#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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.Drawing; using System.Linq; using HeuristicLab.Analysis; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; namespace HeuristicLab.DataPreprocessing { [Item("PreprocessingChart", "Represents a preprocessing chart.")] public class PreprocessingChartContent : Item, IViewChartShortcut { public static new Image StaticItemImage { get { return HeuristicLab.Common.Resources.VSImageLibrary.PieChart; } } private bool allInOneMode = true; public bool AllInOneMode { get { return this.allInOneMode; } set { this.allInOneMode = value; } } private ICheckedItemList variableItemList = null; public ICheckedItemList VariableItemList { get { return this.variableItemList; } set { this.variableItemList = value; } } public IFilteredPreprocessingData PreprocessingData { get; private set; } public PreprocessingChartContent(IFilteredPreprocessingData preprocessingData) { PreprocessingData = preprocessingData; } public PreprocessingChartContent(PreprocessingChartContent content, Cloner cloner) : base(content, cloner) { this.allInOneMode = content.allInOneMode; this.PreprocessingData = content.PreprocessingData; this.variableItemList = cloner.Clone>(variableItemList); } public override IDeepCloneable Clone(Cloner cloner) { return new PreprocessingChartContent(this, cloner); } public DataRow CreateDataRow(string variableName, DataRowVisualProperties.DataRowChartType chartType) { IList values = PreprocessingData.GetValues(PreprocessingData.GetColumnIndex(variableName)); DataRow row = new DataRow(variableName, "", values); row.VisualProperties.ChartType = chartType; return row; } public List CreateAllDataRows(DataRowVisualProperties.DataRowChartType chartType) { List dataRows = new List(); foreach (var name in PreprocessingData.GetDoubleVariableNames()) dataRows.Add(CreateDataRow(name, chartType)); return dataRows; } public DataRow CreateSelectedDataRow(string variableName, DataRowVisualProperties.DataRowChartType chartType) { IDictionary> selection = PreprocessingData.Selection; int variableIndex = PreprocessingData.GetColumnIndex(variableName); if (selection.Keys.Contains(variableIndex)) { List selectedIndices = new List(selection[variableIndex]); //need selection with more than 1 value if (selectedIndices.Count < 2) return null; selectedIndices.Sort(); int start = selectedIndices[0]; int end = selectedIndices[selectedIndices.Count - 1]; DataRow rowSelect = CreateDataRowRange(variableName, start, end, chartType); return rowSelect; } else return null; } public DataRow CreateDataRowRange(string variableName, int start, int end, DataRowVisualProperties.DataRowChartType chartType) { IList values = PreprocessingData.GetValues(PreprocessingData.GetColumnIndex(variableName)); IList valuesRange = new List(); for (int i = 0; i < values.Count; i++) { if (i >= start && i <= end) valuesRange.Add(values[i]); else valuesRange.Add(Double.NaN); } DataRow row = new DataRow(variableName, "", valuesRange); row.VisualProperties.ChartType = chartType; return row; } public List CreateAllSelectedDataRows(DataRowVisualProperties.DataRowChartType chartType) { List dataRows = new List(); foreach (var name in PreprocessingData.GetDoubleVariableNames()) { DataRow row = CreateSelectedDataRow(name, chartType); if (row != null) dataRows.Add(row); } return dataRows; } public ICheckedItemList CreateVariableItemList(IEnumerable checkedItems = null) { ICheckedItemList itemList = new CheckedItemList(); foreach (string name in PreprocessingData.GetDoubleVariableNames()) { var n = new StringValue(name); itemList.Add(n, (checkedItems == null) ? true : checkedItems.Contains(name)); } return new ReadOnlyCheckedItemList(itemList); } public event DataPreprocessingChangedEventHandler Changed { add { PreprocessingData.Changed += value; } remove { PreprocessingData.Changed -= value; } } } }