/// <summary>
/// Initializes a new instance of the <see cref="DoubleArrayChromosome"/> class.
/// </summary>
///
/// <param name="source">Source chromosome to copy.</param>
///
/// <remarks><para>This is a copy constructor, which creates the exact copy
/// of specified chromosome.</para></remarks>
///
public StockTraderChromosome(StockTraderChromosome source)
{
//this.chromosomeGenerator = source.chromosomeGenerator;
this.mutationMultiplierGenerator = source.mutationMultiplierGenerator;
this.mutationAdditionGenerator = source.mutationAdditionGenerator;
this.length = source.length;
this.fitness = source.fitness;
this.mutationBalancer = source.mutationBalancer;
this.crossoverBalancer = source.crossoverBalancer;
// copy genes
val = (double[])source.val.Clone( );
}
/// <summary>
/// Crossover operator.
/// </summary>
///
/// <param name="pair">Pair chromosome to crossover with.</param>
///
/// <remarks><para>The method performs crossover between two chromosomes, selecting
/// randomly the exact type of crossover to perform, which depends on <see cref="CrossoverBalancer"/>.
/// Before crossover is done a random number is generated in [0, 1] range - if the
/// random number is smaller than <see cref="CrossoverBalancer"/>, then the first crossover
/// type is used, otherwise second type is used.</para>
///
/// <para>The <b>first crossover type</b> is based on interchanging
/// range of genes (array elements) between these chromosomes and is known
/// as one point crossover. A crossover point is selected randomly and chromosomes
/// interchange genes, which start from the selected point.</para>
///
/// <para>The <b>second crossover type</b> is aimed to produce one child, which genes'
/// values are between corresponding genes of parents, and another child, which genes'
/// values are outside of the range formed by corresponding genes of parents.
/// Let take, for example, two genes with 1.0 and 3.0 valueû (of course chromosomes have
/// more genes, but for simplicity lets think about one). First of all we randomly choose
/// a factor in the [0, 1] range, let's take 0.4. Then, for each pair of genes (we have
/// one pair) we calculate difference value, which is 2.0 in our case. In the result we’ll
/// have two children – one between and one outside of the range formed by parents genes' values.
/// We may have 1.8 and 3.8 children, or we may have 0.2 and 2.2 children. As we can see
/// we add/subtract (chosen randomly) <i>difference * factor</i>. So, this gives us exploration
/// in between and in near outside. The randomly chosen factor is applied to all genes
/// of the chromosomes participating in crossover.</para>
/// </remarks>
///
public override void Crossover(IChromosome pair)
{
StockTraderChromosome p = (StockTraderChromosome)pair;
// check for correct pair
if ((p != null) && (p.length == length))
{
if (rand.NextDouble( ) < crossoverBalancer)
{
// crossover point
int crossOverPoint = rand.Next(length - 1) + 1;
// length of chromosome to be crossed
int crossOverLength = length - crossOverPoint;
// temporary array
double[] temp = new double[crossOverLength];
// copy part of first (this) chromosome to temp
Array.Copy(val, crossOverPoint, temp, 0, crossOverLength);
// copy part of second (pair) chromosome to the first
Array.Copy(p.val, crossOverPoint, val, crossOverPoint, crossOverLength);
// copy temp to the second
Array.Copy(temp, 0, p.val, crossOverPoint, crossOverLength);
//custom range checking
//for (int i = 0; i < length; i++)
//{
// val[i] = CheckValueRange(val[i], i);
//}
}
//else
//{
// double[] pairVal = p.val;
// double factor = rand.NextDouble( );
// if ( rand.Next( 2 ) == 0 )
// factor = -factor;
// for ( int i = 0; i < length; i++ )
// {
// double portion = ( val[i] - pairVal[i] ) * factor;
// val[i] -= portion;
// pairVal[i] += portion;
// }
//}
}
}