| Multivariate Pattern Analysis in Python

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This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# mappers.wavelet

## Module: `mappers.wavelet`

Inheritance diagram for `mvpa.mappers.wavelet`:

Wavelet mappers

## Classes

### `WaveletPacketMapper`

class `mvpa.mappers.wavelet.``WaveletPacketMapper`(level=None, **kwargs)

  Bases: `mvpa.mappers.wavelet._WaveletMapper`

  Convert signal into an overcomplete representaion using Wavelet packet

  Initialize WaveletPacketMapper mapper

  Parameters: | level (int or None) – What level to decompose at. If ‘None’ data for all levels is provided, but due to different sizes, they are placed in 1D row.

### `WaveletTransformationMapper`

class `mvpa.mappers.wavelet.``WaveletTransformationMapper`(dim=1, wavelet='sym4', mode='per', maxlevel=None)

  Bases: `mvpa.mappers.wavelet._WaveletMapper`

  Convert signal into wavelet representaion

  Initialize _WaveletMapper mapper

  Parameters:

  - dim (int or tuple of int) – dimensions to work across (for now just scalar value, ie 1D transformation) is supported
  - wavelet (basestring) – one from the families available withing pywt package
  - mode (basestring) – periodization mode
  - maxlevel (int or None) – number of levels to use. If None - automatically selected by pywt

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