Simulation of Genetic Drift Gaming Project in C++

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#include <iostream>
#include <vector>
#include <cstdlib>
#include <ctime>
#include <algorithm>

const int POPULATION_SIZE = 100;
const int GENERATIONS = 50;
const int INITIAL_A = 50;  // Initial number of A alleles
const int INITIAL_B = 50;  // Initial number of B alleles

class Population {
public:
    Population() {
        alleles.resize(POPULATION_SIZE, 'A');
        std::fill(alleles.begin(), alleles.begin() + INITIAL_A, 'A');
        std::fill(alleles.begin() + INITIAL_A, alleles.end(), 'B');
        std::random_shuffle(alleles.begin(), alleles.end());
    }

    void simulateGeneration() {
        std::vector<char> newAlleles(POPULATION_SIZE);
        for (int i = 0; i < POPULATION_SIZE; ++i) {
            newAlleles[i] = alleles[std::rand() % POPULATION_SIZE];
        }
        alleles = newAlleles;
    }

    void printStatistics() const {
        int countA = std::count(alleles.begin(), alleles.end(), 'A');
        int countB = std::count(alleles.begin(), alleles.end(), 'B');
        std::cout << "A alleles: " << countA << ", B alleles: " << countB << '\n';
    }

private:
    std::vector<char> alleles;
};

int main() {
    std::srand(static_cast<unsigned>(std::time(0)));

    Population population;

    std::cout << "Initial population:\n";
    population.printStatistics();

    for (int generation = 1; generation <= GENERATIONS; ++generation) {
        population.simulateGeneration();
        std::cout << "Generation " << generation << ":\n";
        population.printStatistics();
    }

    return 0;
}

#include <iostream>

#include <vector>

#include <cstdlib>

#include <ctime>

#include <algorithm>

const int POPULATION_SIZE = 100;

const int GENERATIONS = 50;

const int INITIAL_A = 50; // Initial number of A alleles

const int INITIAL_B = 50; // Initial number of B alleles

class Population {

public:

Population() {

alleles.resize(POPULATION_SIZE, 'A');

std::fill(alleles.begin(), alleles.begin() + INITIAL_A, 'A');

std::fill(alleles.begin() + INITIAL_A, alleles.end(), 'B');

std::random_shuffle(alleles.begin(), alleles.end());

}

void simulateGeneration() {

std::vector<char> newAlleles(POPULATION_SIZE);

for (int i = 0; i < POPULATION_SIZE; ++i) {

newAlleles[i] = alleles[std::rand() % POPULATION_SIZE];

}

alleles = newAlleles;

}

void printStatistics() const {

int countA = std::count(alleles.begin(), alleles.end(), 'A');

int countB = std::count(alleles.begin(), alleles.end(), 'B');

std::cout << "A alleles: " << countA << ", B alleles: " << countB << '\n';

}

private:

std::vector<char> alleles;

};

int main() {

std::srand(static_cast<unsigned>(std::time(0)));

Population population;

std::cout << "Initial population:\n";

population.printStatistics();

for (int generation = 1; generation <= GENERATIONS; ++generation) {

population.simulateGeneration();

std::cout << "Generation " << generation << ":\n";

population.printStatistics();

}

return 0;

}

Explanation

Class Definition (Population):
- Private Members:
  - alleles: A vector storing the alleles in the population (‘A’ or ‘B’).
- Public Methods:
  - Population(): Constructor initializes the population with INITIAL_A ‘A’ alleles and INITIAL_B
    
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    ‘B’ alleles. Shuffles the alleles to randomize their order.
  - void simulateGeneration(): Simulates genetic drift by randomly selecting alleles to form the new generation. Each individual in the new generation is randomly chosen from the current population.
  - void printStatistics() const: Prints the count of ‘A’ and ‘B’ alleles in the current population.
main Function:
- Initializes the random seed with the current time.
- Creates a Population object to start the simulation.
- Prints the initial population statistics.
- Simulates multiple generations, printing the allele statistics for each generation.

Explanation

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