#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.Collections.Generic;
using System.Linq;
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 {
[StorableClass]
[Item("RemoveBranchManipulation", "Removes a random sub-tree of the input tree and fixes the tree by generating random subtrees if necessary..")]
public sealed class RemoveBranchManipulation : SymbolicExpressionTreeManipulator, ISymbolicExpressionTreeSizeConstraintOperator {
private const int MAX_TRIES = 100;
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 RemoveBranchManipulation(bool deserializing) : base(deserializing) { }
private RemoveBranchManipulation(RemoveBranchManipulation original, Cloner cloner) : base(original, cloner) { }
public RemoveBranchManipulation()
: 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 RemoveBranchManipulation(this, cloner);
}
protected override void Manipulate(IRandom random, ISymbolicExpressionTree symbolicExpressionTree) {
RemoveRandomBranch(random, symbolicExpressionTree, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value);
}
public static void RemoveRandomBranch(IRandom random, ISymbolicExpressionTree symbolicExpressionTree, int maxTreeLength, int maxTreeDepth) {
var allowedSymbols = new List();
ISymbolicExpressionTreeNode parent;
int childIndex;
int maxLength;
int maxDepth;
// repeat until a fitting parent and child are found (MAX_TRIES times)
int tries = 0;
var nodes = symbolicExpressionTree.Root.IterateNodesPrefix().Skip(1).Where(n => n.SubtreeCount > 0).ToList();
do {
parent = nodes.SampleRandom(random);
childIndex = random.Next(parent.SubtreeCount);
var child = parent.GetSubtree(childIndex);
maxLength = maxTreeLength - symbolicExpressionTree.Length + child.GetLength();
maxDepth = maxTreeDepth - symbolicExpressionTree.Depth + child.GetDepth();
allowedSymbols.Clear();
foreach (var symbol in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, childIndex)) {
// check basic properties that the new symbol must have
if (symbol.Name != child.Symbol.Name &&
symbol.InitialFrequency > 0 &&
parent.Grammar.GetMinimumExpressionDepth(symbol) + 1 <= maxDepth &&
parent.Grammar.GetMinimumExpressionLength(symbol) <= maxLength) {
allowedSymbols.Add(symbol);
}
}
tries++;
} while (tries < MAX_TRIES && allowedSymbols.Count == 0);
if (tries >= MAX_TRIES) return;
ReplaceWithMinimalTree(random, symbolicExpressionTree.Root, parent, childIndex);
}
private static void ReplaceWithMinimalTree(IRandom random, ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode parent, int childIndex) {
// determine possible symbols that will lead to the smallest possible tree
var possibleSymbols = (from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, childIndex)
where s.InitialFrequency > 0.0
group s by parent.Grammar.GetMinimumExpressionLength(s) into g
orderby g.Key
select g).First().ToList();
var weights = possibleSymbols.Select(x => x.InitialFrequency).ToList();
#pragma warning disable 612, 618
var selectedSymbol = possibleSymbols.SelectRandom(weights, random);
#pragma warning restore 612, 618
var newTreeNode = selectedSymbol.CreateTreeNode();
if (newTreeNode.HasLocalParameters) newTreeNode.ResetLocalParameters(random);
parent.RemoveSubtree(childIndex);
parent.InsertSubtree(childIndex, newTreeNode);
var topLevelNode = newTreeNode as SymbolicExpressionTreeTopLevelNode;
if (topLevelNode != null)
topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
for (int i = 0; i < newTreeNode.Grammar.GetMinimumSubtreeCount(newTreeNode.Symbol); i++) {
// insert a dummy sub-tree and add the pending extension to the list
var dummy = new SymbolicExpressionTreeNode();
newTreeNode.AddSubtree(dummy);
// replace the just inserted dummy by recursive application
ReplaceWithMinimalTree(random, root, newTreeNode, i);
}
}
}
}