AENC/switchchain Changeset - 3e67925ef7ec · Centrum Wiskunde & Informatica (CWI)

Changeset - 3e67925ef7ec

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Tom Bannink - 8 years ago 2017-08-15 17:57:03
tom.bannink@cwi.nl

Add autocorrelation notebook

3 files changed with 66 insertions and 5 deletions:

plots/ccm_initialtris.pdf

bin+mod

triangle_autocorrelations.m

triangle_gcm_initial_analysis.m

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plots/ccm_initialtris.pdf

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triangle_autocorrelations.m

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@@ new file 100644 @@
 (* ::Package:: *)
 (* ::Section:: *)
 (*Data import*)
 gsraw=Import[NotebookDirectory[]<>"data/graphdata_timeevol.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. *) *)
 gdata=GatherBy[gsraw,{#[[1,2]]&,#[[1,1]]&}];
 (* Data format: *)
 (* gdata[[ tau index, n index, run index , datatype index ]] *)
 (* datatype index:
 : {n,tau}
 : #triangles time sequence
 : degree sequence
 : GCM1 starting triangle counts
 : GCM2 starting triangle counts
 : GCM1 time sequence
 : GCM2 time sequence
 *)
 nlabels=Map["n = "<>ToString[#]&,gdata[[1,All,1,1,1]]];
 taulabels=Map["tau = "<>ToString[#]&,gdata[[All,1,1,1,2]]];
 (* ::Section:: *)
 (*Triangle counts autocorrelation*)
 doAutoCorrelate[dataset_,maxlag_]:=Module[{avg,data2,result},
 avg=Mean[dataset];
 data2=dataset-avg;
 result=ParallelTable[Mean[data2[[1+lag;;]]*data2[[;;-1-lag]]],{lag,0,maxlag}];
 result=result/result[[1]]
+]
 doPeriodicAutocorrelate[dataset_,maxlag_]:=Module[{f,result},
 f=Fourier[dataset-Mean[dataset]];
 result=InverseFourier[f*Conjugate[f]];
 result=result[[1;;Min[Floor[Length[result]/2],maxlag]]];
 result=Chop[result];
 result=result/result[[1]]
+]
 dataX=gdata[[1,1]][[3,2]];
 ListPlot[dataX,Joined->True,PlotRange->All]
 dataX=dataX[[15000;;50000]];
 cor1=doAutoCorrelate[dataX,2000];
 cor2=doPeriodicAutocorrelate[dataX,20000];
 ListPlot[{cor1,cor2},Joined->True,PlotRange->{-0.5,1}]

triangle_gcm_initial_analysis.m

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@@ @@ -41,39 +41,41 @@ getAverage[run_]:=Module[{avg}, @@
     , {3,3}]
+]
 getTotalStats[runs_]:=Transpose[Map[getAverage,runs]];
 totalStats=Map[getTotalStats,gdata,{2}];
 (* Yellow: GCM1 (take new highest everytime *)
 (* Blue: GCM2 (finish highest first, more similar to EG) *)
 (* Yellow: CCMu (take new highest everytime *)
 (* Blue: CCMb (finish highest first, more similar to EG) *)
 histogramsTotal=Map[Histogram[#,{0.05},PlotRange->{{-0.5,2},Automatic},ImageSize->300,AxesOrigin->{0,0}]&,totalStats,{2}];
 TableForm[histogramsTotal,TableHeadings->{taulabels,nlabels}]
 (* ::Subsubsection:: *)
 (*Exporting plots*)
 makeHistogram[datasets_,n_,tau_]:=Histogram[datasets,{0.05},"Probability",
 PlotRange->{{0,1},{0,0.5}},
+PlotRange->{{0,1.3},{0,0.5}},
 ImageSize->300,AxesOrigin->{0,0},
 AspectRatio->3/5,
 Frame->True,
 FrameLabel->{"fraction of average #triangles at CCM start","frequency"},
 ChartLegends->Placed[{"CCMu   avg = "<>ToString[NumberForm[N[Mean[datasets[[1]]]],2]],"CCMb   avg = "<>ToString[NumberForm[N[Mean[datasets[[2]]]],2]]},Center],
 (*LabelingFunction->(Placed[NumberForm[#,{2,3}],Above]&),*)
 (*LabelingFunction\[Rule](Placed[If[#2[[2]]\[Equal]1,NumberForm[#1,{2,3}],""],Above]&),*)
 PlotLabel->n<>", "<>tau];
 histogramsTotal=MapIndexed[makeHistogram[#1,nlabels[[#2[[2]]]],taulabels[[#2[[1]]]]]&,totalStats,{2}];
 tauIndices={1,5,9};
-nIndices={3};
+nIndices={1};
 (* TableForm[histogramsTotal[[tauIndices,nIndices]],TableHeadings->{taulabels[[tauIndices]],nlabels[[nIndices]]}]*)
 plotgrid1=GraphicsGrid[histogramsTotal[[tauIndices,nIndices]]]
+plotgrid1=GraphicsGrid[histogramsTotal[[tauIndices,nIndices]],ImageSize->350,ItemAspectRatio->3/5]
 Export[NotebookDirectory[]<>"plots/ccm_initialtris.pdf",plotgrid1]
 (* ::Subsection:: *)

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