Trait linxal::prelude::LinxalMatrixInto

pub trait LinxalMatrixInto<F: LinxalScalar> {
    fn eigenvalues_into(self) -> Result<Array<F::Complex, Ix1>, EigenError>;
    fn eigenvalues_vectors_into(
        self, 
        compute_left: bool, 
        compute_right: bool
    ) -> Result<Solution<F, F::Complex>, EigenError>;
    fn symmetric_eigenvalues_into(
        self, 
        uplo: Symmetric
    ) -> Result<Array<F::RealPart, Ix1>, EigenError>;
    fn solve_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
        self, 
        b: ArrayBase<D1, Ix1>
    ) -> Result<ArrayBase<D1, Ix1>, SolveError>;
    fn solve_symmetric_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
        self, 
        b: ArrayBase<D1, Ix1>, 
        uplo: Symmetric
    ) -> Result<ArrayBase<D1, Ix1>, SolveError>;
    fn solve_multi_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
        self, 
        b: ArrayBase<D1, Ix2>
    ) -> Result<ArrayBase<D1, Ix2>, SolveError>;
    fn solve_symmetric_multi_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
        self, 
        b: ArrayBase<D1, Ix2>, 
        uplo: Symmetric
    ) -> Result<ArrayBase<D1, Ix2>, SolveError>;
    fn svd_full_into(self) -> Result<SVDSolution<F>, SVDError>;
    fn svd_econ_into(self) -> Result<SVDSolution<F>, SVDError>;
    fn singular_values_into(self) -> Result<Array<F::RealPart, Ix1>, SVDError>;
    fn conj_into(self) -> Self;
}

All-encompassing matrix trait, supporting all of the linear algebra operations defined for any LinxalScalar.

Required Methods

fn eigenvalues_into(self) -> Result<Array<F::Complex, Ix1>, EigenError>

Compute the eigenvalues of a matrix.

fn eigenvalues_vectors_into(
    self,
    compute_left: bool,
    compute_right: bool
) -> Result<Solution<F, F::Complex>, EigenError>

Compute the eigenvalues and the right and/or left eigenvectors of a generic matrix.

fn symmetric_eigenvalues_into(
    self,
    uplo: Symmetric
) -> Result<Array<F::RealPart, Ix1>, EigenError>

Compute the eigenvalues of a symmetric matrix.

fn solve_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
    self,
    b: ArrayBase<D1, Ix1>
) -> Result<ArrayBase<D1, Ix1>, SolveError>

Solve a single system of linear equations.

fn solve_symmetric_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
    self,
    b: ArrayBase<D1, Ix1>,
    uplo: Symmetric
) -> Result<ArrayBase<D1, Ix1>, SolveError>

Solve a single system of linear equations with a symmetrix coefficient matrix.

fn solve_multi_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
    self,
    b: ArrayBase<D1, Ix2>
) -> Result<ArrayBase<D1, Ix2>, SolveError>

Solve a system of linear equations with multiple RHS vectors.

fn solve_symmetric_multi_linear_into<D1: DataMut<Elem = F> + DataOwned<Elem = F>>(
    self,
    b: ArrayBase<D1, Ix2>,
    uplo: Symmetric
) -> Result<ArrayBase<D1, Ix2>, SolveError>

Solve a system of linear equations with a symmetrix coefficient matrix for multiple RHS vectors.

Each column of b is a RHS vector to be solved for.

fn svd_full_into(self) -> Result<SVDSolution<F>, SVDError>

Return the full singular value decomposition of the matrix.

The SVDSolution contains full size matrices u (m x m) and vt (n x n).

fn svd_econ_into(self) -> Result<SVDSolution<F>, SVDError>

Return the economic singular value decomposition of the matrix.

The SVDSolution contains sufficient matrices u (m x p) and vt (p x n), where p is the minimum of m and n.

fn singular_values_into(self) -> Result<Array<F::RealPart, Ix1>, SVDError>

Return the full singular value decomposition of the matrix.

The SVDSolution contains full size matrices u (m x m) and vt (n x n).

fn conj_into(self) -> Self

Return the conjugate of the matrix.

Implementors

• impl<F: LinxalScalar, D: DataMut<Elem = F> + DataOwned<Elem = F>> LinxalMatrixInto<F> for ArrayBase<D, Ix2>