# bernoulli_distribution Class

Visual Studio 2015

For the latest documentation on Visual Studio 2017, see Visual Studio 2017 Documentation.

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;
};

```

## 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::bernoulli_distribution`bernoulli_distribution::p``bernoulli_distribution::param`
`bernoulli_distribution::operator()`bernoulli_distribution::param_type

The property member `p()` returns the currently stored distribution parameter value `p`.

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);
}

```

## Output

```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 :::::::::::::::::::::::::::::::::::::::::::::::

```

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 parameter 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

See parent topic bernoulli_distribution Class.

### 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.

<random>

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