def coupled_TF(Y1, Y2):
d = dvma.DataSet()
Y1.tf_data_list[0].tf_coherence = None
Y2.tf_data_list[0].tf_coherence = None
Y1d = Y1.tf_data_list[0].tf_data
Y2d = Y2.tf_data_list[0].tf_data
Yc = 1 / (1 / Y1d + 1 / Y2d)
f = Y1.tf_data_list[0].freq_axis
settings = Y1.tf_data_list[0].settings
tf_data_coupled = dvma.TfData(
f,
Yc,
None,
settings,
id_link=[Y1.tf_data_list[0].id_link, Y2.tf_data_list[0].id_link],
test_name='predicted')
d.add_to_dataset(Y1.tf_data_list[0])
d.add_to_dataset(Y2.tf_data_list[0])
d.add_to_dataset(tf_data_coupled)
return d
def measure_tf2(fs=8000, T=3, fmin=20, fmax=500):
# sweep
Tr = 0.1
t, win = window_signal(fs, T, Tr=0.1)
N = len(t)
x = np.zeros(N)
y = np.zeros(N)
x = win * ss.chirp(t, fmin, T - 6 * Tr, fmax)
f = np.fft.rfftfreq(N, 1 / fs)
#%% LOG DATA
print('Sweep: {} to {} (Hz)'.format(fmin, fmax))
y = sd.playrec(x, samplerate=fs, channels=1, blocking=True)
X = np.fft.rfft(x)
Y = np.fft.rfft(y[:, 0])
G2 = Y / X
settings = dvma.MySettings(fs=fs, channels=1)
tfdata = dvma.TfData(f, G2, None, settings, test_name='sweep')
plot_tf(tfdata)
return tfdata
def save(self, b):
self.out.clear_output(wait=False)
with self.out:
i_sort = np.argsort(self.f)
ff = self.f[i_sort]
GG = self.G[i_sort]
tf_data = dvma.TfData(ff,
GG,
None,
self.rec.settings,
test_name='stepped_sine')
d = dvma.DataSet(tf_data)
d.save_data()
def measure_tf1(fs=8000, T=2, fmin=20, fmax=500, NF=20):
# stepped sine
global fig, ax
#%% LOG DATA
t = np.arange(0, T, 1 / fs)
N = len(t)
f = np.fft.rfftfreq(N, 1 / fs)
freqs = np.linspace(fmin, fmax, NF)
freqs = si.griddata(f, f, freqs, 'nearest')
G1 = np.zeros(len(freqs), dtype=complex)
c = -1
for freq in freqs:
c += 1
t, win = window_signal(fs, T, Tr=0.1)
x = np.sin(2 * np.pi * freq * t)
x *= win
print('Frequency = {} (Hz)'.format(freq))
y = sd.playrec(x, samplerate=fs, channels=1, blocking=True)
X = np.fft.rfft(x)
Y = np.fft.rfft(y[:, 0])
IX = np.argmax(np.abs(X))
IY = np.argmax(np.abs(Y))
G = Y[IY] / X[IX]
G1[c] = G
ax.plot(freq,
20 * np.log10(np.abs(G)),
'x',
markeredgewidth=5,
markersize=20,
color=[0, 0, 0.8],
label="stepped sine")
fig.canvas.draw()
fig.canvas.flush_events()
settings = dvma.MySettings(fs=fs, channels=1)
tfdata = dvma.TfData(freqs, G1, None, settings, test_name='stepped_sine')
#ax.plot(freq,20*np.log10(np.abs(G1)),'x',markeredgewidth=5,markersize=20,color = [0, 0, 0.8],label="stepped sine")
return tfdata
def measure_tf4(filename='sample2021.wav', fs=8000, T=5.9, fmin=20, fmax=500):
# signal
fs, x = wf.read(filename)
Nend = np.int(np.round(fs * T))
x = x[0:Nend, 0]
y = sd.playrec(x, samplerate=fs, channels=1, blocking=True)
N = len(x)
f = np.fft.rfftfreq(N, 1 / fs)
X = np.fft.rfft(x)
Y = np.fft.rfft(y[:, 0])
G4 = Y / X
#%% STORE
settings = dvma.MySettings(fs=fs, channels=1)
tfdata = dvma.TfData(f, G4, None, settings, test_name='sample')
plot_tf(tfdata)
return tfdata
def measure_tf3(fs=8000, T=3, fmin=20, fmax=500):
# noise
t, win = window_signal(fs, T, Tr=0.1)
N = len(t)
x = np.zeros(N)
y = np.zeros(N)
f = np.fft.rfftfreq(N, 1 / fs)
XS = np.zeros(len(f))
XS[(f > fmin) & (f < fmax)] = 1
phase = 2 * np.pi * np.random.rand(len(XS))
XS = XS * np.exp(1j * phase)
xs = np.fft.irfft(XS)
xs = win * xs
#xs = np.transpose(xs)
x = xs / np.max(np.abs(xs))
#%% LOG DATA
print('Sweep: {} to {} (Hz)'.format(fmin, fmax))
y = sd.playrec(x, samplerate=fs, channels=1, blocking=True)
X = np.fft.rfft(x)
Y = np.fft.rfft(y[:, 0])
G3 = Y / X
#%% STORE
settings = dvma.MySettings(fs=fs, channels=1)
tfdata = dvma.TfData(f, G3, None, settings, test_name='noise')
plot_tf(tfdata)
return tfdata