Chebyshev

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## no.uib.cipr.matrix.sparse
Class Chebyshev

    java.lang.Object
      no.uib.cipr.matrix.sparse.AbstractIterativeSolver
          no.uib.cipr.matrix.sparse.Chebyshev

All Implemented Interfaces:
  IterativeSolver

    public class Chebyshev

extends AbstractIterativeSolver

Chebyshev solver. Solves the symmetric positive definite linear system `Ax = b` using the Preconditioned Chebyshev Method. Chebyshev requires an acurate estimate on the bounds of the spectrum of the matrix.

Field Summary

Fields inherited from class no.uib.cipr.matrix.sparse.AbstractIterativeSolver
`iter, M`

Constructor Summary
`Chebyshev(Vector template, double eigmin, double eigmax)` Constructor for Chebyshev.

Method Summary
`void` | `setEigenvalues(double eigmin, double eigmax)` Sets the eigenvalue estimates.
`Vector` | `solve(Matrix A, Vector b, Vector x)` Solves the given problem, writing result into the vector.

Methods inherited from class no.uib.cipr.matrix.sparse.AbstractIterativeSolver
`checkSizes, getIterationMonitor, getPreconditioner, setIterationMonitor, setPreconditioner`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### Chebyshev

    public Chebyshev(Vector template,
                     double eigmin,
                     double eigmax)

  Constructor for Chebyshev. Uses the given vector as template for creating scratch vectors. Typically, the solution or the right hand side vector can be passed, and the template is not modified. Eigenvalue estimates must also be provided

  Parameters:
    `template` - Vector to use as template for the work vectors needed in the solution process
    `eigmin` - Smallest eigenvalue. Must be positive
    `eigmax` - Largest eigenvalue. Must be positive

Method Detail

### setEigenvalues

    public void setEigenvalues(double eigmin,
                               double eigmax)

  Sets the eigenvalue estimates.

  Parameters:
    `eigmin` - Smallest eigenvalue. Must be positive
    `eigmax` - Largest eigenvalue. Must be positive

### solve

    public Vector solve(Matrix A,
                        Vector b,
                        Vector x)
                 throws IterativeSolverNotConvergedException

  Description copied from interface: `IterativeSolver`
  Solves the given problem, writing result into the vector.

  Parameters:
    `A` - Matrix of the problem
    `b` - Right hand side
    `x` - Solution is stored here. Also used as initial guess
  Returns:
    The solution vector x
  Throws:
    `IterativeSolverNotConvergedException`

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