def __init__(self, policy_path, true_path, virtual_path, edge_desty, subpath, axes_file, speed_file, query_name):
self.sigma = 30
self.vopt = VOpt()
self.B = 3
self.policy_path = policy_path
self.true_path = true_path
self.virtual_path = virtual_path
self.edge_desty = edge_desty
self.subpath = subpath
self.axes_file = axes_file
self.speed_file = speed_file
self.speed = 50
self.query_name = query_name
def main(self, ):
data = self.load()
tpath = TPath(self.filename, self.subpath, self.dinx, self.threads_num)
edge_time_freq = tpath.get_edge_time_freq(data)
self.mkgraph = MkGraph(self.filename)
anodes, aedges = self.get_graph()
self.mkgraph.add_node_list(anodes)
self.mkgraph.add_edge_list(aedges)
self.anodes = anodes
points = self.get_axes()
path_desty, path_count, path_num, overlap, TP = self.get_dict()
vopt = VOpt()
print('v opt edge ...')
#self.edge_time_freq = multiprocessing.Manager().dict()
edge_time_freq = self.get_vopt(vopt, edge_time_freq, False, True)
path_desty = self.get_vopt(vopt, path_desty, True, True)
print('gen ...')
#self.vopt = vopt
path_desty, out_degrees, out_degrees2, All_Path = self.gen(vopt, path_desty, path_count, path_num, overlap, edge_time_freq, TP, points)
print('path desty length %d'%len(path_desty))
self.write_degree(out_degrees, self.subpath+self.store_degree_fname)
self.write_degree(out_degrees2, self.subpath+self.store_degree_fname2)
self.store_graph(self.subpath+self.graph_store_fname)
All_Path_ = {}
for ak in All_Path:
All_Path_[ak] = All_Path[ak]
self.write_json(All_Path_, self.subpath+self.store_desty_fname)
class Rout():
def __init__(self, policy_path, true_path, virtual_path, edge_desty,
subpath, axes_file, speed_file, query_name, sigma, eta):
self.sigma = 30
self.vopt = VOpt()
self.B = 3
self.policy_path = policy_path
self.true_path = true_path
self.virtual_path = virtual_path
self.edge_desty = edge_desty
self.subpath = subpath
self.axes_file = axes_file
self.speed_file = speed_file
self.speed = 50
self.query_name = query_name
self.sigma = sigma
self.eta = eta
self.hU = {}
def get_axes(self, ):
fo = open(self.axes_file)
points = {}
for line in fo:
line = line.split('\t')
points[line[0]] = (float(line[2]), float(line[1]))
return points
def get_distance(self, points, point):
(la1, lo1) = points[point[0]]
(la2, lo2) = points[point[1]]
return geodesic((lo1, la1), (lo2, la2)).kilometers
def get_U2(self, u_name):
if u_name in self.hU:
return self.hU[u_name]
if not os.path.isfile(self.policy_path + u_name):
print('no this U : %s' % (self.fpath + u_name))
return {}
fn = open(self.policy_path + u_name)
U = {}
for line in fn:
line = line.strip().split(';')
U[line[0]] = np.zeros(self.eta)
if line[1] == '-1' and line[2] == '-1':
pass
elif line[1] == '-1' and line[2] == '0':
U[line[0]] = np.ones(self.eta)
else:
for i in range(int(line[1]) + 1, int(line[2])):
t = 3 + i - int(line[1]) - 1
U[line[0]][i] = float(line[t])
for i in range(int(line[2]), self.eta):
U[line[0]][i] = 1.0
fn.close()
self.hU[u_name] = U
return U
def get_dict(self, ):
path_desty = {}
for l in range(1, 5):
with open(self.subpath + self.virtual_path +
'_%d.json' % l) as js_file:
path_desty_ = json.load(js_file)
path_desty.update(path_desty_)
with open(self.subpath + self.edge_desty) as js_file:
edge_desty = json.load(js_file)
edge_desty = dict(
sorted(edge_desty.items(), key=operator.itemgetter(0)))
vedge_desty = {}
for p_k in path_desty:
vedge_desty[p_k] = path_desty[p_k][0][1]
return vedge_desty, edge_desty, path_desty
def get_speed(self, ):
speed_dict = {}
with open(self.speed_file) as fn:
for line in fn:
line = line.strip().split('\t')
#speed_dict[line[0]] = {int(float(line[1])/float(line[2])*3600): 1.0}
speed_dict[line[0]] = {
3600 * float(line[1]) / float(line[2]): 1.0
}
return speed_dict
def get_graph(self, edge_desty, vedge_desty):
speed_dict = self.get_speed()
all_nodes, all_edges = set(), set()
for key in speed_dict:
line = key.split('-')
all_nodes.add(line[0])
all_nodes.add(line[1])
all_edges.add(key)
all_nodes, all_edges = list(all_nodes), list(all_edges)
All_edges = []
for edge in all_edges:
edge_ = edge.split('-')
if edge in edge_desty:
cost1 = edge_desty[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
elif edge in speed_dict:
cost1 = speed_dict[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
G2 = nx.DiGraph()
G2.add_nodes_from(all_nodes)
G2.add_weighted_edges_from(All_edges)
return all_edges, all_nodes, G2, speed_dict
def get_P(self, ):
pass
def conv(self, A, B):
D = {}
for a_k in A:
for b_k in B:
n_k = float(a_k) + float(b_k)
n_v = float(A[a_k]) * float(B[b_k])
D[n_k] = n_v
if len(D) <= 3:
return D
D = dict(sorted(D.items(), key=operator.itemgetter(0)))
new_w = self.vopt.v_opt(list(D.keys()), list(D.values()), self.B)
new_w = dict(sorted(new_w.items(), key=operator.itemgetter(0)))
return new_w
def get_dijkstra3(self, G, target):
Gk = G.reverse()
inf = float('inf')
D = {target: 0}
Que = PQDict(D)
P = {}
nodes = Gk.nodes
U = set(nodes)
while U:
#print('len U %d'%len(U))
#print('len Q %d'%len(Que))
if len(Que) == 0: break
(v, d) = Que.popitem()
D[v] = d
U.remove(v)
#if v == target: break
neigh = list(Gk.successors(v))
for u in neigh:
if u in U:
d = D[v] + Gk[v][u]['weight']
if d < Que.get(u, inf):
Que[u] = d
P[u] = v
return P
def get_min(self, U, node):
return np.argwhere(U[node] > 0)[0][0]
def cosin_distance(self, vector1, vector2):
dot_product = 0.0
normA = 0.0
normB = 0.0
for a, b in zip(vector1, vector2):
dot_product += a * b
normA += a**2
normB += b**2
if normA == 0.0 or normB == 0.0:
return None
else:
return dot_product / ((normA * normB)**0.5)
def rout(self, start, desti, edge_desty, vedge_desty, nodes_order, U, G2,
points, speed_dict):
path = []
Q, P_hat = [], []
neigh = list(G2.successors(start))
print('neigh %d' % len(neigh))
start_ax = points[start]
desti_ax = points[desti]
s_d_arr = [desti_ax[0] - start_ax[0], desti_ax[1] - start_ax[1]]
all_expire = 0.0
def get_weight(p_hat):
w_p_hat = {}
if p_hat in edge_desty:
w_p_hat = edge_desty[p_hat]
elif p_hat in speed_dict:
w_p_hat = speed_dict[p_hat]
elif p_hat in vedge_desty:
w_p_hat = vedge_desty[p_hat]
return w_p_hat
def get_maxP(w_p_, vv):
p_max = 0.0
for pk in w_p_:
w_pk = w_p_[pk]
pk_ = int(int(pk) / self.sigma)
if int(pk) % self.sigma == 0: pk_ += 1
p_max += float(w_pk) * U[vv][pk_]
return p_max
has_visit = set()
has_visit.add(start)
Que = PQDict.maxpq()
Q = {}
for vi in neigh:
if vi in has_visit: continue
else: has_visit.add(vi)
p_hat = start + '-' + vi
w_p_hat = get_weight(p_hat)
w_min = min([float(l) for l in w_p_hat.keys()])
p_order = nodes_order[vi] #p_hat]
tcost1 = time.time()
inx_min = np.argwhere(U[vi] > 0)
if len(inx_min) == 0:
#print('u 0 vd: %s %s'%(vi, desti))
continue
inx_min = inx_min[0][0]
all_expire += time.time() - tcost1
cost_time = w_min + inx_min * self.sigma
if cost_time <= self.T:
tcost1 = time.time()
p_max = get_maxP(w_p_hat, vi)
all_expire += time.time() - tcost1
Que[p_hat] = p_max
Q[p_hat] = (p_max, w_p_hat, cost_time)
#print('len Q %d'%len(Q))
QQ = {}
p_best_p, flag = 'none', False
p_max_m, p_best_cost, p_w_p = -1, -1, -1
if len(Q) == 0: return 'none1', -1, -1, -1, all_expire, -1
all_rounds = 0
while len(Q) != 0:
(p_hat, pqv) = Que.popitem()
all_rounds += 1
(p_max, w_p_hat, cost_time) = Q[p_hat]
del Q[p_hat]
a = p_hat.rfind('-')
v_l = p_hat[a + 1:]
if v_l == desti:
p_best_p = p_hat
p_max_m = p_max
p_best_cost = cost_time
p_w_p = w_p_hat
flag = True
break
neigh = list(G2.successors(v_l))
cost_sv = min([float(l) for l in w_p_hat.keys()])
vd_d_arr = [
points[desti][0] - points[v_l][0],
points[desti][1] - points[v_l][1]
]
for u in neigh:
if u == desti:
vu = v_l + '-' + u
w_vu = get_weight(vu)
if len(w_vu) == 0: cost_vu = 0
else: cost_vu = min([float(l) for l in w_vu.keys()])
tcost1 = time.time()
inx_min = np.argwhere(U[u] > 0)
inx_min = inx_min[0][0]
p_best_p = p_hat + ';' + vu
p_w_p = self.conv(w_p_hat, w_vu)
p_max_m = get_maxP(w_p_hat, u)
all_expire += time.time() - tcost1
p_best_cost = cost_sv + cost_vu + inx_min * self.sigma
flag = True
break
if u in has_visit:
#print('u1 %s, vd %s'%(u, desti))
continue
else:
has_visit.add(u)
if u in p_hat:
#print('u2 %s, vd %s'%(u, desti))
continue
vu = v_l + '-' + u
w_vu = get_weight(vu)
if len(w_vu) == 0:
#print('vu %s, vd %s'%(vu, desti))
continue
cost_vu = min([float(l) for l in w_vu.keys()])
p_order = nodes_order[u] #p_hat]
tcost1 = time.time()
inx_min = np.argwhere(U[u] > 0)
if len(inx_min) == 0:
#print('inx vu %s, vd %s'%(vu, desti))
continue
inx_min = inx_min[0][0]
all_expire += time.time() - tcost1
cost_time = cost_sv + cost_vu + inx_min * self.sigma
if cost_time <= self.T:
p_hat_p = p_hat + ';' + vu
w_p_hat_p = self.conv(w_p_hat, w_vu)
tcost1 = time.time()
p_hat_max = get_maxP(w_p_hat, u)
all_expire += time.time() - tcost1
QQ[p_hat_p] = (p_hat_max, w_p_hat_p, cost_time)
if flag: break
if len(Q) == 0:
Q = copy.deepcopy(QQ)
for qqk in QQ:
Que[qqk] = QQ[qqk][0]
QQ = {}
return p_best_p, p_max_m, p_best_cost, p_w_p, all_expire, all_rounds
def main(self, ):
vedge_desty, edge_desty, path_desty = self.get_dict()
edges, nodes, G2, speed_dict = self.get_graph(edge_desty, vedge_desty)
points = self.get_axes()
df2 = open(self.query_name, 'rb')
r_pairs = pickle.load(df2)
df2.close()
nodes_order, i = {}, 0
for node in nodes:
nodes_order[node] = i
i += 1
PT = 5
all_iters, flag = 0, False
One_Plot = np.zeros(20).reshape(4, 5)
One_Plot2 = np.zeros(20).reshape(4, 5)
One_Sums = np.zeros(20).reshape(4, 5)
one_dis = -1
cate = ['0-5km', '5-10km', '10-25km', '25-35km']
for pairs in r_pairs:
one_dis += 1
for pair_ in pairs[:]:
_ = self.get_U2(pair_[-1])
dij_time = 0.0
print('distance category %s' % cate[one_dis])
for pair_ in pairs[:]:
all_iters += 1
tstart = time.time()
print('o-d pair: %s' % pair_[0] + '-' + pair_[1])
start, desti = pair_[-2], pair_[-1]
pred = self.get_dijkstra3(G2, desti)
path_, st1 = [start], start
distan2 = 0
while st1 != desti:
st2 = st1
st1 = pred[st1]
path_.append(st1)
distan2 += self.get_distance(points, (st2, st1))
distan = self.get_distance(points, (start, desti))
st_key = start + '+' + desti + ':' + str(distan) + ':' + str(
distan2)
st1, time_budget = start, 0.0
for st2 in path_[1:]:
sedge = st1 + '-' + st2
if sedge in edge_desty:
speed_key = list(
[float(l) for l in edge_desty[sedge].keys()])
time_budget += max(speed_key)
elif sedge in speed_dict:
speed_key = list(
[float(l) for l in speed_dict[sedge].keys()])
time_budget += max(speed_key)
else:
print(' edge: %s not in speed_dict, exit' % sedge)
sys.exit()
st1 = st2
#print('time budget: %f'%time_budget)
U = self.get_U2(desti)
if len(U) == 0: continue
tend = time.time()
for t_b_, t_b in enumerate([0.5, 0.75, 1.0, 1.25, 1.5]):
tstart = time.time()
self.T = time_budget * t_b
best_p, max_m, best_c, best_pw, all_expires, all_rounds = self.rout(
start, desti, edge_desty, vedge_desty, nodes_order, U,
G2, points, speed_dict)
if best_p == 'none1' or best_p == 'none2' or best_p == 'none':
continue
tend = time.time()
One_Plot2[one_dis][t_b_] += tend - tstart - all_expires
One_Sums[one_dis][t_b_] += 1
One_Plot2 = One_Plot2 / One_Sums
One_Plot2 = np.nan_to_num(One_Plot2)
print('The time cost for routing')
print(One_Plot2)
print('Time cost for budget: 50%, 75%, 100%, 125%, 150%')
print(One_Plot2.mean(0))
print('Time cost for distance: 0-5km, 5-10km, 10-25km, 25-35km')
print(One_Plot2.mean(1))
class Modified():
def __init__(self, policy_path, true_path, virtual_path, edge_desty,
subpath, axes_file, speed_file, query_name):
self.sigma = 30
self.vopt = VOpt()
self.B = 3
self.policy_path = policy_path
self.true_path = true_path
self.virtual_path = virtual_path
self.edge_desty = edge_desty
self.subpath = subpath
self.axes_file = axes_file
self.speed_file = speed_file
self.speed = 50
self.query_name = query_name
def add_tpath(self, ):
with open(self.subpath + self.true_path) as fn:
gt_path_ = json.load(fn)
gt_path = {}
for gt in gt_path_:
a = gt.find('-')
a1 = gt[:a]
b = gt.rfind('-')
b1 = gt[b + 1:]
gt_key = a1 + '-' + b1
nw_key = list(gt_path_[gt].keys())
nw_value = list(gt_path_[gt].values())
lens1 = len(gt.split(';'))
if gt_key not in gt_path:
gt_path[gt_key] = [
str(gt), gt_path_[gt], lens1, nw_key[0], a1, b1
]
else:
ex_path = gt_path[gt_key]
#lens2 = len(ex_path[0].split(';'))
mins = min(len(ex_path[1]), len(gt_path_[gt]))
ex_key = list(ex_path.keys())
ex_value = list(ex_path.values())
a, b = 0, 0
for i in range(mins):
if float(ex_key[i]) < float(nw_key[i]):
a += 1
elif float(ex_key[i]) > float(nw_key[i]):
b += 1
else:
if float(ex_value[i]) > float(nw_value[i]):
a += 1
else:
b += 1
if lens1 < gt_path[gt_key][2]: b += 1
elif lens1 > gt_path[gt_key][2]: a += 1
if a < b:
gt_path[gt_key] = [
str(gt), gt_path_[gt], lens1, nw_key[0], a1, b1
]
return gt_path, gt_path_
def get_axes(self, ):
fo = open(self.axes_file)
points = {}
for line in fo:
line = line.split('\t')
points[line[0]] = (float(line[2]), float(line[1]))
return points
def get_distance(self, points, point):
(la1, lo1) = points[point[0]]
(la2, lo2) = points[point[1]]
return geodesic((lo1, la1), (lo2, la2)).kilometers
def get_dict(self, ):
path_desty = {}
for l in range(1, 5):
with open(self.subpath + self.virtual_path +
'_%d.json' % l) as js_file:
path_desty_ = json.load(js_file)
path_desty.update(path_desty_)
with open(self.subpath + self.edge_desty) as js_file:
edge_desty = json.load(js_file)
edge_desty = dict(
sorted(edge_desty.items(), key=operator.itemgetter(0)))
vedge_desty = {}
for p_k in path_desty:
vedge_desty[p_k] = path_desty[p_k][0][1]
return vedge_desty, edge_desty, path_desty
def get_speed(self, ):
speed_dict = {}
with open(self.speed_file) as fn:
for line in fn:
line = line.strip().split('\t')
speed_dict[line[0]] = {
3600 * float(line[1]) / float(line[2]): 1.0
}
return speed_dict
def get_graph(self, edge_desty, gt_path, vedge_desty):
speed_dict = self.get_speed()
all_nodes, all_edges = set(), set()
for key in speed_dict:
line = key.split('-')
all_nodes.add(line[0])
all_nodes.add(line[1])
all_edges.add(key)
all_nodes, all_edges = list(all_nodes), list(all_edges)
All_edges = []
for edge in all_edges:
edge_ = edge.split('-')
if edge in edge_desty:
cost1 = edge_desty[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
elif edge in speed_dict:
cost1 = speed_dict[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
G2 = nx.DiGraph()
G2.add_nodes_from(all_nodes)
G2.add_weighted_edges_from(All_edges)
for gt_ in gt_path:
#edges.append((gt_path[gt_][-2], gt_path[gt_][-1], abs(float(gt_path[gt_][3]))))
All_edges.append((gt_path[gt_][-2], gt_path[gt_][-1],
abs(float(gt_path[gt_][3]))))
All_edges.append((gt_path[gt_][-1], gt_path[gt_][-2],
abs(float(gt_path[gt_][3]))))
temp_edge = gt_path[gt_][-2] + '-' + gt_path[gt_][-1]
temp_edge2 = gt_path[gt_][-1] + '-' + gt_path[gt_][-2]
if temp_edge not in edge_desty:
edge_desty[temp_edge] = {abs(float(gt_path[gt_][3])): 1.0}
if temp_edge2 not in edge_desty:
edge_desty[temp_edge2] = {abs(float(gt_path[gt_][3])): 1.0}
G = nx.DiGraph()
G.add_nodes_from(all_nodes)
G.add_weighted_edges_from(All_edges)
for edge in speed_dict:
if edge not in edge_desty:
edge_desty[edge] = speed_dict[edge]
return all_edges, all_nodes, G, G2, speed_dict
def conv(self, A, B):
D = {}
for a_k in A:
for b_k in B:
n_k = float(a_k) + float(b_k)
n_v = float(A[a_k]) * float(B[b_k])
D[n_k] = n_v
if len(D) <= 3:
return D
D = dict(sorted(D.items(), key=operator.itemgetter(0)))
new_w = self.vopt.v_opt(list(D.keys()), list(D.values()), self.B)
new_w = dict(sorted(new_w.items(), key=operator.itemgetter(0)))
return new_w
def get_min(self, U, node):
return np.argwhere(U[node] > 0)[0][0]
def cosin_distance(self, vector1, vector2):
dot_product = 0.0
normA = 0.0
normB = 0.0
for a, b in zip(vector1, vector2):
dot_product += a * b
normA += a**2
normB += b**2
if normA == 0.0 or normB == 0.0:
return None
else:
return dot_product / ((normA * normB)**0.5)
def get_dijkstra3(self, G, target):
Gk = G.reverse()
inf = float('inf')
D = {target: 0}
Que = PQDict(D)
P = {}
nodes = Gk.nodes
U = set(nodes)
while U:
#print('len U %d'%len(U))
#print('len Q %d'%len(Que))
if len(Que) == 0: break
(v, d) = Que.popitem()
D[v] = d
U.remove(v)
#if v == target: break
neigh = list(Gk.successors(v))
for u in neigh:
if u in U:
d = D[v] + Gk[v][u]['weight']
if d < Que.get(u, inf):
Que[u] = d
P[u] = v
return P
def get_modified_one_to_all3(self, G, target):
Gk = G.reverse()
inf = float('inf')
D = {target: 0}
Que = PQDict(D)
P = {}
nodes = Gk.nodes
U = set(nodes)
while U:
#print('len U %d'%len(U))
#print('len Q %d'%len(Que))
if len(Que) == 0: break
(v, d) = Que.popitem()
D[v] = d
U.remove(v)
#if v == target: break
neigh = list(Gk.successors(v))
for u in neigh:
if u in U:
d = D[v] + Gk[v][u]['weight']
if d < Que.get(u, inf):
Que[u] = d
P[u] = v
return P
def rout(self, start, desti, edge_desty, vedge_desty, speed_dict,
nodes_order, U, G, G2, points, gt_path, gt_path_, pred):
Q, P_hat = [], []
neigh = list(G2.successors(start))
print('neigh %d' % len(neigh))
start_ax = points[start]
desti_ax = points[desti]
s_d_arr = [desti_ax[0] - start_ax[0], desti_ax[1] - start_ax[1]]
all_expire = 0.0
def get_weight(p_hat):
w_p_hat = {}
if p_hat in edge_desty:
w_p_hat = edge_desty[p_hat]
elif p_hat in gt_path:
w_p_hat = gt_path[p_hat][1]
elif p_hat in vedge_desty:
w_p_hat = vedge_desty[p_hat]
#print('vedge %s' %p_hat)
elif p_hat in speed_dict:
w_p_hat = speed_dict[p_hat]
if len(w_p_hat) == 0:
print('zero %s' % p_hat)
return w_p_hat
def get_maxP3(w_p_, vv, vi_getmin):
p_max = 0.0
for pk in w_p_:
w_pk = w_p_[pk]
pk_ = int(int(pk) / self.sigma)
if int(pk) % self.sigma == 0: pk_ += 1
if (1.0 * self.T - float(pk)) > vi_getmin:
p_max += float(w_pk)
return p_max
def get_vigetmin2(vv):
start1 = time.time()
v = vv
path_ = [v]
while v != desti:
v = pred[v] #[2]
path_.append(v)
paths_ = []
spath = path_[0]
vi_getmin = 0.0
expire_time = time.time() - start1
for epath in path_[1:]:
key = spath + '-' + epath
if key in edge_desty:
vi_getmin += min(
abs(float(l)) for l in edge_desty[key].keys())
elif key in speed_dict:
vi_getmin += min(
abs(float(l)) for l in speed_dict[key].keys())
elif key in gt_path:
vi_getmin += min(
abs(float(l)) for l in gt_path[p_hat][1].keys())
else:
print('edge not in here')
spath = epath
return vi_getmin, expire_time
has_visit = set()
has_visit.add(start)
Que = PQDict.maxpq()
Q = {}
for vi in neigh:
if vi in has_visit: continue
else: has_visit.add(vi)
p_hat = start + '-' + vi
w_p_hat = get_weight(p_hat)
w_min = min([float(l) for l in w_p_hat.keys()])
p_order = nodes_order[vi] #p_hat]
vi_getmin, ex_p = get_vigetmin2(vi)
all_expire += ex_p
cost_time = w_min + vi_getmin
if cost_time <= self.T:
p_max = max(list(w_p_hat.values()))
Que[p_hat] = p_max
Q[p_hat] = (p_max, w_p_hat, cost_time)
print('len Q %d' % len(Q))
QQ = {}
p_best_p, flag = 'none', False
p_max_m, p_best_cost, p_w_p = -1, -1, -1
if len(Q) == 0: return 'none1', -1, -1, -1, all_expire, -1
all_rounds = 0
while len(Q) != 0:
(p_hat, pqv) = Que.popitem()
all_rounds += 1
(p_max, w_p_hat, cost_time) = Q[p_hat]
del Q[p_hat]
a = p_hat.rfind('-')
v_l = p_hat[a + 1:]
if v_l == desti:
p_best_p = p_hat
p_max_m = p_max
p_best_cost = cost_time
p_w_p = w_p_hat
flag = True
break
neigh = list(G2.successors(v_l))
if len(w_p_hat.keys()) == 0:
print(w_p_hat)
print(p_hat)
cost_sv = min([float(l) for l in w_p_hat.keys()])
vd_d_arr = [
points[desti][0] - points[v_l][0],
points[desti][1] - points[v_l][1]
]
for u in neigh:
if u == desti:
vu = v_l + '-' + u
w_vu = get_weight(vu)
if len(w_vu) == 0: cost_vu = 0
else: cost_vu = min([float(l) for l in w_vu.keys()])
vi_getmin, ex_p = get_vigetmin2(u)
all_expire += ex_p
p_best_p = p_hat + ';' + vu
p_w_p = self.conv(w_p_hat, w_vu)
p_max_m = max(list(p_w_p.values()))
p_best_cost = cost_sv + cost_vu + vi_getmin #inx_min*self.sigma
flag = True
break
if u in has_visit:
#print('u1 %s'%u)
continue
else:
has_visit.add(u)
if u in p_hat:
#print('u2 %s'%u)
continue
vu = v_l + '-' + u
w_vu = get_weight(vu)
if len(w_vu) == 0:
#print('vu %s'%vu)
continue
cost_vu = min([float(l) for l in w_vu.keys()])
p_order = nodes_order[u] #p_hat]
vi_getmin, ex_p = get_vigetmin2(u)
all_expire += ex_p
cost_time = cost_sv + cost_vu + vi_getmin #inx_min*self.sigma
if cost_time <= self.T:
p_hat_p = p_hat + ';' + vu
w_p_hat_p = self.conv(w_p_hat, w_vu)
p_hat_max = max(list(w_p_hat_p.values()))
QQ[p_hat_p] = (p_hat_max, w_p_hat_p, cost_time)
if flag: break
if len(Q) == 0:
Q = copy.deepcopy(QQ)
for qqk in QQ:
Que[qqk] = QQ[qqk][0]
QQ = {}
return p_best_p, p_max_m, p_best_cost, p_w_p, all_expire, all_rounds
def main(self, ):
vedge_desty, edge_desty, path_desty = self.get_dict()
gt_path, gt_path_ = self.add_tpath()
#print('len of edge_desty: %d'%len(edge_desty))
edges, nodes, G, G2, speed_dict = self.get_graph(
edge_desty, gt_path, vedge_desty)
#print('len of edge_desty2: %d'%len(edge_desty))
points = self.get_axes()
df2 = open(self.query_name, 'rb')
r_pairs = pickle.load(df2)
df2.close()
nodes_order, i = {}, 0
for node in nodes:
nodes_order[node] = i
i += 1
One_Plot2 = np.zeros(20).reshape(4, 5)
One_Sums = np.zeros(20).reshape(4, 5)
one_dis = -1
cate = ['0-5km', '5-10km', '10-25km', '25-35km']
for pairs in r_pairs:
one_dis += 1
#print('one_dis : %d'%one_dis)
print('distance category %s' % cate[one_dis])
tstart = time.time()
#print('len pairs %d'%len(pairs))
all_expires = 0.0
for pair_ in pairs:
print('o-d pair: %s' % pair_[0] + '-' + pair_[1])
start, desti = pair_[-2], pair_[-1]
pred2 = self.get_modified_one_to_all3(G, desti)
path_2, st1 = [start], start
while st1 != desti:
st2 = st1
st1 = pred2[st1] #[2]
path_2.append(st1)
at = 0
for st2 in path_2[1:]:
sedge = st1 + '-' + st2
if sedge in gt_path:
at += 1
pred = self.get_dijkstra3(G, desti)
path_, st1 = [start], start
distan2 = 0
while st1 != desti:
st2 = st1
st1 = pred[st1]
path_.append(st1)
distan2 += self.get_distance(points, (st2, st1))
distan = self.get_distance(points, (start, desti))
st_key = start + '+' + desti + ':' + str(distan) + ':' + str(
distan2) + ':' + str(len(pred2)) + ':' + str(at)
st1, time_budget = start, 0.0
print(path_)
for st2 in path_[1:]:
sedge = st1 + '-' + st2
if sedge in edge_desty:
speed_key = list(
[float(l) for l in edge_desty[sedge].keys()])
time_budget += max(speed_key)
elif sedge in speed_dict:
speed_key = list(
[float(l) for l in speed_dict[sedge].keys()])
time_budget += max(speed_key)
else:
print(' edge: %s not in speed_dict, exit' % sedge)
sys.exit()
st1 = st2
print('time budget: %f' % time_budget)
for t_b_, t_b in enumerate([0.5, 0.75, 1.0, 1.25, 1.5]):
self.T = time_budget * t_b
tstart = time.time()
best_p, max_m, best_c, best_pw, all_expire, all_rounds = self.rout(
start, desti, edge_desty, vedge_desty, speed_dict,
nodes_order, '', G, G2, points, gt_path, gt_path_,
pred2)
all_expires += all_expire
if best_p == 'none1': continue
if not isinstance(best_pw, dict): continue
tend = time.time()
One_Plot2[one_dis][t_b_] += tend - tstart - all_expire
One_Sums[one_dis][t_b_] += 1
One_Plot2 = One_Plot2 / One_Sums
One_Plot2 = np.nan_to_num(One_Plot2)
print('The success account')
print(One_Sums)
print('The time cost for routing')
print(One_Plot2)
print('Time cost for budget: 50%, 75%, 100%, 125%, 150%')
print(One_Plot2.mean(0))
print('Time cost for distance: 0-5km, 5-10km, 10-25km, 25-35km')
print(One_Plot2.mean(1))
class PaceRout():
def __init__(self, policy_path, true_path, virtual_path, edge_desty,
subpath, axes_file, speed_file, query_name):
self.sigma = 30
self.vopt = VOpt()
self.B = 3
self.policy_path = policy_path
self.true_path = true_path
self.virtual_path = virtual_path
self.edge_desty = edge_desty
self.subpath = subpath
self.axes_file = axes_file
self.speed_file = speed_file
self.speed = 50
self.query_name = query_name
def get_axes(self, ):
fo = open(self.axes_file)
points = {}
for line in fo:
line = line.split('\t')
points[line[0]] = (float(line[2]), float(line[1]))
return points
def get_distance(self, points, point):
(la1, lo1) = points[point[0]]
(la2, lo2) = points[point[1]]
return geodesic((lo1, la1), (lo2, la2)).kilometers
def get_dict(self, ):
path_desty = {}
for l in range(1, 5):
with open(self.subpath + self.virtual_path +
'_%d.json' % l) as js_file:
path_desty_ = json.load(js_file)
path_desty.update(path_desty_)
with open(self.subpath + self.edge_desty) as js_file:
edge_desty = json.load(js_file)
edge_desty = dict(
sorted(edge_desty.items(), key=operator.itemgetter(0)))
vedge_desty = {}
for p_k in path_desty:
vedge_desty[p_k] = path_desty[p_k][0][1]
return vedge_desty, edge_desty, path_desty
def get_speed(self, ):
speed_dict = {}
with open(self.speed_file) as fn:
for line in fn:
line = line.strip().split('\t')
speed_dict[line[0]] = {
3600 * float(line[1]) / float(line[2]): 1.0
}
return speed_dict
def get_graph2(self, edge_desty, vedge_desty, r_pairs, points):
speed_dict = self.get_speed()
all_nodes, all_edges = set(), set()
for key in speed_dict:
line = key.split('-')
all_nodes.add(line[0])
all_nodes.add(line[1])
all_edges.add(key)
All_edges = []
for edge in all_edges:
edge_ = edge.split('-')
if edge in edge_desty:
cost1 = edge_desty[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
elif edge in speed_dict:
cost1 = speed_dict[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
for edge in edge_desty:
#edge_ = edge.split('-')
if edge not in speed_dict:
print(edge)
G2 = nx.DiGraph()
G2.add_nodes_from(all_nodes)
G2.add_weighted_edges_from(All_edges)
temp_edges = set()
for pairs in r_pairs:
for pair in pairs:
stedge = pair[-2] + '-' + pair[-1]
#print(stedge)
temp_edges.add(stedge)
for edge in vedge_desty:
if edge not in edge_desty and edge not in speed_dict:
edge_ = edge.split('-')
cost1 = vedge_desty[edge].keys()
cost = min(float(l) for l in cost1)
All_edges.append((edge_[0], edge_[1], cost))
all_edges.add(edge)
print('len of vedge_desty 2: %d' % len(vedge_desty))
all_nodes, all_edges = list(all_nodes), list(all_edges)
G = nx.DiGraph()
G.add_nodes_from(all_nodes)
G.add_weighted_edges_from(All_edges)
return all_edges, all_nodes, G, G2, speed_dict
def conv(self, A, B):
D = {}
for a_k in A:
for b_k in B:
n_k = int(float(a_k) + float(b_k))
n_v = float(A[a_k]) * float(B[b_k])
D[n_k] = n_v
if len(D) <= 3:
return D
D = dict(sorted(D.items(), key=operator.itemgetter(0)))
new_w = self.vopt.v_opt(list(D.keys()), list(D.values()), self.B)
new_w = dict(sorted(new_w.items(), key=operator.itemgetter(0)))
return new_w
def path_conv(self, prob1, prob2, edge, edge_desty):
DD = {}
edge_w = edge_desty[edge]
wk1, wk2, wk3 = list(prob1.keys()), list(prob2.keys()), list(
edge_w.keys())
N, J, M = len(prob1), len(prob2), len(edge_w)
for n in range(N):
for j in range(J):
for m in range(M):
n_k = int(wk1[n]) + int(wk2[j]) - int(wk3[m])
if n_k < 0: continue
#else: n_k = str(n_k)
if n_k in DD:
DD[n_k] += float(prob1[wk1[n]]) * float(
prob2[wk2[j]]) / float(edge_w[wk3[m]])
else:
DD[n_k] = float(prob1[wk1[n]]) * float(
prob2[wk2[j]]) / float(edge_w[wk3[m]])
if len(DD) <= 3: return DD
#print(DD)
DD = dict(sorted(DD.items(), key=operator.itemgetter(0)))
DD = self.vopt.v_opt(list(DD.keys()), list(DD.values()), self.B)
DD = dict(sorted(DD.items(), key=operator.itemgetter(0)))
return DD
def get_dijkstra(self, G, source, target):
path = nx.dijkstra_path(G, source, target)
return path
def get_last_edge(self, apath):
a = apath.rfind(';')
if a == -1: return apath
else: return apath[a + 1:]
def rout(self, start, desti, edge_desty, vedge_desty, path_desty,
nodes_order, U, G, points, speed_dict):
all_expire = 0.0
neigh = list(G.successors(start))
has_visit = set()
has_visit.add(start)
Que = PQDict.maxpq()
Q, QQ = {}, []
print('neigh : %d' % len(neigh))
for vi in neigh:
if vi in has_visit: continue
else: has_visit.add(vi)
candidite = start + '-' + vi
if candidite in edge_desty:
w_can = edge_desty[candidite]
elif candidite in speed_dict:
w_can = speed_dict[candidite]
elif candidite in vedge_desty:
w_can = vedge_desty[candidite]
w_min = min([float(l) for l in w_can.keys()])
w_exp = 0.0
for w_k, w_v in w_can.items():
w_exp += float(w_k) * float(w_v)
if w_min <= self.T:
Que[candidite] = w_exp
Q[candidite] = w_can
Qkey = list(Q.keys())
flag = False
best_path, best_w = None, -1
bts = time.time()
all_rounds = 0
while len(Q) != 0:
(cand, pqv) = Que.popitem()
all_rounds += 1
w_can = Q[cand]
del Q[cand]
a = cand.rfind('-')
v_l = cand[a + 1:]
if v_l == desti:
best_path = cand
best_w = w_can
flag = True
break
if desti in cand:
a = cand.find('-' + desti)
best_path = cand[:a + len(desti) + 1]
best_w = w_can
flag = True
break
neigh = list(G.successors(v_l))
for u in neigh:
if u == desti:
next_cand = v_l + '-' + u
if next_cand in edge_desty:
next_w = edge_desty[next_cand]
elif next_cand in speed_dict:
next_w = speed_dict[next_cand]
elif next_cand in vedge_desty:
next_w = vedge_desty[next_cand]
tcost1 = time.time()
next_w_min = min([float(l) for l in next_w.keys()])
best_path = cand + ';' + next_cand
best_w = self.conv(w_can, next_w)
all_expire += time.time() - tcost1
flag = True
break
if u in has_visit: continue
else: has_visit.add(u)
if u in cand: continue
next_cand = v_l + '-' + u
if next_cand in vedge_desty:
next_w = vedge_desty[next_cand]
elif next_cand in edge_desty:
next_w = edge_desty[next_cand]
elif next_cand in speed_dict:
next_w = speed_dict[next_cand]
next_w_min = min([float(l) for l in next_w.keys()])
if next_w_min <= self.T:
new_path = cand + ';' + next_cand
temp_1 = cand.rfind(';')
if temp_1 != -1:
new_p = cand[temp_1 + 1:] + ';' + next_cand
if new_p in path_desty:
new_path_w = self.path_conv(
w_can, path_desty[new_p], cand[tep_1 + 1:],
edge_desty)
else:
new_path_w = self.conv(w_can, next_w)
else:
new_path_w = self.conv(w_can, next_w)
w_exp = 0.0
for w_k, w_v in w_can.items():
w_exp += float(w_k) * float(w_v)
QQ.append((new_path, new_path_w, w_exp))
last_edge = self.get_last_edge(cand)
if flag: break
if len(Q) == 0:
for QQ_ in QQ:
Q[QQ_[0]] = QQ_[1]
Que[QQ_[0]] = QQ_[2]
return best_path, best_w, all_rounds, all_expire
def get_dijkstra3(self, G, target):
Gk = G.reverse()
inf = float('inf')
D = {target: 0}
Que = PQDict(D)
P = {}
nodes = Gk.nodes
UU = set(nodes)
while UU:
#print('len U %d'%len(U))
#print('len Q %d'%len(Que))
if len(Que) == 0: break
(v, d) = Que.popitem()
D[v] = d
UU.remove(v)
#if v == target: break
neigh = list(Gk.successors(v))
for u in neigh:
if u in UU:
d = D[v] + Gk[v][u]['weight']
if d < Que.get(u, inf):
Que[u] = d
P[u] = v
return P
def get_U2(self, u_name):
if u_name in self.hU:
return self.hU[u_name]
if not os.path.isfile(self.fpath + u_name):
#print('no this U : %s'%(self.fpath+u_name))
print(u_name)
return {}
fn = open(self.fpath + u_name)
U = {}
for line in fn:
line = line.strip().split(';')
U[line[0]] = np.zeros(self.eta)
if line[1] == '-1' and line[2] == '-1':
pass
elif line[1] == '-1' and line[2] == '0':
U[line[0]] = np.ones(self.eta)
else:
for i in range(int(line[1]) + 1, int(line[2])):
t = 3 + i - int(line[1]) - 1
U[line[0]][i] = float(line[t])
for i in range(int(line[2]), self.eta):
U[line[0]][i] = 1.0
fn.close()
self.hU[u_name] = U
return U
def main(self, ):
df2 = open(self.query_name, 'rb')
r_pairs = pickle.load(df2)
df2.close()
vedge_desty, edge_desty, path_desty = self.get_dict()
points = self.get_axes()
edges, nodes, G, G2, speed_dict = self.get_graph2(
edge_desty, vedge_desty, r_pairs, points)
nodes_order, i = {}, 0
for node in nodes:
nodes_order[node] = i
i += 1
U = ''
PT = 5
One_Plot2 = np.zeros(20).reshape(4, 5)
One_Sums = np.zeros(20).reshape(4, 5)
one_dis = -1
cate = ['0-5km', '5-10km', '10-25km', '25-35km']
for pairs in r_pairs:
one_dis += 1
print('distance category %s' % cate[one_dis])
tstart2 = time.time()
#print('len pairs %d'%len(pairs))
sums2 = 0
mps, mps2 = 0.0, 0.0
alls = 0
cost_t = 0
for pair_ in pairs:
#print(pair_)
print('o-d pair: %s' % pair_[0] + '-' + pair_[1])
start, desti = pair_[-2], pair_[-1]
if start == desti:
print('wrong: start and desti is same')
print(pair_)
continue
start, desti = pair_[-2], pair_[-1]
pred = self.get_dijkstra3(G2, desti)
path_, st1 = [start], start
while st1 != desti:
st1 = pred[st1]
path_.append(st1)
st1, time_budget = start, 0.0
for st2 in path_[1:]:
sedge = st1 + '-' + st2
if sedge in edge_desty:
speed_key = list(
[abs(float(l)) for l in edge_desty[sedge].keys()])
time_budget += max(speed_key)
elif sedge in speed_dict:
speed_key = list(
[abs(float(l)) for l in speed_dict[sedge].keys()])
time_budget += max(speed_key)
elif sedge in vedge_desty:
speed_key = list(
[abs(float(l)) for l in vedge_desty[sedge].keys()])
time_budget += max(speed_key)
else:
print(' edge: %s not in speed_dict, exit' % sedge)
sys.exit()
st1 = st2
tend = time.time()
print('budget %f' % time_budget)
for t_b_, t_b in enumerate([0.5, 0.75, 1.0, 1.25, 1.5]):
tstart = time.time()
self.T = time_budget * t_b
best_p, best_w, all_rounds, all_expire = self.rout(
start, desti, edge_desty, vedge_desty, path_desty,
nodes_order, U, G2, points, speed_dict)
if best_p == None: continue
tend = time.time()
One_Plot2[one_dis][t_b_] += tend - tstart
One_Sums[one_dis][t_b_] += 1
One_Plot2 = One_Plot2 / One_Sums
One_Plot2 = np.nan_to_num(One_Plot2)
print('The success account')
print(One_Sums)
print('The time cost for routing')
print(One_Plot2)
print('Time cost for budget: 50%, 75%, 100%, 125%, 150%')
print(One_Plot2.mean(0))
print('Time cost for distance: 0-5km, 5-10km, 10-25km, 25-35km')
print(One_Plot2.mean(1))
pvalues = vopt.v_opt(
time_cost, time_freq,
B) # pvalues is a dict, contains new key and value
dicts[e_key] = pvalues
else:
if not is_path:
k1 = str(int(np.mean(time_cost)))
pvalues[k1] = 1.0
return norms(dicts, is_norm)
tpath = TPath(fname)
data = tpath.load()
edge_desty = tpath.get_edge_time_freq(data)
vopt = VOpt()
edge_desty_ = get_vopt(vopt, edge_desty, False, True)
keys = list(edge_desty_.keys())
print(keys[0])
print(edge_desty_[keys[0]])
edge_desty_1 = {}
for edge in edge_desty_:
#ky = list(edge.keys())
edge_ = {}
ky = edge_desty_[edge]
for k in ky.keys():
edge_[str(np.abs(k))] = float(ky[k]) / 100
edge_desty_1[edge] = edge_