我想要实现的目标如下：我需要声音文件(.wav)的频率值进行分析.我知道很多程序会给出值的可视图(谱图),但我需要原始数据.我知道这可以通过FFT完成,并且应该在

python中相当容易编写脚本但不确定如何完全执行它.

因此,假设文件中的信号长度为.4s,那么我希望多次测量,为程序测量的每个时间点以及它找到的值(频率)(以及可能的功率(dB))提供输出作为数组.复杂的是我想要分析鸟歌,并且它们通常具有谐波或者信号在一定频率范围内(例如1000-2000Hz).我希望程序也输出这些信息,因为这对于我想对数据做的分析很重要:)

现在有一段看起来非常像我想要的代码,但我认为它并没有给我所有我想要的价值……(感谢Justin Peel将这个问题发布到另一个问题:))所以我聚集在一起我需要numpy和pyaudio但不幸的是我不熟悉python所以我希望Python专家可以帮助我吗？

源代码：

# Read in a WAV and find the freq's

import pyaudio

import wave

import numpy as np

chunk = 2048

# open up a wave

wf = wave.open('test-tones/440hz.wav', 'rb')

swidth = wf.getsampwidth()

RATE = wf.getframerate()

# use a Blackman window

window = np.blackman(chunk)

# open stream

p = pyaudio.PyAudio()

stream = p.open(format =

p.get_format_from_width(wf.getsampwidth()),

channels = wf.getnchannels(),

rate = RATE,

output = True)

# read some data

data = wf.readframes(chunk)

# play stream and find the frequency of each chunk

while len(data) == chunk*swidth:

# write data out to the audio stream

stream.write(data)

# unpack the data and times by the hamming window

indata = np.array(wave.struct.unpack("%dh"%(len(data)/swidth),\

data))*window

# Take the fft and square each value

fftData=abs(np.fft.rfft(indata))**2

# find the maximum

which = fftData[1:].argmax() + 1

# use quadratic interpolation around the max

if which != len(fftData)-1:

y0,y1,y2 = np.log(fftData[which-1:which+2:])

x1 = (y2 - y0) * .5 / (2 * y1 - y2 - y0)

# find the frequency and output it

thefreq = (which+x1)*RATE/chunk

print "The freq is %f Hz." % (thefreq)

else:

thefreq = which*RATE/chunk

print "The freq is %f Hz." % (thefreq)

# read some more data

data = wf.readframes(chunk)

if data:

stream.write(data)

stream.close()

p.terminate()