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Comment générer un nombre aléatoire entre 1 et 10 en C++

La génération de nombres aléatoires est une exigence courante dans de nombreuses applications de programmation, et C++ propose plusieurs façons de générer des nombres aléatoires dans une plage donnée. Dans cet article, nous explorerons différentes méthodes pour générer des nombres aléatoires entre 1 et 10 en C++.

Méthode 1 :

Utilisation de la fonction rand() :

L'une des méthodes les plus simples pour générer un nombre aléatoire entre 1 et 10 en C++ est la rand() fonction. Cette fonction est définie dans le fichier d'en-tête et génère un nombre entier aléatoire dans une plage de 0 à RAND_MAX . La valeur de RAND_MAX dépend de l'implémentation et peut varier d'un compilateur à l'autre.

Exemple:

Prenons un exemple pour générer un nombre aléatoire entre 1 et 10 en utilisant la fonction rand(), nous pouvons utiliser le code suivant :

 #include #include #include using namespace std; int main() { srand(time(0)); cout&lt;&lt; &apos;Random number between 1 and 10 is: &apos;&lt;<endl; for(int i="0;i&lt;10;i++)" cout << (rand() % 10) + 1<<' '; return 0; } < pre> <p> <strong>Output</strong> </p> <pre> Random number between 1 and 10 is: 4 5 7 10 7 5 1 7 10 2 </pre> <p>In this code, we have included the <strong> <em></em> </strong> and <strong> <em></em> </strong> header files. The <strong> <em>srand()</em> </strong> function is used to initialize the random number generator with the current time as the seed. It ensures that every time the program is run, a new sequence of random numbers is generated.</p> <p>The <strong> <em>rand()</em> </strong> function is used to generate a random integer between 0 and <strong> <em>RAND_MAX</em> </strong> . To limit the range between 1 and 10, we take the remainder of this number when divided by 10 and add 1 to it.</p> <h3>Method 2:</h3> <p> <strong>Using C++11 random library</strong> </p> <p>The <strong> <em>C++11</em> </strong> standard introduced a new library called <strong> <em></em> </strong> that provides a better way to generate random numbers. This library provides several random number generation engines and distributions that can generate random numbers with a uniform distribution.</p> <p> <strong>Example:</strong> </p> <p>Let&apos;s take an example to generate a random number between 1 and 10 using the <strong> <em></em> </strong> library, we can use the following code:</p> <pre> #include #include using namespace std; int main() { random_device rand; mt19937 gen(rand()); uniform_int_distributiondis(1, 10); int random_number = dis(gen); cout&lt;&lt; &apos;Random number between 1 and 10 is: &apos; &lt;<random_number<<endl; return 0; } < pre> <p>In this code, we have included the <strong> <em></em> </strong> header file. The <strong> <em>random_device</em> </strong> class is used to obtain a seed value for the random number generator. The <strong> <em>mt19937</em> </strong> class is a random number generation engine that produces random numbers with a uniform distribution. The <strong> <em>uniform_int_distribution</em> </strong> class is used to generate random integers within a given range.</p> <p>By default, the <strong> <em>mt19937</em> </strong> engine uses a seed value of <strong> <em>5489</em> </strong> , which can be changed using the <strong> <em>seed()</em> </strong> method. However, it is recommended to use a <strong> <em>random_device</em> </strong> to obtain a seed value for better randomness.</p> <p>The <strong> <em>uniform_int_distribution</em> </strong> class generates random integers with a uniform distribution within a given range. In this code, we have specified the range as <strong> <em>1</em> </strong> to <strong> <em>10</em> </strong> using the constructor.</p> <p>This method provides better randomness and a uniform distribution of generated numbers compared to the <strong> <em>rand()</em> </strong> function. However, it is slower and more complex to implement.</p> <h3>Method 3:</h3> <p> <strong>Using modulo operator with time():</strong> </p> <p>Another method to generate a random number between 1 and 10 is the <strong> <em>modulo operator</em> </strong> with the current time as a seed value. This method is similar to the first method using <strong> <em>rand()</em> </strong> function, but it uses a more random seed value and provides better randomness.</p> <p> <strong>Example:</strong> </p> <p>Let&apos;s take an example to generate a random number between 1 and 10 using the modulo operator with <strong> <em>time()</em> </strong> , we can use the following code:</p> <pre> #include #include using namespace std; int main() { srand(time(0)); cout&lt;&lt; &apos;Random number between 1 and 10 is: &apos; &lt;<endl; for(int i="0;i&lt;10;i++)" cout << (rand() % 10) + 1<<' '; return 0; } < pre> <p> <strong>Output</strong> </p> <pre> Random number between 1 and 10 is: 6 6 3 6 10 10 1 7 6 4 </pre> <p>In this code, we have used the <strong> <em>time()</em> </strong> function to obtain the current time as a seed value for the <strong> <em>srand()</em> </strong> function. The <strong> <em>srand()</em> </strong> function is used to initialize the random number generator. The <strong> <em>rand()</em> </strong> function generates a random integer between 0 and <strong> <em>RAND_MAX</em> </strong> , which is then limited to a range between 1 and 10 using the <strong> <em>modulo operator</em> </strong> and adding 1 to it.</p> <h2>Conclusion:</h2> <p>In conclusion, there are several methods to generate random numbers between 1 and 10 in C++. The choice of method depends on the requirements of the application, such as <strong> <em>speed, randomness</em> </strong> , and <strong> <em>uniformity</em> </strong> of generated numbers. While the <strong> <em>rand()</em> </strong> function is the simplest and easiest to implement, it may not provide good randomness and uniformity. The <strong> <em></em> </strong> library provides a better way to generate random numbers with a uniform distribution, but it is slower and more complex to implement. The <strong> <em>XORShift</em> </strong> algorithm provides good <strong> <em>randomness</em> </strong> and <strong> <em>uniformity</em> </strong> , but it is more complex to implement and may not be as fast as the <strong> <em>rand()</em> </strong> function.</p> <hr></endl;></pre></random_number<<endl;></pre></endl;>

Dans ce code, nous avons inclus le et fichiers d'en-tête. Le srand() La fonction est utilisée pour initialiser le générateur de nombres aléatoires avec l’heure actuelle comme graine. Cela garantit que chaque fois que le programme est exécuté, une nouvelle séquence de nombres aléatoires est générée.

Le rand() La fonction est utilisée pour générer un entier aléatoire compris entre 0 et RAND_MAX . Pour limiter la plage entre 1 et 10, nous prenons le reste de ce nombre divisé par 10 et y ajoutons 1.

Méthode 2 :

Utilisation de la bibliothèque aléatoire C++11

Le C++11 standard a introduit une nouvelle bibliothèque appelée cela offre une meilleure façon de générer des nombres aléatoires. Cette bibliothèque fournit plusieurs moteurs et distributions de génération de nombres aléatoires qui peuvent générer des nombres aléatoires avec une distribution uniforme.

Exemple:

Prenons un exemple pour générer un nombre aléatoire entre 1 et 10 en utilisant le bibliothèque, nous pouvons utiliser le code suivant :

 #include #include using namespace std; int main() { random_device rand; mt19937 gen(rand()); uniform_int_distributiondis(1, 10); int random_number = dis(gen); cout&lt;&lt; &apos;Random number between 1 and 10 is: &apos; &lt;<random_number<<endl; return 0; } < pre> <p>In this code, we have included the <strong> <em></em> </strong> header file. The <strong> <em>random_device</em> </strong> class is used to obtain a seed value for the random number generator. The <strong> <em>mt19937</em> </strong> class is a random number generation engine that produces random numbers with a uniform distribution. The <strong> <em>uniform_int_distribution</em> </strong> class is used to generate random integers within a given range.</p> <p>By default, the <strong> <em>mt19937</em> </strong> engine uses a seed value of <strong> <em>5489</em> </strong> , which can be changed using the <strong> <em>seed()</em> </strong> method. However, it is recommended to use a <strong> <em>random_device</em> </strong> to obtain a seed value for better randomness.</p> <p>The <strong> <em>uniform_int_distribution</em> </strong> class generates random integers with a uniform distribution within a given range. In this code, we have specified the range as <strong> <em>1</em> </strong> to <strong> <em>10</em> </strong> using the constructor.</p> <p>This method provides better randomness and a uniform distribution of generated numbers compared to the <strong> <em>rand()</em> </strong> function. However, it is slower and more complex to implement.</p> <h3>Method 3:</h3> <p> <strong>Using modulo operator with time():</strong> </p> <p>Another method to generate a random number between 1 and 10 is the <strong> <em>modulo operator</em> </strong> with the current time as a seed value. This method is similar to the first method using <strong> <em>rand()</em> </strong> function, but it uses a more random seed value and provides better randomness.</p> <p> <strong>Example:</strong> </p> <p>Let&apos;s take an example to generate a random number between 1 and 10 using the modulo operator with <strong> <em>time()</em> </strong> , we can use the following code:</p> <pre> #include #include using namespace std; int main() { srand(time(0)); cout&lt;&lt; &apos;Random number between 1 and 10 is: &apos; &lt;<endl; for(int i="0;i&lt;10;i++)" cout << (rand() % 10) + 1<<\' \'; return 0; } < pre> <p> <strong>Output</strong> </p> <pre> Random number between 1 and 10 is: 6 6 3 6 10 10 1 7 6 4 </pre> <p>In this code, we have used the <strong> <em>time()</em> </strong> function to obtain the current time as a seed value for the <strong> <em>srand()</em> </strong> function. The <strong> <em>srand()</em> </strong> function is used to initialize the random number generator. The <strong> <em>rand()</em> </strong> function generates a random integer between 0 and <strong> <em>RAND_MAX</em> </strong> , which is then limited to a range between 1 and 10 using the <strong> <em>modulo operator</em> </strong> and adding 1 to it.</p> <h2>Conclusion:</h2> <p>In conclusion, there are several methods to generate random numbers between 1 and 10 in C++. The choice of method depends on the requirements of the application, such as <strong> <em>speed, randomness</em> </strong> , and <strong> <em>uniformity</em> </strong> of generated numbers. While the <strong> <em>rand()</em> </strong> function is the simplest and easiest to implement, it may not provide good randomness and uniformity. The <strong> <em></em> </strong> library provides a better way to generate random numbers with a uniform distribution, but it is slower and more complex to implement. The <strong> <em>XORShift</em> </strong> algorithm provides good <strong> <em>randomness</em> </strong> and <strong> <em>uniformity</em> </strong> , but it is more complex to implement and may not be as fast as the <strong> <em>rand()</em> </strong> function.</p> <hr></endl;></pre></random_number<<endl;>

Dans ce code, nous avons utilisé le temps() fonction pour obtenir l'heure actuelle comme valeur de départ pour le srand() fonction. Le srand() La fonction est utilisée pour initialiser le générateur de nombres aléatoires. Le rand() la fonction génère un entier aléatoire compris entre 0 et RAND_MAX , qui est ensuite limité à une plage comprise entre 1 et 10 à l'aide de la module opérateur et en y ajoutant 1.

Conclusion:

En conclusion, il existe plusieurs méthodes pour générer des nombres aléatoires entre 1 et 10 en C++. Le choix de la méthode dépend des exigences de l'application, telles que vitesse, hasard , et uniformité de nombres générés. Tandis que le rand() Si la fonction est la plus simple et la plus facile à mettre en œuvre, elle peut ne pas offrir un bon caractère aléatoire et uniforme. Le La bibliothèque offre un meilleur moyen de générer des nombres aléatoires avec une distribution uniforme, mais elle est plus lente et plus complexe à mettre en œuvre. Le XORShift l'algorithme fournit de bons le hasard et uniformité , mais il est plus complexe à mettre en œuvre et n'est peut-être pas aussi rapide que le rand() fonction.