def chirps(freqs, sample_rate, duration):
signals = []
for f1, f2 in zip(freqs, freqs[1:]):
signals.append(
librosa.chirp(f1,
f2,
sr=sample_rate,
duration=duration / len(freqs)))
return np.concatenate(signals)
def __test(fmin, fmax, sr, length, duration, linear, phi):
y = librosa.chirp(fmin=fmin,
fmax=fmax,
sr=sr,
length=length,
duration=duration,
linear=linear,
phi=phi)
if length is not None:
assert len(y) == length
else:
assert len(y) == np.ceil(duration * sr)
def __test(fmin, fmax, sr, length, duration, linear, phi):
y = librosa.chirp(fmin=fmin,
fmax=fmax,
sr=sr,
length=length,
duration=duration,
linear=linear,
phi=phi)
if length is not None:
assert len(y) == length
else:
assert len(y) == np.ceil(duration * sr)
def y_chirp():
sr = 22050
y = librosa.chirp(55, 55 * 2**3, length=sr // 8, sr=sr)
return y
def y_chirp():
sr = 22050
y = librosa.chirp(fmin=55, fmax=55 * 2**3, length=sr // 8, sr=sr)
return y
# We'll also use `mir_eval` to synthesize a signal for us
import mir_eval.sonify
# %%
# Playing a synthetic sound
# -------------------------
# The IPython Audio widget accepts raw numpy data as
# audio signals. This means we can synthesize signals
# directly and play them back in the browser.
#
# For example, we can make a sine sweep from C3 to C5:
sr = 22050
y_sweep = librosa.chirp(fmin=librosa.note_to_hz('C3'),
fmax=librosa.note_to_hz('C5'),
sr=sr,
duration=1)
Audio(data=y_sweep, rate=sr)
# %%
# Playing a real sound
# --------------------
# Of course, we can also play back real recorded sounds
# in the same way.
#
y, sr = librosa.load(librosa.ex('trumpet'))
Audio(data=y, rate=sr)
# %%