[17090] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2019 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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[16218] | 24 | using System.Linq;
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| 25 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 26 | using static HeuristicLab.Problems.DataAnalysis.Symbolic.SymbolicExpressionHashExtensions;
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| 27 |
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| 28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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| 29 | public static class SymbolicExpressionTreeHash {
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| 30 | private static readonly Addition add = new Addition();
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| 31 | private static readonly Subtraction sub = new Subtraction();
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| 32 | private static readonly Multiplication mul = new Multiplication();
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| 33 | private static readonly Division div = new Division();
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| 34 | private static readonly Logarithm log = new Logarithm();
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| 35 | private static readonly Exponential exp = new Exponential();
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| 36 | private static readonly Sine sin = new Sine();
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| 37 | private static readonly Cosine cos = new Cosine();
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| 38 | private static readonly Constant constant = new Constant();
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| 39 |
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[17090] | 40 | private static ISymbolicExpressionTreeNode ActualRoot(this ISymbolicExpressionTree tree) => tree.Root.GetSubtree(0).GetSubtree(0);
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[16218] | 41 |
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[17090] | 42 | #region tree hashing
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| 43 | public static ulong[] Hash(this ISymbolicExpressionTree tree, bool simplify = false, bool strict = false) {
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| 44 | return tree.ActualRoot().Hash(simplify, strict);
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[16218] | 45 | }
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| 46 |
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[17090] | 47 | public static ulong[] Hash(this ISymbolicExpressionTreeNode node, bool simplify = false, bool strict = false) {
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| 48 | ulong hashFunction(byte[] input) => HashUtil.DJBHash(input);
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[16218] | 49 |
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[17090] | 50 | var hashNodes = simplify ? node.MakeNodes(strict).Simplify(hashFunction) : node.MakeNodes(strict).Sort(hashFunction);
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| 51 | var hashes = new ulong[hashNodes.Length];
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| 52 | for (int i = 0; i < hashes.Length; ++i) {
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| 53 | hashes[i] = hashNodes[i].CalculatedHashValue;
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[16218] | 54 | }
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[17090] | 55 | return hashes;
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[16218] | 56 | }
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| 57 |
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[17090] | 58 | public static ulong ComputeHash(this ISymbolicExpressionTree tree, bool simplify = false, bool strict = false) {
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| 59 | return ComputeHash(tree.ActualRoot(), simplify, strict);
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[16218] | 60 | }
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| 61 |
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[17090] | 62 | public static ulong ComputeHash(this ISymbolicExpressionTreeNode treeNode, bool simplify = false, bool strict = false) {
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| 63 | return treeNode.Hash(simplify, strict).Last();
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[16218] | 64 | }
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| 65 |
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[17090] | 66 | public static HashNode<ISymbolicExpressionTreeNode> ToHashNode(this ISymbolicExpressionTreeNode node, bool strict = false) {
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[16218] | 67 | var symbol = node.Symbol;
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| 68 | var name = symbol.Name;
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[17090] | 69 | if (node is ConstantTreeNode constantNode) {
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| 70 | name = strict ? constantNode.Value.ToString() : symbol.Name;
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| 71 | } else if (node is VariableTreeNode variableNode) {
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| 72 | name = strict ? variableNode.Weight.ToString() + variableNode.VariableName : variableNode.VariableName;
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[16218] | 73 | }
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[17090] | 74 | var hash = (ulong)name.GetHashCode();
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[17099] | 75 | var hashNode = new HashNode<ISymbolicExpressionTreeNode> {
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[16218] | 76 | Data = node,
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| 77 | Arity = node.SubtreeCount,
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| 78 | Size = node.SubtreeCount,
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| 79 | IsCommutative = node.Symbol is Addition || node.Symbol is Multiplication,
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| 80 | Enabled = true,
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| 81 | HashValue = hash,
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| 82 | CalculatedHashValue = hash
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| 83 | };
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| 84 | if (symbol is Addition) {
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| 85 | hashNode.Simplify = SimplifyAddition;
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| 86 | } else if (symbol is Multiplication) {
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| 87 | hashNode.Simplify = SimplifyMultiplication;
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| 88 | } else if (symbol is Division) {
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| 89 | hashNode.Simplify = SimplifyDivision;
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| 90 | } else if (symbol is Logarithm || symbol is Exponential || symbol is Sine || symbol is Cosine) {
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| 91 | hashNode.Simplify = SimplifyUnaryNode;
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| 92 | } else if (symbol is Subtraction) {
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| 93 | hashNode.Simplify = SimplifyBinaryNode;
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| 94 | }
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| 95 | return hashNode;
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| 96 | }
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| 97 |
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[17090] | 98 | public static HashNode<ISymbolicExpressionTreeNode>[] MakeNodes(this ISymbolicExpressionTree tree, bool strict = false) {
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| 99 | return MakeNodes(tree.ActualRoot(), strict);
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[16218] | 100 | }
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| 101 |
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[17090] | 102 | public static HashNode<ISymbolicExpressionTreeNode>[] MakeNodes(this ISymbolicExpressionTreeNode node, bool strict = false) {
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| 103 | return node.IterateNodesPostfix().Select(x => x.ToHashNode(strict)).ToArray().UpdateNodeSizes();
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| 104 | }
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| 105 | #endregion
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| 106 |
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| 107 | #region tree similarity
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| 108 | public static double ComputeSimilarity(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, bool simplify = false, bool strict = false) {
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| 109 | return ComputeSimilarity(t1.ActualRoot(), t2.ActualRoot(), simplify, strict);
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| 110 | }
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| 111 |
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| 112 | public static double ComputeSimilarity(ISymbolicExpressionTreeNode t1, ISymbolicExpressionTreeNode t2, bool simplify = false, bool strict = false) {
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| 113 | var lh = t1.Hash(simplify, strict);
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| 114 | var rh = t2.Hash(simplify, strict);
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| 115 |
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| 116 | Array.Sort(lh);
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| 117 | Array.Sort(rh);
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| 118 |
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| 119 | return ComputeSimilarity(lh, rh);
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| 120 | }
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| 121 |
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| 122 | // requires lhs and rhs to be sorted
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| 123 | public static int IntersectCount(this ulong[] lh, ulong[] rh) {
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| 124 | int count = 0;
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| 125 | for (int i = 0, j = 0; i < lh.Length && j < rh.Length;) {
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| 126 | var h1 = lh[i];
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| 127 | var h2 = rh[j];
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| 128 | if (h1 == h2) {
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| 129 | ++count;
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| 130 | ++i;
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| 131 | ++j;
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| 132 | } else if (h1 < h2) {
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| 133 | ++i;
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| 134 | } else if (h1 > h2) {
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| 135 | ++j;
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| 136 | }
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| 137 | }
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| 138 | return count;
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| 139 | }
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| 140 |
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| 141 | public static IEnumerable<ulong> Intersect(this ulong[] lh, ulong[] rh) {
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| 142 | for (int i = 0, j = 0; i < lh.Length && j < rh.Length;) {
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| 143 | var h1 = lh[i];
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| 144 | var h2 = rh[j];
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| 145 | if (h1 == h2) {
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| 146 | yield return h1;
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| 147 | ++i;
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| 148 | ++j;
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| 149 | } else if (h1 < h2) {
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| 150 | ++i;
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| 151 | } else if (h1 > h2) {
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| 152 | ++j;
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| 153 | }
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| 154 | }
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| 155 | }
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| 156 |
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| 157 | // this will only work if lh and rh are sorted
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| 158 | public static double ComputeSimilarity(ulong[] lh, ulong[] rh) {
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| 159 | return 2d * IntersectCount(lh, rh) / (lh.Length + rh.Length);
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| 160 | }
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| 161 |
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| 162 | public static double ComputeAverageSimilarity(IList<ISymbolicExpressionTree> trees, bool simplify = false, bool strict = false) {
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| 163 | var total = trees.Count * (trees.Count - 1) / 2;
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| 164 | double avg = 0;
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| 165 | var hashes = new ulong[trees.Count][];
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| 166 | // build hash arrays
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| 167 | for (int i = 0; i < trees.Count; ++i) {
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| 168 | var nodes = trees[i].MakeNodes(strict);
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| 169 | hashes[i] = (simplify ? nodes.Simplify(HashUtil.DJBHash) : nodes.Sort(HashUtil.DJBHash)).Select(x => x.CalculatedHashValue).ToArray();
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| 170 | Array.Sort(hashes[i]);
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| 171 | }
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| 172 | // compute similarity matrix
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| 173 | for (int i = 0; i < trees.Count - 1; ++i) {
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| 174 | for (int j = i + 1; j < trees.Count; ++j) {
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| 175 | avg += ComputeSimilarity(hashes[i], hashes[j]);
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| 176 | }
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| 177 | }
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| 178 | return avg / total;
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| 179 | }
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| 180 |
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| 181 | public static double[,] ComputeSimilarityMatrix(IList<ISymbolicExpressionTree> trees, bool simplify = false, bool strict = false) {
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| 182 | var sim = new double[trees.Count, trees.Count];
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| 183 | var hashes = new ulong[trees.Count][];
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| 184 | // build hash arrays
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| 185 | for (int i = 0; i < trees.Count; ++i) {
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| 186 | var nodes = trees[i].MakeNodes(strict);
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| 187 | hashes[i] = (simplify ? nodes.Simplify(HashUtil.DJBHash) : nodes.Sort(HashUtil.DJBHash)).Select(x => x.CalculatedHashValue).ToArray();
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| 188 | Array.Sort(hashes[i]);
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| 189 | }
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| 190 | // compute similarity matrix
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| 191 | for (int i = 0; i < trees.Count - 1; ++i) {
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| 192 | for (int j = i + 1; j < trees.Count; ++j) {
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| 193 | sim[i, j] = sim[j, i] = ComputeSimilarity(hashes[i], hashes[j]);
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| 194 | }
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| 195 | }
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| 196 | return sim;
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| 197 | }
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| 198 | #endregion
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| 199 |
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[16218] | 200 | #region parse a nodes array back into a tree
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| 201 | public static ISymbolicExpressionTree ToTree(this HashNode<ISymbolicExpressionTreeNode>[] nodes) {
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| 202 | var root = new ProgramRootSymbol().CreateTreeNode();
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| 203 | var start = new StartSymbol().CreateTreeNode();
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| 204 | root.AddSubtree(start);
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| 205 | start.AddSubtree(nodes.ToSubtree());
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| 206 | return new SymbolicExpressionTree(root);
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| 207 | }
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| 208 |
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| 209 | public static ISymbolicExpressionTreeNode ToSubtree(this HashNode<ISymbolicExpressionTreeNode>[] nodes) {
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| 210 | var treeNodes = nodes.Select(x => x.Data.Symbol.CreateTreeNode()).ToArray();
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| 211 |
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| 212 | for (int i = nodes.Length - 1; i >= 0; --i) {
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| 213 | var node = nodes[i];
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| 214 |
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[17090] | 215 | if (node.IsLeaf) {
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[16218] | 216 | if (node.Data is VariableTreeNode variable) {
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| 217 | var variableTreeNode = (VariableTreeNode)treeNodes[i];
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| 218 | variableTreeNode.VariableName = variable.VariableName;
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[17090] | 219 | variableTreeNode.Weight = variable.Weight;
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[16218] | 220 | } else if (node.Data is ConstantTreeNode @const) {
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| 221 | var constantTreeNode = (ConstantTreeNode)treeNodes[i];
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| 222 | constantTreeNode.Value = @const.Value;
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| 223 | }
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| 224 | continue;
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| 225 | }
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| 226 |
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| 227 | var treeNode = treeNodes[i];
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| 228 |
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| 229 | foreach (var j in nodes.IterateChildren(i)) {
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| 230 | treeNode.AddSubtree(treeNodes[j]);
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| 231 | }
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| 232 | }
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| 233 |
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| 234 | return treeNodes.Last();
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| 235 | }
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| 236 |
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| 237 | private static T CreateTreeNode<T>(this ISymbol symbol) where T : class, ISymbolicExpressionTreeNode {
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| 238 | return (T)symbol.CreateTreeNode();
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| 239 | }
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| 240 | #endregion
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| 241 |
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| 242 | #region tree simplification
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| 243 | // these simplification methods rely on the assumption that child nodes of the current node have already been simplified
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[17090] | 244 | // (in other words simplification should be applied in a bottom-up fashion)
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[16218] | 245 | public static ISymbolicExpressionTree Simplify(ISymbolicExpressionTree tree) {
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[17090] | 246 | ulong hashFunction(byte[] bytes) => HashUtil.JSHash(bytes);
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[16218] | 247 | var root = tree.Root.GetSubtree(0).GetSubtree(0);
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| 248 | var nodes = root.MakeNodes();
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[17090] | 249 | var simplified = nodes.Simplify(hashFunction);
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[16218] | 250 | return simplified.ToTree();
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| 251 | }
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| 252 |
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[17090] | 253 | public static void SimplifyAddition(ref HashNode<ISymbolicExpressionTreeNode>[] nodes, int i) {
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[16218] | 254 | // simplify additions of terms by eliminating terms with the same symbol and hash
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| 255 | var children = nodes.IterateChildren(i);
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| 256 |
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[17090] | 257 | // we always assume the child nodes are sorted
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[16218] | 258 | var curr = children[0];
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| 259 | var node = nodes[i];
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| 260 |
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| 261 | foreach (var j in children.Skip(1)) {
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| 262 | if (nodes[j] == nodes[curr]) {
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[17090] | 263 | nodes.SetEnabled(j, false);
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[16218] | 264 | node.Arity--;
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| 265 | } else {
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| 266 | curr = j;
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| 267 | }
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| 268 | }
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| 269 | if (node.Arity == 1) { // if the arity is 1 we don't need the addition node at all
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| 270 | node.Enabled = false;
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| 271 | }
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| 272 | }
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| 273 |
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[17090] | 274 | // simplify multiplications by reducing constants and div terms
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| 275 | public static void SimplifyMultiplication(ref HashNode<ISymbolicExpressionTreeNode>[] nodes, int i) {
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[16218] | 276 | var node = nodes[i];
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| 277 | var children = nodes.IterateChildren(i);
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| 278 |
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| 279 | for (int j = 0; j < children.Length; ++j) {
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| 280 | var c = children[j];
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| 281 | var child = nodes[c];
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| 282 |
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| 283 | if (!child.Enabled)
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| 284 | continue;
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| 285 |
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| 286 | var symbol = child.Data.Symbol;
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| 287 | if (symbol is Constant) {
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| 288 | for (int k = j + 1; k < children.Length; ++k) {
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| 289 | var d = children[k];
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| 290 | if (nodes[d].Data.Symbol is Constant) {
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| 291 | nodes[d].Enabled = false;
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| 292 | node.Arity--;
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| 293 | } else {
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| 294 | break;
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| 295 | }
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| 296 | }
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| 297 | } else if (symbol is Division) {
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| 298 | var div = nodes[c];
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| 299 | var denominator =
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| 300 | div.Arity == 1 ?
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| 301 | nodes[c - 1] : // 1 / x is expressed as div(x) (with a single child)
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| 302 | nodes[c - nodes[c - 1].Size - 2]; // assume division always has arity 1 or 2
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| 303 |
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| 304 | foreach (var d in children) {
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| 305 | if (nodes[d].Enabled && nodes[d] == denominator) {
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| 306 | nodes[c].Enabled = nodes[d].Enabled = denominator.Enabled = false;
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| 307 | node.Arity -= 2; // matching child + division node
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| 308 | break;
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| 309 | }
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| 310 | }
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| 311 | }
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| 312 |
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| 313 | if (node.Arity == 0) { // if everything is simplified this node becomes constant
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| 314 | var constantTreeNode = constant.CreateTreeNode<ConstantTreeNode>();
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| 315 | constantTreeNode.Value = 1;
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| 316 | nodes[i] = constantTreeNode.ToHashNode();
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| 317 | } else if (node.Arity == 1) { // when i have only 1 arg left i can skip this node
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| 318 | node.Enabled = false;
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| 319 | }
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| 320 | }
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| 321 | }
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| 322 |
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[17090] | 323 | public static void SimplifyDivision(ref HashNode<ISymbolicExpressionTreeNode>[] nodes, int i) {
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[16218] | 324 | var node = nodes[i];
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| 325 | var children = nodes.IterateChildren(i);
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| 326 |
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[17090] | 327 | var tmp = nodes;
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| 328 |
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| 329 | if (children.All(x => tmp[x].Data.Symbol is Constant)) {
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[16218] | 330 | var v = ((ConstantTreeNode)nodes[children.First()].Data).Value;
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| 331 | if (node.Arity == 1) {
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| 332 | v = 1 / v;
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| 333 | } else if (node.Arity > 1) {
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| 334 | foreach (var j in children.Skip(1)) {
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| 335 | v /= ((ConstantTreeNode)nodes[j].Data).Value;
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| 336 | }
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| 337 | }
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| 338 | var constantTreeNode = constant.CreateTreeNode<ConstantTreeNode>();
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| 339 | constantTreeNode.Value = v;
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| 340 | nodes[i] = constantTreeNode.ToHashNode();
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| 341 | return;
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| 342 | }
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| 343 |
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| 344 | var nominator = nodes[children[0]];
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| 345 | foreach (var j in children.Skip(1)) {
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| 346 | var denominator = nodes[j];
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| 347 | if (nominator == denominator) {
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| 348 | // disable all the children of the division node (nominator and children + denominator and children)
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| 349 | nominator.Enabled = denominator.Enabled = false;
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| 350 | node.Arity -= 2; // nominator + denominator
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| 351 | }
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| 352 | if (node.Arity == 0) {
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| 353 | var constantTreeNode = constant.CreateTreeNode<ConstantTreeNode>();
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| 354 | constantTreeNode.Value = 1; // x / x = 1
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| 355 | nodes[i] = constantTreeNode.ToHashNode();
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| 356 | }
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| 357 | }
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| 358 | }
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| 359 |
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[17090] | 360 | public static void SimplifyUnaryNode(ref HashNode<ISymbolicExpressionTreeNode>[] nodes, int i) {
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[16218] | 361 | // check if the child of the unary node is a constant, then the whole node can be simplified
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| 362 | var parent = nodes[i];
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| 363 | var child = nodes[i - 1];
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| 364 |
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| 365 | var parentSymbol = parent.Data.Symbol;
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| 366 | var childSymbol = child.Data.Symbol;
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| 367 |
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| 368 | if (childSymbol is Constant) {
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| 369 | nodes[i].Enabled = false;
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| 370 | } else if ((parentSymbol is Exponential && childSymbol is Logarithm) || (parentSymbol is Logarithm && childSymbol is Exponential)) {
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| 371 | child.Enabled = parent.Enabled = false;
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| 372 | }
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| 373 | }
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| 374 |
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[17090] | 375 | public static void SimplifyBinaryNode(ref HashNode<ISymbolicExpressionTreeNode>[] nodes, int i) {
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[16218] | 376 | var children = nodes.IterateChildren(i);
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[17090] | 377 | var tmp = nodes;
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| 378 | if (children.All(x => tmp[x].Data.Symbol is Constant)) {
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[16218] | 379 | foreach (var j in children) {
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| 380 | nodes[j].Enabled = false;
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| 381 | }
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| 382 | nodes[i] = constant.CreateTreeNode().ToHashNode();
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| 383 | }
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| 384 | }
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| 385 | #endregion
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| 386 | }
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| 387 | }
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