Small World Network model random data generation

[William Ray Wing]

On Aug 26, 2014, at 9:23 AM, Dennis Lee Bieber <wlfraed at ix.netcom.com> wrote:

> On Tue, 26 Aug 2014 12:16:33 +0200, lavanya addepalli <phani.lav at gmail.com>
> declaimed the following:
> 
>> How can i generate a random data that is identical to my realworld data
>> 
> 
> 	By definition, "random data" will be unlikely to ever be "identical" to
> your "realworld data".
> 
> 
>> i am supposed to refer the attached paper
>> 
>> Real Data
>> 
>> node pairs and the time they spend together connected
>> 
>> node node time in seconds
>> 4391 2814 16.0

[byte]

>> 1885 1158 351.0
>> 1349 1174 6375.0
>> 
> 
> 	Since I see no cases of duplicate node /pairs/ it is difficult to
> figure out just what that data really represents...
> 
> 	With enough data, with duplicate pairs having different times, I'd
> likely group by pairs, generate mean and standard deviation for the times
> of the matching pairs, then generate some count of the pairs to develop
> weights... Finally, using the weights I'd attempt to generate random node
> pairs and then use the mean/SD of the result pair to generate a time from
> the gaussian distribution.
> 
> 	With only the data you have, I'd end up with a sparse 2D matrix
> M[first_node, second_node] = time
> 
> 	And then selecting random samples from that...
> -- 
> 	Wulfraed                 Dennis Lee Bieber         AF6VN
>    wlfraed at ix.netcom.com    HTTP://wlfraed.home.netcom.com/

I think the OP wanted to create some sort of test file that was formatted
like his real-world data, but was filled with artificial data.  That, of
course simply becomes an exercise in creating lists of random 4-digit integers
and floats, then arranging them as lines and writing out the data.

-Bill