source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/DataAnalysisProblemData.cs @ 5542

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;

namespace HeuristicLab.Problems.DataAnalysis {
  [StorableClass]
  public abstract class DataAnalysisProblemData : ParameterizedNamedItem,
    IDataAnalysisProblemData {
    private const string DatasetParameterName = "Dataset";
    private const string InputVariablesParameterName = "Input variables";
    private const string TrainingSamplesStartParameterName = "Training partition start";
    private const string TrainingSamplesEndParameterName = "Training partition end";
    private const string TestSamplesStartParameterName = "Test partition start";
    private const string TestSamplesEndParameterName = "Test partition end";

    #region default data
    // y = x^4 + x^3 + x^2 + x
    private static double[,] kozaF1 = new double[,] {
{2.017885919, -1.449165046},
{1.30060506,  -1.344523885},
{1.147134798, -1.317989331},
{0.877182504, -1.266142284},
{0.852562452, -1.261020794},
{0.431095788, -1.158793317},
{0.112586002, -1.050908405},
{0.04594507,  -1.021989402},
{0.042572879, -1.020438113},
{-0.074027291,  -0.959859562},
{-0.109178553,  -0.938094706},
{-0.259721109,  -0.803635355},
{-0.272991057,  -0.387519561},
{-0.161978191,  -0.193611001},
{-0.102489983,  -0.114215349},
{-0.01469968, -0.014918985},
{-0.008863365,  -0.008942626},
{0.026751057, 0.026054094},
{0.166922436, 0.14309643},
{0.176953808, 0.1504144},
{0.190233418, 0.159916534},
{0.199800708, 0.166635331},
{0.261502822, 0.207600348},
{0.30182879,  0.232370249},
{0.83763905,  0.468046718}
    };
    #endregion

    #region parameter properties
    public IValueParameter<Dataset> DatasetParameter {
      get { return (IValueParameter<Dataset>)Parameters[DatasetParameterName]; }
    }
    public IValueParameter<CheckedItemList<StringValue>> InputVariablesParameter {
      get { return (IValueParameter<CheckedItemList<StringValue>>)Parameters[InputVariablesParameterName]; }
    }
    public IValueParameter<IntValue> TrainingSamplesStartParameter {
      get { return (IValueParameter<IntValue>)Parameters[TrainingSamplesStartParameterName]; }
    }
    public IValueParameter<IntValue> TrainingSamplesEndParameter {
      get { return (IValueParameter<IntValue>)Parameters[TrainingSamplesEndParameterName]; }
    }
    public IValueParameter<IntValue> TestSamplesStartParameter {
      get { return (IValueParameter<IntValue>)Parameters[TestSamplesStartParameterName]; }
    }
    public IValueParameter<IntValue> TestSamplesEndParameter {
      get { return (IValueParameter<IntValue>)Parameters[TestSamplesEndParameterName]; }
    }
    #endregion
    #region propeties
    public Dataset Dataset {
      get { return DatasetParameter.Value; }
    }

    public IEnumerable<string> InputVariables {
      get { return InputVariablesParameter.Value.CheckedItems.Select(i => i.Value.Value); }
    }

    public int TrainingSamplesStart {
      get { return TrainingSamplesStartParameter.Value.Value; }
      set {
        if (value != TrainingSamplesStart) {
          TrainingSamplesStartParameter.Value.Value = value;
        }
      }
    }

    public int TrainingSamplesEnd {
      get { return TrainingSamplesEndParameter.Value.Value; }
      set {
        if (value != TrainingSamplesEnd) {
          TrainingSamplesEndParameter.Value.Value = value;
        }
      }
    }

    public int TestSamplesStart {
      get { return TestSamplesStartParameter.Value.Value; }
      set {
        if (value != TestSamplesStart) {
          TestSamplesStartParameter.Value.Value = value;
        }
      }
    }

    public int TestSamplesEnd {
      get { return TestSamplesEndParameter.Value.Value; }
      set {
        if (value != TestSamplesEnd) {
          TestSamplesEndParameter.Value.Value = value;
        }
      }
    }

    public event EventHandler Changed;
    #endregion

    protected DataAnalysisProblemData(DataAnalysisProblemData original, Cloner cloner)
      : base(original, cloner) {
      RegisterEventHandlers();
    }
    [StorableConstructor]
    protected DataAnalysisProblemData(bool deserializing) : base(deserializing) { }
    public DataAnalysisProblemData()
      : base() {
      List<string> variableNames = new List<string>() { "x", "f(x)" };
      Dataset kozaF1Dataset = new Dataset(variableNames, kozaF1);
      kozaF1Dataset.Name = "Fourth-order Polynomial Function Benchmark Dataset";
      kozaF1Dataset.Description = "f(x) = x^4 + x^3 + x^2 + x^1";
      CheckedItemList<StringValue> inputVariablesList = new CheckedItemList<StringValue>();
      StringValue x = new StringValue(variableNames[0]);
      StringValue fx = new StringValue(variableNames[1]);
      inputVariablesList.Add(x, true);
      inputVariablesList.Add(fx, false);
      Parameters.Add(new ValueParameter<Dataset>(DatasetParameterName, kozaF1Dataset));
      Parameters.Add(new ValueParameter<CheckedItemList<StringValue>>(InputVariablesParameterName, inputVariablesList));
      Parameters.Add(new ValueParameter<IntValue>(TrainingSamplesStartParameterName, new IntValue(0)));
      Parameters.Add(new ValueParameter<IntValue>(TrainingSamplesEndParameterName, new IntValue(kozaF1Dataset.Rows)));
      Parameters.Add(new ValueParameter<IntValue>(TestSamplesStartParameterName, new IntValue(kozaF1Dataset.Rows)));
      Parameters.Add(new ValueParameter<IntValue>(TestSamplesEndParameterName, new IntValue(kozaF1Dataset.Rows)));

      RegisterEventHandlers();
    }

    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      RegisterEventHandlers();
    }

    #region changed event propagation
    private void RegisterEventHandlers() {
      DatasetParameter.ValueChanged += new EventHandler(DatasetParameter_ValueChanged);
      TrainingSamplesStartParameter.ValueChanged += new EventHandler(TrainingSamplesStartParameter_ValueChanged);
      TrainingSamplesEndParameter.ValueChanged += new EventHandler(TrainingSamplesEndParameter_ValueChanged);
      TestSamplesStartParameter.ValueChanged += new EventHandler(TestSamplesStartParameter_ValueChanged);
      TestSamplesEndParameter.ValueChanged += new EventHandler(TestSamplesEndParameter_ValueChanged);

      DatasetParameter.Value.Reset += new EventHandler(DatasetChanged);
      DatasetParameter.Value.ColumnsChanged += new EventHandler(DatasetChanged);
      DatasetParameter.Value.RowsChanged += new EventHandler(DatasetChanged);
      InputVariablesParameter.Value.CheckedItemsChanged += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_CheckedItemsChanged);
      InputVariablesParameter.Value.CollectionReset += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_CollectionReset);
      InputVariablesParameter.Value.ItemsAdded += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_ItemsAdded);
      InputVariablesParameter.Value.ItemsMoved += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_ItemsMoved);
      InputVariablesParameter.Value.ItemsRemoved += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_ItemsRemoved);
      InputVariablesParameter.Value.ItemsReplaced += new Collections.CollectionItemsChangedEventHandler<Collections.IndexedItem<StringValue>>(InputVariables_ItemsReplaced);

      TrainingSamplesStartParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      TrainingSamplesEndParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      TestSamplesStartParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      TestSamplesEndParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
    }

    private void DatasetParameter_ValueChanged(object sender, EventArgs e) {
      DatasetParameter.Value.Reset += new EventHandler(DatasetChanged);
      DatasetParameter.Value.ColumnsChanged += new EventHandler(DatasetChanged);
      DatasetParameter.Value.RowsChanged += new EventHandler(DatasetChanged);
      OnProblemChanged();
    }

    private void TestSamplesEndParameter_ValueChanged(object sender, EventArgs e) {
      TestSamplesEndParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      OnProblemChanged();
    }

    private void TestSamplesStartParameter_ValueChanged(object sender, EventArgs e) {
      TestSamplesStartParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      OnProblemChanged();
    }

    private void TrainingSamplesEndParameter_ValueChanged(object sender, EventArgs e) {
      TrainingSamplesEndParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      OnProblemChanged();
    }

    private void TrainingSamplesStartParameter_ValueChanged(object sender, EventArgs e) {
      TrainingSamplesStartParameter.Value.ValueChanged += new EventHandler(Partitions_ValueChanged);
      OnProblemChanged();
    }

    private void Partitions_ValueChanged(object sender, EventArgs e) {
      OnProblemChanged();
    }

    private void InputVariables_ItemsReplaced(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void InputVariables_ItemsRemoved(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void InputVariables_ItemsMoved(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void InputVariables_ItemsAdded(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void InputVariables_CollectionReset(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void InputVariables_CheckedItemsChanged(object sender, Collections.CollectionItemsChangedEventArgs<Collections.IndexedItem<StringValue>> e) {
      OnProblemChanged();
    }

    private void DatasetChanged(object sender, EventArgs e) {
      OnProblemChanged();
    }

    protected virtual void OnProblemChanged() {
      var listeners = Changed;
      if (listeners != null) listeners(this, EventArgs.Empty);
    }
    #endregion
  }
}