Python Trigonometric Function Visualization

The [Coding Druid] series is my cross-platform programming practice notes. Each episode focuses on a theme (math, physics, electronics, graphics, sound...), implemented in several programming languages. Leveling up warrior, mage, healer, and rogue simultaneously — tanking, DPSing, healing, and escaping all at once.

Coding Druid - Math Chapter - Trigonometric Function Visualization: Python Implementation

In the previous two sections, we visualized trigonometric functions (sine and unit circle) using MaxMSP and JavaScript:

[Coding Druid - Math Chapter] MaxMSP Trigonometric Function Visualization

[Coding Druid - Math Chapter] JavaScript (React) Trigonometric Function Visualization

This time we'll implement it in Python.

Python also has many ways to draw graphics. Fortunately, I'm not very familiar with most of them — being a Python newcomer means less choice paralysis than the JavaScript version.

With the goal of getting results quickly, I directly Googled "python data visualization lib" and among the results, sorted by GitHub stars, found the tried-and-true Matplotlib. And just like that, the decision was made.

Matplotlib Installation Considering future practice topics, I chose Anaconda's all-in-one installation, which includes Matplotlib and a bunch of scientific computing and data analysis libraries.

Since I've been working from different locations recently with different computers, I set up a remote development environment (VSCode Remote is amazing!). Code is deployed and runs on an Azure server, while I use a netbook for editing and viewing results. So I chose the Linux version for the server.

Note: Choose the Python 3.x version on the left, since Matplotlib 3.0+ only supports Python 3.

Matplotlib 3.0 is Python 3 only.

For Python 2 support, Matplotlib 2.2.x will be continued as a LTS release and updated with bugfixes until January 1, 2020.

After installing Matplotlib, we can start coding.

(Actually, after writing a few lines, I found that viewing graphical output remotely wasn't very convenient, so I also installed Jupyter Notebook to write and view results directly in the browser.)

I also installed ffmpeg to convert Matplotlib animations to mp4. ffmpeg was also installed via Anaconda — gut feeling says fewer pitfalls this way. conda install -c conda-forge ffmpeg

With Matplotlib, the Sine function animation code is actually just a few lines. Most of the code is actually for coordinate configuration, drawing helper lines, etc.

Code shown below:

Basically following tutorials and reference articles — when using this kind of library, most of the thinking focuses on the math formula logic itself.

Here's a good reference article: Animations with Matplotlib

Final result:

Talk is cheap. Show me the code!

The code for this and most of the [Coding Druid] series is open-sourced here: https://github.com/avantcontra/coding-druid

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Cheers🍻

Contra