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rAKA/src/common/aka_random_generator.hh
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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: Tue Sep 29 2020
*
* @brief generic random generator
*
*
* @section LICENSE
*
* Copyright (©) 2014-2021 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 <random>
/* -------------------------------------------------------------------------- */
#ifndef AKANTU_AKA_RANDOM_GENERATOR_HH_
#define AKANTU_AKA_RANDOM_GENERATOR_HH_
namespace akantu {
/* -------------------------------------------------------------------------- */
/* List of available distributions */
/* -------------------------------------------------------------------------- */
// clang-format off
#define AKANTU_RANDOM_DISTRIBUTION_TYPES \
((uniform , std::uniform_real_distribution )) \
((exponential , std::exponential_distribution )) \
((gamma , std::gamma_distribution )) \
((weibull , std::weibull_distribution )) \
((extreme_value, std::extreme_value_distribution)) \
((normal , std::normal_distribution )) \
((lognormal , std::lognormal_distribution )) \
((chi_squared , std::chi_squared_distribution )) \
((cauchy , std::cauchy_distribution )) \
((fisher_f , std::fisher_f_distribution )) \
((student_t , std::student_t_distribution ))
// clang-format on
#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
};
/* -------------------------------------------------------------------------- */
/* Generator */
/* -------------------------------------------------------------------------- */
template <typename T> class RandomGenerator {
/* ------------------------------------------------------------------------ */
private:
static long int _seed; // NOLINT
static std::default_random_engine generator; // NOLINT
/* ------------------------------------------------------------------------ */
public:
inline T operator()() { return generator(); }
/// function to print the contain of the class
void printself(std::ostream & stream, int /* indent */) const {
stream << "RandGenerator [seed=" << _seed << "]";
}
/* ------------------------------------------------------------------------ */
public:
static void seed(long int s) {
_seed = s;
generator.seed(_seed);
}
static long int seed() { return _seed; }
static constexpr T min() { return std::default_random_engine::min(); }
static constexpr T max() { return std::default_random_engine::max(); }
};
#if defined(__clang__)
template <typename T> long int RandomGenerator<T>::_seed; // NOLINT
template <typename T> std::default_random_engine RandomGenerator<T>::generator;
#endif
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------- */
#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, 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) < \
T> > { \
enum { \
value = AKANTU_RANDOM_DISTRIBUTION_TYPES_PREFIX( \
BOOST_PP_TUPLE_ELEM(2, 0, elem)) \
}; \
\
static void printself(std::ostream & stream) { \
stream << BOOST_PP_STRINGIZE(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
/* -------------------------------------------------------------------------- */
template <class T> class RandomDistribution {
public:
virtual ~RandomDistribution() = default;
RandomDistribution() = default;
RandomDistribution(const RandomDistribution & other) = default;
RandomDistribution(RandomDistribution && other) noexcept = default;
RandomDistribution & operator=(const RandomDistribution & other) = default;
RandomDistribution &
operator=(RandomDistribution && other) noexcept = default;
virtual T operator()(RandomGenerator<Idx> & gen) = 0;
virtual std::unique_ptr<RandomDistribution<T>> make_unique() const = 0;
virtual void printself(std::ostream & stream, int = 0) const = 0;
};
template <class T, class Distribution>
class RandomDistributionProxy : public RandomDistribution<T> {
public:
explicit RandomDistributionProxy(Distribution dist)
: distribution(std::move(dist)) {}
T operator()(RandomGenerator<Idx> & gen) override {
return distribution(gen);
}
std::unique_ptr<RandomDistribution<T>> make_unique() const override {
return std::make_unique<RandomDistributionProxy<T, Distribution>>(
distribution);
}
void printself(std::ostream & stream, int /* indent */ = 0) const override {
RandomDistributionTypeHelper<T, Distribution>::printself(stream);
stream << " [ " << distribution << " ]";
}
private:
Distribution distribution;
};
/* -------------------------------------------------------------------------- */
/* RandomParameter */
/* -------------------------------------------------------------------------- */
template <typename T> class RandomParameter {
public:
template <class Distribution>
explicit RandomParameter(T base_value, Distribution dist)
: base_value(base_value),
type(RandomDistributionType(
RandomDistributionTypeHelper<T, Distribution>::value)),
distribution_proxy(
std::make_unique<RandomDistributionProxy<T, Distribution>>(
std::move(dist))) {}
explicit RandomParameter(T base_value)
: base_value(base_value),
type(RandomDistributionType(
RandomDistributionTypeHelper<
T, std::uniform_real_distribution<T>>::value)),
distribution_proxy(
std::make_unique<
RandomDistributionProxy<T, std::uniform_real_distribution<T>>>(
std::uniform_real_distribution<T>(0., 0.))) {}
RandomParameter(const RandomParameter & other)
: base_value(other.base_value), type(other.type),
distribution_proxy(other.distribution_proxy->make_unique()) {}
RandomParameter & operator=(const RandomParameter & other) {
distribution_proxy = other.distribution_proxy->make_unique();
base_value = other.base_value;
type = other.type;
return *this;
}
RandomParameter(RandomParameter && other) noexcept = default;
RandomParameter & operator=(RandomParameter && other) noexcept = default;
virtual ~RandomParameter() = default;
inline void setBaseValue(const T & value) { this->base_value = value; }
inline T getBaseValue() const { return this->base_value; }
template <template <typename> class Generator, class iterator>
void setValues(iterator it, iterator end) {
RandomGenerator<Idx> gen;
for (; it != end; ++it) {
*it = this->base_value + (*distribution_proxy)(gen);
}
}
virtual void printself(std::ostream & stream,
__attribute__((unused)) int indent = 0) const {
stream << base_value;
stream << " + " << *distribution_proxy;
}
private:
/// Value with no random variations
T base_value;
/// Random distribution type
RandomDistributionType type;
/// Proxy to store a std random distribution
std::unique_ptr<RandomDistribution<T>> distribution_proxy;
};
/* -------------------------------------------------------------------------- */
template <typename T>
inline std::ostream & operator<<(std::ostream & stream,
RandomDistribution<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;
}
} // namespace akantu
#endif /* AKANTU_AKA_RANDOM_GENERATOR_HH_ */
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