[jira] [Created] (RNG-68) AhrensDieterMarsagliaTsangGammaSampler constructor can be optimised for the theta parameter

["Alex D Herbert (JIRA)" <ji...@apache.org>]

Alex D Herbert created RNG-68:
---------------------------------

             Summary: AhrensDieterMarsagliaTsangGammaSampler constructor can be optimised for the theta parameter
                 Key: RNG-68
                 URL: https://issues.apache.org/jira/browse/RNG-68
             Project: Commons RNG
          Issue Type: Improvement
          Components: sampling
    Affects Versions: 1.2
            Reporter: Alex D Herbert


The AhrensDieterExponentialSampler has two algorithms based on the {{theta}} parameter. The constructor precomputes factors for both algorithms even though only one algorithm will even be called.

I suggest optimising the constructor using:

{code:java}
public AhrensDieterMarsagliaTsangGammaSampler(UniformRandomProvider rng,
                                              double alpha,
                                              double theta) {
    super(null);
    this.rng = rng;
    this.alpha = alpha;
    this.theta = theta;
    gaussian = new ZigguratNormalizedGaussianSampler(rng);
    if (theta < 1) {
        oneOverTheta = 1 / theta;
        bGSOptim = 1 + theta / Math.E;
        // Unused
        dOptim = cOptim = 0;
    } else {
        dOptim = theta - ONE_THIRD;
        cOptim = ONE_THIRD / Math.sqrt(dOptim);
        // Unused
        oneOverTheta = bGSOptim = 0;
    }
}
{code}

An alternative is to split the two algorithms into two classes as was done for the {{PoissonSampler}} for small and large mean.




--
This message was sent by Atlassian JIRA
(v7.6.3#76005)