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 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

.. code-block:: rust

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

.. code-block:: rust

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

.. code-block:: rust

use sprs::{CsMat, CsVec}; let eye = CsMat::eye(3); let a = CsMat::newcsc((3, 3), vec![0, 2, 4, 5], vec![0, 1, 0, 2, 2], vec![1., 2., 3., 4., 5.]); let b = &eye * &a; asserteq!(a, b.to_csr());

For a more comple example, be sure to check out the examples/ folder.

Documentation

Documentation is available at docs.rs_.

.. _docs.rs: https://docs.rs/sprs

Changelog

• 0.4.0:
  • panic for contract violations, use errors only for recoverable problems breaking change
  • depend on latest ndarray version: 0.6 braking change
  • refactor API to present shorter import paths breaking change
  • expose sparse matrix / dense vector product via Mul.
  • add an example of building and solving a sparse linear system
• O.4.0-alpha.4 version, most changes are breaking changes:
  • move cholesky factorization into its own crate
  • add to_dense() method for sparse matrices
  • rename borrowed() into view()
  • outer_iterator() no longer returns the index of the dimension we're iterating. The old behavior can be obtained by chaining a call to enumerate().
  • eye() returns a csr matrix by default, a csc matrix can be obtained using eye_csc().
  • rename new_borrowed() into new_view().
  • rename new_raw() into new_view_raw().
  • rename new_owned() into new() or new_csc() depending on the desired ordering, and have the ownning constructors panic on bad input.
  • constructors now take a tuple for shape information
• 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.

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.