Struct ndarray_linalg::solve::LUFactorized

pub struct LUFactorized<S: Data + RawDataClone> { /* private fields */ }

Represents the LU factorization of a matrix A as A = P*L*U.

Trait Implementations

impl<S: Clone + Data + RawDataClone> Clone for LUFactorized<S>

fn clone(&self) -> LUFactorized<S>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<A, S> Determinant<A> for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

fn sln_det(&self) -> Result<(A, A::Real)>

Computes the (sign, natural_log) of the determinant of the matrix.

fn det(&self) -> Result<A>

Computes the determinant of the matrix.

impl<A, S> DeterminantInto<A> for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

fn sln_det_into(self) -> Result<(A, A::Real)>

Computes the (sign, natural_log) of the determinant of the matrix.

fn det_into(self) -> Result<A>

Computes the determinant of the matrix.

impl<A, S> Inverse for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

type Output = ArrayBase<OwnedRepr<A>, Dim<[usize; 2]>>

fn inv(&self) -> Result<Array2<A>>

Computes the inverse of the matrix.

impl<A, S> InverseInto for LUFactorized<S>where
    A: Scalar + Lapack,
    S: DataMut<Elem = A> + RawDataClone,

type Output = ArrayBase<S, Dim<[usize; 2]>>

fn inv_into(self) -> Result<ArrayBase<S, Ix2>>

Computes the inverse of the matrix.

impl<A, S> ReciprocalConditionNum<A> for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

fn rcond(&self) -> Result<A::Real>

Estimates the reciprocal of the condition number of the matrix in 1-norm.

impl<A, S> ReciprocalConditionNumInto<A> for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

fn rcond_into(self) -> Result<A::Real>

Estimates the reciprocal of the condition number of the matrix in 1-norm.

impl<A, S> Solve<A> for LUFactorized<S>where
    A: Scalar + Lapack,
    S: Data<Elem = A> + RawDataClone,

fn solve_inplace<'a, Sb>(
    &self,
    rhs: &'a mut ArrayBase<Sb, Ix1>
) -> Result<&'a mut ArrayBase<Sb, Ix1>>where
    Sb: DataMut<Elem = A>,

Solves a system of linear equations A * x = b where A is self, b is the argument, and x is the successful result.

fn solve_t_inplace<'a, Sb>(
    &self,
    rhs: &'a mut ArrayBase<Sb, Ix1>
) -> Result<&'a mut ArrayBase<Sb, Ix1>>where
    Sb: DataMut<Elem = A>,

Solves a system of linear equations A^T * x = b where A is self, b is the argument, and x is the successful result.

fn solve_h_inplace<'a, Sb>(
    &self,
    rhs: &'a mut ArrayBase<Sb, Ix1>
) -> Result<&'a mut ArrayBase<Sb, Ix1>>where
    Sb: DataMut<Elem = A>,

Solves a system of linear equations A^H * x = b where A is self, b is the argument, and x is the successful result.

fn solve<S: Data<Elem = A>>(&self, b: &ArrayBase<S, Ix1>) -> Result<Array1<A>>

Solves a system of linear equations A * x = b where A is self, b is the argument, and x is the successful result.

fn solve_into<S: DataMut<Elem = A>>(
    &self,
    b: ArrayBase<S, Ix1>
) -> Result<ArrayBase<S, Ix1>>

Solves a system of linear equations A * x = b where A is self, b is the argument, and x is the successful result.

fn solve_t<S: Data<Elem = A>>(&self, b: &ArrayBase<S, Ix1>) -> Result<Array1<A>>

Solves a system of linear equations A^T * x = b where A is self, b is the argument, and x is the successful result.

fn solve_t_into<S: DataMut<Elem = A>>(
    &self,
    b: ArrayBase<S, Ix1>
) -> Result<ArrayBase<S, Ix1>>

Solves a system of linear equations A^T * x = b where A is self, b is the argument, and x is the successful result.

fn solve_h<S: Data<Elem = A>>(&self, b: &ArrayBase<S, Ix1>) -> Result<Array1<A>>

Solves a system of linear equations A^H * x = b where A is self, b is the argument, and x is the successful result.

fn solve_h_into<S: DataMut<Elem = A>>(
    &self,
    b: ArrayBase<S, Ix1>
) -> Result<ArrayBase<S, Ix1>>

Solves a system of linear equations A^H * x = b where A is self, b is the argument, and x is the successful result.