#region License Information /* HeuristicLab * Copyright (C) 2002-2013 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; using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Problems.DataAnalysis.Symbolic.Views; namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views { public abstract partial class InteractiveSymbolicClassificationSolutionSimplifierViewBase : InteractiveSymbolicDataAnalysisSolutionSimplifierView { private readonly SymbolicClassificationSolutionImpactValuesCalculator calculator; public new ISymbolicClassificationSolution Content { get { return (ISymbolicClassificationSolution)base.Content; } set { base.Content = value; } } public InteractiveSymbolicClassificationSolutionSimplifierViewBase() : base() { InitializeComponent(); this.Caption = "Interactive Classification Solution Simplifier"; calculator = new SymbolicClassificationSolutionImpactValuesCalculator(); } /// /// It is necessary to create new models of an unknown type with new trees in the simplifier. /// For this purpose the cloner is used by registering the new tree as already cloned object and invoking the clone mechanism. /// This results in a new model of the same type as the old one with an exchanged tree. /// /// The new tree that should be included in the new object /// protected ISymbolicClassificationModel CreateModel(ISymbolicExpressionTree tree) { var cloner = new Cloner(); cloner.RegisterClonedObject(Content.Model.SymbolicExpressionTree, tree); var model = (ISymbolicClassificationModel)Content.Model.Clone(cloner); model.RecalculateModelParameters(Content.ProblemData, Content.ProblemData.TrainingIndices); return model; } protected override Dictionary CalculateReplacementValues(ISymbolicExpressionTree tree) { return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary( n => n, n => calculator.CalculateReplacementValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices) ); } protected override Dictionary CalculateImpactValues(ISymbolicExpressionTree tree) { return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary( n => n, n => calculator.CalculateImpactValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices, Content.TrainingAccuracy) ); } protected override void btnOptimizeConstants_Click(object sender, EventArgs e) { } } }