Homec4science
Diffusion akantu (bugfixes/pypi-py311) Browse

rAKA/src/common/aka_random_generator.hh
01d5a6530006bugfixes/pypi-py311

Last Change
Raw File

aka_random_generator.hh
View Options

/**
* Copyright (©) 2013-2023 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* This file is part of Akantu
*
* 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 */
/* -------------------------------------------------------------------------- */
#define AKANTU_RANDOM_DISTRIBUTION_TYPES \
(uniform)(exponential)( \
gamma)(weibull)(extreme_value)(normal)(lognormal)(chi_squared)(cauchy)(fisher_f)(student_t)(not_defined)
AKANTU_CLASS_ENUM_DECLARE(RandomDistributionType,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
AKANTU_CLASS_ENUM_OUTPUT_STREAM(RandomDistributionType,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
AKANTU_CLASS_ENUM_INPUT_STREAM(RandomDistributionType,
AKANTU_RANDOM_DISTRIBUTION_TYPES)
/* -------------------------------------------------------------------------- */
/* 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 << "]";
}
std::default_random_engine & getGenerator(); // Needed on apple clang
/* ------------------------------------------------------------------------ */
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
/* -------------------------------------------------------------------------- */
/* Some Helper */
/* -------------------------------------------------------------------------- */
template <typename T, class Distribution> struct RandomDistributionTypeHelper {
static constexpr RandomDistributionType value =
RandomDistributionType::_not_defined;
};
template <>
struct RandomDistributionTypeHelper<Real,
std::uniform_real_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_uniform;
};
template <>
struct RandomDistributionTypeHelper<Real, std::exponential_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_exponential;
};
template <>
struct RandomDistributionTypeHelper<Real, std::gamma_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_gamma;
};
template <>
struct RandomDistributionTypeHelper<Real, std::weibull_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_weibull;
};
template <>
struct RandomDistributionTypeHelper<Real,
std::extreme_value_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_extreme_value;
};
template <>
struct RandomDistributionTypeHelper<Real, std::normal_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_normal;
};
template <>
struct RandomDistributionTypeHelper<Real, std::lognormal_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_lognormal;
};
template <>
struct RandomDistributionTypeHelper<Real, std::chi_squared_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_chi_squared;
};
template <>
struct RandomDistributionTypeHelper<Real, std::cauchy_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_cauchy;
};
template <>
struct RandomDistributionTypeHelper<Real, std::fisher_f_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_fisher_f;
};
template <>
struct RandomDistributionTypeHelper<Real, std::student_t_distribution<Real>> {
static constexpr RandomDistributionType value =
RandomDistributionType::_student_t;
};
/* -------------------------------------------------------------------------- */
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 this->distribution(gen.getGenerator());
}
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 {
stream << std::to_string(
RandomDistributionTypeHelper<T, Distribution>::value);
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;
}
template <typename T>
auto make_random_parameter(
T base,
RandomDistributionType distribution = RandomDistributionType::_uniform,
T a = T(), T b = T()) {
switch (distribution) {
case RandomDistributionType::_not_defined:
return RandomParameter<T>(base, std::uniform_real_distribution<T>(0., 0.));
case RandomDistributionType::_uniform:
return RandomParameter<T>(base, std::uniform_real_distribution<T>(a, b));
case RandomDistributionType::_exponential:
return RandomParameter<T>(base, std::exponential_distribution<T>(a));
case RandomDistributionType::_gamma:
return RandomParameter<T>(base, std::gamma_distribution<T>(a, b));
case RandomDistributionType::_weibull:
return RandomParameter<T>(base, std::weibull_distribution<T>(b, a));
case RandomDistributionType::_extreme_value:
return RandomParameter<T>(base, std::extreme_value_distribution<T>(a, b));
case RandomDistributionType::_normal:
return RandomParameter<T>(base, std::normal_distribution<T>(a, b));
case RandomDistributionType::_lognormal:
return RandomParameter<T>(base, std::lognormal_distribution<T>(a, b));
case RandomDistributionType::_chi_squared:
return RandomParameter<T>(base, std::chi_squared_distribution<T>(a));
case RandomDistributionType::_cauchy:
return RandomParameter<T>(base, std::cauchy_distribution<T>(a, b));
case RandomDistributionType::_fisher_f:
return RandomParameter<T>(base, std::fisher_f_distribution<T>(a, b));
case RandomDistributionType::_student_t:
return RandomParameter<T>(base, std::student_t_distribution<T>(a));
}
return RandomParameter<T>(base, std::uniform_real_distribution<T>(0., 0.));
}
template<typename T>
std::default_random_engine & RandomGenerator<T>::getGenerator() { return generator; } // Needed on apple clang
} // namespace akantu
#endif /* AKANTU_AKA_RANDOM_GENERATOR_HH_ */
c4science · Help