package de.lmu.ifi.dbs.elki.math.statistics.distribution;

/*
 This file is part of ELKI:
 Environment for Developing KDD-Applications Supported by Index-Structures

 Copyright (C) 2015
 Ludwig-Maximilians-Universität München
 Lehr- und Forschungseinheit für Datenbanksysteme
 ELKI Development Team

 This program is free software: you can redistribute it and/or modify
 it under the terms of the GNU Affero General Public License as published by
 the Free Software Foundation, either version 3 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 Affero General Public License for more details.

 You should have received a copy of the GNU Affero General Public License
 along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

import java.util.Random;

import de.lmu.ifi.dbs.elki.math.random.RandomFactory;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter;

/**
 * Weibull distribution.
 * 
 * @author Erich Schubert
 * @since 0.6.0
 */
public class WeibullDistribution extends AbstractDistribution {
  /**
   * Shift offset.
   */
  double theta = 0.;

  /**
   * Shape parameter k.
   */
  double k;

  /**
   * Lambda parameter.
   */
  double lambda;

  /**
   * Constructor.
   * 
   * @param k Shape parameter
   * @param lambda Scale parameter
   */
  public WeibullDistribution(double k, double lambda) {
    this(k, lambda, 0.0, (Random) null);
  }

  /**
   * Constructor.
   * 
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   */
  public WeibullDistribution(double k, double lambda, double theta) {
    this(k, lambda, theta, (Random) null);
  }

  /**
   * Constructor.
   * 
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param random Random number generator
   */
  public WeibullDistribution(double k, double lambda, Random random) {
    this(k, lambda, 0., random);
  }

  /**
   * Constructor.
   * 
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   * @param random Random number generator
   */
  public WeibullDistribution(double k, double lambda, double theta, Random random) {
    super(random);
    this.k = k;
    this.lambda = lambda;
    this.theta = theta;
  }

  /**
   * Constructor.
   * 
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   * @param random Random number generator
   */
  public WeibullDistribution(double k, double lambda, double theta, RandomFactory random) {
    super(random);
    this.k = k;
    this.lambda = lambda;
    this.theta = theta;
  }

  @Override
  public double pdf(double x) {
    return pdf(x, k, lambda, theta);
  }

  /**
   * PDF of Weibull distribution
   * 
   * @param x Value
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   * @return PDF at position x.
   */
  public static double pdf(double x, double k, double lambda, double theta) {
    if (x > theta) {
      double xl = (x - theta) / lambda;
      return k / lambda * Math.pow(xl, k - 1) * Math.exp(-Math.pow(xl, k));
    } else {
      return 0.;
    }
  }

  /**
   * CDF of Weibull distribution
   * 
   * @param val Value
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   * @return CDF at position x.
   */
  public static double cdf(double val, double k, double lambda, double theta) {
    if (val > theta) {
      return 1.0 - Math.exp(-Math.pow((val - theta) / lambda, k));
    } else {
      return 0.0;
    }
  }

  @Override
  public double cdf(double val) {
    return cdf(val, k, lambda, theta);
  }

  /**
   * Quantile function of Weibull distribution
   * 
   * @param val Value
   * @param k Shape parameter
   * @param lambda Scale parameter
   * @param theta Shift offset parameter
   * @return Quantile function at position x.
   */
  public static double quantile(double val, double k, double lambda, double theta) {
    if (val < 0.0 || val > 1.0) {
      return Double.NaN;
    } else if (val == 0) {
      return 0.0;
    } else if (val == 1) {
      return Double.POSITIVE_INFINITY;
    } else {
      return theta + lambda * Math.pow(-Math.log(1.0 - val), 1.0 / k);
    }
  }

  @Override
  public double quantile(double val) {
    return quantile(val, k, lambda, theta);
  }

  @Override
  public double nextRandom() {
    return theta + lambda * Math.pow(-Math.log(1 - random.nextDouble()), 1. / k);
  }

  @Override
  public String toString() {
    return "WeibullDistribution(k=" + k + ", lambda=" + lambda + ", theta=" + theta + ")";
  }

  /**
   * Parameterization class
   * 
   * @author Erich Schubert
   * 
   * @apiviz.exclude
   */
  public static class Parameterizer extends AbstractDistribution.Parameterizer {
    /** Parameters. */
    double theta, k, lambda;

    @Override
    protected void makeOptions(Parameterization config) {
      super.makeOptions(config);

      DoubleParameter thetaP = new DoubleParameter(LOCATION_ID, 0.);
      if (config.grab(thetaP)) {
        theta = thetaP.doubleValue();
      }

      DoubleParameter lambdaP = new DoubleParameter(SCALE_ID);
      if (config.grab(lambdaP)) {
        lambda = lambdaP.doubleValue();
      }

      DoubleParameter kP = new DoubleParameter(SHAPE_ID);
      if (config.grab(kP)) {
        k = kP.doubleValue();
      }
    }

    @Override
    protected WeibullDistribution makeInstance() {
      return new WeibullDistribution(theta, k, lambda, rnd);
    }
  }
}