The trick to navigating the overwhelming Python audio/imaging landscape is understanding how the fundamentals work, using common data processing/visualization libraries, in-depth code samples, and simple math operations.
I use the stdlib, NumPy, SciPy, Matplotlib, PIL, and PyCairo to create building blocks, which I then combine to demonstrate advanced sound and image generation techniques.
The current landscape of audio and imaging in Python is overwhelming. The trick to navigating it is understanding how sound and graphics work at a fundamental level, using first the built-in libraries and then the most common data processing/visualization libraries.
Through a series of in-depth code samples, I rapidly build up from simple math to advanced sound and image generation techniques. I use the Python standard library, NumPy, SciPy, Matplotlib, PIL, and PyCairo to create building blocks, which I then combine in interesting ways to design complex sounds and images.
From waves to music:
What sounds look like:
Creative sound generation techniques:
Using the same tricks on graphics instead:
Putting it all together: