Changeset - 5da240b7cac5
[Not reviewed]
0 1 0
Tom Bannink - 8 years ago 2017-04-03 16:57:22
tombannink@gmail.com
Add GCM1 code
1 file changed with 87 insertions and 44 deletions:
0 comments (0 inline, 0 general)
cpp/switchchain.cpp
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@@ -54,93 +54,129 @@ class SwitchChain {
 
        // 3) e1.u - e2.v and e1.v - e2.u
 
        bool switchType = permutationDistribution(mt);
 
        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;
 
};
 

	
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, auto& rng) {
 
    // Same as Havel-Hakimi but instead of pairing up with the highest ones
 
//
 
// Assumes degree sequence does NOT contain any zeroes!
 
//
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, auto& rng, bool method2) {
 
    // Similar to Havel-Hakimi but instead of pairing up with the highest ones
 
    // that remain, simply pair up with random ones
 
    unsigned int n = ds.size();
 

	
 
    // degree, vertex index
 
    std::vector<std::pair<unsigned int, unsigned int>> degrees(n);
 
    for (unsigned int i = 0; i < n; ++i) {
 
        degrees[i].first = ds[i];
 
        degrees[i].second = i;
 
    }
 
    std::vector<decltype(degrees.begin())> available;
 
    available.reserve(n);
 

	
 
    // Clear the graph
 
    g.reset(n);
 

	
 
    std::uniform_int_distribution<> distr(1, n - 1);
 

	
 
    while (!degrees.empty()) {
 
        std::shuffle(degrees.begin(), degrees.end(), rng);
 
        // Get the highest degree:
 
        // If there are multiple highest ones, we pick a random one,
 
        // ensured by the shuffle.
 
        // The shuffle is needed anyway for the remaining part
 
        unsigned int dmax = 0;
 
        unsigned int u = 0;
 
        auto maxIter = degrees.begin();
 
        auto uIter = degrees.begin();
 
        for (auto iter = degrees.begin(); iter != degrees.end(); ++iter) {
 
            if (iter->first >= dmax) {
 
                dmax = iter->first;
 
                u = iter->second;
 
                maxIter = iter;
 
                uIter = iter;
 
            }
 
        }
 
        // Take the highest degree out of the vector
 
        degrees.erase(maxIter);
 

	
 
        available.clear();
 
        for (auto iter = degrees.begin(); iter != degrees.end(); ++iter) {
 
            if (iter->first)
 
                available.push_back(iter);
 
        }
 

	
 
        if (dmax > available.size())
 
        if (dmax > degrees.size() - 1)
 
            return false;
 

	
 
        std::shuffle(available.begin(), available.end(), rng);
 

	
 
        // Now assign randomly to the remaining vertices
 
        // Pick 'cmax' distinct integers between 1 and degrees.size()
 
        for (unsigned int i = 0; i < dmax; ++i) {
 
            if (!g.addEdge({u,available[i]->second})) {
 
                std::cerr << "ERROR. Could not add edge in greedy configuration model.\n";
 
        unsigned int u = uIter->second;
 

	
 
        if (method2) {
 
            // Take the highest degree out of the vector
 
            degrees.erase(uIter);
 

	
 
            // Now assign randomly to the remaining vertices
 
            // Since its shuffled, we can pick the first 'dmax' ones
 
            auto vIter = degrees.begin();
 
            while (dmax--) {
 
                if (vIter->first == 0)
 
                    std::cerr << "ERROR in GCM2.\n";
 
                if (!g.addEdge({u, vIter->second}))
 
                    std::cerr << "ERROR. Could not add edge in GCM2.\n";
 
                vIter->first--;
 
                if (vIter->first == 0)
 
                    vIter = degrees.erase(vIter);
 
                else
 
                    vIter++;
 
            }
 
        } else {
 
            // Pair with a random vertex that is not u itself
 
            std::uniform_int_distribution<> distr(0, degrees.size() - 2);
 
            auto vIter = degrees.begin() + distr(rng);
 
            if (vIter == uIter)
 
                vIter++;
 
            // pair u to v
 
            if (vIter->first == 0)
 
                std::cerr << "ERROR in GCM1.\n";
 
            if (!g.addEdge({uIter->second, vIter->second}))
 
                std::cerr << "ERROR. Could not add edge in GCM1.\n";
 
            // 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
 
                if (vIter > uIter) {
 
                    degrees.erase(vIter);
 
                    degrees.erase(uIter);
 
                } else {
 
                    degrees.erase(uIter);
 
                    degrees.erase(vIter);
 
                }
 
            } else {
 
                // Remove only v if it reaches zero
 
                vIter->first--;
 
                if (vIter->first == 0)
 
                    degrees.erase(vIter);
 
            }
 
            available[i]->first--;
 
            //degrees.erase(std::remove_if(degrees.begin(), degrees.end(),
 
            //                             [](auto x) { return x.first == 0; }));
 
        }
 
    }
 
    return true;
 
}
 

	
 
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, 2.2f, 2.3f, 2.4f, 2.5f, 2.6f, 2.7f, 2.8f};
 

	
 
    Graph g;
 
    Graph g2;
 

	
 
    std::ofstream outfile("graphdata.m");
 
    outfile << '{';
 
    bool outputComma = false;
 

	
 
    for (int numVertices = 200; numVertices <= 1000; numVertices += 100) {
 
        for (float tau : tauValues) {
 

	
 
            DegreeSequence ds(numVertices);
 
            powerlaw_distribution degDist(tau, 1, numVertices);
 
            //std::poisson_distribution<> degDist(12);
 

	
 
@@ -151,58 +187,64 @@ int main() {
 
                // 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()++;
 
                    }
 

	
 
                    // Option 1:
 
                    if (g.createFromDegreeSequence(ds)) {
 
                        // Test option 2:
 
                        //int good = 0;
 
                        //for (int i = 0; i < 100; ++i) {
 
                        //    if (greedyConfigurationModel(ds, g, rng))
 
                        //        ++good;
 
                        //}
 
                        //std::cerr << "Greedy configuration model success rate: " << good << "%\n";
 

	
 
                        //g.createFromDegreeSequence(ds);
 
                    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";
 
                    }
 
                }
 

	
 
                //
 
                // Test the greedy configuration model success rate
 
                //
 
                std::vector<int> greedyTriangles;
 
                int successrate = 0;
 
                for (int i = 0; i < 100; ++i) {
 
                    if (greedyConfigurationModel(ds, g2, rng, true)) {
 
                        ++successrate;
 
                        greedyTriangles.push_back(g2.countTriangles());
 
                    }
 
                }
 

	
 
                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 = (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 = 10000;
 
                constexpr int measureSkip = 1;
 

	
 

	
 
                int movesDone = 0;
 

	
 
                int triangles[measurements];
 

	
 
                for (int i = 0; i < mixingTime; ++i) {
 
                    if (chain.doMove())
 
                        ++movesDone;
 
                }
 
                for (int i = 0; i < measurements; ++i) {
 
                    for (int j = 0; j < measureSkip; ++j)
 
                        if (chain.doMove())
 
                            ++movesDone;
 
@@ -212,19 +254,20 @@ int main() {
 
                std::cout << movesDone << '/' << mixingTime + measurements * measureSkip
 
                          << " moves succeeded ("
 
                          << 100.0f * float(movesDone) /
 
                                 float(mixingTime + measurements * measureSkip)
 
                          << "%)." << std::endl;
 

	
 
                if (outputComma)
 
                    outfile << ',';
 
                outputComma = true;
 

	
 
                std::sort(ds.begin(), ds.end());
 
                outfile << '{' << '{' << numVertices << ',' << tau << '}';
 
                outfile << ',' << triangles << ',' << ds << '}' << std::flush;
 
                outfile << ',' << triangles << ',' << ds;
 
                outfile << ',' << greedyTriangles << '}' << std::flush;
 
            }
 
        }
 
    }
 
    outfile << '}';
 
    return 0;
 
}
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