Merge pull request #199 from ndawe/master

[MRG] reduce number of travis tests
scikit-hep · May 6, 2015 · f05d4c2 · f05d4c2
2 parents 4f858e0 + bd0711e
commit f05d4c2
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Showing 4 changed files with 7 additions and 4 deletions.
diff --git a/.travis.yml b/.travis.yml
@@ -5,7 +5,6 @@ python:
     - "3.4"
 env:
     - ROOT=v5-34-18
-    - ROOT=v5-34-18 NOTMVA=1
     - ROOT=master COVERAGE=1
 install: source ci/install.sh
 script: bash ci/test.sh

diff --git a/examples/tmva/plot_multiclass.py b/examples/tmva/plot_multiclass.py
@@ -44,9 +44,10 @@
 # Call root_numpy's utility functions to add events from the arrays
 add_classification_events(factory, X_train, y_train, weights=w_train)
 add_classification_events(factory, X_test, y_test, weights=w_test, test=True)
+# The following line is necessary if events have been added individually:
+factory.PrepareTrainingAndTestTree(TCut('1'), 'NormMode=EqualNumEvents')
 
 # Train a BDT
-factory.PrepareTrainingAndTestTree(TCut('1'), 'NormMode=EqualNumEvents')
 factory.BookMethod('BDT', 'BDTG',
                    'nCuts=20:NTrees=20:MaxDepth=4:'
                    'BoostType=Grad:Shrinkage=0.10')

diff --git a/examples/tmva/plot_regression.py b/examples/tmva/plot_regression.py
@@ -28,7 +28,9 @@
 
 add_regression_events(factory, X, y)
 add_regression_events(factory, X, y, test=True)
-factory.PrepareTrainingAndTestTree(TCut('1'), 'NormMode=EqualNumEvents')
+# The following line is necessary if events have been added individually:
+factory.PrepareTrainingAndTestTree(TCut('1'), '')
+
 factory.BookMethod('BDT', 'BDT1',
                    'nCuts=20:NTrees=1:MaxDepth=4:BoostType=AdaBoostR2:'
                    'SeparationType=RegressionVariance')

diff --git a/examples/tmva/plot_twoclass.py b/examples/tmva/plot_twoclass.py
@@ -42,9 +42,10 @@
 # Call root_numpy's utility functions to add events from the arrays
 add_classification_events(factory, X_train, y_train, weights=w_train)
 add_classification_events(factory, X_test, y_test, weights=w_test, test=True)
+# The following line is necessary if events have been added individually:
+factory.PrepareTrainingAndTestTree(TCut('1'), 'NormMode=EqualNumEvents')
 
 # Train a classifier
-factory.PrepareTrainingAndTestTree(TCut('1'), 'NormMode=EqualNumEvents')
 factory.BookMethod('Fisher', 'Fisher',
                    'Fisher:VarTransform=None:CreateMVAPdfs:'
                    'PDFInterpolMVAPdf=Spline2:NbinsMVAPdf=50:'