#region License Information
/* HeuristicLab
* Copyright (C) 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 HEAL.Attic;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Problems.DataAnalysis;
using System;
namespace HeuristicLab.Algorithms.DataAnalysis {
[Item("Spline model (1d)",
"Univariate spline model (wrapper for alglib.spline1dmodel)")]
[StorableType("23D71839-E011-4DC5-B451-2D4C1177D743")]
public sealed class Spline1dModel : RegressionModel {
// not storable! see persistence properties below
private alglib.spline1d.spline1dinterpolant interpolant;
[Storable(OldName = "variablesUsedForPrediction")]
private string[] StorableVariablesUsedForPrediction {
set {
if (value.Length > 1) throw new ArgumentException("A one-dimensional spline model supports only one input variable.");
inputVariable = value[0];
}
}
[Storable]
private string inputVariable;
public override IEnumerable VariablesUsedForPrediction => new[] { inputVariable };
[StorableConstructor]
private Spline1dModel(StorableConstructorFlag deserializing) : base(deserializing) {
this.interpolant = new alglib.spline1d.spline1dinterpolant();
}
private Spline1dModel(Spline1dModel orig, Cloner cloner) : base(orig, cloner) {
this.inputVariable = orig.inputVariable;
if(orig.interpolant != null) this.interpolant = (alglib.spline1d.spline1dinterpolant)orig.interpolant.make_copy();
}
public Spline1dModel(alglib.spline1d.spline1dinterpolant interpolant, string targetVar, string inputVar)
: base(targetVar, $"Spline model ({inputVar})") {
this.interpolant = (alglib.spline1d.spline1dinterpolant)interpolant.make_copy();
this.inputVariable = inputVar;
}
public override IDeepCloneable Clone(Cloner cloner) => new Spline1dModel(this, cloner);
public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
var solution = new RegressionSolution(this, (IRegressionProblemData)problemData.Clone());
solution.Name = $"Regression Spline ({inputVariable})";
return solution;
}
public double GetEstimatedValue(double x) => alglib.spline1d.spline1dcalc(interpolant, x, null);
public override IEnumerable GetEstimatedValues(IDataset dataset, IEnumerable rows) {
return dataset.GetDoubleValues(inputVariable, rows).Select(GetEstimatedValue);
}
#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
}
}