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Subject: Re: Small World Network model random data generation
From: William Ray Wing <wrw@mac.com>
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Date: Tue, 26 Aug 2014 09:57:40 -0400
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Xref: csiph.com comp.lang.python:77042

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

> On Tue, 26 Aug 2014 12:16:33 +0200, lavanya addepalli =
<phani.lav@gmail.com>
> declaimed the following:
>=20
>> How can i generate a random data that is identical to my realworld =
data
>>=20
>=20
> 	By definition, "random data" will be unlikely to ever be =
"identical" to
> your "realworld data".
>=20
>=20
>> i am supposed to refer the attached paper
>>=20
>> Real Data
>>=20
>> node pairs and the time they spend together connected
>>=20
>> node node time in seconds
>> 4391 2814 16.0

[byte]

>> 1885 1158 351.0
>> 1349 1174 6375.0
>>=20
>=20
> 	Since I see no cases of duplicate node /pairs/ it is difficult =
to
> figure out just what that data really represents...
>=20
> 	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.
>=20
> 	With only the data you have, I'd end up with a sparse 2D matrix
> M[first_node, second_node] =3D time
>=20
> 	And then selecting random samples from that...
> --=20
> 	Wulfraed                 Dennis Lee Bieber         AF6VN
>    wlfraed@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=