// Purge anything with degree zero

            // Be careful with invalidating the other iterator!

            // Degree of u is always greater or equal to the degree of v

            if (dmax == 1) {

                // Remove both

                // Erasure invalidates all iterators AFTER the erased one

                if (vIter > uIter) {

                    degrees.erase(vIter);

                    degrees.erase(uIter);

                } else {

                    degrees.erase(uIter);

                    degrees.erase(vIter);

                }

            } else {

                // Remove only v if it reaches zero

                uIter->first--;

                vIter->first--;

                if (vIter->first == 0)

                    degrees.erase(vIter);

            }

            //degrees.erase(std::remove_if(degrees.begin(), degrees.end(),

            //                             [](auto x) { return x.first == 0; }));

        }

    }

    return true;

}

int main(int argc, char* argv[]) {

    // 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[] = {2.5f};

    float tauValues[] = {2.1f, 2.2f, 2.3f, 2.4f, 2.5f, 2.6f, 2.7f, 2.8f, 2.9f};

    Graph g;

    Graph g1;

    Graph g2;

    std::ofstream outfile;

    if (argc >= 2)

        outfile.open(argv[1]);

    else   

    if (!outfile.is_open()) {

        std::cout << "ERROR: Could not open output file.\n";

        return 1;

    }

    outfile << '{';

    bool outputComma = false;

    for (int numVertices = 1000; numVertices <= 1000; numVertices += 1000) {

        for (float tau : tauValues) {

            DegreeSequence ds(numVertices);

            powerlaw_distribution degDist(tau, 1, numVertices);

            //std::poisson_distribution<> degDist(12);

            // For a single n,tau take samples over several instances of

            // the degree distribution.

            // 500 samples seems to give reasonable results

                // Generate a graph

                // might require multiple tries

                for (int i = 1; ; ++i) {

                    std::generate(ds.begin(), ds.end(),

                                  [&degDist, &rng] { return degDist(rng); });

                    // First make the sum even

                    unsigned int sum = std::accumulate(ds.begin(), ds.end(), 0);

                    if (sum % 2) {

                        continue;

                        // Can we do this: ??

                        ds.back()++;

                    }

                    if (g.createFromDegreeSequence(ds))

                        break;

                    // When 10 tries have not worked, output a warning

                    if (i % 10 == 0) {

                        std::cerr << "Warning: could not create graph from "

                                     "degree sequence. Trying again...\n";

                    }

                }

                SwitchChain chain;

                if (!chain.initialize(g)) {

                    std::cerr << "Could not initialize Markov chain.\n";

                    return 1;

                }

                std::cout << "Running n = " << numVertices << ", tau = " << tau

                          << ". \t" << std::flush;

                //int mixingTime = (32.0f - 26.0f*(tau - 2.0f)) * numVertices; //40000;

                //constexpr int measurements = 50;

                //constexpr int measureSkip =

                //    200; // Take a sample every ... steps

                int mixingTime = 0;

                constexpr int measurements = 500;

                constexpr int measureSkip = 100;

                int movesTotal = 0;

                int movesSuccess = 0;

                int triangles[measurements];

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

                    ++movesTotal;

                    if (chain.doMove()) {

                        ++movesSuccess;

                    }

                }

                std::vector<int> successRates;

                successRates.reserve(measurements);

                int successrate = 0;

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

                    for (int j = 0; j < measureSkip; ++j) {

                        ++movesTotal;

                        if (chain.doMove()) {

                            ++movesSuccess;

                            ++successrate;

                        }

                    }

                    triangles[i] = chain.g.countTriangles();

                    successRates.push_back(successrate);

                    successrate = 0;

                }

                std::cout << '('

                          << 100.0f * float(movesSuccess) / float(movesTotal)

                          << "% successrate). " << std::flush;

                // std::cout << std::endl;

                if (outputComma)

                    outfile << ',' << '\n';

                outputComma = true;

                outfile << '{' << '{' << numVertices << ',' << tau << '}';

                outfile << ',' << successRates;

                outfile << '}' << std::flush;

                std::cout << std::endl;

            }

        }

    }

    outfile << '}';

    return 0;

}