#region License Information /* HeuristicLab * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding { public static class SymbolicExpressionTreeLinearCompiler { public static LinearInstruction[] Compile(ISymbolicExpressionTree tree, Func opCodeMapper) { var root = tree.Root.GetSubtree(0).GetSubtree(0); var code = new LinearInstruction[root.GetLength()]; if (root.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)"); code[0] = new LinearInstruction { dynamicNode = root, nArguments = (ushort)root.SubtreeCount, opCode = opCodeMapper(root) }; int c = 1, i = 0; foreach (var node in root.IterateNodesBreadth()) { for (int j = 0; j < node.SubtreeCount; ++j) { var s = node.GetSubtree(j); if (s.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)"); code[c + j] = new LinearInstruction { dynamicNode = s, nArguments = (ushort)s.SubtreeCount, opCode = opCodeMapper(s) }; } code[i].childIndex = c; c += node.SubtreeCount; ++i; } return code; } } }