Caution

You're reading the documentation for a development version. For the latest released version, please have a look at 0.10.2.

librosa.multi_frequency_weighting

librosa.multi_frequency_weighting(frequencies, *, kinds='ZAC', **kwargs)

Compute multiple weightings of a set of frequencies.

Parameters:

frequenciesscalar or np.ndarray [shape=(n,)]

One or more frequencies (in Hz)

kindslist or tuple or str

An iterable of weighting kinds. e.g. (‘Z’, ‘B’), ‘ZAD’, ‘C’

**kwargskeywords to pass to the weighting function.

Returns:

weightingscalar or np.ndarray [shape=(len(kinds), n)]

weighting[i, j] is the weighting of frequencies[j] using the curve determined by kinds[i].

See also

perceptual_weighting

frequency_weighting

A_weighting

B_weighting

C_weighting

D_weighting

Examples

Get the A, B, C, D, and Z weightings for CQT frequencies

>>> import matplotlib.pyplot as plt
>>> freqs = librosa.cqt_frequencies(n_bins=108, fmin=librosa.note_to_hz('C1'))
>>> weightings = 'ABCDZ'
>>> weights = librosa.multi_frequency_weighting(freqs, kinds=weightings)
>>> fig, ax = plt.subplots()
>>> for label, w in zip(weightings, weights):
...     ax.plot(freqs, w, label=label)
>>> ax.set(xlabel='Frequency (Hz)', ylabel='Weighting (log10)',
...        title='Weightings of CQT frequencies')
>>> ax.legend()