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sprs, sparse matrices for Rust
.. image:: https://travis-ci.org/vbarrielle/sprs.svg?branch=master :target: https://travis-ci.org/vbarrielle/sprs
sprs implements some sparse matrix data structures and linear algebra algorithms.
WARNING: this library is still in development, its API is not stable yet.
Features
Structures ..........
- CSR/CSC matrix
- Sparse vector
Operations ..........
- sparse matrix / sparse vector product
- sparse matrix / sparse matrix product
- sparse matrix / sparse matrix addition, subtraction
- sparse vector / sparse vector addition, subtraction, dot product
- sparse/dense matrix operations
Algorithms ..........
- Outer iterator on compressed sparse matrices
- sparse vector iteration
- sparse vectors joint non zero iterations
- simple sparse Cholesky decomposition
- sparse triangular solves with dense right-hand side
Examples
Matrix construction
.. code-block:: rust
use sprs::{CsMat, CsMatOwned, CsVec}; let eye : CsMatOwned = CsMat::eye(sprs::CSR, 3); let a = CsMat::new_owned(sprs::CSC, 3, 3, vec![0, 2, 4, 5], vec![0, 1, 0, 2, 2], vec![1., 2., 3., 4., 5.]).unwrap();
Matrix vector multiplication
.. code-block:: rust
use sprs::{CsMat, CsVec}; let eye = CsMat::eye(sprs::CSR, 5); let x = CsVec::new_owned(5, vec![0, 2, 4], vec![1., 2., 3.]).unwrap(); let y = &eye * &x; assert_eq!(x, y);
Matrix matrix multiplication, addition
.. code-block:: rust
use sprs::{CsMat, CsVec}; let eye = CsMat::eye(sprs::CSR, 3); let a = CsMat::new_owned(sprs::CSC, 3, 3, vec![0, 2, 4, 5], vec![0, 1, 0, 2, 2], vec![1., 2., 3., 4., 5.]).unwrap(); let b = &eye * &a; assert_eq!(a, b.to_csr());
Documentation
https://vbarrielle.github.io/sprs/doc/sprs/
Changelog
- 0.4.0-alpha.1:
- depend on ndarray for dense matrices breaking change
- iterators return reference where possible breaking change
- remove unnecessary copy bounds
- constructors to build sparse matrices from dense matrices
- forward some LdlSymbolic methods in LdlNumeric
- 0.3.3
- switch to dual MIT/Apache-2.0 license
- 0.3.2
- triplet matrix format for easier initialization
- 0.3.1
- trait to abstract over sparse vectors
- 0.3.0
- LDLT decomposition with support for permutations
- 0.2.6
- lifetime issue fixed (revealed by rust 1.4)
- 0.2.5
- sparse triangular / sparse rhs solvers
- 0.2.4
- sparse triangular / dense rhs solvers
- avoid "*" in dependencies
- 0.2.3
- initial support for sparse/dense matrix addition
- 0.2.2
- initial support for sparse/dense matrix multiplication
- 0.2.1
- remove type aliases from impl blocks (doc issue)
- 0.2.0
- matrix multiplication, addition
- block matrix constructors (vstack, hstack, bmat)
- trait to abstract over sparse matrices
- 0.1.0
- first release on crates.io
License
Licensed under either of
- Apache License, Version 2.0, (./LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (./LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Contribution ............
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.