[3294] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[7259] | 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3294] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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[4068] | 23 | using System.Collections.Generic;
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[3294] | 24 | using System.Linq;
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[4068] | 25 | using System.Text;
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[4722] | 26 | using HeuristicLab.Common;
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[3294] | 27 | using HeuristicLab.Core;
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| 28 | using HeuristicLab.Data;
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[5686] | 29 | using HeuristicLab.Parameters;
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[3294] | 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 |
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[5499] | 32 | namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
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[3294] | 33 | /// <summary>
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| 34 | /// Manipulates a symbolic expression by adding one new function-defining branch containing
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| 35 | /// a proportion of a preexisting branch and by creating a reference to the new branch.
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| 36 | /// As described in Koza, Bennett, Andre, Keane, Genetic Programming III - Darwinian Invention and Problem Solving, 1999, pp. 97
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| 37 | /// </summary>
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[5510] | 38 | [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")]
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[3294] | 39 | [StorableClass]
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[5510] | 40 | public sealed class SubroutineCreater : SymbolicExpressionTreeArchitectureManipulator, ISymbolicExpressionTreeSizeConstraintOperator {
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[3360] | 41 | private const double ARGUMENT_CUTOFF_PROBABILITY = 0.05;
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[5510] | 42 | private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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| 43 | private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
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| 44 | #region Parameter Properties
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| 45 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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| 46 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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| 47 | }
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| 48 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
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| 49 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
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| 50 | }
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| 51 | #endregion
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| 52 | #region Properties
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| 53 | public IntValue MaximumSymbolicExpressionTreeLength {
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| 54 | get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
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| 55 | }
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| 56 | public IntValue MaximumSymbolicExpressionTreeDepth {
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| 57 | get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
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| 58 | }
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| 59 | #endregion
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[4722] | 60 | [StorableConstructor]
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| 61 | private SubroutineCreater(bool deserializing) : base(deserializing) { }
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| 62 | private SubroutineCreater(SubroutineCreater original, Cloner cloner) : base(original, cloner) { }
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[5686] | 63 | public SubroutineCreater()
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| 64 | : base() {
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[5510] | 65 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
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| 66 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, "The maximal depth of the symbolic expression tree (a tree with one node has depth = 0)."));
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| 67 | }
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[4722] | 68 |
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| 69 | public override IDeepCloneable Clone(Cloner cloner) {
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| 70 | return new SubroutineCreater(this, cloner);
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| 71 | }
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| 72 |
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[3294] | 73 | public override sealed void ModifyArchitecture(
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| 74 | IRandom random,
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[5510] | 75 | ISymbolicExpressionTree symbolicExpressionTree,
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| 76 | IntValue maxFunctionDefinitions, IntValue maxFunctionArguments) {
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| 77 | CreateSubroutine(random, symbolicExpressionTree, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value, maxFunctionDefinitions.Value, maxFunctionArguments.Value);
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[3294] | 78 | }
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| 79 |
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| 80 | public static bool CreateSubroutine(
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| 81 | IRandom random,
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[5510] | 82 | ISymbolicExpressionTree symbolicExpressionTree,
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| 83 | int maxTreeLength, int maxTreeDepth,
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| 84 | int maxFunctionDefinitions, int maxFunctionArguments) {
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[3294] | 85 | var functionDefiningBranches = symbolicExpressionTree.IterateNodesPrefix().OfType<DefunTreeNode>();
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[5510] | 86 | if (functionDefiningBranches.Count() >= maxFunctionDefinitions)
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[3294] | 87 | // allowed maximum number of ADF reached => abort
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| 88 | return false;
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[5549] | 89 | if (symbolicExpressionTree.Length + 4 > maxTreeLength)
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| 90 | // defining a new function causes an length increase by 4 nodes (max) if the max tree length is reached => abort
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[3360] | 91 | return false;
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[5510] | 92 | string formatString = new StringBuilder().Append('0', (int)Math.Log10(maxFunctionDefinitions * 10 - 1)).ToString(); // >= 100 functions => ###
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| 93 | var allowedFunctionNames = from index in Enumerable.Range(0, maxFunctionDefinitions)
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[3294] | 94 | select "ADF" + index.ToString(formatString);
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[3360] | 95 |
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| 96 | // select a random body (either the result producing branch or an ADF branch)
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[5733] | 97 | var bodies = from node in symbolicExpressionTree.Root.Subtrees
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[5549] | 98 | select new { Tree = node, Length = node.GetLength() };
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| 99 | var totalNumberOfBodyNodes = bodies.Select(x => x.Length).Sum();
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[3294] | 100 | int r = random.Next(totalNumberOfBodyNodes);
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| 101 | int aggregatedNumberOfBodyNodes = 0;
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[5510] | 102 | ISymbolicExpressionTreeNode selectedBody = null;
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[3294] | 103 | foreach (var body in bodies) {
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[5549] | 104 | aggregatedNumberOfBodyNodes += body.Length;
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[3294] | 105 | if (aggregatedNumberOfBodyNodes > r)
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| 106 | selectedBody = body.Tree;
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| 107 | }
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| 108 | // sanity check
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| 109 | if (selectedBody == null) throw new InvalidOperationException();
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[3360] | 110 |
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| 111 | // select a random cut point in the selected branch
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[5686] | 112 | var allCutPoints = (from parent in selectedBody.IterateNodesPrefix()
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[5733] | 113 | from subtree in parent.Subtrees
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[5686] | 114 | select new CutPoint(parent, subtree)).ToList();
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[3360] | 115 | if (allCutPoints.Count() == 0)
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[3294] | 116 | // no cut points => abort
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| 117 | return false;
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[3360] | 118 | string newFunctionName = allowedFunctionNames.Except(functionDefiningBranches.Select(x => x.FunctionName)).First();
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| 119 | var selectedCutPoint = allCutPoints.SelectRandom(random);
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[3294] | 120 | // select random branches as argument cut-off points (replaced by argument terminal nodes in the function)
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[5686] | 121 | List<CutPoint> argumentCutPoints = SelectRandomArgumentBranches(selectedCutPoint.Child, random, ARGUMENT_CUTOFF_PROBABILITY, maxFunctionArguments);
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| 122 | ISymbolicExpressionTreeNode functionBody = selectedCutPoint.Child;
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[3294] | 123 | // disconnect the function body from the tree
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[5733] | 124 | selectedCutPoint.Parent.RemoveSubtree(selectedCutPoint.ChildIndex);
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[3294] | 125 | // disconnect the argument branches from the function
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[5686] | 126 | functionBody = DisconnectBranches(functionBody, argumentCutPoints);
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[3360] | 127 | // insert a function invocation symbol instead
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| 128 | var invokeNode = (InvokeFunctionTreeNode)(new InvokeFunction(newFunctionName)).CreateTreeNode();
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[5733] | 129 | selectedCutPoint.Parent.InsertSubtree(selectedCutPoint.ChildIndex, invokeNode);
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[3360] | 130 | // add the branches selected as argument as subtrees of the function invocation node
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[5686] | 131 | foreach (var argumentCutPoint in argumentCutPoints)
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[5733] | 132 | invokeNode.AddSubtree(argumentCutPoint.Child);
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[3294] | 133 |
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| 134 | // insert a new function defining branch
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| 135 | var defunNode = (DefunTreeNode)(new Defun()).CreateTreeNode();
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[3360] | 136 | defunNode.FunctionName = newFunctionName;
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[5733] | 137 | defunNode.AddSubtree(functionBody);
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| 138 | symbolicExpressionTree.Root.AddSubtree(defunNode);
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[3360] | 139 | // the grammar in the newly defined function is a clone of the grammar of the originating branch
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[5510] | 140 | defunNode.SetGrammar((ISymbolicExpressionTreeGrammar)selectedBody.Grammar.Clone());
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[5686] | 141 | // remove all argument symbols from grammar except that one contained in cutpoints
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| 142 | var oldArgumentSymbols = selectedBody.Grammar.Symbols.OfType<Argument>().ToList();
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[3360] | 143 | foreach (var oldArgSymb in oldArgumentSymbols)
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| 144 | defunNode.Grammar.RemoveSymbol(oldArgSymb);
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| 145 | // find unique argument indexes and matching symbols in the function defining branch
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| 146 | var newArgumentIndexes = (from node in defunNode.IterateNodesPrefix().OfType<ArgumentTreeNode>()
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| 147 | select node.Symbol.ArgumentIndex).Distinct();
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| 148 | // add argument symbols to grammar of function defining branch
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[5686] | 149 | GrammarModifier.AddArgumentSymbol(selectedBody.Grammar, defunNode.Grammar, newArgumentIndexes, argumentCutPoints);
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[3360] | 150 | defunNode.NumberOfArguments = newArgumentIndexes.Count();
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[5686] | 151 | if (defunNode.NumberOfArguments != argumentCutPoints.Count) throw new InvalidOperationException();
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[3360] | 152 | // add invoke symbol for newly defined function to the original branch
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[5686] | 153 | GrammarModifier.AddInvokeSymbol(selectedBody.Grammar, defunNode.FunctionName, defunNode.NumberOfArguments, selectedCutPoint, argumentCutPoints);
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[3360] | 154 |
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| 155 | // when the new function body was taken from another function definition
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| 156 | // add invoke symbol for newly defined function to all branches that are allowed to invoke the original branch
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| 157 | if (selectedBody.Symbol is Defun) {
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| 158 | var originalFunctionDefinition = selectedBody as DefunTreeNode;
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[5733] | 159 | foreach (var subtree in symbolicExpressionTree.Root.Subtrees) {
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[3360] | 160 | var originalBranchInvokeSymbol = (from symb in subtree.Grammar.Symbols.OfType<InvokeFunction>()
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| 161 | where symb.FunctionName == originalFunctionDefinition.FunctionName
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| 162 | select symb).SingleOrDefault();
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| 163 | // when the original branch can be invoked from the subtree then also allow invocation of the function
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| 164 | if (originalBranchInvokeSymbol != null) {
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[5686] | 165 | GrammarModifier.AddInvokeSymbol(subtree.Grammar, defunNode.FunctionName, defunNode.NumberOfArguments, selectedCutPoint, argumentCutPoints);
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[3360] | 166 | }
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| 167 | }
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[3294] | 168 | }
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| 169 | return true;
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| 170 | }
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| 171 |
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[5686] | 172 | private static ISymbolicExpressionTreeNode DisconnectBranches(ISymbolicExpressionTreeNode node, List<CutPoint> argumentCutPoints) {
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| 173 | int argumentIndex = argumentCutPoints.FindIndex(x => x.Child == node);
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| 174 | if (argumentIndex != -1) {
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[3360] | 175 | var argSymbol = new Argument(argumentIndex);
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| 176 | return argSymbol.CreateTreeNode();
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| 177 | }
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[3294] | 178 | // remove the subtrees so that we can clone only the root node
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[5733] | 179 | List<ISymbolicExpressionTreeNode> subtrees = new List<ISymbolicExpressionTreeNode>(node.Subtrees);
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| 180 | while (node.Subtrees.Count() > 0) node.RemoveSubtree(0);
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[3294] | 181 | // recursively apply function for subtrees or append a argument terminal node
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| 182 | foreach (var subtree in subtrees) {
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[5733] | 183 | node.AddSubtree(DisconnectBranches(subtree, argumentCutPoints));
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[3294] | 184 | }
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| 185 | return node;
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| 186 | }
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| 187 |
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[5686] | 188 | private static List<CutPoint> SelectRandomArgumentBranches(ISymbolicExpressionTreeNode selectedRoot,
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[3294] | 189 | IRandom random,
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[3360] | 190 | double cutProbability,
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[3294] | 191 | int maxArguments) {
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[3360] | 192 | // breadth first determination of argument cut-off points
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| 193 | // we must make sure that we cut off all original argument nodes and that the number of new argument is smaller than the limit
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[5686] | 194 | List<CutPoint> argumentBranches = new List<CutPoint>();
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[3360] | 195 | if (selectedRoot is ArgumentTreeNode) {
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[5686] | 196 | argumentBranches.Add(new CutPoint(selectedRoot.Parent, selectedRoot));
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[3360] | 197 | return argumentBranches;
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| 198 | } else {
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| 199 | // get the number of argument nodes (which must be cut-off) in the sub-trees
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[5733] | 200 | var numberOfArgumentsInSubtrees = (from subtree in selectedRoot.Subtrees
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[3360] | 201 | let nArgumentsInTree = subtree.IterateNodesPrefix().OfType<ArgumentTreeNode>().Count()
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| 202 | select nArgumentsInTree).ToList();
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| 203 | // determine the minimal number of new argument nodes for each sub-tree
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[5686] | 204 | //if we exceed the maxArguments return the same cutpoint as the start cutpoint to create a ADF that returns only its argument
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[3360] | 205 | var minNewArgumentsForSubtrees = numberOfArgumentsInSubtrees.Select(x => x > 0 ? 1 : 0).ToList();
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| 206 | if (minNewArgumentsForSubtrees.Sum() > maxArguments) {
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[5686] | 207 | argumentBranches.Add(new CutPoint(selectedRoot.Parent, selectedRoot));
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[3360] | 208 | return argumentBranches;
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[3294] | 209 | }
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[3360] | 210 | // cut-off in the sub-trees in random order
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[5733] | 211 | var randomIndexes = (from index in Enumerable.Range(0, selectedRoot.Subtrees.Count())
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[5686] | 212 | select new { Index = index, OrderValue = random.NextDouble() })
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| 213 | .OrderBy(x => x.OrderValue)
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| 214 | .Select(x => x.Index);
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[3360] | 215 | foreach (var subtreeIndex in randomIndexes) {
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[5733] | 216 | var subtree = selectedRoot.GetSubtree(subtreeIndex);
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[3360] | 217 | minNewArgumentsForSubtrees[subtreeIndex] = 0;
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| 218 | // => cut-off at 0..n points somewhere in the current sub-tree
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| 219 | // determine the maximum number of new arguments that should be created in the branch
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| 220 | // as the maximum for the whole branch minus already added arguments minus minimal number of arguments still left
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| 221 | int maxArgumentsFromBranch = maxArguments - argumentBranches.Count - minNewArgumentsForSubtrees.Sum();
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| 222 | // when no argument is allowed from the current branch then we have to include the whole branch into the function
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| 223 | // otherwise: choose randomly wether to cut off immediately or wether to extend the function body into the branch
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| 224 | if (maxArgumentsFromBranch == 0) {
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| 225 | // don't cut at all => the whole sub-tree branch is included in the function body
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| 226 | // (we already checked ahead of time that there are no arguments left over in the subtree)
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| 227 | } else if (random.NextDouble() >= cutProbability) {
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| 228 | argumentBranches.AddRange(SelectRandomArgumentBranches(subtree, random, cutProbability, maxArgumentsFromBranch));
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| 229 | } else {
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| 230 | // cut-off at current sub-tree
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[5686] | 231 | argumentBranches.Add(new CutPoint(subtree.Parent, subtree));
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[3360] | 232 | }
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| 233 | }
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| 234 | return argumentBranches;
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[3294] | 235 | }
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| 236 | }
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| 237 | }
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| 238 | }
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