Struct ndarray_linalg::krylov::householder::Householder

pub struct Householder<A: Scalar> { /* fields omitted */ }

Iterative orthogonalizer using Householder reflection

Implementations

impl<A: Scalar + Lapack> Householder<A>

pub fn new(dim: usize, tol: A::Real) -> Self

Create a new orthogonalizer

pub fn forward_reflection<S>(&self, a: &mut ArrayBase<S, Ix1>) where
    S: DataMut<Elem = A>, 

Take forward reflection P = P_l ... P_1

pub fn backward_reflection<S>(&self, a: &mut ArrayBase<S, Ix1>) where
    S: DataMut<Elem = A>, 

Take backward reflection P = P_1 ... P_l

Trait Implementations

impl<A: Clone + Scalar> Clone for Householder<A> where
    A::Real: Clone, 

fn clone(&self) -> Householder<A>

Returns a copy of the value.

pub fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<A: Debug + Scalar> Debug for Householder<A> where
    A::Real: Debug, 

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<A: Scalar + Lapack> Orthogonalizer for Householder<A>

type Elem = A

fn dim(&self) -> usize

Dimension of input array

fn len(&self) -> usize

Number of cached basis

fn tolerance(&self) -> A::Real

fn decompose<S>(&self, a: &mut ArrayBase<S, Ix1>) -> Array1<A> where
    S: DataMut<Elem = A>, 

Decompose given vector into the span of current basis and its tangent space

fn coeff<S>(&self, a: ArrayBase<S, Ix1>) -> Array1<A> where
    S: Data<Elem = A>, 

Calculate the coefficient to the current basis basis

fn div_append<S>(&mut self, a: &mut ArrayBase<S, Ix1>) -> AppendResult<A> where
    S: DataMut<Elem = A>, 

Add new vector if the residual is larger than relative tolerance, and return the residual vector

fn append<S>(&mut self, a: ArrayBase<S, Ix1>) -> AppendResult<A> where
    S: Data<Elem = A>, 

Add new vector if the residual is larger than relative tolerance

fn get_q(&self) -> Q<A>

Get Q-matrix of generated basis

fn is_full(&self) -> bool

check if the basis spans entire space

fn is_empty(&self) -> bool