New translations test_ged_env.py (Chinese Simplified)

lang/zh/gklearn/tests/ged/test_ged_env.py

@@ -0,0 +1,57 @@
+"""Tests of GEDEnv.
+"""
+
+
+def test_GEDEnv():
+	"""Test GEDEnv.
+	"""
+	"""**1.   Get dataset.**"""
+
+	from gklearn.utils import Dataset
+	
+	# Predefined dataset name, use dataset "MUTAG".
+	ds_name = 'MUTAG'
+	
+	# Initialize a Dataset.
+	dataset = Dataset()
+	# Load predefined dataset "MUTAG".
+	dataset.load_predefined_dataset(ds_name)
+	graph1 = dataset.graphs[0]
+	graph2 = dataset.graphs[1]
+	
+	"""**2.  Compute graph edit distance.**"""
+	
+	try:	
+		from gklearn.ged.env import GEDEnv		
+		
+		ged_env = GEDEnv() # initailize GED environment.
+		ged_env.set_edit_cost('CONSTANT', # GED cost type.
+		                      edit_cost_constants=[3, 3, 1, 3, 3, 1] # edit costs.
+							  )  
+		ged_env.add_nx_graph(graph1, '') # add graph1
+		ged_env.add_nx_graph(graph2, '') # add graph2
+		listID = ged_env.get_all_graph_ids() # get list IDs of graphs
+		ged_env.init(init_type='LAZY_WITHOUT_SHUFFLED_COPIES') # initialize GED environment.
+		options = {'initialization_method': 'RANDOM', # or 'NODE', etc.
+		           'threads': 1 # parallel threads.
+				   }
+		ged_env.set_method('BIPARTITE', # GED method.
+		                   options # options for GED method.
+						   )
+		ged_env.init_method() # initialize GED method.
+		
+		ged_env.run_method(listID[0], listID[1]) # run.
+		
+		pi_forward = ged_env.get_forward_map(listID[0], listID[1]) # forward map.
+		pi_backward = ged_env.get_backward_map(listID[0], listID[1]) # backward map.
+		dis = ged_env.get_upper_bound(listID[0], listID[1])	# GED bewteen two graphs.
+		
+		import networkx as nx
+		assert len(pi_forward) == nx.number_of_nodes(graph1), len(pi_backward) == nx.number_of_nodes(graph2)
+	
+	except Exception as exception:
+		assert False, exception
+
+
+if __name__ == "__main__":
+	test_GEDEnv()