#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2008 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 System.Text;
using HeuristicLab.Constraints;
using HeuristicLab.DataAnalysis;

namespace HeuristicLab.Functions {
  public class Or : FunctionBase {
    public override string Description {
      get {
        return @"Logical OR operation. Only defined for sub-tree-results 0.0 and 1.0.
Special form, evaluation stops at first sub-tree that evaluates to 1.0 (true).";
      }
    }

    public Or()
      : base() {
      AddConstraint(new NumberOfSubOperatorsConstraint(2, 3));
    }

    public override IFunctionTree GetTreeNode() {
      return new OrFunctionTree(this);
    }
    // or is a special form and can't be applied
    public override double Apply(Dataset dataset, int sampleIndex, double[] args) {
      throw new NotImplementedException();
    }
    public override void Accept(IFunctionVisitor visitor) {
      visitor.Visit(this);
    }
  }

  class OrFunctionTree : FunctionTree {
    public OrFunctionTree() : base() { }
    public OrFunctionTree(Or or) : base(or) { }

    public override double Evaluate(Dataset dataset, int sampleIndex) {
      foreach(IFunctionTree subTree in SubTrees) {
        double result = Math.Round(subTree.Evaluate(dataset, sampleIndex));
        if(result == 1.0) return 1.0; // sub-tree evaluates to 1.0 (true) return 1.0
        else if(result != 0.0) return double.NaN;
      }
      // all sub-trees evaluated to 0.0 (false) return false
      return 0.0;
    }

    public override object Clone(IDictionary<Guid, object> clonedObjects) {
      OrFunctionTree clone = new OrFunctionTree();
      clonedObjects.Add(clone.Guid, clone);
      FillClone(clone, clonedObjects);
      return clone;
    }
  }
}