Program Listing for File discretegaussiangenerator.h

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/*
  This code provides generation of gaussian distributions of discrete values. Discrete uniform generator
  relies on the built-in C++ generator for 32-bit unsigned integers defined in <random>
 */

#ifndef LBCRYPTO_INC_MATH_DISCRETEGAUSSIANGENERATOR_H_
#define LBCRYPTO_INC_MATH_DISCRETEGAUSSIANGENERATOR_H_

#define _USE_MATH_DEFINES  // added for Visual Studio support

#include "math/distributiongenerator.h"

#include <memory>
#include <random>
#include <vector>

namespace lbcrypto {

constexpr double KARNEY_THRESHOLD = 300.0;

template <typename VecType>
class DiscreteGaussianGeneratorImpl {
public:
    explicit DiscreteGaussianGeneratorImpl(double std = 1.0);

    ~DiscreteGaussianGeneratorImpl() = default;

    bool IsInitialized() const;

    void Initialize();

    double GetStd() const;

    void SetStd(double std);

    int32_t GenerateInt() const;

    std::shared_ptr<int64_t> GenerateIntVector(uint32_t size) const;

    typename VecType::Integer GenerateInteger(const typename VecType::Integer& modulus) const;

    VecType GenerateVector(uint32_t size, const typename VecType::Integer& modulus) const;

    typename VecType::Integer GenerateInteger(double mean, double stddev, size_t n,
                                              const typename VecType::Integer& modulus) const;

    int32_t GenerateInteger(double mean, double stddev, size_t n) const;

    // int32_t GenerateInt32 (double mean, double stddev);
    // will be defined later

    static int64_t GenerateIntegerKarney(double mean, double stddev);

private:
    // Gyana to add precomputation methods and data members
    // all parameters are set as int because it is assumed that they are used for
    // generating "small" polynomials only
    double m_std{1.0};
    double m_a{0.0};
    std::vector<double> m_vals;
    bool peikert{false};

    uint32_t FindInVector(const std::vector<double>& S, double search) const;

    static double UnnormalizedGaussianPDF(const double& mean, const double& sigma, int32_t x) {
        return pow(M_E, -pow(x - mean, 2) / (2. * sigma * sigma));
    }

    static double UnnormalizedGaussianPDFOptimized(const double& mean, const double& sigmaFactor, int32_t x) {
        return pow(M_E, sigmaFactor * (x - mean) * (x - mean));
    }

    static bool AlgorithmP(PRNG& g, int32_t n);
    static int32_t AlgorithmG(PRNG& g);
    static bool AlgorithmH(PRNG& g);
    static bool AlgorithmHDouble(PRNG& g);
    static bool AlgorithmB(PRNG& g, int32_t k, double x);
    static bool AlgorithmBDouble(PRNG& g, int32_t k, double x);
};

}  // namespace lbcrypto

#endif  // LBCRYPTO_MATH_DISCRETEGAUSSIANGENERATOR_H_