Question

自从我处理这个问题以来已经有几个小时了。我想知道是否有人可以指出我做错了什么，如果可能的话 - 如何解决它。基本上，我只是尝试生成n个对象对，并将它们存储到vector<pair<Foo, Foo>>中。该算法涉及随机数生成器。我使用STL <random>及其组件，如m19937，uniform_real_distribution和uniform_int_distribution。下面是我试图做的简化版本，代表我手边的情况。第二个循环总是缩短。但是，我没有看到原因。从本质上讲，我从来没有看到程序完全执行。最后两条消息从未显示过。

程序

#include <iostream>
#include <vector>
#include <random>
#include <utility>

// utility
using std::pair;

// random
using std::mt19937;
using std::uniform_int_distribution;
using std::uniform_real_distribution;

// iostream
using std::cout;
using std::endl;

// vector
using std::vector;

class Event{
private:
  double x, y;
public:
  Event(const double X, const double Y);
};

Event::Event(const double X, const double Y): x(X), y(Y){}

int main(){
  cout << "Initializing storage..." << endl;
  vector<Event> population;
  vector<pair<Event,Event>> selection;

  cout << "Initializing necessary member variables..." << endl;
  const unsigned int SEED = 14112017;
  const unsigned int MAX_ITERATIONS = 10000;

  const double MIN = 1;
  const double MAX = 10000;

  mt19937 engine(SEED);

  cout << "Generating the initial population..." << endl;
  uniform_real_distribution<> real_distribution(MIN, MAX);
  for(unsigned int i = 0; i < MAX_ITERATIONS; ++i){
    double x = real_distribution(engine);
    double y = real_distribution(engine);

    Event event(x, y);

    population.push_back(event);
  }
  cout << "Success! The initial population has been generated successfully" << endl;

  population.shrink_to_fit();

  cout << "Starting the selection process..." << endl;
  unsigned int random = 0;
  uniform_int_distribution<> int_distribution(MIN, MAX);
  for(unsigned int i = 0; i < MAX_ITERATIONS; ++i){
    random = int_distribution(engine);
    Event event_x = population.at(random);

    random = int_distribution(engine);
    Event event_y = population.at(random);

    pair<Event, Event> bound(event_x, event_y);

    selection.push_back(bound);
  }
  cout << "Success! The selection process has been completed successfully" << endl;

  selection.shrink_to_fit();

  cout << "population size: " << population.size() << endl;
  cout << "selection size: " << selection.size() << endl;

  return 0;
}

我使用cygwins C ++编译器编译上面的代码，然后在命令提示符下执行代码。操作系统是Windows 10 x64。该盒子有32 GB的内存。

Answer 1

uniform_int_distribution的构造函数如下：

explicit uniform_int_distribution( IntType a = 0,
    IntType b = std::numeric_limits<IntType>::max() );

默认情况下，它返回一个整数，该整数涵盖该类型的所有正值。范围包括第二个参数的值。如果不这样做，那么指定我们想要所有正整数将是麻烦的。

~~cppreference.com没有记录，但C ++标准确实：~~ Thanks @Cubbi
这记录在on cppreference.com或C ++标准中：

26.5.8.2.1班级模板uniform_int_distribution [rand.dist.uni.int]
  1 uniform_int_distribution随机数   分布产生随机整数i，a≤i≤b，分布   根据常数离散概率函数
   [...]
  // constructors and reset functions explicit uniform_int_distribution(IntType a = 0, IntType b = numeric_limits<IntType>::max());

下面：

  uniform_int_distribution<> int_distribution(MIN, MAX);
  for(unsigned int i = 0; i < MAX_ITERATIONS; ++i){
    random = int_distribution(engine);
    Event event_x = population.at(random);

    random = int_distribution(engine);
    Event event_y = population.at(random);

random可以取值MAX，这超出population向量的范围。

程序不会崩溃也不会完全执行

1 个答案: