std::linear_congruential_engine

 

C++

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Feature test macros (C++20)

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Numerics library

Common mathematical functions
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Mathematical constants (C++20)
Basic linear algebra algorithms (C++26)
Floating-point environment (C++11)
Complex numbers
Numeric array (valarray)
Pseudo-random number generation
Factor operations
gcd (C++17)	lcm (C++17)
Interpolations
midpoint (C++20)	lerp (C++20)
Saturation arithmetic
add_sat (C++26) sub_sat (C++26) saturate_cast (C++26)	mul_sat (C++26) div_sat (C++26)
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)
Bit operations
has_single_bit (C++20)     bit_cast (C++20) bit_ceil (C++20) bit_floor (C++20) bit_width (C++20) rotl (C++20) rotr (C++20)	popcount (C++20) countl_zero (C++20) countl_one (C++20) countr_zero (C++20) countr_one (C++20) byteswap (C++23) endian (C++20)

 

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::linear_congruential_engine

Member functions

linear_congruential_engine::linear_congruential_engine

linear_congruential_engine::seed

Generation

linear_congruential_engine::operator()

linear_congruential_engine::discard

Characteristics

linear_congruential_engine::min

linear_congruential_engine::max

Non-member functions

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

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

 

Defined in header <random>
template<     class UIntType,     UIntType a,     UIntType c,     UIntType m > class linear_congruential_engine;		(since C++11)

linear_congruential_engine is a random number engine based on Linear congruential generator (LCG).

Template parameters

UIntType	-	The result type generated by the generator. The effect is undefined if this is not one of unsigned short, unsigned int, unsigned long, or unsigned long long.
a	-	the multiplier term
c	-	the increment term
m	-	the modulus term

When m is not zero, if a >= m or c >= m is true, the program is ill-formed.

Generator properties

The size of the states of linear_congruential_engine is 1, each of them consists of a single integer.

The actual modulus \(\scriptsize m_0\)m
0 is defined as follows:

• If m is not zero, \(\scriptsize m_0\)m
  0 is m.
• If m is zero, \(\scriptsize m_0\)m
  0 is the value of std::numeric_limits<result_type>::max() plus 1 (which means \(\scriptsize m_0\)m
  0 need not be representable as result_type).

The transition algorithm of linear_congruential_engine is \(\scriptsize TA(x_i) = (a \cdot x_i + c)\mod m_0\)TA(x
i) = (a·x
i+c) mod m
0.

The generation algorithm of linear_congruential_engine is \(\scriptsize GA(x_i) = (a \cdot x_i + c)\mod m_0\)GA(x
i) = (a·x
i+c) mod m
0.

The pseudo-random number generated with the current state is also the successor state.

Predefined specializations

The following specializations define the random number engine with two commonly used parameter sets:

Defined in header <random>
Type	Definition
minstd_rand0 (C++11)	std::linear_congruential_engine<std::uint_fast32_t,                                 16807, 0, 2147483647> Discovered in 1969 by Lewis, Goodman and Miller, adopted as "Minimal standard" in 1988 by Park and Miller
minstd_rand (C++11)	std::linear_congruential_engine<std::uint_fast32_t,                                 48271, 0, 2147483647> Newer "Minimum standard", recommended by Park, Miller, and Stockmeyer in 1993

Nested types

Type	Definition
result_type	UIntType

Data members

constexpr UIntType multiplier [static]	a (public static member constant)
constexpr UIntType increment [static]	c (public static member constant)
constexpr UIntType modulus [static]	m (public static member constant)
constexpr UIntType default_seed [static]	1u (public static member constant)

Member functions

Construction and Seeding
(constructor)	constructs the engine (public member function)
seed	sets the current state of the engine (public member function)
Generation
operator()	advances the engine's state and returns the generated value (public member function)
discard	advances the engine's state by a specified amount (public member function)
Characteristics
min [static]	gets the smallest possible value in the output range (public static member function)
max [static]	gets the largest possible value in the output range (public static member function)

Non-member functions

operator==operator!= (C++11)(C++11)(removed in C++20)	compares the internal states of two pseudo-random number engines (function)
operator<<operator>> (C++11)	performs stream input and output on pseudo-random number engine (function template)