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, MatDescriptionlib, 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, MatDescriptionlib, 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, MatDescriptionlib, 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
MatDescriptionlib
SymPy
SciPy
VPython
Tkinter
Numerical calculations
Statistical calculations
Boolean algebra


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