Example usage for java.lang Math exp

Introduction

In this page you can find the example usage for java.lang Math exp.

Prototype

@HotSpotIntrinsicCandidate
public static double exp(double a)

Source Link

Document

Returns Euler's number e raised to the power of a double value.

Usage

From source file:org.wallerlab.yoink.density.service.density.AtomDensityCalculator.java

/**
 * calculate the density of a point from an atom
 * /*from   ww w.  j a v a 2s . co  m*/
 * @param atom
 *            -{@link org.wallerlab.yoink.api.model.molecular.Atom}
 * @param currentCoord
 *            -{@link org.wallerlab.yoink.api.model.molecular.Coord}
 * @return the density of a point from an atom
 */
public Double calculate(Coord currentCoord, Atom atom) {
    double distance = distanceCalculator.calculate(currentCoord, atom);
    Element atomType = atom.getElementType();
    double exp1 = Math.exp(-distance / atomType.z1());
    double exp2 = Math.exp(-distance / atomType.z2());
    double exp3 = Math.exp(-distance / atomType.z3());
    double density = atomType.c1() * exp1 + atomType.c2() * exp2 + atomType.c3() * exp3;
    return density;
}

From source file:emlab.util.GeometricTrendRegression.java

public double predict(double x) {
    return Math.exp(super.predict(x));
}

From source file:com.opengamma.analytics.financial.equity.future.pricing.EquityFutureDividendYield.java

/**
 * @param future EquityFuture derivative
 * @param dataBundle Contains funding curve, spot value and continuous dividend yield 
 * @return Present value of the derivative
 *///from   w  w w .  jav  a  2s .com
@Override
public double presentValue(final EquityFuture future, final EquityFutureDataBundle dataBundle) {
    Validate.notNull(future, "Future");
    Validate.notNull(dataBundle);
    Validate.notNull(dataBundle.getFundingCurve());
    Validate.notNull(dataBundle.getSpotValue());
    Validate.notNull(dataBundle.getDividendYield());

    double timeToExpiry = future.getTimeToSettlement();
    double discountRate = dataBundle.getFundingCurve().getInterestRate(timeToExpiry);
    double costOfCarry = Math.exp(timeToExpiry * (discountRate - dataBundle.getDividendYield()));
    double fwdPrice = dataBundle.getSpotValue() * costOfCarry;
    return (fwdPrice - future.getStrike()) * future.getUnitAmount();
}

From source file:de.biomedical_imaging.ij.steger.Convol.java

private double phi1(double x, double sigma) {
    double t;//ww  w.j  av  a 2s.c  o m
    t = x / sigma;
    return SQRT_2_PI_INV / sigma * Math.exp(-0.5 * t * t);
}

From source file:com.github.tomakehurst.wiremock.http.LogNormal.java

@Override
public long sampleMillis() {
    return Math.round(Math.exp(ThreadLocalRandom.current().nextGaussian() * sigma) * median);
}

From source file:com.opengamma.analytics.financial.model.option.pricing.analytic.LogOptionModel.java

@Override
public Function1D<StandardOptionDataBundle, Double> getPricingFunction(final LogOptionDefinition definition) {
    Validate.notNull(definition);/*  w  w w. ja v a  2s .  c  o m*/
    final Function1D<StandardOptionDataBundle, Double> pricingFunction = new Function1D<StandardOptionDataBundle, Double>() {

        @SuppressWarnings("synthetic-access")
        @Override
        public Double evaluate(final StandardOptionDataBundle data) {
            Validate.notNull(data);
            final double s = data.getSpot();
            final double k = definition.getStrike();
            final double t = definition.getTimeToExpiry(data.getDate());
            final double b = data.getCostOfCarry();
            final double r = data.getInterestRate(t);
            final double sigma = data.getVolatility(t, k);
            final double df = Math.exp(-r * t);
            final double sigmaT = sigma * Math.sqrt(t);
            final double x = (Math.log(s / k) + t * (b - sigma * sigma * 0.5)) / sigmaT;
            return df * sigmaT
                    * (_normalProbabilityDistribution.getPDF(x) + x * _normalProbabilityDistribution.getCDF(x));
        }

    };
    return pricingFunction;
}

From source file:es.udc.gii.common.eaf.benchmark.multiobjective.fon.Fon_Objective_1.java

@Override
public double evaluate(double[] values) {
    double[] x = new double[values.length];
    double sum = 0;
    double k = 1 / Math.sqrt(values.length);

    for (int i = 0; i < values.length; i++) {
        x[i] = 4 * values[i];/*from ww  w.  j  av a  2 s  . c  om*/
        sum += (x[i] - k) * (x[i] - k);
    }

    return 1 - Math.exp(-sum);
}

From source file:com.opengamma.analytics.financial.model.stochastic.BlackScholesGeometricBrownianMotionProcess.java

@Override
public Double getFinalValue(final Double x) {
    return Math.exp(x);
}

From source file:com.joliciel.talismane.machineLearning.GeometricMeanScoringStrategy.java

@Override
public double calculateScore(ClassificationSolution<T> solution) {
    double score = 0;
    if (solution != null && solution.getDecisions().size() > 0) {
        for (Decision<?> decision : solution.getDecisions())
            score += decision.getProbabilityLog();

        score = score / solution.getDecisions().size();
    }// w  ww .  j  a v a 2 s .  c o  m
    score = Math.exp(score);

    if (LOG.isTraceEnabled()) {
        LOG.trace("Score for solution: " + solution.getClass().getSimpleName());
        LOG.trace(solution.toString());
        StringBuilder sb = new StringBuilder();
        for (Decision<?> decision : solution.getDecisions()) {
            sb.append(" * ");
            sb.append(decision.getProbability());
        }
        sb.append(" root ");
        sb.append(solution.getDecisions().size());
        sb.append(" = ");
        sb.append(score);

        LOG.trace(sb.toString());
    }

    for (Solution underlyingSolution : solution.getUnderlyingSolutions()) {
        if (!underlyingSolution.getScoringStrategy().isAdditive())
            score = score * underlyingSolution.getScore();
    }

    if (LOG.isTraceEnabled()) {
        for (Solution underlyingSolution : solution.getUnderlyingSolutions()) {
            if (!underlyingSolution.getScoringStrategy().isAdditive())
                LOG.trace(" * " + underlyingSolution.getScore() + " ("
                        + underlyingSolution.getClass().getSimpleName() + ")");
        }
        LOG.trace(" = " + score);
    }

    return score;
}

From source file:bots.mctsbot.ai.bots.util.Gaussian.java

public final static double smallPhi(double x) {
    return 1.0 / Math.sqrt(2 * Math.PI) * Math.exp(-x * x / 2.0);
}