PhDP · October 10, 2023 03:46 · Apr 2, 2013 · Apr 2, 2013
diff --git a/main.cc b/main.cc
@@ -1,38 +1,48 @@
+// Compile with:
+// $ clang++ -O3 -std=C++11 main.cc -o main
+
 #include <iostream>
-#include <random>
-#include <ctime>
+#include <random> // The header for the generators.
+#include <ctime> // To seed the generator.
 
 using namespace std;
 
 int main() {
-  // Seed:
+  // Seed with time and print the seed:
   const unsigned int seed = time(0);
   cout << "Seed = " << seed << endl; // cout is a way to print in C++, endl ends the line.
-
+  
   // Generating random numbers with C++11's random requires an engine and a distribution.
-
-  // This is the engine based on the Mersenne Twister 19937 (64 bits):
-  mt19937 rng(seed);
-
-  // Creates a uniform distribution in the [0, 1) range (default):
-  uniform_real_distribution<> unif;
-
-  // To get a random number, you send the engine (rng) as argument to a distribution object:
-  for (int i = 0; i < 10; i++) {
+  // This is an engine based on the Mersenne Twister 19937 (64 bits):
+  mt19937_64 rng(seed);
+
+  // Then we create a distribution. We'll start with a uniform distribution in the
+  // default [0, 1) range:
+  uniform_real_distribution<double> unif;
+
+  cout << "\nUniform floats [0, 1): ";
+  for (int i = 0; i < 20; i++) { // Sample 20 numbers.
+    // To get a random number, send the engine (rng) as argument to the distribution object:
     cout << unif(rng) << ' ';
   }
   cout << endl;
 
-  // Creates a uniform integer distribution in the [6, 496) range:
-  uniform_int_distribution<int> unii(6, 496);
-  for (int i = 0; i < 10; i++) {
+  // Now we create another uniform distribution for integers in the [42, 512) range:
+  uniform_int_distribution<int> unii(42, 512);
+  cout << "\nUniform integers [42, 512): ";
+  for (int i = 0; i < 20; i++) {
+    // Again we send the generator as argument to the distribution to get numbers:
     cout << unii(rng) << ' ';
   }
   cout << endl;
-
-  // Normal distribution with mean 5 and std 2:
-  normal_distribution<double> norm(5, 2); 
-  for (int i = 0; i < 10; i++) {
+
+  // C++11 supports all kind of distributions (Normal, Binomial, Gamma, Weibull...).
+  // See this page for more info: en.cppreference.com/w/cpp/numeric/random
+
+  // A last example: normal distribution with mean 5 and std 2:
+  normal_distribution<double> norm(5, 2);
+  cout << "\nNormal with mean 5, std 2: ";
+  for (int i = 0; i < 20; i++) {
     cout << norm(rng) << ' ';
   }
   cout << endl;

diff --git a/main.cc b/main.cc
@@ -0,0 +1,41 @@
+#include <iostream>
+#include <random>
+#include <ctime>
+
+using namespace std;
+
+int main() {
+  // Seed:
+  const unsigned int seed = time(0);
+  cout << "Seed = " << seed << endl; // cout is a way to print in C++, endl ends the line.
+
+  // Generating random numbers with C++11's random requires an engine and a distribution.
+
+  // This is the engine based on the Mersenne Twister 19937 (64 bits):
+  mt19937 rng(seed);
+
+  // Creates a uniform distribution in the [0, 1) range (default):
+  uniform_real_distribution<> unif;
+
+  // To get a random number, you send the engine (rng) as argument to a distribution object:
+  for (int i = 0; i < 10; i++) {
+    cout << unif(rng) << ' ';
+  }
+  cout << endl;
+
+  // Creates a uniform integer distribution in the [6, 496) range:
+  uniform_int_distribution<int> unii(6, 496);
+  for (int i = 0; i < 10; i++) {
+    cout << unii(rng) << ' ';
+  }
+  cout << endl;
+
+  // Normal distribution with mean 5 and std 2:
+  normal_distribution<double> norm(5, 2); 
+  for (int i = 0; i < 10; i++) {
+    cout << norm(rng) << ' ';
+  }
+  cout << endl;
+
+  return 0;
+}
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