Multivariable Calculus Aid
Project description
Axiomathbf is a Mathematical Aid package for Multivariate Calculus, used mainly for Jupyter Notebook due to outputs mainly are in Latex. But users can solve Multivariate Calculus problems using any Python environment. Axiomathbf can find the relative and absolute extrema of a function to calculating the gradient and directional derivative of a function.
I decided to create Axiomathbf when I began Math 200 at Drexel University in the winter. As a freshman, I wanted to implement what I learned from my CS courses. And math was what started my CS journey when I first programmed my TI-84.
Table of Content
Technologies Used
- Python
- Sympy - A computer algebra system written in pure Python
- Jupyter Notebook - an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text
Installation
git clone git@github.com:ow-wow-wang/axiomathbf.git
pip install -r requirements.txt
How Does it Work?
- For each module, I created a class related to the topic of the chapters, like creating the VectorFunction class to solve vector-related problems in chapters 11-12 in the Calculus Early Transcendentals textbook, which talk about Three-Dimensions Space, Vectors, and Vector-Valued Functions.
- I mainly used Sympy to derive, integrate, and other operations to solve these problems
- I also used OOP-design, as it allows me to write more clean code
Documentation
Find the documentation at https://aowangphilly.github.io/axiomathbf to learn how to use Axiomathbf
Further Goals
- I hope to create a Flask web application, so people who aren't familiar with programming can still solve MV problems
- I also want to create an mobile app that solves Linear Algebra problems using Sympy and OpenCV
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