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)

Visualizing networks

A common first step in analyzing a network is to draw the network, which can help us identify some of the prominent features of a network. (Of course, drawings can be misleading, so we should not rely on them too heavily in our analysis.)

In this recipe, we’ll describe how to use the network drawing facilities in the NetworkX package to visualize a network.

Getting ready

For this recipe, we will need to import the NetworkX package under the nx alias, as described in the Technical requirements section. We will also need the Matplotlib package. For this, as usual, we must import the pyplot module as plt using the following import statement:

import matplotlib.pyplot as plt

How to do it...

The following steps outline how to draw a simple network object using the drawing routines from NetworkX:

  1. First, we will create a simple example network to draw:
    G = nx.Graph()
    G.add_nodes_from(range(1, 7))
    G.add_edges_from([
        ...