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aka_random_generator.hh
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/**
* @file aka_random_generator.hh
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Thu Feb 21 2013
* @date last modification: Wed Nov 11 2015
*
* @brief generic random generator
*
* @section LICENSE
*
* Copyright (©) 2014, 2015 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* Akantu is free software: you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation, either version 3 of the License, or (at your option) any
* later version.
*
* Akantu is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Akantu. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include "aka_array.hh"
#include "aka_common.hh"
#ifndef __AKANTU_AKA_RANDOM_GENERATOR_HH__
#define __AKANTU_AKA_RANDOM_GENERATOR_HH__
__BEGIN_AKANTU__
/* -------------------------------------------------------------------------- */
/* List of available distributions */
/* -------------------------------------------------------------------------- */
#define AKANTU_RANDOM_DISTRIBUTION_TYPES \
((uniform, UniformDistribution))((weibull, WeibullDistribution))
#define AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX(elem) BOOST_PP_CAT(_rdt_, elem)
#define AKANTU_RANDOM_DISTRIBUTION_PREFIX(s, data, elem) \
AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX(BOOST_PP_TUPLE_ELEM(2, 0, elem))
enum RandomDistributionType {
BOOST_PP_SEQ_ENUM(BOOST_PP_SEQ_TRANSFORM(AKANTU_RANDOM_DISTRIBUTION_PREFIX, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)),
_rdt_not_defined
};
/* -------------------------------------------------------------------------- */
/* Distribution */
/* -------------------------------------------------------------------------- */
/// Empty base to be able to store a distribution
template <typename T> class RandomDistributionBase {
public:
virtual ~RandomDistributionBase() {}
virtual void printself(std::ostream & stream, int indent = 0) const = 0;
};
/* -------------------------------------------------------------------------- */
/* Uniform distribution */
/* -------------------------------------------------------------------------- */
template <typename T>
class UniformDistribution : public RandomDistributionBase<T> {
public:
UniformDistribution(T min = T(0.), T max = T(1.)) : min(min), max(max){};
/* ------------------------------------------------------------------------ */
template <template <class> class RandomGenerator>
T operator()(RandomGenerator<T> & generator) {
T x = generator() / (RandomGenerator<T>::max() - RandomGenerator<T>::min());
return (x * (max - min) + min);
}
virtual void setParams(std::string value) {
std::stringstream sstr(value);
sstr >> min;
sstr >> max;
}
/// function to print the contain of the class
virtual void printself(std::ostream & stream,
__attribute__((unused)) int indent = 0) const {
stream << "Uniform [ min=" << min << ", max=" << max << " ]";
};
/* ------------------------------------------------------------------------ */
private:
T min;
T max;
};
/* -------------------------------------------------------------------------- */
/* Weibull distribution */
/* -------------------------------------------------------------------------- */
template <typename T>
class WeibullDistribution : public RandomDistributionBase<T> {
public:
WeibullDistribution(T scale, T shape) : m(shape), lambda(scale){};
/* ------------------------------------------------------------------------ */
template <template <class> class RandomGenerator>
T operator()(RandomGenerator<T> & generator) {
T x = generator() / (RandomGenerator<T>::max() - RandomGenerator<T>::min());
T e = T(1) / m;
return lambda * std::pow(-std::log(1. - x), e);
}
virtual void setParams(std::string value) {
std::stringstream sstr(value);
sstr >> m;
sstr >> lambda;
}
/// function to print the contain of the class
virtual void printself(std::ostream & stream,
__attribute__((unused)) int indent = 0) const {
stream << "Weibull [ shape=" << m << ", scale=" << lambda << "]";
}
/* ------------------------------------------------------------------------ */
private:
/// shape parameter or Weibull modulus
T m;
/// scale parameter
T lambda;
};
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
/* Generator */
/* -------------------------------------------------------------------------- */
#if not defined(_WIN32)
template <typename T> class Rand48Generator {
/* ------------------------------------------------------------------------ */
public:
inline T operator()();
/// function to print the contain of the class
virtual void printself(std::ostream & stream, int indent = 0) const;
/* ------------------------------------------------------------------------ */
public:
static void seed(long int s);
static long int seed();
static constexpr T min();
static constexpr T max();
/* ------------------------------------------------------------------------ */
private:
static long int _seed;
};
/* -------------------------------------------------------------------------- */
template <typename T> inline T Rand48Generator<T>::operator()() {
AKANTU_DEBUG_TO_IMPLEMENT();
}
template <> inline double Rand48Generator<double>::operator()() {
return drand48();
}
template <typename T>
void Rand48Generator<T>::printself(std::ostream & stream,
__attribute__((unused)) int indent) const {
stream << "Rand48Generator [seed=" << seed << "]";
}
template <typename T> void Rand48Generator<T>::seed(long int s) {
_seed = s;
srand48(_seed);
}
template <typename T> long int Rand48Generator<T>::seed() { return _seed; }
template <typename T> constexpr T Rand48Generator<T>::min() { return 0.; }
template <typename T> constexpr T Rand48Generator<T>::max() { return 1.; }
#endif
/* -------------------------------------------------------------------------- */
template <typename T> class RandGenerator {
/* ------------------------------------------------------------------------ */
public:
inline T operator()() { return rand(); }
/// function to print the contain of the class
virtual void printself(std::ostream & stream,
__attribute__((unused)) int indent = 0) const {
stream << "RandGenerator [seed=" << _seed << "]";
}
/* ------------------------------------------------------------------------ */
public:
static void seed(long int s) {
_seed = s;
srand(_seed);
}
static long int seed() { return _seed; }
static constexpr T min() { return 0.; }
static constexpr T max() { return RAND_MAX; }
/* ------------------------------------------------------------------------ */
private:
static long int _seed;
};
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
#undef AKANTU_RANDOM_DISTRIBUTION_PREFIX
#define AKANTU_RANDOM_DISTRIBUTION_TYPE_PRINT_CASE(r, data, elem) \
case AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem)): { \
stream << BOOST_PP_STRINGIZE(AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem))); \
break; \
}
inline std::ostream & operator<<(std::ostream & stream,
RandomDistributionType type) {
switch (type) {
BOOST_PP_SEQ_FOR_EACH(AKANTU_RANDOM_DISTRIBUTION_TYPE_PRINT_CASE, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
default:
stream << UInt(type) << " not a RandomDistributionType";
break;
}
return stream;
}
#undef AKANTU_RANDOM_DISTRIBUTION_TYPE_PRINT_CASE
/* -------------------------------------------------------------------------- */
/* Some Helper */
/* -------------------------------------------------------------------------- */
template <typename T, template <typename> class Distribution>
class RandomDistributionTypeHelper {
enum { value = _rdt_not_defined };
};
/* -------------------------------------------------------------------------- */
#define AKANTU_RANDOM_DISTRIBUTION_TYPE_GET_TYPE(r, data, elem) \
template <typename T> \
struct RandomDistributionTypeHelper<T, BOOST_PP_TUPLE_ELEM(2, 1, elem)> { \
enum { \
value = AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem)) \
}; \
};
BOOST_PP_SEQ_FOR_EACH(AKANTU_RANDOM_DISTRIBUTION_TYPE_GET_TYPE, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
#undef AKANTU_RANDOM_DISTRIBUTION_TYPE_GET_TYPE
/* -------------------------------------------------------------------------- */
/* RandomParameter */
/* -------------------------------------------------------------------------- */
template <typename T> class RandomParameter {
public:
explicit RandomParameter(T base_value)
: base_value(base_value), type(_rdt_not_defined), distribution(NULL) {}
template <template <typename> class Distribution>
RandomParameter(T base_value, const Distribution<T> & distribution)
: base_value(base_value),
type((RandomDistributionType)
RandomDistributionTypeHelper<T, Distribution>::value),
distribution(new Distribution<T>(distribution)) {}
#define AKANTU_RANDOM_DISTRIBUTION_TYPE_NEW(r, data, elem) \
else if (type == AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem))) { \
typedef BOOST_PP_TUPLE_ELEM(2, 1, elem)<T> Dist; \
distribution = new Dist(*static_cast<Dist *>(other.distribution)); \
}
RandomParameter(const RandomParameter & other)
: base_value(other.base_value), type(other.type) {
if (type == _rdt_not_defined)
distribution = NULL;
BOOST_PP_SEQ_FOR_EACH(AKANTU_RANDOM_DISTRIBUTION_TYPE_NEW, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
}
inline void setBaseValue(const T & value) { this->base_value = value; }
inline T getBaseValue() const { return this->base_value; }
RandomParameter & operator=(const RandomParameter & other) {
if (this != &other) {
base_value = other.base_value;
type = other.type;
delete distribution;
if (type == _rdt_not_defined)
distribution = NULL;
BOOST_PP_SEQ_FOR_EACH(AKANTU_RANDOM_DISTRIBUTION_TYPE_NEW, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
}
return *this;
}
#undef AKANTU_RANDOM_DISTRIBUTION_TYPE_NEW
/* ------------------------------------------------------------------------ */
#define AKANTU_RANDOM_DISTRIBUTION_TYPE_SET(r, data, elem) \
else if (type == AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem))) { \
this->set<BOOST_PP_TUPLE_ELEM(2, 1, elem), Generator>(it, end); \
}
template <template <typename> class Generator, class iterator>
void setValues(iterator it, iterator end) {
if (type == _rdt_not_defined) {
for (; it != end; ++it)
*it = this->base_value;
}
BOOST_PP_SEQ_FOR_EACH(AKANTU_RANDOM_DISTRIBUTION_TYPE_SET, _,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
}
#undef AKANTU_RANDOM_DISTRIBUTION_TYPE_SET
virtual void printself(std::ostream & stream,
__attribute__((unused)) int indent = 0) const {
stream << base_value;
if (type != _rdt_not_defined)
stream << " " << *distribution;
}
private:
template <template <typename> class Distribution,
template <typename> class Generator, class iterator>
void set(iterator it, iterator end) {
typedef Distribution<T> Dist;
Dist & dist = *(static_cast<Dist *>(this->distribution));
Generator<T> gen;
for (; it != end; ++it)
*it = this->base_value + dist(gen);
}
private:
/// Value with no random variations
T base_value;
/// Random distribution type
RandomDistributionType type;
/// Random distribution to use
RandomDistributionBase<T> * distribution;
};
/* -------------------------------------------------------------------------- */
template <typename T>
inline std::ostream & operator<<(std::ostream & stream,
RandomDistributionBase<T> & _this) {
_this.printself(stream);
return stream;
}
/* -------------------------------------------------------------------------- */
template <typename T>
inline std::ostream & operator<<(std::ostream & stream,
RandomParameter<T> & _this) {
_this.printself(stream);
return stream;
}
__END_AKANTU__
#endif /* __AKANTU_AKA_RANDOM_GENERATOR_HH__ */
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