Struct Qr 

pub struct Qr<T> { /* private fields */ }

$QR$ decomposition

Implementations

impl<T: ComplexField> Qr<T>

pub fn new<C: Conjugate<Canonical = T>>(A: MatRef<'_, C>) -> Self

returns the $QR$ decomposition of $A$

pub fn Q_basis(&self) -> MatRef<'_, T>

returns the householder basis of $Q$

pub fn Q_coeff(&self) -> MatRef<'_, T>

returns the householder coefficients of $Q$

pub fn R(&self) -> MatRef<'_, T>

returns the factor $R$

pub fn thin_R(&self) -> MatRef<'_, T>

returns the upper trapezoidal part of $R$

pub fn compute_Q(&self) -> Mat<T>

computes the factor $Q$

pub fn compute_thin_Q(&self) -> Mat<T>

computes the first $\min(\text{nrows}, \text{ncols})$ columns of the factor $Q$

Trait Implementations

impl<T: Clone> Clone for Qr<T>

fn clone(&self) -> Qr<T>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for Qr<T>

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

Formats the value using the given formatter.

impl<T: ComplexField> DenseSolveCore<T> for Qr<T>

fn reconstruct(&self) -> Mat<T>

returns an approximation of the matrix that was used to create the decomposition

fn inverse(&self) -> Mat<T>

returns an approximation of the inverse of the matrix that was used to create the decomposition

impl<T: ComplexField> ShapeCore for Qr<T>

fn nrows(&self) -> usize

returns the number of rows of the matrix

fn ncols(&self) -> usize

returns the number of columns of the matrix

impl<T: ComplexField> SolveCore<T> for Qr<T>

fn solve_in_place_with_conj(&self, conj: Conj, rhs: MatMut<'_, T>)

solves the equation self × x = rhs, implicitly conjugating self if needed, and stores the result in rhs

fn solve_transpose_in_place_with_conj(&self, conj: Conj, rhs: MatMut<'_, T>)

solves the equation self.transpose() × x = rhs, implicitly conjugating self if needed, and stores the result in rhs

impl<T: ComplexField> SolveLstsqCore<T> for Qr<T>

fn solve_lstsq_in_place_with_conj(&self, conj: Conj, rhs: MatMut<'_, T>)

solves the equation self × x = rhs in the sense of least squares, implicitly conjugating self if needed, and stores the result in the top rows of rhs