X-Git-Url: http://bilbo.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/9104957deccc59e0e804215d5db498fabfd40d29..0ffe6c466e437ebbda9be47bbd77d3775623a2d7:/src/xbt/random.cpp

diff --git a/src/xbt/random.cpp b/src/xbt/random.cpp
index 79bc21b343..088545eb5f 100644
--- a/src/xbt/random.cpp
+++ b/src/xbt/random.cpp
@@ -1,90 +1,158 @@
-/* Copyright (c) 2019-2020. The SimGrid Team. All rights reserved.               */
+/* Copyright (c) 2019-2021. 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();
+}
+
+bool Random::write_state(const std::string& filename) const
+{
+  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();
+}
+
+int StdRandom::uniform_int(int min, int max)
+{
+  std::uniform_int_distribution<> dist(min, max);
+  return dist(mt19937_gen);
+}
+
+double StdRandom::uniform_real(double min, double max)
+{
+  std::uniform_real_distribution<> dist(min, max);
+  return dist(mt19937_gen);
+}
+
+double StdRandom::exponential(double lambda)
+{
+  std::exponential_distribution<> dist(lambda);
+  return dist(mt19937_gen);
+}
+
+double StdRandom::normal(double mean, double sd)
+{
+  std::normal_distribution<> dist(mean, sd);
+  return dist(mt19937_gen);
+}
+
+int XbtRandom::uniform_int(int min, int max)
+{
+  unsigned long range = static_cast<unsigned>(max) - static_cast<unsigned>(min);
+  xbt_assert(min <= max,
+             "The minimum value for the uniform integer distribution must not be greater than the maximum value");
+  xbt_assert(range <= decltype(mt19937_gen)::max(),
+             "Overflow in the uniform integer distribution, please use a smaller range.");
+  if (range == decltype(mt19937_gen)::max())
+    return static_cast<int>(mt19937_gen() + min);
+
+  ++range;
+  unsigned long limit = decltype(mt19937_gen)::max() - decltype(mt19937_gen)::max() % range;
+  unsigned long value;
+  do {
+    value = mt19937_gen();
+  } while (value >= limit);
+  return static_cast<int>(value % range + min);
+}
+
+double XbtRandom::uniform_real(double min, double max)
+{
+  // This reuses Boost's uniform real distribution ideas
+  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) * static_cast<double>(numerator) / divisor;
+}
+
+double XbtRandom::exponential(double lambda)
+{
+  return -1.0 / lambda * log(uniform_real(0.0, 1.0));
+}
+
+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 = std::make_unique<XbtRandom>();
 
 void set_implem_xbt()
 {
-  rng_implem = XBT_RNG_xbt;
+  default_random = std::make_unique<XbtRandom>();
 }
 void set_implem_std()
 {
-  rng_implem = XBT_RNG_std;
+  default_random = std::make_unique<StdRandom>();
 }
+
 void set_mersenne_seed(int seed)
 {
-  mt19937_gen.seed(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)
 {
-  if (rng_implem == XBT_RNG_std) {
-    std::uniform_int_distribution<> dist(min, max);
-    return dist(mt19937_gen);
-    }
-
-  unsigned long range  = max - min + 1;
-  unsigned long value  = mt19937_gen();
-  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");
-  while (value >= mt19937_gen.max() - mt19937_gen.max() % range) {
-    value = mt19937_gen();
-  }
-  return value % range + min;
+  return default_random->uniform_int(min, max);
 }
 
 double 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();
-  return min + (max - min) * numerator / divisor;
+  return default_random->uniform_real(min, max);
 }
 
 double exponential(double lambda)
 {
-  if (rng_implem == XBT_RNG_std) {
-    std::exponential_distribution<> dist(lambda);
-    return dist(mt19937_gen);
-    }
-
-  return -1 / lambda * log(uniform_real(0, 1));
+  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