librosa.clicks(times=None, frames=None, sr=22050, hop_length=512, click_freq=1000.0, click_duration=0.1, click=None, length=None)[source]

Construct a “click track”.

This returns a signal with the signal click sound placed at each specified time.

timesnp.ndarray or None

times to place clicks, in seconds

framesnp.ndarray or None

frame indices to place clicks

srnumber > 0

desired sampling rate of the output signal

hop_lengthint > 0

if positions are specified by frames, the number of samples between frames.

click_freqfloat > 0

frequency (in Hz) of the default click signal. Default is 1KHz.

click_durationfloat > 0

duration (in seconds) of the default click signal. Default is 100ms.

clicknp.ndarray or None

optional click signal sample to use instead of the default click.

lengthint > 0

desired number of samples in the output signal


Synthesized click signal

  • If neither times nor frames are provided.

  • If any of click_freq, click_duration, or length are out of range.


>>> # Sonify detected beat events
>>> y, sr = librosa.load(librosa.ex('choice'), duration=10)
>>> tempo, beats = librosa.beat.beat_track(y=y, sr=sr)
>>> y_beats = librosa.clicks(frames=beats, sr=sr)
>>> # Or generate a signal of the same length as y
>>> y_beats = librosa.clicks(frames=beats, sr=sr, length=len(y))
>>> # Or use timing instead of frame indices
>>> times = librosa.frames_to_time(beats, sr=sr)
>>> y_beat_times = librosa.clicks(times=times, sr=sr)
>>> # Or with a click frequency of 880Hz and a 500ms sample
>>> y_beat_times880 = librosa.clicks(times=times, sr=sr,
...                                  click_freq=880, click_duration=0.5)

Display click waveform next to the spectrogram

>>> import matplotlib.pyplot as plt
>>> fig, ax = plt.subplots(nrows=2, sharex=True)
>>> S = librosa.feature.melspectrogram(y=y, sr=sr)
>>> librosa.display.specshow(librosa.power_to_db(S, ref=np.max),
...                          x_axis='time', y_axis='mel', ax=ax[0])
>>> librosa.display.waveshow(y_beat_times, sr=sr, label='Beat clicks',
...                          ax=ax[1])
>>> ax[1].legend()
>>> ax[0].label_outer()
>>> ax[0].set_title(None)