audiovis

A simple audio visualizer built with Python, using matplotlib for rendering and the Fast Fourier Transform (FFT) for frequency analysis.

Generates a bar-style visualization of the frequency spectrum of input .wav files.

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Install

Clone the repo and set up dependencies:

git clone https://github.com/RynSingleton/audiovis.git
cd audiovis
pip install -r requirements.txt

or install manually:

pip install numpy matplotlib soundfile

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Usage

Run the program with:

python main.py

The program will prompt you for an input audio file:

Input filename: wav_sample.wav

It will then process the file, compute FFT data for each chunk, and display a frequency bar visualization. A GIF animation (visuals.gif) will also be saved to the project directory.

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Example output

For a sample 1 kHz tone, the visualizer produces an animated bar chart where a single frequency band dominates. The frame-by-frame update is handled by matplotlib.animation.FuncAnimation.

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Project structure

audio_processor.py   - loads audio and computes FFT magnitudes
visualizer.py        - handles matplotlib rendering and animation
main.py              - entry point for running the visualizer
requirements.txt     - dependencies

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Requirements

• Python 3.8+
• numpy
• matplotlib
• soundfile

Tested on Linux and Windows.

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Development

make clean    # remove visuals and cache
make run      # launch the visualizer
make help     # list available targets

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Next Steps

Live audio reading with audio devices! tkinter window with customizable colorations and graphics!

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License

MIT