mvpa2.mappers.wavelet.WaveletPacketMapper

class mvpa2.mappers.wavelet.WaveletPacketMapper(level=None, **kwargs)

Convert signal into an overcomplete representaion using Wavelet packet

Notes

Available conditional attributes:

• calling_time+: None
• raw_results: None
• trained_dataset: None
• trained_nsamples+: None
• trained_targets+: None
• training_time+: None

(Conditional attributes enabled by default suffixed with +)

Methods

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.

enable_ca : None or list of str

Names of the conditional attributes which should be enabled in addition to the default ones

disable_ca : None or list of str

Names of the conditional attributes which should be disabled

dim : int or tuple of int

dimensions to work across (for now just scalar value, ie 1D transformation) is supported

wavelet : str

one from the families available withing pywt package

mode : str

periodization mode

maxlevel : int or None

number of levels to use. If None - automatically selected by pywt

Methods