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

15.3.3 Timing with a context manager

Finally, we present the third method. It serves to show another application of a context manager. We first construct a context manager object for measuring the elapsed time as shown:

import time
class Timer:
    def __enter__(self):
        self.start = time.time()
        # return self
    def __exit__(self, ty, val, tb):
        end = time.time()
        self.elapsed=end-self.start
        print(f'Time elapsed {self.elapsed} seconds') 
return False

Recall that the __enter__ and __exit__ methods make this class a context manager. The __exit__ method's parameters ty, val, and tb are in the normal case None. If an exception is raised during execution, they take the exception type, its value, and traceback information. The return value False indicates that the exception has not been caught so far.

We'll now show the use of the ...