FFT Pix

Plotting Input WAV file

from pylab import *

import matplotlib.pyplot as plt

from scipy.fftpack import fft

import wave

import numpy as np

file = "toy-rattle-2.wav"

spf = wave.open(file,'r')

f = spf.getframerate()

sound_info = spf.readframes(-1)

sound_info = fromstring(sound_info, 'Int16')

plt.plot( sound_info )

plt.show() 

 Plotting the F.T. of sound_info (complex numbers)

ft = fft( sound_info )

Magnitude of F.T.

ft_mag = map( abs, ft )

Applying a Windowing Function ( Hanning )

window = np.hanning( len(sound_info ) ) 

Apply the windowing function before taking the FFT: (pythonically)

sound_window = []
for s, w in zip( sound_info, window ):
   sound_window.append( s * w ) 

ft = fft( sound_window  )
ft_mag = map( abs, ft )

It does not seem like much difference, other than slight variations noticeable on the edges. Scale might be affecting it.

ft_u = fft( sound_info )ft_w = fft( sound_window )ft_um = map( abs, ft_u )  ft_wm = map( abs, ft_w ) 

dif = []
for w, u in zip( ft_wm, ft_um):
    dif.append( abs( w -  u ) )

Below, I graphed the difference:

Which doesn't look like any difference. This baffles me...