def plot(self): ''' function to plot the level over time ''' data = self.audiobuffer.newdata() r_m_s = dB(rms(data)) self.stream_data[0:-1] = self.stream_data[1:] self.stream_data[-1] = r_m_s self.PlotSpek.read_array(self.stream_data)
def plot(self): ''' function for Plotting each channel gain as a bar plot''' data = self.audiobuffer.newdata() nchannel, _ = data.shape channel_dB = np.zeros((nchannel), float) #index = np.arange(nchannel) for i in range(nchannel): channel_dB[i] = dB(rms(data[i, :])) nchannel = np.arange(nchannel) self.PlotChannel.readArray(channel_dB, nchannel)
def plot(self, weight): data = self.audiobuffer.newdata() ''' function to obtain and plot the third octave level ''' self.weight = weight self.block = array(data, dtype=float64) self.thirdpow = [] if self.weight == 1: self.frequenzbewertung = self.frequenzbewertung_a elif self.weight == 2: self.frequenzbewertung = self.frequenzbewertung_c else: self.frequenzbewertung = [0.0] * len(self.fc) # obtainment of the third octave levels for freq in range(len(self.fc)): freqpow = (dB(rms(lfilter(self.b[freq], self.a[freq], self.block[:])[0])) + self.frequenzbewertung[freq]) self.thirdpow.append(freqpow) self.PlotSpektro.readArray(self.thirdpow)
def plot(self, weight): data = self.audiobuffer.newdata() ''' function to obtain and plot the third octave level ''' self.weight = weight self.block = array(data, dtype=float64) self.thirdpow = [] if self.weight == 1: self.frequenzbewertung = self.frequenzbewertung_a elif self.weight == 2: self.frequenzbewertung = self.frequenzbewertung_c else: self.frequenzbewertung = [0.0] * len(self.fc) # obtainment of the third octave levels for freq in range(len(self.fc)): freqpow = (dB( rms(lfilter(self.b[freq], self.a[freq], self.block[:])[0])) + self.frequenzbewertung[freq]) self.thirdpow.append(freqpow) self.PlotSpektro.readArray(self.thirdpow)
plt.figure() #fs, fftlines, overlap=overlap, win='hann', averaging='exp',nAverage=10 sp = spectral(fs, fs*5, overlap=0.75, win='hanning', averaging='overall',nAverage=10,winParam={"sym":False},detrend='constant') w1 = sp.w sp.add(y) Y, f = sp.get() plt.semilogy(f,Y) plt.xlabel('f(Hz)') sp = spectral(fs, fs*5, overlap=0.75, win='general_cosine', averaging='overall',nAverage=10,winParam={"sym":False,"a":[1, 1.942604, 1.340318, 0.440811, 0.043097]},detrend='constant') w2 = sp.w sp.add(y) Y, f = sp.get() plt.semilogy(f,Y) plt.legend() plt.figure() plt.plot(w1,lw=0.5) plt.plot(w2) print("temporal rms",calc.rms(y)) ecf = sp.getECF() print("spectral rms",sum((Y*ecf)**2*1/2)**(1/2)) print("NENBW", sp.getNENBW()) print("ECF", ecf) print("ACF", sp.getACF()) sp.listWindows()