olb::util::Randomizer< T, useStored > Class Template Reference

#include <random.h>

Collaboration diagram for olb::util::Randomizer< T, useStored >:

Public Member Functions
	Randomizer ()
	Constructor for (useStored=false)
	Randomizer (std::vector< T > sequence)
	Constructor with passed sequence.
	Randomizer (std::string filePathSequence, bool enforceStored=false)
	Constroctor with filePath to stored sequence.
template<typename O = T>
O	generate ()
	Generate scalar or vector filled with scalars.
T	generateScalarNormal (T avg, T stdDev)
	Generate scalar leading to normal distribution based on the Box-Muller approach.
T	generateScalarNormal (T avg, T stdDev, T cutoff)
void	writeSequence (std::size_t numOfValues, std::string filePathSequence="./randomSequence.dat", int precision=5)
	Write sequence to file for later retrieval.

Detailed Description

template<typename T, bool useStored = false>
class olb::util::Randomizer< T, useStored >

Definition at line 40 of file random.h.

Constructor & Destructor Documentation

Randomizer() [1/3]

template<typename T , bool useStored>

olb::util::Randomizer< T, useStored >::Randomizer

(

)

Constructor for (useStored=false)

Definition at line 35 of file random.hh.

{
  static_assert(!useStored, "ERROR: no sequence provided");
}

Randomizer() [2/3]

template<typename T , bool useStored>

olb::util::Randomizer< T, useStored >::Randomizer

(

std::vector< T >

sequence

)

Constructor with passed sequence.

Definition at line 41 of file random.hh.

  : _storedSequence(sequence)
{}

Randomizer() [3/3]

template<typename T , bool useStored>

olb::util::Randomizer< T, useStored >::Randomizer	(	std::string	filePathSequence,
		bool	enforceStored = false )

Constroctor with filePath to stored sequence.

• throws error, if file does not exist and enforceStored=true

Definition at line 47 of file random.hh.

{
  [[maybe_unused]] std::size_t count = 0;
  int rank = singleton::mpi().getRank();
  if (rank == 0){
    //Check whether file exists and create, if not
    std::ifstream filePre(filePathSequence.c_str(), std::ios::in);
    if (!filePre.good()){
      if (!enforceStored){
        writeSequence(1000,filePathSequence.c_str());
      } else {
        throw std::runtime_error("ERROR: Sequence not provided for Randomizer!");
      }
    }
    //Read actual file
    std::ifstream file(filePathSequence.c_str(), std::ios::in);
    std::string strVal;
    while (std::getline(file, strVal))
    {
      _storedSequence.push_back(std::stod(strVal));
      ++count;
    }
  }
 
#ifdef PARALLEL_MODE_MPI
  //Align count on all cores
  singleton::mpi().bCast<std::size_t>( &count, 1 );
 
  //Align vector size on all cores
  if (rank != 0){
    _storedSequence.resize(count);
  }
 
  //Align vector content on all cores
  singleton::mpi().bCast( _storedSequence.data(), count );
#endif
}

References olb::singleton::MpiManager::bCast(), olb::singleton::MpiManager::getRank(), and olb::singleton::mpi().

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Member Function Documentation

generate()

template<typename T , bool useStored>

template<typename O >

O olb::util::Randomizer< T, useStored >::generate

(

)

Generate scalar or vector filled with scalars.

Definition at line 90 of file random.hh.

{
  if constexpr (std::is_arithmetic<O>::value) {
    O output = generateScalar();
    return output;
  } else {
    O output;
    for(unsigned iDim=0; iDim<O::d; ++iDim){
      output[iDim] = generateScalar();
    }
    return output;
  }
}

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generateScalarNormal() [1/2]

template<typename T , bool useStored>

T olb::util::Randomizer< T, useStored >::generateScalarNormal	(	T	avg,
		T	stdDev )

Generate scalar leading to normal distribution based on the Box-Muller approach.

Definition at line 105 of file random.hh.

{
  T A = generateScalar();
  T B = generateScalar();
  T x = util::cos(2 * M_PI * A) * util::sqrt(-2 * util::log(B));
  T output = avg + x * stdDev;
  return output;
}

References olb::util::cos(), olb::util::log(), M_PI, and olb::util::sqrt().

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generateScalarNormal() [2/2]

template<typename T , bool useStored>

T olb::util::Randomizer< T, useStored >::generateScalarNormal	(	T	avg,
		T	stdDev,
		T	cutoff )

Definition at line 115 of file random.hh.

{
  T scalar = generateScalarNormal( avg, stdDev );
  if (scalar<(avg-cutoff) || scalar>(avg+cutoff)){
    scalar = generateScalarNormal(avg, stdDev, cutoff );
  }
  return scalar;
}

writeSequence()

template<typename T , bool useStored>

void olb::util::Randomizer< T, useStored >::writeSequence	(	std::size_t	numOfValues,
		std::string	filePathSequence = "./randomSequence.dat",
		int	precision = 5 )

Write sequence to file for later retrieval.

Definition at line 125 of file random.hh.

{
  int rank = singleton::mpi().getRank();
  if (rank == 0){
    std::ofstream writer;
    writer.open( filePathSequence );
    writer << std::setprecision(precision);
    for (std::size_t i=0; i<numOfValues; ++i){
      writer << generateScalarRandom() << " " << std::endl;
    }
    writer.close();
  }
}

References olb::singleton::MpiManager::getRank(), and olb::singleton::mpi().

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The documentation for this class was generated from the following files:

• src/utilities/random.h
• src/utilities/random.hh