def get_f0(audio, sampling_rate=22050, frame_length=1024,
hop_length=256, f0_min=100, f0_max=300, harm_thresh=0.1):
f0, harmonic_rates, argmins, times = compute_yin(
audio, sampling_rate, frame_length, hop_length, f0_min, f0_max,
harm_thresh)
pad = int((frame_length / hop_length) / 2)
f0 = [0.0] * pad + f0 + [0.0] * pad
f0 = np.array(f0, dtype=np.float32)
return f0
def toyModel(TMax, h):
omega1 = 2764.
t0 = np.arange(-5, 0, h)
X0 = np.zeros((len(t0), 4))
X0[:, 0] = 1e-1 + 0 * np.cos(100 * np.pi * t0)
X0[:, 1] = 0 * np.cos(3 * np.pi / 2 * t0)
T = TMax * omega1
t, X = dde.rk4Delay(t0, X0, T, 'toy.c', [30, T])
p = X[:, 0] + X[:, 2]
#plt.plot(t, p)
# Calcul les fréquences
w_len = 1024 * 4
w_step = 256 * 4
f0_min = 0.05
f0_max = 3
harmo_thresh = 0.85
sr = int(1 / (t[1] - t[0]))
pitches, harmonic_rates, argmins, times = yin.compute_yin(
p[len(t0):], sr, None, w_len, w_step, f0_min, f0_max, harmo_thresh)
pitches = np.array(pitches)
times = np.array(times)
# Changements de signes
""" Calcul bourrin
I = np.where(p[1:]*p[:-1] < 0)[0]
F = t[I]
treal = 0.1+(T/2-abs(t[I[2:]]-T/2))*30/T
Freal = omega1/(F[2:]-F[:-2])
plt.plot(treal[:len(treal)//2], Freal[:len(treal)//2])
plt.plot(treal[len(treal)//2:], Freal[len(Freal)//2:])"""
tau = 0.1 + (T / 2 - abs(times - T / 2)) * 30 / T
#print(times[-1], t[-1])
plt.plot(tau[:len(tau) // 2], omega1 * np.array(pitches[:len(tau) // 2]))
#plt.plot(tau[len(tau)//2:], omega1*np.array(pitches[len(tau)//2:]))
from scipy.io.wavfile import write
scaled = np.int16(p / np.max(np.abs(p)) * 32767)
write('test.wav', int(sr * omega1), scaled)
def transform_f0(wav, hparams):
sampling_rate = hparams.sampling_rate
frame_length = hparams.filter_length
hop_length = hparams.hop_length
f0_min = hparams.f0_min
f0_max = hparams.f0_max
harm_thresh = hparams.harm_thresh
f0, harmonic_rates, argmins, times = compute_yin(wav, sampling_rate,
frame_length, hop_length,
f0_min, f0_max,
harm_thresh)
pad = int((frame_length / hop_length) / 2)
f0 = [0.0] * pad + f0 + [0.0] * pad
f0 = np.array(f0, dtype=np.float32)
return f0
def runYin(result,
s,
sr,
w_len=1024,
w_step=512,
f0_min=70,
f0_max=450,
harmo_thresh=0.15):
print("Charger F0")
pitches, harmonic_rates, argmins, times = yin.compute_yin(
s,
sr,
None,
w_len=w_len,
w_step=w_step,
f0_min=f0_min,
f0_max=f0_max,
harmo_thresh=harmo_thresh)
pitches = filterPitches(pitches, argmins, 2, 98)
F0 = np.array(zip(times, pitches, harmonic_rates, argmins))
f0Time = time()
result.append(F0)
result.append(f0Time)
def stateArtModel(TMax, h, params, alg='rk4Neutral', interpOrder=2):
t0 = np.arange(-1e-2, h, h)
X0 = np.zeros((len(t0), 2 * K + 2))
label = 'h= ' + str(h) + ', ' + alg #str(h) + ', ' + str(params) +
for i in range(2 * K + 2):
if i % 2 == 0:
X0[:, i] = 1e-6 * np.cos(2 * np.pi * t0 * omega1 / 3.5)
else:
X0[:, i] = -1e-6 * np.sin(2 * np.pi * t0 * omega1 / 3.5)
t0 *= omega1
T = TMax * omega1
t, X = dde.rk4Delay(t0,
X0,
T,
'stateArt.c',
params,
alg=alg,
interpOrder=interpOrder)
p = np.sum(X[:, ::2], axis=1)
# plt.figure("Wave")
# plt.plot(t/omega1, p, label=label)
# plt.legend()
# Calcul les fréquences
w_len = 1024 * 8
w_step = 256 // 2
f0_min = 200
f0_max = 2500
harmo_thresh = 0.6
sr = int(omega1 / (t[1] - t[0]))
pitches, harmonic_rates, argmins, times = yin.compute_yin(
p[len(t0):], sr, None, w_len, w_step, f0_min, f0_max, harmo_thresh)
pitches = np.array(pitches)
times = np.array(times)
Pm = params[0] + (TMax / 2 - abs(times - TMax / 2)) / TMax * (params[1] -
params[0])
plt.figure("Yin")
ax = plt.gca()
color = next(ax._get_lines.prop_cycler)['color']
plt.plot(Pm[:len(Pm) // 2],
np.array(pitches[:len(Pm) // 2]),
'-',
c=color,
label=label)
plt.plot(Pm[len(Pm) // 2:], np.array(pitches[len(Pm) // 2:]), ':', c=color)
plt.legend()
from scipy.io.wavfile import write
scaled = np.int16(p / np.max(np.abs(p)) * 32767)
write('test' + '.'.join(str(e) for e in params) + '.wav', int(sr), scaled)
