Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modelingβthat is, the art of describing and simulating real-world systems.
Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions.
Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.
This book is about dynamical systems, that is, things that change over time. The first example weβll look at is a penny falling from the Empire State Building, where the thing thatβs changing is the position of the penny in space. Other examples include a cup of coffee, where temperature changes over time, and glucose in the human bloodstream, where concentration changes over time.
We will define models, which are simplifications intended to include the most important elements of the real world and leave out the least important, and we will write Python programs that simulate these models. We will use models and simulations to do three kinds of work: predicting how a system will behave, explaining why it behaves as it does, and designing systems to behave the way we want.