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source: branches/HeuristicLab.DataAnalysis.Symbolic.LinearInterpreter/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Creators/ProbabilisticTreeCreator.cs @ 9732

Last change on this file since 9732 was 9732, checked in by bburlacu, 11 years ago

#2021: Merged trunk changes for HeuristicLab.Encodings.SymbolicExpressionTreeEncoding and HeuristicLab.Problems.DataAnalysis.Symbolic. Replaced prefix iteration of nodes in the linear interpretation with breadth iteration for simplified logic and extra performance. Reversed unnecessary changes to other projects.

File size: 18.5 KB
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[645]1#region License Information
2/* HeuristicLab
[9732]3 * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[645]4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
[3462]22using System;
[4068]23using System.Collections.Generic;
[3462]24using System.Linq;
[4722]25using HeuristicLab.Common;
[645]26using HeuristicLab.Core;
27using HeuristicLab.Data;
[5521]28using HeuristicLab.Parameters;
[4068]29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[7012]30using HeuristicLab.PluginInfrastructure;
[645]31
[5499]32namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
[7012]33  [NonDiscoverableType]
[3223]34  [StorableClass]
[5549]35  [Item("ProbabilisticTreeCreator", "An operator that creates new symbolic expression trees with uniformly distributed length")]
[5618]36  public class ProbabilisticTreeCreator : SymbolicExpressionTreeCreator,
[5686]37    ISymbolicExpressionTreeSizeConstraintOperator, ISymbolicExpressionTreeGrammarBasedOperator {
[3369]38    private const int MAX_TRIES = 100;
[5499]39    private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
40    private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
41    private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar";
[6233]42    private const string ClonedSymbolicExpressionTreeGrammarParameterName = "ClonedSymbolicExpressionTreeGrammar";
[5499]43    #region Parameter Properties
44    public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
45      get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
46    }
47    public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
48      get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
49    }
[5686]50    public IValueLookupParameter<ISymbolicExpressionGrammar> SymbolicExpressionTreeGrammarParameter {
51      get { return (IValueLookupParameter<ISymbolicExpressionGrammar>)Parameters[SymbolicExpressionTreeGrammarParameterName]; }
[5499]52    }
[6233]53    public ILookupParameter<ISymbolicExpressionGrammar> ClonedSymbolicExpressionTreeGrammarParameter {
54      get { return (ILookupParameter<ISymbolicExpressionGrammar>)Parameters[ClonedSymbolicExpressionTreeGrammarParameterName]; }
55    }
[5499]56    #endregion
57    #region Properties
58    public IntValue MaximumSymbolicExpressionTreeLength {
59      get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
60    }
61    public IntValue MaximumSymbolicExpressionTreeDepth {
62      get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
63    }
[5686]64    public ISymbolicExpressionGrammar SymbolicExpressionTreeGrammar {
[6233]65      get { return ClonedSymbolicExpressionTreeGrammarParameter.ActualValue; }
[5499]66    }
67    #endregion
68
[4722]69    [StorableConstructor]
[5618]70    protected ProbabilisticTreeCreator(bool deserializing) : base(deserializing) { }
71    protected ProbabilisticTreeCreator(ProbabilisticTreeCreator original, Cloner cloner) : base(original, cloner) { }
[5499]72    public ProbabilisticTreeCreator()
73      : base() {
74      Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
75      Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, "The maximal depth of the symbolic expression tree (a tree with one node has depth = 0)."));
[5686]76      Parameters.Add(new ValueLookupParameter<ISymbolicExpressionGrammar>(SymbolicExpressionTreeGrammarParameterName, "The tree grammar that defines the correct syntax of symbolic expression trees that should be created."));
[6233]77      Parameters.Add(new LookupParameter<ISymbolicExpressionGrammar>(ClonedSymbolicExpressionTreeGrammarParameterName, "An immutable clone of the concrete grammar that is actually used to create and manipulate trees."));
[5499]78    }
[3338]79
[4722]80    public override IDeepCloneable Clone(Cloner cloner) {
81      return new ProbabilisticTreeCreator(this, cloner);
[645]82    }
[6233]83    [StorableHook(HookType.AfterDeserialization)]
84    private void AfterDeserialization() {
85      if (!Parameters.ContainsKey(ClonedSymbolicExpressionTreeGrammarParameterName))
86        Parameters.Add(new LookupParameter<ISymbolicExpressionGrammar>(ClonedSymbolicExpressionTreeGrammarParameterName, "An immutable clone of the concrete grammar that is actually used to create and manipulate trees."));
87    }
[645]88
[6233]89    public override IOperation Apply() {
90      if (ClonedSymbolicExpressionTreeGrammarParameter.ActualValue == null) {
91        SymbolicExpressionTreeGrammarParameter.ActualValue.ReadOnly = true;
92        IScope globalScope = ExecutionContext.Scope;
93        while (globalScope.Parent != null)
94          globalScope = globalScope.Parent;
95
96        globalScope.Variables.Add(new Variable(ClonedSymbolicExpressionTreeGrammarParameterName, (ISymbolicExpressionGrammar)SymbolicExpressionTreeGrammarParameter.ActualValue.Clone()));
97      }
98      return base.Apply();
99    }
100
[5510]101    protected override ISymbolicExpressionTree Create(IRandom random) {
[5686]102      return Create(random, SymbolicExpressionTreeGrammar, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value);
[2447]103    }
104
[7012]105    public override ISymbolicExpressionTree CreateTree(IRandom random, ISymbolicExpressionGrammar grammar, int maxTreeLength, int maxTreeDepth) {
106      return Create(random, grammar, maxTreeLength, maxTreeDepth);
107    }
108
109    public static ISymbolicExpressionTree Create(IRandom random, ISymbolicExpressionGrammar grammar, int maxTreeLength, int maxTreeDepth) {
[3223]110      SymbolicExpressionTree tree = new SymbolicExpressionTree();
[5686]111      var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.ProgramRootSymbol.CreateTreeNode();
[3442]112      if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(random);
[4249]113      rootNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
[5686]114      var startNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();
115      startNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
116      if (startNode.HasLocalParameters) startNode.ResetLocalParameters(random);
[5733]117      rootNode.AddSubtree(startNode);
[5686]118      PTC2(random, startNode, maxTreeLength, maxTreeDepth);
119      tree.Root = rootNode;
[3223]120      return tree;
121    }
122
[3338]123    private class TreeExtensionPoint {
[5499]124      public ISymbolicExpressionTreeNode Parent { get; set; }
[3338]125      public int ChildIndex { get; set; }
126      public int ExtensionPointDepth { get; set; }
[6911]127      public int MaximumExtensionLength { get; set; }
128      public int MinimumExtensionLength { get; set; }
[3223]129    }
[3360]130
[5686]131    public static void PTC2(IRandom random, ISymbolicExpressionTreeNode seedNode,
132      int maxLength, int maxDepth) {
[6009]133      // make sure it is possible to create a trees smaller than maxLength and maxDepth
134      if (seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol) > maxLength)
135        throw new ArgumentException("Cannot create trees of length " + maxLength + " or shorter because of grammar constraints.", "maxLength");
136      if (seedNode.Grammar.GetMinimumExpressionDepth(seedNode.Symbol) > maxDepth)
137        throw new ArgumentException("Cannot create trees of depth " + maxDepth + " or smaller because of grammar constraints.", "maxDepth");
138
[5549]139      // tree length is limited by the grammar and by the explicit size constraints
[5686]140      int allowedMinLength = seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol);
[6911]141      int allowedMaxLength = Math.Min(maxLength, seedNode.Grammar.GetMaximumExpressionLength(seedNode.Symbol, maxDepth));
[3369]142      int tries = 0;
143      while (tries++ < MAX_TRIES) {
[5549]144        // select a target tree length uniformly in the possible range (as determined by explicit limits and limits of the grammar)
145        int targetTreeLength;
146        targetTreeLength = random.Next(allowedMinLength, allowedMaxLength + 1);
[5686]147        if (targetTreeLength <= 1 || maxDepth <= 1) return;
[3369]148
[6911]149        bool success = TryCreateFullTreeFromSeed(random, seedNode, targetTreeLength - 1, maxDepth - 1);
[3369]150
[4189]151        // if successful => check constraints and return the tree if everything looks ok       
[5549]152        if (success && seedNode.GetLength() <= maxLength && seedNode.GetDepth() <= maxDepth) {
[5686]153          return;
[3369]154        } else {
155          // clean seedNode
[5733]156          while (seedNode.Subtrees.Count() > 0) seedNode.RemoveSubtree(0);
[3360]157        }
[5549]158        // try a different length MAX_TRIES times
[3369]159      }
[3825]160      throw new ArgumentException("Couldn't create a random valid tree.");
[3338]161    }
162
[6911]163    private static bool TryCreateFullTreeFromSeed(IRandom random, ISymbolicExpressionTreeNode root,
[5686]164      int targetLength, int maxDepth) {
[3338]165      List<TreeExtensionPoint> extensionPoints = new List<TreeExtensionPoint>();
[6911]166      int currentLength = 0;
167      int actualArity = SampleArity(random, root, targetLength, maxDepth);
[5727]168      if (actualArity < 0) return false;
169
[3223]170      for (int i = 0; i < actualArity; i++) {
171        // insert a dummy sub-tree and add the pending extension to the list
[3338]172        var dummy = new SymbolicExpressionTreeNode();
[5733]173        root.AddSubtree(dummy);
[6911]174        var x = new TreeExtensionPoint { Parent = root, ChildIndex = i, ExtensionPointDepth = 0 };
175        FillExtensionLengths(x, maxDepth);
176        extensionPoints.Add(x);
[3223]177      }
[8311]178      //necessary to use long data type as the extension point length could be int.MaxValue
179      long minExtensionPointsLength = extensionPoints.Select(x => (long)x.MinimumExtensionLength).Sum();
180      long maxExtensionPointsLength = extensionPoints.Select(x => (long)x.MaximumExtensionLength).Sum();
[6911]181
[3223]182      // while there are pending extension points and we have not reached the limit of adding new extension points
[6911]183      while (extensionPoints.Count > 0 && minExtensionPointsLength + currentLength <= targetLength) {
[3294]184        int randomIndex = random.Next(extensionPoints.Count);
[3338]185        TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
[3294]186        extensionPoints.RemoveAt(randomIndex);
[5499]187        ISymbolicExpressionTreeNode parent = nextExtension.Parent;
[3338]188        int argumentIndex = nextExtension.ChildIndex;
189        int extensionDepth = nextExtension.ExtensionPointDepth;
[6911]190
191        if (parent.Grammar.GetMinimumExpressionDepth(parent.Symbol) > maxDepth - extensionDepth) {
[5686]192          ReplaceWithMinimalTree(random, root, parent, argumentIndex);
[6911]193          int insertedTreeLength = parent.GetSubtree(argumentIndex).GetLength();
194          currentLength += insertedTreeLength;
195          minExtensionPointsLength -= insertedTreeLength;
196          maxExtensionPointsLength -= insertedTreeLength;
[3223]197        } else {
[6911]198          //remove currently chosen extension point from calculation
199          minExtensionPointsLength -= nextExtension.MinimumExtensionLength;
200          maxExtensionPointsLength -= nextExtension.MaximumExtensionLength;
201
202          var symbols = from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, argumentIndex)
203                        where s.InitialFrequency > 0.0
204                        where parent.Grammar.GetMinimumExpressionDepth(s) <= maxDepth - extensionDepth
205                        where parent.Grammar.GetMinimumExpressionLength(s) <= targetLength - currentLength - minExtensionPointsLength
206                        select s;
207          if (maxExtensionPointsLength < targetLength - currentLength)
208            symbols = from s in symbols
209                      where parent.Grammar.GetMaximumExpressionLength(s, maxDepth - extensionDepth) >= targetLength - currentLength - maxExtensionPointsLength
210                      select s;
211          var allowedSymbols = symbols.ToList();
212
[6233]213          if (allowedSymbols.Count == 0) return false;
[5499]214          var weights = allowedSymbols.Select(x => x.InitialFrequency).ToList();
215          var selectedSymbol = allowedSymbols.SelectRandom(weights, random);
216          ISymbolicExpressionTreeNode newTree = selectedSymbol.CreateTreeNode();
[3442]217          if (newTree.HasLocalParameters) newTree.ResetLocalParameters(random);
[5733]218          parent.RemoveSubtree(argumentIndex);
219          parent.InsertSubtree(argumentIndex, newTree);
[3338]220
[5686]221          var topLevelNode = newTree as SymbolicExpressionTreeTopLevelNode;
222          if (topLevelNode != null)
223            topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
[3338]224
[5549]225          currentLength++;
[6911]226          actualArity = SampleArity(random, newTree, targetLength - currentLength, maxDepth - extensionDepth);
[5727]227          if (actualArity < 0) return false;
[3223]228          for (int i = 0; i < actualArity; i++) {
229            // insert a dummy sub-tree and add the pending extension to the list
[3338]230            var dummy = new SymbolicExpressionTreeNode();
[5733]231            newTree.AddSubtree(dummy);
[6911]232            var x = new TreeExtensionPoint { Parent = newTree, ChildIndex = i, ExtensionPointDepth = extensionDepth + 1 };
233            FillExtensionLengths(x, maxDepth);
234            extensionPoints.Add(x);
235            maxExtensionPointsLength += x.MaximumExtensionLength;
236            minExtensionPointsLength += x.MinimumExtensionLength;
[3223]237          }
238        }
239      }
240      // fill all pending extension points
[3294]241      while (extensionPoints.Count > 0) {
242        int randomIndex = random.Next(extensionPoints.Count);
[3338]243        TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
[3294]244        extensionPoints.RemoveAt(randomIndex);
[5499]245        ISymbolicExpressionTreeNode parent = nextExtension.Parent;
[3338]246        int a = nextExtension.ChildIndex;
[5686]247        ReplaceWithMinimalTree(random, root, parent, a);
[3223]248      }
[5727]249      return true;
[2210]250    }
[3223]251
[5499]252    private static void ReplaceWithMinimalTree(IRandom random, ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode parent,
[5686]253      int childIndex) {
[3338]254      // determine possible symbols that will lead to the smallest possible tree
[5686]255      var possibleSymbols = (from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, childIndex)
[5925]256                             where s.InitialFrequency > 0.0
[5686]257                             group s by parent.Grammar.GetMinimumExpressionLength(s) into g
[3338]258                             orderby g.Key
[5499]259                             select g).First().ToList();
260      var weights = possibleSymbols.Select(x => x.InitialFrequency).ToList();
261      var selectedSymbol = possibleSymbols.SelectRandom(weights, random);
[3338]262      var tree = selectedSymbol.CreateTreeNode();
[3442]263      if (tree.HasLocalParameters) tree.ResetLocalParameters(random);
[5733]264      parent.RemoveSubtree(childIndex);
265      parent.InsertSubtree(childIndex, tree);
[5686]266
267      var topLevelNode = tree as SymbolicExpressionTreeTopLevelNode;
268      if (topLevelNode != null)
269        topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
270
271      for (int i = 0; i < tree.Grammar.GetMinimumSubtreeCount(tree.Symbol); i++) {
[3338]272        // insert a dummy sub-tree and add the pending extension to the list
273        var dummy = new SymbolicExpressionTreeNode();
[5733]274        tree.AddSubtree(dummy);
[3338]275        // replace the just inserted dummy by recursive application
[5686]276        ReplaceWithMinimalTree(random, root, tree, i);
[3338]277      }
278    }
[3360]279
[6911]280    private static void FillExtensionLengths(TreeExtensionPoint extension, int maxDepth) {
281      var grammar = extension.Parent.Grammar;
282      int maxLength = int.MinValue;
283      int minLength = int.MaxValue;
284      foreach (ISymbol s in grammar.GetAllowedChildSymbols(extension.Parent.Symbol, extension.ChildIndex)) {
285        if (s.InitialFrequency > 0.0) {
286          int max = grammar.GetMaximumExpressionLength(s, maxDepth - extension.ExtensionPointDepth);
287          maxLength = Math.Max(maxLength, max);
288          int min = grammar.GetMinimumExpressionLength(s);
289          minLength = Math.Min(minLength, min);
290        }
291      }
292
293      extension.MaximumExtensionLength = maxLength;
294      extension.MinimumExtensionLength = minLength;
[3338]295    }
296
[6911]297    private static int SampleArity(IRandom random, ISymbolicExpressionTreeNode node, int targetLength, int maxDepth) {
[3223]298      // select actualArity randomly with the constraint that the sub-trees in the minimal arity can become large enough
[5686]299      int minArity = node.Grammar.GetMinimumSubtreeCount(node.Symbol);
300      int maxArity = node.Grammar.GetMaximumSubtreeCount(node.Symbol);
[5549]301      if (maxArity > targetLength) {
302        maxArity = targetLength;
[3223]303      }
[6911]304      if (minArity == maxArity) return minArity;
305
[5549]306      // the min number of sub-trees has to be set to a value that is large enough so that the largest possible tree is at least tree length
307      // if 1..3 trees are possible and the largest possible first sub-tree is smaller larger than the target length then minArity should be at least 2
[3237]308      long aggregatedLongestExpressionLength = 0;
[3223]309      for (int i = 0; i < maxArity; i++) {
[5686]310        aggregatedLongestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
[5925]311                                              where s.InitialFrequency > 0.0
[6911]312                                              select node.Grammar.GetMaximumExpressionLength(s, maxDepth)).Max();
[6803]313        if (i > minArity && aggregatedLongestExpressionLength < targetLength) minArity = i + 1;
[3223]314        else break;
315      }
316
[5549]317      // the max number of sub-trees has to be set to a value that is small enough so that the smallest possible tree is at most tree length
318      // if 1..3 trees are possible and the smallest possible first sub-tree is already larger than the target length then maxArity should be at most 0
[3237]319      long aggregatedShortestExpressionLength = 0;
[3223]320      for (int i = 0; i < maxArity; i++) {
[5686]321        aggregatedShortestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
[5925]322                                               where s.InitialFrequency > 0.0
[5686]323                                               select node.Grammar.GetMinimumExpressionLength(s)).Min();
[5549]324        if (aggregatedShortestExpressionLength > targetLength) {
[3223]325          maxArity = i;
326          break;
327        }
328      }
[5727]329      if (minArity > maxArity) return -1;
[3223]330      return random.Next(minArity, maxArity + 1);
331    }
[6911]332
[2447]333  }
[645]334}
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