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source: branches/2968_infix_string_formatter/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/SymbolicDataAnalysisExpressionTreeNativeInterpreter.cs @ 16796

Last change on this file since 16796 was 16277, checked in by bburlacu, 6 years ago

#2958: Add EvaluatedSolutions as parameter, similar to the other interpreters.

File size: 5.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using System.Runtime.InteropServices;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32
33namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
34  [StorableClass]
35  [Item("SymbolicDataAnalysisExpressionTreeNativeInterpreter", "An interpreter that wraps a native dll")]
36  public class SymbolicDataAnalysisExpressionTreeNativeInterpreter : ParameterizedNamedItem, ISymbolicDataAnalysisExpressionTreeInterpreter {
37    private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";
38
39    #region parameters
40    public IFixedValueParameter<IntValue> EvaluatedSolutionsParameter {
41      get { return (IFixedValueParameter<IntValue>)Parameters[EvaluatedSolutionsParameterName]; }
42    }
43    #endregion
44
45    #region properties
46    public int EvaluatedSolutions {
47      get { return EvaluatedSolutionsParameter.Value.Value; }
48      set { EvaluatedSolutionsParameter.Value.Value = value; }
49    }
50    #endregion
51
52    public void ClearState() { }
53
54    public SymbolicDataAnalysisExpressionTreeNativeInterpreter() {
55      Parameters.Add(new FixedValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
56    }
57
58    [StorableConstructor]
59    protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(bool deserializing) : base(deserializing) { }
60
61
62    protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(SymbolicDataAnalysisExpressionTreeNativeInterpreter original, Cloner cloner) : base(original, cloner) {
63    }
64
65    public override IDeepCloneable Clone(Cloner cloner) {
66      return new SymbolicDataAnalysisExpressionTreeNativeInterpreter(this, cloner);
67    }
68
69    private NativeInstruction[] Compile(ISymbolicExpressionTree tree, Func<ISymbolicExpressionTreeNode, byte> opCodeMapper) {
70      var root = tree.Root.GetSubtree(0).GetSubtree(0);
71      var code = new NativeInstruction[root.GetLength()];
72      if (root.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
73      code[0] = new NativeInstruction { narg = (ushort)root.SubtreeCount, opcode = opCodeMapper(root) };
74      int c = 1, i = 0;
75      foreach (var node in root.IterateNodesBreadth()) {
76        for (int j = 0; j < node.SubtreeCount; ++j) {
77          var s = node.GetSubtree(j);
78          if (s.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
79          code[c + j] = new NativeInstruction { narg = (ushort)s.SubtreeCount, opcode = opCodeMapper(s) };
80        }
81
82        if (node is VariableTreeNode variable) {
83          code[i].weight = variable.Weight;
84          code[i].data = cachedData[variable.VariableName].AddrOfPinnedObject();
85        } else if (node is ConstantTreeNode constant) {
86          code[i].value = constant.Value;
87        }
88
89        code[i].childIndex = c;
90        c += node.SubtreeCount;
91        ++i;
92      }
93      return code;
94    }
95
96    private readonly object syncRoot = new object();
97
98    [ThreadStatic]
99    private static Dictionary<string, GCHandle> cachedData;
100
101    public IEnumerable<double> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows) {
102      if (!rows.Any()) return Enumerable.Empty<double>();
103
104      lock (syncRoot) {
105        EvaluatedSolutions++; // increment the evaluated solutions counter
106      }
107
108      if (cachedData == null) {
109        InitCache(dataset);
110      }
111
112      var code = Compile(tree, OpCodes.MapSymbolToOpCode);
113
114      var rowsArray = rows.ToArray();
115      var result = new double[rowsArray.Length];
116
117      NativeWrapper.GetValuesVectorized(code, code.Length, rowsArray, rowsArray.Length, result);
118      return result;
119    }
120
121    private void InitCache(IDataset dataset) {
122      cachedData = new Dictionary<string, GCHandle>();
123      foreach (var v in dataset.DoubleVariables) {
124        var values = dataset.GetDoubleValues(v).ToArray();
125        var gch = GCHandle.Alloc(values, GCHandleType.Pinned);
126        cachedData[v] = gch;
127      }
128    }
129
130    public void InitializeState() {
131      if (cachedData != null) {
132        foreach (var gch in cachedData.Values) {
133          gch.Free();
134        }
135        cachedData = null;
136      }
137      EvaluatedSolutions = 0;
138    }
139  }
140}
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