#region License Information /* HeuristicLab * Copyright (C) 2002-2010 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.Linq; using System.Windows.Forms; using HeuristicLab.Data; using HeuristicLab.Data.Views; using HeuristicLab.MainForm; using HeuristicLab.MainForm.WindowsForms; using System.Collections.Generic; using HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis.Symbolic; namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis.Views { [View("Prognosis View")] [Content(typeof(SymbolicTimeSeriesPrognosisSolution))] public partial class PrognosisView : AsynchronousContentView { private const string TARGETVARIABLE_SERIES_NAME = "TargetVariable"; private const string ESTIMATEDVALUES_SERIES_NAME = "EstimatedValues"; private int currentTimePoint; public new SymbolicTimeSeriesPrognosisSolution Content { get { return (SymbolicTimeSeriesPrognosisSolution)base.Content; } set { base.Content = value; } } public PrognosisView() : base() { InitializeComponent(); } #region events protected override void RegisterContentEvents() { base.RegisterContentEvents(); Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged); } protected override void DeregisterContentEvents() { base.DeregisterContentEvents(); Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged); } void Content_ProblemDataChanged(object sender, EventArgs e) { OnContentChanged(); } protected override void OnContentChanged() { base.OnContentChanged(); if (Content != null) { UpdateRowIndexValue(); UpdateEstimatedValues(); } } private void UpdateEstimatedValues() { if (InvokeRequired) Invoke((Action)UpdateEstimatedValues); DoubleMatrix matrix = null; if (Content != null) { matrix = CalculateMatrix(); } valuesView.Content = matrix; } public DoubleMatrix CalculateMatrix() { DoubleMatrix matrix = null; IEnumerable targetVariables = Content.ProblemData.TargetVariables.CheckedItems.Select(x => x.Value.Value); List prognosis = Content.GetPrognosis(currentTimePoint).ToList(); double[,] values = new double[prognosis.Count, targetVariables.Count() * 2]; for (int row = 0; row < prognosis.Count; row++) { int col = 0; int t = currentTimePoint + row; foreach (string targetVariable in targetVariables) { values[row, col++] = t < Content.ProblemData.Dataset.Rows ? Content.ProblemData.Dataset[targetVariable, t] : double.NaN; values[row, col++] = prognosis[row][(col - 1) / 2]; } } matrix = new DoubleMatrix(values); string[] partitions = new string[] { "(original)", "(estimated)" }; matrix.ColumnNames = from targetVariable in targetVariables from partition in partitions select targetVariable + " " + partition; ; return matrix; } private void UpdateRowIndexValue() { if(timePointValue.Content!=null) timePointValue.Content.ValueChanged -= new EventHandler(Content_ValueChanged); currentTimePoint = Content.ProblemData.TestSamplesStart.Value; timePointValue.Content = new IntValue(currentTimePoint); timePointValue.Locked = timePointValue.ReadOnly = false; timePointValue.Content.ValueChanged += new EventHandler(Content_ValueChanged); } void Content_ValueChanged(object sender, EventArgs e) { currentTimePoint = int.Parse(timePointValue.Content.GetValue()); UpdateEstimatedValues(); } #endregion } }