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核心代码.py
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核心代码.py
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def dijkstra_with_stepnum(graph, pointType, s, max_stepnum, func_index, jiaozhengType):
# 判断图是否为空，如果为空直接退出
# pointType: -1:起始点,0:水平点,1:垂直点,2:终点
# 改进的Dijkstra算法
if graph is None:
return None
dist = [MAX_value]*len(graph)
dist[s] = 0
shuiping = [MAX_value] * len(graph)
chuizhi = [MAX_value] * len(graph)
shuiping[s] = 0
chuizhi[s] = 0
qianqu = [MAX_value] * len(graph)
tujing_num = [MAX_value] * len(graph)
tujing_num[s] = 0
p_safe = [0] * len(graph)
p_safe[s] = 1
S = []
Q = [i for i in range(len(graph))]
dist_init = [i for i in graph[s]]
dist_weighted = [MAX_value] * len(graph)
dist_weighted[s] = 0
while Q:
u_dist = min([d for v, d in enumerate(dist_init) if v in Q])
u = dist_init.index(u_dist)
S.append(u)
Q.remove(u)
# print(u)
sys.stdout.write('\r dijkstra running:' + str(len(Q)) + '/' + str(len(graph)))
sys.stdout.flush()
# print(len(Q),'/',len(graph))
for v, d in enumerate(graph[u]):
if 0 < d < MAX_value and v in Q:
# if dist[v] > dist[u]+d:
# print(u,v)
route1, route2 = get_two_routes(u,v,qianqu)
p1,p2 = get_safe_P(route1,0,0,graph,pointType,jiaozhengType),get_safe_P(route2,0,0,graph,pointType,jiaozhengType)
# print(route1,route2,p1,p2)
if ALPHA * (dist[v]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((tujing_num[v] + 0.0)/max_stepnum)) + GAMA * p2 > \
ALPHA * ((dist[u] + d)/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((tujing_num[u] + 1.0)/max_stepnum)) + GAMA * p1:
if pointType[v] == 0 and shuiping[u] + d * DELTA < BETA2 \
and chuizhi[u] + d * DELTA < BETA1:
# if jiaozhengType[v] == 1:
dist[v] = dist[u]+d
# dist_init[v] = dist[v]
dist_init[v] = ALPHA * (dist[v]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((tujing_num[v]+0.0)/max_stepnum)) + GAMA * p2
shuiping[v] = 0
chuizhi[v] = chuizhi[u] + d*DELTA
qianqu[v] = u
tujing_num[v] = tujing_num[u] + 1
if pointType[v] == 1 and shuiping[u] + d * DELTA < ALPHA2 \
and chuizhi[u] + d * DELTA < ALPHA1:
dist[v] = dist[u]+d
# dist_init[v] = dist[v]
dist_init[v] = ALPHA * (dist[v]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((tujing_num[v]+0.0)/max_stepnum)) + GAMA * p2
chuizhi[v] = 0
shuiping[v] = shuiping[u] + d * DELTA
qianqu[v] = u
tujing_num[v] = tujing_num[u] + 1
if pointType[v] == 2 and shuiping[u] + d* DELTA < THETA \
and chuizhi[u] + d * DELTA < THETA:
dist[v] = dist[u] + d
# dist_init[v] = dist[v]
dist_init[v] = ALPHA * (dist[v]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((tujing_num[v]+0.0)/max_stepnum)) + GAMA * p2
qianqu[v] = u
tujing_num[v] = tujing_num[u] + 1
return dist, qianqu, tujing_num
def astar(graph, pointsType, s, jiaozhengType, max_time):
# 改进的A*算法
open_list = []
close_list = []
parent = [MAX_value] * len(graph)
parent[s] = 0
G = [MAX_value] * len(graph)
H = [MAX_value] * len(graph)
shuiping = [MAX_value] * len(graph)
chuizhi = [MAX_value] * len(graph)
shuiping[s] = 0
chuizhi[s] = 0
open_list.append(s)
G[s] = 0
H[s] = 0
Dist_ = [MAX_value] * len(graph)
Cishu_ = [MAX_value] * len(graph)
Dist_[s] = 0
Cishu_[s] = 0
while checklist(graph, open_list, close_list):
min_d = open_list[0]
min_f = G_P * G[min_d] + H_P * ((H[min_d]+0.0)/graph[0][-1])
for v,d in enumerate(open_list):
if G_P * G[d] + H_P * ((H[d] + 0.0)/graph[0][-1]) < min_f:
min_f = G_P * G[d] + H_P * ((H[d] + 0.0)/graph[0][-1])
min_d = d
open_list.remove(min_d)
close_list.append(min_d)
node_current = min_d
for i,d in enumerate(graph[node_current]):
if i in close_list:
continue
sp = shuiping[node_current] + d * DELTA
cz = chuizhi[node_current] + d * DELTA
if pointsType[i] == 0 and sp <= BETA2 and cz <= BETA1:
#可达
current_route = get_route(parent, points, pointsType, node_current)
current_route.append(i)
sp_ = get_safe_P(current_route, 0, 0, graph, pointsType, jiaozhengType)
# print(sp_)
if i not in open_list:
open_list.append(i)
parent[i] = node_current
shuiping[i] = 0
chuizhi[i] = cz
Dist_[i] = Dist_[node_current] + d
Cishu_[i] = Cishu_[node_current] + 1
G[i] = ALPHA * (Dist_[i]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[i]+0.0)/max_time)) + GAMA * sp_
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
else:
G_current = ALPHA * ((Dist_[node_current] + d)/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[node_current] + 1.0)/max_time)) + GAMA * sp_
if G_current < G[i]:
parent[i] = node_current
G[i] = G_current
shuiping[i] = 0
chuizhi[i] = cz
Dist_[i] = Dist_[node_current] + d
Cishu_[i] = Cishu_[node_current] + 1
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
elif pointsType[i] == 1 and sp <= ALPHA2 and cz <= ALPHA1:
#可达
current_route = get_route(parent, points, pointsType, node_current)
current_route.append(i)
sp_ = get_safe_P(current_route, 0, 0, graph, pointsType, jiaozhengType)
if i not in open_list:
open_list.append(i)
parent[i] = node_current
shuiping[i] = sp
chuizhi[i] = 0
Dist_[i] = Dist_[node_current] + d
Cishu_[i] = Cishu_[node_current] + 1
G[i] = ALPHA * (Dist_[i]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[i]+0.0)/max_time)) + GAMA * sp_
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
else:
G_current = ALPHA * ((Dist_[node_current] + d)/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[node_current] + 1.0)/max_time)) + GAMA * sp_
if G_current < G[i]:
parent[i] = node_current
G[i] = G_current
shuiping[i] = sp
chuizhi[i] = 0
Dist_[i] = Dist_[node_current] + d
Cishu_[i] = Cishu_[node_current] + 1
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
elif pointsType[i] == 2 and sp <= THETA and cz <= THETA:
#可达
current_route = get_route(parent, points, pointsType, node_current)
current_route.append(i)
sp_ = get_safe_P(current_route, 0, 0, graph, pointsType, jiaozhengType)
if i not in open_list:
open_list.append(i)
parent[i] = node_current
shuiping[i] = 0
chuizhi[i] = 0
Dist_[i] = Dist_[node_current] + d
Cishu_[i] = Cishu_[node_current] + 1
G[i] = ALPHA * (Dist_[i]/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[i]+0.0)/max_time)) + GAMA * sp_
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
else:
G_current = ALPHA * ((Dist_[node_current] + d)/graph[0][-1]) + BETA * funcs[FUNC_INDEX](((Cishu_[node_current] + 1.0)/max_time)) + GAMA * sp_
if G_current < G[i]:
parent[i] = node_current
G[i] = G_current
shuiping[i] = 0
chuizhi[i] = 0
Dist_[i] = Dist_[node_current] + d+ GAMA * sp_
Cishu_[i] = Cishu_[node_current] + 1
H[i] = ((graph[i][-1] + 0.0)/graph[0][-1])
else:
#不可达
continue
return parent, Dist_
def get_safe_P(routes, chushi_shuiping, chushi_chuizhi, graph, pointType, jiaozhengType):
# 计算一条路径的安全概率
if len(routes) <= 1:
return 1
# if chushi_shuiping + d * DELTA
d = graph[routes[0]][routes[1]]
shuiping = chushi_shuiping + d * DELTA
chuizhi = chushi_chuizhi + d * DELTA
if pointType[routes[1]] == 0 and shuiping < BETA2 \
and chuizhi < BETA1:
if jiaozhengType[routes[1]] == 0: #shuiping
return 1 * get_safe_P(routes[1:],0.0, chuizhi, graph, pointType, jiaozhengType)
else:
return 0.8* get_safe_P(routes[1:],0.0, chuizhi, graph, pointType, jiaozhengType) + 0.2 *\
get_safe_P(routes[1:],min(shuiping,5), chuizhi, graph, pointType, jiaozhengType)
elif pointType[routes[1]] == 1 and shuiping< ALPHA2 and chuizhi < ALPHA1:
if jiaozhengType[routes[1]] == 0:
return 1 * get_safe_P(routes[1:],shuiping, 0.0, graph, pointType, jiaozhengType)
else:
return 0.8*get_safe_P(routes[1:],shuiping, 0.0, graph, pointType, jiaozhengType) +\
0.2 * get_safe_P(routes[1:],shuiping, min(chuizhi,5), graph, pointType, jiaozhengType)
elif pointType[routes[1]] == 2 and shuiping < THETA and chuizhi < THETA:
return 1
else:
return 0