#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
  [StorableClass]
  public class SymbolicExpressionTreeNode : DeepCloneable, ISymbolicExpressionTreeNode {
    [Storable]
    private IList<ISymbolicExpressionTreeNode> subTrees;
    [Storable]
    private ISymbol symbol;

    // cached values to prevent unnecessary tree iterations
    private ushort length;
    private ushort depth;

    public ISymbol Symbol {
      get { return symbol; }
      protected set { symbol = value; }
    }

    // parent relation is not persisted or cloned (will be set on AddSubtree or RemoveSubtree)
    private ISymbolicExpressionTreeNode parent;
    public ISymbolicExpressionTreeNode Parent {
      get { return parent; }
      set { parent = value; }
    }

    [StorableConstructor]
    protected SymbolicExpressionTreeNode(bool deserializing) { }
    protected SymbolicExpressionTreeNode(SymbolicExpressionTreeNode original, Cloner cloner)
      : base() {
      symbol = original.symbol; // symbols are reused
      subTrees = new List<ISymbolicExpressionTreeNode>(original.subTrees.Count);
      foreach (var subtree in original.subTrees) {
        var clonedSubTree = cloner.Clone(subtree);
        subTrees.Add(clonedSubTree);
        clonedSubTree.Parent = this;
      }
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new SymbolicExpressionTreeNode(this, cloner);
    }

    internal SymbolicExpressionTreeNode()
      : base() {
      // don't allocate subtrees list here!
      // because we don't want to allocate it in terminal nodes
    }

    public SymbolicExpressionTreeNode(ISymbol symbol)
      : base() {
      subTrees = new List<ISymbolicExpressionTreeNode>(3);
      this.symbol = symbol;
    }


    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      foreach (var subtree in subTrees) {
        subtree.Parent = this;
      }
    }

    public virtual bool HasLocalParameters {
      get { return false; }
    }

    public virtual IEnumerable<ISymbolicExpressionTreeNode> SubTrees {
      get { return subTrees; }
    }

    public virtual ISymbolicExpressionTreeGrammar Grammar {
      get { return parent.Grammar; }
    }

    public int GetLength() {
      if (length > 0) return length;
      else {
        length = 1;
        if (subTrees != null) {
          for (int i = 0; i < subTrees.Count; i++) {
            checked { length += (ushort)subTrees[i].GetLength(); }
          }
        }
        return length;
      }
    }

    public int GetDepth() {
      if (depth > 0) return depth;
      else {
        if (subTrees != null) {
          for (int i = 0; i < subTrees.Count; i++) depth = Math.Max(depth, (ushort)subTrees[i].GetDepth());
        }
        depth++;
        return depth;
      }
    }

    public virtual void ResetLocalParameters(IRandom random) { }
    public virtual void ShakeLocalParameters(IRandom random, double shakingFactor) { }

    public virtual ISymbolicExpressionTreeNode GetSubTree(int index) {
      return subTrees[index];
    }
    public virtual int IndexOfSubTree(ISymbolicExpressionTreeNode tree) {
      return subTrees.IndexOf(tree);
    }
    public virtual void AddSubTree(ISymbolicExpressionTreeNode tree) {
      subTrees.Add(tree);
      tree.Parent = this;
      ResetCachedValues();
    }
    public virtual void InsertSubTree(int index, ISymbolicExpressionTreeNode tree) {
      subTrees.Insert(index, tree);
      tree.Parent = this;
      ResetCachedValues();
    }
    public virtual void RemoveSubTree(int index) {
      subTrees[index].Parent = null;
      subTrees.RemoveAt(index);
      ResetCachedValues();
    }

    public IEnumerable<ISymbolicExpressionTreeNode> IterateNodesPrefix() {
      List<ISymbolicExpressionTreeNode> list = new List<ISymbolicExpressionTreeNode>();
      ForEachNodePrefix((n) => list.Add(n));
      return list;
    }

    public void ForEachNodePrefix(Action<ISymbolicExpressionTreeNode> a) {
      a(this);
      if (SubTrees != null) {
        foreach (var subtree in SubTrees) {
          subtree.ForEachNodePrefix(a);
        }
      }
    }

    public IEnumerable<ISymbolicExpressionTreeNode> IterateNodesPostfix() {
      List<ISymbolicExpressionTreeNode> list = new List<ISymbolicExpressionTreeNode>();
      ForEachNodePostfix((n) => list.Add(n));
      return list;
    }

    public void ForEachNodePostfix(Action<ISymbolicExpressionTreeNode> a) {
      if (SubTrees != null) {
        foreach (var subtree in SubTrees) {
          subtree.ForEachNodePostfix(a);
        }
      }
      a(this);
    }

    public override string ToString() {
      return Symbol.Name;
    }

    private void ResetCachedValues() {
      length = 0; depth = 0;
      SymbolicExpressionTreeNode parentNode = parent as SymbolicExpressionTreeNode;
      if (parentNode != null) parentNode.ResetCachedValues();
    }
  }
}