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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 08 2017
			*
			* @brief generic random generator
			*
			* @section LICENSE
			*
			* Copyright (©) 2014-2018 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 {
			/* ------------------------------------------------------------------------ */
			public:
			inline T operator()() { return generator(); }

			/// function to print the contain of the class
			virtual void printself(std::ostream & stream, int) 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 generator.min(); }
			static constexpr T max() { return generator.max(); }

			/* ------------------------------------------------------------------------ */
			private:
			static long int _seed;
			static std::default_random_engine generator;
			};

			// template <typename T>
			// long int RandomGenerator<T>::_seed = 0;

			/* -------------------------------------------------------------------------- */
			/* -------------------------------------------------------------------------- */
			/* -------------------------------------------------------------------------- */
			#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;
			virtual T operator()(RandomGenerator<UInt> & 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<UInt> & 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 = 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;
			}

			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<UInt> 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;
			}

			} // akantu

			#endif /* __AKANTU_AKA_RANDOM_GENERATOR_HH__ */

rAKA/src/common/aka_random_generator.hh74848b91ed80features/22-problem-in…

aka_random_generator.hhView Options

rAKA/src/common/aka_random_generator.hh
74848b91ed80features/22-problem-in…

aka_random_generator.hh
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