Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
20
About Packt
22
References

Catching exceptions

Dealing with an exception is referred to as catching an exception. Checking for exceptions is done with the commands try and except.

An exception stops the program execution flow and looks for the closest try enclosing block. If the exception is not caught, the program unit is left and it continues searching for the next enclosing try block in a program unit higher up in the calling stack. If no block is found and the exception is not handled, execution stops entirely and the standard traceback information is displayed.

Let's look at the factorial example from previously and use it with the try statement:

n=-3
try: print(factorial(n)) except ValueError: print(factorial(-n)) # Here we catch the error

In this case, if the code inside the try block raises an error of type ValueError, the exception will be caught and the action in the except block is taken. If no exception occurs inside...