[5571] | 1 | #region License Information
|
---|
| 2 | /* HeuristicLab
|
---|
[11646] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
[5571] | 4 | *
|
---|
| 5 | * This file is part of HeuristicLab.
|
---|
| 6 | *
|
---|
| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
| 8 | * it under the terms of the GNU General Public License as published by
|
---|
| 9 | * the Free Software Foundation, either version 3 of the License, or
|
---|
| 10 | * (at your option) any later version.
|
---|
| 11 | *
|
---|
| 12 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
| 15 | * GNU General Public License for more details.
|
---|
| 16 | *
|
---|
| 17 | * You should have received a copy of the GNU General Public License
|
---|
| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
| 19 | */
|
---|
| 20 | #endregion
|
---|
| 21 |
|
---|
| 22 | using System;
|
---|
| 23 | using System.Collections.Generic;
|
---|
| 24 | using HeuristicLab.Common;
|
---|
| 25 | using HeuristicLab.Core;
|
---|
[6740] | 26 | using HeuristicLab.Data;
|
---|
[5571] | 27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
[6740] | 28 | using HeuristicLab.Parameters;
|
---|
[5571] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
| 30 |
|
---|
| 31 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
|
---|
| 32 | [StorableClass]
|
---|
| 33 | [Item("SymbolicDataAnalysisExpressionTreeInterpreter", "Interpreter for symbolic expression trees including automatically defined functions.")]
|
---|
[8436] | 34 | public class SymbolicDataAnalysisExpressionTreeInterpreter : ParameterizedNamedItem, ISymbolicDataAnalysisExpressionTreeInterpreter {
|
---|
[5749] | 35 | private const string CheckExpressionsWithIntervalArithmeticParameterName = "CheckExpressionsWithIntervalArithmetic";
|
---|
[7615] | 36 | private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";
|
---|
[5571] | 37 |
|
---|
[8436] | 38 | public override bool CanChangeName { get { return false; } }
|
---|
| 39 | public override bool CanChangeDescription { get { return false; } }
|
---|
[5571] | 40 |
|
---|
[5749] | 41 | #region parameter properties
|
---|
| 42 | public IValueParameter<BoolValue> CheckExpressionsWithIntervalArithmeticParameter {
|
---|
| 43 | get { return (IValueParameter<BoolValue>)Parameters[CheckExpressionsWithIntervalArithmeticParameterName]; }
|
---|
| 44 | }
|
---|
[7615] | 45 |
|
---|
| 46 | public IValueParameter<IntValue> EvaluatedSolutionsParameter {
|
---|
| 47 | get { return (IValueParameter<IntValue>)Parameters[EvaluatedSolutionsParameterName]; }
|
---|
| 48 | }
|
---|
[5749] | 49 | #endregion
|
---|
| 50 |
|
---|
| 51 | #region properties
|
---|
| 52 | public BoolValue CheckExpressionsWithIntervalArithmetic {
|
---|
| 53 | get { return CheckExpressionsWithIntervalArithmeticParameter.Value; }
|
---|
| 54 | set { CheckExpressionsWithIntervalArithmeticParameter.Value = value; }
|
---|
| 55 | }
|
---|
[7615] | 56 |
|
---|
| 57 | public IntValue EvaluatedSolutions {
|
---|
| 58 | get { return EvaluatedSolutionsParameter.Value; }
|
---|
| 59 | set { EvaluatedSolutionsParameter.Value = value; }
|
---|
| 60 | }
|
---|
[5749] | 61 | #endregion
|
---|
| 62 |
|
---|
[5571] | 63 | [StorableConstructor]
|
---|
[8436] | 64 | protected SymbolicDataAnalysisExpressionTreeInterpreter(bool deserializing) : base(deserializing) { }
|
---|
| 65 | protected SymbolicDataAnalysisExpressionTreeInterpreter(SymbolicDataAnalysisExpressionTreeInterpreter original, Cloner cloner) : base(original, cloner) { }
|
---|
[5571] | 66 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
| 67 | return new SymbolicDataAnalysisExpressionTreeInterpreter(this, cloner);
|
---|
| 68 | }
|
---|
| 69 |
|
---|
| 70 | public SymbolicDataAnalysisExpressionTreeInterpreter()
|
---|
[5749] | 71 | : base("SymbolicDataAnalysisExpressionTreeInterpreter", "Interpreter for symbolic expression trees including automatically defined functions.") {
|
---|
| 72 | Parameters.Add(new ValueParameter<BoolValue>(CheckExpressionsWithIntervalArithmeticParameterName, "Switch that determines if the interpreter checks the validity of expressions with interval arithmetic before evaluating the expression.", new BoolValue(false)));
|
---|
[7615] | 73 | Parameters.Add(new ValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
|
---|
[5571] | 74 | }
|
---|
| 75 |
|
---|
[8436] | 76 | protected SymbolicDataAnalysisExpressionTreeInterpreter(string name, string description)
|
---|
| 77 | : base(name, description) {
|
---|
| 78 | Parameters.Add(new ValueParameter<BoolValue>(CheckExpressionsWithIntervalArithmeticParameterName, "Switch that determines if the interpreter checks the validity of expressions with interval arithmetic before evaluating the expression.", new BoolValue(false)));
|
---|
| 79 | Parameters.Add(new ValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
|
---|
| 80 | }
|
---|
| 81 |
|
---|
[7615] | 82 | [StorableHook(HookType.AfterDeserialization)]
|
---|
| 83 | private void AfterDeserialization() {
|
---|
| 84 | if (!Parameters.ContainsKey(EvaluatedSolutionsParameterName))
|
---|
| 85 | Parameters.Add(new ValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
|
---|
| 86 | }
|
---|
| 87 |
|
---|
| 88 | #region IStatefulItem
|
---|
| 89 | public void InitializeState() {
|
---|
| 90 | EvaluatedSolutions.Value = 0;
|
---|
| 91 | }
|
---|
| 92 |
|
---|
| 93 | public void ClearState() {
|
---|
| 94 | }
|
---|
| 95 | #endregion
|
---|
| 96 |
|
---|
[5571] | 97 | public IEnumerable<double> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, Dataset dataset, IEnumerable<int> rows) {
|
---|
[8436] | 98 | if (CheckExpressionsWithIntervalArithmetic.Value)
|
---|
| 99 | throw new NotSupportedException("Interval arithmetic is not yet supported in the symbolic data analysis interpreter.");
|
---|
[7120] | 100 |
|
---|
[9004] | 101 | lock (EvaluatedSolutions) {
|
---|
| 102 | EvaluatedSolutions.Value++; // increment the evaluated solutions counter
|
---|
| 103 | }
|
---|
[8436] | 104 | var state = PrepareInterpreterState(tree, dataset);
|
---|
| 105 |
|
---|
| 106 | foreach (var rowEnum in rows) {
|
---|
| 107 | int row = rowEnum;
|
---|
| 108 | yield return Evaluate(dataset, ref row, state);
|
---|
| 109 | state.Reset();
|
---|
| 110 | }
|
---|
[7154] | 111 | }
|
---|
| 112 |
|
---|
[9004] | 113 | private static InterpreterState PrepareInterpreterState(ISymbolicExpressionTree tree, Dataset dataset) {
|
---|
[8436] | 114 | Instruction[] code = SymbolicExpressionTreeCompiler.Compile(tree, OpCodes.MapSymbolToOpCode);
|
---|
[5987] | 115 | int necessaryArgStackSize = 0;
|
---|
[8436] | 116 | foreach (Instruction instr in code) {
|
---|
[6860] | 117 | if (instr.opCode == OpCodes.Variable) {
|
---|
[8436] | 118 | var variableTreeNode = (VariableTreeNode)instr.dynamicNode;
|
---|
[9828] | 119 | instr.data = dataset.GetReadOnlyDoubleValues(variableTreeNode.VariableName);
|
---|
[5571] | 120 | } else if (instr.opCode == OpCodes.LagVariable) {
|
---|
[8436] | 121 | var laggedVariableTreeNode = (LaggedVariableTreeNode)instr.dynamicNode;
|
---|
[9828] | 122 | instr.data = dataset.GetReadOnlyDoubleValues(laggedVariableTreeNode.VariableName);
|
---|
[6860] | 123 | } else if (instr.opCode == OpCodes.VariableCondition) {
|
---|
[8436] | 124 | var variableConditionTreeNode = (VariableConditionTreeNode)instr.dynamicNode;
|
---|
[9828] | 125 | instr.data = dataset.GetReadOnlyDoubleValues(variableConditionTreeNode.VariableName);
|
---|
[5987] | 126 | } else if (instr.opCode == OpCodes.Call) {
|
---|
| 127 | necessaryArgStackSize += instr.nArguments + 1;
|
---|
[5571] | 128 | }
|
---|
| 129 | }
|
---|
[8436] | 130 | return new InterpreterState(code, necessaryArgStackSize);
|
---|
| 131 | }
|
---|
[5571] | 132 |
|
---|
[7120] | 133 |
|
---|
[9828] | 134 | public virtual double Evaluate(Dataset dataset, ref int row, InterpreterState state) {
|
---|
[5571] | 135 | Instruction currentInstr = state.NextInstruction();
|
---|
| 136 | switch (currentInstr.opCode) {
|
---|
| 137 | case OpCodes.Add: {
|
---|
[8436] | 138 | double s = Evaluate(dataset, ref row, state);
|
---|
[5571] | 139 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 140 | s += Evaluate(dataset, ref row, state);
|
---|
[5571] | 141 | }
|
---|
| 142 | return s;
|
---|
| 143 | }
|
---|
| 144 | case OpCodes.Sub: {
|
---|
[8436] | 145 | double s = Evaluate(dataset, ref row, state);
|
---|
[5571] | 146 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 147 | s -= Evaluate(dataset, ref row, state);
|
---|
[5571] | 148 | }
|
---|
| 149 | if (currentInstr.nArguments == 1) s = -s;
|
---|
| 150 | return s;
|
---|
| 151 | }
|
---|
| 152 | case OpCodes.Mul: {
|
---|
[8436] | 153 | double p = Evaluate(dataset, ref row, state);
|
---|
[5571] | 154 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 155 | p *= Evaluate(dataset, ref row, state);
|
---|
[5571] | 156 | }
|
---|
| 157 | return p;
|
---|
| 158 | }
|
---|
| 159 | case OpCodes.Div: {
|
---|
[8436] | 160 | double p = Evaluate(dataset, ref row, state);
|
---|
[5571] | 161 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 162 | p /= Evaluate(dataset, ref row, state);
|
---|
[5571] | 163 | }
|
---|
| 164 | if (currentInstr.nArguments == 1) p = 1.0 / p;
|
---|
| 165 | return p;
|
---|
| 166 | }
|
---|
| 167 | case OpCodes.Average: {
|
---|
[8436] | 168 | double sum = Evaluate(dataset, ref row, state);
|
---|
[5571] | 169 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 170 | sum += Evaluate(dataset, ref row, state);
|
---|
[5571] | 171 | }
|
---|
| 172 | return sum / currentInstr.nArguments;
|
---|
| 173 | }
|
---|
| 174 | case OpCodes.Cos: {
|
---|
[8436] | 175 | return Math.Cos(Evaluate(dataset, ref row, state));
|
---|
[5571] | 176 | }
|
---|
| 177 | case OpCodes.Sin: {
|
---|
[8436] | 178 | return Math.Sin(Evaluate(dataset, ref row, state));
|
---|
[5571] | 179 | }
|
---|
| 180 | case OpCodes.Tan: {
|
---|
[8436] | 181 | return Math.Tan(Evaluate(dataset, ref row, state));
|
---|
[5571] | 182 | }
|
---|
[7842] | 183 | case OpCodes.Square: {
|
---|
[8436] | 184 | return Math.Pow(Evaluate(dataset, ref row, state), 2);
|
---|
[7842] | 185 | }
|
---|
[5571] | 186 | case OpCodes.Power: {
|
---|
[8436] | 187 | double x = Evaluate(dataset, ref row, state);
|
---|
| 188 | double y = Math.Round(Evaluate(dataset, ref row, state));
|
---|
[5571] | 189 | return Math.Pow(x, y);
|
---|
| 190 | }
|
---|
[7842] | 191 | case OpCodes.SquareRoot: {
|
---|
[8436] | 192 | return Math.Sqrt(Evaluate(dataset, ref row, state));
|
---|
[7842] | 193 | }
|
---|
[5571] | 194 | case OpCodes.Root: {
|
---|
[8436] | 195 | double x = Evaluate(dataset, ref row, state);
|
---|
| 196 | double y = Math.Round(Evaluate(dataset, ref row, state));
|
---|
[5571] | 197 | return Math.Pow(x, 1 / y);
|
---|
| 198 | }
|
---|
| 199 | case OpCodes.Exp: {
|
---|
[8436] | 200 | return Math.Exp(Evaluate(dataset, ref row, state));
|
---|
[5571] | 201 | }
|
---|
| 202 | case OpCodes.Log: {
|
---|
[8436] | 203 | return Math.Log(Evaluate(dataset, ref row, state));
|
---|
[5571] | 204 | }
|
---|
[7842] | 205 | case OpCodes.Gamma: {
|
---|
[8436] | 206 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 207 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 208 | else return alglib.gammafunction(x);
|
---|
| 209 | }
|
---|
| 210 | case OpCodes.Psi: {
|
---|
[8436] | 211 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 212 | if (double.IsNaN(x)) return double.NaN;
|
---|
[8430] | 213 | else if (x <= 0 && (Math.Floor(x) - x).IsAlmost(0)) return double.NaN;
|
---|
[7842] | 214 | return alglib.psi(x);
|
---|
| 215 | }
|
---|
| 216 | case OpCodes.Dawson: {
|
---|
[8436] | 217 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 218 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 219 | return alglib.dawsonintegral(x);
|
---|
| 220 | }
|
---|
| 221 | case OpCodes.ExponentialIntegralEi: {
|
---|
[8436] | 222 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 223 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 224 | return alglib.exponentialintegralei(x);
|
---|
| 225 | }
|
---|
| 226 | case OpCodes.SineIntegral: {
|
---|
| 227 | double si, ci;
|
---|
[8436] | 228 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 229 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 230 | else {
|
---|
| 231 | alglib.sinecosineintegrals(x, out si, out ci);
|
---|
| 232 | return si;
|
---|
| 233 | }
|
---|
| 234 | }
|
---|
| 235 | case OpCodes.CosineIntegral: {
|
---|
| 236 | double si, ci;
|
---|
[8436] | 237 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 238 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 239 | else {
|
---|
| 240 | alglib.sinecosineintegrals(x, out si, out ci);
|
---|
| 241 | return ci;
|
---|
| 242 | }
|
---|
| 243 | }
|
---|
| 244 | case OpCodes.HyperbolicSineIntegral: {
|
---|
| 245 | double shi, chi;
|
---|
[8436] | 246 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 247 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 248 | else {
|
---|
| 249 | alglib.hyperbolicsinecosineintegrals(x, out shi, out chi);
|
---|
| 250 | return shi;
|
---|
| 251 | }
|
---|
| 252 | }
|
---|
| 253 | case OpCodes.HyperbolicCosineIntegral: {
|
---|
| 254 | double shi, chi;
|
---|
[8436] | 255 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 256 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 257 | else {
|
---|
| 258 | alglib.hyperbolicsinecosineintegrals(x, out shi, out chi);
|
---|
| 259 | return chi;
|
---|
| 260 | }
|
---|
| 261 | }
|
---|
| 262 | case OpCodes.FresnelCosineIntegral: {
|
---|
| 263 | double c = 0, s = 0;
|
---|
[8436] | 264 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 265 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 266 | else {
|
---|
| 267 | alglib.fresnelintegral(x, ref c, ref s);
|
---|
| 268 | return c;
|
---|
| 269 | }
|
---|
| 270 | }
|
---|
| 271 | case OpCodes.FresnelSineIntegral: {
|
---|
| 272 | double c = 0, s = 0;
|
---|
[8436] | 273 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 274 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 275 | else {
|
---|
| 276 | alglib.fresnelintegral(x, ref c, ref s);
|
---|
| 277 | return s;
|
---|
| 278 | }
|
---|
| 279 | }
|
---|
| 280 | case OpCodes.AiryA: {
|
---|
| 281 | double ai, aip, bi, bip;
|
---|
[8436] | 282 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 283 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 284 | else {
|
---|
| 285 | alglib.airy(x, out ai, out aip, out bi, out bip);
|
---|
| 286 | return ai;
|
---|
| 287 | }
|
---|
| 288 | }
|
---|
| 289 | case OpCodes.AiryB: {
|
---|
| 290 | double ai, aip, bi, bip;
|
---|
[8436] | 291 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 292 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 293 | else {
|
---|
| 294 | alglib.airy(x, out ai, out aip, out bi, out bip);
|
---|
| 295 | return bi;
|
---|
| 296 | }
|
---|
| 297 | }
|
---|
| 298 | case OpCodes.Norm: {
|
---|
[8436] | 299 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 300 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 301 | else return alglib.normaldistribution(x);
|
---|
| 302 | }
|
---|
| 303 | case OpCodes.Erf: {
|
---|
[8436] | 304 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 305 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 306 | else return alglib.errorfunction(x);
|
---|
| 307 | }
|
---|
| 308 | case OpCodes.Bessel: {
|
---|
[8436] | 309 | var x = Evaluate(dataset, ref row, state);
|
---|
[7842] | 310 | if (double.IsNaN(x)) return double.NaN;
|
---|
| 311 | else return alglib.besseli0(x);
|
---|
| 312 | }
|
---|
[5571] | 313 | case OpCodes.IfThenElse: {
|
---|
[8436] | 314 | double condition = Evaluate(dataset, ref row, state);
|
---|
[5571] | 315 | double result;
|
---|
| 316 | if (condition > 0.0) {
|
---|
[8436] | 317 | result = Evaluate(dataset, ref row, state); state.SkipInstructions();
|
---|
[5571] | 318 | } else {
|
---|
[8436] | 319 | state.SkipInstructions(); result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 320 | }
|
---|
| 321 | return result;
|
---|
| 322 | }
|
---|
| 323 | case OpCodes.AND: {
|
---|
[8436] | 324 | double result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 325 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 326 | if (result > 0.0) result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 327 | else {
|
---|
[8436] | 328 | state.SkipInstructions();
|
---|
[5571] | 329 | }
|
---|
| 330 | }
|
---|
[6732] | 331 | return result > 0.0 ? 1.0 : -1.0;
|
---|
[5571] | 332 | }
|
---|
| 333 | case OpCodes.OR: {
|
---|
[8436] | 334 | double result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 335 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 336 | if (result <= 0.0) result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 337 | else {
|
---|
[8436] | 338 | state.SkipInstructions();
|
---|
[5571] | 339 | }
|
---|
| 340 | }
|
---|
| 341 | return result > 0.0 ? 1.0 : -1.0;
|
---|
| 342 | }
|
---|
| 343 | case OpCodes.NOT: {
|
---|
[8436] | 344 | return Evaluate(dataset, ref row, state) > 0.0 ? -1.0 : 1.0;
|
---|
[5571] | 345 | }
|
---|
[11646] | 346 | case OpCodes.XOR: {
|
---|
| 347 | //mkommend: XOR on multiple inputs is defined as true if the number of positive signals is odd
|
---|
| 348 | // this is equal to a consecutive execution of binary XOR operations.
|
---|
| 349 | int positiveSignals = 0;
|
---|
| 350 | for (int i = 0; i < currentInstr.nArguments; i++) {
|
---|
| 351 | if (Evaluate(dataset, ref row, state) > 0.0) positiveSignals++;
|
---|
| 352 | }
|
---|
| 353 | return positiveSignals % 2 != 0 ? 1.0 : -1.0;
|
---|
| 354 | }
|
---|
[5571] | 355 | case OpCodes.GT: {
|
---|
[8436] | 356 | double x = Evaluate(dataset, ref row, state);
|
---|
| 357 | double y = Evaluate(dataset, ref row, state);
|
---|
[5571] | 358 | if (x > y) return 1.0;
|
---|
| 359 | else return -1.0;
|
---|
| 360 | }
|
---|
| 361 | case OpCodes.LT: {
|
---|
[8436] | 362 | double x = Evaluate(dataset, ref row, state);
|
---|
| 363 | double y = Evaluate(dataset, ref row, state);
|
---|
[5571] | 364 | if (x < y) return 1.0;
|
---|
| 365 | else return -1.0;
|
---|
| 366 | }
|
---|
| 367 | case OpCodes.TimeLag: {
|
---|
| 368 | var timeLagTreeNode = (LaggedTreeNode)currentInstr.dynamicNode;
|
---|
| 369 | row += timeLagTreeNode.Lag;
|
---|
[8436] | 370 | double result = Evaluate(dataset, ref row, state);
|
---|
[5571] | 371 | row -= timeLagTreeNode.Lag;
|
---|
| 372 | return result;
|
---|
| 373 | }
|
---|
| 374 | case OpCodes.Integral: {
|
---|
| 375 | int savedPc = state.ProgramCounter;
|
---|
| 376 | var timeLagTreeNode = (LaggedTreeNode)currentInstr.dynamicNode;
|
---|
| 377 | double sum = 0.0;
|
---|
| 378 | for (int i = 0; i < Math.Abs(timeLagTreeNode.Lag); i++) {
|
---|
| 379 | row += Math.Sign(timeLagTreeNode.Lag);
|
---|
[8436] | 380 | sum += Evaluate(dataset, ref row, state);
|
---|
[5571] | 381 | state.ProgramCounter = savedPc;
|
---|
| 382 | }
|
---|
| 383 | row -= timeLagTreeNode.Lag;
|
---|
[8436] | 384 | sum += Evaluate(dataset, ref row, state);
|
---|
[5571] | 385 | return sum;
|
---|
| 386 | }
|
---|
| 387 |
|
---|
| 388 | //mkommend: derivate calculation taken from:
|
---|
| 389 | //http://www.holoborodko.com/pavel/numerical-methods/numerical-derivative/smooth-low-noise-differentiators/
|
---|
| 390 | //one sided smooth differentiatior, N = 4
|
---|
| 391 | // y' = 1/8h (f_i + 2f_i-1, -2 f_i-3 - f_i-4)
|
---|
| 392 | case OpCodes.Derivative: {
|
---|
| 393 | int savedPc = state.ProgramCounter;
|
---|
[8436] | 394 | double f_0 = Evaluate(dataset, ref row, state); row--;
|
---|
[5571] | 395 | state.ProgramCounter = savedPc;
|
---|
[8436] | 396 | double f_1 = Evaluate(dataset, ref row, state); row -= 2;
|
---|
[5571] | 397 | state.ProgramCounter = savedPc;
|
---|
[8436] | 398 | double f_3 = Evaluate(dataset, ref row, state); row--;
|
---|
[5571] | 399 | state.ProgramCounter = savedPc;
|
---|
[8436] | 400 | double f_4 = Evaluate(dataset, ref row, state);
|
---|
[5571] | 401 | row += 4;
|
---|
| 402 |
|
---|
| 403 | return (f_0 + 2 * f_1 - 2 * f_3 - f_4) / 8; // h = 1
|
---|
| 404 | }
|
---|
| 405 | case OpCodes.Call: {
|
---|
| 406 | // evaluate sub-trees
|
---|
| 407 | double[] argValues = new double[currentInstr.nArguments];
|
---|
| 408 | for (int i = 0; i < currentInstr.nArguments; i++) {
|
---|
[8436] | 409 | argValues[i] = Evaluate(dataset, ref row, state);
|
---|
[5571] | 410 | }
|
---|
| 411 | // push on argument values on stack
|
---|
| 412 | state.CreateStackFrame(argValues);
|
---|
| 413 |
|
---|
| 414 | // save the pc
|
---|
| 415 | int savedPc = state.ProgramCounter;
|
---|
| 416 | // set pc to start of function
|
---|
[9828] | 417 | state.ProgramCounter = (ushort)currentInstr.data;
|
---|
[5571] | 418 | // evaluate the function
|
---|
[8436] | 419 | double v = Evaluate(dataset, ref row, state);
|
---|
[5571] | 420 |
|
---|
| 421 | // delete the stack frame
|
---|
| 422 | state.RemoveStackFrame();
|
---|
| 423 |
|
---|
| 424 | // restore the pc => evaluation will continue at point after my subtrees
|
---|
| 425 | state.ProgramCounter = savedPc;
|
---|
| 426 | return v;
|
---|
| 427 | }
|
---|
| 428 | case OpCodes.Arg: {
|
---|
[9828] | 429 | return state.GetStackFrameValue((ushort)currentInstr.data);
|
---|
[5571] | 430 | }
|
---|
| 431 | case OpCodes.Variable: {
|
---|
[8486] | 432 | if (row < 0 || row >= dataset.Rows) return double.NaN;
|
---|
[6740] | 433 | var variableTreeNode = (VariableTreeNode)currentInstr.dynamicNode;
|
---|
[9828] | 434 | return ((IList<double>)currentInstr.data)[row] * variableTreeNode.Weight;
|
---|
[5571] | 435 | }
|
---|
| 436 | case OpCodes.LagVariable: {
|
---|
[6740] | 437 | var laggedVariableTreeNode = (LaggedVariableTreeNode)currentInstr.dynamicNode;
|
---|
[5571] | 438 | int actualRow = row + laggedVariableTreeNode.Lag;
|
---|
[8486] | 439 | if (actualRow < 0 || actualRow >= dataset.Rows) return double.NaN;
|
---|
[9828] | 440 | return ((IList<double>)currentInstr.data)[actualRow] * laggedVariableTreeNode.Weight;
|
---|
[5571] | 441 | }
|
---|
| 442 | case OpCodes.Constant: {
|
---|
[8436] | 443 | var constTreeNode = (ConstantTreeNode)currentInstr.dynamicNode;
|
---|
[5897] | 444 | return constTreeNode.Value;
|
---|
[5571] | 445 | }
|
---|
| 446 |
|
---|
| 447 | //mkommend: this symbol uses the logistic function f(x) = 1 / (1 + e^(-alpha * x) )
|
---|
| 448 | //to determine the relative amounts of the true and false branch see http://en.wikipedia.org/wiki/Logistic_function
|
---|
| 449 | case OpCodes.VariableCondition: {
|
---|
[8486] | 450 | if (row < 0 || row >= dataset.Rows) return double.NaN;
|
---|
[5571] | 451 | var variableConditionTreeNode = (VariableConditionTreeNode)currentInstr.dynamicNode;
|
---|
[9828] | 452 | double variableValue = ((IList<double>)currentInstr.data)[row];
|
---|
[5897] | 453 | double x = variableValue - variableConditionTreeNode.Threshold;
|
---|
[5571] | 454 | double p = 1 / (1 + Math.Exp(-variableConditionTreeNode.Slope * x));
|
---|
| 455 |
|
---|
[8436] | 456 | double trueBranch = Evaluate(dataset, ref row, state);
|
---|
| 457 | double falseBranch = Evaluate(dataset, ref row, state);
|
---|
[5571] | 458 |
|
---|
| 459 | return trueBranch * p + falseBranch * (1 - p);
|
---|
| 460 | }
|
---|
| 461 | default: throw new NotSupportedException();
|
---|
| 462 | }
|
---|
| 463 | }
|
---|
| 464 | }
|
---|
| 465 | }
|
---|