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Applying Math with Python

You're reading from  Applying Math with Python

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Pages 358 pages
Edition 1st Edition
Languages
Author (1):
Sam Morley Sam Morley
Profile icon Sam Morley
Toc

Table of Contents (12) Chapters close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Quantifying clustering in a network

There are various quantities associated with networks that measure the characteristics of the network. For example, the clustering coefficient of a node measures the interconnectivity between the nodes nearby (here, nearby means connected by an edge). In effect, it measures how close the neighboring nodes are to forming a complete network or clique.

The clustering coefficient of a node measures the proportion of the adjacent nodes that are connected by an edge; that is, two adjacent nodes form a triangle with the given node. We count the number of triangles and divide this by the total number of possible triangles that could be formed, given the degree of the node. Numerically, the clustering coefficient at a node, u, in a simple unweighted network is given by the following equation:

Here, Tu is the number of triangles at u and the denominator is the total possible number of triangles at u. If the...

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