import networkx as nx
import numba
import pyreason.scripts.numba_wrapper.numba_types.fact_node_type as fact_node
import pyreason.scripts.numba_wrapper.numba_types.fact_edge_type as fact_edge
import pyreason.scripts.numba_wrapper.numba_types.label_type as label
import pyreason.scripts.numba_wrapper.numba_types.interval_type as interval
[docs]
class GraphmlParser:
def __init__(self):
[docs]
self.non_fluent_facts = None
[docs]
def parse_graph(self, graph_path, reverse):
self.graph = nx.read_graphml(graph_path)
self.graph = nx.DiGraph(self.graph)
if reverse:
self.graph = self.graph.reverse()
return self.graph
[docs]
def load_graph(self, graph):
self.graph = nx.DiGraph(graph)
return self.graph
[docs]
def parse_graph_attributes(self, static_facts):
facts_node = numba.typed.List.empty_list(fact_node.fact_type)
facts_edge = numba.typed.List.empty_list(fact_edge.fact_type)
specific_node_labels = numba.typed.Dict.empty(key_type=label.label_type, value_type=numba.types.ListType(numba.types.string))
specific_edge_labels = numba.typed.Dict.empty(key_type=label.label_type, value_type=numba.types.ListType(numba.types.Tuple((numba.types.string, numba.types.string))))
for n in self.graph.nodes:
for key, value in self.graph.nodes[n].items():
# IF attribute is a float or int and it is less than 1, then make it a bound, else make it a label
if (isinstance(value, (float, int)) and 1 >= value >= 0) or (
isinstance(value, str) and value.replace('.', '').isdigit() and 1 >= float(value) >= 0):
label_str = str(key)
lower_bnd = float(value)
upper_bnd = 1
else:
label_str = f'{key}-{value}'
lower_bnd = 1
upper_bnd = 1
if isinstance(value, str):
bnd_str = value.split(',')
if len(bnd_str) == 2:
try:
low = int(bnd_str[0])
up = int(bnd_str[1])
if 1 >= low >= 0 and 1 >= up >= 0:
lower_bnd = low
upper_bnd = up
label_str = str(key)
except (ValueError, TypeError):
pass
if label.Label(label_str) not in specific_node_labels.keys():
specific_node_labels[label.Label(label_str)] = numba.typed.List.empty_list(numba.types.string)
specific_node_labels[label.Label(label_str)].append(n)
f = fact_node.Fact('graph-attribute-fact', n, label.Label(label_str), interval.closed(lower_bnd, upper_bnd), 0, 0, static=static_facts)
facts_node.append(f)
for e in self.graph.edges:
for key, value in self.graph.edges[e].items():
# IF attribute is a float or int and it is less than 1, then make it a bound, else make it a label
if (isinstance(value, (float, int)) and 1 >= value >= 0) or (
isinstance(value, str) and value.replace('.', '').isdigit() and 1 >= float(value) >= 0):
label_str = str(key)
lower_bnd = float(value)
upper_bnd = 1
else:
label_str = f'{key}-{value}'
lower_bnd = 1
upper_bnd = 1
if isinstance(value, str):
bnd_str = value.split(',')
if len(bnd_str) == 2:
try:
low = int(bnd_str[0])
up = int(bnd_str[1])
if 1 >= low >= 0 and 1 >= up >= 0:
lower_bnd = low
upper_bnd = up
label_str = str(key)
except (ValueError, TypeError):
pass
if label.Label(label_str) not in specific_edge_labels.keys():
specific_edge_labels[label.Label(label_str)] = numba.typed.List.empty_list(numba.types.Tuple((numba.types.string, numba.types.string)))
specific_edge_labels[label.Label(label_str)].append((e[0], e[1]))
f = fact_edge.Fact('graph-attribute-fact', (e[0], e[1]), label.Label(label_str), interval.closed(lower_bnd, upper_bnd), 0, 0, static=static_facts)
facts_edge.append(f)
print("Added ", len(facts_node), "graph-attribute node facts and ", len(facts_edge), "graph_attribute edge facts.")
return facts_node, facts_edge, specific_node_labels, specific_edge_labels