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Reference Guide
TMVACrossValidation_BDTG_fold1.class.C
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1 // Class: ReadBDTG_fold1
2 // Automatically generated by MethodBase::MakeClass
3 //
4 
5 /* configuration options =====================================================
6 
7 #GEN -*-*-*-*-*-*-*-*-*-*-*- general info -*-*-*-*-*-*-*-*-*-*-*-
8 
9 Method : BDT::BDTG_fold1
10 TMVA Release : 4.2.1 [262657]
11 ROOT Release : 6.14/05 [396805]
12 Creator : sftnight
13 Date : Fri Nov 2 10:41:50 2018
14 Host : Linux ec-ubuntu-14-04-x86-64-2 3.13.0-157-generic #207-Ubuntu SMP Mon Aug 20 16:44:59 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
15 Dir : /mnt/build/workspace/root-makedoc-v614/rootspi/rdoc/src/v6-14-00-patches/documentation/doxygen
16 Training events: 999
17 Analysis type : [Classification]
18 
19 
20 #OPT -*-*-*-*-*-*-*-*-*-*-*-*- options -*-*-*-*-*-*-*-*-*-*-*-*-
21 
22 # Set by User:
23 V: "False" [Verbose output (short form of "VerbosityLevel" below - overrides the latter one)]
24 H: "False" [Print method-specific help message]
25 NTrees: "100" [Number of trees in the forest]
26 MaxDepth: "2" [Max depth of the decision tree allowed]
27 MinNodeSize: "2.5%" [Minimum percentage of training events required in a leaf node (default: Classification: 5%, Regression: 0.2%)]
28 nCuts: "20" [Number of grid points in variable range used in finding optimal cut in node splitting]
29 BoostType: "Grad" [Boosting type for the trees in the forest (note: AdaCost is still experimental)]
30 Shrinkage: "1.000000e-01" [Learning rate for GradBoost algorithm]
31 NegWeightTreatment: "pray" [How to treat events with negative weights in the BDT training (particular the boosting) : IgnoreInTraining; Boost With inverse boostweight; Pair events with negative and positive weights in training sample and *annihilate* them (experimental!)]
32 # Default:
33 VerbosityLevel: "Default" [Verbosity level]
34 VarTransform: "None" [List of variable transformations performed before training, e.g., "D_Background,P_Signal,G,N_AllClasses" for: "Decorrelation, PCA-transformation, Gaussianisation, Normalisation, each for the given class of events ('AllClasses' denotes all events of all classes, if no class indication is given, 'All' is assumed)"]
35 CreateMVAPdfs: "False" [Create PDFs for classifier outputs (signal and background)]
36 IgnoreNegWeightsInTraining: "False" [Events with negative weights are ignored in the training (but are included for testing and performance evaluation)]
37 AdaBoostR2Loss: "quadratic" [Type of Loss function in AdaBoostR2]
38 UseBaggedBoost: "False" [Use only a random subsample of all events for growing the trees in each boost iteration.]
39 AdaBoostBeta: "5.000000e-01" [Learning rate for AdaBoost algorithm]
40 UseRandomisedTrees: "False" [Determine at each node splitting the cut variable only as the best out of a random subset of variables (like in RandomForests)]
41 UseNvars: "2" [Size of the subset of variables used with RandomisedTree option]
42 UsePoissonNvars: "True" [Interpret "UseNvars" not as fixed number but as mean of a Poisson distribution in each split with RandomisedTree option]
43 BaggedSampleFraction: "6.000000e-01" [Relative size of bagged event sample to original size of the data sample (used whenever bagging is used (i.e. UseBaggedBoost, Bagging,)]
44 UseYesNoLeaf: "True" [Use Sig or Bkg categories, or the purity=S/(S+B) as classification of the leaf node -> Real-AdaBoost]
45 Css: "1.000000e+00" [AdaCost: cost of true signal selected signal]
46 Cts_sb: "1.000000e+00" [AdaCost: cost of true signal selected bkg]
47 Ctb_ss: "1.000000e+00" [AdaCost: cost of true bkg selected signal]
48 Cbb: "1.000000e+00" [AdaCost: cost of true bkg selected bkg ]
49 NodePurityLimit: "5.000000e-01" [In boosting/pruning, nodes with purity > NodePurityLimit are signal; background otherwise.]
50 SeparationType: "giniindex" [Separation criterion for node splitting]
51 RegressionLossFunctionBDTG: "huber" [Loss function for BDTG regression.]
52 HuberQuantile: "7.000000e-01" [In the Huber loss function this is the quantile that separates the core from the tails in the residuals distribution.]
53 DoBoostMonitor: "False" [Create control plot with ROC integral vs tree number]
54 UseFisherCuts: "False" [Use multivariate splits using the Fisher criterion]
55 MinLinCorrForFisher: "8.000000e-01" [The minimum linear correlation between two variables demanded for use in Fisher criterion in node splitting]
56 UseExclusiveVars: "False" [Variables already used in fisher criterion are not anymore analysed individually for node splitting]
57 DoPreselection: "False" [and and apply automatic pre-selection for 100% efficient signal (bkg) cuts prior to training]
58 SigToBkgFraction: "1.000000e+00" [Sig to Bkg ratio used in Training (similar to NodePurityLimit, which cannot be used in real adaboost]
59 PruneMethod: "nopruning" [Note: for BDTs use small trees (e.g.MaxDepth=3) and NoPruning: Pruning: Method used for pruning (removal) of statistically insignificant branches ]
60 PruneStrength: "0.000000e+00" [Pruning strength]
61 PruningValFraction: "5.000000e-01" [Fraction of events to use for optimizing automatic pruning.]
62 SkipNormalization: "False" [Skip normalization at initialization, to keep expectation value of BDT output according to the fraction of events]
63 nEventsMin: "0" [deprecated: Use MinNodeSize (in % of training events) instead]
64 UseBaggedGrad: "False" [deprecated: Use *UseBaggedBoost* instead: Use only a random subsample of all events for growing the trees in each iteration.]
65 GradBaggingFraction: "6.000000e-01" [deprecated: Use *BaggedSampleFraction* instead: Defines the fraction of events to be used in each iteration, e.g. when UseBaggedGrad=kTRUE. ]
66 UseNTrainEvents: "0" [deprecated: Use *BaggedSampleFraction* instead: Number of randomly picked training events used in randomised (and bagged) trees]
67 NNodesMax: "0" [deprecated: Use MaxDepth instead to limit the tree size]
68 ##
69 
70 
71 #VAR -*-*-*-*-*-*-*-*-*-*-*-* variables *-*-*-*-*-*-*-*-*-*-*-*-
72 
73 NVar 2
74 x x x x 'F' [-4.10750675201,4.09692668915]
75 y y y y 'F' [-4.85200452805,4.07606744766]
76 NSpec 1
77 eventID eventID eventID I 'F' [1,1000]
78 
79 
80 ============================================================================ */
81 
82 #include <array>
83 #include <vector>
84 #include <cmath>
85 #include <string>
86 #include <iostream>
87 
88 #define NN new BDTG_fold1Node
89 
90 #ifndef BDTG_fold1Node__def
91 #define BDTG_fold1Node__def
92 
93 class BDTG_fold1Node {
94 
95 public:
96 
97  // constructor of an essentially "empty" node floating in space
98  BDTG_fold1Node ( BDTG_fold1Node* left,BDTG_fold1Node* right,
99  int selector, double cutValue, bool cutType,
100  int nodeType, double purity, double response ) :
101  fLeft ( left ),
102  fRight ( right ),
103  fSelector ( selector ),
104  fCutValue ( cutValue ),
105  fCutType ( cutType ),
106  fNodeType ( nodeType ),
107  fPurity ( purity ),
108  fResponse ( response ){
109  }
110 
111  virtual ~BDTG_fold1Node();
112 
113  // test event if it descends the tree at this node to the right
114  virtual bool GoesRight( const std::vector<double>& inputValues ) const;
115  BDTG_fold1Node* GetRight( void ) {return fRight; };
116 
117  // test event if it descends the tree at this node to the left
118  virtual bool GoesLeft ( const std::vector<double>& inputValues ) const;
119  BDTG_fold1Node* GetLeft( void ) { return fLeft; };
120 
121  // return S/(S+B) (purity) at this node (from training)
122 
123  double GetPurity( void ) const { return fPurity; }
124  // return the node type
125  int GetNodeType( void ) const { return fNodeType; }
126  double GetResponse(void) const {return fResponse;}
127 
128 private:
129 
130  BDTG_fold1Node* fLeft; // pointer to the left daughter node
131  BDTG_fold1Node* fRight; // pointer to the right daughter node
132  int fSelector; // index of variable used in node selection (decision tree)
133  double fCutValue; // cut value applied on this node to discriminate bkg against sig
134  bool fCutType; // true: if event variable > cutValue ==> signal , false otherwise
135  int fNodeType; // Type of node: -1 == Bkg-leaf, 1 == Signal-leaf, 0 = internal
136  double fPurity; // Purity of node from training
137  double fResponse; // Regression response value of node
138 };
139 
140 //_______________________________________________________________________
141  BDTG_fold1Node::~BDTG_fold1Node()
142 {
143  if (fLeft != NULL) delete fLeft;
144  if (fRight != NULL) delete fRight;
145 };
146 
147 //_______________________________________________________________________
148 bool BDTG_fold1Node::GoesRight( const std::vector<double>& inputValues ) const
149 {
150  // test event if it descends the tree at this node to the right
151  bool result;
152  result = (inputValues[fSelector] > fCutValue );
153  if (fCutType == true) return result; //the cuts are selecting Signal ;
154  else return !result;
155 }
156 
157 //_______________________________________________________________________
158 bool BDTG_fold1Node::GoesLeft( const std::vector<double>& inputValues ) const
159 {
160  // test event if it descends the tree at this node to the left
161  if (!this->GoesRight(inputValues)) return true;
162  else return false;
163 }
164 
165 #endif
166 
167 #ifndef IClassifierReader__def
168 #define IClassifierReader__def
169 
170 class IClassifierReader {
171 
172  public:
173 
174  // constructor
175  IClassifierReader() : fStatusIsClean( true ) {}
176  virtual ~IClassifierReader() {}
177 
178  // return classifier response
179  virtual double GetMvaValue( const std::vector<double>& inputValues ) const = 0;
180 
181  // returns classifier status
182  bool IsStatusClean() const { return fStatusIsClean; }
183 
184  protected:
185 
186  bool fStatusIsClean;
187 };
188 
189 #endif
190 
191 class ReadBDTG_fold1 : public IClassifierReader {
192 
193  public:
194 
195  // constructor
196  ReadBDTG_fold1( std::vector<std::string>& theInputVars )
197  : IClassifierReader(),
198  fClassName( "ReadBDTG_fold1" ),
199  fNvars( 2 ),
200  fIsNormalised( false )
201  {
202  // the training input variables
203  const char* inputVars[] = { "x", "y" };
204 
205  // sanity checks
206  if (theInputVars.size() <= 0) {
207  std::cout << "Problem in class \"" << fClassName << "\": empty input vector" << std::endl;
208  fStatusIsClean = false;
209  }
210 
211  if (theInputVars.size() != fNvars) {
212  std::cout << "Problem in class \"" << fClassName << "\": mismatch in number of input values: "
213  << theInputVars.size() << " != " << fNvars << std::endl;
214  fStatusIsClean = false;
215  }
216 
217  // validate input variables
218  for (size_t ivar = 0; ivar < theInputVars.size(); ivar++) {
219  if (theInputVars[ivar] != inputVars[ivar]) {
220  std::cout << "Problem in class \"" << fClassName << "\": mismatch in input variable names" << std::endl
221  << " for variable [" << ivar << "]: " << theInputVars[ivar].c_str() << " != " << inputVars[ivar] << std::endl;
222  fStatusIsClean = false;
223  }
224  }
225 
226  // initialize min and max vectors (for normalisation)
227  fVmin[0] = 0;
228  fVmax[0] = 0;
229  fVmin[1] = 0;
230  fVmax[1] = 0;
231 
232  // initialize input variable types
233  fType[0] = 'F';
234  fType[1] = 'F';
235 
236  // initialize constants
237  Initialize();
238 
239  }
240 
241  // destructor
242  virtual ~ReadBDTG_fold1() {
243  Clear(); // method-specific
244  }
245 
246  // the classifier response
247  // "inputValues" is a vector of input values in the same order as the
248  // variables given to the constructor
249  double GetMvaValue( const std::vector<double>& inputValues ) const override;
250 
251  private:
252 
253  // method-specific destructor
254  void Clear();
255 
256  // common member variables
257  const char* fClassName;
258 
259  const size_t fNvars;
260  size_t GetNvar() const { return fNvars; }
261  char GetType( int ivar ) const { return fType[ivar]; }
262 
263  // normalisation of input variables
264  const bool fIsNormalised;
265  bool IsNormalised() const { return fIsNormalised; }
266  double fVmin[2];
267  double fVmax[2];
268  double NormVariable( double x, double xmin, double xmax ) const {
269  // normalise to output range: [-1, 1]
270  return 2*(x - xmin)/(xmax - xmin) - 1.0;
271  }
272 
273  // type of input variable: 'F' or 'I'
274  char fType[2];
275 
276  // initialize internal variables
277  void Initialize();
278  double GetMvaValue__( const std::vector<double>& inputValues ) const;
279 
280  // private members (method specific)
281  std::vector<BDTG_fold1Node*> fForest; // i.e. root nodes of decision trees
282  std::vector<double> fBoostWeights; // the weights applied in the individual boosts
283 };
284 
285 double ReadBDTG_fold1::GetMvaValue__( const std::vector<double>& inputValues ) const
286 {
287  double myMVA = 0;
288  for (unsigned int itree=0; itree<fForest.size(); itree++){
289  BDTG_fold1Node *current = fForest[itree];
290  while (current->GetNodeType() == 0) { //intermediate node
291  if (current->GoesRight(inputValues)) current=(BDTG_fold1Node*)current->GetRight();
292  else current=(BDTG_fold1Node*)current->GetLeft();
293  }
294  myMVA += current->GetResponse();
295  }
296  return 2.0/(1.0+exp(-2.0*myMVA))-1.0;
297 };
298 
299 void ReadBDTG_fold1::Initialize()
300 {
301  // itree = 0
302  fBoostWeights.push_back(1);
303  fForest.push_back(
304 NN(
305 NN(
306 NN(
307 0,
308 0,
309 -1, 0, 1, -99, 0.0610392,-0.0877922) ,
310 NN(
311 0,
312 0,
313 -1, 0, 1, -99, 0.584054,0.0168107) ,
314 1, 0.169127, 1, 0, 0.18204,-0.31796) ,
315 NN(
316 NN(
317 0,
318 0,
319 -1, 0, 1, -99, 0.509527,0.00190536) ,
320 NN(
321 0,
322 0,
323 -1, 0, 1, -99, 0.947649,0.0895298) ,
324 1, -0.424705, 1, 0, 0.868995,0.368995) ,
325 0, 0.168077, 1, 0, 0.5,-3.334e-18) );
326  // itree = 1
327  fBoostWeights.push_back(1);
328  fForest.push_back(
329 NN(
330 NN(
331 NN(
332 0,
333 0,
334 -1, 0, 1, -99, 0.0604931,-0.0805479) ,
335 NN(
336 0,
337 0,
338 -1, 0, 1, -99, 0.586735,0.0156706) ,
339 1, 0.477773, 1, 0, 0.129275,-0.337384) ,
340 NN(
341 NN(
342 0,
343 0,
344 -1, 0, 1, -99, 0.277803,-0.0414049) ,
345 NN(
346 0,
347 0,
348 -1, 0, 1, -99, 0.909259,0.0751512) ,
349 1, -0.773803, 1, 0, 0.815895,0.287483) ,
350 0, -0.184051, 1, 0, 0.5,-1.04731e-06) );
351  // itree = 2
352  fBoostWeights.push_back(1);
353  fForest.push_back(
354 NN(
355 NN(
356 NN(
357 0,
358 0,
359 -1, 0, 1, -99, 0.0604931,-0.0739644) ,
360 NN(
361 0,
362 0,
363 -1, 0, 1, -99, 0.586735,0.014115) ,
364 1, 0.477773, 1, 0, 0.129275,-0.303939) ,
365 NN(
366 NN(
367 0,
368 0,
369 -1, 0, 1, -99, 0.277803,-0.0374327) ,
370 NN(
371 0,
372 0,
373 -1, 0, 1, -99, 0.909259,0.0688097) ,
374 1, -0.773803, 1, 0, 0.815895,0.258959) ,
375 0, -0.184051, 1, 0, 0.5,-1.49242e-05) );
376  // itree = 3
377  fBoostWeights.push_back(1);
378  fForest.push_back(
379 NN(
380 NN(
381 NN(
382 0,
383 0,
384 -1, 0, 1, -99, 0.0610392,-0.0692494) ,
385 NN(
386 0,
387 0,
388 -1, 0, 1, -99, 0.584054,0.0141159) ,
389 1, 0.169127, 1, 0, 0.18204,-0.236061) ,
390 NN(
391 NN(
392 0,
393 0,
394 -1, 0, 1, -99, 0.509527,0.000765005) ,
395 NN(
396 0,
397 0,
398 -1, 0, 1, -99, 0.947649,0.0702932) ,
399 1, -0.424705, 1, 0, 0.868995,0.27388) ,
400 0, 0.168077, 1, 0, 0.5,-3.27303e-05) );
401  // itree = 4
402  fBoostWeights.push_back(1);
403  fForest.push_back(
404 NN(
405 NN(
406 NN(
407 0,
408 0,
409 -1, 0, 1, -99, 0.0604931,-0.0646418) ,
410 NN(
411 0,
412 0,
413 -1, 0, 1, -99, 0.586735,0.011325) ,
414 1, 0.477773, 1, 0, 0.129275,-0.249695) ,
415 NN(
416 NN(
417 0,
418 0,
419 -1, 0, 1, -99, 0.477521,-0.0065727) ,
420 NN(
421 0,
422 0,
423 -1, 0, 1, -99, 0.951048,0.0675568) ,
424 1, -0.0756064, 1, 0, 0.815895,0.212704) ,
425 0, -0.184051, 1, 0, 0.5,-3.32777e-05) );
426  // itree = 5
427  fBoostWeights.push_back(1);
428  fForest.push_back(
429 NN(
430 NN(
431 NN(
432 0,
433 0,
434 -1, 0, 1, -99, 0.11852,-0.0548337) ,
435 NN(
436 0,
437 0,
438 -1, 0, 1, -99, 0.765881,0.0346552) ,
439 1, 0.512944, 1, 0, 0.253033,-0.160235) ,
440 NN(
441 NN(
442 0,
443 0,
444 -1, 0, 1, -99, 0.84396,0.04485) ,
445 NN(
446 0,
447 0,
448 -1, 0, 1, -99, 0.974378,0.071908) ,
449 0, 1.12476, 1, 0, 0.926781,0.276846) ,
450 0, 0.520205, 1, 0, 0.5,-2.03051e-05) );
451  // itree = 6
452  fBoostWeights.push_back(1);
453  fForest.push_back(
454 NN(
455 NN(
456 NN(
457 0,
458 0,
459 -1, 0, 1, -99, 0.0171842,-0.0669987) ,
460 NN(
461 0,
462 0,
463 -1, 0, 1, -99, 0.326427,-0.0172672) ,
464 1, -0.466219, 1, 0, 0.129275,-0.206849) ,
465 NN(
466 NN(
467 0,
468 0,
469 -1, 0, 1, -99, 0.277803,-0.0307297) ,
470 NN(
471 0,
472 0,
473 -1, 0, 1, -99, 0.909259,0.0538667) ,
474 1, -0.773803, 1, 0, 0.815895,0.176282) ,
475 0, -0.184051, 1, 0, 0.5,1.42199e-05) );
476  // itree = 7
477  fBoostWeights.push_back(1);
478  fForest.push_back(
479 NN(
480 NN(
481 NN(
482 0,
483 0,
484 -1, 0, 1, -99, 0.0847815,-0.0540118) ,
485 NN(
486 0,
487 0,
488 -1, 0, 1, -99, 0.671607,0.0190117) ,
489 1, 0.169127, 1, 0, 0.253033,-0.133559) ,
490 NN(
491 NN(
492 0,
493 0,
494 -1, 0, 1, -99, 0.84396,0.038713) ,
495 NN(
496 0,
497 0,
498 -1, 0, 1, -99, 0.974378,0.066224) ,
499 0, 1.12476, 1, 0, 0.926781,0.230749) ,
500 0, 0.520205, 1, 0, 0.5,-1.96623e-05) );
501  // itree = 8
502  fBoostWeights.push_back(1);
503  fForest.push_back(
504 NN(
505 NN(
506 NN(
507 0,
508 0,
509 -1, 0, 1, -99, 0.0269133,-0.0664516) ,
510 NN(
511 0,
512 0,
513 -1, 0, 1, -99, 0.167462,-0.0319451) ,
514 0, -1.1406, 1, 0, 0.0819103,-0.209438) ,
515 NN(
516 NN(
517 0,
518 0,
519 -1, 0, 1, -99, 0.290304,-0.0247215) ,
520 NN(
521 0,
522 0,
523 -1, 0, 1, -99, 0.907903,0.0514602) ,
524 1, -0.424705, 1, 0, 0.744712,0.122553) ,
525 0, -0.536179, 1, 0, 0.5,-2.06946e-05) );
526  // itree = 9
527  fBoostWeights.push_back(1);
528  fForest.push_back(
529 NN(
530 NN(
531 NN(
532 0,
533 0,
534 -1, 0, 1, -99, 0.11852,-0.0448111) ,
535 NN(
536 0,
537 0,
538 -1, 0, 1, -99, 0.765881,0.0272904) ,
539 1, 0.512944, 1, 0, 0.253033,-0.112118) ,
540 NN(
541 NN(
542 0,
543 0,
544 -1, 0, 1, -99, 0.84396,0.0337797) ,
545 NN(
546 0,
547 0,
548 -1, 0, 1, -99, 0.974378,0.0620761) ,
549 0, 1.12476, 1, 0, 0.926781,0.193707) ,
550 0, 0.520205, 1, 0, 0.5,-1.58065e-05) );
551  // itree = 10
552  fBoostWeights.push_back(1);
553  fForest.push_back(
554 NN(
555 NN(
556 NN(
557 0,
558 0,
559 -1, 0, 1, -99, 0.0269133,-0.0625391) ,
560 NN(
561 0,
562 0,
563 -1, 0, 1, -99, 0.167462,-0.0272487) ,
564 0, -1.1406, 1, 0, 0.0819103,-0.175874) ,
565 NN(
566 NN(
567 0,
568 0,
569 -1, 0, 1, -99, 0.290304,-0.0218797) ,
570 NN(
571 0,
572 0,
573 -1, 0, 1, -99, 0.907903,0.0470952) ,
574 1, -0.424705, 1, 0, 0.744712,0.10298) ,
575 0, -0.536179, 1, 0, 0.5,2.45668e-05) );
576  // itree = 11
577  fBoostWeights.push_back(1);
578  fForest.push_back(
579 NN(
580 NN(
581 NN(
582 0,
583 0,
584 -1, 0, 1, -99, 0.058119,-0.0503675) ,
585 NN(
586 0,
587 0,
588 -1, 0, 1, -99, 0.584604,0.00988662) ,
589 1, -0.17469, 1, 0, 0.253033,-0.0943229) ,
590 NN(
591 NN(
592 0,
593 0,
594 -1, 0, 1, -99, 0.887254,0.0368556) ,
595 NN(
596 0,
597 0,
598 -1, 0, 1, -99, 0.986396,0.0637205) ,
599 0, 1.57733, 1, 0, 0.926781,0.16305) ,
600 0, 0.520205, 1, 0, 0.5,1.88312e-05) );
601  // itree = 12
602  fBoostWeights.push_back(1);
603  fForest.push_back(
604 NN(
605 NN(
606 NN(
607 0,
608 0,
609 -1, 0, 1, -99, 0.0269133,-0.0594155) ,
610 NN(
611 0,
612 0,
613 -1, 0, 1, -99, 0.167462,-0.0230878) ,
614 0, -1.1406, 1, 0, 0.0819103,-0.148312) ,
615 NN(
616 NN(
617 0,
618 0,
619 -1, 0, 1, -99, 0.37294,-0.0134206) ,
620 NN(
621 0,
622 0,
623 -1, 0, 1, -99, 0.931357,0.0471298) ,
624 1, -0.0756064, 1, 0, 0.744712,0.0867944) ,
625 0, -0.536179, 1, 0, 0.5,-8.82571e-06) );
626  // itree = 13
627  fBoostWeights.push_back(1);
628  fForest.push_back(
629 NN(
630 NN(
631 NN(
632 0,
633 0,
634 -1, 0, 1, -99, 0.0594454,-0.0488664) ,
635 NN(
636 0,
637 0,
638 -1, 0, 1, -99, 0.790212,0.0411457) ,
639 0, 0.991921, 1, 0, 0.11911,-0.127117) ,
640 NN(
641 NN(
642 0,
643 0,
644 -1, 0, 1, -99, 0.141479,-0.0408514) ,
645 NN(
646 0,
647 0,
648 -1, 0, 1, -99, 0.875035,0.0399423) ,
649 0, -0.888307, 1, 0, 0.760598,0.086981) ,
650 1, -0.451145, 1, 0, 0.5,5.96208e-06) );
651  // itree = 14
652  fBoostWeights.push_back(1);
653  fForest.push_back(
654 NN(
655 NN(
656 NN(
657 0,
658 0,
659 -1, 0, 1, -99, 0.198498,-0.0295718) ,
660 NN(
661 0,
662 0,
663 -1, 0, 1, -99, 0.977582,0.0662406) ,
664 1, 1.54439, 1, 0, 0.253033,-0.0738208) ,
665 NN(
666 NN(
667 0,
668 0,
669 -1, 0, 1, -99, 0.84396,0.0236127) ,
670 NN(
671 0,
672 0,
673 -1, 0, 1, -99, 0.974378,0.0547206) ,
674 0, 1.12476, 1, 0, 0.926781,0.127449) ,
675 0, 0.520205, 1, 0, 0.5,-4.39898e-05) );
676  // itree = 15
677  fBoostWeights.push_back(1);
678  fForest.push_back(
679 NN(
680 NN(
681 NN(
682 0,
683 0,
684 -1, 0, 1, -99, 0.0594454,-0.0455581) ,
685 NN(
686 0,
687 0,
688 -1, 0, 1, -99, 0.790212,0.0335669) ,
689 0, 0.991921, 1, 0, 0.11911,-0.109782) ,
690 NN(
691 NN(
692 0,
693 0,
694 -1, 0, 1, -99, 0.141479,-0.0365224) ,
695 NN(
696 0,
697 0,
698 -1, 0, 1, -99, 0.875035,0.0368954) ,
699 0, -0.888307, 1, 0, 0.760598,0.0752172) ,
700 1, -0.451145, 1, 0, 0.5,6.30754e-05) );
701  // itree = 16
702  fBoostWeights.push_back(1);
703  fForest.push_back(
704 NN(
705 NN(
706 NN(
707 0,
708 0,
709 -1, 0, 1, -99, 0.0594454,-0.0433557) ,
710 NN(
711 0,
712 0,
713 -1, 0, 1, -99, 0.790212,0.0308133) ,
714 0, 0.991921, 1, 0, 0.11911,-0.0991083) ,
715 NN(
716 NN(
717 0,
718 0,
719 -1, 0, 1, -99, 0.141479,-0.0338907) ,
720 NN(
721 0,
722 0,
723 -1, 0, 1, -99, 0.875035,0.0344383) ,
724 0, -0.888307, 1, 0, 0.760598,0.067829) ,
725 1, -0.451145, 1, 0, 0.5,1.24181e-05) );
726  // itree = 17
727  fBoostWeights.push_back(1);
728  fForest.push_back(
729 NN(
730 NN(
731 NN(
732 0,
733 0,
734 -1, 0, 1, -99, 0.198498,-0.0258349) ,
735 NN(
736 0,
737 0,
738 -1, 0, 1, -99, 0.977582,0.0628846) ,
739 1, 1.54439, 1, 0, 0.253033,-0.0577541) ,
740 NN(
741 NN(
742 0,
743 0,
744 -1, 0, 1, -99, 0.887254,0.0265332) ,
745 NN(
746 0,
747 0,
748 -1, 0, 1, -99, 0.986396,0.0565096) ,
749 0, 1.57733, 1, 0, 0.926781,0.0997211) ,
750 0, 0.520205, 1, 0, 0.5,-3.0538e-05) );
751  // itree = 18
752  fBoostWeights.push_back(1);
753  fForest.push_back(
754 NN(
755 NN(
756 NN(
757 0,
758 0,
759 -1, 0, 1, -99, 0.118594,-0.0335015) ,
760 NN(
761 0,
762 0,
763 -1, 0, 1, -99, 0.912886,0.0461158) ,
764 0, 1.3101, 1, 0, 0.17372,-0.0728711) ,
765 NN(
766 NN(
767 0,
768 0,
769 -1, 0, 1, -99, 0.155679,-0.0350704) ,
770 NN(
771 0,
772 0,
773 -1, 0, 1, -99, 0.914541,0.0374728) ,
774 0, -0.888307, 1, 0, 0.817576,0.0710371) ,
775 1, -0.099843, 1, 0, 0.5,5.5786e-05) );
776  // itree = 19
777  fBoostWeights.push_back(1);
778  fForest.push_back(
779 NN(
780 NN(
781 NN(
782 0,
783 0,
784 -1, 0, 1, -99, 0.0244702,-0.0488661) ,
785 NN(
786 0,
787 0,
788 -1, 0, 1, -99, 0.683042,0.0186654) ,
789 0, 0.695251, 1, 0, 0.0771828,-0.0972312) ,
790 NN(
791 NN(
792 0,
793 0,
794 -1, 0, 1, -99, 0.108215,-0.0306924) ,
795 NN(
796 0,
797 0,
798 -1, 0, 1, -99, 0.830195,0.0273648) ,
799 0, -0.888307, 1, 0, 0.693048,0.0445006) ,
800 1, -0.802446, 1, 0, 0.5,7.36319e-05) );
801  // itree = 20
802  fBoostWeights.push_back(1);
803  fForest.push_back(
804 NN(
805 NN(
806 NN(
807 0,
808 0,
809 -1, 0, 1, -99, 0.177786,-0.0259838) ,
810 NN(
811 0,
812 0,
813 -1, 0, 1, -99, 0.892914,0.027206) ,
814 0, 0.705902, 1, 0, 0.340555,-0.0374682) ,
815 NN(
816 NN(
817 0,
818 0,
819 -1, 0, 1, -99, 0.53682,0.00161695) ,
820 NN(
821 0,
822 0,
823 -1, 0, 1, -99, 0.991571,0.0538552) ,
824 0, -0.295611, 1, 0, 0.940187,0.10339) ,
825 1, 0.954062, 1, 0, 0.5,-1.34912e-05) );
826  // itree = 21
827  fBoostWeights.push_back(1);
828  fForest.push_back(
829 NN(
830 NN(
831 NN(
832 0,
833 0,
834 -1, 0, 1, -99, 0.0594454,-0.0364064) ,
835 NN(
836 0,
837 0,
838 -1, 0, 1, -99, 0.790212,0.018695) ,
839 0, 0.991921, 1, 0, 0.11911,-0.068922) ,
840 NN(
841 NN(
842 0,
843 0,
844 -1, 0, 1, -99, 0.0241374,-0.0583516) ,
845 NN(
846 0,
847 0,
848 -1, 0, 1, -99, 0.816318,0.02457) ,
849 0, -1.59256, 1, 0, 0.760598,0.0472754) ,
850 1, -0.451145, 1, 0, 0.5,7.13531e-05) );
851  // itree = 22
852  fBoostWeights.push_back(1);
853  fForest.push_back(
854 NN(
855 NN(
856 NN(
857 0,
858 0,
859 -1, 0, 1, -99, 0.177786,-0.0234208) ,
860 NN(
861 0,
862 0,
863 -1, 0, 1, -99, 0.892914,0.0244807) ,
864 0, 0.705902, 1, 0, 0.340555,-0.0321135) ,
865 NN(
866 NN(
867 0,
868 0,
869 -1, 0, 1, -99, 0.53682,0.000417545) ,
870 NN(
871 0,
872 0,
873 -1, 0, 1, -99, 0.991571,0.0522709) ,
874 0, -0.295611, 1, 0, 0.940187,0.0886792) ,
875 1, 0.954062, 1, 0, 0.5,5.82558e-06) );
876  // itree = 23
877  fBoostWeights.push_back(1);
878  fForest.push_back(
879 NN(
880 NN(
881 NN(
882 0,
883 0,
884 -1, 0, 1, -99, 0.0244702,-0.0445412) ,
885 NN(
886 0,
887 0,
888 -1, 0, 1, -99, 0.683042,0.0118304) ,
889 0, 0.695251, 1, 0, 0.0771828,-0.0738399) ,
890 NN(
891 NN(
892 0,
893 0,
894 -1, 0, 1, -99, 0.0171842,-0.0555155) ,
895 NN(
896 0,
897 0,
898 -1, 0, 1, -99, 0.756193,0.0196183) ,
899 0, -1.59256, 1, 0, 0.693048,0.0338308) ,
900 1, -0.802446, 1, 0, 0.5,8.05718e-05) );
901  // itree = 24
902  fBoostWeights.push_back(1);
903  fForest.push_back(
904 NN(
905 NN(
906 NN(
907 0,
908 0,
909 -1, 0, 1, -99, 0.254582,-0.0181754) ,
910 NN(
911 0,
912 0,
913 -1, 0, 1, -99, 0.966368,0.0447261) ,
914 0, 1.38455, 1, 0, 0.340555,-0.027836) ,
915 NN(
916 NN(
917 0,
918 0,
919 -1, 0, 1, -99, 0.873353,0.0197781) ,
920 NN(
921 0,
922 0,
923 -1, 0, 1, -99, 0.993291,0.0563811) ,
924 1, 1.63208, 1, 0, 0.940187,0.0767865) ,
925 1, 0.954062, 1, 0, 0.5,-1.64141e-05) );
926  // itree = 25
927  fBoostWeights.push_back(1);
928  fForest.push_back(
929 NN(
930 NN(
931 NN(
932 0,
933 0,
934 -1, 0, 1, -99, 0.0363442,-0.0421857) ,
935 NN(
936 0,
937 0,
938 -1, 0, 1, -99, 0.158106,0.00413915) ,
939 0, -1.02848, 1, 0, 0.0501331,-0.0702394) ,
940 NN(
941 NN(
942 0,
943 0,
944 -1, 0, 1, -99, 0.113401,-0.030213) ,
945 NN(
946 0,
947 0,
948 -1, 0, 1, -99, 0.794178,0.0201904) ,
949 1, -1.15375, 1, 0, 0.67626,0.0276052) ,
950 0, -0.888307, 1, 0, 0.5,6.11253e-05) );
951  // itree = 26
952  fBoostWeights.push_back(1);
953  fForest.push_back(
954 NN(
955 NN(
956 NN(
957 0,
958 0,
959 -1, 0, 1, -99, 0.125999,-0.0240124) ,
960 NN(
961 0,
962 0,
963 -1, 0, 1, -99, 0.931929,0.0399688) ,
964 0, 1.62828, 1, 0, 0.17372,-0.041198) ,
965 NN(
966 NN(
967 0,
968 0,
969 -1, 0, 1, -99, 0.0900304,-0.0369231) ,
970 NN(
971 0,
972 0,
973 -1, 0, 1, -99, 0.88811,0.0252862) ,
974 0, -1.24044, 1, 0, 0.817576,0.0401103) ,
975 1, -0.099843, 1, 0, 0.5,5.78297e-06) );
976  // itree = 27
977  fBoostWeights.push_back(1);
978  fForest.push_back(
979 NN(
980 NN(
981 NN(
982 0,
983 0,
984 -1, 0, 1, -99, 0.254582,-0.0158925) ,
985 NN(
986 0,
987 0,
988 -1, 0, 1, -99, 0.966368,0.0415449) ,
989 0, 1.38455, 1, 0, 0.340555,-0.0229766) ,
990 NN(
991 NN(
992 0,
993 0,
994 -1, 0, 1, -99, 0.53682,-0.0029293) ,
995 NN(
996 0,
997 0,
998 -1, 0, 1, -99, 0.991571,0.0492915) ,
999 0, -0.295611, 1, 0, 0.940187,0.0634649) ,
1000 1, 0.954062, 1, 0, 0.5,8.54987e-06) );
1001  // itree = 28
1002  fBoostWeights.push_back(1);
1003  fForest.push_back(
1004 NN(
1005 NN(
1006 NN(
1007 0,
1008 0,
1009 -1, 0, 1, -99, 0.0244702,-0.0401959) ,
1010 NN(
1011 0,
1012 0,
1013 -1, 0, 1, -99, 0.683042,0.00892751) ,
1014 0, 0.695251, 1, 0, 0.0771828,-0.05461) ,
1015 NN(
1016 NN(
1017 0,
1018 0,
1019 -1, 0, 1, -99, 0.0171842,-0.0512028) ,
1020 NN(
1021 0,
1022 0,
1023 -1, 0, 1, -99, 0.756193,0.016098) ,
1024 0, -1.59256, 1, 0, 0.693048,0.0250589) ,
1025 1, -0.802446, 1, 0, 0.5,8.60263e-05) );
1026  // itree = 29
1027  fBoostWeights.push_back(1);
1028  fForest.push_back(
1029 NN(
1030 NN(
1031 NN(
1032 0,
1033 0,
1034 -1, 0, 1, -99, 0.0363442,-0.0381709) ,
1035 NN(
1036 0,
1037 0,
1038 -1, 0, 1, -99, 0.158106,0.00686703) ,
1039 0, -1.02848, 1, 0, 0.0501331,-0.0538328) ,
1040 NN(
1041 NN(
1042 0,
1043 0,
1044 -1, 0, 1, -99, 0.0764554,-0.0459829) ,
1045 NN(
1046 0,
1047 0,
1048 -1, 0, 1, -99, 0.723776,0.0140177) ,
1049 1, -1.85635, 1, 0, 0.67626,0.0211074) ,
1050 0, -0.888307, 1, 0, 0.5,1.10898e-05) );
1051  // itree = 30
1052  fBoostWeights.push_back(1);
1053  fForest.push_back(
1054 NN(
1055 NN(
1056 NN(
1057 0,
1058 0,
1059 -1, 0, 1, -99, 0.254582,-0.0142875) ,
1060 NN(
1061 0,
1062 0,
1063 -1, 0, 1, -99, 0.966368,0.0389207) ,
1064 0, 1.38455, 1, 0, 0.340555,-0.0196673) ,
1065 NN(
1066 NN(
1067 0,
1068 0,
1069 -1, 0, 1, -99, 0.873353,0.0138784) ,
1070 NN(
1071 0,
1072 0,
1073 -1, 0, 1, -99, 0.993291,0.0546996) ,
1074 1, 1.63208, 1, 0, 0.940187,0.0541639) ,
1075 1, 0.954062, 1, 0, 0.5,-3.5239e-05) );
1076  // itree = 31
1077  fBoostWeights.push_back(1);
1078  fForest.push_back(
1079 NN(
1080 NN(
1081 NN(
1082 0,
1083 0,
1084 -1, 0, 1, -99, 0.0244702,-0.037653) ,
1085 NN(
1086 0,
1087 0,
1088 -1, 0, 1, -99, 0.683042,0.0075221) ,
1089 0, 0.695251, 1, 0, 0.0771828,-0.0456496) ,
1090 NN(
1091 NN(
1092 0,
1093 0,
1094 -1, 0, 1, -99, 0.0171842,-0.0485902) ,
1095 NN(
1096 0,
1097 0,
1098 -1, 0, 1, -99, 0.756193,0.01394) ,
1099 0, -1.59256, 1, 0, 0.693048,0.0208786) ,
1100 1, -0.802446, 1, 0, 0.5,2.48321e-05) );
1101  // itree = 32
1102  fBoostWeights.push_back(1);
1103  fForest.push_back(
1104 NN(
1105 NN(
1106 NN(
1107 0,
1108 0,
1109 -1, 0, 1, -99, 0.254582,-0.0128456) ,
1110 NN(
1111 0,
1112 0,
1113 -1, 0, 1, -99, 0.966368,0.0367079) ,
1114 0, 1.38455, 1, 0, 0.340555,-0.0171567) ,
1115 NN(
1116 NN(
1117 0,
1118 0,
1119 -1, 0, 1, -99, 0.53682,-0.00512096) ,
1120 NN(
1121 0,
1122 0,
1123 -1, 0, 1, -99, 0.991571,0.0468567) ,
1124 0, -0.295611, 1, 0, 0.940187,0.0472442) ,
1125 1, 0.954062, 1, 0, 0.5,-3.21884e-05) );
1126  // itree = 33
1127  fBoostWeights.push_back(1);
1128  fForest.push_back(
1129 NN(
1130 NN(
1131 NN(
1132 0,
1133 0,
1134 -1, 0, 1, -99, 0.0263309,-0.0508513) ,
1135 NN(
1136 0,
1137 0,
1138 -1, 0, 1, -99, 0.0936194,-0.0191303) ,
1139 1, -2.01277, 1, 0, 0.0771828,-0.0401126) ,
1140 NN(
1141 NN(
1142 0,
1143 0,
1144 -1, 0, 1, -99, 0.0171842,-0.0468234) ,
1145 NN(
1146 0,
1147 0,
1148 -1, 0, 1, -99, 0.756193,0.0126047) ,
1149 0, -1.59256, 1, 0, 0.693048,0.01836) ,
1150 1, -0.802446, 1, 0, 0.5,3.12633e-05) );
1151  // itree = 34
1152  fBoostWeights.push_back(1);
1153  fForest.push_back(
1154 NN(
1155 NN(
1156 NN(
1157 0,
1158 0,
1159 -1, 0, 1, -99, 0.0363442,-0.0343219) ,
1160 NN(
1161 0,
1162 0,
1163 -1, 0, 1, -99, 0.158106,0.00880954) ,
1164 0, -1.02848, 1, 0, 0.0501331,-0.0408549) ,
1165 NN(
1166 NN(
1167 0,
1168 0,
1169 -1, 0, 1, -99, 0.0764554,-0.0402647) ,
1170 NN(
1171 0,
1172 0,
1173 -1, 0, 1, -99, 0.723776,0.0113915) ,
1174 1, -1.85635, 1, 0, 0.67626,0.015998) ,
1175 0, -0.888307, 1, 0, 0.5,-6.58108e-06) );
1176  // itree = 35
1177  fBoostWeights.push_back(1);
1178  fForest.push_back(
1179 NN(
1180 NN(
1181 NN(
1182 0,
1183 0,
1184 -1, 0, 1, -99, 0.254582,-0.0116068) ,
1185 NN(
1186 0,
1187 0,
1188 -1, 0, 1, -99, 0.966368,0.0349579) ,
1189 0, 1.38455, 1, 0, 0.340555,-0.0148274) ,
1190 NN(
1191 NN(
1192 0,
1193 0,
1194 -1, 0, 1, -99, 0.873353,0.00929991) ,
1195 NN(
1196 0,
1197 0,
1198 -1, 0, 1, -99, 0.993291,0.0536164) ,
1199 1, 1.63208, 1, 0, 0.940187,0.0407904) ,
1200 1, 0.954062, 1, 0, 0.5,-3.83664e-05) );
1201  // itree = 36
1202  fBoostWeights.push_back(1);
1203  fForest.push_back(
1204 NN(
1205 NN(
1206 NN(
1207 0,
1208 0,
1209 -1, 0, 1, -99, 0.0244702,-0.0335747) ,
1210 NN(
1211 0,
1212 0,
1213 -1, 0, 1, -99, 0.683042,0.00800618) ,
1214 0, 0.695251, 1, 0, 0.0771828,-0.0336746) ,
1215 NN(
1216 NN(
1217 0,
1218 0,
1219 -1, 0, 1, -99, 0.0171842,-0.0443441) ,
1220 NN(
1221 0,
1222 0,
1223 -1, 0, 1, -99, 0.756193,0.0108877) ,
1224 0, -1.59256, 1, 0, 0.693048,0.0153896) ,
1225 1, -0.802446, 1, 0, 0.5,1.00501e-05) );
1226  // itree = 37
1227  fBoostWeights.push_back(1);
1228  fForest.push_back(
1229 NN(
1230 NN(
1231 NN(
1232 0,
1233 0,
1234 -1, 0, 1, -99, 0.198498,-0.0123265) ,
1235 NN(
1236 0,
1237 0,
1238 -1, 0, 1, -99, 0.977582,0.0532691) ,
1239 1, 1.54439, 1, 0, 0.253033,-0.0165631) ,
1240 NN(
1241 NN(
1242 0,
1243 0,
1244 -1, 0, 1, -99, 0.76014,-0.0108702) ,
1245 NN(
1246 0,
1247 0,
1248 -1, 0, 1, -99, 0.943352,0.0236879) ,
1249 0, 0.672178, 1, 0, 0.926781,0.0285406) ,
1250 0, 0.520205, 1, 0, 0.5,-3.00341e-05) );
1251  // itree = 38
1252  fBoostWeights.push_back(1);
1253  fForest.push_back(
1254 NN(
1255 NN(
1256 NN(
1257 0,
1258 0,
1259 -1, 0, 1, -99, 0.0363442,-0.031186) ,
1260 NN(
1261 0,
1262 0,
1263 -1, 0, 1, -99, 0.158106,0.0083403) ,
1264 0, -1.02848, 1, 0, 0.0501331,-0.0330191) ,
1265 NN(
1266 NN(
1267 0,
1268 0,
1269 -1, 0, 1, -99, 0.0764554,-0.0380627) ,
1270 NN(
1271 0,
1272 0,
1273 -1, 0, 1, -99, 0.723776,0.00981384) ,
1274 1, -1.85635, 1, 0, 0.67626,0.0129341) ,
1275 0, -0.888307, 1, 0, 0.5,-2.09938e-06) );
1276  // itree = 39
1277  fBoostWeights.push_back(1);
1278  fForest.push_back(
1279 NN(
1280 NN(
1281 NN(
1282 0,
1283 0,
1284 -1, 0, 1, -99, 0.254582,-0.00991087) ,
1285 NN(
1286 0,
1287 0,
1288 -1, 0, 1, -99, 0.966368,0.0313894) ,
1289 0, 1.38455, 1, 0, 0.340555,-0.0121709) ,
1290 NN(
1291 NN(
1292 0,
1293 0,
1294 -1, 0, 1, -99, 0.53682,-0.006375) ,
1295 NN(
1296 0,
1297 0,
1298 -1, 0, 1, -99, 0.991571,0.044009) ,
1299 0, -0.295611, 1, 0, 0.940187,0.0335003) ,
1300 1, 0.954062, 1, 0, 0.5,-2.67015e-05) );
1301  // itree = 40
1302  fBoostWeights.push_back(1);
1303  fForest.push_back(
1304 NN(
1305 NN(
1306 NN(
1307 0,
1308 0,
1309 -1, 0, 1, -99, 0,-0.0710486) ,
1310 NN(
1311 0,
1312 0,
1313 -1, 0, 1, -99, 0.0647707,-0.0222992) ,
1314 1, -2.56046, 1, 0, 0.0572027,-0.03332) ,
1315 NN(
1316 NN(
1317 0,
1318 0,
1319 -1, 0, 1, -99, 0.0138893,-0.0427468) ,
1320 NN(
1321 0,
1322 0,
1323 -1, 0, 1, -99, 0.71232,0.0087416) ,
1324 0, -1.59256, 1, 0, 0.645026,0.0109381) ,
1325 1, -1.15375, 1, 0, 0.5,1.8841e-05) );
1326  // itree = 41
1327  fBoostWeights.push_back(1);
1328  fForest.push_back(
1329 NN(
1330 NN(
1331 NN(
1332 0,
1333 0,
1334 -1, 0, 1, -99, 0.230547,-0.0104658) ,
1335 NN(
1336 0,
1337 0,
1338 -1, 0, 1, -99, 0.922406,0.0167985) ,
1339 0, 0.705902, 1, 0, 0.416954,-0.00750092) ,
1340 NN(
1341 NN(
1342 0,
1343 0,
1344 -1, 0, 1, -99, 0.964765,0.049868) ,
1345 NN(
1346 0,
1347 0,
1348 -1, 0, 1, -99, 1,0.0518515) ,
1349 0, 0.285969, 1, 0, 0.993104,0.0444573) ,
1350 1, 1.65666, 1, 0, 0.5,-1.16977e-05) );
1351  // itree = 42
1352  fBoostWeights.push_back(1);
1353  fForest.push_back(
1354 NN(
1355 NN(
1356 NN(
1357 0,
1358 0,
1359 -1, 0, 1, -99, 0.00437091,-0.0475965) ,
1360 NN(
1361 0,
1362 0,
1363 -1, 0, 1, -99, 0.269797,0.00185051) ,
1364 0, -0.598964, 1, 0, 0.11911,-0.0209315) ,
1365 NN(
1366 NN(
1367 0,
1368 0,
1369 -1, 0, 1, -99, 0.672094,0.00174875) ,
1370 NN(
1371 0,
1372 0,
1373 -1, 0, 1, -99, 0.993913,0.0511398) ,
1374 1, 1.55881, 1, 0, 0.760598,0.0143512) ,
1375 1, -0.451145, 1, 0, 0.5,1.79948e-05) );
1376  // itree = 43
1377  fBoostWeights.push_back(1);
1378  fForest.push_back(
1379 NN(
1380 NN(
1381 NN(
1382 0,
1383 0,
1384 -1, 0, 1, -99, 0,-0.0721338) ,
1385 NN(
1386 0,
1387 0,
1388 -1, 0, 1, -99, 0.0647707,-0.0195298) ,
1389 1, -2.56046, 1, 0, 0.0572027,-0.0276469) ,
1390 NN(
1391 NN(
1392 0,
1393 0,
1394 -1, 0, 1, -99, 0.0138893,-0.0413179) ,
1395 NN(
1396 0,
1397 0,
1398 -1, 0, 1, -99, 0.71232,0.00757684) ,
1399 0, -1.59256, 1, 0, 0.645026,0.00906198) ,
1400 1, -1.15375, 1, 0, 0.5,5.27552e-06) );
1401  // itree = 44
1402  fBoostWeights.push_back(1);
1403  fForest.push_back(
1404 NN(
1405 NN(
1406 NN(
1407 0,
1408 0,
1409 -1, 0, 1, -99, 0.338236,-0.00693082) ,
1410 NN(
1411 0,
1412 0,
1413 -1, 0, 1, -99, 0.990331,0.0487365) ,
1414 1, 1.65666, 1, 0, 0.416751,-0.00636573) ,
1415 NN(
1416 NN(
1417 0,
1418 0,
1419 -1, 0, 1, -99, 0.943608,0.0293521) ,
1420 NN(
1421 0,
1422 0,
1423 -1, 0, 1, -99, 1,0.0516743) ,
1424 1, 0.0158096, 1, 0, 0.986396,0.0370637) ,
1425 0, 1.57659, 1, 0, 0.5,-1.88926e-05) );
1426  // itree = 45
1427  fBoostWeights.push_back(1);
1428  fForest.push_back(
1429 NN(
1430 NN(
1431 NN(
1432 0,
1433 0,
1434 -1, 0, 1, -99, 0.0363442,-0.0263592) ,
1435 NN(
1436 0,
1437 0,
1438 -1, 0, 1, -99, 0.158106,0.0111867) ,
1439 0, -1.02848, 1, 0, 0.0501331,-0.0228024) ,
1440 NN(
1441 NN(
1442 0,
1443 0,
1444 -1, 0, 1, -99, 0.0764554,-0.0318347) ,
1445 NN(
1446 0,
1447 0,
1448 -1, 0, 1, -99, 0.723776,0.00736702) ,
1449 1, -1.85635, 1, 0, 0.67626,0.00895893) ,
1450 0, -0.888307, 1, 0, 0.5,1.78522e-05) );
1451  // itree = 46
1452  fBoostWeights.push_back(1);
1453  fForest.push_back(
1454 NN(
1455 NN(
1456 NN(
1457 0,
1458 0,
1459 -1, 0, 1, -99, 0.125999,-0.0114811) ,
1460 NN(
1461 0,
1462 0,
1463 -1, 0, 1, -99, 0.931929,0.0222947) ,
1464 0, 1.62828, 1, 0, 0.17372,-0.0141024) ,
1465 NN(
1466 NN(
1467 0,
1468 0,
1469 -1, 0, 1, -99, 0.155679,-0.010867) ,
1470 NN(
1471 0,
1472 0,
1473 -1, 0, 1, -99, 0.914541,0.0131362) ,
1474 0, -0.888307, 1, 0, 0.817576,0.0137273) ,
1475 1, -0.099843, 1, 0, 0.5,5.68542e-07) );
1476  // itree = 47
1477  fBoostWeights.push_back(1);
1478  fForest.push_back(
1479 NN(
1480 NN(
1481 NN(
1482 0,
1483 0,
1484 -1, 0, 1, -99, 0.338236,-0.00614819) ,
1485 NN(
1486 0,
1487 0,
1488 -1, 0, 1, -99, 0.990331,0.0477068) ,
1489 1, 1.65666, 1, 0, 0.416751,-0.00545105) ,
1490 NN(
1491 NN(
1492 0,
1493 0,
1494 -1, 0, 1, -99, 0.943608,0.0265581) ,
1495 NN(
1496 0,
1497 0,
1498 -1, 0, 1, -99, 1,0.0514496) ,
1499 1, 0.0158096, 1, 0, 0.986396,0.0318743) ,
1500 0, 1.57659, 1, 0, 0.5,3.73131e-06) );
1501  // itree = 48
1502  fBoostWeights.push_back(1);
1503  fForest.push_back(
1504 NN(
1505 NN(
1506 NN(
1507 0,
1508 0,
1509 -1, 0, 1, -99, 0,-0.0743739) ,
1510 NN(
1511 0,
1512 0,
1513 -1, 0, 1, -99, 0.0647707,-0.016484) ,
1514 1, -2.56046, 1, 0, 0.0572027,-0.0222534) ,
1515 NN(
1516 NN(
1517 0,
1518 0,
1519 -1, 0, 1, -99, 0.0138893,-0.038743) ,
1520 NN(
1521 0,
1522 0,
1523 -1, 0, 1, -99, 0.71232,0.0063914) ,
1524 0, -1.59256, 1, 0, 0.645026,0.00733281) ,
1525 1, -1.15375, 1, 0, 0.5,3.33683e-05) );
1526  // itree = 49
1527  fBoostWeights.push_back(1);
1528  fForest.push_back(
1529 NN(
1530 NN(
1531 NN(
1532 0,
1533 0,
1534 -1, 0, 1, -99, 0.338236,-0.0055962) ,
1535 NN(
1536 0,
1537 0,
1538 -1, 0, 1, -99, 0.990331,0.0465917) ,
1539 1, 1.65666, 1, 0, 0.416751,-0.00492846) ,
1540 NN(
1541 NN(
1542 0,
1543 0,
1544 -1, 0, 1, -99, 0.943608,0.0254772) ,
1545 NN(
1546 0,
1547 0,
1548 -1, 0, 1, -99, 1,0.0512915) ,
1549 1, 0.0158096, 1, 0, 0.986396,0.0288726) ,
1550 0, 1.57659, 1, 0, 0.5,1.1279e-05) );
1551  // itree = 50
1552  fBoostWeights.push_back(1);
1553  fForest.push_back(
1554 NN(
1555 NN(
1556 NN(
1557 0,
1558 0,
1559 -1, 0, 1, -99, 0,-0.0517908) ,
1560 NN(
1561 0,
1562 0,
1563 -1, 0, 1, -99, 0.194183,0.00251008) ,
1564 0, -0.566704, 1, 0, 0.0771828,-0.0170066) ,
1565 NN(
1566 NN(
1567 0,
1568 0,
1569 -1, 0, 1, -99, 0.0171842,-0.0356985) ,
1570 NN(
1571 0,
1572 0,
1573 -1, 0, 1, -99, 0.756193,0.00630574) ,
1574 0, -1.59256, 1, 0, 0.693048,0.00781852) ,
1575 1, -0.802446, 1, 0, 0.5,3.68857e-05) );
1576  // itree = 51
1577  fBoostWeights.push_back(1);
1578  fForest.push_back(
1579 NN(
1580 NN(
1581 NN(
1582 0,
1583 0,
1584 -1, 0, 1, -99, 0.309253,-0.00519615) ,
1585 NN(
1586 0,
1587 0,
1588 -1, 0, 1, -99, 1,0.0545507) ,
1589 0, 2.0632, 1, 0, 0.340555,-0.00647034) ,
1590 NN(
1591 NN(
1592 0,
1593 0,
1594 -1, 0, 1, -99, 0.53682,-0.00980086) ,
1595 NN(
1596 0,
1597 0,
1598 -1, 0, 1, -99, 0.991571,0.0390563) ,
1599 0, -0.295611, 1, 0, 0.940187,0.0178687) ,
1600 1, 0.954062, 1, 0, 0.5,1.52352e-06) );
1601  // itree = 52
1602  fBoostWeights.push_back(1);
1603  fForest.push_back(
1604 NN(
1605 NN(
1606 NN(
1607 0,
1608 0,
1609 -1, 0, 1, -99, 0.0052002,-0.0430096) ,
1610 NN(
1611 0,
1612 0,
1613 -1, 0, 1, -99, 0.247887,0.00447917) ,
1614 0, -0.161497, 1, 0, 0.0572027,-0.0178779) ,
1615 NN(
1616 NN(
1617 0,
1618 0,
1619 -1, 0, 1, -99, 0.565336,0.000396972) ,
1620 NN(
1621 0,
1622 0,
1623 -1, 0, 1, -99, 1,0.0525546) ,
1624 0, 1.57659, 1, 0, 0.645026,0.00589264) ,
1625 1, -1.15375, 1, 0, 0.5,2.80326e-05) );
1626  // itree = 53
1627  fBoostWeights.push_back(1);
1628  fForest.push_back(
1629 NN(
1630 NN(
1631 NN(
1632 0,
1633 0,
1634 -1, 0, 1, -99, 0.0108445,-0.0395085) ,
1635 NN(
1636 0,
1637 0,
1638 -1, 0, 1, -99, 0.529651,0.00138958) ,
1639 0, -1.33005, 1, 0, 0.416954,-0.00393682) ,
1640 NN(
1641 NN(
1642 0,
1643 0,
1644 -1, 0, 1, -99, 0.964765,0.0401775) ,
1645 NN(
1646 0,
1647 0,
1648 -1, 0, 1, -99, 1,0.0509447) ,
1649 0, 0.285969, 1, 0, 0.993104,0.0235445) ,
1650 1, 1.65666, 1, 0, 0.5,2.43077e-05) );
1651  // itree = 54
1652  fBoostWeights.push_back(1);
1653  fForest.push_back(
1654 NN(
1655 NN(
1656 NN(
1657 0,
1658 0,
1659 -1, 0, 1, -99, 0.00437091,-0.0447747) ,
1660 NN(
1661 0,
1662 0,
1663 -1, 0, 1, -99, 0.269797,0.00403081) ,
1664 0, -0.598964, 1, 0, 0.11911,-0.011196) ,
1665 NN(
1666 NN(
1667 0,
1668 0,
1669 -1, 0, 1, -99, 0.672094,0.000714424) ,
1670 NN(
1671 0,
1672 0,
1673 -1, 0, 1, -99, 0.993913,0.0472208) ,
1674 1, 1.55881, 1, 0, 0.760598,0.00769084) ,
1675 1, -0.451145, 1, 0, 0.5,1.826e-05) );
1676  // itree = 55
1677  fBoostWeights.push_back(1);
1678  fForest.push_back(
1679 NN(
1680 NN(
1681 0,
1682 0,
1683 -1, 0, 1, -99, 0,-0.0777977) ,
1684 NN(
1685 NN(
1686 0,
1687 0,
1688 -1, 0, 1, -99, 0.430794,-0.00164185) ,
1689 NN(
1690 0,
1691 0,
1692 -1, 0, 1, -99, 0.993152,0.0428626) ,
1693 0, 1.57659, 1, 0, 0.514841,0.0015663) ,
1694 1, -2.55895, 1, 0, 0.5,6.81128e-06) );
1695  // itree = 56
1696  fBoostWeights.push_back(1);
1697  fForest.push_back(
1698 NN(
1699 NN(
1700 NN(
1701 0,
1702 0,
1703 -1, 0, 1, -99, 0,-0.077741) ,
1704 NN(
1705 0,
1706 0,
1707 -1, 0, 1, -99, 0.0555249,-0.0189464) ,
1708 1, -2.60989, 1, 0, 0.0401405,-0.0255316) ,
1709 NN(
1710 NN(
1711 0,
1712 0,
1713 -1, 0, 1, -99, 0.00881729,-0.0384934) ,
1714 NN(
1715 0,
1716 0,
1717 -1, 0, 1, -99, 0.630347,0.0038962) ,
1718 0, -1.59256, 1, 0, 0.551353,0.00286485) ,
1719 1, -1.85635, 1, 0, 0.5,1.23179e-05) );
1720  // itree = 57
1721  fBoostWeights.push_back(1);
1722  fForest.push_back(
1723 NN(
1724 NN(
1725 NN(
1726 0,
1727 0,
1728 -1, 0, 1, -99, 0.00437091,-0.0437085) ,
1729 NN(
1730 0,
1731 0,
1732 -1, 0, 1, -99, 0.269797,0.00380688) ,
1733 0, -0.598964, 1, 0, 0.11911,-0.00954598) ,
1734 NN(
1735 NN(
1736 0,
1737 0,
1738 -1, 0, 1, -99, 0.672094,0.000410689) ,
1739 NN(
1740 0,
1741 0,
1742 -1, 0, 1, -99, 0.993913,0.0462078) ,
1743 1, 1.55881, 1, 0, 0.760598,0.00652462) ,
1744 1, -0.451145, 1, 0, 0.5,-3.89824e-06) );
1745  // itree = 58
1746  fBoostWeights.push_back(1);
1747  fForest.push_back(
1748 NN(
1749 NN(
1750 NN(
1751 0,
1752 0,
1753 -1, 0, 1, -99, 0,-0.0776625) ,
1754 NN(
1755 0,
1756 0,
1757 -1, 0, 1, -99, 0.0555249,-0.0168712) ,
1758 1, -2.60989, 1, 0, 0.0401405,-0.0223776) ,
1759 NN(
1760 NN(
1761 0,
1762 0,
1763 -1, 0, 1, -99, 0.00881729,-0.0369973) ,
1764 NN(
1765 0,
1766 0,
1767 -1, 0, 1, -99, 0.630347,0.00342103) ,
1768 0, -1.59256, 1, 0, 0.551353,0.00248613) ,
1769 1, -1.85635, 1, 0, 0.5,-1.15264e-05) );
1770  // itree = 59
1771  fBoostWeights.push_back(1);
1772  fForest.push_back(
1773 NN(
1774 NN(
1775 NN(
1776 0,
1777 0,
1778 -1, 0, 1, -99, 0.210582,-0.00597009) ,
1779 NN(
1780 0,
1781 0,
1782 -1, 0, 1, -99, 0.851597,0.00624135) ,
1783 0, 0.315881, 1, 0, 0.416751,-0.00313808) ,
1784 NN(
1785 NN(
1786 0,
1787 0,
1788 -1, 0, 1, -99, 0.981032,0.0299873) ,
1789 NN(
1790 0,
1791 0,
1792 -1, 0, 1, -99, 1,0.0504749) ,
1793 1, 1.6432, 1, 0, 0.986396,0.0181778) ,
1794 0, 1.57659, 1, 0, 0.5,-2.29456e-05) );
1795  // itree = 60
1796  fBoostWeights.push_back(1);
1797  fForest.push_back(
1798 NN(
1799 NN(
1800 NN(
1801 0,
1802 0,
1803 -1, 0, 1, -99, 0,-0.051253) ,
1804 NN(
1805 0,
1806 0,
1807 -1, 0, 1, -99, 0.194183,0.00239219) ,
1808 0, -0.566704, 1, 0, 0.0771828,-0.010379) ,
1809 NN(
1810 NN(
1811 0,
1812 0,
1813 -1, 0, 1, -99, 0.605988,0.000339587) ,
1814 NN(
1815 0,
1816 0,
1817 -1, 0, 1, -99, 0.993554,0.0447322) ,
1818 1, 1.59113, 1, 0, 0.693048,0.00471916) ,
1819 1, -0.802446, 1, 0, 0.5,-1.34778e-05) );
1820  // itree = 61
1821  fBoostWeights.push_back(1);
1822  fForest.push_back(
1823 NN(
1824 NN(
1825 NN(
1826 0,
1827 0,
1828 -1, 0, 1, -99, 0.338236,-0.00336221) ,
1829 NN(
1830 0,
1831 0,
1832 -1, 0, 1, -99, 0.990331,0.0398711) ,
1833 1, 1.65666, 1, 0, 0.416751,-0.00278237) ,
1834 NN(
1835 NN(
1836 0,
1837 0,
1838 -1, 0, 1, -99, 0.981032,0.0283052) ,
1839 NN(
1840 0,
1841 0,
1842 -1, 0, 1, -99, 1,0.0503926) ,
1843 1, 1.6432, 1, 0, 0.986396,0.0161197) ,
1844 0, 1.57659, 1, 0, 0.5,-1.99953e-05) );
1845  // itree = 62
1846  fBoostWeights.push_back(1);
1847  fForest.push_back(
1848 NN(
1849 NN(
1850 0,
1851 0,
1852 -1, 0, 1, -99, 0,-0.0797551) ,
1853 NN(
1854 NN(
1855 0,
1856 0,
1857 -1, 0, 1, -99, 0.430794,-0.00127554) ,
1858 NN(
1859 0,
1860 0,
1861 -1, 0, 1, -99, 0.993152,0.0395116) ,
1862 0, 1.57659, 1, 0, 0.514841,0.00114627) ,
1863 1, -2.55895, 1, 0, 0.5,-6.38266e-06) );
1864  // itree = 63
1865  fBoostWeights.push_back(1);
1866  fForest.push_back(
1867 NN(
1868 NN(
1869 NN(
1870 0,
1871 0,
1872 -1, 0, 1, -99, 0,-0.078749) ,
1873 NN(
1874 0,
1875 0,
1876 -1, 0, 1, -99, 0.0555249,-0.0157013) ,
1877 1, -2.60989, 1, 0, 0.0401405,-0.018972) ,
1878 NN(
1879 NN(
1880 0,
1881 0,
1882 -1, 0, 1, -99, 0.00881729,-0.0354255) ,
1883 NN(
1884 0,
1885 0,
1886 -1, 0, 1, -99, 0.630347,0.00299413) ,
1887 0, -1.59256, 1, 0, 0.551353,0.00211743) ,
1888 1, -1.85635, 1, 0, 0.5,-1.08438e-06) );
1889  // itree = 64
1890  fBoostWeights.push_back(1);
1891  fForest.push_back(
1892 NN(
1893 NN(
1894 NN(
1895 0,
1896 0,
1897 -1, 0, 1, -99, 0.00437091,-0.0416445) ,
1898 NN(
1899 0,
1900 0,
1901 -1, 0, 1, -99, 0.269797,0.00333392) ,
1902 0, -0.598964, 1, 0, 0.11911,-0.00718271) ,
1903 NN(
1904 NN(
1905 0,
1906 0,
1907 -1, 0, 1, -99, 0.226445,0.00935392) ,
1908 NN(
1909 0,
1910 0,
1911 -1, 0, 1, -99, 0.902527,0.00029097) ,
1912 0, -0.536179, 1, 0, 0.760598,0.0048958) ,
1913 1, -0.451145, 1, 0, 0.5,-1.09742e-05) );
1914  // itree = 65
1915  fBoostWeights.push_back(1);
1916  fForest.push_back(
1917 NN(
1918 NN(
1919 NN(
1920 0,
1921 0,
1922 -1, 0, 1, -99, 0,-0.0776005) ,
1923 NN(
1924 0,
1925 0,
1926 -1, 0, 1, -99, 0.0555249,-0.0139159) ,
1927 1, -2.60989, 1, 0, 0.0401405,-0.0166877) ,
1928 NN(
1929 NN(
1930 0,
1931 0,
1932 -1, 0, 1, -99, 0.00881729,-0.0338053) ,
1933 NN(
1934 0,
1935 0,
1936 -1, 0, 1, -99, 0.630347,0.00262472) ,
1937 0, -1.59256, 1, 0, 0.551353,0.00183431) ,
1938 1, -1.85635, 1, 0, 0.5,-2.62965e-05) );
1939  // itree = 66
1940  fBoostWeights.push_back(1);
1941  fForest.push_back(
1942 NN(
1943 NN(
1944 NN(
1945 0,
1946 0,
1947 -1, 0, 1, -99, 0.0108445,-0.0337758) ,
1948 NN(
1949 0,
1950 0,
1951 -1, 0, 1, -99, 0.529651,0.000974418) ,
1952 0, -1.33005, 1, 0, 0.416954,-0.00229772) ,
1953 NN(
1954 NN(
1955 0,
1956 0,
1957 -1, 0, 1, -99, 0.964765,0.0301055) ,
1958 NN(
1959 0,
1960 0,
1961 -1, 0, 1, -99, 1,0.0505658) ,
1962 0, 0.285969, 1, 0, 0.993104,0.0134205) ,
1963 1, 1.65666, 1, 0, 0.5,-3.21032e-05) );
1964  // itree = 67
1965  fBoostWeights.push_back(1);
1966  fForest.push_back(
1967 NN(
1968 NN(
1969 NN(
1970 0,
1971 0,
1972 -1, 0, 1, -99, 0.210582,-0.00470716) ,
1973 NN(
1974 0,
1975 0,
1976 -1, 0, 1, -99, 0.851597,0.00508586) ,
1977 0, 0.315881, 1, 0, 0.416751,-0.00227701) ,
1978 NN(
1979 NN(
1980 0,
1981 0,
1982 -1, 0, 1, -99, 0.970986,0.00604368) ,
1983 NN(
1984 0,
1985 0,
1986 -1, 0, 1, -99, 0.991115,0.0367625) ,
1987 0, 1.78732, 1, 0, 0.986396,0.0130954) ,
1988 0, 1.57659, 1, 0, 0.5,-3.04749e-05) );
1989  // itree = 68
1990  fBoostWeights.push_back(1);
1991  fForest.push_back(
1992 NN(
1993 NN(
1994 NN(
1995 0,
1996 0,
1997 -1, 0, 1, -99, 0,-0.0510468) ,
1998 NN(
1999 0,
2000 0,
2001 -1, 0, 1, -99, 0.194183,0.00220488) ,
2002 0, -0.566704, 1, 0, 0.0771828,-0.00772745) ,
2003 NN(
2004 NN(
2005 0,
2006 0,
2007 -1, 0, 1, -99, 0.343814,0.00473869) ,
2008 NN(
2009 0,
2010 0,
2011 -1, 0, 1, -99, 0.923141,-0.0013213) ,
2012 0, 0.168077, 1, 0, 0.693048,0.00349597) ,
2013 1, -0.802446, 1, 0, 0.5,-2.20982e-05) );
2014  // itree = 69
2015  fBoostWeights.push_back(1);
2016  fForest.push_back(
2017 NN(
2018 NN(
2019 0,
2020 0,
2021 -1, 0, 1, -99, 0,-0.0779066) ,
2022 NN(
2023 NN(
2024 0,
2025 0,
2026 -1, 0, 1, -99, 0.430794,-0.00116009) ,
2027 NN(
2028 0,
2029 0,
2030 -1, 0, 1, -99, 0.993152,0.037137) ,
2031 0, 1.57659, 1, 0, 0.514841,0.00082417) ,
2032 1, -2.55895, 1, 0, 0.5,-3.36862e-05) );
2033  // itree = 70
2034  fBoostWeights.push_back(1);
2035  fForest.push_back(
2036 NN(
2037 NN(
2038 NN(
2039 0,
2040 0,
2041 -1, 0, 1, -99, 0.0108445,-0.0316992) ,
2042 NN(
2043 0,
2044 0,
2045 -1, 0, 1, -99, 0.529651,0.000809074) ,
2046 0, -1.33005, 1, 0, 0.416954,-0.00203864) ,
2047 NN(
2048 NN(
2049 0,
2050 0,
2051 -1, 0, 1, -99, 0.964765,0.0282599) ,
2052 NN(
2053 0,
2054 0,
2055 -1, 0, 1, -99, 1,0.0505078) ,
2056 0, 0.285969, 1, 0, 0.993104,0.0119239) ,
2057 1, 1.65666, 1, 0, 0.5,-2.60842e-05) );
2058  // itree = 71
2059  fBoostWeights.push_back(1);
2060  fForest.push_back(
2061 NN(
2062 NN(
2063 NN(
2064 0,
2065 0,
2066 -1, 0, 1, -99, 0,-0.0686802) ,
2067 NN(
2068 0,
2069 0,
2070 -1, 0, 1, -99, 0.0664377,-0.00908303) ,
2071 1, -2.35915, 1, 0, 0.0401405,-0.0139625) ,
2072 NN(
2073 NN(
2074 0,
2075 0,
2076 -1, 0, 1, -99, 0.463483,-0.000408873) ,
2077 NN(
2078 0,
2079 0,
2080 -1, 0, 1, -99, 0.993337,0.0399064) ,
2081 1, 1.62437, 1, 0, 0.551353,0.00153214) ,
2082 1, -1.85635, 1, 0, 0.5,-2.43503e-05) );
2083  // itree = 72
2084  fBoostWeights.push_back(1);
2085  fForest.push_back(
2086 NN(
2087 NN(
2088 NN(
2089 0,
2090 0,
2091 -1, 0, 1, -99, 0.210582,-0.00406158) ,
2092 NN(
2093 0,
2094 0,
2095 -1, 0, 1, -99, 0.851597,0.00456269) ,
2096 0, 0.315881, 1, 0, 0.416751,-0.00183501) ,
2097 NN(
2098 NN(
2099 0,
2100 0,
2101 -1, 0, 1, -99, 0.970986,0.00153553) ,
2102 NN(
2103 0,
2104 0,
2105 -1, 0, 1, -99, 0.991115,0.0354961) ,
2106 0, 1.78732, 1, 0, 0.986396,0.0105815) ,
2107 0, 1.57659, 1, 0, 0.5,-2.04532e-05) );
2108  // itree = 73
2109  fBoostWeights.push_back(1);
2110  fForest.push_back(
2111 NN(
2112 NN(
2113 NN(
2114 0,
2115 0,
2116 -1, 0, 1, -99, 0,-0.0509382) ,
2117 NN(
2118 0,
2119 0,
2120 -1, 0, 1, -99, 0.194183,0.00217797) ,
2121 0, -0.566704, 1, 0, 0.0771828,-0.00651618) ,
2122 NN(
2123 NN(
2124 0,
2125 0,
2126 -1, 0, 1, -99, 0.343814,0.00486418) ,
2127 NN(
2128 0,
2129 0,
2130 -1, 0, 1, -99, 0.923141,-0.00230982) ,
2131 0, 0.168077, 1, 0, 0.693048,0.00295453) ,
2132 1, -0.802446, 1, 0, 0.5,-1.41382e-05) );
2133  // itree = 74
2134  fBoostWeights.push_back(1);
2135  fForest.push_back(
2136 NN(
2137 NN(
2138 0,
2139 0,
2140 -1, 0, 1, -99, 0,-0.0761044) ,
2141 NN(
2142 NN(
2143 0,
2144 0,
2145 -1, 0, 1, -99, 0.430794,-0.000966866) ,
2146 NN(
2147 0,
2148 0,
2149 -1, 0, 1, -99, 0.993152,0.0348044) ,
2150 0, 1.57659, 1, 0, 0.514841,0.000696884) ,
2151 1, -2.55895, 1, 0, 0.5,-2.45946e-05) );
2152  // itree = 75
2153  fBoostWeights.push_back(1);
2154  fForest.push_back(
2155 NN(
2156 NN(
2157 NN(
2158 0,
2159 0,
2160 -1, 0, 1, -99, 0.0799047,0.00475493) ,
2161 NN(
2162 0,
2163 0,
2164 -1, 0, 1, -99, 0.637747,-0.0051765) ,
2165 0, -0.312075, 1, 0, 0.340555,-0.00245981) ,
2166 NN(
2167 NN(
2168 0,
2169 0,
2170 -1, 0, 1, -99, 0.53682,-0.0147455) ,
2171 NN(
2172 0,
2173 0,
2174 -1, 0, 1, -99, 0.991571,0.0322213) ,
2175 0, -0.295611, 1, 0, 0.940187,0.00672007) ,
2176 1, 0.954062, 1, 0, 0.5,-1.8839e-05) );
2177  // itree = 76
2178  fBoostWeights.push_back(1);
2179  fForest.push_back(
2180 NN(
2181 NN(
2182 NN(
2183 0,
2184 0,
2185 -1, 0, 1, -99, 0,-0.0671169) ,
2186 NN(
2187 0,
2188 0,
2189 -1, 0, 1, -99, 0.0664377,-0.00814944) ,
2190 1, -2.35915, 1, 0, 0.0401405,-0.0118126) ,
2191 NN(
2192 NN(
2193 0,
2194 0,
2195 -1, 0, 1, -99, 0,-0.05145) ,
2196 NN(
2197 0,
2198 0,
2199 -1, 0, 1, -99, 0.601178,0.0017804) ,
2200 0, -1.94469, 1, 0, 0.551353,0.0013104) ,
2201 1, -1.85635, 1, 0, 0.5,-7.85235e-06) );
2202  // itree = 77
2203  fBoostWeights.push_back(1);
2204  fForest.push_back(
2205 NN(
2206 NN(
2207 NN(
2208 0,
2209 0,
2210 -1, 0, 1, -99, 0.0108445,-0.0291099) ,
2211 NN(
2212 0,
2213 0,
2214 -1, 0, 1, -99, 0.529651,0.000778659) ,
2215 0, -1.33005, 1, 0, 0.416954,-0.00156005) ,
2216 NN(
2217 NN(
2218 0,
2219 0,
2220 -1, 0, 1, -99, 0.964765,0.023973) ,
2221 NN(
2222 0,
2223 0,
2224 -1, 0, 1, -99, 1,0.0503956) ,
2225 0, 0.285969, 1, 0, 0.993104,0.00915802) ,
2226 1, 1.65666, 1, 0, 0.5,-1.51534e-05) );
2227  // itree = 78
2228  fBoostWeights.push_back(1);
2229  fForest.push_back(
2230 NN(
2231 NN(
2232 NN(
2233 0,
2234 0,
2235 -1, 0, 1, -99, 0.0978595,-0.000588002) ,
2236 NN(
2237 0,
2238 0,
2239 -1, 0, 1, -99, 0.841875,-0.0162127) ,
2240 0, 0.991921, 1, 0, 0.17372,-0.00366096) ,
2241 NN(
2242 NN(
2243 0,
2244 0,
2245 -1, 0, 1, -99, 0.670998,-0.00105665) ,
2246 NN(
2247 0,
2248 0,
2249 -1, 0, 1, -99, 0.987301,0.0234518) ,
2250 0, 0.872333, 1, 0, 0.817576,0.00353477) ,
2251 1, -0.099843, 1, 0, 0.5,-1.4453e-05) );
2252  // itree = 79
2253  fBoostWeights.push_back(1);
2254  fForest.push_back(
2255 NN(
2256 NN(
2257 NN(
2258 0,
2259 0,
2260 -1, 0, 1, -99, 0.210582,-0.00343668) ,
2261 NN(
2262 0,
2263 0,
2264 -1, 0, 1, -99, 0.851597,0.00395594) ,
2265 0, 0.315881, 1, 0, 0.416751,-0.00149538) ,
2266 NN(
2267 NN(
2268 0,
2269 0,
2270 -1, 0, 1, -99, 0.970986,-0.00182238) ,
2271 NN(
2272 0,
2273 0,
2274 -1, 0, 1, -99, 0.991115,0.0348117) ,
2275 0, 1.78732, 1, 0, 0.986396,0.0086913) ,
2276 0, 1.57659, 1, 0, 0.5,-6.68592e-06) );
2277  // itree = 80
2278  fBoostWeights.push_back(1);
2279  fForest.push_back(
2280 NN(
2281 NN(
2282 NN(
2283 0,
2284 0,
2285 -1, 0, 1, -99, 0,-0.0666508) ,
2286 NN(
2287 0,
2288 0,
2289 -1, 0, 1, -99, 0.0664377,-0.00698105) ,
2290 1, -2.35915, 1, 0, 0.0401405,-0.0105226) ,
2291 NN(
2292 NN(
2293 0,
2294 0,
2295 -1, 0, 1, -99, 0.463483,-0.000349629) ,
2296 NN(
2297 0,
2298 0,
2299 -1, 0, 1, -99, 0.993337,0.0368883) ,
2300 1, 1.62437, 1, 0, 0.551353,0.00117226) ,
2301 1, -1.85635, 1, 0, 0.5,-2.52576e-06) );
2302  // itree = 81
2303  fBoostWeights.push_back(1);
2304  fForest.push_back(
2305 NN(
2306 NN(
2307 NN(
2308 0,
2309 0,
2310 -1, 0, 1, -99, 0.390308,-0.000207979) ,
2311 NN(
2312 0,
2313 0,
2314 -1, 0, 1, -99, 0.950661,-0.046414) ,
2315 0, 1.32118, 1, 0, 0.416751,-0.00137755) ,
2316 NN(
2317 NN(
2318 0,
2319 0,
2320 -1, 0, 1, -99, 0.970986,-0.00164307) ,
2321 NN(
2322 0,
2323 0,
2324 -1, 0, 1, -99, 0.991115,0.0341555) ,
2325 0, 1.78732, 1, 0, 0.986396,0.00803951) ,
2326 0, 1.57659, 1, 0, 0.5,-1.33218e-06) );
2327  // itree = 82
2328  fBoostWeights.push_back(1);
2329  fForest.push_back(
2330 NN(
2331 NN(
2332 NN(
2333 0,
2334 0,
2335 -1, 0, 1, -99, 0,-0.0508574) ,
2336 NN(
2337 0,
2338 0,
2339 -1, 0, 1, -99, 0.194183,0.00314448) ,
2340 0, -0.566704, 1, 0, 0.0771828,-0.00485707) ,
2341 NN(
2342 NN(
2343 0,
2344 0,
2345 -1, 0, 1, -99, 0.343814,0.00492277) ,
2346 NN(
2347 0,
2348 0,
2349 -1, 0, 1, -99, 0.923141,-0.00356789) ,
2350 0, 0.168077, 1, 0, 0.693048,0.00222601) ,
2351 1, -0.802446, 1, 0, 0.5,5.76266e-06) );
2352  // itree = 83
2353  fBoostWeights.push_back(1);
2354  fForest.push_back(
2355 NN(
2356 NN(
2357 0,
2358 0,
2359 -1, 0, 1, -99, 0,-0.0722853) ,
2360 NN(
2361 NN(
2362 0,
2363 0,
2364 -1, 0, 1, -99, 0.430794,-0.000753441) ,
2365 NN(
2366 0,
2367 0,
2368 -1, 0, 1, -99, 0.993152,0.0317018) ,
2369 0, 1.57659, 1, 0, 0.514841,0.000557964) ,
2370 1, -2.55895, 1, 0, 0.5,-4.93092e-06) );
2371  // itree = 84
2372  fBoostWeights.push_back(1);
2373  fForest.push_back(
2374 NN(
2375 NN(
2376 NN(
2377 0,
2378 0,
2379 -1, 0, 1, -99, 0,-0.0502896) ,
2380 NN(
2381 0,
2382 0,
2383 -1, 0, 1, -99, 0,-0.051668) ,
2384 1, -0.705683, 1, 0, 0,-0.00991203) ,
2385 NN(
2386 NN(
2387 0,
2388 0,
2389 -1, 0, 1, -99, 0.237175,0.00538993) ,
2390 NN(
2391 0,
2392 0,
2393 -1, 0, 1, -99, 0.867984,-0.00580367) ,
2394 0, 0.21131, 1, 0, 0.551535,0.00101918) ,
2395 0, -1.94469, 1, 0, 0.5,-2.22377e-06) );
2396  // itree = 85
2397  fBoostWeights.push_back(1);
2398  fForest.push_back(
2399 NN(
2400 NN(
2401 NN(
2402 0,
2403 0,
2404 -1, 0, 1, -99, 0.0108445,-0.0266535) ,
2405 NN(
2406 0,
2407 0,
2408 -1, 0, 1, -99, 0.529651,0.000715639) ,
2409 0, -1.33005, 1, 0, 0.416954,-0.00122372) ,
2410 NN(
2411 NN(
2412 0,
2413 0,
2414 -1, 0, 1, -99, 0.964765,0.0191917) ,
2415 NN(
2416 0,
2417 0,
2418 -1, 0, 1, -99, 1,0.050337) ,
2419 0, 0.285969, 1, 0, 0.993104,0.0072234) ,
2420 1, 1.65666, 1, 0, 0.5,-6.16252e-06) );
2421  // itree = 86
2422  fBoostWeights.push_back(1);
2423  fForest.push_back(
2424 NN(
2425 NN(
2426 NN(
2427 0,
2428 0,
2429 -1, 0, 1, -99, 0,-0.064841) ,
2430 NN(
2431 0,
2432 0,
2433 -1, 0, 1, -99, 0.0664377,-0.00600672) ,
2434 1, -2.35915, 1, 0, 0.0401405,-0.00882757) ,
2435 NN(
2436 NN(
2437 0,
2438 0,
2439 -1, 0, 1, -99, 0.227036,-0.00184202) ,
2440 NN(
2441 0,
2442 0,
2443 -1, 0, 1, -99, 0.837704,0.00333915) ,
2444 1, 0.0192932, 1, 0, 0.551353,0.000979014) ,
2445 1, -1.85635, 1, 0, 0.5,-6.09439e-06) );
2446  // itree = 87
2447  fBoostWeights.push_back(1);
2448  fForest.push_back(
2449 NN(
2450 NN(
2451 NN(
2452 0,
2453 0,
2454 -1, 0, 1, -99, 0.210582,-0.00342563) ,
2455 NN(
2456 0,
2457 0,
2458 -1, 0, 1, -99, 0.851597,0.00450033) ,
2459 0, 0.315881, 1, 0, 0.416751,-0.00118019) ,
2460 NN(
2461 NN(
2462 0,
2463 0,
2464 -1, 0, 1, -99, 0.970986,-0.00438496) ,
2465 NN(
2466 0,
2467 0,
2468 -1, 0, 1, -99, 0.991115,0.0338859) ,
2469 0, 1.78732, 1, 0, 0.986396,0.00684199) ,
2470 0, 1.57659, 1, 0, 0.5,-7.8206e-06) );
2471  // itree = 88
2472  fBoostWeights.push_back(1);
2473  fForest.push_back(
2474 NN(
2475 NN(
2476 0,
2477 0,
2478 -1, 0, 1, -99, 0,-0.0693062) ,
2479 NN(
2480 NN(
2481 0,
2482 0,
2483 -1, 0, 1, -99, 0.127536,-0.00375409) ,
2484 NN(
2485 0,
2486 0,
2487 -1, 0, 1, -99, 0.763154,0.00226976) ,
2488 1, -0.443982, 1, 0, 0.514841,0.000471606) ,
2489 1, -2.55895, 1, 0, 0.5,-4.19761e-06) );
2490  // itree = 89
2491  fBoostWeights.push_back(1);
2492  fForest.push_back(
2493 NN(
2494 NN(
2495 NN(
2496 0,
2497 0,
2498 -1, 0, 1, -99, 0,-0.0502431) ,
2499 NN(
2500 0,
2501 0,
2502 -1, 0, 1, -99, 0,-0.0514418) ,
2503 1, -0.705683, 1, 0, 0,-0.00842532) ,
2504 NN(
2505 NN(
2506 0,
2507 0,
2508 -1, 0, 1, -99, 0.237175,0.00519456) ,
2509 NN(
2510 0,
2511 0,
2512 -1, 0, 1, -99, 0.867984,-0.00580819) ,
2513 0, 0.21131, 1, 0, 0.551535,0.000862316) ,
2514 0, -1.94469, 1, 0, 0.5,-5.51459e-06) );
2515  // itree = 90
2516  fBoostWeights.push_back(1);
2517  fForest.push_back(
2518 NN(
2519 NN(
2520 NN(
2521 0,
2522 0,
2523 -1, 0, 1, -99, 0.210582,-0.00347014) ,
2524 NN(
2525 0,
2526 0,
2527 -1, 0, 1, -99, 0.851597,0.00466256) ,
2528 0, 0.315881, 1, 0, 0.416751,-0.00114142) ,
2529 NN(
2530 NN(
2531 0,
2532 0,
2533 -1, 0, 1, -99, 0.970986,-0.00309216) ,
2534 NN(
2535 0,
2536 0,
2537 -1, 0, 1, -99, 0.991115,0.033742) ,
2538 0, 1.78732, 1, 0, 0.986396,0.00661122) ,
2539 0, 1.57659, 1, 0, 0.5,-8.44129e-06) );
2540  // itree = 91
2541  fBoostWeights.push_back(1);
2542  fForest.push_back(
2543 NN(
2544 NN(
2545 NN(
2546 0,
2547 0,
2548 -1, 0, 1, -99, 0.230547,-0.00230393) ,
2549 NN(
2550 0,
2551 0,
2552 -1, 0, 1, -99, 0.922406,0.00498724) ,
2553 0, 0.705902, 1, 0, 0.416954,-0.00107807) ,
2554 NN(
2555 NN(
2556 0,
2557 0,
2558 -1, 0, 1, -99, 0.964765,0.0174295) ,
2559 NN(
2560 0,
2561 0,
2562 -1, 0, 1, -99, 1,0.0503007) ,
2563 0, 0.285969, 1, 0, 0.993104,0.00636716) ,
2564 1, 1.65666, 1, 0, 0.5,-4.91737e-06) );
2565  // itree = 92
2566  fBoostWeights.push_back(1);
2567  fForest.push_back(
2568 NN(
2569 NN(
2570 NN(
2571 0,
2572 0,
2573 -1, 0, 1, -99, 0,-0.0686659) ,
2574 NN(
2575 0,
2576 0,
2577 -1, 0, 1, -99, 0.0555249,-0.00764983) ,
2578 1, -2.60989, 1, 0, 0.0401405,-0.00779213) ,
2579 NN(
2580 NN(
2581 0,
2582 0,
2583 -1, 0, 1, -99, 0.216496,0.0028428) ,
2584 NN(
2585 0,
2586 0,
2587 -1, 0, 1, -99, 0.889031,-0.00242899) ,
2588 0, 0.168077, 1, 0, 0.551353,0.00086905) ,
2589 1, -1.85635, 1, 0, 0.5,-9.9803e-07) );
2590  // itree = 93
2591  fBoostWeights.push_back(1);
2592  fForest.push_back(
2593 NN(
2594 NN(
2595 NN(
2596 0,
2597 0,
2598 -1, 0, 1, -99, 0.210582,-0.00314173) ,
2599 NN(
2600 0,
2601 0,
2602 -1, 0, 1, -99, 0.851597,0.00422481) ,
2603 0, 0.315881, 1, 0, 0.416751,-0.00103895) ,
2604 NN(
2605 NN(
2606 0,
2607 0,
2608 -1, 0, 1, -99, 0.970986,-0.00310635) ,
2609 NN(
2610 0,
2611 0,
2612 -1, 0, 1, -99, 0.991115,0.0330849) ,
2613 0, 1.78732, 1, 0, 0.986396,0.00605298) ,
2614 0, 1.57659, 1, 0, 0.5,-2.5263e-06) );
2615  // itree = 94
2616  fBoostWeights.push_back(1);
2617  fForest.push_back(
2618 NN(
2619 NN(
2620 NN(
2621 0,
2622 0,
2623 -1, 0, 1, -99, 0,-0.0601738) ,
2624 NN(
2625 0,
2626 0,
2627 -1, 0, 1, -99, 0.0326984,0.05724) ,
2628 0, -1.79801, 1, 0, 0.00719157,-0.00607125) ,
2629 NN(
2630 NN(
2631 0,
2632 0,
2633 -1, 0, 1, -99, 0.0220392,-0.0313155) ,
2634 NN(
2635 0,
2636 0,
2637 -1, 0, 1, -99, 0.611708,0.00172534) ,
2638 0, -1.34052, 1, 0, 0.58034,0.000989886) ,
2639 0, -1.59256, 1, 0, 0.5,1.04648e-07) );
2640  // itree = 95
2641  fBoostWeights.push_back(1);
2642  fForest.push_back(
2643 NN(
2644 NN(
2645 NN(
2646 0,
2647 0,
2648 -1, 0, 1, -99, 0.0610392,-0.00340871) ,
2649 NN(
2650 0,
2651 0,
2652 -1, 0, 1, -99, 0.584054,0.00796145) ,
2653 1, 0.169127, 1, 0, 0.18204,0.00235031) ,
2654 NN(
2655 NN(
2656 0,
2657 0,
2658 -1, 0, 1, -99, 0.56708,-0.0287356) ,
2659 NN(
2660 0,
2661 0,
2662 -1, 0, 1, -99, 0.909799,0.00525783) ,
2663 0, 0.337246, 1, 0, 0.868995,-0.002753) ,
2664 0, 0.168077, 1, 0, 0.5,-1.17778e-05) );
2665  // itree = 96
2666  fBoostWeights.push_back(1);
2667  fForest.push_back(
2668 NN(
2669 NN(
2670 NN(
2671 0,
2672 0,
2673 -1, 0, 1, -99, 0,-0.0636453) ,
2674 NN(
2675 0,
2676 0,
2677 -1, 0, 1, -99, 0.0664377,-0.00524254) ,
2678 1, -2.35915, 1, 0, 0.0401405,-0.00735923) ,
2679 NN(
2680 NN(
2681 0,
2682 0,
2683 -1, 0, 1, -99, 0.275706,0.00281698) ,
2684 NN(
2685 0,
2686 0,
2687 -1, 0, 1, -99, 0.865278,-0.00282968) ,
2688 1, 0.286806, 1, 0, 0.551353,0.000812515) ,
2689 1, -1.85635, 1, 0, 0.5,-8.36736e-06) );
2690  // itree = 97
2691  fBoostWeights.push_back(1);
2692  fForest.push_back(
2693 NN(
2694 NN(
2695 NN(
2696 0,
2697 0,
2698 -1, 0, 1, -99, 0.396249,-8.52053e-05) ,
2699 NN(
2700 0,
2701 0,
2702 -1, 0, 1, -99, 0.847969,-0.0168441) ,
2703 1, 1.4011, 1, 0, 0.416954,-0.000997414) ,
2704 NN(
2705 NN(
2706 0,
2707 0,
2708 -1, 0, 1, -99, 0.964765,0.0173276) ,
2709 NN(
2710 0,
2711 0,
2712 -1, 0, 1, -99, 1,0.0502701) ,
2713 0, 0.285969, 1, 0, 0.993104,0.00585604) ,
2714 1, 1.65666, 1, 0, 0.5,-9.56239e-06) );
2715  // itree = 98
2716  fBoostWeights.push_back(1);
2717  fForest.push_back(
2718 NN(
2719 NN(
2720 NN(
2721 0,
2722 0,
2723 -1, 0, 1, -99, 0.0119757,-0.0212094) ,
2724 NN(
2725 0,
2726 0,
2727 -1, 0, 1, -99, 0.33293,0.00514467) ,
2728 1, -0.862324, 1, 0, 0.18204,0.00213265) ,
2729 NN(
2730 NN(
2731 0,
2732 0,
2733 -1, 0, 1, -99, 0.56708,-0.0255481) ,
2734 NN(
2735 0,
2736 0,
2737 -1, 0, 1, -99, 0.909799,0.00475078) ,
2738 0, 0.337246, 1, 0, 0.868995,-0.00248624) ,
2739 0, 0.168077, 1, 0, 0.5,-5.22314e-06) );
2740  // itree = 99
2741  fBoostWeights.push_back(1);
2742  fForest.push_back(
2743 NN(
2744 NN(
2745 NN(
2746 0,
2747 0,
2748 -1, 0, 1, -99, 0.234151,-0.00190479) ,
2749 NN(
2750 0,
2751 0,
2752 -1, 0, 1, -99, 0.820257,0.0151755) ,
2753 0, 0.434497, 1, 0, 0.316225,0.00152189) ,
2754 NN(
2755 NN(
2756 0,
2757 0,
2758 -1, 0, 1, -99, 0.725025,-0.0348105) ,
2759 NN(
2760 0,
2761 0,
2762 -1, 0, 1, -99, 0.984282,0.0166134) ,
2763 1, -0.423486, 1, 0, 0.951866,-0.00376654) ,
2764 0, 0.872333, 1, 0, 0.5,-7.08977e-06) );
2765  return;
2766 };
2767 
2768 // Clean up
2769 inline void ReadBDTG_fold1::Clear()
2770 {
2771  for (unsigned int itree=0; itree<fForest.size(); itree++) {
2772  delete fForest[itree];
2773  }
2774 }
2775  inline double ReadBDTG_fold1::GetMvaValue( const std::vector<double>& inputValues ) const
2776  {
2777  // classifier response value
2778  double retval = 0;
2779 
2780  // classifier response, sanity check first
2781  if (!IsStatusClean()) {
2782  std::cout << "Problem in class \"" << fClassName << "\": cannot return classifier response"
2783  << " because status is dirty" << std::endl;
2784  retval = 0;
2785  }
2786  else {
2787  if (IsNormalised()) {
2788  // normalise variables
2789  std::vector<double> iV;
2790  iV.reserve(inputValues.size());
2791  int ivar = 0;
2792  for (std::vector<double>::const_iterator varIt = inputValues.begin();
2793  varIt != inputValues.end(); varIt++, ivar++) {
2794  iV.push_back(NormVariable( *varIt, fVmin[ivar], fVmax[ivar] ));
2795  }
2796  retval = GetMvaValue__( iV );
2797  }
2798  else {
2799  retval = GetMvaValue__( inputValues );
2800  }
2801  }
2802 
2803  return retval;
2804  }
xmin
float xmin
Definition: THbookFile.cxx:93
RooStats::HistFactory::Constraint::GetType
Type GetType(const std::string &Name)
Definition: Systematics.cxx:34
x
Double_t x[n]
Definition: legend1.C:17
NN
#define NN
Definition: TMVACrossValidation_BDTG_fold1.class.C:88
TMVA::TMVAGlob::Initialize
void Initialize(Bool_t useTMVAStyle=kTRUE)
Definition: tmvaglob.cxx:176
xmax
float xmax
Definition: THbookFile.cxx:93
fType
PyObject * fType
Definition: MethodProxy.cxx:120
e
you should not use this method at all Int_t Int_t Double_t Double_t Double_t e
Definition: TRolke.cxx:630
exp
double exp(double)