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

librosa.pitch_tuning

librosa.pitch_tuning(frequencies, *, resolution=0.01, bins_per_octave=12)[source]

Given a collection of pitches, estimate its tuning offset (in fractions of a bin) relative to A440=440.0Hz.

Parameters:

frequenciesarray-like, float: A collection of frequencies detected in the signal. See piptrack
resolutionfloat in (0, 1): Resolution of the tuning as a fraction of a bin. 0.01 corresponds to cents.
bins_per_octaveint > 0 [scalar]: How many frequency bins per octave

Returns:

tuning: float in [-0.5, 0.5): estimated tuning deviation (fractions of a bin)

See also

estimate_tuning: Estimating tuning from time-series or spectrogram input

Examples

>>> # Generate notes at +25 cents
>>> freqs = librosa.cqt_frequencies(n_bins=24, fmin=55, tuning=0.25)
>>> librosa.pitch_tuning(freqs)
0.25

>>> # Track frequencies from a real spectrogram
>>> y, sr = librosa.load(librosa.ex('trumpet'))
>>> freqs, times, mags = librosa.reassigned_spectrogram(y, sr=sr,
...                                                     fill_nan=True)
>>> # Select out pitches with high energy
>>> freqs = freqs[mags > np.median(mags)]
>>> librosa.pitch_tuning(freqs)
-0.07