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 (requires opting into an LGPL license)
• 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::newowned(5, vec![0, 2, 4], vec![1., 2., 3.]).unwrap(); let y = &eye * &x; asserteq!(x, y);

Matrix matrix multiplication, addition

.. code-block:: rust

use sprs::{CsMat, CsVec}; let eye = CsMat::eye(sprs::CSR, 3); let a = CsMat::newowned(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; asserteq!(a, b.to_csr());

Documentation

https://vbarrielle.github.io/sprs/doc/sprs/

Changelog

• 0.4.0-alpha.3:
  • rename at family of functions into get, consistent with the naming scheme in standard library. breaking change
  • move cholesky factorization behind the "lgpl" feature flag rbeaking change
  • per-nnz-element function application (map, map_inplace).
  • binary operations operating on matching non-zero elements (csvec_binop, csmat_binop).
  • introduce nnz_index to retrieve an index of an element allowing for later constant time access.
• 0.4.0-alpha.2:
  • functions in the at family will return references breaking change
  • simpler arguments for at_outer_inner breaking change
  • mutable view types
• 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.

Some parts of the library require opting into the LGPL license. Opting into the LGPL-licensed features can be done by specifying features = ["lgpl"] in Cargo.toml.

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.