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

9.9 Exercises

Ex. 1: Compute the value of the sum:

Ex. 2: Create a generator that computes the sequence defined by the relation:

Ex. 3: Generate all the even numbers.

Ex. 4: Let . In calculus, it is shown that  . Determine experimentally the smallest number  such that . Use a generator for this task.

Ex. 5: Generate all prime numbers less than a given integer. Use the algorithm called Sieve of Eratosthenes.

Ex. 6: Solving the differential equation  by applying the explicit Euler method results in the recursion:

 

Write a generator that computes the solution values  for a given initial value  and for a given value of the time step .

Ex. 7: Compute π using the formula:

The integral can be approximated using the composite trapezoidal rule, that is, with this formula:

where .

Program a generator for the values and evaluate the formula by summing one term after the other. Compare your results...