Module wavelet.wavelets.db9

Daubechies 9 wavelet

""" Daubechies 9 wavelet """


class Daubechies9:
    """
    Properties
    ----------
    asymmetric, orthogonal, bi-orthogonal

    All values are from http://wavelets.pybytes.com/wavelet/db9/
    """
    __name__ = "Daubechies Wavelet 9"
    __motherWaveletLength__ = 18  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        3.9347319995026124e-05,
        - 0.0002519631889981789,
        0.00023038576399541288,
        0.0018476468829611268,
        - 0.004281503681904723,
        - 0.004723204757894831,
        0.022361662123515244,
        0.00025094711499193845,
        - 0.06763282905952399,
        0.030725681478322865,
        0.14854074933476008,
        - 0.09684078322087904,
        - 0.29327378327258685,
        0.13319738582208895,
        0.6572880780366389,
        0.6048231236767786,
        0.24383467463766728,
        0.03807794736316728
    ]

    # high-pass
    decompositionHighFilter = [
        -0.03807794736316728,
        0.24383467463766728,
        - 0.6048231236767786,
        0.6572880780366389,
        - 0.13319738582208895,
        - 0.29327378327258685,
        0.09684078322087904,
        0.14854074933476008,
        - 0.030725681478322865,
        - 0.06763282905952399,
        - 0.00025094711499193845,
        0.022361662123515244,
        0.004723204757894831,
        - 0.004281503681904723,
        - 0.0018476468829611268,
        0.00023038576399541288,
        0.0002519631889981789,
        3.9347319995026124e-05
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        0.03807794736316728,
        0.24383467463766728,
        0.6048231236767786,
        0.6572880780366389,
        0.13319738582208895,
        - 0.29327378327258685,
        - 0.09684078322087904,
        0.14854074933476008,
        0.030725681478322865,
        - 0.06763282905952399,
        0.00025094711499193845,
        0.022361662123515244,
        - 0.004723204757894831,
        - 0.004281503681904723,
        0.0018476468829611268,
        0.00023038576399541288,
        - 0.0002519631889981789,
        3.9347319995026124e-05
    ]

    # high-pass
    reconstructionHighFilter = [
        3.9347319995026124e-05,
        0.0002519631889981789,
        0.00023038576399541288,
        - 0.0018476468829611268,
        - 0.004281503681904723,
        0.004723204757894831,
        0.022361662123515244,
        - 0.00025094711499193845,
        - 0.06763282905952399,
        - 0.030725681478322865,
        0.14854074933476008,
        0.09684078322087904,
        - 0.29327378327258685,
        - 0.13319738582208895,
        0.6572880780366389,
        - 0.6048231236767786,
        0.24383467463766728,
        - 0.03807794736316728,
    ]

Classes

class Daubechies9

Properties

asymmetric, orthogonal, bi-orthogonal

All values are from http://wavelets.pybytes.com/wavelet/db9/

Expand source code

class Daubechies9:
    """
    Properties
    ----------
    asymmetric, orthogonal, bi-orthogonal

    All values are from http://wavelets.pybytes.com/wavelet/db9/
    """
    __name__ = "Daubechies Wavelet 9"
    __motherWaveletLength__ = 18  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        3.9347319995026124e-05,
        - 0.0002519631889981789,
        0.00023038576399541288,
        0.0018476468829611268,
        - 0.004281503681904723,
        - 0.004723204757894831,
        0.022361662123515244,
        0.00025094711499193845,
        - 0.06763282905952399,
        0.030725681478322865,
        0.14854074933476008,
        - 0.09684078322087904,
        - 0.29327378327258685,
        0.13319738582208895,
        0.6572880780366389,
        0.6048231236767786,
        0.24383467463766728,
        0.03807794736316728
    ]

    # high-pass
    decompositionHighFilter = [
        -0.03807794736316728,
        0.24383467463766728,
        - 0.6048231236767786,
        0.6572880780366389,
        - 0.13319738582208895,
        - 0.29327378327258685,
        0.09684078322087904,
        0.14854074933476008,
        - 0.030725681478322865,
        - 0.06763282905952399,
        - 0.00025094711499193845,
        0.022361662123515244,
        0.004723204757894831,
        - 0.004281503681904723,
        - 0.0018476468829611268,
        0.00023038576399541288,
        0.0002519631889981789,
        3.9347319995026124e-05
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        0.03807794736316728,
        0.24383467463766728,
        0.6048231236767786,
        0.6572880780366389,
        0.13319738582208895,
        - 0.29327378327258685,
        - 0.09684078322087904,
        0.14854074933476008,
        0.030725681478322865,
        - 0.06763282905952399,
        0.00025094711499193845,
        0.022361662123515244,
        - 0.004723204757894831,
        - 0.004281503681904723,
        0.0018476468829611268,
        0.00023038576399541288,
        - 0.0002519631889981789,
        3.9347319995026124e-05
    ]

    # high-pass
    reconstructionHighFilter = [
        3.9347319995026124e-05,
        0.0002519631889981789,
        0.00023038576399541288,
        - 0.0018476468829611268,
        - 0.004281503681904723,
        0.004723204757894831,
        0.022361662123515244,
        - 0.00025094711499193845,
        - 0.06763282905952399,
        - 0.030725681478322865,
        0.14854074933476008,
        0.09684078322087904,
        - 0.29327378327258685,
        - 0.13319738582208895,
        0.6572880780366389,
        - 0.6048231236767786,
        0.24383467463766728,
        - 0.03807794736316728,
    ]

Class variables

var decompositionHighFilter

var decompositionLowFilter

var reconstructionHighFilter

var reconstructionLowFilter