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)

Finding minimal spanning trees and dominating sets

Networks have applications for a wide variety of problems. Two obvious areas that see many applications are communication and distribution. For example, we might wish to find a way of distributing goods to several cities (nodes) in a road network that covers the smallest distance from a particular point. For problems like this, we need to look at minimal spanning trees and dominating sets.

In this recipe, we will find a minimal spanning tree and a dominating set in a network.

Getting ready

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

How to do it...

Follow these steps to find a minimum spanning tree and dominating set for a network:

  1. First, we will create a sample network to analyze:
    G = nx.gnm_random_graph(15, 22, seed=12345)
  2. Next, as usual, we will draw the network before doing any analysis:
    fig, ax = plt.subplots()
    pos = nx.circular_layout...