source: branches/2895_PushGP_GenealogyAnalysis/HeuristicLab.Problems.ProgramSynthesis/Push/Problem/PushProblemBase.cs @ 16724

using System;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.ProgramSynthesis {
  [StorableClass]
  public abstract class PushProblemBase<T> : SingleObjectiveBasicProblem<T> where T : class, IEncoding {
    [Storable]
    public readonly PushConfiguration Config;

    protected PushInterpreterPool Pool;
    protected readonly SeededRandomPool RandomPool = new SeededRandomPool();

    [Storable]
    protected readonly IPushEvaluator PushEvaluator;

    private const string BEST_TRAINING_SOLUTION_RESULT_NAME = "Best Solution";
    private const string TEST_QUALITY_RESULT_NAME = "Test Quality";
    private const string PUSH_CONFIGURATION_PARAMETER_NAME = "PushConfiguration";

    public const string CasesScopeParameterName = "CaseQualities";
    public const string CaseQualitiesScopeParameterName = "CaseQualities";
    public const string SeedScopeParameterName = "Seed";

    protected PushProblemBase(IPushEvaluator evaluator) {
      Config = new PushConfiguration();
      PushEvaluator = evaluator;

      InitData();
      InitParameters();
    }

    [StorableConstructor]
    protected PushProblemBase(bool deserializing)
      : base(deserializing) {
    }

    protected PushProblemBase(PushProblemBase<T> original, Cloner cloner)
      : base(original, cloner) {
      Config = cloner.Clone(original.Config);
      PushEvaluator = cloner.Clone(original.PushEvaluator);

      InitData();
    }

    [StorableHook(HookType.AfterDeserialization)]
    // ReSharper disable once UnusedMember.Local
    private void AfterDeserialization() {
      InitData();
      InitParameters();
    }

    private void InitData() {
      Pool = new PushInterpreterPool(Environment.ProcessorCount * 2, 4096, 1024, Config);
    }

    private void InitParameters() {
      foreach (var paramater in Config.Parameters) {
        if (!Parameters.ContainsKey(paramater.Name)) {
          Parameters.Add(paramater);
        }
      }

      if (!Parameters.ContainsKey(PUSH_CONFIGURATION_PARAMETER_NAME))
        Parameters.Add(new ValueParameter<IReadOnlyPushConfiguration>(PUSH_CONFIGURATION_PARAMETER_NAME, Config) {
          Hidden = true
        });

      if (!Parameters.ContainsKey(CasesScopeParameterName))
        Parameters.Add(new LookupParameter<BoolArray>(CasesScopeParameterName, "The training cases that have been successfully executed."));

      if (!Parameters.ContainsKey(CaseQualitiesScopeParameterName))
        Parameters.Add(new LookupParameter<DoubleArray>(CaseQualitiesScopeParameterName, "The quality of every single training case for each individual"));
    }

    public override bool Maximization { get { return false; } }

    public override void Analyze(Individual[] individuals, double[] qualities, ResultCollection results, IRandom random) {
      var bestQuality = Maximization ? qualities.Max() : qualities.Min();
      var bestIdx = Array.IndexOf(qualities, bestQuality);
      var bestIndividual = individuals[bestIdx];
      var seed = (IntValue)bestIndividual[SeedScopeParameterName];
      var program = MapIndividual(bestIndividual);

      var rand = new FastRandom(seed.Value);
      var isIndividualBetter = AnalyzeBestTrainingSolution(program, bestQuality, results, rand);

      if (isIndividualBetter) {
        rand.Reset(seed.Value);
        AnalyzeBestTestSolution(program, results, rand);
      }
    }

    protected void AnalyzeBestTestSolution(PushProgram program, ResultCollection results, IRandom random) {
      var testResult = PushEvaluator.EvaluateTest(Pool, program, random);

      if (!results.ContainsKey(TEST_QUALITY_RESULT_NAME)) {
        results.Add(new Result(TEST_QUALITY_RESULT_NAME, new DoubleValue(testResult.AvgQuality)));
      } else {
        ((DoubleValue)results[TEST_QUALITY_RESULT_NAME].Value).Value = testResult.AvgQuality;
      }
    }

    protected bool AnalyzeBestTrainingSolution(PushProgram program, double bestQuality, ResultCollection results, IRandom random) {
      var solution = CreatePushSolution(
            program,
            bestQuality,
            random, // is already cloned
            (IReadOnlyPushConfiguration)Config.Clone());

      if (!results.ContainsKey(BEST_TRAINING_SOLUTION_RESULT_NAME)) {
        results.Add(new Result(BEST_TRAINING_SOLUTION_RESULT_NAME, solution));
        return true;
      }

      var currentBestQuality = ((PushSolution)results[BEST_TRAINING_SOLUTION_RESULT_NAME].Value).Quality;

      if ((!Maximization && currentBestQuality > bestQuality) ||
           (Maximization && currentBestQuality < bestQuality)) {
        results[BEST_TRAINING_SOLUTION_RESULT_NAME].Value = solution;
        return true;
      }

      return false;
    }

    public override double Evaluate(Individual individual, IRandom random) {
      var program = MapIndividual(individual);
      var seed = random.Next();
      var rand = new FastRandom(seed);
      var result = PushEvaluator.EvaluateTraining(Pool, program, rand);

      individual[CaseQualitiesScopeParameterName] = new DoubleArray(result.ExampleQualities);
      individual[SeedScopeParameterName] = new IntValue(seed);

      return result.AvgQuality;
    }

    protected abstract PushProgram MapIndividual(Individual individual);

    protected abstract PushSolution CreatePushSolution(
      PushProgram program,
      double bestQuality,
      IRandom random,
      IReadOnlyPushConfiguration config);
  }
}