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From "Gilles (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (RNG-20) Initial state diversity
Date Mon, 10 Oct 2016 12:24:20 GMT

     [ https://issues.apache.org/jira/browse/RNG-20?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gilles resolved RNG-20.
-----------------------
    Resolution: Implemented

commit 819d8a5443988a0b864ea3bc5d79a461ca1fa3db

> Initial state diversity
> -----------------------
>
>                 Key: RNG-20
>                 URL: https://issues.apache.org/jira/browse/RNG-20
>             Project: Commons RNG
>          Issue Type: Improvement
>            Reporter: Gilles
>            Assignee: Gilles
>            Priority: Minor
>             Fix For: 1.0
>
>
> A generator usually _assumes_ that its initial state is "sufficiently diverse" for it
to perform correctly.
> For example, it is known that some algorithms (e.g. "Mersenne Twister") will be "stuck"
by the all-zero state.
> To ensure diversity when the seed (passed by the user) contains less information than
the state can hold, {{SeedFactory}} provides a {{fillState}} method to be called from within
the {{setSeedInternal}} method of an RNG implementation.
> In this ticket, it is proposed that the actual code (for replacing zeroes in the initial
state) is inspired from the one that already existed in class {{AbstractWell}}.
> Note: neither the code in {{AbstractWell}} nor another code, in {{MersenneTwister}} and
 {{MersenneTwister64}} (with a similar purpose), will be replaced by a call to {{fillState}}
because for those algorithms, the filling procedure is part of the reference code (and is
thus necessary in order to reproduce the exact same output).



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