petsc4py.PETSc.KSP.NormType

class petsc4py.PETSc.KSP.NormType

Bases: object

KSP norm type.

The available norm types are:

NONE

Skips computing the norm, this should generally only be used if you are using the Krylov method as a smoother with a fixed small number of iterations. Implicitly sets KSPConvergedSkip as KSP convergence test. Note that certain algorithms such as Type.GMRES ALWAYS require the norm calculation, for these methods the norms are still computed, they are just not used in the convergence test.

PRECONDITIONED

The default for left preconditioned solves, uses the l₂ norm of the preconditioned residual P⁻¹(b - Ax).

UNPRECONDITIONED

Uses the l₂ norm of the true b - Ax residual.

NATURAL

Supported by Type.CG, Type.CR, Type.CGNE, Type.CGS.

Attributes Summary

DEFAULT	Constant DEFAULT of type int
NATURAL	Constant NATURAL of type int
NO	Constant NO of type int
NONE	Constant NONE of type int
NORM_DEFAULT	Constant NORM_DEFAULT of type int
NORM_NATURAL	Constant NORM_NATURAL of type int
NORM_NONE	Constant NORM_NONE of type int
NORM_PRECONDITIONED	Constant NORM_PRECONDITIONED of type int
NORM_UNPRECONDITIONED	Constant NORM_UNPRECONDITIONED of type int
PRECONDITIONED	Constant PRECONDITIONED of type int
UNPRECONDITIONED	Constant UNPRECONDITIONED of type int

Attributes Documentation

DEFAULT: int = DEFAULT

Constant DEFAULT of type int

NATURAL: int = NATURAL

Constant NATURAL of type int

NO: int = NO

Constant NO of type int

NONE: int = NONE

Constant NONE of type int

NORM_DEFAULT: int = NORM_DEFAULT

Constant NORM_DEFAULT of type int

NORM_NATURAL: int = NORM_NATURAL

Constant NORM_NATURAL of type int

NORM_NONE: int = NORM_NONE

Constant NORM_NONE of type int

NORM_PRECONDITIONED: int = NORM_PRECONDITIONED

Constant NORM_PRECONDITIONED of type int

NORM_UNPRECONDITIONED: int = NORM_UNPRECONDITIONED

Constant NORM_UNPRECONDITIONED of type int

PRECONDITIONED: int = PRECONDITIONED

Constant PRECONDITIONED of type int

UNPRECONDITIONED: int = UNPRECONDITIONED

Constant UNPRECONDITIONED of type int