

__A	:   str	=					[
    ['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        __UpperCamelCase     (      _A					:							str		)				->Optional[Any]:



							"""simple docstring"""
							lowerCamelCase_								=set()
							for row in edge_array:
														for item in row:
																					distinct_edge.add(item[0]		)
							return list(lowercase__		)




def        __UpperCamelCase     (      _A					:							Optional[Any]      ,  _A					:							Optional[int]		)				->int:



							"""simple docstring"""
							lowerCamelCase_								=["""0"""] * len(lowercase__		)
							for i, row in enumerate(lowercase__		):
														for item in row:
																					if distinct_edge in item[0]:
																												lowerCamelCase_								="""1"""
																												break
							return "".join(lowercase__		)




def        __UpperCamelCase     (      _A					:							Optional[Any]		)				->Union[str, Any]:



							"""simple docstring"""
							lowerCamelCase_								=get_distinct_edge(lowercase__		)
							lowerCamelCase_								={}

							for item in distinct_edge:
														lowerCamelCase_								=get_bitcode(lowercase__      ,  lowercase__		)
														# print('bit',bit)
														# bt=''.join(bit)
														lowerCamelCase_								=bit.count("""1"""		)
														lowerCamelCase_								=[s, bit]
							# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
							lowerCamelCase_								=[
							    [k, v[0], v[1]]
							    for k, v in sorted(frequency_table.items()      ,  key=lambda _A		: v[1][0]      ,  reverse=lowercase__		)
							]
							return sorted_frequency_table




def        __UpperCamelCase     (      _A					:							Optional[Any]		)				->Optional[int]:



							"""simple docstring"""
							lowerCamelCase_								={}
							for _, item in enumerate(lowercase__		):
														nodes.setdefault(item[2]      ,  []		).append(item[0]		)
							return nodes




def        __UpperCamelCase     (      _A					:							int		)				->Dict:



							"""simple docstring"""
							lowerCamelCase_								={}
							for key, value in nodes.items():
														lowerCamelCase_								=value
							return cluster




def        __UpperCamelCase     (      _A					:							Optional[int]		)				->int:



							"""simple docstring"""
							return [i * 100 / len(lowercase__		) for i in cluster]




def        __UpperCamelCase     (      )				->str:



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




def        __UpperCamelCase     (      _A					:							Optional[int]      ,  _A					:							Tuple      ,  _A					:							Optional[Any]      ,  _A					:							Any		)				->Union[str, Any]:



							"""simple docstring"""







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




def        __UpperCamelCase     (      _A					:							int      ,  _A					:							str		)				->Any:



							"""simple docstring"""
							lowerCamelCase_								=cluster[max(cluster.keys()		)]
							lowerCamelCase_								="""Header"""
							lowerCamelCase_								={}
							for i in x:
														if (["Header"],) in graph:
																					graph[(["Header"],)].append(x[i]		)
														else:
																					lowerCamelCase_								=[x[i]]
							for i in x:
														lowerCamelCase_								=[["""Header"""]]
							lowerCamelCase_								=1
							while i < max(lowercase__		) - 1:
														create_edge(lowercase__      ,  lowercase__      ,  lowercase__      ,  lowercase__		)
														lowerCamelCase_								=i + 1
							return graph




def        __UpperCamelCase     (      _A					:							Any      ,  _A					:							Optional[int]      ,  _A					:							List[Any]      ,  _A					:							List[str]=None		)				->List[Any]:



							"""simple docstring"""
							lowerCamelCase_								=(path or []) + [start]
							if start == end:
														paths.append(lowercase__		)
							for node in graph[start]:
														if tuple(lowercase__		) not in path:
																					my_dfs(lowercase__      ,  tuple(lowercase__		)      ,  lowercase__      ,  lowercase__		)




def        __UpperCamelCase     (      _A					:							int      ,  _A					:							str      ,  _A					:							Dict		)				->Tuple:



							"""simple docstring"""
							lowerCamelCase_								=int(s / 100 * (len(lowercase__		) - 1)		)
							for i in cluster[k]:
														my_dfs(lowercase__      ,  tuple(cluster[k][i]		)      ,  (["""Header"""],)		)




def        __UpperCamelCase     (      _A					:							List[Any]		)				->str:



							"""simple docstring"""
							lowerCamelCase_								=[]
							for edges in paths:
														lowerCamelCase_								=[]
														for j in range(len(lowercase__		) - 1		):
																					lowerCamelCase_								=list(edges[j]		)
																					for e in temp:
																												lowerCamelCase_								=(e[0], e[1])
																												el.append(lowercase__		)
														freq_sub_el.append(lowercase__		)
							return freq_sub_el




def        __UpperCamelCase     (      _A					:							int		)				->str:



							"""simple docstring"""







							for i in range(len(lowercase__		)		):
														for j in range(len(edge_array[i]		)		):
																					lowerCamelCase_								=edge_array[i][j].split("""-"""		)
																					lowerCamelCase_								=t


if __name__ == "__main__":
	preprocess(edge_array)
	__A	:   Optional[int]	=					get_frequency_table(edge_array)
	__A	:   Optional[Any]	=					get_nodes(frequency_table)
	__A	:   int	=					get_cluster(nodes)
	__A	:   Optional[int]	=					get_support(cluster)
	__A	:   List[str]	=					construct_graph(cluster, nodes)
	find_freq_subgraph_given_support(60, cluster, graph)
	__A	:   Optional[Any]	=					[]
	__A	:   Optional[int]	=					freq_subgraphs_edge_list(paths)
	print_all()





'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowercase											=      {
    '''configuration_align''': [
        '''ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''AlignConfig''',
        '''AlignTextConfig''',
        '''AlignVisionConfig''',
    ],
    '''processing_align''': ['''AlignProcessor'''],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase											=      [
      '''ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''AlignModel''',
      '''AlignPreTrainedModel''',
      '''AlignTextModel''',
      '''AlignVisionModel''',
  ]

if TYPE_CHECKING:
  from .configuration_align import (
      ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
      AlignConfig,
      AlignTextConfig,
      AlignVisionConfig,
  )
  from .processing_align import AlignProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_align import (
        ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
        AlignModel,
        AlignPreTrainedModel,
        AlignTextModel,
        AlignVisionModel,
    )

else:
  import sys

  lowercase											=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


