2 releases

0.1.1 Jun 7, 2024
0.1.0 Jun 7, 2024

#229 in Machine learning

MIT license

13KB
264 lines

Algebrust

Algebrust is a high-performance linear algebra library for Rust, tailored for efficient mathematical operations on matrices and vectors. Leveraging the safety and expressiveness of Rust, Algebrust provides a reliable toolkit for numerical computing tasks in fields such as machine learning, scientific computing, and computer graphics.

Features

  • Vector addition, subtraction, dot product, scalar multiplication, magnitude, normalization, and cross product.
  • Matrix addition, subtraction, multiplication, scalar multiplication, transpose, LU decomposition, determinant calculation, and inversion.

Usage

To use Algebrust in your project, add it as a dependency in your Cargo.toml file. You can do this manually or by using the cargo add command.

Using cargo add

cargo add algebrust

Manually Editing Cargo.toml

Add the following line to your Cargo.toml under [dependencies]:

[dependencies]
algebrust = "0.1.0"

Usage

Here are some examples to get you started:

Vectors

use algebrust::AlgebrustVector;

// Creating vectors
let v1 = AlgebrustVector::new(&[1.0, 2.0, 3.0]);
let v2 = AlgebrustVector::new_rand(3, 0.0, 10.0);
let v3 = AlgebrustVector::new_zeros(3);

// Vector operations
let v4 = v1.addition(&v2);
let v5 = v1.subtraction(&v2);
let dot = v1.dot_product(&v2);
let cross = v1.cross_product(&v2);
let scalar_mult = v1.scalar_multiplication(2.0);
let magnitude = v1.magnitude();
let normalized = v1.normalization();

Matrices

use algebrust::AlgebrustMatrix;

// Creating matrices
let m1 = AlgebrustMatrix::new(&[
    &[1.0, 2.0],
    &[3.0, 4.0]
]);
let m2 = AlgebrustMatrix::new_rand((2, 2), 0.0, 10.0);
let m3 = AlgebrustMatrix::new_zeros((2, 2));
let m4 = AlgebrustMatrix::new_identitiy(2);

// Matrix operations
let m5 = m1.addition(&m2);
let m6 = m1.subtraction(&m2);
let m7 = m1.multiplication(&m2);
let scalar_mult = m1.scalar_multiplication(2.0);
let transpose = m1.transpose();

// LU decomposition and matrix inversion
let (l, u) = m1.lu_decomposition();
let inverse = m1.inverse();
let determinant = m1.determinant();

Testing

To run tests, use the following command:

cargo test

Contributing

Contributions are welcome! Please fork the repository and submit pull requests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Dependencies

~315KB