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

org.apache.commons.math3.stat.Frequency
Maintains a frequency distribution.
Accepts int, long, char or Comparable values. New values added must be comparable to those that have been added, otherwise the add method will throw an IllegalArgumentException.

Integer values (int, long, Integer, Long) are not distinguished by type -- i.e. addValue(Long.valueOf(2)), addValue(2), addValue(2l) all have the same effect (similarly for arguments to getCount, etc.).

NOTE: byte and short values will be implicitly converted to int values by the compiler, thus there are no explicit overloaded methods for these primitive types.

char values are converted by addValue to Character instances. As such, these values are not comparable to integral values, so attempts to combine integral types with chars in a frequency distribution will fail.

Float is not coerced to Double. Since they are not Comparable with each other the user must do any necessary coercion. Float.NaN and Double.NaN are not treated specially; they may occur in input and will occur in output if appropriate.
The values are ordered using the default (natural order), unless a Comparator is supplied in the constructor.

            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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org.apache.commons.math3.analysis.differentiation.DerivativeStructure

org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction

org.apache.commons.math3.analysis.function.HarmonicOscillator

org.apache.commons.math3.analysis.function.Sin

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.MultivariateFunction

org.apache.commons.math3.analysis.QuinticFunction

org.apache.commons.math3.analysis.solvers.BrentSolver

org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.complex.Complex

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