Module wavelet.wavelets.sym16

Symlet 16 wavelet

""" Symlet 16 wavelet """


class Symlet16:
    """
    Properties
    ----------
     near symmetric, orthogonal, biorthogonal

    All values are from http://wavelets.pybytes.com/wavelet/sym16/
    """
    __name__ = "Symlet Wavelet 16"
    __motherWaveletLength__ = 32  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        6.230006701220761e-06,
        -3.113556407621969e-06,
        -0.00010943147929529757,
        2.8078582128442894e-05,
        0.0008523547108047095,
        -0.0001084456223089688,
        -0.0038809122526038786,
        0.0007182119788317892,
        0.012666731659857348,
        -0.0031265171722710075,
        -0.031051202843553064,
        0.004869274404904607,
        0.032333091610663785,
        -0.06698304907021778,
        -0.034574228416972504,
        0.39712293362064416,
        0.7565249878756971,
        0.47534280601152273,
        -0.054040601387606135,
        -0.15959219218520598,
        0.03072113906330156,
        0.07803785290341991,
        -0.003510275068374009,
        -0.024952758046290123,
        0.001359844742484172,
        0.0069377611308027096,
        -0.00022211647621176323,
        -0.0013387206066921965,
        3.656592483348223e-05,
        0.00016545679579108483,
        -5.396483179315242e-06,
        -1.0797982104319795e-05,
    ]

    # high-pass
    decompositionHighFilter = [
        1.0797982104319795e-05,
        -5.396483179315242e-06,
        -0.00016545679579108483,
        3.656592483348223e-05,
        0.0013387206066921965,
        -0.00022211647621176323,
        -0.0069377611308027096,
        0.001359844742484172,
        0.024952758046290123,
        -0.003510275068374009,
        -0.07803785290341991,
        0.03072113906330156,
        0.15959219218520598,
        -0.054040601387606135,
        -0.47534280601152273,
        0.7565249878756971,
        -0.39712293362064416,
        -0.034574228416972504,
        0.06698304907021778,
        0.032333091610663785,
        -0.004869274404904607,
        -0.031051202843553064,
        0.0031265171722710075,
        0.012666731659857348,
        -0.0007182119788317892,
        -0.0038809122526038786,
        0.0001084456223089688,
        0.0008523547108047095,
        -2.8078582128442894e-05,
        -0.00010943147929529757,
        3.113556407621969e-06,
        6.230006701220761e-06,
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        -1.0797982104319795e-05,
        -5.396483179315242e-06,
        0.00016545679579108483,
        3.656592483348223e-05,
        -0.0013387206066921965,
        -0.00022211647621176323,
        0.0069377611308027096,
        0.001359844742484172,
        -0.024952758046290123,
        -0.003510275068374009,
        0.07803785290341991,
        0.03072113906330156,
        -0.15959219218520598,
        -0.054040601387606135,
        0.47534280601152273,
        0.7565249878756971,
        0.39712293362064416,
        -0.034574228416972504,
        -0.06698304907021778,
        0.032333091610663785,
        0.004869274404904607,
        -0.031051202843553064,
        -0.0031265171722710075,
        0.012666731659857348,
        0.0007182119788317892,
        -0.0038809122526038786,
        -0.0001084456223089688,
        0.0008523547108047095,
        2.8078582128442894e-05,
        -0.00010943147929529757,
        -3.113556407621969e-06,
        6.230006701220761e-06,
    ]

    # high-pass
    reconstructionHighFilter = [
        6.230006701220761e-06,
        3.113556407621969e-06,
        -0.00010943147929529757,
        -2.8078582128442894e-05,
        0.0008523547108047095,
        0.0001084456223089688,
        -0.0038809122526038786,
        -0.0007182119788317892,
        0.012666731659857348,
        0.0031265171722710075,
        -0.031051202843553064,
        -0.004869274404904607,
        0.032333091610663785,
        0.06698304907021778,
        -0.034574228416972504,
        -0.39712293362064416,
        0.7565249878756971,
        -0.47534280601152273,
        -0.054040601387606135,
        0.15959219218520598,
        0.03072113906330156,
        -0.07803785290341991,
        -0.003510275068374009,
        0.024952758046290123,
        0.001359844742484172,
        -0.0069377611308027096,
        -0.00022211647621176323,
        0.0013387206066921965,
        3.656592483348223e-05,
        -0.00016545679579108483,
        -5.396483179315242e-06,
        1.0797982104319795e-05,
    ]

Classes

class Symlet16

Properties

near symmetric, orthogonal, biorthogonal

All values are from http://wavelets.pybytes.com/wavelet/sym16/

Expand source code

class Symlet16:
    """
    Properties
    ----------
     near symmetric, orthogonal, biorthogonal

    All values are from http://wavelets.pybytes.com/wavelet/sym16/
    """
    __name__ = "Symlet Wavelet 16"
    __motherWaveletLength__ = 32  # length of the mother wavelet
    __transformWaveletLength__ = 2  # minimum wavelength of input signal

    # decomposition filter
    # low-pass
    decompositionLowFilter = [
        6.230006701220761e-06,
        -3.113556407621969e-06,
        -0.00010943147929529757,
        2.8078582128442894e-05,
        0.0008523547108047095,
        -0.0001084456223089688,
        -0.0038809122526038786,
        0.0007182119788317892,
        0.012666731659857348,
        -0.0031265171722710075,
        -0.031051202843553064,
        0.004869274404904607,
        0.032333091610663785,
        -0.06698304907021778,
        -0.034574228416972504,
        0.39712293362064416,
        0.7565249878756971,
        0.47534280601152273,
        -0.054040601387606135,
        -0.15959219218520598,
        0.03072113906330156,
        0.07803785290341991,
        -0.003510275068374009,
        -0.024952758046290123,
        0.001359844742484172,
        0.0069377611308027096,
        -0.00022211647621176323,
        -0.0013387206066921965,
        3.656592483348223e-05,
        0.00016545679579108483,
        -5.396483179315242e-06,
        -1.0797982104319795e-05,
    ]

    # high-pass
    decompositionHighFilter = [
        1.0797982104319795e-05,
        -5.396483179315242e-06,
        -0.00016545679579108483,
        3.656592483348223e-05,
        0.0013387206066921965,
        -0.00022211647621176323,
        -0.0069377611308027096,
        0.001359844742484172,
        0.024952758046290123,
        -0.003510275068374009,
        -0.07803785290341991,
        0.03072113906330156,
        0.15959219218520598,
        -0.054040601387606135,
        -0.47534280601152273,
        0.7565249878756971,
        -0.39712293362064416,
        -0.034574228416972504,
        0.06698304907021778,
        0.032333091610663785,
        -0.004869274404904607,
        -0.031051202843553064,
        0.0031265171722710075,
        0.012666731659857348,
        -0.0007182119788317892,
        -0.0038809122526038786,
        0.0001084456223089688,
        0.0008523547108047095,
        -2.8078582128442894e-05,
        -0.00010943147929529757,
        3.113556407621969e-06,
        6.230006701220761e-06,
    ]

    # reconstruction filters
    # low pass
    reconstructionLowFilter = [
        -1.0797982104319795e-05,
        -5.396483179315242e-06,
        0.00016545679579108483,
        3.656592483348223e-05,
        -0.0013387206066921965,
        -0.00022211647621176323,
        0.0069377611308027096,
        0.001359844742484172,
        -0.024952758046290123,
        -0.003510275068374009,
        0.07803785290341991,
        0.03072113906330156,
        -0.15959219218520598,
        -0.054040601387606135,
        0.47534280601152273,
        0.7565249878756971,
        0.39712293362064416,
        -0.034574228416972504,
        -0.06698304907021778,
        0.032333091610663785,
        0.004869274404904607,
        -0.031051202843553064,
        -0.0031265171722710075,
        0.012666731659857348,
        0.0007182119788317892,
        -0.0038809122526038786,
        -0.0001084456223089688,
        0.0008523547108047095,
        2.8078582128442894e-05,
        -0.00010943147929529757,
        -3.113556407621969e-06,
        6.230006701220761e-06,
    ]

    # high-pass
    reconstructionHighFilter = [
        6.230006701220761e-06,
        3.113556407621969e-06,
        -0.00010943147929529757,
        -2.8078582128442894e-05,
        0.0008523547108047095,
        0.0001084456223089688,
        -0.0038809122526038786,
        -0.0007182119788317892,
        0.012666731659857348,
        0.0031265171722710075,
        -0.031051202843553064,
        -0.004869274404904607,
        0.032333091610663785,
        0.06698304907021778,
        -0.034574228416972504,
        -0.39712293362064416,
        0.7565249878756971,
        -0.47534280601152273,
        -0.054040601387606135,
        0.15959219218520598,
        0.03072113906330156,
        -0.07803785290341991,
        -0.003510275068374009,
        0.024952758046290123,
        0.001359844742484172,
        -0.0069377611308027096,
        -0.00022211647621176323,
        0.0013387206066921965,
        3.656592483348223e-05,
        -0.00016545679579108483,
        -5.396483179315242e-06,
        1.0797982104319795e-05,
    ]

Class variables

var decompositionHighFilter

var decompositionLowFilter

var reconstructionHighFilter

var reconstructionLowFilter