librosa.beat.estimate_tempo

librosa.beat.estimate_tempo(onset_envelope, sr=22050, hop_length=512, start_bpm=120, std_bpm=1.0, ac_size=4.0, duration=90.0, offset=0.0)[source]

Estimate the tempo (beats per minute) from an onset envelope

Warning

Deprecated in librosa 0.5 Functionality is superseded by librosa.beat.tempo.

Parameters:

onset_envelope : np.ndarray [shape=(n,)]

onset strength envelope

sr : number > 0 [scalar]

sampling rate of the time series

hop_length : int > 0 [scalar]

hop length of the time series

start_bpm : float [scalar]

initial guess of the BPM

std_bpm : float > 0 [scalar]

standard deviation of tempo distribution

ac_size : float > 0 [scalar]

length (in seconds) of the auto-correlation window

duration : float > 0 [scalar]

length of signal (in seconds) to use in estimating tempo

offset : float > 0 [scalar]

offset (in seconds) of signal sample to use in estimating tempo

Returns:

tempo : float [scalar]

estimated tempo (beats per minute)

Notes

This function caches at level 30.

Examples

>>> y, sr = librosa.load(librosa.util.example_audio_file())
>>> onset_env = librosa.onset.onset_strength(y, sr=sr)
>>> tempo = librosa.beat.estimate_tempo(onset_env, sr=sr)
>>> tempo
103.359375

Plot the estimated tempo against the onset autocorrelation

>>> import matplotlib.pyplot as plt
>>> # Compute 2-second windowed autocorrelation
>>> hop_length = 512
>>> ac = librosa.autocorrelate(onset_env, 2 * sr // hop_length)
>>> freqs = librosa.tempo_frequencies(len(ac), sr=sr,
...                                   hop_length=hop_length)
>>> # Plot on a BPM axis.  We skip the first (0-lag) bin.
>>> plt.figure(figsize=(8,4))
>>> plt.semilogx(freqs[1:], librosa.util.normalize(ac)[1:],
...              label='Onset autocorrelation', basex=2)
>>> plt.axvline(tempo, 0, 1, color='r', alpha=0.75, linestyle='--',
...            label='Tempo: {:.2f} BPM'.format(tempo))
>>> plt.xlabel('Tempo (BPM)')
>>> plt.grid()
>>> plt.legend(frameon=True)
>>> plt.axis('tight')

(Source code)

../_images/librosa-beat-estimate_tempo-1.png