[645] | 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 System.Collections;
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| 33 | using HeuristicLab.Selection;
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| 34 |
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| 35 | namespace HeuristicLab.GP {
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| 36 | internal class TreeGardener {
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| 37 | private IRandom random;
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| 38 | private GPOperatorLibrary funLibrary;
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| 39 | private List<IFunction> functions;
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| 40 |
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| 41 | private List<IFunction> terminals;
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| 42 | internal IList<IFunction> Terminals {
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| 43 | get { return terminals; }
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| 44 | }
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| 45 |
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| 46 | private List<IFunction> allFunctions;
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| 47 | internal IList<IFunction> AllFunctions {
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| 48 | get { return allFunctions; }
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| 49 | }
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| 50 |
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| 51 | #region constructors
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| 52 | internal TreeGardener(IRandom random, GPOperatorLibrary funLibrary) {
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| 53 | this.random = random;
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| 54 | this.funLibrary = funLibrary;
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| 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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| 58 | // init functions and terminals based on constraints
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| 59 | foreach(IFunction fun in funLibrary.Group.Operators) {
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| 60 | if(fun.MaxArity == 0) {
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| 61 | terminals.Add(fun);
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| 62 | allFunctions.Add(fun);
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| 63 | } else {
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| 64 | functions.Add(fun);
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| 65 | allFunctions.Add(fun);
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| 66 | }
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| 67 | }
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| 68 | }
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| 69 | #endregion
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| 70 |
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| 71 | #region random initialization
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| 72 | /// <summary>
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| 73 | /// Creates a random balanced tree with a maximal size and height. When the max-height or max-size are 1 it will return a random terminal.
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| 74 | /// In other cases it will return either a terminal (tree of size 1) or any other tree with a function in it's root (at least height 2).
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| 75 | /// </summary>
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| 76 | /// <param name="maxTreeSize">Maximal size of the tree (number of nodes).</param>
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| 77 | /// <param name="maxTreeHeight">Maximal height of the tree.</param>
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| 78 | /// <returns></returns>
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| 79 | internal IFunctionTree CreateBalancedRandomTree(int maxTreeSize, int maxTreeHeight) {
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| 80 | IFunction rootFunction = GetRandomRoot(maxTreeSize, maxTreeHeight);
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| 81 | IFunctionTree tree = MakeBalancedTree(rootFunction, maxTreeHeight - 1);
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| 82 | return tree;
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| 83 | }
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| 84 |
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| 85 | /// <summary>
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| 86 | /// Creates a random (unbalanced) tree with a maximal size and height. When the max-height or max-size are 1 it will return a random terminal.
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| 87 | /// In other cases it will return either a terminal (tree of size 1) or any other tree with a function in it's root (at least height 2).
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| 88 | /// </summary>
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| 89 | /// <param name="maxTreeSize">Maximal size of the tree (number of nodes).</param>
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| 90 | /// <param name="maxTreeHeight">Maximal height of the tree.</param>
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| 91 | /// <returns></returns>
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| 92 | internal IFunctionTree CreateUnbalancedRandomTree(int maxTreeSize, int maxTreeHeight) {
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| 93 | IFunction rootFunction = GetRandomRoot(maxTreeSize, maxTreeHeight);
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| 94 | IFunctionTree tree = MakeUnbalancedTree(rootFunction, maxTreeHeight - 1);
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| 95 | return tree;
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| 96 | }
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| 97 |
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| 98 | internal IFunctionTree PTC2(IRandom random, int size, int maxDepth) {
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| 99 | return PTC2(random, GetRandomRoot(size, maxDepth), size, maxDepth);
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| 100 | }
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| 101 |
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| 102 | internal IFunctionTree PTC2(IRandom random, IFunction rootF, int size, int maxDepth) {
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| 103 | IFunctionTree root = rootF.GetTreeNode();
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| 104 | if(size <= 1 || maxDepth <= 1) return root;
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| 105 | List<object[]> list = new List<object[]>();
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| 106 | int currentSize = 1;
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| 107 | int totalListMinSize = 0;
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| 108 | int minArity = root.Function.MinArity;
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| 109 | int maxArity = root.Function.MaxArity;
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| 110 | if(maxArity >= size) {
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| 111 | maxArity = size;
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| 112 | }
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| 113 | int actualArity = random.Next(minArity, maxArity + 1);
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| 114 | totalListMinSize += GetMinimalTreeSize(root.Function) - 1;
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| 115 | for(int i = 0; i < actualArity; i++) {
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| 116 | // insert a dummy sub-tree and add the pending extension to the list
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| 117 | root.AddSubTree(null);
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| 118 | list.Add(new object[] { root, i, 2 });
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| 119 | }
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| 120 |
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| 121 | while(list.Count > 0 && totalListMinSize + currentSize < size) {
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| 122 | int randomIndex = random.Next(list.Count);
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| 123 | object[] nextExtension = list[randomIndex];
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| 124 | list.RemoveAt(randomIndex);
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| 125 | IFunctionTree parent = (IFunctionTree)nextExtension[0];
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| 126 | int a = (int)nextExtension[1];
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| 127 | int d = (int)nextExtension[2];
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| 128 | if(d == maxDepth) {
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| 129 | parent.RemoveSubTree(a);
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| 130 | IFunctionTree branch = CreateRandomTree(GetAllowedSubFunctions(parent.Function, a), 1, 1);
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| 131 | parent.InsertSubTree(a, branch); // insert a smallest possible tree
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| 132 | currentSize += branch.Size;
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| 133 | totalListMinSize -= branch.Size;
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| 134 | } else {
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| 135 | IFunction selectedFunction = RandomSelect(GetAllowedSubFunctions(parent.Function, a).Where(
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| 136 | f => !IsTerminal(f) && GetMinimalTreeHeight(f) + (d - 1) <= maxDepth).ToArray());
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| 137 | IFunctionTree newTree = selectedFunction.GetTreeNode();
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| 138 | parent.RemoveSubTree(a);
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| 139 | parent.InsertSubTree(a, newTree);
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| 140 | currentSize++;
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| 141 | totalListMinSize--;
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| 142 |
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| 143 | minArity = selectedFunction.MinArity;
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| 144 | maxArity = selectedFunction.MaxArity;
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| 145 | if(maxArity >= size) {
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| 146 | maxArity = size;
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| 147 | }
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| 148 | actualArity = random.Next(minArity, maxArity + 1);
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| 149 | for(int i = 0; i < actualArity; i++) {
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| 150 | // insert a dummy sub-tree and add the pending extension to the list
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| 151 | newTree.AddSubTree(null);
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| 152 | list.Add(new object[] { newTree, i, d + 1 });
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| 153 | }
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| 154 | totalListMinSize += GetMinimalTreeSize(newTree.Function) - 1;
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| 155 | }
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| 156 | }
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| 157 | while(list.Count > 0) {
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| 158 | int randomIndex = random.Next(list.Count);
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| 159 | object[] nextExtension = list[randomIndex];
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| 160 | list.RemoveAt(randomIndex);
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| 161 | IFunctionTree parent = (IFunctionTree)nextExtension[0];
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| 162 | int a = (int)nextExtension[1];
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| 163 | int d = (int)nextExtension[2];
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| 164 | parent.RemoveSubTree(a);
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| 165 | parent.InsertSubTree(a,
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| 166 | CreateRandomTree(GetAllowedSubFunctions(parent.Function, a), 1, 1)); // append a tree with minimal possible height
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| 167 | }
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| 168 | return root;
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| 169 | }
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| 170 |
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| 171 | /// <summary>
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| 172 | /// selects a random function from allowedFunctions and creates a random (unbalanced) tree with maximal size and height.
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| 173 | /// </summary>
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| 174 | /// <param name="allowedFunctions">Set of allowed functions.</param>
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| 175 | /// <param name="maxTreeSize">Maximal size of the tree (number of nodes).</param>
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| 176 | /// <param name="maxTreeHeight">Maximal height of the tree.</param>
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| 177 | /// <returns>New random unbalanced tree</returns>
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| 178 | internal IFunctionTree CreateRandomTree(ICollection<IFunction> allowedFunctions, int maxTreeSize, int maxTreeHeight) {
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| 179 | // get the minimal needed height based on allowed functions and extend the max-height if necessary
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| 180 | int minTreeHeight = allowedFunctions.Select(f => GetMinimalTreeHeight(f)).Min();
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| 181 | if(minTreeHeight > maxTreeHeight)
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| 182 | maxTreeHeight = minTreeHeight;
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| 183 | // get the minimal needed size based on allowed functions and extend the max-size if necessary
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| 184 | int minTreeSize = allowedFunctions.Select(f => GetMinimalTreeSize(f)).Min();
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| 185 | if(minTreeSize > maxTreeSize)
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| 186 | maxTreeSize = minTreeSize;
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| 187 |
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| 188 | // select a random value for the size and height
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| 189 | int treeHeight = random.Next(minTreeHeight, maxTreeHeight + 1);
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| 190 | int treeSize = random.Next(minTreeSize, maxTreeSize + 1);
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| 191 |
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| 192 | // filter the set of allowed functions and select only from those that fit into the given maximal size and height limits
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| 193 | IFunction[] possibleFunctions = allowedFunctions.Where(f => GetMinimalTreeHeight(f) <= treeHeight &&
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| 194 | GetMinimalTreeSize(f) <= treeSize).ToArray();
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| 195 | IFunction selectedFunction = RandomSelect(possibleFunctions);
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| 196 |
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| 197 | // build the tree
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| 198 | IFunctionTree root;
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| 199 | root = PTC2(random, selectedFunction, maxTreeSize, maxTreeHeight);
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| 200 | return root;
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| 201 | }
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| 202 |
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| 203 | internal CompositeOperation CreateInitializationOperation(ICollection<IFunctionTree> trees, IScope scope) {
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| 204 | // needed for the parameter shaking operation
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| 205 | CompositeOperation initializationOperation = new CompositeOperation();
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| 206 | Scope tempScope = new Scope("Temp. initialization scope");
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| 207 |
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| 208 | var parametricTrees = trees.Where(t => t.Function.GetVariable(FunctionBase.INITIALIZATION) != null);
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| 209 | foreach(IFunctionTree tree in parametricTrees) {
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| 210 | // enqueue an initialization operation for each operator with local variables
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| 211 | IOperator initialization = (IOperator)tree.Function.GetVariable(FunctionBase.INITIALIZATION).Value;
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| 212 | Scope initScope = new Scope();
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| 213 | // copy the local variables into a temporary scope used for initialization
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| 214 | foreach(IVariable variable in tree.LocalVariables) {
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| 215 | initScope.AddVariable(variable);
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| 216 | }
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| 217 | tempScope.AddSubScope(initScope);
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| 218 | initializationOperation.AddOperation(new AtomicOperation(initialization, initScope));
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| 219 | }
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| 220 | Scope backupScope = new Scope("backup");
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| 221 | foreach(Scope subScope in scope.SubScopes) {
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| 222 | backupScope.AddSubScope(subScope);
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| 223 | }
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| 224 | scope.AddSubScope(tempScope);
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| 225 | scope.AddSubScope(backupScope);
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| 226 | // add an operation to remove the temporary scopes
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| 227 | initializationOperation.AddOperation(new AtomicOperation(new RightReducer(), scope));
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| 228 | return initializationOperation;
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| 229 | }
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| 230 | #endregion
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| 231 |
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| 232 | #region tree information gathering
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| 233 | internal IFunctionTree GetRandomParentNode(IFunctionTree tree) {
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| 234 | List<IFunctionTree> parentNodes = new List<IFunctionTree>();
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| 235 |
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| 236 | // add null for the parent of the root node
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| 237 | parentNodes.Add(null);
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| 238 |
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| 239 | TreeForEach(tree, delegate(IFunctionTree possibleParentNode) {
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| 240 | if(possibleParentNode.SubTrees.Count > 0) {
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| 241 | parentNodes.Add(possibleParentNode);
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| 242 | }
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| 243 | });
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| 244 |
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| 245 | return parentNodes[random.Next(parentNodes.Count)];
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| 246 | }
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| 247 |
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| 248 | internal ICollection<IFunctionTree> GetAllSubTrees(IFunctionTree root) {
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| 249 | List<IFunctionTree> allTrees = new List<IFunctionTree>();
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| 250 | TreeForEach(root, t => { allTrees.Add(t); });
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| 251 | return allTrees;
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| 252 | }
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| 253 |
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| 254 | /// <summary>
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| 255 | /// returns the height level of branch in the tree
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| 256 | /// if the branch == tree => 1
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| 257 | /// if branch is in the sub-trees of tree => 2
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| 258 | /// ...
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| 259 | /// if branch is not found => -1
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| 260 | /// </summary>
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| 261 | /// <param name="tree">root of the function tree to process</param>
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| 262 | /// <param name="branch">branch that is searched in the tree</param>
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| 263 | /// <returns></returns>
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| 264 | internal int GetBranchLevel(IFunctionTree tree, IFunctionTree branch) {
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| 265 | return GetBranchLevelHelper(tree, branch, 1);
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| 266 | }
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| 267 |
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| 268 | // 'tail-recursive' helper
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| 269 | private int GetBranchLevelHelper(IFunctionTree tree, IFunctionTree branch, int level) {
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| 270 | if(branch == tree) return level;
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| 271 |
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| 272 | foreach(IFunctionTree subTree in tree.SubTrees) {
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| 273 | int result = GetBranchLevelHelper(subTree, branch, level + 1);
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| 274 | if(result != -1) return result;
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| 275 | }
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| 276 |
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| 277 | return -1;
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| 278 | }
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| 279 |
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| 280 | internal bool IsValidTree(IFunctionTree tree) {
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| 281 | for(int i = 0; i < tree.SubTrees.Count; i++) {
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| 282 | if(!tree.Function.AllowedSubFunctions(i).Contains(tree.SubTrees[i].Function)) return false;
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| 283 | }
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| 284 |
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| 285 | if(tree.SubTrees.Count < tree.Function.MinArity || tree.SubTrees.Count > tree.Function.MaxArity)
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| 286 | return false;
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| 287 | foreach(IFunctionTree subTree in tree.SubTrees) {
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| 288 | if(!IsValidTree(subTree)) return false;
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| 289 | }
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| 290 | return true;
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| 291 | }
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| 292 |
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| 293 | // returns a random branch from the specified level in the tree
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| 294 | internal IFunctionTree GetRandomBranch(IFunctionTree tree, int level) {
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| 295 | if(level == 0) return tree;
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| 296 | List<IFunctionTree> branches = new List<IFunctionTree>();
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| 297 | GetBranchesAtLevel(tree, level, branches);
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| 298 | return branches[random.Next(branches.Count)];
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| 299 | }
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| 300 | #endregion
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| 301 |
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| 302 | #region function information (arity, allowed childs and parents)
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| 303 | internal ICollection<IFunction> GetPossibleParents(List<IFunction> list) {
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| 304 | List<IFunction> result = new List<IFunction>();
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| 305 | foreach(IFunction f in functions) {
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| 306 | if(IsPossibleParent(f, list)) {
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| 307 | result.Add(f);
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| 308 | }
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| 309 | }
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| 310 | return result;
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| 311 | }
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| 312 |
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| 313 | private bool IsPossibleParent(IFunction f, List<IFunction> children) {
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| 314 | int minArity = f.MinArity;
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| 315 | int maxArity = f.MaxArity;
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| 316 | // note: we can't assume that the operators in the children list have different types!
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| 317 |
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| 318 | // when the maxArity of this function is smaller than the list of operators that
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| 319 | // should be included as sub-operators then it can't be a parent
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| 320 | if(maxArity < children.Count()) {
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| 321 | return false;
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| 322 | }
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| 323 | int nSlots = Math.Max(minArity, children.Count);
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| 324 |
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| 325 | List<HashSet<IFunction>> slotSets = new List<HashSet<IFunction>>();
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| 326 |
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| 327 | // we iterate through all slots for sub-trees and calculate the set of
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| 328 | // allowed functions for this slot.
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| 329 | // we only count those slots that can hold at least one of the children that we should combine
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| 330 | for(int slot = 0; slot < nSlots; slot++) {
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| 331 | HashSet<IFunction> functionSet = new HashSet<IFunction>(f.AllowedSubFunctions(slot));
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| 332 | if(functionSet.Count() > 0) {
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| 333 | slotSets.Add(functionSet);
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| 334 | }
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| 335 | }
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| 336 |
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| 337 | // ok at the end of this operation we know how many slots of the parent can actually
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| 338 | // hold one of our children.
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| 339 | // if the number of slots is smaller than the number of children we can be sure that
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| 340 | // we can never combine all children as sub-trees of the function and thus the function
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| 341 | // can't be a parent.
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| 342 | if(slotSets.Count() < children.Count()) {
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| 343 | return false;
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| 344 | }
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| 345 |
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| 346 | // finally we sort the sets by size and beginning from the first set select one
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| 347 | // function for the slot and thus remove it as possible sub-tree from the remaining sets.
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| 348 | // when we can successfully assign all available children to a slot the function is a valid parent
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| 349 | // when only a subset of all children can be assigned to slots the function is no valid parent
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| 350 | slotSets.Sort((p, q) => p.Count() - q.Count());
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| 351 |
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| 352 | int assignments = 0;
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| 353 | for(int i = 0; i < slotSets.Count() - 1; i++) {
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| 354 | if(slotSets[i].Count > 0) {
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| 355 | IFunction selected = slotSets[i].ElementAt(0);
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| 356 | assignments++;
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| 357 | for(int j = i + 1; j < slotSets.Count(); j++) {
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| 358 | slotSets[j].Remove(selected);
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| 359 | }
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| 360 | }
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| 361 | }
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| 362 |
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| 363 | // sanity check
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| 364 | if(assignments > children.Count) throw new InvalidProgramException();
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| 365 | return assignments == children.Count - 1;
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| 366 | }
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| 367 | internal IList<IFunction> GetAllowedParents(IFunction child, int childIndex) {
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| 368 | List<IFunction> parents = new List<IFunction>();
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| 369 | foreach(IFunction function in functions) {
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| 370 | ICollection<IFunction> allowedSubFunctions = GetAllowedSubFunctions(function, childIndex);
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| 371 | if(allowedSubFunctions.Contains(child)) {
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| 372 | parents.Add(function);
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| 373 | }
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| 374 | }
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| 375 | return parents;
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| 376 | }
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| 377 | internal bool IsTerminal(IFunction f) {
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| 378 | return f.MinArity == 0 && f.MaxArity == 0;
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| 379 | }
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| 380 | internal IList<IFunction> GetAllowedSubFunctions(IFunction f, int index) {
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| 381 | if(f == null) {
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| 382 | return allFunctions;
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| 383 | } else {
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| 384 | return f.AllowedSubFunctions(index);
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| 385 | }
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| 386 | }
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| 387 | #endregion
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| 388 |
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| 389 | #region private utility methods
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| 390 | private IFunction GetRandomRoot(int maxTreeSize, int maxTreeHeight) {
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| 391 | if(maxTreeHeight == 1 || maxTreeSize == 1) {
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| 392 | IFunction selectedTerminal = RandomSelect(terminals);
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| 393 | return selectedTerminal;
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| 394 | } else {
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| 395 | IFunction[] possibleFunctions = functions.Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 396 | GetMinimalTreeSize(f) <= maxTreeSize).ToArray();
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| 397 | IFunction selectedFunction = RandomSelect(possibleFunctions);
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| 398 | return selectedFunction;
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| 399 | }
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| 400 | }
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| 401 |
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| 402 |
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| 403 | private IFunctionTree MakeUnbalancedTree(IFunction parent, int maxTreeHeight) {
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| 404 | if(maxTreeHeight == 0) return parent.GetTreeNode();
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| 405 | int minArity = parent.MinArity;
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| 406 | int maxArity = parent.MaxArity;
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| 407 | int actualArity = random.Next(minArity, maxArity + 1);
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| 408 | if(actualArity > 0) {
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| 409 | IFunctionTree parentTree = parent.GetTreeNode();
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| 410 | for(int i = 0; i < actualArity; i++) {
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| 411 | IFunction[] possibleFunctions = GetAllowedSubFunctions(parent, i).Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight).ToArray();
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| 412 | IFunction selectedFunction = RandomSelect(possibleFunctions);
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| 413 | IFunctionTree newSubTree = MakeUnbalancedTree(selectedFunction, maxTreeHeight - 1);
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| 414 | parentTree.InsertSubTree(i, newSubTree);
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| 415 | }
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| 416 | return parentTree;
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| 417 | }
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| 418 | return parent.GetTreeNode();
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| 419 | }
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| 420 |
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| 421 |
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| 422 | // NOTE: this method doesn't build fully balanced trees because we have constraints on the
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| 423 | // types of possible sub-functions which can indirectly impose a limit for the depth of a given sub-tree
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| 424 | private IFunctionTree MakeBalancedTree(IFunction parent, int maxTreeHeight) {
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| 425 | if(maxTreeHeight == 0) return parent.GetTreeNode();
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| 426 | int minArity = parent.MinArity;
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| 427 | int maxArity = parent.MaxArity;
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| 428 | int actualArity = random.Next(minArity, maxArity + 1);
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| 429 | if(actualArity > 0) {
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| 430 | IFunctionTree parentTree = parent.GetTreeNode();
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| 431 | for(int i = 0; i < actualArity; i++) {
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| 432 | // first try to find a function that fits into the maxHeight limit
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| 433 | IFunction[] possibleFunctions = GetAllowedSubFunctions(parent, i).Where(f => GetMinimalTreeHeight(f) <= maxTreeHeight &&
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| 434 | !IsTerminal(f)).ToArray();
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| 435 | // no possible function found => extend function set to terminals
|
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| 436 | if(possibleFunctions.Length == 0) {
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| 437 | possibleFunctions = GetAllowedSubFunctions(parent, i).Where(f => IsTerminal(f)).ToArray();
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| 438 | IFunction selectedTerminal = RandomSelect(possibleFunctions);
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| 439 | IFunctionTree newTree = selectedTerminal.GetTreeNode();
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| 440 | parentTree.InsertSubTree(i, newTree);
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| 441 | } else {
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| 442 | IFunction selectedFunction = RandomSelect(possibleFunctions);
|
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| 443 | IFunctionTree newTree = MakeBalancedTree(selectedFunction, maxTreeHeight - 1);
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| 444 | parentTree.InsertSubTree(i, newTree);
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| 445 | }
|
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| 446 | }
|
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| 447 | return parentTree;
|
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| 448 | }
|
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| 449 | return parent.GetTreeNode();
|
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| 450 | }
|
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| 451 |
|
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| 452 | private int GetMinimalTreeHeight(IOperator op) {
|
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| 453 | return ((IntData)op.GetVariable(GPOperatorLibrary.MIN_TREE_HEIGHT).Value).Data;
|
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| 454 | }
|
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| 455 |
|
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| 456 | private int GetMinimalTreeSize(IOperator op) {
|
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| 457 | return ((IntData)op.GetVariable(GPOperatorLibrary.MIN_TREE_SIZE).Value).Data;
|
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| 458 | }
|
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| 459 |
|
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| 460 | private void TreeForEach(IFunctionTree tree, Action<IFunctionTree> action) {
|
---|
| 461 | action(tree);
|
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| 462 | foreach(IFunctionTree subTree in tree.SubTrees) {
|
---|
| 463 | TreeForEach(subTree, action);
|
---|
| 464 | }
|
---|
| 465 | }
|
---|
| 466 |
|
---|
| 467 | private void GetBranchesAtLevel(IFunctionTree tree, int level, List<IFunctionTree> result) {
|
---|
| 468 | if(level == 1) result.AddRange(tree.SubTrees);
|
---|
| 469 | foreach(IFunctionTree subTree in tree.SubTrees) {
|
---|
| 470 | if(subTree.Height >= level - 1)
|
---|
| 471 | GetBranchesAtLevel(subTree, level - 1, result);
|
---|
| 472 | }
|
---|
| 473 | }
|
---|
| 474 |
|
---|
| 475 | private IFunction RandomSelect(IList<IFunction> functionSet) {
|
---|
| 476 | double[] accumulatedTickets = new double[functionSet.Count];
|
---|
| 477 | double ticketAccumulator = 0;
|
---|
| 478 | int i = 0;
|
---|
| 479 | // precalculate the slot-sizes
|
---|
| 480 | foreach(IFunction function in functionSet) {
|
---|
| 481 | ticketAccumulator += ((DoubleData)function.GetVariable(GPOperatorLibrary.TICKETS).Value).Data;
|
---|
| 482 | accumulatedTickets[i] = ticketAccumulator;
|
---|
| 483 | i++;
|
---|
| 484 | }
|
---|
| 485 | // throw ball
|
---|
| 486 | double r = random.NextDouble() * ticketAccumulator;
|
---|
| 487 | // find the slot that has been hit
|
---|
| 488 | for(i = 0; i < accumulatedTickets.Length; i++) {
|
---|
| 489 | if(r < accumulatedTickets[i]) return functionSet[i];
|
---|
| 490 | }
|
---|
| 491 | // sanity check
|
---|
| 492 | throw new InvalidProgramException(); // should never happen
|
---|
| 493 | }
|
---|
| 494 |
|
---|
| 495 | #endregion
|
---|
| 496 |
|
---|
| 497 | }
|
---|
| 498 | }
|
---|