Eigen::IterativeSolverBase
          
     IterativeSolverBase() [1/2]
    template<typename Derived > 
   
    IterativeSolverBase() [2/2]
    template<typename Derived > 
  template<typename MatrixDerived > 
   
 Initialize the solver with matrix A for further Ax=b solving.
 This constructor is a shortcut for the default constructor followed by a call to compute().
 
- Warning
- this class stores a reference to the matrix A as well as some precomputed values that depend on it. Therefore, if A is changed this class becomes invalid. Call compute() to update it with the new matrix A, or modify a copy of A. 
      analyzePattern()
    template<typename Derived > 
  template<typename MatrixDerived > 
   
 Initializes the iterative solver for the sparsity pattern of the matrix A for further solving Ax=b problems.
 Currently, this function mostly calls analyzePattern on the preconditioner. In the future we might, for instance, implement column reordering for faster matrix vector products. 
      compute()
    template<typename Derived > 
  template<typename MatrixDerived > 
   
 Initializes the iterative solver with the matrix A for further solving Ax=b problems.
 Currently, this function mostly initializes/computes the preconditioner. In the future we might, for instance, implement column reordering for faster matrix vector products.
 
- Warning
- this class stores a reference to the matrix A as well as some precomputed values that depend on it. Therefore, if A is changed this class becomes invalid. Call compute() to update it with the new matrix A, or modify a copy of A. 
     error()
    template<typename Derived > 
   
 
- Returns
- the tolerance error reached during the last solve. It is a close approximation of the true relative residual error |Ax-b|/|b|. 
     factorize()
    template<typename Derived > 
  template<typename MatrixDerived > 
   
 Initializes the iterative solver with the numerical values of the matrix A for further solving Ax=b problems.
 Currently, this function mostly calls factorize on the preconditioner.
 
- Warning
- this class stores a reference to the matrix A as well as some precomputed values that depend on it. Therefore, if A is changed this class becomes invalid. Call compute() to update it with the new matrix A, or modify a copy of A. 
     info()
    template<typename Derived > 
   
 
- Returns
- Success if the iterations converged, and NoConvergence otherwise. 
     iterations()
    template<typename Derived > 
   
 
- Returns
- the number of iterations performed during the last solve 
     maxIterations()
    template<typename Derived > 
   
 
- Returns
- the max number of iterations. It is either the value set by setMaxIterations or, by default, twice the number of columns of the matrix. 
     preconditioner() [1/2]
    template<typename Derived > 
   
 
- Returns
- a read-write reference to the preconditioner for custom configuration. 
     preconditioner() [2/2]
    template<typename Derived > 
   
 
- Returns
- a read-only reference to the preconditioner. 
     setMaxIterations()
    template<typename Derived > 
   
 Sets the max number of iterations. Default is twice the number of columns of the matrix. 
      setTolerance()
    template<typename Derived > 
   
 Sets the tolerance threshold used by the stopping criteria.
 This value is used as an upper bound to the relative residual error: |Ax-b|/|b|. The default value is the machine precision given by NumTraits<Scalar>::epsilon() 
      solveWithGuess()
    template<typename Derived > 
  template<typename Rhs , typename Guess > 
   
 
- Returns
- the solution x of \( A x = b \) using the current decomposition of A and x0 as an initial solution.
- See also
- 
solve(), compute() 
     tolerance()
    template<typename Derived > 
   
 
- Returns
- the tolerance threshold used by the stopping criteria. 
- See also
- 
setTolerance() 
    
The documentation for this class was generated from the following file: