Getting started with Object-Oriented Programming through Signal...
summary
Tutorial uses signal processing to teach OOP by actually building classes and running code: creates Signal and Wave classes with amplitude frequency and offset, uses numpy and matplotlib in Jupyter, and provides helpers.py and classes.py. It implements __mul__ to multiply waves (via a WaveWithMul wrapper), builds AM modulator and demodulator plus filtering that demonstrably recovers a signal, and shows the iterator design pattern with Python's __iter__/__next__ and abstract base classes. Frame rate examples (3000) and sample arrays (~6000) appear in the demos.
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chapters (12)
- 0:00Introduction
- 2:08Why object-oriented programming
- 4:26Course prerequisites and setup
- 5:56Signal processing basics
- 9:47Defining classes and objects
- 16:53Working with waves
- 26:26Exercises and implementation
- 40:40Inheritance and design
- 49:09Advanced OOP and patterns
- 1:12:19Interface design and contracts
- 1:41:25Design patterns and iterators
- 2:25:28Final recap and principles
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