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From "Phil Steitz (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MATH-701) Seeding a default RNG
Date Thu, 03 Nov 2011 17:09:32 GMT

    [ https://issues.apache.org/jira/browse/MATH-701?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13143322#comment-13143322
] 

Phil Steitz commented on MATH-701:
----------------------------------

I agree that there is a problem here; but I would solve it in AbstractContinuousDistribution
by passing a seeded generator to the RandomDataImpl constructor.  The code above is for the
default case where no generator has been supplied or set.  For sampling, a Well generator
would be a better choice.
                
> Seeding a default RNG
> ---------------------
>
>                 Key: MATH-701
>                 URL: https://issues.apache.org/jira/browse/MATH-701
>             Project: Commons Math
>          Issue Type: Bug
>            Reporter: Gilles
>            Assignee: Gilles
>             Fix For: 3.0
>
>
> In "RandomDataImpl":
> {code}
> private RandomGenerator getRan() {
>     if (rand == null) {
>         rand = new JDKRandomGenerator();
>         rand.setSeed(System.currentTimeMillis());
>     }
>     return rand;
> }
> {code}
> The conditional branch is used by "sample()" in "AbstractContinuousDistribution".
> When several "...Distribution" objects are instantiated in a short time interval, they
are seeded with the same value.

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