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::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 comple example, be sure to check out the examples/
folder.
Documentation
Documentation is available at docs.rs_.
.. _docs.rs: https://docs.rs/sprs
Changelog
- 0.4.1:
- add
insert()
method to insert an element inside an owned csmat - add
outer_iterator_mut()
method to enable changing the non-zero values of a sparse matrix while keeping its structure constant. - remove unsafe usage in the library
- add
- 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()
intoview()
outer_iterator()
no longer returns the index of the dimension we're iterating. The old behavior can be obtained by chaining a call toenumerate()
.eye()
returns a csr matrix by default, a csc matrix can be obtained usingeye_csc()
.- rename
new_borrowed()
intonew_view()
. - rename
new_raw()
intonew_view_raw()
. - rename
new_owned()
intonew()
ornew_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 intoget
, 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.
- rename
- 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
- functions in the
- 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.