intertwining_wavelet

class iw.intertwining_wavelet.IntertwiningWavelet

Bases: object

Define an automaton with parameters

Example:

>>> from iw.data.get_dataset_path import get_dataset_path
>>> from iw.intertwining_wavelet import IntertwiningWavelet
>>> graph_file = get_dataset_path("tore1d16.g")
>>> iw = IntertwiningWavelet(graph_file)
>>> iw.mu_initial.size
>>> 16
>>> iw.pretreatment
>>> True
>>> iw.process_analysis(mod='step')
>>> tab = iw.tab_Multires
>>> iw.process_analysis_flag
>>> True
>>> iw.process_reconstruction(signal)

• Input:

Parameters

• graph_file (str) – name of the graph file

• signals (2d array of double can be also one vector) – array of signals

• nbr_signals (int) – number of signals

• transition (list) – the transitions tables

• pretreatment (boolean) – True if pretreatement performed

• Attributes:

Variables

• signals – array of input signal for reconstructions

• pretreatment (bool) – True if pretreatment has been performed

• nbr_signals (int) – number of signals

• graph – current graph iw.gaph_c.Graph_c

• tab_Multires – structure of iw.multiresolution.struct_multires_Lbarre.Tab_Struct_multires_Lbarre

• mu_initial – array of value of initial

• reconstructed_s – array of reconstructed signals

• coeffs – arrays of coefficients

• following_size – array of all sizes

• a (double) – value varaible a (max of trac of laplacien)

• graph_file_initial (str) – name of initial graph for decomposition

• process_analysis_flag (bool) – Tru if process_analysys has been performed

a

coeffs

following_size

graph

graph_file_initial

mu_initial

nbr_signals

pretreatment

process_analysis()

process_analysis launch multiresolution analysis

• Inputs:

Parameters

• mod (string) –

  (default value = ‘step’) define the mod of the multiresolution analysis of multiscale calculations:

  • ’step’ determine the number of steps for decomposition

  • ’card’ determine the minimum cardinal of graph m

• steps (int) – (default value = 10) number of steps for multiresolution

• m (int) – (default value = None) number of minimum cardinality

• theta (double) – (default value = 4.0) parameter which determines the level of sparsification

process_analysis_flag

process_coefficients()

compute multiresolution coefficients of the signals

• Input

Parameters

signals (2d array of double can have only one vector) – array of signals to reconstruct

• Output

Returns

coefficients of the multiresolution decomposition

Return type

coefficients 2d array of double can be also one vector

process_pretreatment()

process_pretreatment function called by init

process_reconstruction_signal()

process reconstruction of the signals given signals (check the reliability of the IW Toolbox)

• Input

Parameters

signals (2d array of double can have only one vector) – array of signals to reconstruct

• Output

Returns

reconstructed_signals

Return type

reconstructed_signals 2d array of double can be also one vector

process_signal()

process reconstruction given coefficients

• Input

Parameters

coeffs (2d array of double, can only have one line in the case of one vector.) – array of wavelet coefficients

• Output

Returns

reconstructed_signals

Return type

reconstructed_signals 2d array of double, can only have one line in the case of one vector.

reconstructed_s

signals

tab_Multires