std::discrete_distribution<IntType>::discrete_distribution

 

C++

Compiler support

Freestanding and hosted

Language

Standard library

Standard library headers

Named requirements

Feature test macros (C++20)

Language support library

Concepts library (C++20)

Diagnostics library

Memory management library

Metaprogramming library (C++11)

General utilities library

Containers library

Iterators library

Ranges library (C++20)

Algorithms library

Strings library

Text processing library

Numerics library

Date and time library

Input/output library

Filesystem library (C++17)

Concurrency support library (C++11)

Execution control library (C++26)

Technical specifications

Symbols index

External libraries

 

Numerics library

Common mathematical functions
Mathematical special functions (C++17)
Mathematical constants (C++20)
Basic linear algebra algorithms (C++26)
Data-parallel types (SIMD) (C++26)
Floating-point environment (C++11)
Complex numbers
Numeric array (valarray)
Pseudo-random number generation
Bit manipulation (C++20)
Saturation arithmetic (C++26)
Factor operations
gcd (C++17)	lcm (C++17)
Interpolations
midpoint (C++20)	lerp (C++20)
Generic numeric operations
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)
C-style checked integer arithmetic
ckd_add (C++26) ckd_sub (C++26)	ckd_mul (C++26)

 

Pseudo-random number generation

Uniform random bit generators   uniform_random_bit_generator (C++20) Random number engines linear_congruential_engine (C++11) mersenne_twister_engine (C++11) subtract_with_carry_engine (C++11) philox_engine (C++26) Random number engine adaptors discard_block_engine (C++11) independent_bits_engine (C++11) shuffle_order_engine (C++11) Predefined random number generators Non-deterministic random numbers random_device (C++11) Utilities generate_canonical (C++11) seed_seq (C++11) Random number algorithms ranges::generate_random (C++26) C random library rand    srand    RAND_MAX

Random number 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)

 

std::discrete_distribution

Member functions

discrete_distribution::discrete_distribution

discrete_distribution::reset

Generation

discrete_distribution::operator()

Characteristics

discrete_distribution::probabilities

discrete_distribution::param

discrete_distribution::min

discrete_distribution::max

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 wi = 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.

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