


'''simple docstring'''

from sklearn.neural_network import MLPClassifier

lowerCAmelCase   :Dict								=    [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase   :Optional[int]								=    [0, 1, 0, 0]


lowerCAmelCase   :str								=    MLPClassifier(
    solver='''lbfgs''', alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


lowerCAmelCase   :List[str]								=    [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowerCAmelCase   :List[Any]								=    clf.predict(test)





def lowerCamelCase    (    lowerCAmelCase       :			int	):





	"""simple docstring"""







	return list(UpperCamelCase__	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()



'''simple docstring'''

lowerCAmelCase   :int								=    [
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''bh-e12''', '''cd-e2''', '''ce-e4''',
     '''de-e1''', '''df-e8''', '''dg-e5''', '''dh-e10''', '''ef-e3''', '''eg-e2''', '''fg-e6''', '''gh-e6''', '''hi-e3'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''cd-e2''', '''de-e1''', '''df-e8''',
     '''ef-e3''', '''eg-e2''', '''fg-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''de-e1''', '''df-e8''', '''dg-e5''', '''ef-e3''', '''eg-e2''',
     '''eh-e12''', '''fg-e6''', '''fh-e10''', '''gh-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''bh-e12''', '''cd-e2''', '''df-e8''', '''dh-e10'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''cd-e2''', '''ce-e4''', '''de-e1''', '''df-e8''',
     '''dg-e5''', '''ef-e3''', '''eg-e2''', '''fg-e6''']
]





def lowerCamelCase    (    lowerCAmelCase       :			Tuple	):





	"""simple docstring"""







	__magic_name__ :					Union[str, Any]  			=  set()
	for row in edge_array:
		for item in row:
			distinct_edge.add(item[0]	)
	return list(lowerCAmelCase	)





def lowerCamelCase    (    lowerCAmelCase       :			List[str]	,	lowerCAmelCase       :			Optional[int]	):





	"""simple docstring"""







	__magic_name__ :					List[Any]  			=  ['0'] * len(lowerCAmelCase	)
	for i, row in enumerate(lowerCAmelCase	):
		for item in row:
			if distinct_edge in item[0]:
				__magic_name__ :					str  			=  '1'
				break
	return "".join(lowerCAmelCase	)





def lowerCamelCase    (    lowerCAmelCase       :			Tuple	):





	"""simple docstring"""







	__magic_name__ :					Any  			=  get_distinct_edge(lowerCAmelCase	)
	__magic_name__ :					Union[str, Any]  			=  {}

	for item in distinct_edge:
		__magic_name__ :					Union[str, Any]  			=  get_bitcode(lowerCAmelCase	,	lowerCAmelCase	)
		# print('bit',bit)
		# bt=''.join(bit)
		__magic_name__ :					Dict  			=  bit.count('1'	)
		__magic_name__ :					Dict  			=  [s, bit]
	# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
	__magic_name__ :					Optional[Any]  			=  [
	    [k, v[0], v[1]]
	    for k, v in sorted(frequency_table.items()	,	key=lambda lowerCAmelCase	: v[1][0]	,	reverse=lowerCAmelCase	)
	]
	return sorted_frequency_table





def lowerCamelCase    (    lowerCAmelCase       :			List[str]	):





	"""simple docstring"""







	__magic_name__ :					Tuple  			=  {}
	for _, item in enumerate(lowerCAmelCase	):
		nodes.setdefault(item[2]	,	[]	).append(item[0]	)
	return nodes





def lowerCamelCase    (    lowerCAmelCase       :			List[str]	):





	"""simple docstring"""







	__magic_name__ :					str  			=  {}
	for key, value in nodes.items():
		__magic_name__ :					Union[str, Any]  			=  value
	return cluster





def lowerCamelCase    (    lowerCAmelCase       :			List[str]	):





	"""simple docstring"""







	return [i * 100 / len(lowerCAmelCase	) for i in cluster]





def lowerCamelCase    (    ):





	"""simple docstring"""







	print('\nNodes\n'	)
	for key, value in nodes.items():
		print(lowerCAmelCase	,	lowerCAmelCase	)
	print('\nSupport\n'	)
	print(lowerCAmelCase	)
	print('\n Cluster \n'	)
	for key, value in sorted(cluster.items()	,	reverse=lowerCAmelCase	):
		print(lowerCAmelCase	,	lowerCAmelCase	)
	print('\n Graph\n'	)
	for key, value in graph.items():
		print(lowerCAmelCase	,	lowerCAmelCase	)
	print('\n Edge List of Frequent subgraphs \n'	)
	for edge_list in freq_subgraph_edge_list:
		print(lowerCAmelCase	)





def lowerCamelCase    (    lowerCAmelCase       :			int	,	lowerCAmelCase       :			str	,	lowerCAmelCase       :			Optional[Any]	,	lowerCAmelCase       :			int	):





	"""simple docstring"""







	for i in cluster[ca]:
		__magic_name__ :					Tuple  			=  0
		__magic_name__ :					Any  			=  ca + 1
		while ca < max(cluster.keys()	):
			for j in cluster[ca]:
				if int(lowerCAmelCase	,	2	) & int(lowerCAmelCase	,	2	) == int(lowerCAmelCase	,	2	):
					if tuple(nodes[i]	) in graph:
						graph[tuple(nodes[i]	)].append(nodes[j]	)
					else:
						__magic_name__ :					List[Any]  			=  [nodes[j]]
					count += 1
			if count == 0:
				__magic_name__ :					Tuple  			=  ca + 1
			else:
				break





def lowerCamelCase    (    lowerCAmelCase       :			Any	,	lowerCAmelCase       :			List[Any]	):





	"""simple docstring"""







	__magic_name__ :					str  			=  cluster[max(cluster.keys()	)]
	__magic_name__ :					Dict  			=  'Header'
	__magic_name__ :					Optional[Any]  			=  {}
	for i in x:
		if (["Header"],) in graph:
			graph[(["Header"],)].append(x[i]	)
		else:
			__magic_name__ :					List[str]  			=  [x[i]]
	for i in x:
		__magic_name__ :					Union[str, Any]  			=  [['Header']]
	__magic_name__ :					List[str]  			=  1
	while i < max(lowerCAmelCase	) - 1:
		create_edge(lowerCAmelCase	,	lowerCAmelCase	,	lowerCAmelCase	,	lowerCAmelCase	)
		__magic_name__ :					Dict  			=  i + 1
	return graph





def lowerCamelCase    (    lowerCAmelCase       :			Dict	,	lowerCAmelCase       :			Tuple	,	lowerCAmelCase       :			List[Any]	,	lowerCAmelCase       :			Union[str, Any]=None	):





	"""simple docstring"""







	__magic_name__ :					str  			=  (path or []) + [start]
	if start == end:
		paths.append(lowerCAmelCase	)
	for node in graph[start]:
		if tuple(lowerCAmelCase	) not in path:
			my_dfs(lowerCAmelCase	,	tuple(lowerCAmelCase	)	,	lowerCAmelCase	,	lowerCAmelCase	)





def lowerCamelCase    (    lowerCAmelCase       :			Optional[Any]	,	lowerCAmelCase       :			Tuple	,	lowerCAmelCase       :			Union[str, Any]	):





	"""simple docstring"""







	__magic_name__ :					Union[str, Any]  			=  int(s / 100 * (len(lowerCAmelCase	) - 1)	)
	for i in cluster[k]:
		my_dfs(lowerCAmelCase	,	tuple(cluster[k][i]	)	,	(['Header'],)	)





def lowerCamelCase    (    lowerCAmelCase       :			Optional[int]	):





	"""simple docstring"""







	__magic_name__ :					str  			=  []
	for edges in paths:
		__magic_name__ :					List[Any]  			=  []
		for j in range(len(lowerCAmelCase	) - 1	):
			__magic_name__ :					List[str]  			=  list(edges[j]	)
			for e in temp:
				__magic_name__ :					Optional[int]  			=  (e[0], e[1])
				el.append(lowerCAmelCase	)
		freq_sub_el.append(lowerCAmelCase	)
	return freq_sub_el





def lowerCamelCase    (    lowerCAmelCase       :			str	):





	"""simple docstring"""







	for i in range(len(lowerCAmelCase	)	):
		for j in range(len(edge_array[i]	)	):
			__magic_name__ :					Any  			=  edge_array[i][j].split('-'	)
			__magic_name__ :					Tuple  			=  t


if __name__ == "__main__":
							preprocess(edge_array)
							lowerCAmelCase   :List[str]								=    get_frequency_table(edge_array)
							lowerCAmelCase   :List[str]								=    get_nodes(frequency_table)
							lowerCAmelCase   :Optional[int]								=    get_cluster(nodes)
							lowerCAmelCase   :Tuple								=    get_support(cluster)
							lowerCAmelCase   :Tuple								=    construct_graph(cluster, nodes)
							find_freq_subgraph_given_support(6_0, cluster, graph)
							lowerCAmelCase   :list								=    []
							lowerCAmelCase   :str								=    freq_subgraphs_edge_list(paths)
							print_all()