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source: branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks.Views/3.3/VariableInteractionNetworkView.cs @ 12229

Last change on this file since 12229 was 12229, checked in by arapeanu, 8 years ago

#2288: VariableInteractionNetworkView - calculates adjacency matrix from the mean impacts

File size: 8.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.ComponentModel;
25using System.Drawing;
26using System.Linq;
27using System.Windows.Forms;
28using HeuristicLab.Common;
29using HeuristicLab.Data;
30using HeuristicLab.MainForm;
31using HeuristicLab.MainForm.WindowsForms;
32using HeuristicLab.Optimization;
33using HeuristicLab.Problems.DataAnalysis;
34using HeuristicLab.Problems.DataAnalysis.Symbolic;
35using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
36using System.Collections;
37
38namespace HeuristicLab.VariableInteractionNetworks.Views {
39  [View("Variable Interaction Network")]
40  [Content(typeof(RunCollection), IsDefaultView = false)]
41
42  public sealed partial class VariableInteractionNetworkView : AsynchronousContentView {
43    private const string variableImpactResultName = "Variable impacts";
44    public new RunCollection Content {
45      get { return (RunCollection)base.Content; }
46      set { base.Content = value; }
47    }
48
49    public VariableInteractionNetworkView() {
50      InitializeComponent();
51    }
52
53    #region events
54   
55  //  #region Event Handlers (Content)
56    protected override void OnContentChanged() {
57      base.OnContentChanged();
58      if (Content == null) {
59        // TODO: Add code when content has been changed and is null
60      } else {
61        // TODO: Add code when content has been changed and is not null
62        CalculateAdjacencyMatrix();
63      }
64    }
65    #endregion
66
67    protected override void SetEnabledStateOfControls() {
68      base.SetEnabledStateOfControls();
69      // TODO: Enable or disable controls based on whether the content is null or the view is set readonly
70    }
71
72    #region Event Handlers (child controls)
73    // TODO: Put event handlers of child controls here.
74    #endregion
75
76    private void CalculateAdjacencyMatrix()
77    {
78        var runCollection = Content;
79        var groupRunCollection = Content.GroupBy(x => ((IRegressionProblemData)x.Parameters["ProblemData"]).TargetVariable).ToList();
80
81        var allVariableImpacts = runCollection.Select(run => (DoubleMatrix)run.Results[variableImpactResultName]);
82        var variableNames = (from variableImpact in allVariableImpacts
83                             from variableName in variableImpact.RowNames
84                             select variableName).Distinct().ToArray();
85
86        var adjMatrix = new DoubleMatrix(variableNames.Length, variableNames.Length);
87        var adjRow = groupRunCollection.Select(x => CalculateAdjacencyRows(x)).ToList();
88        var targets = groupRunCollection.Select(x => x.Key);
89
90        adjMatrix.RowNames = targets;
91        adjMatrix.ColumnNames = adjMatrix.RowNames;
92
93        for (int j = 0; j < groupRunCollection.Count; ++j)
94        {
95            var g = groupRunCollection[j];
96            var matrix = CalculateAdjacencyRows(g);
97            var variables = new List<Tuple<string, double>>();
98            var columnNames = matrix.ColumnNames.ToList();
99           
100            for (int i = 0; i < matrix.Columns; ++i)
101            {
102                variables.Add(new Tuple<string, double>(columnNames[i], matrix[0, i]));
103            }
104            variables.Add(new Tuple<string, double>(g.Key, 0));
105            variables.Sort((a, b) => a.Item1.CompareTo(b.Item1));
106            for (int i = 0; i < variables.Count; ++i)
107            {
108                adjMatrix[j, i] = variables[i].Item2;
109            }
110        }
111        viewHost1.Content = adjMatrix;
112    }
113
114    private DoubleMatrix CalculateAdjacencyRows(IEnumerable<IRun> runs)
115    {
116        IEnumerable<DoubleMatrix> allVariableImpacts = (from run in runs
117                                                      select run.Results[variableImpactResultName]).Cast<DoubleMatrix>();
118        var variableNames = (from variableImpact in allVariableImpacts
119                                           from variableName in variableImpact.RowNames
120                                           select variableName)
121                                          .Distinct().ToArray();
122       
123        List<string> variableNamesList = (from variableName in variableNames
124                                          where GetVariableImpacts(variableName, allVariableImpacts).Any(x => !x.IsAlmost(0.0))
125                                          select variableName)
126                                         .ToList();
127
128        var inputVariables = runs.Select(x => ((IRegressionProblemData)x.Parameters["ProblemData"]).InputVariables).ToArray();     
129        var runNames = runs.Select(x => x.Name).ToArray();
130        var runsArray = runs.ToArray();
131        DoubleMatrix varImpactMatrix = CalculateVariableImpactMatrix(runsArray, runNames);
132        var targetMatrix = new DoubleMatrix(1, variableNames.Length);
133
134        for (int i = 0; i < varImpactMatrix.Rows; ++i)
135        {
136            targetMatrix[0, i] = varImpactMatrix[i, runNames.Length];
137        }
138   
139        targetMatrix.RowNames = new[] { "Target" };
140        targetMatrix.ColumnNames = variableNames;
141
142        return targetMatrix;
143    }
144
145    //taken from RunCollectionVariableImpactView
146    private IEnumerable<double> GetVariableImpacts(string variableName, IEnumerable<DoubleMatrix> allVariableImpacts)
147    {
148        foreach (DoubleMatrix runVariableImpacts in allVariableImpacts)
149        {
150            int row = 0;
151            foreach (string rowName in runVariableImpacts.RowNames)
152            {
153                if (rowName == variableName)
154                    yield return runVariableImpacts[row, 0];
155                row++;
156            }
157        }
158    }
159
160    //adapted from RunCollectionVariableImpactView
161    private DoubleMatrix CalculateVariableImpactMatrix(IRun[] runs, string[] runNames)
162    {
163        IEnumerable<DoubleMatrix> allVariableImpacts = (from run in runs
164                                                        select run.Results[variableImpactResultName]).Cast<DoubleMatrix>();
165        IEnumerable<string> variableNames = (from variableImpact in allVariableImpacts
166                                             from variableName in variableImpact.RowNames
167                                             select variableName).Distinct();
168
169        // filter variableNames: only include names that have at least one non-zero value in a run
170        List<string> variableNamesList = (from variableName in variableNames
171                                          where GetVariableImpacts(variableName, allVariableImpacts).Any(x => !x.IsAlmost(0.0))
172                                          select variableName).ToList();
173
174        List<string> columnNames = new List<string>(runNames);
175        columnNames.Add("Mean");
176     
177        int numberOfRuns = runs.Length;
178
179        DoubleMatrix matrix = new DoubleMatrix(variableNamesList.Count, numberOfRuns + 1);
180        matrix.SortableView = true;
181        matrix.ColumnNames = columnNames;
182
183        List<List<double>> variableImpactsOverRuns = (from variableName in variableNamesList
184                                                      select GetVariableImpacts(variableName, allVariableImpacts).ToList()).ToList();
185
186        for (int row = 0; row < variableImpactsOverRuns.Count; row++)
187        {
188            matrix[row, numberOfRuns] = Math.Round(variableImpactsOverRuns[row].Average(), 3);
189        }
190
191        // fill matrix with impacts from runs
192        for (int i = 0; i < runs.Length; i++)
193        {
194            IRun run = runs[i];
195            DoubleMatrix runVariableImpacts = (DoubleMatrix)run.Results[variableImpactResultName];
196            for (int j = 0; j < runVariableImpacts.Rows; j++)
197            {
198                int rowIndex = variableNamesList.FindIndex(s => s == runVariableImpacts.RowNames.ElementAt(j));
199                if (rowIndex > -1)
200                {
201                    matrix[rowIndex, i] = Math.Round(runVariableImpacts[j, 0], 3);
202                }
203            }
204        }
205        return matrix;
206    }
207  }
208}
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