#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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; using System.Diagnostics.Contracts; using System.Linq; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Problems.DataAnalysis.Symbolic; namespace HeuristicLab.Algorithms.DataAnalysis.MctsSymbolicRegression { // translates byte code to a symbolic expression tree internal class SymbolicExpressionTreeGenerator { const int MaxStackSize = 100; private readonly ISymbolicExpressionTreeNode[] stack; private readonly ConstantTreeNode const0; private readonly ConstantTreeNode const1; private readonly Addition addSy; private readonly Multiplication mulSy; private readonly Exponential expSy; private readonly Logarithm logSy; private readonly Division divSy; private readonly VariableTreeNode varNode; private readonly string[] variableNames; private readonly StartSymbol startSy; private readonly ProgramRootSymbol progRootSy; public SymbolicExpressionTreeGenerator(string[] variableNames) { stack = new ISymbolicExpressionTreeNode[MaxStackSize]; var grammar = new TypeCoherentExpressionGrammar(); this.variableNames = variableNames; grammar.ConfigureAsDefaultRegressionGrammar(); const0 = (ConstantTreeNode)grammar.Symbols.OfType().First().CreateTreeNode(); const0.Value = 0; const1 = (ConstantTreeNode)grammar.Symbols.OfType().First().CreateTreeNode(); const1.Value = 1; varNode = (VariableTreeNode)grammar.Symbols.OfType().First().CreateTreeNode(); addSy = grammar.AllowedSymbols.OfType().First(); mulSy = grammar.AllowedSymbols.OfType().First(); logSy = grammar.AllowedSymbols.OfType().First(); expSy = grammar.AllowedSymbols.OfType().First(); divSy = grammar.AllowedSymbols.OfType().First(); progRootSy = grammar.AllowedSymbols.OfType().First(); startSy = grammar.AllowedSymbols.OfType().First(); } public ISymbolicExpressionTreeNode Exec(byte[] code, double[] consts, int nParams, double[] scalingFactor, double[] scalingOffset) { int topOfStack = -1; int pc = 0; int nextParamIdx = -1; OpCodes op; short arg; while (true) { ReadNext(code, ref pc, out op, out arg); switch (op) { case OpCodes.Nop: break; case OpCodes.LoadConst0: { ++topOfStack; stack[topOfStack] = (ISymbolicExpressionTreeNode)const0.Clone(); break; } case OpCodes.LoadConst1: { ++topOfStack; stack[topOfStack] = (ISymbolicExpressionTreeNode)const1.Clone(); break; } case OpCodes.LoadParamN: { ++topOfStack; var p = (ConstantTreeNode)const1.Clone(); // value will be tuned later (evaluator and tree generator both use 1 as initial values) p.Value = consts[++nextParamIdx]; stack[topOfStack] = p; break; } case OpCodes.LoadVar: ++topOfStack; if (scalingOffset != null) { var sumNode = addSy.CreateTreeNode(); var varNode = (VariableTreeNode)this.varNode.Clone(); var constNode = (ConstantTreeNode)const0.Clone(); varNode.Weight = scalingFactor[arg]; varNode.VariableName = variableNames[arg]; constNode.Value = scalingOffset[arg]; sumNode.AddSubtree(varNode); sumNode.AddSubtree(constNode); stack[topOfStack] = sumNode; } else { var varNode = (VariableTreeNode)this.varNode.Clone(); varNode.Weight = 1.0; varNode.VariableName = variableNames[arg]; stack[topOfStack] = varNode; } break; case OpCodes.Add: { var t1 = stack[topOfStack - 1]; var t2 = stack[topOfStack]; topOfStack--; if (t1.Symbol is Addition) { t1.AddSubtree(t2); } else { var addNode = addSy.CreateTreeNode(); addNode.AddSubtree(t1); addNode.AddSubtree(t2); stack[topOfStack] = addNode; } break; } case OpCodes.Mul: { var t1 = stack[topOfStack - 1]; var t2 = stack[topOfStack]; topOfStack--; if (t1.Symbol is Multiplication) { t1.AddSubtree(t2); } else { var mulNode = mulSy.CreateTreeNode(); mulNode.AddSubtree(t1); mulNode.AddSubtree(t2); stack[topOfStack] = mulNode; } break; } case OpCodes.Log: { var v1 = stack[topOfStack]; var logNode = logSy.CreateTreeNode(); logNode.AddSubtree(v1); stack[topOfStack] = logNode; break; } case OpCodes.Exp: { var v1 = stack[topOfStack]; var expNode = expSy.CreateTreeNode(); expNode.AddSubtree(v1); stack[topOfStack] = expNode; break; } case OpCodes.Inv: { var v1 = stack[topOfStack]; var divNode = divSy.CreateTreeNode(); divNode.AddSubtree(v1); stack[topOfStack] = divNode; break; } case OpCodes.Exit: Contract.Assert(topOfStack == 0); var rootNode = progRootSy.CreateTreeNode(); var startNode = startSy.CreateTreeNode(); startNode.AddSubtree(stack[topOfStack]); rootNode.AddSubtree(startNode); return rootNode; } } } private void ReadNext(byte[] code, ref int pc, out OpCodes op, out short s) { op = (OpCodes)Enum.ToObject(typeof(OpCodes), code[pc++]); s = 0; if (op == OpCodes.LoadVar) { s = (short)((code[pc] << 8) | code[pc + 1]); pc += 2; } } } }