/*
 * This file is part of ADDIS (Aggregate Data Drug Information System).
 * ADDIS is distributed from http://drugis.org/.
 * Copyright © 2009 Gert van Valkenhoef, Tommi Tervonen.
 * Copyright © 2010 Gert van Valkenhoef, Tommi Tervonen, Tijs Zwinkels,
 * Maarten Jacobs, Hanno Koeslag, Florin Schimbinschi, Ahmad Kamal, Daniel
 * Reid.
 * Copyright © 2011 Gert van Valkenhoef, Ahmad Kamal, Daniel Reid, Florin
 * Schimbinschi.
 * Copyright © 2012 Gert van Valkenhoef, Daniel Reid, Joël Kuiper, Wouter
 * Reckman.
 * Copyright © 2013 Gert van Valkenhoef, Joël Kuiper.
 *
 * 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 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 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 <http://www.gnu.org/licenses/>.
 */

package org.drugis.addis.entities.relativeeffect;

import org.apache.commons.math3.distribution.NormalDistribution;
import org.drugis.common.beans.AbstractObservable;

public abstract class GaussianBase extends AbstractObservable implements Distribution {
	private double d_mu;
	private double d_sigma;
	private NormalDistribution d_dist;

	public GaussianBase(double mu, double sigma) {
		if (Double.isNaN(mu)) throw new IllegalArgumentException("mu may not be NaN");
		if (Double.isNaN(sigma)) throw new IllegalArgumentException("sigma may not be NaN");
		if (sigma < 0.0) throw new IllegalArgumentException("sigma must be >= 0.0");
		d_mu = mu;
		d_sigma = sigma;
		if (getSigma() != 0.0) {
			d_dist = new NormalDistribution(d_mu, d_sigma);
		}
	}

	protected double calculateQuantile(double p) {
		if (getSigma() == 0.0) {
			return getMu();
		}
		return d_dist.inverseCumulativeProbability(p);
	}

	protected double calculateCumulativeProbability(double x) {
		return d_dist.cumulativeProbability(x);
	}
	
	public double getSigma() {
		return d_sigma;
	}

	public double getMu() {
		return d_mu;
	}

	public GaussianBase plus(GaussianBase other) {
		if (!canEqual(other)) throw new IllegalArgumentException(
				"Cannot add together " + getClass().getSimpleName() +
				" and " + other.getClass().getSimpleName());
		return newInstance(getMu() + other.getMu(), 
				Math.sqrt(getSigma() * getSigma() + other.getSigma() * other.getSigma()));
	}

	protected abstract GaussianBase newInstance(double mu, double sigma);

	abstract protected boolean canEqual(GaussianBase other);
	
	@Override
	public boolean equals(Object obj) {
		if (obj instanceof GaussianBase) {
			GaussianBase other = (GaussianBase) obj;
			return canEqual(other) && d_mu == other.d_mu && d_sigma == other.d_sigma;
		}
		return false;
	}
	
	@Override
	public int hashCode() {
		return ((Double)d_mu).hashCode() + 31 * ((Double)d_sigma).hashCode();
	}
	
	@Override
	public String toString() {
		return getClass().getSimpleName() + "(mu=" + getMu() + ", sigma=" + getSigma() + ")";
	}
}