28 Numerics library [numerics]

28.5 Random number generation [rand]

28.5.7 Class random_device [rand.device]

1
#
A random_device uniform random bit generator produces nondeterministic random numbers.
2
#
If implementation limitations prevent generating nondeterministic random numbers, the implementation may employ a random number engine.
🔗
namespace std { class random_device { public: // types using result_type = unsigned int; // generator characteristics static constexpr result_type min() { return numeric_limits<result_type>::min(); } static constexpr result_type max() { return numeric_limits<result_type>::max(); } // constructors random_device() : random_device(implementation-defined) {} explicit random_device(const string& token); // generating functions result_type operator()(); // property functions double entropy() const noexcept; // no copy functions random_device(const random_device&) = delete; void operator=(const random_device&) = delete; }; }
🔗
explicit random_device(const string& token);
3
#
Throws: A value of an implementation-defined type derived from exception if the random_device cannot be initialized.
4
#
Remarks: The semantics of the token parameter and the token value used by the default constructor are implementation-defined.228
🔗
double entropy() const noexcept;
5
#
Returns: If the implementation employs a random number engine, returns 0.0.
Otherwise, returns an entropy estimate229 for the random numbers returned by operator(), in the range min() to .
🔗
result_type operator()();
6
#
Returns: A nondeterministic random value, uniformly distributed between min() and max() (inclusive).
It is implementation-defined how these values are generated.
7
#
Throws: A value of an implementation-defined type derived from exception if a random number cannot be obtained.
228)228)
The parameter is intended to allow an implementation to differentiate between different sources of randomness.
229)229)
If a device has n states whose respective probabilities are , the device entropy S is defined as
.