Struct sprs_ldl::LdlNumeric

pub struct LdlNumeric<N> { /* fields omitted */ }

Structure to hold a numeric LDLT decomposition

Methods

impl<N> LdlNumeric<N>

fn new<IpS, IS, DS>(mat: &CsMat<N, IpS, IS, DS>) -> Self where N: Copy + Num + PartialOrd, IpS: Deref<Target=[usize]>, IS: Deref<Target=[usize]>, DS: Deref<Target=[N]>

Compute the numeric LDLT decomposition of the given matrix.

Panics

• if mat is not symmetric

fn new_perm<IpS, IS, DS>(mat: &CsMat<N, IpS, IS, DS>, perm: PermOwned) -> Self where N: Copy + Num + PartialOrd, IpS: Deref<Target=[usize]>, IS: Deref<Target=[usize]>, DS: Deref<Target=[N]>

Compute the numeric decomposition L D L^T = P^T A P where P is a permutation matrix.

Using a good permutation matrix can reduce the non-zero count in L, thus making the decomposition and the solves faster.

Panics

• if mat is not symmetric

fn update<IpS, IS, DS>(&mut self, mat: &CsMat<N, IpS, IS, DS>) where N: Copy + Num + PartialOrd, IpS: Deref<Target=[usize]>, IS: Deref<Target=[usize]>, DS: Deref<Target=[N]>

Update the decomposition with the given matrix. The matrix must have the same non-zero pattern as the original matrix, otherwise the result is unspecified.

fn solve<'a, V>(&self, rhs: &V) -> Vec<N> where N: 'a + Copy + Num, V: Deref<Target=[N]>

Solve the system A x = rhs

fn problem_size(&self) -> usize

The size of the linear system associated with this decomposition

fn nnz(&self) -> usize

The number of non-zero entries in L

Trait Implementations

impl<N: Debug> Debug for LdlNumeric<N>

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.