return g.exchangeEdges(e1index, e2index, switchType);

    }

    Graph g;

    std::mt19937 mt;

    std::uniform_int_distribution<> edgeDistribution;

    //std::uniform_int_distribution<> permutationDistribution;

    std::bernoulli_distribution permutationDistribution;

};

double getProperty(const DegreeSequence& ds) {

    std::vector<std::vector<double>> vals(ds.size());

    for (auto& v : vals) {

        v.resize(ds.size(), 0);

    }

    auto D = 0u;

    for (auto d : ds)

        D += d;

    double factor = 1.0 / double(D);

    for (auto i = 0u; i < ds.size(); ++i) {

        for (auto j = i + 1; j < ds.size(); ++j) {

        }

    }

    double result = 0.0;

    for (auto i = 0u; i < ds.size(); ++i) {

        for (auto j = i + 1; j < ds.size(); ++j) {

            for (auto k = j + 1; k < ds.size(); ++k) {

                result += vals[i][j] * vals[j][k] * vals[i][k];

            }

        }

    }

    return result;

}

int main() {

    // Generate a random degree sequence

    std::mt19937 rng(std::random_device{}());

    // Goal:

    // Degrees follow a power-law distribution with some parameter tau

    // Expect:  #tri = const * n^{ something }

    // The goal is to find the 'something' by finding the number of triangles

    // for different values of n and tau

    float tauValues[] = {2.1f, 2.5f, 2.9f};