chords = [
m21.chord.Chord((soprano[i], alto[i], tenor[i], bass[i]))
for i in range(len(soprano))
]
# row = chord, column = melody
chord_freqs = np.array([[pitch.frequency for pitch in chord.pitches]
for chord in chords])
note_sigs = [[
sts.ClarinetApproxSignal(freq=freq,
duration=note_duration,
samp_rate=samp_rate) for freq in chord_freqs.T[i]
] for i in range(len(chord_freqs))]
melody_data = np.array([nst.NonStationarySignal(ns).data for ns in note_sigs])
left_signal = np.sum((left_intensities * melody_data.T).T, axis=0)
right_signal = np.sum(((1 - left_intensities) * melody_data.T).T, axis=0)
src = np.array((left_signal, right_signal))
_, left_recons, right_recons, extra = adress.adress(
left_signal=left_signal,
right_signal=right_signal,
samp_rate=samp_rate,
left_ds=left_ds,
left_Hs=left_Hs,
right_ds=right_ds,
right_Hs=right_Hs,
beta=beta,
window=window,
durations = [1] * n_signals
# durations = [max(1 - i * 0.25, 0.25) for i in range(n_signals)]
window = "blackmanharris"
#
# Generate data
#
freqs = np.arange(n_signals) * freq_inc + base_freq
signals = [
ss.SineSignal(freq=freqs[i], duration=durations[i], samp_rate=samp_rate)
for i in range(len(freqs))
]
nst = nsts.NonStationarySignal(signals)
# Compute FFT
# Compute STFT
# f: Array of sample frequencies, len 129 real numbers. [0. , 172.265625 , 344.53125...]
# t: Array of segment times, len 1380 real numbers. [0. , 0.00290249 , 0.00580499...]
# Zxx: STFT of x
f, t, Zxx = signal.stft(x=nst.data,
fs=nst.samp_rate,
window=window,
nperseg=100)
print(t.shape, f.shape, Zxx.shape)
# print(f.shape, f[:10])
# print(t.shape, t[:10])
# print(Zxx.shape, Zxx[:10])
#
# Generate signals
#
freqs = anotes.major_chord(scale_name=scale_name, n_notes=n_notes, output="freq")
note_names = " ".join([n.nameWithOctave for n in
anotes.major_chord(scale_name=scale_name, n_notes=n_notes,
output="note")])
underline_note_names = note_names.replace(" ", "_")
duration = sum(durations)
signals = [ss.SineSignal(freq=freqs[i],
duration=durations[i],
samp_rate=samp_rate)
for i in range(len(freqs))]
melody = nsts.NonStationarySignal(signals)
chord = sts.StationarySignal(sin_freqs=freqs,
sin_coeffs=[1] * n_notes,
duration=duration,
samp_rate=samp_rate)
# Only consider positive frequencies (since the spectrum is symmetric)
melody_fft_x = fftfreq(melody.samp_nums.shape[0], 1 / melody.samp_rate)
chord_fft_x = fftfreq(chord.samp_nums.shape[0], 1 / chord.samp_rate)
slice_num = np.where(melody_fft_x > freqs[-1] * 2)[0][0]
# FFT of both
melody_fft = fft(melody.data)[:slice_num] / (melody.duration * samp_rate)
chord_fft = fft(chord.data)[:slice_num] / (chord.duration * samp_rate)
#