-
Notifications
You must be signed in to change notification settings - Fork 1
/
dp_mstest_rdf.C
executable file
·199 lines (141 loc) · 7.25 KB
/
dp_mstest_rdf.C
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
{//begin
#include <TMath.h>
#include <math.h>
#include "scripts/fit1MeV_GaussianPlusCBWithExp_redo.C"
using namespace std;
using namespace ROOT;
EnableImplicitMT();
//create rdataframe for dp data
//RDataFrame dpdf("D2KKpi/DecayTree", {"/share/lazy/D2KKpi/dpmagdown_dec20.root","/share/lazy/D2KKpi/dpmagup_dec20.root"});
//smaller set of data for quicker, experimental runs
//done by taking the smalles magdown and magup subfiles
RDataFrame dpdf("D2KKpi/DecayTree", {"/share/lazy/D2KKpi/dp_data_dec20/dpmagup14-2.root", "/share/lazy/D2KKpi/dp_data_dec20/dpmagdown15-2.root"});
/*
auto test_min = dpdf.Min("Dplus_MM");
auto test_max = dpdf.Max("Dplus_MM");
cout << "minimum dp mass is " << *test_min << endl;
cout << "maximum dp mass is " << *test_max << endl;
auto test_summary = dpdf.Stats("Dplus_MM");
test_summary->Print();
*/
const double phi_pm = 10;//12 for regular cut
const double phiupperbound = (1019.455+phi_pm)*(1019.455+phi_pm)/1000000;
const double philowerbound = (1019.455-phi_pm)*(1019.455-phi_pm)/1000000;
auto inv_m_func = [](double px1, double py1, double pz1, double pe1, double px2, double py2, double pz2, double pe2) {return TLorentzVector(TLorentzVector(px1, py1, pz1, pe1)+TLorentzVector(px2, py2, pz2, pe2)).Mag2()/1000000 ;};
auto prob_func = [](double prob1, double prob2) {return TMath::Log(prob1) - TMath::Log(prob2) ;};
auto probNNx_func = [](double prob1, double prob2, double prob3) {return prob1*prob2*prob3 ;};
auto cut_ipchi2 = [](double x) {return x < 4 ;};//5 for regular cut
auto cut_fdchi2 = [](double x) {return x > 225 ;};//175 for regular cut
auto cut_endvertexchi2 = [](double x) {return x < 9 ;};
auto cut_phi = [&phiupperbound, &philowerbound](double x) {return x > philowerbound && x < phiupperbound ;};
auto cut_prob_5 = [] (double x) {return x>5 ;};
auto cut_prob_0 = [] (double x) {return x>0 ;};
auto cut_probnnx = [] (double x) {return x >= 0.70 ;};
auto cut_pK_ambiguity = [] (double x) {return x> 10000 ;}; //10,000 MeV = 10GeV
auto cut_dira = [] (double x) {return x>0.99999 ;};
//auto cut_tau = [] (double x) {return x > 0.0000000001 ;};//mikes suggestion : 1e-10, ds+ takeover : 2.3e-10
auto signalregion = [](double x) {return ((x > 1855) && (x < 1885)) ;};
auto backgroundregion = [](double x) {return ((x>1810 && x < 1840) || (x > 1900 && x < 1930)) ;};
auto rightbackgroundregion = [](double x) {return (x > 1900 && x < 1950) ;};
auto leftbackgroundregion = [](double x) {return (x > 1790 && x < 1840) ;};
auto dp_cut = dpdf.Filter(cut_ipchi2, {"Dplus_IPCHI2_OWNPV"})
.Filter(cut_fdchi2, {"Dplus_FDCHI2_OWNPV"})
.Filter(cut_endvertexchi2, {"Dplus_ENDVERTEX_CHI2"})
.Filter(cut_pK_ambiguity, {"Kplus_P"})
.Filter(cut_pK_ambiguity, {"Kminus_P"})
.Filter(cut_dira, {"Dplus_DIRA_OWNPV"})
.Define("kminuslog", prob_func, {"Kminus_MC15TuneV1_ProbNNk", "Kminus_MC15TuneV1_ProbNNpi"})
.Define("kpluslog", prob_func, {"Kplus_MC15TuneV1_ProbNNk", "Kplus_MC15TuneV1_ProbNNpi"})
.Define("pipluslog", prob_func, {"Piplus_MC15TuneV1_ProbNNpi", "Piplus_MC15TuneV1_ProbNNk"})
.Filter(cut_prob_5, {"kminuslog"})
.Filter(cut_prob_5, {"kpluslog"})
.Filter(cut_prob_0, {"pipluslog"})
.Define("ProbNNx", probNNx_func, {"Kminus_MC15TuneV1_ProbNNk", "Kplus_MC15TuneV1_ProbNNk", "Piplus_MC15TuneV1_ProbNNpi"})
.Filter(cut_probnnx, {"ProbNNx"})
.Define("mkpkm", inv_m_func, {"Kplus_PX", "Kplus_PY", "Kplus_PZ", "Kplus_PE", "Kminus_PX", "Kminus_PY", "Kminus_PZ", "Kminus_PE"})
.Filter(cut_phi, {"mkpkm"});
auto dp_sig_df = dp_cut.Filter(signalregion, {"Dplus_MM"});
auto dp_bgd_df = dp_cut.Filter(backgroundregion, {"Dplus_MM"});
auto dp_left = dp_cut.Filter(leftbackgroundregion, {"Dplus_MM"});
auto dp_right = dp_cut.Filter(rightbackgroundregion, {"Dplus_MM"});
//Tau tests
/*
const double taubinmin = 0;
const double taubinmax = 0.005;
const int nbins = 100;
auto dptaucan = new TCanvas("dptaucan", "dptaucan", 1200, 800);
dptaucan->cd();
auto dptausighist = dp_sig_df.Fill<double>(TH1D("dptausighist","D+ #tau, uncut",nbins, taubinmin, taubinmax), {"Dplus_TAU"});
dptausighist->SetStats(0);
dptausighist->SetTitleFont(43);
dptausighist->SetTitleSize(35);
dptausighist->GetYaxis()->SetTitle("events per bin");
dptausighist->GetYaxis()->SetTitleFont(43);
dptausighist->GetYaxis()->SetTitleSize(30);
dptausighist->GetYaxis()->CenterTitle(true);
dptausighist->GetXaxis()->SetTitle("decay time (ns)");
dptausighist->GetXaxis()->SetTitleFont(43);
dptausighist->GetXaxis()->SetTitleSize(25);
dptausighist->GetXaxis()->CenterTitle(true);
dptausighist->GetXaxis()->SetTitleOffset(1.2);
dptausighist->SetLineColor(kRed);
dptausighist->SetLineWidth(3);
//total background, not split by left or right
//
//auto dptaubgdhist = dp_bgd_df.Fill<double>(TH1D("bgdhist","D+ #tau, uncut",nbins, taubinmin, taubinmax), {"Dplus_TAU"});
// dptaubgdhist->SetStats(0);
// dptaubgdhist->SetLineColor(kBlue);
// dptaubgdhist->SetLineWidth(3);
auto dptaulefthist = dp_left.Fill<double>(TH1D("dptaulefthist","D+ #tau, uncut",nbins, taubinmin, taubinmax), {"Dplus_TAU"});
dptaulefthist->SetStats(0);
dptaulefthist->SetLineColor(kBlue);
dptaulefthist->SetLineWidth(3);
auto dptaurighthist = dp_right.Fill<double>(TH1D("dptaurighthist","D+ #tau uncut",nbins, taubinmin, taubinmax), {"Dplus_TAU"});
dptaurighthist->SetStats(0);
dptaurighthist->SetLineColor(kGreen + 2);
dptaurighthist->SetLineWidth(3);
auto taulegend = new TLegend(0.7,0.8,0.9,0.9);
taulegend->AddEntry(dptausighist.GetPtr(), "Signal Region", "lp");
//taulegend->AddEntry(dptaubgdhist.GetPtr(), "Background Region", "lp");
taulegend->AddEntry(dptaulefthist.GetPtr(), "Left Background", "lp");
taulegend->AddEntry(dptaurighthist.GetPtr(), "Right Background", "lp");
dptausighist->Draw("");
dptaulefthist->Draw("same");
dptaurighthist->Draw("same");
taulegend->Draw("same");
dptaucan->SaveAs("image/dp_tau_uncut.png");
*/
//particle_x, particle_y
/*
auto pip_pos = dp_cut.Fill<double, double>(TH2D("pip_pos", "#pi^{+} _X, _Y cut",300,-3000,3000,300,-3000,3000), {"Piplus_X","Piplus_Y"});
pip_pos->SetStats(0);
pip_pos->GetXaxis()->SetTitle("Piplus_X");
pip_pos->GetYaxis()->SetTitle("Piplus_Y");
pip_pos_can = new TCanvas("pip_pos_can", "pip_pos_can", 1000, 800);
pip_pos_can->SetRightMargin(0.15);
pip_pos_can->SetLeftMargin(0.15);
pip_pos_can->cd();
pip_pos->Draw("colz");
pip_pos_can->SaveAs("image/dp_XY_cut_pip.png");
auto kp_pos = dp_cut.Fill<double, double>(TH2D("kp_pos", "K^{+} _X, _Y cut",300,-3000,3000,300,-3000,3000), {"Kplus_X","Kplus_Y"});
kp_pos->SetStats(0);
kp_pos->GetXaxis()->SetTitle("Kplus_X");
kp_pos->GetYaxis()->SetTitle("Kplus_Y");
kp_pos_can = new TCanvas("kp_pos_can", "kp_pos_can", 1000, 800);
kp_pos_can->SetRightMargin(0.15);
kp_pos_can->SetLeftMargin(0.15);
kp_pos_can->cd();
kp_pos->Draw("colz");
kp_pos_can->SaveAs("image/dp_XY_cut_kp.png");
auto km_pos = dp_cut.Fill<double, double>(TH2D("km_pos", "K^{-} _X, _Y cut",300,-3000,3000,300,-3000,3000), {"Kminus_X","Kminus_Y"});
km_pos->SetStats(0);
km_pos->GetXaxis()->SetTitle("Kminus_X");
km_pos->GetYaxis()->SetTitle("Kminus_Y");
km_pos_can = new TCanvas("km_pos_can", "km_pos_can", 1000, 800);
km_pos_can->SetRightMargin(0.15);
km_pos_can->SetLeftMargin(0.15);
km_pos_can->cd();
km_pos->Draw("colz");
km_pos_can->SaveAs("image/dp_XY_cut_km.png");
*/
}//end