Signale und Systeme - Digitale Signalverarbeitung - Audiodaten filtern mit Python

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[@rudigerheintz4583]

Quellcode:
import multiprocessing as multiproc
import numpy as np
import soundfile as sf
import pyaudio
import matplotlib.pyplot as plt
def run(value,value2,fig,fileName,saveValue=None):
data, fs = sf.read(fileName)
if(data.ndim>1): data=data[:,0]
ts=1/fs
nt=data.size
T=nt*ts
t = np.arange(0, T,ts)
i = np.arange(-40, 40.1,1)
fx= np.arange(-fs/2, fs/2,1/T)
P=1+value/100*27
Q=1+value2/100*10
gabor=np.exp(-(i*i)*Q/(40*40))*np.sin(2*np.pi*P*i/len(i))
res=np.convolve(data, gabor, mode='same')
fig.clf()
fig.suptitle(fileName+' fs='+str(fs)+" Hz", fontsize=16)
ax = fig.add_subplot(3, 2, 1)
ax.plot(t, data)
ax = fig.add_subplot(3, 2, 2)
ax.plot(fx,np.fft.fftshift(np.abs(np.fft.fft(data)))/nt)
ax = fig.add_subplot(3, 2, 3)
ax.plot(i, gabor)
ax = fig.add_subplot(3, 2, 4)
ax.plot(np.fft.fftshift(np.abs(np.fft.fft(gabor)))/nt)
ax = fig.add_subplot(3, 2, 5)
ax.plot(t, res)
ax = fig.add_subplot(3, 2, 6)
ax.plot(fx,np.fft.fftshift(np.abs(np.fft.fft(res)))/nt)

fig.canvas.draw()
res=res/np.max(np.abs(res))
multiproc.Process(target=playAudio,args=(res,fs)).start()
def playAudio(dat,samplerate):
stream = pyaudio.PyAudio().open(format = pyaudio.paFloat32,channels = 1,rate = samplerate,output = True)
stream.write(dat.astype(np.float32).tobytes())
stream.close()
if __name__ == '__main__':
run(60,0,plt.figure(),"flying-mosquito-105770.mp3")
plt.show()

[@paweleliasz9642]

Interesant Danke

[@rudigerheintz4583]

Freut mich.