Package slimpy_contrib.ana.problems.l1_minimization_problem

Functions
def	solver_callback
	solver_callback( target, source, env, space ) -> Solver Set the default value for the solver.
def	transform_callback
	transform_callback( target, source, env, space ) -> A set the default value for the transform
def	precondition_callback
	precondition_callback(target,source,env, space) -> Identity(space) Default preconditioner defaults to the Identity
Variables
string	__copyright__
	Perform 2D de-noiseing using landweber method.
string	__license__
string	__acknowledgments__
tuple	Get = lambdaenv,item:env.get( item )
dictionary	l1_min = {}

---

Function Documentation

def slimpy_contrib.ana.problems.l1_minimization_problem.precondition_callback	(		target,
			source,
			env,
			space
	)

precondition_callback(target,source,env, space) -> Identity(space) Default preconditioner defaults to the Identity

Definition at line 132 of file l1_minimization_problem.py.

def slimpy_contrib.ana.problems.l1_minimization_problem.solver_callback	(		target,
			source,
			env,
			A
	)

solver_callback( target, source, env, space ) -> Solver Set the default value for the solver.

Solver defaults to the thresholded landweber with a linear cooling threshold scheme.

Returns:

Thresholded Landweber Solver with LinearCooling scheme

Definition at line 90 of file l1_minimization_problem.py.

def slimpy_contrib.ana.problems.l1_minimization_problem.transform_callback	(		target,
			source,
			env,
			space
	)

transform_callback( target, source, env, space ) -> A set the default value for the transform

Returns:

the inverse surfacelet transform

Definition at line 120 of file l1_minimization_problem.py.

---

Variable Documentation

string __acknowledgments__

Initial value:

"""
Author:         G. Hennenfent
                Seismic Laboratory for Imaging and Modeling (SLIM)
                Department of Earth & Ocean Sciences (EOS)
                The University of British Columbia at Vancouver (UBC)

Acknowledgments: 
                Sean Ross-Ross
                Seismic Laboratory for Imaging and Modeling (SLIM)
                Department of Earth & Ocean Sciences (EOS)
                The University of British Columbia at Vancouver (UBC)

                Darren Thomson
                Seismic Laboratory for Imaging and Modeling (SLIM)
                Department of Earth & Ocean Sciences (EOS)
                The University of British Columbia at Vancouver (UBC)

Funding:        This work was carried out as part of the SINBAD project with
                financial support, secured through ITF, from the following
                organizations: BG Group, BP, Chevron, ExxonMobil, and Shell. SINBAD is
                part of a collaborative research and development grant (CRD) number
                334810-05 funded by the Natural Science and Engineering Research
                Council (NSERC)

"""

Definition at line 48 of file l1_minimization_problem.py.

string __copyright__

Initial value:

"""
Copyright 2008 Sean Ross-Ross
"""

Perform 2D de-noiseing using landweber method.

Note:

that, as of August 28, 2006:

• dimension fixed (2D)

REQUIREMENTS:

• Madagascar with SLIM toolbox
• SLIMpy

Parameters:

	lambdaMax=LMAX	[Default=0.01]
	lambdaMin=LMIN	[Default=0.6]
	OuterN=NBOUT	Number of outer loops [Default=2]
	InnerN=NBIN	Number of inner loops [Default=2]

Definition at line 18 of file l1_minimization_problem.py.

string __license__

Initial value:

"""
This file is part of SLIMpy .

SLIMpy is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

SLIMpy is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License
along with SLIMpy . If not, see <http://www.gnu.org/licenses/>.
"""

Definition at line 22 of file l1_minimization_problem.py.

tuple Get = lambdaenv,item:env.get( item )

Definition at line 76 of file l1_minimization_problem.py.

dictionary l1_min = {}

Definition at line 136 of file l1_minimization_problem.py.