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TWEET Untitled a guest May 21st, 2019 86 Never
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1. import scipy.io.wavfile as wavfile
2. import scipy
3. import scipy.fftpack
4. import numpy as np
5. from matplotlib import pyplot as plt
6.
7. fs_rate, signal = wavfile.read("sound.wav")
8. START = 0
9. STOP = 4
10. signal = signal[START*fs_rate:STOP*fs_rate]
11. print ("Frequency sampling", fs_rate)
12. l_audio = len(signal.shape)
13. print ("Channels", l_audio)
14. if l_audio == 2:
15.     signal = signal.sum(axis=1) / 2
16. N = signal.shape
17. print ("Complete Samplings N", N)
18. secs = N / float(fs_rate)
19. print ("secs", secs)
20. Ts = 1.0/fs_rate
21. print ("Timestep between samples Ts", Ts)
22. t = scipy.arange(0, secs, Ts)
23. FFT = abs(scipy.fft(signal))
24. FFT_side = FFT[range(N//2)]
25. freqs = scipy.fftpack.fftfreq(signal.size, t-t)
26. fft_freqs = np.array(freqs)
27. freqs_side = freqs[range(N//2)]
28. fft_freqs_side = np.array(freqs_side)
29. plt.subplot(311)
30. p1 = plt.plot(t, signal, "g")
31. plt.xlabel('Time')
32. plt.ylabel('Amplitude')
33. plt.subplot(312)
34. p2 = plt.plot(freqs, FFT, "r")
35. plt.xlabel('Frequency (Hz)')
36. plt.ylabel('Count dbl-sided')
37. plt.subplot(313)
38. p3 = plt.plot(freqs_side, abs(FFT_side), "b")
39. plt.xlabel('Frequency (Hz)')
40. plt.ylabel('Count single-sided')
41. plt.tight_layout()
42. plt.show()
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