Examples of org.apache.commons.math3.stat.Frequency$NaturalComparator

org.apache.commons.math3.stat.Frequency
A Comparator that compares comparable objects using the natural order. Copied from Commons Collections ComparableComparator.

            hexString = randomData.nextHexString(0);
            Assert.fail("zero length requested -- expecting MathIllegalArgumentException");
        } catch (MathIllegalArgumentException ex) {
            // ignored
        }
        Frequency f = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            hexString = randomData.nextHexString(100);
            if (hexString.length() != 100) {
                Assert.fail("incorrect length for generated string");
            }
            for (int j = 0; j < hexString.length(); j++) {
                f.addValue(hexString.substring(j, j + 1));
            }
        }
        double[] expected = new double[16];
        long[] observed = new long[16];
        for (int i = 0; i < 16; i++) {
            expected[i] = (double) smallSampleSize * 100 / 16;
            observed[i] = f.getCount(hex[i]);
        }
        TestUtils.assertChiSquareAccept(expected, observed, 0.001);
    }

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            hexString = randomData.nextSecureHexString(0);
            Assert.fail("zero length requested -- expecting MathIllegalArgumentException");
        } catch (MathIllegalArgumentException ex) {
            // ignored
        }
        Frequency f = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            hexString = randomData.nextSecureHexString(100);
            if (hexString.length() != 100) {
                Assert.fail("incorrect length for generated string");
            }
            for (int j = 0; j < hexString.length(); j++) {
                f.addValue(hexString.substring(j, j + 1));
            }
        }
        double[] expected = new double[16];
        long[] observed = new long[16];
        for (int i = 0; i < 16; i++) {
            expected[i] = (double) smallSampleSize * 100 / 16;
            observed[i] = f.getCount(hex[i]);
        }
        TestUtils.assertChiSquareAccept(expected, observed, 0.001);
    }

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        binBounds[0] = min + binSize;
        for (int i = 1; i < binCount - 1; i++) {
            binBounds[i] = binBounds[i - 1] + binSize;  // + instead of * to avoid overflow in extreme case
        }
        
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final double value = randomData.nextUniform(min, max);
            Assert.assertTrue("nextUniform range", (value > min) && (value < max));
            // Find bin
            int j = 0;
            while (j < binCount - 1 && value > binBounds[j]) {
                j++;
            }
            freq.addValue(j);
        }
       
        final long[] observed = new long[binCount];
        for (int i = 0; i < binCount; i++) {
            observed[i] = freq.getCount(i);
        }
        final double[] expected = new double[binCount];
        for (int i = 0; i < binCount; i++) {
            expected[i] = 1d / binCount;
        }

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    public void testNextLongDirect() {
        long q1 = Long.MAX_VALUE/4;
        long q2 = 2 *  q1;
        long q3 = 3 * q1;


        Frequency freq = new Frequency();
        long val = 0;
        int value = 0;
        for (int i=0; i<smallSampleSize; i++) {
            val = generator.nextLong();
            val = val < 0 ? -val : val;
            if (val < q1) {
                value = 0;
            } else if (val < q2) {
                value = 1;
            } else if (val < q3) {
                value = 2;
            } else {
                value = 3;
            }
            freq.addValue(value);
        }
        long[] observed = new long[4];
        for (int i=0; i<4; i++) {
            observed[i] = freq.getCount(i);
        }


        /* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
         * Change to 11.34 for alpha = .01
         */

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                testStatistic.chiSquare(expected,observed) < 10.828);
    }


    @Test
    public void testNextFloatDirect() {
        Frequency freq = new Frequency();
        float val = 0;
        int value = 0;
        for (int i=0; i<smallSampleSize; i++) {
            val = generator.nextFloat();
            if (val < 0.25) {
                value = 0;
            } else if (val < 0.5) {
                value = 1;
            } else if (val < 0.75) {
                value = 2;
            } else {
                value = 3;
            }
            freq.addValue(value);
        }
        long[] observed = new long[4];
        for (int i=0; i<4; i++) {
            observed[i] = freq.getCount(i);
        }


        /* Use ChiSquare dist with df = 4-1 = 3, alpha = .001
         * Change to 11.34 for alpha = .01
         */

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            checkNextIntUniform(Integer.MAX_VALUE - 12, Integer.MAX_VALUE - 1);
        }
    }


    private void checkNextIntUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final int value = randomData.nextInt(min, max);
            Assert.assertTrue("nextInt range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }

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            checkNextLongUniform(Long.MAX_VALUE - 12, Long.MAX_VALUE - 1);
        }
    }


    private void checkNextLongUniform(long min, long max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final long value = randomData.nextLong(min, max);
            Assert.assertTrue("nextLong range: " + value + " " + min + " " + max,
                              (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = ((int) (max - min)) + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }

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            checkNextSecureLongUniform(2, 12);
        }
    }
    
    private void checkNextSecureLongUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final long value = randomData.nextSecureLong(min, max);
            Assert.assertTrue("nextLong range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }

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            checkNextSecureIntUniform(2, 12);
        }
    }
     
    private void checkNextSecureIntUniform(int min, int max) {
        final Frequency freq = new Frequency();
        for (int i = 0; i < smallSampleSize; i++) {
            final int value = randomData.nextSecureInt(min, max);
            Assert.assertTrue("nextInt range", (value >= min) && (value <= max));
            freq.addValue(value);
        }
        final int len = max - min + 1;
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = freq.getCount(min + i);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = 1d / len;
        }

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        }
        
        final double mean = 4.0d;
        final int len = 5;
        PoissonDistribution poissonDistribution = new PoissonDistribution(mean);
        Frequency f = new Frequency();
        randomData.reSeed(1000);
        for (int i = 0; i < largeSampleSize; i++) {
            f.addValue(randomData.nextPoisson(mean));
        }
        final long[] observed = new long[len];
        for (int i = 0; i < len; i++) {
            observed[i] = f.getCount(i + 1);
        }
        final double[] expected = new double[len];
        for (int i = 0; i < len; i++) {
            expected[i] = poissonDistribution.probability(i + 1) * largeSampleSize;
        }

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