Update experiments.

gklearn/experiments/papers/PRL_2020/synthesized_graphs_N.py

@@ -43,7 +43,7 @@ def xp_synthesized_graphs_dataset_size():
 			
 			run_time = 'error'
 			try:
-				gram_matrix, run_time = compute_graph_kernel(sub_graphs, kernel_name, n_jobs=1)
+				gram_matrix, run_time = compute_graph_kernel(sub_graphs, kernel_name)
 			except Exception as exp:
 				print('An exception occured when running this experiment:')
 				LOG_FILENAME = save_dir + 'error.txt'
@@ -61,4 +61,4 @@ def xp_synthesized_graphs_dataset_size():
 
 
 if __name__ == '__main__':
-	xp_synthesized_graphs_dataset_size()
+	xp_synthesized_graphs_dataset_size()

gklearn/experiments/papers/PRL_2020/synthesized_graphs_degrees.py

@@ -42,7 +42,7 @@ def xp_synthesized_graphs_degrees():
 			# Compute Gram matrix.
 			run_time = 'error'
 			try:
-				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name, n_jobs=1)
+				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name)
 			except Exception as exp:
 				print('An exception occured when running this experiment:')
 				LOG_FILENAME = save_dir + 'error.txt'

gklearn/experiments/papers/PRL_2020/synthesized_graphs_num_el.py

@@ -42,7 +42,7 @@ def xp_synthesized_graphs_num_edge_label_alphabet():
 			# Compute Gram matrix.
 			run_time = 'error'
 			try:
-				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name, n_jobs=1)
+				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name)
 			except Exception as exp:
 				print('An exception occured when running this experiment:')
 				LOG_FILENAME = save_dir + 'error.txt'

gklearn/experiments/papers/PRL_2020/synthesized_graphs_num_nl.py

@@ -42,7 +42,7 @@ def xp_synthesized_graphs_num_node_label_alphabet():
 			# Compute Gram matrix.
 			run_time = 'error'
 			try:
-				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name, n_jobs=1)
+				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name)
 			except Exception as exp:
 				run_times[kernel_name].append('error')
 				print('An exception occured when running this experiment:')

gklearn/experiments/papers/PRL_2020/synthesized_graphs_num_nodes.py

@@ -42,7 +42,7 @@ def xp_synthesized_graphs_num_nodes():
 			# Compute Gram matrix.
 			run_time = 'error'
 			try:
-				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name, n_jobs=1)
+				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name)
 			except Exception as exp:
 				run_times[kernel_name].append('error')
 				print('An exception occured when running this experiment:')

gklearn/experiments/papers/PRL_2020/utils.py

@@ -62,7 +62,7 @@ def compute_graph_kernel(graphs, kernel_name, n_jobs=multiprocessing.cpu_count()
 		import functools
 		mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel)
 		sub_kernel = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel}
-		params = {'compute_method': 'fp', 'weight': 1e-3, 'node_kernels': sub_kernel, 'edge_kernels': sub_kernel}
+		params = {'compute_method': 'fp', 'weight': 1e-4, 'node_kernels': sub_kernel, 'edge_kernels': sub_kernel}
 		
 	elif kernel_name == 'SpectralDecomposition':
 		from gklearn.kernels.randomWalkKernel import randomwalkkernel