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, blocklength, plotflag=1):
''' function to plot the estimated power spectral densitiy '''
# blocklength may be changed by user
self.plotflag = plotflag
self.blocklength = blocklength
data = self.audiobuffer.newdata()
# limitation of the blocklength to the next lower 2^n in case of
# drainage of buffer
if self.blocklength > len(data[0]):
self.blocklength = 2 ** (self.nextpow2(len(data[0])))
self.data = np.zeros(self.blocklength / 2)
data = data[0][:self.blocklength]
self.data_new = (abs(scipy.fft(data)))
self.data_new = dB(self.data_new[:self.blocklength / 2])
if self.blocklength != self.blocklength_old:
self.data = np.zeros(self.blocklength / 2)
self.must_plot = True
# recursive power spectral density estimation
self.data = (self.recursive_weight * self.data_new
+ (1 - self.recursive_weight) * self.data)
self.blocklength_old = self.blocklength
if self.must_plot:
# plotflag 0 sets the frequency axis to linear stepping
if self.plotflag == 0:
self.lines, = self.PlotSpek.axes.plot(np.linspace(0,
self.fs / 2,
len(self.data)),
self.data)
self.PlotSpek.axes.set_xlim(0, self.fs / 2)
# plotflag 1 sets the frequency axis to logarithmic stepping
else:
self.lines, = self.PlotSpek.axes.semilogx(np.linspace(0,
self.fs / 4, len(self.data)), self.data)
self.PlotSpek.axes.set_xlim(0, self.fs / 2)
self.PlotSpek.axes.set_ylim(-100, 30)
self.PlotSpek.axes.grid(True, which='both')
self.must_plot = False
else:
self.lines.set_ydata(self.data - 20)
self.PlotSpek.draw()
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, blocklength, plotflag=1):
''' function to plot the estimated power spectral densitiy '''
# blocklength may be changed by user
self.plotflag = plotflag
self.blocklength = blocklength
data = self.audiobuffer.newdata()
# limitation of the blocklength to the next lower 2^n in case of
# drainage of buffer
if self.blocklength > len(data[0]):
self.blocklength = 2**(self.nextpow2(len(data[0])))
self.data = np.zeros(self.blocklength / 2)
data = data[0][:self.blocklength]
self.data_new = (abs(scipy.fft(data)))
self.data_new = dB(self.data_new[:self.blocklength / 2])
if self.blocklength != self.blocklength_old:
self.data = np.zeros(self.blocklength / 2)
self.must_plot = True
# recursive power spectral density estimation
self.data = (self.recursive_weight * self.data_new +
(1 - self.recursive_weight) * self.data)
self.blocklength_old = self.blocklength
if self.must_plot:
# plotflag 0 sets the frequency axis to linear stepping
if self.plotflag == 0:
self.lines, = self.PlotSpek.axes.plot(
np.linspace(0, self.fs / 2, len(self.data)), self.data)
self.PlotSpek.axes.set_xlim(0, self.fs / 2)
# plotflag 1 sets the frequency axis to logarithmic stepping
else:
self.lines, = self.PlotSpek.axes.semilogx(
np.linspace(0, self.fs / 4, len(self.data)), self.data)
self.PlotSpek.axes.set_xlim(0, self.fs / 2)
self.PlotSpek.axes.set_ylim(-100, 30)
self.PlotSpek.axes.grid(True, which='both')
self.must_plot = False
else:
self.lines.set_ydata(self.data - 20)
self.PlotSpek.draw()
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)
