-/* Copyright (c) 2019. The SimGrid Team. All rights reserved. */
+/* Copyright (c) 2019-2020. The SimGrid Team. All rights reserved. */
/* This program is free software; you can redistribute it and/or modify it
* under the terms of the license (GNU LGPL) which comes with this package. */
-#include "xbt/random.hpp"
#include "xbt/asserts.h"
+#include <fstream>
+#include <iostream>
#include <limits>
-#include <random>
+#include <memory>
+#include <string>
+#include <xbt/log.hpp>
+#include <xbt/random.hpp>
+
+XBT_LOG_EXTERNAL_CATEGORY(xbt);
+XBT_LOG_NEW_DEFAULT_SUBCATEGORY(xbt_random, xbt, "Random");
namespace simgrid {
namespace xbt {
namespace random {
-enum xbt_random_implem { XBT_RNG_xbt, XBT_RNG_std };
-static xbt_random_implem rng_implem = XBT_RNG_xbt;
-static std::mt19937 mt19937_gen;
+bool Random::read_state(const std::string& filename)
+{
+ std::ifstream file(filename);
+ file >> mt19937_gen;
+ file.close();
+ if (file.fail())
+ XBT_WARN("Could not save the RNG state to file %s.", filename.c_str());
+ return not file.fail();
+}
-void set_implem_xbt()
+bool Random::write_state(const std::string& filename) const
{
- rng_implem = XBT_RNG_xbt;
+ std::ofstream file(filename);
+ file << mt19937_gen;
+ file.close();
+ if (file.fail())
+ XBT_WARN("Could not read the RNG state from file %s.", filename.c_str());
+ return not file.fail();
}
-void set_implem_std()
+
+int StdRandom::uniform_int(int min, int max)
{
- rng_implem = XBT_RNG_std;
+ std::uniform_int_distribution<> dist(min, max);
+ return dist(mt19937_gen);
}
-void set_mersenne_seed(int seed)
+
+double StdRandom::uniform_real(double min, double max)
{
- mt19937_gen.seed(seed);
+ std::uniform_real_distribution<> dist(min, max);
+ return dist(mt19937_gen);
}
-int uniform_int(int min, int max)
+double StdRandom::exponential(double lambda)
+{
+ std::exponential_distribution<> dist(lambda);
+ return dist(mt19937_gen);
+}
+
+double StdRandom::normal(double mean, double sd)
{
- if (rng_implem == XBT_RNG_std) {
- std::uniform_int_distribution<> dist(min, max);
- return dist(mt19937_gen);
- }
+ std::normal_distribution<> dist(mean, sd);
+ return dist(mt19937_gen);
+}
+int XbtRandom::uniform_int(int min, int max)
+{
unsigned long range = max - min + 1;
- unsigned long value = mt19937_gen();
+ xbt_assert(min <= max,
+ "The minimum value for the uniform integer distribution must not be greater than the maximum value");
xbt_assert(range > 0, "Overflow in the uniform integer distribution, please use a smaller range.");
- xbt_assert(
- min <= max,
- "The maximum value for the uniform integer distribution must be greater than or equal to the minimum value");
+ unsigned long value;
+ do {
+ value = mt19937_gen();
+ } while (value >= decltype(mt19937_gen)::max() - decltype(mt19937_gen)::max() % range);
return value % range + min;
}
-double uniform_real(double min, double max)
+double XbtRandom::uniform_real(double min, double max)
{
- if (rng_implem == XBT_RNG_std) {
- std::uniform_real_distribution<> dist(min, max);
- return dist(mt19937_gen);
- }
-
// This reuses Boost's uniform real distribution ideas
- unsigned long numerator = mt19937_gen() - mt19937_gen.min();
- unsigned long divisor = mt19937_gen.max() - mt19937_gen.min();
+ constexpr unsigned long divisor = decltype(mt19937_gen)::max() - decltype(mt19937_gen)::min();
+ unsigned long numerator;
+ do {
+ numerator = mt19937_gen() - decltype(mt19937_gen)::min();
+ } while (numerator == divisor);
return min + (max - min) * numerator / divisor;
}
-double exponential(double lambda)
+double XbtRandom::exponential(double lambda)
{
- if (rng_implem == XBT_RNG_std) {
- std::exponential_distribution<> dist(lambda);
- return dist(mt19937_gen);
- }
+ return -1.0 / lambda * log(uniform_real(0.0, 1.0));
+}
- return -1 / lambda * log(uniform_real(0, 1));
+double XbtRandom::normal(double mean, double sd)
+{
+ double u1;
+ do {
+ u1 = uniform_real(0.0, 1.0);
+ } while (u1 < std::numeric_limits<double>::min());
+ double u2 = uniform_real(0.0, 1.0);
+ double z0 = sqrt(-2.0 * log(u1)) * cos(2.0 * M_PI * u2);
+ return z0 * sd + mean;
+}
+
+static std::unique_ptr<Random> default_random(new XbtRandom);
+
+void set_implem_xbt()
+{
+ default_random.reset(new XbtRandom);
+}
+void set_implem_std()
+{
+ default_random.reset(new StdRandom);
+}
+
+void set_mersenne_seed(int seed)
+{
+ default_random->set_seed(seed);
+}
+
+bool read_mersenne_state(const std::string& filename)
+{
+ return default_random->read_state(filename);
+}
+
+bool write_mersenne_state(const std::string& filename)
+{
+ return default_random->write_state(filename);
+}
+
+int uniform_int(int min, int max)
+{
+ return default_random->uniform_int(min, max);
+}
+
+double uniform_real(double min, double max)
+{
+ return default_random->uniform_real(min, max);
+}
+
+double exponential(double lambda)
+{
+ return default_random->exponential(lambda);
}
double normal(double mean, double sd)
{
- if (rng_implem == XBT_RNG_std) {
- std::normal_distribution<> dist(mean, sd);
- return dist(mt19937_gen);
- }
-
- double u1 = 0;
- while (u1 < std::numeric_limits<double>::min()) {
- u1 = uniform_real(0, 1);
- }
- double u2 = uniform_real(0, 1);
- double z0 = sqrt(-2.0 * log(u1)) * cos(2 * M_PI * u2);
- return z0 * sd + mean;
+ return default_random->normal(mean, sd);
}
} // namespace random