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    std::seed_seq::generate

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    <metanoindex/>

     
    C++
     
    Bibliothèque Numerics
    Fonctions mathématiques courantes
    Virgule flottante environnement
    Nombres complexes
    Tableaux numériques
    La génération de nombres pseudo-aléatoires
    Moment de la compilation arithmétique rationnelle (C++11)
    Génériques des opérations numériques
    Original:
    Generic numeric operations
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    iota (C++11)
    accumulate
    inner_product
    adjacent_difference
    partial_sum
     
    La génération de nombres pseudo-aléatoires
    Les moteurs et les adaptateurs de moteur
    Original:
    Engines and engine adaptors
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    linear_congruential_engine (C++11)
    mersenne_twister_engine (C++11)
    subtract_with_carry_engine (C++11)
    discard_block_engine (C++11)
    independent_bits_engine (C++11)
    shuffle_order_engine (C++11)
    Générateurs
    Original:
    Generators
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    random_device (C++11)
    Les distributions
    Original:
    Distributions
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    Distributions uniformes
    Original:
    Uniform distributions
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    uniform_int_distribution (C++11)
    uniform_real_distribution (C++11)
    generate_canonical (C++11)
    Distributions de Bernoulli
    Original:
    Bernoulli distributions
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    bernoulli_distribution (C++11)
    binomial_distribution (C++11)
    negative_binomial_distribution (C++11)
    geometric_distribution (C++11)
    Distributions de Poisson
    Original:
    Poisson distributions
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    poisson_distribution (C++11)
    exponential_distribution (C++11)
    gamma_distribution (C++11)
    weibull_distribution (C++11)
    extreme_value_distribution (C++11)
    Les distributions normales
    Original:
    Normal distributions
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    normal_distribution (C++11)
    lognormal_distribution (C++11)
    chi_squared_distribution (C++11)
    cauchy_distribution (C++11)
    fisher_f_distribution (C++11)
    student_t_distribution (C++11)
    Distributions d'échantillonnage
    Original:
    Sampling distributions
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    discrete_distribution (C++11)
    piecewise_constant_distribution (C++11)
    piecewise_linear_distribution (C++11)
    Séquences de semences
    Original:
    Seed Sequences
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    seed_seq (C++11)
    Bibliothèque C
    Original:
    C library
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    rand
    srand
    RAND_MAX
     
    std::seed_seq
    Les fonctions membres
    Original:
    Member functions
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    seed_seq::seed_seq
    seed_seq::generate
    seed_seq::size
    seed_seq::param
     
    <tbody> </tbody>
    template< class RandomIt > void generate( RandomIt begin, RandomIt end );
    		 (depuis C++11)
    Remplit le [begin, end) gamme avec des entiers non signés i, 0 ≤ i < 232
    , sur la base des données fournies à l'origine dans le constructeur de cette seed_seq. Les valeurs produites sont réparties sur toute la plage de 32-bit, même si les valeurs initiales ont été fortement sollicitée .
    Original:
    Fills the range [begin, end) with unsigned integer values i, 0 ≤ i < 232
    , based on the data originally provided in the constructor of this seed_seq. The produced values are distributed over the entire 32-bit range even if the initial values were strongly biased.
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    L'algorithme suivant est utilisé (adapté à partir de la séquence d'initialisation du générateur Mersenne Twister par Makoto Matsumoto and Takuji Nishimura, intégrant les améliorations apportées par Mutsuo Saito in 2007)
    Original:
    The following algorithm is used (adapted from the initialization sequence of the Mersenne Twister generator by Makoto Matsumoto and Takuji Nishimura, incorporating the improvements made by Mutsuo Saito in 2007)
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    • Si begin == end, ne rien faire. Dans le cas contraire,
      Original:
      If begin == end, do nothing. Otherwise,
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    • Tout d'abord, définir chaque élément de la plage de sortie de la valeur 0x8b8b8b8b
      Original:
      First, set each element of the output range to the value 0x8b8b8b8b
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    • Transformer les éléments de la gamme de puissance selon l'algorithme suivant:
      Original:
      Transform the elements of the output range according to the following algorithm:
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    For k = 0,..., m-1

    où m=max(s+1, n)
    Original:
    where m=max(s+1, n)
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    and n=begin-end
    and s=v.size()

    et v est le conteneur privé qui détient les valeurs fournies à l'origine par le constructeur de cet objet seed_seq,
    Original:
    and v is the private container holding the values originally provided by the constructor of this seed_seq object,
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    1. begin[k+p] += r1
    2. begin[k+q] += r2
    3. begin[k] = r2,
    où p=(n-t)/2
    Original:
    where p=(n-t)/2
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    and q=p+t
    and t=(n >= 623) ? 11 : (n >= 68) ? 7 : (n >= 39) ? 5 : (n >= 7) ? 3 : (n - 1) / 2
    and r1=1664525 * T(begin[k]^begin[k+p]^begin[k−1])
    and T(x) = x ^ (x << 27)
    and r2=r1+s if k==0, r2=r1 + k%n + v[k-1] if 0<k<=s, r2=r1 + k%n if k>s.

    For k = m,..., m+n-1,

    1. begin[k+p] ^= r3
    2. begin[k+q] ^= r4
    3. begin[k]=r4
    où r3 = 1566083941 * T(begin[k]+begin[k+p]+begin[k-1])
    Original:
    where r3 = 1566083941 * T(begin[k]+begin[k+p]+begin[k-1])
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    and r4=r3 - k%n

    où tous les calculs sont effectués modulo 232
     et où l'indexage de la plage de sortie (begin[x]) est prise modulo n .
    Original:
    where all calculations are performed modulo 232
     and where the indexing of the output range (begin[x]) is taken modulo n.
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    Paramètres

    begin, end -
    mutables itérateurs d'accès aléatoire dont std::iterator_traits<>::value_type est un entier non signé pour le stockage des valeurs 32 bits
    Original:
    mutable random-access iterators whose std::iterator_traits<>::value_type is an unsigned integer type suitable for storing 32-bit values
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    Type requirements
    -
    RandomIt must meet the requirements of RandomAccessIterator.

    Retourne la valeur

    aucun, les résultats sont écrits dans la gamme [begin, end) .
    Original:
    none, the results are written to the [begin, end) range.
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    Exemple

    #include <random>
#include <iostream>

int main()
{
    std::seed_seq seq({1,2,3,4,5});
    std::vector<std::uint32_t> seeds(10);
    seq.generate(seeds.begin(), seeds.end());
// Step 1: fill with 0x8b8b8b8b
// seeds = {2341178251, 2341178251, 2341178251, 2341178251, 2341178251,
//          2341178251, 2341178251, 2341178251, 2341178251, 2341178251 }
//
// Step 2: 
// n = 10, s = 5, t = 3, p = 3, q = 6, m = 10
//
// First iteration, k = 0; r1 = 1371501266, r2 = 1371501271
//
// seeds = {1371501271, 2341178251, 2341178251, 3712679517, 2341178251,
//          2341178251, 3712679522, 2341178251, 2341178251, 2341178251 }
//
// Iterations from k = 1 to k = 5 (r2 = r1 + k%n + v[k-1])
//
// r1 = 2786190137, 3204727651, 4173325571, 1979226628, 401983366
// r2 = 2786190139, 3204727655, 4173325577, 1979226636, 401983376
//
// seeds = {3350727907, 3188173515, 3204727655, 4173325577, 1979226636,
//           401983376, 3591037797, 2811627722, 1652921976, 2219536532 } 
//
// Iterations from k = 6 to k = 9 (r2 = r1 + k%n)
//
// r1 = 2718637909, 1378394210, 2297813071, 1608643617
// r2 = 2718637915, 1378394217, 2297813079, 1608643626
//
// seeds = { 434154821, 1191019290, 3237041891, 1256752498, 4277039715,
//          2010627002, 2718637915, 1378394217, 2297813079, 1608643626 } 
//
// Step 3
// iterations from k = 10 to k = 19, using ^= to modify the output
//
// r1 = 1615303485, 3210438310, 893477041, 2884072672, 1918321961,
// r2 = 1615303485, 3210438309, 893477039, 2884072669, 1918321957
//
// seeds = { 303093272, 3210438309,  893477039, 2884072669, 1918321957,
//          1117182731, 1772877958, 2669970405, 3182737656, 4094066935 }
//
// r1 =  423054846, 46783064, 3904109085, 1534123446, 1495905687
// r2 =  423054841, 46783058, 3904109078, 1534123438, 1495905678
//
// seeds = { 4204997637, 4246533866, 1856049002, 1129615051, 690460811,
//           1075771511,   46783058, 3904109078, 1534123438, 1495905678 }

    for(std::uint32_t n : seeds)
        std::cout << n << '\n';
}

    Résultat : 

    4204997637
4246533866
1856049002
1129615051
690460811
1075771511
46783058
3904109078
1534123438
1495905678