diff --git a/lang/fr/gklearn/kernels/weisfeilerLehmanKernel.py b/lang/fr/gklearn/kernels/weisfeilerLehmanKernel.py
index 222f5c5..469dcd8 100644
--- a/lang/fr/gklearn/kernels/weisfeilerLehmanKernel.py
+++ b/lang/fr/gklearn/kernels/weisfeilerLehmanKernel.py
@@ -32,15 +32,15 @@ def weisfeilerlehmankernel(*args,
 						   n_jobs=None, 
 						   chunksize=None,
 						   verbose=True):
-	"""Calculate Weisfeiler-Lehman kernels between graphs.
+	"""Compute Weisfeiler-Lehman kernels between graphs.
 	
 	Parameters
 	----------
 	Gn : List of NetworkX graph
-		List of graphs between which the kernels are calculated.
+		List of graphs between which the kernels are computed.
 	
 	G1, G2 : NetworkX graphs
-		Two graphs between which the kernel is calculated.		
+		Two graphs between which the kernel is computed.		
 
 	node_label : string
 		Node attribute used as label. The default node label is atom.		
@@ -115,12 +115,12 @@ def weisfeilerlehmankernel(*args,
 
 
 def _wl_kernel_do(Gn, node_label, edge_label, height, parallel, n_jobs, chunksize, verbose):
-	"""Calculate Weisfeiler-Lehman kernels between graphs.
+	"""Compute Weisfeiler-Lehman kernels between graphs.
 
 	Parameters
 	----------
 	Gn : List of NetworkX graph
-		List of graphs between which the kernels are calculated.	   
+		List of graphs between which the kernels are computed.	   
 	node_label : string
 		node attribute used as label.
 	edge_label : string
@@ -146,7 +146,7 @@ def _wl_kernel_do(Gn, node_label, edge_label, height, parallel, n_jobs, chunksiz
 		# number of occurence of each label in G
 		all_num_of_each_label.append(dict(Counter(labels_ori)))
 
-	# calculate subtree kernel with the 0th iteration and add it to the final kernel
+	# Compute subtree kernel with the 0th iteration and add it to the final kernel
 	compute_kernel_matrix(Kmatrix, all_num_of_each_label, Gn, parallel, n_jobs, chunksize, False)
 
 	# iterate each height
@@ -255,7 +255,7 @@ def _wl_kernel_do(Gn, node_label, edge_label, height, parallel, n_jobs, chunksiz
 #			all_labels_ori.update(labels_comp)
 			all_num_of_each_label.append(dict(Counter(labels_comp)))
 
-		# calculate subtree kernel with h iterations and add it to the final kernel
+		# Compute subtree kernel with h iterations and add it to the final kernel
 		compute_kernel_matrix(Kmatrix, all_num_of_each_label, Gn, parallel, n_jobs, chunksize, False)
 
 	return Kmatrix
@@ -316,7 +316,7 @@ def compute_kernel_matrix(Kmatrix, all_num_of_each_label, Gn, parallel, n_jobs,
 		do_partial = partial(wrapper_compute_subtree_kernel, Kmatrix)
 		parallel_gm(do_partial, Kmatrix, Gn, init_worker=init_worker, 
 					glbv=(all_num_of_each_label,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose)
-	elif parallel == None:
+	elif parallel is None:
 		for i in range(len(Kmatrix)):
 			for j in range(i, len(Kmatrix)):
 				Kmatrix[i][j] = compute_subtree_kernel(all_num_of_each_label[i],
@@ -345,12 +345,12 @@ def wrapper_compute_subtree_kernel(Kmatrix, itr):
 				
 
 def _wl_spkernel_do(Gn, node_label, edge_label, height):
-	"""Calculate Weisfeiler-Lehman shortest path kernels between graphs.
+	"""Compute Weisfeiler-Lehman shortest path kernels between graphs.
 	
 	Parameters
 	----------
 	Gn : List of NetworkX graph
-		List of graphs between which the kernels are calculated.	   
+		List of graphs between which the kernels are computed.	   
 	node_label : string
 		node attribute used as label.	  
 	edge_label : string
@@ -413,7 +413,7 @@ def _wl_spkernel_do(Gn, node_label, edge_label, height):
 			for node in G.nodes(data = True):
 				node[1][node_label] = set_compressed[set_multisets[node[0]]]
 				
-		# calculate subtree kernel with h iterations and add it to the final kernel
+		# Compute subtree kernel with h iterations and add it to the final kernel
 		for i in range(0, len(Gn)):
 			for j in range(i, len(Gn)):
 				for e1 in Gn[i].edges(data = True):
@@ -427,12 +427,12 @@ def _wl_spkernel_do(Gn, node_label, edge_label, height):
 
 
 def _wl_edgekernel_do(Gn, node_label, edge_label, height):
-	"""Calculate Weisfeiler-Lehman edge kernels between graphs.
+	"""Compute Weisfeiler-Lehman edge kernels between graphs.
 	
 	Parameters
 	----------
 	Gn : List of NetworkX graph
-		List of graphs between which the kernels are calculated.	   
+		List of graphs between which the kernels are computed.	   
 	node_label : string
 		node attribute used as label.	  
 	edge_label : string
@@ -491,7 +491,7 @@ def _wl_edgekernel_do(Gn, node_label, edge_label, height):
 			for node in G.nodes(data = True):
 				node[1][node_label] = set_compressed[set_multisets[node[0]]]
 				
-		# calculate subtree kernel with h iterations and add it to the final kernel
+		# Compute subtree kernel with h iterations and add it to the final kernel
 		for i in range(0, len(Gn)):
 			for j in range(i, len(Gn)):
 				for e1 in Gn[i].edges(data = True):
@@ -504,12 +504,12 @@ def _wl_edgekernel_do(Gn, node_label, edge_label, height):
 
 
 def _wl_userkernel_do(Gn, node_label, edge_label, height, base_kernel):
-	"""Calculate Weisfeiler-Lehman kernels based on user-defined kernel between graphs.
+	"""Compute Weisfeiler-Lehman kernels based on user-defined kernel between graphs.
 	
 	Parameters
 	----------
 	Gn : List of NetworkX graph
-		List of graphs between which the kernels are calculated.	   
+		List of graphs between which the kernels are computed.	   
 	node_label : string
 		node attribute used as label.	  
 	edge_label : string
@@ -564,7 +564,7 @@ def _wl_userkernel_do(Gn, node_label, edge_label, height, base_kernel):
 			for node in G.nodes(data = True):
 				node[1][node_label] = set_compressed[set_multisets[node[0]]]
 				
-		# calculate kernel with h iterations and add it to the final kernel
+		# Compute kernel with h iterations and add it to the final kernel
 		Kmatrix += base_kernel(Gn, node_label, edge_label)
 		
 	return Kmatrix