Struct JacobiPreconditioner 

pub struct JacobiPreconditioner<F> { /* private fields */ }

Jacobi (diagonal) preconditioner

This preconditioner uses the inverse of the diagonal of the matrix. M^(-1) = diag(1/a_11, 1/a_22, …, 1/a_nn)

Implementations

impl<F: Float> JacobiPreconditioner<F>

pub fn new(matrix: &CsrMatrix<F>) -> SparseResult<Self>

where F: Debug,

Create a new Jacobi preconditioner from a sparse matrix

pub fn from_diagonal(diagonal: Vec<F>) -> SparseResult<Self>

Create from diagonal values directly

Trait Implementations

impl<F: Float + NumAssign> LinearOperator<F> for JacobiPreconditioner<F>

fn shape(&self) -> (usize, usize)

The shape of the operator (rows, columns)

fn matvec(&self, x: &[F]) -> SparseResult<Vec<F>>

Apply the operator to a vector: y = A * x

fn has_adjoint(&self) -> bool

Check if the operator supports adjoint operations

fn rmatvec(&self, x: &[F]) -> SparseResult<Vec<F>>

Apply the adjoint of the operator to a vector: y = A^H * x Default implementation returns an error

fn matmat(&self, x: &[Vec<F>]) -> SparseResult<Vec<Vec<F>>>

Apply the operator to a matrix: Y = A * X where X is column-major (each column is a vector)

fn rmatmat(&self, x: &[Vec<F>]) -> SparseResult<Vec<Vec<F>>>

Apply the adjoint of the operator to a matrix: Y = A^H * X Default implementation calls rmatvec for each column