Book Image

Applying Math with Python - Second Edition

By : Sam Morley
Book Image

Applying Math with Python - Second Edition

By: Sam Morley

Overview of this book

The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you’ve developed a solid base in these topics, you’ll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Table of Contents (13 chapters)

Coloring a network

Networks are also useful in scheduling problems, where you need to arrange activities into different slots so that there are no conflicts. For example, we could use networks to schedule classes to make sure that students who are taking different options do not have to be in two classes at once. In this scenario, the nodes will represent the different classes and the edges will indicate that students are taking both classes. The process we use to solve these kinds of problems is called network coloring. This process involves assigning the fewest possible colors to the nodes in a network so that no two adjacent nodes have the same color.

In this recipe, we will learn how to color a network to solve a simple scheduling problem.

Getting ready

For this recipe, we need the NetworkX package imported under the nx alias and the Matplotlib pyplot module imported as plt.

How to do it...

Follow these steps to solve a network coloring problem:

  1. First, we...