diff --git a/Genetic_Algorithm/log.txt b/Genetic_Algorithm/log.txt
new file mode 100755
index 0000000000000000000000000000000000000000..65da0d9bad97b26c3110a656e699a5f81667db13
--- /dev/null
+++ b/Genetic_Algorithm/log.txt
@@ -0,0 +1,6573 @@
+05/03/2018 07:02:48 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:02:48 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:04:25 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:04:25 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:05:21 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:05:21 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:08:40 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:08:40 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:08:40 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:08:40 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:08:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:08:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:08:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:08:47 PM - INFO - Creating new RobustScaler
+05/03/2018 07:08:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:08:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:08:47 PM - INFO - Training and test data transformed
+05/03/2018 07:08:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:08:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:08:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:08:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:08:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:08:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:08:49 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:08:49 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:08:49 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:08:49 PM - DEBUG - findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans (u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000
+05/03/2018 07:08:49 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:08:49 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:08:49 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:08:49 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:08:49 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:08:49 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:08:49 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:08:49 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:08:49 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:08:49 PM - INFO - Train model
+05/03/2018 07:08:49 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:17:44 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:17:44 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:17:44 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:17:44 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:17:46 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:17:46 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:17:46 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:17:46 PM - INFO - Creating new RobustScaler
+05/03/2018 07:17:46 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:17:46 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:17:46 PM - INFO - Training and test data transformed
+05/03/2018 07:17:46 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:17:46 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:17:46 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:17:46 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:17:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:17:46 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:17:46 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:17:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:17:46 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:17:46 PM - DEBUG - findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans (u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000
+05/03/2018 07:17:46 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:17:46 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:17:46 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:17:46 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:17:46 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:17:46 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:17:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:17:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:17:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:17:47 PM - INFO - Train model
+05/03/2018 07:17:47 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:17:47 PM - INFO - KeyError
+05/03/2018 07:17:47 PM - INFO - Using sgd(**{}) as Optimizer
+05/03/2018 07:17:47 PM - INFO - Compile model
+05/03/2018 07:17:47 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:17:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:18:24 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:18:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:19:58 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:19:58 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:19:58 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:19:58 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:20:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:20:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:20:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:20:00 PM - INFO - Creating new RobustScaler
+05/03/2018 07:20:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:20:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:20:00 PM - INFO - Training and test data transformed
+05/03/2018 07:20:01 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:20:01 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:20:01 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:20:01 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:20:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:20:01 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:20:01 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:20:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:20:01 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:20:01 PM - DEBUG - findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans (u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000
+05/03/2018 07:20:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:20:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:20:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:20:01 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:20:01 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:20:01 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:20:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:20:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:20:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:20:01 PM - INFO - Train model
+05/03/2018 07:20:01 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:20:01 PM - INFO - KeyError
+05/03/2018 07:20:01 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:20:01 PM - INFO - Compile model
+05/03/2018 07:20:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:20:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:20:09 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:20:11 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:21:08 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:21:08 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:21:08 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:21:08 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:21:09 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:21:09 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:21:09 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:21:09 PM - INFO - Creating new RobustScaler
+05/03/2018 07:21:09 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:21:09 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:21:09 PM - INFO - Training and test data transformed
+05/03/2018 07:21:10 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:21:10 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:21:10 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:21:10 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:21:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:21:10 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:21:10 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:21:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:21:11 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:21:11 PM - DEBUG - findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans (u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000
+05/03/2018 07:21:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:21:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:21:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:21:11 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:21:11 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:21:11 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:21:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:21:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:21:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:21:11 PM - INFO - Train model
+05/03/2018 07:21:11 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:21:11 PM - INFO - KeyError
+05/03/2018 07:21:11 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:21:11 PM - INFO - Compile model
+05/03/2018 07:21:11 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:21:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:21:51 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:21:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:23:12 PM - INFO - ***Evolving 10 generations with population 20***
+05/03/2018 07:23:12 PM - INFO - ***Doing generation 1 of 10***
+05/03/2018 07:23:12 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:23:12 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:23:13 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:23:13 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:23:13 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:23:13 PM - INFO - Creating new RobustScaler
+05/03/2018 07:23:13 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:23:13 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:23:13 PM - INFO - Training and test data transformed
+05/03/2018 07:23:14 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:23:14 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:23:14 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:23:14 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:23:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:23:14 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:23:14 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:23:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:23:14 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:23:14 PM - DEBUG - findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans (u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000
+05/03/2018 07:23:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:23:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:23:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:23:14 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:23:14 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:23:14 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:23:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:23:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:23:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:23:14 PM - INFO - Train model
+05/03/2018 07:23:14 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:23:14 PM - INFO - KeyError
+05/03/2018 07:23:14 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:23:14 PM - INFO - Compile model
+05/03/2018 07:23:14 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:23:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:23:49 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:23:51 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:23:53 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:23:53 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:23:55 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:23:55 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:23:55 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:23:55 PM - INFO - Creating new RobustScaler
+05/03/2018 07:23:55 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:23:55 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:23:55 PM - INFO - Training and test data transformed
+05/03/2018 07:23:55 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:23:55 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:23:55 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:23:55 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:23:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:23:55 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:23:55 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:23:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:23:55 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:23:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:23:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:23:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:23:55 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:23:55 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:23:55 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:23:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:23:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:23:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:23:55 PM - INFO - Train model
+05/03/2018 07:23:55 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:23:55 PM - INFO - KeyError
+05/03/2018 07:23:55 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:23:55 PM - INFO - Compile model
+05/03/2018 07:23:55 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:23:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:01 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:24:02 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:24:03 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:24:03 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:24:04 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:24:04 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:24:04 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:24:04 PM - INFO - Creating new RobustScaler
+05/03/2018 07:24:04 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:24:04 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:24:04 PM - INFO - Training and test data transformed
+05/03/2018 07:24:04 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:24:04 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:24:04 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:24:04 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:24:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:04 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:24:04 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:24:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:04 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:24:04 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:04 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:04 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:04 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:24:04 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:24:04 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:24:04 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:04 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:04 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:04 PM - INFO - Train model
+05/03/2018 07:24:04 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:24:04 PM - INFO - KeyError
+05/03/2018 07:24:04 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:24:04 PM - INFO - Compile model
+05/03/2018 07:24:04 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:24:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:09 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:24:10 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:24:11 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:24:11 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:24:12 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:24:12 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:24:12 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:24:12 PM - INFO - Creating new RobustScaler
+05/03/2018 07:24:12 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:24:12 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:24:12 PM - INFO - Training and test data transformed
+05/03/2018 07:24:12 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:24:12 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:24:12 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:24:12 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:24:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:12 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:24:12 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:24:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:12 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:24:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:24:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:24:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:24:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:13 PM - INFO - Train model
+05/03/2018 07:24:13 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:24:13 PM - INFO - KeyError
+05/03/2018 07:24:13 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:24:13 PM - INFO - Compile model
+05/03/2018 07:24:13 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:24:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:22 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:24:23 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:24:24 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:24:24 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:24:26 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:24:26 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:24:26 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:24:26 PM - INFO - Creating new RobustScaler
+05/03/2018 07:24:26 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:24:26 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:24:26 PM - INFO - Training and test data transformed
+05/03/2018 07:24:26 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:24:26 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:24:26 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:24:26 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:24:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:26 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:24:26 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:24:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:26 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:24:26 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:26 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:26 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:26 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:24:26 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:24:26 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:24:26 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:26 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:26 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:26 PM - INFO - Train model
+05/03/2018 07:24:26 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:24:26 PM - INFO - KeyError
+05/03/2018 07:24:26 PM - INFO - Using sgd(**{}) as Optimizer
+05/03/2018 07:24:26 PM - INFO - Compile model
+05/03/2018 07:24:26 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:24:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:33 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:24:35 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:24:36 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:24:36 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:24:38 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:24:38 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:24:38 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:24:38 PM - INFO - Creating new RobustScaler
+05/03/2018 07:24:38 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:24:38 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:24:38 PM - INFO - Training and test data transformed
+05/03/2018 07:24:38 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:24:38 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:24:38 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:24:38 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:24:38 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:38 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:24:38 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:24:38 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:38 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:24:38 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:38 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:38 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:38 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:24:38 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:24:38 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:24:38 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:38 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:38 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:38 PM - INFO - Train model
+05/03/2018 07:24:38 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:24:38 PM - INFO - KeyError
+05/03/2018 07:24:38 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:24:38 PM - INFO - Compile model
+05/03/2018 07:24:38 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:24:38 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:44 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:24:45 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:24:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:24:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:24:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:24:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:24:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:24:47 PM - INFO - Creating new RobustScaler
+05/03/2018 07:24:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:24:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:24:47 PM - INFO - Training and test data transformed
+05/03/2018 07:24:47 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:24:47 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:24:47 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:24:47 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:24:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:47 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:24:47 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:24:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:24:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:24:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:24:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:24:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:24:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:24:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:24:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:24:48 PM - INFO - Train model
+05/03/2018 07:24:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:24:48 PM - INFO - KeyError
+05/03/2018 07:24:48 PM - INFO - Using adadelta(**{}) as Optimizer
+05/03/2018 07:24:48 PM - INFO - Compile model
+05/03/2018 07:24:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:24:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:25 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:25:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:25:29 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:25:29 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:25:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:25:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:25:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:25:31 PM - INFO - Creating new RobustScaler
+05/03/2018 07:25:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:25:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:25:31 PM - INFO - Training and test data transformed
+05/03/2018 07:25:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:25:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:25:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:25:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:25:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:25:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:25:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:31 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:25:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:25:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:25:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:25:31 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:25:31 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:25:31 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:25:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:25:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:25:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:25:31 PM - INFO - Train model
+05/03/2018 07:25:31 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:25:31 PM - INFO - KeyError
+05/03/2018 07:25:31 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:25:31 PM - INFO - Compile model
+05/03/2018 07:25:31 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:25:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:37 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:25:38 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:25:39 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:25:39 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:25:41 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:25:41 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:25:41 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:25:41 PM - INFO - Creating new RobustScaler
+05/03/2018 07:25:41 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:25:41 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:25:41 PM - INFO - Training and test data transformed
+05/03/2018 07:25:41 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:25:41 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:25:41 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:25:41 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:25:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:41 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:25:41 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:25:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:25:41 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:25:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:25:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:25:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:25:41 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:25:41 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:25:41 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:25:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:25:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:25:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:25:41 PM - INFO - Train model
+05/03/2018 07:25:41 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:25:41 PM - INFO - KeyError
+05/03/2018 07:25:41 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:25:41 PM - INFO - Compile model
+05/03/2018 07:25:41 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:25:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:26:38 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:26:43 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:26:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:26:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:26:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:26:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:26:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:26:47 PM - INFO - Creating new RobustScaler
+05/03/2018 07:26:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:26:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:26:47 PM - INFO - Training and test data transformed
+05/03/2018 07:26:47 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:26:47 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:26:47 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:26:47 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:26:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:26:47 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:26:47 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:26:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:26:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:26:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:26:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:26:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:26:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:26:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:26:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:26:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:26:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:26:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:26:48 PM - INFO - Train model
+05/03/2018 07:26:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:26:48 PM - INFO - KeyError
+05/03/2018 07:26:48 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:26:48 PM - INFO - Compile model
+05/03/2018 07:26:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:26:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:26:56 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:26:58 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:26:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:26:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:00 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:00 PM - INFO - Training and test data transformed
+05/03/2018 07:27:00 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:00 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:00 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:00 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:00 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:00 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:00 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:00 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:00 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:00 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:01 PM - INFO - Train model
+05/03/2018 07:27:01 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:01 PM - INFO - KeyError
+05/03/2018 07:27:01 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:27:01 PM - INFO - Compile model
+05/03/2018 07:27:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:27:07 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:27:08 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:27:08 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:09 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:09 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:09 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:09 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:09 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:09 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:09 PM - INFO - Training and test data transformed
+05/03/2018 07:27:09 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:09 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:09 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:09 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:09 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:09 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:09 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:09 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:09 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:09 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:09 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:09 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:09 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:09 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:09 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:09 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:09 PM - INFO - Train model
+05/03/2018 07:27:09 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:09 PM - INFO - KeyError
+05/03/2018 07:27:09 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:27:09 PM - INFO - Compile model
+05/03/2018 07:27:09 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:16 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:27:17 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:27:18 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:27:18 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:20 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:20 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:20 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:20 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:20 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:20 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:20 PM - INFO - Training and test data transformed
+05/03/2018 07:27:20 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:20 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:20 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:20 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:20 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:20 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:20 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:20 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:20 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:20 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:20 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:20 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:20 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:20 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:20 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:20 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:20 PM - INFO - Train model
+05/03/2018 07:27:20 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:20 PM - INFO - KeyError
+05/03/2018 07:27:20 PM - INFO - Using sgd(**{}) as Optimizer
+05/03/2018 07:27:20 PM - INFO - Compile model
+05/03/2018 07:27:20 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:25 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:27:26 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:27:27 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:27:27 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:28 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:28 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:28 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:28 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:28 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:28 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:28 PM - INFO - Training and test data transformed
+05/03/2018 07:27:28 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:28 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:28 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:28 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:28 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:28 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:28 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:29 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:29 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:29 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:29 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:29 PM - INFO - Train model
+05/03/2018 07:27:29 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:29 PM - INFO - KeyError
+05/03/2018 07:27:29 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:27:29 PM - INFO - Compile model
+05/03/2018 07:27:29 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:42 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:27:44 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:27:45 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:27:45 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:46 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:46 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:46 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:46 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:46 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:46 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:46 PM - INFO - Training and test data transformed
+05/03/2018 07:27:46 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:46 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:46 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:46 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:46 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:46 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:46 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:46 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:47 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:47 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:47 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:47 PM - INFO - Train model
+05/03/2018 07:27:47 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:47 PM - INFO - KeyError
+05/03/2018 07:27:47 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:27:47 PM - INFO - Compile model
+05/03/2018 07:27:47 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:52 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:27:53 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:27:54 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:27:54 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:27:55 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:27:55 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:27:55 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:27:55 PM - INFO - Creating new RobustScaler
+05/03/2018 07:27:55 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:27:55 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:27:55 PM - INFO - Training and test data transformed
+05/03/2018 07:27:55 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:27:55 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:27:55 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:27:55 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:27:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:55 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:27:55 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:27:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:27:55 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:27:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:55 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:27:55 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:27:55 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:27:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:27:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:27:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:27:56 PM - INFO - Train model
+05/03/2018 07:27:56 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:27:56 PM - INFO - KeyError
+05/03/2018 07:27:56 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:27:56 PM - INFO - Compile model
+05/03/2018 07:27:56 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:27:56 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:28:03 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:28:05 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:28:06 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:28:06 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:28:07 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:28:07 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:28:07 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:28:07 PM - INFO - Creating new RobustScaler
+05/03/2018 07:28:07 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:28:07 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:28:07 PM - INFO - Training and test data transformed
+05/03/2018 07:28:07 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:28:07 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:28:07 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:28:07 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:28:07 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:28:07 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:28:07 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:28:07 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:28:07 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:28:07 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:28:07 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:28:07 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:28:08 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:28:08 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:28:08 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:28:08 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:28:08 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:28:08 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:28:08 PM - INFO - Train model
+05/03/2018 07:28:08 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:28:08 PM - INFO - KeyError
+05/03/2018 07:28:08 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:28:08 PM - INFO - Compile model
+05/03/2018 07:28:08 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:28:08 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:34 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:29:42 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:29:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:29:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:29:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:29:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:29:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:29:47 PM - INFO - Creating new RobustScaler
+05/03/2018 07:29:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:29:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:29:47 PM - INFO - Training and test data transformed
+05/03/2018 07:29:47 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:29:47 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:29:47 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:29:47 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:29:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:47 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:29:47 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:29:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:47 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:29:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:29:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:29:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:29:47 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:29:47 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:29:47 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:29:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:29:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:29:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:29:47 PM - INFO - Train model
+05/03/2018 07:29:47 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:29:47 PM - INFO - KeyError
+05/03/2018 07:29:48 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:29:48 PM - INFO - Compile model
+05/03/2018 07:29:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:29:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:55 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:29:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:29:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:29:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:29:59 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:29:59 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:29:59 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:29:59 PM - INFO - Creating new RobustScaler
+05/03/2018 07:29:59 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:29:59 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:29:59 PM - INFO - Training and test data transformed
+05/03/2018 07:29:59 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:29:59 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:29:59 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:29:59 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:29:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:59 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:29:59 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:29:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:29:59 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:29:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:29:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:29:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:29:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:29:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:29:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:29:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:29:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:29:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:29:59 PM - INFO - Train model
+05/03/2018 07:29:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:29:59 PM - INFO - KeyError
+05/03/2018 07:29:59 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:29:59 PM - INFO - Compile model
+05/03/2018 07:29:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:29:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:30:08 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:30:09 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:30:09 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:30:10 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:30:10 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:30:10 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:30:10 PM - INFO - Creating new RobustScaler
+05/03/2018 07:30:10 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:30:10 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:30:10 PM - INFO - Training and test data transformed
+05/03/2018 07:30:10 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:30:10 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:30:10 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:30:10 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:30:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:10 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:30:10 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:30:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:10 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:30:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:30:10 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:30:10 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:30:11 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:30:11 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:30:11 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:30:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:30:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:30:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:30:11 PM - INFO - Train model
+05/03/2018 07:30:11 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:30:11 PM - INFO - KeyError
+05/03/2018 07:30:11 PM - INFO - Using sgd(**{}) as Optimizer
+05/03/2018 07:30:11 PM - INFO - Compile model
+05/03/2018 07:30:11 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:30:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:31 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:30:34 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:30:36 PM - INFO - Generation average: 88.28%
+05/03/2018 07:30:36 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:30:36 PM - INFO - ***Doing generation 2 of 10***
+05/03/2018 07:30:36 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:30:36 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:30:37 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:30:37 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:30:37 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:30:37 PM - INFO - Creating new RobustScaler
+05/03/2018 07:30:37 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:30:37 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:30:37 PM - INFO - Training and test data transformed
+05/03/2018 07:30:37 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:30:37 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:30:37 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:30:37 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:30:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:37 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:30:37 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:30:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:37 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:30:37 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:30:37 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:30:37 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:30:37 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:30:37 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:30:37 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:30:37 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:30:37 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:30:37 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:30:37 PM - INFO - Train model
+05/03/2018 07:30:37 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:30:37 PM - INFO - KeyError
+05/03/2018 07:30:38 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:30:38 PM - INFO - Compile model
+05/03/2018 07:30:38 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:30:38 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:30:55 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:30:58 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:31:00 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:31:00 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:31:01 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:31:01 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:31:01 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:31:01 PM - INFO - Creating new RobustScaler
+05/03/2018 07:31:01 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:31:01 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:31:01 PM - INFO - Training and test data transformed
+05/03/2018 07:31:01 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:31:01 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:31:01 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:31:01 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:31:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:02 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:31:02 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:31:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:02 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:31:02 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:02 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:02 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:02 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:31:02 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:31:02 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:31:02 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:02 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:02 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:02 PM - INFO - Train model
+05/03/2018 07:31:02 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:31:02 PM - INFO - KeyError
+05/03/2018 07:31:02 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:31:02 PM - INFO - Compile model
+05/03/2018 07:31:02 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:31:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:08 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:31:10 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:31:11 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:31:11 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:31:12 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:31:12 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:31:12 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:31:12 PM - INFO - Creating new RobustScaler
+05/03/2018 07:31:12 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:31:12 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:31:12 PM - INFO - Training and test data transformed
+05/03/2018 07:31:12 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:31:12 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:31:12 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:31:12 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:31:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:12 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:31:12 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:31:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:12 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:31:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:12 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:12 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:31:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:31:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:31:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:13 PM - INFO - Train model
+05/03/2018 07:31:13 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:31:13 PM - INFO - KeyError
+05/03/2018 07:31:13 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:31:13 PM - INFO - Compile model
+05/03/2018 07:31:13 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:31:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:19 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:31:20 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:31:21 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:31:21 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:31:22 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:31:22 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:31:22 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:31:22 PM - INFO - Creating new RobustScaler
+05/03/2018 07:31:22 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:31:22 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:31:22 PM - INFO - Training and test data transformed
+05/03/2018 07:31:23 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:31:23 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:31:23 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:31:23 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:31:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:23 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:31:23 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:31:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:23 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:31:23 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:23 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:23 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:23 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:31:23 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:31:23 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:31:23 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:23 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:23 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:23 PM - INFO - Train model
+05/03/2018 07:31:23 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:31:23 PM - INFO - KeyError
+05/03/2018 07:31:23 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:31:23 PM - INFO - Compile model
+05/03/2018 07:31:23 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:31:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:27 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:31:29 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:31:30 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:31:30 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:31:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:31:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:31:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:31:31 PM - INFO - Creating new RobustScaler
+05/03/2018 07:31:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:31:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:31:31 PM - INFO - Training and test data transformed
+05/03/2018 07:31:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:31:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:31:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:31:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:31:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:32 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:31:32 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:31:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:32 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:31:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:32 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:31:32 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:31:32 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:31:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:32 PM - INFO - Train model
+05/03/2018 07:31:32 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:31:32 PM - INFO - KeyError
+05/03/2018 07:31:32 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:31:32 PM - INFO - Compile model
+05/03/2018 07:31:32 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:31:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:48 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:31:50 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:31:52 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:31:52 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:31:53 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:31:53 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:31:53 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:31:53 PM - INFO - Creating new RobustScaler
+05/03/2018 07:31:53 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:31:53 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:31:53 PM - INFO - Training and test data transformed
+05/03/2018 07:31:53 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:31:53 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:31:53 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:31:53 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:31:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:53 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:31:53 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:31:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:31:53 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:31:53 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:53 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:53 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:54 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:31:54 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:31:54 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:31:54 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:31:54 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:31:54 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:31:54 PM - INFO - Train model
+05/03/2018 07:31:54 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:31:54 PM - INFO - KeyError
+05/03/2018 07:31:54 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:31:54 PM - INFO - Compile model
+05/03/2018 07:31:54 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:31:54 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:32:08 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:32:09 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:32:09 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:32:10 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:32:10 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:32:10 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:32:10 PM - INFO - Creating new RobustScaler
+05/03/2018 07:32:10 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:32:10 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:32:10 PM - INFO - Training and test data transformed
+05/03/2018 07:32:10 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:32:10 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:32:10 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:32:10 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:32:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:10 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:32:10 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:32:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:10 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:32:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:10 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:10 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:10 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:32:10 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:32:10 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:32:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:11 PM - INFO - Train model
+05/03/2018 07:32:11 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:32:11 PM - INFO - KeyError
+05/03/2018 07:32:11 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:32:11 PM - INFO - Compile model
+05/03/2018 07:32:11 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:32:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:16 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:32:17 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:32:18 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:32:18 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:32:19 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:32:19 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:32:19 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:32:19 PM - INFO - Creating new RobustScaler
+05/03/2018 07:32:19 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:32:20 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:32:20 PM - INFO - Training and test data transformed
+05/03/2018 07:32:20 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:32:20 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:32:20 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:32:20 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:32:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:20 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:32:20 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:32:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:20 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:32:20 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:20 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:20 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:20 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:32:20 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:32:20 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:32:20 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:20 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:20 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:20 PM - INFO - Train model
+05/03/2018 07:32:20 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:32:20 PM - INFO - KeyError
+05/03/2018 07:32:20 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:32:20 PM - INFO - Compile model
+05/03/2018 07:32:20 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:32:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:28 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:32:30 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:32:32 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:32:32 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:32:33 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:32:33 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:32:33 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:32:33 PM - INFO - Creating new RobustScaler
+05/03/2018 07:32:33 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:32:33 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:32:33 PM - INFO - Training and test data transformed
+05/03/2018 07:32:33 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:32:33 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:32:33 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:32:33 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:32:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:33 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:32:33 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:32:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:33 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:32:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:33 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:32:33 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:32:33 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:32:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:33 PM - INFO - Train model
+05/03/2018 07:32:34 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:32:34 PM - INFO - KeyError
+05/03/2018 07:32:34 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:32:34 PM - INFO - Compile model
+05/03/2018 07:32:34 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:32:34 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:40 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:32:42 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:32:43 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:32:43 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:32:44 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:32:44 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:32:44 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:32:44 PM - INFO - Creating new RobustScaler
+05/03/2018 07:32:44 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:32:44 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:32:44 PM - INFO - Training and test data transformed
+05/03/2018 07:32:44 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:32:44 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:32:44 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:32:44 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:32:44 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:44 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:32:45 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:32:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:45 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:32:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:45 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:32:45 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:32:45 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:32:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:45 PM - INFO - Train model
+05/03/2018 07:32:45 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:32:45 PM - INFO - KeyError
+05/03/2018 07:32:45 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:32:45 PM - INFO - Compile model
+05/03/2018 07:32:45 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:32:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:50 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:32:52 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:32:53 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:32:53 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:32:54 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:32:54 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:32:54 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:32:54 PM - INFO - Creating new RobustScaler
+05/03/2018 07:32:54 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:32:54 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:32:54 PM - INFO - Training and test data transformed
+05/03/2018 07:32:54 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:32:54 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:32:54 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:32:54 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:32:54 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:54 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:32:54 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:32:54 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:32:54 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:32:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:55 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:32:55 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:32:55 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:32:55 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:32:55 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:32:55 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:32:55 PM - INFO - Train model
+05/03/2018 07:32:55 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:32:55 PM - INFO - KeyError
+05/03/2018 07:32:55 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:32:55 PM - INFO - Compile model
+05/03/2018 07:32:55 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:32:55 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:26 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:33:29 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:33:31 PM - INFO - Generation average: 96.58%
+05/03/2018 07:33:31 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:33:31 PM - INFO - ***Doing generation 3 of 10***
+05/03/2018 07:33:31 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:33:31 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:33:33 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:33:33 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:33:33 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:33:33 PM - INFO - Creating new RobustScaler
+05/03/2018 07:33:33 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:33:33 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:33:33 PM - INFO - Training and test data transformed
+05/03/2018 07:33:33 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:33:33 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:33:33 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:33:33 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:33:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:33 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:33:33 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:33:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:33 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:33:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:33 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:33:33 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:33:33 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:33:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:33 PM - INFO - Train model
+05/03/2018 07:33:33 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:33:33 PM - INFO - KeyError
+05/03/2018 07:33:33 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:33:33 PM - INFO - Compile model
+05/03/2018 07:33:33 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:33:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:36 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:33:38 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:33:39 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:33:39 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:33:41 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:33:41 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:33:41 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:33:41 PM - INFO - Creating new RobustScaler
+05/03/2018 07:33:41 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:33:41 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:33:41 PM - INFO - Training and test data transformed
+05/03/2018 07:33:41 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:33:41 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:33:41 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:33:41 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:33:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:41 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:33:41 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:33:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:41 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:33:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:41 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:33:41 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:33:41 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:33:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:41 PM - INFO - Train model
+05/03/2018 07:33:41 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:33:41 PM - INFO - KeyError
+05/03/2018 07:33:41 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:33:41 PM - INFO - Compile model
+05/03/2018 07:33:41 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:33:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:46 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:33:48 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:33:49 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:33:49 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:33:51 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:33:51 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:33:51 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:33:51 PM - INFO - Creating new RobustScaler
+05/03/2018 07:33:51 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:33:51 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:33:51 PM - INFO - Training and test data transformed
+05/03/2018 07:33:51 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:33:51 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:33:51 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:33:51 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:33:51 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:51 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:33:51 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:33:51 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:51 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:33:51 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:51 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:51 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:51 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:33:51 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:33:51 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:33:51 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:33:51 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:33:51 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:33:51 PM - INFO - Train model
+05/03/2018 07:33:51 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:33:51 PM - INFO - KeyError
+05/03/2018 07:33:51 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:33:51 PM - INFO - Compile model
+05/03/2018 07:33:51 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:33:51 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:33:59 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:34:01 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:34:02 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:34:02 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:34:03 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:34:03 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:34:03 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:34:03 PM - INFO - Creating new RobustScaler
+05/03/2018 07:34:03 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:34:03 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:34:03 PM - INFO - Training and test data transformed
+05/03/2018 07:34:03 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:34:03 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:34:03 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:34:03 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:34:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:03 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:34:03 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:34:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:03 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:34:03 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:03 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:03 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:04 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:34:04 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:34:04 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:34:04 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:04 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:04 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:04 PM - INFO - Train model
+05/03/2018 07:34:04 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:34:04 PM - INFO - KeyError
+05/03/2018 07:34:04 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:34:04 PM - INFO - Compile model
+05/03/2018 07:34:04 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:34:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:09 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:34:11 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:34:12 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:34:12 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:34:13 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:34:13 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:34:13 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:34:13 PM - INFO - Creating new RobustScaler
+05/03/2018 07:34:13 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:34:13 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:34:13 PM - INFO - Training and test data transformed
+05/03/2018 07:34:13 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:34:13 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:34:13 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:34:13 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:34:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:13 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:34:13 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:34:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:13 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:34:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:34:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:34:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:34:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:14 PM - INFO - Train model
+05/03/2018 07:34:14 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:34:14 PM - INFO - KeyError
+05/03/2018 07:34:14 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:34:14 PM - INFO - Compile model
+05/03/2018 07:34:14 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:34:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:26 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:34:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:34:30 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:34:30 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:34:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:34:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:34:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:34:31 PM - INFO - Creating new RobustScaler
+05/03/2018 07:34:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:34:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:34:31 PM - INFO - Training and test data transformed
+05/03/2018 07:34:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:34:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:34:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:34:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:34:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:34:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:34:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:32 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:34:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:32 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:34:32 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:34:32 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:34:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:32 PM - INFO - Train model
+05/03/2018 07:34:32 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:34:32 PM - INFO - KeyError
+05/03/2018 07:34:32 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:34:32 PM - INFO - Compile model
+05/03/2018 07:34:32 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:34:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:39 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:34:41 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:34:42 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:34:42 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:34:44 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:34:44 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:34:44 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:34:44 PM - INFO - Creating new RobustScaler
+05/03/2018 07:34:44 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:34:44 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:34:44 PM - INFO - Training and test data transformed
+05/03/2018 07:34:44 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:34:44 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:34:44 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:34:44 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:34:44 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:44 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:34:44 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:34:44 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:44 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:34:44 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:44 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:44 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:44 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:34:44 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:34:44 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:34:44 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:34:44 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:34:44 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:34:44 PM - INFO - Train model
+05/03/2018 07:34:44 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:34:44 PM - INFO - KeyError
+05/03/2018 07:34:44 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:34:44 PM - INFO - Compile model
+05/03/2018 07:34:44 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:34:44 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:34:56 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:34:58 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:34:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:34:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:35:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:35:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:35:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:35:00 PM - INFO - Creating new RobustScaler
+05/03/2018 07:35:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:35:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:35:00 PM - INFO - Training and test data transformed
+05/03/2018 07:35:00 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:35:00 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:35:00 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:35:00 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:35:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:01 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:35:01 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:35:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:01 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:35:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:01 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:35:01 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:35:01 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:35:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:01 PM - INFO - Train model
+05/03/2018 07:35:01 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:35:01 PM - INFO - KeyError
+05/03/2018 07:35:01 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:35:01 PM - INFO - Compile model
+05/03/2018 07:35:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:35:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:12 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:35:14 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:35:16 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:35:16 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:35:17 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:35:17 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:35:17 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:35:17 PM - INFO - Creating new RobustScaler
+05/03/2018 07:35:17 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:35:17 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:35:17 PM - INFO - Training and test data transformed
+05/03/2018 07:35:17 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:35:17 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:35:17 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:35:17 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:35:17 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:17 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:35:17 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:35:17 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:17 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:35:17 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:17 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:17 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:17 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:35:17 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:35:17 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:35:18 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:18 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:18 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:18 PM - INFO - Train model
+05/03/2018 07:35:18 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:35:18 PM - INFO - KeyError
+05/03/2018 07:35:18 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:35:18 PM - INFO - Compile model
+05/03/2018 07:35:18 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:35:18 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:24 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:35:26 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:35:27 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:35:27 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:35:28 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:35:28 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:35:28 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:35:28 PM - INFO - Creating new RobustScaler
+05/03/2018 07:35:28 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:35:28 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:35:28 PM - INFO - Training and test data transformed
+05/03/2018 07:35:28 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:35:28 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:35:28 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:35:28 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:35:28 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:28 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:35:28 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:35:28 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:28 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:35:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:29 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:35:29 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:35:29 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:35:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:29 PM - INFO - Train model
+05/03/2018 07:35:29 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:35:29 PM - INFO - KeyError
+05/03/2018 07:35:29 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:35:29 PM - INFO - Compile model
+05/03/2018 07:35:29 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:35:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:36 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:35:38 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:35:39 PM - INFO - Generation average: 96.85%
+05/03/2018 07:35:39 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:35:39 PM - INFO - ***Doing generation 4 of 10***
+05/03/2018 07:35:39 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:35:39 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:35:40 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:35:40 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:35:40 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:35:40 PM - INFO - Creating new RobustScaler
+05/03/2018 07:35:40 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:35:40 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:35:40 PM - INFO - Training and test data transformed
+05/03/2018 07:35:40 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:35:40 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:35:40 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:35:40 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:35:40 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:40 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:35:40 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:35:40 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:40 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:35:40 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:40 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:40 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:40 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:35:40 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:35:40 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:35:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:41 PM - INFO - Train model
+05/03/2018 07:35:41 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:35:41 PM - INFO - KeyError
+05/03/2018 07:35:41 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:35:41 PM - INFO - Compile model
+05/03/2018 07:35:41 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:35:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:48 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:35:50 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:35:51 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:35:51 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:35:52 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:35:52 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:35:52 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:35:52 PM - INFO - Creating new RobustScaler
+05/03/2018 07:35:52 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:35:52 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:35:52 PM - INFO - Training and test data transformed
+05/03/2018 07:35:52 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:35:52 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:35:52 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:35:52 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:35:52 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:52 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:35:52 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:35:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:35:53 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:35:53 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:53 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:53 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:53 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:35:53 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:35:53 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:35:53 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:35:53 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:35:53 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:35:53 PM - INFO - Train model
+05/03/2018 07:35:53 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:35:53 PM - INFO - KeyError
+05/03/2018 07:35:53 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:35:53 PM - INFO - Compile model
+05/03/2018 07:35:53 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:35:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:36:03 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:36:06 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:36:07 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:36:07 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:36:09 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:36:09 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:36:09 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:36:09 PM - INFO - Creating new RobustScaler
+05/03/2018 07:36:09 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:36:09 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:36:09 PM - INFO - Training and test data transformed
+05/03/2018 07:36:09 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:36:09 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:36:09 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:36:09 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:36:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:36:09 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:36:09 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:36:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:36:09 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:36:09 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:36:09 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:36:09 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:36:09 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:36:09 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:36:09 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:36:09 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:36:09 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:36:09 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:36:09 PM - INFO - Train model
+05/03/2018 07:36:09 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:36:09 PM - INFO - KeyError
+05/03/2018 07:36:09 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:36:09 PM - INFO - Compile model
+05/03/2018 07:36:09 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:36:09 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:36:49 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:36:55 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:36:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:36:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:37:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:37:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:37:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:37:00 PM - INFO - Creating new RobustScaler
+05/03/2018 07:37:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:37:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:37:00 PM - INFO - Training and test data transformed
+05/03/2018 07:37:00 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:37:00 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:37:00 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:37:00 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:37:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:37:00 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:37:00 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:37:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:37:00 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:37:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:37:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:37:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:37:00 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:37:00 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:37:00 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:37:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:37:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:37:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:37:01 PM - INFO - Train model
+05/03/2018 07:37:01 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:37:01 PM - INFO - KeyError
+05/03/2018 07:37:01 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:37:01 PM - INFO - Compile model
+05/03/2018 07:37:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:37:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:37:51 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:37:57 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:38:01 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:38:01 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:38:02 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:38:02 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:38:02 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:38:02 PM - INFO - Creating new RobustScaler
+05/03/2018 07:38:02 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:38:02 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:38:02 PM - INFO - Training and test data transformed
+05/03/2018 07:38:02 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:38:02 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:38:02 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:38:02 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:38:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:03 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:38:03 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:38:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:03 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:38:03 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:03 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:03 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:03 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:38:03 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:38:03 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:38:03 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:03 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:03 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:03 PM - INFO - Train model
+05/03/2018 07:38:03 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:38:03 PM - INFO - KeyError
+05/03/2018 07:38:03 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:38:03 PM - INFO - Compile model
+05/03/2018 07:38:03 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:38:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:11 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:38:14 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:38:15 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:38:15 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:38:16 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:38:16 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:38:16 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:38:16 PM - INFO - Creating new RobustScaler
+05/03/2018 07:38:16 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:38:16 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:38:16 PM - INFO - Training and test data transformed
+05/03/2018 07:38:17 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:38:17 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:38:17 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:38:17 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:38:17 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:17 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:38:17 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:38:17 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:17 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:38:17 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:17 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:17 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:17 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:38:17 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:38:17 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:38:17 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:17 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:17 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:17 PM - INFO - Train model
+05/03/2018 07:38:17 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:38:17 PM - INFO - KeyError
+05/03/2018 07:38:17 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:38:17 PM - INFO - Compile model
+05/03/2018 07:38:17 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:38:17 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:25 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:38:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:38:29 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:38:29 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:38:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:38:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:38:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:38:31 PM - INFO - Creating new RobustScaler
+05/03/2018 07:38:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:38:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:38:31 PM - INFO - Training and test data transformed
+05/03/2018 07:38:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:38:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:38:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:38:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:38:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:38:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:38:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:38:31 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:38:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:31 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:38:31 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:38:31 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:38:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:38:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:38:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:38:31 PM - INFO - Train model
+05/03/2018 07:38:31 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:38:31 PM - INFO - KeyError
+05/03/2018 07:38:31 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:38:31 PM - INFO - Compile model
+05/03/2018 07:38:31 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:38:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:40:43 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:40:52 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:40:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:40:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:40:58 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:40:58 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:40:58 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:40:58 PM - INFO - Creating new RobustScaler
+05/03/2018 07:40:58 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:40:58 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:40:58 PM - INFO - Training and test data transformed
+05/03/2018 07:40:58 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:40:58 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:40:58 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:40:58 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:40:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:40:59 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:40:59 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:40:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:40:59 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:40:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:40:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:40:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:40:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:40:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:40:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:40:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:40:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:40:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:40:59 PM - INFO - Train model
+05/03/2018 07:40:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:40:59 PM - INFO - KeyError
+05/03/2018 07:40:59 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:40:59 PM - INFO - Compile model
+05/03/2018 07:40:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:40:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:07 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:41:09 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:41:10 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:41:10 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:41:12 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:41:12 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:41:12 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:41:12 PM - INFO - Creating new RobustScaler
+05/03/2018 07:41:12 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:41:12 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:41:12 PM - INFO - Training and test data transformed
+05/03/2018 07:41:12 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:41:12 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:41:12 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:41:12 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:41:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:12 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:41:12 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:41:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:12 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:41:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:12 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:12 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:12 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:41:12 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:41:12 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:41:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:12 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:12 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:12 PM - INFO - Train model
+05/03/2018 07:41:12 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:41:12 PM - INFO - KeyError
+05/03/2018 07:41:12 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:41:12 PM - INFO - Compile model
+05/03/2018 07:41:12 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:41:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:38 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:41:42 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:41:44 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:41:44 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:41:46 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:41:46 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:41:46 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:41:46 PM - INFO - Creating new RobustScaler
+05/03/2018 07:41:46 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:41:46 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:41:46 PM - INFO - Training and test data transformed
+05/03/2018 07:41:46 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:41:46 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:41:46 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:41:46 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:41:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:46 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:41:46 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:41:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:46 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:41:46 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:46 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:46 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:46 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:41:46 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:41:46 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:41:46 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:46 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:46 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:46 PM - INFO - Train model
+05/03/2018 07:41:46 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:41:46 PM - INFO - KeyError
+05/03/2018 07:41:46 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:41:46 PM - INFO - Compile model
+05/03/2018 07:41:46 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:41:46 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:53 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:41:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:41:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:41:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:41:58 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:41:58 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:41:58 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:41:58 PM - INFO - Creating new RobustScaler
+05/03/2018 07:41:58 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:41:58 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:41:58 PM - INFO - Training and test data transformed
+05/03/2018 07:41:58 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:41:58 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:41:58 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:41:58 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:41:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:59 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:41:59 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:41:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:41:59 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:41:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:41:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:41:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:41:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:41:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:41:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:41:59 PM - INFO - Train model
+05/03/2018 07:41:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:41:59 PM - INFO - KeyError
+05/03/2018 07:41:59 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:41:59 PM - INFO - Compile model
+05/03/2018 07:41:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:41:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:42:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:42:09 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:42:10 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:42:10 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:42:11 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:42:11 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:42:11 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:42:11 PM - INFO - Creating new RobustScaler
+05/03/2018 07:42:11 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:42:11 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:42:11 PM - INFO - Training and test data transformed
+05/03/2018 07:42:11 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:42:11 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:42:11 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:42:11 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:42:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:42:12 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:42:12 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:42:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:42:12 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:42:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:42:12 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:42:12 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:42:12 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:42:12 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:42:12 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:42:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:42:12 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:42:12 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:42:12 PM - INFO - Train model
+05/03/2018 07:42:12 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:42:12 PM - INFO - KeyError
+05/03/2018 07:42:12 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:42:12 PM - INFO - Compile model
+05/03/2018 07:42:12 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:42:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:44:32 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:44:44 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:44:50 PM - INFO - Generation average: 96.95%
+05/03/2018 07:44:50 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:44:50 PM - INFO - ***Doing generation 5 of 10***
+05/03/2018 07:44:50 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:44:50 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:44:51 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:44:51 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:44:51 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:44:51 PM - INFO - Creating new RobustScaler
+05/03/2018 07:44:51 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:44:51 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:44:51 PM - INFO - Training and test data transformed
+05/03/2018 07:44:51 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:44:51 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:44:51 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:44:51 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:44:51 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:44:51 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:44:51 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:44:51 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:44:51 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:44:51 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:44:51 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:44:51 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:44:52 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:44:52 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:44:52 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:44:52 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:44:52 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:44:52 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:44:52 PM - INFO - Train model
+05/03/2018 07:44:52 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:44:52 PM - INFO - KeyError
+05/03/2018 07:44:52 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:44:52 PM - INFO - Compile model
+05/03/2018 07:44:52 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:44:52 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:44:59 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:45:02 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:45:03 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:45:03 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:45:05 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:45:05 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:45:05 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:45:05 PM - INFO - Creating new RobustScaler
+05/03/2018 07:45:05 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:45:05 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:45:05 PM - INFO - Training and test data transformed
+05/03/2018 07:45:05 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:45:05 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:45:05 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:45:05 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:45:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:05 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:45:05 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:45:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:05 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:45:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:05 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:45:05 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:45:05 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:45:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:05 PM - INFO - Train model
+05/03/2018 07:45:05 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:45:05 PM - INFO - KeyError
+05/03/2018 07:45:05 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:45:05 PM - INFO - Compile model
+05/03/2018 07:45:05 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:45:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:13 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:45:15 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:45:17 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:45:17 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:45:18 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:45:18 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:45:18 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:45:18 PM - INFO - Creating new RobustScaler
+05/03/2018 07:45:18 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:45:18 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:45:18 PM - INFO - Training and test data transformed
+05/03/2018 07:45:18 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:45:18 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:45:18 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:45:18 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:45:18 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:18 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:45:18 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:45:18 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:18 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:45:18 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:18 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:18 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:18 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:45:18 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:45:18 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:45:18 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:18 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:18 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:18 PM - INFO - Train model
+05/03/2018 07:45:18 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:45:18 PM - INFO - KeyError
+05/03/2018 07:45:18 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:45:18 PM - INFO - Compile model
+05/03/2018 07:45:18 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:45:18 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:24 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:45:27 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:45:28 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:45:28 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:45:30 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:45:30 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:45:30 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:45:30 PM - INFO - Creating new RobustScaler
+05/03/2018 07:45:30 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:45:30 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:45:30 PM - INFO - Training and test data transformed
+05/03/2018 07:45:30 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:45:30 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:45:30 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:45:30 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:45:30 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:30 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:45:30 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:45:30 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:30 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:45:30 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:30 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:30 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:30 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:45:30 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:45:30 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:45:30 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:30 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:30 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:30 PM - INFO - Train model
+05/03/2018 07:45:30 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:45:30 PM - INFO - KeyError
+05/03/2018 07:45:30 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:45:30 PM - INFO - Compile model
+05/03/2018 07:45:30 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:45:30 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:39 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:45:42 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:45:44 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:45:44 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:45:45 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:45:45 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:45:45 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:45:45 PM - INFO - Creating new RobustScaler
+05/03/2018 07:45:45 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:45:45 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:45:45 PM - INFO - Training and test data transformed
+05/03/2018 07:45:45 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:45:45 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:45:45 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:45:45 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:45:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:45 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:45:45 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:45:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:45 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:45:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:45 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:45:45 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:45:45 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:45:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:45 PM - INFO - Train model
+05/03/2018 07:45:45 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:45:45 PM - INFO - KeyError
+05/03/2018 07:45:45 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:45:45 PM - INFO - Compile model
+05/03/2018 07:45:45 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:45:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:53 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:45:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:45:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:45:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:45:58 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:45:58 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:45:58 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:45:58 PM - INFO - Creating new RobustScaler
+05/03/2018 07:45:58 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:45:58 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:45:58 PM - INFO - Training and test data transformed
+05/03/2018 07:45:58 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:45:58 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:45:58 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:45:58 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:45:58 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:58 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:45:58 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:45:58 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:45:58 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:45:58 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:58 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:58 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:45:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:45:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:45:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:45:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:45:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:45:59 PM - INFO - Train model
+05/03/2018 07:45:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:45:59 PM - INFO - KeyError
+05/03/2018 07:45:59 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:45:59 PM - INFO - Compile model
+05/03/2018 07:45:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:45:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:46:07 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:46:10 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:46:11 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:46:11 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:46:12 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:46:12 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:46:12 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:46:12 PM - INFO - Creating new RobustScaler
+05/03/2018 07:46:12 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:46:12 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:46:12 PM - INFO - Training and test data transformed
+05/03/2018 07:46:12 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:46:12 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:46:12 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:46:12 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:46:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:46:12 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:46:12 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:46:12 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:46:12 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:46:12 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:46:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:46:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:46:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:46:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:46:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:46:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:46:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:46:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:46:13 PM - INFO - Train model
+05/03/2018 07:46:13 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:46:13 PM - INFO - KeyError
+05/03/2018 07:46:13 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:46:13 PM - INFO - Compile model
+05/03/2018 07:46:13 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:46:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:46:50 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:46:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:46:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:46:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:47:01 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:47:01 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:47:01 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:47:01 PM - INFO - Creating new RobustScaler
+05/03/2018 07:47:01 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:47:01 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:47:01 PM - INFO - Training and test data transformed
+05/03/2018 07:47:01 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:47:01 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:47:01 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:47:01 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:47:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:01 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:47:01 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:47:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:01 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:47:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:01 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:47:01 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:47:01 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:47:01 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:01 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:01 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:01 PM - INFO - Train model
+05/03/2018 07:47:01 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:47:01 PM - INFO - KeyError
+05/03/2018 07:47:01 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:47:01 PM - INFO - Compile model
+05/03/2018 07:47:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:47:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:10 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:47:13 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:47:14 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:47:14 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:47:16 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:47:16 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:47:16 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:47:16 PM - INFO - Creating new RobustScaler
+05/03/2018 07:47:16 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:47:16 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:47:16 PM - INFO - Training and test data transformed
+05/03/2018 07:47:16 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:47:16 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:47:16 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:47:16 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:47:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:16 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:47:16 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:47:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:16 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:47:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:16 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:47:16 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:47:16 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:47:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:16 PM - INFO - Train model
+05/03/2018 07:47:16 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:47:16 PM - INFO - KeyError
+05/03/2018 07:47:16 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:47:16 PM - INFO - Compile model
+05/03/2018 07:47:16 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:47:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:27 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:47:30 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:47:32 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:47:32 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:47:33 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:47:33 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:47:33 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:47:33 PM - INFO - Creating new RobustScaler
+05/03/2018 07:47:33 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:47:33 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:47:33 PM - INFO - Training and test data transformed
+05/03/2018 07:47:33 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:47:33 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:47:33 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:47:33 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:47:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:33 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:47:33 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:47:33 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:47:33 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:47:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:33 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:47:33 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:47:33 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:47:33 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:47:33 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:47:33 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:47:33 PM - INFO - Train model
+05/03/2018 07:47:34 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:47:34 PM - INFO - KeyError
+05/03/2018 07:47:34 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:47:34 PM - INFO - Compile model
+05/03/2018 07:47:34 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:47:34 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:48:53 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:49:04 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:49:09 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:49:09 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:49:10 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:49:10 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:49:10 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:49:10 PM - INFO - Creating new RobustScaler
+05/03/2018 07:49:10 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:49:10 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:49:10 PM - INFO - Training and test data transformed
+05/03/2018 07:49:10 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:49:10 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:49:10 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:49:10 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:49:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:10 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:49:10 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:49:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:10 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:49:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:10 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:10 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:11 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:49:11 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:49:11 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:49:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:11 PM - INFO - Train model
+05/03/2018 07:49:11 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:49:11 PM - INFO - KeyError
+05/03/2018 07:49:11 PM - INFO - Using adam(**{}) as Optimizer
+05/03/2018 07:49:11 PM - INFO - Compile model
+05/03/2018 07:49:11 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:49:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:21 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:49:24 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:49:25 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:49:25 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:49:26 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:49:26 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:49:26 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:49:26 PM - INFO - Creating new RobustScaler
+05/03/2018 07:49:26 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:49:26 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:49:26 PM - INFO - Training and test data transformed
+05/03/2018 07:49:26 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:49:26 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:49:26 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:49:26 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:49:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:26 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:49:26 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:49:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:26 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:49:26 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:26 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:26 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:27 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:49:27 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:49:27 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:49:27 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:27 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:27 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:27 PM - INFO - Train model
+05/03/2018 07:49:27 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:49:27 PM - INFO - KeyError
+05/03/2018 07:49:27 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:49:27 PM - INFO - Compile model
+05/03/2018 07:49:27 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:49:27 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:36 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:49:39 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:49:41 PM - INFO - Generation average: 97.03%
+05/03/2018 07:49:41 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:49:41 PM - INFO - ***Doing generation 6 of 10***
+05/03/2018 07:49:41 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:49:41 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:49:42 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:49:42 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:49:42 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:49:42 PM - INFO - Creating new RobustScaler
+05/03/2018 07:49:42 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:49:42 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:49:42 PM - INFO - Training and test data transformed
+05/03/2018 07:49:42 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:49:42 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:49:42 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:49:42 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:49:42 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:42 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:49:42 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:49:42 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:42 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:49:42 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:42 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:42 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:42 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:49:42 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:49:42 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:49:42 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:42 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:42 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:42 PM - INFO - Train model
+05/03/2018 07:49:43 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:49:43 PM - INFO - KeyError
+05/03/2018 07:49:43 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:49:43 PM - INFO - Compile model
+05/03/2018 07:49:43 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:49:43 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:51 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:49:54 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:49:55 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:49:55 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:49:56 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:49:56 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:49:56 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:49:56 PM - INFO - Creating new RobustScaler
+05/03/2018 07:49:56 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:49:56 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:49:56 PM - INFO - Training and test data transformed
+05/03/2018 07:49:56 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:49:56 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:49:56 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:49:56 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:49:56 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:56 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:49:56 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:49:57 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:49:57 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:49:57 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:57 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:57 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:57 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:49:57 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:49:57 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:49:57 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:49:57 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:49:57 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:49:57 PM - INFO - Train model
+05/03/2018 07:49:57 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:49:57 PM - INFO - KeyError
+05/03/2018 07:49:57 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:49:57 PM - INFO - Compile model
+05/03/2018 07:49:57 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:49:57 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:04 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:50:07 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:50:08 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:50:08 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:50:10 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:50:10 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:50:10 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:50:10 PM - INFO - Creating new RobustScaler
+05/03/2018 07:50:10 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:50:10 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:50:10 PM - INFO - Training and test data transformed
+05/03/2018 07:50:10 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:50:10 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:50:10 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:50:10 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:50:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:10 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:50:10 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:50:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:10 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:50:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:50:10 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:50:10 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:50:10 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:50:10 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:50:10 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:50:10 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:50:10 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:50:10 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:50:10 PM - INFO - Train model
+05/03/2018 07:50:10 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:50:10 PM - INFO - KeyError
+05/03/2018 07:50:10 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:50:10 PM - INFO - Compile model
+05/03/2018 07:50:10 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:50:10 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:17 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:50:20 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:50:21 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:50:21 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:50:22 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:50:22 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:50:22 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:50:22 PM - INFO - Creating new RobustScaler
+05/03/2018 07:50:22 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:50:22 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:50:22 PM - INFO - Training and test data transformed
+05/03/2018 07:50:23 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:50:23 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:50:23 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:50:23 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:50:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:23 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:50:23 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:50:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:50:23 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:50:23 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:50:23 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:50:23 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:50:23 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:50:23 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:50:23 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:50:23 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:50:23 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:50:23 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:50:23 PM - INFO - Train model
+05/03/2018 07:50:23 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:50:23 PM - INFO - KeyError
+05/03/2018 07:50:23 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:50:23 PM - INFO - Compile model
+05/03/2018 07:50:23 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:50:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:28 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:51:38 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:51:44 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:51:44 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:51:45 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:51:45 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:51:45 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:51:45 PM - INFO - Creating new RobustScaler
+05/03/2018 07:51:45 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:51:45 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:51:45 PM - INFO - Training and test data transformed
+05/03/2018 07:51:45 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:51:45 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:51:45 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:51:45 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:51:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:45 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:51:45 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:51:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:45 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:51:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:51:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:51:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:51:45 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:51:45 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:51:45 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:51:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:51:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:51:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:51:45 PM - INFO - Train model
+05/03/2018 07:51:45 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:51:45 PM - INFO - KeyError
+05/03/2018 07:51:45 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:51:45 PM - INFO - Compile model
+05/03/2018 07:51:45 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:51:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:53 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:51:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:51:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:51:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:51:58 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:51:58 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:51:58 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:51:58 PM - INFO - Creating new RobustScaler
+05/03/2018 07:51:58 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:51:58 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:51:58 PM - INFO - Training and test data transformed
+05/03/2018 07:51:58 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:51:58 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:51:58 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:51:58 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:51:58 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:58 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:51:58 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:51:58 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:51:58 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:51:58 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:51:58 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:51:58 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:51:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:51:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:51:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:51:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:51:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:51:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:51:59 PM - INFO - Train model
+05/03/2018 07:51:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:51:59 PM - INFO - KeyError
+05/03/2018 07:51:59 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 07:51:59 PM - INFO - Compile model
+05/03/2018 07:51:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:51:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:52:07 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:52:10 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:52:11 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:52:11 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:52:13 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:52:13 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:52:13 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:52:13 PM - INFO - Creating new RobustScaler
+05/03/2018 07:52:13 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:52:13 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:52:13 PM - INFO - Training and test data transformed
+05/03/2018 07:52:13 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:52:13 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:52:13 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:52:13 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:52:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:52:13 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:52:13 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:52:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:52:13 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:52:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:52:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:52:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:52:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:52:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:52:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:52:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:52:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:52:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:52:13 PM - INFO - Train model
+05/03/2018 07:52:13 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:52:13 PM - INFO - KeyError
+05/03/2018 07:52:13 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:52:13 PM - INFO - Compile model
+05/03/2018 07:52:13 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:52:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:53:46 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:53:56 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:54:01 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:54:01 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:54:02 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:54:02 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:54:02 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:54:02 PM - INFO - Creating new RobustScaler
+05/03/2018 07:54:02 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:54:02 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:54:02 PM - INFO - Training and test data transformed
+05/03/2018 07:54:02 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:54:02 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:54:02 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:54:02 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:54:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:54:02 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:54:02 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:54:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:54:02 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:54:03 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:54:03 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:54:03 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:54:03 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:54:03 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:54:03 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:54:03 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:54:03 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:54:03 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:54:03 PM - INFO - Train model
+05/03/2018 07:54:03 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:54:03 PM - INFO - KeyError
+05/03/2018 07:54:03 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:54:03 PM - INFO - Compile model
+05/03/2018 07:54:03 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:54:03 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:55:57 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:56:07 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:56:12 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:56:12 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:56:14 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:56:14 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:56:14 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:56:14 PM - INFO - Creating new RobustScaler
+05/03/2018 07:56:14 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:56:14 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:56:14 PM - INFO - Training and test data transformed
+05/03/2018 07:56:14 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:56:14 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:56:14 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:56:14 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:56:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:56:14 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:56:14 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:56:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:56:14 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:56:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:56:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:56:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:56:14 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:56:14 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:56:14 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:56:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:56:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:56:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:56:14 PM - INFO - Train model
+05/03/2018 07:56:14 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:56:14 PM - INFO - KeyError
+05/03/2018 07:56:14 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:56:14 PM - INFO - Compile model
+05/03/2018 07:56:14 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:56:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:56:28 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:56:32 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:56:34 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:56:34 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:56:35 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:56:35 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:56:35 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:56:35 PM - INFO - Creating new RobustScaler
+05/03/2018 07:56:35 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:56:35 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:56:35 PM - INFO - Training and test data transformed
+05/03/2018 07:56:35 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:56:35 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:56:35 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:56:35 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:56:35 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:56:35 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:56:35 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:56:35 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:56:35 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:56:35 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:56:35 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:56:35 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:56:35 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:56:35 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:56:35 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:56:35 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:56:35 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:56:35 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:56:35 PM - INFO - Train model
+05/03/2018 07:56:35 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:56:35 PM - INFO - KeyError
+05/03/2018 07:56:35 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:56:35 PM - INFO - Compile model
+05/03/2018 07:56:35 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:56:35 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:57:30 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:57:41 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:57:46 PM - INFO - Generation average: 96.79%
+05/03/2018 07:57:46 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 07:57:46 PM - INFO - ***Doing generation 7 of 10***
+05/03/2018 07:57:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:57:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:57:48 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:57:48 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:57:48 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:57:48 PM - INFO - Creating new RobustScaler
+05/03/2018 07:57:48 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:57:48 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:57:48 PM - INFO - Training and test data transformed
+05/03/2018 07:57:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:57:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:57:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:57:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:57:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:57:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:57:48 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:57:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:57:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:57:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:57:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:57:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:57:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:57:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:57:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:57:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:57:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:57:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:57:48 PM - INFO - Train model
+05/03/2018 07:57:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:57:48 PM - INFO - KeyError
+05/03/2018 07:57:48 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:57:48 PM - INFO - Compile model
+05/03/2018 07:57:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:57:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:58:42 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:58:53 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:58:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:58:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:59:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:59:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:59:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:59:00 PM - INFO - Creating new RobustScaler
+05/03/2018 07:59:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:59:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:59:00 PM - INFO - Training and test data transformed
+05/03/2018 07:59:00 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:59:00 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:59:00 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:59:00 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:59:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:00 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:59:00 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:59:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:00 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:59:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:00 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:59:00 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:59:00 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:59:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:00 PM - INFO - Train model
+05/03/2018 07:59:00 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:59:00 PM - INFO - KeyError
+05/03/2018 07:59:01 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 07:59:01 PM - INFO - Compile model
+05/03/2018 07:59:01 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:59:01 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:10 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:59:13 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:59:14 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:59:14 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:59:16 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:59:16 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:59:16 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:59:16 PM - INFO - Creating new RobustScaler
+05/03/2018 07:59:16 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:59:16 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:59:16 PM - INFO - Training and test data transformed
+05/03/2018 07:59:16 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:59:16 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:59:16 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:59:16 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:59:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:16 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:59:16 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:59:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:16 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:59:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:16 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:59:16 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:59:16 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:59:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:16 PM - INFO - Train model
+05/03/2018 07:59:16 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:59:16 PM - INFO - KeyError
+05/03/2018 07:59:16 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:59:16 PM - INFO - Compile model
+05/03/2018 07:59:16 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:59:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:25 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:59:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:59:30 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:59:30 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:59:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:59:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:59:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:59:31 PM - INFO - Creating new RobustScaler
+05/03/2018 07:59:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:59:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:59:31 PM - INFO - Training and test data transformed
+05/03/2018 07:59:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:59:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:59:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:59:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:59:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:59:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:59:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:31 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:59:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:31 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:59:31 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:59:31 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:59:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:31 PM - INFO - Train model
+05/03/2018 07:59:31 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:59:31 PM - INFO - KeyError
+05/03/2018 07:59:31 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 07:59:31 PM - INFO - Compile model
+05/03/2018 07:59:31 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:59:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:39 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:59:42 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:59:44 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:59:44 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 07:59:45 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 07:59:45 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 07:59:45 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 07:59:45 PM - INFO - Creating new RobustScaler
+05/03/2018 07:59:45 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 07:59:45 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 07:59:45 PM - INFO - Training and test data transformed
+05/03/2018 07:59:45 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 07:59:45 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 07:59:45 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 07:59:45 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 07:59:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:45 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 07:59:45 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 07:59:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:45 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 07:59:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:45 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 07:59:45 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 07:59:45 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 07:59:45 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 07:59:45 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 07:59:45 PM - DEBUG - Writing TrueType font.
+05/03/2018 07:59:45 PM - INFO - Train model
+05/03/2018 07:59:45 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 07:59:45 PM - INFO - KeyError
+05/03/2018 07:59:45 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 07:59:45 PM - INFO - Compile model
+05/03/2018 07:59:45 PM - INFO - No weights found, starting completely new model
+05/03/2018 07:59:45 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 07:59:54 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 07:59:57 PM - INFO - Get test loss and metrics of the model
+05/03/2018 07:59:59 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 07:59:59 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:00:00 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:00:00 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:00:00 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:00:00 PM - INFO - Creating new RobustScaler
+05/03/2018 08:00:00 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:00:00 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:00:00 PM - INFO - Training and test data transformed
+05/03/2018 08:00:00 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:00:00 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:00:00 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:00:00 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:00:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:00 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:00:00 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:00:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:00 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:00:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:00 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:00:00 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:00:00 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:00:00 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:00 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:00 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:00 PM - INFO - Train model
+05/03/2018 08:00:00 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:00:00 PM - INFO - KeyError
+05/03/2018 08:00:00 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:00:00 PM - INFO - Compile model
+05/03/2018 08:00:00 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:00:00 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:09 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:00:12 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:00:14 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:00:14 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:00:15 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:00:15 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:00:15 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:00:15 PM - INFO - Creating new RobustScaler
+05/03/2018 08:00:15 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:00:15 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:00:15 PM - INFO - Training and test data transformed
+05/03/2018 08:00:15 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:00:15 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:00:15 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:00:15 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:00:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:15 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:00:15 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:00:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:15 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:00:15 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:16 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:00:16 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:00:16 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:00:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:16 PM - INFO - Train model
+05/03/2018 08:00:16 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:00:16 PM - INFO - KeyError
+05/03/2018 08:00:16 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:00:16 PM - INFO - Compile model
+05/03/2018 08:00:16 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:00:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:25 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:00:29 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:00:30 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:00:30 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:00:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:00:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:00:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:00:31 PM - INFO - Creating new RobustScaler
+05/03/2018 08:00:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:00:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:00:31 PM - INFO - Training and test data transformed
+05/03/2018 08:00:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:00:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:00:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:00:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:00:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:00:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:00:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:32 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:00:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:32 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:00:32 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:00:32 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:00:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:32 PM - INFO - Train model
+05/03/2018 08:00:32 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:00:32 PM - INFO - KeyError
+05/03/2018 08:00:32 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:00:32 PM - INFO - Compile model
+05/03/2018 08:00:32 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:00:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:41 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:00:45 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:00:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:00:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:00:48 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:00:48 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:00:48 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:00:48 PM - INFO - Creating new RobustScaler
+05/03/2018 08:00:48 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:00:48 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:00:48 PM - INFO - Training and test data transformed
+05/03/2018 08:00:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:00:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:00:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:00:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:00:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:00:48 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:00:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:00:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:00:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:00:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:00:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:00:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:00:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:00:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:00:48 PM - INFO - Train model
+05/03/2018 08:00:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:00:48 PM - INFO - KeyError
+05/03/2018 08:00:48 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:00:48 PM - INFO - Compile model
+05/03/2018 08:00:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:00:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:01:11 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:01:13 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:01:13 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:01:14 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:01:14 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:01:14 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:01:14 PM - INFO - Creating new RobustScaler
+05/03/2018 08:01:14 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:01:14 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:01:14 PM - INFO - Training and test data transformed
+05/03/2018 08:01:14 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:01:14 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:01:14 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:01:14 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:01:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:14 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:01:14 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:01:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:14 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:01:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:14 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:01:14 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:01:14 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:01:14 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:14 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:14 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:14 PM - INFO - Train model
+05/03/2018 08:01:14 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:01:14 PM - INFO - KeyError
+05/03/2018 08:01:15 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 08:01:15 PM - INFO - Compile model
+05/03/2018 08:01:15 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:01:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:24 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:01:28 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:01:30 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:01:30 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:01:31 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:01:31 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:01:31 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:01:31 PM - INFO - Creating new RobustScaler
+05/03/2018 08:01:31 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:01:31 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:01:31 PM - INFO - Training and test data transformed
+05/03/2018 08:01:31 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:01:31 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:01:31 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:01:31 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:01:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:31 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:01:31 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:01:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:31 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:01:31 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:31 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:31 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:31 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:01:31 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:01:31 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:01:32 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:32 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:32 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:32 PM - INFO - Train model
+05/03/2018 08:01:32 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:01:32 PM - INFO - KeyError
+05/03/2018 08:01:32 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:01:32 PM - INFO - Compile model
+05/03/2018 08:01:32 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:01:32 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:41 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:01:45 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:01:46 PM - INFO - Generation average: 97.01%
+05/03/2018 08:01:46 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 08:01:46 PM - INFO - ***Doing generation 8 of 10***
+05/03/2018 08:01:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:01:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:01:48 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:01:48 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:01:48 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:01:48 PM - INFO - Creating new RobustScaler
+05/03/2018 08:01:48 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:01:48 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:01:48 PM - INFO - Training and test data transformed
+05/03/2018 08:01:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:01:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:01:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:01:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:01:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:01:48 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:01:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:01:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:01:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:01:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:01:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:01:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:01:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:01:48 PM - INFO - Train model
+05/03/2018 08:01:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:01:48 PM - INFO - KeyError
+05/03/2018 08:01:48 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:01:48 PM - INFO - Compile model
+05/03/2018 08:01:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:01:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:01:55 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:01:59 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:02:00 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:02:00 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:02:02 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:02:02 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:02:02 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:02:02 PM - INFO - Creating new RobustScaler
+05/03/2018 08:02:02 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:02:02 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:02:02 PM - INFO - Training and test data transformed
+05/03/2018 08:02:02 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:02:02 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:02:02 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:02:02 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:02:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:02 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:02:02 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:02:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:02 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:02:02 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:02 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:02 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:02 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:02:02 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:02:02 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:02:02 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:02 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:02 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:02 PM - INFO - Train model
+05/03/2018 08:02:02 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:02:02 PM - INFO - KeyError
+05/03/2018 08:02:02 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:02:02 PM - INFO - Compile model
+05/03/2018 08:02:02 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:02:02 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:09 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:02:12 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:02:14 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:02:14 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:02:15 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:02:15 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:02:15 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:02:15 PM - INFO - Creating new RobustScaler
+05/03/2018 08:02:15 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:02:15 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:02:15 PM - INFO - Training and test data transformed
+05/03/2018 08:02:15 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:02:15 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:02:15 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:02:15 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:02:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:15 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:02:15 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:02:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:15 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:02:15 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:15 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:15 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:15 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:02:15 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:02:15 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:02:16 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:16 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:16 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:16 PM - INFO - Train model
+05/03/2018 08:02:16 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:02:16 PM - INFO - KeyError
+05/03/2018 08:02:16 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:02:16 PM - INFO - Compile model
+05/03/2018 08:02:16 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:02:16 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:23 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:02:27 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:02:29 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:02:29 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:02:30 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:02:30 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:02:30 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:02:30 PM - INFO - Creating new RobustScaler
+05/03/2018 08:02:30 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:02:30 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:02:30 PM - INFO - Training and test data transformed
+05/03/2018 08:02:30 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:02:30 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:02:30 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:02:30 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:02:30 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:30 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:02:30 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:02:30 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:30 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:02:30 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:30 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:30 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:30 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:02:30 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:02:30 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:02:30 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:30 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:30 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:30 PM - INFO - Train model
+05/03/2018 08:02:31 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:02:31 PM - INFO - KeyError
+05/03/2018 08:02:31 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:02:31 PM - INFO - Compile model
+05/03/2018 08:02:31 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:02:31 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:41 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:02:45 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:02:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:02:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:02:48 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:02:48 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:02:48 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:02:48 PM - INFO - Creating new RobustScaler
+05/03/2018 08:02:48 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:02:48 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:02:48 PM - INFO - Training and test data transformed
+05/03/2018 08:02:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:02:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:02:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:02:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:02:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:02:48 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:02:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:02:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:02:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:02:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:02:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:02:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:02:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:02:48 PM - INFO - Train model
+05/03/2018 08:02:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:02:48 PM - INFO - KeyError
+05/03/2018 08:02:48 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:02:48 PM - INFO - Compile model
+05/03/2018 08:02:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:02:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:02:58 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:03:02 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:03:03 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:03:03 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:03:05 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:03:05 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:03:05 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:03:05 PM - INFO - Creating new RobustScaler
+05/03/2018 08:03:05 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:03:05 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:03:05 PM - INFO - Training and test data transformed
+05/03/2018 08:03:05 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:03:05 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:03:05 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:03:05 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:03:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:05 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:03:05 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:03:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:05 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:03:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:05 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:03:05 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:03:05 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:03:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:05 PM - INFO - Train model
+05/03/2018 08:03:05 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:03:05 PM - INFO - KeyError
+05/03/2018 08:03:05 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:03:05 PM - INFO - Compile model
+05/03/2018 08:03:05 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:03:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:14 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:03:17 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:03:19 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:03:19 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:03:20 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:03:20 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:03:20 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:03:20 PM - INFO - Creating new RobustScaler
+05/03/2018 08:03:20 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:03:20 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:03:20 PM - INFO - Training and test data transformed
+05/03/2018 08:03:20 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:03:20 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:03:20 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:03:20 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:03:20 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:20 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:03:20 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:03:21 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:21 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:03:21 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:21 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:21 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:21 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:03:21 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:03:21 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:03:21 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:21 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:21 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:21 PM - INFO - Train model
+05/03/2018 08:03:21 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:03:21 PM - INFO - KeyError
+05/03/2018 08:03:21 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:03:21 PM - INFO - Compile model
+05/03/2018 08:03:21 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:03:21 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:28 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:03:32 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:03:34 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:03:34 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:03:35 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:03:35 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:03:35 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:03:35 PM - INFO - Creating new RobustScaler
+05/03/2018 08:03:35 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:03:35 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:03:35 PM - INFO - Training and test data transformed
+05/03/2018 08:03:35 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:03:35 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:03:35 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:03:35 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:03:35 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:35 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:03:35 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:03:35 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:35 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:03:35 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:35 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:35 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:35 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:03:35 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:03:35 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:03:35 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:35 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:35 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:36 PM - INFO - Train model
+05/03/2018 08:03:36 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:03:36 PM - INFO - KeyError
+05/03/2018 08:03:36 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:03:36 PM - INFO - Compile model
+05/03/2018 08:03:36 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:03:36 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:42 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:03:46 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:03:48 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:03:48 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:03:49 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:03:49 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:03:49 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:03:49 PM - INFO - Creating new RobustScaler
+05/03/2018 08:03:49 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:03:49 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:03:49 PM - INFO - Training and test data transformed
+05/03/2018 08:03:49 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:03:49 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:03:49 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:03:49 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:03:49 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:49 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:03:49 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:03:49 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:03:49 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:03:49 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:49 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:49 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:49 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:03:49 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:03:49 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:03:49 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:03:49 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:03:49 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:03:50 PM - INFO - Train model
+05/03/2018 08:03:50 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:03:50 PM - INFO - KeyError
+05/03/2018 08:03:50 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:03:50 PM - INFO - Compile model
+05/03/2018 08:03:50 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:03:50 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:01 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:04:04 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:04:06 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:04:06 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:04:07 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:04:07 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:04:07 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:04:07 PM - INFO - Creating new RobustScaler
+05/03/2018 08:04:07 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:04:07 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:04:07 PM - INFO - Training and test data transformed
+05/03/2018 08:04:07 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:04:07 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:04:07 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:04:07 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:04:08 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:08 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:04:08 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:04:08 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:08 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:04:08 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:08 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:08 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:08 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:04:08 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:04:08 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:04:08 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:08 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:08 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:08 PM - INFO - Train model
+05/03/2018 08:04:08 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:04:08 PM - INFO - KeyError
+05/03/2018 08:04:08 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:04:08 PM - INFO - Compile model
+05/03/2018 08:04:08 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:04:08 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:17 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:04:20 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:04:22 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:04:22 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:04:23 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:04:23 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:04:23 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:04:23 PM - INFO - Creating new RobustScaler
+05/03/2018 08:04:23 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:04:23 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:04:23 PM - INFO - Training and test data transformed
+05/03/2018 08:04:23 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:04:23 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:04:23 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:04:23 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:04:23 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:23 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:04:23 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:04:24 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:24 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:04:24 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:24 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:24 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:24 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:04:24 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:04:24 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:04:24 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:24 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:24 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:24 PM - INFO - Train model
+05/03/2018 08:04:24 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:04:24 PM - INFO - KeyError
+05/03/2018 08:04:24 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:04:24 PM - INFO - Compile model
+05/03/2018 08:04:25 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:04:25 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:35 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:04:38 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:04:40 PM - INFO - Generation average: 96.94%
+05/03/2018 08:04:40 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 08:04:40 PM - INFO - ***Doing generation 9 of 10***
+05/03/2018 08:04:40 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:04:40 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:04:41 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:04:41 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:04:41 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:04:41 PM - INFO - Creating new RobustScaler
+05/03/2018 08:04:41 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:04:41 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:04:41 PM - INFO - Training and test data transformed
+05/03/2018 08:04:41 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:04:41 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:04:41 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:04:41 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:04:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:41 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:04:41 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:04:41 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:04:41 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:04:41 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:41 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:41 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:42 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:04:42 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:04:42 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:04:42 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:04:42 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:04:42 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:04:42 PM - INFO - Train model
+05/03/2018 08:04:42 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:04:42 PM - INFO - KeyError
+05/03/2018 08:04:42 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:04:42 PM - INFO - Compile model
+05/03/2018 08:04:42 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:04:42 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:05:33 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:05:41 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:05:45 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:05:45 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:05:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:05:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:05:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:05:47 PM - INFO - Creating new RobustScaler
+05/03/2018 08:05:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:05:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:05:47 PM - INFO - Training and test data transformed
+05/03/2018 08:05:47 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:05:47 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:05:47 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:05:47 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:05:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:05:47 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:05:47 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:05:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:05:47 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:05:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:05:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:05:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:05:47 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:05:47 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:05:47 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:05:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:05:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:05:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:05:47 PM - INFO - Train model
+05/03/2018 08:05:47 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:05:47 PM - INFO - KeyError
+05/03/2018 08:05:47 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:05:47 PM - INFO - Compile model
+05/03/2018 08:05:47 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:05:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:06:45 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:06:57 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:07:02 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:07:02 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:07:04 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:07:04 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:07:04 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:07:04 PM - INFO - Creating new RobustScaler
+05/03/2018 08:07:04 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:07:04 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:07:04 PM - INFO - Training and test data transformed
+05/03/2018 08:07:04 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:07:04 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:07:04 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:07:04 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:07:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:04 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:07:04 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:07:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:04 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:07:04 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:04 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:04 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:04 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:07:04 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:07:04 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:07:04 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:04 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:04 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:04 PM - INFO - Train model
+05/03/2018 08:07:04 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:07:04 PM - INFO - KeyError
+05/03/2018 08:07:04 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:07:04 PM - INFO - Compile model
+05/03/2018 08:07:04 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:07:04 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:14 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:07:18 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:07:19 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:07:19 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:07:21 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:07:21 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:07:21 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:07:21 PM - INFO - Creating new RobustScaler
+05/03/2018 08:07:21 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:07:21 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:07:21 PM - INFO - Training and test data transformed
+05/03/2018 08:07:21 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:07:21 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:07:21 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:07:21 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:07:21 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:21 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:07:21 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:07:21 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:21 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:07:21 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:21 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:21 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:21 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:07:21 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:07:21 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:07:21 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:21 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:21 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:21 PM - INFO - Train model
+05/03/2018 08:07:21 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:07:21 PM - INFO - KeyError
+05/03/2018 08:07:21 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:07:21 PM - INFO - Compile model
+05/03/2018 08:07:21 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:07:21 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:29 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:07:33 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:07:35 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:07:35 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:07:36 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:07:36 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:07:36 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:07:36 PM - INFO - Creating new RobustScaler
+05/03/2018 08:07:36 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:07:36 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:07:36 PM - INFO - Training and test data transformed
+05/03/2018 08:07:36 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:07:36 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:07:36 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:07:36 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:07:36 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:36 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:07:36 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:07:36 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:36 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:07:36 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:36 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:36 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:37 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:07:37 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:07:37 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:07:37 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:37 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:37 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:37 PM - INFO - Train model
+05/03/2018 08:07:37 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:07:37 PM - INFO - KeyError
+05/03/2018 08:07:37 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:07:37 PM - INFO - Compile model
+05/03/2018 08:07:37 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:07:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:46 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:07:50 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:07:51 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:07:51 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:07:53 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:07:53 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:07:53 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:07:53 PM - INFO - Creating new RobustScaler
+05/03/2018 08:07:53 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:07:53 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:07:53 PM - INFO - Training and test data transformed
+05/03/2018 08:07:53 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:07:53 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:07:53 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:07:53 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:07:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:53 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:07:53 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:07:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:07:53 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:07:53 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:53 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:53 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:53 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:07:53 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:07:53 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:07:53 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:07:53 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:07:53 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:07:53 PM - INFO - Train model
+05/03/2018 08:07:53 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:07:53 PM - INFO - KeyError
+05/03/2018 08:07:53 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:07:53 PM - INFO - Compile model
+05/03/2018 08:07:53 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:07:53 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:04 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:08:08 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:08:09 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:08:09 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:08:11 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:08:11 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:08:11 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:08:11 PM - INFO - Creating new RobustScaler
+05/03/2018 08:08:11 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:08:11 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:08:11 PM - INFO - Training and test data transformed
+05/03/2018 08:08:11 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:08:11 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:08:11 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:08:11 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:08:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:11 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:08:11 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:08:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:11 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:08:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:11 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:08:11 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:08:11 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:08:11 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:11 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:11 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:11 PM - INFO - Train model
+05/03/2018 08:08:11 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:08:11 PM - INFO - KeyError
+05/03/2018 08:08:11 PM - INFO - Using adamax(**{}) as Optimizer
+05/03/2018 08:08:11 PM - INFO - Compile model
+05/03/2018 08:08:11 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:08:11 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:22 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:08:26 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:08:28 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:08:28 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:08:29 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:08:29 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:08:29 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:08:29 PM - INFO - Creating new RobustScaler
+05/03/2018 08:08:29 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:08:29 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:08:29 PM - INFO - Training and test data transformed
+05/03/2018 08:08:29 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:08:29 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:08:29 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:08:29 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:08:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:29 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:08:29 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:08:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:29 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:08:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:29 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:08:29 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:08:29 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:08:29 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:29 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:29 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:29 PM - INFO - Train model
+05/03/2018 08:08:29 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:08:29 PM - INFO - KeyError
+05/03/2018 08:08:29 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:08:29 PM - INFO - Compile model
+05/03/2018 08:08:29 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:08:29 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:40 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:08:44 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:08:46 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:08:46 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:08:47 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:08:47 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:08:47 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:08:47 PM - INFO - Creating new RobustScaler
+05/03/2018 08:08:47 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:08:47 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:08:47 PM - INFO - Training and test data transformed
+05/03/2018 08:08:47 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:08:47 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:08:47 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:08:47 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:08:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:47 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:08:47 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:08:47 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:47 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:08:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:47 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:08:47 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:08:47 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:08:47 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:08:47 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:08:47 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:08:48 PM - INFO - Train model
+05/03/2018 08:08:48 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:08:48 PM - INFO - KeyError
+05/03/2018 08:08:48 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:08:48 PM - INFO - Compile model
+05/03/2018 08:08:48 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:08:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:08:58 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:09:02 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:09:04 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:09:04 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:09:05 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:09:05 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:09:05 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:09:05 PM - INFO - Creating new RobustScaler
+05/03/2018 08:09:05 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:09:05 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:09:05 PM - INFO - Training and test data transformed
+05/03/2018 08:09:05 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:09:05 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:09:05 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:09:05 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:09:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:05 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:09:05 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:09:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:05 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:09:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:05 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:09:05 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:09:05 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:09:05 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:05 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:05 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:05 PM - INFO - Train model
+05/03/2018 08:09:05 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:09:05 PM - INFO - KeyError
+05/03/2018 08:09:05 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:09:05 PM - INFO - Compile model
+05/03/2018 08:09:05 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:09:05 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:14 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:09:18 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:09:20 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:09:20 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:09:21 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:09:21 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:09:21 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:09:21 PM - INFO - Creating new RobustScaler
+05/03/2018 08:09:21 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:09:22 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:09:22 PM - INFO - Training and test data transformed
+05/03/2018 08:09:22 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:09:22 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:09:22 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:09:22 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:09:22 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:22 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:09:22 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:09:22 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:22 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:09:22 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:22 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:22 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:22 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:09:22 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:09:22 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:09:22 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:22 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:22 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:22 PM - INFO - Train model
+05/03/2018 08:09:22 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:09:22 PM - INFO - KeyError
+05/03/2018 08:09:22 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:09:22 PM - INFO - Compile model
+05/03/2018 08:09:22 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:09:22 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:30 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:09:34 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:09:36 PM - INFO - Generation average: 96.99%
+05/03/2018 08:09:36 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 08:09:36 PM - INFO - ***Doing generation 10 of 10***
+05/03/2018 08:09:36 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:09:36 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:09:37 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:09:37 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:09:37 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:09:37 PM - INFO - Creating new RobustScaler
+05/03/2018 08:09:37 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:09:37 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:09:37 PM - INFO - Training and test data transformed
+05/03/2018 08:09:37 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:09:37 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:09:37 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:09:37 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:09:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:37 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:09:37 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:09:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:09:37 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:09:37 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:37 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:37 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:37 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:09:37 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:09:37 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:09:37 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:09:37 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:09:37 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:09:37 PM - INFO - Train model
+05/03/2018 08:09:38 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:09:38 PM - INFO - KeyError
+05/03/2018 08:09:38 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:09:38 PM - INFO - Compile model
+05/03/2018 08:09:38 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:09:38 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:14 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:10:21 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:10:24 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:10:24 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:10:25 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:10:25 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:10:25 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:10:25 PM - INFO - Creating new RobustScaler
+05/03/2018 08:10:25 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:10:25 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:10:25 PM - INFO - Training and test data transformed
+05/03/2018 08:10:25 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:10:25 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:10:25 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:10:25 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:10:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:26 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:10:26 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:10:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:26 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:10:26 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:26 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:26 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:26 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:10:26 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:10:26 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:10:26 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:26 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:26 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:26 PM - INFO - Train model
+05/03/2018 08:10:26 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:10:26 PM - INFO - KeyError
+05/03/2018 08:10:26 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:10:26 PM - INFO - Compile model
+05/03/2018 08:10:26 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:10:26 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:35 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:10:39 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:10:41 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:10:41 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:10:42 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:10:42 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:10:42 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:10:42 PM - INFO - Creating new RobustScaler
+05/03/2018 08:10:42 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:10:42 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:10:42 PM - INFO - Training and test data transformed
+05/03/2018 08:10:42 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:10:42 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:10:42 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:10:42 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:10:42 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:42 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:10:42 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:10:42 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:42 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:10:42 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:42 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:42 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:42 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:10:42 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:10:42 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:10:42 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:42 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:42 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:42 PM - INFO - Train model
+05/03/2018 08:10:43 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:10:43 PM - INFO - KeyError
+05/03/2018 08:10:43 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:10:43 PM - INFO - Compile model
+05/03/2018 08:10:43 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:10:43 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:51 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:10:55 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:10:57 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:10:57 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:10:58 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:10:58 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:10:58 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:10:58 PM - INFO - Creating new RobustScaler
+05/03/2018 08:10:58 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:10:58 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:10:58 PM - INFO - Training and test data transformed
+05/03/2018 08:10:58 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:10:58 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:10:58 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:10:58 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:10:58 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:58 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:10:59 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:10:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:10:59 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:10:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:59 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:10:59 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:10:59 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:10:59 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:10:59 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:10:59 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:10:59 PM - INFO - Train model
+05/03/2018 08:10:59 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:10:59 PM - INFO - KeyError
+05/03/2018 08:10:59 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:10:59 PM - INFO - Compile model
+05/03/2018 08:10:59 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:10:59 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:06 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:11:10 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:11:12 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:11:12 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:11:13 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:11:13 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:11:13 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:11:13 PM - INFO - Creating new RobustScaler
+05/03/2018 08:11:13 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:11:13 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:11:13 PM - INFO - Training and test data transformed
+05/03/2018 08:11:13 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:11:13 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:11:13 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:11:13 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:11:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:13 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:11:13 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:11:13 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:13 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:11:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:13 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:11:13 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:11:13 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:11:13 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:13 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:13 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:14 PM - INFO - Train model
+05/03/2018 08:11:14 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:11:14 PM - INFO - KeyError
+05/03/2018 08:11:14 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:11:14 PM - INFO - Compile model
+05/03/2018 08:11:14 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:11:14 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:27 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:11:32 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:11:35 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:11:35 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:11:36 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:11:36 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:11:36 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:11:36 PM - INFO - Creating new RobustScaler
+05/03/2018 08:11:36 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:11:36 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:11:36 PM - INFO - Training and test data transformed
+05/03/2018 08:11:36 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:11:36 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:11:36 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:11:36 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:11:36 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:36 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:11:36 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:11:36 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:36 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:11:36 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:36 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:36 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:36 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:11:36 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:11:36 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:11:36 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:36 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:36 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:36 PM - INFO - Train model
+05/03/2018 08:11:36 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:11:36 PM - INFO - KeyError
+05/03/2018 08:11:36 PM - INFO - Using rmsprop(**{}) as Optimizer
+05/03/2018 08:11:36 PM - INFO - Compile model
+05/03/2018 08:11:37 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:11:37 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:49 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:11:53 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:11:55 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:11:55 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:11:56 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:11:56 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:11:56 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:11:56 PM - INFO - Creating new RobustScaler
+05/03/2018 08:11:56 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:11:56 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:11:56 PM - INFO - Training and test data transformed
+05/03/2018 08:11:56 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:11:56 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:11:56 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:11:56 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:11:56 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:56 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:11:56 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:11:56 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:11:56 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:11:56 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:57 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:57 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:57 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:11:57 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:11:57 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:11:57 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:11:57 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:11:57 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:11:57 PM - INFO - Train model
+05/03/2018 08:11:57 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:11:57 PM - INFO - KeyError
+05/03/2018 08:11:57 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:11:57 PM - INFO - Compile model
+05/03/2018 08:11:57 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:11:57 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:07 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:12:12 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:12:13 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:12:13 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:12:15 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:12:15 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:12:15 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:12:15 PM - INFO - Creating new RobustScaler
+05/03/2018 08:12:15 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:12:15 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:12:15 PM - INFO - Training and test data transformed
+05/03/2018 08:12:15 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:12:15 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:12:15 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:12:15 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:12:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:15 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:12:15 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:12:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:15 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:12:15 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:15 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:15 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:15 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:12:15 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:12:15 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:12:15 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:15 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:15 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:15 PM - INFO - Train model
+05/03/2018 08:12:15 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:12:15 PM - INFO - KeyError
+05/03/2018 08:12:15 PM - INFO - Using nadam(**{}) as Optimizer
+05/03/2018 08:12:15 PM - INFO - Compile model
+05/03/2018 08:12:15 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:12:15 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:27 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:12:31 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:12:33 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:12:33 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:12:34 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:12:34 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:12:34 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:12:34 PM - INFO - Creating new RobustScaler
+05/03/2018 08:12:34 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:12:34 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:12:34 PM - INFO - Training and test data transformed
+05/03/2018 08:12:34 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:12:34 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:12:34 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:12:34 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:12:34 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:34 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:12:34 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:12:34 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:34 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:12:34 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:34 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:34 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:34 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:12:34 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:12:34 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:12:34 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:34 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:34 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:34 PM - INFO - Train model
+05/03/2018 08:12:34 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:12:34 PM - INFO - KeyError
+05/03/2018 08:12:34 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:12:34 PM - INFO - Compile model
+05/03/2018 08:12:34 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:12:34 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:40 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:12:45 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:12:47 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:12:47 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:12:48 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:12:48 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:12:48 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:12:48 PM - INFO - Creating new RobustScaler
+05/03/2018 08:12:48 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:12:48 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:12:48 PM - INFO - Training and test data transformed
+05/03/2018 08:12:48 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:12:48 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:12:48 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:12:48 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:12:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:48 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:12:48 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:12:48 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:48 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:12:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:48 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:12:48 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:12:48 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:12:48 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:12:48 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:12:48 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:12:49 PM - INFO - Train model
+05/03/2018 08:12:49 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:12:49 PM - INFO - KeyError
+05/03/2018 08:12:49 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:12:49 PM - INFO - Compile model
+05/03/2018 08:12:49 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:12:49 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:12:58 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:13:02 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:13:04 PM - INFO - Trying to load x_train from ./outputs/x_train.h5
+05/03/2018 08:13:04 PM - INFO - Couldn't load all datasets - reading from ROOT trees
+05/03/2018 08:13:05 PM - DEBUG - training data before transformation: [[950.8178   310.67346 ]
+ [689.7896   164.79187 ]
+ [605.84894   76.77965 ]
+ ...
+ [221.43806   57.68829 ]
+ [478.28116   27.593285]
+ [759.3491    47.761116]]
+05/03/2018 08:13:05 PM - DEBUG - minimum values: [200.00388, 0.00040848268]
+05/03/2018 08:13:05 PM - DEBUG - maximum values: [2972.1663, 6567.212]
+05/03/2018 08:13:05 PM - INFO - Creating new RobustScaler
+05/03/2018 08:13:05 PM - INFO - Fitting RobustScaler to training data
+05/03/2018 08:13:05 PM - DEBUG - training data after transformation: [[ 4.678216    5.0818543 ]
+ [ 2.8512027   2.122609  ]
+ [ 2.2636774   0.3372586 ]
+ ...
+ [-0.42692736 -0.05001445]
+ [ 1.370793   -0.6604993 ]
+ [ 3.3380704  -0.25138968]]
+05/03/2018 08:13:05 PM - INFO - Training and test data transformed
+05/03/2018 08:13:05 PM - DEBUG - Plotting bkg (min=-0.576951563358, max=18.8262271881) from [-0.36245644 -0.571032   -0.5530677  ... -0.42692736  1.370793
+  3.3380704 ]
+05/03/2018 08:13:05 PM - DEBUG - Plotting sig (min=-0.576769471169, max=8.76014995575) from [ 4.678216    2.8512027   2.2636774  ... -0.28397465  0.3377439
+  7.3467083 ]
+05/03/2018 08:13:05 PM - DEBUG - Calculated range based on percentiles: (-0.5013251566886902, 6.450924358367917)
+05/03/2018 08:13:05 PM - DEBUG - Calculating background weights for plotting
+05/03/2018 08:13:06 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:13:06 PM - DEBUG - Background weights: [4.59655514e-06 4.59655514e-06 4.59655514e-06 ... 1.48291876e-07
+ 1.48291876e-07 1.51569264e-07]
+05/03/2018 08:13:06 PM - DEBUG - Calculating signal weights for plotting
+05/03/2018 08:13:06 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:13:06 PM - DEBUG - Signal weights: [2.18542941e-05 2.18542941e-05 2.18542941e-05 ... 2.18542941e-05
+ 2.18542941e-05 2.37158099e-05]
+05/03/2018 08:13:06 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:13:06 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:13:06 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:13:06 PM - DEBUG - Plotting bkg (min=-1.22022783756, max=131.997329712) from [-0.26027325 -0.4640601  -0.76443064 ... -0.05001445 -0.6604993
+ -0.25138968]
+05/03/2018 08:13:06 PM - DEBUG - Plotting sig (min=-1.21512341499, max=33.6264152527) from [ 5.0818543  2.122609   0.3372586 ...  7.0550213  7.685349  20.405071 ]
+05/03/2018 08:13:06 PM - DEBUG - Calculated range based on percentiles: (-1.0662700653076171, 25.562595825195302)
+05/03/2018 08:13:06 PM - DEBUG - Assigning font /F1 = u'/home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf'
+05/03/2018 08:13:06 PM - DEBUG - Embedding font /home/t/Thomas.Weber/.miniconda2/envs/ml_env/lib/python2.7/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf.
+05/03/2018 08:13:06 PM - DEBUG - Writing TrueType font.
+05/03/2018 08:13:06 PM - INFO - Train model
+05/03/2018 08:13:06 PM - INFO - Trying to load pred_test from ./outputs/pred_test.h5
+05/03/2018 08:13:06 PM - INFO - KeyError
+05/03/2018 08:13:06 PM - INFO - Using adagrad(**{}) as Optimizer
+05/03/2018 08:13:06 PM - INFO - Compile model
+05/03/2018 08:13:06 PM - INFO - No weights found, starting completely new model
+05/03/2018 08:13:06 PM - DEBUG - Calculated class_weight: [0.5026114128283947, 96.2336187069562]
+05/03/2018 08:13:15 PM - INFO - Create/Update predictions for ROC curve
+05/03/2018 08:13:19 PM - INFO - Get test loss and metrics of the model
+05/03/2018 08:13:21 PM - INFO - Generation average: 96.98%
+05/03/2018 08:13:21 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 08:13:21 PM - INFO - --------------------------------------------------------------------------------
+05/03/2018 08:13:21 PM - INFO - {'nb_layers': 4, 'activation': 'elu', 'optimizer': 'rmsprop', 'nb_neurons': 64}
+05/03/2018 08:13:21 PM - INFO - Network accuracy: 97.29%
+05/03/2018 08:13:21 PM - INFO - {'nb_layers': 4, 'activation': 'elu', 'optimizer': 'nadam', 'nb_neurons': 64}
+05/03/2018 08:13:21 PM - INFO - Network accuracy: 97.28%
+05/03/2018 08:13:21 PM - INFO - {'nb_layers': 2, 'activation': 'elu', 'optimizer': 'nadam', 'nb_neurons': 64}
+05/03/2018 08:13:21 PM - INFO - Network accuracy: 97.27%
+05/03/2018 08:13:21 PM - INFO - {'nb_layers': 2, 'activation': 'elu', 'optimizer': 'nadam', 'nb_neurons': 64}
+05/03/2018 08:13:21 PM - INFO - Network accuracy: 97.27%
+05/03/2018 08:13:21 PM - INFO - {'nb_layers': 2, 'activation': 'elu', 'optimizer': 'adagrad', 'nb_neurons': 64}
+05/03/2018 08:13:21 PM - INFO - Network accuracy: 97.25%
diff --git a/Genetic_Algorithm/main.py b/Genetic_Algorithm/main.py
new file mode 100755
index 0000000000000000000000000000000000000000..074a7c1b28a6a4a2c62f0d3a2f79d6937aae040e
--- /dev/null
+++ b/Genetic_Algorithm/main.py
@@ -0,0 +1,111 @@
+#!/usr/bin/env python
+
+import logging
+from optimizer import Optimizer
+from tqdm import tqdm
+
+# Setup logging.
+logging.basicConfig(
+    format='%(asctime)s - %(levelname)s - %(message)s',
+    datefmt='%m/%d/%Y %I:%M:%S %p',
+    level=logging.DEBUG,
+    filename='log.txt'
+)
+
+def train_networks(networks):
+    """Train each network.
+
+    Args:
+        networks (list): Current population of networks
+    """
+    pbar = tqdm(total=len(networks))
+    for network in networks:
+        network.train()
+        pbar.update(1)
+    pbar.close()
+
+def get_average_accuracy(networks):
+    """Get the average accuracy for a group of networks.
+
+    Args:
+        networks (list): List of networks
+
+    Returns:
+        float: The average accuracy of a population of networks.
+
+    """
+    total_accuracy = 0
+    for network in networks:
+        total_accuracy += network.accuracy
+
+    return total_accuracy / len(networks)
+
+def generate(generations, population, nn_param_choices):
+    """Generate a network with the genetic algorithm.
+
+    Args:
+        generations (int): Number of times to evole the population
+        population (int): Number of networks in each generation
+        nn_param_choices (dict): Parameter choices for networks
+
+    """
+    optimizer = Optimizer(nn_param_choices)
+    networks = optimizer.create_population(population)
+
+    # Evolve the generation.
+    for i in range(generations):
+        logging.info("***Doing generation %d of %d***" %
+                     (i + 1, generations))
+
+        # Train and get accuracy for networks.
+        train_networks(networks)
+
+        # Get the average accuracy for this generation.
+        average_accuracy = get_average_accuracy(networks)
+
+        # Print out the average accuracy each generation.
+        logging.info("Generation average: %.2f%%" % (average_accuracy * 100))
+        logging.info('-'*80)
+
+        # Evolve, except on the last iteration.
+        if i != generations - 1:
+            # Do the evolution.
+            networks = optimizer.evolve(networks)
+
+    # Sort our final population.
+    networks = sorted(networks, key=lambda x: x.accuracy, reverse=True)
+
+    # Print out the top 5 networks.
+    print_networks(networks[:5])
+
+def print_networks(networks):
+    """Print a list of networks.
+
+    Args:
+        networks (list): The population of networks
+
+    """
+    logging.info('-'*80)
+    for network in networks:
+        network.print_network()
+
+def main():
+    """Evolve a network."""
+    generations = 10  # Number of times to evole the population.
+    population = 20  # Number of networks in each generation.
+
+    nn_param_choices = {
+        'nb_neurons': [64, 128, 256, 512, 768, 1024],
+        'nb_layers': [1, 2, 3, 4],
+        'activation': ['relu', 'elu', 'tanh', 'sigmoid'],
+        'optimizer': ['rmsprop', 'adam', 'sgd', 'adagrad',
+                      'adadelta', 'adamax', 'nadam'],
+    }
+
+    logging.info("***Evolving %d generations with population %d***" %
+                 (generations, population))
+
+    generate(generations, population, nn_param_choices)
+
+if __name__ == '__main__':
+    main()
diff --git a/Genetic_Algorithm/network.py b/Genetic_Algorithm/network.py
new file mode 100755
index 0000000000000000000000000000000000000000..03f90d8d695feb35ba1092687919b64ea3036677
--- /dev/null
+++ b/Genetic_Algorithm/network.py
@@ -0,0 +1,54 @@
+#!/usr/bin/env python
+
+"""Class that represents the network to be evolved."""
+import random
+import logging
+from train import train_and_score
+
+class Network(object):
+    """Represent a network and let us operate on it.
+
+    Currently only works for an MLP.
+    """
+
+    def __init__(self, nn_param_choices=None):
+        """Initialize our network.
+
+        Args:
+            nn_param_choices (dict): Parameters for the network, includes:
+                nb_neurons (list): [64, 128, 256]
+                nb_layers (list): [1, 2, 3, 4]
+                activation (list): ['relu', 'elu']
+                optimizer (list): ['rmsprop', 'adam']
+        """
+        self.accuracy = 0.
+        self.nn_param_choices = nn_param_choices
+        self.network = {}  # (dic): represents MLP network parameters
+
+    def create_random(self):
+        """Create a random network."""
+        for key in self.nn_param_choices:
+            self.network[key] = random.choice(self.nn_param_choices[key])
+
+    def create_set(self, network):
+        """Set network properties.
+
+        Args:
+            network (dict): The network parameters
+
+        """
+        self.network = network
+
+    def train(self):
+        """Train the network and record the accuracy.
+
+        Args:
+
+        """
+        if self.accuracy == 0.:
+            self.accuracy = train_and_score(self.network)
+
+    def print_network(self):
+        """Print out a network."""
+        logging.info(self.network)
+        logging.info("Network accuracy: %.2f%%" % (self.accuracy * 100))
diff --git a/Genetic_Algorithm/optimizer.py b/Genetic_Algorithm/optimizer.py
new file mode 100755
index 0000000000000000000000000000000000000000..5e43338141d45459d0d1dad1bb76f614b508b40e
--- /dev/null
+++ b/Genetic_Algorithm/optimizer.py
@@ -0,0 +1,184 @@
+#!/usr/bin/env python
+
+"""
+Class that holds a genetic algorithm for evolving a network.
+
+Credit:
+    A lot of those code was originally inspired by:
+    http://lethain.com/genetic-algorithms-cool-name-damn-simple/
+"""
+from functools import reduce
+from operator import add
+import random
+from network import Network
+
+class Optimizer(object):
+    """Class that implements genetic algorithm for MLP optimization."""
+
+    def __init__(self, nn_param_choices, retain=0.4,
+                 random_select=0.1, mutate_chance=0.2):
+        """Create an optimizer.
+
+        Args:
+            nn_param_choices (dict): Possible network paremters
+            retain (float): Percentage of population to retain after
+                each generation
+            random_select (float): Probability of a rejected network
+                remaining in the population
+            mutate_chance (float): Probability a network will be
+                randomly mutated
+
+        """
+        self.mutate_chance = mutate_chance
+        self.random_select = random_select
+        self.retain = retain
+        self.nn_param_choices = nn_param_choices
+
+    def create_population(self, count):
+        """Create a population of random networks.
+
+        Args:
+            count (int): Number of networks to generate, aka the
+                size of the population
+
+        Returns:
+            (list): Population of network objects
+
+        """
+        pop = []
+        for _ in range(0, count):
+            # Create a random network.
+            network = Network(self.nn_param_choices)
+            network.create_random()
+
+            # Add the network to our population.
+            pop.append(network)
+
+        return pop
+
+    @staticmethod
+    def fitness(network):
+        """Return the accuracy, which is our fitness function."""
+        return network.accuracy
+
+    def grade(self, pop):
+        """Find average fitness for a population.
+
+        Args:
+            pop (list): The population of networks
+
+        Returns:
+            (float): The average accuracy of the population
+
+        """
+        summed = reduce(add, (self.fitness(network) for network in pop))
+        return summed / float((len(pop)))
+
+    def breed(self, mother, father):
+        """Make two children as parts of their parents.
+
+        Args:
+            mother (dict): Network parameters
+            father (dict): Network parameters
+
+        Returns:
+            (list): Two network objects
+
+        """
+        children = []
+        for _ in range(2):
+
+            child = {}
+
+            # Loop through the parameters and pick params for the kid.
+            for param in self.nn_param_choices:
+                child[param] = random.choice(
+                    [mother.network[param], father.network[param]]
+                )
+
+            # Now create a network object.
+            network = Network(self.nn_param_choices)
+            network.create_set(child)
+
+            # Randomly mutate some of the children.
+            if self.mutate_chance > random.random():
+                network = self.mutate(network)
+
+            children.append(network)
+
+        return children
+
+    def mutate(self, network):
+        """Randomly mutate one part of the network.
+
+        Args:
+            network (dict): The network parameters to mutate
+
+        Returns:
+            (Network): A randomly mutated network object
+
+        """
+        # Choose a random key.
+        mutation = random.choice(list(self.nn_param_choices.keys()))
+
+        # Mutate one of the params.
+        network.network[mutation] = random.choice(self.nn_param_choices[mutation])
+
+        return network
+
+    def evolve(self, pop):
+        """Evolve a population of networks.
+
+        Args:
+            pop (list): A list of network parameters
+
+        Returns:
+            (list): The evolved population of networks
+
+        """
+        # Get scores for each network.
+        graded = [(self.fitness(network), network) for network in pop]
+
+        # Sort on the scores.
+        graded = [x[1] for x in sorted(graded, key=lambda x: x[0], reverse=True)]
+
+        # Get the number we want to keep for the next gen.
+        retain_length = int(len(graded)*self.retain)
+
+        # The parents are every network we want to keep.
+        parents = graded[:retain_length]
+
+        # For those we aren't keeping, randomly keep some anyway.
+        for individual in graded[retain_length:]:
+            if self.random_select > random.random():
+                parents.append(individual)
+
+        # Now find out how many spots we have left to fill.
+        parents_length = len(parents)
+        desired_length = len(pop) - parents_length
+        children = []
+
+        # Add children, which are bred from two remaining networks.
+        while len(children) < desired_length:
+
+            # Get a random mom and dad.
+            male = random.randint(0, parents_length-1)
+            female = random.randint(0, parents_length-1)
+
+            # Assuming they aren't the same network...
+            if male != female:
+                male = parents[male]
+                female = parents[female]
+
+                # Breed them.
+                babies = self.breed(male, female)
+
+                # Add the children one at a time.
+                for baby in babies:
+                    # Don't grow larger than desired length.
+                    if len(children) < desired_length:
+                        children.append(baby)
+
+        parents.extend(children)
+
+        return parents
diff --git a/Genetic_Algorithm/train.py b/Genetic_Algorithm/train.py
new file mode 100755
index 0000000000000000000000000000000000000000..4faac3482b302a77ebf17ba23eeb3f1a694d218f
--- /dev/null
+++ b/Genetic_Algorithm/train.py
@@ -0,0 +1,47 @@
+#!/usr/bin/env python
+
+import os,sys,inspect
+currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
+parentdir = os.path.dirname(currentdir)
+sys.path.insert(0,parentdir) 
+import toolkit
+from toolkit import KerasROOTClassification
+
+def init_model(network):
+    
+    nb_layers = network['nb_layers']
+    nb_neurons = network['nb_neurons']
+    activation = network['activation']
+    optimizer = network['optimizer']
+
+    filename = "/project/etp4/nhartmann/trees/allTrees_m1.8_NoSys.root"
+    
+    c = KerasROOTClassification("",
+                                signal_trees = [(filename, "GG_oneStep_1705_1105_505_NoSys")],
+                                bkg_trees = [(filename, "ttbar_NoSys"),
+                                             (filename, "wjets_Sherpa221_NoSys")
+                                ],
+                                dumping_enabled=False,
+                                optimizer=optimizer,
+                                layers=nb_layers,
+                                nodes=nb_neurons,
+                                activation_function=activation,
+                                #optimizer_opts=dict(lr=100., decay=1e-6, momentum=0.9),
+                                earlystopping_opts=dict(monitor='val_loss',
+                                    min_delta=0, patience=2, verbose=0, mode='auto'),
+                                # optimizer="Adam",
+                                selection="lep1Pt<5000", # cut out a few very weird outliers
+                                branches = ["met", "mt"],
+                                weight_expr = "eventWeight*genWeight",
+                                identifiers = ["DatasetNumber", "EventNumber"],
+                                step_bkg = 100)
+    return c
+
+def train_and_score(network):
+    model = init_model(network)
+
+    model.train()
+
+    score = model.score
+
+    return score[1]  # 1 is accuracy. 0 is loss.
diff --git a/toolkit.py b/toolkit.py
index 25231056fb769f6253fe6c825eac65e85451aaf9..286e3cf74adb3f1948511250ee1c07b2ac62492d 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -44,19 +44,21 @@ class KerasROOTClassification(object):
 
 
     # Datasets that are stored to (and dynamically loaded from) hdf5
-    dataset_names = ["x_train", "x_test", "y_train", "y_test", "w_train", "w_test", "scores_train", "scores_test"]
+    dataset_names = ["x_train", "x_test", "y_train", "y_test", "w_train", "w_test", "pred_train", "pred_test"]
 
     # Datasets that are retrieved from ROOT trees the first time
     dataset_names_tree = ["x_train", "x_test", "y_train", "y_test", "w_train", "w_test"]
 
     def __init__(self, name, *args, **kwargs):
         self._init_from_args(name, *args, **kwargs)
-        with open(os.path.join(self.project_dir, "options.json"), "w") as of:
-            json.dump(dict(args=args, kwargs=kwargs), of)
+        if self.dumping_enabled:
+            with open(os.path.join(self.project_dir, "options.json"), "w") as of:
+                json.dump(dict(args=args, kwargs=kwargs), of)
 
 
     def _init_from_args(self, name,
                         signal_trees, bkg_trees, branches, weight_expr, identifiers,
+                        dumping_enabled=True,
                         selection=None,
                         layers=3,
                         nodes=64,
@@ -72,6 +74,7 @@ class KerasROOTClassification(object):
                         earlystopping_opts=None):
 
         self.name = name
+        self.dumping_enabled = dumping_enabled
         self.signal_trees = signal_trees
         self.bkg_trees = bkg_trees
         self.branches = branches
@@ -114,8 +117,9 @@ class KerasROOTClassification(object):
         self._y_test = None
         self._w_train = None
         self._w_test = None
-        self._scores_train = None
-        self._scores_test = None
+        self.pred_train = None
+        self.pred_test = None
+        self.score = None
 
         self.s_eventlist_train = None
         self.b_eventlist_train = None
@@ -169,8 +173,8 @@ class KerasROOTClassification(object):
                                      branches=self.branches+[self.weight_expr],
                                      selection=self.selection,
                                      start=1, step=self.step_bkg)
-
-            self._dump_training_list()
+            if self.dumping_enabled:
+                self._dump_training_list()
             self.s_eventlist_train = self.s_train[self.identifiers]
             self.b_eventlist_train = self.b_train[self.identifiers]
 
@@ -196,7 +200,8 @@ class KerasROOTClassification(object):
             self.y_test[:len(self.s_test)] = 1
             self.y_test[len(self.s_test):] = 0
 
-            self._dump_to_hdf5(*self.dataset_names_tree)
+            if self.dumping_enabled:
+                self._dump_to_hdf5(*self.dataset_names_tree)
 
         self.data_loaded = True
 
@@ -261,7 +266,8 @@ class KerasROOTClassification(object):
                 # probably we either want to fit only training data or training and test data together
                 # logger.info("Fitting StandardScaler to test data")
                 # self._scaler.fit(self.x_test)
-                joblib.dump(self._scaler, filename)
+                if self.dumping_enabled:
+                    joblib.dump(self._scaler, filename)
         return self._scaler
 
 
@@ -354,8 +360,9 @@ class KerasROOTClassification(object):
                 logger.info("No weights found, starting completely new model")
 
             # dump to json for documentation
-            with open(os.path.join(self.project_dir, "model.json"), "w") as of:
-                of.write(self._model.to_json())
+            if self.dumping_enabled:
+                with open(os.path.join(self.project_dir, "model.json"), "w") as of:
+                    of.write(self._model.to_json())
 
         return self._model
 
@@ -386,9 +393,9 @@ class KerasROOTClassification(object):
         np.random.shuffle(self.y_train)
         np.random.set_state(rn_state)
         np.random.shuffle(self.w_train)
-        if self._scores_test is not None:
+        if self.pred_test is not None:
             np.random.set_state(rn_state)
-            np.random.shuffle(self._scores_test)
+            np.random.shuffle(self.pred_test)
 
 
     def train(self, epochs=10):
@@ -418,20 +425,25 @@ class KerasROOTClassification(object):
         except KeyboardInterrupt:
             logger.info("Interrupt training - continue with rest")
 
-        logger.info("Save history")
-        self._dump_history()
+        if self.dumping_enabled:
+            logger.info("Save history")
+            self._dump_history()
+
+            logger.info("Save weights")
+            self.model.save_weights(os.path.join(self.project_dir, "weights.h5"))
 
-        logger.info("Save weights")
-        self.model.save_weights(os.path.join(self.project_dir, "weights.h5"))
+            self.total_epochs += epochs
+            self._write_info("epochs", self.total_epochs)
 
-        self.total_epochs += epochs
-        self._write_info("epochs", self.total_epochs)
+        logger.info("Create/Update predictions for ROC curve")
+        self.pred_test = self.model.predict(self.x_test)
+        self.pred_train = self.model.predict(self.x_train)
 
-        logger.info("Create/Update scores for ROC curve")
-        self.scores_test = self.model.predict(self.x_test)
-        self.scores_train = self.model.predict(self.x_train)
+        logger.info("Get test loss and metrics of the model")
+        self.score = self.model.evaluate(self.x_test, self.y_test, verbose=0, sample_weight=None)
 
-        self._dump_to_hdf5("scores_train", "scores_test")
+        if self.dumping_enabled:
+            self._dump_to_hdf5("pred_train", "pred_test")
 
 
 
@@ -521,7 +533,7 @@ class KerasROOTClassification(object):
     def plot_ROC(self):
 
         logger.info("Plot ROC curve")
-        fpr, tpr, threshold = roc_curve(self.y_test, self.scores_test, sample_weight = self.w_test)
+        fpr, tpr, threshold = roc_curve(self.y_test, self.pred_test, sample_weight = self.w_test)
 
         fpr = 1.0 - fpr
         roc_auc = auc(tpr, fpr)
@@ -571,7 +583,10 @@ class KerasROOTClassification(object):
 def create_getter(dataset_name):
     def getx(self):
         if getattr(self, "_"+dataset_name) is None:
-            self._load_from_hdf5(dataset_name)
+            try:
+                self._load_from_hdf5(dataset_name)
+            except KeyError:
+                logger.info("KeyError")
         return getattr(self, "_"+dataset_name)
     return getx