Code Directory
 Visual Basic & VB.NET
New Code
Excel .Net Library 2020.6
fsMediaLibrary.NET 2019.11
VaxVoIP SIP Server SDK 5.2.0
Database Workbench Pro 5.7.4
dbForge Data Generator for Oracle 2.2
dbExpress driver for SQL Server 8.2
Grobino Online Grocery Shopping 1.1
PortalNest: Dynamics CRM Customer Portal 1.0
Purbis: JustEat Clone Scripts 1.1
Monoline MLM Software 1.3.4
Cab Booking Android Application by iNet Mobile 1.4
Shopping Cart Script by i-Netsolution 1.3.4
PortalNest: SuiteCRM Customer Portal 1.0
SugarCRM WordPress Customer Portal 3.2.0
The C# PDF Library 2020.6.0
Top Code
IcrediBB Bulletin Board System 1.0
Ez Paypal Clone 7.4.2
MLM Software ONE 1.5.46
Simple Web Content Management System for Scripts 1.1
quicktest 0.6.1
POST Affiliate Pro 1.2.1
dbm I.13
Dots and Boxes 1.0
Affiliate Pro Plus 2.9
Free PHPNuke Subscription Module 1.0
Ninja Playland 1.1
Post Affiliate Pro Tracker 1.0.0
Basic Calendar
Top Rated
phpEnter 5.1.
Single Leg MLM 1.2.1
Azizi search engine script PHP 4.1.10
Paste phpSoftPro 1.4.1
Extreme Injector 3.7
Deals and Discounts Website Script 1.0.2
Solid File System OS edition 5.1
Classified Ad Lister 1.0
Aglowsoft SQL Query Tools 8.2
Invoice Manager by PHPJabbers 3.0
ICPennyBid Penny Auction Script 4.0
PHP Review Script 1.0
ATN Resume Finder 2.0
ATN Site Builder 3.0
Availability Booking Calendar PHP 1.0
B-A Scale-Free Network Generation and Visualization 1.0
File ID: 78899

B-A Scale-Free Network Generation and Visualization 1.0
Download B-A Scale-Free Network Generation and Visualization 1.0http://www.mathworks.comReport Error Link
License: Shareware
File Size: 61.4 KB
Downloads: 29
Submit Rating:
B-A Scale-Free Network Generation and Visualization 1.0 Description
Description: *Description and Cautions

-The SFNG m-file is used to simulate the B-A algorithm and returns scale-free networks of given node sizes. Understanding the B-A algorithm is key to using this code to its fullest. Due to Matlab resource limitations, it may not be possible to generate networks much larger than 15000 nodes, and increasing the mlinks variable increases processing time severely. This code was developed so that one could generate a network of small size, and then use that network as a seed to build a greater sized network, continuing this process until the actual desired network size is reached. This is for processor and time management purposes. However, realize that the initial seed does not have to have scale-free properties, while the later seeds may happen to have these properties. Therefore, it is prudent not to make the initial seed size much larger than a few nodes (most commonly 5 interconnected nodes). In addition, the mlinks should be kept constant throughout the creation of the scale-free network.

-The PLplot m-file takes a scale-free network in adjacency matrix format and draws a best fit line to the frequency of degrees distribution of the nodes. Degree is the number of links that connect to and from a single node For scale-free networks, the frequency of degrees distribution forms a power-law curve, with an exponent usually between -2 and -3. This code is designed to allow only non-zero frequencies to be graphed in log-log format. The function returns the equation of the power-law fit in a cfit variable.

-The CNet m-file function creates a network graph using the gplot function with circular coordinates. It allows for a simple, yet intuitive, visualization of a given network.



-Nodes is the desired network size, including the seed network size (i.e. Nodes minus seed network size equals the number of nodes to be added).

-mlinks controls the number of links a new node can make to the existing network nodes.

-seed is the original network to which the B-A algorithm links additional nodes with a specific preferential attachment procedure. This undirected adjacency matrix can be created manually, or one could use the Adjacency Matrix GUI. Each node must have at least one link. The seed variable can be replaced with a developed scale-free network to generate a larger one. Make sure the new Nodes variable is greater than the size of the seed network.

-Net is the input network which is to be graphed.

-Net is the input network which is to be graphed.

Note that variables Nodes, mlinks, and size must be whole numbers and variables seed and Net must be undirected adjacency matrices. The diagonal elements of any adjacency matrix used with these functions must all be zero.

*Sample Output

Here is a small example to demonstrate how to use the code. This code creates a seed network of 5 nodes, generates a scale-free network of 300 nodes from the seed network, and then performs the two graphing procedures.

seed =[0 1 0 0 1;1 0 0 1 0;0 0 0 1 0;0 1 1 0 0;1 0 0 0 0]
Net = SFNG(300, 1, seed);
PL_Equation = PLplot(Net)


One explanation of the B-A Algorithm can be found on this PDF website

Undirected Adjecency Matrices are defined on

The Adjacency Matrix GUI file by Steve Chuang can be found on the Matlab File Exchange


Special thanks to Mark Ballerini with the Massapequa High School Science Research Program and Zoltan Dezso at the University of Notre Dame for their invaluable help in researching network theory as well as to my family for providing motivation and encouragement in pursuing science

License: Shareware

Related: Matrix, replaced, Input, adjacency, manually, Attachment, Procedure, undirected, created

O/S:BSD, Linux, Solaris, Mac OS X

File Size: 61.4 KB

Downloads: 29

More Similar Code

Development of a database for the storage and visualization of (network) graphs with associated node and edge attributes. The project comprises the necessary database layer, web interface layer and visualization layer.

This project aims to do for MULTICS what Linux and GNU have done for UNIX - that is, to produce a totally free, totally unencumbered, and totally compliant OS that learns from prior work, rather than copies it.

A generic database schema generation and modeling tool. Allows a generic schema to be manually designed and edited or automatically generated. Schemas can be deployed to any of the supported database systems (Oracle,MySQL,SqlServer+).

Lock & Key is a royalty free security component for you applications. Distribute trial versions of your products which can be easily ounlockedo to the fully working versions over the phone or via the Internet. Use either a okill dateo or a...

Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink.
Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink.

Marcelo Augusto Costa Fernandes

A Practical Comparison of ADO and ADO.NET - Part II is an article in which the author compares the recordset of ADO with the Rowset of the ADO.NET. The rowset of the ADO.NET belongs to the OleDbDataReader and SqlDataReader classes. Using Recordset...

A Practical Comparison of XSLT and ASP.NET is an article in which the author shows you the diference in the performace of ASP.NET and XSLT. The author compares both ASP.NET and XSLT by providing the solution for getting the XML data and convert it...

A Quick Comparison of ADO and ADO.NET - Part I is an interesting article in which the author discusses about the difference between ADO and ADO.NET. ADO 2.x contains 9 classes to perform various database operations. But in ADO.NET you have two...

Creating a Weblog using JScript .NET and ASP.NET is an article in which author discusses about creating a web log by using ASP.NET and jscript. The author elaborates about web log, which represents the personal journal. The author gives details...

Mercurial (hg) is a distributed source control tool and Mercurial Queues (mq) is a patch management tool extension to hg. gwsmhg is a PyGTK GUI wrapper for hg and mq allowing them to be used in an integrated manner to manage a work space.

User Review for B-A Scale-Free Network Generation and Visualization
- required fields

Please enter text on the image