piecewise_linear_distribution 类

生成包含以线性变化的概率分布在每个区间中的不等宽区间的分段线性分布。

template<class RealType = double> class piecewise_linear_distribution { public:     // types     typedef RealType result_type;     struct param_type;     // constructor and reset functions     piecewise_linear_distribution();     template<class InputIteratorI, class InputIteratorW>     piecewise_linear_distribution(InputIteratorI firstI, InputIteratorI lastI, InputIteratorW firstW);     template<class UnaryOperation>     piecewise_linear_distribution(initializer_list<RealType> intervals, UnaryOperation weightfunc);     template<class UnaryOperation>     piecewise_linear_distribution(size_t count, RealType xmin, RealType xmax, UnaryOperation weightfunc);     explicit piecewise_linear_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     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; };

参数

• RealType
  浮点结果类型，默认为 double。 有关可能的类型，请参阅 <random>。

备注

此示例分布包含以线性变化的概率分布在每个区间中的不等宽区间。 有关其他示例分布的信息，请参阅 piecewise_constant_distribution 和 discrete_distribution。

下表链接到有关各个成员的文章：

piecewise_linear_distribution::piecewise_linear_distribution	piecewise_linear_distribution::intervals	piecewise_linear_distribution::param
piecewise_linear_distribution::operator()	piecewise_linear_distribution::densities	piecewise_linear_distribution::param_type

属性函数 intervals() 将返回 vector<RealType> 以及分布的存储区间集。

属性函数 densities() 将返回 vector<RealType> 以及每个区间集的存储密度，根据构造函数参数中提供的权重计算存储密度。

有关分布类及其成员的详细信息，请参阅 <random>。

示例

 

// compile with: /EHsc /W4
#include <random> 
#include <iostream>
#include <iomanip>
#include <string>
#include <map>

using namespace std;

void test(const int s) {

    // uncomment to use a non-deterministic generator
    // random_device rd;
    // mt19937 gen(rd());
    mt19937 gen(1701);

    // Three intervals, non-uniform: 0 to 1, 1 to 6, and 6 to 15
    vector<double> intervals{ 0, 1, 6, 15 };
    // weights determine the densities used by the distribution
    vector<double> weights{ 1, 5, 5, 10 };

    piecewise_linear_distribution<double> distr(intervals.begin(), intervals.end(), weights.begin());

    cout << endl;
    cout << "min() == " << distr.min() << endl;
    cout << "max() == " << distr.max() << endl;
    cout << "intervals (index: interval):" << endl;
    vector<double> i = distr.intervals();
    int counter = 0;
    for (const auto& n : i) {
        cout << fixed << setw(11) << counter << ": " << setw(14) << setprecision(10) << n << endl;
        ++counter;
    }
    cout << endl;
    cout << "densities (index: density):" << endl;
    vector<double> d = distr.densities();
    counter = 0;
    for (const auto& n : d) {
        cout << fixed << setw(11) << counter << ": " << setw(14) << setprecision(10) << n << endl;
        ++counter;
    }
    cout << endl;

    // generate the distribution as a histogram
    map<int, int> histogram;
    for (int i = 0; i < s; ++i) {
        ++histogram[distr(gen)];
    }

    // print results
    cout << "Distribution for " << s << " samples:" << endl;
    for (const auto& elem : histogram) {
        cout << setw(5) << elem.first << '-' << elem.first + 1 << ' ' << string(elem.second, ':') << endl;
    }
    cout << endl;
}

int main()
{
    int samples = 100;

    cout << "Use CTRL-Z to bypass data entry and run using default values." << endl;
    cout << "Enter an integer value for the sample count: ";
    cin >> samples;

    test(samples);
}

输出

要求

标头：<random>

命名空间: std

请参见

参考

<random>