// CMSC 341 - Spring 2024 - Project 1
#include "fastq.h"
#include <random>
#include <vector>
#include <algorithm>
const int MINID = 1000;     // dealer ID
const int MAXID = 9999;     // dealer ID
enum RANDOM {UNIFORMINT, UNIFORMREAL, NORMAL, SHUFFLE};
class Random {
public:
    Random(int min, int max, RANDOM type=UNIFORMINT, int mean=50, int stdev=20) : m_min(min), m_max(max), m_type(type)
    {
        if (type == NORMAL){
            //the case of NORMAL to generate integer numbers with normal distribution
            m_generator = std::mt19937(m_device());
            //the data set will have the mean of 50 (default) and standard deviation of 20 (default)
            //the mean and standard deviation can change by passing new values to constructor 
            m_normdist = std::normal_distribution<>(mean,stdev);
        }
        else if (type == UNIFORMINT) {
            //the case of UNIFORMINT to generate integer numbers
            // Using a fixed seed value generates always the same sequence
            // of pseudorandom numbers, e.g. reproducing scientific experiments
            // here it helps us with testing since the same sequence repeats
            m_generator = std::mt19937(10);// 10 is the fixed seed value
            m_unidist = std::uniform_int_distribution<>(min,max);
        }
        else if (type == UNIFORMREAL) { //the case of UNIFORMREAL to generate real numbers
            m_generator = std::mt19937(10);// 10 is the fixed seed value
            m_uniReal = std::uniform_real_distribution<double>((double)min,(double)max);
        }
        else { //the case of SHUFFLE to generate every number only once
            m_generator = std::mt19937(m_device());
        }
    }
    void setSeed(int seedNum){
        // we have set a default value for seed in constructor
        // we can change the seed by calling this function after constructor call
        // this gives us more randomness
        m_generator = std::mt19937(seedNum);
    }

    void getShuffle(vector<int> & array){
        // the user program creates the vector param and passes here
        // here we populate the vector using m_min and m_max
        for (int i = m_min; i<=m_max; i++){
            array.push_back(i);
        }
        shuffle(array.begin(),array.end(),m_generator);
    }

    void getShuffle(int array[]){
        // the param array must be of the size (m_max-m_min+1)
        // the user program creates the array and pass it here
        vector<int> temp;
        for (int i = m_min; i<=m_max; i++){
            temp.push_back(i);
        }
        std::shuffle(temp.begin(), temp.end(), m_generator);
        vector<int>::iterator it;
        int i = 0;
        for (it=temp.begin(); it != temp.end(); it++){
            array[i] = *it;
            i++;
        }
    }

    int getRandNum(){
        // this function returns integer numbers
        // the object must have been initialized to generate integers
        int result = 0;
        if(m_type == NORMAL){
            //returns a random number in a set with normal distribution
            //we limit random numbers by the min and max values
            result = m_min - 1;
            while(result < m_min || result > m_max)
                result = m_normdist(m_generator);
        }
        else if (m_type == UNIFORMINT){
            //this will generate a random number between min and max values
            result = m_unidist(m_generator);
        }
        return result;
    }

    double getRealRandNum(){
        // this function returns real numbers
        // the object must have been initialized to generate real numbers
        double result = m_uniReal(m_generator);
        // a trick to return numbers only with two deciaml points
        // for example if result is 15.0378, function returns 15.03
        // to round up we can use ceil function instead of floor
        result = std::floor(result*100.0)/100.0;
        return result;
    }
    
    private:
    int m_min;
    int m_max;
    RANDOM m_type;
    std::random_device m_device;
    std::mt19937 m_generator;
    std::normal_distribution<> m_normdist;//normal distribution
    std::uniform_int_distribution<> m_unidist;//integer uniform distribution
    std::uniform_real_distribution<double> m_uniReal;//real uniform distribution

};
class Tester{

};
int main(){
    Random RndID(MINID,MAXID);
    int bufferSize = 2;
    vector<int> tempStorage;
    try{
        cout << "\nHere is an example of enqueue results for 12 data points:" << endl;
        ListBuffer bufferList(bufferSize);
        for (int i=12;i>0;i--){
            int data = RndID.getRandNum();
            bufferList.enqueue(data);
            tempStorage.push_back(data);
        }
        bufferList.dump();
        cout << "\nHere is an example of dequeue results for 5 data points:" << endl;
        for(int j=1;j<=5;j++){
            int data = bufferList.dequeue();
            cout << j << " - The dequeued data point is " << data << endl;
            if (tempStorage.front() != data){
                cout << "Error: expected " << tempStorage.front() << "dequeued " << data << endl; 
            }
            tempStorage.erase(tempStorage.begin()); 
        }
        cout << endl;
        bufferList.dump();
    }
    catch(underflow_error &e){
            cout << e.what() << endl << endl;
    }
    return 0;
}