BayesianClusterSearch.h

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#pragma once
 
#include <limits>
#include <map>
#include <set>
#include <unordered_set>
 
#include "GaussianModel/GaussianCluster.h"
#include "TuningStrategyInterface.h"
#include "autopas/containers/CompatibleLoadEstimators.h"
#include "autopas/containers/CompatibleTraversals.h"
#include "autopas/tuning/searchSpace/EvidenceCollection.h"
#include "autopas/tuning/utils/FeatureVectorEncoder.h"
#include "autopas/utils/NumberSet.h"
 
namespace autopas {
 
class BayesianClusterSearch : public TuningStrategyInterface {
  constexpr static size_t maxAttempts = 10;
  constexpr static double secondsPerMicroseconds = 1. / 1000000.;
  constexpr static size_t continuousDims = FeatureVectorEncoder::tunableContinuousDims + 1;
  constexpr static double sigma = 0.01;
 
  constexpr static double iterationScalePerMaxEvidence = 5.;
 
  constexpr static double suggestedMaxDistance = 7.;
 
 public:
  explicit BayesianClusterSearch(
      const InteractionTypeOption &interactionType,
      const std::set<ContainerOption> &allowedContainerOptions = ContainerOption::getAllOptions(),
      const NumberSet<double> &allowedCellSizeFactors = NumberInterval<double>(1., 2.),
      const std::set<TraversalOption> &allowedTraversalOptions = TraversalOption::getAllOptions(),
      const std::set<LoadEstimatorOption> &allowedLoadEstimatorOptions = LoadEstimatorOption::getAllOptions(),
      const std::set<DataLayoutOption> &allowedDataLayoutOptions = DataLayoutOption::getAllOptions(),
      const std::set<Newton3Option> &allowedNewton3Options = Newton3Option::getAllOptions(), size_t maxEvidence = 10,
      AcquisitionFunctionOption predAcqFunction = AcquisitionFunctionOption::upperConfidenceBound,
      const std::string &outputSuffix = "", size_t predNumLHSamples = 50, unsigned long seed = std::random_device()());
 
  ~BayesianClusterSearch() override;
 
  TuningStrategyOption getOptionType() const override;
 
  void addEvidence(const Configuration &configuration, const Evidence &evidence) override;
 
  bool reset(size_t iteration, size_t tuningPhase, std::vector<Configuration> &configQueue,
             const autopas::EvidenceCollection &evidenceCollection) override;
 
  bool optimizeSuggestions(std::vector<Configuration> &configQueue,
                           const EvidenceCollection &evidenceCollection) override;
 
  void rejectConfiguration(const Configuration &configuration, bool indefinitely) override;
 
  bool searchSpaceIsEmpty() const;
 
  bool needsSmoothedHomogeneityAndMaxDensity() const override { return false; }
 
 private:
  std::vector<autopas::GaussianModelTypes::VectorPairDiscreteContinuous> sampleAcquisitions(
      size_t n, AcquisitionFunctionOption af);
 
  void updateOptions();
 
  const InteractionTypeOption _interactionType;
 
  std::set<ContainerOption> _containerOptionsSet;
  std::vector<FeatureVector::ContainerTraversalEstimatorOption> _containerTraversalEstimatorOptions;
  std::vector<DataLayoutOption> _dataLayoutOptions;
  std::vector<Newton3Option> _newton3Options;
  std::unique_ptr<NumberSet<double>> _cellSizeFactors;
  FeatureVectorEncoder _encoder;
 
  std::vector<GaussianModelTypes::VectorPairDiscreteContinuous> _currentAcquisitions;
  std::unordered_set<FeatureVector, ConfigHash> _invalidConfigs;
  Random _rng;
  GaussianCluster _gaussianCluster;
  GaussianModelTypes::NeighbourFunction _neighbourFun;
  const size_t _maxEvidence;
  const AcquisitionFunctionOption _predAcqFunction;
  const size_t _predNumLHSamples;
  bool _firstTuningPhase;
  size_t _currentIteration;
  const double _iterationScale;
  size_t _currentNumEvidence;
  long _currentOptimalTime;
  FeatureVector _currentOptimalConfig;
};
}  // namespace autopas