daniel-vainsencher/sprs

sparse linear algebra library for rust

sprs, sparse matrices for Rust

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

use sprs::{CsMat, CsMatOwned, CsVec};
let eye : CsMatOwned<f64> = 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

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

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/

License

MIT license. See LICENSE.txt