/*
 * This file is part of Jstacs.
 * 
 * Jstacs 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.
 * 
 * Jstacs 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
 * Jstacs. If not, see <http://www.gnu.org/licenses/>.
 * 
 * For more information on Jstacs, visit http://www.jstacs.de
 */

package de.jstacs.utils.random;

import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;

/**
 * Class for generating random numbers of many different distributions.<br>
 * <br>
 * 
 * This class was written by Sundar Dorai-Raj and was downloaded from <a
 * href="http://www.stat.vt.edu/~sundar/java/"
 * >http://www.stat.vt.edu/~sundar/java/</a>. Only a few modifications were made
 * by Jens Keilwagen eliminating some not used variables and making the comments
 * visible for javadoc.<br>
 * <br>
 * 
 * RandomNumberGenerator.java Copyright (c) 2000 by Sundar Dorai-Raj<br>
 * <br>
 * 
 * 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, provided that any use properly credits the author.<br>
 * <br>
 * 
 * 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
 * at <a href="http://www.gnu.org">http://www.gnu.org</a><br>
 * <br>
 * 
 * Reference. M. Matsumoto and T. Nishimura, "Mersenne Twister: A
 * 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator",
 * ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1, January
 * 1998, pp 3--30.
 * 
 * @author Sundar Dorai-Raj Email: <a
 *         href="mailto:sdoraira@vt.edu">sdoraira@vt.edu</a>
 */

public class RandomNumberGenerator implements java.io.Serializable {

	static final long serialVersionUID = 3905348978240129619L;

	// Period parameters
	private static final int N = 624;

	private static final int M = 397;

	private static final int MATRIX_A = 0x9908b0df;

	private static final int UPPER_MASK = 0x80000000;

	private static final int LOWER_MASK = 0x7fffffff;

	// Tempering parameters
	private static final int TEMPERING_MASK_B = 0x9d2c5680;

	private static final int TEMPERING_MASK_C = 0xefc60000;

	private int mt[]; // the array for the state vector

	private int mti; // mti==N+1 means mt[N] is not initialized

	private int mag01[];

	private synchronized void writeObject( ObjectOutputStream out ) throws IOException {
		// just so we're synchronized.
		out.defaultWriteObject();
	}

	private synchronized void readObject( ObjectInputStream in ) throws IOException, ClassNotFoundException {
		// just so we're synchronized.
		in.defaultReadObject();
	}

	protected synchronized void setSeed( long seed ) {
		haveNextGaussian = false;

		mt = new int[N];

		// setting initial seeds to mt[N] using
		// the generator Line 25 of Table 1 in
		// [KNUTH 1981, The Art of Computer Programming
		// Vol. 2 (2nd Ed.), pp102]

		// the 0xffffffff is commented out because in Java
		// ints are always 32 bits; hence i & 0xffffffff == i

		mt[0] = ( (int)seed ); // & 0xffffffff;

		for( mti = 1; mti < N; mti++ )
			mt[mti] = ( 69069 * mt[mti - 1] );

		// mag01[x] = x * MATRIX_A for x=0,1
		mag01 = new int[2];
		mag01[0] = 0x0;
		mag01[1] = MATRIX_A;
	}

	protected synchronized int next( int bits ) {
		int y;

		if( mti >= N ) {
			int kk;
			for( kk = 0; kk < N - M; kk++ ) {
				y = ( mt[kk] & UPPER_MASK ) | ( mt[kk + 1] & LOWER_MASK );
				mt[kk] = mt[kk + M] ^ ( y >>> 1 ) ^ mag01[y & 0x1];
			}
			for( ; kk < N - 1; kk++ ) {
				y = ( mt[kk] & UPPER_MASK ) | ( mt[kk + 1] & LOWER_MASK );
				mt[kk] = mt[kk + ( M - N )] ^ ( y >>> 1 ) ^ mag01[y & 0x1];
			}
			y = ( mt[N - 1] & UPPER_MASK ) | ( mt[0] & LOWER_MASK );
			mt[N - 1] = mt[M - 1] ^ ( y >>> 1 ) ^ mag01[y & 0x1];
			mti = 0;
		}
		y = mt[mti++];
		y ^= y >>> 11;
		y ^= ( y << 7 ) & TEMPERING_MASK_B;
		y ^= ( y << 15 ) & TEMPERING_MASK_C;
		y ^= ( y >>> 18 );
		return y >>> ( 32 - bits );
	}

	public RandomNumberGenerator() {
		this( System.currentTimeMillis() );
	}

	public RandomNumberGenerator( long seed ) {
		setSeed( seed );
	}

	/**
	 * generates an integer between 0 and 2^32
	 */
	public synchronized int nextInt() {
		return next( 32 );
	}

	/**
	 * generates an integer between 0 and n-1 (inclusive)
	 */
	public synchronized int nextInt( int n ) {
		if( n <= 0 ) throw new IllegalArgumentException( "n must be positive" );
		if( ( n & -n ) == n ) {
			// i.e., n is a power of 2
			return (int)( ( n * (long)next( 31 ) ) >> 31 );
		}
		int bits, val;
		do {
			bits = next( 31 );
			val = bits % n;
		} while( bits - val + ( n - 1 ) < 0 );
		return val;
	}

	/**
	 * generates a random number from Poisson(lambda) (E(X)=lambda ;
	 * Var(X)=lambda)
	 */
	public synchronized int nextPoisson( double lambda ) {
		int v = -1;
		double l = Math.exp( -lambda ), p;
		p = 1.0;
		while( p >= l ) {
			p *= nextUniform();
			v++;
		}
		return v;
	}

	/**
	 * generates a random number from Poisson(1) (E(X)=1 ; Var(X)=1)
	 */
	public synchronized int nextPoisson() {
		return nextPoisson( 1 );
	}

	/**
	 * generates a random boolean variable
	 */
	public synchronized boolean nextBoolean() {
		return ( next( 32 ) & 1 << 15 ) != 0;
	}

	/**
	 * generates true with probability p
	 */
	public synchronized boolean nextBoolean( double p ) {
		double u = nextUniform();
		if( u < p ) return true;
		return false;
	}

	/**
	 * generates a random number from U(0,1) (E(X)=1/2 ; Var(X)=1/12)
	 */
	public synchronized double nextUniform() {
		long l = ( (long)( next( 26 ) ) << 27 ) + next( 27 );
		return l / (double)( 1L << 53 );
	}

	/**
	 * generates a random number from U(a,b) (E(X)=(b-a)/2 ; Var(X)=(b-a)^2/12)
	 */
	public synchronized double nextUniform( double a, double b ) {
		return a + ( b - a ) * nextUniform();
	}

	private double nextGaussian;

	private boolean haveNextGaussian = false;

	/**
	 * generates a random number from N(0,1) (E(X)=0 ; Var(X)=1)
	 */
	public synchronized double nextGaussian() {
		if( !haveNextGaussian ) {
			double v1 = nextUniform(), v2 = nextUniform();
			double x1, x2;
			x1 = Math.sqrt( -2 * Math.log( v1 ) ) * Math.cos( 2 * Math.PI * v2 );
			x2 = Math.sqrt( -2 * Math.log( v1 ) ) * Math.sin( 2 * Math.PI * v2 );
			nextGaussian = x2;
			haveNextGaussian = true;
			return x1;
		} else {
			haveNextGaussian = false;
			return nextGaussian;
		}
	}

	/**
	 * generates a random number from N(m,s2) (E(X)=m ; Var(X)=s2)
	 */
	public synchronized double nextGaussian( double m, double s2 ) {
		return nextGaussian() * Math.sqrt( s2 ) + m;
	}

	/**
	 * generates a random number from Gamma(1,1) (E(X)=1 ; Var(X)=1)
	 */
	public synchronized double nextGamma() {
		return nextGamma( 1, 1, 0 );
	}

	/**
	 * generates a random number from Gamma(alpha,beta) (E(X)=alpha*beta ;
	 * Var(X)=alpha*beta^2)
	 */
	public synchronized double nextGamma( double alpha, double beta ) {
		return nextGamma( alpha, beta, 0 );
	}

	/**
	 * generates a random number from shifted-Gamma(alpha,beta)
	 * (E(X)=alpha*beta+lambda ; Var(X)=alpha*beta^2)
	 */
	public synchronized double nextGamma( double alpha, double beta, double lambda ) {
		double gamma = 0;
		if( alpha <= 0 || beta <= 0 ) throw new IllegalArgumentException( "alpha and beta must be strictly positive." );
		if( alpha < 1 ) {
			double b, p;
			boolean flag = false;
			b = 1 + alpha * Math.exp( -1 );
			while( !flag ) {
				p = b * nextUniform();
				if( p > 1 ) {
					gamma = -Math.log( ( b - p ) / alpha );
					if( nextUniform() <= Math.pow( gamma, alpha - 1 ) ) flag = true;
				} else {
					gamma = Math.pow( p, 1 / alpha );
					if( nextUniform() <= Math.exp( -gamma ) ) flag = true;
				}
			}
		} else if( alpha == 1 ) gamma = -Math.log( nextUniform() );
		else {
			double y = -Math.log( nextUniform() );
			while( nextUniform() > Math.pow( y * Math.exp( 1 - y ), alpha - 1 ) )
				y = -Math.log( nextUniform() );
			gamma = alpha * y;
		}
		return beta * gamma + lambda;
	}

	/**
	 * generates a random number from Exp(1) (E(X)=1 ; Var(X)=1)
	 */
	public synchronized double nextExp() {
		return nextGamma( 1, 1, 0 );
	}

	/**
	 * generates a random number from Exp(beta) (E(X)=beta ; Var(X)=beta^2)
	 */
	public synchronized double nextExp( double beta ) {
		return nextGamma( 1, beta, 0 );
	}

	/**
	 * generates a random number from shifted-Exp(beta) (E(X)=beta+lambda ;
	 * Var(X)=beta^2)
	 */
	public synchronized double nextExp( double beta, double lambda ) {
		return nextGamma( 1, beta, lambda );
	}

	/**
	 * generates a random number from ChiSq(1) (E(X)=1 ; Var(X)=2)
	 */
	public synchronized double nextChiSq() {
		return nextGamma( 0.5, 2, 0 );
	}

	/**
	 * generates a random number from ChiSq(df) (E(X)=df ; Var(X)=2*df)
	 */
	public synchronized double nextChiSq( int df ) {
		return nextGamma( 0.5 * (double)df, 2, 0 );
	}

	/**
	 * generates a random number from shifted-ChiSq(df) (E(X)=df+lambda ;
	 * Var(X)=2*df)
	 */
	public synchronized double nextChiSq( int df, double lambda ) {
		return nextGamma( 0.5 * (double)df, 2, lambda );
	}

	/**
	 * generates a random number from Beta(alpha,beta) (E(X)=a/(a+b) ;
	 * Var(X)=ab/[(a+b+1)(a+b)^2])
	 */
	public synchronized double nextBeta( double alpha, double beta ) {
		if( alpha <= 0 || beta <= 0 ) throw new IllegalArgumentException( "alpha and beta must be strictly positive." );
		if( alpha == 1 && beta == 1 ) return nextUniform();
		else if( alpha >= 1 && beta >= 1 ) {
			double A = alpha - 1, B = beta - 1, C = A + B, L = C * Math.log( C ), mu = A / C, sigma = 0.5 / Math.sqrt( C );
			double y = nextGaussian(), x = sigma * y + mu;
			while( x < 0 || x > 1 ) {
				y = nextGaussian();
				x = sigma * y + mu;
			}
			double u = nextUniform();
			while( Math.log( u ) >= A * Math.log( x / A ) + B * Math.log( ( 1 - x ) / B ) + L + 0.5 * y * y ) {
				y = nextGaussian();
				x = sigma * y + mu;
				while( x < 0 || x > 1 ) {
					y = nextGaussian();
					x = sigma * y + mu;
				}
				u = nextUniform();
			}
			return x;
		} else {
			double v1 = Math.pow( nextUniform(), 1 / alpha ), v2 = Math.pow( nextUniform(), 1 / beta );
			while( v1 + v2 > 1 ) {
				v1 = Math.pow( nextUniform(), 1 / alpha );
				v2 = Math.pow( nextUniform(), 1 / beta );
			}
			return v1 / ( v1 + v2 );
		}
	}
}
