petsc4py.PETSc.SNES#

class petsc4py.PETSc.SNES#

Bases: Object

Nonlinear equations solver.

SNES is described in the PETSc manual.

See also

SNES

Enumerations

`ConvergedReason`	SNES solver termination reason.
`NewtonALCorrectionType`	SNESNEWTONAL correction type.
`NormSchedule`	SNES norm schedule.
`Type`	SNES solver type.

Methods Summary

`appendOptionsPrefix`(prefix)	Append to the prefix used for searching for options in the database.
`callConvergenceTest`(its, xnorm, ynorm, fnorm)	Compute the convergence test.
`computeFunction`(x, f)	Compute the function.
`computeJacobian`(x, J[, P])	Compute the Jacobian.
`computeNGS`(x[, b])	Compute a nonlinear Gauss-Seidel step.
`computeObjective`(x)	Compute the value of the objective function.
`converged`(its, xnorm, ynorm, fnorm)	Compute the convergence test and update the solver converged reason.
`create`([comm])	Create a SNES solver.
`createPython`([context, comm])	Create a nonlinear solver of Python type.
`destroy`()	Destroy the solver.
`getApplicationContext`()	Return the application context.
`getCompositeNumber`()	Return the number of solvers in the composite.
`getCompositeSNES`(n)	Return the n-th solver in the composite.
`getConvergedReason`()	Return the termination flag.
`getConvergenceHistory`()	Return the convergence history.
`getConvergenceTest`()	Return the callback to used as convergence test.
`getDM`()	Return the `DM` associated with the solver.
`getDivergenceTolerance`()	Get the divergence tolerance parameter used in the convergence tests.
`getErrorIfNotConverged`()	Return the flag indicating error on divergence.
`getFASCoarseCorrectionLineSearch`(level)	Return the line search for coarse correction in the FAS cycle.
`getFASCoarseSolve`()	Return the `SNES` used at the coarsest level of the FAS hierarchy.
`getFASCycleSNES`(level)	Return the `SNES` corresponding to a particular level of the FAS hierarchy.
`getFASInjection`(level)	Return the `Mat` used to apply the injection from level-1 to level.
`getFASInterpolation`(level)	Return the `Mat` used to apply the interpolation from level-1 to level.
`getFASLevels`()	Return the number of levels used.
`getFASRestriction`(level)	Return the `Mat` used to apply the restriction from level-1 to level.
`getFASSmoother`(level)	Return the smoother used at a given level of the FAS hierarchy.
`getFASSmootherDown`(level)	Return the downsmoother used at a given level of the FAS hierarchy.
`getFASSmootherUp`(level)	Return the upsmoother used at a given level of the FAS hierarchy.
`getFunction`()	Return the callback to compute the nonlinear function.
`getFunctionEvaluations`()	Return the current number of function evaluations.
`getFunctionNorm`()	Return the function norm.
`getInitialGuess`()	Return the callback to compute the initial guess.
`getIterationNumber`()	Return the current iteration number.
`getJacobian`()	Return the matrices used to compute the Jacobian and the callback tuple.
`getKSP`()	Return the linear solver used by the nonlinear solver.
`getKSPFailures`()	Return the current number of linear solve failures.
`getLineSearch`()	Return the linesearch object associated with this SNES.
`getLinearSolveIterations`()	Return the total number of linear iterations.
`getMaxFunctionEvaluations`()	Return the maximum allowed number of function evaluations.
`getMaxKSPFailures`()	Return the maximum allowed number of linear solve failures.
`getMaxStepFailures`()	Return the maximum allowed number of step failures.
`getMonitor`()	Return the callback used to monitor solver convergence.
`getNASMNumber`()	Return the number of solvers in NASM.
`getNASMSNES`(n)	Return the n-th solver in NASM.
`getNGS`()	Return the nonlinear Gauss-Seidel callback tuple.
`getNPC`()	Return the nonlinear preconditioner associated with the solver.
`getNPCSide`()	Return the nonlinear preconditioning side.
`getNewtonALLoadParameter`()	Return the load parameter for SNESNEWTONAL.
`getNormSchedule`()	Return the norm schedule.
`getObjective`()	Return the objective callback tuple.
`getOptionsPrefix`()	Return the prefix used for searching for options in the database.
`getParamsEW`()	Get the parameters of the Eisenstat and Walker trick.
`getPythonContext`()	Return the instance of the class implementing the required Python methods.
`getPythonType`()	Return the fully qualified Python name of the class used by the solver.
`getRhs`()	Return the vector holding the right-hand side.
`getSolution`()	Return the vector holding the solution.
`getSolutionUpdate`()	Return the vector holding the solution update.
`getStepFailures`()	Return the current number of step failures.
`getTRTolerances`()	Return the tolerance parameters used for the trust region.
`getTRUpdateParameters`()	Return the update parameters used for the trust region.
`getTolerances`()	Return the tolerance parameters used in the solver convergence tests.
`getType`()	Return the type of the solver.
`getUpdate`()	Return the callback to compute the update at the beginning of each step.
`getUseEW`()	Return the flag indicating if the solver uses the Eisenstat-Walker trick.
`getUseFD`()	Return `true` if the solver uses color finite-differencing for the Jacobian.
`getUseKSP`()	Return the flag indicating if the solver uses a linear solver.
`getUseMF`()	Return the flag indicating if the solver uses matrix-free finite-differencing.
`getVIInactiveSet`()	Return the index set for the inactive set.
`getVariableBounds`()	Get the vectors for the variable bounds.
`hasNPC`()	Return a boolean indicating whether the solver has a nonlinear preconditioner.
`logConvergenceHistory`(norm[, linear_its])	Log residual norm and linear iterations.
`monitor`(its, rnorm)	Monitor the solver.
`monitorCancel`()	Cancel all the monitors of the solver.
`reset`()	Reset the solver.
`setApplicationContext`(appctx)	Set the application context.
`setConvergedReason`(reason)	Set the termination flag.
`setConvergenceHistory`([length, reset])	Set the convergence history.
`setConvergenceTest`(converged[, args, kargs])	Set the callback to use as convergence test.
`setDM`(dm)	Associate a `DM` with the solver.
`setDivergenceTolerance`(dtol)	Set the divergence tolerance parameter used in the convergence tests.
`setErrorIfNotConverged`([flag])	Immediately generate an error if the solver has not converged.
`setFASInjection`(level, mat)	Set the `Mat` to be used to apply the injection from level-1 to level.
`setFASInterpolation`(level, mat)	Set the `Mat` to be used to apply the interpolation from level-1 to level.
`setFASLevels`(levels[, comms])	Set the number of levels to use with FAS.
`setFASRScale`(level, vec)	Set the scaling factor of the restriction operator from level to level-1.
`setFASRestriction`(level, mat)	Set the `Mat` to be used to apply the restriction from level-1 to level.
`setFASUseCoarseCorrectionLineSearch`([use])	Set if to use a line search for the coarse corrections in FAS.
`setForceIteration`([force])	Force solve to take at least one iteration.
`setFromOptions`()	Configure the solver from the options database.
`setFunction`(function[, f, args, kargs])	Set the callback to compute the nonlinear function.
`setFunctionNorm`(norm)	Set the function norm value.
`setInitialGuess`(initialguess[, args, kargs])	Set the callback to compute the initial guess.
`setIterationNumber`(its)	Set the current iteration number.
`setJacobian`(jacobian[, J, P, args, kargs])	Set the callback to compute the Jacobian.
`setKSP`(ksp)	Set the linear solver that will be used by the nonlinear solver.
`setLineSearch`(linesearch)	Set the linesearch object to be used by this SNES.
`setLineSearchPreCheck`(precheck[, args, kargs])	Set the callback that will be called before applying the linesearch.
`setMaxFunctionEvaluations`(max_funcs)	Set the maximum allowed number of function evaluations.
`setMaxKSPFailures`(max_fails)	Set the maximum allowed number of linear solve failures.
`setMaxStepFailures`(max_fails)	Set the maximum allowed number of step failures.
`setMonitor`(monitor[, args, kargs])	Set the callback used to monitor solver convergence.
`setNGS`(ngs[, args, kargs])	Set the callback to compute nonlinear Gauss-Seidel.
`setNPC`(snes)	Set the nonlinear preconditioner.
`setNPCSide`(side)	Set the nonlinear preconditioning side.
`setNewtonALCorrectionType`(corrtype)	Set the correction type for SNESNEWTONAL.
`setNewtonALFunction`(function[, args, kargs])	Set the callback to compute the tangent load vector for SNESNEWTONAL.
`setNormSchedule`(normsched)	Set the norm schedule.
`setObjective`(objective[, args, kargs])	Set the callback to compute the objective function.
`setOptionsPrefix`(prefix)	Set the prefix used for searching for options in the database.
`setParamsEW`([version, rtol_0, rtol_max, ...])	Set the parameters for the Eisenstat and Walker trick.
`setPatchCellNumbering`(sec)	Set cell patch numbering.
`setPatchComputeFunction`(function[, args, kargs])	Set patch compute function.
`setPatchComputeOperator`(operator[, args, kargs])	Set patch compute operator.
`setPatchConstructType`(typ[, operator, args, ...])	Set patch construct type.
`setPatchDiscretisationInfo`(dms, bs, ...)	Set patch discretisation information.
`setPythonContext`(context)	Set the instance of the class implementing the required Python methods.
`setPythonType`(py_type)	Set the fully qualified Python name of the class to be used.
`setResetCounters`([reset])	Set the flag to reset the counters.
`setSolution`(vec)	Set the vector used to store the solution.
`setTRTolerances`([delta_min, delta_max, delta_0])	Set the tolerance parameters used for the trust region.
`setTRUpdateParameters`([eta1, eta2, eta3, t1, t2])	Set the update parameters used for the trust region.
`setTolerances`([rtol, atol, stol, max_it])	Set the tolerance parameters used in the solver convergence tests.
`setType`(snes_type)	Set the type of the solver.
`setUp`()	Set up the internal data structures for using the solver.
`setUpMatrices`()	Ensures that matrices are available for Newton-like methods.
`setUpdate`(update[, args, kargs])	Set the callback to compute update at the beginning of each step.
`setUseEW`([flag])	Tell the solver to use the Eisenstat-Walker trick.
`setUseFD`([flag])	Set the boolean flag to use coloring finite-differencing for Jacobian assembly.
`setUseKSP`([flag])	Set the boolean flag indicating to use a linear solver.
`setUseMF`([flag])	Set the boolean flag indicating to use matrix-free finite-differencing.
`setVariableBounds`(xl, xu)	Set the vector for the variable bounds.
`solve`([b, x])	Solve the nonlinear equations.
`view`([viewer])	View the solver.

Attributes Summary

`appctx`	Application context.
`atol`	Absolute residual tolerance.
`dm`	`DM`.
`history`	Convergence history.
`is_converged`	Boolean indicating if the solver has converged.
`is_diverged`	Boolean indicating if the solver has failed.
`is_iterating`	Boolean indicating if the solver has not converged yet.
`its`	Number of iterations.
`ksp`	Linear solver.
`linesearch`	The linesearch object associated with this SNES.
`max_funcs`	Maximum number of function evaluations.
`max_it`	Maximum number of iterations.
`norm`	Function norm.
`npc`	Nonlinear preconditioner.
`reason`	Converged reason.
`rtol`	Relative residual tolerance.
`stol`	Solution update tolerance.
`use_ew`	Use the Eisenstat-Walker trick.
`use_fd`	Boolean indicating if the solver uses coloring finite-differencing.
`use_ksp`	Boolean indicating if the solver uses a linear solver.
`use_mf`	Boolean indicating if the solver uses matrix-free finite-differencing.
`vec_rhs`	Right-hand side vector.
`vec_sol`	Solution vector.
`vec_upd`	Update vector.

Methods Documentation

appendOptionsPrefix(prefix)#

Append to the prefix used for searching for options in the database.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:246

Parameters:: prefix (str | None)
Return type:: None

callConvergenceTest(its, xnorm, ynorm, fnorm)#

Compute the convergence test.

Collective.

Parameters:

its (int) – Iteration number.
xnorm (float) – Solution norm.
ynorm (float) – Update norm.
fnorm (float) – Function norm.

Return type:

ConvergedReason

Source code at petsc4py/PETSc/SNES.pyx:1376

computeFunction(x, f)#

Compute the function.

Collective.

Parameters:

x (Vec) – The input state vector.
f (Vec) – The output vector.

Return type:

None

See also

setFunction, SNESComputeFunction

Source code at petsc4py/PETSc/SNES.pyx:1077

computeJacobian(x, J, P=None)#

Compute the Jacobian.

Collective.

Parameters:

x (Vec) – The input state vector.
J (Mat) – The output Jacobian matrix.
P (Mat | None) – The output Jacobian matrix used to construct the preconditioner.

Return type:

None

See also

setJacobian, SNESComputeJacobian

Source code at petsc4py/PETSc/SNES.pyx:1096

computeNGS(x, b=None)#

Compute a nonlinear Gauss-Seidel step.

Collective.

Parameters:

x (Vec) – The input/output state vector.
b (Vec | None) – The input right-hand side vector.

Return type:

None

See also

setNGS, getNGS, SNESComputeNGS

Source code at petsc4py/PETSc/SNES.pyx:1182

computeObjective(x)#

Compute the value of the objective function.

Collective.

Parameters:: x (Vec) – The input state vector.
Return type:: float

See also

setObjective, SNESComputeObjective

Source code at petsc4py/PETSc/SNES.pyx:1119

converged(its, xnorm, ynorm, fnorm)#

Compute the convergence test and update the solver converged reason.

Collective.

Parameters:

its (int) – Iteration number.
xnorm (float) – Solution norm.
ynorm (float) – Update norm.
fnorm (float) – Function norm.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:1406

create(comm=None)#

Create a SNES solver.

Collective.

Parameters:: comm (Comm | None) – MPI communicator, defaults to Sys.getDefaultComm.
Return type:: Self

See also

Sys.getDefaultComm, SNESCreate

Source code at petsc4py/PETSc/SNES.pyx:164

createPython(context=None, comm=None)#

Create a nonlinear solver of Python type.

Collective.

Parameters:

context (Any) – An instance of the Python class implementing the required methods.
comm (Comm | None) – MPI communicator, defaults to Sys.getDefaultComm.

Return type:

Self

Source code at petsc4py/PETSc/SNES.pyx:2235

destroy()#

Destroy the solver.

Collective.

See also

SNESDestroy

Source code at petsc4py/PETSc/SNES.pyx:151

Return type:: Self

getApplicationContext()#

Return the application context.

Source code at petsc4py/PETSc/SNES.pyx:283

Return type:: Any

getCompositeNumber()#

Return the number of solvers in the composite.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2336

Return type:: int

getCompositeSNES(n)#

Return the n-th solver in the composite.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2319

Parameters:: n (int)
Return type:: SNES

getConvergedReason()#

Return the termination flag.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1780

Return type:: ConvergedReason

getConvergenceHistory()#

Return the convergence history.

Not collective.

See also

SNESGetConvergenceHistory

Source code at petsc4py/PETSc/SNES.pyx:1457

Return type:: tuple[ArrayReal, ArrayInt]

getConvergenceTest()#

Return the callback to used as convergence test.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1364

Return type:: tuple[SNESConvergedFunction, tuple[Any, …], dict[str, Any]] | None

getDM()#

Return the DM associated with the solver.

Not collective.

See also

setDM, SNESGetDM

Source code at petsc4py/PETSc/SNES.pyx:294

Return type:: DM

getDivergenceTolerance()#

Get the divergence tolerance parameter used in the convergence tests.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1288

Return type:: float

getErrorIfNotConverged()#

Return the flag indicating error on divergence.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1807

Return type:: bool

getFASCoarseCorrectionLineSearch(level)#

Return the line search for coarse correction in the FAS cycle.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:638

Parameters:: level (int)
Return type:: SNESLineSearch | None

getFASCoarseSolve()#

Return the SNES used at the coarsest level of the FAS hierarchy.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:609

Return type:: SNES

getFASCycleSNES(level)#

Return the SNES corresponding to a particular level of the FAS hierarchy.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:592

Parameters:: level (int)
Return type:: SNES

getFASInjection(level)#

Return the Mat used to apply the injection from level-1 to level.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:515

Parameters:: level (int)
Return type:: Mat

getFASInterpolation(level)#

Return the Mat used to apply the interpolation from level-1 to level.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:455

Parameters:: level (int)
Return type:: Mat

getFASLevels()#

Return the number of levels used.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:578

Return type:: int

getFASRestriction(level)#

Return the Mat used to apply the restriction from level-1 to level.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:485

Parameters:: level (int)
Return type:: Mat

getFASSmoother(level)#

Return the smoother used at a given level of the FAS hierarchy.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:656

Parameters:: level (int)
Return type:: SNES

getFASSmootherDown(level)#

Return the downsmoother used at a given level of the FAS hierarchy.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:673

Parameters:: level (int)
Return type:: SNES

getFASSmootherUp(level)#

Return the upsmoother used at a given level of the FAS hierarchy.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:690

Parameters:: level (int)
Return type:: SNES

getFunction()#

Return the callback to compute the nonlinear function.

Not collective.

See also

setFunction, SNESGetFunction

Source code at petsc4py/PETSc/SNES.pyx:892

Return type:: tuple[Vec, tuple[SNESFunction, tuple[Any, …], dict[str, Any]] | None]

getFunctionEvaluations()#

Return the current number of function evaluations.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1608

Return type:: int

getFunctionNorm()#

Return the function norm.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1878

Return type:: float

getInitialGuess()#

Return the callback to compute the initial guess.

Not collective.

See also

setInitialGuess

Source code at petsc4py/PETSc/SNES.pyx:843

Return type:: tuple[SNESGuessFunction, tuple[Any, …], dict[str, Any]] | None

getIterationNumber()#

Return the current iteration number.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1836

Return type:: int

getJacobian()#

Return the matrices used to compute the Jacobian and the callback tuple.

Not collective.

Returns:

J (Mat) – The matrix to store the Jacobian.
P (Mat) – The matrix to construct the preconditioner.
callback (SNESJacobianFunction) – callback, positional and keyword arguments.

Return type:

tuple[Mat, Mat, SNESJacobianFunction]

See also

setJacobian, SNESGetJacobian

Source code at petsc4py/PETSc/SNES.pyx:1006

getKSP()#

Return the linear solver used by the nonlinear solver.

Not collective.

See also

setKSP, SNESGetKSP

Source code at petsc4py/PETSc/SNES.pyx:1977

Return type:: KSP

getKSPFailures()#

Return the current number of linear solve failures.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1690

Return type:: int

getLineSearch()#

Return the linesearch object associated with this SNES.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2644

Return type:: SNESLineSearch

getLinearSolveIterations()#

Return the total number of linear iterations.

Not collective.

See also

SNESGetLinearSolveIterations

Source code at petsc4py/PETSc/SNES.pyx:1892

Return type:: int

getMaxFunctionEvaluations()#

Return the maximum allowed number of function evaluations.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1592

Return type:: int

getMaxKSPFailures()#

Return the maximum allowed number of linear solve failures.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1676

Return type:: int

getMaxStepFailures()#

Return the maximum allowed number of step failures.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1635

Return type:: int

getMonitor()#

Return the callback used to monitor solver convergence.

Not collective.

See also

setMonitor

Source code at petsc4py/PETSc/SNES.pyx:1529

Return type:: list[tuple[SNESMonitorFunction, tuple[Any, …], dict[str, Any]]]

getNASMNumber()#

Return the number of solvers in NASM.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2368

Return type:: int

getNASMSNES(n)#

Return the n-th solver in NASM.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2352

Parameters:: n (int)
Return type:: SNES

getNGS()#

Return the nonlinear Gauss-Seidel callback tuple.

Not collective.

See also

setNGS, computeNGS

Source code at petsc4py/PETSc/SNES.pyx:1170

Return type:: tuple[SNESNGSFunction, tuple[Any, …], dict[str, Any]] | None

getNPC()#

Return the nonlinear preconditioner associated with the solver.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:709

Return type:: SNES

getNPCSide()#

Return the nonlinear preconditioning side.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:762

Return type:: Side

getNewtonALLoadParameter()#

Return the load parameter for SNESNEWTONAL.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2712

Return type:: float

getNormSchedule()#

Return the norm schedule.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1314

Return type:: NormSchedule

getObjective()#

Return the objective callback tuple.

Not collective.

See also

setObjective

Source code at petsc4py/PETSc/SNES.pyx:1065

Return type:: tuple[SNESObjFunction, tuple[Any, …], dict[str, Any]] | None

getOptionsPrefix()#

Return the prefix used for searching for options in the database.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:232

Return type:: str

getParamsEW()#

Get the parameters of the Eisenstat and Walker trick.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2081

Return type:: dict[str, int | float]

getPythonContext()#

Return the instance of the class implementing the required Python methods.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2272

Return type:: Any

getPythonType()#

Return the fully qualified Python name of the class used by the solver.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2302

Return type:: str

getRhs()#

Return the vector holding the right-hand side.

Not collective.

See also

SNESGetRhs

Source code at petsc4py/PETSc/SNES.pyx:1906

Return type:: Vec

getSolution()#

Return the vector holding the solution.

Not collective.

See also

setSolution, SNESGetSolution

Source code at petsc4py/PETSc/SNES.pyx:1921

Return type:: Vec

getSolutionUpdate()#

Return the vector holding the solution update.

Not collective.

See also

SNESGetSolutionUpdate

Source code at petsc4py/PETSc/SNES.pyx:1948

Return type:: Vec

getStepFailures()#

Return the current number of step failures.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:1649

Return type:: int

getTRTolerances()#

Return the tolerance parameters used for the trust region.

Not collective.

Returns:

delta_min (float) – The minimum allowed trust region size.
delta_max (float) – The maximum allowed trust region size.
delta_0 (float) – The initial trust region size.

Return type:

tuple[float, float, float]

Source code at petsc4py/PETSc/SNES.pyx:352

getTRUpdateParameters()#

Return the update parameters used for the trust region.

Not collective.

Returns:

eta1 (float) – The step acceptance tolerance.
eta2 (float) – The shrinking tolerance.
eta3 (float) – The enlarging tolerance.
t1 (float) – The shrinking factor.
t2 (float) – The enlarging factor.

Return type:

tuple[float, float, float, float, float]

Source code at petsc4py/PETSc/SNES.pyx:411

getTolerances()#

Return the tolerance parameters used in the solver convergence tests.

Not collective.

Returns:

rtol (float) – The relative norm of the residual.
atol (float) – The absolute norm of the residual.
stol (float) – The absolute norm of the step.
max_it (int) – The maximum allowed number of iterations.

Return type:

tuple[float, float, float, int]

See also

setTolerances, SNESGetTolerances

Source code at petsc4py/PETSc/SNES.pyx:1244

getType()#

Return the type of the solver.

Not collective.

See also

setType, SNESGetType

Source code at petsc4py/PETSc/SNES.pyx:204

Return type:: str

getUpdate()#

Return the callback to compute the update at the beginning of each step.

Not collective.

See also

setUpdate

Source code at petsc4py/PETSc/SNES.pyx:953

Return type:: tuple[SNESUpdateFunction, tuple[Any, …], dict[str, Any]] | None

getUseEW()#

Return the flag indicating if the solver uses the Eisenstat-Walker trick.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2015

Return type:: bool

getUseFD()#

Return true if the solver uses color finite-differencing for the Jacobian.

Not collective.

See also

setUseFD

Source code at petsc4py/PETSc/SNES.pyx:2175

Return type:: bool

getUseKSP()#

Return the flag indicating if the solver uses a linear solver.

Not collective.

See also

setUseKSP

Source code at petsc4py/PETSc/SNES.pyx:2119

Return type:: bool

getUseMF()#

Return the flag indicating if the solver uses matrix-free finite-differencing.

Not collective.

See also

setUseMF

Source code at petsc4py/PETSc/SNES.pyx:2148

Return type:: bool

getVIInactiveSet()#

Return the index set for the inactive set.

Not collective.

See also

SNESVIGetInactiveSet

Source code at petsc4py/PETSc/SNES.pyx:2218

Return type:: IS

getVariableBounds()#

Get the vectors for the variable bounds.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:2203

Return type:: tuple[Vec, Vec]

hasNPC()#

Return a boolean indicating whether the solver has a nonlinear preconditioner.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:724

Return type:: bool

logConvergenceHistory(norm, linear_its=0)#

Log residual norm and linear iterations.

Source code at petsc4py/PETSc/SNES.pyx:1475

Parameters:

norm (float)
linear_its (int)

Return type:

None

monitor(its, rnorm)#

Monitor the solver.

Collective.

Parameters:

its – Current number of iterations.
rnorm – Current value of the residual norm.

Return type:

None

See also

setMonitor, SNESMonitor

Source code at petsc4py/PETSc/SNES.pyx:1554

monitorCancel()#

Cancel all the monitors of the solver.

Logically collective.

See also

setMonitor, SNESMonitorCancel

Source code at petsc4py/PETSc/SNES.pyx:1541

Return type:: None

reset()#

Reset the solver.

Collective.

See also

SNESReset

Source code at petsc4py/PETSc/SNES.pyx:1732

Return type:: None

setApplicationContext(appctx)#

Set the application context.

Source code at petsc4py/PETSc/SNES.pyx:274

Parameters:: appctx (Any)
Return type:: None

setConvergedReason(reason)#

Set the termination flag.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1767

Parameters:: reason (ConvergedReason)
Return type:: None

setConvergenceHistory(length=None, reset=False)#

Set the convergence history.

Logically collective.

See also

SNESSetConvergenceHistory

Source code at petsc4py/PETSc/SNES.pyx:1433

Return type:: None

setConvergenceTest(converged, args=None, kargs=None)#

Set the callback to use as convergence test.

Logically collective.

Parameters:

converged (SNESConvergedFunction | Literal['skip', 'default']) – The convergence testing callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:1328

setDM(dm)#

Associate a DM with the solver.

Not collective.

See also

getDM, SNESSetDM

Source code at petsc4py/PETSc/SNES.pyx:311

Parameters:: dm (DM)
Return type:: None

setDivergenceTolerance(dtol)#

Set the divergence tolerance parameter used in the convergence tests.

Logically collective.

Parameters:: dtol (float) – The divergence tolerance.
Return type:: None

Source code at petsc4py/PETSc/SNES.pyx:1271

setErrorIfNotConverged(flag=True)#

Immediately generate an error if the solver has not converged.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1794

Parameters:: flag (bool)
Return type:: None

setFASInjection(level, mat)#

Set the Mat to be used to apply the injection from level-1 to level.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:501

Parameters:

level (int)
mat (Mat)

Return type:

None

setFASInterpolation(level, mat)#

Set the Mat to be used to apply the interpolation from level-1 to level.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:441

Parameters:

level (int)
mat (Mat)

Return type:

None

setFASLevels(levels, comms=None)#

Set the number of levels to use with FAS.

Collective.

Parameters:

levels (int) – The number of levels
comms (Sequence[Comm] | None) – An optional sequence of communicators of length Logging Levels, or None for the default communicator Sys.getDefaultComm.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:544

setFASRScale(level, vec)#

Set the scaling factor of the restriction operator from level to level-1.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:531

Parameters:

level (int)
vec (Vec)

Return type:

None

setFASRestriction(level, mat)#

Set the Mat to be used to apply the restriction from level-1 to level.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:471

Parameters:

level (int)
mat (Mat)

Return type:

None

setFASUseCoarseCorrectionLineSearch(use=True)#

Set if to use a line search for the coarse corrections in FAS.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:624

Parameters:: use (bool)
Return type:: None

setForceIteration(force=True)#

Force solve to take at least one iteration.

Collective.

See also

SNESSetForceIteration

Source code at petsc4py/PETSc/SNES.pyx:1850

Parameters:: force (bool)
Return type:: None

setFromOptions()#

Configure the solver from the options database.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:260

Return type:: None

setFunction(function, f=None, args=None, kargs=None)#

Set the callback to compute the nonlinear function.

Logically collective.

Parameters:

function (SNESFunction | None) – The callback.
f (Vec | None) – An optional vector to store the result.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getFunction, SNESSetFunction

Source code at petsc4py/PETSc/SNES.pyx:855

setFunctionNorm(norm)#

Set the function norm value.

Collective.

This is only of use to implementers of custom SNES types.

Source code at petsc4py/PETSc/SNES.pyx:1863

Parameters:: norm (float)
Return type:: None

setInitialGuess(initialguess, args=None, kargs=None)#

Set the callback to compute the initial guess.

Logically collective.

Parameters:

initialguess (SNESGuessFunction | None) – The callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:812

setIterationNumber(its)#

Set the current iteration number.

Collective.

This is only of use to implementers of custom SNES types.

Source code at petsc4py/PETSc/SNES.pyx:1821

Parameters:: its (int)
Return type:: None

setJacobian(jacobian, J=None, P=None, args=None, kargs=None)#

Set the callback to compute the Jacobian.

Logically collective.

Parameters:

jacobian (SNESJacobianFunction | None) – The Jacobian callback.
J (Mat | None) – The matrix to store the Jacobian.
P (Mat | None) – The matrix to construct the preconditioner.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getJacobian, SNESSetJacobian

Source code at petsc4py/PETSc/SNES.pyx:965

setKSP(ksp)#

Set the linear solver that will be used by the nonlinear solver.

Logically collective.

See also

getKSP, SNESSetKSP

Source code at petsc4py/PETSc/SNES.pyx:1965

Parameters:: ksp (KSP)
Return type:: None

setLineSearch(linesearch)#

Set the linesearch object to be used by this SNES.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:2659

Parameters:: linesearch (SNESLineSearch)
Return type:: None

setLineSearchPreCheck(precheck, args=None, kargs=None)#

Set the callback that will be called before applying the linesearch.

Logically collective.

Parameters:

precheck (SNESLSPreFunction | None) – The callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

SNESLineSearchSetPreCheck

Source code at petsc4py/PETSc/SNES.pyx:778

setMaxFunctionEvaluations(max_funcs)#

Set the maximum allowed number of function evaluations.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1577

Parameters:: max_funcs (int)
Return type:: None

setMaxKSPFailures(max_fails)#

Set the maximum allowed number of linear solve failures.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1663

Parameters:: max_fails (int)
Return type:: None

setMaxStepFailures(max_fails)#

Set the maximum allowed number of step failures.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1622

Parameters:: max_fails (int)
Return type:: None

setMonitor(monitor, args=None, kargs=None)#

Set the callback used to monitor solver convergence.

Logically collective.

Parameters:

monitor (SNESMonitorFunction | None) – The callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getMonitor, SNESMonitorSet

Source code at petsc4py/PETSc/SNES.pyx:1496

setNGS(ngs, args=None, kargs=None)#

Set the callback to compute nonlinear Gauss-Seidel.

Logically collective.

Parameters:

ngs (SNESNGSFunction | None) – The nonlinear Gauss-Seidel callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getNGS, computeNGS, SNESSetNGS

Source code at petsc4py/PETSc/SNES.pyx:1138

setNPC(snes)#

Set the nonlinear preconditioner.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:738

Parameters:: snes (SNES)
Return type:: None

setNPCSide(side)#

Set the nonlinear preconditioning side.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:750

Parameters:: side (Side)
Return type:: None

setNewtonALCorrectionType(corrtype)#

Set the correction type for SNESNEWTONAL.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:2727

Parameters:: corrtype (NewtonALCorrectionType)
Return type:: None

setNewtonALFunction(function, args=None, kargs=None)#

Set the callback to compute the tangent load vector for SNESNEWTONAL.

Logically collective.

Parameters:

function (SNESFunction | None) – The callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:2681

setNormSchedule(normsched)#

Set the norm schedule.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:1302

Parameters:: normsched (NormSchedule)
Return type:: None

setObjective(objective, args=None, kargs=None)#

Set the callback to compute the objective function.

Logically collective.

Parameters:

objective (SNESObjFunction | None) – The Jacobian callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getObjective, SNESSetObjective

Source code at petsc4py/PETSc/SNES.pyx:1033

setOptionsPrefix(prefix)#

Set the prefix used for searching for options in the database.

Logically collective.

Source code at petsc4py/PETSc/SNES.pyx:218

Parameters:: prefix (str | None)
Return type:: None

setParamsEW(version=None, rtol_0=None, rtol_max=None, gamma=None, alpha=None, alpha2=None, threshold=None)#

Set the parameters for the Eisenstat and Walker trick.

Logically collective.

Parameters:

version (int | None) – The version of the algorithm. Defaults to CURRENT.
rtol_0 (float | None) – The initial relative residual norm. Defaults to CURRENT.
rtol_max (float | None) – The maximum relative residual norm. Defaults to CURRENT.
gamma (float | None) – Parameter. Defaults to CURRENT.
alpha (float | None) – Parameter. Defaults to CURRENT.
alpha2 (float | None) – Parameter. Defaults to CURRENT.
threshold (float | None) – Parameter. Defaults to CURRENT.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:2029

setPatchCellNumbering(sec)#

Set cell patch numbering.

Source code at petsc4py/PETSc/SNES.pyx:2384

Parameters:: sec (Section)
Return type:: None

setPatchComputeFunction(function, args=None, kargs=None)#

Set patch compute function.

Source code at petsc4py/PETSc/SNES.pyx:2437

Return type:: None

setPatchComputeOperator(operator, args=None, kargs=None)#

Set patch compute operator.

Source code at petsc4py/PETSc/SNES.pyx:2429

Return type:: None

setPatchConstructType(typ, operator=None, args=None, kargs=None)#

Set patch construct type.

Source code at petsc4py/PETSc/SNES.pyx:2445

Return type:: None

setPatchDiscretisationInfo(dms, bs, cellNodeMaps, subspaceOffsets, ghostBcNodes, globalBcNodes)#

Set patch discretisation information.

Source code at petsc4py/PETSc/SNES.pyx:2388

Return type:: None

setPythonContext(context)#

Set the instance of the class implementing the required Python methods.

Not collective.

Source code at petsc4py/PETSc/SNES.pyx:2260

Parameters:: context (Any)
Return type:: None

setPythonType(py_type)#

Set the fully qualified Python name of the class to be used.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:2287

Parameters:: py_type (str)
Return type:: None

setResetCounters(reset=True)#

Set the flag to reset the counters.

Collective.

See also

SNESSetCountersReset

Source code at petsc4py/PETSc/SNES.pyx:1481

Parameters:: reset (bool)
Return type:: None

setSolution(vec)#

Set the vector used to store the solution.

Collective.

See also

getSolution, SNESSetSolution

Source code at petsc4py/PETSc/SNES.pyx:1936

Parameters:: vec (Vec)
Return type:: None

setTRTolerances(delta_min=None, delta_max=None, delta_0=None)#

Set the tolerance parameters used for the trust region.

Logically collective.

Parameters:

delta_min (float | None) – The minimum allowed trust region size. Defaults to CURRENT.
delta_max (float | None) – The maximum allowed trust region size. Defaults to CURRENT.
delta_0 (float | None) – The initial trust region size. Defaults to CURRENT.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:325

setTRUpdateParameters(eta1=None, eta2=None, eta3=None, t1=None, t2=None)#

Set the update parameters used for the trust region.

Logically collective.

Parameters:

eta1 (float | None) – The step acceptance tolerance. Defaults to CURRENT.
eta2 (float | None) – The shrinking tolerance. Defaults to CURRENT.
eta3 (float | None) – The enlarging tolerance. Defaults to CURRENT.
t1 (float | None) – The shrinking factor. Defaults to CURRENT.
t2 (float | None) – The enlarging factor. Defaults to CURRENT.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:376

setTolerances(rtol=None, atol=None, stol=None, max_it=None)#

Set the tolerance parameters used in the solver convergence tests.

Logically collective.

Parameters:

rtol (float | None) – The relative norm of the residual, or DETERMINE to use the value when the object’s type was set. Defaults to CURRENT.
atol (float | None) – The absolute norm of the residual, or DETERMINE to use the value when the object’s type was set. Defaults to CURRENT.
stol (float | None) – The absolute norm of the step, or DETERMINE to use the value when the object’s type was set. Defaults to CURRENT.
max_it (int | None) – The maximum allowed number of iterations, or DETERMINE to use the value when the object’s type was set. Defaults to CURRENT. Use UNLIMITED to have no maximum.

Return type:

None

See also

getTolerances, SNESSetTolerances

Source code at petsc4py/PETSc/SNES.pyx:1205

setType(snes_type)#

Set the type of the solver.

Logically collective.

Parameters:: snes_type (Type | str) – The type of the solver.
Return type:: None

See also

getType, SNESSetType

Source code at petsc4py/PETSc/SNES.pyx:185

setUp()#

Set up the internal data structures for using the solver.

Collective.

See also

SNESSetUp

Source code at petsc4py/PETSc/SNES.pyx:1706

Return type:: None

setUpMatrices()#

Ensures that matrices are available for Newton-like methods.

Collective.

This is only of use to implementers of custom SNES types.

See also

setUp, SNESSetUpMatrices

Source code at petsc4py/PETSc/SNES.pyx:1718

Return type:: None

setUpdate(update, args=None, kargs=None)#

Set the callback to compute update at the beginning of each step.

Logically collective.

Parameters:

update (SNESUpdateFunction | None) – The callback.
args (tuple[Any, ...] | None) – Positional arguments for the callback.
kargs (dict[str, Any] | None) – Keyword arguments for the callback.

Return type:

None

See also

getUpdate, SNESSetUpdate

Source code at petsc4py/PETSc/SNES.pyx:922

setUseEW(flag=True, *targs, **kargs)#

Tell the solver to use the Eisenstat-Walker trick.

Logically collective.

Parameters:

flag (bool) – Whether or not to use the Eisenstat-Walker trick.
*targs (Any) – Positional arguments for setParamsEW.
**kargs (Any) – Keyword arguments for setParamsEW.

Return type:

None

Source code at petsc4py/PETSc/SNES.pyx:1992

setUseFD(flag=True)#

Set the boolean flag to use coloring finite-differencing for Jacobian assembly.

Logically collective.

See also

getUseFD

Source code at petsc4py/PETSc/SNES.pyx:2162

Return type:: None

setUseKSP(flag=True)#

Set the boolean flag indicating to use a linear solver.

Logically collective.

See also

getUseKSP

Source code at petsc4py/PETSc/SNES.pyx:2106

Return type:: None

setUseMF(flag=True)#

Set the boolean flag indicating to use matrix-free finite-differencing.

Logically collective.

See also

getUseMF

Source code at petsc4py/PETSc/SNES.pyx:2135

Return type:: None

setVariableBounds(xl, xu)#

Set the vector for the variable bounds.

Collective.

Source code at petsc4py/PETSc/SNES.pyx:2191

Parameters:

xl (Vec)
xu (Vec)

Return type:

None

solve(b=None, x=None)#

Solve the nonlinear equations.

Collective.

Parameters:

b (Vec | None) – The affine right-hand side or None to use zero.
x (Vec | None) – The starting vector or None to use the vector stored internally.

Return type: