/// <summary>
/// Generate chromosome's subtree of specified level.
/// </summary>
///
/// <param name="node">Sub tree's node to generate.</param>
/// <param name="level">Sub tree's level to generate.</param>
///
protected void Generate(GPTreeNode node, int level)
{
// create gene for the node
if (level == 0)
{
// the gene should be an argument
node.Gene = root.Gene.CreateNew(GPGeneType.Argument);
}
else
{
// the gene can be function or argument
node.Gene = root.Gene.CreateNew();
}
// add children
if (node.Gene.ArgumentsCount != 0)
{
node.Children = new List <GPTreeNode>();
for (var i = 0; i < node.Gene.ArgumentsCount; i++)
{
// create new child
var child = new GPTreeNode();
Generate(child, level - 1);
// add the new child
node.Children.Add(child);
}
}
}
/// <summary>
/// Get tree representation of the chromosome.
/// </summary>
///
/// <returns>Returns expression's tree represented by the chromosome.</returns>
///
/// <remarks><para>The method builds expression's tree for the native linear representation
/// of the GEP chromosome.</para></remarks>
///
protected GPTreeNode GetTree( )
{
// function node queue. the queue contains function node,
// which requires children. when a function node receives
// all children, it will be removed from the queue
Queue functionNodes = new Queue( );
// create root node
GPTreeNode root = new GPTreeNode(genes[0]);
// check children amount of the root node
if (root.Gene.ArgumentsCount != 0)
{
root.Children = new List <GPTreeNode>( );
// place the root to the queue
functionNodes.Enqueue(root);
// go through genes
for (int i = 1; i < length; i++)
{
// create new node
GPTreeNode node = new GPTreeNode(genes[i]);
// if next gene represents function, place it to the queue
if (genes[i].GeneType == GPGeneType.Function)
{
node.Children = new List <GPTreeNode>( );
functionNodes.Enqueue(node);
}
// get function node from the top of the queue
GPTreeNode parent = (GPTreeNode)functionNodes.Peek( );
// add new node to children of the parent node
parent.Children.Add(node);
// remove the parent node from the queue, if it is
// already complete
if (parent.Children.Count == parent.Gene.ArgumentsCount)
{
functionNodes.Dequeue( );
// check the queue if it is empty
if (functionNodes.Count == 0)
{
break;
}
}
}
}
// return formed tree
return(root);
}
/// <summary>
/// Generate random chromosome value.
/// </summary>
///
/// <remarks><para>Regenerates chromosome's value using random number generator.</para>
/// </remarks>
///
public override void Generate()
{
// randomize the root
root.Gene.Generate();
// create children
if (root.Gene.ArgumentsCount != 0)
{
root.Children = new List <GPTreeNode>();
for (var i = 0; i < root.Gene.ArgumentsCount; i++)
{
// create new child
var child = new GPTreeNode();
Generate(child, rand.Next(maxInitialLevel));
// add the new child
root.Children.Add(child);
}
}
}
/// <summary>
/// Clone the tree node.
/// </summary>
///
/// <returns>Returns exact clone of the node.</returns>
///
public object Clone( )
{
GPTreeNode clone = new GPTreeNode( );
// clone gene
clone.Gene = this.Gene.Clone( );
// clone its children
if (this.Children != null)
{
clone.Children = new List <GPTreeNode>( );
// clone each child gene
foreach (GPTreeNode node in Children)
{
clone.Children.Add((GPTreeNode)node.Clone( ));
}
}
return(clone);
}
/// <summary>
/// Clone the tree node.
/// </summary>
///
/// <returns>Returns exact clone of the node.</returns>
///
public object Clone( )
{
GPTreeNode clone = new GPTreeNode( );
// clone gene
clone.Gene = this.Gene.Clone( );
// clone its children
if ( this.Children != null )
{
clone.Children = new List<GPTreeNode>( );
// clone each child gene
foreach ( GPTreeNode node in Children )
{
clone.Children.Add( (GPTreeNode) node.Clone( ) );
}
}
return clone;
}
/// <summary>
/// Crossover operator.
/// </summary>
///
/// <param name="pair">Pair chromosome to crossover with.</param>
///
/// <remarks><para>The method performs crossover between two chromosomes – interchanging
/// randomly selected sub trees.</para></remarks>
///
public override void Crossover(IChromosome pair)
{
var p = (GPTreeChromosome)pair;
// check for correct pair
if (p != null)
{
// do we need to use root node for crossover ?
if ((root.Children == null) || (rand.Next(maxLevel) == 0))
{
// give the root to the pair and use pair's part as a new root
root = p.RandomSwap(root);
}
else
{
var node = root;
for (; ;)
{
// choose random child
var r = rand.Next(node.Gene.ArgumentsCount);
var child = node.Children[r];
// swap the random node, if it is an end node or
// random generator "selected" this node
if ((child.Children == null) || (rand.Next(maxLevel) == 0))
{
// swap the node with pair's one
node.Children[r] = p.RandomSwap(child);
break;
}
// go further by tree
node = child;
}
}
// trim both of them
Trim(root, maxLevel);
Trim(p.root, maxLevel);
}
}
/// <summary>
/// Trim tree node, so its depth does not exceed specified level.
/// </summary>
private static void Trim(GPTreeNode node, int level)
{
// check if the node has children
if (node.Children != null)
{
if (level == 0)
{
// remove all children
node.Children = null;
// and make the node of argument type
node.Gene.Generate(GPGeneType.Argument);
}
else
{
// go further to children
foreach (var n in node.Children)
{
Trim(n, level - 1);
}
}
}
}
/// <summary>
/// Crossover helper routine - selects random node of chromosomes tree and
/// swaps it with specified node.
/// </summary>
private GPTreeNode RandomSwap(GPTreeNode source)
{
GPTreeNode retNode = null;
// swap root node ?
if ((root.Children == null) || (rand.Next(maxLevel) == 0))
{
// replace current root and return it
retNode = root;
root = source;
}
else
{
var node = root;
for (; ;)
{
// choose random child
var r = rand.Next(node.Gene.ArgumentsCount);
var child = node.Children[r];
// swap the random node, if it is an end node or
// random generator "selected" this node
if ((child.Children == null) || (rand.Next(maxLevel) == 0))
{
// swap the node with pair's one
retNode = child;
node.Children[r] = source;
break;
}
// go further by tree
node = child;
}
}
return(retNode);
}
/// <summary>
/// Trim tree node, so its depth does not exceed specified level.
/// </summary>
private static void Trim( GPTreeNode node, int level )
{
// check if the node has children
if ( node.Children != null )
{
if ( level == 0 )
{
// remove all children
node.Children = null;
// and make the node of argument type
node.Gene.Generate( GPGeneType.Argument );
}
else
{
// go further to children
foreach ( GPTreeNode n in node.Children )
{
Trim( n, level - 1 );
}
}
}
}
/// <summary>
/// Mutation operator.
/// </summary>
///
/// <remarks><para>The method performs chromosome's mutation by regenerating tree's
/// randomly selected node.</para></remarks>
///
public override void Mutate()
{
// current tree level
var currentLevel = 0;
// current node
var node = root;
for (; ;)
{
// regenerate node if it does not have children
if (node.Children == null)
{
if (currentLevel == maxLevel)
{
// we reached maximum possible level, so the gene
// can be an argument only
node.Gene.Generate(GPGeneType.Argument);
}
else
{
// generate subtree
Generate(node, rand.Next(maxLevel - currentLevel));
}
break;
}
// if it is a function node, than we need to get a decision, about
// mutation point - the node itself or one of its children
var r = rand.Next(node.Gene.ArgumentsCount + 1);
if (r == node.Gene.ArgumentsCount)
{
// node itself should be regenerated
node.Gene.Generate();
// check current type
if (node.Gene.GeneType == GPGeneType.Argument)
{
node.Children = null;
}
else
{
// create children's list if it was absent
if (node.Children == null)
{
node.Children = new List <GPTreeNode>();
}
// check for missing or extra children
if (node.Children.Count != node.Gene.ArgumentsCount)
{
if (node.Children.Count > node.Gene.ArgumentsCount)
{
// remove extra children
node.Children.RemoveRange(node.Gene.ArgumentsCount, node.Children.Count - node.Gene.ArgumentsCount);
}
else
{
// add missing children
for (var i = node.Children.Count; i < node.Gene.ArgumentsCount; i++)
{
// create new child
var child = new GPTreeNode();
Generate(child, rand.Next(maxLevel - currentLevel));
// add the new child
node.Children.Add(child);
}
}
}
}
break;
}
// mutation goes further to one of the children
node = node.Children[r];
currentLevel++;
}
}
/// <summary>
/// Get tree representation of the chromosome.
/// </summary>
///
/// <returns>Returns expression's tree represented by the chromosome.</returns>
///
/// <remarks><para>The method builds expression's tree for the native linear representation
/// of the GEP chromosome.</para></remarks>
///
protected GPTreeNode GetTree( )
{
// function node queue. the queue contains function node,
// which requires children. when a function node receives
// all children, it will be removed from the queue
Queue<GPTreeNode> functionNodes = new Queue<GPTreeNode>();
// create root node
GPTreeNode root = new GPTreeNode(genes[0]);
// check children amount of the root node
if ( root.Gene.ArgumentsCount != 0 )
{
root.Children = new List<GPTreeNode>( );
// place the root to the queue
functionNodes.Enqueue( root );
// go through genes
for ( int i = 1; i < length; i++ )
{
// create new node
GPTreeNode node = new GPTreeNode( genes[i] );
// if next gene represents function, place it to the queue
if ( genes[i].GeneType == GPGeneType.Function )
{
node.Children = new List<GPTreeNode>( );
functionNodes.Enqueue( node );
}
// get function node from the top of the queue
GPTreeNode parent = (GPTreeNode) functionNodes.Peek( );
// add new node to children of the parent node
parent.Children.Add( node );
// remove the parent node from the queue, if it is
// already complete
if ( parent.Children.Count == parent.Gene.ArgumentsCount )
{
functionNodes.Dequeue( );
// check the queue if it is empty
if ( functionNodes.Count == 0 )
break;
}
}
}
// return formed tree
return root;
}
/// <summary>
/// Generate random chromosome value.
/// </summary>
///
/// <remarks><para>Regenerates chromosome's value using random number generator.</para>
/// </remarks>
///
public override void Generate( )
{
// randomize the root
root.Gene.Generate( );
// create children
if ( root.Gene.ArgumentsCount != 0 )
{
root.Children = new List<GPTreeNode>( );
for ( int i = 0; i < root.Gene.ArgumentsCount; i++ )
{
// create new child
GPTreeNode child = new GPTreeNode( );
Generate( child, rand.Next( maxInitialLevel ) );
// add the new child
root.Children.Add( child );
}
}
}
/// <summary>
/// Initializes a new instance of the <see cref="GPTreeChromosome"/> class.
/// </summary>
///
/// <param name="source">Source genetic tree to clone from.</param>
///
/// <remarks><para>This constructor creates new genetic tree as a copy of the
/// specified <paramref name="source"/> tree.</para></remarks>
///
protected GPTreeChromosome( GPTreeChromosome source )
{
root = (GPTreeNode) source.root.Clone( );
fitness = source.fitness;
}
/// <summary>
/// Initializes a new instance of the <see cref="GPTreeChromosome"/> class.
/// </summary>
///
/// <param name="source">Source genetic tree to clone from.</param>
///
/// <remarks><para>This constructor creates new genetic tree as a copy of the
/// specified <paramref name="source"/> tree.</para></remarks>
///
protected GPTreeChromosome(GPTreeChromosome source)
{
root = (GPTreeNode)source.root.Clone();
fitness = source.fitness;
}
/// <summary>
/// Generate chromosome's subtree of specified level.
/// </summary>
///
/// <param name="node">Sub tree's node to generate.</param>
/// <param name="level">Sub tree's level to generate.</param>
///
protected void Generate( GPTreeNode node, int level )
{
// create gene for the node
if ( level == 0 )
{
// the gene should be an argument
node.Gene = root.Gene.CreateNew( GPGeneType.Argument );
}
else
{
// the gene can be function or argument
node.Gene = root.Gene.CreateNew( );
}
// add children
if ( node.Gene.ArgumentsCount != 0 )
{
node.Children = new List<GPTreeNode>( );
for ( int i = 0; i < node.Gene.ArgumentsCount; i++ )
{
// create new child
GPTreeNode child = new GPTreeNode( );
Generate( child, level - 1 );
// add the new child
node.Children.Add( child );
}
}
}
/// <summary>
/// Mutation operator.
/// </summary>
///
/// <remarks><para>The method performs chromosome's mutation by regenerating tree's
/// randomly selected node.</para></remarks>
///
public override void Mutate( )
{
// current tree level
int currentLevel = 0;
// current node
GPTreeNode node = root;
for ( ; ; )
{
// regenerate node if it does not have children
if ( node.Children == null )
{
if ( currentLevel == maxLevel )
{
// we reached maximum possible level, so the gene
// can be an argument only
node.Gene.Generate( GPGeneType.Argument );
}
else
{
// generate subtree
Generate( node, rand.Next( maxLevel - currentLevel ) );
}
break;
}
// if it is a function node, than we need to get a decision, about
// mutation point - the node itself or one of its children
int r = rand.Next( node.Gene.ArgumentsCount + 1 );
if ( r == node.Gene.ArgumentsCount )
{
// node itself should be regenerated
node.Gene.Generate( );
// check current type
if ( node.Gene.GeneType == GPGeneType.Argument )
{
node.Children = null;
}
else
{
// create children's list if it was absent
if ( node.Children == null )
node.Children = new List<GPTreeNode>( );
// check for missing or extra children
if ( node.Children.Count != node.Gene.ArgumentsCount )
{
if ( node.Children.Count > node.Gene.ArgumentsCount )
{
// remove extra children
node.Children.RemoveRange( node.Gene.ArgumentsCount, node.Children.Count - node.Gene.ArgumentsCount );
}
else
{
// add missing children
for ( int i = node.Children.Count; i < node.Gene.ArgumentsCount; i++ )
{
// create new child
GPTreeNode child = new GPTreeNode( );
Generate( child, rand.Next( maxLevel - currentLevel ) );
// add the new child
node.Children.Add( child );
}
}
}
}
break;
}
// mutation goes further to one of the children
node = (GPTreeNode) node.Children[r];
currentLevel++;
}
}
/// <summary>
/// Crossover helper routine - selects random node of chromosomes tree and
/// swaps it with specified node.
/// </summary>
private GPTreeNode RandomSwap( GPTreeNode source )
{
GPTreeNode retNode = null;
// swap root node ?
if ( ( root.Children == null ) || ( rand.Next( maxLevel ) == 0 ) )
{
// replace current root and return it
retNode = root;
root = source;
}
else
{
GPTreeNode node = root;
for ( ; ; )
{
// choose random child
int r = rand.Next( node.Gene.ArgumentsCount );
GPTreeNode child = (GPTreeNode) node.Children[r];
// swap the random node, if it is an end node or
// random generator "selected" this node
if ( ( child.Children == null ) || ( rand.Next( maxLevel ) == 0 ) )
{
// swap the node with pair's one
retNode = child;
node.Children[r] = source;
break;
}
// go further by tree
node = child;
}
}
return retNode;
}
/// <summary>
/// Crossover operator.
/// </summary>
///
/// <param name="pair">Pair chromosome to crossover with.</param>
///
/// <remarks><para>The method performs crossover between two chromosomes – interchanging
/// randomly selected sub trees.</para></remarks>
///
public override void Crossover( IChromosome pair )
{
GPTreeChromosome p = (GPTreeChromosome) pair;
// check for correct pair
if ( p != null )
{
// do we need to use root node for crossover ?
if ( ( root.Children == null ) || ( rand.Next( maxLevel ) == 0 ) )
{
// give the root to the pair and use pair's part as a new root
root = p.RandomSwap( root );
}
else
{
GPTreeNode node = root;
for ( ; ; )
{
// choose random child
int r = rand.Next( node.Gene.ArgumentsCount );
GPTreeNode child = (GPTreeNode) node.Children[r];
// swap the random node, if it is an end node or
// random generator "selected" this node
if ( ( child.Children == null ) || ( rand.Next( maxLevel ) == 0 ) )
{
// swap the node with pair's one
node.Children[r] = p.RandomSwap( child );
break;
}
// go further by tree
node = child;
}
}
// trim both of them
Trim( root, maxLevel );
Trim( p.root, maxLevel );
}
}
