Module wavelet.wavelets.coif3

Coiflets 3 wavelet

""" Coiflets 3 wavelet """


class Coiflets3:
    """
    Properties
    ----------
     near symmetric, orthogonal, biorthogonal

    All values are from http://wavelets.pybytes.com/wavelet/coif3/
    """
    __name__ = "Coiflets Wavelet 3"
    __motherWaveletLength__ = 18  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        -3.459977283621256e-05,
        -7.098330313814125e-05,
        0.0004662169601128863,
        0.0011175187708906016,
        -0.0025745176887502236,
        -0.00900797613666158,
        0.015880544863615904,
        0.03455502757306163,
        -0.08230192710688598,
        -0.07179982161931202,
        0.42848347637761874,
        0.7937772226256206,
        0.4051769024096169,
        -0.06112339000267287,
        -0.0657719112818555,
        0.023452696141836267,
        0.007782596427325418,
        -0.003793512864491014,
    ]

    # high-pass
    decompositionHighFilter = [
        0.003793512864491014,
        0.007782596427325418,
        -0.023452696141836267,
        -0.0657719112818555,
        0.06112339000267287,
        0.4051769024096169,
        -0.7937772226256206,
        0.42848347637761874,
        0.07179982161931202,
        -0.08230192710688598,
        -0.03455502757306163,
        0.015880544863615904,
        0.00900797613666158,
        -0.0025745176887502236,
        -0.0011175187708906016,
        0.0004662169601128863,
        7.098330313814125e-05,
        -3.459977283621256e-05,
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        -0.003793512864491014,
        0.007782596427325418,
        0.023452696141836267,
        -0.0657719112818555,
        -0.06112339000267287,
        0.4051769024096169,
        0.7937772226256206,
        0.42848347637761874,
        -0.07179982161931202,
        -0.08230192710688598,
        0.03455502757306163,
        0.015880544863615904,
        -0.00900797613666158,
        -0.0025745176887502236,
        0.0011175187708906016,
        0.0004662169601128863,
        -7.098330313814125e-05,
        -3.459977283621256e-05,
    ]

    # high-pass
    reconstructionHighFilter = [
        -3.459977283621256e-05,
        7.098330313814125e-05,
        0.0004662169601128863,
        -0.0011175187708906016,
        -0.0025745176887502236,
        0.00900797613666158,
        0.015880544863615904,
        -0.03455502757306163,
        -0.08230192710688598,
        0.07179982161931202,
        0.42848347637761874,
        -0.7937772226256206,
        0.4051769024096169,
        0.06112339000267287,
        -0.0657719112818555,
        -0.023452696141836267,
        0.007782596427325418,
        0.003793512864491014,
    ]

Classes

class Coiflets3

Properties

near symmetric, orthogonal, biorthogonal

All values are from http://wavelets.pybytes.com/wavelet/coif3/

Expand source code

class Coiflets3:
    """
    Properties
    ----------
     near symmetric, orthogonal, biorthogonal

    All values are from http://wavelets.pybytes.com/wavelet/coif3/
    """
    __name__ = "Coiflets Wavelet 3"
    __motherWaveletLength__ = 18  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        -3.459977283621256e-05,
        -7.098330313814125e-05,
        0.0004662169601128863,
        0.0011175187708906016,
        -0.0025745176887502236,
        -0.00900797613666158,
        0.015880544863615904,
        0.03455502757306163,
        -0.08230192710688598,
        -0.07179982161931202,
        0.42848347637761874,
        0.7937772226256206,
        0.4051769024096169,
        -0.06112339000267287,
        -0.0657719112818555,
        0.023452696141836267,
        0.007782596427325418,
        -0.003793512864491014,
    ]

    # high-pass
    decompositionHighFilter = [
        0.003793512864491014,
        0.007782596427325418,
        -0.023452696141836267,
        -0.0657719112818555,
        0.06112339000267287,
        0.4051769024096169,
        -0.7937772226256206,
        0.42848347637761874,
        0.07179982161931202,
        -0.08230192710688598,
        -0.03455502757306163,
        0.015880544863615904,
        0.00900797613666158,
        -0.0025745176887502236,
        -0.0011175187708906016,
        0.0004662169601128863,
        7.098330313814125e-05,
        -3.459977283621256e-05,
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        -0.003793512864491014,
        0.007782596427325418,
        0.023452696141836267,
        -0.0657719112818555,
        -0.06112339000267287,
        0.4051769024096169,
        0.7937772226256206,
        0.42848347637761874,
        -0.07179982161931202,
        -0.08230192710688598,
        0.03455502757306163,
        0.015880544863615904,
        -0.00900797613666158,
        -0.0025745176887502236,
        0.0011175187708906016,
        0.0004662169601128863,
        -7.098330313814125e-05,
        -3.459977283621256e-05,
    ]

    # high-pass
    reconstructionHighFilter = [
        -3.459977283621256e-05,
        7.098330313814125e-05,
        0.0004662169601128863,
        -0.0011175187708906016,
        -0.0025745176887502236,
        0.00900797613666158,
        0.015880544863615904,
        -0.03455502757306163,
        -0.08230192710688598,
        0.07179982161931202,
        0.42848347637761874,
        -0.7937772226256206,
        0.4051769024096169,
        0.06112339000267287,
        -0.0657719112818555,
        -0.023452696141836267,
        0.007782596427325418,
        0.003793512864491014,
    ]

Class variables

var decompositionHighFilter

var decompositionLowFilter

var reconstructionHighFilter

var reconstructionLowFilter