Numeric Rust

General-purpose N-dimensional matrix class for Rust. It links to OpenBLAS and LAPACK to make tensor operations fast (such as matrix multiplications and linear solvers). It utilizes Rust's move semantics as much as possible to avoid unnecessary copies.

Documentation

http://numeric.rs/doc/numeric/index.html

Features

Some of the completed and planned features:

[x] Element-wise addition, subtraction, multiplication, division
[x] Matrix multiplication and scalar product
[x] Indexing
[x] Slicing
[x] Generic (anything from Tensor<bool> to Tensor<f64>)
[x] Mathematical functions
[x] Linear solver
[x] Basic random number generation
[x] Creation macro
[x] Updating slices
[x] Saving/loading HDF5
[x] Strided slices
[ ] Broadcasted axes
[ ] Matrix inverse and SVD

Recent progress is summarized in CHANGELOG.md.

Example

```rust

[macro_use(tensor)]

extern crate numeric;

use numeric::Tensor;

fn main() { let a: Tensor = Tensor::range(6).reshape(&[2, 3]); let b = tensor![7.0, 3.0, 2.0; -3.0, 2.0, -5.0]; let c = tensor![7.0, 3.0, 2.0];

let d = &a + &b;         // a copy is made
println!("d = {}", d);

let e = a.dot(&c);       // matrix multiplication (returns a new tensor)
println!("e = {}", e);

let f = a + &b;          // a is moved (no new memory is allocated)
println!("f = {}", f);

// Higher-dimensional
let g: Tensor<f64> = Tensor::ones(&[2, 3, 4, 5]);
println!("g = {}", g);

} ```

Output:

d = 7 4 4 0 6 0 [Tensor<f64> of shape 2x3] e = 7 43 [Tensor<f64> of shape 2] f = 7 4 4 0 6 0 [Tensor<f64> of shape 2x3] g = ... [Tensor<f64> of shape 2x3x4x5]

Contribute

We love pull requests and there are tons of things to work on for this project. Don't hesitate to ask if you want suggestions for contributions (big or small). Add your name to the CONTRIBUTORS.md file as part of your PR, no matter how small it may seem.

Acknowledgements

Numeric Rust is primarily inspired by Numpy and borrows heavily from that project. Even the name is a play on Numeric Python. Another source of some inspiration is Torch7.