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

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Persistence.Default.Xml;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.EvolutionTracking.Tests {
  [TestClass]
  public class GenealogyOperationsPerformanceTests {
    private readonly IGenealogyGraph<ISymbolicExpressionTree> graph;

    public GenealogyOperationsPerformanceTests() {
      graph = XmlParser.Deserialize<IGenealogyGraph<ISymbolicExpressionTree>>("genealogyGraph.hl");
    }

    [TestMethod]
    public void TestTracingPerformance() {
      var tc = new TraceCalculator();
      //      var bestIndividual = (IGenealogyGraphNode<ISymbolicExpressionTree>)graph.Ranks.Last().Value.OrderBy(x => x.Quality).Last();
      var sw = new Stopwatch();
      sw.Start();
      //      double s = graph.Ranks.Last().Value.Average(x => tc.Trace((IGenealogyGraphNode<ISymbolicExpressionTree>) x, 2));  
      double s = graph.Ranks.Last().Value.Aggregate<IGenealogyGraphNode, double>(0, (current, individual) => current + tc.Trace((IGenealogyGraphNode<ISymbolicExpressionTree>)individual, 2).Vertices.Count());
      //      var trace = tc.Trace(bestIndividual, 2);
      sw.Stop();
      Console.WriteLine("Avg trace size: {0}", s / graph.Ranks.Last().Value.Count());
      //      var ancestry = bestIndividual.Ancestors;
      //      Console.WriteLine("Ancestry size: {0}", ancestry.Count());
      //      Console.WriteLine("Trace size: {0}", trace.Vertices.Count());
      Console.WriteLine("Elapsed time: {0}", sw.ElapsedMilliseconds / 1000.0);
    }

    [TestMethod]
    public void TestAncestorsPerformance() {
      var sw = new Stopwatch();
      sw.Start();
      List<IEnumerable<IGenealogyGraphNode>> ancestries = graph.Ranks.Last().Value.Select(x => x.Ancestors).ToList();
      sw.Stop();
      Console.WriteLine("Average ancestry size: {0}", ancestries.Average(x => x.Count()));
      Console.WriteLine("Elapsed time: {0}", sw.ElapsedMilliseconds / 1000.0);

      sw.Restart();
      var overlap = ancestries[0].Intersect(ancestries[1]).Count();
      sw.Stop();
      Console.WriteLine("Overlap: {0}", overlap);
      Console.WriteLine("Elapsed time: {0}", sw.ElapsedMilliseconds / 1000.0);
    }
  }
}