multiNormal.C

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#include "multiNormal.H"
#include "mathematicalConstants.H"
#include "addToRunTimeSelectionTable.H"
 
// * * * * * * * * * * * * * * Static Data Members * * * * * * * * * * * * * //
 
namespace Foam
{
namespace distributions
{
    defineTypeNameAndDebug(multiNormal, 0);
    addToRunTimeSelectionTable(distribution, multiNormal, dictionary);
}
}
 
 
// * * * * * * * * * * * Private Static Member Functions * * * * * * * * * * //
 
Foam::scalarList Foam::distributions::multiNormal::readCumulativeStrengths
(
    const dictionary& dict
)
{
    const scalarList s(dict.lookup<scalarList>("strength"));
 
    const scalarList sHat(s/sum(s));
 
    scalarList cumSHat(s.size() + 1, scalar(0));
    forAll(sHat, i)
    {
        cumSHat[i + 1] = cumSHat[i] + sHat[i];
    }
 
    return cumSHat;
}
 
 
// * * * * * * * * * * * * * Private Member Functions  * * * * * * * * * * * //
 
Foam::tmp<Foam::scalarField> Foam::distributions::multiNormal::phi
(
    const label q,
    const scalarField& x
) const
{
    scalarField phiQ0(x.size(), 0);
 
    forAll(distributions_, i)
    {
        phiQ0 +=
            (cumulativeStrengths_[i + 1] - cumulativeStrengths_[i])
           *distributions_[i].phi(0, x);
    }
 
    return integerPow(x, q)*phiQ0;
}
 
 
Foam::tmp<Foam::scalarField> Foam::distributions::multiNormal::PhiForZeroQ
(
    const scalarField& x
) const
{
    tmp<scalarField> tPhiQ0(new scalarField(x.size(), 0));
    scalarField& PhiQ0 = tPhiQ0.ref();
 
    forAll(distributions_, i)
    {
        PhiQ0 +=
            (cumulativeStrengths_[i + 1] - cumulativeStrengths_[i])
           *distributions_[i].Phi(0, x);
    }
 
    return tPhiQ0;
}
 
 
// * * * * * * * * * * * * * * * * Constructors  * * * * * * * * * * * * * * //
 
Foam::distributions::multiNormal::multiNormal
(
    const unitConversion& units,
    const dictionary& dict,
    const label sampleQ,
    randomGenerator&& rndGen
)
:
    FieldDistribution<unintegrableForNonZeroQ, multiNormal>
    (
        typeName,
        units,
        dict,
        sampleQ,
        std::move(rndGen)
    ),
    cumulativeStrengths_(readCumulativeStrengths(dict))
{
    const scalar min
    (
        dict.lookupBackwardsCompatible<scalar>({"min", "minValue"}, units)
    );
    const scalar max
    (
        dict.lookupBackwardsCompatible<scalar>({"max", "maxValue"}, units)
    );
    const scalarList mu
    (
        dict.lookupBackwardsCompatible<scalarList>({"mu", "expectation"}, units)
    );
    const scalarList sigma
    (
        dict.lookup<scalarList>("sigma", units)
    );
 
    if
    (
        mu.size() != cumulativeStrengths_.size() - 1
     || sigma.size() != cumulativeStrengths_.size() - 1
    )
    {
        FatalIOErrorInFunction(dict)
            << type() << ": Differing numbers of means, standard deviations "
            << "and strengths were given:" << nl << "    mu = " << mu
            << ", sigma = " << sigma << ", strength = "
            << dict.lookup<scalarList>("strength") << abort(FatalIOError);
    }
 
    distributions_.resize(mu.size());
    forAll(mu, i)
    {
        distributions_.set
        (
            i,
            new normal
            (
                0,
                0,
                rndGen_.generator(),
                -1,
                min,
                max,
                mu[i],
                sigma[i]
            )
        );
    }
 
    validateBounds(dict);
    if (q() != 0) validatePositive(dict);
    mean();
}
 
 
Foam::distributions::multiNormal::multiNormal
(
    const multiNormal& d,
    const label sampleQ
)
:
    FieldDistribution<unintegrableForNonZeroQ, multiNormal>(d, sampleQ),
    cumulativeStrengths_(d.cumulativeStrengths_),
    distributions_(d.distributions_.size())
{
    forAll(d.distributions_, i)
    {
        distributions_.set
        (
            i,
            new normal
            (
                0,
                0,
                randomGenerator(d.distributions_[i].rndGen_),
                -1,
                d.distributions_[i].min_,
                d.distributions_[i].max_,
                d.distributions_[i].mu_,
                d.distributions_[i].sigma_
            )
        );
    }
}
 
 
// * * * * * * * * * * * * * * * * Destructor  * * * * * * * * * * * * * * * //
 
Foam::distributions::multiNormal::~multiNormal()
{}
 
 
// * * * * * * * * * * * * * * * Member Functions  * * * * * * * * * * * * * //
 
Foam::scalar Foam::distributions::multiNormal::sampleForZeroQ() const
{
    const scalar S = rndGen_.sample01<scalar>();
 
    label i = 0;
    for
    (
        ;
        i < cumulativeStrengths_.size() - 1
     && cumulativeStrengths_[i + 1] < S;
     ++ i
    );
 
    const scalar s =
        (S - cumulativeStrengths_[i])
       /(cumulativeStrengths_[i + 1] - cumulativeStrengths_[i]);
 
    return distributions_[i].sampleForZeroQ(s);
}
 
 
Foam::scalar Foam::distributions::multiNormal::min() const
{
    return distributions_[0].min();
}
 
 
Foam::scalar Foam::distributions::multiNormal::max() const
{
    return distributions_[0].max();
}
 
 
void Foam::distributions::multiNormal::write
(
    Ostream& os,
    const unitConversion& units
) const
{
    FieldDistribution<unintegrableForNonZeroQ, multiNormal>::write(os, units);
 
    writeEntry(os, "min", units, distributions_[0].min());
    writeEntry(os, "max", units, distributions_[0].max());
 
    scalarList mu(distributions_.size()), sigma(distributions_.size());
    forAll(distributions_, i)
    {
        mu[i] = distributions_[i].mu();
        sigma[i] = distributions_[i].sigma();
    }
 
    writeEntry(os, "mu", units, mu);
    writeEntry(os, "sigma", units, sigma);
}
 
 
Foam::tmp<Foam::scalarField>
Foam::distributions::multiNormal::plotX(const label n) const
{
    return distributions_[0].plotX(n);
}
 
 
// ************************************************************************* //