librosa.filters.chroma

librosa.filters.chroma(sr, n_fft, n_chroma=12, A440=440.0, ctroct=5.0, octwidth=2, norm=2, base_c=True)

Create a Filterbank matrix to convert STFT to chroma

Parameters:

sr : number > 0 [scalar]

audio sampling rate

n_fft : int > 0 [scalar]

number of FFT bins

n_chroma : int > 0 [scalar]

number of chroma bins

A440 : float > 0 [scalar]

Reference frequency for A440

ctroct : float > 0 [scalar]

octwidth : float > 0 or None [scalar]

ctroct and octwidth specify a dominance window - a Gaussian weighting centered on ctroct (in octs, A0 = 27.5Hz) and with a gaussian half-width of octwidth. Set octwidth to None to use a flat weighting.

norm : float > 0 or np.inf

Normalization factor for each filter

base_c : bool

If True, the filter bank will start at ‘C’. If False, the filter bank will start at ‘A’.

Returns:

wts : ndarray [shape=(n_chroma, 1 + n_fft / 2)]

Chroma filter matrix

See also

util.normalize, feature.chroma_stft

Notes

This function caches at level 10.

Examples

Build a simple chroma filter bank

>>> chromafb = librosa.filters.chroma(22050, 4096)
array([[  1.689e-05,   3.024e-04, ...,   4.639e-17,   5.327e-17],
       [  1.716e-05,   2.652e-04, ...,   2.674e-25,   3.176e-25],
...,
       [  1.578e-05,   3.619e-04, ...,   8.577e-06,   9.205e-06],
       [  1.643e-05,   3.355e-04, ...,   1.474e-10,   1.636e-10]])

Use quarter-tones instead of semitones

>>> librosa.filters.chroma(22050, 4096, n_chroma=24)
array([[  1.194e-05,   2.138e-04, ...,   6.297e-64,   1.115e-63],
       [  1.206e-05,   2.009e-04, ...,   1.546e-79,   2.929e-79],
...,
       [  1.162e-05,   2.372e-04, ...,   6.417e-38,   9.923e-38],
       [  1.180e-05,   2.260e-04, ...,   4.697e-50,   7.772e-50]])

Equally weight all octaves

>>> librosa.filters.chroma(22050, 4096, octwidth=None)
array([[  3.036e-01,   2.604e-01, ...,   2.445e-16,   2.809e-16],
       [  3.084e-01,   2.283e-01, ...,   1.409e-24,   1.675e-24],
...,
       [  2.836e-01,   3.116e-01, ...,   4.520e-05,   4.854e-05],
       [  2.953e-01,   2.888e-01, ...,   7.768e-10,   8.629e-10]])

>>> import matplotlib.pyplot as plt
>>> plt.figure()
>>> librosa.display.specshow(chromafb, x_axis='linear')
>>> plt.ylabel('Chroma filter')
>>> plt.title('Chroma filter bank')
>>> plt.colorbar()
>>> plt.tight_layout()

(Source code)