AENC/switchchain Changeset - a410aaa16af7 · Centrum Wiskunde & Informatica (CWI)

Changeset - a410aaa16af7

Parent rev.

Child rev.

[Not reviewed]

0 3 0

Tom Bannink - 8 years ago 2017-07-03 14:37:10
tombannink@gmail.com

Remove spectrum computation from canonical switchchain

3 files changed with 28 insertions and 28 deletions:

cpp/graph_powerlaw.hpp

cpp/switchchain_canonical_properties.cpp

triangle_exponent_plots.m

0 comments (0 inline, 0 general)

cpp/graph_powerlaw.hpp

➞

Show inline comments

     // 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
+        // First check if the sum is even
         unsigned int sum = std::accumulate(ds.begin(), ds.end(), 0);
-        if (sum % 2) {
         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) {
                                     DegreeSequence &ds) {
     ds.resize(n);
     powerlaw_distribution degDist(tau, 1, n);
     degDist.getFixedDistribution(n, ds.begin());
     unsigned int sum = std::accumulate(ds.begin(), ds.end(), 0);
     if (sum % 2) {
         //TODO: Can we do this: ??
     if (sum % 2)
         ds.back()++;
+    }
     if (g.createFromDegreeSequence(ds))
         return;
     g.reset(n);
     std::cerr << "ERROR: Canonical ds is not graphical" << std::endl;
+}

cpp/switchchain_canonical_properties.cpp

➞

Show inline comments

@@ @@ -75,13 +75,14 @@ int main(int argc, char* argv[]) { @@
     outfile << "mixingTime: 50 * (50 - 30 (tau - 2)) n\n";
     outfile << "data:\n";
     outfile << "1: {n,tau}\n";
     outfile << "2: avgTriangles\n";
     outfile << "3: edges\n";
     outfile << "4: dstn\n";
     outfile << "5: { HH A, HH L, average A, average L }  where for each there is (average of) {lambda1 , lambda1 - lambda2, lambda1/lambda2}\n";
     //outfile << "5: { HH A, HH L, average A, average L }  where for each there is (average of) {lambda1 , lambda1 - lambda2, lambda1/lambda2}\n";
     outfile << "5: empty\n";
     outfile << "6: switching successrate after mixing\n";
     outfile << "7: initial HH triangles\n";
     outfile << "*)" << std::endl;
     // Mathematica does not accept normal scientific notation
     outfile << std::fixed;
@@ @@ -124,56 +125,59 @@ int main(int argc, char* argv[]) { @@
                 return {l1, l1 - l2, l1 / l2};
             };
             GraphSpectrum gs_start(g);
             GraphSpectrum gs(chain.g);
             HHAspectrum =
                 getSpectralValues(gs_start.computeAdjacencySpectrum());
             HHLspectrum =
                 getSpectralValues(gs_start.computeLaplacianSpectrum());
             HHAspectrum.fill(0);
             HHLspectrum.fill(0);
             //HHAspectrum =
             //    getSpectralValues(gs_start.computeAdjacencySpectrum());
             //HHLspectrum =
             //    getSpectralValues(gs_start.computeLaplacianSpectrum());
             long long trianglesTotal = 0;
             int movesDone = 0;
             avgAspectrum.fill(0);
             avgLspectrum.fill(0);
             for (int i = 0; i < measurements; ++i) {
                 for (int j = 0; j < measureSkip; ++j)
                     if (chain.doMove())
                         ++movesDone;
                 trianglesTotal += chain.g.countTriangles();
                 auto sA = getSpectralValues(gs.computeAdjacencySpectrum());
                 auto sL = getSpectralValues(gs.computeLaplacianSpectrum());
                 for (auto i = 0u; i < 3; ++i) {
                     avgAspectrum[i] += sA[i];
                     avgLspectrum[i] += sL[i];
+                }
                 //auto sA = getSpectralValues(gs.computeAdjacencySpectrum());
                 //auto sL = getSpectralValues(gs.computeLaplacianSpectrum());
                 //for (auto i = 0u; i < 3; ++i) {
                 //    avgAspectrum[i] += sA[i];
                 //    avgLspectrum[i] += sL[i];
                 //}
+            }
             float avgTriangles = float(trianglesTotal) / float(measurements);
             float successrate =
                 float(movesDone) / float(measurements * measureSkip);
             for (auto &f : avgAspectrum)
                 f /= float(measurements);
             for (auto &f : avgLspectrum)
                 f /= float(measurements);
             std::cout << "Measuring done." << std::flush;
+            std::cout << "Measuring done. " << std::flush;
             if (outputComma)
                 outfile << ',' << '\n';
             outputComma = true;
             outfile << '{' << '{' << numVertices << ',' << tau << '}';
             outfile << ',' << avgTriangles;
             outfile << ',' << g.edgeCount();
             outfile << ',' << getDSTN(ds);
             outfile << ',' << '{' << HHAspectrum;
             outfile << ',' << HHLspectrum;
             outfile << ',' << avgAspectrum;
             outfile << ',' << avgLspectrum;
             outfile << '}';
             outfile << ",{}";
             //outfile << ',' << '{' << HHAspectrum;
             //outfile << ',' << HHLspectrum;
             //outfile << ',' << avgAspectrum;
             //outfile << ',' << avgLspectrum;
             //outfile << '}';
             outfile << ',' << successrate;
             outfile << ',' << g.countTriangles();
             outfile << '}' << std::flush;
             std::cout << "Output done." << std::endl;
+        }

triangle_exponent_plots.m

➞

Show inline comments

 (* ::Subsection:: *)
 (*T(\[Tau]) including error bars*)
 (* For visual, shift the tau values slightly left or right to distinguish the two datasets *)
 tauValues=averagesGrouped[[All,1,1,1,2]];
 averagesExponentsErrorBars=Map[{{#[[1]],#[[2]]["BestFitParameters"][[2]]},ErrorBar[#[[2]]["ParameterConfidenceIntervals"][[2]]-#[[2]]["BestFitParameters"][[2]]]}&,
 Transpose[{tauValues,averagesFitsExtra}]];
+Transpose[{tauValues-0.005,averagesFitsExtra}]];
 mediansExponentsErrorBars=Map[{{#[[1]],#[[2]]["BestFitParameters"][[2]]},ErrorBar[#[[2]]["ParameterConfidenceIntervals"][[2]]-#[[2]]["BestFitParameters"][[2]]]}&,
 Transpose[{tauValues+0.01,mediansFitsExtra}]];
 plot2=Show[ErrorListPlot[{averagesExponentsErrorBars,mediansExponentsErrorBars},Joined->True,PlotMarkers->Automatic,Frame->True,FrameLabel->{"tau","triangle exponent"},PlotRange->{{2,3},{0,1.6}},ImageSize->300],Plot[3/2(3-tau),{tau,2,3},PlotStyle->{Dashed}]]
 Transpose[{tauValues+0.005,mediansFitsExtra}]];
 plot4=Show[ErrorListPlot[{averagesExponentsErrorBars,mediansExponentsErrorBars},Joined->True,PlotMarkers->Automatic,Frame->True,FrameLabel->{"tau","triangle exponent"},PlotRange->{{2,3},{0,1.6}},ImageSize->300],Plot[3/2(3-tau),{tau,2,3},PlotStyle->{Dashed}]]
 Export[NotebookDirectory[]<>"plots/triangle_exponent.pdf",plot2]

0 comments (0 inline, 0 general)