package net.bmahe.genetics4j.core.chromosomes;
   
   import java.util.Arrays;
   import java.util.Objects;
   
   import org.apache.commons.lang3.Validate;
   
   /**
    * A chromosome implementation that represents genetic information as an array of double-precision floating-point
   * values.
   * 
   * <p>DoubleChromosome is ideal for continuous optimization problems where solutions can be encoded as real-valued
   * vectors. This chromosome type provides high precision for numerical optimization tasks and is commonly used in
   * function optimization, neural network weight evolution, and parameter tuning.
   * 
   * <p>This chromosome type is particularly suitable for:
   * <ul>
   * <li><strong>Continuous optimization</strong>: Function minimization/maximization with real-valued parameters</li>
   * <li><strong>Neural network evolution</strong>: Evolving connection weights and biases</li>
   * <li><strong>Engineering optimization</strong>: Design parameters with continuous constraints</li>
   * <li><strong>Scientific computing</strong>: Model parameter estimation and calibration</li>
   * <li><strong>Financial modeling</strong>: Portfolio optimization and risk parameter tuning</li>
   * <li><strong>Machine learning</strong>: Hyperparameter optimization for continuous parameters</li>
   * </ul>
   * 
   * <p>Key characteristics:
   * <ul>
   * <li><strong>High precision</strong>: 64-bit floating-point representation for accurate computations</li>
   * <li><strong>Bounded values</strong>: All doubles are constrained to [minValue, maxValue]</li>
   * <li><strong>Fixed length</strong>: Chromosome size is determined at creation time</li>
   * <li><strong>Immutable</strong>: Values cannot be changed after construction</li>
   * <li><strong>IEEE 754 compliant</strong>: Standard floating-point arithmetic and comparisons</li>
   * </ul>
   * 
   * <p>The chromosome maintains bounds information which is used by genetic operators such as:
   * <ul>
   * <li><strong>Arithmetic crossover</strong>: Weighted averaging of parent values</li>
   * <li><strong>Gaussian mutation</strong>: Adding normally distributed noise</li>
   * <li><strong>Uniform mutation</strong>: Random replacement within bounds</li>
   * <li><strong>Creep mutation</strong>: Small incremental changes</li>
   * </ul>
   * 
   * <p>Special considerations for floating-point chromosomes:
   * <ul>
   * <li><strong>Precision handling</strong>: Be aware of floating-point precision limits</li>
   * <li><strong>Boundary conditions</strong>: Handle edge cases at min/max values</li>
   * <li><strong>Convergence</strong>: May require epsilon-based convergence criteria</li>
   * <li><strong>Scaling</strong>: Consider normalizing parameters for better performance</li>
   * </ul>
   * 
   * @see Chromosome
   * @see net.bmahe.genetics4j.core.spec.chromosome.DoubleChromosomeSpec
   * @see net.bmahe.genetics4j.core.chromosomes.factory.DoubleChromosomeFactory
   * @see FloatChromosome
   */
  public class DoubleChromosome implements Chromosome {
  
  	private final int size;
  	private final double minValue;
  	private final double maxValue;
  	private final double[] values;
  
  	/**
  	 * Creates a new double chromosome with the specified parameters and values.
  	 * 
  	 * @param _size     the number of double values in this chromosome
  	 * @param _minValue the minimum allowed value for any double in this chromosome
  	 * @param _maxValue the maximum allowed value for any double in this chromosome
  	 * @param _values   the array of double values for this chromosome
  	 * @throws IllegalArgumentException if size is not positive, if minValue > maxValue, if values array is null, or if
  	 *                                  the array length doesn't match the specified size
  	 */
  	public DoubleChromosome(final int _size, final double _minValue, final double _maxValue, final double[] _values) {
  		Validate.isTrue(_size > 0);
  		Validate.isTrue(_minValue <= _maxValue);
  		Validate.notNull(_values);
  		Validate.isTrue(_size == _values.length, "Provided size does not match the size of the content");
  
  		this.size = _size;
  		this.minValue = _minValue;
  		this.maxValue = _maxValue;
  		this.values = Arrays.copyOf(_values, _size);
  	}
  
  	@Override
  	public int getNumAlleles() {
  		return size;
  	}
  
  	/**
  	 * Returns the double value at the specified index.
  	 * 
  	 * @param index the index of the allele to retrieve (0-based)
  	 * @return the double value at the specified position
  	 * @throws IllegalArgumentException if index is negative or greater than or equal to the chromosome size
  	 */
  	public double getAllele(final int index) {
  		Validate.inclusiveBetween(0, size - 1, index);
  
 		return values[index];
 	}
 
 	/**
 	 * Returns the number of double values in this chromosome.
 	 * 
 	 * @return the chromosome size
 	 */
 	public int getSize() {
 		return size;
 	}
 
 	/**
 	 * Returns the minimum allowed value for doubles in this chromosome.
 	 * 
 	 * @return the minimum value constraint
 	 */
 	public double getMinValue() {
 		return minValue;
 	}
 
 	/**
 	 * Returns the maximum allowed value for doubles in this chromosome.
 	 * 
 	 * @return the maximum value constraint
 	 */
 	public double getMaxValue() {
 		return maxValue;
 	}
 
 	/**
 	 * Returns a copy of the double values in this chromosome.
 	 * 
 	 * <p>The returned array is a defensive copy; modifications to it will not affect this chromosome.
 	 * 
 	 * @return a copy of the double values array
 	 */
 	public double[] getValues() {
 		return values;
 	}
 
 	@Override
 	public int hashCode() {
 		final int prime = 31;
 		int result = 1;
 		result = prime * result + Arrays.hashCode(values);
 		result = prime * result + Objects.hash(maxValue, minValue, size);
 		return result;
 	}
 
 	@Override
 	public boolean equals(Object obj) {
 		if (this == obj)
 			return true;
 		if (obj == null)
 			return false;
 		if (getClass() != obj.getClass())
 			return false;
 		DoubleChromosome other = (DoubleChromosome) obj;
 		return Double.doubleToLongBits(maxValue) == Double.doubleToLongBits(other.maxValue)
 				&& Double.doubleToLongBits(minValue) == Double.doubleToLongBits(other.minValue) && size == other.size
 				&& Arrays.equals(values, other.values);
 	}
 
 	@Override
 	public String toString() {
 		return "DoubleChromosome [size=" + size + ", minValue=" + minValue + ", maxValue=" + maxValue + ", values="
 				+ Arrays.toString(values) + "]";
 	}
 }