List of usage examples for java.lang Math pow
@HotSpotIntrinsicCandidate public static double pow(double a, double b)
From source file:k_means.Kmeans.java
public void calDist() { double distance = 0; double minimum = 0; int cluster = 0; double bignum = Math.pow(10, 10); for (int i = 0; i < dataSet.size(); i++) { minimum = bignum;/*from w w w. j a v a 2 s. c om*/ for (int j = 0; j < k; j++) { distance = Distance.EDistance(dataSet.get(i), centroids.get(j)); if (distance < minimum) { minimum = distance; cluster = j; } dataSet.get(i).setCluster(cluster); } } }
From source file:com.cloudera.hts.utils.math.MyFunc2.java
public double value(double t, double... parameters) { return parameters[0] * Math.pow(t, parameters[1]) * Math.exp(-parameters[2] * t); }
From source file:me.datamining.bandwidth.ScottsRule.java
public double bandWidth(double variance, int dimensions, long number) { double pow = -1.0 / (dimensions + 4); return variance * Math.pow(number, pow); }
From source file:de.termininistic.serein.examples.benchmarks.functions.multimodal.StyblinskiTangFunction.java
@Override public double map(RealVector v) { double[] x = v.toArray(); int n = x.length; double sum = 0.0; for (int i = 0; i < n; i++) { sum += Math.pow(x[i], 4) - 16 * x[i] * x[i] + 5 * x[i]; }/* ww w . j a v a 2 s. c o m*/ return 0.5 * sum; }
From source file:es.udc.gii.common.eaf.benchmark.constrained_real_param.g03.G03ObjectiveFunction.java
@Override public double evaluate(double[] values) { double[] norm_values; norm_values = G03Function.normalize(values); return -Math.pow(Math.sqrt(norm_values.length), norm_values.length) * StatUtils.product(norm_values); }
From source file:Main.java
/** * Creates an approximated cubic gradient using a multi-stop linear gradient. See * <a href="https://plus.google.com/+RomanNurik/posts/2QvHVFWrHZf">this post</a> for more * details./*ww w. j a v a 2s . co m*/ */ public static Drawable makeCubicGradientScrimDrawable(int baseColor, int numStops, int gravity) { // Generate a cache key by hashing together the inputs, based on the method described in the Effective Java book int cacheKeyHash = baseColor; cacheKeyHash = 31 * cacheKeyHash + numStops; cacheKeyHash = 31 * cacheKeyHash + gravity; Drawable cachedGradient = cubicGradientScrimCache.get(cacheKeyHash); if (cachedGradient != null) { return cachedGradient; } numStops = Math.max(numStops, 2); PaintDrawable paintDrawable = new PaintDrawable(); paintDrawable.setShape(new RectShape()); final int[] stopColors = new int[numStops]; int red = Color.red(baseColor); int green = Color.green(baseColor); int blue = Color.blue(baseColor); int alpha = Color.alpha(baseColor); for (int i = 0; i < numStops; i++) { float x = i * 1f / (numStops - 1); float opacity = constrain(0, 1, (float) Math.pow(x, 3)); stopColors[i] = Color.argb((int) (alpha * opacity), red, green, blue); } final float x0, x1, y0, y1; switch (gravity & Gravity.HORIZONTAL_GRAVITY_MASK) { case Gravity.LEFT: x0 = 1; x1 = 0; break; case Gravity.RIGHT: x0 = 0; x1 = 1; break; default: x0 = 0; x1 = 0; break; } switch (gravity & Gravity.VERTICAL_GRAVITY_MASK) { case Gravity.TOP: y0 = 1; y1 = 0; break; case Gravity.BOTTOM: y0 = 0; y1 = 1; break; default: y0 = 0; y1 = 0; break; } paintDrawable.setShaderFactory(new ShapeDrawable.ShaderFactory() { @Override public Shader resize(int width, int height) { return new LinearGradient(width * x0, height * y0, width * x1, height * y1, stopColors, null, Shader.TileMode.CLAMP); } }); cubicGradientScrimCache.put(cacheKeyHash, paintDrawable); return paintDrawable; }
From source file:beast.math.distributions.NegativeBinomialDistribution.java
public double logPdf(double x) { if (x < 0) return Double.NEGATIVE_INFINITY; double r = -1 * (mean * mean) / (mean - stdev * stdev); double p = mean / (stdev * stdev); return Math.log(Math.pow(1 - p, x)) + Math.log(Math.pow(p, r)) + GammaFunction.lnGamma(r + x) - GammaFunction.lnGamma(r) - GammaFunction.lnGamma(x + 1); }
From source file:com.opengamma.analytics.math.statistics.descriptive.SampleCentralMomentCalculator.java
/** * @param x The array of data, not null. Must contain at least two data points. * @return The sample central moment./*from ww w .j av a2s. co m*/ */ @Override public Double evaluate(final double[] x) { Validate.notNull(x, "x"); Validate.isTrue(x.length >= 2, "Need at least 2 data points to calculate central moment"); if (_n == 0) { return 1.; } final double mu = MEAN.evaluate(x); double sum = 0; for (final Double d : x) { sum += Math.pow(d - mu, _n); } return sum / (x.length - 1); }
From source file:de.termininistic.serein.examples.benchmarks.functions.unimodal.DixonPriceFunction.java
@Override public RealVector getOptimum(int dimension) { double[] optimum = new double[dimension]; for (int i = 0; i < optimum.length; i++) { optimum[i] = Math.pow(2, -((Math.pow(2, i) - 2 / Math.pow(2, i)))); }/*www . ja v a2s . c o m*/ return new ArrayRealVector(optimum); }
From source file:net.bither.util.ChartsUtil.java
public static List<IStickEntity> formatJsonArray(MarketType marketType, KlineTimeType klineTimeType, JSONArray jsonArray) throws JSONException { double rate = ExchangeUtil.getRate(marketType); List<IStickEntity> ohlc = new ArrayList<IStickEntity>(); for (int i = jsonArray.length() - 1; i >= 0; i--) { JSONArray tickerArray = jsonArray.getJSONArray(i); long time = tickerArray.getLong(0) * 1000; Date date = new Date(time); String title = DateTimeUtil.getXTitle(klineTimeType, date); double open = tickerArray.getDouble(1) / 100 * rate; double high = tickerArray.getDouble(2) / 100 * rate; double low = tickerArray.getDouble(3) / 100 * rate; double close = tickerArray.getDouble(4) / 100 * rate; double volume = tickerArray.getDouble(5) / Math.pow(10, 8); if (volume == 0) { if (i == 0) { continue; } else { BitherOHLCEntity bitherOHLCEntity = (BitherOHLCEntity) ohlc.get(i - 1); open = bitherOHLCEntity.getOpen(); high = bitherOHLCEntity.getHigh(); low = bitherOHLCEntity.getLow(); close = bitherOHLCEntity.getClose(); }//from www .j av a2 s . com } BitherOHLCEntity bitherOHLCEntity = new BitherOHLCEntity(open, high, low, close, volume, title, time); ohlc.add(bitherOHLCEntity); } return ohlc; }