def init_geometric(num_drones):
r = 250
list_drones = list()
for i in xrange(num_drones):
if i == 0:
list_drones.append(
global_variables.Drone(i, random.uniform(0, 1000),
random.uniform(0, 1000)))
else:
drone = random.randint(0, len(list_drones) - 1)
if random.randint(0, 10) > 5: #flip a coin
x = list_drones[drone].node_x + random.uniform(0, r) # add
if x > 1000:
x = 1000
else:
x = list_drones[drone].node_x - random.uniform(0,
r) # substract
if x < 0:
x = 0
aux = x - list_drones[drone].node_x
delta_y = math.sqrt((r * r) - (aux * aux))
if random.randint(0, 10) > 5:
y = list_drones[drone].node_y + random.uniform(0, delta_y)
if y > 1000:
y = 1000
else:
y = list_drones[drone].node_y - random.uniform(0, delta_y)
if y < 0:
y = 0
list_drones.append(global_variables.Drone(i, x, y))
return list_drones
def init_modified(list_drones_genetic, num_drones):
""" this function is used if different number of drones is used during the initial deployment
and the adaptation to the real conditions"""
accomplished = 0
global total
while accomplished == 0:
list_drones = list()
for j in list_drones_genetic:
x = j.node_x
y = j.node_y
list_drones.append(global_variables.Drone(total, x, y))
for i in range(len(list_drones_genetic), num_drones):
x_cor = random.random() * 1000
y_cor = random.random() * 1000
list_drones.append(global_variables.Drone(total, x_cor, y_cor))
if check_drones_conectivity(list_drones) < 0:
accomplished = 0
else:
accomplished = 1
total = total + 1
print "we got one, total number %d" % total
return list_drones
def copy_drones_positions():
""" copies drones positions from the file to be used in local optimization"""
list_drones = []
x = open("x_drones_positions.txt",'r')
y = open("y_drones_positions.txt", 'r')
ident = 0
for i, j in zip(x, y):
list_drones.append(global_variables.Drone(ident,float(i),float(j)))
ident = ident + 1
return list_drones
def init(num_drones):
accomplished = 0
global total
while accomplished == 0:
list_drones = list()
for i in range(0, num_drones):
x_cor = random.random() * 1000
y_cor = random.random() * 1000
list_drones.append(global_variables.Drone(i, x_cor, y_cor))
if check_drones_conectivity(list_drones) < 0:
accomplished = 0
else:
accomplished = 1
total = total + 1
print "we got one, total number %d" % total
return list_drones
def initPredefIndiv(icls, input_file):
## deterministic, uavs coordinates given as argument
f = open(input_file, 'r')
tmp=[line[:-1] for line in f ]
uavs_list=[[float(j) for j in ele.split(",")] for ele in tmp ]
f.close()
list_drones = list()
i=0
for a_uav in uavs_list :
x_cor = a_uav[0]
y_cor = a_uav[1]
##print(i, " reading indiv content ", x_cor, " and ",y_cor)
list_drones.append(global_variables.Drone(i,x_cor,y_cor))
i=i+1
if check_drones_conectivity(list_drones) < 0:
print("It's terrible, this individual is not connected, and that it not supposed to happen")
return icls(list_drones)
def init_grid(num_drones):
list_x = list()
list_y = list()
accomplished = 0
global total
for i in range(0, 1100, 150):
list_x.append(i)
list_y.append(i)
while accomplished == 0:
list_drones = []
for i in range(0, num_drones):
ind_x = random.randint(0, len(list_x) - 1)
ind_y = random.randint(0, len(list_y) - 1)
x_cor = list_x[ind_x]
y_cor = list_y[ind_y]
list_drones.append(global_variables.Drone(total, x_cor, y_cor))
if check_drones_conectivity(list_drones) < 0:
accomplished = 0
else:
accomplished = 1
total = total + 1
print "we got one, total number %d" % total
return list_drones
def positions_from_file(fil, num, k, nodes, UAVs, fig):
""" It plots the solution"""
#global list_victim
#global list_partial_victims
f = open(fil, 'r')
scenarios.generate_victim_positions_traces()
scenarios.partial_knowledge_generation(k)
#print list_victims
list_drones = list()
for line in f:
fields = line.split(",")
list_drones.append(
global_variables.Drone(int(fields[0]), float(fields[1]),
float(fields[2])))
for i in list_drones:
print(i.id, i.node_x, i.node_y)
#CO= quality.evaluate_coverage(list_drones)
#G= quality.create_drones_graph(list_drones)
#print quality.check_graph_connectivity(G)
#for i in list_drones:
# print i.neighbordrones
#F= quality.evaluate_weighted(list_drones)
CO = quality.evaluate_coverage(list_drones)
print("coverage", CO)
#FTO= quality.evaluate_tolerance(list_drones)
#print FTO
#RO= quality.evaluate_redundancy(list_drones)
#print "redundancy", RO
ground_x = list() # victims' positions
ground_y = list()
ground_x_covered = list() # victims' positions
ground_y_covered = list()
UAV_x = list() # drones' positions
UAV_y = list()
UAV_ground_x = list() # links among drones and victims
UAV_ground_y = list()
UAV_UAV_x = list() # links among drones
UAV_UAV_y = list()
for i in global_variables.list_partial_victims:
ground_x.append(i.node_x)
ground_y.append(i.node_y)
for j in list_drones:
UAV_x.append(j.node_x)
UAV_y.append(j.node_y)
#print UAV_x, UAV_y
#print ground_x, ground_y
UAV_ground_x, UAV_ground_y, ground_x_covered, ground_y_covered = plot_links(
list_drones, 1)
UAV_UAV_x, UAV_UAV_y = plot_links_drones(list_drones)
#print UAV_ground_x
# plotting drones connectivity
#fig = plt.figure(figsize= (10,20), dpi = 300)
ax1 = fig.add_subplot(4, 2, num)
#s1= ax1.scatter(ground_x, ground_y, c = 'y', label = "ground_nodes", marker = 'o')
s1 = ax1.scatter(UAV_x, UAV_y, c='r', label="UAV", marker='x')
for i in range(0, len(UAV_UAV_x)):
if i % 2 == 0:
x1 = UAV_UAV_x[i]
x11 = UAV_UAV_x[i + 1]
y1 = UAV_UAV_y[i]
y11 = UAV_UAV_y[i + 1]
ax1.plot([x1, x11], [y1, y11],
'r--',
label="UAV-UAV links",
marker='_')
ax1.set_xlabel("X [m]", fontsize=11)
ax1.set_ylabel("Y [m]", fontsize=11)
ax1.axis([-50, 1050, -50, 1050])
ax1.set_title(UAVs, fontsize=12)
ax1.grid("on")
ax2 = fig.add_subplot(4, 2, num + 1)
s2 = ax2.scatter(ground_x,
ground_y,
c='c',
label="ground_nodes",
marker='x')
s3 = ax2.scatter(ground_x_covered,
ground_y_covered,
c='m',
label="ground_nodes",
marker='x')
ax2.scatter(UAV_x, UAV_y, c='r', label="UAV", marker='x')
for i in range(0, len(UAV_ground_x)):
if i % 2 == 0:
x1 = UAV_ground_x[i]
x11 = UAV_ground_x[i + 1]
y1 = UAV_ground_y[i]
y11 = UAV_ground_y[i + 1]
ax2.plot([x1, x11], [y1, y11],
'g--',
label="UAV-ground links",
marker='_')
ax2.set_xlabel("X [m]", fontsize=11)
ax2.set_ylabel("Y [m]", fontsize=11)
ax2.axis([-50, 1050, -50, 1050])
ax2.set_title(nodes, fontsize=12)
ax2.grid("on")
#l = ["unknown victims", "known victims", "drones"]
#c = ['b', 'k', 'r', 'y', 'g', 'r']
#m = ['o', 'o', 'o', '_', '_', '_']
UAV_links = mlines.Line2D([], [],
color='red',
linestyle='--',
label='Blue stars')
GN_links = mlines.Line2D([], [],
color='green',
linestyle='--',
label='Blue stars')
if num == 1:
fig.legend(handles=[s1, s2, s3, UAV_links, GN_links],
labels=['UAV', 'GN', 'Cov-GN', 'UAV-links', 'GN-links'],
loc='upper center')
#fig.legend(handles=[s1, s2, s3, s4, s5, s6], ('UAV', 'GN','Cov-GN','UAV-links', 'GN-GN.links'), loc= 'upper right')
fig.savefig("Positions.png")