cr.sparse.wt.dwt

cr.sparse.wt.dwt(data, wavelet, mode='symmetric', axis=- 1)[source]

Computes single level discrete wavelet decomposition

Parameters

  • data (jax.numpy.ndarray) – Input signal array whose DWT is to be computed

  • wavelet (str or cr.sparse.wt.DiscreteWavelet) – The wavelet to be used to compute DWT (by name or object)

  • mode (str, optional) – Signal extension mode to be used during DWT computation. Default ‘symmetric’. See Modes for available modes.

  • axis (int, optional) – The axis along which the vectors from data will be picked for computing DWT. Default -1 (last axis).

Returns

A tuple (cA, cD) containing the approximation and detail coefficients for the data.

Return type

(jax.numpy.ndarray, jax.numpy.ndarray)

Example

Computing the haar/db1 wavelet decomposition:

>>> ca, cd = wt.dwt([1,2,3,4,4,3,2,1], 'db1')
>>> print(ca)
>>> print(cd)
[2.12132034 4.94974747 4.94974747 2.12132034]
[-0.70710678 -0.70710678  0.70710678  0.70710678]