diff --git a/cpp/showgraphs.m b/cpp/showgraphs.m
index beec01993c5f52bbb41157fe018ab21c4d0297b0..f56096863698088e74f7f69514e24da3384a5a0a 100644
--- a/cpp/showgraphs.m
+++ b/cpp/showgraphs.m
@@ -31,7 +31,7 @@ Grid[Partition[gs,10],Frame->All]
 gsraw=Import[NotebookDirectory[]<>"graphdata_merged.m"];
 
 
-newData=Import[NotebookDirectory[]<>"graphdata_tau_multi3.m"];
+newData=Import[NotebookDirectory[]<>"graphdata_tau_multi4.m"];
 mergedData=Import[NotebookDirectory[]<>"graphdata_merged.m"];
 Export[NotebookDirectory[]<>"graphdata_merged_new.m",Join[mergedData,newData]]
 
@@ -44,22 +44,23 @@ maxDegrees=Map[{#[[1]],Max[#[[3]]]}&,gsraw];
 maxDegrees=GatherBy[maxDegrees,{#[[1,2]]&,#[[1,1]]&}];
 
 
-Histogram[maxDegrees[[1,-1,All,2]],PlotRange->{{0,1100},{0,200}},AxesLabel->{"d_max","frequency"}]
-Histogram[maxDegrees[[2,-1,All,2]],PlotRange->{{0,1100},{0,200}},AxesLabel->{"d_max","frequency"}]
-Histogram[maxDegrees[[3,-1,All,2]],PlotRange->{{0,1100},{0,200}},AxesLabel->{"d_max","frequency"}]
+Histogram[maxDegrees[[1,-1,All,2]],PlotRange->{{0,2000},{0,100}},AxesLabel->{"d_max","frequency"}]
+Histogram[maxDegrees[[2,-1,All,2]],PlotRange->{{0,2000},{0,100}},AxesLabel->{"d_max","frequency"}]
+Histogram[maxDegrees[[3,-1,All,2]],PlotRange->{{0,2000},{0,100}},AxesLabel->{"d_max","frequency"}]
 
 
 (* ::Subsection:: *)
 (*Plot triangle count over "time" in Markov chain instances*)
 
 
-numPlots=10;
-minCount=Min[Map[Min[#[[2]]]&,gsraw[[1;;numPlots]]]];
-maxCount=Max[Map[Max[#[[2]]]&,gsraw[[1;;numPlots]]]];
-maxTime=Max[Map[Length[#[[2]]]&,gsraw[[1;;numPlots]]]];
+numPlots=15;
+selectedData=gsraw[[-numPlots-1;;-1]];
+minCount=Min[Map[Min[#[[2]]]&,selectedData]];
+maxCount=Max[Map[Max[#[[2]]]&,selectedData]];
+maxTime=Max[Map[Length[#[[2]]]&,selectedData]];
 skipPts=Round[maxTime/100]; (* Plotting every point is slow. Plot only once per `skipPts` timesteps *)
-coarseData=Map[#[[2,1;;-1;;skipPts]]&,gsraw[[1;;numPlots]]];
-labels=Map["{n,tau} = "<>ToString[#[[1]]]&,gsraw[[1;;numPlots]]];
+coarseData=Map[#[[2,1;;-1;;skipPts]]&,selectedData];
+labels=Map["{n,tau} = "<>ToString[#[[1]]]&,selectedData];
 ListPlot[coarseData,Joined->True,PlotRange->{minCount,maxCount},DataRange->{0,maxTime},PlotLegends->labels]
 (* Map[ListPlot[#,Joined->True,PlotRange\[Rule]{minCount,maxCount},DataRange\[Rule]{0,maxTime}]&,coarseData] *)
 
@@ -69,6 +70,9 @@ ListPlot[coarseData,Joined->True,PlotRange->{minCount,maxCount},DataRange->{0,ma
 
 
 averages=Map[{#[[1]],Mean[#[[2,1;;-1]]]}&,gsraw];
+(* Sort by n *)
+averages=SortBy[averages,#[[1,1]]&];
+(* Split by n,tau *)
 averagesGrouped=GatherBy[averages,{#[[1,1]]&,#[[1,2]]&}];
 (* averagesGroupes[[ n index, tau index , run index, {ntau, tri, ds} ]] *)
 averagesGrouped=Transpose[averagesGrouped];
@@ -84,6 +88,9 @@ ErrorBar[StandardDeviation[#[[All,2]]]/Sqrt[Length[#]]]
 ErrorListPlot[averagesErrorBars,Joined->True,PlotMarkers->Automatic,AxesLabel->{"n","\[LeftAngleBracket]triangles\[RightAngleBracket]"},PlotLegends->taulabels]
 
 
+ListLogPlot[averagesErrorBars[[All,All,1]],Joined->True,PlotMarkers->Automatic,AxesLabel->{"n","\[LeftAngleBracket]triangles\[RightAngleBracket]"},PlotLegends->taulabels]
+
+
 (* ::Subsection:: *)
 (*Plot #triangles distribution for specific (n,tau)*)