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
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]