def get_sentence_reference_graph(self, ):
# a graph containing sentence to sentence links
self.get_sentence_boundaries_amr()
sentence_connections = []
weights = {}
for index_node, node in enumerate(self.amr):
current_sent_index = self.node_index_to_sent_index(index_node)
if current_sent_index == -1: continue
current_var = node['variable']
for location in self.var_to_index[current_var]:
location_sent_index = self.node_index_to_sent_index(location)
if location_sent_index != current_sent_index:
if (current_sent_index,
location_sent_index) not in sentence_connections:
sentence_connections.append(
(current_sent_index, location_sent_index))
sentence_connections.append(
(location_sent_index, current_sent_index))
weights[str(current_sent_index) + ' ' +
str(location_sent_index)] = 1
weights[str(location_sent_index) + ' ' +
str(current_sent_index)] = 1
else:
weights[str(current_sent_index) + ' ' +
str(location_sent_index)] += 1
weights[str(location_sent_index) + ' ' +
str(current_sent_index)] += 1
self.sentence_reference_graph = Graph(
connections=sentence_connections,
nodes=range(0, len(self.sentence_boundries)),
weights=weights)
def __init__(self,
text_list=[],
amr_with_attributes=False,
text='',
alignments=[],
var_to_sent={},
sent_index=0):
# If the 'amr' that we get doesn't has attributes, it is just as text,
# i.e. each element of the list is just a line of the text
# else the amr that has all the attributes, and it is in the required form
self.text_list = text_list
self.amr = self.text_list
# mapping from 'variables' to indices in self.amr
self.var_to_index = {}
if amr_with_attributes == False:
# add attributes
self.add_attributes()
# add other attributes like 'variable_start_index'
self.add_variable_info()
# contains the edge lable for every class
self.edges = {}
self.connections = self.get_edge_info()
self.get_var_to_index_mapping()
# Contains all the 'variables' in the list
self.nodes = self.get_node_info()
self.common_text = self.get_common_text_var_mapping()
# get 'var_to_sent'
if var_to_sent == {}:
for key in self.var_to_index.keys():
var_to_sent[key] = [sent_index]
self.var_to_sent = var_to_sent
self.alignments = None
self.get_alignments(alignments)
# Not updated while mering any 2 nodes
self.get_sentence_boundaries_amr()
self.get_text_index_to_var()
self.directed_graph = Graph(connections=self.connections,
nodes=self.nodes,
edge_lables=self.edges,
var_to_sent=self.var_to_sent,
common_text=self.common_text,
text_index_to_var=self.text_index_to_var,
root=self.amr[0]['variable'])
self.topological_order = self.directed_graph.topological_order
# self.text is a list of sentences in case of a document AMR
self.text = text
self.split_text = (' '.join(self.text)).split()
# get detph_list
self.depth_dict = {}
self.get_depth_dict()
def main():
g = Graph()
g.add_edge(0, 1)
g.add_edge(0, 5)
# g.add_edge(1, 2)
# g.add_edge(2, 3)
g.add_edge(3, 4)
g.add_edge(3, 5)
g.add_edge(4, 0)
g.add_edge(5, 4)
# g.add_edge(5, 2)
print route_between_nodes(g, 3, 5)
def reconstruct_amr(self):
text_list=self.directed_graph.generate_text_amr()
text_list =[line + '\n' for line in text_list]
text_index_to_var = self.directed_graph.text_index_to_var
var_to_sent = self.directed_graph.var_to_sent
# Reconstruct the AMR after merging two nodes
del self.text_list
del self.amr
del self.var_to_index
del self.nodes
del self.edges
del self.directed_graph
del self.topological_order
del self.depth_dict
# self.text is a list of sentences in case of a document AMR
self.text_list = text_list
self.amr = self.text_list
# mapping from 'variables' to indices in self.amr
self.var_to_index = {}
# add attributes
self.add_attributes()
# add other attributes like 'variable_start_index'
self.add_variable_info()
# contains the edge lable for every class
self.edges = {}
self.connections = self.get_edge_info()
self.get_var_to_index_mapping()
# Contains all the 'variables' in the list
self.nodes = self.get_node_info()
del self.var_to_sent
self.var_to_sent = {}
for var in var_to_sent.keys():
if var in self.nodes:
self.var_to_sent[var] = var_to_sent[var]
self.common_text = self.get_common_text_var_mapping()
temp = set(self.alignments.keys())
del self.alignments
self.alignments = {}
for text_index in text_index_to_var.keys():
# alignment in case of KeyError is mostly useless (but not always)
self.alignments[text_index] = []
for var in text_index_to_var[text_index]:
try: node_index = self.var_to_index[var][0]
except KeyError: break
var_path = self.node_index_to_alignment(node_index)
self.alignments[text_index].append(var_path)
alignments = []
for key in self.alignments.keys():
for alignment in self.alignments[key]:
alignments.append(key+'-'+'.'.join(alignment))
self.alignments = None
self.get_alignments(alignments)
self.get_text_index_to_var()
var_set = []
for key in self.text_index_to_var.keys():
var_set.extend(self.text_index_to_var[key])
var_set = list(set(var_set))
for var in var_set:
if var not in self.nodes:
print 'some bug'
0/0
self.directed_graph = Graph(connections=self.connections,nodes=self.nodes,
edge_lables=self.edges,var_to_sent=self.var_to_sent,
common_text=self.common_text,
text_index_to_var=self.text_index_to_var,
root=self.amr[0]['variable'])
self.topological_order = self.directed_graph.topological_order
self.get_depth_dict()