Example usage for java.lang Math log

List of usage examples for java.lang Math log

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Introduction

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

Prototype

@HotSpotIntrinsicCandidate
public static double log(double a)

Source Link

Document

Returns the natural logarithm (base e) of a double value.

Usage

From source file:com.doplgangr.secrecy.FileSystem.File.java

private static String humanReadableByteCount(long bytes) {
    int unit = 1024;
    if (bytes < unit)
        return bytes + " B";
    int exp = (int) (Math.log(bytes) / Math.log(unit));
    char pre = ("KMGTPE").charAt(exp - 1);
    return String.format("%.1f %sB", bytes / Math.pow(unit, exp), pre);
}

From source file:it.cnr.jatecs.indexing.tsr.ConfWeight.java

private double strength(double minPosRelFreq, double minPos, double maxNeg) {
    if (minPos > maxNeg) {
        return Math.log(2 * minPosRelFreq) / log2;
    } else {// w  w w.ja  v  a  2 s  . c o m
        return 0.0;
    }
}

From source file:hivemall.utils.math.MathUtils.java

/**
 * <a href="https://en.wikipedia.org/wiki/Logit">Logit</a> is the inverse of
 * {@link #sigmoid(double)} function./*from  w  w  w .  j a  v a  2s .c  o  m*/
 */
public static double logit(final double p) {
    return Math.log(p / (1.d - p));
}

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

@Override
public Function1D<StandardOptionDataBundle, Double> getPricingFunction(
        final ForwardStartOptionDefinition definition) {
    Validate.notNull(definition, "definition");
    return new Function1D<StandardOptionDataBundle, Double>() {

        @SuppressWarnings("synthetic-access")
        @Override//ww w  . j a v  a 2  s. com
        public Double evaluate(final StandardOptionDataBundle data) {
            Validate.notNull(data, "data");
            final ZonedDateTime date = data.getDate();
            final double s = data.getSpot();
            final double t = definition.getTimeToExpiry(date);
            final double start = definition.getTimeToStart(date);
            final double b = data.getCostOfCarry();
            final double r = data.getInterestRate(t); // does this need r at both times?
            final double alpha = definition.getAlpha();
            final double sigma = data.getVolatility(t, alpha * s);
            final double deltaT = t - start;
            final double df1 = Math.exp(start * (b - r));
            final double df2 = Math.exp(deltaT * (b - r));
            final double df3 = Math.exp(-r * deltaT);
            final double sigmaT = sigma * Math.sqrt(deltaT);
            final double d1 = (Math.log(1. / alpha) + deltaT * (b + 0.5 * sigma * sigma)) / sigmaT;
            final double d2 = d1 - sigmaT;
            final int sign = definition.isCall() ? 1 : -1;
            return s * df1 * (sign * (df2 * NORMAL.getCDF(sign * d1) - alpha * df3 * NORMAL.getCDF(sign * d2)));
        }

    };
}

From source file:dr.evomodel.epidemiology.casetocase.periodpriors.OneOverStDevPeriodPriorDistribution.java

public double calculateLogLikelihood(double[] values) {

    DescriptiveStatistics stats = new DescriptiveStatistics(values);

    logL = -Math.log(stats.getStandardDeviation());

    return logL;//  w  w  w . j  ava2  s  . co m

}

From source file:com.mapr.synth.samplers.VectorSamplerTest.java

@Test
public void testVector() throws IOException {
    SchemaSampler s = new SchemaSampler(
            Resources.asCharSource(Resources.getResource("schema029.json"), Charsets.UTF_8).read());
    for (int i = 0; i < 10; i++) {
        JsonNode data = s.sample();/*from   w ww. j av  a  2  s .  c  o m*/
        /*
        {
        "class": "vector",
        "name": "prices",
        "mean": 4.65,
        "sd": 0.01,
        "length": 10000,
        "transform": "exp",
        "seed": 1,
        },
        */
        JsonNode v = data.get("prices");
        assertTrue(v.isArray());
        assertEquals(10000, v.size());
        double[] v1 = new double[10000];
        double[] v2 = new double[10000];
        for (int j = 0; j < 10000; j++) {
            v1[j] = v.get(j).asDouble();
            v2[j] = Math.log(v1[j]);
        }
        assertEquals(100, median(v1), 0.03);
        assertEquals(100, mean(v1), 0.05);
        assertEquals(Math.log(100), mean(v2), 0.001);
        assertEquals(0.01, sd(v2), 0.0003);
        assertTrue(isNormal(v2, Math.log(100), 0.01));

        /*
        {
        "class": "vector",
        "name": "zero",
        "mean": 0,
        "sd": 10,
        "length": 10000,
        "seed": 2
        },
        */
        v = data.get("zero");
        assertTrue(v.isArray());
        for (int j = 0; j < 10000; j++) {
            v1[j] = v.get(j).asDouble();
        }
        assertEquals(0, mean(v1), 0.3);
        assertEquals(10, sd(v1), 0.2);
        assertTrue(isNormal(v1, 0, 10));
        /*
        {
        "class": "vector",
        "name": "clipped",
        "mean": 0,
        "sd": 10,
        "length": 10000,
        "max": 0,
        "seed": 3
        },
        */
        v = data.get("clipped");
        assertTrue(v.isArray());
        Random rand = new Random();
        for (int j = 0; j < 10000; j++) {
            v1[j] = v.get(j).asDouble();
            assertTrue(v1[j] <= 0);
            v1[j] = v1[j] * (rand.nextBoolean() ? 1 : -1);
        }
        assertEquals(0, mean(v1), 0.3);
        assertEquals(10, sd(v1), 0.3);
        assertTrue(isNormal(v1, 0, 10));

        /*
        {
        "class": "vector",
        "name": "ten",
        "min": 1,
        "max": 10,
        "length": 20000,
        "transform": "log",
        "seed": 4
        }
        ]
                */
        v = data.get("ten");
        assertTrue(v.isArray());
        for (int j = 0; j < 10000; j++) {
            v1[j] = v.get(j).asDouble();
            v2[j] = Math.exp(v1[j]);
            assertTrue(v1[j] >= 1);
            assertTrue(v1[j] <= 10);
        }
        assertTrue(isUniform(v2, Math.exp(1), Math.exp(10)));

        v = data.get("coarse");
        assertTrue(v.isArray());
        for (int j = 0; j < 10000; j++) {
            double x = v.get(j).asDouble();
            assertTrue(x >= 1);
            assertTrue(x <= 10);
            assertEquals(Math.rint(x / 0.1) * 0.1, x, 1e-10);
        }
    }
}

From source file:de.tudarmstadt.ukp.dkpro.bigdata.collocations.AssociationMetrics.java

public double pmi() {
    return Math.log(e11 / (e12) * (e21)) / Math.log(2);
}

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

@Override
public double calcLogP(Function fun) {
    if (fun.getDimension() != 2) {
        throw new IllegalArgumentException("Argument to calcLogP has the wrong dimension (should be 2)");
    }//  w  ww. ja  v  a  2 s. c o  m

    double mu = getMu();
    double lambda = getLambda();
    double alpha = getAlpha();
    double beta = getBeta();

    double x = fun.getArrayValue(0);
    double tau = fun.getArrayValue(1);

    return alpha * Math.log(beta) + 0.5 * Math.log(lambda) + (alpha - 0.5) * Math.log(tau) - beta * tau
            - lambda * tau * Math.pow(x - mu, 2) / 2 - GammaFunction.lnGamma(alpha)
            - 0.5 * Math.log(2 * Math.PI);
}

From source file:etymology.util.EtyMath.java

public static double logPlus(double a, double b) {
    double logPlus = 0;
    double max = Math.max(a, b);
    double min = Math.min(a, b);

    logPlus = max + Math.log(1.0 + Math.exp(min - max));

    return logPlus;
}

From source file:com.exzogeni.dk.graphics.Bitmaps.java

public static int calculateInSampleSize(BitmapFactory.Options ops, int hwSize) {
    final int outHeight = ops.outHeight;
    final int outWidth = ops.outWidth;
    if (outWidth > hwSize || outHeight > hwSize) {
        final double ratio = Math.max(Math.round((double) outWidth / (double) hwSize),
                Math.round((double) outHeight / (double) hwSize));
        return ratio > 0 ? (int) Math.pow(2, Math.floor(Math.log(ratio) / LN_2)) : 1;
    }//from  w  w w .  j a  v a 2 s.c o m
    return 1;
}