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source: branches/ParameterConfigurationEncoding/HeuristicLab.Encodings.ParameterConfigurationEncoding/3.3/ExperimentFactory.cs @ 10913

Last change on this file since 10913 was 8574, checked in by jkarder, 12 years ago

#1853:

  • extracted experiment generation from encoding
  • added creators
  • added crossovers
  • added manipulators
  • added support for parameters of type IFixedValueParameter
  • minor code improvements
File size: 3.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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.Threading;
25using HeuristicLab.Optimization;
26using HeuristicLab.Problems.Instances;
27
28namespace HeuristicLab.Encodings.ParameterConfigurationEncoding {
29  public class ExperimentFactory {
30    private double experimentGenerationProgress;
31    public double ExperimentGenerationProgress {
32      get { return experimentGenerationProgress; }
33      private set {
34        if (experimentGenerationProgress != value) {
35          experimentGenerationProgress = value;
36          OnExperimentGenerationProgressChanged();
37        }
38      }
39    }
40
41    public event EventHandler ExperimentGenerationProgressChanged;
42    private void OnExperimentGenerationProgressChanged() {
43      var handler = ExperimentGenerationProgressChanged;
44      if (handler != null) handler(this, EventArgs.Empty);
45    }
46
47    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration, bool createBatchRuns, int repetitions, Dictionary<IProblemInstanceProvider, HashSet<IDataDescriptor>> problemInstances, CancellationToken ct) {
48      var experiment = new Experiment();
49      var algorithms = new List<IAlgorithm>(1 + problemInstances.Values.Count) { (IAlgorithm)algorithm.Clone() };
50      foreach (var provider in problemInstances) {
51        foreach (var descriptor in provider.Value) {
52          var alg = (IAlgorithm)algorithm.Clone();
53          ProblemInstanceManager.LoadData(provider.Key, descriptor, (IProblemInstanceConsumer)alg.Problem);
54          algorithms.Add(alg);
55        }
56      }
57      ExperimentGenerationProgress = 0;
58      foreach (var alg in algorithms) {
59        foreach (ParameterizedValueConfiguration combination in configuration) {
60          ct.ThrowIfCancellationRequested();
61          var clonedAlg = (IAlgorithm)alg.Clone();
62          clonedAlg.Name = combination.ParameterInfoString;
63          combination.Parameterize(clonedAlg);
64          clonedAlg.StoreAlgorithmInEachRun = false;
65          if (createBatchRuns) {
66            var batchRun = new BatchRun(string.Format("BatchRun: {0}", combination.ParameterInfoString));
67            batchRun.Optimizer = clonedAlg;
68            batchRun.Repetitions = repetitions;
69            experiment.Optimizers.Add(batchRun);
70          } else {
71            experiment.Optimizers.Add(clonedAlg);
72          }
73          ExperimentGenerationProgress = (double)experiment.Optimizers.Count / (configuration.GetCombinationCount(0) * algorithms.Count);
74        }
75      }
76      return experiment;
77    }
78
79    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration) {
80      return GenerateExperiment(algorithm, configuration, false, 0, null, CancellationToken.None);
81    }
82
83    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration, bool createBatchRuns, int repetitions) {
84      return GenerateExperiment(algorithm, configuration, createBatchRuns, repetitions, null, CancellationToken.None);
85    }
86  }
87}
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