def convert2graph(self, road_network=None, directed=True,
edge_weighted_by_distance=True,
node_weighted_by_dwelling=True):
""" Return a graph representation of human mobility, one which
is weighted by traveling distance for edge and dwelling time for node.
**PerfStat** (PersonNum,Calls,AccTime): 100,1519,54.191s
"""
graph = seq2graph(self.coordinates, directed)
if edge_weighted_by_distance:
for edge in graph.edges_iter():
if road_network:
dist = road_network.shortest_path_distance(edge[0], edge[1])
else:
dist = greate_circle_distance(edge[0][0], edge[0][1], edge[1][0], edge[1][1])
graph.edge[edge[0]][edge[1]]['weight'] = dist
if edge in self.freq:
graph.edge[edge[0]][edge[1]]['frequency'] = self.freq[edge]
else:
graph.edge[edge[0]][edge[1]]['frequency'] = 1
if node_weighted_by_dwelling:
for node in graph.nodes_iter():
graph.node[node]['weight'] = self.accdwelling.get(node)
return graph
def convert2graph(self, road_network, directed=True,
edge_weighted_by_distance=True,
node_weighted_by_dwelling=True):
""" Return a graph representation of human mobility, one which
is weighted by traveling distance for edge and dwelling time for node.
**PerfStat** (PersonNum,Calls,AccTime): 100,1519,54.191s
"""
graph = seq2graph(self.coordinates, directed)
if edge_weighted_by_distance:
for edge in graph.edges_iter():
graph.edge[edge[0]][edge[1]]['distance'] = \
road_network.shortest_path_distance(edge[0], edge[1])
if node_weighted_by_dwelling:
for node in graph.nodes_iter():
graph.node[node]['dwelling'] = self.accdwelling.get(node)
return graph
