bernoulli_distribution Class
Generates a Bernoulli distribution.
Syntax
class bernoulli_distribution
{
public:
// types
typedef bool result_type;
struct param_type;
// constructors and reset functions
explicit bernoulli_distribution(double p = 0.5);
explicit bernoulli_distribution(const param_type& parm);
void reset();
// generating functions
template <class URNG>
result_type operator()(URNG& gen);
template <class URNG>
result_type operator()(URNG& gen, const param_type& parm);
// property functions
double p() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
};
Parameters
URNG
The uniform random number generator engine. For possible types, see <random>.
Remarks
The class describes a distribution that produces values of type bool
, distributed according to the Bernoulli distribution discrete probability function. The following table links to articles about individual members.
bernoulli_distribution
param_type
The property member p()
returns the currently stored distribution parameter value p
.
The property member param()
sets or returns the param_type
stored distribution parameter package.
The min()
and max()
member functions return the smallest possible result and largest possible result, respectively.
The reset()
member function discards any cached values, so that the result of the next call to operator()
does not depend on any values obtained from the engine before the call.
The operator()
member functions return the next generated value based on the URNG engine, either from the current parameter package, or the specified parameter package.
For more information about distribution classes and their members, see <random>.
For detailed information about the Bernoulli distribution discrete probability function, see the Wolfram MathWorld article Bernoulli Distribution.
Example
// compile with: /EHsc /W4
#include <random>
#include <iostream>
#include <iomanip>
#include <string>
#include <map>
void test(const double p, const int s) {
// uncomment to use a non-deterministic seed
// std::random_device rd;
// std::mt19937 gen(rd());
std::mt19937 gen(1729);
std::bernoulli_distribution distr(p);
std::cout << "p == " << distr.p() << std::endl;
// generate the distribution as a histogram
std::map<bool, int> histogram;
for (int i = 0; i < s; ++i) {
++histogram[distr(gen)];
}
// print results
std::cout << "Histogram for " << s << " samples:" << std::endl;
for (const auto& elem : histogram) {
std::cout << std::boolalpha << std::setw(5) << elem.first << ' ' << std::string(elem.second, ':') << std::endl;
}
std::cout << std::endl;
}
int main()
{
double p_dist = 0.5;
int samples = 100;
std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
std::cout << "Enter a double value for p distribution (where 0.0 <= p <= 1.0): ";
std::cin >> p_dist;
std::cout << "Enter an integer value for a sample count: ";
std::cin >> samples;
test(p_dist, samples);
}
Use CTRL-Z to bypass data entry and run using default values.
Enter a double value for p distribution (where 0.0 <= p <= 1.0): .45
Enter an integer value for a sample count: 100
p == 0.45
Histogram for 100 samples:
false :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
true :::::::::::::::::::::::::::::::::::::::::
Requirements
Header: <random>
Namespace: std
bernoulli_distribution::bernoulli_distribution
Constructs the distribution.
explicit bernoulli_distribution(double p = 0.5);
explicit bernoulli_distribution(const param_type& parm);
Parameters
p
The stored p
distribution parameter.
parm
The param_type
structure used to construct the distribution.
Remarks
Precondition: 0.0 ≤ p ≤ 1.0
The first constructor constructs an object whose stored p
value holds the value p.
The second constructor constructs an object whose stored parameters are initialized from parm. You can obtain and set the current parameters of an existing distribution by calling the param()
member function.
bernoulli_distribution::param_type
Contains the parameters of the distribution.
struct param_type { typedef bernoulli_distribution distribution_type; param_type(double p = 0.5); double p() const;
bool operator==(const param_type& right) const; bool operator!=(const param_type& right) const; };
Parameters
p
The stored p
distribution parameter.
Remarks
Precondition: 0.0 ≤ p ≤ 1.0
This structure can be passed to the distribution's class constructor at instantiation, to the param()
member function to set the stored parameters of an existing distribution, and to operator()
to be used in place of the stored parameters.