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345 lines
13 KiB
345 lines
13 KiB
#include "ParamValues.hpp"
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using namespace std;
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using namespace RooFit;
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using namespace RooStats;
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void ParamValues::printProperties(){
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coutDebug("Name\t\t\t" + name);
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coutDebug("LaTeX name\t\t" + latexName);
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coutDebug("Fixed\t\t\t" + string(fix ? "yes" : "no"));
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coutDebug("Constrained\t\t" + string(constrain ? "yes" : "no"));
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coutDebug("val\t\t\t" + to_string(value));
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coutDebug("valError\t\t" + to_string(error));
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coutDebug("lowRange\t\t" + to_string(ranges[0]));
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coutDebug("upRange\t\t\t" + to_string(ranges[1]));
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}
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void ParamValues::SetParamValues(string s_string, bool fitRef){
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if (s_string == "mean"){
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name = "sig_mean";
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latexName = "B^{+} #mu";
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value = PDGMASS.B_PLUS;
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error = 0.5;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? false : false;
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ranges[0] = 5250.0;
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ranges[1] = 5320.0;
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}
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else if (s_string == "sigma"){
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name = "sig_sigma";
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latexName = "B^{+} #sigma_{1}";
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value = OneCB ? 30.0 : 15.0;
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error = 1.0;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? true : !fitRef;
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ranges[0] = 5.0;
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ranges[1] = 150.;
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}
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else if (s_string == "sigma2"){
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name = "sig_sigma2";
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latexName = "B^{+} #sigma_{2}";
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value = anyGaussain ? 18.0 : 12.0;
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error = 1.0;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? anyGaussain : anyGaussain;
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ranges[0] = 5.0;
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ranges[1] = DoubleGaussian ? 150. : 100.;
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}
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else if (s_string == "alpha"){
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name = "sig_alpha";
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latexName = "B^{+} #alphaCB_{1}";
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value = (RightCB || OneCB) ? 1.5 : -1.5;
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error = 0.1;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? true : true;
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ranges[0] = (RightCB || OneCB) ? 0.01 : -3.5;
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ranges[1] = (RightCB || OneCB) ? 3.5 : -0.01;
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}
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else if (s_string == "alpha2"){
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name = "sig_alpha2";
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latexName = "B^{+} #alphaCB_{2}";
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value = 1.5;
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error = 1.0;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? true : true;
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ranges[0] = 0.01;
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ranges[1] = 3.5;
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}
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else if (s_string == "n"){
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name = "sig_n";
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latexName = "B^{+} #nCB_{1}";
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value = 3.1;
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error = 0.1;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? true : true;
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ranges[0] = 2.1;
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ranges[1] = 4.0;
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}
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else if (s_string == "n2"){
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name = "sig_n2";
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latexName =" B^{+} #nCB_{2}";
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value = 4.0;
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error = 0.1;
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constrain = KshortChannel ? false : false;
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fix = KshortChannel ? true : true;
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ranges[0] = 1.0;
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ranges[1] = 6.0;
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}
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else if (s_string == "f"){
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name = "sig_f";
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latexName = "f__{B^{+}}";
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if (DoubleGaussian) value = 0.5;
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else if (DoubleCB) value = 0.55; //0.5; CB_left >= CB_right
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else value = 0.0;
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error = 0.02;
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constrain = KshortChannel ? DoubleCB : DoubleCB;
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fix = KshortChannel ? false : false;
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ranges[0] = KshortChannel ? 0.05 : 0.15;
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ranges[1] = KshortChannel ? 0.95 : (DoubleGaussian ? 0.95 : 0.55);
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}
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else if (s_string == "exp_par1"){
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name = "exp_par1";
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latexName = "#lambda_{1}";
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value = -0.0015;
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error = 0.0001;
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constrain = false;
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fix = false;
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ranges[0] = -0.02;
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ranges[1] = 0.0;
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}
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else if (s_string == "exp_par2"){
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name = "exp_par2";
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latexName = "#lambda_{0}";
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value = -0.0016;
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error = 0.0001;
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constrain = false;
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fix = false;
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ranges[0] = -0.016;
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ranges[1] = 0.0;
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}
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else if (s_string == "bkg_mean"){ //ExpGaus mean
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name = "bkg_mean";
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latexName = "B^{+} #mu";
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value = ExpGaus? 5144.0 : PDGMASS.B_PLUS;
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error = 30.0;
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constrain = true;
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fix = false;
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ranges[0] = ExpGaus ? 5115.0 : PDGMASS.B_PLUS-10;
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ranges[1] = ExpGaus ? 5175.0 : PDGMASS.B_PLUS+10;
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}
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else if (s_string == "bkg_sigma"){
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name = "bkg_sigma";
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latexName = "B^{+} #sigma_{bkg}";
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value = 11.0;
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error = 1.0;
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constrain = ExpGaus;
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fix = !ExpGaus;
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ranges[0] = 2.0;
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ranges[1] = 50.;
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}
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else if (s_string == "bkg_decay"){
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name = "bkg_decay";
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latexName = "B^{+} decay coeff";
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value = 5140;
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error = 0.1;
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constrain = false;
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fix = false;
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ranges[0] = 5000.0;
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ranges[1] = 5150.0;
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}
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else if (s_string == "bkg_alpha1"){
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name = "bkg_alpha1";
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latexName = "B^{+} #alphaCB_{1}^{bkg}";
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value = 1.5;
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error = 1.0;
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constrain = false;
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fix = true;
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ranges[0] = 0.01;
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ranges[1] = 3.5;
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}
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else if (s_string == "bkg_alpha2"){
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name = "bkg_alpha2";
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latexName = "B^{+} #alphaCB_{2}^{bkg}";
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value = 1.5;
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error = 1.0;
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constrain = false;
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fix = true;
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ranges[0] = 0.01;
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ranges[1] = 3.5;
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}
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else if (s_string == "bkg_n1"){
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name = "bkg_n1";
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latexName = "B^{+} #nCB_{1}^{bkg}";
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value = 5.1;
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error = 0.1;
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constrain = false;
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fix = true;
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ranges[0] = 0.1;
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ranges[1] = 20.;
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}
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else if (s_string == "bkg_n2"){
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name = "bkg_n2";
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latexName =" B^{+} #nCB_{2}^{bkg}";
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value = 1.4;
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error = 0.1;
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constrain = false;
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fix = true;
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ranges[0] = 0.1;
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ranges[1] = 30.;
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}
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else if (s_string == "bkg_f"){
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name = "bkg_f";
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latexName = "f^{bckgnd}_{B^{+}}";
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value = 0.5;
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error = 0.01;
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constrain = false;
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fix = false;
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ranges[0] = 0.15;
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ranges[1] = 0.99;
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}
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if (verboseLevel<3) printProperties();
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};
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FitValuesWithName getSignalSavedFitValue(string s_name){ //This would have been so much nicer in Python
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if (s_name == "sig_mean") return FitValuesSignal.sig_mean ;
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else if (s_name == "sig_sigma") return FitValuesSignal.sig_sigma ;
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else if (s_name == "sig_sigma2") return FitValuesSignal.sig_sigma2;
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else if (s_name == "sig_alpha") return FitValuesSignal.sig_alpha ;
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else if (s_name == "sig_alpha2") return FitValuesSignal.sig_alpha2;
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else if (s_name == "sig_n") return FitValuesSignal.sig_n ;
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else if (s_name == "sig_n2") return FitValuesSignal.sig_n2 ;
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else if (s_name == "sig_f") return FitValuesSignal.sig_f ;
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else{
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coutERROR("Parameter " + s_name + " was not found in the FitValuesSignal vector!");
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coutERROR("Returning 0.");
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return FitValuesWithName("",0.0,0.0);
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}
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}
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FitValuesWithName getBackgroundSavedFitValue(string s_name){ //This would have been so much nicer in Python
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if (s_name == "bkg_mean") return FitValuesBackground.bkg_mean ;
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else if (s_name == "bkg_sigma") return FitValuesBackground.bkg_sigma ;
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else if (s_name == "bkg_decay") return FitValuesBackground.bkg_decay ;
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else if (s_name == "bkg_alpha1") return FitValuesBackground.bkg_alpha ;
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else if (s_name == "bkg_alpha2") return FitValuesBackground.bkg_alpha2;
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else if (s_name == "bkg_n1") return FitValuesBackground.bkg_n ;
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else if (s_name == "bkg_n2") return FitValuesBackground.bkg_n2 ;
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else if (s_name == "bkg_f") return FitValuesBackground.bkg_f ;
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else{
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coutERROR("Parameter " + s_name + " was not found in the FitValuesBackground vector!");
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coutERROR("Returning 0.");
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return FitValuesWithName("",0.0,0.0);
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}
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}
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RooRealVar *ParamValues::getRooRealVar(string s_name, bool sig, bool fitRef){
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SetParamValues(s_name, fitRef);
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RooRealVar *variable = new RooRealVar(name.c_str(), latexName.c_str(), value, ranges[0], ranges[1]);
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if (fix && (sig ? FixParameters : FixBkgParameters)){
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coutDebug("Fixing parameter " + string(variable->GetName()));
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sig ? variable->setVal(getSignalSavedFitValue(variable->GetName()).val) : variable->setVal(getBackgroundSavedFitValue(variable->GetName()).val);
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variable->setConstant("kTrue");
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}
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if (constrain && (sig ? ConstrParameters: ConstrBkgParameters)){
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coutDebug("Adding constrain to " + string(variable->GetName()));
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if (fix) coutWarning("Cannot constrain parameter " + string(variable->GetName()) + " which is already fixed. Ignore constraining!");
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else{
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string ConstrName = name + "Constr";
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RooGaussian *gauss_contrain_sig = sig ? new RooGaussian(ConstrName.c_str(), ConstrName.c_str(), *variable, RooConst(getSignalSavedFitValue(variable->GetName()).val), RooConst(getSignalSavedFitValue(variable->GetName()).err)) : new RooGaussian();
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if (verboseLevel<2 && sig) gauss_contrain_sig->Print();
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RooGaussian *gauss_contrain_bkg = sig ? new RooGaussian() : new RooGaussian(ConstrName.c_str(), ConstrName.c_str(), *variable, RooConst(getBackgroundSavedFitValue(variable->GetName()).val), RooConst(getBackgroundSavedFitValue(variable->GetName()).err));
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if (verboseLevel<2 && !sig) gauss_contrain_bkg->Print();
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sig ? ConsPDF->add(*gauss_contrain_sig) : BkgConsPDF->add(*gauss_contrain_bkg);
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sig ? ConsParameter->add(*variable) : BkgConsParameter->add(*variable);
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sig ? AtLeastOneConstrainFound = true : BkgAtLeastOneConstrainFound = true;
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if (verboseLevel<2) sig ? ConsPDF->Print() : BkgConsPDF->Print() ;
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}
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}
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coutDebug("Created variable: ");
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if (verboseLevel<2) variable->Print();
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return variable;
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}
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void setSignalSavedFitValue(string s_name, double d_val, double d_err){ //This would have been so much nicer in Python
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coutDebug("Setting " + s_name +" to " + to_string(d_val) + " +- " + to_string(d_err));
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if (s_name == "sig_mean") {
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FitValuesSignal.sig_mean.val = d_val;
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FitValuesSignal.sig_mean.err = d_err;}
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else if (s_name == "sig_sigma") {
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FitValuesSignal.sig_sigma.val = d_val;
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FitValuesSignal.sig_sigma.err = d_err;}
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else if (s_name == "sig_sigma2") {
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FitValuesSignal.sig_sigma2.val = d_val;
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FitValuesSignal.sig_sigma2.err = d_err;}
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else if (s_name == "sig_alpha") {
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FitValuesSignal.sig_alpha.val = d_val;
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FitValuesSignal.sig_alpha.err = d_err;}
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else if (s_name == "sig_alpha2") {
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FitValuesSignal.sig_alpha2.val = d_val;
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FitValuesSignal.sig_alpha2.err = d_err;}
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else if (s_name == "sig_n") {
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FitValuesSignal.sig_n.val = d_val;
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FitValuesSignal.sig_n.err = d_err;}
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else if (s_name == "sig_n2") {
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FitValuesSignal.sig_n2.val = d_val;
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FitValuesSignal.sig_n2.err = d_err;}
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else if (s_name == "sig_f") {
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FitValuesSignal.sig_f.val = d_val;
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FitValuesSignal.sig_f.err = d_err;}
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else if (s_name == "sig_effSigma"){
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FitValuesSignal.sig_effSigma.val = d_val;
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FitValuesSignal.sig_effSigma.err = d_err;}
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else{
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coutWarning("Parameter " + s_name + " was not found in the FitValuesSignal vector!");
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coutWarning("Cannot set anything!");
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}
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return;
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}
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void setBackgroundSavedFitValue(string s_name, double d_val, double d_err){ //This would have been so much nicer in Python
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coutDebug("Setting " + s_name +" to " + to_string(d_val) + " +- " + to_string(d_err));
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if (s_name == "bkg_mean") {
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FitValuesBackground.bkg_mean.val = d_val;
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FitValuesBackground.bkg_mean.err = d_err;}
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else if (s_name == "bkg_sigma") {
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FitValuesBackground.bkg_sigma.val = d_val;
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FitValuesBackground.bkg_sigma.err = d_err;}
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else if (s_name == "bkg_alpha1") {
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FitValuesBackground.bkg_alpha.val = d_val;
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FitValuesBackground.bkg_alpha.err = d_err;}
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else if (s_name == "bkg_alpha2") {
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FitValuesBackground.bkg_alpha2.val = d_val;
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FitValuesBackground.bkg_alpha2.err = d_err;}
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else if (s_name == "bkg_n1") {
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FitValuesBackground.bkg_n.val = d_val;
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FitValuesBackground.bkg_n.err = d_err;}
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else if (s_name == "bkg_n2") {
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FitValuesBackground.bkg_n2.val = d_val;
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FitValuesBackground.bkg_n2.err = d_err;}
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else if (s_name == "bkg_f") {
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FitValuesBackground.bkg_f.val = d_val;
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FitValuesBackground.bkg_f.err = d_err;}
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else{
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coutWarning("Parameter " + s_name + " was not found in the FitValuesBackground vector!");
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coutWarning("Cannot set anything!");
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}
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return;
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}
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//Set parameters to get the values needed by the constrained fit
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void ParamValues::setValuesAndErrors(bool sig){
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for (auto var : (sig ? SigRooVars : BkgRooVars)){
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coutDebug("Setting " + string(var->GetName()));
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if (verboseLevel < 3) var->Print();
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sig ? setSignalSavedFitValue(var->GetName(),var->getVal(),var->getError()) : setBackgroundSavedFitValue(var->GetName(),var->getVal(),var->getError());
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}
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if (sig) setSignalSavedFitValue("sig_effSigma",getEffSigmaFromResult(),0.04);
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return;
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}
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