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A comprehensive collection of matrix data structures, linear solvers, least squares methods,
eigenvalue, and singular value decompositions.
Forked from: https://github.com/fommil/matrix-toolkits-java
and added support for eigenvalue computation of general matrices
Unstructured sparse matrices and vectors with iterative solvers and
preconditioners. The classes and interfaces can be grouped as follows:
- General sparse matrices
- CompRowMatrix -
Compressed row storage. Generally the best sparse matrix if the non-zero
structure is known.
- CompColMatrix -
Compressed column storage.
- CompDiagMatrix -
Compressed diagonal storage.
- FlexCompRowMatrix -
Flexible compressed row storage. Stores each row as a growable sparse
vector.
- FlexCompColMatrix -
Flexible compressed column storage. Stores each column as a growable sparse
vector.
- SparseVector -
Growable sparse vector.
- Iterative solvers
- BiCG -
BiConjugate gradients.
- BiCGstab -
BiConjugate gradients stabilized.
- CG -
Conjugate gradients.
- CGS -
Conjugate gradients squared.
- Chebyshev -
The Chebyshev iteration for symmetrical, positive definite matrices.
- GMRES -
Generalized minimal residual using restart.
- IR -
Iterative refinement (Richardson's method).
- QMR -
Quasi-minimal residual.
- Preconditioners