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librosa.util.axis_sort

librosa.util.axis_sort(S, axis=- 1, index=False, value=None)

Sort an array along its rows or columns.

Parameters

Snp.ndarray [shape=(d, n)]

Array to be sorted

axisint [scalar]

The axis along which to compute the sorting values

• axis=0 to sort rows by peak column index

• axis=1 to sort columns by peak row index

indexboolean [scalar]

If true, returns the index array as well as the permuted data.

valuefunction

function to return the index corresponding to the sort order. Default: np.argmax.

Returns

S_sortnp.ndarray [shape=(d, n)]

S with the columns or rows permuted in sorting order

idxnp.ndarray (optional) [shape=(d,) or (n,)]

If index == True, the sorting index used to permute S. Length of idx corresponds to the selected axis.

Raises

ParameterError

If S does not have exactly 2 dimensions (S.ndim != 2)

Examples

Visualize NMF output for a spectrogram S

>>> # Sort the columns of W by peak frequency bin
>>> y, sr = librosa.load(librosa.util.example_audio_file())
>>> S = np.abs(librosa.stft(y))
>>> W, H = librosa.decompose.decompose(S, n_components=32)
>>> W_sort = librosa.util.axis_sort(W)

Or sort by the lowest frequency bin

>>> W_sort = librosa.util.axis_sort(W, value=np.argmin)

Or sort the rows instead of the columns

>>> W_sort_rows = librosa.util.axis_sort(W, axis=0)

Get the sorting index also, and use it to permute the rows of H

>>> W_sort, idx = librosa.util.axis_sort(W, index=True)
>>> H_sort = H[idx, :]

>>> import matplotlib.pyplot as plt
>>> plt.figure()
>>> plt.subplot(2, 2, 1)
>>> librosa.display.specshow(librosa.amplitude_to_db(W, ref=np.max),
...                          y_axis='log')
>>> plt.title('W')
>>> plt.subplot(2, 2, 2)
>>> librosa.display.specshow(H, x_axis='time')
>>> plt.title('H')
>>> plt.subplot(2, 2, 3)
>>> librosa.display.specshow(librosa.amplitude_to_db(W_sort,
...                                                  ref=np.max),
...                          y_axis='log')
>>> plt.title('W sorted')
>>> plt.subplot(2, 2, 4)
>>> librosa.display.specshow(H_sort, x_axis='time')
>>> plt.title('H sorted')
>>> plt.tight_layout()
>>> plt.show()