Ceci est une ancienne révision du document !
Modeling and Simulation in Python An Introduction for Scientists and Engineers Allen B. Downey
Publisher: No Starch Press Release date: March 2023 Pages: 280 ISBN-13: 9781718502161 Price: $39.99 USD Level: Intermediate
I’ve read a number of Allen Downey’s books before, the most notable is Think Python. I’ve always enjoyed his writing. Modeling and Simulation in Python is no different. I thoroughly enjoyed this book!
That having been said, I have to grab a quote from the introduction.
“I assume that you know what derivatives and integrals are, but that’s about all. In particular, you don’t need to know (or remember) much about finding derivatives or integrals of functions analytically. If you know the derivative of x2 and you can integrate 2x dx, that will do it. More importantly, you should understand what those concepts mean; but if you don’t, this book might help you figure it out.”
So, don’t let the higher math scare you if you want to jump into simulations and modeling. Yes, some of the math is a bit on the “deep” side, but given the resources on the Internet these days, you should be able to get to a point where the whole thing starts to make sense.
One of the chapters that drew my attention right away, is Chapter 17 - Modeling Blood Sugar. Being a diabetic, this hits close to home for me. I constantly struggle with my blood sugar levels and many times, it doesn’t seem to matter what I do, it seems to always be out of whack. This chapter really was a blessing. I intend to revisit it again and again.
Usually, I dislike when an author uses a Jupyter Notebook for demonstration of their code. I understand the reasons why they do, but it always frustrates me. It kind of seems like cheating. But, the projects in the book all make sense to use it in this case.
Bottom line here is that I LOVE this book, as well as all the other books of Professor Downey’s that I have read. If you want to get a firm grip on using Python for modeling or simulations, PLEASE get this book and make it part of your library. But don’t just put it on the bookshelf. Sit down with it, read the chapter, and follow along with the projects. If you don’t understand something, jump on the Internet and learn.
Who knows, this might get you started on a new profession in Python!
Table of Contents Acknowledgments Introduction PART I: DISCRETE SYSTEMS Chapter 1: Introduction to Modeling Chapter 2: Modeling a Bike Share System Chapter 3: Iterative Modeling Chapter 4: Parameters and Metrics Chapter 5: Building a Population Model Chapter 6: Iterating the Population Model Chapter 7: Limits to Growth Chapter 8: Projecting into the Future Chapter 9: Analysis and Symbolic Computation Chapter 10: Case Studies Part I PART II: FIRST-ORDER SYSTEMS Chapter 11: Epidemiology and SIR Models Chapter 12: Quantifying Interventions Chapter 13: Sweeping Parameters Chapter 14: Nondimensionalization Chapter 15: Thermal Systems Chapter 16: Solving the Coffee Problem Chapter 17: Modeling Blood Sugar Chapter 18: Implementing the Minimal Model Chapter 19: Case Studies Part II PART III: SECOND-ORDER SYSTEMS Chapter 20: The Falling Penny Revisited Chapter 21: Drag Chapter 22: Two-Dimensional Motion Chapter 23: Optimization Chapter 24: Rotation Chapter 25: Torque Chapter 26: Case Studies Part III Appendix: Under the Hood Index