Caution

You're reading an old version of this documentation. If you want up-to-date information, please have a look at 0.9.1.

librosa.core.pitch_tuning¶

librosa.core.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(24, 55, tuning=0.25)
>>> librosa.pitch_tuning(freqs)
0.25

>>> # Track frequencies from a real spectrogram
>>> y, sr = librosa.load(librosa.util.example_audio_file())
>>> pitches, magnitudes, stft = librosa.ifptrack(y, sr)
>>> # Select out pitches with high energy
>>> pitches = pitches[magnitudes > np.median(magnitudes)]
>>> librosa.pitch_tuning(pitches)
0.089999999999999969