/*
 * $Id$
 * This file is a part of the Arakhne Foundation Classes, http://www.arakhne.org/afc
 *
 * Copyright (c) 2000-2012 Stephane GALLAND.
 * Copyright (c) 2005-10, Multiagent Team, Laboratoire Systemes et Transports,
 *                        Universite de Technologie de Belfort-Montbeliard.
 * Copyright (c) 2013-2016 The original authors, and other authors.
 *
 * 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 org.arakhne.afc.math.stochastic;

import java.util.Map;
import java.util.Random;

import org.eclipse.xtext.xbase.lib.Pure;

/**
 * Law that representes a logistic density.
 *
 * <p>Reference:
 * <a href="http://en.wikipedia.org/wiki/Logistic_distribution">Logistic Distribution</a>.
 *
 * <p>This class uses the uniform random number distribution provided by {@link Random}.
 *
 * @author $Author: cbohrhauer$
 * @version $FullVersion$
 * @mavengroupid $GroupId$
 * @mavenartifactid $ArtifactId$
 * @since 13.0
 */
public class LogisticStochasticLaw extends StochasticLaw {

    private final double mu;

    private final double scale;

    /**
     * Construct a law with the following parameters.
     * <ul>
     * <li><code>mu</code></li>
     * <li><code>scale</code></li>
     * </ul>
     *
     * @param parameters is the set of accepted paramters.
     * @throws LawParameterNotFoundException if the list of parameters does not permits to create the law.
     * @throws OutsideDomainException when scale is negative.
     */
    public LogisticStochasticLaw(Map<String, String> parameters) throws OutsideDomainException, LawParameterNotFoundException {
        this.mu = paramFloat("mu", parameters); //$NON-NLS-1$
        this.scale = paramFloat("scale", parameters); //$NON-NLS-1$
        if (this.scale <= 0) {
            throw new OutsideDomainException(this.scale);
        }
    }

    /**
     * @param mu1 is the location of the distribution
     * @param scale is the scale of the distristibution ({@code >0})
     * @throws OutsideDomainException when scale is negative.
     */
    public LogisticStochasticLaw(double mu1, double scale) throws OutsideDomainException {
        if (scale <= 0) {
            throw new OutsideDomainException(scale);
        }
        this.mu = mu1;
        this.scale = scale;
    }

    /** Replies a random value that respect
     * the current stochastic law.
     *
     * @param mu is the location of the distribution
     * @param scale is the scale of the distristibution ({@code >0})
     * @return a value depending of the stochastic law parameters
     * @throws MathException when error in math definition.
     */
    @Pure
    public static double random(double mu, double scale) throws MathException {
        return StochasticGenerator.generateRandomValue(new LogisticStochasticLaw(mu, scale));
    }

    @Pure
    @Override
    public String toString() {
        final StringBuilder b = new StringBuilder();
        b.append("LOGISTIC(mu="); //$NON-NLS-1$
        b.append(this.mu);
        b.append(", scale="); //$NON-NLS-1$
        b.append(this.scale);
        b.append(')');
        return b.toString();
    }

    @Pure
    @Override
    public double f(double x)  throws MathException {
        final double ex = Math.exp((this.mu - x) / this.scale);
        final double denom = (1. + ex) * (1. + ex);
        return ex / (this.scale * denom);
    }

    @Pure
    @Override
    public MathFunctionRange[] getRange() {
        return MathFunctionRange.createInfinitySet();
    }

    /** Replies the x according to the value of the distribution function.
     *
     * @param u is a value given by the uniform random variable generator {@code U(0, 1)}.
     * @return {@code F<sup>-1</sup>(u)}
     * @throws MathException in case {@code F<sup>-1</sup>(u)} could not be computed
     */
    @Pure
    @Override
    public double inverseF(double u) throws MathException {
        return this.mu + this.scale * Math.log(u / (1. - u));
    }

}