def validate():
if not env.method == "validate.pts":
return
vPs = []
vPd = []
n = 0
total = env.veh_total
for i in range(2 * env.veh_total):
try:
vehicle.shortest_path(i)
n += 1
purr.update(n, total, "Gathering valid points ")
vPs.append(env.vPs[i])
vPd.append(env.vPd[i])
if len(vPs) == env.veh_total:
print("\nValid points determined. Exiting...")
purr.save(env.valid_points_file, (vPs, vPd, env.tP))
purr.save(env.status_file, True)
sys.exit(0)
except nx.NetworkXNoPath:
pass
continue
print("Not good points, need to reload.")
purr.save(env.status_file, False)
sys.exit(0)
return
def main():
global OPTIONS
OPTIONS = get_options()
edg_xml = purr.mrf(OPTIONS.map_dir, r'*.edg.xml')
edges = purr.readXMLtag(edg_xml, 'edge')
original_edges = speedhist.load_edges()
connections = speedhist.load_connections()
fn = 'hhh.edg.xml'
with open(fn, 'w') as f:
f.write('<edges>')
n = 0
total = len(edges)
for edge in edges:
conn = purr.filterdicts(connections, 'ID', edge['id'])[0]
child_edges = speedhist.get_edges(conn, original_edges)
_sum = 0
for ce in child_edges:
_sum += ce['mean']
speed = _sum / len(child_edges)
f.write(
'\n\t<edge id="%s" from="%s" to="%s" priority="%s" numLanes="%s" speed="%.3f"/>'
% (edge['id'], edge['from'], edge['to'], edge['priority'],
edge['numLanes'], speed))
n += 1
purr.update(n, total)
continue
f.write('\n</edges>')
return
def load_complete_spm():
complete_spm_pybin = "temp/complete-spm.pybin"
try:
env.spm_complete = purr.load(complete_spm_pybin)
except FileNotFoundError:
nodes = list(env.nx.nodes)
weights = []
n = 0
total = len(nodes) * len(nodes)
for irow, rn in enumerate(nodes):
row = []
for icol, cn in enumerate(nodes):
weight = float('inf')
if not cn == rn:
weight = None
row.append(weight)
n += 1
purr.update(n, total, "Generating Complete SPM...")
continue
weights.append(row)
continue
spm = {'colnames': nodes, 'rownames': nodes, 'weights': weights}
env.spm_complete = spm
purr.save(complete_spm_pybin, env.spm_complete)
print("Complete!")
return
def initialize(traci):
os.system("cls")
print("Initializing...")
preprocess.initialize_nx()
preprocess.initialize_edges_for_spawns_and_sinks(traci)
target.initialize(traci)
env.traci = traci
vehicle.initialize()
spm.generate_tar2dest()
env.dist = distance.distance()
n = 0
total = env.veh_exists_max
for i in range(0, env.veh_exists_max):
vehicle.add()
n += 1
purr.update(n,
total,
msg="Adding first %d vehicles " % (env.veh_exists_max))
continue
# ~ env.update_vehicle_info = True
print("Initialization complete!")
return
def main():
global OPTIONS
OPTIONS = get_options()
# Nodes
nod_xml = purr.mrf(OPTIONS.map_dir, r'*.nod.xml')
nodes = purr.readXMLtag(nod_xml, 'node')
print("nodes: ", len(nodes))
# Edges
edg_xml = purr.mrf(OPTIONS.map_dir, r'*.edg.xml')
edges = purr.readXMLtag(edg_xml, 'edge')
print("edges: ", len(edges))
# Load in Uber speed data
original_edges = speedhist.load_edges()
connections = speedhist.load_connections()
with open(OPTIONS.output, 'w') as f:
f.write("% from to weight id\n")
# Each each is a connection
n = 0
total = len(edges)
for edge in edges:
# Edges with shape
try:
length = length_from_shape(edge['shape'])
# Edges w/o shape
except KeyError:
node_from = purr.filterdicts(nodes, 'id', edge['from'])[0]
node_to = purr.filterdicts(nodes, 'id', edge['to'])[0]
length = length_from_nodes(node_from, node_to)
# Determine Speed
# ~ speed = float(edge['speed'])
conn = purr.filterdicts(connections, 'ID', edge['id'])[0]
child_edges = speedhist.get_edges(conn, original_edges)
_sum = 0
for ce in child_edges:
_sum += ce['mean']
speed = _sum / len(child_edges)
f.write("%s %s %.3f %s\n" %
(edge['from'], edge['to'], length / speed, edge['id']))
n += 1
purr.update(n, total, msg="Calculating edge lengths ")
continue
pass
print()
return
def main():
map_dir = "../london-seg4/data/100"
edges = purr.readXMLtag(purr.mrf(map_dir, r'*.edg.xml'), 'edge')
connections = purr.readCSV(purr.mrf(map_dir, r'*.conn.csv'))
stats = purr.readCSV('edges.stats.csv')
purr.head(edges)
purr.head(connections)
purr.head(stats)
# ~ return
eids = [edge['id'] for edge in edges]
connections = purr.flattenlist(
purr.batchfilterdicts(connections,
'CONNECTION ID',
eids,
show_progress=True))
print()
total = len(connections) - 1
for i, conn in enumerate(connections):
try:
speeds = purr.flattenlist(
purr.batchfilterdicts(stats, 'ID', conn['EDGE IDS']))
except TypeError:
speeds = purr.flattenlist(
purr.batchfilterdicts(stats, 'ID', [conn['EDGE IDS']]))
mean = [float(speed['mean']) for speed in speeds]
std = [float(speed['std']) for speed in speeds]
p50 = [float(speed['p50']) for speed in speeds]
p85 = [float(speed['p85']) for speed in speeds]
edges[i]['mean'] = "%.3f" % (statistics.mean(mean))
edges[i]['std'] = "%.3f" % (statistics.mean(std))
edges[i]['p50'] = "%.3f" % (statistics.mean(p50))
edges[i]['p85'] = "%.3f" % (statistics.mean(p85))
purr.update(i, total, "Correlating speeds with edges ")
continue
with open("edg.xml", 'w') as f:
f.write("<edges>")
for edge in edges:
f.write("\n\t<edge")
for key, val in edge.items():
f.write(' %s="%s"' % (key, val))
f.write("/>")
continue
f.write("\n</edges>")
print("COMPLETE!")
return
def initialize():
env.vehicles = [None for iveh in range(env.veh_total)]
total = len(env.vehicles)
for i, x in enumerate(env.vehicles):
veh = vehdict()
veh['id'] = 'veh%d' % (i)
veh['shortest path'] = random_shortest_path()
veh['source'] = veh['shortest path']['nids'][0]
veh['destination'] = veh['shortest path']['nids'][-1]
veh['shortest path length'] = veh['shortest path']['weight']
env.vehicles[i] = veh
purr.update(i+1,total,"Initializing Vehicles ")
print()
return
def main():
global OPTIONS
OPTIONS = get_options()
# Nodes
nod_xml = purr.mrf(OPTIONS.map_dir, r'*.nod.xml')
nodes = purr.readXMLtag(nod_xml, 'node')
print("nodes: ", len(nodes))
# Edges
edg_xml = purr.mrf(OPTIONS.map_dir, r'*.edg.xml')
edges = purr.readXMLtag(edg_xml, 'edge')
print("edges: ", len(edges))
with open(OPTIONS.output, 'w') as f:
f.write("% from to weight id\n")
# Each each is a connection
n = 0
total = len(edges)
for edge in edges:
if edge['from'] == edge['to']:
n += 1
continue
# Edges with shape
try:
length = length_from_shape(edge['shape'])
# Edges w/o shape
except KeyError:
node_from = purr.filterdicts(nodes, 'id', edge['from'])[0]
node_to = purr.filterdicts(nodes, 'id', edge['to'])[0]
length = length_from_nodes(node_from, node_to)
speed = float(edge['speed'])
f.write("%s %s %.3f %s\n" %
(edge['from'], edge['to'], length / speed, edge['id']))
n += 1
purr.update(n, total, msg="Calculating edge lengths ")
continue
pass
print()
return
def initialize(traci):
os.system("cls")
print("Initializing...")
trips = purr.readXMLtag(purr.mrf(env.map_dir,r"*.trips.xml"),"trip")
total = len(trips) - 1
print('Number of trips:',len(trips))
for i,trip in enumerate(trips):
veh = vehicle.Vehicle("veh%d" % (i))
try:
veh.add(traci,trip['from'],trip['to'],trip['depart'])
except:
pass
env.vehicles.append(veh)
purr.update(i,total)
print("Initialization complete!")
return
def generate(colnames, rownames):
weights = []
n = 0
total = len(colnames) * len(rownames)
for irow, rn in enumerate(rownames):
row = []
for icol, cn in enumerate(colnames):
weight = float('inf')
if not cn == rn:
weight = nxops.path_info(env.nx,
nx.dijkstra_path(env.nx, cn, rn))[0]
row.append(weight)
n += 1
purr.update(n, total, "Generating SPM ")
continue
weights.append(row)
continue
spm = {'colnames': colnames, 'rownames': rownames, 'weights': weights}
print()
return spm
def correlateNormalPoints2SumoNodes(self, P, msg=''):
closestNode = [None for p in P]
total = len(self.nodes) - 1
for n, node in enumerate(self.nodes):
nx = node['normX']
ny = node['normY']
for i, p in enumerate(P):
px, py = p
px = float(px)
py = float(py)
dist = math.sqrt(math.pow(nx - px, 2) + math.pow(ny - py, 2))
if closestNode[i] == None or closestNode[i]['err'] > dist:
node['err'] = dist
closestNode[i] = node
continue
purr.update(n, total, msg)
continue
print()
err = [node['err'] for node in closestNode]
print("Mean err %.5f" % (statistics.mean(err)))
return closestNode
def initialize():
env.vehicles = [None for iveh in range(env.veh_total)]
for i, item in enumerate(env.vehicles):
veh = vehdict()
veh['id'] = 'veh%d' % (i)
try:
veh['shortest path'] = shortest_path(i)
# Starting points
xy = (float(env.vPs[i]['x']),float(env.vPs[i]['y']))
preprocess.add_radius_polygon(xy,50,(0,0,255),3)
preprocess.add_radius_polygon(xy,10,(0,255,255),4)
# Ending points
xy = (float(env.vPd[i]['x']),float(env.vPd[i]['y']))
preprocess.add_radius_polygon(xy,50,(255,0,0),3)
preprocess.add_radius_polygon(xy,10,(255,255,0),4)
except nx.NetworkXNoPath:
# Starting points
xy0 = (float(env.vPs[i]['x']),float(env.vPs[i]['y']))
preprocess.add_radius_polygon(xy0,50,(0,0,150),i+3)
preprocess.add_radius_polygon(xy0,10,(0,150,150),i+4)
# Ending points
xy1 = (float(env.vPd[i]['x']),float(env.vPd[i]['y']))
preprocess.add_radius_polygon(xy1,50,(150,0,0),i+3)
preprocess.add_radius_polygon(xy1,10,(150,150,0),i+4)
purr.save(env.status_file,False)
print("\nPoints improperly placed.")
sys.exit(0)
pass
veh['source'] = veh['shortest path']['nids'][0]
veh['destination'] = veh['shortest path']['nids'][-1]
veh['shortest path length'] = veh['shortest path']['weight']
env.vehicles[i] = veh
purr.update(i+1,env.veh_total,"Initializing vehicles ")
continue
return
def initialize(traci):
os.system("cls")
print("Initializing...")
env.traci = traci
preprocess.initialize_nx()
preprocess.initialize_edges_and_nodes()
point.validate()
vehicle.initialize()
target.initialize(traci)
spm.generate_tar2dest()
env.dist = distance.distance()
n = 0
total = env.veh_exists_max
for i in range(0, env.veh_exists_max):
vehicle.add()
n += 1
purr.update(n,
total,
msg="Adding first %d vehicles " % (env.veh_exists_max))
continue
print()
vehicle.update()
spm.update_veh2tar()
env.nash_assigner = ss2.nashAssigner(N=len(env.vPd),
M=len(env.tP),
R=env.R,
tau=env.tau,
dist=env.dist)
if env.method == "greedy":
vehicle.set_route(env.nash_assigner.greedyAssignments())
else:
vehicle.set_route(env.nash_assigner.getAssignments())
# ~ env.update_vehicle_info = True
print("Initialization complete!")
return
def cone_spread():
cones = cone_target_region()
target_node_candidates = []
total = len(env.nodes) - 1
for n, node in enumerate(env.nodes):
x = float(node['x'])
y = float(node['y'])
for shape in cones:
if purr.point_inside_polygon(x, y, shape):
target_node_candidates.append(node)
break
continue
purr.update(n, total, "Finding target node candidates ")
continue
print()
print('Found %d target node candidates.' % (len(target_node_candidates)))
if env.target_n > len(target_node_candidates):
print(
"Not enough nodes for requested target amount. Increase target.node.angle."
)
sys.exit(1)
random.seed(env.seed)
return random.sample(target_node_candidates, env.target_n)
def initialize(traci):
os.system("cls")
print("Initializing...")
preprocess.initialize_nx()
preprocess.initialize_shortest_path_weights()
preprocess.initialize_edges_for_spawns_and_sinks(traci)
target.initialize(traci)
n = 0
total = env.veh_exists_max
for i in range(0, env.veh_exists_max):
vehicle.add(traci)
n += 1
purr.update(n,
total,
msg="Adding first %d vehicles " % (env.veh_exists_max))
continue
if env.method == 'nash':
env.dist = distance()
print("Initialization complete!")
return
def update():
env.update_vehicle_info = False
# Clean out the old object
env.vehicles_active = []
# Refill
total = len(env.vehicles)
for i,v in enumerate(env.vehicles):
veh = dict()
# Who am I?
veh['id'] = v['id']
# Where am I?
veh['route index'] = env.traci.vehicle.getRouteIndex(veh['id'])
# What is my route?
veh['route id'] = env.traci.vehicle.getRouteID(veh['id'])
# What is my sink node?
veh['destination node'] = env.vehicles_dest[int(veh['id'][3:])]
if veh['route index'] < 0:
veh['route index'] = 0
veh['position on edge (m)'] = 0.000001
eid = env.traci.route.getEdges(veh['route id'])[0]
else:
# How far along the edge am I (m)?
veh['position on edge (m)'] = env.traci.vehicle.getLanePosition(veh['id'])
# What edge am I on?
eid = env.traci.vehicle.getRoadID(veh['id'])
# Obtain the edge object. Here we can have two cases:
# 1. veh is at an intersection
# 2. veh is on an edg
# Veh is within an intersection. Assume the start of the next edge with a position on edge (m) of zero.
if ':' in eid:
veh['route'] = env.traci.route.getEdges(veh['route id'])
eid = veh['route'][veh['route index']+1]
veh['current edge'] = purr.filterdicts(env.edges,'id',eid)[0]
veh['position on edge (m)'] = 0.000001
else:
veh['current edge'] = purr.filterdicts(env.edges,'id',eid)[0]
# How far am I along the edge (weight)
veh['position on edge (s)'] = veh['position on edge (m)'] / float(veh['current edge']['speed'])
# How much weight to the end of the edge?
edge_candidates = env.nx.get_edge_data(veh['current edge']['from'],veh['current edge']['to'])
for j in range(len(edge_candidates)):
if veh['current edge']['id'] == edge_candidates[j]['id']:
veh['weight remaining'] = edge_candidates[j]['weight'] - veh['position on edge (s)']
break
continue
# What is the weight of Veh --> Dest
veh['veh2dest weight'] = veh['weight remaining'] + nxops.path_info(env.nx,nx.dijkstra_path(env.nx,veh['current edge']['to'],veh['destination node']['id']))[0]
env.vehicles_active.append(veh)
purr.update(i+1,total,"Updating vehicle location data ")
# ~ env.recalculate_nash = True
continue
print()
return
def main():
map_dir = "../orlando-seg1/"
# Load Nodes
nod_xml = purr.mrf(map_dir, r'*.nod.xml')
nodes = purr.readXMLtag(nod_xml, 'node')
# Load Edges
edg_xml = purr.mrf(map_dir, r'*edg.xml')
edges = purr.readXMLtag(edg_xml, 'edge')
# Correlate From/To Nodes with edges
print('Finding Nodes From')
nids_from = [edge['from'] for edge in edges]
nodes_from = purr.flattenlist(
purr.batchfilterdicts(nodes, 'id', nids_from, show_progress=True))
print('\nFinding Nodes To')
nids_to = [edge['to'] for edge in edges]
nodes_to = purr.flattenlist(
purr.batchfilterdicts(nodes, 'id', nids_to, show_progress=True))
print()
# Create the CSV for Nodes
node_attr = [
'id', 'x', 'y', 'z', 'type', 'tlType', 'tl', 'radius', 'keepClear',
'rightOfWay'
]
node_csv = 'node.csv'
with open(node_csv, 'w') as csv:
# Column Names
csv.write(node_attr[0])
for attr in node_attr[1:]:
csv.write(',%s' % (attr))
csv.write('\n')
# Fill in rows
n = 0
total = len(nodes)
for node in nodes:
csv.write(node[node_attr[0]])
for attr in node_attr[1:]:
csv.write(',')
try:
csv.write(node[attr])
except KeyError:
pass
continue
csv.write('\n')
n += 1
purr.update(n, total, msg="Writing node.csv ")
continue
pass
print()
# Create the CSV for Edges
edge_attr = [
'id', 'from', 'to', 'type', 'numLanes', 'speed', 'priority',
'spreadType', 'width', 'name', 'endOffset', 'sidewalkWidth'
]
edge_allow = [
'emergency', 'authority', 'passenger', 'hov', 'taxi', 'bus',
'delivery', 'truck', 'trailer', 'motorcyle', 'moped'
]
edge_csv = 'edge.csv'
with open(edge_csv, 'w') as csv:
# Column Names
csv.write(edge_attr[0])
for attr in edge_attr[1:]:
csv.write(',%s' % (attr))
csv.write(',length')
for attr in edge_allow:
csv.write(',%s' % (attr))
csv.write('\n')
# Fill in Rows
n = 0
total = len(edges)
for i, edge in enumerate(edges):
# id
csv.write(edge[edge_attr[0]])
# Attributes
for attr in edge_attr[1:]:
csv.write(',')
try:
csv.write(edge[attr])
except KeyError:
pass
continue
# Length
try:
csv.write(',%.3f' % (shape_len(edge['shape'])))
except KeyError:
x0 = float(nodes_from[i]['x'])
y0 = float(nodes_from[i]['y'])
x1 = float(nodes_to[i]['x'])
y1 = float(nodes_to[i]['y'])
csv.write(',%.3f' % (dist(x0, y0, x1, y1)))
# Vehicle Types
vtype_allowed = [0 for item in edge_allow]
# Has neither tag. It is assumed that all vehicles are allowed.
if (not purr.xml_has_atrribute(edge, 'allow')) and (
not purr.xml_has_atrribute(edge, 'disallow')):
vtype_allowed = [1 for item in edge_allow]
# Has the allow tag. Those specified are allowed
elif (purr.xml_has_atrribute(edge, 'allow')):
vtypes = edge['allow'].split(' ')
for j, vt in enumerate(edge_allow):
if vt in vtypes:
edge_allow[j] = 1
continue
# Lastly it has the dissalow tag, and what is not speficied is allowed
elif (purr.xml_has_atrribute(edge, 'disallow')):
vtype_allowed = [1 for item in edge_allow]
vtypes = edge['allow'].split(' ')
for j, vt in enumerate(edge_allow):
if vt in vtypes:
edge_allow[j] = 0
continue
# ~ for j,vt in enumerate(edge_allow):
# ~ print(edge_allow[j],vtype_allowed[j])
for vt in vtype_allowed:
csv.write(',%d' % (vt))
csv.write('\n')
n += 1
purr.update(n, total, 'Writing edges.csv ')
continue
pass
print('\nComplete.')
return