Crate dual_num

Dual Numbers

Fully-featured Dual Number implementation with features for automatic differentiation of multivariate vectorial functions into gradients.

Usage

extern crate dual_num;

use dual_num::{Dual, Float, differentiate};

fn main() {
    // find partial derivative at x=4.0
    println!("{:.5}", differentiate(4.0f64, |x| {
        x.sqrt() + Dual::from_real(1.0)
    })); // 0.25000
}

Previous Work

• https://github.com/FreeFull/dual_numbers
• https://github.com/ibab/rust-ad
• https://github.com/tesch1/cxxduals

Modules

linalg

Structs

Dual

Dual Number structure

Traits

Float

Generic trait for floating point numbers

FloatConst

Num

The base trait for numeric types, covering 0 and 1 values, comparisons, basic numeric operations, and string conversion.

One

Defines a multiplicative identity element for Self.

Scalar

The basic scalar type for all structures of nalgebra.

Zero

Defines an additive identity element for Self.

Functions

differentiate

Evaluates the function using dual numbers to get the partial derivative at the input point

partials

Computes the state and partials of the provided function.

partials_t

Computes the state and the partials matrix of the provided function with a preliminary time parameter.