#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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;
}
}
}