Struct ndarray_linalg::solve::LUFactorized

[+] Show declaration

pub struct LUFactorized<S: Data> {
    pub a: ArrayBase<S, Ix2>,
    pub ipiv: Pivot,
}

[−] Expand description

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

Fields

a: ArrayBase<S, Ix2>

[−] Expand description

The factors L and U; the unit diagonal elements of L are not stored.

ipiv: Pivot

[−] Expand description

The pivot indices that define the permutation matrix P.

Trait Implementations

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

[+] Show hidden undocumented items

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>, [+]

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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>, [+]

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type Output = Array2<A>

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>, [+]

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type Output = ArrayBase<S, Ix2>

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>, [+]

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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>, [+]

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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>, [+]

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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.