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.rhwlab.ace3d.SegmentationLinePlot.java

public void setTree(BHCTree tree) {
    XYSeriesCollection collect = new XYSeriesCollection();
    XYSeries series = new XYSeries("");
    collect.addSeries(series);/*from w ww  .  ja  va  2 s . c o  m*/

    TreeMap<Integer, TreeSet<NucleusLogNode>> map = tree.allTreeCuts(500);

    for (Integer i : map.keySet()) {
        TreeSet<NucleusLogNode> nodes = map.get(i);
        double lnP = nodes.first().getLogPosterior();
        series.add((double) i, Math.exp(lnP));

    }
    int t = tree.getTime();
    int nu = tree.getNu();

    JFreeChart chart = ChartFactory.createXYLineChart(
            String.format("Time=%d,nu=%d,alpha=%e", tree.getTime(), tree.getNu(), tree.getAlpha()), "Index",
            "Probability", collect, PlotOrientation.VERTICAL, false, true, true);
    XYPlot plot = (XYPlot) chart.getPlot();

    ChartPanel panel = new ChartPanel(chart);
    this.add(panel);
}

From source file:blackscholes.EuropeanCall.java

public double ValuationMethod() {
    NormalDistribution N = new NormalDistribution();
    double _b = r - b;
    double d1 = (Math.log(S / X) + (b + 0.5 * Math.pow(sigma, 2)) * T) / (sigma * Math.sqrt(T));
    double d2 = d1 - sigma * Math.sqrt(T);

    double Nd1 = N.cumulativeProbability(d1);
    double Nd2 = N.cumulativeProbability(d2);
    return S * Nd1 - X * Nd2 * Math.exp((b - r) * T);
}

From source file:beast.math.distributions.NegativeBinomialDistribution.java

public double pdf(double x) {
    if (x < 0)
        return 0;
    return Math.exp(logPdf(x));
}

From source file:com.opengamma.analytics.financial.interestrate.ContinuousInterestRate.java

@Override
public double getDiscountFactor(final double t) {
    return Math.exp(-getRate() * t);
}

From source file:com.example.PJS.java

/** Otra version de la NORMSDIST (z) sacada de aca: 
* http://www.codeproject.com/Articles/408214/Excel-Function-NORMSDIST-z
*Esta es la Cumulative Normal Ditribution Function
*//*from  www  .ja va2  s . c  om*/
private static double erf(double x) {
    //A&S formula 7.1.26
    double a1 = 0.254829592;
    double a2 = -0.284496736;
    double a3 = 1.421413741;
    double a4 = -1.453152027;
    double a5 = 1.061405429;
    double p = 0.3275911;
    x = Math.abs(x);
    double t = 1 / (1 + p * x);
    //Direct calculation using formula 7.1.26 is absolutely correct
    //But calculation of nth order polynomial takes O(n^2) operations
    //return 1 - (a1 * t + a2 * t * t + a3 * t * t * t + a4 * t * t * t * t + a5 * t * t * t * t * t) * Math.Exp(-1 * x * x);

    //Horner's method, takes O(n) operations for nth order polynomial
    return 1 - ((((((a5 * t + a4) * t) + a3) * t + a2) * t) + a1) * t * Math.exp(-1 * x * x);
}

From source file:com.opengamma.analytics.financial.model.option.pricing.tree.LeisenReimerLatticeSpecification.java

@Override
public double[] getParameters(final double spot, final double strike, final double timeToExpiry,
        final double volatility, final double interestRate, final int nSteps, final double dt) {
    Validate.isTrue((nSteps % 2 == 1), "The number of steps should be odd");
    final double sigmaRootT = volatility * Math.sqrt(timeToExpiry);
    final double d1 = (Math.log(spot / strike) + interestRate * timeToExpiry) / sigmaRootT + 0.5 * sigmaRootT;
    final double d2 = d1 - sigmaRootT;
    final double sig1 = d1 >= 0. ? 1. : -1.;
    final double sig2 = d2 >= 0. ? 1. : -1.;
    final double coef1 = d1 / (nSteps + 1. / 3. + 0.1 / (nSteps + 1.));
    final double coef2 = d2 / (nSteps + 1. / 3. + 0.1 / (nSteps + 1.));
    final double p1 = 0.5 + sig1 * 0.5 * Math.sqrt(1. - Math.exp(-coef1 * coef1 * (nSteps + 1. / 6.)));
    final double p2 = 0.5 + sig2 * 0.5 * Math.sqrt(1. - Math.exp(-coef2 * coef2 * (nSteps + 1. / 6.)));
    final double rr = Math.exp(interestRate * dt);
    final double upFactor = rr * p1 / p2;
    final double downFactor = (rr - p2 * upFactor) / (1 - p2);

    return new double[] { upFactor, downFactor, p2, 1 - p2 };
}

From source file:com.opengamma.analytics.financial.interestrate.NelsonSiegelBondCurveModel.java

public ParameterizedFunction<Double, DoubleMatrix1D, Double> getParameterizedFunction() {
    return new ParameterizedFunction<Double, DoubleMatrix1D, Double>() {

        @Override//from w  ww  . j  a v a2  s  .c o  m
        public Double evaluate(final Double t, final DoubleMatrix1D parameters) {
            Validate.notNull(t, "t");
            Validate.notNull(parameters, "parameters");
            Validate.isTrue(parameters.getNumberOfElements() == 4);
            final double beta0 = parameters.getEntry(0);
            final double beta1 = parameters.getEntry(1);
            final double beta2 = parameters.getEntry(2);
            final double lambda = parameters.getEntry(3);
            final double x1 = t / lambda;
            final double x2 = Epsilon.epsilon(-x1);
            return beta0 + beta1 * x2 + beta2 * (x2 - Math.exp(-x1));
        }

        public Object writeReplace() {
            return new InvokedSerializedForm(NelsonSiegelBondCurveModel.class, "getParameterizedFunction");
        }

    };
}

From source file:com.opengamma.analytics.financial.interestrate.PeriodicInterestRate.java

@Override
public double fromContinuousDerivative(final ContinuousInterestRate continuous) {
    Validate.notNull(continuous);//  w ww.j av a  2 s .c o m
    return Math.exp(continuous.getRate() / getCompoundingPeriodsPerYear());
}

From source file:com.opengamma.analytics.financial.interestrate.NelsonSiegelSvennsonBondCurveModel.java

public ParameterizedFunction<Double, DoubleMatrix1D, Double> getParameterizedFunction() {
    return new ParameterizedFunction<Double, DoubleMatrix1D, Double>() {

        @Override/*w ww  .  jav  a 2s .co  m*/
        public Double evaluate(final Double t, final DoubleMatrix1D parameters) {
            Validate.notNull(t, "t");
            Validate.notNull(parameters, "parameters");
            Validate.isTrue(parameters.getNumberOfElements() == 6);
            final double beta0 = parameters.getEntry(0);
            final double beta1 = parameters.getEntry(1);
            final double beta2 = parameters.getEntry(2);
            final double lambda1 = parameters.getEntry(3);
            final double beta3 = parameters.getEntry(4);
            final double lambda2 = parameters.getEntry(5);
            final double x1 = t / lambda1;
            final double x2 = (1 - Math.exp(-x1)) / x1;
            final double x3 = t / lambda2;
            final double x4 = (1 - Math.exp(-x3)) / x3;
            return beta0 + beta1 * x2 + beta2 * (x2 - Math.exp(-x1)) + beta3 * (x4 - Math.exp(-x3));
        }

        public Object writeReplace() {
            return new InvokedSerializedForm(NelsonSiegelSvennsonBondCurveModel.class,
                    "getParameterizedFunction");
        }

    };
}

From source file:com.cloudera.science.mgps.NFunction.java

public double eval(int n, double e) {
    double x = -n * Math.log(1 + beta / e);
    double y = -alpha * Math.log(1 + e / beta);
    double z = Gamma.logGamma(alpha + n);
    double d = Gamma.logGamma(alpha) + MathUtils.factorialLog(n);
    return Math.exp(x + y + z - d);
}