26 Numerics library [numerics]

26.6 Random number generation [rand]

26.6.8 Random number distribution class templates [rand.dist]

26.6.8.1 In general [rand.dist.general]

Each type instantiated from a class template specified in this subclause [rand.dist] meets the requirements of a random number distribution type.
Descriptions are provided in this subclause [rand.dist] only for distribution operations that are not described in [rand.req.dist] or for operations where there is additional semantic information.
In particular, declarations for copy constructors, for copy assignment operators, for streaming operators, and for equality and inequality operators are not shown in the synopses.
The algorithms for producing each of the specified distributions are implementation-defined.
The value of each probability density function p(z) and of each discrete probability function specified in this subclause is 0 everywhere outside its stated domain.

26.6.8.2 Uniform distributions [rand.dist.uni]

26.6.8.2.1 Class template uniform_­int_­distribution [rand.dist.uni.int]

A uniform_­int_­distribution random number distribution produces random integers i, , distributed according to the constant discrete probability function
template<class IntType = int>
  class uniform_int_distribution {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // constructors and reset functions
    uniform_int_distribution() : uniform_int_distribution(0) {}
    explicit uniform_int_distribution(IntType a, IntType b = numeric_limits<IntType>::max());
    explicit uniform_int_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
    result_type a() const;
    result_type b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit uniform_int_distribution(IntType a, IntType b = numeric_limits<IntType>::max());
Preconditions: .
Remarks: a and b correspond to the respective parameters of the distribution.
result_type a() const;
Returns: The value of the a parameter with which the object was constructed.
result_type b() const;
Returns: The value of the b parameter with which the object was constructed.

26.6.8.2.2 Class template uniform_­real_­distribution [rand.dist.uni.real]

A uniform_­real_­distribution random number distribution produces random numbers x, , distributed according to the constant probability density function
[Note
:
This implies that is undefined when a == b.
— end note
]
template<class RealType = double>
  class uniform_real_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructors and reset functions
    uniform_real_distribution() : uniform_real_distribution(0.0) {}
    explicit uniform_real_distribution(RealType a, RealType b = 1.0);
    explicit uniform_real_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
    result_type a() const;
    result_type b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit uniform_real_distribution(RealType a, RealType b = 1.0);
Preconditions: and .
Remarks: a and b correspond to the respective parameters of the distribution.
result_type a() const;
Returns: The value of the a parameter with which the object was constructed.
result_type b() const;
Returns: The value of the b parameter with which the object was constructed.

26.6.8.3 Bernoulli distributions [rand.dist.bern]

26.6.8.3.1 Class bernoulli_­distribution [rand.dist.bern.bernoulli]

A bernoulli_­distribution random number distribution produces bool values b distributed according to the discrete probability function
class bernoulli_distribution {
public:
  // types
  using result_type = bool;
  using param_type  = unspecified;

  // constructors and reset functions
  bernoulli_distribution() : bernoulli_distribution(0.5) {}
  explicit bernoulli_distribution(double p);
  explicit bernoulli_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
  double p() const;
  param_type param() const;
  void param(const param_type& parm);
  result_type min() const;
  result_type max() const;
};
explicit bernoulli_distribution(double p);
Preconditions: .
Remarks: p corresponds to the parameter of the distribution.
double p() const;
Returns: The value of the p parameter with which the object was constructed.

26.6.8.3.2 Class template binomial_­distribution [rand.dist.bern.bin]

A binomial_­distribution random number distribution produces integer values distributed according to the discrete probability function
template<class IntType = int>
  class binomial_distribution {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // constructors and reset functions
    binomial_distribution() : binomial_distribution(1) {}
    explicit binomial_distribution(IntType t, double p = 0.5);
    explicit binomial_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
    IntType t() const;
    double p() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit binomial_distribution(IntType t, double p = 0.5);
Preconditions: and .
Remarks: t and p correspond to the respective parameters of the distribution.
IntType t() const;
Returns: The value of the t parameter with which the object was constructed.
double p() const;
Returns: The value of the p parameter with which the object was constructed.

26.6.8.3.3 Class template geometric_­distribution [rand.dist.bern.geo]

A geometric_­distribution random number distribution produces integer values distributed according to the discrete probability function
template<class IntType = int>
  class geometric_distribution {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // constructors and reset functions
    geometric_distribution() : geometric_distribution(0.5) {}
    explicit geometric_distribution(double p);
    explicit geometric_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
    double p() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit geometric_distribution(double p);
Preconditions: .
Remarks: p corresponds to the parameter of the distribution.
double p() const;
Returns: The value of the p parameter with which the object was constructed.

26.6.8.3.4 Class template negative_­binomial_­distribution [rand.dist.bern.negbin]

A negative_­binomial_­distribution random number distribution produces random integers distributed according to the discrete probability function
[Note
:
This implies that is undefined when p == 1.
— end note
]
template<class IntType = int>
  class negative_binomial_distribution {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // constructor and reset functions
    negative_binomial_distribution() : negative_binomial_distribution(1) {}
    explicit negative_binomial_distribution(IntType k, double p = 0.5);
    explicit negative_binomial_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
    IntType k() const;
    double p() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit negative_binomial_distribution(IntType k, double p = 0.5);
Preconditions: and .
Remarks: k and p correspond to the respective parameters of the distribution.
IntType k() const;
Returns: The value of the k parameter with which the object was constructed.
double p() const;
Returns: The value of the p parameter with which the object was constructed.

26.6.8.4 Poisson distributions [rand.dist.pois]

26.6.8.4.1 Class template poisson_­distribution [rand.dist.pois.poisson]

A poisson_­distribution random number distribution produces integer values distributed according to the discrete probability function
The distribution parameter μ is also known as this distribution's mean.
template<class IntType = int>
  class poisson_distribution
  {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // constructors and reset functions
    poisson_distribution() : poisson_distribution(1.0) {}
    explicit poisson_distribution(double mean);
    explicit poisson_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
    double mean() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit poisson_distribution(double mean);
Preconditions: .
Remarks: mean corresponds to the parameter of the distribution.
double mean() const;
Returns: The value of the mean parameter with which the object was constructed.

26.6.8.4.2 Class template exponential_­distribution [rand.dist.pois.exp]

An exponential_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class exponential_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructors and reset functions
    exponential_distribution() : exponential_distribution(1.0) {}
    explicit exponential_distribution(RealType lambda);
    explicit exponential_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
    RealType lambda() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit exponential_distribution(RealType lambda);
Preconditions: .
Remarks: lambda corresponds to the parameter of the distribution.
RealType lambda() const;
Returns: The value of the lambda parameter with which the object was constructed.

26.6.8.4.3 Class template gamma_­distribution [rand.dist.pois.gamma]

A gamma_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class gamma_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructors and reset functions
    gamma_distribution() : gamma_distribution(1.0) {}
    explicit gamma_distribution(RealType alpha, RealType beta = 1.0);
    explicit gamma_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
    RealType alpha() const;
    RealType beta() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit gamma_distribution(RealType alpha, RealType beta = 1.0);
Preconditions: and .
Remarks: alpha and beta correspond to the parameters of the distribution.
RealType alpha() const;
Returns: The value of the alpha parameter with which the object was constructed.
RealType beta() const;
Returns: The value of the beta parameter with which the object was constructed.

26.6.8.4.4 Class template weibull_­distribution [rand.dist.pois.weibull]

A weibull_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class weibull_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    weibull_distribution() : weibull_distribution(1.0) {}
    explicit weibull_distribution(RealType a, RealType b = 1.0);
    explicit weibull_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
    RealType a() const;
    RealType b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit weibull_distribution(RealType a, RealType b = 1.0);
Preconditions: and .
Remarks: a and b correspond to the respective parameters of the distribution.
RealType a() const;
Returns: The value of the a parameter with which the object was constructed.
RealType b() const;
Returns: The value of the b parameter with which the object was constructed.

26.6.8.4.5 Class template extreme_­value_­distribution [rand.dist.pois.extreme]

An extreme_­value_­distribution random number distribution produces random numbers x distributed according to the probability density function247
template<class RealType = double>
  class extreme_value_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    extreme_value_distribution() : extreme_value_distribution(0.0) {}
    explicit extreme_value_distribution(RealType a, RealType b = 1.0);
    explicit extreme_value_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
    RealType a() const;
    RealType b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit extreme_value_distribution(RealType a, RealType b = 1.0);
Preconditions: .
Remarks: a and b correspond to the respective parameters of the distribution.
RealType a() const;
Returns: The value of the a parameter with which the object was constructed.
RealType b() const;
Returns: The value of the b parameter with which the object was constructed.
The distribution corresponding to this probability density function is also known (with a possible change of variable) as the Gumbel Type I, the log-Weibull, or the Fisher-Tippett Type I distribution.

26.6.8.5 Normal distributions [rand.dist.norm]

26.6.8.5.1 Class template normal_­distribution [rand.dist.norm.normal]

A normal_­distribution random number distribution produces random numbers x distributed according to the probability density function
The distribution parameters μ and σ are also known as this distribution's mean and standard deviation.
template<class RealType = double>
  class normal_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructors and reset functions
    normal_distribution() : normal_distribution(0.0) {}
    explicit normal_distribution(RealType mean, RealType stddev = 1.0);
    explicit normal_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
    RealType mean() const;
    RealType stddev() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit normal_distribution(RealType mean, RealType stddev = 1.0);
Preconditions: .
Remarks: mean and stddev correspond to the respective parameters of the distribution.
RealType mean() const;
Returns: The value of the mean parameter with which the object was constructed.
RealType stddev() const;
Returns: The value of the stddev parameter with which the object was constructed.

26.6.8.5.2 Class template lognormal_­distribution [rand.dist.norm.lognormal]

A lognormal_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class lognormal_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    lognormal_distribution() : lognormal_distribution(0.0) {}
    explicit lognormal_distribution(RealType m, RealType s = 1.0);
    explicit lognormal_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
    RealType m() const;
    RealType s() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit lognormal_distribution(RealType m, RealType s = 1.0);
Preconditions: .
Remarks: m and s correspond to the respective parameters of the distribution.
RealType m() const;
Returns: The value of the m parameter with which the object was constructed.
RealType s() const;
Returns: The value of the s parameter with which the object was constructed.

26.6.8.5.3 Class template chi_­squared_­distribution [rand.dist.norm.chisq]

A chi_­squared_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class chi_squared_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    chi_squared_distribution() : chi_squared_distribution(1.0) {}
    explicit chi_squared_distribution(RealType n);
    explicit chi_squared_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
    RealType n() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit chi_squared_distribution(RealType n);
Preconditions: .
Remarks: n corresponds to the parameter of the distribution.
RealType n() const;
Returns: The value of the n parameter with which the object was constructed.

26.6.8.5.4 Class template cauchy_­distribution [rand.dist.norm.cauchy]

A cauchy_­distribution random number distribution produces random numbers x distributed according to the probability density function
template<class RealType = double>
  class cauchy_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    cauchy_distribution() : cauchy_distribution(0.0) {}
    explicit cauchy_distribution(RealType a, RealType b = 1.0);
    explicit cauchy_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
    RealType a() const;
    RealType b() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit cauchy_distribution(RealType a, RealType b = 1.0);
Preconditions: .
Remarks: a and b correspond to the respective parameters of the distribution.
RealType a() const;
Returns: The value of the a parameter with which the object was constructed.
RealType b() const;
Returns: The value of the b parameter with which the object was constructed.

26.6.8.5.5 Class template fisher_­f_­distribution [rand.dist.norm.f]

A fisher_­f_­distribution random number distribution produces random numbers distributed according to the probability density function
template<class RealType = double>
  class fisher_f_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    fisher_f_distribution() : fisher_f_distribution(1.0) {}
    explicit fisher_f_distribution(RealType m, RealType n = 1.0);
    explicit fisher_f_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
    RealType m() const;
    RealType n() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit fisher_f_distribution(RealType m, RealType n = 1);
Preconditions: and .
Remarks: m and n correspond to the respective parameters of the distribution.
RealType m() const;
Returns: The value of the m parameter with which the object was constructed.
RealType n() const;
Returns: The value of the n parameter with which the object was constructed.

26.6.8.5.6 Class template student_­t_­distribution [rand.dist.norm.t]

A student_­t_­distribution random number distribution produces random numbers x distributed according to the probability density function
template<class RealType = double>
  class student_t_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    student_t_distribution() : student_t_distribution(1.0) {}
    explicit student_t_distribution(RealType n);
    explicit student_t_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
    RealType n() const;
    param_type param() const;
    void param(const param_type& parm);
    result_type min() const;
    result_type max() const;
  };
explicit student_t_distribution(RealType n);
Preconditions: .
Remarks: n corresponds to the parameter of the distribution.
RealType n() const;
Returns: The value of the n parameter with which the object was constructed.

26.6.8.6 Sampling distributions [rand.dist.samp]

26.6.8.6.1 Class template discrete_­distribution [rand.dist.samp.discrete]

A discrete_­distribution random number distribution produces random integers i, , distributed according to the discrete probability function
Unless specified otherwise, the distribution parameters are calculated as: for , in which the values , commonly known as the weights, shall be non-negative, non-NaN, and non-infinity.
Moreover, the following relation shall hold: .
template<class IntType = int>
  class discrete_distribution {
  public:
    // types
    using result_type = IntType;
    using param_type  = unspecified;

    // 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 URBG>
      result_type operator()(URBG& g);
    template<class URBG>
      result_type operator()(URBG& 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;
  };
discrete_distribution();
Effects: Constructs a discrete_­distribution object with and .
[Note
:
Such an object will always deliver the value 0.
— end note
]
template<class InputIterator> discrete_distribution(InputIterator firstW, InputIterator lastW);
Mandates: is_­convertible_­v<iterator_­traits<InputIterator>​::​value_­type, double> is true.
Preconditions: InputIterator meets the Cpp17InputIterator requirements ([input.iterators]).
If firstW == lastW, let and .
Otherwise, forms a sequence w of length .
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);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Preconditions: If , let , otherwise let .
The relation holds.
Effects: Constructs a discrete_­distribution object with probabilities given by the formula above, using the following values: If , let .
Otherwise, let for .
Complexity: The number of invocations of fw does not exceed n.
vector<double> probabilities() const;
Returns: A vector<double> whose size member returns n and whose operator[] member returns when invoked with argument k for .

26.6.8.6.2 Class template piecewise_­constant_­distribution [rand.dist.samp.pconst]

A piecewise_­constant_­distribution random number distribution produces random numbers x, , uniformly distributed over each subinterval according to the probability density function
The distribution parameters , also known as this distribution's interval boundaries, shall satisfy the relation for .
Unless specified otherwise, the remaining n distribution parameters are calculated as:
in which the values , commonly known as the weights, shall be non-negative, non-NaN, and non-infinity.
Moreover, the following relation shall hold: .
template<class RealType = double>
  class piecewise_constant_distribution {
  public:
    // types
    using result_type = RealType;
    using param_type  = unspecified;

    // constructor and reset functions
    piecewise_constant_distribution();
    template<class InputIteratorB, class InputIteratorW>
      piecewise_constant_distribution(InputIteratorB firstB, InputIteratorB lastB,
                                      InputIteratorW firstW);
    template<class UnaryOperation>
      piecewise_constant_distribution(initializer_list<RealType> bl, UnaryOperation fw);
    template<class UnaryOperation>
      piecewise_constant_distribution(size_t nw, RealType xmin, RealType xmax,
                                      UnaryOperation fw);
    explicit piecewise_constant_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_constant_distribution();
Effects: Constructs a piecewise_­constant_­distribution object with , , , and .
template<class InputIteratorB, class InputIteratorW> piecewise_constant_distribution(InputIteratorB firstB, InputIteratorB lastB, InputIteratorW firstW);
Mandates: Both of
  • is_­convertible_­v<iterator_­traits<InputIteratorB>​::​value_­type, double>
  • is_­convertible_­v<iterator_­traits<InputIteratorW>​::​value_­type, double>
are true.
Preconditions: InputIteratorB and InputIteratorW each meet the Cpp17InputIterator requirements ([input.iterators]).
If firstB == lastB or ++firstB == lastB, let , , , and .
Otherwise, forms a sequence b of length , the length of the sequence w starting from firstW is at least n, and any for are ignored by the distribution.
Effects: Constructs a piecewise_­constant_­distribution object with parameters as specified above.
template<class UnaryOperation> piecewise_constant_distribution(initializer_list<RealType> bl, UnaryOperation fw);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Effects: Constructs a piecewise_­constant_­distribution object with parameters taken or calculated from the following values: If , let , , , and .
Otherwise, let form a sequence , and let for .
Complexity: The number of invocations of fw does not exceed n.
template<class UnaryOperation> piecewise_constant_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Preconditions: If , let , otherwise let .
The relation holds.
Effects: Constructs a piecewise_­constant_­distribution object with parameters taken or calculated from the following values: Let for , and for .
Complexity: The number of invocations of fw does not exceed n.
vector<result_type> intervals() const;
Returns: A vector<result_­type> whose size member returns and whose operator[] member returns when invoked with argument k for .
vector<result_type> densities() const;
Returns: A vector<result_­type> whose size member returns n and whose operator[] member returns when invoked with argument k for .

26.6.8.6.3 Class template piecewise_­linear_­distribution [rand.dist.samp.plinear]

A piecewise_­linear_­distribution random number distribution produces random numbers x, , distributed over each subinterval according to the probability density function
The distribution parameters , also known as this distribution's interval boundaries, shall satisfy the relation for .
Unless specified otherwise, the remaining distribution parameters are calculated as for , in which the values , commonly known as the weights at boundaries, shall be non-negative, non-NaN, and non-infinity.
Moreover, the following relation shall hold:
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();
Effects: Constructs a piecewise_­linear_­distribution object with , , , and .
template<class InputIteratorB, class InputIteratorW> piecewise_linear_distribution(InputIteratorB firstB, InputIteratorB lastB, InputIteratorW firstW);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Preconditions: InputIteratorB and InputIteratorW each meet the Cpp17InputIterator requirements ([input.iterators]).
If firstB == lastB or ++firstB == lastB, let , , , and .
Otherwise, forms a sequence b of length , the length of the sequence w starting from firstW is at least , and any for are ignored by the distribution.
Effects: Constructs a piecewise_­linear_­distribution object with parameters as specified above.
template<class UnaryOperation> piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Effects: Constructs a piecewise_­linear_­distribution object with parameters taken or calculated from the following values: If , let , , , and .
Otherwise, let form a sequence , and let for .
Complexity: The number of invocations of fw does not exceed .
template<class UnaryOperation> piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
Mandates: is_­invocable_­r_­v<double, UnaryOperation&, double> is true.
Preconditions: If , let , otherwise let .
The relation holds.
Effects: Constructs a piecewise_­linear_­distribution object with parameters taken or calculated from the following values: Let for , and for .
Complexity: The number of invocations of fw does not exceed .
vector<result_type> intervals() const;
Returns: A vector<result_­type> whose size member returns and whose operator[] member returns when invoked with argument k for .
vector<result_type> densities() const;
Returns: A vector<result_­type> whose size member returns n and whose operator[] member returns when invoked with argument k for .