With this book you will:Explore how the this binding points to objects based on how the function is calledLook into the nature of JS objects and why you’d need to point to themLearn how developers use the mixin pattern to fake classes in JSExamine how JS’s prototype mechanism forms links between objectsLearn how to move from class/inheritance design to behavior delegationUnderstand how the OLOO (objects-linked-to-other-objects) coding style naturally implements behavior delegation
Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.
In this updated second edition, you will:Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier TransformStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automataExplore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism
Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
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