44 {
47
48 string inputFile;
50 string summaryFile;
51 int windowSize;
52 double fractionThreshold;
55
56 try {
57
58 JParser<> zap(
"Auxiliary program to build supernova background from JKexing2D output");
59
60 zap[
'f'] =
make_field(inputFile,
"input file (JKexing2D).");
62 zap[
'w'] =
make_field(windowSize,
"size of the sliding window to test") = 5;
64 zap[
'F'] =
make_field(fractionThreshold,
"minimum fraction of active channels to compute distribution") = 0.99;
66
67 zap(argc, argv);
68 }
69 catch(const exception &error) {
70 FATAL(error.what() << endl);
71 }
72
73 typedef JManager<int, TH1D> JManager_i1D_t;
74 typedef JManager<string, TH1D> JManager_s1D_t;
75 typedef JManager<string, TH2D> JManager2D_t;
76
77
78
79 TFile in(inputFile.c_str(), "exist");
80
81 TParameter<int>* runNumber;
82
83 in.GetObject("RUNNR", runNumber);
84
85 JManager2D_t MT = JManager2D_t::Read(in,
mul_p ,
'%');
86 JManager_s1D_t ST = JManager_s1D_t::Read(in,
status_p,
'%');
87
88 in.Close();
89
90
91
92 const int factoryLimit_peak = 250;
93 const int factoryLimit_runs = 10000;
94
95
96
98
100
101 for (vector<string>::const_iterator f = filters.begin(); f != filters.end(); ++f) {
102 string title = "MD_" + (*f) + "_%";
103 mmap[*f] = JManager_i1D_t(new TH1D(title.c_str(), NULL, factoryLimit_peak, 0, factoryLimit_peak));
104 }
105
106 const int nx = 1 + NUMBER_OF_PMTS;
107 const double xmin = -0.5;
108 const double xmax = nx - 0.5;
109
110
111
112 JManager_s1D_t TD(
new TH1D(Form(
"SNT_[%d,%d]_", multiplicity.
first, multiplicity.
second) + TString(
"%"), NULL, factoryLimit_peak, -0.5, -0.5 + factoryLimit_peak));
113
115
116
117 JManager2D_t BL(new TH2D("BL_%", NULL, 100, epsilon, 1 + epsilon, factoryLimit_peak, -0.5, -0.5 + factoryLimit_peak));
118 JManager2D_t MUL_EFF(new TH2D("MUL_EFF_%", NULL, 100, epsilon, 1 + epsilon, nx, xmin, xmax));
119
120
121 JManager_s1D_t H(new TH1D("H_%", NULL, factoryLimit_runs, 0, factoryLimit_runs));
122
123
124
125 TH1D* LT = new TH1D("LIVETIME_ACF", NULL, 100, epsilon, 1 + epsilon);
126
127
128
130
131 const int nb = activeChannelFraction->GetN();
132 const Double_t* arr_acf_y = activeChannelFraction->GetY();
133
135
136 LT->FillN(nb, arr_acf_y, NULL);
137
138 for (int M = 0; M <= NUMBER_OF_PMTS; M++) {
139
141
142
143
144 for (vector<string>::const_iterator f = filters.begin(); f != filters.end(); ++f) {
145
146
147
149
151
152 delete px;
153
154
155
156
159
160
161
162 transform(vec_acf_y.begin(),
163 vec_acf_y.end(),
164 threshold.begin(),
165 back_inserter(select),
166 greater_equal<double> {});
167
168 mmap[*f][M]->FillN(nb, count_vs_frame[*f]->GetY(), &select[0]);
169
170
171
173
174 MUL_EFF[*f]->FillN(nb,
175 arr_acf_y,
176 &nb_M[0],
177 count_vs_frame[*f]->GetY());
178
179 }
180 }
181
182 int RUNNR = runNumber->GetVal();
183
184 for (vector<string>::const_iterator f = filters.begin(); f != filters.end(); ++f) {
185
186
187
189
191
192 delete px;
193
194 TD[*f]->FillN(events_per_frame->GetN(), events_per_frame->GetY(), NULL);
195
196
197
198
199 vector<double> vec(events_per_frame->GetY(), events_per_frame->GetY() + nb);
201
203
204 TD[(*f) + "_nTS"]->FillN(events_per_frame_sliding.size(),
205 &events_per_frame_sliding[0],
206 NULL);
207
208
209
210 BL[*f]->FillN(nb,
211 arr_acf_y,
212 events_per_frame->GetY(),
213 NULL, 1);
214
215
216
218
219 int peak = px->GetMaximum();
220
221 delete px;
222
223 H["PK_" + (*f)]->Fill(RUNNR, peak);
224
225 }
226
227
228
229 double BI = (ST["PMT"]->GetSumOfWeights() / ST["PMT"]->GetEntries());
230
231 H["BIOLUM"]->Fill(RUNNR, BI);
232
233
234
236
237 TD.Write(out);
238
239 TDirectory* bm = out.mkdir("BIOLUM");
240 TDirectory* hs = out.mkdir("HISTORY");
241
242 H.Write(*hs);
243 BL.Write(*bm);
244
245 MUL_EFF.Write(*bm);
246
247 for (vector<string>::const_iterator f = filters.begin(); f != filters.end(); ++f) {
248 string dir_name = "MUL_" + (*f);
249 TDirectory* dir = out.mkdir(dir_name.c_str());
250 mmap[*f].Write(*dir);
251 }
252
253 LT->Write();
254
255 out.Close();
256
257}
static const char * status_p
static const char * mul_p
#define make_field(A,...)
macro to convert parameter to JParserTemplateElement object
Utility class to parse command line options.
bool select(const Trk &trk, const Evt &evt)
Event selection.
std::vector< T > convolve(const std::vector< T > &input, const std::vector< T > &kernel)
Convolute data with given kernel.
This name space includes all other name spaces (except KM3NETDAQ, KM3NET and ANTARES).
TGraph * histogramToGraph(const TH1 &h1)
Helper method to convert a 1D histogram to a graph.
TH1 * projectHistogram(const TH2 &h2, const Double_t xmin, const Double_t xmax, const char projection)
Helper method for ROOT histogram projections.