com.github.tommyettinger.random.distribution.DiscreteUniformDistribution Maven / Gradle / Ivy

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/*
 * Copyright (c) 2023 See AUTHORS file.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 */

package com.github.tommyettinger.random.distribution;

import com.github.tommyettinger.digital.MathTools;
import com.github.tommyettinger.random.EnhancedRandom;
import com.github.tommyettinger.random.WhiskerRandom;

/**
 * A two-parameter discrete distribution with integer range between the given parameters, both inclusive.
 * @see Wikipedia's page on this distribution.
 */
public class DiscreteUniformDistribution extends Distribution {
    public String getTag() {
        return "DiscreteUniform";
    }

    @Override
    public DiscreteUniformDistribution copy() {
        return new DiscreteUniformDistribution(generator.copy(), alpha, beta);
    }

    private int alpha;
    private int beta;

    public int getAlpha() {
        return alpha;
    }

    public int getBeta() {
        return beta;
    }

    @Override
    public double getParameterA() {
        return alpha;
    }

    @Override
    public double getParameterB() {
        return beta;
    }

    /**
     * Uses a {@link WhiskerRandom}, alpha = 0, beta = 1 .
     */
    public DiscreteUniformDistribution() {
        this(new WhiskerRandom(), 0, 1);
    }

    /**
     * Uses a {@link WhiskerRandom} and the given alpha and beta.
     */
    public DiscreteUniformDistribution(int alpha, int beta) {
        this(new WhiskerRandom(), alpha, beta);
    }

    /**
     * Uses the given EnhancedRandom directly. Uses the given alpha and beta.
     */
    public DiscreteUniformDistribution(EnhancedRandom generator, int alpha, int beta)
    {
        this.generator = generator;
        if(!setParameters(alpha, beta, 0.0))
            throw new IllegalArgumentException("Given alpha and/or beta are invalid.");
    }

    @Override
    public double getMaximum() {
        return beta;
    }

    @Override
    public double getMean() {
        return (alpha + beta) * 0.5;
    }

    @Override
    public double getMedian() {
        return (alpha + beta) * 0.5;
    }

    @Override
    public double getMinimum() {
        return alpha;
    }

    @Override
    public double[] getMode() {
        throw new UnsupportedOperationException("Mode is undefined.");
    }

    @Override
    public double getVariance() {
        return (MathTools.square(beta - alpha + 1.0) - 1.0) / 12.0;
    }
    /**
     * Sets all parameters and returns true if they are valid, otherwise leaves parameters unchanged and returns false.
     * @param a alpha; will be cast to int, and should be less than or equal to beta
     * @param b beta; will be cast to int, and should be greater than or equal to alpha
     * @param c ignored
     * @return true if the parameters given are valid and will be used
     */
    @Override
    public boolean setParameters(double a, double b, double c) {
        if((int)a <= (int)b){
            alpha = (int)a;
            beta = (int)b;
            return true;
        }
        return false;
    }

    @Override
    public double nextDouble() {
        return sample(generator, alpha, beta);
    }

    public static double sample(EnhancedRandom generator, int alpha, int beta) {
        return generator.nextLong(alpha, beta+1L);
    }
}