AENC/switchchain Changeset - 5da240b7cac5 · Centrum Wiskunde & Informatica (CWI)

Changeset - 5da240b7cac5

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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:

cpp/switchchain.cpp

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cpp/switchchain.cpp

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@@ @@ -63,8 +63,11 @@ class SwitchChain { @@
     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();
         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;
@@ @@ -132,6 +167,7 @@ int main() { @@
     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 << '{';
@@ @@ -160,19 +196,8 @@ int main() { @@
                         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) {
@@ @@ -181,6 +206,18 @@ int main() { @@
+                    }
+                }
                 //
                 // 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";
@@ @@ -190,10 +227,15 @@ int main() { @@
                 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 =
 ; // 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];
@@ @@ -221,7 +263,8 @@ int main() { @@
                 std::sort(ds.begin(), ds.end());
                 outfile << '{' << '{' << numVertices << ',' << tau << '}';
                 outfile << ',' << triangles << ',' << ds << '}' << std::flush;
                 outfile << ',' << triangles << ',' << ds;
                 outfile << ',' << greedyTriangles << '}' << std::flush;
+            }
+        }
+    }

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