an automatic differentiation package created by AC207 students
Project description
team21
Brief Introduction
funAD is a PyPi-distributed package that executes forward-mode of automatic differentiation, enabling users to solve functional derivatives with high computational efficiency and machine precision.
This project/package is the fruit of Harvard CS107/AC207 class final project in 2022 Fall. Our package utilize forward mode and dual number. Additionally, we also allow users to define their own seeds vector for the Jacobian Matrix and the option to calculate local maxima and minima through gradient descent.
To install, run the following command in your terminal
pip install funAD
For details instruction on how to use this package, please follow the steps in the usage page.
Group Number:
Group 21
Group Members:
Zhecheng Yao zhechengyao@g.harvard.edu
Hanlin Zhu hzhu@g.harvard.edu
Xu Tang xutang@g.harvard.edu
Tiantong Li tiantongli@g.harvard.edu
Harvard University, Fall 2022
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.