Caution

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librosa.effects.harmonic

librosa.effects.harmonic(y, *, kernel_size=31, power=2.0, mask=False, margin=1.0, n_fft=2048, hop_length=None, win_length=None, window='hann', center=True, pad_mode='constant')[source]

Extract harmonic elements from an audio time-series.

Parameters:

ynp.ndarray [shape=(…, n)]: audio time series. Multi-channel is supported.
kernel_size
power
mask
margin: See librosa.deocmpose.hpss
n_fft
hop_length
win_length
window
center
pad_mode: See librosa.stft

Returns:

y_harmonicnp.ndarray [shape=(…, n)]: audio time series of just the harmonic portion

See also

hpss: Separate harmonic and percussive components
percussive: Extract only the percussive component
librosa.decompose.hpss: HPSS for spectrograms

Examples

>>> # Extract harmonic component
>>> y, sr = librosa.load(librosa.ex('choice'))
>>> y_harmonic = librosa.effects.harmonic(y)

>>> # Use a margin > 1.0 for greater harmonic separation
>>> y_harmonic = librosa.effects.harmonic(y, margin=3.0)