Java Code Examples for org.apache.commons.math3.exception.util.LocalizedFormats#NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE

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Example 1
Source File: IntervalUtils.java    From astor with GNU General Public License v2.0 6 votes vote down vote up 
/**
 * Verifies that parameters satisfy preconditions.
 *
 * @param numberOfTrials number of trials (must be positive)
 * @param numberOfSuccesses number of successes (must not exceed numberOfTrials)
 * @param confidenceLevel confidence level (must be strictly between 0 and 1)
 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
 */
static void checkParameters(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) {
    if (numberOfTrials <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, numberOfTrials);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NEGATIVE_NUMBER_OF_SUCCESSES, numberOfSuccesses);
    }
    if (numberOfSuccesses > numberOfTrials) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, numberOfTrials, true);
    }
    if (confidenceLevel <= 0 || confidenceLevel >= 1) {
        throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUNDS_CONFIDENCE_LEVEL,
                                      confidenceLevel, 0, 1);
    }
}
Example 2
Source File: IntervalUtils.java    From astor with GNU General Public License v2.0 6 votes vote down vote up 
/**
 * Verifies that parameters satisfy preconditions.
 *
 * @param numberOfTrials number of trials (must be positive)
 * @param numberOfSuccesses number of successes (must not exceed numberOfTrials)
 * @param confidenceLevel confidence level (must be strictly between 0 and 1)
 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
 */
static void checkParameters(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) {
    if (numberOfTrials <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, numberOfTrials);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NEGATIVE_NUMBER_OF_SUCCESSES, numberOfSuccesses);
    }
    if (numberOfSuccesses > numberOfTrials) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, numberOfTrials, true);
    }
    if (confidenceLevel <= 0 || confidenceLevel >= 1) {
        throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUNDS_CONFIDENCE_LEVEL,
                                      confidenceLevel, 0, 1);
    }
}
Example 3
Source File: Cardumen_00162_t.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 4
Source File: Cardumen_00162_s.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 5
Source File: Cardumen_0036_s.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 6
Source File: Cardumen_0036_t.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 7
Source File: Math_2_HypergeometricDistribution_t.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 8
Source File: Math_2_HypergeometricDistribution_s.java    From coming with MIT License 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 9
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 10
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 11
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 12
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 13
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Construct a new hypergeometric distribution with the specified population
 * size, number of successes in the population, and sample size.
 *
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 */
public HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 14
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 15
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}
Example 16
Source File: HypergeometricDistribution.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * Creates a new hypergeometric distribution.
 *
 * @param rng Random number generator.
 * @param populationSize Population size.
 * @param numberOfSuccesses Number of successes in the population.
 * @param sampleSize Sample size.
 * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @since 3.1
 */
public HypergeometricDistribution(RandomGenerator rng,
                                  int populationSize,
                                  int numberOfSuccesses,
                                  int sampleSize)
throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
    super(rng);

    if (populationSize <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.POPULATION_SIZE,
                                               populationSize);
    }
    if (numberOfSuccesses < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SUCCESSES,
                                       numberOfSuccesses);
    }
    if (sampleSize < 0) {
        throw new NotPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,
                                       sampleSize);
    }

    if (numberOfSuccesses > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                            numberOfSuccesses, populationSize, true);
    }
    if (sampleSize > populationSize) {
        throw new NumberIsTooLargeException(LocalizedFormats.SAMPLE_SIZE_LARGER_THAN_POPULATION_SIZE,
                                            sampleSize, populationSize, true);
    }

    this.numberOfSuccesses = numberOfSuccesses;
    this.populationSize = populationSize;
    this.sampleSize = sampleSize;
}