如何在python中提取与fft值关联的频率

如何在python中提取与fft值关联的频率

np.fft.fftfreq

告诉您与系数相关的频率：

import numpy as npx = np.array([1,2,1,0,1,2,1,0])w = np.fft.fft(x)freqs = np.fft.fftfreq(len(x))for coef,freq in zip(w,freqs):    if coef:        print('{c:>6} * exp(2 pi i t * {f})'.format(c=coef,f=freq))# (8+0j) * exp(2 pi i t * 0.0)#    -4j * exp(2 pi i t * 0.25)#     4j * exp(2 pi i t * -0.25)

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OP询问如何找到以赫兹为单位的频率。我相信公式是

frequency (Hz) = abs(fft_freq * frame_rate)

。

这是一些证明这一点的代码。

首先，我们制作一个440 Hz的波形文件：

import mathimport waveimport structif __name__ == '__main__':    # http://stackoverflow.com/questions/3637350/how-to-write-stereo-wav-files-in-python    # http://www.sonicspot.com/guide/wavefiles.html    freq = 440.0    data_size = 40000    fname = "test.wav"    frate = 11025.0    amp = 64000.0    nchannels = 1    sampwidth = 2    framerate = int(frate)    nframes = data_size    comptype = "NONE"    compname = "not compressed"    data = [math.sin(2 * math.pi * freq * (x / frate)) for x in range(data_size)]    wav_file = wave.open(fname, 'w')    wav_file.setparams(        (nchannels, sampwidth, framerate, nframes, comptype, compname))    for v in data:        wav_file.writeframes(struct.pack('h', int(v * amp / 2)))    wav_file.close()

这将创建文件

test.wav

。现在我们读取数据，对其进行FFT，找到具有最大功率的系数，并找到相应的fft频率，然后转换为赫兹：

import waveimport structimport numpy as npif __name__ == '__main__':    data_size = 40000    fname = "test.wav"    frate = 11025.0    wav_file = wave.open(fname, 'r')    data = wav_file.readframes(data_size)    wav_file.close()    data = struct.unpack('{n}h'.format(n=data_size), data)    data = np.array(data)    w = np.fft.fft(data)    freqs = np.fft.fftfreq(len(w))    print(freqs.min(), freqs.max())    # (-0.5, 0.499975)    # Find the peak in the coefficients    idx = np.argmax(np.abs(w))    freq = freqs[idx]    freq_in_hertz = abs(freq * frate)    print(freq_in_hertz)    # 439.8975