using System;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;

namespace HeuristicLab.Algorithms.SAPBA.Strategies {
  public class IndividualStrategy : StrategyBase {
    public const string SampledIndividualsParameterName = "SampledIndividals";
    public IFixedValueParameter<IntValue> SampledIndividualsParameter => Parameters[SampledIndividualsParameterName] as IFixedValueParameter<IntValue>;
    public IntValue SampledIndividuals => SampledIndividualsParameter.Value;

    #region Constructors
    private IndividualStrategy(IndividualStrategy original, Cloner cloner) : base(original, cloner) {
    }
    public IndividualStrategy() {
      Parameters.Add(new FixedValueParameter<IntValue>(SampledIndividualsParameterName, "The number of individuals that are sampled each generation", new IntValue(3)));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new IndividualStrategy(this, cloner);
    }
    #endregion

    public override double Evaluate(RealVector r, IRandom random) {
      return EstimateSample(r, random).Item2;
    }

    protected override void Analyze(Individual[] individuals, double[] qualities, ResultCollection results, ResultCollection globalResults, IRandom random) {
    }

    protected override void ProcessPopulation(Individual[] individuals, double[] qualities, IRandom random) {
      var samples = individuals.Zip(qualities, (individual, d) => new Tuple<Individual, double>(individual, d)).OrderBy(t => Algorithm.Problem.Maximization ? -t.Item2 : t.Item2).Take(SampledIndividuals.Value).Select(t => t.Item1.RealVector());
      foreach (var indi in samples) EvaluateSample(indi, random);
      BuildRegressionSolution(random);
    }

    protected override void Initialize() {
    }
  }
}