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

The IPython magic command – run

IPython has a special magic command named run that executes a file as if you were running it directly in Python. This means that the file is executed independently of what is already defined in IPython. This is the recommended method to execute files from within IPython when you want to test a script intended as a standalone program. You must import all you need in the executed file in the same way as if you were executing it from the command line. A typical example of running code in myfile.py is:

from numpy import array
...
a = array(...)

This script file is executed in Python by exec(open('myfile.py').read()). Alternatively, in IPython the magic command run myfile can be used if you want to make sure that the script runs independently of the previous imports. Everything that is defined in the file is imported into the IPython workspace.