Struct ndarray_linalg::krylov::MGS

pub struct MGS<A> { /* fields omitted */ }

Iterative orthogonalizer using modified Gram-Schmit procedure

let mut mgs = MGS::new(3);
let coef = mgs.append(array![0.0, 1.0, 0.0], 1e-9).unwrap();
close_l2(&coef, &array![1.0], 1e-9);

let coef = mgs.append(array![1.0, 1.0, 0.0], 1e-9).unwrap();
close_l2(&coef, &array![1.0, 1.0], 1e-9);

// Fail if the vector is linearly dependent
assert!(mgs.append(array![1.0, 2.0, 0.0], 1e-9).is_err());

// You can get coefficients of dependent vector
if let Err(coef) = mgs.append(array![1.0, 2.0, 0.0], 1e-9) {
    close_l2(&coef, &array![2.0, 1.0, 0.0], 1e-9);
}

Methods

impl<A: Scalar> MGS<A>

pub fn new(dimension: usize) -> Self

Create an empty orthogonalizer

Trait Implementations

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

type Elem = A

fn dim(&self) -> usize

Dimension of input array

fn len(&self) -> usize

Number of cached basis

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

Orthogonalize given vector using current basis

fn append<S>(
    &mut self,
    a: ArrayBase<S, Ix1>,
    rtol: A::Real
) -> Result<Array1<A>, Array1<A>> where
    A: Lapack,
    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

impl<A: Clone> Clone for MGS<A>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<A: Debug> Debug for MGS<A>

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

Formats the value using the given formatter.