rsr45-dual-autodiff-x 0.1.17

A package for dual number-based automatic differentiation

rsr45-dual-autodiff-x

rsr45-dual-autodiff-x is optimised using Cython for improved performance.

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Features

• Dual Number Arithmetic: Supports basic operations like addition, subtraction, multiplication, and division.
• Mathematical Functions: Includes trigonometric, exponential, logarithmic, and other common mathematical functions.
• Automatic Differentiation: Computes derivatives automatically as a natural part of the computation.
• Cython Optimization: Improved performance for computationally intensive tasks.

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Installation

Using pip

Install the package directly from PyPI:

pip install rsr45-dual-autodiff-x

Using github

1. Clone the repository

git clone https://gitlab.developers.cam.ac.uk/phy/data-intensive-science-mphil/assessments/c1_coursework1/rsr45.git
cd dual_autodiff
pip install -r requirements.txt
cd dual_autodiff_x
pip install e .

Usage

Importing the Package

import dual_autodiff_x as df_x
from dual_autodiff_x.dual import Dual as DualOptimised
from dual_autodiff_x.functions import sin as sin_optimised, cos as cos_optimised, log as log_optimised

Using dual_autodiff_x (Optimised Version)

x_optimised = DualOptimised(2, 1)  # Represents the dual number 2 + 1ε

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Performing Operations

Using dual_autodiff_x (Optimised Version)

# Example: f(x) = log(sin(x)) + x^2 * cos(x)
f_x_optimised = log_optimised(sin_optimised(x_optimised)) + x_optimised**2 * cos_optimised(x_optimised)
print(f_x_optimised)  # Output the result and its derivative

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Why Use dual_autodiff_x?

The rsr-dual-autodiff-x package is an optimized version of dual_autodiff, built with Cython for better performance. Use it when speed is a priority, especially for computationally intensive tasks.

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Licence

This project is licensed under the MIT License.