rhai-ml

Crates.iorhai-ml
lib.rsrhai-ml
version0.1.2
sourcesrc
created_at2023-04-12 23:52:47.757809
updated_at2024-02-09 16:36:29.079119
descriptionMachine learning in the Rhai scripting language
homepagehttps://github.com/rhaiscript/rhai-ml
repositoryhttps://github.com/rhaiscript/rhai-ml
max_upload_size
id837579
size36,440
Chris McComb (cmccomb)

documentation

https://docs.rs/rhai-ml

README

tests Crates.io docs.rs

About rhai-ml

This crate provides some basic machine learning and artificial intelligence utilities for the Rhai scripting language. For a complete API reference, check the docs.

Install

To use the latest released version of rhai-ml, add this to your Cargo.toml:

rhai-ml = "0.1.2"

To use the bleeding edge instead, add this:

rhai-ml = { git = "https://github.com/cmccomb/rhai-ml" }

Usage

Using this crate is pretty simple! If you just want to evaluate a single line of Rhai, then you only need:

use rhai::FLOAT;
use rhai_ml::eval;
let result = eval::<FLOAT>("\
let xdata = [[1.0, 2.0], [2.0, 3.0], [3.0, 4.0]]; \
let ydata = [1.0, 2.0, 3.0]; \
let model = train(xdata, ydata, \"linear\"); \
let ypred = predict(xdata, model);
ypred[0]
").unwrap();

If you need to use rhai-ml as part of a persistent Rhai scripting engine, then do this instead:

use rhai::{Engine, packages::Package, FLOAT};
use rhai_ml::MLPackage;

// Create a new Rhai engine
let mut engine = Engine::new();

// Add the rhai-ml package to the new engine
engine.register_global_module(MLPackage::new().as_shared_module());

// Now run your code
let value = engine.eval::<FLOAT>("\
let xdata = [[1.0, 2.0], [2.0, 3.0], [3.0, 4.0]]; \
let ydata = [1.0, 2.0, 3.0]; \
let model = train(xdata, ydata, \"linear\"); \
let ypred = predict(xdata, model);
ypred[0]
").unwrap();

Features

Feature Default Description
metadata Disabled Enables exporting function metadata and is necessary for running doc-tests on Rhai examples.
Commit count: 8

cargo fmt