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pysparse Package Documentation

This page contains the pysparse Package documentation.

The linearCGSSolver Module

class fipy.solvers.pysparse.linearCGSSolver.LinearCGSSolver(*args, **kwargs)

Bases: fipy.solvers.pysparse.pysparseSolver.PysparseSolver

The LinearCGSSolver solves a linear system of equations using the conjugate gradient squared method (CGS), a variant of the biconjugate gradient method (BiCG). CGS solves linear systems with a general non-symmetric coefficient matrix.

The LinearCGSSolver is a wrapper class for the the PySparse itsolvers.cgs() method.

The linearGMRESSolver Module

class fipy.solvers.pysparse.linearGMRESSolver.LinearGMRESSolver(*args, **kwargs)

Bases: fipy.solvers.pysparse.pysparseSolver.PysparseSolver

The LinearGMRESSolver solves a linear system of equations using the generalised minimal residual method (GMRES) with Jacobi preconditioning. GMRES solves systems with a general non-symmetric coefficient matrix.

The LinearGMRESSolver is a wrapper class for the the PySparse itsolvers.gmres() and precon.jacobi() methods.

The linearJORSolver Module

class fipy.solvers.pysparse.linearJORSolver.LinearJORSolver(tolerance=1e-10, iterations=1000, steps=None, relaxation=1.0, precon=None)

Bases: fipy.solvers.pysparse.pysparseSolver.PysparseSolver

The LinearJORSolver solves a linear system of equations using Jacobi over-relaxation. This method solves systems with a general non-symmetric coefficient matrix.

The Solver class should not be invoked directly.

Parameters :
  • tolerance: The required error tolerance.
  • iterations: The maximum number of iterative steps to perform.
  • steps: A deprecated name for iterations.
  • relaxation: The relaxation.

The linearLUSolver Module

class fipy.solvers.pysparse.linearLUSolver.LinearLUSolver(tolerance=1e-10, iterations=10, steps=None, precon=None, maxIterations=10)

Bases: fipy.solvers.pysparse.pysparseSolver.PysparseSolver

The LinearLUSolver solves a linear system of equations using LU-factorisation. This method solves systems with a general non-symmetric coefficient matrix using partial pivoting.

The LinearLUSolver is a wrapper class for the the PySparse superlu.factorize() method.

Creates a LinearLUSolver.

Parameters :
  • tolerance: The required error tolerance.
  • iterations: The number of LU decompositions to perform.
  • steps: A deprecated name for iterations. For large systems a number of iterations is generally required.
  • precon: not used but maintains a common interface.

The linearPCGSolver Module

class fipy.solvers.pysparse.linearPCGSolver.LinearPCGSolver(*args, **kwargs)

Bases: fipy.solvers.pysparse.pysparseSolver.PysparseSolver

The LinearPCGSolver solves a linear system of equations using the preconditioned conjugate gradient method (PCG) with symmetric successive over-relaxation (SSOR) preconditioning. The PCG method solves systems with a symmetric positive definite coefficient matrix.

The LinearPCGSolver is a wrapper class for the the PySparse itsolvers.pcg() and precon.ssor() methods.

The pysparseSolver Module

class fipy.solvers.pysparse.pysparseSolver.PysparseSolver(*args, **kwargs)

Bases: fipy.solvers.solver.Solver

The base pysparseSolver class.

Attention

This class is abstract. Always create one of its subclasses.