dual_autodiff Package

Welcome to the documentation for version 1.1 of the Dual Autodiff package.

Recent Updates - Version v1.1.0

• Enhanced Mathematical Functions: All mathematical functions such as sin, cos, tan, exp, log, sqrt, and more are now fully compatible with numpy arrays of dual numbers .

• Advanced Auto-differentiation Functions: Extended auto_diff to be fully compatible with numpy arrays, enabling automatic differentiation over arrays of dual numbers.

• Multi-Function Differentiation: Introduced the multi_auto_diff function, allowing users to evaluate multiple functions and their derivatives at once, and even over a range (array) of points.

• Advanced Error Handling and Testing: Improved error handling mechanisms and added comprehensive test coverage to ensure robustness and reliability.

Contents:

• Overview
  • Why the Dual Autodiff Package?
  • What are Dual Numbers
  • Why Are Dual Numbers Useful?
  • Package Features
• User Guide - Installation
  • Method 1: Build Package
  • Method 2: Use Pre-Built Wheels (Cython)
  • Usage
• Optional package features
  • Testing
  • Tutorial Notebook
• Package Examples
  • Initialise Dual Numbers
  • Basic Arithmetic Operations
  • Basic Arithmetic Operations with numpy arrays
  • Basic Comparison Operations
  • Mathematical Functions
  • Mathematical Functions in ‘numpy’ array
  • Automatic Differentiation
  • Tutorial Notebook
• Developer Notes:
  • Contributing
  • License
• API Reference
  • dual_autodiff.dual
  • dual_autodiff.math_functions