#ifndef SIMGRID_XBT_RANDOM_HPP
#define SIMGRID_XBT_RANDOM_HPP
+#include "xbt/base.h"
+#include <random>
+
namespace simgrid {
namespace xbt {
namespace random {
+/** A random number generator.
+ *
+ * It uses a std::mersenne_twister_engine (std::mt19937) and provides several distributions.
+ * This interface is implemented by StdRandom and XbtRandom.
+ */
+class XBT_PUBLIC Random {
+public:
+ std::mt19937 mt19937_gen; // the random number engine
+
+ /** @brief Build a new random number generator with default seed */
+ Random() = default;
+ /** @brief Build a new random number generator with given seed */
+ Random(int seed) : mt19937_gen(seed) {}
+
+ virtual ~Random() = default;
+
+ /**
+ * @brief Sets the seed of the Mersenne-Twister RNG
+ */
+ void set_seed(int seed) { mt19937_gen.seed(seed); }
+
+ /**
+ * @brief Draws an integer number uniformly in range [min, max] (min and max included)
+ *
+ * @param min Minimum value
+ * @param max Maximum value
+ */
+ virtual int uniform_int(int min, int max) = 0;
+
+ /**
+ * @brief Draws a real number uniformly in range [min, max) (min included, and max excluded)
+ *
+ * @param min Minimum value
+ * @param max Maximum value
+ */
+ virtual double uniform_real(double min, double max) = 0;
+
+ /**
+ * @brief Draws a real number according to the given exponential distribution
+ *
+ * @param lambda Parameter of the exponential law
+ */
+ virtual double exponential(double lambda) = 0;
+
+ /**
+ * @brief Draws a real number according to the given normal distribution
+ *
+ * @param mean Mean of the normal distribution
+ * @param sd Standard deviation of the normal distribution
+ */
+ virtual double normal(double mean, double sd) = 0;
+};
+
+/** A random number generator using the C++ standard library.
+ *
+ * Caution: reproducibility is not guaranteed across different implementations.
+ */
+class XBT_PUBLIC StdRandom : public Random {
+public:
+ StdRandom() = default;
+ StdRandom(int seed) : Random(seed) {}
+
+ int uniform_int(int min, int max) override;
+ double uniform_real(double min, double max) override;
+ double exponential(double lambda) override;
+ double normal(double mean, double sd) override;
+};
+
+/** A reproducible random number generator.
+ *
+ * Uses our own implementation of distributions to ensure reproducibility.
+ */
+class XBT_PUBLIC XbtRandom : public Random {
+public:
+ XbtRandom() = default;
+ XbtRandom(int seed) : Random(seed) {}
+
+ int uniform_int(int min, int max) override;
+ double uniform_real(double min, double max) override;
+ double exponential(double lambda) override;
+ double normal(double mean, double sd) override;
+};
+
/**
* @brief Tells xbt/random to use the ad-hoc distribution implementation.
*/
#include "xbt/random.hpp"
#include "xbt/asserts.h"
#include <limits>
-#include <random>
+#include <memory>
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;
-
-void set_implem_xbt()
+int StdRandom::uniform_int(int min, int max)
{
- rng_implem = XBT_RNG_xbt;
+ std::uniform_int_distribution<> dist(min, max);
+ return dist(mt19937_gen);
}
-void set_implem_std()
+
+double StdRandom::uniform_real(double min, double max)
{
- rng_implem = XBT_RNG_std;
+ std::uniform_real_distribution<> dist(min, max);
+ return dist(mt19937_gen);
}
-void set_mersenne_seed(int seed)
+
+double StdRandom::exponential(double lambda)
{
- mt19937_gen.seed(seed);
+ std::exponential_distribution<> dist(lambda);
+ return dist(mt19937_gen);
}
-int uniform_int(int min, int max)
+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;
xbt_assert(min <= max,
"The minimum value for the uniform integer distribution must not be greater than the maximum value");
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
constexpr unsigned long divisor = decltype(mt19937_gen)::max() - decltype(mt19937_gen)::min();
unsigned long numerator;
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));
}
-double normal(double mean, double sd)
+double XbtRandom::normal(double mean, double sd)
{
- if (rng_implem == XBT_RNG_std) {
- std::normal_distribution<> dist(mean, sd);
- return dist(mt19937_gen);
- }
-
double u1;
do {
u1 = uniform_real(0.0, 1.0);
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);
+}
+
+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)
+{
+ return default_random->normal(mean, sd);
+}
+
} // namespace random
} // namespace xbt
} // namespace simgrid
