#include <algorithm>
#include <cmath>
#include <functional>
#include <vector>
#include <iostream>
#include <random>
#include <iomanip>
using namespace std;


double MathFunction(double x, double y) {
  return 1 / sqrt(0.01 + x * x + y * y);
}

double randomPoint(int a, int b) {
  random_device rd;
  mt19937 gen(rd());
  uniform_real_distribution<> dis(a, b);
  return dis(gen);
}

void generateIndividual(pair<double,double>& individual,int x1,int x2,int y1,int y2){
  individual.first = randomPoint(x1,x2);
  individual.second = randomPoint(y1,y2);
}

pair<double, double> generateIndividual(int x1, int x2, int y1, int y2) {
  pair<double, double> individual;
  individual.first = randomPoint(x1, x2);
  individual.second = randomPoint(y1, y2);
  return individual;
}

double maxValue(const vector<pair<double, double>>& population) {
  vector<double> result;
  result.reserve(population.size());
  for (auto& i : population) {
    result.push_back(MathFunction(i.first, i.second));
  }
  return *max_element(result.begin(), result.end());
}

double averageValue(const vector<pair<double, double>>& population) {
  vector<double> result;
  result.reserve(population.size());
  for (auto& i : population) {
    result.push_back(MathFunction(i.first, i.second));
  }
  double sum = 0;
  for (auto& i : result) {
    sum += i;
  }
  return sum / result.size();
}

void print(vector<pair<double, double>> population, size_t i) {
  cout << setw(4) << i << setw(11) << fixed << setprecision(6) << population[0].first << setw(11) << population[0].second << setw(11) << MathFunction(population[0].first, population[0].second) << setw(13) << maxValue(population) << setw(13) << averageValue(population) << endl;
  for (size_t j = 1; j < population.size(); ++j) {
    cout << setw(15) << fixed << setprecision(6) << population[j].first << setw(11) << population[j].second << setw(11) << MathFunction(population[j].first, population[j].second) << endl;
  }
  cout << endl;
}

vector<size_t> Roulette(vector<pair<double, double>>& points) {
  double sum = 0;
  for (auto value : points) {
    sum += MathFunction(value.first, value.second);
  }

  vector<size_t> answer;

  for (auto value : points) {
    answer.push_back(MathFunction(value.first, value.second) / sum * 100);
  }
  return answer;
}

size_t CheckIndex(vector<size_t>& prob, double p) {
  size_t a = 0;
  for (size_t i = 0; i < prob.size(); i++) {
    a += prob[i];
    if (a > p) return i;
  }
  return -1;
}

bool func_sort(pair<double, double> pair1, pair<double, double> pair2) {
  return (MathFunction(pair1.first, pair1.second) > MathFunction(pair2.first, pair2.second));
}

vector<pair<double, double>> Crossover(vector<size_t> prob,
                                                 vector<pair<double, double>>& points){

  vector<pair<double, double>> answer;
  for (auto value : points) {
    random_device rd;
    mt19937 gen(rd());
    uniform_real_distribution<double> probability(0, 100);
    auto p = static_cast<double>(100 - probability(gen));

    size_t index = CheckIndex(prob, p);
    if (index != -1) {
      answer.push_back(make_pair(points[index].first, value.second));
      answer.push_back(make_pair(value.first, points[index].second));
    }

  }


  sort(answer.begin(), answer.end(), func_sort);

  answer.resize(4);
  return answer;
}

void Mutation(vector<pair<double, double>>& points) {
  random_device rd;
  mt19937 gen(rd());
  uniform_real_distribution<double> probability(0, 100);
  auto p = static_cast<size_t>(probability(gen));

  for (auto value : points) {
    if (p > 25) {
      uniform_real_distribution<double> probability(0, 100);
      auto p = static_cast<size_t>(probability(gen));
      if (p > 50) {
        value.first += 0.1;
        value.second += 0.1;
      }
      else {
        value.first -= 0.1;
        value.second -= 0.1;
      }
    }
  }
}

void genetic(int x1, int x2, int y1, int y2) {
  pair<double, double> individual;
  vector<pair<double, double>> population;
  // Генерация начальной популяции (4 рандомных особи)
  for (size_t i = 0; i < 4; ++i) {
    individual = generateIndividual(x1, x2, y1, y2);
    population.push_back(individual);
  }
  cout << setw(4) << "N" << setw(11) << "X" << setw(11) << "Y" << setw(11) << " FIT " << setw(13) << "MAX  " << setw(13) << "Average" << endl;

  for (size_t i = 0; i < 10; ++i) {
    print(population, i);
    population = Crossover(Roulette(population), population);
    Mutation(population);
  }
}

int main() {
  genetic(-1, 1, -1, 1);

  return 0;
}