pub fn new_perm(mat: CsMatViewI<N, I>, perm: PermOwnedI<I>) -> Self
    where N: Copy + Num + PartialOrd,
    {
        let symbolic = LdlSymbolic::new_perm(mat.view(), perm);
        symbolic.factor(mat)
    }
/// 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
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.
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 .
pub fn new_perm(mat: CsMatViewI<N, I>, perm: PermOwnedI<I>) -> Self
    where N: Copy + Num + PartialOrd,
    {
        let symbolic = LdlSymbolic::new_perm(mat.view(), perm);
        symbolic.factor(mat)
    }
pub fn new_perm ( mat : CsMatViewI < N , I > , perm : PermOwnedI < I > ) -> Self where N : Copy + Num + PartialOrd , { let symbolic = LdlSymbolic :: new_perm ( mat . view ( ) , perm ) ; symbolic . factor ( mat ) }
Compute the numeric decomposition L D L^T = P^T A P
where P is a permutation matrix.
Compute the numeric decomposition L D L^T = P^T A P where P is a permutation matrix .
mat
CsMatViewI<N, I>
perm
PermOwnedI<I>
mat
CsMatViewI<N, I>
perm
PermOwnedI<I>
panics
if mat is not symmetric
if mat is not symmetric