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You're reading from  Network Science with Python and NetworkX Quick Start Guide

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955316
Edition1st Edition
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Edward L. Platt
Edward L. Platt
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Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
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Measuring resilience

Resilience is the ability of a system to withstand errors and attacks. In an electrical grid, for example, resilience would mean keeping power flowing when a transmission line or generator broke down. In traffic, it could mean the ability to reroute cars when a street is closed due to an accident.

Resilience is fundamentally a network property because it is usually achieved with redundant paths. When one path is no longer available, the others can still be used.

The simplest (and crudest) measure of resilience is the density of a network: the fraction of possible edges that exist. The more edges present in a network, the more redundant paths exist between its nodes. The following code uses the density() function to calculate this value for the example networks:

nx.density(G_karate)
0.13903743315508021

nx.density(G_karate)
0.011368341803124411

nx.density(G_karate...
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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316

Author (1)

author image
Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt