#include <iostream>
#include <iterator>
#include <algorithm>
#include <random>
#include <fstream>

using namespace std;

template <typename T>
void rand_perm(T data[], int N)
{
    default_random_engine dre;
    dre.seed(time(NULL));
    for (int i = 0; i < N; i++)
    {
        uniform_int_distribution<int> uid(i, N - 1);
        swap(data[i], data[uid(dre)]);
    }
}

void uni(int n)
{
    default_random_engine dre;
    dre.seed(time(NULL));
    uniform_real_distribution<float> uid;
    ofstream file;
    file.open("uni.csv");
    for (int i = 0; i < n; i++)
    {
        file << uid(dre) << "\n";
    }
    file.close();
}

void bin(int n)
{
    default_random_engine dre;
    dre.seed(time(NULL));
    binomial_distribution<int> bd(1000, 0.5);
    ofstream file;
    file.open("bin.csv");
    for (int i = 0; i < n; i++)
    {
        file << bd(dre) << "\n";
    }
    file.close();
}

void norm(int n)
{
    default_random_engine dre;
    dre.seed(time(NULL));
    normal_distribution<double> nd;
    ofstream file;
    file.open("norm.csv");
    for (int i = 0; i < n; i++)
    {
        file << nd(dre) << "\n";
    }
    file.close();
}

int main()
{
    int tab[10];
    for (int i = 0; i < 10; i++)
    {
        tab[i] = i;
    }
    rand_perm(tab, size(tab));
    for (int i = 0; i < 10; i++)
    {
        cout << tab[i] << " ";
    }
    cout<<endl;
    uni(1000);
    bin(1000);
    norm(1000);
}
/*
 Wchodzisz na google colab wklejasz kod. Wchodzisz w lewy pasek -> Files -> wrzucasz pliki z cpp i wywolujesz make_plot(uni.csv itd).
import pandas as pd
import seaborn as sns

def make_plot(filename):
    data = pd.read_csv(filename)
    return sns.distplot(data, hist=True, kde=True,
             bins=int(300), color = 'blue',
             hist_kws={'edgecolor':'black'})

*/