gamma_distribution Class
Generates a gamma distribution.
Syntax
template<class RealType = double>
class gamma_distribution {
public:
// types
typedef RealType result_type;
struct param_type;
// constructors and reset functions
explicit gamma_distribution(result_type alpha = 1.0, result_type beta = 1.0);
explicit gamma_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
result_type alpha() const;
result_type beta() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
};
Parameters
RealType
The floating-point result type, defaults to double. For possible types, see <random>.
URNG
The uniform random number generator engine. For possible types, see <random>.
Remarks
The class template describes a distribution that produces values of a user-specified floating-point type, or type double if none is provided, distributed according to the Gamma Distribution. The following table links to articles about individual members.
The property functions alpha() and beta() return their respective values for stored distribution parameters alpha and beta.
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 gamma distribution, see the Wolfram MathWorld article Gamma Distribution.
Example
// compile with: /EHsc /W4
#include <random>
#include <iostream>
#include <iomanip>
#include <string>
#include <map>
void test(const double a, const double b, const int s) {
// uncomment to use a non-deterministic generator
// std::random_device gen;
std::mt19937 gen(1701);
std::gamma_distribution<> distr(a, b);
std::cout << std::endl;
std::cout << "min() == " << distr.min() << std::endl;
std::cout << "max() == " << distr.max() << std::endl;
std::cout << "alpha() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.alpha() << std::endl;
std::cout << "beta() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.beta() << std::endl;
// generate the distribution as a histogram
std::map<double, int> histogram;
for (int i = 0; i < s; ++i) {
++histogram[distr(gen)];
}
// print results
std::cout << "Distribution for " << s << " samples:" << std::endl;
int counter = 0;
for (const auto& elem : histogram) {
std::cout << std::fixed << std::setw(11) << ++counter << ": "
<< std::setw(14) << std::setprecision(10) << elem.first << std::endl;
}
std::cout << std::endl;
}
int main()
{
double a_dist = 0.0;
double b_dist = 1;
int samples = 10;
std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
std::cout << "Enter a floating point value for the 'alpha' distribution parameter (must be greater than zero): ";
std::cin >> a_dist;
std::cout << "Enter a floating point value for the 'beta' distribution parameter (must be greater than zero): ";
std::cin >> b_dist;
std::cout << "Enter an integer value for the sample count: ";
std::cin >> samples;
test(a_dist, b_dist, samples);
}
Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'alpha' distribution parameter (must be greater than zero): 1
Enter a floating point value for the 'beta' distribution parameter (must be greater than zero): 1
Enter an integer value for the sample count: 10
min() == 4.94066e-324
max() == 1.79769e+308
alpha() == 1.0000000000
beta() == 1.0000000000
Distribution for 10 samples:
1: 0.0936880533
2: 0.1225944894
3: 0.6443593183
4: 0.6551171649
5: 0.7313457551
6: 0.7313557977
7: 0.7590097389
8: 1.4466885214
9: 1.6434088411
10: 2.1201210996
Requirements
Header: <random>
Namespace: std
gamma_distribution::gamma_distribution
Constructs the distribution.
explicit gamma_distribution(result_type alpha = 1.0, result_type beta = 1.0);
explicit gamma_distribution(const param_type& parm);
Parameters
alpha
The alpha distribution parameter.
beta
The beta distribution parameter.
parm
The parameter structure used to construct the distribution.
Remarks
Precondition: 0.0 < alpha and 0.0 < beta
The first constructor constructs an object whose stored alpha value holds the value alpha and whose stored beta value holds the value beta.
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.
gamma_distribution::param_type
Stores the parameters of the distribution.
struct param_type {
typedef gamma_distribution<result_type> distribution_type;
param_type(result_type alpha = 1.0, result_type beta 1.0);
result_type alpha() const;
result_type beta() const;
bool operator==(const param_type& right) const;
bool operator!=(const param_type& right) const;
};
Parameters
alpha
The alpha distribution parameter.
beta
The beta distribution parameter.
right
The param_type instance to compare this to.
Remarks
Precondition: 0.0 < alpha and 0.0 < beta
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.