A discrete_distribution random number distribution produces random integers i, 0 ≤ i < n, distributed according to the discrete probability function P(i | p0,…,pn-1) = pi .
Unless specified otherwise, the distribution parameters are calculated as: pk = wk / S for k = 0, …, n-1 , in which the values wk, commonly known as the weights, shall be non-negative, non-NaN, and non-infinity. Moreover, the following relation shall hold: 0 < S = w0 + ⋯ + wn-1 .
template<class IntType = int>
class discrete_distribution{
public:
// types
typedef IntType result_type;
typedef unspecified param_type;
// constructor and reset functions
discrete_distribution();
template<class InputIterator>
discrete_distribution(InputIterator firstW, InputIterator lastW);
discrete_distribution(initializer_list<double> wl);
template<class UnaryOperation>
discrete_distribution(size_t nw, double xmin, double xmax, UnaryOperation fw);
explicit discrete_distribution(const param_type& parm);
void reset();
// generating functions
template<class URNG>
result_type operator()(URNG& g);
template<class URNG>
result_type operator()(URNG& g, const param_type& parm);
// property functions
vector<double> probabilities() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
};
Effects: Constructs a discrete_distribution object with n = 1 and p0 = 1 . [ Note: Such an object will always deliver the value 0. — end note ]
template<class InputIterator>
discrete_distribution(InputIterator firstW, InputIterator lastW);
Requires: InputIterator shall satisfy the requirements of an input iterator (Table [tab:iterator.input.requirements]) type. Moreover, iterator_traits<InputIterator>::value_type shall denote a type that is convertible to double. If firstW == lastW, let n = 1 and w0 = 1 . Otherwise, [firstW, lastW) shall form a sequence w of length n > 0.
Effects: Constructs a discrete_distribution object with probabilities given by the formula above.
discrete_distribution(initializer_list<double> wl);
Effects: Same as discrete_distribution(wl.begin(), wl.end()).
template<class UnaryOperation>
discrete_distribution(size_t nw, double xmin, double xmax, UnaryOperation fw);
Requires: Each instance of type UnaryOperation shall be a function object ([function.objects]) whose return type shall be convertible to double. Moreover, double shall be convertible to the type of UnaryOperation's sole parameter. If nw = 0 , let n = 1 , otherwise let n = nw. The relation 0 < δ = (xmax - xmin) / n shall hold.
Effects: Constructs a discrete_distribution object with probabilities given by the formula above, using the following values: If nw = 0, let w0 = 1 . Otherwise, let wk = fw(xmin + k · δ + δ / 2) for k = 0, …, n-1 .
Complexity: The number of invocations of fw shall not exceed n.
vector<double> probabilities() const;
Returns: A vector<double> whose size member returns n and whose operator[] member returns pk when invoked with argument k for k = 0, …, n-1 .