#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 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 System.Windows.Forms;
using HeuristicLab.Common;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Views;
using HeuristicLab.MainForm.WindowsForms;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Views {
public abstract partial class InteractiveSymbolicDataAnalysisSolutionSimplifierView : AsynchronousContentView {
private Dictionary replacementNodes;
private Dictionary nodeImpacts;
public InteractiveSymbolicDataAnalysisSolutionSimplifierView() {
InitializeComponent();
this.replacementNodes = new Dictionary();
this.nodeImpacts = new Dictionary();
this.Caption = "Interactive Solution Simplifier";
}
public new ISymbolicDataAnalysisSolution Content {
get { return (ISymbolicDataAnalysisSolution)base.Content; }
set { base.Content = value; }
}
protected override void RegisterContentEvents() {
base.RegisterContentEvents();
Content.ModelChanged += new EventHandler(Content_ModelChanged);
Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
}
protected override void DeregisterContentEvents() {
base.DeregisterContentEvents();
Content.ModelChanged -= new EventHandler(Content_ModelChanged);
Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
}
private void Content_ModelChanged(object sender, EventArgs e) {
OnModelChanged();
}
private void Content_ProblemDataChanged(object sender, EventArgs e) {
OnProblemDataChanged();
}
protected virtual void OnModelChanged() {
this.CalculateReplacementNodesAndNodeImpacts();
}
protected virtual void OnProblemDataChanged() {
this.CalculateReplacementNodesAndNodeImpacts();
}
protected override void OnContentChanged() {
base.OnContentChanged();
this.CalculateReplacementNodesAndNodeImpacts();
this.viewHost.Content = this.Content;
}
private void CalculateReplacementNodesAndNodeImpacts() {
if (Content != null && Content.Model != null && Content.ProblemData != null) {
var tree = Content.Model.SymbolicExpressionTree;
var replacementValues = CalculateReplacementValues(tree);
foreach (var pair in replacementValues) {
if (!(pair.Key is ConstantTreeNode)) {
replacementNodes[pair.Key] = MakeConstantTreeNode(pair.Value);
}
}
nodeImpacts = CalculateImpactValues(Content.Model.SymbolicExpressionTree);
// automatically fold all branches with impact = 1
List nodeList = Content.Model.SymbolicExpressionTree.Root.GetSubtree(0).IterateNodesPrefix().ToList();
foreach (var parent in nodeList) {
for (int subTreeIndex = 0; subTreeIndex < parent.SubtreesCount; subTreeIndex++) {
var child = parent.GetSubtree(subTreeIndex);
if (!(child.Symbol is Constant) && nodeImpacts[child].IsAlmost(1.0)) {
SwitchNodeWithReplacementNode(parent, subTreeIndex);
}
}
}
// show only interesting part of solution
this.treeChart.Tree = new SymbolicExpressionTree(tree.Root.GetSubtree(0).GetSubtree(0));
this.PaintNodeImpacts();
}
}
protected abstract Dictionary CalculateReplacementValues(ISymbolicExpressionTree tree);
protected abstract Dictionary CalculateImpactValues(ISymbolicExpressionTree tree);
protected abstract void UpdateModel(ISymbolicExpressionTree tree);
private ConstantTreeNode MakeConstantTreeNode(double value) {
Constant constant = new Constant();
constant.MinValue = value - 1;
constant.MaxValue = value + 1;
ConstantTreeNode constantTreeNode = (ConstantTreeNode)constant.CreateTreeNode();
constantTreeNode.Value = value;
return constantTreeNode;
}
private void treeChart_SymbolicExpressionTreeNodeDoubleClicked(object sender, MouseEventArgs e) {
VisualSymbolicExpressionTreeNode visualTreeNode = (VisualSymbolicExpressionTreeNode)sender;
var tree = Content.Model.SymbolicExpressionTree;
foreach (SymbolicExpressionTreeNode treeNode in tree.IterateNodesPostfix()) {
for (int i = 0; i < treeNode.SubtreesCount; i++) {
ISymbolicExpressionTreeNode subTree = treeNode.GetSubtree(i);
if (subTree == visualTreeNode.SymbolicExpressionTreeNode) {
SwitchNodeWithReplacementNode(treeNode, i);
}
}
}
// show only interesting part of solution
this.treeChart.Tree = new SymbolicExpressionTree(tree.Root.GetSubtree(0).GetSubtree(0));
UpdateModel(tree);
}
private void SwitchNodeWithReplacementNode(ISymbolicExpressionTreeNode parent, int subTreeIndex) {
ISymbolicExpressionTreeNode subTree = parent.GetSubtree(subTreeIndex);
parent.RemoveSubtree(subTreeIndex);
if (replacementNodes.ContainsKey(subTree)) {
var replacementNode = replacementNodes[subTree];
parent.InsertSubtree(subTreeIndex, replacementNode);
// exchange key and value
replacementNodes.Remove(subTree);
replacementNodes.Add(replacementNode, subTree);
}
}
private void PaintNodeImpacts() {
var impacts = nodeImpacts.Values;
double max = impacts.Max();
double min = impacts.Min();
foreach (ISymbolicExpressionTreeNode treeNode in Content.Model.SymbolicExpressionTree.IterateNodesPostfix()) {
if (!(treeNode is ConstantTreeNode) && nodeImpacts.ContainsKey(treeNode)) {
double impact = nodeImpacts[treeNode];
VisualSymbolicExpressionTreeNode visualTree = treeChart.GetVisualSymbolicExpressionTreeNode(treeNode);
// impact = 0 if no change
// impact < 0 if new solution is better
// impact > 0 if new solution is worse
if (impact < 0.0) {
// min is guaranteed to be < 0
visualTree.FillColor = Color.FromArgb((int)(impact / min * 255), Color.Red);
} else if (impact.IsAlmost(0.0)) {
visualTree.FillColor = Color.White;
} else {
// max is guaranteed to be > 0
visualTree.FillColor = Color.FromArgb((int)(impact / max * 255), Color.Green);
}
visualTree.ToolTip += Environment.NewLine + "Node impact: " + impact;
var constantReplacementNode = replacementNodes[treeNode] as ConstantTreeNode;
if (constantReplacementNode != null) {
visualTree.ToolTip += Environment.NewLine + "Replacement value: " + constantReplacementNode.Value;
}
}
}
this.PaintCollapsedNodes();
this.treeChart.Repaint();
}
private void PaintCollapsedNodes() {
foreach (ISymbolicExpressionTreeNode treeNode in Content.Model.SymbolicExpressionTree.IterateNodesPostfix()) {
if (treeNode is ConstantTreeNode && replacementNodes.ContainsKey(treeNode))
this.treeChart.GetVisualSymbolicExpressionTreeNode(treeNode).LineColor = Color.DarkOrange;
else {
VisualSymbolicExpressionTreeNode visNode = treeChart.GetVisualSymbolicExpressionTreeNode(treeNode);
if (visNode != null)
visNode.LineColor = Color.Black;
}
}
}
private void btnSimplify_Click(object sender, EventArgs e) {
SymbolicDataAnalysisExpressionTreeSimplifier simplifier = new SymbolicDataAnalysisExpressionTreeSimplifier();
var simplifiedExpressionTree = simplifier.Simplify(Content.Model.SymbolicExpressionTree);
UpdateModel(simplifiedExpressionTree);
}
}
}