#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.Drawing; using System.Linq; using HeuristicLab.Analysis; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.DataPreprocessing { [Item("Histogram", "Represents the histogram grid.")] [StorableClass] public class HistogramContent : PreprocessingChartContent { public static new Image StaticItemImage { get { return HeuristicLab.Common.Resources.VSImageLibrary.Statistics; } } [Storable] public string GroupingVariableName { get; set; } [Storable] public int Bins { get; set; } [Storable] public bool ExactBins { get; set; } [Storable] public LegendOrder Order { get; set; } #region Constructor, Cloning & Persistence public HistogramContent(IFilteredPreprocessingData preprocessingData) : base(preprocessingData) { Bins = 10; ExactBins = false; } public HistogramContent(HistogramContent original, Cloner cloner) : base(original, cloner) { GroupingVariableName = original.GroupingVariableName; Bins = original.Bins; ExactBins = original.ExactBins; Order = original.Order; } public override IDeepCloneable Clone(Cloner cloner) { return new HistogramContent(this, cloner); } [StorableConstructor] protected HistogramContent(bool deserializing) : base(deserializing) { } #endregion public static DataTable CreateHistogram(IFilteredPreprocessingData preprocessingData, string variableName, string groupingVariableName, DataTableVisualProperties.DataTableHistogramAggregation aggregation, LegendOrder legendOrder = LegendOrder.Alphabetically) { var dataTable = new DataTable { VisualProperties = { Title = variableName, HistogramAggregation = aggregation }, }; if (string.IsNullOrEmpty(groupingVariableName)) { var row = PreprocessingChartContent.CreateDataRow(preprocessingData, variableName, DataRowVisualProperties.DataRowChartType.Histogram); row.VisualProperties.IsVisibleInLegend = false; dataTable.Rows.Add(row); return dataTable; } int variableIndex = preprocessingData.GetColumnIndex(variableName); var variableValues = preprocessingData.GetValues(variableIndex); int groupVariableIndex = preprocessingData.GetColumnIndex(groupingVariableName); var groupingValues = Enumerable.Empty(); if (preprocessingData.VariableHasType(groupVariableIndex)) { groupingValues = preprocessingData.GetValues(groupVariableIndex).Select(x => x.ToString()); } else if (preprocessingData.VariableHasType(groupVariableIndex)) { groupingValues = preprocessingData.GetValues(groupVariableIndex); } else if (preprocessingData.VariableHasType(groupVariableIndex)) { groupingValues = preprocessingData.GetValues(groupVariableIndex).Select(x => x.ToString()); } var groups = groupingValues.Zip(variableValues, Tuple.Create).GroupBy(t => t.Item1, t => t.Item2); if (legendOrder == LegendOrder.Alphabetically) groups = groups.OrderBy(x => x.Key, new NaturalStringComparer()); foreach (var group in groups) { var classRow = new DataRow { Name = group.Key, VisualProperties = { ChartType = DataRowVisualProperties.DataRowChartType.Histogram, IsVisibleInLegend = !string.IsNullOrEmpty(groupingVariableName) } }; classRow.Values.AddRange(group); dataTable.Rows.Add(classRow); } return dataTable; } } }