Added different fitting times for comparison

code/RDownScriptalphabeta.m

@@ -33,18 +33,19 @@ SetOptions[InputNotebook[], AutoGeneratedPackage -> Automatic]
 mysxscase=rootpath<>"/SXS/BBH_SKS_d14.3_q1.22_sA_0_0_0.330_sB_0_0_-0.440";
 ntones=1;
 tshift=19;
-npoints=1000;
+npoints=3000;
 (*n=1:19, n=2:12, n=3:8, n=4:5, n=5:3, n=6:1, n=7:0 (not sure; is that really a minimum???) *)
 allspectrum = {x0,x1,x2,x3,x4,x5,x6,x7};
-spectrum = allspectrum[[;;ntones+1]];
+allalphas = {\[Alpha]1,\[Alpha]2,\[Alpha]3,\[Alpha]4,\[Alpha]5,\[Alpha]6,\[Alpha]7};
+allbetas = {\[Beta]1,\[Beta]2,\[Beta]3,\[Beta]4,\[Beta]5,\[Beta]6,\[Beta]7};
+spectrum = allspectrum[[;;ntones+1]]
+alphas = allalphas[[;;ntones]]
+betas = allbetas[[;;ntones]]
 \[Omega]fact=0.1;
 \[Tau]fact=0.1;
 params = {tshift, ntones, \[Omega]fact, \[Tau]fact}
 
 
-combinations = DeleteCases[Tuples[Range[1, ntones],2],Alternatives@@Subsets[Reverse[Range[0, ntones]],{2}]]
-
-
 (* Change them accordingly *)
 (*Notebook directory*)
 notdir=rootpath<>"code/";
@@ -130,44 +131,69 @@ Print["Tag = ",tag=("alternative-names"/.metadata)[[2]]]
 sxsrhs=Flatten[Conjugate/@GetAsymptoticMultiMode[#,2,modes,"ReSample"->True]&/@mysxscaserh,1];
 
 
-t0=TimeOfMaximum[sxsrhs[[1]]]+tshift
+tmax = TimeOfMaximum[sxsrhs[[1]]]
+t0 = tmax+tshift
 data = Select[sxsrhs[[1]],#[[1]]>= t0&];
 
 
-tab\[Alpha]s=Table[Table[randomvar1= RandomReal[{-\[Omega]fact, \[Omega]fact}];randomvar2 = RandomReal[{-\[Omega]fact, \[Omega]fact}];
-ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},t0,"Fit\[Alpha]"->combinations[[k]],"Fit\[Tau]"->{},"ModesData"->Modedata]/.ToExpression["\[Alpha]"<>ToString[combinations[[k]][[1]]]]->randomvar1/.ToExpression["\[Alpha]"<>ToString[combinations[[k]][[2]]]] -> randomvar2;
-cfit=NonlinearModelFit[data,ansatz,spectrum,t];
-cfitd=Transpose[{data[[All,1]],Normal[cfit]/.t->data[[All,1]]}];
-comp\[Alpha]s = spectrum/.cfit["BestFitParameters"];
-mismatchlist = {{randomvar1, randomvar2}, combinations[[k]], {tshift, 1-EasyMatchT[data,cfitd,t0,t0+90]}};
-ampandphs = Transpose[{Re[Sqrt[comp\[Alpha]s * Conjugate[comp\[Alpha]s]]], Mod[Arg[comp\[Alpha]s], 2 Pi]}];
-Join[mismatchlist, ampandphs], {j,npoints}], {k, Length[combinations]}];
+(*tmax=TimeOfMaximum[sxsrhs[[1]]];
+t01=tmax
+mysxscase22modeRD=Select[sxsrhs[[1]],#[[1]]\[GreaterEqual] tmax-25&];
+data1 = Select[mysxscase22modeRD, #[[1]]\[GreaterEqual]tmax+tshift&]*)
 
 
-tab\[Alpha]\[Beta]s=Flatten[Table[Table[randomvar1= RandomReal[{-\[Omega]fact, \[Omega]fact}];randomvar2 = RandomReal[{-\[Tau]fact, \[Tau]fact}];
-ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},t0,"Fit\[Alpha]"->{k},"Fit\[Tau]"->{l},"ModesData"->Modedata]/.ToExpression["\[Alpha]"<>ToString[k]]->randomvar1/.ToExpression["\[Beta]"<>ToString[l]] -> randomvar2;
+(*tabvars=Table[
+randomvar\[Alpha]s= RandomReal[{-\[Omega]fact, \[Omega]fact}, ntones];
+randomvar\[Beta]s = RandomReal[{-\[Tau]fact, \[Tau]fact}, ntones];
+ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},t0,"Fit\[Alpha]"\[Rule]Range[1, ntones],"Fit\[Tau]"\[Rule]Range[1, ntones],"ModesData"->Modedata]
+/.Table[alphas[[i]]\[Rule]randomvar\[Alpha]s[[i]],{i,ntones}]/.Table[betas[[j]]\[Rule]randomvar\[Beta]s[[j]],{j,ntones}];
+data=Select[mysxscase22modeRD, #[[1]]\[GreaterEqual]tmax+19&];
 cfit=NonlinearModelFit[data,ansatz,spectrum,t];
 cfitd=Transpose[{data[[All,1]],Normal[cfit]/.t->data[[All,1]]}];
-comp\[Alpha]\[Beta]s = spectrum/.cfit["BestFitParameters"];
-mismatchlist = {{randomvar1, randomvar2}, {k, l}, {tshift, 1-EasyMatchT[data,cfitd,t0,t0+90]}};
-ampandphs = Transpose[{Re[Sqrt[comp\[Alpha]\[Beta]s * Conjugate[comp\[Alpha]\[Beta]s]]], Mod[Arg[comp\[Alpha]\[Beta]s], 2 Pi]}];
-Join[mismatchlist, ampandphs], {j,npoints}], {k, Range[1, ntones]}, {l, Range[1, ntones]}], 1];
-
-
-tab\[Beta]s=Table[Table[randomvar1= RandomReal[{-\[Tau]fact, \[Tau]fact}];randomvar2 = RandomReal[{-\[Tau]fact, \[Tau]fact}];
-ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},t0,"Fit\[Alpha]"->{},"Fit\[Tau]"->combinations[[k]],"ModesData"->Modedata]/.ToExpression["\[Beta]"<>ToString[combinations[[k]][[1]]]]->randomvar1/.ToExpression["\[Beta]"<>ToString[combinations[[k]][[2]]]] -> randomvar2;
+alphasandmis = Join[alphas/.Table[alphas[[i]]\[Rule]randomvar\[Alpha]s[[i]],{i,ntones}], {1-EasyMatchT[data,cfitd,tmax+19,tmax+90]}]; 
+(* This extra step is to make sure everything's correct, and also to make the output a uniform shape *)
+betasandtfit = Join[betas/.Table[betas[[j]]\[Rule]randomvar\[Beta]s[[j]],{j,ntones}], {tshift}];
+complexamps = spectrum/.cfit["BestFitParameters"];
+amplitudes = Re[Sqrt[complexamps * Conjugate[complexamps]]];
+phases = Mod[Arg[complexamps], 2 Pi];
+{alphasandmis, betasandtfit, amplitudes, phases}, {j,npoints}];*)
+
+
+tabvars=Table[
+randomvar\[Alpha]s= RandomReal[{-\[Omega]fact, \[Omega]fact}, ntones];
+randomvar\[Beta]s = RandomReal[{-\[Omega]fact, \[Omega]fact}, ntones];
+ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},t0,"Fit\[Alpha]"->Range[1, ntones],"Fit\[Tau]"->Range[1, ntones],"ModesData"->Modedata]
+/.Table[alphas[[i]]->randomvar\[Alpha]s[[i]],{i,ntones}]/.Table[betas[[j]]->randomvar\[Beta]s[[j]],{j,ntones}];
+cfit=NonlinearModelFit[data,ansatz,spectrum,t];
+cfitd=Transpose[{data[[All,1]],Normal[cfit]/.t->data[[All,1]]}];
+alphasandmis = Join[alphas/.Table[alphas[[i]]->randomvar\[Alpha]s[[i]],{i,ntones}], {1-EasyMatchT[data,cfitd,t0,t0+90]}]; 
+(* This extra step is to make sure everything's correct, and also to make the output a uniform shape *)
+betasandtfit = Join[betas/.Table[betas[[j]]->randomvar\[Beta]s[[j]],{j,ntones}], {tshift}];
+complexamps = spectrum/.cfit["BestFitParameters"];
+amplitudes = Re[Sqrt[complexamps * Conjugate[complexamps]]];
+phases = Mod[Arg[complexamps], 2 Pi];
+{alphasandmis, betasandtfit, amplitudes, phases}, {j,npoints}];
+
+
+tabvars1=Table[
+randomvar\[Alpha]s= RandomReal[{-\[Omega]fact, \[Omega]fact}, ntones];
+randomvar\[Beta]s = RandomReal[{-\[Omega]fact, \[Omega]fact}, ntones];
+ansatz=OvertoneModelV2[ntones,{\[Eta],\[Chi]1,\[Chi]2},tmax,"Fit\[Alpha]"->Range[1, ntones],"Fit\[Tau]"->Range[1, ntones],"ModesData"->Modedata]
+/.Table[alphas[[i]]->randomvar\[Alpha]s[[i]],{i,ntones}]/.Table[betas[[j]]->randomvar\[Beta]s[[j]],{j,ntones}];
 cfit=NonlinearModelFit[data,ansatz,spectrum,t];
 cfitd=Transpose[{data[[All,1]],Normal[cfit]/.t->data[[All,1]]}];
-comp\[Beta]s = spectrum/.cfit["BestFitParameters"];
-mismatchlist = {{randomvar1, randomvar2}, combinations[[k]], {tshift, 1-EasyMatchT[data,cfitd,t0,t0+90]}};
-ampandphs = Transpose[{Re[Sqrt[comp\[Beta]s * Conjugate[comp\[Beta]s]]], Mod[Arg[comp\[Beta]s], 2 Pi]}];
-Join[mismatchlist, ampandphs], {j,npoints}], {k, Length[combinations]}];
+alphasandmis = Join[alphas/.Table[alphas[[i]]->randomvar\[Alpha]s[[i]],{i,ntones}], {1-EasyMatchT[data,cfitd,t0,t0+90]}]; 
+(* This extra step is to make sure everything's correct, and also to make the output a uniform shape *)
+betasandtfit = Join[betas/.Table[betas[[j]]->randomvar\[Beta]s[[j]],{j,ntones}], {tshift}];
+complexamps = spectrum/.cfit["BestFitParameters"];
+amplitudes = Re[Sqrt[complexamps * Conjugate[complexamps]]];
+phases = Mod[Arg[complexamps], 2 Pi];
+{alphasandmis, betasandtfit, amplitudes, phases}, {j,npoints}];
 
 
 Export[rootpath<>"plots/n="<>ToString[ntones]<>"_params.fits", params]
-Export[rootpath<>"plots/n="<>ToString[ntones]<>"_as.fits", tab\[Alpha]s]
-Export[rootpath<>"plots/n="<>ToString[ntones]<>"_abs.fits", tab\[Alpha]\[Beta]s]
-Export[rootpath<>"plots/n="<>ToString[ntones]<>"_bs.fits", tab\[Beta]s]
+Export[rootpath<>"plots/n="<>ToString[ntones]<>"_t0="<>ToString[tshift]<>"M_data.fits", tabvars]
+Export[rootpath<>"plots/n="<>ToString[ntones]<>"_t0="<>ToString[tshift]<>"M_data@tmax.fits", tabvars1]