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package com.softwaremagico.tm.random.selectors;

import java.util.Random;
import java.util.Set;

/*-
 * #%L
 * Think Machine (Core)
 * %%
 * Copyright (C) 2017 - 2018 Softwaremagico
 * %%
 * This software is designed by Jorge Hortelano Otero. Jorge Hortelano Otero
 *  Valencia (Spain).
 *
 * This program is free software; you can redistribute it and/or modify it under
 * the terms of the GNU General Public License as published by the Free Software
 * Foundation; either version 2 of the License, or (at your option) any later
 * version.
 *
 * This program is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 * FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
 * details.
 *
 * You should have received a copy of the GNU General Public License along with
 * this program; If not, see .
 * #L%
 */

public enum SpecializationPreferences implements ICharacterCreationPreference, IGaussianDistribution {

    // Gaussian distribution.
    VERY_GENERALIZED(1, 6, 1, 4),

    GENERALIZED(1, 7, 2, 4),

    FAIR(2, 8, 3, 3),

    SPECIALIZED(2, 9, 4, 3),

    VERY_SPECIALIZED(4, 10, 7, 3),

    ANY(1, 10, 5, 5);

    private final int minimum;
    private final int maximum;
    private final int mean;
    private final int variance;
    private final Random random = new Random();

    SpecializationPreferences(int minimumValue, int maximumValue, int mean, int variance) {
        this.maximum = maximumValue;
        this.minimum = minimumValue;
        this.variance = variance;
        this.mean = mean;
    }

    @Override
    public int maximum() {
        return maximum;
    }

    @Override
    public int minimum() {
        return minimum;
    }

    @Override
    public int variance() {
        return variance;
    }

    @Override
    public int mean() {
        return mean;
    }

    public static SpecializationPreferences getSelected(Set> preferences) {
        for (final IRandomPreference preference : preferences) {
            if (preference instanceof SpecializationPreferences) {
                return (SpecializationPreferences) preference;
            }
        }
        return FAIR;
    }

    @Override
    public int randomGaussian() {
        int selectedValue;
        do {
            selectedValue = (int) (random.nextGaussian() * Math.sqrt(variance) + mean);
        } while (selectedValue < minimum() || selectedValue > maximum());
        return selectedValue;
    }

    @Override
    public IRandomPreference getDefault() {
        return getDefaultOption();
    }

    public static SpecializationPreferences getDefaultOption() {
        return null;
    }

}




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