Changeset - e65372736dde
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0 7 3
Tom Bannink - 8 years ago 2017-06-02 11:50:31
tom.bannink@cwi.nl
Merge branch 'master' of https://scm.cwi.nl/AC/switchchain
7 files changed with 105 insertions and 45 deletions:
cpp/Makefile
2
1
cpp/switchchain.cpp
57
33
cpp/switchchain_initialtris.cpp
2
1
plots/avgtris_n.pdf
bin+new file
plots/triangle_exponent.pdf
bin+new file
triangle_analysis.m
34
6
triangle_exponent_plots.m
10
4
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cpp/Makefile
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#CXX=clang++
 

			




	
	
	
		
 
INCLUDES += -I.

			




	
	
	
		
 

			




	
	
	
		
 
CXXFLAGS += -std=c++14 -O3 -Wall -Wextra -Wfatal-errors -Wno-deprecated-declarations $(INCLUDES)

			




	
	
	
		
 
CXXFLAGS += -std=c++14 -O3 -Wall -Wextra -Wfatal-errors -Werror -pedantic -Wno-deprecated-declarations $(INCLUDES)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
all: switchchain switchchain_exponent switchchain_initialtris

			




        

    


    
    

    

        

                

                    cpp/switchchain.cpp
                

                

                  
                      
                        

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@@ -73,8 +73,8 @@ void getTriangleDegrees(const Graph& g) {

			




	
	
	
		
 
            for (unsigned int j = i + 1; j < v.size(); ++j) {

			




	
	
	
		
 
                if (g.hasEdge({v[i], v[j]})) {

			




	
	
	
		
 
                    ++triangles;

			




	
	
	
		
 
                    std::array<std::size_t, 3> ds = {v.size(), adj[v[i]].size(),

			




	
	
	
		
 
                                                     adj[v[j]].size()};

			




	
	
	
		
 
                    std::array<std::size_t, 3> ds = {{v.size(), adj[v[i]].size(),

			




	
	
	
		
 
                                                     adj[v[j]].size()}};

			




	
	
	
		
 
                    std::sort(ds.begin(), ds.end());

			




	
	
	
		
 
                    trids.push_back(ds);

			




	
	
	
		
 
                }

			




	
	
		
 
@@ -90,7 +90,8 @@ void getTriangleDegrees(const Graph& g) {

			




	
	
	
		
 
//

			




	
	
	
		
 
// method2 = true  -> take highest degree and finish its pairing completely

			




	
	
	
		
 
// method2 = false -> take new highest degree after every pairing

			




	
	
	
		
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, auto& rng, bool method2) {

			




	
	
	
		
 
template <typename RNG>

			




	
	
	
		
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, RNG& 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();

			




	
	
		
 
@@ -194,7 +195,7 @@ bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, auto& rng, bool meth

			




	
	
	
		
 
    return true;

			




	
	
	
		
 
}

			




	
	
	
		
 

			




	
	
	
		
 
int main() {

			




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

			




	
	
	
		
 
    // Generate a random degree sequence

			




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

			




	
	
	
		
 

			




	
	
		
 
@@ -209,11 +210,22 @@ int main() {

			




	
	
	
		
 
    Graph g1;

			




	
	
	
		
 
    Graph g2;

			




	
	
	
		
 

			




	
	
	
		
 
    std::ofstream outfile("graphdata.m");

			




	
	
	
		
 
    std::ofstream outfile;

			




	
	
	
		
 

			




	
	
	
		
 
    if (argc >= 2)

			




	
	
	
		
 
        outfile.open(argv[1]);

			




	
	
	
		
 
    else   

			




	
	
	
		
 
        outfile.open("graphdata.m");

			




	
	
	
		
 

			




	
	
	
		
 
    if (!outfile.is_open()) {

			




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

			




	
	
	
		
 
        return 1;

			




	
	
	
		
 
    }

			




	
	
	
		
 

			




	
	
	
		
 
    outfile << '{';

			




	
	
	
		
 
    bool outputComma = false;

			




	
	
	
		
 

			




	
	
	
		
 
    for (int numVertices = 200; numVertices <= 2000; numVertices += 400) {

			




	
	
	
		
 
    for (int numVertices = 500; numVertices <= 500; numVertices += 1000) {

			




	
	
	
		
 
        for (float tau : tauValues) {

			




	
	
	
		
 

			




	
	
	
		
 
            DegreeSequence ds(numVertices);

			




	
	
		
 
@@ -223,7 +235,7 @@ int main() {

			




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

			




	
	
	
		
 
            // the degree distribution.

			




	
	
	
		
 
            // 500 samples seems to give reasonable results

			




	
	
	
		
 
            for (int degreeSample = 0; degreeSample < 1; ++degreeSample) {

			




	
	
	
		
 
            for (int degreeSample = 0; degreeSample < 5; ++degreeSample) {

			




	
	
	
		
 
                // Generate a graph

			




	
	
	
		
 
                // might require multiple tries

			




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

			




	
	
		
 
@@ -247,6 +259,7 @@ int main() {

			




	
	
	
		
 
                    }

			




	
	
	
		
 
                }

			




	
	
	
		
 

			




	
	
	
		
 
#if 0

			




	
	
	
		
 
                //

			




	
	
	
		
 
                // Test the GCM1 and GCM2 success rate

			




	
	
	
		
 
                //

			




	
	
		
 
@@ -269,6 +282,9 @@ int main() {

			




	
	
	
		
 
                        g2 = gtemp;

			




	
	
	
		
 
                    }

			




	
	
	
		
 
                }

			




	
	
	
		
 
#endif

			




	
	
	
		
 

			




	
	
	
		
 
                for (int i = 1; i < 5; ++i) {

			




	
	
	
		
 

			




	
	
	
		
 
                SwitchChain chain;

			




	
	
	
		
 
                if (!chain.initialize(g)) {

			




	
	
		
 
@@ -276,17 +292,6 @@ int main() {

			




	
	
	
		
 
                    return 1;

			




	
	
	
		
 
                }

			




	
	
	
		
 

			




	
	
	
		
 
                SwitchChain chain1, chain2;

			




	
	
	
		
 
                bool do1 = true, do2 = true;

			




	
	
	
		
 
                if (!chain1.initialize(g1)) {

			




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

			




	
	
	
		
 
                    do1 = false;

			




	
	
	
		
 
                }

			




	
	
	
		
 
                if (!chain2.initialize(g2)) {

			




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

			




	
	
	
		
 
                    do2 = false;

			




	
	
	
		
 
                }

			




	
	
	
		
 

			




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

			




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

			




	
	
	
		
 

			




	
	
		
 
@@ -299,28 +304,41 @@ int main() {

			




	
	
	
		
 
                constexpr int measureSkip = 1;

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
                int movesDone = 0;

			




	
	
	
		
 
                int movesTotal = 0;

			




	
	
	
		
 
                int movesSuccess = 0;

			




	
	
	
		
 

			




	
	
	
		
 
                int triangles[measurements];

			




	
	
	
		
 

			




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

			




	
	
	
		
 
                    if (chain.doMove())

			




	
	
	
		
 
                        ++movesDone;

			




	
	
	
		
 
                    ++movesTotal;

			




	
	
	
		
 
                    if (chain.doMove()) {

			




	
	
	
		
 
                        ++movesSuccess;

			




	
	
	
		
 
                    }

			




	
	
	
		
 
                }

			




	
	
	
		
 

			




	
	
	
		
 
                std::vector<int> successRates;

			




	
	
	
		
 
                successRates.reserve(measurements * measureSkip);

			




	
	
	
		
 
                int successrate = 0;

			




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

			




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

			




	
	
	
		
 
                        if (chain.doMove())

			




	
	
	
		
 
                            ++movesDone;

			




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

			




	
	
	
		
 
                        ++movesTotal;

			




	
	
	
		
 
                        if (chain.doMove()) {

			




	
	
	
		
 
                            ++movesSuccess;

			




	
	
	
		
 
                            ++successrate;

			




	
	
	
		
 
                        }

			




	
	
	
		
 
                    }

			




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

			




	
	
	
		
 

			




	
	
	
		
 
                    if ((i+1) % 100 == 0) {

			




	
	
	
		
 
                        successRates.push_back(successrate);

			




	
	
	
		
 
                        successrate = 0;

			




	
	
	
		
 
                    }

			




	
	
	
		
 
                }

			




	
	
	
		
 

			




	
	
	
		
 
                std::cout << movesDone << '/' << mixingTime + measurements * measureSkip

			




	
	
	
		
 
                          << " moves succeeded ("

			




	
	
	
		
 
                          << 100.0f * float(movesDone) /

			




	
	
	
		
 
                                 float(mixingTime + measurements * measureSkip)

			




	
	
	
		
 
                          << "%).";

			




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

			




	
	
	
		
 
                std::cout << '('

			




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

			




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

			




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

			




	
	
	
		
 

			




	
	
	
		
 
                if (outputComma)

			




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

			




	
	
		
 
@@ -330,10 +348,12 @@ int main() {

			




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

			




	
	
	
		
 
                outfile << ',' << triangles;

			




	
	
	
		
 
                outfile << ',' << ds;

			




	
	
	
		
 
#if 0

			




	
	
	
		
 
                outfile << ',' << greedyTriangles1;

			




	
	
	
		
 
                outfile << ',' << greedyTriangles2;

			




	
	
	
		
 

			




	
	
	
		
 
                if (do1) {

			




	
	
	
		
 
                SwitchChain chain1, chain2;

			




	
	
	
		
 
                if (chain1.initialize(g1)) {

			




	
	
	
		
 
                    movesDone = 0;

			




	
	
	
		
 
                    SwitchChain& c = chain1;

			




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

			




	
	
		
 
@@ -355,7 +375,7 @@ int main() {

			




	
	
	
		
 

			




	
	
	
		
 
                    outfile << ',' << triangles;

			




	
	
	
		
 
                }

			




	
	
	
		
 
                if (do2) {

			




	
	
	
		
 
                if (chain2.initialize(g2)) {

			




	
	
	
		
 
                    movesDone = 0;

			




	
	
	
		
 
                    SwitchChain& c = chain2;

			




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

			




	
	
		
 
@@ -377,10 +397,14 @@ int main() {

			




	
	
	
		
 

			




	
	
	
		
 
                    outfile << ',' << triangles;

			




	
	
	
		
 
                }

			




	
	
	
		
 
#endif

			




	
	
	
		
 

			




	
	
	
		
 
                outfile << ',' << successRates;

			




	
	
	
		
 

			




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

			




	
	
	
		
 

			




	
	
	
		
 
                std::cout << std::endl;

			




	
	
	
		
 
                }

			




	
	
	
		
 
            }

			




	
	
	
		
 
        }

			




	
	
	
		
 
    }

			




        

    


    
    

    

        

                

                    cpp/switchchain_initialtris.cpp
                

                

                  
                      
                        

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@@ -68,7 +68,8 @@ class SwitchChain {

			




	
	
	
		
 
//

			




	
	
	
		
 
// method2 = true  -> take highest degree and finish its pairing completely

			




	
	
	
		
 
// method2 = false -> take new highest degree after every pairing

			




	
	
	
		
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, auto& rng, bool method2) {

			




	
	
	
		
 
template <typename RNG>

			




	
	
	
		
 
bool greedyConfigurationModel(DegreeSequence& ds, Graph& g, RNG& 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();

			




        

    


    
    

    

        

                

                    plots/avgtris_n.pdf
                

                

                  
                      
                        

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new file 100644

			




	
	
		
 
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                    plots/triangle_exponent.pdf
                

                

                  
                      
                        

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new file 100644

			




	
	
		
 
binary diff not shown

			




        

    


    
    

    

        

                

                    triangle_analysis.m
                

                

                  
                      
                        

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@@ -71,7 +71,7 @@ Needs["ErrorBarPlots`"]

			




	
	
	
		
 
(*Data import*)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
gsraw=Import[NotebookDirectory[]<>"data/graphdata_partial.m"];

			




	
	
	
		
 
gsraw=Import[NotebookDirectory[]<>"data/graphdata_temp2.m"];

			




	
	
	
		
 
(* gsraw=SortBy[gsraw,{#[[1,1]]&,#[[1,2]]&}]; (* Sort by n and then by tau. The {} forces a *stable* sort because otherwise Mathematica sorts also on triangle count and other things. *) *)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
		
 
@@ -146,19 +146,47 @@ Show[ListPlot[avgAndProp,AxesOrigin->{0,0},AxesLabel->{"degree-sequence-property

			




	
	
	
		
 
(*Plot triangle count over "time" in Markov chain instances*)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
numPlots=20;

			




	
	
	
		
 
selectedData=gdata[[4,-1]][[-numPlots;;-1]];

			




	
	
	
		
 
numPlots=10;

			




	
	
	
		
 
selectedData=gdata[[1,-1]][[-numPlots;;-1]];

			




	
	
	
		
 
measureSkip=1;

			




	
	
	
		
 
minCount=Min[Map[Min[#[[2]]]&,selectedData]];

			




	
	
	
		
 
maxCount=Max[Map[Max[#[[2]]]&,selectedData]];

			




	
	
	
		
 
maxTime=Max[Map[Length[#[[2]]]&,selectedData]];

			




	
	
	
		
 
skipPts=Max[1,Round[maxTime/200]]; (* Plotting every point is slow. Plot only once per `skipPts` timesteps *)

			




	
	
	
		
 
coarseData=Map[#[[2,1;;-1;;skipPts]]&,selectedData];

			




	
	
	
		
 
maxTime=30000;

			




	
	
	
		
 
skipPts=Max[1,Round[maxTime/400]]; (* Plotting every point is slow. Plot only once per `skipPts` timesteps *)

			




	
	
	
		
 
coarseData=Map[#[[2,1;;maxTime;;skipPts]]&,selectedData];

			




	
	
	
		
 
labels=Map["{n,tau} = "<>ToString[#[[1]]]&,selectedData];

			




	
	
	
		
 
ListPlot[coarseData,Joined->True,PlotRange->{minCount,maxCount},DataRange->{0,measureSkip*maxTime},PlotLegends->labels]

			




	
	
	
		
 
ListPlot[coarseData,Joined->True,PlotRange->{0*minCount,maxCount},DataRange->{0,measureSkip*maxTime},PlotLegends->labels]

			




	
	
	
		
 
(* Map[ListPlot[#,Joined->True,PlotRange\[Rule]{minCount,maxCount},DataRange\[Rule]{0,maxTime}]&,coarseData] *)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* ::Subsection:: *)

			




	
	
	
		
 
(*Plot success rate over "time"*)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
numPlots=10;

			




	
	
	
		
 
selectedData=gdata[[1,-1]][[-numPlots;;-1]];

			




	
	
	
		
 
measureSkip=100;

			




	
	
	
		
 
maxTime=Max[Map[Length[#[[4]]]&,selectedData]];

			




	
	
	
		
 
maxTime=10000;

			




	
	
	
		
 
coarseData=Map[#[[4,1;;maxTime/measureSkip]]&,selectedData];

			




	
	
	
		
 
labels=Map["{n,tau} = "<>ToString[#[[1]]]&,selectedData];

			




	
	
	
		
 
ListPlot[coarseData,Joined->True,PlotRange->{0,100},DataRange->{0,maxTime},PlotLegends->labels]

			




	
	
	
		
 
(* Map[ListPlot[#,Joined->True,PlotRange\[Rule]{minCount,maxCount},DataRange\[Rule]{0,maxTime}]&,coarseData] *)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* ::Subsection:: *)

			




	
	
	
		
 
(*Correlation of avgsuccess rate vs other things*)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
compare1=Map[{Mean[#[[4]]],Mean[#[[2]]]}&,gdata,{3}];

			




	
	
	
		
 
(* { GCM1 rate, GCM2 rate, mixing time from ErdosGallai } *)

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
scatterPlots=Map[ListPlot[#,PlotRange->{{0,100},All},PlotStyle->PointSize[Large]]&,compare1,{2}];

			




	
	
	
		
 
TableForm[scatterPlots,TableHeadings->{taulabels,nlabels}]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* ::Subsection:: *)

			




	
	
	
		
 
(*Compute 'mixing time'*)

			




	
	
	
		
 

			




        

    


    
    

    

        

                

                    triangle_exponent_plots.m
                

                

                  
                      
                        

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@@ -16,7 +16,7 @@ Needs["ErrorBarPlots`"]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* When importing from exponent-only-data file *)

			




	
	
	
		
 
gsraw=Import[NotebookDirectory[]<>"data/graphdata_exponent.m"];

			




	
	
	
		
 
gsraw=Import[NotebookDirectory[]<>"data/graphdata_exponent_mix32.m"];

			




	
	
	
		
 
gsraw=SortBy[gsraw,#[[1,1]]&]; (* Sort by n *)

			




	
	
	
		
 
averagesGrouped=GatherBy[gsraw,{#[[1,2]]&,#[[1,1]]&}];

			




	
	
	
		
 

			




	
	
		
 
@@ -51,7 +51,10 @@ fitsExtra[[1]]["ParameterErrors"]

			




	
	
	
		
 
fitsExtra[[1]]["ParameterConfidenceIntervals"]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
Show[ListLogLogPlot[averagesErrorBars[[All,All,1]],Joined->True,PlotMarkers->Automatic,AxesLabel->{"n","\[LeftAngleBracket]triangles\[RightAngleBracket]"},PlotLegends->taulabels],Plot[fits,{logn,1,2000}]]

			




	
	
	
		
 
plot1=Show[ListLogLogPlot[averagesErrorBars[[All,All,1]],Joined->False,PlotMarkers->Automatic,AxesLabel->{"n","\[LeftAngleBracket]triangles\[RightAngleBracket]"},PlotLegends->taulabels],Plot[fits,{logn,1,2000}]]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
Export[NotebookDirectory[]<>"plots/avgtris_n.pdf",plot1]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* ::Subsection:: *)

			




	
	
		
 
@@ -60,7 +63,7 @@ Show[ListLogLogPlot[averagesErrorBars[[All,All,1]],Joined->True,PlotMarkers->Aut

			




	
	
	
		
 

			




	
	
	
		
 
tauValues=averagesGrouped[[All,1,1,1,2]];

			




	
	
	
		
 
exponents=Transpose[{tauValues,fits[[All,2,1]]}];

			




	
	
	
		
 
Show[ListPlot[exponents,Joined->True,PlotMarkers->Automatic,AxesLabel->{"tau","T(\[Tau])"},PlotRange->{{2,3},{0,1.6}}],Plot[3/2(3-tau),{tau,2,3}]]

			




	
	
	
		
 
Show[ListPlot[exponents,Joined->True,PlotMarkers->Automatic,AxesLabel->{"tau","exponent"},PlotRange->{{2,3},{0,1.6}}],Plot[3/2(3-tau),{tau,2,3}]]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
(* ::Subsection:: *)

			




	
	
		
 
@@ -70,4 +73,7 @@ Show[ListPlot[exponents,Joined->True,PlotMarkers->Automatic,AxesLabel->{"tau","T

			




	
	
	
		
 
tauValues=averagesGrouped[[All,1,1,1,2]];

			




	
	
	
		
 
exponentsErrorBars=Map[{{#[[1]],#[[2]]["BestFitParameters"][[2]]},ErrorBar[#[[2]]["ParameterConfidenceIntervals"][[2]]-#[[2]]["BestFitParameters"][[2]]]}&,

			




	
	
	
		
 
Transpose[{tauValues,fitsExtra}]];

			




	
	
	
		
 
Show[ErrorListPlot[exponentsErrorBars,Joined->True,PlotMarkers->Automatic,AxesLabel->{"tau","T(\[Tau])"},PlotRange->{{2,3},{0,1.6}}],Plot[3/2(3-tau),{tau,2,3}]]

			




	
	
	
		
 
plot2=Show[ErrorListPlot[exponentsErrorBars,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]

			




        

    



    


    



    



      

      





    
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