sprs, sparse matrices for Rust
sprs implements some sparse matrix data structures and linear algebra algorithms in pure Rust.
The API is a work in progress, and feedback on its rough edges is highly appreciated :)
Features
Structures
- CSR/CSC matrix
- triplet 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 (requires opting into an LGPL license)
- sparse triangular solves with dense right-hand side
Examples
Matrix construction
use sprs::{CsMat, CsMatOwned, CsVec};
let eye : CsMatOwned<f64> = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
vec![0, 2, 4, 5],
vec![0, 1, 0, 2, 2],
vec![1., 2., 3., 4., 5.]);
Matrix vector multiplication
use sprs::{CsMat, CsVec};
let eye = CsMat::eye(5);
let x = CsVec::new(5, vec![0, 2, 4], vec![1., 2., 3.]);
let y = &eye * &x;
assert_eq!(x, y);
Matrix matrix multiplication, addition
use sprs::{CsMat, CsVec};
let eye = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
vec![0, 2, 4, 5],
vec![0, 1, 0, 2, 2],
vec![1., 2., 3., 4., 5.]);
let b = &eye * &a;
assert_eq!(a, b.to_csr());
For a more complete example, be sure to check out the heat diffusion example.
Documentation
Documentation is available at docs.rs.
Changelog
See the changelog.
Minimum Supported Rust Version
The minimum supported Rust version currently is 1.64. Prior to a 1.0 version, bumping the MSRV will not be considered a breaking change, but breakage will be avoided on a best effort basis.
License
Licensed under either of
- Apache License, Version 2.0, (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or https://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.
Please see the contribution guidelines for additional information about contributing.