adv_linalg_lib

Crates.ioadv_linalg_lib
lib.rsadv_linalg_lib
version0.1.1
sourcesrc
created_at2023-08-29 12:22:33.211675
updated_at2023-09-03 06:43:38.858204
descriptionCore library for Adv_LinAlg procedral macros
homepage
repositoryhttps://github.com/Adv-LinAlg/adv_linalg_lib
max_upload_size
id958018
size46,444
Eric Ovenden (the-mcmaster)

documentation

https://docs.rs/adv_linalg_lib

README

Adv_LinAlg_Lib

⚠️ This library is currently under construction! Design is subject to change! ⚠️

The backbone of the linear algebra framework adv_linalg.

Usage

Cargo.toml

adv_linalg_lib = "0.1"

![no_std] Compliance Feature

If you need a version of this library that uses only the core crate, simply import this library as such:

Cargo.toml

adv_linalg_lib = { version = "0.1", features=["no_std"] }

Do note that this drastically simplifies the library structure and that the dependencies of this crate do not neccessarily use #![no_std].

Basic Types

Simply, this is a linear algebra library. It features two main types:

  • Vector<T>
  • Matrix<T>

These are simple wrappers around the standard library's Vec<T> type.

Most developers will often only need these two types.

However, for users requiring an optimized run-time performance, this library features two options:

  • use the framework adv_linalg alongside this library for automatic compile-time optimizations (recommended)
  • manually use advanced types

In fact, adv_linalg simply uses adv_linalg_lib as as a "ghost" type-system.

To learn more, read about advanced types

Advanced Types

For developers just wanting a simple tool, just know that this section is optional.

Every type in this crate is either a "Vector" or a "Matrix". All types include this base in their name.

The type's functionality is described by it's both optional:

  • prefix (description of mutability)
  • and/or suffix (special functionality).

Prefix

There is only one prefix: Mut.

Mut

This states explicitly to allow interior mutability.

Click here to learn about "interior mutability"

To learn about interior mutability, first understand "interior immutability".

Interior immutability means that the interior of the type is unchanging. This forces the following rule: if the data mutated, then it is a different vector.

In other words, to change the data, an allocation is needed.

Below is example code for interior mutability from regular mutability:

fn main() {
    // MUTABILITY TYPES

    // initial value
    let mut std_vec = vec![1, 2, 3];
    
    // Example of mutability that follows `interior 
    // immutability`.
    // We essentially "overwrite" the variable.
    std_vec = std_vec.iter().map(|val| val + 1).collect();

    // Example of only 'interior mutability'.
    // Imagine the next three lines as a single operation.
    // We are reusing the already allocated memory.
    {
        std_vec[0] = std_vec[0] + 1;
        std_vec[1] = std_vec[1] + 1;
        std_vec[2] = std_vec[2] + 1;
    }

    // Exterior mutability "overwrote the varaiable", utilizing an entire new heap allocation in the process.
    // Interior mutability "overwrote the memory", reusuing the already allocated memory.
}

By being selective when to use interior mutability or not can be useful to reducing time spent allocating memory.

Suffix

There are currently three suffixes:

  1. Slice
  2. Simd (planned/nightly)
  3. Gpu (planned)

Slice

A subsection view of an existing vector. This is simply a slice of a Vec under-the-hood.

Example

use adv_linalg_lib::vector;
use adv_linalg_lib::vectors::{Vector, VectorSlice};

fn main() {
    let vector: Vector<u32> = vector![1, 2, 3];

    let vector_slice: VectorSlice<'_, u32> = vector.as_slice(1..vector.len());

    assert_eq!(
        vector_slice.to_vector(), vector![2, 3]
    )
}

Simd

⚠️Design is still under-construction and is nightly.⚠️

This feature is still in the design process. The produced design will use core::simd::Simd. Therefore, when the design is implemented, this require to build with nightly until Rust stabilizes core::simd::Simd.

Gpu

⚠️Design is still under-construction.⚠️

This feature is still in the design process. The produced design will support OpenCL.

Some Advanced Type Examples:

  • MutVector
  • MatrixSlice
  • MutVectorSimd

License

This software is licensed ultimately described under the terms of the SPDX 2.1 License Expression "MIT OR Apache-2.0".

see files 'LICENSE.md', 'LICENSE-MIT', and 'LICENSE-APACHE' in the root of this crate for more details

Commit count: 2

cargo fmt