class template
<random>

std::piecewise_constant_distribution

template <class RealType = double> class piecewise_constant_distribution;
Piecewise constant distribution
Random number distribution that produces floating-point values that are uniformly distributed over each of a sequence of contiguous subintervals, as defined by the following probability density function:



A set of n non-negative individual weights (the w's) for each of the subintervals [bi,bi+1) are set on construction. The probability of producing a value within each subinterval being their corresponding weight (wi) divided by the total of all weights.

To produce a random value following this distribution, call its member function operator().

Template parameters

RealType
A floating-point type. Aliased as member type result_type.
By default, this is double.

Member types

The following aliases are member types of piecewise_constant_distribution:

member typedefinitionnotes
result_typeThe first template parameter (RealType)The type of the numbers generated (defaults to double)
param_typenot specifiedThe type returned by member param.

Member functions


Distribution parameters:


Non-member functions


Example

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// piecewise_constant_distribution
#include <iostream>
#include <array>
#include <random>

int main()
{
  const int nrolls = 10000; // number of experiments
  const int nstars = 100;   // maximum number of stars to distribute

  std::default_random_engine generator;
  std::array<double,6> intervals {0.0, 2.0, 4.0, 6.0, 8.0, 10.0};
  std::array<double,5> weights {2.0, 1.0, 2.0, 1.0, 2.0};
  std::piecewise_constant_distribution<double>
    distribution (intervals.begin(),intervals.end(),weights.begin());

  int p[10]={};

  for (int i=0; i<nrolls; ++i) {
    int number = distribution(generator);
    ++p[number];
  }

  std::cout << "a piecewise_constant_distribution:" << std::endl;
  for (int i=0; i<10; ++i) {
    std::cout << i << "-" << i+1 << ": ";
    std::cout << std::string(p[i]*nstars/nrolls,'*') << std::endl;
  }
  return 0;
}


Possible output:
a piecewise_constant_distribution:
0-1: ************
1-2: *************
2-3: *****
3-4: ******
4-5: ************
5-6: ************
6-7: ******
7-8: ******
8-9: ************
9-10: ************

See also