A piecewise_linear_distribution random number distribution produces random numbers x, b0≤x<bn, distributed over each subinterval [bi,bi+1) according to the probability density function
p(x|b0,…,bn,ρ0,…,ρn)=ρi⋅bi+1−xbi+1−bi+ρi+1⋅x−bibi+1−bi, for bi≤x<bi+1.
The n+1 distribution parameters bi, also known as this distribution's interval boundaries, shall satisfy the relation bi<bi+1 for i=0,…,n−1. Unless specified otherwise, the remaining n+1 distribution parameters are calculated as ρk=wk/S for k=0,…,n, in which the values wk, commonly known as the weights at boundaries, shall be non-negative, non-NaN, and non-infinity. Moreover, the following relation shall hold:
0<S=12⋅n−1∑k=0(wk+wk+1)⋅(bk+1−bk).
template<class RealType = double>
class piecewise_linear_distribution {
public:
// types
using result_type = RealType;
using param_type = unspecified;
// constructor and reset functions
piecewise_linear_distribution();
template<class InputIteratorB, class InputIteratorW>
piecewise_linear_distribution(InputIteratorB firstB, InputIteratorB lastB,
InputIteratorW firstW);
template<class UnaryOperation>
piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw);
template<class UnaryOperation>
piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
explicit piecewise_linear_distribution(const param_type& parm);
void reset();
// generating functions
template<class URBG>
result_type operator()(URBG& g);
template<class URBG>
result_type operator()(URBG& g, const param_type& parm);
// property functions
vector<result_type> intervals() const;
vector<result_type> densities() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
};piecewise_linear_distribution();
template<class InputIteratorB, class InputIteratorW>
piecewise_linear_distribution(InputIteratorB firstB, InputIteratorB lastB,
InputIteratorW firstW);
Requires: InputIteratorB and InputIteratorW shall each satisfy the requirements of an input iterator type. Moreover, iterator_traits<InputIteratorB>::value_type and iterator_traits<InputIteratorW>::value_type shall each denote a type that is convertible to double. If firstB == lastB or ++firstB == lastB, let n=1, ρ0=ρ1=1, b0=0, and b1=1. Otherwise, [firstB,lastB) shall form a sequence b of length n+1, the length of the sequence w starting from firstW shall be at least n+1, and any wk for k≥n+1 shall be ignored by the distribution.
template<class UnaryOperation>
piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw);
Requires: Each instance of type UnaryOperation shall be a function object whose return type shall be convertible to double. Moreover, double shall be convertible to the type of UnaryOperation's sole parameter.
Effects: Constructs a piecewise_linear_distribution object with parameters taken or calculated from the following values: If bl.size()<2, let n=1, ρ0=ρ1=1, b0=0, and b1=1. Otherwise, let [bl.begin(),bl.end()) form a sequence b0,…,bn, and let wk=fw(bk) for k=0,…,n.
template<class UnaryOperation>
piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
Requires: Each instance of type UnaryOperation shall be a function object 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 piecewise_linear_distribution object with parameters taken or calculated from the following values: Let bk=xmin+k⋅δ for k=0,…,n, and wk=fw(bk) for k=0,…,n.
vector<result_type> intervals() const;
Returns: A vector<result_type> whose size member returns n+1 and whose operator[] member returns bk when invoked with argument k for k=0,…,n.
vector<result_type> densities() const;