List of usage examples for java.lang Math log
@HotSpotIntrinsicCandidate public static double log(double a)
From source file:com.opengamma.analytics.financial.model.stochastic.BlackScholesGeometricBrownianMotionProcess.java
@Override public Double getInitialValue(final T t, final U u) { return Math.log(u.getSpot()); }
From source file:com.uber.hoodie.common.BloomFilter.java
/** * Create a new Bloom filter with the given configurations. *//*from w w w. j a v a2 s .c o m*/ public BloomFilter(int numEntries, double errorRate, int hashType) { // Bit size int bitSize = (int) Math.ceil(numEntries * (-Math.log(errorRate) / LOG2_SQUARED)); // Number of the hash functions int numHashs = (int) Math.ceil(Math.log(2) * bitSize / numEntries); // The filter this.filter = new org.apache.hadoop.util.bloom.BloomFilter(bitSize, numHashs, hashType); }
From source file:es.udc.gii.common.eaf.benchmark.constrained_real_param.g14.G14ObjectiveFunction.java
@Override public double evaluate(double[] values) { double sum, fitness = 0.0; double[] norm_values; double[] c = { -6.089, -17.164, -34.054, -5.914, -24.721, -14.986, -24.1, -10.708, -26.662, -22.179 }; norm_values = G14Function.normalize(values); sum = StatUtils.sum(norm_values);// ww w . j a v a 2 s.c o m for (int i = 0; i < 10; i++) { fitness += norm_values[i] * (c[i] + Math.log(norm_values[i] / sum)); } return fitness; }
From source file:org.wallerlab.yoink.density.service.densityProperties.SingleExponentialDecayDetectorComputer.java
/** * calculate SEDD of a denstiy point//from w ww . j a v a 2 s . c o m * * @param densityPoint * -{@link org.wallerlab.yoink.api.model.density.DensityPoint} * @param seddValue * pre-calculated * @return seddValue final-calculated */ protected double getSilvaValue(DensityPoint densityPoint, double seddValue) { double density = densityPoint.getDensity(); seddValue *= (4.0 / Math.pow(density, 8)); seddValue = Math.log((1.0 + seddValue)); return seddValue; }
From source file:bide.prior.PriorBeta.java
public static double pdf(double x, double alpha, double beta) { double z = recomputeZ(alpha, beta); double logX = Math.log(x); double log1mX = Math.log1p(-x); return Math.exp((alpha - 1) * logX + (beta - 1) * log1mX - z); }
From source file:com.opengamma.analytics.math.interpolation.ExponentialInterpolator1D.java
@Override public double firstDerivative(final Interpolator1DDataBundle data, final Double value) { Validate.notNull(value, "value"); Validate.notNull(data, "data bundle"); final Double x1 = data.getLowerBoundKey(value); final Double y1 = data.get(x1); if (data.getLowerBoundIndex(value) == data.size() - 1) { return 0.; }//from ww w .j av a2s .com final Double x2 = data.higherKey(x1); final Double y2 = data.get(x2); final double xDiff = x2 - x1; return Math.pow(y1, value * (x2 - value) / xDiff / x1) * Math.pow(y2, value * (value - x1) / xDiff / x2) * (Math.log(y1) * (x2 - 2. * value) / x1 + Math.log(y2) * (2. * value - x1) / x2) / xDiff; }
From source file:gr.eap.LSHDB.HammingKey.java
@Override public int optimizeL() { L = (int) Math.ceil(Math.log(delta) / Math.log(1 - Math.pow((1.0 - (t * 1.0 / this.size)), k))); return L;/*from w ww . jav a 2 s . co m*/ }
From source file:com.cloudera.oryx.rdf.common.information.Information.java
/** * @param counts counts of distinct categories in a sample * @return entropy, in nats, of those counts *///from www. j a v a 2 s. com public static double entropy(int[] counts) { // Entropy is really, over all counts: // sum (-p_i * ln p_i) // where p_i = count_i / total // terms where count is 0 or 1 are 0, so can go away // Here we actually compute total as we go and account for it later, which avoids // a second loop and avoids some divisions. // This means we divide by total at the end to account for the missing denominator in the first p_i term, // and end up adding (subtracting negative) ln total at the end to account for ln p_i. double entropy = 0.0; int total = 0; for (int count : counts) { // if count = 0 or count = 1 then count*ln(count) = 0 if (count > 1) { // This is in nats to match differential entropy -- base e, not 2 entropy -= count * Math.log(count); } total += count; } return entropy / total + Math.log(total); }
From source file:Methods.CalculusSecant.java
public static void secant2(double xold1, double xold2, double decPoint) {//method used calculate root point acording the paramethers that enter the method and store the data in a global Stack double xnew, fxold1, fxold2, fxnew, diff; int iteration = 0; S = new BidimensionalArrayStack();//Declaring a new Stack beeing sure is clear before using it Xold1 = new BidimensionalArrayStack(); Xold2 = new BidimensionalArrayStack(); do {// w w w . j a va 2 s . c o m iteration += 1; // determine f(xold1) and f(xold2) fxold1 = (Math.log(xold1 + 1.0)) + 1.0; fxold2 = (Math.log(xold2 + 1.0)) + 1.0; Xold1.push(xold1, fxold1);//Inserting data in the Stack Xold2.push(xold2, fxold2); xnew = xold1 - (fxold1 * (xold1 - xold2)) / (fxold1 - fxold2); System.out.println("Approx for iteration{}" + iteration + " is " + xnew); diff = Math.abs(xnew - xold1); xold2 = xold1; xold1 = xnew; fxnew = (Math.log(xnew + 1.0)) + 1.0; S.push(xnew, fxnew); } while (diff > decPoint); System.out.println("root to six decimal places is " + xnew); }
From source file:ch.unil.genescore.vegas.DistributionMethods.java
public static double normalCumulativeProbabilityUpperTailApprox(double q) { q = Math.abs(q);/*w w w. ja v a 2s .c o m*/ double aa = -(q * q) / 2 - Math.log(q) - 0.5 * Math.log(2 * Math.PI); return (Math.exp(aa)); }