#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab 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.
*
* HeuristicLab 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 HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
///
/// Manipulates a symbolic expression by adding one new function-defining branch containing
/// a proportion of a preexisting branch and by creating a reference to the new branch.
/// As described in Koza, Bennett, Andre, Keane, Genetic Programming III - Darwinian Invention and Problem Solving, 1999, pp. 97
///
[Item("SubroutineCreater", "Manipulates a symbolic expression by adding one new function-defining branch containing a proportion of a preexisting branch and by creating a reference to the new branch. As described in Koza, Bennett, Andre, Keane, Genetic Programming III - Darwinian Invention and Problem Solving, 1999, pp. 97")]
[StorableClass]
public sealed class SubroutineCreater : SymbolicExpressionTreeArchitectureManipulator, ISymbolicExpressionTreeSizeConstraintOperator {
private const double ARGUMENT_CUTOFF_PROBABILITY = 0.05;
private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
#region Parameter Properties
public IValueLookupParameter MaximumSymbolicExpressionTreeLengthParameter {
get { return (IValueLookupParameter)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
}
public IValueLookupParameter MaximumSymbolicExpressionTreeDepthParameter {
get { return (IValueLookupParameter)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
}
#endregion
#region Properties
public IntValue MaximumSymbolicExpressionTreeLength {
get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
}
public IntValue MaximumSymbolicExpressionTreeDepth {
get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
}
#endregion
[StorableConstructor]
private SubroutineCreater(bool deserializing) : base(deserializing) { }
private SubroutineCreater(SubroutineCreater original, Cloner cloner) : base(original, cloner) { }
public SubroutineCreater()
: base() {
Parameters.Add(new ValueLookupParameter(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
Parameters.Add(new ValueLookupParameter(MaximumSymbolicExpressionTreeDepthParameterName, "The maximal depth of the symbolic expression tree (a tree with one node has depth = 0)."));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SubroutineCreater(this, cloner);
}
public override sealed void ModifyArchitecture(
IRandom random,
ISymbolicExpressionTree symbolicExpressionTree,
IntValue maxFunctionDefinitions, IntValue maxFunctionArguments) {
CreateSubroutine(random, symbolicExpressionTree, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value, maxFunctionDefinitions.Value, maxFunctionArguments.Value);
}
public static bool CreateSubroutine(
IRandom random,
ISymbolicExpressionTree symbolicExpressionTree,
int maxTreeLength, int maxTreeDepth,
int maxFunctionDefinitions, int maxFunctionArguments) {
var functionDefiningBranches = symbolicExpressionTree.IterateNodesPrefix().OfType();
if (functionDefiningBranches.Count() >= maxFunctionDefinitions)
// allowed maximum number of ADF reached => abort
return false;
if (symbolicExpressionTree.Length + 4 > maxTreeLength)
// defining a new function causes an length increase by 4 nodes (max) if the max tree length is reached => abort
return false;
string formatString = new StringBuilder().Append('0', (int)Math.Log10(maxFunctionDefinitions * 10 - 1)).ToString(); // >= 100 functions => ###
var allowedFunctionNames = from index in Enumerable.Range(0, maxFunctionDefinitions)
select "ADF" + index.ToString(formatString);
// select a random body (either the result producing branch or an ADF branch)
var bodies = from node in symbolicExpressionTree.Root.Subtrees
select new { Tree = node, Length = node.GetLength() };
var totalNumberOfBodyNodes = bodies.Select(x => x.Length).Sum();
int r = random.Next(totalNumberOfBodyNodes);
int aggregatedNumberOfBodyNodes = 0;
ISymbolicExpressionTreeNode selectedBody = null;
foreach (var body in bodies) {
aggregatedNumberOfBodyNodes += body.Length;
if (aggregatedNumberOfBodyNodes > r)
selectedBody = body.Tree;
}
// sanity check
if (selectedBody == null) throw new InvalidOperationException();
// select a random cut point in the selected branch
var allCutPoints = (from parent in selectedBody.IterateNodesPrefix()
from subtree in parent.Subtrees
select new CutPoint(parent, subtree)).ToList();
if (!allCutPoints.Any())
// no cut points => abort
return false;
string newFunctionName = allowedFunctionNames.Except(functionDefiningBranches.Select(x => x.FunctionName)).First();
var selectedCutPoint = allCutPoints.SampleRandom(random);
// select random branches as argument cut-off points (replaced by argument terminal nodes in the function)
List argumentCutPoints = SelectRandomArgumentBranches(selectedCutPoint.Child, random, ARGUMENT_CUTOFF_PROBABILITY, maxFunctionArguments);
ISymbolicExpressionTreeNode functionBody = selectedCutPoint.Child;
// disconnect the function body from the tree
selectedCutPoint.Parent.RemoveSubtree(selectedCutPoint.ChildIndex);
// disconnect the argument branches from the function
functionBody = DisconnectBranches(functionBody, argumentCutPoints);
// insert a function invocation symbol instead
var invokeNode = (InvokeFunctionTreeNode)(new InvokeFunction(newFunctionName)).CreateTreeNode();
selectedCutPoint.Parent.InsertSubtree(selectedCutPoint.ChildIndex, invokeNode);
// add the branches selected as argument as subtrees of the function invocation node
foreach (var argumentCutPoint in argumentCutPoints)
invokeNode.AddSubtree(argumentCutPoint.Child);
// insert a new function defining branch
var defunNode = (DefunTreeNode)(new Defun()).CreateTreeNode();
defunNode.FunctionName = newFunctionName;
defunNode.AddSubtree(functionBody);
symbolicExpressionTree.Root.AddSubtree(defunNode);
// the grammar in the newly defined function is a clone of the grammar of the originating branch
defunNode.SetGrammar((ISymbolicExpressionTreeGrammar)selectedBody.Grammar.Clone());
var allowedChildSymbols = selectedBody.Grammar.GetAllowedChildSymbols(selectedBody.Symbol);
foreach (var allowedChildSymbol in allowedChildSymbols)
defunNode.Grammar.AddAllowedChildSymbol(defunNode.Symbol, allowedChildSymbol);
var maxSubtrees = selectedBody.Grammar.GetMaximumSubtreeCount(selectedBody.Symbol);
for (int i = 0; i < maxSubtrees; i++) {
foreach (var allowedChildSymbol in selectedBody.Grammar.GetAllowedChildSymbols(selectedBody.Symbol, i))
defunNode.Grammar.AddAllowedChildSymbol(defunNode.Symbol, allowedChildSymbol);
}
// remove all argument symbols from grammar except that one contained in cutpoints
var oldArgumentSymbols = selectedBody.Grammar.Symbols.OfType().ToList();
foreach (var oldArgSymb in oldArgumentSymbols)
defunNode.Grammar.RemoveSymbol(oldArgSymb);
// find unique argument indexes and matching symbols in the function defining branch
var newArgumentIndexes = (from node in defunNode.IterateNodesPrefix().OfType()
select node.Symbol.ArgumentIndex).Distinct();
// add argument symbols to grammar of function defining branch
GrammarModifier.AddArgumentSymbol(selectedBody.Grammar, defunNode.Grammar, newArgumentIndexes, argumentCutPoints);
defunNode.NumberOfArguments = newArgumentIndexes.Count();
if (defunNode.NumberOfArguments != argumentCutPoints.Count) throw new InvalidOperationException();
// add invoke symbol for newly defined function to the original branch
GrammarModifier.AddInvokeSymbol(selectedBody.Grammar, defunNode.FunctionName, defunNode.NumberOfArguments, selectedCutPoint, argumentCutPoints);
// when the new function body was taken from another function definition
// add invoke symbol for newly defined function to all branches that are allowed to invoke the original branch
if (selectedBody.Symbol is Defun) {
var originalFunctionDefinition = selectedBody as DefunTreeNode;
foreach (var subtree in symbolicExpressionTree.Root.Subtrees) {
var originalBranchInvokeSymbol = (from symb in subtree.Grammar.Symbols.OfType()
where symb.FunctionName == originalFunctionDefinition.FunctionName
select symb).SingleOrDefault();
// when the original branch can be invoked from the subtree then also allow invocation of the function
if (originalBranchInvokeSymbol != null) {
GrammarModifier.AddInvokeSymbol(subtree.Grammar, defunNode.FunctionName, defunNode.NumberOfArguments, selectedCutPoint, argumentCutPoints);
}
}
}
return true;
}
private static ISymbolicExpressionTreeNode DisconnectBranches(ISymbolicExpressionTreeNode node, List argumentCutPoints) {
int argumentIndex = argumentCutPoints.FindIndex(x => x.Child == node);
if (argumentIndex != -1) {
var argSymbol = new Argument(argumentIndex);
return argSymbol.CreateTreeNode();
}
// remove the subtrees so that we can clone only the root node
List subtrees = new List(node.Subtrees);
while (node.Subtrees.Count() > 0) node.RemoveSubtree(0);
// recursively apply function for subtrees or append a argument terminal node
foreach (var subtree in subtrees) {
node.AddSubtree(DisconnectBranches(subtree, argumentCutPoints));
}
return node;
}
private static List SelectRandomArgumentBranches(ISymbolicExpressionTreeNode selectedRoot,
IRandom random,
double cutProbability,
int maxArguments) {
// breadth first determination of argument cut-off points
// we must make sure that we cut off all original argument nodes and that the number of new argument is smaller than the limit
List argumentBranches = new List();
if (selectedRoot is ArgumentTreeNode) {
argumentBranches.Add(new CutPoint(selectedRoot.Parent, selectedRoot));
return argumentBranches;
} else {
// get the number of argument nodes (which must be cut-off) in the sub-trees
var numberOfArgumentsInSubtrees = (from subtree in selectedRoot.Subtrees
let nArgumentsInTree = subtree.IterateNodesPrefix().OfType().Count()
select nArgumentsInTree).ToList();
// determine the minimal number of new argument nodes for each sub-tree
//if we exceed the maxArguments return the same cutpoint as the start cutpoint to create a ADF that returns only its argument
var minNewArgumentsForSubtrees = numberOfArgumentsInSubtrees.Select(x => x > 0 ? 1 : 0).ToList();
if (minNewArgumentsForSubtrees.Sum() > maxArguments) {
argumentBranches.Add(new CutPoint(selectedRoot.Parent, selectedRoot));
return argumentBranches;
}
// cut-off in the sub-trees in random order
var randomIndexes = (from index in Enumerable.Range(0, selectedRoot.Subtrees.Count())
select new { Index = index, OrderValue = random.NextDouble() })
.OrderBy(x => x.OrderValue)
.Select(x => x.Index);
foreach (var subtreeIndex in randomIndexes) {
var subtree = selectedRoot.GetSubtree(subtreeIndex);
minNewArgumentsForSubtrees[subtreeIndex] = 0;
// => cut-off at 0..n points somewhere in the current sub-tree
// determine the maximum number of new arguments that should be created in the branch
// as the maximum for the whole branch minus already added arguments minus minimal number of arguments still left
int maxArgumentsFromBranch = maxArguments - argumentBranches.Count - minNewArgumentsForSubtrees.Sum();
// when no argument is allowed from the current branch then we have to include the whole branch into the function
// otherwise: choose randomly wether to cut off immediately or wether to extend the function body into the branch
if (maxArgumentsFromBranch == 0) {
// don't cut at all => the whole sub-tree branch is included in the function body
// (we already checked ahead of time that there are no arguments left over in the subtree)
} else if (random.NextDouble() >= cutProbability) {
argumentBranches.AddRange(SelectRandomArgumentBranches(subtree, random, cutProbability, maxArgumentsFromBranch));
} else {
// cut-off at current sub-tree
argumentBranches.Add(new CutPoint(subtree.Parent, subtree));
}
}
return argumentBranches;
}
}
}
}