std::discrete_distribution<IntType>::discrete_distribution

 

C++

Compiler support

Freestanding and hosted

Language

Standard library headers

Named requirements

Feature test macros (C++20)

Language support library

Concepts library (C++20)

Metaprogramming library (C++11)

Diagnostics library

General utilities library

Strings library

Containers library

Iterators library

Ranges library (C++20)

Algorithms library

Numerics library

Localizations library

Input/output library

Filesystem library (C++17)

Regular expressions library (C++11)

Concurrency support library (C++11)

Technical specifications

Symbols index

External libraries

 

Numerics library

Common mathematical functions

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Mathematical constants (C++20)

Floating-point environment (C++11)

Complex numbers

Numeric arrays

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Factor operations

gcd (C++17)

lcm (C++17)

Interpolations

midpoint (C++20)

lerp (C++20)

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iota (C++11)

ranges::iota (C++23)

accumulate

inner_product

adjacent_difference

partial_sum

reduce (C++17)

transform_reduce (C++17)

inclusive_scan (C++17)

exclusive_scan (C++17)

transform_inclusive_scan (C++17)

transform_exclusive_scan (C++17)

Bit operations

bit_cast (C++20)

byteswap (C++23)

has_single_bit (C++20)

bit_ceil (C++20)

bit_floor (C++20)

bit_width (C++20)

rotl (C++20)

rotr (C++20)

countl_zero (C++20)

countl_one (C++20)

countr_zero (C++20)

countr_one (C++20)

popcount (C++20)

endian (C++20)

 

Pseudo-random number generation

Uniform random bit generators

uniform_random_bit_generator (C++20)

Engines and engine adaptors

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)

Non-deterministic generator

random_device (C++11)

Distributions

Uniform distributions

uniform_int_distribution (C++11)

uniform_real_distribution (C++11)

generate_canonical (C++11)

Bernoulli distributions

bernoulli_distribution (C++11)

binomial_distribution (C++11)

negative_binomial_distribution (C++11)

geometric_distribution (C++11)

Poisson distributions

poisson_distribution (C++11)

exponential_distribution (C++11)

gamma_distribution (C++11)

weibull_distribution (C++11)

extreme_value_distribution (C++11)

Normal distributions

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)

Sampling distributions

discrete_distribution (C++11)

piecewise_constant_distribution (C++11)

piecewise_linear_distribution (C++11)

Seed Sequences

seed_seq (C++11)

C library

rand

srand

RAND_MAX

 

std::discrete_distribution

Member functions

discrete_distribution::discrete_distribution (C++11)

discrete_distribution::reset (C++11)

Generation

discrete_distribution::operator() (C++11)

Characteristics

discrete_distribution::probabilities (C++11)

discrete_distribution::param (C++11)

discrete_distribution::min (C++11)

discrete_distribution::max (C++11)

Non-member functions

operator==operator!= (C++11)(C++11)(until C++20)

operator<<operator>> (C++11)(C++11)

 

discrete_distribution();	(1)	(since C++11)
template< class InputIt > discrete_distribution( InputIt first, InputIt last );	(2)	(since C++11)
discrete_distribution( std::initializer_list<double> weights );	(3)	(since C++11)
template< class UnaryOperation > discrete_distribution( std::size_t count, double xmin, double xmax,                        UnaryOperation unary_op );	(4)	(since C++11)
explicit discrete_distribution( const param_type& params );	(5)	(since C++11)

Constructs a new distribution object.

1) Default constructor. Constructs the distribution with a single weight p={1}. This distribution will always generate ​0​.

2) Constructs the distribution with weights in the range [first, last). If first == last, the effects are the same as of the default constructor.

3) Constructs the distribution with weights in weights. Effectively calls discrete_distribution(weights.begin(), weights.end()).

4) 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(i + 0.5)), 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.

5) Constructs the distribution with params as the distribution parameters.

Parameters

first, last	-	the range of elements defining the numbers to use as weights. The type of the elements referred by InputIterator must be convertible to double
weights	-	initializer list containing the weights
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	-	the distribution parameter set
Type requirements
- InputIt must meet the requirements of LegacyInputIterator.