random.hpp

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#ifndef MLPACK_CORE_MATH_RANDOM_HPP
#define MLPACK_CORE_MATH_RANDOM_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/mlpack_export.hpp>
#include <random>

namespace mlpack {
namespace math  {

// Global random object.
extern MLPACK_EXPORT std::mt19937 randGen;
// Global uniform distribution.
extern MLPACK_EXPORT std::uniform_real_distribution<> randUniformDist;
// Global normal distribution.
extern MLPACK_EXPORT std::normal_distribution<> randNormalDist;

inline void RandomSeed(const size_t seed)
{
  #if (!defined(BINDING_TYPE) || BINDING_TYPE != BINDING_TYPE_TEST)
    randGen.seed((uint32_t) seed);
    srand((unsigned int) seed);
    arma::arma_rng::set_seed(seed);
  #else
    (void) seed;
  #endif
}

#if (BINDING_TYPE == BINDING_TYPE_TEST)
inline void FixedRandomSeed()
{
  const static size_t seed = rand();
  randGen.seed((uint32_t) seed);
  srand((unsigned int) seed);
  arma::arma_rng::set_seed(seed);
}
#endif

inline double Random()
{
  return randUniformDist(randGen);
}

inline double Random(const double lo, const double hi)
{
  return lo + (hi - lo) * randUniformDist(randGen);
}

inline double RandBernoulli(const double input)
{
  if (Random() < input)
    return 1;
  else
    return 0;
}

inline int RandInt(const int hiExclusive)
{
  return (int) std::floor((double) hiExclusive * randUniformDist(randGen));
}

inline int RandInt(const int lo, const int hiExclusive)
{
  return lo + (int) std::floor((double) (hiExclusive - lo)
                               * randUniformDist(randGen));
}

inline double RandNormal()
{
  return randNormalDist(randGen);
}

inline double RandNormal(const double mean, const double variance)
{
  return variance * randNormalDist(randGen) + mean;
}

inline void ObtainDistinctSamples(const size_t loInclusive,
                                  const size_t hiExclusive,
                                  const size_t maxNumSamples,
                                  arma::uvec& distinctSamples)
{
  const size_t samplesRangeSize = hiExclusive - loInclusive;

  if (samplesRangeSize > maxNumSamples)
  {
    arma::Col<size_t> samples;

    samples.zeros(samplesRangeSize);

    for (size_t i = 0; i < maxNumSamples; i++)
      samples [ (size_t) math::RandInt(samplesRangeSize) ]++;

    distinctSamples = arma::find(samples > 0);

    if (loInclusive > 0)
      distinctSamples += loInclusive;
  }
  else
  {
    distinctSamples.set_size(samplesRangeSize);
    for (size_t i = 0; i < samplesRangeSize; i++)
      distinctSamples[i] = loInclusive + i;
  }
}

} // namespace math
} // namespace mlpack

#endif // MLPACK_CORE_MATH_MATH_LIB_HPP