#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Threading;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.Instances;

namespace HeuristicLab.Encodings.ParameterConfigurationEncoding {
  public class ExperimentFactory {
    private double experimentGenerationProgress;
    public double ExperimentGenerationProgress {
      get { return experimentGenerationProgress; }
      private set {
        if (experimentGenerationProgress != value) {
          experimentGenerationProgress = value;
          OnExperimentGenerationProgressChanged();
        }
      }
    }

    public event EventHandler ExperimentGenerationProgressChanged;
    private void OnExperimentGenerationProgressChanged() {
      var handler = ExperimentGenerationProgressChanged;
      if (handler != null) handler(this, EventArgs.Empty);
    }

    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration, bool createBatchRuns, int repetitions, Dictionary<IProblemInstanceProvider, HashSet<IDataDescriptor>> problemInstances, CancellationToken ct) {
      var experiment = new Experiment();
      var algorithms = new List<IAlgorithm>(1 + problemInstances.Values.Count) { (IAlgorithm)algorithm.Clone() };
      foreach (var provider in problemInstances) {
        foreach (var descriptor in provider.Value) {
          var alg = (IAlgorithm)algorithm.Clone();
          ProblemInstanceManager.LoadData(provider.Key, descriptor, (IProblemInstanceConsumer)alg.Problem);
          algorithms.Add(alg);
        }
      }
      ExperimentGenerationProgress = 0;
      foreach (var alg in algorithms) {
        foreach (ParameterizedValueConfiguration combination in configuration) {
          ct.ThrowIfCancellationRequested();
          var clonedAlg = (IAlgorithm)alg.Clone();
          clonedAlg.Name = combination.ParameterInfoString;
          combination.Parameterize(clonedAlg);
          clonedAlg.StoreAlgorithmInEachRun = false;
          if (createBatchRuns) {
            var batchRun = new BatchRun(string.Format("BatchRun: {0}", combination.ParameterInfoString));
            batchRun.Optimizer = clonedAlg;
            batchRun.Repetitions = repetitions;
            experiment.Optimizers.Add(batchRun);
          } else {
            experiment.Optimizers.Add(clonedAlg);
          }
          ExperimentGenerationProgress = (double)experiment.Optimizers.Count / (configuration.GetCombinationCount(0) * algorithms.Count);
        }
      }
      return experiment;
    }

    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration) {
      return GenerateExperiment(algorithm, configuration, false, 0, null, CancellationToken.None);
    }

    public Experiment GenerateExperiment(IAlgorithm algorithm, ParameterConfigurationTree configuration, bool createBatchRuns, int repetitions) {
      return GenerateExperiment(algorithm, configuration, createBatchRuns, repetitions, null, CancellationToken.None);
    }
  }
}