1 | #region License Information
|
---|
2 | /* HeuristicLab
|
---|
3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
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;
|
---|
26 | using HeuristicLab.Data;
|
---|
27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
28 | using HeuristicLab.Parameters;
|
---|
29 | using HEAL.Attic;
|
---|
30 | using MathNet.Numerics.Statistics;
|
---|
31 |
|
---|
32 | using DoubleVector = MathNet.Numerics.LinearAlgebra.Vector<double>;
|
---|
33 |
|
---|
34 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
|
---|
35 | [StorableType("DE68A1D9-5AFC-4DDD-AB62-29F3B8FC28E0")]
|
---|
36 | [Item("SymbolicDataAnalysisExpressionTreeVectorInterpreter", "Interpreter for symbolic expression trees including vector arithmetic.")]
|
---|
37 | public class SymbolicDataAnalysisExpressionTreeVectorInterpreter : ParameterizedNamedItem, ISymbolicDataAnalysisExpressionTreeInterpreter {
|
---|
38 | [StorableType("2612504E-AD5F-4AE2-B60E-98A5AB59E164")]
|
---|
39 | public enum Aggregation {
|
---|
40 | Mean,
|
---|
41 | Median,
|
---|
42 | Sum,
|
---|
43 | NaN,
|
---|
44 | Exception
|
---|
45 | }
|
---|
46 |
|
---|
47 | private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";
|
---|
48 | private const string FinalAggregationParameterName = "FinalAggregation";
|
---|
49 |
|
---|
50 | public override bool CanChangeName {
|
---|
51 | get { return false; }
|
---|
52 | }
|
---|
53 |
|
---|
54 | public override bool CanChangeDescription {
|
---|
55 | get { return false; }
|
---|
56 | }
|
---|
57 |
|
---|
58 | #region parameter properties
|
---|
59 | public IFixedValueParameter<IntValue> EvaluatedSolutionsParameter {
|
---|
60 | get { return (IFixedValueParameter<IntValue>)Parameters[EvaluatedSolutionsParameterName]; }
|
---|
61 | }
|
---|
62 | public IFixedValueParameter<EnumValue<Aggregation>> FinalAggregationParameter {
|
---|
63 | get { return (IFixedValueParameter<EnumValue<Aggregation>>)Parameters[FinalAggregationParameterName]; }
|
---|
64 | }
|
---|
65 | #endregion
|
---|
66 |
|
---|
67 | #region properties
|
---|
68 | public int EvaluatedSolutions {
|
---|
69 | get { return EvaluatedSolutionsParameter.Value.Value; }
|
---|
70 | set { EvaluatedSolutionsParameter.Value.Value = value; }
|
---|
71 | }
|
---|
72 | public Aggregation FinalAggregation {
|
---|
73 | get { return FinalAggregationParameter.Value.Value; }
|
---|
74 | set { FinalAggregationParameter.Value.Value = value; }
|
---|
75 | }
|
---|
76 | #endregion
|
---|
77 |
|
---|
78 | [StorableConstructor]
|
---|
79 | protected SymbolicDataAnalysisExpressionTreeVectorInterpreter(StorableConstructorFlag _) : base(_) { }
|
---|
80 |
|
---|
81 | protected SymbolicDataAnalysisExpressionTreeVectorInterpreter(SymbolicDataAnalysisExpressionTreeVectorInterpreter original, Cloner cloner)
|
---|
82 | : base(original, cloner) { }
|
---|
83 |
|
---|
84 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
85 | return new SymbolicDataAnalysisExpressionTreeVectorInterpreter(this, cloner);
|
---|
86 | }
|
---|
87 |
|
---|
88 | public SymbolicDataAnalysisExpressionTreeVectorInterpreter()
|
---|
89 | : this("SymbolicDataAnalysisExpressionTreeVectorInterpreter", "Interpreter for symbolic expression trees including vector arithmetic.") {
|
---|
90 | }
|
---|
91 |
|
---|
92 | protected SymbolicDataAnalysisExpressionTreeVectorInterpreter(string name, string description)
|
---|
93 | : base(name, description) {
|
---|
94 | Parameters.Add(new FixedValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
|
---|
95 | Parameters.Add(new FixedValueParameter<EnumValue<Aggregation>>(FinalAggregationParameterName, "If root node of the expression tree results in a Vector it is aggregated according to this parameter", new EnumValue<Aggregation>(Aggregation.Mean)));
|
---|
96 | }
|
---|
97 |
|
---|
98 | [StorableHook(HookType.AfterDeserialization)]
|
---|
99 | private void AfterDeserialization() {
|
---|
100 | if (!Parameters.ContainsKey(FinalAggregationParameterName)) {
|
---|
101 | Parameters.Add(new FixedValueParameter<EnumValue<Aggregation>>(FinalAggregationParameterName, "If root node of the expression tree results in a Vector it is aggregated according to this parameter", new EnumValue<Aggregation>(Aggregation.Mean)));
|
---|
102 | }
|
---|
103 | }
|
---|
104 |
|
---|
105 | #region IStatefulItem
|
---|
106 | public void InitializeState() {
|
---|
107 | EvaluatedSolutions = 0;
|
---|
108 | }
|
---|
109 |
|
---|
110 | public void ClearState() { }
|
---|
111 | #endregion
|
---|
112 |
|
---|
113 | private readonly object syncRoot = new object();
|
---|
114 | public IEnumerable<double> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows) {
|
---|
115 | lock (syncRoot) {
|
---|
116 | EvaluatedSolutions++; // increment the evaluated solutions counter
|
---|
117 | }
|
---|
118 | var state = PrepareInterpreterState(tree, dataset);
|
---|
119 |
|
---|
120 | foreach (var rowEnum in rows) {
|
---|
121 | int row = rowEnum;
|
---|
122 | var result = Evaluate(dataset, ref row, state);
|
---|
123 | if (result.IsScalar)
|
---|
124 | yield return result.Scalar;
|
---|
125 | else if (result.IsVector) {
|
---|
126 | if (FinalAggregation == Aggregation.Mean) yield return result.Vector.Mean();
|
---|
127 | else if (FinalAggregation == Aggregation.Median) yield return Statistics.Median(result.Vector);
|
---|
128 | else if (FinalAggregation == Aggregation.Sum) yield return result.Vector.Sum();
|
---|
129 | else if (FinalAggregation == Aggregation.Exception) throw new InvalidOperationException("Result of the tree is not a scalar.");
|
---|
130 | else yield return double.NaN;
|
---|
131 | } else
|
---|
132 | yield return double.NaN;
|
---|
133 | state.Reset();
|
---|
134 | }
|
---|
135 | }
|
---|
136 |
|
---|
137 | private static InterpreterState PrepareInterpreterState(ISymbolicExpressionTree tree, IDataset dataset) {
|
---|
138 | Instruction[] code = SymbolicExpressionTreeCompiler.Compile(tree, OpCodes.MapSymbolToOpCode);
|
---|
139 | int necessaryArgStackSize = 0;
|
---|
140 | foreach (Instruction instr in code) {
|
---|
141 | if (instr.opCode == OpCodes.Variable) {
|
---|
142 | var variableTreeNode = (VariableTreeNode)instr.dynamicNode;
|
---|
143 | if (dataset.VariableHasType<double>(variableTreeNode.VariableName))
|
---|
144 | instr.data = dataset.GetReadOnlyDoubleValues(variableTreeNode.VariableName);
|
---|
145 | else if (dataset.VariableHasType<DoubleVector>(variableTreeNode.VariableName))
|
---|
146 | instr.data = dataset.GetReadOnlyDoubleVectorValues(variableTreeNode.VariableName);
|
---|
147 | else throw new NotSupportedException($"Type of variable {variableTreeNode.VariableName} is not supported.");
|
---|
148 | } else if (instr.opCode == OpCodes.FactorVariable) {
|
---|
149 | var factorTreeNode = instr.dynamicNode as FactorVariableTreeNode;
|
---|
150 | instr.data = dataset.GetReadOnlyStringValues(factorTreeNode.VariableName);
|
---|
151 | } else if (instr.opCode == OpCodes.BinaryFactorVariable) {
|
---|
152 | var factorTreeNode = instr.dynamicNode as BinaryFactorVariableTreeNode;
|
---|
153 | instr.data = dataset.GetReadOnlyStringValues(factorTreeNode.VariableName);
|
---|
154 | } else if (instr.opCode == OpCodes.LagVariable) {
|
---|
155 | var laggedVariableTreeNode = (LaggedVariableTreeNode)instr.dynamicNode;
|
---|
156 | instr.data = dataset.GetReadOnlyDoubleValues(laggedVariableTreeNode.VariableName);
|
---|
157 | } else if (instr.opCode == OpCodes.VariableCondition) {
|
---|
158 | var variableConditionTreeNode = (VariableConditionTreeNode)instr.dynamicNode;
|
---|
159 | instr.data = dataset.GetReadOnlyDoubleValues(variableConditionTreeNode.VariableName);
|
---|
160 | } else if (instr.opCode == OpCodes.Call) {
|
---|
161 | necessaryArgStackSize += instr.nArguments + 1;
|
---|
162 | }
|
---|
163 | }
|
---|
164 | return new InterpreterState(code, necessaryArgStackSize);
|
---|
165 | }
|
---|
166 |
|
---|
167 |
|
---|
168 | public struct EvaluationResult {
|
---|
169 | public double Scalar { get; }
|
---|
170 | public bool IsScalar => !double.IsNaN(Scalar);
|
---|
171 |
|
---|
172 | public DoubleVector Vector { get; }
|
---|
173 | public bool IsVector => !(Vector.Count == 1 && double.IsNaN(Vector[0]));
|
---|
174 |
|
---|
175 | public bool IsNaN => !IsScalar && !IsVector;
|
---|
176 |
|
---|
177 | public EvaluationResult(double scalar) {
|
---|
178 | Scalar = scalar;
|
---|
179 | Vector = NaNVector;
|
---|
180 | }
|
---|
181 | public EvaluationResult(DoubleVector vector) {
|
---|
182 | if (vector == null) throw new ArgumentNullException(nameof(vector));
|
---|
183 | Vector = vector;
|
---|
184 | Scalar = double.NaN;
|
---|
185 | }
|
---|
186 |
|
---|
187 | public override string ToString() {
|
---|
188 | if (IsScalar) return Scalar.ToString();
|
---|
189 | if (IsVector) return Vector.ToVectorString();
|
---|
190 | return "NaN";
|
---|
191 | }
|
---|
192 |
|
---|
193 | private static readonly DoubleVector NaNVector = DoubleVector.Build.Dense(1, double.NaN);
|
---|
194 | public static readonly EvaluationResult NaN = new EvaluationResult(double.NaN);
|
---|
195 | }
|
---|
196 |
|
---|
197 | private static EvaluationResult ArithmeticApply(EvaluationResult lhs, EvaluationResult rhs,
|
---|
198 | Func<double, double, double> ssFunc = null,
|
---|
199 | Func<double, DoubleVector, DoubleVector> svFunc = null,
|
---|
200 | Func<DoubleVector, double, DoubleVector> vsFunc = null,
|
---|
201 | Func<DoubleVector, DoubleVector, DoubleVector> vvFunc = null) {
|
---|
202 | if (lhs.IsScalar && rhs.IsScalar && ssFunc != null) return new EvaluationResult(ssFunc(lhs.Scalar, rhs.Scalar));
|
---|
203 | if (lhs.IsScalar && rhs.IsVector && svFunc != null) return new EvaluationResult(svFunc(lhs.Scalar, rhs.Vector));
|
---|
204 | if (lhs.IsVector && rhs.IsScalar && vsFunc != null) return new EvaluationResult(vsFunc(lhs.Vector, rhs.Scalar));
|
---|
205 | if (lhs.IsVector && rhs.IsVector && vvFunc != null) return new EvaluationResult(vvFunc(lhs.Vector, rhs.Vector));
|
---|
206 | return EvaluationResult.NaN;
|
---|
207 | }
|
---|
208 |
|
---|
209 | private static EvaluationResult FunctionApply(EvaluationResult val,
|
---|
210 | Func<double, double> sFunc = null,
|
---|
211 | Func<DoubleVector, DoubleVector> vFunc = null) {
|
---|
212 | if (val.IsScalar && sFunc != null) return new EvaluationResult(sFunc(val.Scalar));
|
---|
213 | if (val.IsVector && vFunc != null) return new EvaluationResult(vFunc(val.Vector));
|
---|
214 | return EvaluationResult.NaN;
|
---|
215 | }
|
---|
216 | private static EvaluationResult AggregateApply(EvaluationResult val,
|
---|
217 | Func<double, double> sFunc = null,
|
---|
218 | Func<DoubleVector, double> vFunc = null) {
|
---|
219 | if (val.IsScalar && sFunc != null) return new EvaluationResult(sFunc(val.Scalar));
|
---|
220 | if (val.IsVector && vFunc != null) return new EvaluationResult(vFunc(val.Vector));
|
---|
221 | return EvaluationResult.NaN;
|
---|
222 | }
|
---|
223 |
|
---|
224 | public virtual EvaluationResult Evaluate(IDataset dataset, ref int row, InterpreterState state) {
|
---|
225 | Instruction currentInstr = state.NextInstruction();
|
---|
226 | switch (currentInstr.opCode) {
|
---|
227 | case OpCodes.Add: {
|
---|
228 | var cur = Evaluate(dataset, ref row, state);
|
---|
229 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
230 | var op = Evaluate(dataset, ref row, state);
|
---|
231 | cur = ArithmeticApply(cur, op,
|
---|
232 | (s1, s2) => s1 + s2,
|
---|
233 | (s1, v2) => s1 + v2,
|
---|
234 | (v1, s2) => v1 + s2,
|
---|
235 | (v1, v2) => v1 + v2);
|
---|
236 | }
|
---|
237 | return cur;
|
---|
238 | }
|
---|
239 | case OpCodes.Sub: {
|
---|
240 | var cur = Evaluate(dataset, ref row, state);
|
---|
241 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
242 | var op = Evaluate(dataset, ref row, state);
|
---|
243 | cur = ArithmeticApply(cur, op,
|
---|
244 | (s1, s2) => s1 - s2,
|
---|
245 | (s1, v2) => s1 - v2,
|
---|
246 | (v1, s2) => v1 - s2,
|
---|
247 | (v1, v2) => v1 - v2);
|
---|
248 | }
|
---|
249 | return cur;
|
---|
250 | }
|
---|
251 | case OpCodes.Mul: {
|
---|
252 | var cur = Evaluate(dataset, ref row, state);
|
---|
253 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
254 | var op = Evaluate(dataset, ref row, state);
|
---|
255 | cur = ArithmeticApply(cur, op,
|
---|
256 | (s1, s2) => s1 * s2,
|
---|
257 | (s1, v2) => s1 * v2,
|
---|
258 | (v1, s2) => v1 * s2,
|
---|
259 | (v1, v2) => v1.PointwiseMultiply(v2));
|
---|
260 | }
|
---|
261 | return cur;
|
---|
262 | }
|
---|
263 | case OpCodes.Div: {
|
---|
264 | var cur = Evaluate(dataset, ref row, state);
|
---|
265 | for (int i = 1; i < currentInstr.nArguments; i++) {
|
---|
266 | var op = Evaluate(dataset, ref row, state);
|
---|
267 | cur = ArithmeticApply(cur, op,
|
---|
268 | (s1, s2) => s1 / s2,
|
---|
269 | (s1, v2) => s1 / v2,
|
---|
270 | (v1, s2) => v1 / s2,
|
---|
271 | (v1, v2) => v1 / v2);
|
---|
272 | }
|
---|
273 | return cur;
|
---|
274 | }
|
---|
275 | case OpCodes.Absolute: {
|
---|
276 | var cur = Evaluate(dataset, ref row, state);
|
---|
277 | return FunctionApply(cur, Math.Abs, DoubleVector.Abs);
|
---|
278 | }
|
---|
279 | case OpCodes.Tanh: {
|
---|
280 | var cur = Evaluate(dataset, ref row, state);
|
---|
281 | return FunctionApply(cur, Math.Tanh, DoubleVector.Tanh);
|
---|
282 | }
|
---|
283 | case OpCodes.Cos: {
|
---|
284 | var cur = Evaluate(dataset, ref row, state);
|
---|
285 | return FunctionApply(cur, Math.Cos, DoubleVector.Cos);
|
---|
286 | }
|
---|
287 | case OpCodes.Sin: {
|
---|
288 | var cur = Evaluate(dataset, ref row, state);
|
---|
289 | return FunctionApply(cur, Math.Sin, DoubleVector.Sin);
|
---|
290 | }
|
---|
291 | case OpCodes.Tan: {
|
---|
292 | var cur = Evaluate(dataset, ref row, state);
|
---|
293 | return FunctionApply(cur, Math.Tan, DoubleVector.Tan);
|
---|
294 | }
|
---|
295 | case OpCodes.Square: {
|
---|
296 | var cur = Evaluate(dataset, ref row, state);
|
---|
297 | return FunctionApply(cur,
|
---|
298 | s => Math.Pow(s, 2),
|
---|
299 | v => v.PointwisePower(2));
|
---|
300 | }
|
---|
301 | case OpCodes.Cube: {
|
---|
302 | var cur = Evaluate(dataset, ref row, state);
|
---|
303 | return FunctionApply(cur,
|
---|
304 | s => Math.Pow(s, 3),
|
---|
305 | v => v.PointwisePower(3));
|
---|
306 | }
|
---|
307 | case OpCodes.Power: {
|
---|
308 | var x = Evaluate(dataset, ref row, state);
|
---|
309 | var y = Evaluate(dataset, ref row, state);
|
---|
310 | return ArithmeticApply(x, y,
|
---|
311 | (s1, s2) => Math.Pow(s1, Math.Round(s2)),
|
---|
312 | (s1, v2) => DoubleVector.Build.Dense(v2.Count, s1).PointwisePower(DoubleVector.Round(v2)),
|
---|
313 | (v1, s2) => v1.PointwisePower(Math.Round(s2)),
|
---|
314 | (v1, v2) => v1.PointwisePower(DoubleVector.Round(v2)));
|
---|
315 | }
|
---|
316 | case OpCodes.SquareRoot: {
|
---|
317 | var cur = Evaluate(dataset, ref row, state);
|
---|
318 | return FunctionApply(cur,
|
---|
319 | s => Math.Sqrt(s),
|
---|
320 | v => DoubleVector.Sqrt(v));
|
---|
321 | }
|
---|
322 | case OpCodes.CubeRoot: {
|
---|
323 | var cur = Evaluate(dataset, ref row, state);
|
---|
324 | return FunctionApply(cur,
|
---|
325 | s => s < 0 ? -Math.Pow(-s, 1.0 / 3.0) : Math.Pow(s, 1.0 / 3.0),
|
---|
326 | v => v.Map(s => s < 0 ? -Math.Pow(-s, 1.0 / 3.0) : Math.Pow(s, 1.0 / 3.0)));
|
---|
327 | }
|
---|
328 | case OpCodes.Root: {
|
---|
329 | var x = Evaluate(dataset, ref row, state);
|
---|
330 | var y = Evaluate(dataset, ref row, state);
|
---|
331 | return ArithmeticApply(x, y,
|
---|
332 | (s1, s2) => Math.Pow(s1, 1.0 / Math.Round(s2)),
|
---|
333 | (s1, v2) => DoubleVector.Build.Dense(v2.Count, s1).PointwisePower(1.0 / DoubleVector.Round(v2)),
|
---|
334 | (v1, s2) => v1.PointwisePower(1.0 / Math.Round(s2)),
|
---|
335 | (v1, v2) => v1.PointwisePower(1.0 / DoubleVector.Round(v2)));
|
---|
336 | }
|
---|
337 | case OpCodes.Exp: {
|
---|
338 | var cur = Evaluate(dataset, ref row, state);
|
---|
339 | return FunctionApply(cur,
|
---|
340 | s => Math.Exp(s),
|
---|
341 | v => DoubleVector.Exp(v));
|
---|
342 | }
|
---|
343 | case OpCodes.Log: {
|
---|
344 | var cur = Evaluate(dataset, ref row, state);
|
---|
345 | return FunctionApply(cur,
|
---|
346 | s => Math.Log(s),
|
---|
347 | v => DoubleVector.Log(v));
|
---|
348 | }
|
---|
349 | case OpCodes.Sum: {
|
---|
350 | var cur = Evaluate(dataset, ref row, state);
|
---|
351 | return AggregateApply(cur,
|
---|
352 | s => s,
|
---|
353 | v => v.Sum());
|
---|
354 | }
|
---|
355 | case OpCodes.Mean: {
|
---|
356 | var cur = Evaluate(dataset, ref row, state);
|
---|
357 | return AggregateApply(cur,
|
---|
358 | s => s,
|
---|
359 | v => v.Mean());
|
---|
360 | }
|
---|
361 | case OpCodes.StandardDeviation: {
|
---|
362 | var cur = Evaluate(dataset, ref row, state);
|
---|
363 | return AggregateApply(cur,
|
---|
364 | s => 0,
|
---|
365 | v => v.Count > 1 ? Statistics.StandardDeviation(v) : 0);
|
---|
366 | }
|
---|
367 | case OpCodes.Variable: {
|
---|
368 | if (row < 0 || row >= dataset.Rows) return EvaluationResult.NaN;
|
---|
369 | var variableTreeNode = (VariableTreeNode)currentInstr.dynamicNode;
|
---|
370 | if (currentInstr.data is IList<double> doubleList)
|
---|
371 | return new EvaluationResult(doubleList[row] * variableTreeNode.Weight);
|
---|
372 | if (currentInstr.data is IList<DoubleVector> doubleVectorList)
|
---|
373 | return new EvaluationResult(doubleVectorList[row] * variableTreeNode.Weight);
|
---|
374 | throw new NotSupportedException($"Unsupported type of variable: {currentInstr.data.GetType().GetPrettyName()}");
|
---|
375 | }
|
---|
376 | case OpCodes.BinaryFactorVariable: {
|
---|
377 | if (row < 0 || row >= dataset.Rows) return EvaluationResult.NaN;
|
---|
378 | var factorVarTreeNode = currentInstr.dynamicNode as BinaryFactorVariableTreeNode;
|
---|
379 | return new EvaluationResult(((IList<string>)currentInstr.data)[row] == factorVarTreeNode.VariableValue ? factorVarTreeNode.Weight : 0);
|
---|
380 | }
|
---|
381 | case OpCodes.FactorVariable: {
|
---|
382 | if (row < 0 || row >= dataset.Rows) return EvaluationResult.NaN;
|
---|
383 | var factorVarTreeNode = currentInstr.dynamicNode as FactorVariableTreeNode;
|
---|
384 | return new EvaluationResult(factorVarTreeNode.GetValue(((IList<string>)currentInstr.data)[row]));
|
---|
385 | }
|
---|
386 | case OpCodes.Constant: {
|
---|
387 | var constTreeNode = (ConstantTreeNode)currentInstr.dynamicNode;
|
---|
388 | return new EvaluationResult(constTreeNode.Value);
|
---|
389 | }
|
---|
390 |
|
---|
391 | default:
|
---|
392 | throw new NotSupportedException($"Unsupported OpCode: {currentInstr.opCode}");
|
---|
393 | }
|
---|
394 | }
|
---|
395 | }
|
---|
396 | } |
---|