StatisticsUtilities { public static int softmax(double[] ps, double temperature) { double[] posExps = new double[ps.length]; for (int i = 0; i < posExps.length; i++) { posExps[i] = Math.exp(ps[i] / temperature); } posExps = distribution(posExps); return RandomNumbers.probabilisticSelection(posExps); }  static double percentile(final double[] values, final double p); static double median(double[] xs); static int argmax(double[] xs); static int argmax(int[] xs); @SuppressWarnings("unchecked") static int argmax(int[] xs, int rank); static int argmin(double[] xs); static int argmin(int[] xs); static int softmax(double[] ps, double temperature); static int probabilistic(double[] ps); static double[] distribution(double[] raw); static double[] distribution(int[] raw); static double mode(double[] xs); static double mode(double[] xs, double epsilon); static double maximum(double[] xs); static int maximum(Collection<Integer> xs); static long maximum(long[] xs); static double minimum(double[] xs); static double average(double[] xs); static int sum(int[] vals); static double sum(double[] vals); static int sum(Collection<Integer> xs); static double sumDouble(Collection<Double> xs); static double populationStandardDeviation(double[] xs); static double sampleStandardDeviation(double[] xs); static double populationVariance(double[] xs); static double sampleVariance(double[] xs); static double sumOfSquares(double[] xs); static double instantaneousErrorEnergy(double desired, double output); static double instantaneousTotalErrorEnergy(ArrayList<Pair<Double, Double>> pairs); static double averageSquaredErrorEnergy(ArrayList<ArrayList<Pair<Double, Double>>> samples); static double tValue(int runs);  }
@Test public void testSoftmax() { double[] test = {6}; double temp = 3; double[] test1 = {2, 2}; double temp1 = 2; assertEquals(StatisticsUtilities.softmax(test, temp), 0); int result1 = StatisticsUtilities.softmax(test1, temp1); assertFalse(result1 == 2); assertTrue(result1 == 0 || result1 == 1); }