1 | #region License Information
|
---|
2 | /* HeuristicLab
|
---|
3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
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 |
|
---|
22 | using System;
|
---|
23 | using System.Collections.Generic;
|
---|
24 | using System.Linq;
|
---|
25 | using HeuristicLab.Analysis;
|
---|
26 | using HeuristicLab.Common;
|
---|
27 | using HeuristicLab.Core;
|
---|
28 | using HeuristicLab.Data;
|
---|
29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
30 | using HeuristicLab.Operators;
|
---|
31 | using HeuristicLab.Optimization;
|
---|
32 | using HeuristicLab.Parameters;
|
---|
33 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
34 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
|
---|
35 |
|
---|
36 | namespace HeuristicLab.EvolutionaryTracking {
|
---|
37 | /// <summary>
|
---|
38 | /// An analyzer that looks at individual lineages in the genealogy graph
|
---|
39 | /// </summary>
|
---|
40 | [Item("SymbolicExpressionTreeFrequentPatternsAnalyzer", "An operator that tries to find frequent tree fragments in the population")]
|
---|
41 | [StorableClass]
|
---|
42 | public sealed class SymbolicExpressionTreeFrequentPatternsAnalyzer : SingleSuccessorOperator, IAnalyzer {
|
---|
43 | #region Parameter names
|
---|
44 | private const string UpdateIntervalParameterName = "UpdateInterval";
|
---|
45 | private const string UpdateCounterParameterName = "UpdateCounter";
|
---|
46 | private const string ResultsParameterName = "Results";
|
---|
47 | private const string GenerationsParameterName = "Generations";
|
---|
48 | private const string MaximumGenerationsParameterName = "MaximumGenerations";
|
---|
49 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
|
---|
50 | private const string RandomParameterName = "Random";
|
---|
51 | private const string MaximumFragmentDepthParameterName = "MaximumFragmentDepth";
|
---|
52 | private const string MaximumFragmentLengthParameterName = "MaximumFragmentLength";
|
---|
53 | private const string NumberOfFragmentsToGenerateParameterName = "NumberOfFragmentsToGenerate";
|
---|
54 | private const string FrequentFragmentOccurrenceThresholdParameterName = "FrequentFragmentOccurrenceThreshold";
|
---|
55 | private const string PopulationGraphParameterName = "PopulationGraph";
|
---|
56 | private const string CommonFragmentsParameterName = "CommonFragments";
|
---|
57 | private const string EnforceGrammarArityParameterName = "EnforceGrammarArity";
|
---|
58 | #endregion
|
---|
59 |
|
---|
60 | #region Parameter properties
|
---|
61 | public ILookupParameter<IRandom> RandomParameter {
|
---|
62 | get { return (ILookupParameter<IRandom>)Parameters[RandomParameterName]; }
|
---|
63 | }
|
---|
64 | public ValueParameter<IntValue> UpdateIntervalParameter {
|
---|
65 | get { return (ValueParameter<IntValue>)Parameters[UpdateIntervalParameterName]; }
|
---|
66 | }
|
---|
67 | public ValueParameter<IntValue> UpdateCounterParameter {
|
---|
68 | get { return (ValueParameter<IntValue>)Parameters[UpdateCounterParameterName]; }
|
---|
69 | }
|
---|
70 | public LookupParameter<ResultCollection> ResultsParameter {
|
---|
71 | get { return (LookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
|
---|
72 | }
|
---|
73 | public LookupParameter<IntValue> GenerationsParameter {
|
---|
74 | get { return (LookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
|
---|
75 | }
|
---|
76 | public LookupParameter<IntValue> MaximumGenerationsParameter {
|
---|
77 | get { return (LookupParameter<IntValue>)Parameters[MaximumGenerationsParameterName]; }
|
---|
78 | }
|
---|
79 | public IScopeTreeLookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
|
---|
80 | get { return (IScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
|
---|
81 | }
|
---|
82 | public ValueParameter<IntValue> MaximumFragmentDepthParameter {
|
---|
83 | get { return (ValueParameter<IntValue>)Parameters[MaximumFragmentDepthParameterName]; }
|
---|
84 | }
|
---|
85 | public ValueParameter<IntValue> MaximumFragmentLengthParameter {
|
---|
86 | get { return (ValueParameter<IntValue>)Parameters[MaximumFragmentLengthParameterName]; }
|
---|
87 | }
|
---|
88 | public ValueParameter<IntValue> NumberOfFragmentsToGenerateParameter {
|
---|
89 | get { return (ValueParameter<IntValue>)Parameters[NumberOfFragmentsToGenerateParameterName]; }
|
---|
90 | }
|
---|
91 | public ValueParameter<DoubleValue> FrequentFragmentOccurrenceThresholdParameter {
|
---|
92 | get { return (ValueParameter<DoubleValue>)Parameters[FrequentFragmentOccurrenceThresholdParameterName]; }
|
---|
93 | }
|
---|
94 | public ValueParameter<BoolValue> EnforceGrammarArityParameter {
|
---|
95 | get { return (ValueParameter<BoolValue>)Parameters[EnforceGrammarArityParameterName]; }
|
---|
96 | }
|
---|
97 | #endregion
|
---|
98 | #region Properties
|
---|
99 | public bool EnabledByDefault {
|
---|
100 | get { return true; }
|
---|
101 | }
|
---|
102 | public IntValue UpdateInterval {
|
---|
103 | get { return UpdateIntervalParameter.Value; }
|
---|
104 | }
|
---|
105 | public IntValue UpdateCounter {
|
---|
106 | get { return UpdateCounterParameter.Value; }
|
---|
107 | }
|
---|
108 | public IntValue Generations {
|
---|
109 | get { return GenerationsParameter.ActualValue; }
|
---|
110 | }
|
---|
111 | public IntValue MaximumGenerations {
|
---|
112 | get { return MaximumGenerationsParameter.ActualValue; }
|
---|
113 | }
|
---|
114 | public ResultCollection Results {
|
---|
115 | get { return ResultsParameter.ActualValue; }
|
---|
116 | }
|
---|
117 | public IntValue MaximumFragmentDepth {
|
---|
118 | get { return MaximumFragmentDepthParameter.Value; }
|
---|
119 | }
|
---|
120 | public IntValue MaximumFragmentLength {
|
---|
121 | get { return MaximumFragmentLengthParameter.Value; }
|
---|
122 | }
|
---|
123 | public IntValue NumberOfFragmentsToGenerate {
|
---|
124 | get { return NumberOfFragmentsToGenerateParameter.Value; }
|
---|
125 | }
|
---|
126 | public DoubleValue FrequentFragmentOccurrenceThreshold {
|
---|
127 | get { return FrequentFragmentOccurrenceThresholdParameter.Value; }
|
---|
128 | }
|
---|
129 | public BoolValue EnforceGrammarArity {
|
---|
130 | get { return EnforceGrammarArityParameter.Value; }
|
---|
131 | }
|
---|
132 | #endregion
|
---|
133 |
|
---|
134 | [StorableConstructor]
|
---|
135 | private SymbolicExpressionTreeFrequentPatternsAnalyzer(bool deserializing) : base(deserializing) { }
|
---|
136 | private SymbolicExpressionTreeFrequentPatternsAnalyzer(SymbolicExpressionTreeFrequentPatternsAnalyzer original, Cloner cloner) : base(original, cloner) { }
|
---|
137 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
138 | return new SymbolicExpressionTreeFrequentPatternsAnalyzer(this, cloner);
|
---|
139 | }
|
---|
140 | public SymbolicExpressionTreeFrequentPatternsAnalyzer() {
|
---|
141 | #region Add parameters
|
---|
142 | Parameters.Add(new LookupParameter<IRandom>(RandomParameterName, "The random number generator to use."));
|
---|
143 | Parameters.Add(new ValueParameter<IntValue>(UpdateIntervalParameterName, "The interval in which the tree length analysis should be applied.", new IntValue(1)));
|
---|
144 | Parameters.Add(new ValueParameter<IntValue>(UpdateCounterParameterName, "The value which counts how many times the operator was called since the last update", new IntValue(0)));
|
---|
145 | Parameters.Add(new ValueLookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
|
---|
146 | Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "The number of generations so far"));
|
---|
147 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
|
---|
148 | Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees to analyze."));
|
---|
149 | Parameters.Add(new ValueParameter<IntValue>(MaximumFragmentDepthParameterName, "The maximum allowed depth for generated fragments.", new IntValue(4)));
|
---|
150 | Parameters.Add(new ValueParameter<IntValue>(MaximumFragmentLengthParameterName, "The maximum allowed length for generated fragments.", new IntValue(15)));
|
---|
151 | Parameters.Add(new ValueParameter<IntValue>(NumberOfFragmentsToGenerateParameterName, "The number of fragments to generate.", new IntValue(1000)));
|
---|
152 | Parameters.Add(new ValueParameter<DoubleValue>(FrequentFragmentOccurrenceThresholdParameterName, "Occurrence used to discriminate frequent fragments.", new DoubleValue(0.3)));
|
---|
153 | Parameters.Add(new ValueParameter<BoolValue>(EnforceGrammarArityParameterName, "Whether to use minimum arity as defined by the grammar", new BoolValue(true)));
|
---|
154 | #endregion
|
---|
155 | UpdateCounterParameter.Hidden = true;
|
---|
156 | UpdateIntervalParameter.Hidden = true;
|
---|
157 | MaximumFragmentDepthParameter.Hidden = false;
|
---|
158 | MaximumFragmentLengthParameter.Hidden = false;
|
---|
159 |
|
---|
160 | //this.Successor = new SymbolicExpressionTreeGenealogyGraphBuilder();
|
---|
161 | }
|
---|
162 |
|
---|
163 | #region AfterDeserialization
|
---|
164 | [StorableHook(HookType.AfterDeserialization)]
|
---|
165 | private void AfterDeserialization() {
|
---|
166 | if (!Parameters.ContainsKey(MaximumFragmentDepthParameterName)) {
|
---|
167 | Parameters.Add(new ValueParameter<IntValue>(MaximumFragmentDepthParameterName, "The maximum allowed depth for generated fragments.", new IntValue(4)));
|
---|
168 | }
|
---|
169 | if (!Parameters.ContainsKey(MaximumFragmentLengthParameterName)) {
|
---|
170 | Parameters.Add(new ValueParameter<IntValue>(MaximumFragmentLengthParameterName, "The maximum allowed length for generated fragments.", new IntValue(15)));
|
---|
171 | }
|
---|
172 | if (!Parameters.ContainsKey(NumberOfFragmentsToGenerateParameterName)) {
|
---|
173 | Parameters.Add(new ValueParameter<IntValue>(NumberOfFragmentsToGenerateParameterName, "The number of fragments to generate.", new IntValue(1000)));
|
---|
174 | }
|
---|
175 | if (!Parameters.ContainsKey(FrequentFragmentOccurrenceThresholdParameterName)) {
|
---|
176 | Parameters.Add(new ValueParameter<DoubleValue>(FrequentFragmentOccurrenceThresholdParameterName, "Occurrence used to discriminate frequent fragments.", new DoubleValue(0.3)));
|
---|
177 | }
|
---|
178 | if (!Parameters.ContainsKey(EnforceGrammarArityParameterName)) {
|
---|
179 | Parameters.Add(new ValueParameter<BoolValue>(EnforceGrammarArityParameterName, "Whether to use minimum arity as defined by the grammar", new BoolValue(true)));
|
---|
180 | }
|
---|
181 | }
|
---|
182 | #endregion
|
---|
183 |
|
---|
184 | #region IStatefulItem members
|
---|
185 | public override void InitializeState() {
|
---|
186 | base.InitializeState();
|
---|
187 | UpdateCounter.Value = 0;
|
---|
188 | }
|
---|
189 |
|
---|
190 | public override void ClearState() {
|
---|
191 | base.ClearState();
|
---|
192 | UpdateCounter.Value = 0;
|
---|
193 | }
|
---|
194 | #endregion
|
---|
195 |
|
---|
196 | public override IOperation Apply() {
|
---|
197 | UpdateCounter.Value++;
|
---|
198 | if (UpdateCounter.Value == UpdateInterval.Value) {
|
---|
199 | if (!Results.ContainsKey("SymbolGraph")) return base.Apply();
|
---|
200 |
|
---|
201 | UpdateCounter.Value = 0;
|
---|
202 |
|
---|
203 | var trees = SymbolicExpressionTreeParameter.ActualValue.ToList();
|
---|
204 | var grammar = trees[0].Root.Grammar;
|
---|
205 |
|
---|
206 | // bring trees to a canonical form to eliminate permuted fragments
|
---|
207 | var canonicalSorter = new SymbolicExpressionTreeCanonicalSorter();
|
---|
208 | foreach (var t in trees)
|
---|
209 | canonicalSorter.SortSubtrees(t);
|
---|
210 |
|
---|
211 | var graph = Results["SymbolGraph"].Value as SymbolGraph;
|
---|
212 |
|
---|
213 | var similarityComparer = new SymbolicExpressionTreeNodeSimilarityComparer { MatchVariableNames = true };
|
---|
214 | var fragmentSimilarityComparer = new SymbolicExpressionTreeFragmentSimilarityComparer { SimilarityComparer = similarityComparer };
|
---|
215 | // generate fragments out of the probability graph and match them against the population
|
---|
216 | var fragments = GenerateFragments(graph, grammar, NumberOfFragmentsToGenerate.Value, MaximumFragmentDepth.Value, MaximumFragmentLength.Value).ToList();
|
---|
217 | // subtree-sort fragments to bring them to a canonical form
|
---|
218 | // var canonicalSorter = new SymbolicExpressionTreeCanonicalSorter();
|
---|
219 | foreach (var fragment in fragments)
|
---|
220 | canonicalSorter.SortSubtrees(fragment.Root);
|
---|
221 |
|
---|
222 | if (!Results.ContainsKey(CommonFragmentsParameterName)) {
|
---|
223 | Results.Add(new Result(CommonFragmentsParameterName, new ItemDictionary<IFragment, DoubleValue>()));
|
---|
224 | }
|
---|
225 |
|
---|
226 | var mostCommonFragmentsResult = Results[CommonFragmentsParameterName].Value as ItemDictionary<IFragment, DoubleValue>; // should never be null
|
---|
227 | var mostCommonFragments = mostCommonFragmentsResult.Select(x => x.Key).ToList();
|
---|
228 | mostCommonFragments.AddRange(fragments);
|
---|
229 | mostCommonFragmentsResult.Clear();
|
---|
230 |
|
---|
231 | mostCommonFragments = mostCommonFragments.Distinct(fragmentSimilarityComparer).ToList();
|
---|
232 |
|
---|
233 | foreach (var fragment in mostCommonFragments) {
|
---|
234 | var frequency = trees.Count(x => x.Root.ContainsFragment(fragment, similarityComparer)) / (double)trees.Count;
|
---|
235 | if (frequency > 0) mostCommonFragmentsResult.Add(fragment, new DoubleValue(frequency));
|
---|
236 | }
|
---|
237 |
|
---|
238 | // update fragment frequencies DataTable
|
---|
239 | if (!Results.ContainsKey("FrequentFragments")) {
|
---|
240 | var dt = new DataTable("Frequent Fragments");
|
---|
241 | Results.Add(new Result("FrequentFragments", dt));
|
---|
242 | }
|
---|
243 |
|
---|
244 | var fragmentFrequenciesTable = Results["FrequentFragments"].Value as DataTable; // should never be null
|
---|
245 | foreach (var fragment in mostCommonFragmentsResult) {
|
---|
246 | var prefixString = fragment.Key.Root.ToPrefixString();
|
---|
247 | if (!fragmentFrequenciesTable.Rows.ContainsKey(prefixString)) {
|
---|
248 | if (fragment.Value.Value > FrequentFragmentOccurrenceThreshold.Value) {
|
---|
249 | fragmentFrequenciesTable.Rows.Add(new DataRow(prefixString) { VisualProperties = { StartIndexZero = true } });
|
---|
250 | var row = fragmentFrequenciesTable.Rows[prefixString];
|
---|
251 | if (!Results.ContainsKey(PopulationGraphParameterName)) {
|
---|
252 | row.Values.AddRange(Enumerable.Repeat(0.0, Generations.Value));
|
---|
253 | } else {
|
---|
254 | var populationGraph = Results[PopulationGraphParameterName].Value as SymbolicExpressionTreeGenealogyGraph;
|
---|
255 | var layers = populationGraph.Nodes.Where(n => n.Rank % 1 == 0).GroupBy(n => n.Rank).OrderBy(g => g.Key);
|
---|
256 | var f = fragment;
|
---|
257 | row.Values.AddRange(from g in layers
|
---|
258 | select g.Count(n => n.SymbolicExpressionTree.Root.ContainsFragment(f.Key, similarityComparer)) / (double)g.Count());
|
---|
259 | }
|
---|
260 | fragmentFrequenciesTable.Rows[prefixString].Values.Add(fragment.Value.Value);
|
---|
261 | }
|
---|
262 | } else {
|
---|
263 | fragmentFrequenciesTable.Rows[prefixString].Values.Add(fragment.Value.Value);
|
---|
264 | }
|
---|
265 | }
|
---|
266 | foreach (var row in fragmentFrequenciesTable.Rows.Where(row => row.Values.Count == Generations.Value))
|
---|
267 | row.Values.Add(0.0);
|
---|
268 |
|
---|
269 | #region Write fragment information to file
|
---|
270 |
|
---|
271 | // using (var streamWriter = new StreamWriter(Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.UserProfile), "CommonFragments.txt"))) {
|
---|
272 | // streamWriter.WriteLine("Median edge weight: " + medianWeight);
|
---|
273 | // streamWriter.WriteLine("Average edge weight: " + averageWeight);
|
---|
274 | // streamWriter.WriteLine("Symbol frequencies: ");
|
---|
275 | // double sum = graph.Nodes.Sum(node => node.Weight);
|
---|
276 | // foreach (var symbolNode in graph.Nodes.OrderBy(node => node.Weight)) {
|
---|
277 | // streamWriter.WriteLine("{0}\t{1}", symbolNode.Label, String.Format("{0:0.00}", symbolNode.Weight / sum));
|
---|
278 | // }
|
---|
279 | // streamWriter.WriteLine();
|
---|
280 | // streamWriter.WriteLine("Fragment root symbol frequencies:");
|
---|
281 | // foreach (var group in fragments.GroupBy(x => x.Root.Symbol.Name)) {
|
---|
282 | // streamWriter.WriteLine("{0}\t{1}", group.Key, String.Format("{0:0.00}", (double)group.Count() / NumberOfFragmentsToGenerate.Value));
|
---|
283 | // }
|
---|
284 | // streamWriter.WriteLine();
|
---|
285 | // foreach (var fragment in mostCommonFragments) {
|
---|
286 | // streamWriter.WriteLine(fragment.Key.ToPrefixString());
|
---|
287 | // streamWriter.WriteLine("Frequency in last generation: {0}, Contained in best individual: {1}",
|
---|
288 | // fragment.Value, trees[0].ContainsFragment(fragment.Key, SimilarityLevel.High) ? "YES" : "NO");
|
---|
289 | // SymbolicExpressionTreeMatching.RenderNode(streamWriter, fragment.Key, string.Empty);
|
---|
290 | // if (Results.ContainsKey(PopulationGraphParameterName)) {
|
---|
291 | // var populationGraph = (SymbolicExpressionTreeGenealogyGraph)Results[PopulationGraphParameterName].Value;
|
---|
292 | // streamWriter.Write("Frequencies per generation: ");
|
---|
293 | // var groups = populationGraph.Nodes.GroupBy(n => n.Rank).OrderBy(g => g.Key);
|
---|
294 | // var frequencies = (from g in groups.Where(g => g.Key == (int)g.Key)
|
---|
295 | // let freq = g.Count(n => n.SymbolicExpressionTree.ContainsFragment(fragment.Key, SimilarityLevel.High))
|
---|
296 | // select freq);
|
---|
297 | // foreach (var freq in frequencies)
|
---|
298 | // streamWriter.Write(freq / count + " ");
|
---|
299 | // streamWriter.WriteLine();
|
---|
300 | // } else {
|
---|
301 | // streamWriter.WriteLine("Frequecy in current population: {0}", fragment.Value);
|
---|
302 | // }
|
---|
303 | // streamWriter.WriteLine("\n");
|
---|
304 | // }
|
---|
305 | // streamWriter.WriteLine("Average fragment length: {0}", avgFragmentLength);
|
---|
306 | // streamWriter.WriteLine("Average fragment depth: {0}", avgFragmentDepth);
|
---|
307 | // streamWriter.WriteLine("Percentage of unique generated fragments: {0}", distinctFragments.Count() / (double)fragments.Count);
|
---|
308 | // }
|
---|
309 |
|
---|
310 | #endregion
|
---|
311 | }
|
---|
312 | return base.Apply();
|
---|
313 | }
|
---|
314 |
|
---|
315 | private IEnumerable<IFragment> GenerateFragments(SymbolGraph graph, ISymbolicExpressionTreeGrammar grammar, int numFragments, int maxDepth, int maxLength) {
|
---|
316 | var fragments = new List<IFragment>();
|
---|
317 | var random = RandomParameter.ActualValue;
|
---|
318 | var count = SymbolicExpressionTreeParameter.ActualValue.Count();
|
---|
319 | var threshold = count * FrequentFragmentOccurrenceThreshold.Value;
|
---|
320 | var availableSymbols = graph.Nodes.Where(x => x.OutEdges != null && x.OutEdges.Count > 0 && x.Weight >= threshold).ToList();
|
---|
321 | var weights = availableSymbols.Select(x => x.Weight).ToList();
|
---|
322 |
|
---|
323 | if (!(availableSymbols.Count == 0 || weights.Count == 0))
|
---|
324 | for (int i = 0; i != numFragments; ++i) {
|
---|
325 | var symbol = availableSymbols.SelectRandom(weights, random);
|
---|
326 | var fragment = CreateFragment(symbol, random, grammar, threshold, maxDepth, maxLength, EnforceGrammarArity.Value);
|
---|
327 | fragments.Add(new Fragment(fragment));
|
---|
328 | }
|
---|
329 | return fragments;
|
---|
330 | }
|
---|
331 |
|
---|
332 | private static ISymbolicExpressionTreeNode CreateFragment(SymbolNode symbolNode, IRandom random, ISymbolicExpressionTreeGrammar grammar, double threshold, int depthLimit, int lengthLimit, bool enforceGrammarArity = true) {
|
---|
333 | var node = symbolNode.Symbol.CreateTreeNode();
|
---|
334 | if (node.HasLocalParameters) node.ResetLocalParameters(random);
|
---|
335 | if (node is VariableTreeNode) (node as VariableTreeNode).VariableName = symbolNode.Label;
|
---|
336 |
|
---|
337 | if (symbolNode.OutEdges == null || symbolNode.OutEdges.Count == 0 || depthLimit < 0)
|
---|
338 | return node; // node is a leaf so we just return it
|
---|
339 |
|
---|
340 | int maxCount = grammar.GetMaximumSubtreeCount(node.Symbol);
|
---|
341 | if (maxCount > 0) {
|
---|
342 | int minCount = grammar.GetMinimumSubtreeCount(node.Symbol);
|
---|
343 | var arity = random.Next(enforceGrammarArity ? minCount : 1, maxCount + 1);
|
---|
344 | var possibleChildConnections = new List<Arc>();
|
---|
345 |
|
---|
346 | if (depthLimit <= 2 || lengthLimit <= maxCount) { // if we are near the depth limit then we want to add leafs on the next level
|
---|
347 | possibleChildConnections.AddRange(from e in symbolNode.OutEdges
|
---|
348 | let n = (SymbolNode)e.Target
|
---|
349 | where grammar.GetMaximumSubtreeCount(n.Symbol) == 0
|
---|
350 | where n.Weight >= threshold
|
---|
351 | select e);
|
---|
352 | }
|
---|
353 | // if there are no available connections towards leaf nodes (in case depthLimit <= 2)
|
---|
354 | // or in case the depthLimit has not been reached yet
|
---|
355 | if (possibleChildConnections.Count == 0)
|
---|
356 | possibleChildConnections.AddRange(symbolNode.OutEdges.Where(a => ((SymbolNode)a.Target).Weight >= threshold)); // this will not be empty since we check above if the OutEdges are null
|
---|
357 | var weights = new double[possibleChildConnections.Count];
|
---|
358 |
|
---|
359 | for (int i = 0; i != arity; ++i) {
|
---|
360 | // adjust weights according to the probability a child will find itself on a certain argument position
|
---|
361 | for (int j = 0; j != possibleChildConnections.Count; ++j) {
|
---|
362 | var childSymbolNode = (SymbolNode)possibleChildConnections[j].Target;
|
---|
363 | double sumPos = childSymbolNode.Positions.Sum(x => x.Value);
|
---|
364 | int v; childSymbolNode.Positions.TryGetValue(i, out v);
|
---|
365 | weights[j] = possibleChildConnections[j].Weight * v / sumPos;
|
---|
366 | }
|
---|
367 |
|
---|
368 | if (weights.Sum().IsAlmost(0.0)) continue;
|
---|
369 |
|
---|
370 | var selectedConnection = possibleChildConnections.SelectRandom(weights, random);
|
---|
371 | var selectedChildSymbolNode = selectedConnection.Target as SymbolNode;
|
---|
372 | var child = CreateFragment(selectedChildSymbolNode, random, grammar, threshold, depthLimit - 1, --lengthLimit);
|
---|
373 | if (child == null) throw new Exception("Child cannot be null.");
|
---|
374 | node.AddSubtree(child);
|
---|
375 | }
|
---|
376 | }
|
---|
377 | return node;
|
---|
378 | }
|
---|
379 | }
|
---|
380 | }
|
---|