rsparse

A Rust library for solving sparse linear systems using direct methods.

https://github.com/rlado/rsparse

Science Score: 57.0%

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Low similarity (7.0%) to scientific vocabulary

Keywords

linear-algebra math matrix rust sparse-matrices

Last synced: 4 months ago · JSON representation ·

Repository

A Rust library for solving sparse linear systems using direct methods.

Basic Info

Host: GitHub
Owner: RLado
License: mit
Language: Rust
Default Branch: master
Homepage:
Size: 968 KB

Statistics

Stars: 17
Watchers: 1
Forks: 3
Open Issues: 1
Releases: 1

Topics

linear-algebra math matrix rust sparse-matrices

Created about 3 years ago · Last pushed 9 months ago

Metadata Files

Readme License Citation

rsparse

A Rust library for solving sparse linear systems using direct methods.

GitHub Workflow Status

Data structures

CSC matrix (Sprs)
Triplet matrix (Trpl)

Features

Convert from dense [Vec<T>] or Vec<Vec<T>> matrix to CSC sparse matrix Sprs
Convert from sparse to dense Vec<Vec<T>>
Convert from a triplet format matrix Trpl to CSC Sprs
Sparse matrix addition [C=A+B]
Sparse matrix multiplication [C=A*B]
Transpose sparse matrices
Solve sparse linear systems

Solvers

lsolve: Solve a lower triangular system. Solves Lx=b where x and b are dense.
ltsolve: Solve L’x=b where x and b are dense.
usolve: Solve an upper triangular system. Solves Ux=b where x and b are dense
utsolve: Solve U’x=b where x and b are dense
cholsol: A\b solver using Cholesky factorization. Where A is a defined positive Sprs matrix and b is a dense vector
lusol: A\b solver using LU factorization. Where A is a square Sprs matrix and b is a dense vector
qrsol: A\b solver using QR factorization. Where A is a rectangular Sprs matrix and b is a dense vector

Examples

Basic matrix operations

```rust use rsparse;

fn main() { // Create a CSC sparse matrix A let a = rsparse::data::Sprs{ // Maximum number of entries nzmax: 5, // number of rows m: 3, // number of columns n: 3, // Values x: vec![1., 9., 9., 2., 9.], // Indices i: vec![1, 2, 2, 0, 2], // Pointers p: vec![0, 2, 3, 5] };

// Import the same matrix from a dense structure
let mut a2 = rsparse::data::Sprs::new_from_vec(
    &[
        vec![0., 0., 2.],
        vec![1., 0., 0.],
        vec![9., 9., 9.]
    ]
);

// Check if they are the same
assert_eq!(a.nzmax, a2.nzmax);
assert_eq!(a.m,a2.m);
assert_eq!(a.n,a2.n);
assert_eq!(a.x,a2.x);
assert_eq!(a.i,a2.i);
assert_eq!(a.p,a2.p);

// Transform A to dense and print result
println!("\nA");
print_matrix(&a.to_dense());

// Transpose A
let at = rsparse::transpose(&a);
// Transform to dense and print result
println!("\nAt");
print_matrix(&at.to_dense());

// B = A + A'
let b = &a + &at;
// Transform to dense and print result
println!("\nB");
print_matrix(&b.to_dense());

// C = A * B
let c = &a * &b;
// Transform to dense and print result
println!("\nC");
print_matrix(&c.to_dense());

}

fn print_matrix(vec: &[Vec]) { for row in vec { println!("{:?}", row); } } ```

Output:

``` A 0 0 2 1 0 0 9 9 9

At 0 1 9 0 0 9 2 0 9

B 0 1 11 1 0 9 11 9 18

C 22 18 36 0 1 11 108 90 342 ```

Solve a linear system

```rust use rsparse;

fn main() { // Arbitrary A matrix (dense) let a = [ vec![8.2541e-01, 9.5622e-01, 4.6698e-01, 8.4410e-03, 6.3193e-01, 7.5741e-01, 5.3584e-01, 3.9448e-01], vec![7.4808e-01, 2.0403e-01, 9.4649e-01, 2.5086e-01, 2.6931e-01, 5.5866e-01, 3.1827e-01, 2.9819e-02], vec![6.3980e-01, 9.1615e-01, 8.5515e-01, 9.5323e-01, 7.8323e-01, 8.6003e-01, 7.5761e-01, 8.9255e-01], vec![1.8726e-01, 8.9339e-01, 9.9796e-01, 5.0506e-01, 6.1439e-01, 4.3617e-01, 7.3369e-01, 1.5565e-01], vec![2.8015e-02, 6.3404e-01, 8.4771e-01, 8.6419e-01, 2.7555e-01, 3.5909e-01, 7.6644e-01, 8.9905e-02], vec![9.1817e-01, 8.6629e-01, 5.9917e-01, 1.9346e-01, 2.1960e-01, 1.8676e-01, 8.7020e-01, 2.7891e-01], vec![3.1999e-01, 5.9988e-01, 8.7402e-01, 5.5710e-01, 2.4707e-01, 7.5652e-01, 8.3682e-01, 6.3145e-01], vec![9.3807e-01, 7.5985e-02, 7.8758e-01, 3.6881e-01, 4.4553e-01, 5.5005e-02, 3.3908e-01, 3.4573e-01], ];

// Convert A to sparse
let mut a_sparse = rsparse::data::Sprs::new();
a_sparse.from_vec(&a);

// Generate arbitrary b vector
let mut b = [
    0.4377,
    0.7328,
    0.1227,
    0.1817,
    0.2634,
    0.6876,
    0.8711,
    0.4201
];

// Known solution:
/*
     0.264678,
    -1.228118,
    -0.035452,
    -0.676711,
    -0.066194,
     0.761495,
     1.852384,
    -0.282992
*/

// A*x=b -> solve for x -> place x in b
rsparse::lusol(&a_sparse, &mut b, 1, 1e-6);
println!("\nX");
println!("{:?}", &b);

} ```

Output:

X [0.2646806068156303, -1.2280777288645675, -0.035491404094236435, -0.6766064748053932, -0.06619898266432682, 0.7615102544801993, 1.8522970972589123, -0.2830302118359591]

Documentation

Documentation is available at docs.rs.

Sources

Davis, T. (2006). Direct Methods for Sparse Linear Systems. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9780898718881
CSparse: A Concise Sparse Matrix Package in C

Owner

Name: Ricard Lado
Login: RLado
Kind: user
Location: Barcelona
Company: Universitat Ramon Llull (IQS School of Engineering)

Website: lado.one
Repositories: 24
Profile: https://github.com/RLado

PhD Candidate. I love Linux and all things open source.

Citation (CITATION.cff)

cff-version: 1.2.0
title: rsparse
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - family-names: Lado-Roigé
    given-names: Ricard
    orcid: 'https://orcid.org/0000-0002-6421-7351'
repository-code: 'https://github.com/RLado/rsparse'
url: 'https://crates.io/crates/rsparse'
abstract: >-
  A Rust library for solving sparse linear systems using
  direct methods.
keywords:
  - sparse-matrices
  - linear-algebra
  - math
  - rust
license: MIT
version: 1.2.1
date-released: '2025-03-29'

GitHub Events

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Watch event: 3
Delete event: 1
Issue comment event: 9
Push event: 8
Pull request review event: 2
Pull request event: 6
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Last Year

Issues event: 3
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Fork event: 1
Create event: 2

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Last synced: over 2 years ago

All Time

Total Commits: 54
Total Committers: 1
Avg Commits per committer: 54.0
Development Distribution Score (DDS): 0.0

Past Year

Commits: 54
Committers: 1
Avg Commits per committer: 54.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Ricard Lado	r**o@h**m	54

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 6
Total pull requests: 10
Average time to close issues: 6 days
Average time to close pull requests: about 23 hours
Total issue authors: 5
Total pull request authors: 3
Average comments per issue: 1.17
Average comments per pull request: 1.2
Merged pull requests: 10
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 2
Pull requests: 6
Average time to close issues: N/A
Average time to close pull requests: 1 day
Issue authors: 2
Pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 1.0
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

MothNik (3)
RLado (1)
cheginit (1)
Voidheart88 (1)
Makogan (1)

Pull Request Authors

RLado (5)
Masterchef365 (4)
MothNik (1)

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question (1)

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Packages

Total packages: 1
Total downloads:
- cargo 24,900 total

Total dependent packages: 2
Total dependent repositories: 1
Total versions: 18
Total maintainers: 1

crates.io: rsparse

A Rust library for solving sparse linear systems using direct methods.

Documentation: https://docs.rs/rsparse/
License: MIT
Latest release: 1.2.1
published 9 months ago

Versions: 18
Dependent Packages: 2
Dependent Repositories: 1
Downloads: 24,900 Total

Rankings

Dependent packages count: 12.2%

Dependent repos count: 16.7%

Average: 28.2%

Stargazers count: 32.7%

Downloads: 38.9%

Forks count: 40.7%

Maintainers (1)

RLado

Last synced: 5 months ago

Dependencies

.github/workflows/rust.yml actions

actions/checkout v3 composite

Cargo.toml cargo

rsparse

Science Score: 57.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

rsparse

Data structures

Features

Solvers

Examples

Basic matrix operations

Solve a linear system

Documentation

Sources

Owner

Citation (CITATION.cff)

GitHub Events

Total

Last Year

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Past Year

Top Committers

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crates.io: rsparse

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