Merge pull request #3803 from besser82/bugfix/examples_python_modular

Fix possible IndexError and/or TypeError in undocumented/python_modular
shogun-toolbox · Apr 30, 2017 · 6d96064 · 6d96064
2 parents df0eb1c + de18ed0
commit 6d96064
Show file tree

Hide file tree

Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/examples/undocumented/python_modular/classifier_larank_modular.py b/examples/undocumented/python_modular/classifier_larank_modular.py
@@ -18,8 +18,8 @@ def classifier_larank_modular (num_vec,num_class,distance,C=0.9,num_threads=1,nu
 	fm_train=array(random.randn(num_class,num_vec))
 	fm_test=array(random.randn(num_class,num_vec))
 	for i in range(len(label_train)):
-		fm_train[label_train[i],i]+=distance
-		fm_test[label_test[i],i]+=distance
+		fm_train[label_train[i],int(i)]+=distance
+		fm_test[label_test[i],int(i)]+=distance
 
 	feats_train=RealFeatures(fm_train)
 	feats_test=RealFeatures(fm_test)

diff --git a/examples/undocumented/python_modular/classifier_multiclassocas_modular.py b/examples/undocumented/python_modular/classifier_multiclassocas_modular.py
@@ -21,8 +21,8 @@ def classifier_multiclassocas_modular (num_vec=10,num_class=3,distance=15,width=
 	fm_train=array(random.randn(num_class,num_vec))
 	fm_test=array(random.randn(num_class,num_vec))
 	for i in range(len(label_train)):
-		fm_train[label_train[i],i]+=distance
-		fm_test[label_test[i],i]+=distance
+		fm_train[label_train[i],int(i)]+=distance
+		fm_test[label_test[i],int(i)]+=distance
 
 	feats_train=RealFeatures(fm_train)
 	feats_test=RealFeatures(fm_test)

diff --git a/examples/undocumented/python_modular/multiclass_c45classifiertree_modular.py b/examples/undocumented/python_modular/multiclass_c45classifiertree_modular.py
@@ -25,8 +25,8 @@ def multiclass_c45classifiertree_modular(train=traindat,test=testdat,labels=labe
 
 	# divide train dataset into training and validation subsets in the ratio 2/3 to 1/3
 	subset=int32(random.permutation(feats_train.get_num_vectors()))
-	vsubset=subset[1:subset.size/3]
-	trsubset=subset[1+subset.size/3:subset.size]
+	vsubset=subset[1:int(subset.size/3)]
+	trsubset=subset[1+int(subset.size/3):subset.size]
 
 	# C4.5 Tree formation using training subset
 	train_labels.add_subset(trsubset)

diff --git a/examples/undocumented/python_modular/stochasticgbmachine_modular.py b/examples/undocumented/python_modular/stochasticgbmachine_modular.py
@@ -31,8 +31,8 @@ def stochasticgbmachine_modular(train=traindat,train_labels=label_traindat,ft=fe
 	s=StochasticGBMachine(cart,loss,500,0.01,0.6)
 
 	# train
-	feats.add_subset(np.int32(p[0:num]))
-	labels.add_subset(np.int32(p[0:num]))
+	feats.add_subset(np.int32(p[0:int(num)]))
+	labels.add_subset(np.int32(p[0:int(num)]))
 	s.set_labels(labels)
 	s.train(feats)
 	feats.remove_subset()