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# librosa.multi_frequency_weighting

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

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]`.

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()
```