Caution

You're reading the documentation for a development version. For the latest released version, please have a look at 0.9.1.

librosa.filters.chroma

librosa.filters.chroma(*, sr, n_fft, n_chroma=12, tuning=0.0, ctroct=5.0, octwidth=2, norm=2, base_c=True, dtype=<class 'numpy.float32'>)

Create a chroma filter bank.

This creates a linear transformation matrix to project FFT bins onto chroma bins (i.e. pitch classes).

Parameters

srnumber > 0 [scalar]

audio sampling rate

n_fftint > 0 [scalar]

number of FFT bins

n_chromaint > 0 [scalar]

number of chroma bins

tuningfloat

Tuning deviation from A440 in fractions of a chroma bin.

ctroctfloat > 0 [scalar]

octwidthfloat > 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.

normfloat > 0 or np.inf

Normalization factor for each filter

base_cbool

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

dtypenp.dtype

The data type of the output basis. By default, uses 32-bit (single-precision) floating point.

Returns

wtsndarray [shape=(n_chroma, 1 + n_fft / 2)]

Chroma filter matrix

See also

librosa.util.normalize

librosa.feature.chroma_stft

Notes

This function caches at level 10.

Examples

Build a simple chroma filter bank

>>> chromafb = librosa.filters.chroma(sr=22050, n_fft=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(sr=22050, n_fft=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(sr=22050, n_fft=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
>>> fig, ax = plt.subplots()
>>> img = librosa.display.specshow(chromafb, x_axis='linear', ax=ax)
>>> ax.set(ylabel='Chroma filter', title='Chroma filter bank')
>>> fig.colorbar(img, ax=ax)