#region License Information
/* HeuristicLab
* Copyright (C) 2002-2014 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 .
*/
#endregion
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.DataAnalysis {
[StorableClass]
[Item("ClusteringProblemData", "Represents an item containing all data defining a clustering problem.")]
public sealed class ClusteringProblemData : DataAnalysisProblemData, IClusteringProblemData, IStorableContent {
public string Filename { get; set; }
#region default data
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}
};
private static Dataset defaultDataset;
private static IEnumerable defaultAllowedInputVariables;
static ClusteringProblemData() {
defaultDataset = new Dataset(new string[] { "y", "x" }, kozaF1);
defaultDataset.Name = "Fourth-order Polynomial Function Benchmark Dataset";
defaultDataset.Description = "f(x) = x^4 + x^3 + x^2 + x^1";
defaultAllowedInputVariables = new List() { "x", "y" };
}
#endregion
[StorableConstructor]
private ClusteringProblemData(bool deserializing) : base(deserializing) { }
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
}
private ClusteringProblemData(ClusteringProblemData original, Cloner cloner)
: base(original, cloner) {
}
public override IDeepCloneable Clone(Cloner cloner) { return new ClusteringProblemData(this, cloner); }
public ClusteringProblemData()
: this(defaultDataset, defaultAllowedInputVariables) {
}
public ClusteringProblemData(Dataset dataset, IEnumerable allowedInputVariables, IEnumerable transformations = null)
: base(dataset, allowedInputVariables, transformations ?? Enumerable.Empty()) {
}
}
}