sprs 0.4.0-alpha.3

A sparse matrix library
Documentation

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::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.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

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.