#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
* and the BEACON Center for the Study of Evolution in Action.
*
* 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;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis;
namespace HeuristicLab.Algorithms.DataAnalysis {
[Item("Spline model (1d)",
"Univariate spline model (wrapper for alglib.spline1dmodel)")]
[StorableClass]
public sealed class Spline1dModel : RegressionModel {
// not storable! see persistence properties below
private alglib.spline1d.spline1dinterpolant interpolant;
[Storable]
private string[] variablesUsedForPrediction;
public override IEnumerable VariablesUsedForPrediction {
get {
return variablesUsedForPrediction;
}
}
[StorableConstructor]
private Spline1dModel(bool deserializing) : base(deserializing) {
this.interpolant = new alglib.spline1d.spline1dinterpolant();
}
private Spline1dModel(Spline1dModel orig, Cloner cloner) : base(orig, cloner) {
this.variablesUsedForPrediction = orig.VariablesUsedForPrediction.ToArray();
this.interpolant = (alglib.spline1d.spline1dinterpolant)orig.interpolant.make_copy();
}
public Spline1dModel(alglib.spline1d.spline1dinterpolant interpolant, string targetVar, string inputVar)
: base("Spline model (1d)", "Spline model (1d)") {
this.interpolant = (alglib.spline1d.spline1dinterpolant)interpolant.make_copy();
this.TargetVariable = targetVar;
this.variablesUsedForPrediction = new string[] { inputVar };
}
public override IDeepCloneable Clone(Cloner cloner) {
return new Spline1dModel(this, cloner);
}
public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
return new RegressionSolution(this, (IRegressionProblemData)problemData.Clone());
}
public double GetEstimatedValue(double x) {
return alglib.spline1d.spline1dcalc(interpolant, x);
}
public override IEnumerable GetEstimatedValues(IDataset dataset, IEnumerable rows) {
var x = dataset.GetDoubleValues(VariablesUsedForPrediction.First(), rows).ToArray();
foreach (var xi in x) {
yield return GetEstimatedValue(xi);
}
}
#region persistence
[Storable]
private double[] Interpolant_c {
get { return interpolant.c; }
set { interpolant.c = value; }
}
[Storable]
private double[] Interpolant_x {
get { return interpolant.x; }
set { interpolant.x = value; }
}
[Storable]
private int Interpolant_continuity {
get { return interpolant.continuity; }
set { interpolant.continuity = value; }
}
[Storable]
private int Interpolant_k {
get { return interpolant.k; }
set { interpolant.k = value; }
}
[Storable]
private int Interpolant_n {
get { return interpolant.n; }
set { interpolant.n = value; }
}
[Storable]
private bool Interpolant_periodic {
get { return interpolant.periodic; }
set { interpolant.periodic = value; }
}
#endregion
}
}