This page contains the pysparse Package documentation.
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.
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.
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.
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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.
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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.
Bases: fipy.solvers.solver.Solver
The base pysparseSolver class.
Attention
This class is abstract. Always create one of its subclasses.