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) # %%