Execution Time1.83s

Test: gtest-tmva-tmva-test-crossvalidation-testCrossValidationMultiProc (Passed)
Build: PR-4623-x86_64-fedora27-gcc7-opt (sft-fedora-27-2.cern.ch) on 2019-11-14 10:11:28
Repository revision: 40f17f5d2096bfd8b3844c3195a20ad01a6fb2eb

Test Timing: Passed
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Test output
Running main() from gtest_main.cc
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from CrossValidationMultiprocess
[ RUN      ] CrossValidationMultiprocess.EqualOutputTo
create data set info cv-multiproc
DataSetInfo              : [cv-multiproc] : Added class "Signal"
                         : Add Tree  of type Signal with 50 events
DataSetInfo              : [cv-multiproc] : Added class "Background"
                         : Add Tree  of type Background with 50 events
                         : Dataset[cv-multiproc] : Class index : 0  name : Signal
                         : Dataset[cv-multiproc] : Class index : 1  name : Background
<HEADER> Factory                  : You are running ROOT Version: 6.19/01, May 29, 2019
                         : 
                         : _/_/_/_/_/ _|      _|  _|      _|    _|_|   
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                         :  _/        _|      _|    _|  _|    _|    _| 
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                         : 
                         : ___________TMVA Version 4.2.1, Feb 5, 2015
                         : 
<HEADER> Factory                  : You are running ROOT Version: 6.19/01, May 29, 2019
                         : 
                         : _/_/_/_/_/ _|      _|  _|      _|    _|_|   
                         :    _/      _|_|  _|_|  _|      _|  _|    _| 
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                         :  _/        _|      _|    _|  _|    _|    _| 
                         : _/         _|      _|      _|      _|    _| 
                         : 
                         : ___________TMVA Version 4.2.1, Feb 5, 2015
                         : 
                         : Building event vectors for type 2 Signal
                         : Dataset[cv-multiproc] :  create input formulas for tree 
                         : Building event vectors for type 2 Background
                         : Dataset[cv-multiproc] :  create input formulas for tree 
<HEADER> DataSetFactory           : [cv-multiproc] : Number of events in input trees
                         : 
                         : 
                         : Dataset[cv-multiproc] : Weight renormalisation mode: "EqualNumEvents": renormalises all event classes ...
                         : Dataset[cv-multiproc] :  such that the effective (weighted) number of events in each class is the same 
                         : Dataset[cv-multiproc] :  (and equals the number of events (entries) given for class=0 )
                         : Dataset[cv-multiproc] : ... i.e. such that Sum[i=1..N_j]{w_i} = N_classA, j=classA, classB, ...
                         : Dataset[cv-multiproc] : ... (note that N_j is the sum of TRAINING events
                         : Dataset[cv-multiproc] :  ..... Testing events are not renormalised nor included in the renormalisation factor!)
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 50
                         : Signal     -- testing events             : 0
                         : Signal     -- training and testing events: 50
                         : Background -- training events            : 50
                         : Background -- testing events             : 0
                         : Background -- training and testing events: 50
                         : 
<ERROR>                          : Dataset cv-multiproc does not have any testing events, guess that will cause problems later..but for now, I continue 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ------------------------
                         :                x       y
                         :       x:  +1.000  +0.070
                         :       y:  +0.070  +1.000
                         : ------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ------------------------
                         :                x       y
                         :       x:  +1.000  -0.238
                         :       y:  -0.238  +1.000
                         : ------------------------
<HEADER> DataSetFactory           : [cv-multiproc] :  
                         : 
                         : 
                         : 
                         : ========================================
                         : Processing folds for method BDT
                         : ========================================
                         : 
<HEADER> Factory                  : Booking method: BDT_fold1
                         : 
<HEADER> BDT_fold1                : #events: (reweighted) sig: 25 bkg: 25
                         : #events: (unweighted) sig: 25 bkg: 25
                         : Training 100 Decision Trees ... patience please
                         : Elapsed time for training with 50 events: 0.00664 sec         
<HEADER> BDT_fold1                : [cv-multiproc] : Evaluation of BDT_fold1 on training sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000461 sec       
                         : Creating xml weight file: cv-multiproc/weights/1-proc_BDT_fold1.weights.xml
                         : Creating standalone class: cv-multiproc/weights/1-proc_BDT_fold1.class.C
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT_fold1 for Classification performance
                         : 
<HEADER> BDT_fold1                : [cv-multiproc] : Evaluation of BDT_fold1 on testing sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000307 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT_fold1
                         : 
<HEADER> BDT_fold1                : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT_fold1      : 0.576
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT_fold1      : 0.000 (0.756)       0.119 (0.761)      0.400 (0.797)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
<HEADER> Factory                  : Booking method: BDT_fold2
                         : 
<HEADER> BDT_fold2                : #events: (reweighted) sig: 25 bkg: 25
                         : #events: (unweighted) sig: 25 bkg: 25
                         : Training 100 Decision Trees ... patience please
                         : Elapsed time for training with 50 events: 0.0122 sec         
<HEADER> BDT_fold2                : [cv-multiproc] : Evaluation of BDT_fold2 on training sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000288 sec       
                         : Creating xml weight file: cv-multiproc/weights/1-proc_BDT_fold2.weights.xml
                         : Creating standalone class: cv-multiproc/weights/1-proc_BDT_fold2.class.C
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT_fold2 for Classification performance
                         : 
<HEADER> BDT_fold2                : [cv-multiproc] : Evaluation of BDT_fold2 on testing sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000289 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT_fold2
                         : 
<HEADER> BDT_fold2                : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT_fold2      : 0.573
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT_fold2      : 0.157 (0.677)       0.243 (0.759)      0.398 (0.839)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
<HEADER> Factory                  : Booking method: BDT
                         : 
                         : Reading weightfile: cv-multiproc/weights/1-proc_BDT_fold1.weights.xml
                         : Reading weight file: cv-multiproc/weights/1-proc_BDT_fold1.weights.xml
                         : Reading weightfile: cv-multiproc/weights/1-proc_BDT_fold2.weights.xml
                         : Reading weight file: cv-multiproc/weights/1-proc_BDT_fold2.weights.xml
                         : 
                         : 
                         : ========================================
                         : Folds processed for all methods, evaluating.
                         : ========================================
                         : 
                         : Elapsed time for training with 100 events: 5.01e-06 sec         
<HEADER> BDT                      : [cv-multiproc] : Evaluation of BDT on training sample (100 events)
                         : Elapsed time for evaluation of 100 events: 0.000523 sec       
                         : Creating xml weight file: cv-multiproc/weights/1-proc_BDT.weights.xml
                         : Creating standalone class: cv-multiproc/weights/1-proc_BDT.class.C
<WARNING> <WARNING>                : MakeClassSpecificHeader not implemented for CrossValidation
<WARNING> <WARNING>                : MakeClassSpecific not implemented for CrossValidation
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT for Classification performance
                         : 
<HEADER> BDT                      : [cv-multiproc] : Evaluation of BDT on testing sample (100 events)
                         : Elapsed time for evaluation of 100 events: 0.000495 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT
                         : 
<HEADER> BDT                      : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT            : 0.569
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT            : 0.000 (0.000)       0.196 (0.196)      0.380 (0.380)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
                         : Evaluation done.
create data set info cv-multiproc
<HEADER> DataSetInfo              : [cv-multiproc] : Added class "Signal"
                         : Add Tree  of type Signal with 50 events
<HEADER> DataSetInfo              : [cv-multiproc] : Added class "Background"
                         : Add Tree  of type Background with 50 events
                         : Dataset[cv-multiproc] : Class index : 0  name : Signal
                         : Dataset[cv-multiproc] : Class index : 1  name : Background
<HEADER> Factory                  : You are running ROOT Version: 6.19/01, May 29, 2019
                         : 
                         : _/_/_/_/_/ _|      _|  _|      _|    _|_|   
                         :    _/      _|_|  _|_|  _|      _|  _|    _| 
                         :   _/       _|  _|  _|  _|      _|  _|_|_|_| 
                         :  _/        _|      _|    _|  _|    _|    _| 
                         : _/         _|      _|      _|      _|    _| 
                         : 
                         : ___________TMVA Version 4.2.1, Feb 5, 2015
                         : 
<HEADER> Factory                  : You are running ROOT Version: 6.19/01, May 29, 2019
                         : 
                         : _/_/_/_/_/ _|      _|  _|      _|    _|_|   
                         :    _/      _|_|  _|_|  _|      _|  _|    _| 
                         :   _/       _|  _|  _|  _|      _|  _|_|_|_| 
                         :  _/        _|      _|    _|  _|    _|    _| 
                         : _/         _|      _|      _|      _|    _| 
                         : 
                         : ___________TMVA Version 4.2.1, Feb 5, 2015
                         : 
                         : Building event vectors for type 2 Signal
                         : Dataset[cv-multiproc] :  create input formulas for tree 
                         : Building event vectors for type 2 Background
                         : Dataset[cv-multiproc] :  create input formulas for tree 
<HEADER> DataSetFactory           : [cv-multiproc] : Number of events in input trees
                         : 
                         : 
                         : Dataset[cv-multiproc] : Weight renormalisation mode: "EqualNumEvents": renormalises all event classes ...
                         : Dataset[cv-multiproc] :  such that the effective (weighted) number of events in each class is the same 
                         : Dataset[cv-multiproc] :  (and equals the number of events (entries) given for class=0 )
                         : Dataset[cv-multiproc] : ... i.e. such that Sum[i=1..N_j]{w_i} = N_classA, j=classA, classB, ...
                         : Dataset[cv-multiproc] : ... (note that N_j is the sum of TRAINING events
                         : Dataset[cv-multiproc] :  ..... Testing events are not renormalised nor included in the renormalisation factor!)
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 50
                         : Signal     -- testing events             : 0
                         : Signal     -- training and testing events: 50
                         : Background -- training events            : 50
                         : Background -- testing events             : 0
                         : Background -- training and testing events: 50
                         : 
<ERROR>                          : Dataset cv-multiproc does not have any testing events, guess that will cause problems later..but for now, I continue 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ------------------------
                         :                x       y
                         :       x:  +1.000  +0.070
                         :       y:  +0.070  +1.000
                         : ------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ------------------------
                         :                x       y
                         :       x:  +1.000  -0.238
                         :       y:  -0.238  +1.000
                         : ------------------------
<HEADER> DataSetFactory           : [cv-multiproc] :  
                         : 
                         : 
                         : 
                         : ========================================
                         : Processing folds for method BDT
                         : ========================================
                         : 
<HEADER> Factory                  : Booking method: BDT_fold1
                         : 
<HEADER> BDT_fold1                : #events: (reweighted) sig: 25 bkg: 25
                         : #events: (unweighted) sig: 25 bkg: 25
                         : Training 100 Decision Trees ... patience please
<HEADER> Factory                  : Booking method: BDT_fold2
                         : 
<HEADER> BDT_fold2                : #events: (reweighted) sig: 25 bkg: 25
                         : #events: (unweighted) sig: 25 bkg: 25
                         : Training 100 Decision Trees ... patience please
                         : Elapsed time for training with 50 events: 0.008 sec         
<HEADER> BDT_fold1                : [cv-multiproc] : Evaluation of BDT_fold1 on training sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000601 sec       
                         : Creating xml weight file: cv-multiproc/weights/2-proc_BDT_fold1.weights.xml
                         : Elapsed time for training with 50 events: 0.00888 sec         
<HEADER> BDT_fold2                : [cv-multiproc] : Evaluation of BDT_fold2 on training sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000301 sec       
                         : Creating xml weight file: cv-multiproc/weights/2-proc_BDT_fold2.weights.xml
                         : Creating standalone class: cv-multiproc/weights/2-proc_BDT_fold1.class.C
                         : Creating standalone class: cv-multiproc/weights/2-proc_BDT_fold2.class.C
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT_fold1 for Classification performance
                         : 
<HEADER> BDT_fold1                : [cv-multiproc] : Evaluation of BDT_fold1 on testing sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000286 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT_fold1
                         : 
<HEADER> BDT_fold1                : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT_fold2 for Classification performance
                         : 
<HEADER> BDT_fold2                : [cv-multiproc] : Evaluation of BDT_fold2 on testing sample (50 events)
                         : Elapsed time for evaluation of 50 events: 0.000326 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT_fold2
                         : 
<HEADER> BDT_fold2                : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT_fold1      : 0.576
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT_fold1      : 0.000 (0.756)       0.119 (0.761)      0.400 (0.797)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT_fold2      : 0.573
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT_fold2      : 0.157 (0.677)       0.243 (0.759)      0.398 (0.839)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
<HEADER> Factory                  : Booking method: BDT
                         : 
                         : Reading weightfile: cv-multiproc/weights/2-proc_BDT_fold1.weights.xml
                         : Reading weight file: cv-multiproc/weights/2-proc_BDT_fold1.weights.xml
                         : Reading weightfile: cv-multiproc/weights/2-proc_BDT_fold2.weights.xml
                         : Reading weight file: cv-multiproc/weights/2-proc_BDT_fold2.weights.xml
                         : 
                         : 
                         : ========================================
                         : Folds processed for all methods, evaluating.
                         : ========================================
                         : 
                         : Elapsed time for training with 100 events: 5.01e-06 sec         
<HEADER> BDT                      : [cv-multiproc] : Evaluation of BDT on training sample (100 events)
                         : Elapsed time for evaluation of 100 events: 0.000511 sec       
                         : Creating xml weight file: cv-multiproc/weights/2-proc_BDT.weights.xml
                         : Creating standalone class: cv-multiproc/weights/2-proc_BDT.class.C
<WARNING> <WARNING>                : MakeClassSpecificHeader not implemented for CrossValidation
<WARNING> <WARNING>                : MakeClassSpecific not implemented for CrossValidation
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDT for Classification performance
                         : 
<HEADER> BDT                      : [cv-multiproc] : Evaluation of BDT on testing sample (100 events)
                         : Elapsed time for evaluation of 100 events: 0.000478 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDT
                         : 
<HEADER> BDT                      : [cv-multiproc] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : cv-multiproc  BDT            : 0.569
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : cv-multiproc         BDT            : 0.000 (0.000)       0.196 (0.196)      0.380 (0.380)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
                         : Evaluation done.
CV with 1 process took  : 0.467255
CV with 2 processes took: 0.211366
create data set info Default
                         : Booking "BDT1" of type "CrossValidation" from cv-multiproc/weights/1-proc_BDT.weights.xml.
                         : Reading weight file: cv-multiproc/weights/1-proc_BDT.weights.xml
<HEADER> DataSetInfo              : [Default] : Added class "Signal"
<HEADER> DataSetInfo              : [Default] : Added class "Background"
                         : Reading weightfile: cv-multiproc/weights/1-proc_BDT_fold1.weights.xml
                         : Reading weight file: cv-multiproc/weights/1-proc_BDT_fold1.weights.xml
                         : Reading weightfile: cv-multiproc/weights/1-proc_BDT_fold2.weights.xml
                         : Reading weight file: cv-multiproc/weights/1-proc_BDT_fold2.weights.xml
                         : Booked classifier "BDT" of type: "CrossValidation"
                         : Booking "BDT2" of type "CrossValidation" from cv-multiproc/weights/2-proc_BDT.weights.xml.
                         : Reading weight file: cv-multiproc/weights/2-proc_BDT.weights.xml
                         : Reading weightfile: cv-multiproc/weights/2-proc_BDT_fold1.weights.xml
                         : Reading weight file: cv-multiproc/weights/2-proc_BDT_fold1.weights.xml
                         : Reading weightfile: cv-multiproc/weights/2-proc_BDT_fold2.weights.xml
                         : Reading weight file: cv-multiproc/weights/2-proc_BDT_fold2.weights.xml
                         : Booked classifier "BDT" of type: "CrossValidation"
[       OK ] CrossValidationMultiprocess.EqualOutputTo (743 ms)
[----------] 1 test from CrossValidationMultiprocess (743 ms total)

[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (743 ms total)
[  PASSED  ] 1 test.