#print(robot)
while distance>0.5:
loc_x = -x_total/40.0
loc_y = -y_total/40.0
lock.acquire()
#print(robot.id,loc_x,loc_y,distance)
lock.release()
robot.move(loc_x,loc_y)
x_total,y_total = relative_distance(robot,robots)
distance = distance_magnitude(x_total,y_total)
time.sleep(0.1)
def simulate_meeting_point(robots):
#run simulation using multithreading
for robot in robots:
dynamics_meeting_point(robot,robots)
# worker = threading.Thread(target=dynamics_meeting_point,args=(robot,robots))
# print(worker)
# worker.setDaemon(True)
# worker.start()
if __name__ == '__main__':
#main program
win = draw_windows(1024,1024) #draw window with width = 700 and height = 600
robots = draw_swarm(70,win) #draw 7 swarm in win
win.getMouse() #blocking call
simulate_meeting_point(robots) #start simulation meeting point
win.getMouse()
plotter = VisdomLinePlotter(env_name="Swarm_Simulation")
simulation_time = time.time()
trial_no="TURK1 s2"
N=100
rho_bar, sigma =10,100
mu=100
l=5*rho_bar
times=pow(2,-8)
rho_k,patches = normal_distribution(rho_bar,sigma,trial_no)
particles=list()
win = draw_windows(1024,1024,trial_no) #draw window with width = 700 and height = 600.
robots = draw_swarm(N,win,l,rho_k,patches) #draw N swarm in win
win.getMouse() #blocking call
for i in range(1,N+1,1):
particles.append([i,rho_k[i-1]])
#pairwise_list= list(combinations(particles,2))
pairwise_list = random.sample(particles, 2)
#mt_shuffle()
step=0
rho_kmean =np.mean(rho_k)# second term of the energy function
combination= (N*(N-1))/2
U_knot=0 #Order Parameter
plt.show()
return rho_k
N = 1000
rho_bar, sigma = 5, 100
mu = 100
l = 5 * rho_bar
times = pow(2, -8)
rho_k = normal_distribution(rho_bar, sigma)
particles = list()
win = draw_windows(1024, 1024) #draw window with width = 700 and height = 600.
robots = draw_swarm(N, win, l) #draw N swarm in win
win.getMouse() #blocking call
for i in range(1, N + 1, 1):
particles.append([i, rho_k[i - 1]])
#pairwise_list= list(combinations(particles,2))
pairwise_list = random.sample(particles, 2)
#mt_shuffle()
step = 0
while (1): #replace with energy function
pairwise_list = random.sample(particles, 2)
robot_j = robots[pairwise_list[0][0] - 1]
rho_j = pairwise_list[0][1]
trial_no = "WEBOTS-SOL3-T1"
N = 100
mu = 100
times = pow(2, -8)
#rho_k,patches = normal_distribution(rho_bar,sigma,trial_no)
particles = list()
w, h = 1024, 1024
win = draw_windows(1024, 1024,
trial_no) #draw window with width = 700 and height = 600.
robots, rho_k = draw_swarm(N, win, trial_no) #draw N swarm in win
#robots,rho_k = init_uniform_rhok(rho_k,robots,1024,1024,win)
patches = normal_distribution_color(rho_k)
robots = draw_robots(N, win, robots, rho_k, patches)
win.getMouse() #blocking call.
for i in range(1, N + 1, 1):
particles.append([i, rho_k[i - 1]])
pairwise_list = list(permutations(particles, 2))
#pairwise_list = random.sample(particles, 2)
mt_shuffle()
step = 0
rho_kmean = np.mean(rho_k) # second term of the energy function
combination = (N * (N - 1)) / 2
