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std::discrete_distribution::discrete_distribution

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Numéricos biblioteca
Funciones matemáticas comunes
Floating-point medio ambiente
Los números complejos
Matrices numéricas
Pseudo-aleatoria de generación de números
En tiempo de compilación aritmética racional (C++11)
Genéricos operaciones numéricas
Original:
Generic numeric operations
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iota(C++11)
accumulate
inner_product
adjacent_difference
partial_sum
 
Pseudo-aleatoria de generación de números
Motores y adaptadores de motor
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)
Generadores
Original:
Generators
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random_device(C++11)
Distribuciones
Original:
Distributions
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Distribuciones uniformes
Original:
Uniform distributions
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uniform_int_distribution(C++11)
uniform_real_distribution(C++11)
generate_canonical(C++11)
Bernoulli distribuciones
Original:
Bernoulli distributions
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bernoulli_distribution(C++11)
binomial_distribution(C++11)
negative_binomial_distribution(C++11)
geometric_distribution(C++11)
Poisson distribuciones
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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)
Distribuciones normales
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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)
Distribuciones de muestreo
Original:
Sampling distributions
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discrete_distribution(C++11)
piecewise_constant_distribution(C++11)
piecewise_linear_distribution(C++11)
Secuencias de semillas
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Seed Sequences
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seed_seq(C++11)
C biblioteca
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C library
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rand
srand
RAND_MAX
 
std::discrete_distribution
Las funciones miembro
Original:
Member functions
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discrete_distribution::discrete_distribution
discrete_distribution::reset
Generación
Original:
Generation
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discrete_distribution::operator()
Características
Original:
Characteristics
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discrete_distribution::probabilities
discrete_distribution::param
discrete_distribution::min
discrete_distribution::max
Terceros funciones
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Non-member functions
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operator==
operator!=
operator<<
operator>>
 
discrete_distribution();
(1) (desde C++11)
template< class InputIt >
discrete_distribution( InputIt first, InputIt last );
(2) (desde C++11)
discrete_distribution( std::initializer_list<double> weights );
(3) (desde C++11)
template< class UnaryOperation >

discrete_distribution( std::size_t count, double xmin, double xmax,

                       UnaryOperation unary_op );
(4) (desde C++11)
explicit discrete_distribution( const param_type& params );
(2) (desde C++11)
Construye un objeto nuevo reparto .
Original:
Constructs a new distribution object.
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1)
Por defecto constructor. Construye la distribución con pesos. Esta distribución siempre 0 generar .
Original:
Default constructor. Constructs the distribution with weights . This distribution will always generate 0.
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2)
Construye la distribución de pesos en el [first, last) rango. Si first == last, los efectos son los mismos que de la constructor predeterminado .
Original:
Constructs the distribution with weights in the range [first, last). If first == last, the effects are the same as of the default constructor.
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3)
Constructos de la distribución con los pesos en weights. Efectivamente llama initializer_list(weigths.begin(), weights.end()) .
Original:
Constructs the distribution with weights in weights. Effectively calls initializer_list(weigths.begin(), weights.end()).
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4)
Constructos de la distribución con pesos count que se generan utilizando unary_op función. Cada uno de los pesos es igual a w
i
= unary_op(xmin + δ/2 + i · δ)
, donde δ =
(xmax − xmin)
count
y i ∈ {0, ..., count−1}. xmin y xmax debe ser tal que δ > 0. Si count == 0 los efectos son los mismos que de la constructor predeterminado .
Original:
Constructs the distribution with count weights that are generated using function unary_op. Each of the weights is equal to w
i
= unary_op(xmin + δ/2 + i · δ)
, where δ =
(xmax − xmin)
count
and i ∈ {0, ..., count−1}. xmin and xmax must be such that δ > 0. If count == 0 the effects are the same as of the default constructor.
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5)
Constructos de la distribución con params como los parámetros de distribución .
Original:
Constructs the distribution with params as the distribution parameters.
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[editar] Parámetros

first, last -
la gama de elementos que definen los números a utilizar como pesos. El tipo de los elementos mencionados por InputIterator debe ser convertible a double
Original:
the range of elements defining the numbers to use as weights. The type of the elements referred by InputIterator must be convertible to double
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weights -
inicializador lista que contiene los pesos
Original:
initializer list containing the weights
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unary_op - unary operation function object that will be applied.

The signature of the function should be equivalent to the following:

 Ret fun(const Type &a);

The signature does not need to have const &.
The type  Type must be such that an object of type double can be dereferenced and then implicitly converted to  Type. The type  Ret must be such that an object of type double can be dereferenced and assigned a value of type  Ret. ​

params -
el parámetro de distribución establecido
Original:
the distribution parameter set
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Type requirements
-
InputIt must meet the requirements of InputIterator.