#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 } }