def _connector_edges(osm_nodes, transit_nodes, travel_speed_mph=3):
"""
Generate the connector edges between the osm and transit edges and
weight by travel time
Parameters
----------
osm_nodes : pandas.DataFrame
osm nodes DataFrame
transit_nodes : pandas.DataFrame
transit nodes DataFrame
travel_speed_mph : int, optional
travel speed to use to calculate travel time across a
distance on a edge. units are in miles per hour (MPH)
for pedestrian travel this is assumed to be 3 MPH
Returns
-------
net_connector_edges : pandas.DataFrame
"""
start_time = time.time()
transit_nodes['nearest_osm_node'] = _nearest_neighbor(
osm_nodes[['x', 'y']],
transit_nodes[['x', 'y']])
net_connector_edges = []
for transit_node_id, row in transit_nodes.iterrows():
# create new edge between the node in df2 (transit)
# and the node in openstreetmap (pedestrian)
osm_node_id = int(row['nearest_osm_node'])
osm_row = osm_nodes.loc[osm_node_id]
distance = vincenty((row['y'], row['x']),
(osm_row['y'], osm_row['x'])).miles
time_ped_to_transit = distance / travel_speed_mph * 60
time_transit_to_ped = distance / travel_speed_mph * 60
# save the edge
net_type = 'transit to osm'
net_connector_edges.append((transit_node_id, osm_node_id,
time_transit_to_ped, net_type))
# make the edge bi-directional
net_type = 'osm to transit'
net_connector_edges.append((osm_node_id, transit_node_id,
time_ped_to_transit, net_type))
net_connector_edges = pd.DataFrame(net_connector_edges,
columns=["from", "to",
"weight", "net_type"])
log(
'Connector edges between the OSM and transit network nodes '
'successfully completed. Took {:,.2f} seconds'.format(
time.time() - start_time))
return net_connector_edges
评论列表
文章目录
