List of usage examples for java.lang Math sqrt
@HotSpotIntrinsicCandidate public static double sqrt(double a)
From source file:com.itemanalysis.psychometrics.rasch.ScaleQualityStatistics.java
public double adjustedStandardDeviation() { return Math.sqrt(adjustedVariance()); }
From source file:es.udc.gii.common.eaf.stoptest.cma.CMATolXStopTest.java
@Override public boolean isReach(EvolutionaryAlgorithm algorithm) { double current_tol_x, sigma, minstartsigma, maxsqrtdiagC, pc; CMAEvolutionaryAlgorithm cma = (CMAEvolutionaryAlgorithm) algorithm; minstartsigma = StatUtils.min(cma.getStartSigma()); current_tol_x = Math.max(this.tol_x, this.tol_x_factor * minstartsigma); maxsqrtdiagC = Math.sqrt(StatUtils.max(cma.diag(cma.getC()))); sigma = cma.getSigma();//from w w w .j a v a 2s. c om pc = -Double.MAX_VALUE; for (double d : cma.getPc()) { pc = Math.max(pc, Math.abs(d)); } if (sigma * maxsqrtdiagC < current_tol_x && sigma * pc < current_tol_x) { return true; } return false; }
From source file:apiserver.services.images.services.jhlabs.BumpFilterService.java
public Object doFilter(Message<?> message) throws MessageConfigException { BumpJob props = (BumpJob) message.getPayload(); int edgeAction = props.getEdgeAction(); boolean useAlpha = props.isUseAlpha(); float[] embossMatrix = props.getMatrix(); try {// w w w. j a v a 2s. c o m // calculate int rows = new Double(Math.sqrt(new Integer(embossMatrix.length).doubleValue())).intValue(); int cols = new Double(Math.sqrt(new Integer(embossMatrix.length).doubleValue())).intValue(); //run filter BumpFilter filter = new BumpFilter(); filter.setEdgeAction(edgeAction); filter.setUseAlpha(useAlpha); filter.setKernel(new Kernel(rows, cols, embossMatrix)); BufferedImage bufferedImage = props.getBufferedImage(); if (bufferedImage == null) { throw new MessageConfigException(MessageConfigException.MISSING_PROPERTY); } BufferedImage outFile = filter.filter(bufferedImage, null); props.setBufferedImage(outFile); return message; } catch (Throwable e) { //log.error(e.getMessage(), e); throw new RuntimeException(e); } }
From source file:com.opengamma.analytics.financial.model.option.pricing.analytic.GramCharlierModel.java
@Override public Function1D<SkewKurtosisOptionDataBundle, Double> getPricingFunction(final OptionDefinition definition) { Validate.notNull(definition);/* w w w.j a va 2 s . co m*/ final Function1D<SkewKurtosisOptionDataBundle, Double> pricingFunction = new Function1D<SkewKurtosisOptionDataBundle, Double>() { @SuppressWarnings("synthetic-access") @Override public Double evaluate(final SkewKurtosisOptionDataBundle 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 sigmaT = sigma * Math.sqrt(t); final double d1 = getD1(s, k, t, sigma, b); final double d2 = getD2(d1, sigma, t); final double skew = data.getAnnualizedSkew(); final double kurtosis = data.getAnnualizedPearsonKurtosis(); final double correction = sigmaT * (skew * (2 * sigmaT - d1) / (6. * Math.sqrt(t)) - kurtosis * (1 - d1 * d1 + 3 * sigmaT * (d1 - sigmaT)) / (24 * t)); final double df1 = Math.exp(-r * t); final double df2 = getDF(r, b, t); final double callPrice = s * df2 * (NORMAL.getCDF(d1) + NORMAL.getPDF(d1) * correction) - k * df1 * NORMAL.getCDF(d2); if (!definition.isCall()) { return callPrice + k * df1 - s * df2; } return callPrice; } }; return pricingFunction; }
From source file:dnimp.Statistics.java
private double studT(double t, int n) { t = Math.abs(t);// w w w . jav a 2 s . co m double th = Math.atan(t / Math.sqrt(n)); double sth = Math.sin(th); double cth = Math.cos(th); if (n == 1) return 1 - th / (Math.PI / 2.0); if (n % 2 == 1) { return 1 - (th + sth * cth * statCom(cth * cth, 2, n - 3, -1)) / (Math.PI / 2.0); } else { return 1 - sth * statCom(cth * cth, 1, n - 3, -1); } }
From source file:edu.umd.umiacs.clip.tools.math.CorrelationUtils.java
public static double pr(final double[] xUnsorted, final double[] yUnsorted) { Pair<double[], double[]> pairs = sort(xUnsorted, yUnsorted); double[] x = minMaxScale(pairs.getLeft()); double[] y = minMaxScale(pairs.getRight()); return range(1, x.length).parallel() .mapToDouble(i -> x[i] * (range(0, i).mapToDouble(j -> (x[j] - x[i]) * (y[j] - y[i])).sum()) / (Math.sqrt((range(0, i).mapToDouble(j -> Math.pow(x[j] - x[i], 2)).sum()) * (range(0, i).mapToDouble(j -> Math.pow(y[j] - y[i], 2)).sum())))) .sum() / range(1, x.length).mapToDouble(i -> x[i]).sum(); }
From source file:es.logongas.encuestas.modelo.resultados.InferenciaEstadistica.java
public InferenciaEstadistica(EstadisticaDescriptiva estadisticaDescriptiva, BigDecimal nivelConfianza, int numDecimals) { this.numDecimals = numDecimals; if (nivelConfianza.compareTo(BigDecimal.ZERO) <= 0) { throw new IllegalArgumentException("El nivelConfianza debe ser mayor que 0"); }//from w w w . j a va 2s . c o m if (nivelConfianza.compareTo(BigDecimal.ONE) >= 0) { throw new IllegalArgumentException("El nivelConfianza debe ser menor que 1"); } TDistribution tDistribution = new TDistribution(estadisticaDescriptiva.getNumMuestras() - 1); double t = tDistribution.inverseCumulativeProbability(nivelConfianza.doubleValue()); BigDecimal delta = new BigDecimal(t * (estadisticaDescriptiva.getDesviacionEstandar().doubleValue() / Math.sqrt(estadisticaDescriptiva.getNumMuestras()))); BigDecimal min = estadisticaDescriptiva.getMedia().subtract(delta).setScale(this.numDecimals, RoundingMode.HALF_UP); BigDecimal max = estadisticaDescriptiva.getMedia().add(delta).setScale(this.numDecimals, RoundingMode.HALF_UP); intervaloConfianzaMedia = new IntervaloConfianza(min, max, nivelConfianza); }
From source file:org.wallerlab.yoink.density.service.densityProperties.ReducedDensityGradientComputer.java
private double calculateRdg(double density, double gradient) { double rdg = Math.sqrt(gradient) / (Math.pow(density, 4.0 / 3)); rdg = rdg / Constants.RDG_COEFFICIENT; return rdg;//from w w w. j a v a 2 s .c o m }
From source file:Float11.java
static public double asin(double x) { if (x < -1. || x > 1.) return Double.NaN; if (x == -1.) return -Math.PI / 2; if (x == 1)/* w w w .j a v a 2 s .c om*/ return Math.PI / 2; return atan(x / Math.sqrt(1 - x * x)); }
From source file:com.opengamma.analytics.financial.model.volatility.curve.FXVannaVolgaVolatilityCurveModel.java
@Override public VolatilityCurve getCurve(final FXVannaVolgaVolatilityCurveDataBundle marketQuotes, final FXOptionDataBundle data) { Validate.notNull(marketQuotes);/* w ww. j a v a 2 s. c om*/ Validate.notNull(data); final double sigmaRR = marketQuotes.getRiskReversal(); final double sigmaATM = marketQuotes.getAtTheMoney(); final double sigmaVWB = marketQuotes.getVegaWeightedButterfly(); final double sigmaDeltaCall = sigmaVWB + sigmaATM + 0.5 * sigmaRR; final double sigmaDeltaPut = sigmaDeltaCall - sigmaRR; final double t = DateUtils.getDifferenceInYears(data.getDate(), marketQuotes.getMaturity()); if (t < 0) { throw new IllegalArgumentException("Cannot have date after time to maturity"); } final double sqrtT = Math.sqrt(t); final double s = data.getSpot(); final double rd = data.getInterestRate(t); final double rf = data.getForeignInterestRate(t); final double alpha = -NORMAL.getInverseCDF(Math.exp(rf * t) * marketQuotes.getDelta()); final double k1 = s * Math.exp(-alpha * sigmaDeltaPut * sqrtT + t * (rd - rf + 0.5 * sigmaDeltaPut * sigmaDeltaPut)); final double k2 = s * Math.exp(t * (rd - rf + 0.5 * sigmaATM * sigmaATM)); final double k3 = s * Math.exp(alpha * sigmaDeltaCall * sqrtT + t * (rd - rf + 0.5 * sigmaDeltaCall * sigmaDeltaCall)); final double lnk21 = Math.log(k2 / k1); final double lnk31 = Math.log(k3 / k1); final double lnk32 = Math.log(k3 / k2); final double sigma = sigmaATM; return new VolatilityCurve(FunctionalDoublesCurve.from(new Function1D<Double, Double>() { @SuppressWarnings("synthetic-access") @Override public Double evaluate(final Double x) { Validate.notNull(x); final double k = x; final double a1 = Math.log(k2 / k) * Math.log(k3 / k) / lnk21 / lnk31; final double a2 = Math.log(k / k1) * Math.log(k3 / k) / lnk21 / lnk32; final double a3 = Math.log(k / k1) * Math.log(k / k2) / lnk31 / lnk32; final double x1 = a1 * sigmaDeltaPut; final double x2 = a2 * sigmaATM; final double x3 = a3 * sigmaDeltaCall; final double e1 = x1 + x2 + x3 - sigma; final double d1k1 = getD1(s, k1, t, rd, rf, sigma, sqrtT); final double d1k2 = getD1(s, k2, t, rd, rf, sigma, sqrtT); final double d1k3 = getD1(s, k3, t, rd, rf, sigma, sqrtT); final double x4 = a1 * d1k1 * getD2(d1k1, sigma, sqrtT) * (sigmaDeltaPut - sigma) * (sigmaDeltaPut - sigma); final double x5 = a2 * d1k2 * getD2(d1k2, sigma, sqrtT) * (sigmaATM - sigma) * (sigmaATM - sigma); final double x6 = a3 * d1k3 * getD2(d1k3, sigma, sqrtT) * (sigmaDeltaCall - sigma) * (sigmaDeltaCall - sigma); final double e2 = x4 + x5 + x6; final double d1k = getD1(s, k, t, rd, rf, sigma, sqrtT); final double d2k = getD2(d1k, sigma, sqrtT); return sigma + (-sigma + Math.sqrt(sigma * sigma + d1k * d2k * (2 * sigma * e1 + e2))) / d1k / d2k; } })); }