/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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.apache.commons.math.random;

import org.apache.commons.math.MathRuntimeException;

/**
 * Abstract class implementing the {@link RandomGenerator} interface. Default
 * implementations for all methods other than {@link #nextDouble()} and
 * {@link #setSeed(long)} are provided.
 * <p>
 * All data generation methods are based on <code>nextDouble().</code> Concrete
 * implementations <strong>must</strong> override this method and
 * <strong>should</strong> provide better / more performant implementations of
 * the other methods if the underlying PRNG supplies them.
 * </p>
 *
 * @since 1.1
 * @version $Revision$ $Date$
 */
public abstract class AbstractRandomGenerator implements RandomGenerator {

	/**
	 * Cached random normal value. The default implementation for
	 * {@link #nextGaussian} generates pairs of values and this field caches the
	 * second value so that the full algorithm is not executed for every
	 * activation. The value <code>Double.NaN</code> signals that there is no
	 * cached value. Use {@link #clear} to clear the cached value.
	 */
	private double cachedNormalDeviate = Double.NaN;

	/**
	 * Construct a RandomGenerator.
	 */
	public AbstractRandomGenerator() {
		super();

	}

	/**
	 * Clears the cache used by the default implementation of
	 * {@link #nextGaussian}. Implemementations that do not override the default
	 * implementation of <code>nextGaussian</code> should call this method in
	 * the implementation of {@link #setSeed(long)}
	 */
	public void clear() {
		cachedNormalDeviate = Double.NaN;
	}

	/**
	 * Sets the seed of the underyling random number generator using a
	 * <code>long</code> seed. Sequences of values generated starting with the
	 * same seeds should be identical.
	 * <p>
	 * Implementations that do not override the default implementation of
	 * <code>nextGaussian</code> should include a call to {@link #clear} in the
	 * implementation of this method.
	 * </p>
	 *
	 * @param seed
	 *            the seed value
	 */
	public abstract void setSeed(long seed);

	/**
	 * Generates random bytes and places them into a user-supplied byte array.
	 * The number of random bytes produced is equal to the length of the byte
	 * array.
	 * <p>
	 * The default implementation fills the array with bytes extracted from
	 * random integers generated using {@link #nextInt}.
	 * </p>
	 * 
	 * @param bytes
	 *            the non-null byte array in which to put the random bytes
	 */
	public void nextBytes(byte[] bytes) {
		int bytesOut = 0;
		while (bytesOut < bytes.length) {
			int randInt = nextInt();
			for (int i = 0; i < 3; i++) {
				if (i > 0) {
					randInt = randInt >> 8;
				}
				bytes[bytesOut++] = (byte) randInt;
				if (bytesOut == bytes.length) {
					return;
				}
			}
		}
	}

	/**
	 * Returns the next pseudorandom, uniformly distributed <code>int</code>
	 * value from this random number generator's sequence. All
	 * 2<font size="-1"><sup>32</sup></font> possible <tt>int</tt> values should
	 * be produced with (approximately) equal probability.
	 * <p>
	 * The default implementation provided here returns
	 * 
	 * <pre>
	 * <code>(int) (nextDouble() * Integer.MAX_VALUE)</code>
	 * </pre>
	 * </p>
	 *
	 * @return the next pseudorandom, uniformly distributed <code>int</code>
	 *         value from this random number generator's sequence
	 */
	public int nextInt() {
		return (int) (nextDouble() * Integer.MAX_VALUE);
	}

	/**
	 * Returns a pseudorandom, uniformly distributed <tt>int</tt> value between
	 * 0 (inclusive) and the specified value (exclusive), drawn from this random
	 * number generator's sequence.
	 * <p>
	 * The default implementation returns
	 * 
	 * <pre>
	 * <code>(int) (nextDouble() * n</code>
	 * </pre>
	 * </p>
	 *
	 * @param n
	 *            the bound on the random number to be returned. Must be
	 *            positive.
	 * @return a pseudorandom, uniformly distributed <tt>int</tt> value between
	 *         0 (inclusive) and n (exclusive).
	 * @throws IllegalArgumentException
	 *             if n is not positive.
	 */
	public int nextInt(int n) {
		if (n <= 0) {
			throw MathRuntimeException.createIllegalArgumentException("upper bound must be positive ({0})", n);
		}
		int result = (int) (nextDouble() * n);
		return result < n ? result : n - 1;
	}

	/**
	 * Returns the next pseudorandom, uniformly distributed <code>long</code>
	 * value from this random number generator's sequence. All
	 * 2<font size="-1"><sup>64</sup></font> possible <tt>long</tt> values
	 * should be produced with (approximately) equal probability.
	 * <p>
	 * The default implementation returns
	 * 
	 * <pre>
	 * <code>(long) (nextDouble() * Long.MAX_VALUE)</code>
	 * </pre>
	 * </p>
	 *
	 * @return the next pseudorandom, uniformly distributed <code>long</code>
	 *         value from this random number generator's sequence
	 */
	public long nextLong() {
		return (long) (nextDouble() * Long.MAX_VALUE);
	}

	/**
	 * Returns the next pseudorandom, uniformly distributed <code>boolean</code>
	 * value from this random number generator's sequence.
	 * <p>
	 * The default implementation returns
	 * 
	 * <pre>
	 * <code>nextDouble() <= 0.5</code>
	 * </pre>
	 * </p>
	 * 
	 * @return the next pseudorandom, uniformly distributed <code>boolean</code>
	 *         value from this random number generator's sequence
	 */
	public boolean nextBoolean() {
		return nextDouble() <= 0.5;
	}

	/**
	 * Returns the next pseudorandom, uniformly distributed <code>float</code>
	 * value between <code>0.0</code> and <code>1.0</code> from this random
	 * number generator's sequence.
	 * <p>
	 * The default implementation returns
	 * 
	 * <pre>
	 * <code>(float) nextDouble() </code>
	 * </pre>
	 * </p>
	 *
	 * @return the next pseudorandom, uniformly distributed <code>float</code>
	 *         value between <code>0.0</code> and <code>1.0</code> from this
	 *         random number generator's sequence
	 */
	public float nextFloat() {
		return (float) nextDouble();
	}

	/**
	 * Returns the next pseudorandom, uniformly distributed <code>double</code>
	 * value between <code>0.0</code> and <code>1.0</code> from this random
	 * number generator's sequence.
	 * <p>
	 * This method provides the underlying source of random data used by the
	 * other methods.
	 * </p>
	 *
	 * @return the next pseudorandom, uniformly distributed <code>double</code>
	 *         value between <code>0.0</code> and <code>1.0</code> from this
	 *         random number generator's sequence
	 */
	public abstract double nextDouble();

	/**
	 * Returns the next pseudorandom, Gaussian ("normally") distributed
	 * <code>double</code> value with mean <code>0.0</code> and standard
	 * deviation <code>1.0</code> from this random number generator's sequence.
	 * <p>
	 * The default implementation uses the <em>Polar Method</em> due to G.E.P.
	 * Box, M.E. Muller and G. Marsaglia, as described in D. Knuth, <u>The Art
	 * of Computer Programming</u>, 3.4.1C.
	 * </p>
	 * <p>
	 * The algorithm generates a pair of independent random values. One of these
	 * is cached for reuse, so the full algorithm is not executed on each
	 * activation. Implementations that do not override this method should make
	 * sure to call {@link #clear} to clear the cached value in the
	 * implementation of {@link #setSeed(long)}.
	 * </p>
	 * 
	 * @return the next pseudorandom, Gaussian ("normally") distributed
	 *         <code>double</code> value with mean <code>0.0</code> and standard
	 *         deviation <code>1.0</code> from this random number generator's
	 *         sequence
	 */
	public double nextGaussian() {
		if (!Double.isNaN(cachedNormalDeviate)) {
			double dev = cachedNormalDeviate;
			cachedNormalDeviate = Double.NaN;
			return dev;
		}
		double v1 = 0;
		double v2 = 0;
		double s = 1;
		while (s >= 1) {
			v1 = 2 * nextDouble() - 1;
			v2 = 2 * nextDouble() - 1;
			s = v1 * v1 + v2 * v2;
		}
		if (s != 0) {
			s = Math.sqrt(-2 * Math.log(s) / s);
		}
		cachedNormalDeviate = v2 * s;
		return v1 * s;
	}
}
