source: trunk/MagicSoft/Mars/mtemp/mmpi/macros/SuperCutsONOFFMacro.C@ 6723

Last change on this file since 6723 was 6232, checked in by mazin, 20 years ago
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1// Silly macro to run the classes that optimize supercuts
2// using ON and OFF data.
3
4// The user only needs to fill/change the variables that control
5// the optimization procedure.
6
7
8gROOT -> Reset();
9
10void SuperCutsONOFFMacroNew()
11{
12 gLog.SetNoColors();
13
14 // File containing the data (ON/OFF DATA and path for files (root/ps))
15
16 // From magicserv01
17// TString ONDataFilename("/.magic/data16a/mazin/data/mcdata/2004_06_30/*HillasON.root");
18
19// TString OFFDataFilename("/.magic/data16a/mazin/data/mcdata/2004_06_30/*HillasOFF.root");
20
21// TString ONDataFilename("/.magic/magicserv01/scratch/Period21/HillasFiles/CrabNebula_20040914.root");
22// TString ONDataFilename("/.magic/magicserv01/scratch/Period21/HillasFiles/CrabNebula_20040921.root");
23// TString ONDataFilename("/.magic/magicserv01/scratch/Period21/HillasFiles/CrabNebula_20040922.root");
24
25// TString ONDataFilename("/.magic/magicserv01/scratch/Period21/HillasFiles/CrabNebula_2004*.root");
26
27 //TString ONDataFilename("/.magic/data22a/mazin/HillasParam/Period24/2004_12_18/Crab_40_25_1_AbsHillas.root");
28 TString ONDataFilename("/.magic/data04a/nadia/Analysis/starfiles/DF/40_25_1/CrabNebula_*_Hillas_Abs.root");
29 TString OFFDataFilename("/.magic/data04a/nadia/Analysis/starfiles/DF/40_25_1/OffCrab1*Hillas_Abs.root");
30 //TString ONDataFilename("/.magic/data03a/mazin/results/2004_09_21/CrabNebulaNadiaHillas.root");
31 //TString OFFDataFilename("/.magic/data03a/mazin/results/2004_09_21/CrabNebulaNadiaHillas.root");
32
33
34 TString PathForFiles ("/.magic/data03a/mazin/results/Crab/DF/CrabNadia/SuperCuts/Size2000/");
35
36// TString PathForFiles ("/.magic/magicserv01/scratch/hbartko/SC/"); // was: Daniel/SuperCuts/Mrk421/2004_04_22/4slices_3520_nc/E800_1200_Opt_MC_Test/
37
38
39
40 // Boolean variables defining the job of the
41 // macro
42
43 // Boolean variable that decides wether data is read from files specified above
44 // (ON/OFF) or read from already existing Matrices (which are obviously stored
45 // in a root file). The names of the files storing those matrices are produced
46 // automatically using information provided by some of the next variables whose
47 // values must be specified by user.
48
49 Bool_t ReadMatrixFromRootFiles = kTRUE;
50
51
52 // Boolean variable that controls the supercuts
53 // optimization using the training sample
54 // The optimized cuts will be written in root file
55 // located in directory specified before. Name of
56 // the root files is created automatically.
57
58 Bool_t TrainParams = kTRUE;
59
60 // Variable that allows the user to skip the optimization on the
61 // train sample. If optimization is skipped (value kTRUE), the
62 // previously optimized supercuts (stored in root file) are used
63 // on the train sample.
64
65 Bool_t SkipOptimization = kFALSE;
66
67 // Boolean variable that allows the user to write the initial parameters
68 // into the root file that will be used to store the optimum cuts.
69 // If fUseInitialSCParams = kTRUE , parameters are written.
70 // In this way, the initial SC parameters can be applied on the data (train/test)
71
72 // The initial parameters are ONLY written to the root file if
73 // there is NO SC params optimization, i.e., if variable
74 // fSkipOptimization = kTRUE;
75
76 // NOTE: be aware that, if there was a file with the optimized cuts
77 // (previously computed), it will be overwritten with the initial
78 // SC parameters. This is something that I WILL HAVE TO CHANGE IN
79 // future. Yet for the time being...
80
81 Bool_t UseInitialSCParams = kTRUE; // was kFALSE
82
83
84
85 // Variable that decides whether the optimized cuts are used
86 // in the test sample.
87
88 Bool_t TestParams = kTRUE;
89
90
91 // Boolean variable that controls wether to combine, OR not, the
92 // alpha distributions computed (after cuts) for the several theta bins
93 // in which the TRAIN sample was divided.
94
95 Bool_t CombineCosThetaBinsForTrainSample = kFALSE;
96
97 // Boolean variable that controls wether to combine, OR not, the
98 // alpha distribution computed (after cuts) for the several theta bins
99 // in which the TEST sample was divided.
100
101 Bool_t CombineCosThetaBinsForTestSample = kFALSE;
102
103
104 // Fraction of ON events used for the training/testing
105 Double_t whichfractiontrain = 0.5;
106 Double_t whichfractiontest = 0.5;
107
108 // Fraction of OFF events used for the training/testing
109 Double_t whichfractiontrainOFF = 0.5;
110 Double_t whichfractiontestOFF = 0.5;
111
112
113 // Efficiency for gammas when using this set of dynamical cuts
114 // (i.e., fraction of initial gammas that remain after cuts)
115
116 // Current value is the first estimation of the efficiency of cuts
117 // on Mkn421 at a SIZE > 2000 photons
118
119 Double_t gammaeff = 0.6;
120
121
122 // Alpha value (degrees) below which signal is expected
123
124 Double_t alphasig = 9;
125
126 // Definition of alpha bkg region (where no signal is expected)
127
128 Double_t alphabkgmin = 30;
129 Double_t alphabkgmax = 90;
130
131 // Definition of the Size range
132
133 Double_t SizeLow = 2000;
134// Double_t SizeUp = 2000;
135 Double_t SizeUp = 1000000;
136
137 Double_t LeakageMax = 0.04;
138 Double_t DistMax = 1.5;
139 Double_t DistMin = 0.1;
140
141 // Definition of binning of alpha plots
142 Int_t NAlphaBins = 35;
143 Double_t AlphaBinLow = -9;
144 Double_t AlphaBinUp = 96;
145
146
147 // Boolean variable used to determine wether the normalization factor is
148 // computed from method 1) or 2)
149 // 1) Using total number of ON and OFF events before cuts, and tuning the factor
150 // correcting for "contamination" of gamma events in ON sample
151 // 2) Using number of ON and OFF events after cuts in the background
152 // region determined by variables fAlphaBkgMin-fAlphaBkgMax
153
154 Bool_t NormFactorFromAlphaBkg = kTRUE; // if kTRUE, method 2) is used
155
156
157 // Boolean variable used to disable the usage ("serious" usage) of the
158 // quantities computed from fits. This will be useful in those cases
159 // where there is too few events to perform a decent fit to the
160 // alpha histograms.
161
162 Bool_t UseFittedQuantities = kTRUE;
163
164
165 // Boolean variable used to control wether to use theta information
166 // in the computation of teh dynamical cuts that take place within
167 // class MCT1SupercutsCalc
168 //Bool_t NotUseTheta = kFALSE; // kTRUE removes theta from the parameterization of cuts
169 Bool_t NotUseTheta = kTRUE; // kTRUE removes theta from the parameterization of cuts
170
171 // Boolean variable used to decide wether to use dynamical cuts or static cuts
172 // kTRUE means that static cuts are used.
173 Bool_t UseStaticCuts = kFALSE;
174
175
176
177
178
179 // Name of the Postscript document where all plots
180 // will be saved.
181 // STORAGE OF PSFILE IS NOT WORKING PROPERLY
182 // For the time being, several ps files are produced
183 // and saved in the directory specified by PathForFiles
184
185 /*
186 TString PsFileName = ("PsTest23.ps");
187 TString CompletePsFileName = (PathForFiles);
188 CompletePsFileName += PsFileName;
189 TPostScript* PsFile = new TPostScript(CompletePsFileName, 111);
190 */
191
192 // Boolean variable used to decide wether initial parameters are
193 // read from ascii file or not. If kTRUE, parameters are retrieved
194 // from ascii file.
195
196 Bool_t ReadInitParamsFromAsciiFile = kTRUE;
197
198 // Number of SC parameters. The aim of this variable is to cross check
199 // that the number of parameters read from an ascii file
200 // is teh one the user wants.
201
202 Int_t NInitSCPar = 104;
203
204 // Name of the ascii file containing the 2 columns, the first one
205 // for initial parameters and the second one for the steps
206 // Name must contain also the path.
207
208 const char* InitSCParamAsciiFile =
209 // {"../InitialSCParametersSteps/InitSCParamsAndStepsDanielModified1.txt"};
210 // {"../InitialSCParametersSteps/FixedStaticCutsInLengthWidthDist.txt"};
211 // {"../InitialSCParametersSteps/FixedStaticCutsInLengthWidthDist11.txt"};
212 // {"../InitialSCParametersSteps/InitSCParamsAndStepsDanielModified1.txt"};
213 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421.txt"};
214 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynStaticCutsFixedPol2SizeCut3000.txt"};
215 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynWithDistParametersFixed.txt"};
216 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynStaticCutsVariablePol2.txt"};
217 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynStaticCutsVariablePol2WidthCutLowFixed.txt"};
218 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynCutsOnSize.txt"};
219 // {"../InitialSCParametersSteps/StartingValuesForOptimizationMkn421DynCutsOnSizeAndDist.txt"};
220 //{"mtemp/mmpi/asciifiles/OptimizedMkn421DynCutsGridWithSelected22pointsMay19.txt"};
221 //{"/home/pcmagic16/mazin/mars/Mars260804/mtemp/mmpi/asciifiles/StartingValuesForSmallSizes1.txt"};
222// {"/home/pcmagic16/mazin/mars/Mars260804/mtemp/mmpi/asciifiles/SmallSizeRFStartValues.txt"};
223 {"/home/pcmagic16/mazin/mars/Mars260804/mtemp/mmpi/asciifiles/OptimizedCrabFrom2000_a.txt"};
224 //{"mtemp/mmpi/asciifiles/VeryGoodDummyValuesWithConcCut.txt"};
225
226
227 // Name of the root file where alpha distributions, TTree objects
228 // with info about the events and cuts applied and info support histograms
229 // will be stored.
230 // Write only the name of the file. The Path
231 // is the one defined previously
232
233 TString RootFilename = ("RootFileDynCuts.root");
234
235
236
237
238
239
240 // Vector containing the theta bins in which data (ON/OFF train/test)
241 // will be divided. Actually this vector contains the cosinus of
242 // these theta bins. The dimension of the vector is N+1, where
243 // N is the number of theta bins intended. The first component of the
244 // vector is the low bin edge of the first bin, and the last
245 // vector component the upper bin edge of the last bin.
246
247
248 TArrayD CosThetaRangeVector(2);
249 CosThetaRangeVector[1] = 0.866; //30
250 //CosThetaRangeVector[1] = 0.74; //42
251 //CosThetaRangeVector[1] = 0.82; //35
252 //CosThetaRangeVector[1] = 0;
253 //CosThetaRangeVector[1] = 0.825;
254 //CosThetaRangeVector[2] = 0.921;
255 //CosThetaRangeVector[3] = 0.961;
256 CosThetaRangeVector[0] = 0.5; // 60
257 //CosThetaRangeVector[0] = 1;
258
259
260 /*
261 TArrayD CosThetaRangeVector(2);
262 CosThetaRangeVector[0] = 0.622;
263 // CosThetaRangeVector[1] = 0.825;
264 //CosThetaRangeVector[2] = 0.921;
265 //CosThetaRangeVector[0] = 0.961;
266 CosThetaRangeVector[1] = 0.984;
267
268 */
269 // Object of MCT1FindSupercutsONOFFThetaLoop created, data that was specified
270 // above is introduced and ... and the party starts.
271
272 MFindSupercutsONOFFThetaLoop FindSupercuts("MFindSupercutsONOFFThetaLoop",
273 "Optimizer for the supercuts");
274
275
276 FindSupercuts.SetPathForFiles(PathForFiles);
277
278 FindSupercuts.SetDataONOFFRootFilenames(ONDataFilename, OFFDataFilename);
279
280 FindSupercuts.SetFractionTrainTestOnOffEvents(whichfractiontrain,
281 whichfractiontest,
282 whichfractiontrainOFF,
283 whichfractiontestOFF);
284
285
286 FindSupercuts.SetGammaEfficiency(gammaeff);
287
288
289 FindSupercuts.SetAlphaSig(alphasig);
290
291 // Bkg alpha region is set
292 FindSupercuts.SetAlphaBkgMin(alphabkgmin);
293 FindSupercuts.SetAlphaBkgMax(alphabkgmax);
294
295 // alpha bkg and signal region set in object FindSupercuts
296 // are re-checked in order to be sure that make sense
297
298 FindSupercuts.CheckAlphaSigBkg();
299
300
301 // binning for alpha plots is defined
302
303 FindSupercuts.SetAlphaPlotBinining(NAlphaBins, AlphaBinLow,
304 AlphaBinUp);
305
306
307
308
309 // Size range is defined
310
311 FindSupercuts.SetSizeRange(SizeLow, SizeUp);
312 FindSupercuts.SetFilters(LeakageMax, DistMax, DistMin);
313// FindSupercuts.SetFilters(0.001, 1.5, 0.2);
314
315
316
317 FindSupercuts.SetNormFactorFromAlphaBkg(NormFactorFromAlphaBkg);
318
319 FindSupercuts.SetUseFittedQuantities(UseFittedQuantities);
320
321 FindSupercuts.SetVariableUseStaticCuts(UseStaticCuts);
322
323 FindSupercuts.SetVariableNotUseTheta(NotUseTheta);
324
325 FindSupercuts.SetReadMatricesFromFile(ReadMatrixFromRootFiles);
326
327 FindSupercuts.SetTrainParameters(TrainParams);
328 FindSupercuts.SetSkipOptimization(SkipOptimization);
329 FindSupercuts.SetUseInitialSCParams(UseInitialSCParams);
330
331 FindSupercuts.SetTestParameters(TestParams);
332
333
334
335 FindSupercuts.SetHadronnessName("MHadSC");
336 FindSupercuts.SetHadronnessNameOFF("MHadOFFSC");
337
338 FindSupercuts.SetAlphaDistributionsRootFilename (RootFilename);
339
340 // FindSupercuts.SetPostScriptFile (PsFile);
341
342 FindSupercuts.SetCosThetaRangeVector (CosThetaRangeVector);
343
344
345 // Names for all root files (matrices, alpha distributions...)
346 // are created
347 FindSupercuts.SetALLNames();
348
349 if(ReadInitParamsFromAsciiFile)
350 {
351 // Initial SC Parameters and steps are retrieved from
352 // Ascii file
353 if(!FindSupercuts.ReadSCParamsFromAsciiFile(InitSCParamAsciiFile,
354 NInitSCPar))
355 {
356 cout << "Initial SC Parameters could not be read from Ascii file "
357 << InitSCParamAsciiFile << endl
358 << "Aborting execution of macro... " << endl;
359 return;
360
361 }
362 }
363
364
365
366
367 // Finally loop over all theta bins defined is executed
368
369 if (!FindSupercuts.LoopOverThetaRanges())
370 {
371 cout << "Function MFindSupercutsONOFFThetaLoop::LoopOverThetaRanges()" << endl
372 << "could not be performed" << endl;
373
374 }
375
376
377
378 // Nex and Significance are computed vs alphasig
379
380 if (!FindSupercuts.ComputeNexSignificanceVSAlphaSig())
381 {
382 cout << "Function MFindSupercutsONOFFThetaLoop::ComputeNexSignificanceVSAlphaSig()" << endl
383 << "could not be performed" << endl;
384
385
386 }
387
388
389
390
391 // Option to store ps files in a single ps document is still not working
392 /*
393 PsFile -> Close();
394 PsFile = NULL;
395 */
396
397 // Several theta bins are combined to produced a single alpha plot (for train and test)
398 // with single Nex and significances
399
400 if (CombineCosThetaBinsForTrainSample || CombineCosThetaBinsForTestSample)
401 {
402 if(!FindSupercuts.ComputeOverallSignificance(CombineCosThetaBinsForTrainSample,
403 CombineCosThetaBinsForTestSample))
404 {
405 cout << "Function MFindSupercutsONOFFThetaLoop::ComputeOverallSignificance" << endl
406 << "could not be performed" << endl;
407 }
408
409
410 }
411
412
413
414}
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