Python for Engineering and Scientific Computing

It’s finally here—your guide to Python for engineers and scientists, by an engineer and scientist! Get to know your development environments and the key Python modules you’ll need: NumPy, SymPy, SciPy, Matplotlib, and VPython. Understand basic Python program structures and walk through practical exercises that start simple and increase in complexity as you work your way through the book. With information on statistical calculations, Boolean algebra, and interactive programming with Tkinter, this Python guide belongs on every scientist’s shelf! A practical guide to Python for nonprogrammers Work with NumPy, SymPy, SciPy, Matplotlib, and VPython Automate numerical calculations, create simulations and visualizations, perform statistical analysis, and more Python for Scientists You already know how to solve problems in your field. In this guide you’ll find the tools you need to map your existing calculations with Python. Python Modules Learn how NumPy, SymPy, SciPy, Matplotlib, and VPython can help you with your scientific work. From solving linear equations and creating animations to using discrete Fourier transformations to reconstruct a noisy signal, you’ll find the practical advice you need. Python in Action Start simple by sizing a shaft and then move on to increasingly advanced exercises: animating a pendulum, simulating a rolling element bearing defect, creating a predator-prey model, and more. For every exercise, review the complete source code, with extensive comments, and analyze the output. Program structures NumPy Matplotlib SymPy SciPy VPython Tkinter Numerical calculations Statistical calculations Boolean algebra