[2] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 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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| 23 | using System.Collections.Generic;
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| 24 | using System.Text;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Constraints;
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| 27 | using System.Diagnostics;
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| 28 | using HeuristicLab.Data;
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| 29 | using System.Linq;
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| 30 | using HeuristicLab.Random;
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| 31 | using HeuristicLab.Operators;
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| 32 | using HeuristicLab.Selection;
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[142] | 33 | using HeuristicLab.Functions;
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[2] | 34 |
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| 35 | namespace HeuristicLab.StructureIdentification {
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| 36 | internal class TreeGardener {
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| 37 | private IRandom random;
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[143] | 38 | private IOperatorLibrary funLibrary;
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| 39 | private List<IFunction> functions;
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| 40 | private List<IFunction> terminals;
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[2] | 41 |
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[143] | 42 | internal IList<IFunction> Terminals {
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[2] | 43 | get { return terminals.AsReadOnly(); }
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| 44 | }
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[143] | 45 | private List<IFunction> allFunctions;
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[2] | 46 |
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[143] | 47 | internal IList<IFunction> AllFunctions {
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| 48 | get { return allFunctions.AsReadOnly(); }
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[2] | 49 | }
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| 50 |
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[143] | 51 | internal TreeGardener(IRandom random, IOperatorLibrary funLibrary) {
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[2] | 52 | this.random = random;
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[143] | 53 | this.funLibrary = funLibrary;
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[2] | 54 |
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[143] | 55 | this.allFunctions = new List<IFunction>();
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| 56 | terminals = new List<IFunction>();
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| 57 | functions = new List<IFunction>();
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[2] | 58 |
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| 59 | // init functions and terminals based on constraints
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[143] | 60 | foreach (IFunction fun in funLibrary.Group.Operators) {
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[2] | 61 | int maxA, minA;
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[143] | 62 | GetMinMaxArity(fun, out minA, out maxA);
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[2] | 63 | if (maxA == 0) {
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[143] | 64 | terminals.Add(fun);
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[2] | 65 | } else {
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[143] | 66 | functions.Add(fun);
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[2] | 67 | }
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| 68 | }
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| 69 |
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[143] | 70 | allFunctions.AddRange(functions);
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| 71 | allFunctions.AddRange(terminals);
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[2] | 72 | }
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| 73 |
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| 74 | #region random initialization
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[143] | 75 | internal IFunctionTree CreateRandomTree(ICollection<IFunction> allowedFunctions, int maxTreeSize, int maxTreeHeight, bool balanceTrees) {
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[2] | 76 |
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[143] | 77 | int minTreeHeight = allowedFunctions.Select(f => ((IntData)f.GetVariable(GPOperatorLibrary.MIN_TREE_HEIGHT).Value).Data).Min();
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[2] | 78 | if (minTreeHeight > maxTreeHeight)
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| 79 | maxTreeHeight = minTreeHeight;
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| 80 |
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[143] | 81 | int minTreeSize = allowedFunctions.Select(f => ((IntData)f.GetVariable(GPOperatorLibrary.MIN_TREE_SIZE).Value).Data).Min();
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[2] | 82 | if (minTreeSize > maxTreeSize)
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| 83 | maxTreeSize = minTreeSize;
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| 84 |
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| 85 | int treeHeight = random.Next(minTreeHeight, maxTreeHeight + 1);
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| 86 | int treeSize = random.Next(minTreeSize, maxTreeSize + 1);
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| 87 |
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[143] | 88 | IFunction[] possibleFunctions = allowedFunctions.Where(f => ((IntData)f.GetVariable(GPOperatorLibrary.MIN_TREE_HEIGHT).Value).Data <= treeHeight &&
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| 89 | ((IntData)f.GetVariable(GPOperatorLibrary.MIN_TREE_SIZE).Value).Data <= treeSize).ToArray();
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| 90 | IFunction selectedFunction = possibleFunctions[random.Next(possibleFunctions.Length)];
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[2] | 91 |
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[143] | 92 | return CreateRandomTree(selectedFunction, treeSize, treeHeight, balanceTrees);
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[2] | 93 | }
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| 94 |
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[142] | 95 | internal IFunctionTree CreateRandomTree(int maxTreeSize, int maxTreeHeight, bool balanceTrees) {
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[2] | 96 | if (balanceTrees) {
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[23] | 97 | if (maxTreeHeight == 1 || maxTreeSize==1) {
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[143] | 98 | IFunction selectedTerminal = terminals[random.Next(terminals.Count())];
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[142] | 99 | return new FunctionTree(selectedTerminal);
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[2] | 100 | } else {
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[143] | 101 | IFunction[] possibleFunctions = functions.Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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[2] | 102 | GetMinimalTreeSize(f) <= maxTreeSize).ToArray();
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[143] | 103 | IFunction selectedFunction = possibleFunctions[random.Next(possibleFunctions.Length)];
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[142] | 104 | FunctionTree root = new FunctionTree(selectedFunction);
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| 105 | MakeBalancedTree(root, maxTreeSize - 1, maxTreeHeight - 1);
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| 106 | return root;
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[2] | 107 | }
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| 108 |
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| 109 | } else {
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[143] | 110 | IFunction[] possibleFunctions = allFunctions.Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 111 | GetMinimalTreeSize(f) <= maxTreeSize).ToArray();
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| 112 | IFunction selectedFunction = possibleFunctions[random.Next(possibleFunctions.Length)];
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| 113 | FunctionTree root = new FunctionTree(selectedFunction);
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[142] | 114 | MakeUnbalancedTree(root, maxTreeSize - 1, maxTreeHeight - 1);
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| 115 | return root;
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[2] | 116 | }
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| 117 | }
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| 118 |
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[143] | 119 | internal IFunctionTree CreateRandomTree(IFunction rootFunction, int maxTreeSize, int maxTreeHeight, bool balanceTrees) {
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| 120 | IFunctionTree root = new FunctionTree(rootFunction);
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[2] | 121 | if (balanceTrees) {
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| 122 | MakeBalancedTree(root, maxTreeSize - 1, maxTreeHeight - 1);
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| 123 | } else {
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| 124 | MakeUnbalancedTree(root, maxTreeSize - 1, maxTreeHeight - 1);
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| 125 | }
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| 126 | if (GetTreeSize(root) > maxTreeSize ||
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| 127 | GetTreeHeight(root) > maxTreeHeight) {
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| 128 | throw new InvalidProgramException();
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| 129 | }
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| 130 | return root;
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| 131 | }
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| 132 |
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| 133 |
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[142] | 134 | private void MakeUnbalancedTree(IFunctionTree parent, int maxTreeSize, int maxTreeHeight) {
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[2] | 135 | if (maxTreeHeight == 0 || maxTreeSize == 0) return;
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| 136 | int minArity;
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| 137 | int maxArity;
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[142] | 138 | GetMinMaxArity(parent.Function, out minArity, out maxArity);
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[2] | 139 | if (maxArity >= maxTreeSize) {
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| 140 | maxArity = maxTreeSize;
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| 141 | }
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| 142 | int actualArity = random.Next(minArity, maxArity + 1);
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| 143 | if (actualArity > 0) {
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| 144 | int maxSubTreeSize = maxTreeSize / actualArity;
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| 145 | for (int i = 0; i < actualArity; i++) {
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[143] | 146 | IFunction[] possibleFunctions = GetAllowedSubFunctions(parent.Function, i).Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 147 | GetMinimalTreeSize(f) <= maxSubTreeSize).ToArray();
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| 148 | IFunction selectedFunction = possibleFunctions[random.Next(possibleFunctions.Length)];
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| 149 | FunctionTree newSubTree = new FunctionTree(selectedFunction);
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[142] | 150 | MakeUnbalancedTree(newSubTree, maxSubTreeSize - 1, maxTreeHeight - 1);
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| 151 | parent.InsertSubTree(i, newSubTree);
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[2] | 152 | }
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| 153 | }
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| 154 | }
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| 155 |
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| 156 | // NOTE: this method doesn't build fully balanced trees because we have constraints on the
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[143] | 157 | // types of possible sub-functions which can indirectly impose a limit for the depth of a given sub-tree
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[142] | 158 | private void MakeBalancedTree(IFunctionTree parent, int maxTreeSize, int maxTreeHeight) {
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[2] | 159 | if (maxTreeHeight == 0 || maxTreeSize == 0) return; // should never happen anyway
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| 160 | int minArity;
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| 161 | int maxArity;
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[142] | 162 | GetMinMaxArity(parent.Function, out minArity, out maxArity);
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[2] | 163 | if (maxArity >= maxTreeSize) {
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| 164 | maxArity = maxTreeSize;
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| 165 | }
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| 166 | int actualArity = random.Next(minArity, maxArity + 1);
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| 167 | if (actualArity > 0) {
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| 168 | int maxSubTreeSize = maxTreeSize / actualArity;
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| 169 | for (int i = 0; i < actualArity; i++) {
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| 170 | if (maxTreeHeight == 1 || maxSubTreeSize == 1) {
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[143] | 171 | IFunction[] possibleTerminals = GetAllowedSubFunctions(parent.Function, i).Where(
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| 172 | f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 173 | GetMinimalTreeSize(f) <= maxSubTreeSize &&
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| 174 | IsTerminal(f)).ToArray();
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| 175 | IFunction selectedTerminal = possibleTerminals[random.Next(possibleTerminals.Length)];
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[142] | 176 | IFunctionTree newTree = new FunctionTree(selectedTerminal);
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| 177 | parent.InsertSubTree(i, newTree);
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[2] | 178 | } else {
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[143] | 179 | IFunction[] possibleFunctions = GetAllowedSubFunctions(parent.Function, i).Where(
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| 180 | f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 181 | GetMinimalTreeSize(f) <= maxSubTreeSize &&
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| 182 | !IsTerminal(f)).ToArray();
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| 183 | IFunction selectedFunction = possibleFunctions[random.Next(possibleFunctions.Length)];
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[142] | 184 | FunctionTree newTree = new FunctionTree(selectedFunction);
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| 185 | parent.InsertSubTree(i, newTree);
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| 186 | MakeBalancedTree(newTree, maxSubTreeSize - 1, maxTreeHeight - 1);
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[2] | 187 | }
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| 188 | }
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| 189 | }
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| 190 | }
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| 191 |
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[142] | 192 | internal CompositeOperation CreateInitializationOperation(ICollection<IFunctionTree> trees, IScope scope) {
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[2] | 193 | // needed for the parameter shaking operation
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| 194 | CompositeOperation initializationOperation = new CompositeOperation();
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| 195 | Scope tempScope = new Scope("Temp. initialization scope");
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| 196 |
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[143] | 197 | var parametricTrees = trees.Where(t => t.Function.GetVariable(GPOperatorLibrary.INITIALIZATION) != null);
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[2] | 198 |
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[142] | 199 | foreach (IFunctionTree tree in parametricTrees) {
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[2] | 200 | // enqueue an initialization operation for each operator with local variables
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[142] | 201 | IOperator initialization = (IOperator)tree.Function.GetVariable(GPOperatorLibrary.INITIALIZATION).Value;
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[2] | 202 | Scope initScope = new Scope();
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| 203 |
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| 204 | // copy the local variables into a temporary scope used for initialization
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[142] | 205 | foreach (IVariable variable in tree.LocalVariables) {
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| 206 | initScope.AddVariable(variable);
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[2] | 207 | }
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| 208 |
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| 209 | tempScope.AddSubScope(initScope);
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| 210 | initializationOperation.AddOperation(new AtomicOperation(initialization, initScope));
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| 211 | }
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| 212 |
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| 213 | Scope backupScope = new Scope("backup");
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| 214 | foreach (Scope subScope in scope.SubScopes) {
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| 215 | backupScope.AddSubScope(subScope);
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| 216 | }
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| 217 |
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| 218 | scope.AddSubScope(tempScope);
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| 219 | scope.AddSubScope(backupScope);
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| 220 |
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| 221 | // add an operation to remove the temporary scopes
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| 222 | initializationOperation.AddOperation(new AtomicOperation(new RightReducer(), scope));
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| 223 | return initializationOperation;
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| 224 | }
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| 225 | #endregion
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| 226 |
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| 227 | #region tree information gathering
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[142] | 228 | internal int GetTreeSize(IFunctionTree tree) {
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| 229 | return 1 + tree.SubTrees.Sum(f => GetTreeSize(f));
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[2] | 230 | }
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| 231 |
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[142] | 232 | internal int GetTreeHeight(IFunctionTree tree) {
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| 233 | if (tree.SubTrees.Count == 0) return 1;
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| 234 | return 1 + tree.SubTrees.Max(f => GetTreeHeight(f));
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[2] | 235 | }
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| 236 |
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[142] | 237 | internal IFunctionTree GetRandomParentNode(IFunctionTree tree) {
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| 238 | List<IFunctionTree> parentNodes = new List<IFunctionTree>();
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[2] | 239 |
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| 240 | // add null for the parent of the root node
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| 241 | parentNodes.Add(null);
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| 242 |
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[142] | 243 | TreeForEach(tree, delegate(IFunctionTree possibleParentNode) {
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| 244 | if (possibleParentNode.SubTrees.Count > 0) {
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| 245 | parentNodes.Add(possibleParentNode);
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[2] | 246 | }
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| 247 | });
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| 248 |
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| 249 | return parentNodes[random.Next(parentNodes.Count)];
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| 250 | }
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| 251 |
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[143] | 252 | internal IList<IFunction> GetAllowedSubFunctions(IFunction f, int index) {
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| 253 | if (f == null) {
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| 254 | return allFunctions;
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[2] | 255 | } else {
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| 256 |
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| 257 | SubOperatorsConstraintAnalyser analyser = new SubOperatorsConstraintAnalyser();
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[143] | 258 | analyser.AllPossibleOperators = allFunctions.Cast<IOperator>().ToArray<IOperator>();
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[2] | 259 |
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[143] | 260 | return analyser.GetAllowedOperators(f, index).Cast<IFunction>().ToList<IFunction>();
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[2] | 261 | }
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| 262 | }
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[143] | 263 | internal void GetMinMaxArity(IFunction f, out int minArity, out int maxArity) {
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| 264 | foreach (IConstraint constraint in f.Constraints) {
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[2] | 265 | NumberOfSubOperatorsConstraint theConstraint = constraint as NumberOfSubOperatorsConstraint;
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| 266 | if (theConstraint != null) {
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| 267 | minArity = theConstraint.MinOperators.Data;
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| 268 | maxArity = theConstraint.MaxOperators.Data;
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| 269 | return;
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| 270 | }
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| 271 | }
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| 272 | // the default arity is 2
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| 273 | minArity = 2;
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| 274 | maxArity = 2;
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| 275 | }
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[143] | 276 | internal bool IsTerminal(IFunction f) {
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[2] | 277 | int minArity;
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| 278 | int maxArity;
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| 279 | GetMinMaxArity(f, out minArity, out maxArity);
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| 280 | return minArity == 0 && maxArity == 0;
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| 281 | }
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| 282 |
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[143] | 283 | internal IList<IFunction> GetAllowedParents(IFunction child, int childIndex) {
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| 284 | List<IFunction> parents = new List<IFunction>();
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| 285 | foreach (IFunction function in functions) {
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| 286 | IList<IFunction> allowedSubFunctions = GetAllowedSubFunctions(function, childIndex);
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| 287 | if (allowedSubFunctions.Contains(child, new FunctionEqualityComparer())) {
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[2] | 288 | parents.Add(function);
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| 289 | }
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| 290 | }
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| 291 | return parents;
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| 292 | }
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| 293 |
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[143] | 294 | internal ICollection<IFunctionTree> GetAllSubTrees(IFunctionTree root) {
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| 295 | List<IFunctionTree> allTrees = new List<IFunctionTree>();
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| 296 | TreeForEach(root, t => { allTrees.Add(t); });
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| 297 | return allTrees;
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[2] | 298 | }
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| 299 |
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| 300 | /// <summary>
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[143] | 301 | /// returns the height level of branch in the tree
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| 302 | /// if the branch == tree => 1
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| 303 | /// if branch is in the sub-trees of tree => 2
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[2] | 304 | /// ...
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[143] | 305 | /// if branch is not found => -1
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[2] | 306 | /// </summary>
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[143] | 307 | /// <param name="tree">root of the function tree to process</param>
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| 308 | /// <param name="branch">branch that is searched in the tree</param>
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[2] | 309 | /// <returns></returns>
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[143] | 310 | internal int GetBranchLevel(IFunctionTree tree, IFunctionTree branch) {
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| 311 | return GetBranchLevelHelper(tree, branch, 1);
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[2] | 312 | }
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| 313 |
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[143] | 314 | // 'tail-recursive' helper
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| 315 | private int GetBranchLevelHelper(IFunctionTree tree, IFunctionTree branch, int level) {
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| 316 | if (branch == tree) return level;
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[2] | 317 |
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[142] | 318 | foreach (IFunctionTree subTree in tree.SubTrees) {
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[143] | 319 | int result = GetBranchLevelHelper(subTree, branch, level + 1);
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[2] | 320 | if (result != -1) return result;
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| 321 | }
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| 322 |
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| 323 | return -1;
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| 324 | }
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| 325 |
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[142] | 326 | internal bool IsValidTree(IFunctionTree tree) {
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[145] | 327 | foreach(IConstraint constraint in tree.Function.Constraints) {
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| 328 | if(constraint is NumberOfSubOperatorsConstraint) {
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| 329 | int max = ((NumberOfSubOperatorsConstraint)constraint).MaxOperators.Data;
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| 330 | int min = ((NumberOfSubOperatorsConstraint)constraint).MinOperators.Data;
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| 331 | if(tree.SubTrees.Count < min || tree.SubTrees.Count > max) return false;
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| 332 | }
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[2] | 333 | }
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[145] | 334 | foreach(IFunctionTree subTree in tree.SubTrees) {
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| 335 | if(!IsValidTree(subTree)) return false;
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| 336 | }
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[2] | 337 | return true;
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| 338 | }
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| 339 |
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[143] | 340 | // returns a random branch from the specified level in the tree
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| 341 | internal IFunctionTree GetRandomBranch(IFunctionTree tree, int level) {
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[2] | 342 | if (level == 0) return tree;
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[143] | 343 | List<IFunctionTree> branches = GetBranchesAtLevel(tree, level);
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| 344 | return branches[random.Next(branches.Count)];
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[2] | 345 | }
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| 346 | #endregion
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| 347 |
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| 348 | #region private utility methods
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| 349 |
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| 350 | private int GetMinimalTreeHeight(IOperator op) {
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| 351 | return ((IntData)op.GetVariable(GPOperatorLibrary.MIN_TREE_HEIGHT).Value).Data;
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| 352 | }
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| 353 |
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| 354 | private int GetMinimalTreeSize(IOperator op) {
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| 355 | return ((IntData)op.GetVariable(GPOperatorLibrary.MIN_TREE_SIZE).Value).Data;
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| 356 | }
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| 357 |
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[142] | 358 | private void TreeForEach(IFunctionTree tree, Action<IFunctionTree> action) {
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[2] | 359 | action(tree);
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[142] | 360 | foreach (IFunctionTree subTree in tree.SubTrees) {
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| 361 | TreeForEach(subTree, action);
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[2] | 362 | }
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| 363 | }
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| 364 |
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[143] | 365 | private List<IFunctionTree> GetBranchesAtLevel(IFunctionTree tree, int level) {
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[142] | 366 | if (level == 1) return new List<IFunctionTree>(tree.SubTrees);
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[2] | 367 |
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[143] | 368 | List<IFunctionTree> branches = new List<IFunctionTree>();
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[142] | 369 | foreach (IFunctionTree subTree in tree.SubTrees) {
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[143] | 370 | branches.AddRange(GetBranchesAtLevel(subTree, level - 1));
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[2] | 371 | }
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[143] | 372 | return branches;
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[2] | 373 | }
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| 374 |
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| 375 |
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| 376 | #endregion
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| 377 |
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[143] | 378 | internal class FunctionEqualityComparer : IEqualityComparer<IFunction> {
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| 379 | #region IEqualityComparer<IFunction> Members
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| 380 | public bool Equals(IFunction x, IFunction y) {
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[142] | 381 | return x==y ||
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| 382 | ((StringData)x.GetVariable(GPOperatorLibrary.TYPE_ID).Value).Data ==
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[2] | 383 | ((StringData)y.GetVariable(GPOperatorLibrary.TYPE_ID).Value).Data;
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| 384 | }
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| 385 |
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[143] | 386 | public int GetHashCode(IFunction obj) {
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[2] | 387 | return ((StringData)obj.GetVariable(GPOperatorLibrary.TYPE_ID).Value).Data.GetHashCode();
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| 388 | }
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| 389 | #endregion
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| 390 | }
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| 391 |
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[143] | 392 | internal ICollection<IFunction> GetPossibleParents(List<IFunction> list) {
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| 393 | List<IFunction> result = new List<IFunction>();
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| 394 | foreach (IFunction f in functions) {
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| 395 | if (IsPossibleParent(f, list)) {
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| 396 | result.Add(f);
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[2] | 397 | }
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| 398 | }
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| 399 | return result;
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| 400 | }
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| 401 |
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[143] | 402 | private bool IsPossibleParent(IFunction f, List<IFunction> children) {
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[2] | 403 | int minArity;
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| 404 | int maxArity;
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[143] | 405 | GetMinMaxArity(f, out minArity, out maxArity);
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[2] | 406 |
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| 407 | // note: we can't assume that the operators in the children list have different types!
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| 408 |
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| 409 | // when the maxArity of this function is smaller than the list of operators that
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| 410 | // should be included as sub-operators then it can't be a parent
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| 411 | if (maxArity < children.Count()) {
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| 412 | return false;
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| 413 | }
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| 414 | int nSlots = Math.Max(minArity, children.Count);
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| 415 |
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| 416 | SubOperatorsConstraintAnalyser analyzer = new SubOperatorsConstraintAnalyser();
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[143] | 417 | analyzer.AllPossibleOperators = children.Cast<IOperator>().ToArray<IOperator>();
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[2] | 418 |
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[143] | 419 | List<HashSet<IFunction>> slotSets = new List<HashSet<IFunction>>();
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[2] | 420 |
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[143] | 421 | // we iterate through all slots for sub-trees and calculate the set of
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| 422 | // allowed functions for this slot.
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[2] | 423 | // we only count those slots that can hold at least one of the children that we should combine
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| 424 | for (int slot = 0; slot < nSlots; slot++) {
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[143] | 425 | HashSet<IFunction> functionSet = new HashSet<IFunction>(analyzer.GetAllowedOperators(f, slot).Cast<IFunction>());
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| 426 | if (functionSet.Count() > 0) {
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| 427 | slotSets.Add(functionSet);
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[2] | 428 | }
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| 429 | }
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| 430 |
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| 431 | // ok at the end of this operation we know how many slots of the parent can actually
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| 432 | // hold one of our children.
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| 433 | // if the number of slots is smaller than the number of children we can be sure that
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[143] | 434 | // we can never combine all children as sub-trees of the function and thus the function
|
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[2] | 435 | // can't be a parent.
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| 436 | if (slotSets.Count() < children.Count()) {
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| 437 | return false;
|
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| 438 | }
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| 439 |
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| 440 | // finally we sort the sets by size and beginning from the first set select one
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[143] | 441 | // function for the slot and thus remove it as possible sub-tree from the remaining sets.
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| 442 | // when we can successfully assign all available children to a slot the function is a valid parent
|
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| 443 | // when only a subset of all children can be assigned to slots the function is no valid parent
|
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[2] | 444 | slotSets.Sort((p, q) => p.Count() - q.Count());
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| 445 |
|
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| 446 | int assignments = 0;
|
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| 447 | for (int i = 0; i < slotSets.Count() - 1; i++) {
|
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| 448 | if (slotSets[i].Count > 0) {
|
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[143] | 449 | IFunction selected = slotSets[i].ElementAt(0);
|
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[2] | 450 | assignments++;
|
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| 451 | for (int j = i + 1; j < slotSets.Count(); j++) {
|
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| 452 | slotSets[j].Remove(selected);
|
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| 453 | }
|
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| 454 | }
|
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| 455 | }
|
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| 456 |
|
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| 457 | // sanity check
|
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| 458 | if (assignments > children.Count) throw new InvalidProgramException();
|
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| 459 | return assignments == children.Count - 1;
|
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| 460 | }
|
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| 461 | }
|
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| 462 | }
|
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