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| From | Terry Reedy <tjreedy@udel.edu> |
|---|---|
| Subject | Re: Small World Network model random data generation |
| Date | 2014-08-26 13:37 -0400 |
| References | <CAJsaReSKh2GiBohMv_6wQRNTruMjgSDnRnEHBux+uCiQ9OApCA@mail.gmail.com> |
| Newsgroups | comp.lang.python |
| Message-ID | <mailman.13473.1409074680.18130.python-list@python.org> (permalink) |
On 8/26/2014 6:16 AM, lavanya addepalli wrote: > How can i generate a random data that is identical to my realworld data I presume you mean same statistical properties. https://en.wikipedia.org/wiki/Small-world_network explains the difference between random networks and many real sw networks. > i am supposed to refer the attached paper By Watts and Strogatz https://en.wikipedia.org/wiki/Watts_and_Strogatz_Model gives a compact description of their algorithm, without proofs. > Real Data > node pairs and the time they spend together connected Your real data should have connect and disconnect (start and stop) times. The data below could represent a decay situation where all connections exist at time 0 and the time represents how long they last before breaking. Or a much different growth situation where there are initially no connections and they slowly accumulate. Or some sort of steady situation. > node node time in seconds > 4391 2814 16.0 > 4945 3545 386.0 > 5045 4921 63078.0 etc. The small-world-network concept is a static, or perhaps snapshot concept. Modeling link changes in a way that maintains the statistical properties is a harder problem. -- Terry Jan Reedy
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Re: Small World Network model random data generation Terry Reedy <tjreedy@udel.edu> - 2014-08-26 13:37 -0400
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