2021-07-06 13:40:01
信号应该是float32类型,而不是float64:
x_gpu = gpuarray.to_gpu(signal.astype(np.float32))https://stackoverflow.com/questions/56448047
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