#region License Information
/* HeuristicLab
* Copyright (C) 2002-2014 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.Linq;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
//using HeuristicLab.EvolutionTracking;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
public static class SymbolicExpressionTreeMatching {
public static bool ContainsSubtree(this ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode subtree, SymbolicExpressionTreeNodeSimilarityComparer comparer) {
return FindMatches(root, subtree, comparer).Any();
}
public static IEnumerable FindMatches(ISymbolicExpressionTree tree, ISymbolicExpressionTreeNode subtree, SymbolicExpressionTreeNodeSimilarityComparer comparer) {
return FindMatches(tree.Root, subtree, comparer);
}
public static IEnumerable FindMatches(ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode subtree, SymbolicExpressionTreeNodeSimilarityComparer comp) {
var fragmentLength = subtree.GetLength();
// below, we use ">=" for Match(n, subtree, comp) >= fragmentLength because in case of relaxed conditions,
// we can have multiple matches of the same node
return root.IterateNodesBreadth().Where(n => n.GetLength() >= fragmentLength && Match(n, subtree, comp) == fragmentLength);
}
///
/// Finds the longest common subsequence in quadratic time and linear space
/// Variant of:
/// D. S. Hirschberg. A linear space algorithm for or computing maximal common subsequences. 1975.
/// http://dl.acm.org/citation.cfm?id=360861
///
/// Number of pairs that were matched
public static int Match(ISymbolicExpressionTreeNode a, ISymbolicExpressionTreeNode b, SymbolicExpressionTreeNodeSimilarityComparer comp) {
if (!comp.Equals(a, b)) return 0;
int m = a.SubtreeCount;
int n = b.SubtreeCount;
if (m == 0 || n == 0) return 1;
var matrix = new int[m + 1, n + 1];
for (int i = 1; i <= m; ++i) {
var ai = a.GetSubtree(i - 1);
for (int j = 1; j <= n; ++j) {
var bj = b.GetSubtree(j - 1);
int match = Match(ai, bj, comp);
matrix[i, j] = Math.Max(Math.Max(matrix[i, j - 1], matrix[i - 1, j]), matrix[i - 1, j - 1] + match);
}
}
return matrix[m, n] + 1;
}
///
/// Calculates the difference between two symbolic expression trees.
///
/// The first symbolic expression tree
/// The second symbolic expression tree
/// Returns the root of the subtree (from T1) by which T1 differs from T2, or null if no difference is found.
public static ISymbolicExpressionTreeNode Difference(this ISymbolicExpressionTree tree, ISymbolicExpressionTree other) {
return Difference(tree.Root, other.Root);
}
public static ISymbolicExpressionTreeNode Difference(this ISymbolicExpressionTreeNode node, ISymbolicExpressionTreeNode other) {
var a = node.IterateNodesPrefix().ToList();
var b = other.IterateNodesPrefix().ToList();
var list = new List();
for (int i = 0, j = 0; i < a.Count && j < b.Count; ++i, ++j) {
var s1 = a[i].ToString();
var s2 = b[j].ToString();
if (s1 == s2) continue;
list.Add(a[i]);
// skip subtrees since the parents are already different
i += a[i].SubtreeCount;
j += b[j].SubtreeCount;
}
ISymbolicExpressionTreeNode result = list.Count > 0 ? LowestCommonAncestor(node, list) : null;
return result;
}
private static ISymbolicExpressionTreeNode LowestCommonAncestor(ISymbolicExpressionTreeNode root, List nodes) {
if (nodes.Count == 0)
throw new ArgumentException("The nodes list should contain at least one element.");
if (nodes.Count == 1)
return nodes[0];
int minLevel = nodes.Min(x => root.GetBranchLevel(x));
// bring the nodes in the nodes to the same level (relative to the root)
for (int i = 0; i < nodes.Count; ++i) {
var node = nodes[i];
var level = root.GetBranchLevel(node);
for (int j = minLevel; j < level; ++j)
node = node.Parent;
nodes[i] = node;
}
// while not all the elements in the nodes are equal, go one level up
while (nodes.Any(x => x != nodes[0])) {
for (int i = 0; i < nodes.Count; ++i)
nodes[i] = nodes[i].Parent;
}
return nodes[0];
}
}
}