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.