Function sprs::linalg::trisolve::lsolve_csc_sparse_rhs

pub fn lsolve_csc_sparse_rhs<N, I, Iptr, V>(
    lower_tri_mat: CsMatViewI<'_, N, I, Iptr>, 
    rhs: CsVecViewI<'_, N, I>, 
    dstack: &mut DStack<StackVal<usize>>, 
    x_workspace: V, 
    visited: &mut [bool]
) -> Result<(), LinalgError> where
    N: Clone + Num + SubAssign,
    &'r N: Mul<&'r N, Output = N>,
    &'r N: Div<&'r N, Output = N>,
    V: DenseVectorMut + DenseVector<Scalar = N>,
    I: SpIndex,
    Iptr: SpIndex, 

Sparse triangular CSC / sparse vector solve

lower_tri_mat is a sparse lower triangular matrix of shape (n, n) rhs is a sparse vector of size n dstack is a double stack with capacity 2*n x_workspace is a workspace vector with length equal to the number of rows of lower_tri_mat. Its input values can be anything. visited is a workspace vector of same size as upper_tri_mat.indptr(), and should be all false.

On succesful execution, dstack will hold the non-zero pattern in its right stack, and x_workspace will contain the solve values at the indices contained in right stack. The non-zero pattern indices are not guaranteed to be sorted (they are sorted for each connected component of the matrix’s graph).

Panics

• if dstack.capacity() is too small
• if dstack is not empty
• if w_workspace is not of length n