ndarray-free safe Rust wrapper for LAPACK FFI
As the property of $A$, several types of triangular factorization are used:
- LU-decomposition for general matrix
- $PA = LU$, where $L$ is lower matrix, $U$ is upper matrix, and $P$ is permutation matrix
- Bunch-Kaufman diagonal pivoting method for nonpositive-definite Hermitian matrix
- $A = U D U^\dagger$, where $U$ is upper matrix, $D$ is Hermitian and block diagonal with 1-by-1 and 2-by-2 diagonal blocks.
|matrix type||Triangler factorization (TRF)||Solve (TRS)||Inverse matrix (TRI)||Reciprocal condition number (CON)|
|Symmetric (SY) / Hermitian (HE)||bk||solveh||invh||-|
Solve eigenvalue problem for a matrix $A$
$$ Av_i = \lambda_i v_i $$
or generalized eigenvalue problem
$$ Av_i = \lambda_i B v_i $$
|matrix type||Eigenvalue (EV)||Generalized Eigenvalue Problem (EG)|
|Symmetric (SY) / Hermitian (HE)||eigh||eigh_generalized|
Represents the LU factorization of a tridiagonal matrix
A = P*L*U.
Result of LeastSquares
Result of SVD
Represents a tridiagonal matrix as 3 one-dimensional vectors.
Upper/Lower specification for seveal usages
Specifies how many of the columns of U and rows of Vᵀ are computed and returned.
*geev for general matrices
Trait for primitive types which implements LAPACK subroutines