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.opengamma.analytics.math.statistics.distribution.NonCentralChiSquaredDistributionTest.java

/**
 * Numbers computed from R//ww w . j a v a  2s  . c  o m
 */
@Test
public void debugTest() {
    final double dof = 3.666;
    final double nonCentrality = 75;
    final double x = 13.89;

    final NonCentralChiSquaredDistribution chiSq1 = new NonCentralChiSquaredDistribution(dof, nonCentrality);
    final double y1 = Math.log(chiSq1.getCDF(x));
    assertEquals(-15.92129, y1, 1e-5);
}

From source file:com.skratchdot.electribe.model.esx.impl.SampleTuneImpl.java

/**
 * <!-- begin-user-doc -->//from   w  w w .ja  v  a 2s .  com
 * Calculates the SampleTune value from the given sampleRate (using a
 * baseSamplingRate of 44100)
 * <p>Formula Used:</p>
 * <table>
 * <tr><td></td><td align="center">log(sampleRate/44100)</td><td></td></tr>
 * <tr><td>12 *</td><td align="center">----------------------</td><td>= SampleTune</td></tr>
 * <tr><td></td><td align="center">log(2)</td><td></td></tr>
 * </table>
 * <!-- end-user-doc -->
 * @generated NOT
 */
public float calculateSampleTuneFromSampleRate(int sampleRate) {
    float x = ((float) sampleRate) / 44100;
    float y = (float) Math.log(x);
    float z = (float) (y / Math.log(2));
    BigDecimal bd = new BigDecimal(12 * z).setScale(2, RoundingMode.HALF_EVEN);
    return bd.floatValue();
}

From source file:aliview.primer.OligoCalc.java

public static double getBaseStackingTM(String sequence, double conc_primer, double conc_salt, double conc_mg) {

    sequence = sequence.toUpperCase();/* w  w  w .  ja  v  a2  s  .  c o m*/

    // to do check only valid bases
    // to do check len > 0

    // effect on entropy by salt correction; von Ahsen et al 1999
    // Increase of stability due to presence of Mg;
    double salt_effect = conc_salt / 1000 + conc_mg / 1000 * 140;

    double h = 0;
    double s = 0;

    // effect on entropy
    s = 0.368 * (sequence.length() - 1) * Math.log(salt_effect);

    // terminal corrections. Santalucia 1998
    char firstnucleotide = sequence.charAt(0);
    if (firstnucleotide == 'G' || firstnucleotide == 'C') {
        h += 0.1;
        s += -2.8;
    }
    if (firstnucleotide == 'A' || firstnucleotide == 'T') {
        h += 2.3;
        s += 4.1;
    }
    char lastnucleotide = sequence.charAt(sequence.length() - 1);
    if (lastnucleotide == 'G' || lastnucleotide == 'C') {
        h += 0.1;
        s += -2.8;
    }
    if (lastnucleotide == 'A' || lastnucleotide == 'T') {
        h += 2.3;
        s += 4.1;
    }

    // compute new H and s based on sequence. Santalucia 1998
    for (int i = 0; i < sequence.length() - 1; i++) {
        String subSeq = sequence.substring(i, i + 2);
        h += getEnthalpy(subSeq);
        s += getEntropy(subSeq);
    }

    double tm = ((1000 * h) / (s + (1.987 * Math.log(conc_primer / 2000000000)))) - 273.15;
    //print "Tm:                 <font color=880000><b>".round($tm,1)." &deg;C</b></font>";
    //print  "\n<font color=008800>  Enthalpy: ".round($h,2)."\n  Entropy:  ".round($s,2)."</font>";
    return tm;
}

From source file:com.itemanalysis.psychometrics.polycor.PolyserialLogLikelihoodTwoStep.java

public double value(double x) {
    double z = 0.0;
    double prbZ = 0.0;
    double loglik = 0.0;
    double tauStar = 0.0;
    double tauStarM1 = 0.0;
    double dif = 0.0;

    for (int i = 0; i < dataX.length; i++) {
        z = (dataX[i] - meanX.getResult()) - sdX.getResult();
        prbZ = normal.density(z);/*from   www . j a va  2s . com*/
        tauStar = (alpha[dataY[i] - 1] - x * z) / Math.sqrt(1 - x * x);
        if (dataY[i] > 1) {
            tauStarM1 = (alpha[dataY[i] - 1] - x * z) / Math.sqrt(1 - x * x);
        } else {
            tauStarM1 = -10;//some large number greater than negative infinity
        }
        dif = normal.cumulativeProbability(tauStar) - normal.cumulativeProbability(tauStarM1);
        loglik += Math.log(prbZ * dif);
    }
    return -loglik;
}

From source file:com.analog.lyric.dimple.factorfunctions.Binomial.java

@Override
public final double evalEnergy(Value[] arguments) {
    int index = 0;
    if (!_NParameterConstant) {
        _N = arguments[index++].getInt(); // First argument is N parameter
        if (_N < 0)
            return Double.POSITIVE_INFINITY;
        _negativeLogFactorialN = -org.apache.commons.math3.special.Gamma.logGamma(_N + 1);
    }/*from   w  w w. j  av a2  s . c o  m*/

    final double p = arguments[index++].getDouble(); // Next argument is the probability parameter
    if (p < 0 || p > 1)
        return Double.POSITIVE_INFINITY;

    final int numOnes = arguments[index++].getInt(); // Next argument is the one-count
    if (numOnes < 0 || numOnes > _N)
        return Double.POSITIVE_INFINITY;
    int numZeros = _N - numOnes;

    if (p == 0)
        if (numOnes > 0)
            return Double.POSITIVE_INFINITY;
        else
            return 0;
    else if (p == 1)
        if (numZeros > 0)
            return Double.POSITIVE_INFINITY;
        else
            return 0;
    else
        return -(numOnes * Math.log(p) + numZeros * Math.log(1 - p)) + _negativeLogFactorialN
                + org.apache.commons.math3.special.Gamma.logGamma(numOnes + 1)
                + org.apache.commons.math3.special.Gamma.logGamma(numZeros + 1);
}

From source file:com.joptimizer.optimizers.NewtonLEConstrainedFSPTest.java

/**
 * Minimize x - Log[-x^2 + 1], //  w  w  w.jav  a  2 s .c o  m
 * dom f ={x | x^2<1}
 * N.B.: this simulate a centering step of the barrier method 
 * applied to the problem:
 * Minimize x
 * s.t. x^2<1
 * when t=1.
 */
public void testOptimize2() throws Exception {
    log.debug("testOptimize2");

    // START SNIPPET: NewtonLEConstrainedFSP-1

    // Objective function
    ConvexMultivariateRealFunction objectiveFunction = new ConvexMultivariateRealFunction() {

        public double value(double[] X) {
            double x = X[0];
            return x - Math.log(1 - x * x);
        }

        public double[] gradient(double[] X) {
            double x = X[0];
            return new double[] { 1 + 2 * x / (1 - x * x) };
        }

        public double[][] hessian(double[] X) {
            double x = X[0];
            return new double[][] { { 4 * Math.pow(x, 2) / Math.pow(1 - x * x, 2) + 2 / (1 - x * x) } };
        }

        public int getDim() {
            return 1;
        }
    };

    OptimizationRequest or = new OptimizationRequest();
    or.setCheckKKTSolutionAccuracy(true);
    or.setF0(objectiveFunction);
    or.setInitialPoint(new double[] { 0 });//must be feasible

    // optimization
    NewtonLEConstrainedFSP opt = new NewtonLEConstrainedFSP();
    opt.setOptimizationRequest(or);
    int returnCode = opt.optimize();

    // END SNIPPET: NewtonLEConstrainedFSP-1

    if (returnCode == OptimizationResponse.FAILED) {
        fail();
    }

    OptimizationResponse response = opt.getOptimizationResponse();
    double[] sol = response.getSolution();
    double value = objectiveFunction.value(sol);
    log.debug("sol   : " + ArrayUtils.toString(sol));
    log.debug("value : " + value);
    assertEquals(-0.41421356, sol[0], 0.0000001);//=1-Math.sqrt(2)
    assertEquals(-0.22598716, value, 0.0000001);
}

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

@Override
public JsonNode sample() {
    synchronized (this) {
        TextNode r = new TextNode(df.format(new Date((long) start)));
        start += minInterval - meanInterval * Math.log(1 - base.nextDouble());
        return r;
    }/*from ww  w.j  a  v  a 2s  . c om*/
}

From source file:edu.ucuenca.authorsrelatedness.Distance.java

public double NWD(String uri1, String end1, String uri2, String end2, String quy) throws Exception {

    List<String> prms = new ArrayList();
    prms.add(uri1 + "+" + end1);
    prms.add(uri2 + "+" + end2);

    prms.add(quy);//from w ww . j a  va2 s. c  o  m

    Collections.sort(prms);

    Double rspc = GetCacheDistance(prms.toString());
    if (rspc == null) {
        Map<String, List<String>> map = new HashMap<>();
        List<String> Authors = new ArrayList();
        Authors.add(uri1);
        Authors.add(uri2);
        List<String> Endpoints = new ArrayList();
        Endpoints.add(end1);
        Endpoints.add(end2);
        Map<String, Double> Result = new HashMap<>();
        for (int i = 0; i < Authors.size(); i++) {
            for (int j = i + 1; j < Authors.size(); j++) {
                String a1 = Authors.get(i);
                String a2 = Authors.get(j);
                List<String> ka1 = null;
                List<String> ka2 = null;
                if (map.containsKey(a1)) {
                    ka1 = map.get(a1);
                } else {
                    ka1 = consultado2(a1, Endpoints.get(i));
                    //String t1_ = traductor(Joiner.on(" | ").join(ka1)).toLowerCase();
                    ka1 = traductor(ka1);//new LinkedList<String>(java.util.Arrays.asList(t1_.split("\\s\\|\\s")));
                    ka1 = clean(ka1);
                    System.out.println(uri1 + "|E:" + Joiner.on(",").join(ka1));
                    ka1 = TopT(ka1, (int) (2.0 * Math.log(ka1.size())));
                    System.out.println(uri1 + "|F:" + Joiner.on(",").join(ka1));
                    map.put(a1, ka1);
                }

                if (map.containsKey(a2)) {
                    ka2 = map.get(a2);
                } else {
                    ka2 = consultado2(a2, Endpoints.get(j));
                    //String t2_ = traductor(Joiner.on(" | ").join(ka2)).toLowerCase();
                    ka2 = traductor(ka2);//new LinkedList<String>(java.util.Arrays.asList(t2_.split("\\s\\|\\s")));
                    ka2 = clean(ka2);
                    System.out.println(uri2 + "|E:" + Joiner.on(",").join(ka2));
                    ka2 = TopT(ka2, (int) (2.0 * Math.log(ka2.size())));
                    System.out.println(uri2 + "|F:" + Joiner.on(",").join(ka2));
                    map.put(a2, ka2);
                }
                //System.out.println(ka1.size() + "," + ka2.size());

                double sum = 0;
                double num = 0;

                for (String t1 : ka1) {
                    for (String t2 : ka2) {
                        num++;
                        String tt1 = t1;
                        String tt2 = t2;
                        double v = NGD(tt1, tt2);
                        sum += v;
                    }
                }
                double prom = sum / num;
                if (num == 0 && sum == 0) {
                    prom = 2;
                }
                Result.put(i + "," + j, prom);
            }
        }

        double r = 0;
        for (Map.Entry<String, Double> cc : Result.entrySet()) {
            r = cc.getValue();
        }
        rspc = r;
        PutCacheDistance(prms.toString(), rspc);
    }
    return rspc;
}

From source file:ml.shifu.shifu.udf.PSICalculatorUDF.java

@Override
public Tuple exec(Tuple input) throws IOException {
    if (input == null || input.size() < 2) {
        return null;
    }/*from w  w  w  . j  a v a  2 s.c om*/

    Integer columnId = (Integer) input.get(0);
    DataBag databag = (DataBag) input.get(1);

    ColumnConfig columnConfig = this.columnConfigList.get(columnId);

    List<Integer> negativeBin = columnConfig.getBinCountNeg();
    List<Integer> positiveBin = columnConfig.getBinCountPos();
    List<Double> expected = new ArrayList<Double>(negativeBin.size());
    for (int i = 0; i < columnConfig.getBinCountNeg().size(); i++) {
        if (columnConfig.getTotalCount() == 0) {
            expected.add(0D);
        } else {
            expected.add(
                    ((double) negativeBin.get(i) + (double) positiveBin.get(i)) / columnConfig.getTotalCount());
        }
    }

    Iterator<Tuple> iter = databag.iterator();
    Double psi = 0D;
    List<String> unitStats = new ArrayList<String>();

    while (iter.hasNext()) {
        Tuple tuple = iter.next();
        if (tuple != null && tuple.size() != 0) {
            String subBinStr = (String) tuple.get(1);
            String[] subBinArr = StringUtils.split(subBinStr, CalculateStatsUDF.CATEGORY_VAL_SEPARATOR);
            List<Double> subCounter = new ArrayList<Double>();
            Double total = 0D;
            for (String binningElement : subBinArr) {
                Double dVal = Double.valueOf(binningElement);
                subCounter.add(dVal);
                total += dVal;
            }

            int i = 0;
            for (Double sub : subCounter) {
                if (total == 0) {
                    continue;
                } else if (expected.get(i) == 0) {
                    continue;
                } else {
                    double logNum = (sub / total) / expected.get(i);
                    if (logNum <= 0) {
                        continue;
                    } else {
                        psi = psi + ((sub / total - expected.get(i)) * Math.log(logNum));
                    }
                }
                i++;
            }

            unitStats.add((String) tuple.get(2));
        }
    }

    // sort by unit
    Collections.sort(unitStats);

    Tuple output = TupleFactory.getInstance().newTuple(3);
    output.set(0, columnId);
    output.set(1, psi);
    output.set(2, StringUtils.join(unitStats, CalculateStatsUDF.CATEGORY_VAL_SEPARATOR));

    return output;
}

From source file:bide.math.NormalDistribution.java

public static double logPdfBT(double x, double m, double sd, double lLim, double uLim) {

    double dnorm = 0;

    try {//from   w w  w. ja va 2 s. c  o m
        double limit = Math.log(NormalDistribution.cdf(uLim, m, sd) - NormalDistribution.cdf(lLim, m, sd));

        if (x > lLim && x < uLim) {
            dnorm = NormalDistribution.logPdf(x, m, sd) - limit;
        }
    } catch (Exception e) {

        e.printStackTrace();
    }
    return dnorm;
}