Lib.rs

• Define and evaluate any multivariable polynomial or equation at compile time.
• Handle any number of variables and function types (Pow, Sin, Exp, Ln, etc.) with a single abstraction that is always const-safe.
• Zero Dependencies and no_std, ensuring no heap allocations, no panics, and no external crates.
• Helps reduce boilerplate so you don't have to keep defining custom const fn for each equation.

Introduction

const_poly is a lightweight abstraction for evaluating multi-variable polynomials entirely at compile time. Instead of writing specialized const fn evaluators for every equation you need, const_poly abstracts all of this away using generic, compile-time constructs. The implementation can handle any number of variables, and is capable of evaluating any complex equation with high accuracy. This approach reduces boilerplate, so you can focus on the actual algorithms while writing math expressions in a natural, equation-like syntax:

use const_poly::VarFunction::*;
use const_poly::{Polynomial, const_poly};

//define f(x,y) = 2.5 * x² * y³
const POLY = Polynomial<2> = const_poly!([2.5, Pow(2), Pow(3)]);

//evaluate f(x,y) at (x,y) = (10.0, -5.0)
const RESULT: f64 = POLY_1.evaluate(&[10.0, -5.0]); // -31250.0

// Multi-term polynomial g(x,y,z)
const POLY_2: Polynomial<3> = const_poly!({
    [1.2, Pow(2), Pow(-1), Pow(0)],  // 1.2 * x² * y⁻¹ * z⁰
    [-0.8, Pow(3), Pow(1), Pow(-2)], // -0.8 * x³ * y¹ * z⁻²
    [2.5, Pow(-3), Pow(4), Pow(1)],  // 2.5 * x⁻³ * y⁴ * z¹
    [-1.1, Pow(0), Pow(-2), Pow(3)], // -1.1 * x⁰ * y⁻² * z³
    [0.9, Pow(1), Pow(2), Pow(-1)]   // 0.9 * x¹ * y² * z⁻¹
});

// (x,y,z) = (2.0,3.0,0.5)
const VARS: [f64; 3] = [2.0, 3.0, 0.5]; 
const RES: f64 = POLY_2.evaluate(&VARS); // -30.159027778

Every polynomial defined with const_poly is a fully constant object, meaning it can be safely passed, composed, or evaluated anywhere in the codebase in a const context. You can freely pass this object to other const fn, or embed it inside larger data structures. const_poly has zero dependencies and is written completely in a no_std environment.

Who is this for?

• This library is primarily meant to empower scientific computing and mathematical libraries in rust to perform all numerical approximations entirely at compile time or in const contexts.

• Embedded and no_std environments where heapless, panic-free code is essential.

• Metaprogramming and symbolic math tools that benefit from evaluating complex expressions entirely at compile time.

More code examples

1. Simple polynomial

//define f(x) = 3 * x²
const POLY: Polynomial<1> = const_poly!([3.0, Pow(2)]);

const RESULT: f64 = POLY.evaluate(&[4.0]); // 3 * (4^2) = 48.0

2. Trigonometric Functions

// define f(x, y) = 2.0 * Sin(x) * Cos(y)
const POLY: Polynomial<2> = const_poly!([2.0, Sin, Cos]);
const RESULT: f64 = POLY.evaluate(&[1.57079632679, 0.0]); // 2.0 * sin(π/2) * cos(0) = 2.0

3. Multi-Term Mixed Polynomial

const POLY: Polynomial<2> = const_poly!({
    [1.0, Pow(2), Pow(1)],   // 1.0 * x² * y
    [0.5, Sin, Cos],         // 0.5 * sin(x) * cos(y)
    [-2.0, Exp, Pow(-1)]     // -2.0 * e^(x) * y⁻¹
});

const RESULT: f64 = POLY.evaluate(&[1.0, 2.0]); // -0.2182818

4. Logarithmic and Root Operations

// f(x, y) = 1.5 * ln(x) * sqrt(y)
const POLY: Polynomial<2> = const_poly!([1.5, Ln, Sqrt]);
const RESULT: f64 = POLY.evaluate(&[2.0, 9.0]); // 3.119162312

5. Full Expression with Multiple Terms & Complex Functions

const POLY: Polynomial<3> = const_poly!({
    [2.0, Pow(2), Sin, Exp],       // 2x² * sin(y) * e^(z)
    [-1.5, Ln, Pow(-1), Cos],      // -1.5 * ln(x) * y⁻¹ * cos(z)
    [0.5, Sqrt, Tan, Pow(0)],      // 0.5 * sqrt(x) * tan(y)
    [1.0, Pow(1), Pow(1), Pow(1)]  // x * y * z
});

const VARS: [f64; 3] = [2.0, 0.5, 1.0];
const RESULT: f64 = POLY.evaluate(&VARS); // 10.688476972

Tutorials

Follow the full tutorial at TUTORIAL.md

Benchmarks

See BENCHMARKS.md

Contributions Guide

See CONTRIBUTIONS.md

LICENSE

const_poly is licensed under the MIT license.

Contact

[email protected]

If you use this library in your project, a shoutout or mention would be awesome!

TODO

• Add polynomial operations like add/subtract/multiply.
• String representation for the polynomial.
• Add more benchmarking.