Nejaušu skaitļu ģenerēšana ir izplatīta prasība daudzās programmēšanas lietojumprogrammās, un C++ nodrošina vairākus veidus, kā ģenerēt nejaušus skaitļus noteiktā diapazonā. Šajā rakstā mēs izpētīsim dažādas metodes, kā ģenerēt nejaušus skaitļus no 1 līdz 10 valodā C++.
1. metode:
Izmantojot funkciju rand():
Viena no vienkāršākajām metodēm nejauša skaitļa ģenerēšanai no 1 līdz 10 C++ valodā ir rands () funkciju. Šī funkcija ir definēta galvenes failu un ģenerē nejaušu veselu skaitli diapazonā no 0 uz RAND_MAX . Vērtība RAND_MAX ir atkarīgs no ieviešanas un var atšķirties atkarībā no kompilatora.
Piemērs:
Ņemsim piemēru, lai ģenerētu nejaušu skaitli no 1 līdz 10, izmantojot funkciju rand(), mēs varam izmantot šādu kodu:
#include #include #include using namespace std; int main() { srand(time(0)); cout<< 'Random number between 1 and 10 is: '<<endl; for(int i="0;i<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'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<< 'Random number between 1 and 10 is: ' <<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'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<< 'Random number between 1 and 10 is: ' <<endl; for(int i="0;i<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;> Šajā kodā mēs esam iekļāvuši un galvenes faili. The srand () funkcija tiek izmantota, lai inicializētu nejaušo skaitļu ģeneratoru ar pašreizējo laiku kā sākumu. Tas nodrošina, ka katru reizi, kad programma tiek palaista, tiek ģenerēta jauna nejaušu skaitļu secība.
The rands () funkcija tiek izmantota, lai ģenerētu nejaušu veselu skaitli no 0 līdz RAND_MAX . Lai ierobežotu diapazonu no 1 līdz 10, mēs ņemam šī skaitļa atlikušo daļu, dalot ar 10, un pievienojam tam 1.
2. metode:
Izmantojot C++11 izlases bibliotēku
The C++11 standarts ieviesa jaunu bibliotēku ar nosaukumu kas nodrošina labāku veidu, kā ģenerēt nejaušus skaitļus. Šī bibliotēka nodrošina vairākus nejaušu skaitļu ģenerēšanas dzinējus un sadalījumus, kas var ģenerēt nejaušus skaitļus ar vienmērīgu sadalījumu.
Piemērs:
Ņemsim piemēru, lai ģenerētu nejaušu skaitli no 1 līdz 10, izmantojot bibliotēkā, mēs varam izmantot šādu kodu:
#include #include using namespace std; int main() { random_device rand; mt19937 gen(rand()); uniform_int_distributiondis(1, 10); int random_number = dis(gen); cout<< 'Random number between 1 and 10 is: ' <<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'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<< 'Random number between 1 and 10 is: ' <<endl; for(int i="0;i<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;> Šajā kodā mēs esam izmantojuši laiks() funkcija, lai iegūtu pašreizējo laiku kā sākuma vērtību srand () funkciju. The srand () funkcija tiek izmantota, lai inicializētu nejaušo skaitļu ģeneratoru. The rands () funkcija ģenerē nejaušu veselu skaitli no 0 līdz RAND_MAX , kas pēc tam tiek ierobežots līdz diapazonam no 1 līdz 10, izmantojot operatora modulis un pievienojot tai 1.
Secinājums:
Visbeidzot, ir vairākas metodes, kā ģenerēt nejaušus skaitļus no 1 līdz 10 C++ valodā. Metodes izvēle ir atkarīga no pieteikuma prasībām, piemēram, ātrums, nejaušība , un viendabīgums no ģenerētajiem skaitļiem. Kamēr rand () funkcija ir visvienkāršākā un visvieglāk īstenojama, tā var nenodrošināt labu nejaušību un viendabīgumu. The bibliotēka nodrošina labāku veidu, kā ģenerēt nejaušus skaitļus ar vienmērīgu sadalījumu, taču tā ieviešana ir lēnāka un sarežģītāka. The XORShift algoritms nodrošina labu nejaušība un viendabīgums , taču to ir sarežģītāk ieviest, un tas var nebūt tik ātrs kā rand () funkciju.