Struct Lapack 

pub struct Lapack { /* private fields */ }

Implementations

impl Lapack

pub fn new() -> Self

pub fn config_svd(self, config: SVDConfig) -> Self

pub fn config_qr(self, _config: LapackQRConfig) -> Self

Trait Implementations

impl Clone for Lapack

fn clone(&self) -> Lapack

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Lapack

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

Formats the value using the given formatter.

impl Default for Lapack

fn default() -> Lapack

Returns the “default value” for a type.

impl<T> Eig<T> for Lapack

where T: ComplexFloat + Default + LapackScalar + NeedsRwork<Elem = T>, i8: Into<T::Real>, T::Real: Into<T>,

fn eig<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> EigResult<T>

where T: ComplexFloat,

Compute eigenvalues and right eigenvectors with new allocated matrices

fn eig_full<L: Layout>(&self, _a: &mut DSlice<T, 2, L>) -> EigResult<T>

Compute eigenvalues and both left/right eigenvectors with new allocated matrices

fn eig_values<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> EigResult<T>

Compute only eigenvalues with new allocated vectors

fn eigh<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> EigResult<T>

Compute eigenvalues and eigenvectors of a Hermitian matrix

fn eigs<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> EigResult<T>

Compute eigenvalues and eigenvectors of a Hermitian matrix

fn schur<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> SchurResult<T>

Compute Schur decomposition with new allocated matrices

fn schur_overwrite<L: Layout>( &self, a: &mut DSlice<T, 2, L>, t: &mut DSlice<T, 2, Dense>, z: &mut DSlice<T, 2, Dense>, ) -> Result<(), SchurError>

Compute Schur decomposition overwriting existing matrices

fn schur_complex<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> SchurResult<T>

Compute Schur (complex) decomposition with new allocated matrices

fn schur_complex_overwrite<L: Layout>( &self, a: &mut DSlice<T, 2, L>, t: &mut DSlice<T, 2, Dense>, z: &mut DSlice<T, 2, Dense>, ) -> Result<(), SchurError>

Compute Schur (complex) decomposition overwriting existing matrices

impl<T> LU<T> for Lapack

where T: ComplexFloat + Default + LapackScalar + Workspace, T::Real: Into<T>,

fn choleski<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> InvResult<T>

Computes the Cholesky decomposition, returning a lower-triangular matrix

fn choleski_overwrite<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> Result<(), InvError>

Computes the Cholesky decomposition in-place, overwriting the input matrix

fn lu_overwrite<L: Layout, Ll: Layout, Lu: Layout, Lp: Layout>( &self, a: &mut DSlice<T, 2, L>, l: &mut DSlice<T, 2, Ll>, u: &mut DSlice<T, 2, Lu>, p: &mut DSlice<T, 2, Lp>, )

Computes LU decomposition overwriting existing matrices

fn lu<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> (DTensor<T, 2>, DTensor<T, 2>, DTensor<T, 2>)

Computes LU decomposition with new allocated matrices: L, U, P (permutation matrix)

fn inv_overwrite<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> Result<(), InvError>

Computes inverse overwriting the input matrix

fn inv<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> InvResult<T>

Computes inverse with new allocated matrix

fn det<L: Layout>(&self, a: &mut DSlice<T, 2, L>) -> T

Computes the determinant of a square matrix. Panics if the matrix is non-square.

impl<T> QR<T> for Lapack

where T: ComplexFloat + Default + LapackScalar + NeedsRwork, T::Real: Into<T>,

fn qr_overwrite<L: Layout, Lq: Layout, Lr: Layout>( &self, a: &mut DSlice<T, 2, L>, q: &mut DSlice<T, 2, Lq>, r: &mut DSlice<T, 2, Lr>, )

Compute QR decomposition overwriting existing matrices

fn qr<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> (DTensor<T, 2>, DTensor<T, 2>)

Compute QR decomposition with new allocated matrices

impl<T> SVD<T> for Lapack

where T: ComplexFloat + Default + LapackScalar + NeedsRwork, T::Real: Into<T>,

fn svd<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> Result<SVDDecomp<T>, SVDError>

Compute full SVD with new allocated matrices

fn svd_s<L: Layout>( &self, a: &mut DSlice<T, 2, L>, ) -> Result<DTensor<T, 2>, SVDError>

Compute only singular values with new allocated matrix

fn svd_overwrite<L: Layout, Ls: Layout, Lu: Layout, Lvt: Layout>( &self, a: &mut DSlice<T, 2, L>, s: &mut DSlice<T, 2, Ls>, u: &mut DSlice<T, 2, Lu>, vt: &mut DSlice<T, 2, Lvt>, ) -> Result<(), SVDError>

Compute full SVD, overwriting existing matrices The matrix A is decomposed as A = U * S * V^T where:

fn svd_overwrite_s<L: Layout, Ls: Layout>( &self, a: &mut DSlice<T, 2, L>, s: &mut DSlice<T, 2, Ls>, ) -> Result<(), SVDError>

Compute only singular values, overwriting existing matrix Computes only the diagonal elements of the S matrix from the SVD decomposition.

impl<T> Solve<T> for Lapack

where T: ComplexFloat + Default + LapackScalar, T::Real: Into<T>,

fn solve_overwrite<La: Layout, Lb: Layout, Lp: Layout>( &self, a: &mut DSlice<T, 2, La>, b: &mut DSlice<T, 2, Lb>, p: &mut DSlice<T, 2, Lp>, ) -> Result<(), SolveError>

Solves linear system AX = b overwriting existing matrices A is overwritten with its LU decomposition B is overwritten with the solution X P is filled with the permutation matrix such that A = PLU Returns Ok(()) on success, Err(SolveError) on failure

fn solve<La: Layout, Lb: Layout>( &self, a: &mut DSlice<T, 2, La>, b: &DSlice<T, 2, Lb>, ) -> SolveResultType<T>

Solves linear system AX = B with new allocated solution matrix A is modified (overwritten with LU decomposition) Returns the solution X and P the permutation matrix, or error