librosa.core.clicks¶

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

Returns a signal with the signal click placed at each specified time

Parameters:	times : np.ndarray or None times to place clicks, in seconds frames : np.ndarray or None frame indices to place clicks sr : number > 0 desired sampling rate of the output signal hop_length : int > 0 if positions are specified by frames, the number of samples between frames. click_freq : float > 0 frequency (in Hz) of the default click signal. Default is 1KHz. click_duration : float > 0 duration (in seconds) of the default click signal. Default is 100ms. click : np.ndarray or None optional click signal sample to use instead of the default blip. length : int > 0 desired number of samples in the output signal
Returns:	click_signal : np.ndarray Synthesized click signal
Raises:	ParameterError If neither times nor frames are provided. If any of click_freq, click_duration, or length are out of range.

Examples

>>> # Sonify detected beat events
>>> y, sr = librosa.load(librosa.util.example_audio_file())
>>> 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
>>> plt.figure()
>>> S = librosa.feature.melspectrogram(y=y, sr=sr)
>>> ax = plt.subplot(2,1,2)
>>> librosa.display.specshow(librosa.power_to_db(S, ref=np.max),
...                          x_axis='time', y_axis='mel')
>>> plt.subplot(2,1,1, sharex=ax)
>>> librosa.display.waveplot(y_beat_times, sr=sr, label='Beat clicks')
>>> plt.legend()
>>> plt.xlim(15, 30)
>>> plt.tight_layout()

(Source code)