#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; }
}
}
}