def add_assignment(self, i, k):
if i != dummy_node():
if i < len(self.__forward_map):
self.__forward_map[i] = k
else:
raise Exception('The node with ID ', str(i), ' is not contained in the source nodes of the node map.')
if k != dummy_node():
if k < len(self.__backward_map):
self.__backward_map[k] = i
else:
raise Exception('The node with ID ', str(k), ' is not contained in the target nodes of the node map.')
def construct_node_map_from_solver(solver, node_map, solution_id):
node_map.clear()
num_nodes_g = node_map.num_source_nodes()
num_nodes_h = node_map.num_target_nodes()
# add deletions and substitutions
for row in range(0, num_nodes_g):
col = solver.get_assigned_col(row, solution_id)
if col >= num_nodes_h:
node_map.add_assignment(row, dummy_node())
else:
node_map.add_assignment(row, col)
# insertions.
for col in range(0, num_nodes_h):
if solver.get_assigned_row(col, solution_id) >= num_nodes_g:
node_map.add_assignment(dummy_node(), col)
def as_relation(self, relation):
relation.clear()
for i in range(0, len(self._forward_map)):
k = self._forward_map[i]
if k != undefined_node():
relation.append(tuple((i, k)))
for k in range(0, len(self._backward_map)):
i = self._backward_map[k]
if i == dummy_node():
relation.append(tuple((i, k)))
def compute_induced_cost(self, g, h, node_map):
"""
/*!
* @brief Computes the edit cost between two graphs induced by a node map.
* @param[in] g Input graph.
* @param[in] h Input graph.
* @param[in,out] node_map Node map whose induced edit cost is to be computed.
*/
"""
cost = 0
# collect node costs
for node in g.nodes():
image = node_map.image(node)
label2 = (SpecialLabel.DUMMY
if image == dummy_node() else h.nodes[image]['label'])
cost += self.node_cost(g.nodes[node]['label'], label2)
for node in h.nodes():
pre_image = node_map.pre_image(node)
if pre_image == dummy_node():
cost += self.node_cost(SpecialLabel.DUMMY,
h.nodes[node]['label'])
# collect edge costs
for (n1, n2) in g.edges():
image1 = node_map.image(n1)
image2 = node_map.image(n2)
label2 = (h.edges[(image2, image1)]['label'] if h.has_edge(
image2, image1) else SpecialLabel.DUMMY)
cost += self.edge_cost(g.edges[(n1, n2)]['label'], label2)
for (n1, n2) in h.edges():
if not g.has_edge(node_map.pre_image(n2), node_map.pre_image(n1)):
cost += self.edge_cost(SpecialLabel.DUMMY,
h.edges[(n1, n2)]['label'])
node_map.set_induced_cost(cost)