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package org.apache.commons.math3.stat.interval;

import org.apache.commons.math3.exception.NotPositiveException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NumberIsTooLargeException;
import org.apache.commons.math3.exception.OutOfRangeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;

Factory methods to generate confidence intervals for a binomial proportion.
The supported methods are:

Agresti-Coull interval
Clopper-Pearson method (exact method)
Normal approximation (based on central limit theorem)
Wilson score interval

Since:
3.3/**
 * Factory methods to generate confidence intervals for a binomial proportion.
 * The supported methods are:
 * <ul>
 * <li>Agresti-Coull interval</li>
 * <li>Clopper-Pearson method (exact method)</li>
 * <li>Normal approximation (based on central limit theorem)</li>
 * <li>Wilson score interval</li>
 * </ul>
 *
 * @since 3.3
 */
public final class IntervalUtils {

    
Singleton Agresti-Coull instance. /** Singleton Agresti-Coull instance. */
    private static final BinomialConfidenceInterval AGRESTI_COULL = new AgrestiCoullInterval();

    
Singleton Clopper-Pearson instance. /** Singleton Clopper-Pearson instance. */
    private static final BinomialConfidenceInterval CLOPPER_PEARSON = new ClopperPearsonInterval();

    
Singleton NormalApproximation instance. /** Singleton NormalApproximation instance. */
    private static final BinomialConfidenceInterval NORMAL_APPROXIMATION = new NormalApproximationInterval();

    
Singleton Wilson score instance. /** Singleton Wilson score instance. */
    private static final BinomialConfidenceInterval WILSON_SCORE = new WilsonScoreInterval();

    
Prevent instantiation.
/**
     * Prevent instantiation.
     */
    private IntervalUtils() {
    }

    
Create an Agresti-Coull binomial confidence interval for the true
probability of success of an unknown binomial distribution with the given
observed number of trials, successes and confidence level.
Params:
numberOfTrials – number of trials
numberOfSuccesses – number of successes
confidenceLevel – desired probability that the true probability of
       success falls within the returned interval
Throws:
NotStrictlyPositiveException – if numberOfTrials <= 0.
NotPositiveException – if numberOfSuccesses < 0.
NumberIsTooLargeException – if numberOfSuccesses > numberOfTrials.
OutOfRangeException – if confidenceLevel is not in the interval (0, 1).
Returns:
Confidence interval containing the probability of success with probability confidenceLevel/**
     * Create an Agresti-Coull binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @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)}.
     */
    public static ConfidenceInterval getAgrestiCoullInterval(int numberOfTrials, int numberOfSuccesses,
                                                             double confidenceLevel) {
        return AGRESTI_COULL.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    
Create a Clopper-Pearson binomial confidence interval for the true
probability of success of an unknown binomial distribution with the given
observed number of trials, successes and confidence level.

Preconditions:

numberOfTrials must be positive
numberOfSuccesses may not exceed numberOfTrials
confidenceLevel must be strictly between 0 and 1 (exclusive)


Params:
numberOfTrials – number of trials
numberOfSuccesses – number of successes
confidenceLevel – desired probability that the true probability of
       success falls within the returned interval
Throws:
NotStrictlyPositiveException – if numberOfTrials <= 0.
NotPositiveException – if numberOfSuccesses < 0.
NumberIsTooLargeException – if numberOfSuccesses > numberOfTrials.
OutOfRangeException – if confidenceLevel is not in the interval (0, 1).
Returns:
Confidence interval containing the probability of success with probability confidenceLevel/**
     * Create a Clopper-Pearson binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     * <p>
     * Preconditions:
     * <ul>
     * <li>{@code numberOfTrials} must be positive</li>
     * <li>{@code numberOfSuccesses} may not exceed {@code numberOfTrials}</li>
     * <li>{@code confidenceLevel} must be strictly between 0 and 1 (exclusive)</li>
     * </ul>
     * </p>
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @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)}.
     */
    public static ConfidenceInterval getClopperPearsonInterval(int numberOfTrials, int numberOfSuccesses,
                                                               double confidenceLevel) {
        return CLOPPER_PEARSON.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    
Create a binomial confidence interval for the true probability of success
of an unknown binomial distribution with the given observed number of
trials, successes and confidence level using the Normal approximation to
the binomial distribution.
Params:
numberOfTrials – number of trials
numberOfSuccesses – number of successes
confidenceLevel – desired probability that the true probability of
       success falls within the interval
Returns:
Confidence interval containing the probability of success with probability confidenceLevel/**
     * Create a binomial confidence interval for the true probability of success
     * of an unknown binomial distribution with the given observed number of
     * trials, successes and confidence level using the Normal approximation to
     * the binomial distribution.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     */
    public static ConfidenceInterval getNormalApproximationInterval(int numberOfTrials, int numberOfSuccesses,
                                                                    double confidenceLevel) {
        return NORMAL_APPROXIMATION.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    
Create a Wilson score binomial confidence interval for the true
probability of success of an unknown binomial distribution with the given
observed number of trials, successes and confidence level.
Params:
numberOfTrials – number of trials
numberOfSuccesses – number of successes
confidenceLevel – desired probability that the true probability of
       success falls within the returned interval
Throws:
NotStrictlyPositiveException – if numberOfTrials <= 0.
NotPositiveException – if numberOfSuccesses < 0.
NumberIsTooLargeException – if numberOfSuccesses > numberOfTrials.
OutOfRangeException – if confidenceLevel is not in the interval (0, 1).
Returns:
Confidence interval containing the probability of success with probability confidenceLevel/**
     * Create a Wilson score binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @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)}.
     */
    public static ConfidenceInterval getWilsonScoreInterval(int numberOfTrials, int numberOfSuccesses,
                                                            double confidenceLevel) {
        return WILSON_SCORE.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    
Verifies that parameters satisfy preconditions.
Params:
numberOfTrials – number of trials (must be positive)
numberOfSuccesses – number of successes (must not exceed numberOfTrials)
confidenceLevel – confidence level (must be strictly between 0 and 1)
Throws:
NotStrictlyPositiveException – if numberOfTrials <= 0.
NotPositiveException – if numberOfSuccesses < 0.
NumberIsTooLargeException – if numberOfSuccesses > numberOfTrials.
OutOfRangeException – if confidenceLevel is not in the interval (0, 1)./**
     * 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);
        }
    }

}